GLOBALINNOVATIONINDEX 2019
Creating Healthy Lives—The Future of Medical InnovationGLOBALINNOVATIONINDEX 2019
Creating Healthy Lives—The Future of Medical Innovation
12TH EDITION

Soumitra Dutta, Bruno Lanvin, and Sacha Wunsch-Vincent
Editors

The Global Innovation Index 2019: Creating Healthy Lives—The Future of
Medical Innovation is the result of a collaboration between Cornell University,
INSEAD, and the World Intellectual Property Organization (WIPO) as co-publishers,
and their Knowledge Partners.
The report and any opinions expressed in this publication are the sole
responsibility of the authors. They do not purport to reflect the opinions or
views of WIPO Member States or the WIPO Secretariat.
The terms ‘country’, ‘economy’, and ‘nation’ as used in this report do not in allcases refer to a territorial entity that is a state as understood by internationallaw and practice. The terms cover well-defined, geographically self-contained
economic areas that may not be states but for which statistical data aremaintained on a separate and independent basis. Any boundaries and names
shown, and the designations used on any visual maps, do not imply official
endorsement or acceptance by any of the co-publishers. Chapters 2-17 may
deviate from UN terminology for countries and regions.
© Cornell University, INSEAD, and the World Intellectual Property Organization, 2019
This work is licensed under the Creative Commons Attribution Non-commercial
No-Derivatives 3.0 IGO License. The user is allowed to reproduce, distribute,and publicly perform this publication without explicit permission, provided
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INSEAD, and WIPO are the source. No part of this publication can be used
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When content, such as an image, graphic, data, trademark, or logo, isattributed to a third party, the user is solely responsible for clearing the rights
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Suggested citation: Cornell University, INSEAD, and WIPO (2019);
The Global Innovation Index 2019: Creating Healthy Lives—The Futureof Medical Innovation, Ithaca, Fontainebleau, and Geneva.
ISSN 2263-3693
ISBN 979-10-95870-14-2
Printed and bound in Geneva, Switzerland, by the World Intellectual Property
Organization (WIPO), and in New Delhi, India, by the Confederation of Indian
Industry (CII).
Cover design by LOWERCASE Inc. (lowercaseinc.com)

ii

The Global Innovation Index 2019

CONTENTS

vii

Preface: Releasing the Global Innovation
Index 2019: Creating Healthy Lives—The Futureof Medical Innovation
By Soumitra Dutta, SC Johnson College of Business,
Cornell University; Francis Gurry, World Intellectual
Property Organization (WIPO); and Bruno Lanvin, INSEAD

ix

Foreword: Innovating for a Healthy Nation
By Chandrajit Banerjee, Director General, Confederationof Indian Industry (CII)xi

Foreword: Health in the Age of Experience
By Bernard Charlès, Chief Executive Officer
and the Vice-Chairman of the Board of Directors ofDassault Systèmesxiii

KEY FINDINGS
xvi

Key Findings 2019

RANKINGS
xxxiv

Global Innovation Index 2019 rankings

xli

Contributors to the Report

xlvii

Advisory Board to the Global Innovation Index

Foreword: Innovation in Health and Medicine:
New Possibilities for Brazil
By Robson Braga de Andrade, President of CNI, Directorof SESI, and President of SENAI’s National Council;
and Carlos Melles, President of SEBRAE.

Contentsiii

CHAPTERS
1Chapter 1: The Global Innovation Index 2019
By Soumitra Dutta, Rafael Escalona Reynoso, andAntanina Garanasvili, SC Johnson College of Business,
Cornell University; Bruno Lanvin, INSEAD;
Sacha Wunsch-Vincent, Lorena Rivera León,Francesca Guadagno* and Cashelle Hardman,
World Intellectual Property Organization (WIPO)

41

Theme Section: Creating Healthy Lives—
The Future of Medical Innovation
By Soumitra Dutta, and Rafael Escalona Reynoso,
SC Johnson College of Business, Cornell University;
Sacha Wunsch-Vincent, Lorena Rivera León andCashelle Hardman, World Intellectual Property
Organization (WIPO)

61

Special Section: Cluster Rankings
Identifying and Ranking the World’s Largest
Science and Technology Clusters
By Kyle Bergquist and Carsten Fink, WorldIntellectual Property Organization (WIPO)

81

Chapter 2: The Economics of Health Innovation:
Looking Back and Looking Forward
By Bhaven Sampat, Columbia University

87

Chapter 3: Trends in Healthcare and Medical
Innovation
By Pratap Khedkar & Dharmendra Sahay, ZS Associates

95

Chapter 4: Ten Opportunities for Biomedical
Innovation over the Next Ten Years
By Francis Collins, National Institutes of Health (NIH)103

Chapter 5: Application of Artificial Intelligence and
Big Data in China's Healthcare Services
By Ma Huateng, Tencent

111

Chapter 6: Reaching New Frontiers for Alzheimer’s
through Research and Innovation
By David Ricks and Brandy Matthews, Eli Lilly and Company

121

Chapter 7: Improving Patient Healthcare throughVirtual Platforms
By Claire Biot, Patrick Johnson, Sébastien Massart, &Nicolas Pécuchet, Dassault Systèmes

129

Chapter 8: How Data will Improve Healthcare
without Adding Staff or Beds
By Kieran Murphy, GE Healthcare

135

Chapter 9: Case of iamYiam—Innovating in Preventive
Health Delivery
By Lorena Puica, iamYiam; and Jack Bauersachs,
University of Applied Sciences Deggendorf

141

Chapter 10: How Particle Physics Research at CERN
Contributes to Medical Innovation
By Giovanni Anelli, Manuela Cirilli and Anais Rassat,
European Organization for Nuclear Research (CERN)

149

Chapter 11: Overcoming Barriers to Medical
Innovation for Low Resource Settings
By David C. Kaslow, PATH

157

Chapter 12: Life is too Short with HCV and NCDs—
100 Million Healthy Lives Initiative
By Hala Zaid, Aysam Salaheldein, Mohamed Hassany
and Mostafa Monier Othman, Ministry of Health andPopulation, Egypt; and Ahmed Sorour, Egypt Country Office,World Health Organization.

iv

The Global Innovation Index 2019

APPENDICES
163

Chapter 13: Innovations in Healthcare Affordability
and Delivery – An Indian Perspective

205

Appendix I: The Global Innovation Index
Conceptual Framework

213

Appendix II: Economy Profiles & Data Tables

349

Appendix III: Sources and Definitions

367

Appendix IV: Adjustments to the Global Innovation
Index Framework, Year-on-Year Comparabilityof Results, and Technical Notes

375

Appendix V: Joint Research Centre Statistical Auditof the Global Innovation Index 2019

By Devi Shetty, Narayana Health169

Chapter 14: A Brazilian Outlook on Health andMedical Innovation
By Robson Braga de Andrade, National Confederation ofIndustry (CNI) Brazil; and Carlos Melles, Brazilian Micro andSmall Business Support Service (SEBRAE)

177

Chapter 15: Integration of Health and Medical
Innovations in Rwanda to Promote Health Equity
By Parfait Uwaliraye, Patrick Ndimubanzi, Andrew Muhire
and Valencia Lyle, Ministry of Health, Rwanda

185

Chapter 16: Iran’s Experience in Developing High-techMedical Innovations and the Path Ahead
By Kiarash Fartash, Shahid Beheshti University; andMahdi Elyasi, Allameh Tabataba’I University

195

By Michaela Saisana, Marcos Álvarez-Díaz,
Marcos Dominguez-Torreiro and Daniel Vertesy,
European Commission, Joint Research Centre (JRC),
Ispra, Italy.

391

Appendix VI: About the Authors

Chapter 17: Social and Economic Aspects of Healthand Medical Innovation in Thailand
By Krithpaka Boonfueng and Chaiyatorn Limapornvanich,
National Innovation Agency (NIA) Thailand; and Thanaphan
Suksaard, Ministry of Public Health, Thailand.

Contentsv

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The Global Innovation Index 2019

P RE FAC E

RELEASING THE GLOBAL INNOVATIONINDEX 2019: CREATING HEALTHY LIVES—
THE FUTURE OF MEDICAL INNOVATION
ways. First, the GII helps place innovation firmly on the map forcountries, in particular for low- and middle-income economies.
Second, the GII allows countries to assess the relative performanceof their national innovation system. A significant number ofcountries work hard to “unpack their GII innovation ranking” andto analyze their innovation strengths and weaknesses. Thesefindings then inform innovation policies and actions. Third, theGII provides a strong impetus for countries to collect fitting
innovation metrics.
© Emmanuel Berrod/WIPO

We are pleased to present the 12th edition of the Global Innovation
Index (GII). The special theme for this edition is Creating Healthy
Lives—The Future of Medical Innovation.
Over the last two centuries, improvements in healthcare haveprompted a sustained increase in life expectancy and in thequality of life, resulting in substantial contributions to economic
growth. Medical innovation has largely contributed to this progress.
As we look into the future, new technologies and non-technologicalinnovations will likely continue to enrich the provision ofhealthcare at a rapid pace. Artificial intelligence, genomics,
stem cell research, big data, and mobile health applications
will open doors to improved health. Likewise, novelties suchas the delivery of medicines via drones have potential for ruraland low-resource contexts in developing countries.
Focusing on the next two decades, the GII 2019 will shed lighton the role of medical innovation as it shapes the future ofhealthcare. The insights shared within the report show that
we have an exciting opportunity ahead of us. In addition to thetheme, and as every year, the GII report analyzes global innovation
trends and the performance of approximately 130 economies.
For more than a decade, the GII has fostered national innovation
strategies and international debates on innovation in three main

Soumitra Dutta
Professor of Management and Former
Founding Dean
SC Johnson College of Business
Cornell University

With this in mind, however, the GII is only as good as its data
ingredients. The current state of innovation metrics is improving.
Yet, despite this progress, the figures available to assess
innovation outputs and impacts—a topic of critical importance—
remain poor. Similarly, sound metrics on key components ofinnovation systems, such as the state of entrepreneurship,
the availability of venture capital, the nature of innovation
linkages, or the degree to which innovations are successfullycommercialized, are lacking.
To improve the state of innovation metrics, the GII will continue tobe a laboratory for measuring and analyzing emerging innovation
data. Trial and error will be required to provide the most accurate
assessment of perpetually changing innovation contexts. We
appreciate the feedback we continue to receive from innovation
experts and decision-makers, whose insights contribute to how
we refine the GII methodology.
For this GII edition, we thank our Knowledge Partners; theConfederation of Indian Industry (CII); Dassault Systèmes, The
3DEXPERIENCE Company; the National Confederation of Industry
Brazil (CNI); and the Brazilian Service of Support to Micro andSmall Enterprises (SEBRAE) for their support. Likewise, we recognize
the contributions of the GII’s prominent Advisory Board members.
Finally, we express our sincere appreciation for the annual
audits and technical assistance provided by the CompetenceCentre on Composite Indicators and Scoreboards (COIN) of the
Joint Research Centre at the European Commission.

Francis Gurry
Director General,
World Intellectual Property
Organization (WIPO)

Bruno Lanvin
Executive Director for Global Indices,
INSEAD

Preface

vii

viii

The Global Innovation Index 2019

F O RE WOR DINNOVATING FOR A HEALTHY NATION

Private healthcare service providers are also investing ininnovative products and the latest technology. At the same time,
the Confederation of Indian Industry (CII) has been creatingawareness to improve the quality of healthcare processes.
The CII is actively involved in the development and disseminationof healthcare standards and practices.
These efforts are lifting India’s Global Innovation Index (GII)rank, which improved to 66 in 2016, 60 in 2017, and 57 in 2018.
Honorable Prime Minister Narendra Modi has envisioned India
as one of the top 25 globally innovative nations—which has
led to a series of enabling policies and practices for the country.
Healthcare is a sector of critical importance in India, encompassing
an array of areas including hospitals, medicines, medical
devices, clinical trials, outsourcing, telemedicine, medical tourism,
health insurance, and medical equipment. The sector holds
enormous opportunity for public and private stakeholders todevelop innovative processes that democratize healthcare andincrease affordability.

The theme of this year’s Global Innovation Index, Creating
Healthy Lives—The Future of Medical Innovation, is quite relevant
as technology advances in the healthcare sector. The applicationsof artificial intelligence, robotics, remote diagnosis, genomics,
big data, mobile health, stem cell research, regenerative
medicine, biomarkers, and nano-technology will pave the way
for healthy living.

Last year, the Government of India introduced breakthroughinitiatives for improving coverage of immunization and reducing
mortality and morbidity for all citizens, particularly the deprived
and vulnerable sections of society. Since India’s innovative
healthcare delivery initiatives must function across a wide
spectrum of geographical, agro-climatic, socio-economic,
and cultural diversity, the initiatives are adaptable and easy toreplicate in India or any other country.

CII is happy to be a 12-year partner in the GII, supporting its
goal to capture the multi-dimensional facets of innovation
across countries and assisting in tailoring GII policies topromote long-term growth, improved productivity, andjob creation. I wholeheartedly thank the GII team for their
passionate stewardship and in-depth research in bringing out
the 2019 report.

Chandrajit Banerjee
Director General
Confederation of Indian Industry

Prefaceix

x

The Global Innovation Index 2019

F O RE WO R D

HEALTH IN THE AGE OF EXPERIENCE

Healthcare is at the core of the Industry Renaissance that is
emerging worldwide with new ways of inventing, learning,producing, trading, and treating. We must no longer thinkof industry as a set of means of production, but instead as
a vision of the world and a process of value creation thatembraces all sectors in the economy and society. Today, we
see new categories of innovators creating new categories ofsolutions for new categories of customers, citizens, and patients.
As we enter the age of the experience economy—in which value
is in the usage rather than the product—innovation is driven
by consumer and patient experience. Today, society seeks
personalized health and tailored patient experiences while
ensuring optimum industrial security. Improving global healthrequires a holistic approach that includes cities, food, andeducation. It also implies a shift from reactive medicine topredictive and preventive approaches.
To achieve this multiscale purpose, we must connect people,
ideas, data, and solutions. Healthcare today calls for a
fresh and collaborative approach to innovation, which cuts
across scientific disciplines and breaks down silos to allow
education, research, big firms, retailers, and patients tocollaborate in real time.

Collaborative experience platforms are the infrastructure ofthis change. They provide a continuum of transformational
disciplines to imagine, create, produce, and operate experiencesfrom end to end. This is one of the primary functions of Dassault
Systèmes’ 3DEXPERIENCE platform. In addition to cross-disciplinary
collaboration, the platform empowers teams to conduct insilico 3D experiments, produce multiscale and multidisciplinary
digital models, simulate healthcare scenarios, and turn big
data into smart data. It connects biology, material sciences,multiscale and multiphysics simulation with model data andcommunities. This translates into continuous improvements inindustrial processes, enhanced and customized treatments, andthe development of new services from the lab to the hospitaland beyond. For example, a city platform like Virtual Singapore
is useful not only in city management but also in healthcare
management. In parallel, 3D printing is already changing how
prosthetics are designed. In the not too distant future, we will
be able to create the virtual twin of the human body—not justany body, but each individual’s own body. We will also see moredata brokers marketing health data to private firms, insurancecompanies, and others.
The time has come for the healthcare sector—governments,
businesses, researchers, and patients—to leverage thetremendous power of the virtual world. Virtual environments
are pushing the bounds of possibility to transform research,science, the pharmaceutical industry, and medicine. These
virtual environments will also empower the workforce of the
future with knowledge and know-how, while eliminating the
gap between experimentation and learning—both globallyand locally. Virtual worlds are revolutionizing our relationshipwith knowledge, just as the printing press did in the 15th century.
The new book is the virtual experience.

Bernard Charlès
Vice-Chairman and Chief Executive Officer
Dassault Systèmes

Forewordxi

xii

The Global Innovation Index 2019

F O RE WO R D

INNOVATION IN HEALTH AND MEDICINE:
NEW POSSIBILITIES FOR BRAZIL

Brazil could be a significant player in the international market for
health care. A majority of the population—approximately 210 million
people—is covered by the public health system. The country
spends over 9% of its GDP on health and, with an aging population,
this percentage is expected to increase. In addition to scienceand technology policies, the country has developed health policies,
such as the National Policy for Innovation in Health, which
encourages using public procurement to foster innovation in the
sector. Brazil is currently pursuing innovation in several areas,
including biopharmaceuticals and the use of digital technologies
to improve health care.
Today, innovating in health means a great deal more than justdeveloping new medicines. It means creating equipment capableof assisting in the diagnosis of diseases, developing medical
devices for health monitoring and treatment, and conceiving
customized treatments and protocols for each patient. Innovation
goes beyond technological innovation—taking multiple forms
that improve medicines, vaccines, and medical devices andthat consider prevention, treatment, and the broader healthcaredelivery and organization.

Robson Braga de Andrade
President; CNI; Director, SESI; President;
SENAI’s National Council

This broad view of innovation in health and medicine drives the
National Confederation of Industry–Brazil (CNI), Social Service
of Industry (SESI), National Service for Industrial Training (SENAI),
Euvaldo Lodi Institute (IEL), Brazilian Micro and Small BusinessSupport Service (SEBRAE), and the Entrepreneurial Mobilization for
Innovation (MEI). MEI is comprised of Brazilian business leaders,
including leaders of industries that serve the health and medicine
sector, who have been promoting innovation as the center ofstrong business strategy and aiming to increase the strengthand efficiency of innovation policies in Brazil. CNI, SESI, SENAI,
IEL, SEBRAE, and MEI are confident that the emergence ofintelligent, interconnected devices, sensors, and mobile trackers
are essential for the country to develop telemedicine, which
is one of the emerging technologies in this field. Artificial
intelligence (AI) is another promising technology in health that is
gaining momentum due to the expansion of information processing
capacity and data availability. AI can be used, among otherthings, to reduce medical errors. In countries like Brazil, where
it is difficult for doctors to reach all regions of the country, telemedicine
and AI could prove helpful in advancing medical care.
CNI, SESI, SENAI, IEL, and SEBRAE strive to stimulate research andinnovation and to promote the competitiveness of the Brazilian
industry and economy. From academic studies to working incollaboration with legislative and executive branches in Brazil
to advocate broad and well-informed innovation policies, CNI,SESI, SENAI, IEL, and SEBRAE have made important contributions
to building a dynamic ecosystem for innovation in health andmedicine in Brazil. The Global Innovation Index (GII) has played an
influential role in this effort by sharing data and insights that guidecountries on how to build a more innovative economy.

Carlos Melles
President, SEBRAE

Foreword

xiii

xiv

KEY FINDINGSFIGURE A

Global leaders in innovation in 2019
Every year, the Global Innovation Index ranks the innovation performance of nearly
130 economies around the world.
Top 3 innovation economies by region
NORTHERN AMERICAEUROPENORTHERN AFRICA AND
WESTERN ASIA

SOUTH EAST ASIA,
EAST ASIA, AND OCEANIA

1. U.S.

1. Switzerland

1. Israel

1. Singapore

2. Canada

2. Sweden ↑2. Cyprus

2. Republic of Korea

3. Netherlands ↓3. United Arab Emirates

3. Hong Kong, China ★

2

1

3
4

5

6

7

LATIN AMERICA AND
THE CARIBBEAN

SUB-SAHARAN AFRICA

CENTRAL AND
SOUTHERN ASIA

1. Chile

1. South Africa

1. India

2. Costa Rica

2. Kenya ↑2. Iran

3. Mexico

3. Mauritius ↓3. Kazakhstan↑↓ indicates the movement of rank within the top 3 relative to 2018, and ★ indicates a new entrant into the top 3 in 2019.
Top 3 innovation economies by income group
HIGH INCOME

UPPER-MIDDLE INCOME

LOWER-MIDDLE INCOME

LOW INCOME

1. Switzerland

1. China

1. Viet Nam ↑1. Rwanda ↑2. Sweden ↑2. Malaysia

2. Ukraine ↓2. Senegal ↑3. U.S. ★

3. Bulgaria

3. Georgia ★

3. Tanzania ↓Source: Figure 1.4 in Chapter 1.

xvi

The Global Innovation Index 2019

K E Y F I N D IN G S

KEY FINDINGS2019

The main messages of the Global Innovation Index 2019 can besummarized in seven key findings.

1: Amid economic slowdown, innovationis blossoming around the world;
but new obstacles pose risks to global
innovation
Global economic growth appears to be losing momentum
relative to last year. Productivity growth is at a record low.
Trade battles are brewing. Economic uncertainty is high.
Despite this gloomy perspective, innovation is blossoming
around the world. In developed and developing economies alike,formal innovation—as measured by research and development(R&D) and patents—and less formal modes of innovation
are thriving.
Today, developed and developing economies of all types
promote innovation to achieve economic and social development.
It is now also better understood that innovation is taking placein all realms of the economy, not only in high-tech companies
and technology sectors. As a result, economies are firmly
centering their attention on the creation and upkeep of soundand dynamic innovation ecosystems and networks.
The world witnessed an increase in innovation investments
over recent years, as measured by the average investmentsof economies across all levels of development. The use of
intellectual property (IP) reached record highs in 2017 and 2018.

Global R&D expenditures have been growing faster than the
global economy, more than doubling between 1996 and 2016.
In 2017, global government expenditures in R&D (GERD) grewby about 5% while business R&D expenditures grew by 6.7%,
the largest increase since 2011 (Figure B and C). Never in history
have so many scientists worldwide labored at solving the mostpressing global scientific challenges.
What can we expect in terms of innovation efforts in the years
to come?
Despite economic uncertainty, innovation expenditures
have been growing and seem resilient in light of the current
economic cycle.
As global economic growth declines in 2019, the question iswhether this trend will continue. Two concerns stand out:First, the GII 2019 shows that public R&D expenditures—inparticular, in some high-income economies responsible fordriving the technology frontier—are growing slowly or not at all.
Waning public support for R&D in high-income economies isconcerning given its central role in funding basic R&D and otherblue sky research, which are key to future innovations—
including for health innovation, this year’s GII theme.
Second, increased protectionism—in particular, protectionismthat impacts technology-intensive sectors and knowledge
flows—poses risks to global innovation networks and innovation
diffusion. If left uncontained, these new obstacles to international
trade, investment, and workforce mobility will lead to a
slowdown of growth in innovation productivity and diffusion
across the globe.

Key Findings

xvii

FIGURE B

R&D expenditure growth, 2000-2017

9

8

7

Business
R&D growth
6

Total
R&D growth

5

4

GDP
growth

3

2

1

0

-1
2000

2002

▲ %
⊲ Year

Source: Figure 1.3 in Chapter 1.

xviii

The Global Innovation Index 2019

2004

2006

2008

GDP growth forecast

2010

2012

2014

2016

2018

2019

FIGURE C

Regional and economy shares in world business expenditures, 2017

Other
Argentina

Colombia
Saudi
ArabiaMexicoOther

United Arab Emirates

Switzerland

IsraelEgypt

Denmark

Other
FranceSouth Africa
Italy

Belgium
Germany

NorwayAustria

SwedenUnitedKingdom

PolandNetherlands
Spain

Chile

BrazilTurkeyRussianFederation

Finland

Japan

Other

Ireland

CanadaChina

Australia

United States of America

Republic of Korea

Malaysia
Indonesia
Singapore

India
Pakistan
Iran Northern America
 Europe

Hong Kong, China
Other

Philippines
ThailandBangladesh
Other South East Asia, East Asia, and Oceania
 Northern Africa and Western Asia
 Latin America and the Caribbean

 Central and Southern Asia
 Sub-Saharan Africa

Source: Figure 1.2 in Chapter 1.

Key Findingsxix

2: Shifts in the global innovation
landscape are materializing;some middle-income economies
are on the riseThis year, again, the geography of innovation is changing.
In the top echelon, Switzerland, Sweden, and the United Statesof America (U.S.) lead the innovation rankings, with the latter
two moving up in GII 2019. Other European nations, such as the
Netherlands and Germany, along with Singapore in Asia, remain
consistent members of the GII top 10. This year, Israel moves
up to the 10th position, marking the first time an economy fromthe Northern Africa and Western Asia region cracks the top
10 rankings.
In the top 20, the Republic of Korea edges closer to the top
10. China, continues its upward rise, moving to 14th (from 17th in2018), and thus firmly establishing itself in the group of leading
innovative nations. China remains the only middle-income
economy in the top 30. China’s innovation strengths become
evident in numerous areas; it maintains top ranks in Patents byorigin, Industrial designs, and Trademarks by origin as well as
High-tech net exports and Creative goods exports.
Notable moves in GII rankings this year include the United ArabEmirates (36th); Viet Nam (42nd), and Thailand (43rd) getting
closer to the top 40; India (52nd) getting closer to the top 50;
the Philippines (54th) breaking into the top 55; and the Islamic
Republic of Iran (61st) getting closer to the top 60.
The performance improvement of India is particularly noteworthy.
India continues to be the most innovative economy in Central &Southern Asia—a distinction held since 2011 (Figure A)—improving
its global rank to 52nd in 2019. India is consistently among the
top in the world in innovation drivers such as ICT services
exports, Graduates in science & engineering, the quality ofuniversities, Gross capital formation—a measure of economy-wide
investments—and Creative goods exports. India also stands
out in the GII ranking of the world’s top science and technology
clusters (Key Finding #6), with Bengaluru, Mumbai, and New
Delhi featuring prominently among the global top 100 clusters.
Given its size—and if progress is upheld—India will make a true
impact on global innovation in the years to come.
As always, it must be noted that for year-on-year comparisonsof the above type, GII ranks are influenced by various factors,
such as changes in metrics and data availability.
When comparing levels of innovation to the level of economic
development, India, Viet Nam, Kenya, and the Republic ofMoldova stand out for outperforming on innovation relative to
GDP for the ninth consecutive year—a record.
Other economies also outperform in innovation relative to theirGDP, catching-up with innovation leaders more quickly thantheir peers (Table A). Middle-income economies outperformingxx

The Global Innovation Index 2019

on innovation relative to their level of development include, forexample, Costa Rica—the only country in Latin America and the
Caribbean—South Africa, Thailand, Georgia, and the Philippines.
Burundi, Malawi, Mozambique, and Rwanda stand out as thriving
economies within the low-income group.
As in previous years, Africa shines in terms of innovation relative
to level of development. Out of the 18 innovation achievers
identified in the GII 2019, six (the most from any one region)are from the Sub-Saharan African region. Importantly, Kenya,
Rwanda, Mozambique, Malawi, and Madagascar stand out forbeing innovation achievers at least three times in the previous
eight years.

3: Innovation inputs and outputs
are still concentrated in very few
economies; a global innovation
divide persists
The geography of innovation is shifting from high-income to
middle-income economies. Nonetheless, innovation expenditures
remain concentrated in a few economies and regions. Movingfrom a successful middle-income economy with innovation
potential into an innovation powerhouse remains hard; animpermeable innovation glass ceiling exists that divides middleand high-income economies. Most of the drive to breakthrough that ceiling comes from China and to some extent India,
Brazil, and the Russian Federation.
In terms of innovation scores and ranks, the innovation divide
is evident across the GII—existing between income groups
and across all GII pillars, from Institutions to Creative outputs(Figure E).
On a regional level, continuous innovation performance
improvements are primarily happening in Asia. Other world
regions struggle to catch up with Northern America, Europe,and South East Asia, East Asia, and Oceania.
It will take time and persistence, perhaps over decades, for
the innovation policy ambitions of economies at all levels to
influence the global innovation landscape.

4: Some economies get more
return on their innovation investments
than others
A divide also exists in how effective economies are in translating
innovation inputs into innovation outputs (Figure F); some
economies simply achieve more with less. This discrepancy exists
even among high-income economies: while Switzerland, theNetherlands, and Sweden effectively translate their innovation
inputs into a higher level of outputs, Singapore (8th) and theUnited Arab Emirates (36th), for example, produce lower levelsof output relative to their innovation inputs.

FIGURE D

Movement in the GII, top 10, 2019

2019

1

2

3

4

5

6

7

8

9

10

CH

SE

US

NL

GB

FI

DK

SG

DE

IL
Israel enters
the top 10
for the ﬁrst timein 2019.

2018

2017

CH

CH

NL

SE

SE

NL

GB

US

SG

GB

US

DK

FI

SG

DK

FI

DE

DE

IE

IE

In 2018,
Singaporemakes it to
the top 5of the GII.

The Netherlands
entered the top 3
in 2017. Sweden
maintained
2nd place for thesecond time.

Germany
re-entered the
top 10 in 2016.
2016

CH

SE

GB

US

FI

SG

IE

DK

NL

DE

Since 2011,
Switzerland has
ranked 1st in the
GII every year.
2015

CH

GB

CH Switzerland
GB United Kingdom
SE Sweden

SE

NL

US

FI

NL Netherlands
US United States of America
FI Finland

SG

IE

LU

SG Singapore
IE Ireland
LU Luxembourg

DK

DK Denmark
DE Germany
IL Israel

Source: Figure 1.5 in Chapter 1.

Key Findingsxxi

TABLE A

Innovation performance at different income levels, 2019
High Income

Above
expectations
for level ofdevelopment

In line withexpectations
for level ofdevelopment

Upper-middle Income
Armenia

Georgia

BurundiFinland

China

India

Malawi

Netherlands

Costa Rica

Kenya

MozambiqueSingaporeMontenegro

Mongolia

RwandaSweden

North Macedonia

Philippines

Senegal

Switzerland

South Africa

Republic of Moldova

United Republic of Tanzania

United Kingdom

ThailandUkraineTajikistan

United States of America

Malaysia

Viet Nam

UgandaGermany

Bulgaria

Tunisia

Nepal

IsraelRomania

MoroccoEthiopia

Republic of Korea

MexicoIndonesia

Mali

Ireland

SerbiaSri Lanka

Burkina Faso

Hong Kong, China

Iran (Islamic Republic of)

Kyrgyzstan

Madagascar

Japan

BrazilEgypt

Zimbabwe

FranceColombia

Cambodia

Niger

CanadaPeru

Côte d’Ivoire

Benin

Luxembourg

Belarus

Honduras

GuineaNorwayBosnia and Herzegovina

Cameroon

Togo

Iceland

Jamaica

Pakistan

Yemen

Austria

Albania

Ghana

Australia

Azerbaijan

El Salvador

Belgium

JordanBolivia (Plurinational State of)Estonia

LebanonNigeria

New ZealandRussian Federation

Bangladesh

Czech RepublicTurkeyNicaragua

Malta

Kazakhstan

ZambiaCyprus

Mauritius

Spain

Dominican Republic

Italy

Botswana

Slovenia

Paraguay

Portugal

EcuadorHungary

Namibia

LatviaGuatemalaSlovakia

Algeria

GreeceCroatia
Chile
UruguayArgentina
United Arab Emirates
Lithuania
Kuwait
Qatar
Saudi Arabia
Brunei Darussalam
PanamaBahrainOman
Trinidad and Tobago

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.

xxii

Low Income

Denmark

PolandBelow
expectations
for level ofdevelopment

Lower-middle Income

The Global Innovation Index 2019

FIGURE E

Innovation divide across income groups, 2019
1
2
3
4
5
6

1
2
3
4
5
6

89.1
85.2
70.9
61.3
53.8
50.5

INSTITUTIONS

1
2
3
4
5
6

HUMAN CAPITAL AND
RESEARCH

63.4
61.9
53.3
44.2
37.4
29.2

1
2
3
4
5
6

INFRASTRUCTURE

1
2
3
4
5
6

66.9
61.5
49.3
47.5
45.9
36.5

MARKETSOPHISTICATION
1
2
3
4
5
6

Top 10 high income
11 to 25 high and upper-middle income

3
4

65.6
51.8
35.6
29.8
26.4
24.3

BUSINESSSOPHISTICATION
1
2
3
4
5
6

57.2
41.5
25.9
19.9
20.2
12.8

KNOWLEDGE ANDTECHNOLOGY OUTPUTS

1
2

59.9
51.5
37.3
29.0
21.5
15.2

49.0
45.4
32.6
25.7
22.7
15.1

CREATIVE OUTPUTS

Other high income
Other upper-middle income

5
6

Lower-middle income
Low income

Source: Box 2, Figure 1 in Chapter 1.

Key Findings

xxiii

FIGURE F

Innovation input/output performance by income group, 201970

CH
Group 2

60

NL
IL

CN

DE

FI

SE
US

Highlight 2

50
CZ

SG Group 3

Highlight 1
40
VN

IN

30

AE

KW
TZ

QA
BH

20
Group 1

TT

OM
BN

ZM
10

0
20

30

40

50

70

60

▲ Output score⊲ Input score● High income● Upper-middle income● Lower-middle income● Low income— Fitted values

AE
BH
BN
CH
CN

CZ
DE
FI
IL
IN
KW

NL Netherlands
OM Oman
QA Qatar
SE Sweden
SG Singapore
TT Trinidad and Tobago

TZ

United Arab Emirates
BahrainBrunei Darussalam
Switzerland
China

Source: Figure 1.8 in Chapter 1.

xxiv

The Global Innovation Index 2019

Czech Republic
Germany
FinlandIsraelIndia
Kuwait80

United Republicof Tanzania
US United States of America
VN Viet Nam
ZM Zambia

China (CN), Malaysia, and Bulgaria are the only middle-income
economies that perform as well on most GII innovation input andoutput measures as the high-income group. China stands out for
producing innovation output that is equivalent to Germany (DE),the U.K., Finland (FI), Israel (IL), and the United States of America(US)—but with considerably lower levels of input.
Among lower middle-income economies, Viet Nam (VN) andIndia (IN) are among a small group of countries that achieve highimpact for their innovation efforts. In the low-income group, theUnited Republic of Tanzania (TZ) achieves the same (Figure F).

5: Shifting focus from innovation
quantity to innovation quality
remains a priority
Assessing the quality, rather than only the quantity, of innovation
inputs and outputs has become an overarching concern to theinnovation policy community.
The GII makes a modest attempt at measuring innovation quality
by looking at 1) the quality of local universities (QS university
ranking); 2) the internationalization of patented inventions(Patent families 2+ offices); and 3) the quality of scientific publications(Citable documents H-index).
Among the high-income economies, the U.S. regains the top
rank—moving ahead of Japan, which moves down to 3rd thisyear (Figure G). For the first time, Germany has moved up to 2nd.

The ranking of middle-income economies in these innovation
quality indicators remains steady, with China, India, and theRussian Federation in the top 3 positions. Positioned 15th
globally, China is the only middle-income economy that is
closing the gap with the high-income group in all three indicators.
India ranks 2nd among the middle-income economies, with
top positions in quality of universities and in quality of scientificpublications.
With regards to the quality of universities, the U.S. and the U.K.
occupy the top 2 positions in the GII 2019, followed by China,
which takes the 3rd spot this year (moving up from the 5th
position in 2018). In the middle-income group, China is followedby Malaysia and India, thanks to the high scores for their
top universities. The Russian Federation, Mexico, and Brazil
also appear in the top 10, due largely to the quality of their
universities (Table B).
Regarding the quality of publications, rankings are rather stablewith the U.S., the U.K., and Germany leading the GII rankings.
Among middle-income economies, China takes the top position,
followed by India.
Regarding international patents, European countries take sevenof the top 10 positions—with the three remaining spots going
to Israel, Japan, and the Republic of Korea. Among the
middle-income economies, China and South Africa take the
top two positions, with India and Turkey registering improvementsin this indicator.

TABLE BTop 10 universities in middle-income economies
Location

University

Score

China

Tsinghua University

87.2

China

Peking University

82.6

China

Fudan University

77.6

Malaysia

Universiti Malaya (UM)62.6

Russian Federation

Lomonosov Moscow State University

62.3

MexicoUniversidad Nacional Autónoma de México (UNAM)

56.8

BrazilUniversidade de São Paulo (USP)

55.5

India

Indian Institute of Technology Bombay (IITB)

48.2

India

Indian Institute of Science (IISC) Bengaluru

47.1

India

Indian Institute of Technology Delhi (IITD)

46.6

Source: Table 1.3 in Chapter 1.

Key Findings

xxv

FIGURE G

Metrics for quality of innovation: top 10 high- and middle-income
economies, 2019
High-income economies
1

United States of America

2Germany

3

Japan

4

Switzerland

5

United Kingdom

6

Netherlands

7

Sweden8

Republic of Korea

9

France10 Canada
Average (50 economies)

Middle-income economies
15 China
26 India
27 Russian Federation
28 Brazil
32 Malaysia
33 Mexico
36 South Africa
41 Turkey
43 Colombia
44 Thailand
Average (60 economies)0⊲ Sum of scores

Source: Figure 1.7 in Chapter 1.

xxvi

The Global Innovation Index 2019

■
■
■

50

100

150

200

2.3.4: QS university ranking average score of top 3 universities
5.2.5: Patent famililes ﬁled in two or more oﬃces
6.1.5: Citable documents H-index

250

300

6: Most top science and technology
clusters are in the U.S., China, andGermany; Brazil, India, Iran, theRussian Federation, and Turkey also
make the top 100 list
As in the previous two years, the GII 2019 includes a Special
Section, which presents the latest ranking of the world’s largest
science and technology (S&T) clusters.
The top 10 clusters are the same as last year (Table C). Tokyo–
Yokohama tops this ranking, followed by Shenzhen–Hong Kong.
Figure H shows the concentration of top science and technology
clusters worldwide. The U.S. continues to host the largest numberof clusters (26), followed by China (18, two more than in 2018),
Germany (10), France (5), the U.K. (4), and Canada (4). Australia,
India, Japan, the Republic of Korea, and Switzerland all hosted
three clusters each. In addition, there are clusters from fivemiddle-income economies in the top 100—Brazil, India, theIslamic Republic of Iran, the Russian Federation, and Turkey.

TABLE CTop cluster of economies orcross-border regions within
the top 50, 2019

Compared to last year, almost all Chinese clusters moved
up the ranks.
Also, compared to last year, there is a notable shift in the
distribution of top patenting fields. Coinciding with this year’s
GII theme, medical technology is now the most frequent
patenting field—present in 19 clusters. Pharmaceuticals dropped
to second place.
Beijing is the top collaborating cluster for scientific co-authorships,
followed by Washington, DC–Baltimore, MD; New York City, NY;
Boston–Cambridge, MA; and Cologne, Germany. San Jose–San Francisco, CA is the most frequent top co-inventing cluster,followed by Beijing; Shenzhen–Hong Kong; and New York City,
NY. The Chinese Academy of Sciences was the top academic
entity for all of Beijing's collaborations. Entities that also drove
their clusters’ collaborations were Johns Hopkins University (8,Washington, DC–Baltimore, MD), Columbia University (7, New York
City, NY), and Harvard University (6, Boston–Cambridge, MA).

7: Creating healthy lives throughmedical innovation requires
more investment in innovationand increased diffusion efforts

Rank

Cluster name

Economy(ies)

The 2019 GII theme is Creating Healthy Lives—The Future of
Medical Innovation, which explores the role of medical innovation as it shapes the future of healthcare. In the years to come,medical innovations such as artificial intelligence (AI), genomics,
and mobile health applications will transform the delivery ofhealthcare in both developed and emerging nations.

1

Tokyo-Yokohama

JP

The key questions addressed in this edition of the GII include:2

Shenzhen-Hong Kong

CN/HK

3

Seoul

KR

4

Beijing

CN

5

San Jose-San Francisco, CA

US

9

Paris

FR

15

LondonGB

18

Amsterdam-Rotterdam

NL

20

CologneDE23

Tel Aviv-Jerusalem

IL

28

SingaporeSG

31

Eindhoven

BE/NL

32

Stockholm

SE

33

Moscow

RU

35

Melbourne

AU

39

Toronto, ON

CA

40

BrusselsBE

42

MadridES

46

Tehran

IR

48

Milan

IT

50

ZürichCH/DE

Source: Special Section: Identifying and ranking the world’s largest scienceand technology clusters (Cluster Rankings).

• What is the potential impact of medical innovation onsociety and economic growth, and what obstacles must be
overcome to reach that potential?
• How is the global landscape for R&D and medical innovation
changing?
• What health challenges do future innovations need to address
and what types of breakthroughs are on the horizon?
• What are the main opportunities and obstacles to future
medical innovation and what role might new policies play?
The following six learnings emerge:• High quality and affordable healthcare for all is important forsustainable economic growth and the overall quality of lifeof citizens. While significant progress has been achieved
across many dimensions over the last decades, significant
gaps in access to quality healthcare for large parts of the
global population remain.

Key Findings

xxvii

FIGURE H

Top science and technology clusters worldwide, 2019

Clusters

Source: Special Section: Cluster Rankings

xxviii

The Global Innovation Index 2019

Noise

0

2500

5000 km• Medical innovations are critical for closing the gaps in global
healthcare provision. Yet, nowadays, there are obstacles tohealth innovation and its diffusion which urgently need to be
overcome. First, in the recent past, productivity in healthcare
R&D has slowed; the identification of new cures for new
diseases is painstakingly long. As a result, many acuteand chronic conditions, such as cancer, depression, or
Alzheimer’s, have not yet been matched with breakthroughcures. Second, innovations in healthcare generally diffuse
more slowly relative to other sectors. Moving medical
innovations from “bench to bedside” is a long process,sometimes over decades. This is due to the complexityof the health innovation ecosystem and the diverging
incentives of healthcare actors at play.
• Thankfully, a resurgence of health R&D and health innovation
is taking place, possibly helping to overcome the innovation
productivity decline of the pharmaceutical industry in
the past decades. These innovations are happening acrossmultiple dimensions, including core sciences, drug
development, care delivery, and organizational and businessmodels. Figure I shows the most promising fields for medical
innovation in the years to come. In particular, medical
technology related innovations are blossoming, withmedical technology patents more numerous and growing
at a faster path than pharmaceutical patents for the last
decade (Figure J).

• Emerging markets have a unique opportunity to leverage
medical innovations and invest in new healthcare delivery
models to close the healthcare gap with more developed
markets. Caution should be taken to ensure that new healthinnovations, and their related costs, do not exacerbate
the health gap between the rich and poor. The true
challenge for developing economies is often the lack ofminimally functional health systems—and not necessarily
a need for more R&D or new technologies. Low-tech or
adapted technology applications can save more lives thanthe latest high-tech solutions.
• Finally, the GII 2019 report suggests a few key healthinnovation policy priorities, including the importance ofensuring sufficient medical innovation funding, in particularfor public sector research; building functional medical
innovation systems; facilitating the innovation path from“bench to bedside”; establishing and maintaining a skilled
health workforce; moving from research on cures toinnovation in the field of prevention; carefully evaluating
the costs and benefits of medical innovations; supporting
new data infrastructure and digital health strategies tofocus on creating data infrastructure; and developing
processes for efficient and safe data collection, management,
and sharing.

• The convergence of digital and biological technologies
is disrupting healthcare and increasing the importance ofdata integration and management across the healthcare
ecosystem. Innovation in the field of health now massively
evolves around big data, the internet of things and artificial
intelligence, entailing huge power shifts within and awayfrom the health sector. This phenomenon will also drive
future health-related innovation into non-technological fields,such as business model reorganization and new processes,
rather than new technologies alone.

Key Findings

xxix

FIGURE I

Promising ﬁelds for medical innovation and technologies
NEW SCIENTIFIC BREAKTHROUGHS,TREATMENTS, AND CURESNew generation of vaccines
and immunotherapy

Genetics and stem cell research— Single-cell analysis— Gene and stem cell therapies— Genetic engineering and editing
including CRISPR technology— HIV and universal ﬂu vaccine— Cancer vaccine— Immunotherapy— New vaccine delivery methods

Nanotechnology— Swallowable small devices

Pain management

Biologics— Development and manufactureof complex biologics— Eﬀective, non-addictive medicines forpain management

Brain research, neurology, andneurosurgery

Mental health treatments— Pre-symptomatic diagnosis and treatmentof Alzheimer’s disease and othercognitive declines— Characterization of the brain’s major circuits— New brain imagery for mental disorders— Migraine treatment

NEW MEDICAL TECHNOLOGIESPrecision and personalized
medicine

Medical devices— 3D printing— Cardiac devices— Implants and bionics— Computer-assisted surgery— Surgical robots— Personalized medicine

Medical imaging and diagnostics

Regenerative medicine— Optical high-deﬁnition imaging and virtualanatomic models— Biosensors and markers— 4D human charting and virtual reality— Screening for diseases— Tissue engineering— Eﬀective bioartiﬁcial pancreas

ORGANIZATIONAL AND PROCESSINNOVATIONSNovel approaches in healthcare
research

New ways of delivering
healthcare— Software-based modeling to speed
up research— Artiﬁcial intelligence techniques tospeed up research and clinical trials— Telemedicine applications— Drone delivery of medications— Remote monitoring and portablediagnostics— Improved data sharing

Source: Figure T-1.4 in Theme Section.

xxx

The Global Innovation Index 2019

FIGURE J

Patent Cooperation Treaty (PCT) ﬁlings by technology, 2000-2018
35,00030,00025,00020,000PHARMACEUTICALS

15,000

BIOTECHNOLOGY
10,0005,000

MEDICAL TECHNOLOGY

0
2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

▲ Patent publications⊲ Year

Source: Figure T-1.3 in Theme Section.

Key Findings

xxxi

xxxii

The Global Innovation Index 2019RANKINGS

Advisory Board

xxxiiiGlobal Innovation Index 2019 rankings
Country/Economy
Switzerland
SwedenUnited States of America
Netherlands
United Kingdom
FinlandDenmark
Singapore
Germany
IsraelRepublic of Korea
IrelandHong Kong, China
China
Japan
FranceCanadaLuxembourg
NorwayIceland
Austria
Australia
Belgium
Estonia
New ZealandCzech Republic
Malta
CyprusSpain
Italy
Slovenia
Portugal
Hungary
LatviaMalaysia
United Arab Emirates
Slovakia
Lithuania
PolandBulgaria
GreeceViet Nam
ThailandCroatia
Montenegro
Russian Federation
UkraineGeorgia
TurkeyRomania
Chile
India
Mongolia
Philippines
Costa Rica
MexicoSerbiaRepublic of Moldova
North Macedonia
KuwaitIran (Islamic Republic of)
UruguaySouth Africa
Armenia
Qatar

Score
(0–100)

Rank

IncomeRank

Region

Rank

67.24
63.65
61.73
61.44
61.30
59.83
58.44
58.37
58.19
57.43
56.55
56.10
55.54
54.82
54.68
54.25
53.88
53.47
51.87
51.53
50.94
50.34
50.18
49.97
49.55
49.43
49.01
48.34
47.85
46.30
45.25
44.65
44.51
43.23
42.68
42.17
42.05
41.46
41.31
40.35
38.90
38.84
38.63
37.82
37.70
37.62
37.40
36.98
36.95
36.76
36.64
36.58
36.29
36.18
36.13
36.06
35.71
35.52
35.29
34.55
34.43
34.32
34.04
33.98
33.86

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65

HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
UM
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
UM
HI
HI
HI
HI
UM
HI
LM
UM
HI
UM
UM
LM
LM
UM
UM
HI
LM
LM
LM
UM
UM
UM
LM
UM
HI
UM
HI
UM
UM
HI

1
2
3
4
5
6
7
8
9
10
11
12
13
1
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
2
34
35
36
37
3
38
1
4
39
5
6
2
3
7
8
40
4
5
6
9
10
11
7
12
41
13
42
14
15
43

EUR
EUR
NAC
EUR
EUR
EUR
EUR
SEAO
EUR
NAWA
SEAO
EUR
SEAO
SEAO
SEAO
EUR
NAC
EUR
EUR
EUR
EUR
SEAO
EUR
EUR
SEAO
EUR
EUR
NAWA
EUR
EUR
EUR
EUR
EUR
EUR
SEAO
NAWA
EUR
EUR
EUR
EUR
EUR
SEAO
SEAO
EUR
EUR
EUR
EUR
NAWA
NAWA
EUR
LCN
CSA
SEAO
SEAO
LCN
LCN
EUR
EUR
EUR
NAWA
CSA
LCN
SSF
NAWA
NAWA

1
2
1
3
4
5
6
1
7
1
2
8
3
4
5
9
2
10
11
12
13
6
14
15
7
16
17
2
18
19
20
21
22
23
8
3
24
25
26
27
28
9
10
29
30
31
32
4
5
33
1
1
11
12
2
3
34
35
36
6
2
4
1
7
8

Median33.86

CONTINUED
xxxiv

The Global Innovation Index 2019

Global Innovation Index 2019 rankings, continued
Country/Economy

Score(0–100)

Rank

IncomeRank

RegionRank

BrazilColombia
Saudi Arabia
Peru
Tunisia
Brunei Darussalam
BelarusArgentina
MoroccoPanamaBosnia and Herzegovina
Kenya
BahrainKazakhstan
Oman
Jamaica
Mauritius
Albania
Azerbaijan
Indonesia
JordanDominican Republic
LebanonSri Lanka
Kyrgyzstan
Trinidad and Tobago
Egypt
Botswana
RwandaParaguay
SenegalUnited Republic of Tanzania
Cambodia
EcuadorTajikistan
Namibia
UgandaCôte d’Ivoire
Honduras
Pakistan
Ghana
Guatemala
El Salvador
Nepal
Bolivia (Plurinational State of)Ethiopia
Mali
Algeria
Nigeria
Cameroon
Bangladesh
Burkina Faso
MalawiMozambique
Nicaragua
Madagascar
Zimbabwe
Benin
ZambiaGuineaTogo
Niger
Burundi
Yemen

33.82
33.00
32.93
32.93
32.83
32.35
32.07
31.95
31.63
31.51
31.41
31.13
31.10
31.03
30.98
30.80
30.61
30.34
30.21
29.72
29.61
28.56
28.54
28.45
28.38
28.08
27.47
27.43
27.38
27.09
26.83
26.63
26.59
26.56
26.43
25.85
25.60
25.55
25.48
25.36
25.27
25.07
24.89
24.85
24.76
24.16
24.03
23.98
23.93
23.90
23.31
23.30
23.00
22.87
22.55
22.38
22.30
20.42
20.36
19.50
18.54
18.13
17.65
14.49

66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129

UM
UM
HI
UM
LM
HI
UM
HI
LM
HI
UM
LM
HI
UM
HI
UM
UM
UM
UM
LM
UM
UM
UM
LM
LM
HI
LM
UM
LI
UM
LI
LI
LM
UM
LI
UM
LI
LM
LM
LM
LM
UM
LM
LI
LM
LI
LI
UM
LM
LM
LM
LI
LI
LI
LM
LI
LI
LI
LM
LI
LI
LI
LI
LI

16
17
44
18
8
45
19
46
9
47
20
10
48
21
49
22
23
24
25
11
26
27
28
12
13
50
14
29
1
30
2
3
15
31
4
32
5
16
17
18
19
33
20
6
21
7
8
34
22
23
24
9
10
11
25
12
13
14
26
15
16
17
18
19

LCN
LCN
NAWA
LCN
NAWA
SEAO
EUR
LCN
NAWA
LCN
EUR
SSF
NAWA
CSA
NAWA
LCN
SSF
EUR
NAWA
SEAO
NAWA
LCN
NAWA
CSA
CSA
LCN
NAWA
SSF
SSF
LCN
SSF
SSF
SEAO
LCN
CSA
SSF
SSF
SSF
LCN
CSA
SSF
LCN
LCN
CSA
LCN
SSF
SSF
NAWA
SSF
SSF
CSA
SSF
SSF
SSF
LCN
SSF
SSF
SSF
SSF
SSF
SSF
SSF
SSF
NAWA

5
6
9
7
10
13
37
8
11
9
38
2
12
3
13
10
3
39
14
14
15
11
16
4
5
12
17
4
5
13
6
7
15
14
6
8
9
10
15
7
11
16
17
8
18
12
13
18
14
15
9
16
17
18
19
19
20
21
22
23
24
25
26
19

Median33.86

Notes: World Bank Income Group Classification (July 2018): LI = low income; LM = lower-middle income; UM = upper-middle income; and HI = high income.
Regions are based on the United Nations Classification: EUR = Europe; NAC = Northern America; LCN = Latin America and the Caribbean; CSA = Central andSouthern Asia; SEAO = South East Asia, East Asia, and Oceania; NAWA = Northern Africa and Western Asia; SSF = Sub-Saharan Africa.
Rankings

xxxv

Innovation Input Sub-Index rankings
Country/Economy
Singapore
Switzerland
United States of America
SwedenDenmark
United Kingdom
FinlandHong Kong, China
CanadaRepublic of Korea
Netherlands
Germany
NorwayJapan
Australia
FranceIsraelNew ZealandAustria
Ireland
Belgium
Iceland
Luxembourg
United Arab Emirates
Spain
China
Estonia
CyprusCzech Republic
Italy
Portugal
Malta
Slovenia
Malaysia
Brunei Darussalam
LatviaPolandLithuania
Hungary
GreeceRussian Federation
Slovakia
Chile
Georgia
Bulgaria
Croatia
ThailandPeru
Saudi Arabia
BelarusSouth Africa
North Macedonia
Qatar
Romania
Montenegro
TurkeyOman
Colombia
MexicoBrazilIndia
SerbiaViet Nam
Kazakhstan
RwandaScore(0–100)

Rank

IncomeRank

Region

Rank

72.15
71.02
70.85
70.43
69.33
68.22
68.04
66.69
66.40
65.95
65.40
65.28
65.27
65.03
64.35
63.50
63.28
63.09
62.82
62.13
60.73
59.07
57.73
57.65
57.29
56.88
56.10
55.54
55.43
54.74
54.69
54.58
54.10
52.93
51.74
51.29
50.97
50.58
50.35
50.20
49.11
48.54
48.26
48.19
48.08
47.37
46.58
46.50
46.40
46.02
45.74
45.72
45.59
45.51
45.43
45.26
45.08
45.06
44.74
44.71
44.66
44.50
43.75
43.74
43.46

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65

HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
UM
HI
HI
HI
HI
HI
HI
HI
UM
HI
HI
HI
HI
HI
HI
UM
HI
HI
LM
UM
HI
UM
UM
HI
UM
UM
UM
HI
UM
UM
UM
HI
UM
UM
UM
LM
UM
LM
UM
LI

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
1
26
27
28
29
30
31
32
2
33
34
35
36
37
38
3
39
40
1
4
41
5
6
42
7
8
9
43
10
11
12
44
13
14
15
2
16
3
17
1

SEAO
EUR
NAC
EUR
EUR
EUR
EUR
SEAO
NAC
SEAO
EUR
EUR
EUR
SEAO
SEAO
EUR
NAWA
SEAO
EUR
EUR
EUR
EUR
EUR
NAWA
EUR
SEAO
EUR
NAWA
EUR
EUR
EUR
EUR
EUR
SEAO
SEAO
EUR
EUR
EUR
EUR
EUR
EUR
EUR
LCN
NAWA
EUR
EUR
SEAO
LCN
NAWA
EUR
SSF
EUR
NAWA
EUR
EUR
NAWA
NAWA
LCN
LCN
LCN
CSA
EUR
SEAO
CSA
SSF

1
1
1
2
3
4
5
2
2
3
6
7
8
4
5
9
1
6
10
11
12
13
14
2
15
7
16
3
17
18
19
20
21
8
9
22
23
24
25
26
27
28
1
4
29
30
10
2
5
31
1
32
6
33
34
7
8
3
4
5
1
35
11
2
2

Median43.46

CONTINUED
xxxvi

The Global Innovation Index 2019

Innovation Input Sub-Index rankings, continued
Country/Economy

Score(0–100)

Rank

IncomeRank

RegionRank

Uruguay
Mauritius
Costa Rica
Bahrain
Albania
Bosnia and Herzegovina
Argentina
Mongolia
Tunisia
KuwaitPhilippines
Azerbaijan
Kyrgyzstan
PanamaBotswana
Republic of Moldova
UkraineMoroccoJamaica
Armenia
Iran (Islamic Republic of)Indonesia
Trinidad and Tobago
Kenya
Dominican Republic
JordanLebanonNepal
Sri Lanka
Paraguay
UgandaEl Salvador
EcuadorNamibia
Algeria
Honduras
Bolivia (Plurinational State of)SenegalCambodia
Guatemala
Egypt
Tajikistan
Nicaragua
Ghana
Côte d’Ivoire
Burkina Faso
Cameroon
Pakistan
Benin
United Republic of Tanzania
Nigeria
Bangladesh
Mozambique
MalawiMali
Togo
Madagascar
Zimbabwe
Ethiopia
Niger
ZambiaGuineaBurundi
Yemen

43.31
43.25
42.95
42.89
42.42
42.41
42.34
42.24
42.13
41.90
41.68
41.59
41.48
41.06
40.86
40.77
40.73
39.91
39.47
39.36
39.00
38.64
38.63
38.07
37.86
37.10
37.08
36.71
36.07
35.93
35.66
35.62
35.42
34.97
34.64
34.46
34.43
33.58
33.51
33.33
33.32
33.12
32.96
32.80
32.43
32.32
31.71
31.62
31.49
31.47
31.46
31.07
30.92
30.76
30.73
29.79
29.30
29.22
28.23
27.99
27.97
27.76
26.54
22.53

66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129

HI
UM
UM
HI
UM
UM
HI
LM
LM
HI
LM
UM
LM
HI
UM
LM
LM
LM
UM
UM
UM
LM
HI
LM
UM
UM
UM
LI
LM
UM
LI
LM
UM
UM
UM
LM
LM
LI
LM
UM
LM
LI
LM
LM
LM
LI
LM
LM
LI
LI
LM
LM
LI
LI
LI
LI
LI
LI
LI
LI
LM
LI
LI
LI

45
18
19
46
20
21
47
4
5
48
6
22
7
49
23
8
9
10
24
25
26
11
50
12
27
28
29
2
13
30
3
14
31
32
33
15
16
4
17
34
18
5
19
20
21
6
22
23
7
8
24
25
9
10
11
12
13
14
15
16
26
17
18
19

LCN
SSF
LCN
NAWA
EUR
EUR
LCN
SEAO
NAWA
NAWA
SEAO
NAWA
CSA
LCN
SSF
EUR
EUR
NAWA
LCN
NAWA
CSA
SEAO
LCN
SSF
LCN
NAWA
NAWA
CSA
CSA
LCN
SSF
LCN
LCN
SSF
NAWA
LCN
LCN
SSF
SEAO
LCN
NAWA
CSA
LCN
SSF
SSF
SSF
SSF
CSA
SSF
SSF
SSF
CSA
SSF
SSF
SSF
SSF
SSF
SSF
SSF
SSF
SSF
SSF
SSF
NAWA

6
3
7
9
36
37
8
12
10
11
13
12
3
9
4
38
39
13
10
14
4
14
11
5
12
15
16
5
6
13
6
14
15
7
17
16
17
8
15
18
18
7
19
9
10
11
12
8
13
14
15
9
16
17
18
19
20
21
22
23
24
25
26
19

Median43.46

Notes: World Bank Income Group Classification (July 2018): LI = low income; LM = lower-middle income; UM = upper-middle income; and HI = high income.
Regions are based on the United Nations Classification: EUR = Europe; NAC = Northern America; LCN = Latin America and the Caribbean; CSA = Central andSouthern Asia; SEAO = South East Asia, East Asia, and Oceania; NAWA = Northern Africa and Western Asia; SSF = Sub-Saharan Africa.
Rankings

xxxviiInnovation Output Sub-Index rankings
Country/Economy
Switzerland
Netherlands
SwedenUnited Kingdom
China
United States of America
FinlandIsraelGermany
Ireland
Luxembourg
Denmark
Republic of Korea
FranceSingapore
Hong Kong, China
Japan
Iceland
Estonia
Malta
Czech Republic
CanadaCyprusBelgium
Austria
Hungary
NorwaySpain
Italy
Slovenia
Australia
New Zealand
Slovakia
LatviaPortugal
UkraineViet Nam
Bulgaria
Malaysia
Lithuania
PolandPhilippines
ThailandMongolia
Republic of Moldova
Montenegro
Iran (Islamic Republic of)
Costa Rica
TurkeyArmenia
India
Croatia
Romania
GreeceMexicoKuwaitSerbiaUnited Arab Emirates
Russian Federation
Georgia
Uruguay
Chile
North Macedonia
Kenya
TunisiaScore(0–100)

Rank

IncomeRank

Region

Rank

63.45
57.49
56.87
54.38
52.75
52.61
51.62
51.59
51.10
50.08
49.20
47.55
47.15
45.00
44.59
44.40
44.32
43.99
43.83
43.44
43.44
41.36
41.13
39.63
39.06
38.67
38.46
38.42
37.87
36.40
36.33
36.01
35.55
35.17
34.60
34.07
33.93
32.61
32.42
32.34
31.66
30.68
30.67
30.35
30.26
29.96
29.85
29.31
28.64
28.60
28.49
28.28
28.02
27.61
27.38
27.21
26.93
26.68
26.13
25.76
25.32
25.03
24.86
24.20
23.54

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65

HI
HI
HI
HI
UM
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
HI
LM
LM
UM
UM
HI
HI
LM
UM
LM
LM
UM
UM
UM
UM
UM
LM
HI
UM
HI
UM
HI
UM
HI
UM
LM
HI
HI
UM
LM
LM

1
2
3
4
1
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
1
2
2
3
35
36
3
4
4
5
5
6
7
8
9
6
37
10
38
11
39
12
40
13
7
41
42
14
8
9

EUR
EUR
EUR
EUR
SEAO
NAC
EUR
NAWA
EUR
EUR
EUR
EUR
SEAO
EUR
SEAO
SEAO
SEAO
EUR
EUR
EUR
EUR
NAC
NAWA
EUR
EUR
EUR
EUR
EUR
EUR
EUR
SEAO
SEAO
EUR
EUR
EUR
EUR
SEAO
EUR
SEAO
EUR
EUR
SEAO
SEAO
SEAO
EUR
EUR
CSA
LCN
NAWA
NAWA
CSA
EUR
EUR
EUR
LCN
NAWA
EUR
NAWA
EUR
NAWA
LCN
LCN
EUR
SSF
NAWA

1
2
3
4
1
1
5
1
6
7
8
9
2
10
3
4
5
11
12
13
14
2
2
15
16
17
18
19
20
21
6
7
22
23
24
25
8
26
9
27
28
10
11
12
29
30
1
1
3
4
2
31
32
33
2
5
34
6
35
7
3
4
36
1
8

Median
23.54

CONTINUED
xxxviii The Global Innovation Index 2019

Innovation Output Sub-Index rankings, continued
Country/Economy

Score(0–100)

Rank

IncomeRank

RegionRank

MoroccoBrazilSouth Africa
Jamaica
Qatar
JordanPanamaUnited Republic of Tanzania
Egypt
Argentina
Colombia
Sri Lanka
Indonesia
Bosnia and Herzegovina
Ethiopia
SenegalLebanonTajikistan
Cambodia
Saudi Arabia
Peru
Bahrain
Dominican Republic
PakistanAzerbaijan
Côte d’Ivoire
Kazakhstan
AlbaniaParaguay
Belarus
Mauritius
Ghana
Ecuador
Trinidad and Tobago
Mali
Oman
GuatemalaNamibia
Honduras
Nigeria
Cameroon
UgandaBangladesh
Madagascar
Zimbabwe
Kyrgyzstan
Malawi
Bolivia (Plurinational State of)Mozambique
Burkina Faso
El Salvador
Botswana
Algeria
Nepal
Brunei Darussalam
ZambiaNicaragua
RwandaGuineaBenin
Burundi
Niger
Togo
Yemen

23.34
22.93
22.34
22.14
22.13
22.12
21.95
21.78
21.62
21.56
20.94
20.83
20.80
20.41
20.10
20.09
20.00
19.74
19.68
19.46
19.35
19.31
19.25
19.10
18.83
18.67
18.32
18.26
18.25
18.12
17.96
17.74
17.71
17.54
17.34
16.88
16.81
16.73
16.51
16.40
16.09
15.55
15.55
15.47
15.38
15.29
15.25
15.09
14.82
14.29
14.16
13.99
13.32
12.99
12.95
12.74
12.13
11.31
11.24
9.36
8.75
8.26
7.29
6.44

66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129

LM
UM
UM
UM
HI
UM
HI
LI
LM
HI
UM
LM
LM
UM
LI
LI
UM
LI
LM
HI
UM
HI
UM
LM
UM
LM
UM
UM
UM
UM
UM
LM
UM
HI
LI
HI
UM
UM
LM
LM
LM
LI
LM
LI
LI
LM
LI
LM
LI
LI
LM
UM
UM
LI
HI
LM
LM
LI
LI
LI
LI
LI
LI
LI

10
15
16
17
43
18
44
1
11
45
19
12
13
20
2
3
21
4
14
46
22
47
23
15
24
16
25
26
27
28
29
17
30
48
5
49
31
32
18
19
20
6
21
7
8
22
9
23
10
11
24
33
34
12
50
25
26
13
14
15
16
17
18
19

NAWA
LCN
SSF
LCN
NAWA
NAWA
LCN
SSF
NAWA
LCN
LCN
CSA
SEAO
EUR
SSF
SSF
NAWA
CSA
SEAO
NAWA
LCN
NAWA
LCN
CSA
NAWA
SSF
CSA
EUR
LCN
EUR
SSF
SSF
LCN
LCN
SSF
NAWA
LCN
SSF
LCN
SSF
SSF
SSF
CSA
SSF
SSF
CSA
SSF
LCN
SSF
SSF
LCN
SSF
NAWA
CSA
SEAO
SSF
LCN
SSF
SSF
SSF
SSF
SSF
SSF
NAWA

9
5
2
6
10
11
7
3
12
8
9
3
13
37
4
5
13
4
14
14
10
15
11
5
16
6
6
38
12
39
7
8
13
14
9
17
15
10
16
11
12
13
7
14
15
8
16
17
17
18
18
19
18
9
15
20
19
21
22
23
24
25
26
19

Median23.54

Notes: World Bank Income Group Classification (July 2018): LI = low income; LM = lower-middle income; UM = upper-middle income; and HI = high income.
Regions are based on the United Nations Classification: EUR = Europe; NAC = Northern America; LCN = Latin America and the Caribbean; CSA = Central andSouthern Asia; SEAO = South East Asia, East Asia, and Oceania; NAWA = Northern Africa and Western Asia; SSF = Sub-Saharan Africa.
Rankings

xxxix

xl

The Global Innovation Index 2019

CO N T RI B UTO R S

CONTRIBUTORS TO THE REPORTThe Global Innovation Index 2019: Creating Healthy Lives—The Future of Medical Innovation was developed under thegeneral direction of Francis GURRY (Director General, World Intellectual Property Organization), and the editors of the report,
Soumitra DUTTA, Bruno LANVIN, and Sacha WUNSCH-VINCENT.

The report was prepared and coordinated by a core team comprising:

CORE TEAM
Soumitra DUTTA, Professor of Management and Former Founding Dean, Cornell SC Johnson College of Business, Cornell University
Rafael ESCALONA REYNOSO, Lead Researcher, Cornell SC Johnson College of Business, Cornell University
Antanina GARANASVILI, Consultant, Cornell SC Johnson College of Business, Cornell University
Francesca GUADAGNO, Consultant, Composite Indicator Research Section, Economics and Statistics Division, WIPO
Cashelle HARDMAN, Project Manager, Composite Indicator Research Section, Economics and Statistics Division, WIPO
Bruno LANVIN, Executive Director for Global Indices, INSEAD
Lorena RIVERA LEÓN, Program Officer, Composite Indicator Research Section, Economics and Statistics Division, WIPO
Sacha WUNSCH-VINCENT, Head, Composite Indicator Research Section, Economics and Statistics Division, WIPO

CO-PUBLISHERS
Cornell University

World Intellectual Property Organization (WIPO)

Library Public Services Office, Cornell University
Susan F. KENDRICK, Business Research and Data Librarian,Marion (Amy) DIETTERICH, Director, Global Challenges Division
Carsten FINK, Chief Economist, Economics and Statistics Division
Mosahid KHAN, Head, IP Statistics Section, Economics andInterim Assistant Director of Business and Hospitality ResearchServices, Management Library, Samuel Curtis Johnson
Graduate School of Management, Cornell College of BusinessPR & Media Relations
External Relations

INSEAD
Virginie BONGEOT-MINET, Senior Coordinator
Chris HOWELLS, Director Media Relations & ResearchCommunications

Aileen HUANG, Associate Director, Strategic Communications
Robert LOXHAM, Community Manager
Rachael NOYES, Senior Editor, INSEAD Knowledge
Axel TAGLIAVINI, Chief Communications Officer

Statistics DivisionCharles RANDOLPH, Head, Global Health Unit
Conference and General Services Division
Economics and Statistics Division
Global Challenges Division and Global Health Unit
Language DivisionMarketing and Customer Service DivisionNews and Media Division
Publications Division
Printing Plant
Regional Bureaus, External Offices, WIPO Office in China and
WIPO Coordination Office in New YorkSpecial Representative of the Director General on the
UN Sustainable Development Goals (SDGs)

Contributors

xliKNOWLEDGE PARTNERS
Confederation of Indian Industry
Anjan DAS, Executive Director
Gaurav GUPTA, Executive Officer
Shalini S. SHARMA, Principal—Business Innovation Centre
Prince THOMAS, Executive
Priyanka MUKJIJA, Executive Officer
Namita BAHL, Deputy Director
Jyoti KUMAR, Director
Divya ARYA, Executive Officer
Soumitra BISWAS, Advisor
Media and Communications

Brazilian National Confederation of Industry (CNI), and theBrazilian Micro and Small Business Support Service (SEBRAE)
Julieta Costa CUNHA, Project Manager, Innovation Directory, CNI
Fernanda DE NEGRI, Consultant, Innovation Directory, CNI
Suely LIMA, Innovation Manager, Innovation Directory, CNI
Idenilza MIRANDA, Industrial Development Specialist, Innovation
Directory, CNI

Gianna SAGAZIO, Innovation Director, Innovation Directory, CNI
Roberta AVIZ, Competitiveness Unit Substitute Manager,
Technical Directory, SEBRAE
Célio CABRAL, Innovation Unit Manager, Technical
Directory, SEBRAE
Olívia CASTRO, Innovation Unit Project Manager, SEBRAE
Eduardo DIOGO, Chief Management and Financial Officer, SEBRAE
Léa LAGARES, Health and Wellness Project Manager of theCompetitiveness Unit, Technical Directory, SEBRAE
Bruno QUICK, Technical Director, SEBRAE
Kelly SANCHES, Competitiveness Unit Manager, Technical
Directory, SEBRAE
Paulo ZANDONADI, Innovation Unit Substitute Manager,
Technical Directory, SEBRAE

xlii

The Global Innovation Index 2019

In collaboration with the National Service of Industrial Training(SENAI-DN) and the National Department of Social Service
of Industry (SESI)Luis Gustavo DELMONT, Specialist in Industrial Development,
Innovation and Technology Unit, SENAI-DN

Alberto Xavier PAVIM, Specialist in Industrial Development,
Innovation and Technology Unit, SENAI-DN

Marcelo Fabrício PRIM, Executive Manager, Innovation andTechnology Unit, SENAI-DN

Gustavo Leal SALLES FILHO, Operations Director, SENAI-DN
Fabio Henrique CORDEIRO, Project Manager, SESIEmmanuel LACERDA, Executive Manager in Health and Safety
in Industry, SESIPaulo MÓL JÚNIOR, Director of Operations, SESI
Antonio Eduardo MUZZI, Manager in Health Promotion, SESI
Thiago Yhudi TAHO, Coordinator of the innovation program, SESI

Dassault Systèmes
Sébastien MASSART, Head of Corporate Strategy
Patrick JOHNSON, Vice President of Corporate Scienceand ResearchMedia Relations
Global Affairs

COLLABORATORS
Abdallah Al MAZROA, Acting Director General, Secretariat

Delphine BENOIT, Communications Director, Europe,

General of the Gulf Cooperation Council (GCC) Patent Office

GE Healthcare

Irene MIA, Global Editorial Director, Thought Leadership, andEmily MANSFIELD, Country Forecast Director, both from the

J.K. WALL, Advisor, Executive Communications,
Eli Lilly and Company

Economist Intelligence Unit

Christopher MCKEE, Chief Executive and Owner, and Thomas
L. GERKEN, Customer Service Specialist, both at The PRS Group Inc.
Anand SANWAL, CEO & Co-Founder, Patrick MCKINLEY,
Customer Support Manager, and Adrienne LEWIS, Customer
Success Manager, all from CB Insights.
Peter CORNELIUS, Managing Director at AlpInvest Partners/
The Carlyle GroupJosh LERNER, Chair, Entrepreneurial Management Unit,
and Jacob H. SCHIFF Professor of Investment Banking,
Harvard Business School

Grega KUMER, Head of Director General’s Office & Legal
Issues, International Federation of Pharmaceutical Manufacturers& Associations (IFPMA)

Creative Production
Tim BRUCE, Co-Founder and Creative Director, andStacy CHYLA, Co-Founder and Business Design Director,
both from LOWERCASE Inc.

AuXenta (Pvt) Ltd.
StratAgile PTE Ltd.

Statistical Audit Team, Joint Research Centre
Kirk CALVO, Account Manager, PitchBook Data, Inc.
Bertalan MESKÓ, Director of The Medical Futurist
Christine WILLIAMS, General Manager, Innovation Metrics Review,
Economic and Analytical Services Division, Department of Industry,Innovation and Science, Australia

Michaela SAISANA, Head, and Researchers
Marcos ÁLVAREZ-DÍAZ, Marcos DOMINGUEZ-TORREIRO,
and Daniel VERTESY, all from the Competence Centre
on Composite Indicators & Scoreboards (COIN), European
Commission, Joint ResearchCentre (JRC).

Eric SHUM, Gary YAU, and Joyce CHEUNG, all from theInnovation and Technology Bureau, Hong Kong, China.
Frederico GENTILE, Anne-Catherine REIS, and Noemi
BAUSCH, all from Service des Médias et des Communications,
Ministère d’État, Le Gouvernement du Grand-Duché de Luxembourg.

Hui LIM, Kelvin KEE and Angelia CHIA, all from the Intellectual
Property Office of Singapore
HE. Valentine RUGWABIZA SENDANYOYE, Ambassador andPermanent Representative of Rwanda to the United Nations, New YorkHE. François XAVIER NGARAMBE, Ambassador and Permanent
Representative of Rwanda to the United Nations, Geneva

Edouard BIZUMUREMYI, Commercial Attaché at thePermanent Mission of Rwanda, Geneva

Contributors

xliiiDATA COLLABORATORSWe are grateful to the following individuals and respective
institutions for their collaboration with data requests:

Bertrand SCHMITT, Chief Strategist & Co-Founder, Bertrand
SALORD, Vice President of Marketing EMEA, Danielle LEVITAS,
Executive Vice President of Marketing and Insights, andAmir GHODRATI, Director of Market Insights, all at App Annie.

Metri SANTHOSH, Global Head of IP Products and Solutions, andPetra STEINER, Regional Head of Government and Public Sector,
both from Bureau van Dijk Electronic Publishing GmbH

Zachary A. WENDLING, Principal Investigator for the Environmental

Esperanza MAGPANTAY, Senior Statistician, Martin SCHAAPER,
Senior ICT Analyst, and Nathalie DELMAS, Assistant, all at the
ICT Data and Statistics Division (IDS); Susan TELTSCHER, Head,
Human Capacity Building Division, and Vanessa GRAY, Head,
Least Developed Countries, Small Island Developing States &Emergency Telecommunications Division; all at the Telecommunication
Development Bureau (BDT), International Telecommunication
Union (ITU)

Christina WIEDERER, Economist in the Macroeconomics, Trade& Investment Global Trade and Regional Integration Unit of theWorld Bank

Performance Index, at the Yale Center for Environmental Law &Policy, Yale University

MIXMarket Premium Support, premium@themix.org

Héctor HERNANDEZ, Project Leader—Innovation, AlexanderTÜBKE, Team Leader—Industrial Research & Innovation andTechnology Analysis (IRITEC), Nicola GRASSANO, Economic Data
Analyst, and Sara AMOROSO, Economic Analyst, all from theof the OECD

Territorial Development Unit of the European Commission, Joint
Research Centre, Directorate for Growth and Innovation

Urška ARSENJUK, and Gregor KYI, R&D Team, Eurostat G4:

Fabien VERGER, Economic Analysis and Statistics Division

OECD, Programme for International Student Assessment (PISA),
http://www.oecd.org/pisa/

Angela SUH, Senior Manager, Global Marketing & Insights,
and Nicolas BRAUDE, Global Communications, both atPricewaterhouse Coopers (PwC)

Innovation and digitalization, European Commission

Energy Data Centre, headed by Duncan Millard, International
Energy Agency (IEA), http://data.iea.org

Mohsen BONAKDARPOUR, Executive Director, andKaren CAMPBELL, Associate Director, both from IHS Markit
László SZERB, Professor at the University of Pecs, from The Global
Entrepreneurship Index

David BESCOND, Statistician, Steven KAPSOS, Head of Unit,
Yves PERARDEL, Senior Econometrician, and Marie-Claire
SODERGREN, Senior Economist, all at the Data Production andAnalysis Unit (DPAU), Department of Statistics, International Labour
Office (ILO)

International Monetary Fund (IMF) Data Centre, https://www.imf.
org/en/Data

Sean MACCURTAIN, Director, Conformity Assessment andConsumer Matters, and Laurent CHARLET, Project Manager,
Conformity Assessment, both at International Organization forStandardization (ISO) Central Secretariat

Ben SOWTER, Director, David REGGIO FRSA, Global Head ofConsulting, and Selina GRIFFIN, Rankings Manager, all from QSIntelligence Unit, QS Quacquarelli Symonds Ltd
Félix DE MOYA ANEGÓN, SCImago Founder
Klass DE VRIES, Associate Economist at the Conference Board
Richard LAMBERT, Manager, Global Government IP Sales,
William EDGAR, Team Lead, and Simon THOMSON, Senior
Scientific Analyst, all from Clarivate Analytics

José PESSOA, Head of Unit, Culture and Communication Statistics,
Lydia DELOUMEAUX, Associate Programme Specialist, both in the
Culture and Communication Unit; Saïd Ould A. VOFFAL, Head,
Talal EL HOURANI, Statistician, Pascale RATOVONDRAHONA,
Statistician, and Hugo CASTELLANO TOLMOS, Statistics
Assistant, all in the Education Survey Section; Roberto DANTESDE PINHO, Head of Section, Science, Culture and Communication,
and Rohan PATHIRAGE, Assistant Programme Specialists,
Science, Technology and Innovation Unit; all from the United Nations
Educational, Scientific and Cultural Organization (UNESCO) Institutefor Statistics (UIS)

Valentin TODOROV, Senior Information Management Officer,
and Martin HAITZMANN, Statistical Assistant, both from theStatistics Division, Department of Policy, Research and Statistics,
United Nations Industrial Development Organization (UNIDO)

xliv

The Global Innovation Index 2019

UN Public Administration Network (UPAN) http://unpan3.un.org/
egovkb/en-us/Data-Center[bd]Leila ZIA, Senior Research Scientist, Research Team,Dan ANDREESCU, Senior Software Engineer, Analytics Team, andDiego SAÉZ-TRUMPER, Research Scientist, all from Wikimedia
Foundation.

Hao ZHOU, Head, Data Development Section, Mosahid KHAN,
Head, IP Statistics Section, Kyle BERGQUIST, Data Analyst, andRyan LAMB, Statistics Analyst, all from the Economics and Statistics
Division, WIPO
Aart KRAAY, Economist in the Development Research Group, andFrédéric MEUNIER, Private Sector Development Specialist, Global
Indicators Group, Development Economics, both at the World Bank

Thierry GEIGER, Head of Analytics and Quantitative Research,
Roberto CROTTI, Economist, Global Competitiveness and Risks,
Silja BALLER, Practice Lead, Digital Economy and Innovation, andCiara PORAWSKI, Head of Engagement, Future of Economic
Progress, all from the Word Economic Forum

Andreas MAURER, Chief, International Trade Statistics Section
Economic Research and Statistics Division, Barbara D'ANDREA,
Senior Statistician, International Trade Statistics Section, Adelina
MENDOZA, Senior Statistical Officer, Market Access Intelligence
Section, and Antonella LIBERATORE, Statistician, International
Trade Statistics Section, all from the Economic Research andStatistics Division, World Trade Organization (WTO)
Matthew ZOOK, Professor at the University of Kentucky andPresident, ZookNIC Inc.
United Nations Commodity Trade Statistics Database,
Department of Economic and Social Affairs/ Statistics Division

Contributors

xlv

xlvi

The Global Innovation Index 2019

A DV I S O RY B OA R D

ADVISORY BOARD TO THE
GLOBAL INNOVATION INDEXIn 2011, an Advisory Board was established to provide advice on the research underlying the Global Innovation Index (GII), generatesynergies at its stages of development, and assist with the dissemination of its messages and results. The Advisory Board is aselect group of leading international practitioners with expertise in the realm of innovation. Its members are from diverse geographicaland institutional backgrounds and participate in their personal capacity. We extend our gratitude to all Advisory Board members fortheir continuous support and collaboration.
We wish to thank Hugo Hollanders, Senior Researcher at UNU-MERIT (Maastricht University) for his contribution to previous editionsof the GII as a member of the Advisory Board.

ADVISORY BOARD MEMBERS
Robert D. ATKINSON
President, Information Technology and Innovation Foundation(ITIF), United States of America
Audrey AZOULAY
Director-General, United Nations Educational, Scientific andCultural Organization (UNESCO)
Dongmin CHEN
Dean, Innovation and Entrepreneurship, and Professor,
Faculty of Academy for Advanced Interdisciplinary Studies,
Peking University, China

Raghunath Anant MASHELKAR
National Research Professor, Global Research Alliance,
Former Director General, Council of Scientific & Industrial
Research (CSIR), and Former Chairperson, National
Innovation Foundation, India
Philippe Kuhutama MAWOKO
Executive Secretary, African Observatory for STI,
African Union Commission
Sergio MUJICA
Secretary-General, International Organization forStandardization (ISO)Fabiola GIANOTTI
Director-General, European Organization for Nuclear
Research (CERN)

Mary O’KANE
Professor, NSW Chief Scientist and Engineer, Australia

Leonid GOKHBERGFirst Vice-Rector, National Research University Higher Schoolof Economics (HSE), and Director, Institute for Statistical Studies
and Economics of Knowledge (HSE), the Russian Federation

Sibusiso SIBISI
Director, WITS Business School, and Former President andChief Executive Officer, Council for Scientific and Industrial
Research (CSIR), South Africa

Yuko HARAYAMA
Professor Emeritus, Tohoku University, and Former Executive
Member, Council for Science, Technology and Innovation (CSTI),
Cabinet Office of Japan

Pedro WONGTSCHOWSKI
Chairperson of the Board of Directors, Ultrapar Participações
S.A., Embraer S.A., the Brazilian Enterprise for Researchand Innovation (EMBRAPII), and the Brazilian Association of
Innovative Companies (ANPEI)

Beethika KHAN
Program Director, National Science Foundation (NSF)
Chuan Poh LIM
Chairperson of the Singapore Food Agency, andFormer Chairperson, Agency for Science, Technology
and Research (A*STAR), Singapore

Houlin ZHAOSecretary-General, International Telecommunication
Union (ITU)

Advisory Board

xlvii

xlviii

The Global Innovation Index 2019

CHAPTERSKey Findings

xlix

l

The Global Innovation Index 2019

CH AP T E R 1

THE GLOBAL INNOVATIONINDEX 2019
Soumitra Dutta, Rafael Escalona Reynoso, and Antanina Garanasvili, SC Johnson Collegeof Business, Cornell University
Bruno Lanvin, INSEAD
Sacha Wunsch-Vincent, Lorena Rivera León, Cashelle Hardman, and Francesca Guadagno1,
World Intellectual Property Organization (WIPO)

Since the release of the Global Innovation Index (GII) 2018,global economic growth has weakened and new risks
have emerged. The global innovation landscape, in turn,has further evolved.
This scene-setting chapter of the GII 2019 takes a look at
the pulse of innovation around the world, before revealing
the innovation performance of economies. Chapter 1 iscomplemented by two additional sections this year. First,
we present the Theme Section: Creating Healthy Lives—
The Future of Medical Innovation main findings and takea look at the role of innovation for health, which is covered
by world experts in the chapters that follow. Second, we
present the new ranking of the world’s largest science andtechnology clusters in the Special Section: Identifying andRanking the World’s Largest Science and Technology
Clusters (Cluster Rankings).

Key findings in brief
1.

2.

3.
4.
5.
6.

7.

Amid economic slowdown, innovation is blossoming
around the world; but new obstacles pose risks toglobal innovation.
Shifts in the global innovation landscape arematerializing; some middle-income economies areon the rise.
Innovation inputs and outputs are still concentrated invery few economies; a global innovation divide persists.
Some economies get more return on their innovation
investments than others.
Shifting focus from innovation quantity to innovation
quality remains a priority.
Most top science and technology clusters are in
the U.S., China, and Germany; Brazil, India, Iran,the Russian Federation, and Turkey also make the
top 100 list.
Creating healthy lives through medical innovation
requires more investment in innovation and increased
diffusion efforts.

Chapter 1

1

Taking the pulse of innovation
expenditures and policies aroundthe world
Previous editions of the GII have underscored the paramountimportance of laying the foundation for innovation-driven growth.2
Current economic figures show a level of uncertainty that
contrasts with the optimism observed in the GII 2018 edition.
Global economic growth appears to be losing momentum,
relative to last year and earlier predictions.3 Investment andproductivity growth around the world—of which innovation
is a significant engine—are still sluggish by historical standards
and certainly compared to the years before the last financial
crisis in 2009.4 Global foreign direct investment (FDI) fell lastyear.5 Despite a short-lived revival in 2017, labor productivity
growth is at a record low after a decade of slowdown.6 Yet,
an increase in productivity will be one of the most effective ways
to prevent global growth from slowing down prematurely.
From an innovation perspective, two possible bottlenecks exist:
a decline in the level and speed of innovation—possibly due
to sub-par investments in research and development (R&D)—
and uneven adoption of innovation across the economy andthe world at large.7 While breakthrough innovation related
to digital technologies, automation, data processing, andartificial intelligence (AI) are proliferating, some fear that theirimpact on medium-term productivity growth is likely to bemodest.8 Moreover, businesses do not seem to engage ininnovative processes, products, and solutions evenly, leading
to slow productivity growth.9 Knowledge gaps at the global
level are still prominent and possibly growing.
In all likelihood, a combination of both factors is likely the
culprit—noting that current economic and geopolitical uncertainties
are a possible deterrent to forward-looking innovation investment
and adoption. New barriers to international innovation networks,
trade, and workforce mobility are likely to negatively impact
the formation of more proficient global innovation networks.
As we are at a critical juncture in our search for new sources ofinnovation-driven growth, it helps to take the pulse of innovation
around the world on these matters.

True progress in fostering innovationon the ground
Regardless of the economic and geopolitical uncertainties
over the last few years, formal and informal innovation seem tobe blossoming globally. The news is positive as regards
the political determination across the globe to foster innovation
and related policies on the ground.
A few years ago, innovation and innovation policies were still
the reserve of high-income economies. Today, developed
and developing economies—including those with an abundanceof natural resources—have placed innovation firmly on theiragenda to boost economic and social development. To someextent, the North-South divide of how economies perceive
innovation has improved.

2

The Global Innovation Index 2019As a result, encouragingly, many developing economies—
including low-income economies—increasingly monitor theirinnovation performance closely and work on improving it.
In that same vein, there is a better understanding that innovation
is taking place in all realms of the economy, including sectors
originally—and possibly erroneously—classified as low-tech.
As previous editions of the GII have shown, countries are
well-advised to see the potential for innovation in all economic
sectors, including agriculture, food, energy, and tourism, be theyclassified as high- or low-tech.10 This entails breaking the myththat innovation is solely concerned with heavily science-driven
and high-tech outputs.
The move towards conceptualizing innovation as something
beyond high-tech R&D—to also be a concept that is applicableto local industries and that solves local problems throughincremental innovation—is well on its way. Policymakers
nowadays take an active interest in promoting local, frugal,
and inclusive innovation drawing on local riches, crafts, andskill sets.
Consequently, a number of important trends are visible inmodern-day innovation policy.
First, innovation policy is invoked not only in relation to economic
objectives related to growth and technological change, butalso to cope with modern societal challenges, such as foodsecurity, environment, energy transitions, and health, asevidenced in the current and past editions of the GII.11
On the organizational front, innovation policies have moved outof the reserve of one ministry or policy agency only—usually
the Science Ministry—into cross-ministerial task forces or various
ministries, often with the attention of high-level policymakers,
such as the Prime Minister’s office.
Hearteningly, the center of attention is gravitating from fosteringscience and R&D expenditures alone to striving for the creation
and upkeep of sound and dynamic innovation ecosystems.
Economies at all development levels now ask questions on how
to instill the curiosity of science and entrepreneurship in children
and students, how to make public research more relevant tobusiness, how to promote inward technology transfer and foster
business innovation expenditures, or how to make intellectual
property work for local innovation. The focus of innovation policies
has also shifted to increasingly emphasize the adoption of
innovation, necessitating investment in enabling conditions,such as infrastructure for research and technology transfer,
education and skills, entrepreneurs, and venture capital markets.
Finally, data-based evidence and innovation metrics are
increasingly at the center of crafting, deploying, and evaluating
innovation policies. The availability and use of innovation
metrics has advanced over the last years (Box 3).
These are big steps forward. The determination to anchor policy
objectives in innovation across all economies is now strong andgrowing—not only on paper but also as evidenced by actions
on the ground.

Innovation remains concentrated
in a few economies, while someothers show potential to catch up
Innovation is thus finally part of policy ambitions around theworld. This good news aside, across countries and economies,
divides still exist as to the absolute scale of innovation inputs
and outputs.
Change on this front is sparse and slow. Innovation investments
and outputs, as we measure them today, continue to beconcentrated in a handful of economies—and in specific regionalinnovation clusters within countries (Special Section: Cluster
Rankings).
“Leapfrogging”, the way in which latecomers can catch up withforerunners and become important players worldwide, is not aneasy feat. Moving from a successful middle-income economy
with innovation potential to an innovation powerhouse remains
hard; an impermeable innovation glass ceiling exists between
middle- and high-income economies.
But, what do top performers in the GII have in common?
For years, we have noted a positive correlation between an
economy’s level of development (measured by GDP per capita)
and innovation performance. In other words, wealthiereconomies perform better on innovation. However, we havealso found that:12
1. There is a positive and statistically significant relation
between economy size and innovation performancethat indicates that scale, and thus a large market that isable to sustain innovation activities and the demand forinnovation, continues to matter.
2. Economies with a diversified export basket that extends
beyond a few commodities are more innovative.
This year, as in the past eleven years of publication, the global
innovation divide between income groups and regions persists(Box 2). Historically, only a few countries have managed to join
the fray of top innovation nations—notably Japan and theRepublic of Korea in the 1980s and 1990s.13 Northern America,
and Europe continue to lead in the top 10 global innovation
rankings, while Singapore continues to lead in Asia. In general,
Asia has made formidable progress over the last decades.
Recently, only China—an upper middle-income economy andan exception among the otherwise stable group of high-income
economies—had entered the top 20 in the GII. Progress remains
slower in other regions, such as Africa, and Latin America andthe Caribbean.
Even within the most innovative nations, innovation activities
are often concentrated in a few cities, regions, or clusters driven
by agglomeration effects, as discussed in the Special Section
presenting the Cluster Rankings in this edition.14

Shifting global R&D and theinnovation landscape
The global innovation landscape is changing; innovation
expenditures and innovation efforts, including the number of
researchers and entrepreneurs who actively drive innovation
efforts, have been scaled up massively. Yet innovation remains
relatively “spiky”, concentrated in a few countries and regions
only. This is reflected in other key innovation indicators, suchas R&D, researchers, and intellectual property (IP).
From a historic perspective, the global landscape of scienceand technology investment, and investments in educationand human capital, have undergone important shifts over thelast three decades. Global R&D expenditures have continued
to rise, more than doubling between 1996 and 2017.
Today, it is not only high-income economies carrying out R&D inearnest. While in 1996 high-income economies accounted
for 87% of global R&D, in 2017, they only represented 64% of
total investments—the lowest share registered in the last
30 years. In contrast, the share of R&D investments from upper
middle-income economies, notably China, has consistently
increased, from only 10% of global R&D expenditures in 1996 to
31% in 2017 (Figure 1.1). Middle-income economies represented
35% of total R&D expenditures in 2017. Asian R&D powerhouses,
such as China, Japan, the Republic of Korea, and India,
contributed to as much as 40% of the world’s R&D in 2017, up
from 22% in 1996. Of this 40%, China was responsible for
24% of the world’s R&D expenditures in 2017, up from only
2.6% in 1996.
The world share of other emerging economies, such as India,
have also substantially increased—from 1.8% in 1996 to2.9% in 2017. In contrast, the regional R&D shares of Europe,and Latin America and the Caribbean have fallen with the riseof Asian economies. Sub-Saharan Africa continues to have
low levels of R&D investments compared to what other world
regions spend.
Private sector R&D funding also remains concentrated but it isevolving too. Only eight countries—the United States of America(U.S.), China, Japan, the Republic of Korea, Germany, France,
the United Kingdom (U.K.), and India accounted for 82% ofprivate sector R&D investments in 2017. Private sector R&D
investments from China represented 27% of the world’s total in2017, almost on par with U.S. firms, and up from a negligible
2% in 1996 (Figure 1.2).
Middle-income economies and the South East Asia, East Asia,and Oceania region also played a central role when looking
at the top 2,500 private sector companies who invested thelargest sums in R&D in the world in the financial year 2017/18.
In 2017, 591 companies from middle-income economies
made the list of the top 2,500 private spenders.15 Companies
located in Argentina, Brazil, China, India, Iraq, Malaysia, Mexico,South Africa, Thailand, Turkey and Venezuela made it into
the top ranks.

Chapter 1

3

FIGURE 1.1

Worldwide R&D expenditures by income group, 1996, 2005, 2017

1,200

1,079
1000

800

783

600

598

568
400

200

198
83

0

High income▲ Million 2005 PPP US$

Middle and low income(with China)

195
66

111

Middle and low income(without China)■ 1996■ 2005■ 2017

Source: Authors’ estimate based on the UNESCO Institute for Statistics (UIS) database, OECD Main Science and Technology Indicators (MSTI), Eurostat,and the IMF World Economic Outlook database.
Notes: R&D data refers to gross domestic expenditure on R&D. The high-income group includes 54 economies, and the middle- and low-income
groups include 97 economies.

4

The Global Innovation Index 2019

FIGURE 1.2

Regional and economy shares in world business expenditures, 2017

Other
Argentina

Colombia
Saudi
ArabiaMexicoOther

United Arab Emirates

Switzerland

IsraelEgypt

Denmark

Other
FranceSouth Africa
Italy

Belgium
Germany

NorwayAustria

SwedenUnitedKingdom

PolandNetherlands
Spain

Chile

BrazilTurkeyRussianFederation

Finland

Japan

Other

Ireland

CanadaChina

Australia

United States of America

Republic of Korea

Malaysia
Indonesia
Singapore

India
Pakistan
Iran Northern America
 Europe

Hong Kong, China
Other

Philippines
ThailandBangladesh
Other South East Asia, East Asia, and Oceania
 Northern Africa and Western Asia
 Latin America and the Caribbean

 Central and Southern Asia
 Sub-Saharan Africa

Source: Authors’ estimate based on the UNESCO Institute for Statistics (UIS) database, OECD Main Science and Technology Indicators (MSTI), Eurostat,and the IMF World Economic Outlook database.
Note: In PPP US$ in constant prices, 2015.

Chapter 1

5

The number of researchers is also growing, again largely driven
by China and emerging Asian innovation economies. In the
period from 2008 to 2016, the number of researchers per million
inhabitants grew by 19% worldwide. The largest contributors
to this increase were middle-income economies, whose numberof researchers increased by 34% in the same period.16
The same trends are true for intellectual property. Worldwide
demand for IP reached record highs in 2017 and 2018, including
for patents, trademarks, industrial designs, and other IP rightsthat are at the heart of the global innovation economy.17
While in 1997, 88% of all patent applications originated fromhigh-income economies, in 2017—largely driven by China—the
origin of patent applications was almost equally distributed
between high-income and upper middle-income economies.
While in 1997 China accounted for 2% of all patent applications,in 2017 it represented 44% of the total.

Uncertainty around R&D andinnovation in the years to comeSo, what can we expect in terms of innovation efforts and R&D
in the years to come? How will modest medium-term growth
and world R&D intensities affect innovation in the future?
Last year, we warned of the challenge of keeping the global
economy at sustained levels of economic growth in the years
to come. We also warned that year-on-year growth of corporate
and public R&D spending was still lower in 2016 than it was
before the financial crisis.18
The good news this year is that global R&D expenditures havebeen growing faster than the global economy in real terms.
Despite economic uncertainty and mirroring the determinationof economies to stay true to their innovation agendas, innovation
expenditures have been growing and are surprisingly resilient,suggesting a possible decoupling from economic cycles.
R&D grew in 2017 by 5.2%, the highest growth registered since2011. These levels are more in line with the pre-crisis period(Figure 1.3). Projections show that this positive trend could
continue: the 2018 Global R&D Outlook forecasts global R&D
budgets to increase over the next five years.19 By the same
token, private sector funding has also been growing at a fasterrate than the world economy and total R&D (Figure 1.3). 20
The world’s business expenditures in R&D (BERD) grew by 6.7%
in 2017, the largest increase registered since 2011 (Figure 1.2
and Figure 1.3). Private sector R&D also increased by 8.3% in thefinancial year 2017/18 relative to 2016/17.21

6

The Global Innovation Index 2019

Are global R&D expenditures at risk to falter again, in line withslower GDP growth? Global government expenditures in
R&D (GERD) fell on three occasions: in 2002, after a marked
slowdown of the world economy; in 2009, with the aftermathof the global financial crisis; and most recently, in 2016, becauseof tighter government budgets in certain high-income economies
and slower spending growth in key emerging economies.
On these three occasions, public and private R&D followed the
downward trajectory of global GDP growth. As global economic
growth is declining in 2019, the question is whether R&D
expenditures will remain resilient in light of the economic cycle
this time around.
Another question is how to spread innovation expenditures
more equally. R&D intensity, defined as global R&D expenditures
divided by global GDP, has been relatively stable, increasingfrom 1.4% in 1996 to 1.7% since 2013. Most of the growth in R&D
intensity has been registered among upper middle-income
economies, with intensities passing from 0.6% in 1996 to 1.5%
in 2017. Growth in R&D intensity is concentrated in a few
countries, notably China, which increased from 0.6% in 1996
to 2.1% in 2017, and Malaysia, which increased from 0.2% to 1.3%
in the same period. In contrast, R&D intensity has only improved
marginally among middle-income economies, excluding China,
from 0.5% in 1996 to 0.6% in 2017, and in low-income economies
from 0.2% to 0.4%.
One additional worry is the waning public support for R&D, also
relative to the strong expenditure increases in the post-crisis
years (Box 1 in GII 2017 and 2018). R&D funding allocated bygovernments in the Organisation for Economic Co-operation
and Development (OECD) countries show an increase of 0.9%
in real terms in 2017, which is considerably lower than the 3.3%
growth in 2016. R&D budgets decreased in the U.S. in 2017
relative to 2016. Moreover, even if public R&D in China grew by
7.9% in 2017, this is the lowest reported growth since 1997. In
sum, most R&D budgets of governments in high-investing R&D
countries remain below their pre-crisis levels. While companies
become increasingly more important in driving global R&D
expenditure growth—sometimes more important than countries(Box 1)—public R&D funding remains central to creating future
breakthrough technologies. Public expenditures focus moreon blue sky and basic research, which is critical to progress inthe next decades, while private sector R&D is closer to productdevelopment. The importance of public and basic R&D—andcurrent budgetary cuts to R&D programs—are further discussed
in the Theme Section.

FIGURE 1.3

R&D expenditure growth, 2000-2017

9

8

7

Business
R&D growth
6

Total
R&D growth

5

4

GDP
growth

3

2

1

0

-1
2000

▲ %
⊲ Year

2002

2004

2006

2008

2010

2012

2014

2016

2018

2019

GDP growth forecast

Source: Authors’ estimate based on the UNESCO Institute for Statistics (UIS) database, OECD Main Science and Technology Indicators (MSTI), Eurostat,and the IMF World Economic Outlook database.

Chapter 1

7

BOX 1

Private sector R&D investments on par with countries
Today, the R&D expenditure levels of a number of private sector
companies are as high as government expenditures in R&D
of a number of economies (Box 1, Figure 1). Companies suchas Samsung (Republic of Korea), Alphabet (U.S.), Volkswagen(Germany), Microsoft (U.S.) and Huawei (China) are investing
more, or almost the same, in R&D as governments locatedin the top-ranked countries in the GII 2019, including Sweden,
Israel, Austria, and Switzerland.

BOX 1, FIGURE 1

Public and private R&D expenditures, 2017 (or latest available year)
511

United States of America
China

452

Japan

166
119

Germany
78

Republic of Korea

62

FranceIndia

50

United Kingdom

48

Brazil

41

Russian Federation

37

Italy

30

Canada26

Australia

21

Spain

20

Netherlands

18

Switzerland

18

Turkey17

Samsung (Republic of Korea)

16

Alphabet (United States of America)

16

Sweden16

Volkswagen (Germany)

16

Microsoft (United States of America)

16

Israel15

Austria

14

Huawei (China)

14⊲ Billion US$

0

100

■
■

EconomyCompany

200

300

400

Source: Authors’ estimates, based on data from UNESCO Institute for Statistics (UIS); and EU Industrial R&D investment Scoreboard 2018.

8

The Global Innovation Index 2019

500

600

In an environment dominated by uncertainty, the role ofpolicymakers remains central in ensuring that this does not
weaken R&D investments.22
While innovation remains concentrated in a few economies—
although only a few have broken out as innovation leaders—the GII emphasizes the existence of success stories and thatthese economies need to be encouraged. It will take time andpersistence, sometimes over decades, for the above-mentioned
innovation policy ambitions to trickle down and make a true
dent in the global innovation landscape. History has shown,however, that when developing economies consistently invest
in innovation, they can embark on a journey that leads toprosperity. This includes all regions, in particular, certain African
economies, such as Kenya or Rwanda, that have made a realdifference in the global innovation landscape.
Over the years, the GII has shown that international openness
and knowledge flows are critical to the development of successful innovation nations and international innovation networks.
Economies at all levels of development are more innovative
when they have a diversified export basket. The rise of global
value chains and of global innovation networks has proven an
essential building block of today’s innovation landscape (seealso the forthcoming WIPO World IP report).23
Finally, policymakers need to ensure that new barriers tointernational innovation networks, trade, and workforce mobility
do not throttle the positive innovation dynamics at work. If left
uncontained, these new obstacles to international trade,investment, and workplace mobility will lead to a slowdown ofgrowth in innovation productivity and diffusion across the globe.

The Global Innovation Index
2019 results
Conceptual framework
The GII helps create an environment in which innovation
factors are continually evaluated. This year, it provides detailed
innovation metrics for 129 economies. All economies covered
represent 91.8% of the world’s population and 96.8% of theworld’s GDP.24
Three indices are calculated: the overall GII, the Innovation Input
Sub-Index and the Innovation Output Sub-Index (Appendix I).25• The overall GII score is the average of the Input and
Output Sub-Index scores.
• The Innovation Input Sub-Index is comprised of five pillars
that capture elements of the national economy that enable
innovative activities: (1) Institutions, (2) Human capital andresearch, (3) Infrastructure, (4) Market sophistication, and(5) Business sophistication.
• The Innovation Output Sub-Index provides information about
outputs that are the result of innovative activities within
economies. There are two output pillars: (6) Knowledge andtechnology outputs and (7) Creative outputs.

Each pillar is divided into three sub-pillars and each sub-pillar iscomposed of individual indicators, a total of 80 this year.26
The development of fitting and accurate innovation indicators is
an ongoing priority for the GII (Box 3).

Results
The main GII 2019 findings are discussed in the following sections.
The Rankings Section presents the GII results in tabular form
for all economies covered this year, for the GII and for theInnovation Input and Output Sub-Indices.

Movement at the top: Switzerland,
Sweden, and the United Statesof America lead
There are important changes to the top 10 in the GII 2019.
Switzerland leads the rankings for the ninth consecutive year,
while Sweden returns to the 2nd position, as held alreadysix times in the past. The U.S. moves up to 3rd. The Netherlands
ranks 4th with the U.K. moving into 5th position. Finland andDenmark follow, each gaining one position from 2018, taking
6th and 7th place respectively. Singapore ranks 8th this year
and, for the third consecutive year, Germany holds the 9th spot.
Israel enters the top 10 for the first time, moving up one spotfrom 2018, marking the first occasion an economy from theNorthern Africa and Western Asia region has featured in the
top 10 rankings. Ireland leaves the top 10 and ranks 12th this year.
Figure 1.5 shows movement in the top 10 ranked economies
over the last four years:
1. Switzerland
2. Sweden
3. The United States of America
4. The Netherlands
5. The United Kingdom
6. Finland
7. Denmark
8. Singapore
9. Germany
10. Israel
In the top 20, a notable move is the Republic of Korea, whichedges closer to the top 10. Most notably, China continues its
upward rise, moving to 14th (up from the 17th rank in 2018), andfirmly establishes itself as one of the innovation leaders.
In the top 25, Hong Kong (China) (13th), Canada (17th), Iceland(20th), and Belgium (23rd) all move up, gaining between one
and three spots each. Ireland (12th), Japan (15th), Luxembourg(18th), Australia (22nd), and New Zealand (25th) move down,
while France (16th), Norway (19th), Austria (21st), and Estonia(24th) remain stable.

Chapter 1

9

FIGURE 1.4

Global leaders in innovation in 2019
Every year, the Global Innovation Index ranks the innovation performance of nearly
130 economies around the world.
Top 3 innovation economies by region
NORTHERN AMERICAEUROPENORTHERN AFRICA AND
WESTERN ASIA

SOUTH EAST ASIA,
EAST ASIA, AND OCEANIA

1. U.S.

1. Switzerland

1. Israel

1. Singapore

2. Canada

2. Sweden ↑2. Cyprus

2. Republic of Korea

3. Netherlands ↓3. United Arab Emirates

3. Hong Kong, China ★

2

1

3
4

5

6

7

LATIN AMERICA AND
THE CARIBBEAN

SUB-SAHARAN AFRICA

CENTRAL AND
SOUTHERN ASIA

1. Chile

1. South Africa

1. India

2. Costa Rica

2. Kenya ↑2. Iran

3. Mexico

3. Mauritius ↓3. Kazakhstan↑↓ indicates the movement of rank within the top 3 relative to 2018, and ★ indicates a new entrant into the top 3 in 2019.
Top 3 innovation economies by income group
HIGH INCOME

UPPER-MIDDLE INCOME

LOWER-MIDDLE INCOME

LOW INCOME

1. Switzerland

1. China

1. Viet Nam ↑1. Rwanda ↑2. Sweden ↑2. Malaysia

2. Ukraine ↓2. Senegal ↑3. U.S. ★

3. Bulgaria

3. Georgia ★

3. Tanzania ↓Source: Global Innovation Index Database; Cornell, INSEAD, and WIPO. 2019.
Notes: World Bank Income Group Classiﬁcation (July 2018); Year-on-year GII rank changes are inﬂuenced by performance and methodological considerations;some economy data are incomplete (Appendix IV).

10

The Global Innovation Index 2019

FIGURE 1.5

Movement in the GII, top 10, 2019

2019

1

2

3

4

5

6

7

8

9

10

CH

SE

US

NL

GB

FI

DK

SG

DE

IL
Israel enters
the top 10
for the ﬁrst timein 2019.

2018

2017

CH

CH

NL

SE

SE

NL

GB

US

SG

GB

US

DK

FI

SG

DK

FI

DE

DE

IE

IE

In 2018,
Singaporemakes it to
the top 5of the GII.

The Netherlands
entered the top 3
in 2017. Sweden
maintained
2nd place for thesecond time.

Germany
re-entered the
top 10 in 2016.
2016

CH

SE

GB

US

FI

SG

IE

DK

NL

DE

Since 2011,
Switzerland has
ranked 1st in the
GII every year.
2015

CH

GB

CH Switzerland
GB United Kingdom
SE Sweden

SE

NL

US

FI

NL Netherlands
US United States of America
FI Finland

SG

IE

LU

DK

SG Singapore
IE Ireland
LU Luxembourg

DK Denmark
DE Germany
IL Israel

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.
Note: Year-on-year comparisons of the GII ranks are inﬂuenced by changes in the GII model and data availability.

Chapter 1

11

Notable changes in GII rankings this year include Viet Nam andThailand, who each edged closer to the top 40. India moved
closer to the top 50, the Philippines broke into the top 55, andthe Islamic Republic of Iran stepped closer to the top 60 basedon better innovation performance. The United Arab Emirates,
36th, is moving closer to the top 35 of the GII.

Despite fast movers in terms of innovation “catch-up”, the global
innovation divide between income groups and regions
remains (Box 2). The catching-up of economies from relatively
emergent and fragmented innovation systems to more matureand functional ones is an arduous process.27

As always, it must be noted that year-on-year comparisons of
the GII ranks are influenced by various factors, such as changes
in the underlying indicators at source and changes in data
availability (Appendix IV).

BOX 2

The global innovation divide
China breaks into the top 15 GII economies;
otherwise, the gap across income groups andregions largely persists.
1. High-income economies and China in the top 15
The top-performing economies in the GII are almost exclusively
from the high-income group. China is the only exception, ranking
14th this year and the only middle-income economy in the top 30.
China edged into the top 25 in 2016 and moved to 17th in 2018.
Box 2, Figure 1 shows the average scores for six groups:(1) the top 10, composed of only high-income economies; (2) the
top 11-25, also all high-income economies, with the exceptionof China; (3) other high-income economies; (4) other upper
middle-income economies; (5) lower middle-income economies;and (6) low-income economies.
2. China, Malaysia, and Bulgaria continue to lead the
middle-income group
Aside from China, Malaysia (35th) and Bulgaria (40th) remain
the only other middle-income economies that are close to
the top 25. The divide between economies in ranks 11 to 25 andthe group of upper middle-income economies remains wide.
Thailand (43rd), Montenegro (45th), and the Russian Federation(46th) are among the upper middle-income economies thatare performing above high-income economies in selected
GII pillars. Other middle-income economies in the top 50 are:Turkey (49th) and Romania (50th), in the upper middle-income
group; and Viet Nam (42nd), Ukraine (47th), and Georgia (48th),
in the lower middle-income group. In the latter, Viet Nam
continues to show a consistent improvement in its scoresin Human capital and research, Market sophistication, andKnowledge and technology outputs.

12

The Global Innovation Index 2019

This year, India (52nd) edges closer to the top 50, performing
above the lower middle-income group average in all pillars.
India performs higher on Human capital and research, Market
and Business sophistication, and Knowledge and technology
outputs when compared to the upper middle-income groupaverage. Finally, India scores above the high-income group in
Market sophistication.
Generally speaking, however, the innovation systems of most
low- and middle-income economies have a set of common
characteristics: low education levels, low levels of scienceand technology investments, reduced exposure to foreigntechnologies, limited inward knowledge flows, weaker scienceand industry linkages, challenging business environments withinadequate access to financial resources and underdeveloped
venture capital markets, low absorptive and innovative capacity
within domestic firms, and limited use of intellectual property.
Informality is also widespread, making innovation more difficult
to measure and study.28
3. Regional divide
The innovation ranking of geographic regions has been stablesince 2014. However, the South East Asia, East Asia, andOceania region has been edging closer to Northern America
and Europe over time. Northern America maintains its position
as the top-performing region showing top average scores in
all innovation pillars. Europe comes in 2nd, followed by South
East Asia, East Asia, and Oceania, 3rd, and Northern Africa andWestern Asia, 4th. Latin America and the Caribbean remain in
5th, with Central and Southern Asia, and Sub-Saharan Africa
following in at 6th and 7th, respectively.
Scores this year show that Northern America, driven mainly
by U.S. prowess, has the largest average score increase.
Central and Southern Asia follow, driven by India and the Islamic
Republic of Iran.

BOX 2, FIGURE 1

Innovation divide across income groups, 2019
1
2
3
4
5
6

1
2
3
4
5
6

89.1
85.2
70.9
61.3
53.8
50.5

INSTITUTIONS

1
2
3
4
5
6

HUMAN CAPITAL AND
RESEARCH

63.4
61.9
53.3
44.2
37.4
29.2

1
2
3
4
5
6

INFRASTRUCTURE

1
2
3
4
5
6

66.9
61.5
49.3
47.5
45.9
36.5

MARKETSOPHISTICATION
1
2
3
4
5
6

Top 10 high income
11 to 25 high and upper-middle income

3
4

65.6
51.8
35.6
29.8
26.4
24.3

BUSINESSSOPHISTICATION
1
2
3
4
5
6

57.2
41.5
25.9
19.9
20.2
12.8

KNOWLEDGE ANDTECHNOLOGY OUTPUTS

1
2

59.9
51.5
37.3
29.0
21.5
15.2

49.0
45.4
32.6
25.7
22.7
15.1

CREATIVE OUTPUTS

Other high income
Other upper-middle income

5
6

Lower-middle income
Low income

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.

Chapter 1

13

BOX 3The importance of timely and apt innovation indicators
The provision of GII economy profiles and briefs—indicating
missing and outdated data sources—actively helps policy or
statistical officials to monitor their state of innovation metrics
and collection efforts more closely. At times, cross-ministerial
task forces address data requirements and are involved in
the design of innovation policy responses. This interest hashelped move innovation metrics to the center of policymaking,including in lower middle- and low-income economies.
Accordingly, in the past years, indicator coverage has grown,with some 32 GII economies improving their data coverageby between 5 and 12 indicators.29 Regionally speaking, progresshas been widely visible in African economies (Appendix IV).
That said, the GII is only good as its data ingredients—see thePreface. The availability of data to assess innovation outputs
and impacts remains medium to weak. Likewise, convincing
metrics on key components of national innovation systems—bethey from official statistical bodies or the private sector, such as
entrepreneurship, venture capital, innovation linkages, orcommercialization efforts—are lacking.
The GII appreciates the initiatives of economies seeking to
improve the measurement of innovation performance throughbetter data collection and design, and the reports and eventsof organizations such as the U.S. National Science Foundation’s

The top performers by income group
Table 1.1 shows the 10 best-ranked economies by income
group in the GII, and the top-ranked in the innovation input
and output sub-indices. Switzerland, Sweden, the U.S., the U.K.,
and Finland are among the high-income top 10 in all indices.
A new entrant in the top 10 upper middle-income group is
Mexico (56th). Among the lower middle-income group, Kenya(77th) rejoins the top 10 this year.32
Rwanda becomes the top low-income economy (94th) this year,
gaining 5 positions since last year in the GII, and one position
among the low-income group. Three economies enter the
low-income group top 10: Tajikistan (100th), Ethiopia (111th) andBurkina Faso (117th).33

14

The Global Innovation Index 2019

Science and Engineering Indicators Report, the African
Innovation Outlook, and the OECD Blue Sky Forum on Scienceand Innovation Indicators.30
Developing economies, for example, regularly suggest
additional innovation measurements, particularly as their contexts
may be different from high-income contexts, where innovation
metrics were originally devised. These metrics include
innovation in the informal sector, or measures to captureknowledge and technology diffusion and adaptation efforts.
High-income economies, too, are not content with the state ofplay. The Australian Innovation Metrics Review, for example,
was recently established to identify better innovation metrics.31
The future offers promising venues to also improve the way
innovation data are collected. More bottom-up and big dataapproaches to gathering innovation metrics will become
feasible, if certain shortcomings can be overcome (GII 2018,
Annex 1, Box 1, developed with the U.K.’s Innovation Foundation
Nesta). To improve the state of innovation metrics and thequality of relevant data, the GII will continue to act as a laboratory
for novel innovation data.

Which economies are outperforming
on innovation relative to their peers?
The GII also identifies the innovation performance of economies
relative to their peers with a similar level of development,
as measured by GDP per capita (Figure 1.6). Most economies
perform as expected on innovation based on their level ofdevelopment. Yet, some economies break from this pattern tostrongly outperform or underperform, relative to expectations.
All economies that are innovation leaders (dark blue) this year
were also in the top 25 in 2018. As observed in previous years,
all of them—with the exception of China—are high-income
economies.

TABLE 1.1

10 best-ranked economies by income group (rank)
Rank

Global Innovation Index

Innovation Input Sub-index

Innovation Output Sub-index

High-income economies (50 in total)		
1

Switzerland (1)Singapore (1)Switzerland (1)2Sweden (2)Switzerland (2)Netherlands (2)3United States of America (3)United States of America (3)Sweden (3)4Netherlands (4)Sweden (4)United Kingdom (4)5United Kingdom (5)Denmark (5)United States of America (6)6Finland (6)United Kingdom (6)Finland (7)7Denmark (7)Finland (7)Israel (8)8Singapore (8)Hong Kong, China (8)Germany (9)9Germany (9)Canada (9)Ireland (10)10Israel (10)Republic of Korea (10)Luxembourg (11)Upper middle-income economies (34 in total)
1

China (14)China (26)China (5)2

Malaysia (35)

Malaysia (34)

Bulgaria (38)3Bulgaria (40)

Russian Federation (41)

Malaysia (39)4Thailand (43)

Bulgaria (45)Thailand (43)5Montenegro (45)Thailand (47)Montenegro (46)6

Russian Federation (46)Peru (48)

Iran (Islamic Republic of) (47)7

Turkey (49)

Belarus (50)

Costa Rica (48)8

Romania (50)South Africa (51)Turkey (49)9

Costa Rica (55)North Macedonia (52)Armenia (50)10

Mexico (56)

Romania (54)Romania (53)Lower middle-income economies (26 in total)
1

Viet Nam (42)Georgia (44)Ukraine (36)2

Ukraine (47)

India (61)Viet Nam (37)3Georgia (48)Viet Nam (63)Philippines (42)4India (52)Mongolia (73)

Mongolia (44)5Mongolia (53)

Tunisia (74)

Republic of Moldova (45)6Philippines (54)Philippines (76)India (51)7

Republic of Moldova (58)

Kyrgyzstan (78)Georgia (60)8Tunisia (70)

Republic of Moldova (81)

Kenya (64)9Morocco (74)

Ukraine (82)

Tunisia (65)10

Kenya (77)

Morocco (83)

Morocco (66)

Low-income economies (19 in total)
1

Rwanda (94)

Rwanda (65)

United Republic of Tanzania (73)2Senegal (96)

Nepal (93)

Ethiopia (80)3United Republic of Tanzania (97)

Uganda (96)

Senegal (81)4Tajikistan (100)Senegal (103)

Tajikistan (83)5

Uganda (102)

Tajikistan (107)Mali (100)6Nepal (109)

Burkina Faso (111)

Uganda (107)7

Ethiopia (111)Benin (114)Madagascar (109)8Mali (112)

United Republic of Tanzania (115)

Zimbabwe (110)9Burkina Faso (117)

Mozambique (118)Malawi (112)10Malawi (118)Malawi (119)Mozambique (114)Note: Economies with top 10 positions in the GII, the Input Sub-Index, and the Output Sub-Index within their income group are highlighted.

Chapter 1

15

FIGURE 1.6

GII scores and GDP per capita in PPP US$(bubbles sized by population)
70
CH
65

SE
NL

US

GB
60

FI
DK

55

EE

50

CZ

HU
LV
VN

BG

IN

40

TH

BE

AT

NZ

LU
NO

IS
AU

MT

ES
IT

PT

PL
GR

IE

CA

CY

45

HK

FR

JP

CN

SG

DE

IL
KR

SI
AE

MY
SK
LT

UA

MD

35
KE
30

MA

KG
RW

TZ
TJ

UG
ET
25

MZ

MG

BF

CI
ML

NP
ZW

MW
GN

20
BI

SN

BJ

KH

PK

HN

BO GT

CM
BD

GH SV

NI

HR
RU
GE MN ME MX RO
CR
PH
TR
RS
CL
MK
ZA
UY
AM
IR
BR
TN PE
AR PA
CO
KZ
BA
BY
JMAL
OM
MU
AZ
JO
ID
LB
LK
DO
TT
EG
BW
NA

KW
SA

QA
BN

BH

EC
DZ

NG

ZM

TG
NE

15

YE

10
700

▲ GII score
 GDP per capita in PPP$
(logarithmic scale)

2,800

 Innovation leaders Innovation achievers

11,20044,800 Performing at expectations for level of development
 Performing below expectations for level of development

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.
Notes: As in past editions, Figure 1.6 presents the GII scores plotted against GDP per capita in natural logs and PPP US$. The main element of the figure is the trendline, which shows the expected levels of innovation performance for a given economy relative to its level of GDP per capita. The figure presents all economies
covered in the GII 2019 against this trend line. The trend line is the cubic spline with five knots determined by Harrell’s default percentiles (R2 = 0.6928).
Economies that are close to the trend line are those whose innovation performance is in line with expectations given its level of development (pink). The further
above an economy is in relation to this trend line, the better its innovation performance is relative to its level of development and thus other peer economies
at similar levels. In contrast, those economies located below the trend line are those whose innovation performance is lower than expectations (light blue).

16

The Global Innovation Index 2019

ISO-2 codes
Code

AE
AL
AM
AR
AT
AU
AZ
BA
BD
BE
BF
BG
BH
BI
BJ
BN
BO
BR
BW
BY
CA
CH
CI
CL
CM
CN
CO
CR
CY
CZ
DE
DK
DO
DZ
EC
EE
EG
ES
ET
FI
FR
GB
GE

Country/Economy

CodeUnited Arab Emirates (the)

GH
GN
GR
GT
HK
HN
HR
HU
ID
IE
IL
IN
IR
IS
IT
JM
JO
JP
KE
KG
KH
KR
KW
KZ
LB
LK
LT
LU
LV
MA
MD
ME
MG
MK
ML
MN
MT
MU
MW
MX
MY
MZ
NA

Albania
Armenia
Argentina
Austria
Australia
Azerbaijan
Bosnia and Herzegovina
Bangladesh
Belgium
Burkina Faso
Bulgaria
BahrainBurundiBenin
Brunei Darussalam
Bolivia (Plurinational State of)BrazilBotswana
BelarusCanadaSwitzerland
Côte d’Ivoire
Chile
Cameroon
China
Colombia
Costa Rica
CyprusCzech Republic (the)Germany
Denmark
Dominican Republic (the)Algeria
EcuadorEstonia
Egypt
Spain
Ethiopia
FinlandFranceUnited Kingdom (the)Georgia

Country/Economy

CodeCountry/Economy

Ghana

NE
NG
NI
NL
NO
NP
NZ
OM
PA
PE
PH
PK
PL
PT
PY
QA
RO
RS
RU
RW
SA
SE
SG
SI
SK
SN
SV
TG
TH
TJ
TN
TR
TT
TZ
UA
UG
US
UY
VN
YE
ZA
ZM
ZW

Niger (the)GuineaGreeceGuatemalaHong Kong, China
Honduras
Croatia
Hungary
Indonesia
IrelandIsrael
India
Iran (Islamic Republic of)Iceland
Italy
Jamaica
JordanJapan
Kenya
Kyrgyzstan
Cambodia
Republic of Korea (the)KuwaitKazakhstan
LebanonSri Lanka
Lithuania
Luxembourg
LatviaMoroccoRepublic of Moldova (the)Montenegro
Madagascar
North Macedonia
Mali
Mongolia
Malta
Mauritius
Malawi
MexicoMalaysia
Mozambique
Namibia

Nigeria
Nicaragua
Netherlands (the)NorwayNepal
New Zealand
Oman
PanamaPeru
Philippines
Pakistan
PolandPortugal
Paraguay
Qatar
Romania
SerbiaRussian Federation (the)RwandaSaudi Arabia
SwedenSingapore
Slovenia
Slovakia
SenegalEl Salvador
Togo
ThailandTajikistan
Tunisia
TurkeyTrinidad and Tobago
United Republic of Tanzania (the)UkraineUgandaUnited States of America (the)Uruguay
Viet Nam
Yemen
South Africa
ZambiaZimbabwe

Chapter 1

17

TABLE 1.2

Innovation achievers in 2019: income group, region and years as
an innovation achiever
EconomyIncome groupYears as an innovation achiever (total)

RegionViet Nam

Lower-middle income

South East Asia, East Asia, and Oceania

India

Lower-middle income

Central and Southern Asia

2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011 (9)Europe2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011 (9)Republic of Moldova Lower-middle income

2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011 (9)Kenya

Lower-middle income

Sub-Saharan Africa

2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012, 2011 (9)Armenia

Upper-middle income

Northern Africa and Western Asia

2019, 2018, 2017, 2016, 2015, 2014, 2013, 2012 (8)UkraineLower-middle income

Europe2019, 2018, 2017, 2016, 2015, 2014, 2012 (7)RwandaLow income

Sub-Saharan Africa

2019, 2018, 2017, 2016, 2015, 2014, 2012 (7)Malawi

Low income

Sub-Saharan Africa

2019, 2018, 2017, 2016, 2015, 2014, 2012 (7)Mozambique

Low income

Sub-Saharan Africa

2019, 2018, 2017, 2016, 2015, 2014, 2012 (7)2019, 2018, 2015, 2014, 2013, 2012, 2011 (7)Mongolia

Lower-middle income

South East Asia, East Asia, and Oceania

ThailandUpper-middle income

South East Asia, East Asia, and Oceania

2019, 2018, 2015, 2014, 2011 (5)Montenegro

Upper-middle income

Europe2019, 2018, 2015, 2013, 2012 (5)Georgia

Lower-middle income

Northern Africa and Western Asia

2019, 2018, 2014, 2013, 2012 (5)Costa Rica

Upper-middle income

Latin America and the Caribbean

2019, 2018, 2013 (3)BurundiLow income

Sub-Saharan Africa

2019, 2017 (2)South Africa

Upper-middle income

Sub-Saharan Africa

2019, 2018 (2)Philippines

Lower-middle income

South East Asia, East Asia, and Oceania

2019 (1)

North Macedonia

Upper-middle income

Europe2019 (1)

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.
Notes: Income group classification follows the World Bank Income Group Classification of June 2018. Geographic regions correspond to the United Nations
publication on standard country or area codes for statistical use (M49).

Eighteen economies outperform on innovation relative to GDP
this year. These are called innovation achievers (in purple).34
Burundi, North Macedonia, and the Philippines are new entrants
to this group, relative to the innovation achievers in 2018. North
Macedonia and the Philippines are also innovation achievers forthe first time in the GII. Bulgaria, Serbia, Tunisia, Colombia, andMadagascar—all innovation achievers in 2018—are no longer
part of the group in 2019. South Africa, who joined the group ofachievers in 2018 for the first time, remains an achiever this year.
As in previous years, six of the innovation achievers—and thus
the largest group of economies—are from the Sub-SaharanAfrica region (6). Innovation achievers from South East Asia, East
Asia, and Oceania (4); Europe (4); Northern Africa and Western
Asia (2); Central and Southern Asia (1) and Latin America and the
Caribbean (1) complete the group by geographic region.
Viet Nam and Rwanda are ranked as the top economy in theirincome groups, which are lower middle-income and low-income,respectively. Viet Nam has been an innovation achiever for nineconsecutive years, holding that record together with India,
Republic of Moldova, and Kenya. Viet Nam scores above averagein all the dimensions measured in the GII relative to the lower
middle-income group and has an overall innovation performancethat is comparable to the top economies in the upper

18

The Global Innovation Index 2019

middle-income group. Rwanda scores above the average ofthe low-income group in all innovation dimensions with the
exception of Knowledge and technology outputs.
India ranks 4th among the economies in the lower middle-income
group. It has also been an innovation achiever for nineconsecutive years (Table 1.2).
The Philippines appears for the first time in the group of innovationachievers. It scores above average in all innovation dimensions,with the exception of Market sophistication, relative to its
lower middle-income peers. It has remarkable performance inKnowledge diffusion and Knowledge absorption, not only
relative to its income group and geographic region, but also
relative to all other economies assessed in the GII.
Finally, the economies whose innovation performance is below
their expected levels of economic development are coloredin light blue. This group consists of 33 economies from different
income groups and world regions. The majority (11 economies)
are from the upper middle-income group, notably four from
Latin America and the Caribbean (Dominican Republic, Paraguay,
Ecuador, and Guatemala). The high-income group follows with
10 economies, notably six from the Western Asia region(the United Arab Emirates, Kuwait, Qatar, Saudi Arabia,Bahrain, and Oman). Eight underperformers are from the lower
middle-income group, notably three from Sub-Saharan Africa(Ghana, Nigeria, and Zambia) and three from Latin America andthe Caribbean (El Salvador, Bolivia, and Nicaragua). Only four
economies underperform relative to their levels of development
and are from the low-income group (Yemen, Benin, Guinea,
and Togo). The regions with the most number of economies
performing lower than expectations relative to their level ofdevelopment are Latin America and the Caribbean (9), Northern
Africa and Western Asia (9), and Sub-Saharan Africa (9).

The world’s top innovators in the
Global Innovation Index 2019
The top 10 economies
Switzerland remains the world’s leader in innovation in 2019.
It ranks first in the GII for the ninth consecutive year. It has
ranked 1st in the Innovation Output Sub-Index and in the Knowledge
and technology output pillar since 2012. It also keeps its 1st rank
in the Creative outputs pillar since last year, consolidating once
again its leadership in innovation outputs. Switzerland keeps
its 2nd position in the Innovation Input Sub-Index. It improves
its rank in three innovation input pillars: Market sophistication(up by 1); Business sophistication (up by 2); and notably
Infrastructure (up by 5). In the latter, all improvements are
In the Information and communication technologies (ICTs)
sub-pillar; and notably in the Government’s online service,
and E-participation indicators. In contrast, the country drops
positions in two innovation inputs pillars: Institutions, andHuman capital and research.
In quality of innovation, Switzerland is ranked 4th worldwide,
after the U.S., Germany, and Japan. Its rank decreases thisyear in the metrics for quality of innovation, notably in thequality of local universities and the internationalization of local
inventions. Additionally, rank decreases are seen in the General
infrastructure sub-pillar, where it positions below the top 25(28th, down from 25th in 2018); and in Trade, competition, andmarket scale (26th, down from 19th).
Switzerland is a world leader in several key innovation indicators,
including PCT patent applications by origin (a spot it shareswith Sweden and Finland); ICT services imports; IP receipts;
FDI net outflows; and Environmental performance. Conversely,
and relative to the top 25 in the GII 2019, it has opportunities
to improve in Ease of starting a business, Ease of resolving
insolvency, and Ease of protecting minority investors.
Sweden recovers its 2nd position worldwide this year (up from
3rd), and remains the top Nordic economy in the GII 2019.
It drops by one rank in the Innovation Input Sub-Index to 4th
position; and retains 3rd in the Innovation Output Sub-Index.
It ranks among the top 10 economies in all pillars except forMarket sophistication (14th) where it loses two positions.
It improves its rank in four pillars: Business sophistication,achieving 1st position in the world; Infrastructure (2nd);
Knowledge and technology outputs (2nd); and Human capitaland research (6th). Sweden makes remarkable improvements
in Knowledge absorption (6th), Education (6th), ICTs (12th),and Knowledge diffusion (6th). The significant improvementsin the Knowledge absorption sub-pillar are mainly due toimprovements in the indicator FDI inflows, which remains a
relative weakness for Sweden.
At the indicator level, Sweden keeps its 1st position in PCT
patent applications by origin and IP receipts; and gains the 1st
position on patent families (up from 5th). Sweden’s areas for
improvement include Pupil-teacher ratio, GDP per unit of energyuse, Ease of getting credit, GERD financed by abroad, productivity
growth (Growth rate of PPP$), and Printing and other media.
The United States of America reaches the 3rd position
worldwide, in part due to performance increases and theavailability of new U.S. innovation data (see below). The U.S.
improves its rank in five of the seven GII pillars: Institutions(11th); Human capital and research (12th); Infrastructure (23rd);
Business sophistication (7th); and Knowledge and technology
outputs (4th).35
Keeping its world leading position in Market sophistication (1st);
it also makes important progress in the Knowledge workers
sub-pillar (4th); and in the Innovation linkages sub-pillar (9th).
Relative to the top 25, it is strong in the sub-pillars of Businessenvironment (2nd); R&D (3rd); Credit (1st); Knowledge creation(3rd); and Knowledge impact (2nd). It maintains leadership in aseries of key innovation metrics such as Global R&D companies,
quality of universities (QS university ranking), Venture capitaldeals, State of cluster development (Special Section: Cluster
Rankings), quality of scientific publications (Citable documents
H-index), Computer software spending, IP receipts, andEntertainment and media market. The U.S. also reaches 1st in
University/industry research collaboration this year. It makes
important innovation performance increases in a numberof indicators, notably Creative goods exports (up by 17);
Knowledge-intensive employment (up by 18); Government’s
online service; and E-participation, both up by 7.
The U.S.’ improved ranking in the Human capital and research
pillar, notably in sub-pillar Tertiary education, and in Knowledge
workers is because of improved data availability in the indicators
Tertiary enrolment and Females employed with advanced
degrees, for which data was missing in GII 2018 and became
available in GII 2019.
With regards to the quality of innovation, the U.S. ranks 1st,
above Japan and Switzerland (Figure 1.7). The country achieves
this top position thanks to a combination of its sustained world
leadership on all innovation quality metrics and becauseof decreases in the performance of Switzerland (see above)
and Japan.
The Netherlands is the 4th most innovative economy in theworld. It ranks 11th in the Innovation Input Sub-Index and retains
2nd position in the Innovation Output Sub-Index. Innovation
outputs remain a strength for the Netherland’s innovation
ecosystem, ranking 3rd in Knowledge and technology outputs,
and 5th in Creative outputs.

Chapter 1

19

The Netherlands remains in the top 25 in all innovation input
pillars, and in the top 10 worldwide for Institutions (8th) andBusiness sophistication (6th). At the sub-pillar level, the country’s
strengths remain Innovation linkages (5th), ICTs (4th) and
Knowledge absorption (2nd). At the indicator level, it remains
1st in IP payments and it is consistently strong on Regulatory
quality, E-participation, Intensity of local competition, University/
industry collaboration, State of cluster development(Special Section: Cluster Rankings), and FDI inflows. Important
improvements are also observed in GERD financed by business,
and Females employed with advanced degrees. Conversely,
most of the decreases observed this year are in the Human
capital and research pillar (17th), and notably on the Education(23rd), and Tertiary education sub-pillars (59th). In Education,
the decrease is explained by data availability, notably for theindicator Government funding per pupil, where the country
ranks 36th this year, and for which data was previously missing.
In Tertiary education—amid the same levels of performancein Tertiary enrolment, Graduates in science and engineering,and Tertiary inbound mobility—the country drops ranks inrelative terms as other economies improved their performancein these areas.
In Innovation Outputs, the Netherlands is strong on Knowledge
diffusion (2nd) and Online Creativity (2nd), in particular in indicatorssuch as IP receipts, FDI net outflows, ICTs and business model
creation, and ICTs and organizational model creation. Progressis also observed in the quality of scientific publications (8th) andin Cultural and creative services exports (10th).
The United Kingdom ranks 5th this year, 6th in the Innovation
Input Sub-Index, and gains two spots in the Innovation Output
Sub-Index (4th). The U.K. improves its rank in two pillars:
Knowledge and technology outputs (8th); and Market sophistication(4th). At the sub-pillar level, important increases are in
Knowledge diffusion (12th), Intangible assets (12th), andKnowledge creation (5th). Some indicators that are responsible
for rank improvements in these pillars include Industrial designs
by origin (16th), IP receipts (8th), ICT services exports (28th),and High-tech net exports (18th). Despite these important gains,
the U.K. loses between one and four positions in four of theGII pillars: Business sophistication (16th), Creative outputs (6th),
Infrastructure (8th), and Human capital and research (9th).
The country maintains its lead in the quality of scientificpublications and remains strong in indicators, such as School
life expectancy, the quality of its universities, ICT access,Government’s online service, Environmental performance,
Venture capital deals, Computer software spending, andCultural and creative services exports. Due to its historic
universities and the quality of its scientific publications, the U.K.
is still the 5th world economy in quality of innovation (Figure 1.7).
A frequent question these days is how the U.K.’s planned
withdrawal from the European Union affects the country’s GII
rank. As noted in previous years, the causal relations between
plans or the actual withdrawal from the EU and the GII indicators
are complex and uncertain in size and direction.

20

The Global Innovation Index 2019

Finland moves up to the 6th position this year, continuing its
upward trend from 2017. It ranks 7th in both the Innovation Input
and Output Sub-Indices. On the input side, it improves its
position in three of the GII pillars: Human capital and research(2nd, up by 2), Infrastructure (12th, up by 5), and Businesssophistication (5th, up by 1). The largest decrease is observed inMarket sophistication (27th, down by 12), notably in theInvestment sub-pillar (34th); while it loses one position in
Institutions (3rd). At the sub-pillar level, the largest increases are
in Education (4th, up by 3); and Knowledge absorption (12th,
up by 3), notably in indicator FDI inflows (31st, up by 18). On the
output side, Finland improves notably in Knowledge diffusion(7th); particularly in the indicator FDI outflows (14th), and in
Online creativity (6th). For the latter, changes to the GII model
also partially explain the increase, notably in the indicator
Mobile app creation, where Finland ranks 1st worldwide(Appendix IV).
Finland maintains its lead in PCT patent applications by origin,while it achieves the 1st rank this year in both Rule of law
and E-participation. It remains a world leader in a number ofimportant innovation metrics, such as Patent families, School life
expectancy, and Ease of resolving insolvency. Relatively weak
performance is observed in Pupil-teacher ratio, Gross capitalformation, productivity growth, Trademarks by origin, andPrinting and other media.
Denmark ranks 7th in the GII 2019, increasing by one rank
from last year. It increases by two spots in the Innovation Input
Sub-Index (5th), and by one spot in the Innovation Output
Sub-Index (12th). Denmark remains in the top 15 in all GII pillars,
and improves its position in 4 of the pillars: Human capital andresearch (4th, up by 2), Infrastructure (6th, up by 9), Businesssophistication (9th, up by 5), and Knowledge and technology
outputs (14th, up by 1). In Human capital and research, the mostnotable improvement is in the Education sub-pillar (2nd), notably
because of sustained high levels of expenditure on education.
In Infrastructure, increases are observed in ICTs (2nd) and
General infrastructure (33rd) and, in particular, in indicators ICT
use (1st), Government’s online service (1st), E-participation (1st),and Logistics performance (8th). In Business sophistication, mostimprovements occurred in the sub-pillars Innovation linkages(7th, up by 11), notably in the indicator GERD financed by abroad;and in Knowledge absorption (20th, up by 6), in particular in
ICT services imports. In addition, Denmark ranks in the top 3 ina number of indicators such as Scientific and technical articles(1st), Researchers (2nd) and Environmental performance (3rd).
Opportunities for further improvement still exist, notably inindicators such as Graduates in science and engineering, Gross
capital formation, Utility models by origin, productivity growth,Trademarks by origin, and Printing and other media.

Singapore ranks 8th this year. It remains first in the world in
the Innovation Input Sub-Index and keeps its 15th positionin the Innovation Output Sub-Index. However, Singapore loses
positions in all Inputs pillars, with the exception of Institutions,in which it still ranks 1st. Improved data availability partiallyexplains ranking decreases. Some indicators that were
unavailable last year became available this year, notably in the
Human capital and research pillar (5th), in which Singapore
loses 4 ranks. In this pillar, there is an important decrease in theindicator Global R&D companies (30th). Drops in this indicator
are caused by a re-location back to the U.S. of Broadcom,
a technology hardware and equipment company. Broadcom
was the largest R&D spender in Singapore until last year.36
Singapore loses two ranks in the pillars Infrastructure (7th) andBusiness sophistication (4th). In Infrastructure, ICTs (11th) andEcological sustainability (22nd) are the weaker performing
sub-pillars, with several indicators decreasing—notably
E-participation, ICT use, and ISO 14001 environmental certificates.
In Business sophistication, the country loses several ranks,
particularly in the indicator Females employed with advanced
degrees, but also in FDI inflows and IP payments. It loses one
rank in the Market sophistication pillar (5th). Ease of getting
credit and Market capitalization are the indicators where thecountry loses most positions in this pillar.
Singapore increases its performance in several indicators within
the Knowledge and technology outputs pillar (11th), notably inlabor productivity growth, and ICT services exports. However,other indicators, such as ISO 9001 quality certificates, FDI net
outflows and Computer software spending, have decreased,leaving performance in this pillar unchanged relative to last year.
Singapore improves its position by one rank in the Creative
outputs pillar (34th), thanks to the indicator of Mobile app
creation, in which it ranks 10th worldwide.
Singapore becomes the global leader (1st) in a number ofimportant innovation parameters, notably in Tertiary inboundmobility (up from 5th), Knowledge-intensive employment(up from 2nd), and JV-strategic alliances deals (up from 3rd).
Germany retains 9th place for the third consecutive year.
It improves to 12th position in the Innovation Input Sub-Index(up by 5 positions), and ranks 9th in the Innovation Output
Sub-Index. It ranks in the top 20 across all GII pillars, and in the
top 10 worldwide in both innovation output pillars. Germany
improves its performance in three pillars: notably in Human
capital and research, where it gains 7 positions and moves
into the top 3; Infrastructure (13th); and Business sophistication(12th). In these three pillars, it improves the most in Tertiary
education (5th), Innovation linkages (10th) and Informationand communication technologies (15th). The largest increasein the Tertiary education sub-pillar is mainly due to betterdata coverage. For the indicator Graduates in science andengineering—for which data was missing in the GII 2018—
Germany ranks 4th worldwide. On the output side, Germany
keeps its 10th rank in Knowledge and technology outputs andloses three spots in Creative outputs (10th).

As in previous years, Germany remains 1st in Logistics
performance and in Patents by origin. It remains 2nd in
Global R&D companies; improves to 2nd in State of cluster
development (up by 1); and remains 3rd in the quality of scientificpublications. Thanks to these high ranks, Germany ranks
2nd in the quality of innovation. This increase is partly due
to the increased quality of its scientific publications, butalso to the relative decrease of innovation quality in Switzerland
and Japan (Figure 1.7).
Despite important achievements, there is still opportunity for
improvement in some innovation areas, such as the Easeof starting a business, Expenditure on education, Gross
capital formation, GERD financed by abroad, FDI net inflows,
productivity growth, New businesses, and Printing and othermedia. These opportunities for improvement have remained
unchanged since last year.
Israel breaks into the top 10 of the most innovative economies
in the world for the first time, after several years of increased
performance. It remains 1st in the Northern Africa and Western
Asia region, and keeps its position in the top 10 worldwide in
two pillars: Business sophistication (3rd) and Knowledge andtechnology outputs (7th). This year it improves its rank in two
pillars, Institutions (31st) and Creative outputs (14th). At the
sub-pillar level, Israel improves in Research and development(2nd), and keeps its top rank in Innovation linkages. It also
retains its 1st position in a number of important indicators, such
Researchers, R&D intensity (GERD performed by business,% GDP), Research talent in business enterprise, ICT services
exports, and Wikipedia edits. It also reaches the 1st rank in
Mobile app creation.37 Other indicators where Israel ranks inthe top 3 include Patent families (2nd), a notable performanceincrease relative to last year; Females employed with advanced
degrees (3rd); University/industry research collaboration (2nd),
GERD financed by abroad (3rd); and Venture capital deals (3rd).
Israel’s innovation weaknesses are mostly in innovation inputs.
The Tertiary education sub-pillar is a weakness, and notably theindicator Tertiary inbound mobility. Other areas for improvement
include Government funding per pupil, PISA results, Gross
capital formation, Firms offering formal training, GERD financedby business, and IP payments. On the output side, there are twoareas for improvement in the pillar Creative outputs: Trademarksby origin, and Printing and other media.

Chapter 1

21

BOX 4

What is the innovation secret of small economies?
Why do a number of city-states or small economies—measured
by their population or geographic size—make it into the
GII top 20?
Here we look more in-depth at three examples to seek ananswer: Singapore—ranked 8th with a population of 5.6 million;
Hong Kong (China)—ranked 13th with a population of
7.5 million; and Luxembourg—ranked 18th with a populationof 0.6 million. All three small economies share similar traits—
reduced geographical space, no natural resources, andextremely open economies. They act as regional hubs for tradeand investment and are strong in services—in particular,
financial services. Relative to all high-income economies,
these three economies score high in Institutions—in particular,
Singapore and Hong Kong (China), Infrastructure—Hong Kong
(China) and Singapore, and Business sophistication—Singapore
and Luxembourg. Their high scores demonstrate an excellent
environment that, for example, is supportive of innovation,
has good regulatory quality, and ranks well in the ease ofstarting a business. In the pillar Human capital and research,
Singapore stands out.
For innovation outputs, Singapore and Hong Kong (China)score high relative to other high-income economies in thepillar Knowledge and technology outputs. Yet, only Singapore
has a strong lead. Except for Singapore, these economies
are often not directly involved in high-tech manufacturing andtheir manufacturing base is small. They export few locally
produced high-tech products.38 In Creative outputs, in turn,
Luxembourg and Hong Kong (China) perform best (Box 5).
What innovation ambitions and policies do these economies
harbor for the near future? 39
Singapore aims to be a center of innovation and a key node
along the global innovation supply chain where innovative firms
thrive on the basis of intellectual property and intangible assets.
To achieve this ambition, one strategy is to strengthen
Singapore’s innovation ecosystem by helping enterprises toinnovate and scale up. Singapore envisages advancing its
conducive environment, international linkages, capabilities inintangible asset management, IP commercialization, and skilledworkforce. In 2016, the Government of Singapore committed
US$14 billion for research, innovation, and enterprise activities.
It identified four strategic domains for prioritized researchfunding: (1) advanced manufacturing and engineering, (2) healthand biomedical sciences, (3) services and digital economy,and (4) urban solutions and sustainability.40 The Intellectual
Property Office of Singapore (IPOS) has also transformed tobetter serve global innovation communities by conducting
regular reviews of Singapore’s IP policies and building capabilities
in intangible asset management and IP commercialization,
including IP skills.41

22

The Global Innovation Index 2019

Hong Kong, China also plans to develop into a leadinginternational innovation hub, benefiting from its position in Asiaand its proximity and links to other parts of China. There areplans by China and Hong Kong (China) to further develop the
Guangdong-Hong Kong-Macao Greater Bay Area (Bay Area)—
which encapsulates the city of Hong Kong and Shenzhen—as
a major global innovation cluster. The Government of Hong
Kong (China) has committed over US$13.5 billion since 2017to promote innovation and technology. Two research clusters
are to be established—one on healthcare technologies andthe other on artificial intelligence and robotics. In addition,
the government has promoted re-industrialization to develop
high-end manufacturing. In sum, innovation and technology
development is pressing ahead swiftly under an eight-pronged
strategy, including (1) increasing resources for R&D, (2) poolingtechnology talent, (3) providing investment funding, (4) providing
technological research infrastructure, (5) reviewing legislations
and regulations, (6) opening up government data, (7) enhancing
government procurement arrangements, and (8) promoting
science education. A Technology Talent Admission Scheme was
set up to attract non-local talent. The government has also put
emphasis on fostering smart city innovations.
Luxembourg, in turn, aims to develop its innovation leadership
through its strong infrastructure, its location in the heart ofEurope, its strong services economy, and its talent base.
Luxembourg’s efforts are focused on five key areas: infrastructure,skills, government, ecosystem, and policy. Luxembourg aims
to invest around 2.5% of its GDP in research in 2020. New
financing programs will be launched to foster digital high-techstart-ups. In May 2019, Luxembourg presented its national AI
strategy and is rolling out its data-driven innovation strategy
with focus on seven specific sectors: ICT, manufacturing industry,
eco technologies, health technology, space, logistics, andfinancial services.42 Examples of innovative initiatives are therollout of fiber optic cable to homes, 5th generation networks,
and its National CyberSecurity Strategy. Other areas ofpolicy focus include increasing investments and strides inhigh-performance computing,43 creating a national strategy
for AI,44 boosting the commercial adoption of block chain,45
fostering digital skills,46 and developing further the local spaceindustry.47 Luxembourg also prioritizes the exploitation of public
sector information and open data to spur innovation. In thearea of talent, Luxembourg has simplified residence permits forhighly qualified workers.

What are the top 10 economies ininnovation inputs?
The top 10 economies in the Innovation Input Sub-Index are
Singapore, Switzerland, the U.S., Sweden, Denmark, the U.K.,
Finland, Hong Kong (China), Canada, and the Republic of Korea.
Hong Kong (China), Canada, and the Republic of Korea are theonly economies in this group that are not in the GII top 10.
Box 4 takes an in-depth look at the relationship between
economy size and innovation performance.
Hong Kong, China keeps the 8th spot in the Innovation Input
Sub-Index for the third consecutive year and ranks 13th in the
GII overall, up from 14th in 2018. It moves downward in all input
pillars except for Institutions (7th, up by 3) where it benefits fromthe introduction of the new indicator of Political and operational
stability (Appendix IV). In this pillar, it keeps its top rank in
the indicator of Cost of redundancy dismissal and gains inRegulatory quality. Government effectiveness and Ease ofstarting a business also rank well (5th rank overall). Hong Kong
(China) also retains good rankings in Market sophistication (3rd)and Infrastructure (4th). In five of the 15 input sub-pillars, it ranks
in the top 10; these are Political environment (4th), Regulatoryenvironment (3rd), Ecological sustainability (2nd), Credit (2nd),and Knowledge absorption (8th). It ranks in the top 3 in several
indicators, such as PISA results, GDP per unit of energy use,
Domestic credit to private sector, High-tech imports, and
FDI net inflows. Relative weaknesses on the input side include
Expenditure on education, Global R&D companies, GERD
financed by abroad, IP payments, and ICT services imports.
Canada moves up to the 9th position in the Innovation Input
Sub-Index and to the 17th in the GII ranking, up one from2018. Its strengths on the input side are a result of high andimproved rankings in two pillars: Market sophistication (2nd)and Institutions (4th). This year, the country also improves in
Business sophistication (22nd), where it gains the top rank in
JV-strategic alliance deals. In Market sophistication, Canada
maintains its top rank in Venture capital deals. However,country data for indicators Domestic credit to private sector andMicrofinance gross loans were unavailable, making the Credit
sub-pillar difficult to measure. In Institutions, the country ranks
3rd in Ease of starting a business and is in the top 10 in
Political and operational stability, Government effectiveness,
Regulatory quality, and Rule of law. Interesting changes occur
also in Human capital and research, where data for four
variables became available this year. This allows a bettermeasurement of Canada’s performance in Education (51st)and Tertiary education (32nd). In this pillar, the country takes
the 6th spot in the quality of universities. Thanks to this higherscore and to a higher score in quality of scientific publications,
Canada also joins the top 10 in the quality of innovation thisyear (Figure 1.7). Canada’s relative weak areas include
Graduates in science and engineering, GDP per unit of energyuse, and ICT services imports.

The Republic of Korea (Korea) enters the top 10 in the
Innovation Input Sub-Index this year, keeping up its good
performance and gaining four positions since 2018. In theoverall GII ranking, it moves closer to the top 10 (11th, up by 1).
On the input side, Korea improves the most in Businesssophistication (10th, up by 10) and gains positions in Human
capital and research—where it becomes the top economy in
the world—and in Market sophistication (11th, up by 3). In thesepillars, the indicators that see the largest gains include
Knowledge-intensive employment, JV-strategic alliance deals,
Expenditure on education, and Venture capital deals. Korea
maintains its good ranks in a number of crucial variables,
including most of the R&D-related indicators, as well as Tertiaryenrolment, Researchers, Research talent in business enterprises,
E-participation, ICT use, and Patent families in two or more
offices. Despite this good performance, the country presents
areas of relative weakness, which include Tertiary inboundmobility, GDP per unit of energy use, GERD financed by abroad,
ICT services imports, and FDI net inflows.

What are the top 10 economies ininnovation outputs?
The top 10 economies in the Innovation Output Sub-Index thisyear are Switzerland, the Netherlands, Sweden, the U.K., China,
the U.S., Finland, Israel, Germany, and Ireland.
The 10 economies leading the Innovation Output Sub-Index
remain broadly the same as in 2018, with six shifts and one
substitution: the U.K., China, the U.S., and Finland move upwardwithin the top 10; while Germany and Ireland move downward.
Israel enters the top 10, while Luxembourg exits. Eight of these
economies are ranked in the GII top 10. The innovation profileof the other two economies, China and Ireland, are discussed
below. Box 5 presents an in-depth look at this year’s results on
the Creative outputs pillar.
China makes an impressive improvement in the Innovation
Output Sub-Index this year, reaching the 5th position worldwide,
up five positions from 2018—the year in which it reached the
top 10 in the GII Output Sub-Index for the first time.
In Knowledge and technology outputs, it moves up one
place in Knowledge impact to regain its 1st rank worldwide,and maintains its position in Knowledge creation (4th) and
Knowledge diffusion (22nd). Most improvements in thispillar are due to sustained and increased performance invariables such as PCT patent applications (17th), ISO 9001
quality certificates (20th), and ICT services exports (75th).
Improvements in this pillar are partially due to model changes,
notably in the productivity growth variable, where China ranks
1st this year (up by 3). In this same pillar, China remains 1st inother key innovation metrics: Patents by origin, Utility models
by origin, and High-tech net exports.
In Creative outputs, China improves in two sub-pillars: Creative
goods and services (15th, up by 13); and Online creativity(79th, up by 5). It keeps its 1st position in Intangible assets.
It remains top-ranked in Industrial designs by origin andChapter 1

23

Creative goods exports, and achieves the 1st rank this year in
Trademarks by origin (up by 2). China also maintains its firstplace in quality of innovation among middle-income economies
for the seventh consecutive year (Figure 1.7). It improves its
performance in all innovation quality metrics and ranks 3rd
globally in the quality of universities.
Areas of improvement in the innovation output side include
National feature films, Printing and other media, and Wikipedia edits.
Ireland ranks 10th in the Innovation Output Sub-Index this year.
It is 6th in the Knowledge and technology outputs pillar—
despite progress in a few areas, Ireland loses two ranks sincelast year, in part driven by better innovation performance in othereconomies. Ireland keeps its 19th position in Creative outputs.

In Knowledge and technology outputs, it moves up in Knowledge
creation (31st, up by 6), and Knowledge impact (3rd, up by 2). It
remains the top economy worldwide in Knowledge diffusion (1st).
The most important improvements in this pillar are in PCT patentapplications (22nd, up by 4), and High- and medium-high-tech
manufactures (2nd, up by 1). Conversely, weaker performance isobserved in Patents by origin (39th, down by 3), Scientific andtechnical articles (39th, down by 2), and High-tech net exports(16th, down by 1). In this pillar, Ireland remains 1st in the world in
ICT services exports and FDI net outflows, and 2nd in Computer
software spending.
In Creative outputs, Ireland improves in Intangible assets(8th, up by 4), but decreases in Creative goods and services(59th, down by 11), and Online creativity (24th, down by 2). Someof the areas responsible for the decreases are National featurefilms (21st) and Creative goods exports (40th). In contrast, progress
is observed in Industrial designs by origin (59th, up by 9).

BOX 5

Which economies rank high on Creative outputs?
The GII considers creativity, and non-technological forms
of innovation, as important ingredients befitting innovative
economies and societies.
China leads in Intangible assets, Hong Kong (China) in
Creative goods & services, and Luxembourg in Online creativity.
Few economies rank in the top 10 for all three categories, but
Luxembourg and Switzerland stand out with a top 10 position
in all three. Hong Kong (China), and Malta each hold top 10
positions in two categories. The strength of small economies isparticularly true in Online creativity, where Luxembourg trumps
the list among other similarly small economies (Box 4). However,there are exceptions as large economies scoring high in Online
creativity include Germany, France, the U.S., and the U.K.
Since last year, in collaboration with App Annie and its mobile
data platform, which tracks Google Play store and iOS AppStore activity in each economy, the GII has been generating
performance metrics based on the creation of mobile apps
(Appendix IV). In absolute numbers, the U.S. is the uncontested
leader in app creation, followed by France, India, the Republicof Korea, the U.K., and the Russian Federation (Box 5, Figure 1).
Complete data for China is not available, but it would occupy
a top slot.

24

The Global Innovation Index 2019

When the GII scales this data for GDP, a different picture emerges.
Cyprus, Finland, and Israel lead followed by economies in
Eastern Europe (Lithuania and Estonia), and Asian economies
such as Hong Kong (China) and Singapore.
Frequently, markets with companies that perform well in theapp world are also ones with strong enough economies toattract entrepreneurs. The U.S. is where many tech companies
are located and where the world’s largest app stores began.
For companies headquartered outside the U.S., their successrepresents both the size of their home markets and their ability
to carve out a sizable share when it comes to app creation.
While India, Brazil, and the Russian Federation are near the top,
other large countries, such as Indonesia, primarily utilize apps
created by companies from other countries. It is easier tocreate apps that address needs in local markets and then
expand internationally from there. Gaming apps are unique in
that, while regional preferences and localization influence
success, they are generally scalable globally. In gaming, one
or two successful companies have the potential to move theneedle for an entire country.48

BOX 5, FIGU RE 1

Global app downloads (billions) produced by local companies, 2018
18
16
14
12
10
8
6
4
2
0

UnitedStates ofAmericaFranceIndia

Republicof Korea

UnitedKingdom

RussianFederation

Japan

Germany

TurkeyBrazil▲ Global app download (billions) produced by local companies
Source: App Annie, 2019.

Who is best on the quality ofinnovation?
Moving beyond quantity to quality indicators of innovation
has become an overarching concern to the innovation policy
community. With this in mind, three indicators that measure
the quality of innovation were introduced into the GII in 2013:
1) quality of local universities (indicator 2.3.4, QS university
ranking, average score of top 3 universities); (2) theinternationalization of local inventions (indicator 5.2.5,
Patent families filed in at least two offices); and (3) the qualityof scientific publications, as measured by the number ofcitations that locally produced research documents receive
abroad (indicator 6.1.5, Citable documents H-index).
Figure 1.7 shows how the scores of these three indicators
are added to capture the top 10 highest performing high- andmiddle-income economies in the quality of innovation.
Among the high-income economies, the U.S. regains the top
rank for quality of innovation, moving ahead of Japan, whichmoves down to 3rd this year. Germany is 2nd for the first time,
above both Japan and Switzerland. The U.K. is stable at 5th,
while the Netherlands moves up to 6th—its highest ranking in
the quality of innovation to date. Sweden and the Republic ofKorea rank 7th and 8th, respectively. France is stable at 9th
and Canada, whose last appearance in this group was in 2016,re-enters in 10th, replacing Finland.
The U.S. returns this year to the top position in quality of innovation
among the high-income economies. This achievement, seen
before in 2017, reflects consistent performance in the qualityof publications and high scores for the top 3 U.S. universities:
The Massachusetts Institute of Technology (MIT), Stanford
University, and Harvard University.
Germany improves this year in the quality of innovation (2nd)with a higher score in quality of scientific publications H-Index(1,059 to 1,131) and better scores for its top three universities: theTechnical University of Munich (TUM), the Ludwig Maximilian
University of Munich, and Heidelberg University.

Chapter 1

25

FIGURE 1.7

Metrics for quality of innovation: top 10 high- and middle-income
economies, 2019
High-income economies
1

United States of America

2Germany

3

Japan

4

Switzerland

5

United Kingdom

6

Netherlands

7

Sweden8

Republic of Korea

9

France10 Canada
Average (50 economies)

Middle-income economies
15 China
26 India
27 Russian Federation
28 Brazil
32 Malaysia
33 Mexico
36 South Africa
41 Turkey
43 Colombia
44 Thailand
Average (60 economies)0⊲ Sum of scores

■
■
■

50

100

150

200

250

300

2.3.4: QS university ranking average score of top 3 universities
5.2.5: Patent famililes ﬁled in two or more oﬃces
6.1.5: Citable documents H-index

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.
Notes: Numbers to the left of the economy name are the innovation quality rank. Economies are classiﬁed by income according to the World Bank Income GroupClassiﬁcation (July 2018). Upper- and lower middle-income categories are grouped together as middle-income economies.

26

The Global Innovation Index 2019

The U.K. remains stable in quality of innovation (5th) andremains 2nd in the quality of universities, with top scores for
University of Oxford, University of Cambridge, and Imperial
College London. The U.K. shares 1st place in quality of scientificpublications with the U.S.—for the sixth consecutive year.
Sweden reaches the top position in patent families for the
first time.
Canada joins the top 10 in quality of innovation with higherscores in the quality of scientific publications.
The ranking of middle-income economies in these innovation
quality indicators remains steady, with China (15th), India (26th),
and the Russian Federation (27th) in the top 3 positions. Brazil(28th), Malaysia (32nd), and Mexico (33rd) are next in line,
followed by South Africa (36th), Turkey (41st), Colombia (43rd),and Thailand (44th). This year, aside from China, Malaysia andThailand are the fastest movers in this group. Colombia is thethird economy from Latin America and the Caribbean in this list.
China remains as the top middle-income economy in the qualityof innovation for the seventh consecutive year. Positioned 15th,
China is the only middle-income economy that is closing the gap
with the high-income group in all three indicators. China ranks
3rd in quality of universities. Similarly, China’s score for qualityof scientific publications stands above the high-income groupaverage.
India ranks 2nd in the quality of innovation among the
middle-income economies for the fourth consecutive year,with top positions in quality of scientific publications (2nd) andin the quality of universities (3rd), notably due to the performanceof its top 3 universities: the Indian Institute of Technology(Delhi and Bombay) and the Indian Institute of Science Bengaluru.

Brazil retains its 4th place among its middle-income peers and28th globally, although displaying lower scores in the quality ofuniversities this year.
Malaysia is 5th among middle-income economies and 32nd
overall in the quality of innovation.
Colombia, 9th in this group, enters the middle-income top 10
for the first time since 2016. Higher scores in both international
patents and the quality of scientific publications assist
Colombia’s performance, leading to an overall ranking of 43rd.
Colombia is 8th among its income group peers in the qualityof its universities, with notable scores for Los Andes Universityof Colombia, National University of Colombia, and Externado
University of Colombia.
With regards to the quality of universities, high-income economies
hold almost all top ranks. The U.S. and the U.K. take the top
5 positions for individual universities. Singapore is the only
non-Northern American or European economy with universities
in the top 15 worldwide (National University of Singapore andNanyang Technological University).
In the middle-income group, the top 3 universities are locatedin China, after which, India holds the most top slots. India isalso the only lower middle-income economy with a university
in the top 10 among middle-income economies (Table 1.3).
Regarding the quality of scientific publications (Citable documents
H-index), among the top 5 in the high-income group, only
the U.S. and Canada are non-European economies. In the
middle-income group, China takes the top position. India is
2nd, as the only lower middle-income economy in the top ranks.
The Islamic Republic of Iran ranks 9th among middle-income
economies in the quality of publications and 12th overall in thequality of innovation among middle-income economies.

TABLE 1.3

Top 10 universities in middle-income economies
Location

University

Score

China

Tsinghua University

87.2

China

Peking University

82.6
77.6

China

Fudan University

Malaysia

Universiti Malaya (UM)*62.6

Russian Federation

Lomonosov Moscow State University

62.3

MexicoUniversidad Nacional Autónoma de México (UNAM)

56.8

BrazilUniversidade de São Paulo (USP)

55.5

India

Indian Institute of Technology Bombay (IITB)

48.2

India

Indian Institute of Science (IISC) Bengaluru

47.1

India

Indian Institute of Technology Delhi (IITD)**

46.6

Source: QS Quacquarelli Symonds Ltd, QS World University Ranking 2018/2019
Notes: Only universities among the top 3 in each economy are considered. *Shares the same rank (87th worldwide) with Rice University in the U.S.
**Shares the same rank (172nd worldwide) with the University of Aberdeen in the U.K. and University of Twente in the Netherlands.

Chapter 1

27

On international patents, European economies take seven of
the top 10 positions, with the other three spots going to Israel,
Japan, and the Republic of Korea. Among middle-income
economies, China and South Africa take the top two positions,with India and Turkey registering improvements in this indicator.

Which economies get more returnon their innovation investments?
On the basis of the GII data, we analyze which economies mosteffectively translate innovation inputs into innovation outputs.
In 2018, the GII started plotting the input-output performanceof economies against each other (Figure 1.8) based on advice
from the European Commission’s Competence Centre on
Composite Indicators and Scoreboards (COIN) at the Joint
Research Centre (JRC).
Among the high-income economies, located more towards
the right of Figure 1.8, economies like Switzerland (CH), theNetherlands (NL) and Sweden (SE) produce more outputs
relative to their levels of innovation inputs. In turn, Singapore(SG), the United Arab Emirates, Brunei Darussalam (BN),and Trinidad and Tobago (TT) are producing less outputs fortheir levels of inputs invested in innovation.
Viet Nam (VN) and India (IN) stand out as lower middle-income
economies that are getting much more outputs for their inputs.
Their levels are above those of high-income oil-rich economies
like Kuwait (KW), Qatar (QA), Bahrain (BH), and Oman (OM)
(Figure 1.8, Highlight 1).
Within upper middle-income economies, China stands out for
producing innovation outputs that are comparable to thoseof Germany (DE), the U.K., Finland (FI), and Israel (IL), but
at a lower level of innovation inputs invested. Assuming thatboth inputs and outputs are properly measured, both the U.S.
and China produce similar outputs, with the U.S. investing moreon the input side (Figure 1.8, Highlight 2).
Various economies at different levels of development havecomparable output levels, although the efforts on the input sidediffer. With significantly lower investments on the input side,
Zambia (ZM), a low-income economy, achieves the same levelof outputs as Brunei, a high-income economy (Group 1). The
Czech Republic (CZ) also achieves the same level of outputs as
Singapore (SG), yet at much lower levels of input (Group 3).

Which countries lead theirrespective regions?
Sub-Saharan Africa (24 economies)
For several editions, the GII has noted that Sub-Saharan Africa
performs relatively well on innovation (Table 1.2). Since 2012,
Sub-Saharan Africa has had more economies among the groupof innovation achievers than any other world region.

28

The Global Innovation Index 2019

As in 2018, South Africa takes the top spot among all economies
in the region (63rd), followed by Kenya (77th), Mauritius (82nd),
Botswana (93rd), Rwanda (94th), Senegal (96th), and the United
Republic of Tanzania (97th). Among these, Kenya, Rwanda, andSenegal improve their GII ranking compared to 2018, while
South Africa, Mauritius, Botswana, and the Republic of Tanzania
drop positions.
The remaining 19 economies in this region can be found at
ranks lower than 100. Five of them have improved since 2018:
Uganda (102nd), Côte d’Ivoire (103rd), Ghana (106th), Nigeria(114th), and Burkina Faso (117th).
Because of improved data coverage, Ethiopia (111th) and Burundi(128th) are covered in the GII rankings this year (Appendix IV).

Central and Southern Asia (9 economies)
Economies of the Central and Southern Asia region have seen
further improvements in their GII rankings in 2019, with fiveeconomies improving their rankings and India moving forward
into the top half of the GII.
India maintains its top place in the region, moving up fivespots—from 57th last year to 52nd this year. The Islamic Republicof Iran remains 2nd in the region, moving up four positions totake the 61st spot. Kazakhstan moves down five positions,ranking 79th this year. The remaining economies rank in order
within the region as follows: Sri Lanka ranks 89th this year,
followed by Kyrgyzstan (90th), Tajikistan (100th), Pakistan (105th),
Nepal (109th), and Bangladesh (116th).
India ranks 52nd in the GII this year, gaining five positions since
2018. It remains 1st in the region and moves up to the 4th
position in the GII rankings among lower-middle-income
economies. India has also outperformed on innovation relative
to its GDP per capita for nine years in a row, as shown in
Table 1.2. The country confirms its rank among the top
50 economies in two pillars—Market sophistication (33rd) and
Knowledge and technology outputs (32nd)—with the latterbeing the pillar in which India ranks the highest this year.
Thanks to higher scores in patent families in two or more offices
and the quality of scientific publications, India remains the 26th
economy in the quality of innovation aggregate and the 2nd
after China among middle-income economies (Figure 1.7).
India's improvement this year is largely due to its relative
performance and less so to new GII data or methods. It improvesin four of the seven GII pillars.
The pillar that improves the most is Knowledge and technology
outputs, where the country gains 11 spots. Ranking improves
for several variables—the most notable gains are in IP-related
variables, notably Patents by origin and PCT patent applications
by origin, and IP receipts, which benefits from a methodologicalchanges (Appendix IV). In this pillar, India maintains its top
position in ICT services exports, where it ranks 1st in the world,
and in labor productivity growth (4th).

FIGURE 1.8

Innovation input/output performance by income group, 201970

CH
Group 2

60

NL
IL

CN

DE

FI

SE
US

Highlight 2

50
CZ

SG Group 3

Highlight 1
40
VN

IN

30

AE

KW
TZ

QA
BH

20
Group 1

TT

OM
BN

ZM
10

0
20

30

40

50

70

60

▲ Output score⊲ Input score● High income● Upper-middle income● Lower-middle income● Low income— Fitted values

AE
BH
BN
CH
CN

CZ
DE
FI
IL
IN
KW

NL Netherlands
OM Oman
QA Qatar
SE Sweden
SG Singapore
TT Trinidad and Tobago

TZ

United Arab Emirates
BahrainBrunei Darussalam
Switzerland
China

Czech Republic
Germany
FinlandIsraelIndia
Kuwait80

United Republicof Tanzania
US United States of America
VN Viet Nam
ZM Zambia

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.

Chapter 1

29

FIGURE 1.9

India ahead of average lower middle-, upper middle-, andhigh-income economies, 2019
100

80

60

40

20

0
Gross
expenditure
on R&D

Intellectual
property
payments

High-tech
imports▲ GII 2019 Score

CitableHigh- &
documents medium-high
H-indextech
manufactures● India● High income

QS top 3
university
rankings

Gross capital Graduates in Growth rate
formationscience &GDP perengineering
personengaged

Eparticipation

ICT services
exports● Upper-middle income● Lower-middle income

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.

The other three GII pillars that move up this year are all related
to innovation inputs; these are Institutions (77th, up by 3), Human
capital and research (53rd, up by 3), and Market sophistication(33rd, up by 3).
In Institutions, the majority of the indicators present a better
ranking this year. The most notable gains are found in Politicaland operational stability where a new indicator is used thisyear (Appendix IV) and in Ease of starting a business, thanks
to important reforms aimed at streamlining bureaucratic
procedures.49
In Human capital and research, two important variables
improve: Gross expenditure on R&D and Global R&D companies(a relative strength for the country). In the former, despite
improvement, India is still 50th. Its share in world R&D expenditures
has increased since the mid-1990s, but less sharply thanother middle-income countries, such as China, or other Asian
powerhouses, such as the Republic of Korea (Figure 1.9).
In Global R&D companies, India reaches the 15th spot as the30

The Global Innovation Index 2019second middle-income economy. In this pillar, the indicator
Graduates in science and engineering (7th) remains a relative
strength for the country. Thanks to the quality of its top 3
universities—the Indian Institute of Technology (Delhi and
Bombay) and the Indian Institute of Science in Bengaluru, India
achieves a relatively strong ranking in the indicator quality ofuniversities (21st).
In Market sophistication, six of the nine indicators improve,and some quite substantially. Ease of getting credit (20th),
Microfinance gross loans (23rd), Market capitalization (20th),and Venture capital deals (30th) all gain positions. In this pillar,
Intensity of local competition also contributes to the improved
performance of the country, moving up 23 positions.
The other three GII pillars—Infrastructure (79th), Businesssophistication (65th), and Creative outputs (78th)—lose inrelative strengths to other countries. In these pillars, the largest
drops are found in Logistics performance, Females employedwith advanced degrees, and Printing and other media.

Significant improvements are found in some pillars—for example,in State of cluster development. This is also confirmed in theSpecial Section: Cluster Rankings, highlighting the performanceof Bengaluru, New Delhi, and Mumbai. In addition, High-tech
imports move up by 24 spots, in part reflecting improved data
(Appendix IV).
While India improved in the GII ranking, some relative weaknesses
still persist. These include Environmental performance, New
businesses, and Entertainment and media market.
Finally, it is worth noting that while India’s data coverage isamong the highest in the GII, two important indicators—notably
GERD financed by business and GERD financed by abroad—arestill missing. Moreover, a significant number of indicators are
outdated. Almost half of them are in the pillar Human capitaland research, with Education having 4 out of 5 variables outdated.

Many relate to research—Researchers, R&D intensity (GERD
as a percentage of GDP), R&D performed by business, andResearch talent in business enterprise. The availability ofcomplete innovation metrics would help obtain a fuller pictureof India’s performance. The country could also benefit greatly
from updating and measuring all aspects of R&D more
systematically. One example is the indicator on Global R&D
companies’ expenditures, which improved further this year andreflects the efforts of the Indian private sector in R&D.
The sub-region of Central Asia is noteworthy for starting toprioritize innovation activities and related policies in a sustainedmanner. Three economies in the sub-region are covered in the
GII 2019: Kazakhstan (79th), Kyrgyzstan (90th) and Tajikistan(100th) (Figure 1.10). Uzbekistan is making continuous progress indata collection to be included in the GII rankings.

FIGURE 1.10

GII 2019 rankings of economies in Central Asia

Kazakhstan

Uzbekistan
Kyrgyzstan

Turkmenistan

Tajikistan■

Top 80■Top 90■

Top 100■

Not covered

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.

Chapter 1

31

Latin America and the Caribbean(18 economies)
Latin America and the Caribbean economies all position below
the top 50 in the GII ranking. Most economies in this region are
either among the upper middle- or lower middle-income groups,
with five exceptions in the high-income group: Chile, Uruguay,
Trinidad and Tobago, Argentina, and Panama, which are nowclassified in this group. The top 3 economies in the region are
Chile (51st), followed by Costa Rica (55th), and Mexico (56th).
Following this group are Uruguay (62nd), Brazil (66th), andColombia (67th). An additional eight economies in the region
stand in the top 100. These are Peru (69th), Argentina (73rd),
Panama (75th), Jamaica (81st), the Dominican Republic (87th),
Trinidad and Tobago (91st), Paraguay (95th), and Ecuador (99th).
Despite incremental improvements and encouraging initiatives,no clear signs for significant take-off are visible in Latin America
and the Caribbean.50 The GII has insisted that Latin America’s
innovation potential remains largely untapped.51
Despite these concerns, this year, one economy from thisregion—Costa Rica—continues to outperform on innovation
relative to its level of development (Figure 1.6). Chile is the only
country in the region that scores above the regional averagein all GII pillars. Colombia and Peru score above the regional
average in all innovation input pillars, showing potential for
take-off in the future. Costa Rica, Mexico, and Uruguay show
higher scores than the regional average in the innovation
output pillars.
Chile ranks 51st, down from last year but remaining at the topof the region for the fourth consecutive year. It has rankings in
the top 50 in three pillars: Institutions (39th), Infrastructure (50th),and Market sophistication (49th), and also shows an improved
position in the latter two and Human capital and research (57th).
Chile’s best improvement at the pillar level is in Market
sophistication, with higher rankings in Credit (51st) assisted by
the indicators Microfinance gross loans, and in Trade, competition,and market scale, with improved Applied tariff rate and better
perceived Intensity of local competition. On the Input side,
it shows higher performance in Education (60th) with improvementin the Expenditure on education, Government funding per pupil,and School life expectancy (20th). In the Outputs, Chile advancesin Knowledge creation (56th), with better rankings in Patents
by origin, PCT patent applications by origin, and Utility models.
It does well in Online creativity (58th), thanks to an improved
measurement of Mobile app creation introduced this year. Chile
shows areas of weakness in Business sophistication (53rd),particularly in high-tech imports, and ICT services imports (88th),both part of Knowledge absorption (49th). Outputs weaknesses
for Chile are ICT services exports, Industrial designs by origin,
and Creative goods exports.
Brazil ranks 66th in the GII this year, down two positions from2018. In the Innovation Input Sub-Index, it improves in
Institutions (80th) and Human capital and research (48th). In the
Innovation Output Sub-Index, it improves in Knowledge andtechnology outputs (58th). Brazil ranks in the top 25 in several
indicators in the 5 GII pillars: Human capital and research (48th),32

The Global Innovation Index 2019

Infrastructure (64th), Market sophistication (84th), Businesssophistication (40th), and Knowledge and technology outputs(58th). Most of Brazil’s strengths are in Human capital andresearch, mainly in Expenditure on education (18th), Gross
expenditure on R&D (28th), Global R&D companies (22nd), andthe Quality of universities (25th). Other input strengths for Brazil
are Government’s online service (22nd), E-participation (12th),
Domestic market scale (8th), Intellectual property payments(10th) and High-tech imports (28th). The quality of publications
measured through the H-index (24th) is the only Innovation
output strength for Brazil. Two areas of opportunity are also
noted among Innovation inputs in the General infrastructure(102nd) and Credit (105th) sub-pillars: Gross capital formation(115th) and Microfinance gross loans (74th). Relative weaknesses
in Innovation Outputs include the labor productivity growth(96th) and New businesses (98th).
Peru ranks 69th in the GII 2019, moving up two positions from2018. The economy progresses the most in Human capital andresearch (66th), Infrastructure (65th), and Creative outputs (79th).
Peru gains positions in Human capital and research due in partto available coverage for indicators in Tertiary education (21st)—
mainly Tertiary enrolment (28th), and Graduates in science &engineering (36th). Peru has available data this year for School
life expectancy, also located in this pillar. In Infrastructure, thecountry gains the most positions in Information and communication
technologies (70th) and, in particular, in Government’s online
service (41st), and E-participation (36th). In Market sophistication,
Peru moves up various positions in Trade, competition, andmarket scale (30th) due in part to a higher performance inApplied tariff rate (6th). Also in that pillar, it gains the most positions
in Venture capital deals and the Intensity of local competition.
In Business sophistication, Knowledge workers (27th) remains astrength for Peru, assisted by Females employed with advanced
degrees (38th). On Innovation Outputs, Peru moves up in
Creative outputs with gains in Entertainment & media market(41st) and Printing and other media (10th). Despite these
improvements, Peru is relatively weak in Gross expenditure
on R&D, Global R&D companies, University/industry researchcollaboration, and Joint venture-strategic alliance deals.
Knowledge diffusion is also a relative weakness, both in ICT
services exports and FDI net outflows.

Northern Africa and Western Asia
(19 economies)
Israel, ranking 10th worldwide (up by 1), continues to be the mostinnovative economy in Northern Africa and Western Asia region
since 2009. Cyprus (28th, up by 1) is second in the region, while
the United Arab Emirates (36th, up by 2) achieves the third spot
for the fourth consecutive year.
Five of the 19 economies in the region, including Cyprus (28th)—
the only European Union member state in the region, theUnited Arab Emirates (36th), Georgia (48th), and Turkey (49th)
rank within the top 50 of the GII. All of these countries exhibit
an improvement in their global GII rank. Other countries which
demonstrate an upward movement in the innovation landscape
are Armenia (64th), Morocco (74th), Lebanon (88th), andEgypt (92nd).

Qatar (65th, down by 14) and Oman (80th, down by 11) experiencethe largest decrease in their global ranking relative to othercountries in the region. Saudi Arabia (68th), Tunisia (70th),
Bahrain (78th), Azerbaijan (84th), Jordan (86th), Algeria (113th)and Yemen (129th) see a more modest decline in their GII position.
Georgia (48th) leaps 11 positions—the highest move in theregion. Such improvements are reinforced by Georgia’s
productivity growth rate where it ranks 8th, positive FDI net
inflows (11th), and Ease of starting a business, where it positions
2nd globally. At the pillar level, Georgia improved its positionin six of seven pillars, most remarkably in Market sophistication(15th). In the Investment sub-pillar, Georgia now places 1st
globally (up from 21st last year), and is the 2nd top economy forthe ease of protecting minority investors.
Algeria (113) sees its ranking decrease in all but one pillar thisyear—Human capital and research (74th), where it moves up by
6 spots. At the sub-pillar level, a weakening position is seen in
Innovation linkages (122nd, down from 104th) and Knowledge
absorption (117th, down from 86th). More notably, Algeria moves
down in indicator High-tech net imports, placing 53rd (downfrom 28th last year). Algeria remains strong in its position of
Infrastructure (81st), particularly in indicator Gross capital formation,
where it has a 2nd spot globally, and in Human capital andresearch (74th), where it places as the 9th economy in Graduatesin science and engineering.
Algeria is currently implementing a new innovation strategy
in a move towards a knowledge-based society. The aim is to
put firms at the center of innovation, to foster the innovation ofsmall- and medium-sized enterprises, to aim at better integrationof science and innovation policies, and to achieve better
linkages between scientific research and innovation in firms.
Several legislative changes are on the way in this regard.52

South East Asia, East Asia, and Oceania(15 economies)
This year, as in last year, all economies in the South East Asia,
East Asia, and Oceania region rank in the top 100 of the GII.
All economies in the region, except for Cambodia and Brunei
Darussalam, are also in the top 100 of the Innovation Input andInnovation Output Sub-Indices.
Seven of the 15 economies in the region rank in the top 25 of
the GII: Singapore (8th), the Republic of Korea (11th), Hong Kong
(China) (13th), China (14th), Japan (15th), Australia (22nd) and New
Zealand (25th). The top three economies in the region—Singapore,
the Republic of Korea, and Hong Kong (China)—also rank in
the top 25 of the GII in both the Innovation Input and Output
Sub-Indices.
Malaysia ranks 8th in the region after New Zealand, and 35th
overall in the GII. Viet Nam makes important progress this year,
moving up three positions and reaching the 42nd place overall.
It gains between 4 and 8 positions in three of the GII pillars:
Human capital and research (61st), Market sophistication (29th)
and Knowledge and technology outputs (27th). Thailand gains

one position this year, ranking 43rd overall. Following next are
Mongolia (53rd), the Philippines (54th), Brunei Darussalam (71st),Indonesia (85th) and Cambodia (98th).
As noted in previous editions of the GII, most economies
in the ASEAN region continue to improve their GII rankings
through better performance in innovation, R&D, and economic
development indicators. Figure 1.11 shows the scores forselected input and output indicators for the ASEAN economies
featured in the GII this year. Singapore is the top performer inmost of these indicators. Viet Nam continues to lead in areas
like Expenditure on education and trademarks, as well as on
High-tech imports. Indonesia does the same in Gross capitalformation and Thailand in Creative goods exports, where it
shares the top position with Malaysia. With Myanmar still absent
from the global innovation landscape, Cambodia is still the newest
ASEAN economy to be part of the GII. Cambodia remains 2ndin the group in FDI net inflows and also takes that position in
Joint venture-strategic alliance deals, behind Singapore.
Yet, Cambodia shows the weakest scores in the group on
most of the selected input and output indicators, with its lowest
performance in Patents by origin.
In input indicators, Viet Nam performs well in FDI net inflows but
shows relatively low scores in Tertiary enrolment and Females
employed with advanced degrees. It scores lowest in the groupin Knowledge-intensive employment. In outputs, Viet Namscores well in Scientific and technical publications, Creative
goods and exports, and Patents by origin, and shows its lowest
score for Citable documents H-index. This year Thailand is
2nd in Tertiary enrolment and quality of scientific publications
and 3rd in Trademarks by origin. Malaysia scores well in both
selected inputs and outputs, taking the 2nd position in Females
employed with advanced degrees, Expenditure on education,
High-tech imports, Patents by origin, and Scientific and technicalarticles. It also scores well in Tertiary enrolment, Knowledgeintensive employment, Joint venture and strategic alliancedeals, and the quality of scientific publications. While performingat the top in Gross capital formation and relatively well in Tertiaryenrolment, Indonesia shows relatively low scores for most of
the other selected indicators. Philippines also displays relatively
good scores for over half of the selected indicators, achieving
2nd in Trademarks and 3rd in Females employed with advanced
degrees, High-tech imports, and Creative goods exports.
Lastly, in input indicators, Brunei Darussalam ranks 2nd in both
Gross capital formation and Knowledge-intensive employment,
and 3rd in Expenditure on education. The difference between
the top performers and the other economies for these selectedindicators is slightly larger for input indicators than for output
indicators.
Malaysia ranks 35th, keeping the same position as last year. It
remains among the middle-income economies that are bridging
the innovation divide, thanks to its first rank in indicatorssuch as High-tech net exports and Creative goods exports(Box 2). This year, Malaysia improves its rankings in four of theseven GII pillars: Institutions (40th), Infrastructure (42nd),
Business sophistication (36th), and Creative outputs (44th).
At the indicator level, the most significant improvements are in

Chapter 1

33

FIGURE 1.11

ASEAN in selected innovation indicators, 2019
100

80

60

40

20

0
Patents by origin▲ GII 2019 Score

Scientiﬁc &technical articles● Singapore● Malaysia

Citable documents
H-index● Viet Nam● Thailand

Trademarksby origin● Philippines● Brunei Darussalam

Creative goods
exports● Indonesia● Cambodia

100

80

60

40

20

0
Tertiary
enrolment▲ GII 2019 Score

Females
employedwith advanced
degrees

Expenditure on
education● Singapore● Malaysia

Gross capitalformation● Viet Nam● Thailand

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.

34

The Global Innovation Index 2019

Knowledgeintensive
employment

Joint venturestrategic
alliance deals● Philippines● Brunei Darussalam

High-tech
imports

FDI netinﬂows● Indonesia● Cambodia

quality of universities, where it ranks 17th this year, and GERD
performed by business as well as GERD financed by business,where it takes the 25th and 16th positions respectively. In
several indicators, Malaysia ranks in the top 10; these include
Graduates in science and engineering (8th), University-industry
research collaboration (8th), State of cluster development (8th),and several trade-related variables—such as High-tech imports
and High-tech net exports (respectively 3rd and 1st) and
Creative goods exports (1st). Despite these top ranks, areasof relative weakness include PISA results, GERD financed byabroad, and Trademarks and industrial designs by origin.
Thailand ranks 43rd, gaining one position from last year. Like
last year, the country remains among the innovation achieversof the GII 2019 and among the middle-income economies thatare bridging the innovation divide (Box 2 and Table 1.2). This
year, four of the seven GII pillars see improvements: Institutions(57th), Human capital and research (52nd), Business sophistication (60th), and Knowledge and technology outputs (38th).
Thailand benefits from improvements in important indicatorssuch as R&D expenditures, Research talent, and GERD financedby business, where it ranks 4th, as well as Tertiary enrolment,
Researchers, and Patent families. As for other ASEAN economies,
Thailand is exceptionally strong in trade-related variables,
ranking 8th in High-tech net exports and 1st in Creative goods
exports. If addressed, some weak areas—including PISA results,
Venture capital deals, GERD financed by abroad, and ICT
services imports and exports—could help the economy
progress even faster on its path to catch up.
Philippines ranks 54th this year, gaining several positions fromlast year. While some changes to the GII model explain a smallpart of this leap, newly available metrics give a more thoroughassessment of the country’s innovation performance, which itself
shows some signs of progress. Almost all GII pillars move up,
except for Market sophistication. In the Business sophistication(32nd) pillar, the Philippines improves in almost all the indicators
related to Innovation linkages and gains top ranks in High-tech
imports (5th) and Research talent (6th). In Knowledge andtechnology outputs (31st), the data for indicator High-tech net
exports became available this year and the country ranks 1st.
Four other indicators rank in the top 10: Firms offering formal
training (9th), productivity growth (10th), ICT services exports(8th), and Creative goods exports (8th). Despite these top
ranks, Philippines presents a number of weak areas, which areconcentrated in the innovation input side; these include Easeof starting a business, Ease of getting credit, Expenditure on
education, and Global R&D companies. Scientific and technicalarticles and New businesses are relatively weak on theinnovation output side.

Europe (39 economies)
As in the last two years, in this year’s edition of the GII, 15 of
the top 25 economies are from Europe. Seven of them are in
the top 10 of the GII 2019: Switzerland (1st), Sweden (2nd), theNetherlands (4th), the U.K. (5th), Finland (6th), Denmark (7th),and Germany (9th). Following these innovation leaders, top
25 economies from the region are Ireland (12th), France (16th),
Luxembourg (18th), Norway (19th), Iceland (20th), Austria (21st),

Belgium (23rd), and Estonia (24th). It should be noted that mostof the economies in this region have the fewest missing
values, leading them to display the most accurate GII rankings(Appendix IV). This includes the following economies with
100% data coverage in the Innovation Input Sub-Index, theInnovation Output Sub-Index, or both: Finland, Denmark,Germany, France, Austria, the Czech Republic, Spain, Italy,
Portugal, Hungary, Poland, Romania, and the Russian Federation.
The following 18 economies are among the top 50, with mostof them maintaining relatively stable rankings since 2014: theCzech Republic (26th), Malta (27th), Spain (29th), Italy (30th),
Slovenia (31st), Portugal (32nd), Hungary (33rd), Latvia (34th),
Slovakia (37th), Lithuania (38th), Poland (39th), Bulgaria (40th),
Greece (41st), Croatia (44th), Montenegro (45th), the RussianFederation (46th), Ukraine (47th), and Romania (50th).
The remaining European economies remain among the top
100 economies overall. The region’s rankings continue asfollows: Serbia (57th), the Republic of Moldova (58th), North
Macedonia (59th), Belarus (72nd), Bosnia and Herzegovina(76th), and Albania (83rd).
France remains stable in 16th position in the GII 2019. It ranks
in the top 15 economies in four of the seven GII pillars: Human
capital and research and Infrastructure (11th in both), Market
sophistication (12th), and Knowledge and technology outputs(15th). It shows top ranks in indicators such as Global R&D
companies (7th), Environmental performance (2nd), and Venture
capital deals (5th). This year, France gains most positions in
Knowledge and technology outputs (15th, up by 4) where
High- and medium-high-tech manufactures move to the 13th
spot. At the indicator level, the most remarkable improvements
are found in JV–strategic alliance deals and FDI net inflows,
although the latter is also a weakness. Possibly benefiting froma new turn in French innovation and science policies, important
gains are also visible in other areas related to universities
and research, such as Graduates in science and engineering,Researchers, Quality of universities, and University/industry
research collaboration. Despite these encouraging trends,
France presents relatively weak ranks in Pupil-teacher ratio,
Gross capital formation, Ease of getting credit, GERD financed
by abroad, Utility models by origin, productivity growth, New
businesses, ICT services exports, and Printing and other media.
The Russian Federation maintains the 46th position in the GII
this year. The Russian Federation improves two positions in the
Innovation Inputs Sub-index (41st) and ranks 59th in the Innovation
Outputs Sub-Index, losing three positions from last year. On the
inputs side, it increases its rank in Infrastructure pillar (62nd, upby 1), with higher rankings in Information and communication
technologies (29th, up by 8), and in indicators ICT use (45th),
Government’s online services (25th), and E-participation (23rd).
Although losing one position in Human capital and research(23rd), this year the Russian Federation shows strengths in
Tertiary education (14th) due to its high levels of Tertiary enrolment(17th) and Graduates in science and engineering (10th). Pupil-teacher
ratio is also a strength for the Russian Federation in the sub-pillar
Education. In Market sophistication, its rank in Trade, competition,and domestic market scale are signaled as a relative strength

Chapter 1

35

(11th). In Business sophistication, the Russian Federation’s
performance in Knowledge-intensive employment (18th) andthe Females employed with advanced degrees (7th) are also
strengths. Its most noted improvement in that sub-pillar is in
High-tech imports (39th). On the Innovation Output side, theRussian Federation maintains its position in both the Knowledge
and technology outputs (47th) and Creative outputs (72nd)
sub-pillars. Although losing two positions in Knowledge creation,
the Russian Federation maintains its top performance in Patents
by origin (20th), as well as in Utility models (8th), where it gains
one position since last year. In Creative outputs, rankings
improve in Trademarks (38th) and Industrial designs (69th),
while its rank for Intangible assets remains at 71st. In the qualityof innovation, the Russian Federation retains its 3rd position
among middle-income economies.

Northern America (2 economies)
The Northern America region includes two economies—the U.S.
and Canada—in the top 20 in this year’s GII. Both the U.S. andCanada are high-income economies. The U.S. ranks 3rd overall
this year, up 3 positions from 2018, and is in the top 10 economies
in both the Innovation Input Sub-Index (3th) and the Innovation
Output Sub-Index (6th). Canada moves up both in overall rank
(17, up by 1) as well as Innovation Inputs, where it ranks 9th. In
the Innovation Output Sub-Index, Canada also achieves a higher
position, reaching 22nd. These improvements are due, in part,to a better performance in Joint venture-strategic alliances deals
in inputs and Trademarks by origin in outputs.

Conclusions
The theme for this year’s GII is Creating Healthy Lives—The
Future of Medical Innovation. For the first time, the thematic
results are presented in a self-standing special section.
This chapter presented the main GII 2019 results, distilling main
messages and noting some evolutions that have taken placesince last year (see the Key Findings for more details).
The aim of the GII team is to continuously improve the report
methodology in concert with its application and related analysis—
based on the audit, external feedback, changing data availability,
and shifting policy priorities. In this light, the GII team also
continues to experiment with the use of novel innovation
metrics. Every year, several dozen new innovation metrics areanalyzed and tested for inclusion. These new metrics often
replace currently inadequate data points on topics such as
entrepreneurship, innovation linkages, open innovation, andnew metrics for innovation outcomes at the local and national
level. With each new edition, the GII seeks to improve theunderstanding of the innovation ecosystem with a view tofacilitating evidence-based policymaking.

36

The Global Innovation Index 2019

Over the last years, the GII has also been used by governments
around the world to improve their innovation performance andassociated innovation policies to craft and coordinate. In 2018and 2019, numerous GII workshops in different countries andeconomies—including Algeria, Brazil, Belgium at the European
Commission, China, the Czech Republic, Egypt, Germany,
Hong Kong (China), India, Morocco, Oman, Peru, Thailand,
Viet Nam, among others—took place or will take place, oftenwith the presence of key ministers.
The mission of this work is to apply the insights gleaned fromthe GII. In a first step, statisticians and decision-makers arebrought together to help improve innovation data availability.
This work helps to shape the innovation measurement agenda
at WIPO and at other international and domestic statisticalorganizations. In a second step, the challenge is to use theGII metrics and experiences in other countries to leverage
domestic innovation opportunities while overcoming
country-specific weaknesses. These exchanges generate
feedback that, in turn, improves the GII and assists the journey
towards improved innovation measurement and policy.
Often these activities are an exercise in careful coordinationand orchestration among different public and private innovation
actors, as well as between government entities at local,
regional, and national levels. The GII becomes a tool for such
coordination because the country is united in its common
objective: to foster enhanced domestic innovation performance.
At best, this coordination leads to policy goals and targets thatare regularly revisited and evaluated.
For it is those countries that have persevered in their innovation
agenda, with consistent focus and a set of priorities over time,that have been most successful in achieving the status ofinnovation leader or achiever relative to their level development.

Notes:
1

WIPO Consultant

2

Guellec et al., 2009; Dutta et al. 2017, 2018; WIPO, 2015, 2017; OECD,
2018.

3

IMF, 2019; OECD, 2019; World Bank, 2019.

4

IMF, 2019; Conference Board, 2019; OECD, 2019; World Bank, 2019.

5

UNCTAD, 2019.

6

Van Ark, 2018; OECD, 2018; Conference Board, 2019.

7

Dutta et al., 2018.

8

IMF, 2019; Van Ark, 2018; Conference Board, 2019.

9

Dutta et al., 2017, 2018; OECD, 2018; van Ark, 2018.

10

Cornell et al., 2015, 2017, 2018.

11

Dutta et al., 2017, 2018; OECD, 2018; Pfotenhauer et al., 2018;
Edler & Boon, 2018.

29

One caveat applies: the indicator framework of the GII is adapted
marginally every year. This year-on-year comparison of data
completeness is based on the given data requirements of the year inquestion, and not a fully stable list of indicators over time. For the mostpart, however, the indicators are the same; coverage is comparable.
That caveat aside, Algeria, Brunei Darussalam, Burkina Faso,
Mozambique, the United Arab Emirates, Yemen and Zimbabwe standout as economies where data coverage has improved the most.

In 2003, only 5 companies in middle-income economies made it to the
top private sector R&D spenders (Hernández et al., 2018)30

See: http://www.oecd.org/innovation/blue-sky.htm; https://www.nsf.gov/
statistics/2018/nsb20181/

The number of researchers in countries like Brazil, China, India andTurkey, even if still low relative to the global stock of knowledge, havebeen rapidly increasing. These increases have been equal to 40% in
China in the period 2008-2016, 38% in India between 2010-2015; 62%
in Turkey between 2008-2016, and will be likely to continue rising given
the countries’ increased financial investments in R&D (UNESCO-UIS,2019).

31

Australian Department of Industry, Innovation and Science andAustralian Academy of Technology and Engineering (2019). WIPO
is a contributor to this process. The review singles out a few areas
where innovation data is in need of urgent improvement and inparticular the following:

12

The relationship between innovation (as measured by GII scores) andcountry characteristics such as size and economic structure was initiallyexplored in Box 3 of the GII 2018 (Cornell et al., 2018). We haveupdated this analysis with the most recent data from GII 2019.

13

Lee, 2019.

14

Dutta et al., 2013; Bergquist et al., 2017, 2018.

15

16

17

Innovators across the globe filed 3.17 million patent applications in 2017,
up 5.8% for an eighth straight yearly increase. International patentapplications filed under WIPO’s Patent Cooperation Treaty (PCT) in 2018
grew at an annual growth of 3.9%, a ninth consecutive
year of growth (WIPO, 2018; WIPO, 2019a).

18

Dutta et al., 2018.

19

R&D Magazine, 2018.

20

OECD, 2019.

21

Hernandez et al., 2018. R&D by the Higher Education sector
and government institutions grew by 1.6% and 1.3% respectively(OECD, 2019)22

In particular given that innovation is a long-term investment that
requires action in the short-term, but with impacts that are noticeable
in the medium- to long-term.

23

WIPO, 2017; Chen et al., 2017; WIPO, 2019b.

24

In current U.S. dollars.

25This year the Innovation Efficiency Ratio has been replaced by ananalysis of the connection between Innovation Inputs and Innovation
Outputs, initially introduced in the GII 2018 (see Section “Whicheconomies are best in translating innovation investments into
innovation outputs?”).

26

Further details on the GII framework and the indicators used areprovided in Appendix I. It is important to note that each year theindicators included in the computation of the GII are reviewed andupdated to provide the best and most current assessment of innovation.
Methodological issues—such as missing data, the revision of scaling
factors, and the number of economies covered in the sample—also
impact the year-on-year comparability of the rankings. Details on thechanges done this year to the methodological framework and an analysisof the factors impacting year-on-year comparability are provided in
the Appendix IV.
Most notably, a more stringent criterion for the inclusion of countries
in the GII was adopted in 2016, following the Joint Research Centre(JRC) recommendation of past GII audits (Appendix IV). Economies were
included in the GII 2019 only if 66% of data were available within eachof the two sub-indices and if at least two sub-pillars in each pillar could
be computed.

27

See also Chaminade et al. (2018), and in particular Box 6.1; Lee, 2019.

28

On innovation in informal settings, see also Kraemer-Mbula andWunsch-Vincent, 2016.

•
•
•
•
•
•
•
•

non-R&D-based knowledge and idea creation
capability to implement innovation
new products and processes
start-ups and spinouts
stocks and flows of intangible capital
employee skills
innovation outputs and impacts
entrepreneurship culture

32

Armenia is no longer part of the top 10 lower middle-income
economies this year, as it has been reclassified as an upper
middle-income economy. It ranks 15th among the 34 upper
middle-income economies covered in the GII 2019.

33

Tajikistan was reclassified into the low-income group this year by theWorld Bank, after being part of the lower middle-income group up until
2018. See: https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups

34

Economies that outperform on innovation relative to their level ofdevelopment (by at least 10% relative to their peers at the same levels
of GDP).

35

This year, the U.S. had no available data for four indicators used in
the GII (in GII 2018 it did not have available data for six indicators).
Data availability is crucial in interpreting the GII results in particularacross years.

36

See also https://www.reuters.com/article/us-broadcom-domicile/broadcom-completes-move-to-u-s-from-singapore-idUSKCN1HB34G

37

Note that model changes influence Israel’s improvement in thisindicator. See Appendix IV for more information.

38

Particularly, Hong Kong (China) re-exports high-tech products previously
imported from elsewhere, notably from China, resulting in high levelsof so-called re-exports.

39

For this Box, contributions have also been received from the Innovation
and Technology Bureau, Government of the Hong Kong Special
Administrative Region from Hong Kong (China), from the Ministry of State
and Ministry of the Economy, Luxembourg Government, Grand Duchy of
Luxembourg and from the Intellectual Property Office of Singapore (IPOS),
Government of Singapore.

40

See also https://www.nrf.gov.sg/rie2020/advanced-manufacturing-and-engineering; https://www.nrf.gov.sg/rie2020/
health-and-biomedical-science; https://www.nrf.gov.sg/rie2020/
services-and-digital-economy; and https://www.nrf.gov.sg/rie2020/urban-solutions-and-sustainability.

41

See also https://www.ssg.gov.sg/wsq/Industry-and-Occupational-Skills/
intellectual-property.html

42

See https://digital-luxembourg.public.lu/news/national-ai-vision-prioritizes-people

Chapter 1

37

43

On June 25, 2018, the European Commission decided to establish
the EuroHPC joint headquarters in Luxembourg. It will equip the EU witha pre-exascale and petascale infrastructure (1015 calculation operations
per second) by 2020, and develop the technologies and applications
needed to reach the exascale level (1018 calculation operations per
second) by 2023. Lastly, the University of Luxembourg is home to an
HPC and a €10 million budget was allocated for a new, faster one.
More information is available at: https://meco.gouvernement.lu/

Cornell University, INSEAD, & WIPO. (2015). Global Innovation Index 2015:
Effective Innovation Policies for Development. S. Dutta, B. Lanvin, &S. Wunsch-Vincent (Eds.). Ithaca, Fontainebleau, and Geneva: Cornell,
INSEAD, and WIPO.

44

See https://digital-luxembourg.public.lu/news/luxembourg-gains-access-ai-technology-expertise-new-nvidia-partnership——— . (2018). Global Innovation Index 2018: Energizing the World with
Innovation. S. Dutta, B. Lanvin, & S. Wunsch-Vincent (Eds.). Ithaca,
Fontainebleau, and Geneva: Cornell, INSEAD, and WIPO.

45

See https://infrachain.com

46

More information available at: https://portal.education.lu/digital4education/; and https://www.skillsbridge.lu/

47

See https://space-agency.public.lu/en.html; and https://spaceresources.
public.lu/en.html

48

For additional insights from App Annie on the mobile economy, checkout App Annie’s State of Mobile in 2019 report, available at: https://www.appannie.com/insights/market-data/the-state-of-mobile-2019/49

See http://www.doingbusiness.org/content/dam/doingBusiness/country/i/india/IND.pdf

50

De la Torre and Ize, 2019 have argued that success in international
markets, as measured by rising share of world exports, has been theroute to income convergence in Latin American countries, including
Peru, Chile, Uruguay, Costa Rica, the Dominican Republic,and Panama.
See also: https://www.economist.com/the-americas/2019/05/30/why-latin-americas-economies-are-stagnating

51

52

See http://www.tradeforum.org/news/Latin-Americas-innovation-potential-remains-largely-untapped/
In December 2018, Algeria hosted a two-day GII conference
to build on its innovation strength in the formulation of new
innovation policies.

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Innovation Index 2018: Energizing the World with Innovation. Ithaca,
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Dutta, S., Escalona Reynoso, R., Litner, J. et al. (2016). Winning with Global
Innovation. In S. Dutta, B. Lanvin, & S. Wunsch-Vincent (Eds.), Global
Innovation Index 2016: Winning with Global Innovation. Ithaca, Fontainebleau, and Geneva: Cornell, INSEAD, and WIPO.
——— . (2017). The Global Innovation Index 2017: Innovation Feeding theWorld [Chapter 1]. In S. Dutta, B. Lanvin, & S. Wunsch-Vincent (Eds.),
Global Innovation Index 2017: Innovation Feeding the World. Ithaca,
Fontainebleau, and Geneva: Cornell, INSEAD, and WIPO.
Edler, J., & Boon, W. P. (2018). The next generation of innovation policy:
Directionality and the role of demand-oriented instruments—
Introduction to the special section. Science and Public Policy, 45(4):433–434. DOI: https://doi.org/10.1093/scipol/scy026
Guellec, D., & Wunsch-Vincent, S. (2009). Policy Responses to the Economic
Crisis: Investing in Innovation for Long-Term Growth. Paris: OECD
Publishing. Retrieved from https://www.oecd.org/sti/42983414.pdf.
Griffith, B. (2011). Middle-Income Trap. In R. Nallari, S. Yusuf., B. Griffith, andR. Bhattacharya (Eds.), Frontiers in Development Policy. A Premier on
Emerging Issues. Washington, DC: World Bank.
Hernández, H., Grassano, N., Tübke, A. et al. (2018). The 2018 EU
Industrial R&D Investment Scoreboard; EUR 29450 EN; Publications
Office of the European Union, Luxembourg, 2018, ISBN 978-92-7997293-5, doi:10.2760/131813, JRC113807. Retrieved from http://iri.jrc.
ec.europa.eu/scoreboard18.html
IMF (International Monetary Fund). (2019, April). World Economic Outlook:
Global Prospects and Policies. World Economic Outlook (WEO): Growth
Slowdown, Precarious Recovery. Washington, DC: IMF.

Chaminade, C., Lundvall, B-A., & Haneef, S. (2018). National Innovation
Systems and Economic Development. Advanced Introduction to
National Innovation Systems. Cheltenham: Edward Elgar.

Kraemer-Mbula, E., & Wunsch-Vincent, S. (2016). The Informal Economy in
Developing Nations: Hidden Engine of Innovation? Cambridge:
Cambridge University Press. DOI:10.1017/CBO9781316662076.

Chen, W., Gouma, R., Los, B. et al. (2017). Measuring the income to intangibles
in goods production: A global value chain approach. WIPO Economic
Research Working Paper No. 36. Retrieved from https://www.wipo.int/
edocs/pubdocs/en/wipo_pub_econstat_wp_36.pdf.

Lee, K. (2013). Schumpeterian Analysis of Economic Catch-up: Knowledge,
Path-Creation, and the Middle-Income Trap. New York: Cambridge
University Press.

Conference Board. (2019, April). The Conference Board Productivity
Brief 2019.

——— . (2019). The Art of Economic Catch-Up: Barriers, Detours and Leapfrogging in Innovation Systems. Cambridge: Cambridge University Press.
DOI:10.1017/9781108588232
National Science Board. (2018). Science and Engineering Indicators 2018.

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NSB-2018-1. Alexandria, VA: National Science Foundation. Retrieved
from https://www.nsf.gov/statistics/indicators/.https://www.nsf.gov/statistics/2018/nsb20181/
OECD (Organisation for Economic Co-operation and Development). (2018).
OECD Science, Technology and Innovation Outlook 2018: Adapting
to Technological and Societal Disruption. OECD Publishing, Paris. DOI:
https://doi.org/10.1787/sti_in_outlook-2018-en——— . (2019). Interim Economic Outlook: Global Growth Weakening as Some
Risks Materialise. OECD Publishing, Paris. Retrieved from https://www.
oecd.org/economy/outlook/global-growth-weakening-as-some-risks-materialise-OECD-interim-economic-outlook-handout-march-2019.pdf
Pfotenhauer, S. M., Juhl, J., & Aarden, E. (2018). Challenging the ‘deficit model’of innovation: Framing policy issues under the innovation imperative.
Research Policy, 48(4): 895-904. DOI: https://doi.org/10.1016/j.
respol.2018.10.015
R&D Magazine. (2018). 2018 Global R&D Funding Forecast, Winter 2018.
Retrieved from: https://digital.rdmag.com/researchanddevelopment/2018_global_r_d_funding_forecast?pg=1#pg1
United Nations Conference on Trade and Development (UNCTAD). (2019).
UNCTAD’s World Investment Report 2019, Geneva: UNCTAD.
UNESCO (United Nations Educational, Scientific and Cultural Organization).
(2015). UNESCO Science Report: Towards 2030. Paris. UNESCO.
Retrieved from https://en.unesco.org/unesco_science_report
UNESCO-UIS (UNESCO Institute for Statistics). (2019, April). UNESCO-UIS
Science & Technology Data Center.
Van Ark, B. (2018, May 8). We may be missing the productivity revival in the
global economy. Stronger demand and more investment bode well
for a new phase of growth. Financial Times. Retrieved fromhttps://www.ft.com/content/864b7dba-489b-11e8-8c77-ff51caedcde6
WIPO (World Intellectual Property Organization). (2011). World Intellectual
Property Report: The Changing Face of Innovation. Geneva: WIPO.
——— . (2015). World Intellectual Property Report: Breakthrough Innovationand Economic Growth. Geneva: WIPO.
——— . (2017). World Intellectual Property Report: Intangible Assets and Global
Value Chains. Geneva: WIPO.
——— . (2018). World Intellectual Property Indicators 2018. Geneva: WIPO.
Retrieved from https://www.wipo.int/publications/en/details.jsp?id=4369——— . (2019a). Patent Cooperation Treaty Yearly Review–2019. Geneva:
WIPO. Retrieved from https://www.wipo.int/publications/en/details.
jsp?id=4424——— . (2019b). [Unpublished]. World Intellectual Property Report.
Geneva: WIPO.
World Bank. (2019). Global Outlook: Darkening Skies. Global Economic
Prospects: Darkening Skies. Washington, DC: World Bank.

Chapter 1

39

40

The Global Innovation Index 2019

T H E ME SE C T I O N

CREATING HEALTHY LIVES—
THE FUTURE OF MEDICALINNOVATION
Soumitra Dutta and Rafael Escalona Reynoso, SC Johnson College of Business, Cornell University
Sacha Wunsch-Vincent, Lorena Rivera León, and Cashelle Hardman, World Intellectual Property
Organization (WIPO)

The 2019 edition of the Global Innovation Index (GII) focuseson the theme Creating Healthy Lives—The Future of Medical
Innovation. In the years to come, medical innovations suchas artificial intelligence (AI), genomics, and mobile healthapplications will transform the delivery of healthcare in bothdeveloped and emerging nations.
The key questions addressed in this edition of the GII include:• What is the potential impact of medical innovation onsociety and economic growth, and what obstacles must
be overcome to reach that potential?
• How is the global landscape for research and development(R&D) and medical innovation changing?
• What health challenges do future innovations need to address
and what types of breakthroughs are on the horizon?
• What are the main opportunities and obstacles to future
medical innovation and what role might new policies play?
Five key messages emerge:
1. High quality and affordable healthcare for all is important forsustainable economic growth and the overall quality of lifeof citizens. While significant progress has been achieved
across many dimensions over the last decades, significant
gaps in access to quality healthcare for large parts of the
global population remain.

2. Medical innovations are critical for closing the gaps in global
healthcare provision. These innovations are happening
across multiple dimensions, including core sciences, drug
development, care delivery, and organizational and businessmodels. In particular, medical technology related innovations
are blossoming, with medical technology patents more
numerous and growing at a faster path than pharmaceutical patents for the last decade. However, some challenges
need to be overcome—notably, a decline in pharmaceutical
R&D productivity and a prolonged process for deploying
health innovations due to complex health ecosystems.
3. The convergence of digital and biological technologies
is disrupting healthcare and increasing the importanceof data integration and management across the healthcare
ecosystem. New digital health strategies need to focus
on creating data infrastructure and processes for efficientand safe data collection, management, and sharing.
4. Emerging markets have a unique opportunity to leverage
medical innovations and invest in new healthcare delivery
models to close the healthcare gap with more developed
markets. Caution should be taken to ensure that new
health innovations, and their related costs, do not exacerbate
the health gap between the rich and poor.
5. To maximize the potential for future health innovation,
it is important to encourage collaboration across key actors,
increase funding from public and private sources, establish
and maintain a skilled health workforce, and carefully
evaluate the costs and benefits of medical innovations.

The section has benefited from comments by Hans Georg Bartels, Kyle Bergquist, Ridha Bouabid, Amy Dietterich, Carsten Fink, Mosahid Khan, Charles Randolph,
and Ola Zahran, all at WIPO, Bruno Lanvin, INSEAD, and Bertalan Mesko, Author, The Medical Futurist. It draws on all outside chapter contributions that follow.

Theme Section

41

The impact of medical innovation—a high-stakes policy matter
Over the last century, improvements in healthcare have led to adoubling of life expectancy in both high-income and developing
economies.1 This increase in life expectancy has helped
expand the global workforce, drive economic growth, andimprove the quality of life for many.2
Innovations—on both technological and non-technologicalfronts—have contributed to better health and economic
development. Improved hygiene, enhanced public healthplanning, the persistent pursuit of R&D in the medical field,
and the increasing role of information technologies have been
key. In particular, the decades after World War II are often
considered the “golden age’’ of medical innovation. Manyof the tools of modern medicine were developed between
1940 and 1980, including antibiotics, the polio vaccine, heartprocedures, chemotherapy, radiation, and medical devices
such as joint replacements.3
The benefits of improved health via innovation are becoming
accessible to a growing number of people within and acrossdeveloped and developing countries. As societies get richer,wealth buys better health and a higher quality of life, withmore people in low- and middle-income economies having
access to functioning health systems.4
Indeed, over the last decade, global spending on health has
been growing faster than gross domestic product (GDP)—atroughly double the rate.5 Health spending has been growing
even more rapidly in low- and middle-income countries—close
to 6% on average—than in high-income countries, which
average 4%. In 2018, global healthcare expenditures amounted
to US$7.6 trillion, accounting for around 10% of global GDP(Figure T-1.1).6 By 2020, estimated global health expenditures
will reach close to US$9 trillion.7

While significant progress in global healthcare has been madeover the last couple of decades, there are major challenges
that remain. A large proportion of the world’s population lacks
access to quality healthcare. Increasing health costs arealso an issue, in particular, out-of-pocket payments by privatehouseholds without complete medical insurance.
Medical innovation is expected to contribute to increased
cost-effectiveness in the healthcare sector in the years tocome. It is also key to the realization of the health-related
United Nations Sustainable Development Goals (Box T-1.1).8
Now the logical question for economists and policymakers is
how health innovations will continue to drive well-being andeconomic growth in the future.
At a glance, upcoming health innovations and their possible
contributions are impressive. Policy and news reports abundantly
cover much-anticipated innovations in health and medicine
and the resulting improvements that patients will see.
If history is any guide, one has to avoid unwarranted optimism
as to how fast health innovation arises and how efficiently
it is deployed. Productivity in healthcare R&D has slowed insome respects.12 Also, traditionally, innovation in health has
diffused more slowly relative to other sectors.13 This is due tothe complex health innovation ecosystem and the seriousnessof the outcomes that healthcare addresses: the life andwell-being of people.14
While there is significant potential for new medical innovations,several obstacles must be overcome. Though the demandfor innovation is high, there are concerns that the golden yearsof medical innovation may be behind us, as measured bydecreases in major medical advances by year,15 drug approvals,16
and research productivity.17

BOX T-1.1

Sustainable development goals—innovation, health,and the United Nations
The United Nations (UN) Sustainable Development Goals (SDGs)
are a collection of 17 global goals that seek to make significant
progress on global matters, including health, by 2030.
Specifically, SDG 3 sets global health targets in several areas.
Importantly, it specifies the goal of universal health coverage—
including access to essential healthcare services—and setstargets to support R&D for vaccines for communicable diseases,
for example.9
To reach the 2030 goals, the UN General Assembly adopted
health-related political declarations.10 The SDGs and theensuing declarations recognize the critical role of innovation
and R&D. As a result, SDG Indicators were set up to monitor
innovation and R&D progress—for example, SDG Indicators

42

The Global Innovation Index 2019

9.5.1-2 measure gross domestic R&D expenditure on health(health GERD) as a percentage of gross domestic product,
and the number of health researchers is measured in full-time
equivalents (FTEs) per million inhabitants.11
In September 2019, the United Nations High-level Political
Forum (HLPF) on Sustainable Development will convene toreview the progress made on the first four-year cycle of the2030 Agenda. The GII 2019—with up-to-date metrics on theunderlying innovation systems—aims to be a useful guide,
helping policymakers and other stakeholders engage in crafting
coherent policies and implementation strategies to harness
innovation for the achievement of SDG 3.

FIGURE T-1.1

Evolution of healthcare expenditures over time, in US$,and as a share of GDP
2.0
1.9
1.8
1.7
1.6
1.5
1.4
1.3
1.2
1.1
1.0
0.9
0.8
2000

2004

▲ Growth of health expenditures
as a % per capita⊲ Year2008——

Low income
Lower-middle income

2012

—
—

2016

Upper-middle income
High income

6.0
5.5
5.0
4.5
4.0
3.5
3.0
2.5
2.0
1.5
1.0
0.5
0.0
2000

2004

▲ Government spending on healthas a % of GDP⊲ Year2008——

Low income
Lower-middle income

2012

—
—

2016

Upper-middle income
High income

Source: Authors based on Xu et al., 2018; WHO data.

Theme Section

43

Pharmaceutical research is limited by rapidly increasing costs
and a decline in major drug approvals over the past decade.18
Cost increases are caused by multiple factors, including
extensive research requirements, lengthier approval processes,
longer development times, higher marketing expenditures,
and a concentration of R&D investments in areas where therisk of failure is high.19 To develop a drug for Alzheimer’s, theprocess involves a commitment of nearly 10 years from research
to use on patients—plus over 4 years of preclinical discovery
and testing (Chapter 6–Eli Lilly and Company).20 Diminishingreturns on drug innovation may also be reducing incentives toinvest in breakthroughs.
While later sections in this chapter point to a possible, recent
turnaround in pharma R&D productivity, progress is generally
slow with respect to some tenacious health challenges (Chapter
2–Bhaven Sampat). Many acute and chronic conditions have
few treatment options beyond marginally mitigating diseaseprogression and/or reducing discomfort resulting from symptoms.
For some illnesses, such as cancer, depression, or Alzheimer’s(Chapter 6), innovation has not yet produced breakthroughcures; failure rates and clinical trial setbacks are high.
Scientific advances in life sciences or biotech have often
not been matched by a corresponding increase in medical
innovation.21 Efforts by pharmaceutical firms to overcome thepipeline challenge by buying biotechnology firms have notalways produced the desired effect.22 Gene development
technologies have not created the breakthroughs many might
have expected.23 Moreover, new health-related research
fields such as neuroscience are still in their infancy.
From the innovation diffusion perspective, the speed of adoptionof existing medical innovations has been slow too, primarily
due to complex interactions between actors in the healthecosystem.24 Moving medical innovations “from bench to
bedside” is a long process, sometimes extending over several
decades. Multiple parties may be involved, such as private
and public research actors, including medical technology,
pharmaceutical firms, and universities; providers of healthcare,such as physicians and hospitals; patients; and payers, suchas medical insurance companies.25 Finally, the whole process
is constrained by regulatory contexts and incentives, set
by government or independent regulators to ensure safety
and access.26
The fragmentation of healthcare across different actors—suchas payers, insurers, providers, and manufacturers—leads
to challenges (Chapter 8–GE Healthcare). The underlying
innovation incentives for technology or new process adoption
are regularly misaligned. Technologies to decrease the roleof particular medical activities—such as minimally invasive
surgery—might find lukewarm reception from a particular
medical profession, slowing its deployment.27 In addition,
patients and insurers frequently have differing views as tothe acceptable cost of new treatments.28

44

The Global Innovation Index 2019

Slow feedback and knowledge flow between the actors canslow collaboration—often due to a lack of communication
channels or lack of shared standards on how to exchange dataand information across silos. These inefficiencies can lead towasted time. They can also negatively affect patient outcomes(Chapter 8).29
It is noteworthy that the slow diffusion of medical innovations
is more than a developed versus developing country issue.
Many innovations fail to achieve widespread and sustainable
use, even in economies with advanced health systems.
This is true although many medical innovations are about
applying existing technologies from non-medical fields in new
ways in the health sector.30
Medical innovations are only slowly gravitating to developing
countries; large segments of the population in the developingworld remain underserved in terms of access to medical
technologies and basic healthcare.31 A broader diffusion ofexisting technologies and practices would pay large dividends(Chapter 2). The development of drugs, vaccines, medical
devices, and overall healthcare operations designed for
low-resource settings is key (Chapter 11–PATH).32 Currently,
market forces still result in pharmaceutical R&D targeting
diseases that are typical of affluent societies, to the detrimentof developing economies.33
Furthermore, while the focus is often on access to medicines,
inadequate attention is given to contributions that would ensure
the functioning of health systems in developing countries.
Investments in innovations aimed at the delivery of healthcare
are needed (Chapter 12–Ministry of Health, Egypt and Chapter
13–Narayana Health, India).34
Finally, too much effort is still spent on fixing health problems
rather than preventing them in the first place (Chapter 9–iamYiam).35
Technological and non-technological medical innovations go
a long way to remedy this situation and improve prevention.

Medical innovations are changing
the landscape of healthIn the years to come, new technologies are likely to enrich theprovision of healthcare at a rapid pace; they will help facesome of the new medical challenges outlined in the section
above while producing efficiencies and disrupting current waysof delivering healthcare.
This is not only about new technology. Innovation in healthsystem organization—for example, how doctors are consulted,
how monitoring is done, how diagnoses are established andshared, and how prevention takes place—is also on the way.36
These evolutions might help fix innovation obstacles in thehealth system, such as overcoming knowledge silos—created
when specific medical actors keep data and information
about patients to themselves—or allowing for a better assessmentof the true impact of particular medical technologies or
pharmaceutical inventions.

Beyond increasing innovation at the corporate- and country-level,
the geographical landscape of global medical innovation ischanging too.
Historically, the markets for health innovation—as well as theinnovation pipelines themselves—have been concentrated inhigh-income economies, mostly in Europe and North America.37
Today, the most R&D-intensive health industry firms are still inEurope and the United States of America (U.S.): Switzerland,
the United Kingdom (U.K.), and the U.S. are the top holdersof pharmaceutical patents; the Netherlands and the U.S. leadin medical technology patents; and Switzerland and the U.K.
lead in biotech patents.
However, the geography of medical innovation is changing toprogressively include emerging economies. The demandfor improved health services is growing in these regions, driven
by a rising middle class and robust economic growth. This is
not only true for large emerging economies such as China
and India but also Mexico, Viet Nam, Indonesia, South Africa,
Nigeria, and many others.38 The innovation capacity in emerging
markets is also growing, with increasing R&D, patents, andinvestment in these countries (Figures T-1.2 and T-1.3, and Table
T-1.1). Accordingly, pharmaceutical companies based in emerging
economies have shown strong growth in recent years.39
A resurgence of health R&D
After the financial crisis in 2009 and a significant slowdown
across sectors, worldwide pharmaceutical R&D plateauedat around US$135 billion for more than five years, including
in 2013. Investment in health began a resurgence after 2013,reaching US$177 billion worldwide in 2019.40
Overall, the healthcare sector is one of the most importantinvestors in innovation, second to the information technology(IT) sector. Pharmaceutical, biotech, and medical device firms
are among the top global corporate investors in R&D, spending
over US$100 billion annually; this represents close to 20%
of global annual R&D expenditures by the top 2,500 R&D firms
across all sectors.41
Health R&D is also a significant component of total private andpublic R&D expenditures, ranging from 10 to 12% of averageannual R&D expenditures in high- and middle-income economies
to about 14% in low-income economies.42 In countries suchas the U.K. and the U.S., governments place an even greater
focus on R&D, allocating 20 to 25% of all government R&D
expenditures on health.43
Medical technology patents growing fasterthan pharmaceutical patents
Patents in pharmaceuticals, biotechnology, and medical
technology have been growing strongly year-over-year forthe last decade (Figure T-1.2). Medical technology patents
grew the fastest at close to 6% per year. This puts medical
technologies among the top five fastest-growing technology
fields since 2016, with the other four being IT-related fields.44
Consequently, medical technology patents are now as
numerous—about 100,000 patents worldwide—as pharmaceuticalpatents, with biotech at half that volume. Medical technology-related
PCT filings are also nearly double the volume of pharmaceuticalpatents today, reflecting the increased importance of innovation
in medical technology relative to pharmaceutical (Figure T-1.3).
Finally, as evidenced in the 2019 Special Section on Identifying
and Ranking the World’s Largest Science and Technology
Clusters, medical technology is now the most frequent fieldof patenting in these top clusters, overtaking pharmaceuticalpatents for the first time.45
Reflecting the increased spread of innovative capacity, Mexicoand India are increasingly specialized in pharmaceuticalpatents relative to other patents—with India home to someof the top 10 pharmaceutical firms worldwide, such as Sun
Pharmaceutical, Lupin, and Dr. Reddy’s.46 In absolute numbersof patents, China is also now the most important pharmaceuticalpatent origin (Table T-1.1).
As regards patent application filings under the Patent
Cooperation Treaty (PCT) at WIPO, medical technologies
accounted for close to 7% of all applications in 2017 and were
the fourth largest technology filing area in 2018, with IT-related
fields topping this ranking.47
However, the above figures likely underestimate actual medical
innovation activity. Health-related R&D and patenting are
taking place in fields and firms as diverse as electrical andmechanical engineering, instruments—in particular, optics
and measurement, chemistry, and the IT sector. Patents in thefield of artificial intelligence are also forecast to be significant
to future health systems.48
Furthermore, a number of the process and organizationalinnovations that are bound to have a positive influence in thehealth sector are not captured by R&D and patenting figuresin the traditional health sector, as reported in the above data.

Is a revival of medical research productivity on the horizon?
While pharmaceutical research productivity might have beenslower in past decades, more recently, new health-related
patenting and drugs on the market are signaling a possible
reversal of the productivity crisis outlined earlier in this chapter.49
Since 2015, the number of drugs in Phase I and II clinical trials
has grown substantially.50 The launch of new drugs, such asnovel active substances, has increased in the last decade andis expected to continue growing. The drug approval rates at
the U.S. Food and Drug Administration (FDA) and the European
Medicines Agency (EMA) increased in 2017 and 2018; they are
considerably higher today than in prior years.51 The pending
lineup of immunotherapies and drugs with the potential to
become blockbusters—for diabetes, hepatitis C, and cancer—istrending upward.52
Does this mean the end of the medical research productivity
decline? This is hard to answer with certainty. The numberof drugs in Phase III clinical trials has yet to reach the high levels
seen during the golden times of pharmaceutical innovation;a large percentage of drugs still fail to make the transition from

Theme Section

45

FIGURE T-1.2

Patent publications by technology, 1980-2017
350,000

300,000

250,000

200,000

150,000

100,000

50,000

0
1980

1985

▲ Patent publications⊲ Year

Source: WIPO Statistics Database, March 2019.

46

The Global Innovation Index 2019

1990

—
—
—
—
—
—

1995

2000

2005

World
High income
Upper-middle income (with China)
Upper-middle income (without China)
Lower-middle income
Low income

2010

■
■
■

2015

Biotechnology
Pharmaceuticals
Medical technology

FIGURE T-1.3

Patent Cooperation Treaty (PCT) ﬁlings by technology, 2000-2018
35,00030,00025,00020,000PHARMACEUTICALS

15,000

BIOTECHNOLOGY
10,0005,000

MEDICAL TECHNOLOGY

0
2000

2002

2004

2006

2008

2010

2012

2014

2016

2018

▲ Patent publications⊲ Year

Source: WIPO Statistics Database, March 2019.

Theme Section

47

TABLE T-1.1

Overview of the top origins in health patent publications, 2010-2017
Top 10 in patent publications, 2010-2017
Biotechnology
EconomyPharmaceuticals
Patent Publications

EconomyMedical technology
Patent Publications

EconomyPatent Publications

United States of America

126,581China

214,992

United States of America

284,223

China

92,107

United States of America

204,057

Japan

116,745

Japan

33,818

Japan

45,850China

115,805

Germany

24,094Germany

38,279Germany

62,050

Republic of Korea

21,045

Switzerland

33,694

Republic of Korea

43,533

Switzerland

15,750

Republic of Korea

28,036

Netherlands

21,984

France15,292

France25,814

Switzerland

21,909

United Kingdom

12,697

United Kingdom

21,697

France20,643

Netherlands

9,237

Russian Federation

11,566

United Kingdom

19,643

Denmark

7,942

Italy

10,286

Russian Federation

16,171

Source: WIPO Statistics Database, March 2019.
Note: Figures show the sum of patent publications from 2010 to 2017 for all economies.

The fastest growing middle-income economies in health patent publications, 2010-2017

EconomySum

Average

Compound growth

Biotechnology
China

92,107

11,51419.0%

Mexico

509

64

8.8%

India

2,341

293

1.4%

China

214,992

26,874

17.6%

Turkey

2,164

271

11.7%

Mexico

1,378

173

10.8%

Ukraine

1,032

129

3.3%

Russian Federation

11,566

1,446

0.9%

China

115,805

14,476

29.7%

India

1,934

242

9.8%

Mexico

863

108

7.9%

Turkey

1,299

163

5.8%

Russian Federation

16,171

2,022

0.9%

Pharmaceuticals

Medical technology

Source: WIPO Statistics Database, March 2019.
Note: Economies considered for biotechnology show > 50 average patent publications from 2010 to 2017, and those considered for medical technology andpharmaceuticals show > 100 average patent publications over the period.

48

The Global Innovation Index 2019

Phase II to Phase III. New pharmaceutical cures are harder
to come by (Chapter 2).53 While research expenditures are
increasing, the return on drug-related R&D investments continues
to be low.54
However, innovation is burgeoning in other increasingly
health-related sectors, such as medical technologies or IT andsoftware applications.55 Over the last five years, regulatory
agencies such as the FDA have announced record rates ofnovel medical device approvals for mechanical heart valves,
digital health technologies, and 3D printing devices.56
Process and organizational innovations in healthcare delivery
are also taking place due to increased automation andefficiency. These innovations are not necessarily captured
by traditional R&D and patenting figures.
Finally, some important but less high-tech—and less measurable—
medical innovation is taking place in low- and middle-income
countries. Countries in Africa, Central and Eastern Asia,and Latin America have witnessed the novel use of existing
technologies—“frugal” or “adapted” medical innovations—with
considerable impact in low-resource contexts. For example,
clean “delivery kits” contain essential items that allow doctors
in low-resource contexts to deliver babies more safely, while
many other examples arise in countries such as India.57

Upcoming breakthroughs in medical
and health innovation
Novel ways to improve healthcare, to diagnose health problems,
and to cure diseases are imminent (Chapter 4–National
Institutes of Health, U.S. and Chapter 7–Dassault Systèmes).58
Health-related technologies and organizational innovations
have the potential to disrupt existing business models, to lower
healthcare costs, and to improve overall healthcare efficiency(Chapter 3–ZS Associates and Chapter 5–Tencent, China).59
Many of these medical innovations are relevant to developing
countries, whether they are technological, such as 3D printing;new tools to diagnose infections, such as malaria, in Brazil(Chapter 14–CNI and SEBRAE);60 organizational, such as the
improved screening for non-communicable diseases in Egypt(Chapter 12); or remote telemedicine applications in Rwanda(Chapter 15–Ministry of Health, Rwanda).61 While medical
breakthroughs and their diffusion are tough to predict, thesections below describe several possible scientific andtechnological breakthroughs, developments in process, andorganizational innovations.62
Identifying promising fields
The fields of genetics and stem cell research, nanotechnology,
biologics, and brain research are promising domains forscientific breakthroughs. Breakthroughs may also come fromprevention techniques and cures through new vaccines
and immunotherapy, new pain management techniques,
and cures for mental diseases. A large number of innovations
are pending in the areas of medical devices, medical imaging
and diagnostics, precision and personalized medicine, andregenerative medicine.

Organizational and process innovations are also improving
healthcare delivery through novel approaches to researchand clinical trials and new ways of delivering healthcare. These
medical innovations could have a significant impact byhelping overcome fragmentation of the healthcare ecosystem
across different sectors—payers, insurers, providers, andmanufacturers—and improving healthcare efficiency (Figure T-1.4).
IT and big data are often at the source of these innovations.
New technologies, such as virtual modeling and AI techniques,enable new ways of conducting medical research (Chapter 5),
facilitating breakthroughs, and increasing invention efficiency.63
Many IT-enabled innovations have the potential to affectthe delivery of healthcare and mitigate rising health costs(Chapter 14). Supported by the appropriate technology, healthcan be monitored in real time, conditions tracked remotely, data
analyzed and shared, new modes of diagnosis applied, andtreatments personalized. Individuals can also have access totheir health data for the first time in history.64
These technologies have also begun impacting mobile healthpossibilities, some of which are critical for prevention andhealth monitoring. The technologies are starting to supporta shift from a “react and revive” focus on ill-health to a “predictand prevent” model of wellness (Chapter 3, Chapter 7, Chapter
9, and Chapter 17–Thailand).65 Examples include telemedicine
applications, remote monitoring, portable diagnostics, andthe delivery of medicines via drones. The surveillance of publichealth threats and the availability of data to drive policy andplanning are key to optimizing health services in low-resource
contexts (Chapter 12, Chapter 13, and Chapter 15).
The novel and better use of health data plays an important rolein this context. Through big data analytics, machine learning,
and AI, patient harm—and unintended consequences—may be
predicted before they occur, and interventions can be provided
to caregivers. Integrated data can help overcome silos andsupport medical professionals and care providers with insightsthat enable more predictive and efficient care (Chapter 5 andChapter 8).66
The data-driven shifts in health policies and strategies could
be a core driver in reordering the relationships among—andprocesses between—health services providers, medical
equipment manufacturers, patients, governments, public research,social security, and financial/insurance companies. In this setup,
the patient is at the center of better feedback flows.
As the same time, as more innovation is geared to enriching
the data intensity of medical equipment and processes, it
Is to be expected that the relative power of those who havethe ability to collect, combine, and analyze large data sets will
increase relative to that of traditional players in the healthand medical arena. This may have important consequences,such as increased inequalities between the haves and thehave nots of relevant technologies or a rising reliance on
algorithms to make medical decisions, which may generate
distrust vis-à-vis the medical profession.

Theme Section

49

FIGURE T-1.4

Promising ﬁelds for medical innovation and technologies
NEW SCIENTIFIC BREAKTHROUGHS,TREATMENTS, AND CURESNew generation of vaccines
and immunotherapy

Genetics and stem cell research— Single-cell analysis— Gene and stem cell therapies— Genetic engineering and editing
including CRISPR technology— HIV and universal ﬂu vaccine— Cancer vaccine— Immunotherapy— New vaccine delivery methods

Nanotechnology— Swallowable small devices

Pain management

Biologics— Development and manufactureof complex biologics— Eﬀective, non-addictive medicines forpain management

Brain research, neurology, andneurosurgery

Mental health treatments— Pre-symptomatic diagnosis and treatmentof Alzheimer’s disease and othercognitive declines— Characterization of the brain’s major circuits— New brain imagery for mental disorders— Migraine treatment

NEW MEDICAL TECHNOLOGIESPrecision and personalized
medicine

Medical devices— 3D printing— Cardiac devices— Implants and bionics— Computer-assisted surgery— Surgical robots— Personalized medicine

Medical imaging and diagnostics

Regenerative medicine— Optical high-deﬁnition imaging and virtualanatomic models— Biosensors and markers— 4D human charting and virtual reality— Screening for diseases— Tissue engineering— Eﬀective bioartiﬁcial pancreas

ORGANIZATIONAL AND PROCESSINNOVATIONSNovel approaches in healthcare
research

New ways of delivering
healthcare— Software-based modeling to speed
up research— Artiﬁcial intelligence techniques tospeed up research and clinical trials— Telemedicine applications— Drone delivery of medications— Remote monitoring and portablediagnostics— Improved data sharing

Sources: GII 2019 chapters, in particular Collins, 2010; Collins, 2019. Also, Kraft, 2019; Nature, 2018; Nature, 2019; Frost & Sullivan, 2018; Frost & Sullivan, 2019;
European Commission, 2007; Medical Futurist, 2017; Mesko, 2018.

50

The Global Innovation Index 2019

Opportunities and policy imperatives
enabling healthy futures
Business and policy imperatives are key to creating a strong
foundation for medical innovation systems—ranging fromstable and predictable funding to technology transfer, skills,
and regulation.
Ensuring sufficient medical innovation funding
The social returns of medical innovation expenditures far exceed
the private returns of R&D.67 For this reason, government R&D
spending is still the primary source of scientific health researchworldwide. Health-related R&D in public research institutes
is of paramount importance. In fact, many state-of-the-art
technologies behind healthcare innovations are initiallydeveloped as basic research projects carried out or financedby the public sector (Chapter 10–CERN, European Organization
for Nuclear Research).68
It is thus vital to prioritize public funding—in particular, basic
R&D. This holds true in middle- and low-income economies
where health R&D expenditures are still relatively low, but also
in high-income economies that have faced declining public
R&D budgets—notably in health-related public research
institutions—in recent years.69 Discontinuities in public fundingfor health R&D can lead to brain drain and training gaps for
qualified staff, not to mention the obsolescence of equipment(Chapter 14).
Government investment can help set up large funds to advanceparticular fields of research and to create health research
centers or clusters, such as the Thai Center of Excellence
for Life Sciences (Chapter 17), the Brazilian SENAI Innovation
Institutes (Chapter 14), or the Iranian dedicated science andtechnology parks (Chapter 16–Iran).70 More can be done topromote international research collaborations, which play a vitalrole as basic research ideas are translated into useful medical
applications and solutions in the marketplace.71
There is also a need for innovative funding approaches—
especially in the earliest and riskiest phases of drug discovery
research (Chapter 6).72 Often companies have difficulty
funding early stage or strongly disruptive technology. The
ability of academic spin-offs to become sustainable venturesis uneven; they remain highly dependent upon venture
capitalists, who tend to foster short-term financial growth
and whose understanding of healthcare challenges andneeds remains incomplete.73
Funding for product R&D, outcomes research, and market
analyses of uses for health technologies in low-resource
settings remain insufficient (Chapter 11).74 This is not a newconsideration and positive developments are on the way.
Entities such as the Bill & Melinda Gates Foundation and Gavi—an organization bringing together public and private actors
to deliver vaccines to children in low-income countries—
contribute significantly to the financing and deployment of
medical innovation.75

Still, new ideas and incentives are required to address certain
health problems, particularly those affecting the least
developed countries. R&D for such health innovations should
be encouraged, along with special incentives and funding
programs to encourage investment in health and medical
research (Chapter 2).76
Finding solutions to these challenges requires multi-stakeholder
consultation and coordination. The WIPO Re:Search public-private
consortium, for example, shares valuable intellectual property
and expertise with the health research community to promote
the development of new drugs, vaccines, and diagnostics forneglected tropical diseases, malaria, and tuberculosis.77
Building functional medical innovation systems: from“bench to bedside”
Once significant health R&D is financed and carried out,
effective medical innovation—and its diffusion—depend on
linkages between public and private actors to translate
basic research into medical applications. This is often a“giant leap” (Chapter 10).78
Businesses and policy actors need to focus on the translationof research into commercially viable applications, which may
require initiating public-private collaborations, building a cultureof entrepreneurship in public research bodies, stimulating
academic spin-offs, and creating business incubators andcenters of excellence.79
The actors involved in shaping medical innovation need to bereconsidered. Academic healthcare organizations, such asuniversity hospitals, have traditionally been boundary-spanning
organizations between care and science.80 The critical role ofhospitals and doctors in future demand-led health innovation isundeniable.81 In health innovation systems, patients could also
have a more central role in leading the direction of innovation.82
The same is true for insurers. Building on the information
they have for individual patients and the impact of particulartreatments, insurers could contribute more toward raisingawareness, informing patients, and preventing diseases—movingfrom a payer to a more active health system player.83
In sum, hospitals, insurers, patients, and regulators will needto cooperate more to influence the rate and direction of
innovation by identifying prioritized needs and redefining
modes of financing that incentivize the creation and diffusionof health solutions.84
For this to materialize, the various health system actors will haveto create and use better channels and to transmit relevant
information and feedback.85 Improving knowledge flows acrossthe different health actors will help. Practically speaking,this will require understanding differing needs and improving
shared data infrastructures to overcome significant gaps inintersectoral communication.86
More funding instruments need to be made available to fundthe stage between prototype and final product. Public-private
partnerships can help in this precompetitive stage. Awards to

Theme Section

51

particular researchers or research teams to encourage high-risk,
high-reward research are promising (Chapter 4), as is launchingprize competitions aimed at finding innovative solutions tomajor health challenges.87 Other new possibilities include
crowdfunding and funding through patient advocacy groups.
Policymakers can also strongly influence the translation anddiffusion of research to medical applications throughdemand-side policies that specify innovation targets and focus
areas. Moreover, governments can exert influence on thefunding of innovation by influencing prices and reimbursements
for health costs and by helping to align the costs and benefitsof new technologies and related incentives.88
Moving from cure to prevention
Generally, as mirrored in this year’s GII chapters, attention
should also gravitate from curing diseases and health conditions
to preventing them in the first place. Of course, prevention
goes beyond medical research and innovation. Environmental,
agricultural, and infrastructure policies with an impact on clean
air, clean water, or functioning sewage systems, for example,
also have a well-documented impact on overall health andwell-being, as well as on the incidence of disease. All too often,
however, health-related policies, including those governing
R&D, are treated separately—condemning medical research
to a perpetual game of catch-up with diseases and conditions
that are triggered or aggravated by environmental pollutants.89
The result is an inefficient use of resources.
Advancing skills and science education
The most important resource for the future of medical research
will be having a workforce with the right skill sets (Chapter 4
and Chapter 7). Serious medical staff shortages exist in bothdeveloped and emerging markets. In addition, medical
staff and researchers will need new sets of skills. The responsible
implementation of health innovations requires local healthcare
providers who are appropriately trained to use the latest
technologies (Chapter 11 and Chapter 13).
To act as a bridge between research and the application of
innovation in a real-life context, medical professionals withexperience in research, training in the use of new hardware
and software, and training in advanced research technologies—
such as 3D modeling—are needed (Chapter 7 and the AustralianCommonwealth Scientific and Industrial Research Organisation,
CSIRO, 2017). Workforce planning is required to ensure thatprofessionals and staff are equipped with the appropriate typesof skills to put new health technologies into practice.
To ensure better transfer of knowledge, researchers andmedical professionals should also move more freely between
research and business contexts. Research institutes should
be incentivized to employ a higher proportion of experienced
industry professionals, while researchers should be encouraged
to spend time in industry.90 These exchanges will also help
with the translation of research to applied medical solutions.

52

The Global Innovation Index 2019

Supporting new data infrastructure and regulatory processes
Healthcare stakeholders will require increased health data
sharing to increase their efficacy. At the same, time, patients will
want greater access and control over their health data, alongwith assurances that their information is safe.
The security and privacy of health information have been
confirmed as top priorities, and regulations on personal healthdata are being progressively harmonized (Chapter 7). Digital
health strategies that create strong data infrastructure—as well
as new processes for efficient and safe data collection,
management, and sharing—will be required. Agreements
will also be required to define how to design and operationalize
electronic health records and how to create standards andinteroperable technologies.91
How to harness the promise of big data medical research while
respecting the security of data and honoring patient privacy?
System security and data security principles need to beestablished for healthcare institutions (Chapter 5). Otherwise,a lack of data governance could decrease transparency andraise concerns about security and trust (Chapter 4, Chapter 7,
and Chapter 12).
In addition to data infrastructure, new regulatory processes areneeded to overcome the increasing duration and complexityof clinical trials. Breakthroughs in therapy have almost always
been coupled with breakthroughs in regulatory standards(Chapter 6). Yet, current regulations and health regulation agencies
may not be equipped for health innovation, while current
processes may be too cumbersome (Chapter 14).92 Developing
countries, in particular, may not have the capacity to deal withmultiple national regulatory regimes (Chapter 11).
Improving cost-benefit assessments of medical innovation
To prioritize and foster the diffusion of research and medical
technologies, cost-benefit assessments must be improved.93
Going forward, health technology assessments will be
increasingly important as a tool to foster industry accountability,
cost-efficient solutions, and outcome-oriented innovationsin healthcare.94
The idea of better assessing health innovation is not new.
Sweden and Switzerland, for example, have been at theforefront of health technology assessments for many years.95
In the U.K., the National Institute for Health and Care Excellence
provides evidence-based guidance on metrics, including on
new medical technologies.96 More can be done to spread theseapproaches to more countries. Better collection, analysis,
and sharing of outcomes and cost data—and possibly mandating a better tracking of technology-specific health outcomes—
will help in this regard.97

Debating risks, social values, and the value of life
New technologies will bring new possibilities but also new risks
and uncertainties—some of which will challenge current
ethics and societal values (Chapter 4). This is the case for novel
approaches in the field of genetic engineering in particular.
As in the past, possibilities in the field of medical innovation
will entail adaptable oversight and risk management functions,and possibly higher levels of precautionary oversight. To
avoid a race to the bottom—in which countries will adopt thelowest-common safety or ethical denominator—international
coordination is needed.
The challenges raised by novel approaches are not simply
technical issues, but larger questions that will require discussion
and agreement on matters at the core of ethics. Decision-making
structures must be developed to encapsulate the far-reaching
impacts on societal values. Similarly, as costs for new technologies
increase exponentially, the potential for further challenges—toequity or access—may grow. Are there limits to the preservationof human life “at any price” and over an increasing life span?
What are the limits to the cost of developing a new technology
and under what circumstances should these limits be imposed?98
These questions are beyond the scope of this edition of the
GII research; nonetheless, societies around the world will
increasingly have to confront them in this nexus between
technology and health.

Conclusion
The future of medical innovation, and the role of medical innovationin improving health outcomes going forward, will depend
crucially on the policies and institutions created by national andglobal actors to support research and innovation. There areimportant issues for policymakers to consider carefully, given
the transformative economic, social, and health impact new
medical technologies have had historically and the enormous
potential value of further health improvements for current andfuture generations.
Some overarching observations are useful in the particularcase of developing countries. While developing countries face
many of the same constraints as developed countries, these
low-resource contexts may have access to opportunities thatdeveloped countries lack. One indicator of this possibility isthat some of the more interesting examples of new healthtechnology applications have recently come from developing
countries in fields such as telemedicine, real-time diagnostic
tools, and even the establishment of electronic health records.
In the optimal scenario, developing countries might “leapfrog”
their current health systems, due to lower sunk costs related
to existing infrastructure and equipment, lower fixed costs
from not building overcapacity, and possibly less regulatory
constraint. They also have at their disposal technologicalinnovations, alternative operating and financing models, andlegal frameworks that were not previously available todeveloped countries. As a result, new health solutions might be
deployed quickly and with immediate impact in developing

countries—possibly without the need to proportionately
increase healthcare facilities and professionals. The disruptionof established health systems in developed countries is morechallenging.
Several caveats apply:
First, although leapfrogging implies the closing of a health gap
between the rich and the poor, there are risks that costly new
health innovations will exacerbate the health gap rather thannarrow it. This will require careful monitoring. Diffusion should
be encouraged, proper financing made available, public-private
partnerships created, and technologies fostered (Chapter 2).
Second, new health innovations aside, the true challenge todeveloping countries is the lack of minimally functional healthsystems and not necessarily a need for more R&D or new
technologies. The most pervasive unmet need in the developingworld is still providing basic and affordable healthcare at scale(Chapter 3).99 Technology is not always the remedy. The mere
availability and training of nurses that can go door-to-door
looking for signs of childhood diseases such as diarrhea,
malaria, and pneumonia have been shown to have widespreadand sustainable impacts in countries such as Mali.100 Basicbut impactful improvements of this kind are not necessarily
devoid of technology. Often the contrary is the case: low-tech or
adapted technology applications can save more lives than thelatest high-tech solutions.
Third, evidence-based decision-making and assessments will
be particularly important in developing countries. As newtechnologies, such as drones for the delivery of medicines,
are much discussed, and hyped to some extent, a sober
evidence-based look at the true costs and benefits of these
innovations will bear great value.

Notes:
1

Roser, 2019; Ma, 2019; Shetty, 2019.

2

WIPO, 2015a; Sampat, 2019.

3

Gordon, 2012, 2014; WIPO, 2015a, 2015b; Sampat, 2019.

4

Kenny, 2011; WIPO, 2015a.

5Deloitte, 2018a; EIU, 2017, 2018.

6

Deloitte, 2018a; Biot et al., 2019.

7

Deloitte, 2018a; EIU, 2017, 2018; Frost et al., 2019.

8

Dutta et al., 2019.

9

It also sets up targets aimed at specific challenges including, forexample, maternal mortality, AIDS, tuberculosis, malaria and neglected
tropical diseases and a goal to support R&D for vaccines and medicines
for communicable and non-communicable diseases.

Theme Section

53

10

11

First in 2016, the Political Declaration on Antimicrobial Resistance and
the Political Declaration on HIV and AIDS; and in 2018, the Political
Declaration on the Fight against Tuberculosis and the Political Declaration
on Non-Communicable Diseases.
To illustrate the cross-border dimension, and the need for specificresearch aimed at developing countries, SDG Indicator 3.b.2 monitors,
the Official development assistance (ODA) for medical research andbasic health sectors as a % of gross national income (GNI) and as a % of
all ODA, by donor country.

12

Sheiner et al., 2016.

13

Nelson, 2003.

14

Bartfai et al., 2013; Andrade et al., 2019.

15

Casadevall, 2018.

16

Scannell et al., 2012.

17

Bloom et al., 2017—While most of the economic literature confirms thisprospect of declining R&D pharmaceutical productivity, some contributions
question the extent finding that the above trends are exaggerated as
R&D costs are seriously overstated. Measuring the R&D productivityof a sector, let alone the overall productivity, in a field such as health isdaunting. Invariably metrics are imperfect.; Cockburn, 2006—e.g., byfailing to account for inflation in R&D input costs; Schmid et al., 2005.

18

Vijg, 2011—In one study, the total out-of-pocket R&D costs per new
approved drug are estimated to be around US$1.9 billion.; Pammolli etal., 2011; DiMasi et al.,2016.

19

Cross, 2018.—The development of a new health product is a risky
activity; estimates indicate that the percentage of drugs that reach themarket after starting clinical trials, which is already an advanced phaseof R&D in the sector, varies between 6% and 13.8% depending on theestimate.

35

Puica et al. 2019.

36

Dewhurst, 2017.

37

Tannoury et al., 2017.

38

Frost et al., 2018.

39

EIU, 2017, 2018.

40

Evaluate Pharmaceutical, 2018; WifOR, 2018.

41

Hernández et al., 2018; R&D Magazine, 2018.—Top investors such as
Roche (Switzerland), Johnson and Johnson (U.S.) and Merck US (U.S.)
invested on average around US$10 billion in R&D last year.

42

In some countries, the figures can be significantly higher—typically
about 30% of total R&D—e.g. in selected African countries such as
Kenya. Some high-income economies also stand out with a remarkably
high share of health R&D; e.g. Singapore and Qatar (both 19%), but also
the Netherlands (17%). Data drawn from Global Observatory on Health
R&D of the WHO, with special tabulations made available to authors.
The gross domestic expenditure on R&D (GERD) and GERD in the healthand medical sciences (health GERD) are collected from the United
Nations Educational, Scientific and Cultural Organization (UNESCO), theOrganisation for Economic Co-operation and Development (OECD), andEurostat, the statistical office of the European Union. They are reported
using the most recent available data since 2010 by country (Note: not
all countries have reported data on this indicator). See also https://www.
who.int/research-observatory/monitoring/inputs/gerd/en/

43

Among high-income countries ranges vary greatly with, for example,
France, Germany, Republic of Korea, and Italy between 5-10%, andother such as New Zealand, Spain, Denmark, Canada and Norway
between 10-15%. Source: Authors based on OECD R&D Statistics.

44

WIPO, 2018.— see Patent applications and grants worldwide

45

Bergquist et al., 2019.

46

WIPO, 2018, WIPO Statistics Database, 2017; Retrived fromhttps://www.wipo.int/ipstats/en/; Gokhale, 2017.

47

WIPO, 2018; WIPO, 2019b.

48

Cornell University, INSEAD, and WIPO, 2019; Ma, 2019; Bergquist et al.,2019; WIPO, 2019a; WIPO, 2019b.

20

Ricks et al., 2019.

21

Hopkins et al., 2007; Singh, 2018.

22

Comanor, 2013.—Note that recent mergers have indeed contributed tothe observed decline in pharmaceutical innovation.

23

R&D Magazine, 2018.

24

Abrishami et al., 2014; Penter, 2018.

49

Bloom et al., 2017.

25

Drolet et al., 2011.

50

Pharmaceutical Intelligence, 2019 ; Smietana, 2016.

26

Metcalfe et al., 2005.

51

27

Herzlinger, 2006.

28

Herzlinger, 2006.

Baedeker et al., 2018; Nature, 2019a; R&D Magazine, 2019; IQVIA
Institute, 2019.—In 2018, the European Medicines Agency (EMA) had
approved 84 (vs 94 in 2017) new drugs with 42 (vs 35 in 2017) of thesebeing new active substances. At the same time, the US Food and Drug
Administration (FDA) had approved 59 novel drugs and biologics in2018 (vs 46 in 2017).

29

Murphy, 2019.
52

EIU, 2017; EIU, 2018; Casadevall, 2018.

30Żaneta, 2019.
53

Bloom et al., 2017; Vijg, 2011; Casadevall, 2018; Gordon, 2018.

31

WHO, WIPO, and WTO, 2012, 2018.—Lack of access to medical
technologies is rarely due to a single determinant. Important factors
include: needs-based research, development, and innovation;
intellectual property and trade policies; manufacturing processes andsystems; regulatory environment; price transparency, pricing policies,
and health system infrastructure; integrity and efficiency in procurement
and supply chain management; and appropriate selection, prescribing
and use.

54

R&D Magazine, 2018; Deloitte, 2018b.

55

Coffano, 2016.—gives an analysis of the dynamic field of medical
device innovation.

56

FDA Statement from FDA Commissioner Scott Gottlieb, M.D., andJeff Shuren, M.D., Director of the Center for Devices and Radiological
Health, on a record year for device innovation, January 28, 2019.

57

On the delivery kits, see PATH, 2002; Beun et al., 2003; On frugal
medical innovation in India, see Verma, 2017.

58

Collins, 2019; Biot, 2019.

59

Khedkar et al., 2019; Ma, 2019.

60

Andrade et al., 2019; Jewell, 2018.

32

Kaslow, 2019.

33

Murray et al., 2012; Woodson, 2016; von Philipsborn et al., 2015.—One
study finds that diseases prominent in low-income economies cause
about 14 % of the global disease burden. Yet they only receive about
1.3 % of health-related R&D expenditure.

34

54

Zaid et al., 2019; Shetty, 2019.

The Global Innovation Index 2019

61

Zaid et al., 2019; Uwaliraye, 2019.

92

The Medical Futurist, 2017.

62

See on this caveat: GII 2019 chapters, in particular Sampat, 2019;
Collins, 2019 and also earlier work on breakthrough innovation; WIPO,
2015a; WIPO 2015b.

93

Thune, 2016.

94

Proksch et al., 2019.

63

Ma, 2019; Mahnken, 2018.

95

See also: http://www.inahta.org/members/sbu/ and https://www.bag.
admin.ch/bag/de/home/begriffe-a-z/health-technology-assessment.html

64

CSIRO, 2017; Basel et al.,2013.
96

More information at https://www.nice.org.uk/about

65

Khedkar et al., 2019; Biot et al., 2019; Puica et al., 2019,; Boonfueng etal., 2019.

97

BCG and World Economic Forum, 2017.

66

Ma, 2019; Murphy, 2019.

98

Mossialos, 2018.

67

For pharmaceuticals in particular, see Lichtenberg, 2003 and Grabowski
et al., 2002.

99

Khedkar et al., 2019.

68

Anelli et al., 2019.

69

R&D Magazine, 2018; Research!America, 2018.

70

Boonfueng et al., 2019; Andrade et al., 2019; Fartash et al., 2019.

71

Anelli et al., 2019.

72

Ricks et al., 2019.

73

Lehoux et al., 2016; Foray et al.,2012.

74

Kaslow, 2019.

75

For more information see: https://www.gatesfoundation.org/What-WeDo; and https://www.gavi.org/

76

Sampat, 2019.

77

WIPO actively involves a wide range of stakeholders—from civil society,to academia, business, and more—in order to ensure that all membersof society benefit from intellectual property. For its multi-stakeholder
platforms, see https://www.wipo.int/cooperation/en/multi_stakeholder_platforms/

78

Anelli et al, 2019.

79

Gelijns et al., 1994; Thune, 2016.

80

Lander, 2016; Miller, 2016.

81

Gulbrandsen et al., 2016; Smits et al., 2008.

82

Llopis et al., 2016; The Medical Futurist, 2017, including the idea for arole of patients on the board of pharmaceutical companies.

83

See the Daniel Schmutz, CEO, Helsana, Interview at https://pharmaboardroom.com/interviews/interview-daniel-schmutz-ceo-helsana-switzerland/84

Thune et al., 2016.

85

Barberá-Tomás et al., 2012.

86

Li et al., 2018.

87

Gandjour, 2011; Murray et al., 2012.

88

BCG and World Economic Forum, 2017.

89

There are many studies that tie air pollution in to increased rates
of cardiovascular disease and death, for example. See https://www.
eurekalert.org/pub_releases/2019-03/esoc-apc030819.php for astudy on the European Union.

90

CSRIO, 2017.

91

BCG and World Economic Forum, 2018.—In January 2017, the healthministers of OECD recommended that countries develop and implement
health-data governance frameworks that secure privacy while enabling
health data uses that are in public interest.

100 Mali’s “astounding” community health programme should be emulated,
By David Pilling, Financial Times, March 1, 2019.

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Theme Section

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Theme Section

59

60

The Global Innovation Index 2019

SP E C I AL S EC TIO N : C LUSTER R A NKINGSIDENTIFYING AND RANKING
THE WORLD’S LARGESTSCIENCE AND TECHNOLOGY
CLUSTERS
Kyle Bergquist and Carsten Fink, World Intellectual Property Organization (WIPO)

As in the previous two years, this Special Section presents thelatest ranking of the world’s largest science and technology(S&T) clusters. This spatial view of innovation performanceis rooted in the recognition that innovation activities tend tobe geographically concentrated. In other words, innovation
performance often varies substantially within countries, andthe cluster perspective highlights where such performanceis strong—at least as far as the S&T dimension of innovationis concerned.
The methodological approach underlying this year’s ranking
is the same as last year. We identify clusters based on thelocations of inventors listed in international patent applications
and authors appearing in scientific journal articles. Our data
sources continue to be patent application filings under WIPO’s
Patent Cooperation Treaty (PCT) and scientific publications
contained in the Web of Science’s SCI Expanded, publishedby Clarivate. Our data for this year’s ranking spans 2013-2017,
compared to the 2012-2016 time frame used last year.
For a more detailed description of the cluster ranking methodology,
we refer the interested reader to last year’s Special Section(Bergquist et al., 2018).

The top 100 S&T clusters
Table S-1.1 summarizes our geocoding results, and Table S-1.2
presents our top 100 cluster rankings. There are relatively few
changes from last year, partly reflecting the overlap in timeframes but arguably also the persistence of local innovation
performance. The composition of the top 10 clusters remains

unchanged, with Tokyo–Yokohama at the top of the list, followed
by Shenzhen–Hong Kong (2) and Seoul (3). Beijing (4) and San
Jose–San Francisco, CA (5) swapped rank compared to lastyear.
In both 2018 and 2019, the same 27 countries comprise the
top 100 clusters. The United States of America (U.S.) continues
to host the largest number of clusters (26), followed by China(18)—which is two more than China hosted in 2018. Germany (10),France (5), the United Kingdom (U.K.) (4), Canada (4), and Japan(3) follow next, all unchanged from the previous year.1
Compared to last year, almost all of the Chinese clusters moved
up the ranks. Guangzhou, the 21st ranked cluster in 2019,
moved up 11 places as compared to its 2018 ranking (21, +11).
Likewise, Hangzhou (30, +11), Qingdao (80, +22), Suzhou (81,+19), Chongqing (88, +15) and Jinan (89, +10) also registereddouble-digit rank increases. This reflects faster overall growth ininternational patent applications and scientific publications by
Chinese entities compared to most other countries (Figure S-1.1).
Two factors may explain rank changes from one year to thenext. First, rank changes may be due to changes in the volumeof patent applications and scientific publications during thetwo time frames. The declines in the rankings of Heidelberg–
Mannheim, 53 in 2019 as compared to 46 in 2018 (53, -7), andStuttgart (26, -5) mostly reflect declining S&T output while theclimb in rankings by Phoenix (76, +10) and Portland (44, +4)
reflect increases in S&T output. Second, rank changes may be
due to a growing or shrinking cluster geography. For example,
the rank increases of Brussels (40, +11) and Istanbul (69, +15)
mostly reflect growing cluster areas.2 It is important to note thatsuch geographical shifts may be sensitive to the threshold

The views expressed here are those of the authors and do not necessarily reflect those of WIPO or its member states.

Special Section: Cluster Rankings

61TABLE S-1.1

Summary of geocoding results
Scientific publications
Country

Number ofaddresses

City-level
address
accuracy (%)

PCT applications
Number ofaddresses

Block-level
address
accuracy (%)

Sub-City-level
address
accuracy (%)

City-level
address
accuracy (%)

Total address
accuracy (%)

United States of America

5,659,179

97.23

838,413

94.13

5.46

0.17

99.76

China

3,414,955

97.53

375,251

14.25

0.63

84.13

99.02

Japan

1,090,018

93.96

530,013

38.21

31.07

29.50

98.79

Germany

1,218,674

97.33

254,040

97.49

0.43

1.56

99.48

Republic of Korea

706,44293.55

200,694

0.14

0.94

80.84

81.92

United Kingdom

1,219,072

96.55

77,764

77.87

8.28

11.48

97.63

France1,028,646

92.81

105,291

85.29

1.51

7.19

93.99

Italy

948,100

95.47

40,238

86.57

5.00

7.02

98.59

Canada775,947

98.23

41,799

96.71

2.37

0.55

99.63

India

587,078

92.25

36,651

32.63

43.42

19.41

95.46

Spain

716,434

96.63

26,598

69.98

9.54

19.11

98.64

Netherlands

458,825

97.32

50,294

88.96

0.53

10.00

99.49

Australia

712,786

81.55

20,032

92.29

5.30

1.28

98.87

Brazil541,686

98.67

8,949

78.74

12.71

7.15

98.59

Sweden263,589

97.60

39,949

94.59

0.88

3.93

99.40

Switzerland

284,132

90.65

35,052

88.15

5.29

4.74

98.17

Russian Federation

313,634

99.02

15,279

83.24

5.56

9.22

98.02

Turkey360,651

96.56

11,173

31.17

50.54

14.63

96.35

Iran (Islamic Republic of)

326,572

97.00

317

0.63

1.58

86.44

88.64

Israel140,961

89.81

27,369

50.39

8.51

30.09

88.98

Source: WIPO Statistics Database, March 2019.
Notes: This list includes the top 20 countries that account for the highest combined shares of patents and scientific articles. PCT inventor addresses were
geocoded to the highest level of detail. Due to the much larger volume, scientific author addresses were geocoded to the city level only.

parameters of our clustering algorithm.3 In particular, the additionof relatively few inventor and author locations may lead tosizeable shifts in the identified clusters. The rank changes
associated with geographical shifts should therefore be treatedwith due caution.
Figure S-1.1 depicts the percentage change in net S&T output
by country. It highlights the fast growth of Chinese clusters andthe declining S&T outputs for selected clusters—especially inGermany. US clusters show high variance in net S&T output,
with two showing double-digit increases and several registering
small declines.
Table S-1.3 shows the top field of scientific publishing, the top
organizations with which scientific authors are affiliated, the top
patenting field, and the top patent applicant. The data illustrates
the diversity of clusters around the world in terms of thetechnology fields represented and the entities generating mostS&T output. Compared to last year, there is a notable shift in the
distribution of top patenting fields. Coinciding with this year’s
GII theme, medical technology is now the most frequent top
field—appearing in 19 clusters, compared to 16 last year.
Pharmaceuticals dropped to second place, with only 15 clusters
featuring this field as the top field, compared to 22 clusters in
2018. Digital communications also saw a decline, with this field

62

The Global Innovation Index 2019as the top field in 14 clusters, compared to 16 clusters in 2018.
Within the top scientific fields, chemistry remained the mostfrequent one, though it declined from 36 clusters in 2018 to 32
clusters in 2019 (32, -4). Neurosciences & Neurology (17 clusters,+4) became more prominent, whereas Oncology (4 clusters, -6)
turned out to be less prominent.
To provide insight into the national and global innovation
networks in which the top 100 clusters operate, we list their top
collaborating clusters in Table S-1.4. These collaborating clusters
are identified by the volume of co-inventor relationships forpatents and co-authorships for scientific publications. Table S-1.4
also lists the top collaborating entities within those top
collaborating clusters. For many clusters, the top co-inventing
and top co-authoring clusters are the same, partly reflecting thesize and proximity of nearby clusters. However, there also manycases for which they do not coincide. For example, Beijing’s
strongest scientific links are with Shanghai, whereas thestrongest patenting links are with San Jose–San Francisco,
CA. Overall, Beijing is the top collaborating cluster for scientificco-authorships (18 cases), followed by Washington, DC–Baltimore,
MD (8), New York City, NY (7), Boston-Cambridge, MA (6), andCologne (6). San Jose–San Francisco, CA is the most frequent
top co-inventing cluster (20 cases), followed by Beijing (8),Shenzhen–Hong Kong (6), and New York City, NY (5).

FIGURE S-1.1

Net science and technology (S&T) output

25

Qingdao
Guangzhou
20

15

Portland, OR

10

Phoenix, AZ

50

Stuttgart
-5
China

India

Republicof Korea▲ Net S&T output(contribution to growth (%))

U.K.

Switzerland Canada

Clusters

Australia

U.S.

Japan

FranceGermany

MedianSource: WIPO Statistics Database, March 2019.
Notes: Net S&T output refers to the diﬀerence of total patents and publications for each cluster, for all points that were located inside the samecluster as the previous year. For simplicity, Switzerland was assigned all three clusters it was associated with. Only economies with 3 or more clusters
are presented here.

Special Section: Cluster Rankings

63TABLE S-1.2

Top 100 cluster rankings
Rank

Cluster name

EconomyPCT
Scientificapplications publications

Share oftotal PCT
filings, %Share oftotal pubs,
%

Total

Rank
2012-16

Rank
change1

Tokyo-YokohamaJP108,973

144,559

10.90

1.72

12.62

1

-

2

Shenzhen-Hong Kong

CN/HK

55,43345,393

5.54

0.54

6.08

2

-

3

Seoul

KR

39,545

136,654

3.95

1.63

5.58

3

-

4

BeijingCN

23,014

222,668

2.30

2.65

4.95

5

1

5

San Jose-San Francisco, CAUS38,39988,243

3.84

1.05

4.89

4

-1

6

Osaka-Kobe-Kyoto

JP28,027

67,127

2.80

0.80

3.60

6

-

7

Boston-Cambridge, MA

US

14,364120,404

1.44

1.43

2.87

7

-

8

New York City, NYUS

12,329133,195

1.23

1.59

2.82

8

-

9

Paris

FR

13,426

94,982

1.34

1.13

2.47

9

-

10

San Diego, CAUS

19,28034,403

1.93

0.41

2.34

10

-

11

Shanghai

CN

8,736

114,395

0.87

1.36

2.24

12

1

12

NagoyaJP

19,37023,705

1.94

0.28

2.22

11

-1

13

Washington, DC-Baltimore, MD

US

4,498

117,623

0.45

1.40

1.85

13

-

14

Los Angeles, CA

US

9,398

68,337

0.94

0.81

1.75

14

-

15

LondonGB

4,070

107,131

0.41

1.28

1.68

15

-

16

Houston, TX

US

10,681

49,969

1.07

0.59

1.66

16

-

17

Seattle, WAUS

10,77333,796

1.08

0.40

1.48

18

1

18

Amsterdam-Rotterdam

NL

4,491

78,994

0.45

0.94

1.39

17

-1

19

Chicago, IL

US

6,455

55,718

0.65

0.66

1.31

19

-

20

CologneDE

7,374

43,621

0.74

0.52

1.26

20

-

21

Guangzhou

CN

4,029

59,762

0.40

0.71

1.11

32

11

22

DaejeonKR

7,699

25,689

0.77

0.31

1.08

23

1

23

Tel Aviv-Jerusalem

IL

6,950

30,971

0.70

0.37

1.06

22

-1

24

MunichDE

6,833

30,764

0.68

0.37

1.05

24

-

25

NanjingCN

1,440

75,749

0.14

0.90

1.05

27

2

26

Stuttgart

DE

8,261

18,347

0.83

0.22

1.04

21

-5

27

Minneapolis, MN

US

6,438

24,878

0.64

0.30

0.94

25

-2

28

Singapore

SG

3,899

44,988

0.39

0.54

0.93

28

-

29

Philadelphia, PA

US

3,176

50,014

0.32

0.60

0.91

26

-3

30

Hangzhou

CN

3,773

44,950

0.38

0.54

0.91

41

11

31

Eindhoven

BE/NL

8,175

6,198

0.82

0.07

0.89

29

-2

32

Stockholm

SE

5,587

27,121

0.56

0.32

0.88

31

-1

33

Moscow

RU

2,147

55,451

0.21

0.66

0.87

30

-3

34

Raleigh, NC

US

3,006

46,797

0.30

0.56

0.86

34

-

35

Melbourne

AU

1,955

54,842

0.20

0.65

0.85

33

-2

36

Frankfurt Am Main

DE

5,226

25,235

0.52

0.30

0.82

35

-1

37

SydneyAU

2,454

47,979

0.25

0.57

0.82

36

-1

38

Wuhan

CN

1,333

56,349

0.13

0.67

0.80

43

5

39

Toronto, ON

CA

2,298

47,218

0.23

0.56

0.79

37

-2

40

Brussels

BE

3,149

39,340

0.31

0.47

0.78

51

11

41

BerlinDE

3,393

35,542

0.34

0.42

0.76

39

-2

42

MadridES

1,605

49,980

0.16

0.59

0.76

38

-4

43

TaipeiTW

1,428

51,144

0.14

0.61

0.75

40

-3

44

Barcelona

ES

2,283

43,549

0.23

0.52

0.75

42

-2

45

Portland, OR

US

5,813

12,041

0.58

0.14

0.72

49

4

46

TehranIR

99

59,717

0.01

0.71

0.72

44

-2

47

Xi’an

CN

745

51,701

0.07

0.62

0.69

52

5

48

Milan

IT

2,177

37,953

0.22

0.45

0.67

45

-3

49

Denver, CO

US

2,818

31,458

0.28

0.37

0.66

47

-2

50

Zürich

CH/DE

3,007

29,651

0.30

0.35

0.65

48

-2
CONTINUED

64

The Global Innovation Index 2019

TABLE S-1.2

Top 100 cluster rankings, continued
Rank

Cluster name

EconomyPCT
Scientificapplications publications

Share oftotal PCT
filings, %Share oftotal pubs,
%

Total

Rank
2012-16

Rank
change-151Montréal, QC

CA

2,046

36,761

0.20

0.44

0.64

50

52

ChengduCN

1,364

42,467

0.14

0.51

0.64

56

4

53

Heidelberg-Mannheim

DE

3,903

20,938

0.39

0.25

0.64

46

-7

54

Istanbul

TR

2,437

31,452

0.24

0.37

0.62

69

15

55

Copenhagen

DK

2,854

27,185

0.29

0.32

0.61

53

-2

56

Atlanta, GA

US

1,591

36,308

0.16

0.43

0.59

54

-2

57

Rome

IT

821

40,435

0.08

0.48

0.56

55

-2

58

Cambridge

GB

2,431

26,164

0.24

0.31

0.55

59

1

59

São Paulo

BR

756

38,494

0.08

0.46

0.53

57

-2

60

TianjinCN

807

37,572

0.08

0.45

0.53

67

7

61

Cincinnati, OH

US

3,616

13,736

0.36

0.16

0.53

62

1

62

Nuremberg-Erlangen

DE

3,699

12,357

0.37

0.15

0.52

58

-4

63

Pittsburgh, PA

US

1,555

30,051

0.16

0.36

0.51

60

-3

64

Dallas, TX

US

3,135

16,772

0.31

0.20

0.51

61

-3

65

Bengaluru

IN

3,119

16,800

0.31

0.20

0.51

65

-

66

Ann Arbor, MI

US

1,413

30,555

0.14

0.36

0.51

63

-3

67

ChangshaCN

984

33,067

0.10

0.39

0.49

68

1

68

Helsinki

FI

2,837

17,100

0.28

0.20

0.49

64

-4

69

ViennaAT

1,523

26,719

0.15

0.32

0.47

66

-3

70

Delhi

IN

782

32,275

0.08

0.38

0.46

72

2

71

OxfordGB

1,419

26,692

0.14

0.32

0.46

70

-1

72

Vancouver, BC

CA

1,478

24,217

0.15

0.29

0.44

73

1

73

Cleveland, OH

US

1,460

23,982

0.15

0.29

0.43

71

-2

74

Lyon

FR

2,270

16,950

0.23

0.20

0.43

74

-

75

Busan

KR

2,136

17,640

0.21

0.21

0.42

75

-

76

Phoenix, AZ

US

2,318

13,166

0.23

0.16

0.39

86

10

77

AnkaraTR

435

28,652

0.04

0.34

0.38

76

-1

78

Ottawa, ON

CA

1,829

16,573

0.18

0.20

0.38

80

2

79

Austin, TX

US

2,151

13,516

0.22

0.16

0.38

77

-2

80

QingdaoCN

1,480

19,128

0.15

0.23

0.38

102

22

81

SuzhouCN

2,11913,692

0.21

0.16

0.37

100

19

82

Bridgeport-New Haven, CT

US

1,275

20,583

0.13

0.24

0.37

81

-1

83

Brisbane

AU

1,098

21,591

0.11

0.26

0.37

83

-

84

Hamburg

DE

1,874

15,020

0.19

0.18

0.37

79

-5

85

Grenoble

FR

2,045

13,286

0.20

0.16

0.36

78

-7

86

Lausanne

CH/FR

1,859

14,605

0.19

0.17

0.36

85

-1

87

HarbinCN

168

28,773

0.02

0.34

0.36

93

6

88

ChongqingCN

333

26,799

0.03

0.32

0.35

103

15

89

Jinan

CN

477

25,528

0.05

0.30

0.35

99

10

90

Hefei

CN

350

26,560

0.04

0.32

0.35

97

7

91

Basel

CH/DE/FR

2,064

11,889

0.21

0.14

0.35

82

-9

92

Manchester

GB

965

21,028

0.10

0.25

0.35

84

-8

93

ChangchunCN

191

27,372

0.02

0.33

0.34

95

2

94

St. Louis, MO

US

916

20,729

0.09

0.25

0.34

89

-5

95

Lund

SE

1,925

12,124

0.19

0.14

0.34

90

-5

96

Columbus, OH

US

991

19,902

0.10

0.24

0.34

88

-8

97

MumbaiIN

1,199

17,784

0.12

0.21

0.33

92

-5

98

Indianapolis, IN

US

1,755

12,616

0.18

0.15

0.33

91

-7

99

DublinIE

766

20,750

0.08

0.25

0.32

94

-5

100 Warsaw

PL

429

23,419

0.04

0.28

0.32

98

-2

Source: WIPO Statistics Database, March 2019.
Notes: Patent filing and scientific publication shares refer to the 2013–17 time frame and are based on fractional counts, as explained in the text. Codes referto the ISO-2 codes. See page 17 for a full list, with the following addition: TW = Taiwan, Province of China.

Special Section: Cluster Rankings

65The entities driving collaboration between two clusters
remained constant for scientific publications but differed forpatenting. The Chinese Academy of Sciences (18, Beijing)
emerged as the most frequent top collaborating entity for all
18 times that Beijing is listed as collaborating cluster for scientificco-authorships. The same is true for Johns Hopkins University(8, Washington, DC–Baltimore, MD), Columbia University(7, New York City, NY), and Harvard University (6, BostonCambridge, MA). In contrast, a wider array of firms drive
co-patenting relationships. For example, 14 different firms arelisted as the top collaborating entities for the 20 times that
San Jose–San Francisco, CA is listed as a top collaboratingcluster. Beijing has 8 different entities as the primary driverfor its patent collaborations. Shenzhen-Hong Kong,
conversely, has only 2 entities for the 6 times it is listed
as a top collaborating cluster for co-patenting—Huawei (5)and Shenzhen Guohua OptoElectronics (1).

Concluding remarks
The 2019 S&T cluster ranking offers a window into the world’s
innovation hotspots. The microdata, on the basis of which we
identify and measure S&T clusters, further provide insight into
the nature and direction of innovative activity taking place withindifferent clusters.
As in previous years, it is important to point out several caveats
and limitations of our approach. First, the precise shape of
the identified clusters depends critically on the thresholdparameters of our clustering algorithm. Although the relative
ranking does not change substantially within a plausible rangeof threshold parameters, especially for the top 25 clusters, thegeographic coverage of each cluster does fluctuate dependingon the parameters chosen.
Second, our approach places equal weight on patenting andscientific output. Different weights would imply different rankorders, though changes would only be significant for the lower
half of the top 100 list. Finally, while S&T activity is central toinnovation performance, it naturally focuses on the upstream
segments of the innovation value chain. Our data do not capture
how S&T activity translates to productivity gains as well as new
products and services in the marketplace.

Notes:
1

Gothenburg (Sweden) and Tainan–Kaohsiung (Taiwan) dropped outof the top 100; Qingdao (China) and Chongqing (China) entered the
top 100.

2

Both Guangzhou (#21, + 11) and Phoenix, AZ (#76, +10) also experienced
non-trivial increases in cluster area, however their growth was still
primarily driven by new S&T output.

3

See Bergquist et al. (2018) for a description of our clustering
algorithm and the threshold parameters chosen.

66

The Global Innovation Index 2019

References:
Bergquist, K., Fink, C., & Raffo, J. (2018). Special section: Identifying and ranking
the world’s largest science and technology clusters. In S. Dutta,
B. Lanvin, & S. Wunsch-Vincent (Eds.), Global Innovation Index 2018:
Energizing the World with Innovation. Ithaca, Fontainebleau, andGeneva: Cornell, INSEAD, and WIPO. 193–209.
Ester, M., Kriegel, H., Sander, J., & Xu, X. (1996). A density-based algorithm fordiscovering clusters in large spatial databases with noise. Proceedingsof 2nd International Conference on Knowledge Discovery and Data
Mining. 226–231.
Falagas, M.E., Pitsouni, E. I., Malietzis, G. A., & Pappas, G. (2007). Comparisonof PubMed, Scopus, Web of Science, and Google Scholar: Strengths
and Weaknesses. The FASEB Journal, 22(2), 338–42. Retrieved fromhttps://doi.org/10.1096/fj.07-9492LSF.
Garfield, E. (1970). Citation indexing for studying science. Nature, 227(5259),
669–671.
Garfield, E. (1972). Citation analysis as a tool in journal evaluation. Science,
178(4060), 471–79.
Harzing, A. W., Alakangas, S. (2016). Google Scholar, Scopus and the Webof Science: A longitudinal and cross-disciplinary comparison.
Scientometrics, 106(2), 787–804. Retrieved from https://doi.org/10.1007/
s11192-015-1798-9.

FIGURE S-1.2

Top 100 clusters worldwide

Clusters

Noise

0

2500

5000 km

Source: WIPO Statistics Database, March 2019.
Note: Noise refers to all inventor / author locations not classified in a cluster.

Special Section: Cluster Rankings

67

TABLE S-1.3

Top 100 cluster rankings by publishing and patent performance
Scientific publishing performance
Rank

Cluster name

Economy(ies)Top science field

Share, %Top scientific organization

1

Tokyo-Yokohama

JP

Physics

9.22

University of Tokyo2

Shenzhen-Hong Kong

CN/HK

Engineering

10.81

University of Hong Kong

3

Seoul

KR

Engineering

7.53

Seoul National University

4

Beijing

CN

Chemistry

10.30

Chinese Academy of Sciences

5

San Jose-San Francisco, CA

USChemistry

6.14

University of California

6

Osaka-Kobe-Kyoto

JP

Chemistry

10.41

Kyoto University

7

Boston-Cambridge, MA

US

Oncology

5.63

Harvard University

8

New York City, NY

US

Neurosciences & Neurology

5.72

Columbia University

9

Paris

FR

Physics

7.48

CNRS

10

San Diego, CA

USScience & Technology-Other Topics

6.21

University of California

11

ShanghaiCN

Chemistry

13.07

Shanghai Jiao Tong University

12

NagoyaJP

Chemistry

9.24

Nagoya University

13

Washington, DC-Baltimore, MD

US

Neurosciences & Neurology

5.11

Johns Hopkins University

14

Los Angeles, CA

US

Neurosciences & Neurology

5.35

University of California

15

LondonGB

General & Internal Medicine

6.90

University of London

16

Houston, TX

US

Oncology

11.86

Baylor College of Medicine

17

Seattle, WA

USGeneral & Internal Medicine

4.79

University of Washington

18

Amsterdam-Rotterdam

NL

Cardiovascular System & Cardiology

6.09

University of Utrecht

19

Chicago, IL

US

Neurosciences & Neurology

5.26

Northwestern University

20

CologneDE

Chemistry

6.77

University of Bonn

21

Guangzhou

CN

Chemistry

10.32

Sun Yat Sen University

22

DaejeonKR

Engineering

13.45

KAIST

23

Tel Aviv-Jerusalem

IL

Neurosciences & Neurology

6.21

Tel Aviv University

24

MunichDE

Physics

7.95

University of Munich

25

Nanjing

CN

Chemistry

12.35

Nanjing University

26

Stuttgart

DE

Chemistry

7.23

Eberhard Karls University of Tubingen

27

Minneapolis, MN

USChemistry

5.64

University of Minnesota

28

Singapore

SG

Engineering

10.56

National University of Singapore

29

Philadelphia, PA

US

Neurosciences & Neurology

5.84

University of Pennsylvania

30

HangzhouCN

Chemistry

12.43

Zhejiang University

31

Eindhoven

BE/NL

Engineering

14.72

Eindhoven University of Tech.

32

StockholmSE

Science & Technology-Other Topics

5.70

Karolinska Institutet

33

Moscow

RU

Physics

17.44

Russian Academy of Sciences

34

Raleigh, NC

USScience & Technology-Other Topics

4.56

University of North Carolina

35

Melbourne

AU

General & Internal Medicine

5.42

University of Melbourne

36Frankfurt Am Main

DE

Physics

9.05

Goethe University Frankfurt

37

SydneyAU

General & Internal Medicine

5.43

University of Sydney

38

Wuhan

CN

Chemistry

10.43

Huazhong University of Science & Tech.

39

Toronto, ON

CANeurosciences & Neurology

7.07

University of Toronto

40

BrusselsBE

Physics

4.93

KU Leuven

41

BerlinDE

Chemistry

7.28

Free University Of Berlin

42

MadridES

Chemistry

5.77

CSIC

43

TaipeiTW

Engineering

8.22

National Taiwan University

44

Barcelona

ES

Chemistry

5.29

University of Barcelona

45

Portland, OR

US

Neurosciences & Neurology

6.54

Oregon University System

46

TehranIR

Engineering

15.92

Tehran University of Medical Sciences

47

Xi’an

CN

Engineering

13.97

Xi’an Jiaotong University

48

Milan

IT

Neurosciences & Neurology

7.96

University of Milan49

Denver, COUS

Meteorology & Atmospheric Sciences

5.00

University of Colorado

50

ZürichCH/DE

Chemistry

7.87

University of Zurich

68

The Global Innovation Index 2019

Patent performance
Share, %Top patenting field

Share, %Top applicant

Share, %13.85

Electrical machinery, apparatus, energy

9.86

Mitsubishi Electric

7.83

17.23

Digital communication

38.39

Huawei

25.76

16.10

Digital communication

16.63

LG Electronics

18.71

22.69

Digital communication

23.60

BOE Technology Group

24.43

38.59

Computer technology

23.18

Google

8.04

22.53

Electrical machinery, apparatus, energy

13.27

Murata Manufacturing

10.61

53.87

Pharmaceuticals

17.03

M.I.T

6.81

13.26

Pharmaceuticals

14.52

Honeywell

5.49

22.81

Transport

11.49

L’Oréal

7.60

51.51

Digital communication

30.37

Qualcomm

58.45

23.06

Digital communication

10.48

Alcatel Lucent

3.36

37.49

Electrical machinery, apparatus, energy

17.99

Toyota

23.97

24.62

Pharmaceuticals

17.74

Johns Hopkins University

13.52

44.49

Medical technology

18.52

University of California

6.00

49.28

Digital communication

11.71

British Telecom

8.06

20.49

Civil engineering

34.74

Halliburton

18.55

65.07

Computer technology

41.74

Microsoft

35.47

13.01

Civil engineering

6.61

Shell

8.86

28.12

Digital communication

8.22

Illinois Tool Works

14.76

15.84

Basic materials chemistry

10.37

Henkel

9.55

27.92

Electrical machinery, apparatus, energy

8.95

South China University of Tech.

5.26

25.41

Electrical machinery, apparatus, energy

20.90

LG Chem

40.16

34.05

Computer technology

17.76

Intel

5.30

50.80

Transport

12.33

BMW

15.74

17.55

Electrical machinery, apparatus, energy

10.35

Southeast University

9.36

44.09

Electrical machinery, apparatus, energy

13.02

Robert Bosch

46.89

70.89

Medical technology

30.22

3M Innovative Properties

35.40

37.35

Computer technology

7.64

A*Star

17.76

50.32

Pharmaceuticals

20.85

University of Pennsylvania

10.85

57.90

Computer technology

31.29

Alibaba Group

48.68

61.43

Medical technology

26.00

Philips Electronics

77.26

49.23

Digital communication

39.76

LM Ericsson

45.89

37.50

Computer technology

11.24

Yandex Europe

3.91

50.62

Pharmaceuticals

12.78

Duke University

8.44

24.56

Pharmaceuticals

8.99

Monash University

5.56

23.62

Medical technology

12.31

Merck Patent

9.04

40.15

Medical technology

12.09

Cochlear

4.83

29.81

Optics

15.27

Wuhan China Star Optoelectronics Tech.

16.88

81.09

Medical technology

12.76

Synaptive Medical

5.10

34.62

Basic materials chemistry

7.79

Procter & Gamble Company

5.23

36.71

Electrical machinery, apparatus, energy

11.12

Siemens

12.67

15.35

Digital communication

12.45

CSIC

9.16

26.77

Computer technology

12.08

Hewlett-Packard

12.13

29.52

Pharmaceuticals

9.93

Hewlett-Packard

19.87

65.73

Computer technology

24.08

Intel

53.80

10.85

Medical technology

12.43

Gharooni, Milad

3.04

29.28

Digital communication

16.74

Xi’an Jiaotong University

11.90

24.40

Electrical machinery, apparatus, energy

6.97

Pirelli Tyre

7.64

56.07

Medical technology

13.77

University of Colorado

6.94

36.18

Medical technology

8.39

Sika Technology

5.14

Special Section: Cluster Rankings

69

TABLE S-1.3

Top 100 cluster rankings by publishing and patent performance, continued
Scientific publishing performance
Rank

Cluster name

Economy(ies)Top science field

Share, %Top scientific organization

51

Montréal, QC

CAEngineering

7.20

McGill University

52

ChengduCN

Engineering

11.14

Sichuan University

53

Mannheim

DE

Oncology

9.31

Ruprecht Karl University Heidelberg

54

Istanbul

TR

Engineering

6.99

Istanbul University

55

Copenhagen

DK

Neurosciences & Neurology

5.41

University of Copenhagen

56

Atlanta, GA

US

Public, Environmental & Occupational Health 6.76

Emory University

57

Rome

IT

Neurosciences & Neurology

6.62

Sapienza University Rome

58

Cambridge

GB

Science & Technology-Other Topics

7.50

University of Cambridge

59

São Paulo

BR

Neurosciences & Neurology

4.24

Universidade de Sao Paulo60

Tianjin

CN

Chemistry

18.13

Tianjin University

61

Cincinnati, OH

US

Pediatrics

6.49

University of Cincinnati

62

Nürnberg

DE

Chemistry

7.95

University of Erlangen Nuremberg

63

Pittsburgh, PA

US

Neurosciences & Neurology

5.76

PCSHE

64

Dallas, TX

US

Cardiovascular System & Cardiology

6.50

Univ. of Texas Southwestern Med. Center

65

Bengaluru

IN

Chemistry

12.54

IISC-Bengaluru

66

Ann Arbor, MI

US

Chemistry

4.68

University of Michigan

67

ChangshaCN

Engineering

10.81

Central South University

68

HelsinkiFI

Science & Technology-Other Topics

4.81

University of Helsinki

69

ViennaAT

Physics

4.89

Medical University of Vienna

70

Delhi

IN

Chemistry

7.83

All India Institute of Medical Sciences

71

OxfordGB

Physics

7.19

University of Oxford

72

Vancouver, BC

CA

Neurosciences & Neurology

4.86

University of British Columbia

73

Cleveland, OH

US

Cardiovascular System & Cardiology

7.84

Cleveland Clinic

74

Lyon

FR

Chemistry

6.98

CNRS

75

Busan

KR

Engineering

9.69

Pusan National University

76

Phoenix, AZ

USNeurosciences & Neurology

6.76

Arizona State University

77

AnkaraTR

Cardiovascular System & Cardiology

5.64

Hacettepe University

78

Ottawa, ON

CAEngineering

6.12

University of Ottawa

79

Austin, TX

USChemistry

10.52

University Of Texas Austin

80

QingdaoCN

Chemistry

13.52

Ocean University of China

81

SuzhouCN

Chemistry

17.40

Suzhou University

82

Bridgeport-New Haven, CT

US

Neurosciences & Neurology

6.27

Yale University

83

Brisbane

AU

Engineering

5.32

University of Queensland

84

HamburgDE

Physics

7.89

University of Hamburg

85

GrenobleFR

Physics

17.55

CNRS

86

Lausanne

CH/FR

Chemistry

7.95

EPFL

87

HarbinCN

Engineering

12.15

Harbin Institute of Technology

88

ChongqingCN

Chemistry

10.09

Chongqing University

89

Jinan

CN

Chemistry

14.24

Shandong University

90

Hefei

CN

Physics

14.69

University of Science & Tech. of China

91

Basel

CH/DE/FR

Pharmacology & Pharmacy

7.54

University of Basel

92

Manchester

GB

Chemistry

6.77

University of Manchester

93

Changchun

CN

Chemistry

23.62

Jilin University

94

St. Louis, MO

US

Neurosciences & Neurology

6.39

Washington University (WUSTL)

95

Lund

SE

Science & Technology-Other Topics

5.59

Lund University

96

Columbus, OH

US

Oncology

5.29

Ohio State University

97

MumbaiIN

Chemistry

16.28

Bhabha Atomic Research Center98

Indianapolis, IN

US

Pharmacology & Pharmacy

5.05

Indiana University

99

DublinIE

General & Internal Medicine

17.79

Trinity College

100

WarsawPL

Chemistry

9.32

Polish Academy of Sciences

Source: WIPO Statistics Database, March 2019.
Notes: Patent filing and scientific publication shares refer to the 2013–17 period and are based on fractional counts, as explained in the text. We use the location of inventors to
associate patent applicants to clusters; note that addresses of applicants may well be outside the cluster(s) to which they are associated. The identification of technology fields
relies on the WIPO technology concordance table linking International Patent Classification (IPC) symbols with 35 fields of technology (available at http://www.wipo.int/ipstats/en/).
70

The Global Innovation Index 2019

Patent performance
Share, %Top patenting field

Share, %Top applicant

Share, %42.47

Digital communication

17.11

LM Ericsson

42.54

Pharmaceuticals

11.70

Sichuan Haisco Pharmaceutical

9.10
4.32

58.56

Basic materials chemistry

13.27

BASF

42.53

18.58

Other consumer goods

18.74

Arcelik

46.21

72.62

Biotechnology

15.25

Novozymes

11.02

37.21

Medical technology

13.66

Georgia Tech

7.93

31.67

Medical technology

10.87

Bridgestone

7.12

73.38

Computer technology

15.46

ARM

9.09

46.86

Medical technology

8.32

Mahle Metal Leve

3.23

29.17

Pharmaceuticals

9.14

Tianjin University

11.93

46.17

Medical technology

32.37

Procter & Gamble Company

43.19

67.33

Electrical machinery, apparatus, energy

16.91

Siemens

37.99

67.50

Medical technology

12.86

University of Pittsburgh

13.39

39.25

Civil engineering

17.24

Halliburton

16.39

30.39

Computer technology

22.79

Hewlett-Packard

11.26

89.15

Pharmaceuticals

10.20

University of Michigan

27.71

42.83

Civil engineering

15.63

Zoomlion

32.84

56.72

Digital communication

31.13

Nokia

10.89

28.13

Pharmaceuticals

9.29

Siemens

4.11

14.08

Pharmaceuticals

13.98

Ranbaxy Laboratories

6.49

78.10

Biotechnology

12.84

Oxford University

17.77

70.21

Medical technology

9.60

University of British Columbia

7.07

47.33

Medical technology

15.62

Cleveland Clinic

10.83

31.25

Basic materials chemistry

10.63

IFP Energies Nouvelles

10.95

35.02

Electrical machinery, apparatus, energy

7.61

Pusan National University

5.09

50.97

Semiconductors

15.41

Intel

23.66

17.32

Medical technology

13.63

Aselsan

21.65

57.42

Digital communication

44.40

Huawei

35.66

66.99

Computer technology

22.27

University Of Texas

12.58

21.54

Other consumer goods

33.11

Qingdao Haier Washing Machine

14.66

68.69

Electrical machinery, apparatus, energy

9.53

Positec Power Tools

4.68

85.32

Pharmaceuticals

15.50

Yale University

11.13

49.46

Civil engineering

12.68

University of Queensland

8.84

57.59

Organic fine chemistry

16.14

Henkel

9.17

42.01

Electrical machinery, apparatus, energy

13.97

CEA

40.01

46.74

Food chemistry

8.87

NESTEC

26.77

42.85

Measurement

12.51

Harbin Institute of Technology

38.65

26.46

Medical technology

13.23

Chongqing Runze Pharmaceutical

10.51

58.50

Computer technology

10.79

Shandong University

10.04

41.28

Other consumer goods

12.12

Anhui Jianghuai Automobile

10.56

60.83

Pharmaceuticals

19.04

F. Hoffmann-La Roche

13.38

65.91

Electrical machinery, apparatus, energy

15.71

Micromass

13.76

57.67

Measurement

14.00

Changchun Institute Of Applied Chemistry

15.69

69.55

Biotechnology

16.63

Monsanto Technology

16.54

86.72

Digital communication

22.79

LM Ericsson

21.81

89.88

Pharmaceuticals

13.23

Abbott Laboratories

13.01

22.72

Organic fine chemistry

18.23

Piramal Enterprises

5.26

68.17

Basic materials chemistry

11.81

Dow AgroSciences

22.46

30.49

Computer technology

11.08

Alcatel Lucent

8.07

19.76

Medical technology

8.18

General Electric

4.00

The top scientific field is based on SCIE’s Extended Ascatype subject field. An article can be assigned to more than one subject field. Fractional counting was used whenmore than one subject was assigned to an article. Codes refer to the ISO-2 codes. See page 17 for a full list, with the following addition: TW = Taiwan, Province of China.
CNRS = Centre National de la Recherche Scientifique, CSIC = Consejo Superior de Investigaciones Cientificas, PCSHE = Pennsylvania Commonwealth System of Higher
Education, IISC = Indian Institute of Science, EPFL = Ecole Polytechnique Federale de Lausanne, CEA = Commissariat a L’Energie Atomique et aux Energies Alternatives.
Special Section: Cluster Rankings

71TABLE S-1.4

Top collaborating entities by cluster
Scientific publishing collaboration
Rank

Cluster name

Economy(ies)Top scientific collaborating cluster

Share, %Top collaborating organization

1

Tokyo-Yokohama

JP

Osaka-Kobe-Kyoto

8.15

Kyoto University

2

Shenzhen-Hong Kong

CN/HK

Beijing

9.66

Chinese Academy of Sciences

3

Seoul

KR

Daejeon

4.32

KAIST

4

BeijingCN

Shanghai

3.15

Chinese Academy of Sciences

5

San Jose-San Francisco, CA

US

Boston-Cambridge, MA

5.28

Harvard University

6

Osaka-Kobe-Kyoto

JPTokyo-Yokohama

20.16

University of Tokyo

7

Boston-Cambridge, MA

USNew York City, NY

4.95

Columbia University

8

New York City, NY

US

Boston-Cambridge, MA

4.88

Harvard University

9

Paris

FR

Lyon

2.53

CNRS

10

San Diego, CA

USSan Jose-San Francisco, CA

5.36

University of California

11

ShanghaiCN

Beijing

6.00

Chinese Academy of Sciences

12

NagoyaJPTokyo-Yokohama

24.42

University of Tokyo

13

Washington, DC-Baltimore, MD US

Boston-Cambridge, MA

4.62

Harvard University

14

Los Angeles, CA

US

San Jose-San Francisco, CA

4.77

University of California

15

LondonGB

Oxford

2.62

University of Oxford

16

Houston, TX

USSan Jose-San Francisco, CA

6.49

Stanford University

17

Seattle, WA

US

Boston-Cambridge, MA

5.30

Harvard University

18

Amsterdam-Rotterdam

NL

Nijmegen4.70

Radboud University Nijmegen

19

Chicago, IL

US

New York City, NY

4.35

Columbia University

20

CologneDE

Berlin3.97

Free University of Berlin

21

GuangzhouCN

Beijing

7.06

Chinese Academy of Sciences

22

Daejeon

KR

Seoul

29.76

Seoul National University

23

Tel Aviv-Jerusalem

IL

Haifa

4.11

Technion Israel Institute of Tech.

24

MunichDE

Cologne

5.12

University of Bonn

25

NanjingCN

Beijing

6.55

Chinese Academy of Sciences

26

StuttgartDE

Cologne

4.42

University of Bonn

27

Minneapolis, MN

USWashington, DC-Baltimore, MD

4.14

Johns Hopkins University

28

SingaporeSG

Beijing

2.39

Chinese Academy of Sciences

29

Philadelphia, PA

US

New York City, NY

6.27

Columbia University

30

HangzhouCN

Beijing

5.58

Chinese Academy of Sciences

31

Eindhoven

BE/NL

Amsterdam-Rotterdam

24.27

Delft University of Technology

32

Stockholm

SE

Uppsala6.31

Uppsala University

33

Moscow

RU

Saint Petersburg

2.02

Russian Academy of Sciences

34

Raleigh, NC

USWashington, DC-Baltimore, MD

4.85

Johns Hopkins University

35

Melbourne

AU

Sydney6.37

University of Sydney

36Frankfurt Am Main

DE

Cologne

5.74

University of Bonn

37

SydneyAU

Melbourne

7.47

University of Melbourne

38

Wuhan

CN

Beijing

7.48

Chinese Academy of Sciences

39

Toronto, ON

CAMississauga, ON

2.97

McMaster University

40

Brussels

BE

Gent

5.43

Ghent University

41

BerlinDE

Cologne4.95

University of Cologne

42

MadridES

Barcelona

8.82

University of Barcelona

43

TaipeiTW

Taichung

7.15

China Medical University Taiwan

44

Barcelona

ES

Madrid

8.24

CSIC

45

Portland, OR

US

San Jose-San Francisco, CA

6.12

University of California

46

TehranIR

Kuala Lumpur

0.34

Universiti Malaya

47

Xi’an

CN

Beijing

6.89

Chinese Academy of Sciences

48

Milan

IT

Rome

6.10

Sapienza University Rome49

Denver, COUS

Washington, DC-Baltimore, MD

5.05

Johns Hopkins University

50

Zürich

CH/DE

Bern

3.38

University of Bern

72

The Global Innovation Index 2019

Patent collaboration
Share, %Top patent collaborating cluster

Share, %Top collaborating applicant

Share, %24.89

Osaka-Kobe-Kyoto

1.30

Hitachi

4.15

20.15

Beijing

0.21

Huawei

70.34

16.93

Daejeon

2.82

LG Chem

9.80

32.13

San Jose-San Francisco, CA

1.19

Intel

58.38

55.82

Portland, OR

1.71

Intel

83.05

13.44

Tokyo-Yokohama

5.16

Hitachi

3.20

15.52

San Jose-San Francisco, CA

2.65

Robert Bosch

4.78

56.89

Boston-Cambridge, MA

3.18

Merck Sharp & Dohme Corp.

7.76

25.27

Lyon

1.39

IFP Energies Nouvelles

26.68

35.93

San Jose-San Francisco, CA

2.04

Qualcomm

10.11

38.80

New York City, NY

1.72

Merck Sharp & Dohme Corp.

63.36

12.98

Tokyo-Yokohama

3.35

Toyota

6.70

56.85

San Jose-San Francisco, CA

3.13

Robert Bosch

6.33

37.56

San Jose-San Francisco, CA

4.22

University of California

4.07

76.75

Cambridge

1.73

British American Tobacco

7.08

51.03

New York City, NY

0.89

Exxonmobil

16.76

61.10

San Jose-San Francisco, CA

2.28

Elwha LLC

10.62

54.38

Houston, TX

1.70

Shell

53.50

16.34

San Jose-San Francisco, CA

1.69

Motorola Mobility

10.53

39.63

Aachen2.61

Grüenthal

15.95

38.12

Shenzhen-Hong Kong

0.83

Shenzhen Guohua Optoelectronics

18.10

16.14

Seoul

12.69

Lg Hausys

6.30

46.91

Haifa

5.72

Intel

18.77

15.48

Nürnberg

1.95

Siemens

56.89

36.02

Beijing

1.78

LM Ericsson

15.08

14.55

Mannheim

1.25

BASF

26.75

28.14

San Jose-San Francisco, CA

1.18

Pure Storage

8.08

23.94

San Jose-San Francisco, CA

1.72

Hewlett-Packard

17.96

14.00

New York City, NY

14.37

Merck Sharp & Dohme Corp.

19.73

20.88

Shanghai

0.73

Shenzhen Luoshuhe Tech. Development

17.31

14.23

Amsterdam-Rotterdam

0.67

ASML

8.99

80.32

Uppsala2.88

LM Ericsson

61.77

29.89

Saint Petersburg

2.45

Rawllin International

11.87

26.58

San Jose-San Francisco, CA

3.19

Carbon3D

12.51

38.37

Sydney1.92

Onesteel Wire

5.33

15.29

Mannheim

10.18

BASF

44.98

23.95

San Jose-San Francisco, CA

1.73

Dolby Laboratories

48.55

38.69

Shenzhen-Hong Kong

2.08

Huawei

79.45

85.53

Mississauga, ON

4.05

Flextronics AP

7.51

85.67

Gent

2.70

Universiteit Gent

8.91

13.95

Cologne

5.50

Bayer

36.76

29.91

Barcelona

2.19

Laboratorios del Dr. Esteve S.A.

14.83

32.62

Hsinchu

7.86

MediaTek

55.61

8.11

Madrid

1.25

CSIC

11.30

37.69

San Jose-San Francisco, CA

9.93

Intel

76.00

79.81

Houston, TX

2.10

Rice University

100.0025.90

Shenzhen-Hong Kong

3.60

Huawei

91.60

22.38

Turin

1.13

Pirelli Tyre

30.35

20.28

San Jose-San Francisco, CA

3.99

Intel

7.59

78.28

Basel

2.30

F. Hoffmann-La Roche

13.27
CONTINUED

Special Section: Cluster Rankings

73TABLE S-1.4

Top collaborating entities by cluster, continued
Scientific publishing collaboration
Rank

Cluster name

Economy(ies)Top scientific collaborating cluster

Share, %Top collaborating organization

51

Montréal, QC

CAToronto, ON

3.94

University of Toronto

52

ChengduCN

Beijing

7.46

Chinese Academy of Sciences

53

MannheimDE

Cologne

5.91

University of Cologne

54

IstanbulTR

Ankara5.06

Hacettepe University

55

Copenhagen

DK

Århus

4.79

Aarhus University

56

Atlanta, GA

US

Washington, DC-Baltimore, MD

4.99

Johns Hopkins University

57

Rome

IT

Milan

5.60

University of Milan

58

Cambridge

GB

London10.73

University of London

59

São PauloBR

Rio De Janeiro

2.99

Universidade Federal do Rio de Janeiro

60

TianjinCN

Beijing

9.34

Chinese Academy of Sciences

61

Cincinnati, OH

US

Washington, DC-Baltimore, MD

4.07

Johns Hopkins University

62

Nürnberg

DE

Munich

9.44

University of Munich

63

Pittsburgh, PA

US

Washington, DC-Baltimore, MD

4.30

Johns Hopkins University

64

Dallas, TX

USNew York City, NY

4.61

Columbia University

65

Bengaluru

IN

Delhi

2.40

CSIR

66

Ann Arbor, MIUS

Boston-Cambridge, MA

4.41

Harvard University

67

ChangshaCN

Beijing

5.61

Chinese Academy of Sciences

68

HelsinkiFI

Stockholm

3.32

Karolinska Institutet

69

Vienna

AT

Graz

2.37

Medical University of Graz

70

Delhi

IN

Pune

1.31

CSIR

71

OxfordGB

London12.14

University of London

72

Vancouver, BCCA

Toronto, ON

5.55

University of Toronto

73

Cleveland, OH

US

New York City, NY

3.93

Columbia University

74

Lyon

FR

Paris

19.11

APHP

75

Busan

KR

Seoul

26.06

Seoul National University

76

Phoenix, AZ

USWashington, DC-Baltimore, MD

3.79

Johns Hopkins University

77

AnkaraTR

Istanbul

5.04

Istanbul University

78

Ottawa, ON

CA

Toronto, ON

8.78

University of Toronto

79

Austin, TX

US

Houston, TX

3.81

UTMD Anderson Cancer Center80

QingdaoCN

Beijing

12.97

Chinese Academy of Sciences

81

SuzhouCN

Beijing

8.30

Chinese Academy of Sciences

82

Bridgeport-New Haven, CT

US

New York City, NY

7.29

Columbia University

83

BrisbaneAU

Melbourne

8.32

University of Melbourne

84

Hamburg

DE

Cologne

6.12

University of Bonn85

Grenoble

FR

Paris

15.85

CNRS

86

Lausanne

CH/FR

Zürich

5.93

University of Zurich

87

HarbinCN

Beijing

6.73

Chinese Academy of Sciences

88

ChongqingCN

Beijing

5.73

Chinese Academy of Sciences

89

Jinan

CN

Beijing

7.03

Chinese Academy of Sciences

90

Hefei

CN

Beijing

8.33

Chinese Academy of Sciences

91

Basel

CH/DE/FR

Zürich

7.78

University of Zurich

92

Manchester

GB

London8.03

University of London

93

ChangchunCN

Beijing

11.07

Chinese Academy of Sciences

94

St. Louis, MO

US

Boston-Cambridge, MA

4.13

Harvard University

95

Lund

SE

Stockholm

7.38

Karolinska Institutet

96

Columbus, OH

US

Washington, DC-Baltimore, MD

3.58

Johns Hopkins University

97

Mumbai

IN

Pune

2.11

University of Pune

98

Indianapolis, IN

US

New York City, NY

4.21

Columbia University

99

DublinIE

London2.49

University of London

100

Warsaw

PL

Kraków

3.37

Jagiellonian University

Source: WIPO Statistics Database, March 2019.
Notes: Patent filing and scientific publication shares refer to the 2013–17 period and are based on fractional counts, as explained in the text. Collaboration is basedon the locations of authors/inventors listed on the same article/patent. Codes refer to the ISO-2 codes. See page 17 for a full list, with the following addition:
TW = Taiwan, Province of China. CNRS = Centre National de la Recherche Scientifique, CSIC = Consejo Superior de Investigaciones Cientificas, CSIR = Council of
74

The Global Innovation Index 2019

Patent collaboration
Share, %Top patent collaborating cluster

Share, %Top collaborating applicant

Share, %80.05

New York City, NY

2.80

Interdigital Patent Holdings

41.02

32.60

Shenzhen-Hong Kong

1.24

Huawei

73.47

16.50

Frankfurt Am Main

10.81

BASF

25.02

16.01

Ankara0.41

Arcelik

21.92

89.74

Lund

1.37

Danmarks Tekniske Universitet

12.22

21.76

San Jose-San Francisco, CA

2.85

Stanford University

6.43

20.88

Cologne

2.45

Bayer

96.21

55.30

London2.83

British American Tobacco

9.31

30.80

Rio De Janeiro

1.31

Petrobras

20.65

25.00

Beijing

1.28

China Electric Power Research Institute

16.67

22.88

Frankfurt Am Main

2.57

Procter & Gamble Company

82.39

50.66

Munich

3.54

Siemens

58.26

30.78

Boston-Cambridge, MA

2.51

Berkshire Grey

17.44

15.18

San Jose-San Francisco, CA

3.73

Hewlett-Packard

17.20

10.25

San Jose-San Francisco, CA

5.33

Applied Materials

28.00

63.27

Detroit, MI

4.72

BASF

11.23

25.37

Basel

0.42

Novartis100.0057.86

Beijing

2.75

Broadcom

32.12

46.22

Graz

2.00

AVL List

21.15

40.65

Bengaluru

3.84

Mcafee

13.62

54.67

London

2.73

Sony

12.24

80.16

San Jose-San Francisco, CA

3.37

Genentech

6.45

12.65

San Jose-San Francisco, CA

1.08

Cisco Technology

23.30

26.28

Paris

8.28

IFP Energies Nouvelles

22.25

15.30

Seoul

21.29

Samsung Electronics

8.84

24.62

Portland, OR

6.03

Intel

94.14

11.74

Istanbul

3.16

Santa Farma Ilac

30.02

76.62

Dallas, TX

2.74

Blackberry

51.43

15.98

San Jose-San Francisco, CA

7.32

Applied Materials

9.51

45.07

Shanghai

0.52

Dow Global Technologies

74.23

42.80

Beijing

1.74

Jiangsu Huadong Inst. of Li-Ion Battery

74.93

14.93

New York City, NY

5.71

Bristol-Myers Squibb

25.73

24.30

Melbourne

1.70

University of Queensland

10.59

15.45

Cologne2.40

Henkel

35.93

30.03

Paris

5.99

CEA

39.14

32.16

Genève5.00

NESTEC

18.14

17.84

Beijing

3.61

MediaTek

50.84

24.88

Shenzhen-Hong Kong

1.30

Huawei

83.08

22.11

Beijing

1.13

Nokia

23.13

36.97

Shenzhen-Hong Kong

3.27

Huawei

76.16

44.58

Zürich

3.71

Abb Technology Ag

8.13

51.13

Cambridge

2.46

AstraZeneca

28.01

58.97

Beijing

3.75

Peking University

22.07

67.33

Seattle, WA

2.62

Elwha LLC

75.48

64.40

Stockholm

9.26

LM Ericsson

81.90

27.09

Cincinnati, OH

2.48

Procter & Gamble Company

36.43

23.22

Bengaluru

3.95

Unilever

25.91

12.66

Boston-Cambridge, MA

1.17

Constellation Pharmaceuticals

13.32

50.08

San Jose-San Francisco, CA

1.62

Hewlett-Packard

25.04

42.84

Kraków

1.91

ABB Technology

20.10

Scientific & Industrial Research – India, APHP = Assistance Publique Hopitaux Paris (APHP), KAIST = Korea Advanced Institute of Science & Technology,
CEA = Commissariat a L’Energie Atomique et aux Energies Alternatives.

Special Section: Cluster Rankings

75

FIGURE S-1.3

Regional clusters: Asia

Beijing
Seoul
Tokyo Yokohama
DaejeonOsaka - Kobe
- Kyoto
NagoyaXian

NanjingShanghai

Wuhan

Hangzhou

Cluster Rank
Taipei1 - 2526 - 50

Guangzhou

51 - 75
76 - 100

Shenzhen Hong Kong
0250

Source: WIPO Statistics Database, March 2019.
Note: Cluster rank is based on total share in patent filing and scientific publication using fractional counting and the publication period of 2013-2017,as explained in the text.

76

The Global Innovation Index 2019

500 kmFIGURE S-1.4

Regional clusters: Europe

Stockholm
MoscowAmsterdam Rotterdam

BerlinEindhoven
LondonBrussels Cologne

Frankfurt Am
Main

Paris
Stuttgart
MunichZürichMilanBarcelona
MadridCluster Rank
1 - 2526 - 50
51 - 75
76 - 100

0250

500 kmSource: WIPO Statistics Database, March 2019.
Note: Cluster rank is based on total share in patent filing and scientific publication using fractional counting and the publication period of 2013-2017,as explained in the text.

Special Section: Cluster Rankings

77

FIGURE S-1.5

Regional clusters: Northern America

Seattle, WA
Portland, OR
Minneapolis,
MN

Toronto, ON

BostonCambridge, MA

New York City,NY
San Jose
San Francisco,CA

Chicago, IL

Denver, CO

Washington, DC
Baltimore, MD

Los Angeles,
CA

Raleigh, NC

San Diego, CA

Houston, TX

Cluster Rank
1 - 2526 - 50
51 - 75
76 - 100

0250

500 kmSource: WIPO Statistics Database, March 2019.
Note: Cluster rank is based on total share in patent filing and scientific publication using fractional counting and the publication period of 2013-2017,as explained in the text.

78

The Global Innovation Index 2019

Philadelphia,
PASpecial Section: Cluster Rankings

79

80

The Global Innovation Index 2019

CH AP T E R 2

THE ECONOMICS OF
HEALTH INNOVATION:LOOKING BACK AND
LOOKING FORWARD
Bhaven Sampat, Columbia University

Technological progress is widely recognized as a source oflong-run economic growth. Some forms of progress, however, arenot captured by standard growth statistics. Health improvements
are one example. The Nobel-Prize winning economist William
Nordhaus has calculated that the economic value of increases
in longevity in the last 100 years is as large as measured
economic growth in all other sectors. He illustrates the basic
point with the following thought experiment:1
Consider the improvements to both health and non-healthtechnologies over the last half century (say from 1948 to1998). Health technologies include a variety of changes
such as the Salk polio vaccine, new pharmaceuticals, joint
replacement, improved sanitation, improved automotive safety,
smoke-free workplaces. Over this period, life expectancy
at birth increased from a little above 68 years to a little lessthan 76 years. Non-health technologies were also wide-ranging
and included the jet plane, television, superhighways, VCRs,
and computers....
Now consider the following choice. You must forgo either thehealth improvements over the last half-century or the nonhealth improvements. That is, you must choose either (a) 1948
health conditions and 1998 non-health living standards or(b) 1998 health conditions and 1948 non-health living standards.
Which would you choose?
If you choose (b) or have difficulty choosing, you basically agreewith the idea that improvements in health are as valuable as
improvements in all other sectors combined. While these estimates
were based on data from the United States of America (U.S.),
similar health improvements were observed in other high-income
countries over the past half century. Lower income countries
also saw significant improvements in standard indicators ofhealth status during the 1950s, 1960s, and 1970s.2

Looking back: the role of innovationin health improvement
Nordhaus and others have suggested that the creation anddiffusion of new medical knowledge and technologies—medical
innovation—were important sources of these health improvements.
What is medical innovation? While this is a more complicatedquestion than it may seem, our focus here is on the incorporation
into practice of new drugs, diagnostic methods, procedures,and devices that improve healthcare, as well as of new medical
knowledge that shapes individual health behaviors, clinicalpractices, and informs public health policies and interventions.
Over the first half of the twentieth century, with some important
exceptions,3 new physical technologies had a limited role in
improving health. Indeed, one influential scholar has argued
that most historical improvements in health had little to dowith healthcare or medical interventions at all, instead reflecting
broader socioeconomic factors such as higher incomes,
improved nutrition, and better sanitation.4
The antibiotics and sulfa drugs developed during the 1930s and1940s were the first miracle medical technologies.5 The diffusionof these drugs, first in rich countries and then globally, led to
sharp decreases in morbidity and mortality in the 1940s and 1950s.
Many new antibiotics and other new drugs, vaccines, and treatments
were introduced in the two decades after World War II—often
considered the “golden age’’ of medical innovation. By about
1960, antibiotics and vaccines virtually eliminated known infectious
diseases as a major source of mortality in developed countries.
There has been continued improvement in health since thattime. In most high-income countries, the main source of thesegains has been a reduction in cardiovascular disease mortality.

Chapter 2

81Even though cardiovascular disease remains a leading cause ofdeath, mortality fell sharply in the second half of the twentiethcentury. In the U.S., mortality from heart disease has fallen by
about two-thirds since 1950, leading to a 5-year increase in life
expectancy for the average 45-year-old.6 Much of this has comethrough new knowledge of risk factors, which led to behavioral
changes—such as less smoking and better diets—and disease
prevention. Estimates suggest that about one-third of the gains
are due to drug innovation, one-third to prevention, and thefinal third to high-tech medical treatments such as cardiac
catheterization, bypass surgery, angioplasty, and others.7 In
reducing cardiovascular mortality, both medical technologies
and new medical knowledge play an important role.
Another major source of morbidity and mortality is cancer. Cancer
deaths have not declined in most countries in the postwar era,
despite billions of dollars spent globally on the “war on cancer.”
One reason that deaths have not declined is competing risks:with fewer people dying of cardiovascular disease, more develop
cancer. However, despite decades of frustration, there havebeen recent signs of progress in reducing mortality fromsome cancers, driven by screening technologies, such as
mammography for breast cancer and colonoscopy, and by
behavioral changes. In addition to better prevention, there havebeen new treatments as well, including surgeries, radiation,
chemotherapy, and new drugs.8 In an approach similar to
Nordhaus, economists have found that improvements in cancer
survival generated social benefits valued around US$1.9 trillion
in the U.S. between 1988 and 2000.9
The HIV/AIDS epidemic threatened to negate some of the
improvements in global life expectancy in the 1980s. For thisdisease, new technologies—especially antiretroviral therapy
and follow-on drugs—have been crucial to making it a treatabledisease. Economic estimates suggest that, by the end of thelast century, new HIV/AIDS drugs generated US$1.4 trillion ineconomic value in the U.S.—a figure that would be significantly
higher if global gains were included.10 As with cancer andcardiovascular disease, more needs to be done to reduce thetoll of HIV in developing countries in particular, yet the responseto the HIV/AIDS epidemic presents perhaps the strongest
recent example of the benefits from new medical technologies.
The basic empirical approach in many of the assessments
above is to put an economic value on improvements in individual
health outcomes, such as mortality and/or quality of life, thatare linked to medical innovation. But there are other benefits
from medical innovation as well. A study of AIDS treatment
in sub-Saharan Africa shows that beyond the health benefits,these drugs helped improve labor force participation, childhood
schooling, and other economic outcomes that influenced
productivity and economic growth.11 Beyond the value of
reduced mortality and improved productivity, new medical
technologies also improve the quality of life. Depression
treatments and hip replacement, for example, have dramaticallyreduced morbidity and improved quality of life. Some new
medical technologies, such as birth control pills, have completely
revolutionized the labor force and social dynamics.12

82

The Global Innovation Index 2019

In many cases, these advances have not come cheap. New
medical technologies are widely recognized as major driversof healthcare costs, perhaps because of the unique demandfor improved health—in medicine invention may be the motherof necessity. There is now a large body of literature on whether
the “technological imperative” in medicine is worthwhileand sustainable.13 Overall, medical innovations seem to becost-effective, and the social value of the technologies surveyed
above—HIV treatments, cardiovascular improvements,
infectious disease interventions— are orders of magnitude larger
than their measured costs.14 But there are many treatments
where cost and value are out of line, which may account fora large share of health expenditures by patients and insurers.15
Even technologies that are valuable from a clinical perspective
can create budgetary pressures and affordability problems
for governments and patients. The recent policy debate abouthigh-cost prescription drugs is but one vivid illustration of
the tension between new technologies, prices/access, andbudgetary impact.

Unevenness and potential
While medical knowledge and technology have been essential
to generating valuable health improvements, progress has been
uneven.16 Many cancers remain untreated and diseases—from
Alzheimer’s to neglected tropical diseases and mental healthdisorders—lack effective prevention, treatment, and/or management
and continue to drive morbidity and mortality globally. Perhaps
worse, antibiotic resistance, rising obesity, and emerging
infectious diseases could reverse some benefits of the past.
The potential economic benefits from new approaches topreventing and treating disease are significant. In a framework
similar to that used by Nordhaus, economists have estimatedthat in the U.S., a 10% reduction in mortality from heart disease
would generate US$6 trillion in value to current and present
generations.17 Reductions in morbidity and mortality fromother major diseases would yield benefits of similar orders ofmagnitude. Economists have also calculated that delaying aging
by 20% would generate social benefits of over US$7 trillion in
the U.S.—even as it would create serious fiscal challenges dueto the need for supporting a growing, elderly population.18
Economically valuable health gains and productivity improvements
could also come from reducing the burden of neglected tropicaldiseases, continuing progress in HIV/AIDS, combating antibiotic
resistance, and improving the efficiency of healthcare delivery.

Can future medical innovation matchthe gains from the past?
It is important to remember that innovations in medical careare not the only route to improving health status and achieving
potential gains, and in some contexts, they may not even be
the most productive. Promoting broader economic development,
reducing income disparities, and improving educational
attainment could also generate health improvements, independentof medical care. As discussed above, these “social determinants”
have been extremely important in the past, and poverty,

education, and diets continue to be associated with healthoutcomes today. Even as we focus on new technologies, thediffusion and adaptation of existing technologies and practices
may also pay large dividends.

medical innovation system itself.

That said, the scope for new medical knowledge and technology
to improve health and generate value is tremendous. But thisraises another question: Is medical innovation up to the task?
While the demand for innovation is high, there is concern thatthe golden years may be behind us—whether measured by the
decline in major medical advances by year,19 drug approvals,20
or research productivity.21 There is no consensus explanation forthese trends. They may reflect that scientific and technologicalopportunities have dried up, ideas are getting harder to find, orthe “low hanging fruit” has been picked. Perhaps more troubling,
they may also reveal fundamental structural problems with thebiomedical innovation system and incentives facing both public
and private sector researchers.22• innovations must help prevent or treat diseases with a highdisease burden, or at least eventually spill over to diseases
and health problems with broad prevalence;• treatments or interventions focused on specific diseases
would have a cumulative impact, such as when genetic
therapies target individual diseases;• beyond individual disease-specific interventions, the processof innovation would be transformed by new general-purpose
technologies, such as AI, machine learning, gene editing,cell therapy, and synthetic biology that open up new areasof exploration and invention;28 or• new technologies (e.g., digital technologies) facilitate broadsystemic improvements in healthcare delivery, loweringcosts and/or improving outcomes.

It is interesting that, at the same time, there is also tremendous
enthusiasm about the future of medical science and technology.
In the past few years, we have seen the launch of new hepatitis
C treatments that essentially cure the disease—for those who
can afford them—and cures for some cancers.23 New areasof science and technology—cancer immunotherapies, gene
editing, improvements in imaging and diagnostics, and manyothers—could transform prevention and treatment of specificdiseases or healthcare in general. At the same time, somebelieve these new approaches may ultimately have limited
impact on population health and potentially high costs. For
example, echoing the historical debates about the role ofhealthcare in health alluded to earlier, public health scholars havequestioned whether current levels of investment and enthusiasm
in personalized medicine are the best route forward for
improving population health, as opposed to greater investment
in known behavioral and structural interventions.24 Somewarn that over-enthusiasm and hype may surround the new
fields of medical science and innovation, as is also common for
emerging technologies.25
Interestingly, much of the discussion about innovation in healthtoday—in both high- and low-income countries—is not about
new pills or products, but instead about improving healthcaredelivery.26 There is also excitement about new technologies andorganizational innovations that may “disrupt’’ existing businessmodels—and, in particular, reduce costs without sacrificing
value—though, at the same time, concerns exist about the
obstacles to developing and diffusing such innovations inexisting healthcare systems.27 These trends reveal not only
widespread dissatisfaction with current healthcare delivery
models in many countries but also demand for new technologies
that lead to cost-effective care. Interestingly, many of these
new technologies are enabled by advances from anothersector—information and communication technology. Information
technology (IT) could have particular relevance in developing
countries and resource-poor locations. Beyond their impact on
healthcare delivery, new IT approaches—in particular, artificial
intelligence (AI), machine learning, and big data—may also
reshape drug discovery, new treatment evaluations, and theConceptually, for medical innovations to have major economic
impact, one of several things will have to be true:

Predictions are hard. History teaches us that “the vast majority
of attempts at innovation fail.”29 Enthusiasts making strong
statements that any technology will transform, revolutionize, or
disrupt healthcare should keep this in mind. However, history
has also demonstrated an “inability to anticipate the future
impact of successful innovations, even after their technicalfeasibility has been established.”30 Nathan Rosenberg andother economic historians have emphasized that technologicalforecasting is very difficult, since the success and economic
impact of individual technologies depend, among other factors,
on the rate and direction of incremental innovation following
introduction, improvements in complementary enabling
technologies, the scope for learning by doing and using, andthe state of broader technological systems.31 History shows thatnew technologies, including general purpose technologies, cantake a long time to generate economic impact, and their ability
to do so is contingent on many broader socio-economic factors.32
Technical advances are often enabled by complementaryadvances in other fields, some of which are completely
unanticipated.33 Complicating things further, whether a technology“works” is often not known until it is embedded in clinicalpractice for a large number of patients.34
Although predicting the impact of specific areas of medical
innovation is difficult, the potential for new medical innovation
to generate valuable gains going forward certainly seems
high, given the large value of health improvements and theunevenness of progress to date. Whether these potential gains
are realized will depend on factors such as whether investments
in innovation are aligned with social value, the pool of scientificand technological opportunities for advancement in different
fields, the scalability of individual technical advances, andthe extent to which healthcare providers and healthcare
systems are incentivized to adopt and diffuse valuable newtechnologies. The costs of these innovations will determine
affordability and ultimate benefit to patients.

Chapter 2

83

Looking ahead: governing the future

5World Intellectual Property Report (WIPO), 2015.

Policymakers will face trade-offs in supporting and regulating
new medical innovation. These include, among others:

6

Cutler et al., 2003.

7

Cutler et al., 2003.

• Public funding: How much should the government bespending on research? What is the right balance between
spending on fundamental science and more clinical andapplied activities? How should public funds be allocatedacross different diseases and fields, between new scienceand old approaches?
• Human capital: What kinds of educational and otherinvestments are needed to enable the development andeffective diffusion of new medical innovations?
• Patents and intellectual property: How should national
patent laws and global governance regimes be designed topromote innovation and access/diffusion?
• Regulation: How strong should regulations on new healthtechnologies be to balance risk, including potential
ethical considerations, against benefits from innovationand incentives/costs of entrepreneurship?
• Evaluation: How and when should policymakers evaluate
the cost and benefits of new medical technologies to enable
the creation and diffusion of safe, effective, high-value care?
• Costs: What role should governments have in influencing
prices? How should they do so, and how would thesepolicies affect the rate and direction of health innovationand diffusion?
• Diffusion: How should health and health innovation systems
be designed to promote broad diffusion of, and access to,valuable existing technologies and organizational models?
How should systems be designed to encourage “disadoption”
of technologies that don’t work or are too costly?

8

Cutler, 2008; Lichtenberg, 2013.

9

Lakdawalla et al., 2010.

10

Philipson et al., 2006

11

Thirumurthy et al., 2012.

12

Bailey, 2006.

13

Cutler et al., 2001

14

Cutler et al., 2006.

15

Cutler, 2005.

16

Nelson et al., 2011.

17

Murphy et al., 2006.

18

Goldman et al., 2013.

19

Casadevall, 2018.

20

Scannell et al., 2012.

21

Bloom et al., 2017.

22

Sarewitz, 2016; Casadevall, 2018; Gittelman, 2016; Scannell et al.,
2012.

23

Casadevall, 2018.

24

Bayer et al., 2015.

25

Deyo et al., 2005.

26

Herzlinger, 2006.

The future of health innovation, and the role of medical innovationin improving health outcomes going forward, will depend on
the policies and institutions created by national and global
actors to support research and innovation. There are no easyanswers to the questions above; they are the subject of considerable
research by economists and others and in many cases involve
starkly competing values and objectives. Nonetheless, they areimportant issues for policymakers and the public to consider
carefully and deliberately—given the transformative economic,
social, and health impacts that new medical technologies
have had historically and the enormous potential value of further
health improvements for current and future generations.

27

Hwang et al., 2008; Cutler, 2011.

28

Mokyr, 2018.

29

Rosenberg, 1998.

30

Rosenberg, 1998.

31

Rosenberg, 1969.

32

David, 1989.

33

Rosenberg, 1969.

34

Gelijns et al., 2001.

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Notes:
1

Nordhaus, 2002.

2

Cutler et al., 2006.

3

Cutler et al., 2005.

4

McKeown, 1976; However even in the early twentieth century, newmedical knowledge, including the germ theory of disease, helped
buttress the sanitation and hygiene movements that contributed toreductions in infectious disease mortality that accounted for most of the
global decline in mortality over this period; Mokyr, 1993.

84

The Global Innovation Index 2019

Bailey, M. J. (2006). More Power to the Pill: The Impact of Contraceptive
Freedom on Women’s Life Cycle Labor Supply. The Quarterly Journal of
Economics, 121(1), 289-320.
Bayer, R., & Galea, S. (2015). Public health in the precision-medicine era. New
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Goldman, D. P. et al. (2013). Substantial Health and Economic Returns from
Delayed Aging May Warrant a New Focus for Medical Research. Health
Affairs, 32(10), 1698-1705.
Herzlinger, R. E. (2006). Why Innovation in Health Care is so Hard. Harvard
Business Review, 84(5), 58.
Hwang, J., & Christensen, C. M. (2008). Disruptive innovation in health caredelivery: a framework for business-model innovation. Health Affairs,
27(5). 1329-1335.
Lakdawalla, D. N. et al. (2010). An economic evaluation of the war on cancer.
Journal of Health Economics, 29(3), 333-346.
Lichtenberg, F. R. (2013). Has Medical Innovation Reduced Cancer Mortality?.
CESifo Economic Studies, 60(1), 135-177.
McKeown, T. (1976). The Role of Medicine: Dream, Mirage, or Nemesis?
London, England: Nuffield Provincial Hospitals Trust.
Mokyr, J. (1993). Technological progress and the decline of European mortality.
The American Economic Review, 83, 324-330.
Mokyr, J. (2018). The Past and the Future of Innovation: Some Lessons from
Economic History. Explorations in Economic History, 69, 13-26.
Murphy, K. M., & Topel, R. H. (2006). The Value of Health and Longevity.
Journal of Political Economy, 114(5), 871-904.
Nelson, R. R. et al. (2011). How Medical Know-how Progresses. Research
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CH AP T E R 3

TRENDS IN HEALTHCAREAND MEDICAL INNOVATION
Pratap Khedkar and Dharmendra Sahay, ZS Associates

Global healthcare’s significant progress in the last several
decades can be attributed to advancements in biologicalscience, which were made possible by innovative medicines,
medical devices, and health provider infrastructure. Whilebiotechnology will continue to contribute, due in large part toa combination of genomics, microbiomics, and proteomics,
information technology will drive the next wave of healthcare
evolution. As a result, healthcare will benefit from rapid
advancements in digital technology and artificial intelligence.
The primacy of the electron over the molecule impacts all aspectsof health, from helping patients stay healthy to discovering
more precise and cost-effective solutions for diagnosis andtreatment, and improving outcomes. Furthermore, while theinnovations of previous decades disproportionately benefited
the developed world, IT-led innovation should give a much-needed
boost to providing basic healthcare at a greater scale and reducesignificant gaps that exist between developed and developing
countries today. That said, the combined innovation inbiotechnology and information technology will provide
individualized solutions for the developed world by discoveringcures and treatments for niche and unmet medical needs.

Drivers of innovation
Five key underlying trends will bring significant change to global
healthcare. Of these trends, three are technological and two
are related to human behavior and preferences. Many of thesetrends are reaching maturity in other industries, giving healthcarea chance to leverage those that are best suited for the industry.

1. An information revolution is taking place globally.
Broadband access and smartphone usage are becoming
ubiquitous throughout the world, with 90% of the developed
world and 41% of the developing world on broadband.1
Such access enables not only the transmission of information
to the patient but also the transmission of data from thepatient to the provider, with room for future growth. The
availability of smartphones, projected to reach 40% of the
global population by 2021, also enables providers to gather
patient details and deliver treatment remotely.2 In addition
to advances in communication, the collection of healthcare
data has also exploded. Two examples are the sequencing,storing, and studying of individual genomes—expected
to cost US$1 by 20253—and the penetration of electronic
health records (EHR), which currently exceeds 80% in thedeveloped world.4 Both have been driven largely by policy
and cost.
2. The healthcare industry is gathering all the ingredients tosucceed with artificial intelligence (AI). In its applications,
AI needs rich data on the individual, cross-sectional data
across a population, affordable computing, and accurate
non-linear models. Prior waves of AI were unremarkablebecause they were missing some of these key ingredients.5
But the information revolution has put all of the pieces into
place, making it possible for healthcare practitioners to
predict and diagnose diseases earlier and more accurately,
select the most effective treatment, and close the loop tonudge human behavior. This will enable AI to serve as a
substitute for hard-to-find clinical skills and knowledge,
when appropriate.

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3. Deeper understanding of science is enabling more targeted
treatments. As more genomic data becomes available andour understanding of human biochemistry improves, thepush is on to design custom products for biomarker-tagged
populations, offering significant efficacy all the way up
to a curative therapy. In fact, 73% of the compounds undertrial in oncology are associated with biomarkers,6 and thefuture will involve many highly effective—and expensive—
niche medicines.7
4. Consumerism is on the rise. Particularly in the developed
world, healthcare consumers have assumed a larger shareof the financial burden, have access to better information
for comparisons, and have developed higher expectationsof a good experience. Technologies like AI combinedwith a push for transparency are making it feasible for
consumers to demand metrics on provider quality and price.
At the same time, the emphasis on experience is encouraging
providers and manufacturers to offer better services.
5. Healthcare’s traditional business models are evolving.
Over time, the fragmentation of healthcare into different
sectors—such as payers, insurers, providers, andmanufacturers—has made the healthcare industry inefficientand rife with misaligned incentives. Many of these sectorial
distinctions are now beginning to blur in the U.S., with
employers getting into health management, insurers
investing in care delivery, and providers exploring
manufacturing opportunities.8 Meanwhile, horizontal
consolidation continues as well. Public-private partnerships

are a powerful force here because the public sector has asense of mission, the power to mandate, and the perspective
to set policy for an ecosystem, whereas the private partners
have the resources, the technology, and the expertise.
These five drivers are combining to create change, but to whatend? The World Health Organization (WHO) defined healthin its broader sense as “a state of complete physical, mental,
and social well-being and not merely the absence of diseaseor infirmity.”9 At an individual or population level, this goal canbe broken down into four main areas: diagnosis, treatment,
outcome, and wellness (see Table 3.1 for a summary ofinnovations in these four steps). As each of these areas
continues to be influenced by the information revolution
and technological advancements, we’ll get closer to creatinga holistically healthy population.
Diagnosis
To improve the way that patients are diagnosed on a global
scale, healthcare providers need to make tests and toolkits
available to patients, have the medical skills to administer andinterpret the tests, and be able to do so cheaply. Thanks inpart to the prevalence of smartphones and broadband, we cantele-diagnose patients and send the data to an interpreter rather
than requiring patients to travel to the access point. Technologicaladvancements also are seeking to streamline the ongoinghealth tracking aspect of diagnosis by making follow-up tests,
measurements, and other onerous parts of chronic conditions
more convenient and less expensive. Because it’s not enough

TABLE 3.1

Current innovations in the four steps to a healthy planet
Diagnosis• Two-way datatransmission fromthe patient• Wearable tech formonitoring

Treatment• Focused factories(industrialization)• Digital therapeutics• AI for treatment selection• AI for diagnosis,
reducing skill needed• Data on social
determinants of health• Telehealth, reducing
need for proximity• Drug discovery in silica• Faster global trials• Cell and gene therapies• Oncology advances• Precision medicine

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The Global Innovation Index 2019

OutcomeWellness• Real-world evidence• Prevention incentives• Value-based care

• Interventions for social
determinants of healthto produce continuous data if the system cannot consume it,
AI-based technologies are stepping in to digest the data. AI,of course, is “always on” and is looking for signals in data in a waythat human reasoning might not be able to emulate, potentiallymaking AI-enabled diagnoses more accurate and effective.
Moreover, AI-powered diagnoses could take the place ofhuman-driven diagnoses in some cases. An algorithm can detectpneumonia by listening to your cough on the phone,10 whereasa human would want to listen to your heart through your lungs.
This is not just moving the process of diagnosing to a remotelocation but reducing the need for human expertise altogether.
Treatment
Artificial intelligence can leverage data to select the mosteffective treatment, though it cannot by itself make that treatment
option more affordable. But as business models change,
providers are beginning to invest in specialized care—creating
focused factories that treat a narrow problem repeatedly andthat drive costs down. Examples of this range from the Mayo
Clinic in the developed world to Narayana Health in India.11
Vertical integration—especially between payers, providers, andinsurers—makes it worthwhile by aligning incentives so thatcheaper treatments aren’t equated with revenue losses.
Increasingly, social determinants of health, which include
attributes that drive 60% of your health and go beyond yourgenome and medical history,12 are making the enablement ofhealth and wellness more effective in the long run. For example,
food insecurity and loneliness are bigger drivers of morbidity
than drugs in the elderly population,13 and only a cross-sector
entity would have the resources and influence to solve that.
Pharmaceutical drugs are a key aspect of treatment. One trend
here is invention efficiency: drug development costs roughly
double every 10 years.14 Can the development be sped up
or automated? A third of all AI investments in healthcare areprojected to be in drug discovery,15 specifically using computer
simulation to find better molecules faster. Companies are also
beginning to leverage AI and data to reduce clinical trial costs
and waste, though progress has been slower than desired.
The other trend in drug creation is precision medicine, which
focuses on increasing efficacy by designing treatments fora specific patient population.
OutcomePricing pressures in the U.S. and the developing world arenecessitating a shift to value- and evidence-based medicine.
The overarching question is, are we getting good value for thecountries’ total healthcare spending, and at what percentage
of GDP is it affordable? The value needs to include the obvious
medical metrics such as disease indicators, morbidity, mortality
rates, and lifespan. In the developed world, consumers need tobe satisfied with the experience and patient-reported outcomes,
as patients begin to demand much more than sick care. The
shift from cost to value is happening slowly because incentives
aren’t well aligned. Healthcare stakeholders need an objective
and comprehensive approach to evaluate the impact oftreatment in the real world—not in an ideal, clinical trial world.
The collection of healthcare data from actual patient treatments

is making this real-world evidence generation possible, andinvestment and interest in real-world evidence have spiked
threefold in the last 10 years.16
Wellness
We can expect to see continued taming of diseases during thenext decade, but the WHO’s broader goal of well-being—andavoiding all of these interventions—is coming into focus in thedeveloped world. Will we soon be able to “predict and prevent”
as opposed to “react and revive”? The biggest wellness trends
are in addressing social determinants of health—for example,
identifying and eliminating food deserts and promoting
vaccination penetration—and individual incentives, such as
nudges for exercise, proper nutrition, and data collection.17
Information technology plays a secondary role to the change
management challenges that healthcare will face when turning
its focus to wellness efforts.

The promise of global health
There is universal dissatisfaction with the healthcare status quo,
but the challenges and unmet needs vary widely between
the developed and developing worlds. Regardless, an IT-led
healthcare innovation trend promises to address the needsof patients across the globe, but in different ways (summarizedin Table 3.2).
In the developed world, the rising cost of healthcare has beena prominent subject lately, but other issues such as medical
errors, overworked healthcare professionals, and poor patient
experiences are equally important. In contrast, the developingworld is challenged to provide basic healthcare beyond a small
urban segment, with limited government budgets and a severe
shortage of healthcare professionals and infrastructure. The
contrast is stark. For example, while India and Africa combined
share nearly 45% of the global disease burden,18 they employ
less than 5% of the world’s healthcare professionals.
The next wave of healthcare innovation ideally will connect all
aspects of individual and population health, including diagnosis,
treatment, outcome, and wellness. It will also impact the fourmain elements of the healthcare delivery system: cost, access,outcome and customer experience. And because healthsystems have different needs in different parts of the world, thelevel of impact will vary.
Impact in the developed world
In the developed world, innovation is likely to have the greatest
impact on reducing costs, improving outcomes, and moving
to targeted and individualized treatment. We’re also likely to see
an improvement in the experiences for patient and healthcare
professionals.
On the cost front, manual processes and health data silos aresome of the key drivers for wasted spending. It is estimated thatin the United States of America (U.S.) alone, wasted spending
exceeds US$1 trillion annually.19 In recent years, there has been

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TABLE 3.2

The four elements of the healthcare delivery system will impact thedeveloped and developing worlds differently
Level of impact and potential solutions
Element of the healthcaredelivery system

Reduced cost

Developed
world

Developingworld

Impact: highImpact: high• Reduce administrative cost with automation• Scale basic healthcare without
proportionate increase in cost

• Reduce waste with diagnostics andmore targeted treatment• Reduce drug development cost with drug
development in silica and precision medicine
Improved healthcare
access

Impact: moderate

Impact: very high

• Provide better healthcare support inremote areas and convenience withtelemedicine• Provide platform-based basic healthcare
to a large population using a combinationof universal electronic health record (EHR)
systems and mobile health applications

Health outcome

Impact: highImpact: moderate• Raise health awareness with wellness
applications• Improve health outcomes for therising middle class• Improve diagnosis with AI-based
diagnostics and targeted treatments• Move to value-based healthcare where
outcome is the new currency of successand focus for healthcare players• Make treatments more targeted andindividualized with move to precision
medicine
Customer experience

Impact: highImpact: low• Improve consumer experience with
reduced wait time, improved long-term
engagement• Recognize that customer experience isimportant to a small percentage of theurban population in a largely cash market

a surge in start-ups promising to reduce inefficiencies using
intelligent automation. These range from intelligent schedulingand revenue booking systems to AI-based virtual assistants
that can capture patient stories into electronic health records
systems. Moreover, two-thirds of doctors would like AI to help
with workflow management, administrative assistant tasks, andpatient experience analysis.20
The high cost of drug development is also a source of rising
healthcare spending. AI can speed up drug discovery (morethan a third of AI investment in healthcare is in this space15), cut
R&D costs, decrease failure rates in drug trials, and eventuallycreate better medicines. Artificial intelligence also will help
reduce clinical trial costs and timelines by not just predicting
trial enrollment and duration, but also making them adaptive.

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The Global Innovation Index 2019

Remote monitoring can make clinical trials more patient-centric
and thereby help to cut a 30% abandonment rate.21
Another trend in the developed world is the move from a
fee-for-service to a value- or outcome-based care model.
As patient data becomes richer and more complete, the ability
to measure the outcome has improved significantly. This shift
likely will encourage a “holistic” treatment team approach tocare in which parties will be paid for providing better care—outcomes and satisfaction—at a lower cost.
The current “react and revive” approach to healthcare isdesigned to help the sick get better as opposed to the “predictand prevent” approach in which the focus is on helping people
stay healthy. A focus on wellness and preventive measureshelps to delay the onset of disease, and self-diagnosis tools
help to reduce the dependency on healthcare systems forongoing health maintenance. More precise diagnosis augmented
with automated expertise will significantly reduce onerous tests
that are currently conducted to identify and monitor disease
conditions.

China is turning to AI-based technologies to provide better
healthcare, especially in rural areas where doctors are relying
on perceptual senses, like vision and hearing, to gather
information about patient health.28 In India, Arvind Eye Care is
working with Google Brain to detect signs of diabetes-related
eye disease by analyzing photographs.29

Care is also likely to move to more customization, as treatments
can be targeted for individual genetic profiles and biomarkers.
Pharmaceutical companies are making large investments inprecision medicine to create more targeted and niche therapies
that are angling to replace mass-market medicine.22

To offer platform-based healthcare access at scale, countries
will need mobile health, telemedicine, and AI to integrate with
universal patient health records. This would help healthcare
access evolve from acute diagnosis and treatment to thedeployment of preventive measures and the managementof chronic diseases. Encouraged by the success of Aadhaar,a biometric-based universal identification system for 1 billion
people,30 India is embarking on an ambitious project called
Ayushman Bharat to provide health insurance to 100 millionfamilies.31 One goal of such a program will be to develop a
database of EHR records for registered patients. China isembarking on a similar effort with a Precision Medicine Initiative
to sequence the genomes of 100 million individuals by 2030.
But there are multiple challenges to overcome in building
a universal EHR database, and it’s likely to be a while before
we see material progress in this area.

Poor patient experience is another major source of dissatisfaction.
In the U.S., patients wait over 24 days for scheduled
appointments and have to provide the same information multiple
times to different healthcare professionals.23 Healthcare
stakeholders are increasingly using virtual and augmented
reality to make the patient experience more engaging andinteractive. These technologies are being integrated into patient
treatment and engagement efforts, enhancing the ability to
improve patient outcomes.
Impact in the developing world
In the developing world, the biggest unmet need is providing
basic and affordable healthcare at scale. The last decade has
seen a significant increase in government focus on healthcare,including several mobile health, telemedicine, and AI-based
initiatives in China, India, and some African countries. China has
already edged closer to Europe in leading health indicators,
while Africa still lags far behind and India is somewhere in
between. As an example, the leading cause of death is movingfrom infectious diseases to non-communicable diseases (85% in
China compared to 61% in India24). The next phase of healthcare
evolution in these countries will require universal access tobasic healthcare and a way to address the demanding needsof growing middle-class populations.
A platform-based healthcare approach, with an integrated
e-health record system powered by mobile health, telemedicine,and AI-based diagnosis and treatment can help developing
countries leapfrog ahead on healthcare access at scale without
the need to proportionately increase healthcare facilities andprofessionals.
Mobile devices have become increasingly common in developing
countries and, most recently, there has been an emergenceof inexpensive smartphones like Reliance Jio in India. The
smartphone’s applications enable users to schedule appointments
and order medicines,25 and to access simple diagnostics andself-monitoring tools. The growing wearable devices market
provides mobile devices with an interface designed to capture
vital signs. For example, South African start-up Vitls developed
a tool that enables healthcare providers to continuously andremotely monitor a patient’s pulse, respiration rate, bodytemperature, sleep, and movement patterns.26 In anotherexample, Khushi Baby developed a program to address anunmet need in rural India with its digital necklace that stores
immunization records.27

By focusing on providing healthcare access at scale, developing
countries will improve healthcare quality, outcomes, andexperiences for their growing middle- and upper-middle-class
populations. These populations often pay cash for healthcare
and demand a better experience, which is why China and India,
in particular, are launching advanced technology-led customer
experience initiatives to serve them.

Moving from defining the promise
to realizing the promise
A variety of forces, in both the developed and developingworlds, will challenge technology-led changes to healthcare.
In developed countries, overcoming legacy issues, such as silos
in healthcare data and systems, and leading change management
for healthcare professionals and other stakeholders will be thegreatest challenges. That said, the enablers for change will
include increasing cost pressure and rising consumer power,
likely resulting in operational efficiencies through automationand leveraging AI as an assistant—rather than a peer or advisor—
to the physician. Government will play an important role insetting up policies and enable an environment where different
stakeholder incentives align to drive the intended change.
Meanwhile, developing countries are starting with more ofa clean slate, but they are challenged by affordability and thepriority that their governments give to healthcare. China is an
exception, since its government is likely to drive the change,
but elsewhere in the developing world, effective public-private
partnerships may be critical to driving progress in platform-based
healthcare. To entice the private sector to invest in healthcare,developing countries can leverage well-structured partnershipsthat mobilize private investment into public service delivery,
and that have a risk-sharing agreement built in. In the last few
years, public-private partnerships in the health sector have

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brought immense benefits to the poor in Africa,32 and theapproach to healthcare innovation has been effective in a few
countries, including Kenya, Tanzania, and Ghana. As partnershipsof this kind are highly complex undertakings, it is important forgovernments to ensure that project outcomes support larger
health system goals and that facilities and services developedby the public-private partnerships are integrated into the broader
health system.

23

Forbes, 2017.

24

World Health Organization, 2015; Times of India, 2017.

25

Practo; MedLife.

26

Disrupt Africa, 2017.

27

Global Citizen, 2018.

28

TechWire Asia, 2018.

We are at the beginning of a significant shift as the primary
driver of global healthcare impact switches from biotechnology
to information technology. This shift holds considerable
promise for healthcare in all parts of the world—developed
and developing. The overall impact of this evolution ought toincrease life expectancy and quality of life everywhere. But
while the promise is exciting and immense, the speed ofprogress will depend on how the various stakeholders work
to find common ground, focus on the right priorities, and findcreative models for success through affordable scale.

29

VentureBeat, 2019.

30

FirstPost, 2017.

31

World Health Organization, 2018.

32

Health Policy and Planning, 2018.

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Notes:
1

ITU, 2017.

2

Next Conference, 2018.

3

Medium, 2017.

4

KPMG, 2018; The Office of the National Coordinator for
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5

Quartz, 2018; Quartz, 2017.

6

ThermoFisher Scientific, 2018.

7

Genome Biology, 2018; The Conversation, 2018.

8

Bailey Southwell & Co., 2018.

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World Health Organization, 2011.

10

MedCity News, 2017.

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12

GoInvo, 2017.

13

NCBI, 2018; BMJ Open, 2017.

14

The Library of Economics and Liberty, 2017.

15

MarketWatch, 2019.

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Leela Barham Economic Consulting, 2017.

17

Healthcare Intelligence Network, 2019.

18

NCBI, 2018; BusinessWorld, 2019.

19

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The Global Innovation Index 2019

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Quartz. (2017, July 10). If you’re not a white male, artificial intelligence’s use inhealthcare could be dangerous. Retrieved from https://qz.com/1023448/
if-youre-not-a-white-male-artificial-intelligences-use-in-healthcare-couldbe-dangerous/——— . (2018, September 6). If AI is going to be the world’s doctor, it needs
better textbooks. Retrieved from https://qz.com/1367177/if-ai-is-going-tobe-the-worlds-doctor-it-needs-better-textbooks/
TechWire Asia. (2018, June 27). China’s quest for better healthcare with AI.
Retrieved from https://techwireasia.com/2018/06/chinas-quest-for-better-healthcare-with-ai/
The Active Ingredient. (2018, August 29). How do doctors feel about robots
in the exam room? Retrieved from https://info.zs.com/activeingredient/
how-do-doctors-feel-about-robots-in-the-exam-room
The Commonwealth Fund. (2017, November 9). Expanding access to lowcost, high-quality tertiary care. Retrieved from https://www.commonwealthfund.org/publications/case-study/2017/nov/expanding-access-low-cost-high-quality-tertiary-care
The Conversation. (2018, October 15). Boyer Lectures: gene therapy is still in
its infancy, but the future looks promising. Retrieved from https://theconversation.com/boyer-lectures-gene-therapy-is-still-in-its-infancy-but-thefuture-looks-promising-104558
The Library of Economics and Liberty. (2017, August 7). Hooper’s law of drug
development. Retrieved from https://www.econlib.org/library/Columns/y2017/Hooperdrugdevelopment.html

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CH AP T E R 4

TEN OPPORTUNITIES FOR
BIOMEDICAL INNOVATIONOVER THE NEXT TEN YEARSFrancis Collins, National Institutes of Health (NIH)

As the world’s largest public funder of biomedical research, theNational Institutes of Health (NIH) provides a unique vantage
point from which to survey—and to shape—the rapidly evolving
landscape of biomedical innovation. Over many decades, NIH’s
scientific vision has proven crucial to the health and economic
well-being of those living in the United States of America (U.S.).
But NIH is also a major supporter of global health that holds
increasing promise for low- and middle-income countries, andmedical research essentially knows no national boundaries.
Let us begin by recognizing that the future of biomedical innovationis built on fundamental knowledge—that the long arc of discovery
begins with basic science. Experiments going on right now inbasic laboratories around the globe contain the seeds ofadvances that will transform medicine and improve humanhealth. We can already identify a great number of promising
opportunities on the near horizon. This chapter will highlight
10 of the most exciting areas in which, given a sustainedcommitment of resources for biomedical research, we can
expect to see striking progress 10 years from now. It will also
examine scientific and public policy challenges that fall along
the pathway to biomedical innovation, as well as explore a few
examples of the many creative mechanisms being used by
NIH and its partners to address such challenges.

Making big plans
The architect Daniel Burnham once said, “Make no little plans,
they have no magic to stir men’s blood and probably themselves
will not be realized.” While the source of the next majorinnovative breakthrough is hard to predict, the NIH has big
plans—some might even say audacious plans—for biomedical
innovation in the near future. Following is a high-level overview

of 10 of the many rapidly emerging fields of biomedicine in which
we anticipate extraordinary advances over the next decade.
Single-cell analysis
Let us fast-forward to 2029 and what is likely to be among thefirst of these 10 breakthroughs: advances in the understandingof the exquisite complexity of the functions of individual humancells. Cells are to biology what atoms are to chemistry—the
basic unit of understanding. Yet, during the long history ofbiomedical research, scientists have not possessed the technicalability to study individual cells in their normal environment.
Instead, they have had to be content with low-resolution
technologies that could only analyze millions, or maybe evenbillions, of cells as a group. With a variety of new technologies
invented in the last few years, especially to ascertain whatgenes are turned on or off in an individual cell, this is all changing.1
For example, using new approaches to single-cell analysis,
we can now decode the process by which individual immune
cells attack and destroy healthy tissue in autoimmune disorders.
This promises to transform how healthcare professionals
approach lupus, rheumatoid arthritis, multiple sclerosis, andmany other autoimmune diseases. Likewise, single-cell analysis
will likely prove valuable in understanding—and combating—thedeadly process of cancer metastasis, in which malignant cells
spread from their original location into other vital parts of thebody, such as the brain, bone, lungs, and liver.
Mapping the brain
Improved understanding of basic science is also the aim of
the NIH-led Brain Research through Advancing Innovative
Neurotechnologies® (BRAIN) Initiative.2 With roughly 100 billion
cells and 100 trillion connections, the human brain remains

Chapter 495one of science’s most daunting frontiers and one of medicine’s
greatest challenges. In a decade, researchers will have used thetools and technologies developed through BRAIN to identify thehundreds of different types and subtypes of cells within ourbrain. Beyond that, BRAIN-supported research will also havemapped the key features of the circuits responsible for motor
function, vision, memory, and emotion—all functioning at the
speed of thought. As a result, we will have a much bettergrasp of the details of how the brain works in real time. This
understanding will enable healthcare professionals to diagnose
neurological conditions earlier and more precisely. We will
also have uncovered new targets to explore for prevention
and treatment of autism, epilepsy, traumatic brain injury,
schizophrenia, Parkinson’s disease, and many other disorders
in urgent need of new approaches. Progress will even be
made against formidable foes like Alzheimer’s disease andspinal cord injuries.
Alzheimer’s disease
Aided by new imaging techniques developed and optimized by
the BRAIN Initiative, and biomarker discoveries made through
NIH’s partnership with private sector collaborators,3 we will
be able in 10 years time to identify individuals at high risk for
Alzheimer’s disease even before symptoms appear. Right now,
this fatal, neurodegenerative condition can only be conclusively
diagnosed by examining the brain after death. With the arrivalof ways to diagnose Alzheimer’s much earlier, healthcare
professionals may be able to provide at-risk people with effective
therapies aimed at slowing or changing the course of thedisease. Such innovation would delay or avert countless personaland family tragedies all around the world and translate into
hundreds of billions of dollars of economic savings in the U.S.
alone. Even the ability to delay the onset of cognitive decline by
five years could provide profound human and economic benefit.
Spinal cord injuries
A decade from now, we will have developed effective treatments
for spinal cord injuries. Already, groundbreaking researchsupported by NIH has enabled several young men, paralyzed
from the waist down by a traumatic injury, to move their legs andwalk through the use of surgically implanted electrical stimulatorsthat bypass the severed cord.4 Other NIH-funded work has
used a noninvasive spinal stimulation technique—electrodes
strategically placed on the skin—to help people with lower bodyparalysis move their limbs again and those with upper bodyparalysis improve hand strength and dexterity.5 With additional
follow-up studies, we may be able to give freedom of movementback to many more of the millions of people worldwide who arecoping with spinal cord damage from traffic accidents, sports
injuries, and other trauma.
Pain management
Ten years from now, researchers in the public and private sectors
will have made tremendous progress toward developing
effective, non-addictive, non-opioid approaches to pain
management. Chronic pain is a serious and costly public health96

The Global Innovation Index 2019problem, affecting tens of millions of people worldwide. NIH
researchers recently showed that disability is just as likely forpeople suffering from chronic pain as it is for those with kidney
failure, emphysema, or stroke. Unfortunately, current treatments
used to manage chronic pain can be addictive, and that canlead to tragic outcomes. In the U.S., more than 130 people dieevery day from overdosing on opioids.
To help tackle this monumental challenge, the NIH recently
launched the Helping to End Addiction Long-Term (HEAL)
research initiative.6 A key part of this effort is developing
non-addictive strategies for preventing and managing pain.
Toward that end, NIH-supported researchers are utilizing thelatest advances in genomics, neuroscience, and structural
biology to better understand the biology of pain, and to uncoverentirely new targets for treating this longtime scourge ofhumankind. For example, in a recent study of over 1,600
people injured in traffic accidents, researchers discovered that
individuals with a specific variant in a stress-controlling gene,
called FKBP5, were more likely to develop pain than those withother variants.7 The findings suggest that non-addictive small
molecules that target the FKBP5 protein might reduce the pain
response or prevent the transition from acute to chronic pain.
Regenerative medicine
The next decade will also witness large strides in regenerative
medicine.8 For example, many are eagerly awaiting the
introduction of a safe and effective bioartificial pancreas. For
individuals with diabetes, such a system will continuously trackchanges in blood glucose levels and use that information todeliver more precise doses of insulin. Already approved arevarious “closed loop” systems,9 which typically use wirelesstechnology to connect a monitor that continually measures theamount of glucose in a person’s body with a small pump that,using real-time data from the monitor, infuses an appropriate
dose of insulin subcutaneously. Such real-time monitoring anddose adjustment should significantly improve the managementof diabetes, preventing countless complications like heartdisease, amputations, and vision loss.
However, the ultimate achievement would be the creation of
a completely biological replacement pancreas. To reach thisgoal, researchers might take advantage of bioengineering
advances that enable reprogramming of a patient’s own cells,
ideally implanted within the portal circulation.10 The amazing
innovation that makes this type of breakthrough a real possibility
is induced pluripotent stem cell (iPS) technology. Derived frommature human skin or blood cells, iPS cells can be encouraged
to differentiate into a wide variety of human tissues in the lab,
including pancreatic islet cells that respond to blood glucose
and make insulin. In fact, some researchers recently used
iPS cells, in combination with other regenerative medicine
techniques, to produce human pancreatic islets that not only
secrete insulin, but also develop their own circulatory system
to nourish the islets.11 When transplanted into a mouse model oftype 1 diabetes, these bioengineered islets successfully treatedthe animals’ diabetes. Not only do iPS cells hold the potential
to help people with diabetes, they may also make it possible tomake advances in many other areas of regenerative medicine.
For example, it will likely be possible to rebuild damaged hearts,
kidneys, and livers—rendering many organ transplants, organ
waiting lists, and anti-rejection drugs a thing of the past.
Cancer immunotherapy
Cancer is another regrettably common disease poised forsignificant progress over the next decade, especially in thearea of immunotherapy.12 In the early 1970s, basic research,
spearheaded in large part by NIH-funded scientists, led to thedevelopment of methods to splice fragments of DNA together,giving birth to the field of biotechnology. When merged with
fundamental advances in molecular immunology, this set oftechnologies made it possible to pursue ideas for cancer
immunotherapy—a radical new approach that involves enlistinga patient’s own immune system in the fight against cancer.
In one promising strategy, immune cells are collected frompatients and engineered to produce special cancer-fighting
warriors, called chimeric antigen receptors. This work has alreadysaved the lives of many children and adults with treatment-resistantleukemia, lymphoma, and other blood cancers.13
Now, cancer researchers in the public and private sectors are
setting their sights on even tougher targets: breast, prostate,colon, ovarian, pancreatic, and other solid types of cancer,
which have so far proven rather resistant to immunotherapy.
Recent developments make us optimistic that a pathway
forward is taking shape. In the last couple of years, an NIH
team announced a novel modification of an immunotherapy
approach, built upon a precise understanding of the driver
mutations in a particular individual’s cancer. This strategy led
to regression, most likely cure, of widely metastatic disease inindividuals with breast cancer and bile duct cancer.14 Of course,
this must be replicated in further studies, but without a doubt,
these life-saving experiences represents hope for millions more.
How phenomenal it would be if we could offer people withsolid tumors that have metastasized to other parts of the bodya chance of not just being treated, but actually being cured of
their disease.
New vaccines
Important strides will also be made in the next 10 years in theprevention of influenza, HIV, and many other infectious diseases,
thanks to the development of innovative vaccine strategies.
Currently, a new flu vaccine must be produced each year toprotect against the rapidly mutating influenza virus. Despite ourbest efforts, the vaccine isn’t always ideal and, in an average
year in the U.S. alone, the flu kills nearly 50,000 people, at a
cost to the economy of more than US$87 billion. But it does nothave to be that way. NIH is providing substantial resources tocatalyze the arrival of a “universal” flu vaccine—strategicallydesigned to target mutation-resistant parts of the influenza
virus—that will provide long-lasting protection against a wide
variety of flu strains. Not only will such a vaccine reduce theneed for the annual flu shot, it will prepare us for the next
overdue worldwide pandemic, potentially saving millions of
lives. Human clinical trials of the first version of such vaccines

are now underway, through active collaboration between NIH
and industry.15
We are also optimistic that a safe, effective vaccine for HIV/AIDS
will finally be available, providing an opportunity to bring an
end to this most frightening and costly global epidemic. One
approach involves the assumption that a particular type of
immune response would be protective against HIV infection.
After all, some people living with HIV naturally produce broadly
neutralizing antibodies (bNAbs), albeit too late after infection toclear the virus. Researchers have isolated— from people livingwith HIV—several varieties of bNAbs that have been shown in
the laboratory to inhibit most HIV strains from infecting humancells. The challenge is to use that information to design avaccine that will induce production of bNAbs in individuals who
have never been exposed to HIV. Tests in animals have beenencouraging, and a first-in-human trial is expected to begin
within a year.16
Gene editing to cure disease
Within the next 10 years, biomedical research will also begin torealize the promise of new genetic technologies to treat or evencure diseases that once seemed out of reach. Scientists haveidentified the molecular causes of nearly 6,500 humandiseases, yet treatments currently exist for only about 500(Figure 4.1). Particularly exciting is the potential of Clustered
Regularly Interspaced Short Palindromic Repeats (CRISPR-Cas)
technology for somatic cell gene editing—an approach that
corrects gene mutations only in relevant tissues without the riskof passing those changes on to a future generation.
One of the first successful applications of gene editing will likely
be for curing sickle cell disease (SCD), which affects over 20
million people worldwide, mostly in developing nations.17 SCD
is the first “molecular disease,” with its genetic cause having
been identified many decades ago. However, the need for awidespread cure for SCD has not been met. Since 1998, doctors
have used a drug called hydroxyurea to reduce symptoms, but it
can cause serious side effects. At present, the only way to cure
SCD is through a bone marrow transplant, which is not an option
for many patients due to a lack of matched donors, or possibly
through experimental gene therapies delivered by viral vectors.
CRISPR-Cas gene editing is offering a new strategy: remove
blood precursor cells, called hematopoietic stem cells (HSCs),
from a patient’s own bone marrow or bloodstream; use themagic of CRISPR-Cas to fix or offset the negative effects of the
SCD-causing gene mutation in the HSCs; and then return the
now-cured—no longer sickling—HSCs to the patient. Admittedly,that rather complicated process may not be practical for quite
some time in places like sub-Saharan Africa. That is one reason
why NIH recently launched a new effort to speed the developmentof safe, effective genome-editing approaches that could bedelivered directly into a patient’s body (in vivo), perhaps byinfusion of the CRISPR gene editing apparatus.18
As research moves forward in the fast-paced field of genetic
therapy, it will be important that these endeavors remain ethical,
but also remain bold, on behalf of the hundreds of millions

Chapter 4

97

FIGURE 4.1

Disorders with known molecular basis

6,500

6,000

5,500

5,000

4,500

~500
with therapy

4,000

3,500

3,000

2,500

2,000

1,500

1,000

500

0
1990

1992

1994

1996

1998

2000

2002

2004

2006

Source: Online Mendelian Inheritance in Man, available at https://www.omim.org/statistics/geneMap.

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2008

2010

2012

2014

2016

2018

of people with genetic diseases who are still awaiting cures.
Importantly, those therapeutic strategies can be pursued without
altering the part of the genome that is inherited by future
offspring. Over the next decade and beyond, scientific, economic,
and thought leaders around the globe must continue to assess
and address the very serious ethical concerns raised bygermline gene editing of human embryos, which will irreversibly
alter the DNA instruction book of future generations of humankind.
NIH contends that our society is not ready to undertake such
experiments in the foreseeable future.19

to major health challenges; and fostering the developmentof public-private partnerships to accelerate and transformcurrent models for developing new diagnostics and treatments.
However, NIH cannot do this alone. We need partners in the
public policy and private sectors from all around the world torealize the full potential of biomedical innovation over the next
decade and beyond. Among the areas in which we are calling
our global partners to join us are measures aimed at facilitating
data sharing, improving scientific rigor and reproducibility, andestablishing oversight for emerging biotechnologies.

Precision medicine

Data sharing

Thanks to opportunities that span a wide range of biomedical
disciplines, we also have the potential to develop a wide varietyof tailored approaches to medicine that reflect the fact that not
all individuals are the same. In the U.S., this opportunity will
be enabled by the NIH-led All of Us Research Program.20
This monumental undertaking is building a research cohort of
1 million or more volunteers from all across the nation, withroughly half of those participants coming from traditionally
underrepresented racial and ethnic minorities. All of Us willcapitalize on a broad array of innovations in a wide range ofscientific fields. For example, it will apply the latest methods andapproaches in data science, including advances in large-scale
databases, computational tools, and “omics” methodologies
of characterizing individuals. The aim is to pioneer efforts
to merge, integrate, and analyze data from a wide variety ofsources—biological, environmental, socioeconomic, andgeospatial—that have implications for individualized disease
prevention and treatment, and for understanding the causes
and the solutions to health disparities.

Opportunities to harness the power of big data and newtechnological breakthroughs in artificial intelligence (AI) andmachine learning will depend on the development of infrastructure
and policies that reflect the Findable, Accessible, Interoperable,
and Reusable (FAIR) principles.21 This includes the establishmentof field-appropriate data standards and interoperable, sustainable
data resources. While protection of privacy and confidentialityof research participants is crucial, certain data protection
policies and regulations may present obstacles to data sharing,
especially through variable and conservative interpretationof such regulations in the absence of clear guidance fromgovernmental entities and coalitions.22 We are working with ourglobal counterparts across the public sector to find the balance
between appropriate data protection and accessibility for
research progress.

NIH envisions that the willingness of the diverse array of All of
Us participants to share a wide variety of their health-related
information will establish a valuable research resource that will
foster the emergence of important new insights—basic, translational,
and clinical. Such insights will ensure that people from all walksof life, all around the world, will be healthier than ever.

Overcoming challenges together
This list of opportunities for biomedical innovation is ambitious.
Not only will it take tremendous effort and ingenuity on thepart of the worldwide research community to make these 10
advances happen in just 10 years, but it will also require someserious actions by other sectors of society. Perhaps the mostsignificant action will be encouraging the next generation ofresearchers through a strong, sustained commitment to biomedical
research by the public sector. The most important resource
for the future of biomedical research is not buildings ortechnologically advanced equipment—it is the people that will
have the dreams and do the work.
NIH leadership has recently taken several creative steps aimed
at spurring biomedical innovation. These actions include:
initiating special awards to encourage high-risk, high-reward
research; encouraging the next generation of researchers;
launching prize competitions aimed at finding innovative solutions

Rigor and reproducibility
Two of the related cornerstones of biomedical innovation are
rigor in designing and performing research, along with theability to reproduce research findings.23 The application ofrigor ensures robust and unbiased experimental design,
methodology, analysis, interpretation, and reporting of results.
When a result can be reproduced by multiple scientists, itvalidates the original results and indicates readiness to progressto the next phase of research. This is especially important forclinical trials in humans, which are built on studies that havedemonstrated a particular effect or outcome. Research funders
and journals are establishing policies to ensure rigorous
methodology in all realms of research, including power analyses,
validation/authentication of reagents or cell lines, justification ofanimal models, and consideration of sex as a biological variable.
Oversight of emerging biotechnologies
For new and emerging biotechnologies, it is appropriate toestablish oversight systems commensurate with the risk anduncertainty related to the technology. However, such oversightsystems need to be flexible enough to adjust as the technology,
and the related risks, are better understood. For example,
recombinant DNA merited intense scrutiny and oversight in
the late 1970s, when the technology was new, the risks were
unknown, and biosafety systems to contain the risk were in theirinfancy. Over time, our understanding of the risks has become
highly sophisticated, the technology has become ubiquitous,
and biosafety protocols have become well established, thus
allowing a risk-based adjustment to the framework of oversight.24

Chapter 499Compare that to a new technology such as gene editing. The
use of CRISPR-Cas for creating gene-edited babies has alreadybeen highlighted above. But that is not the only applicationthat raises ethical and societal concerns. Consider the use of
CRISPR-based gene drives for control of disease vectors likemosquitoes, where the environmental risk is still uncertain andwhere high levels of precautionary oversight are still warranted.
In closing, it is imperative that we keep our minds open to thepossibility that this vision of future opportunities—and futurechallenges—may change, perhaps even dramatically, over the
next decade. There certainly is no guarantee that these 10 goals
will be attained by 2029, but they are offered as examples inhope of inspiring the rapidly moving field of biomedical researchto aim even higher for the benefit of all humankind. As has
been the case so often in the past, the greatest biomedical
innovations of tomorrow may very well come from directions
that none of us could anticipate today.

Notes:
1

National Institutes of Health. 2018c.

2

National Institutes of Health, n.d.-b.

3

National Institutes of Health, n.d.-c.

4National Institutes of Health, 2014.

5Lu et al., 2016.

6

National Institutes of Health, 2019a.

7

Linnstaedt et al., 2018.

8

National Institutes of Health, n.d.-d.

9

Russell et al., 2014.

10

Yoshihara et al., 2016.

11

Takahshi et al., 2018.

12

National Institute of Health, 2018e.

13

Novartis, 2017.

14

Zacharakis et al., 2018.

15

National Institutes of Health, 2018a.

16

National Institutes of Health, 2018f.

17

Collins, 2018b.

18

National Institutes of Health, 2019b.

19

Collins, 2018a.

20

National Institutes of Health, n.d.-a.

21

National Institutes of Health, 2018b.

22

European Commission.

23

National Institutes of Health, 2018d.

24

Collins et al., 2018.

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References:
Collins, F. S. (2018a, November 28). Statement on Claim of First
Gene-Edited Babies by a Chinese Researcher. Retrieved fromhttps://www.nih.gov/about-nih/who-we-are/nih-director/statements/statement-claim-first-gene-edited-babies-chinese-researcher——— . (2018b, December 11). Accelerating Cures in the Genomic Age:The Sickle Cell Example. Retrieved from https://directorsblog.nih.
gov/2018/12/11/accelerating-cures-in-the-genomic-age-the-sickle-cell-example/
Collins, F. S., & Gottlieb, S. (2018, August 15).. The next phase of humangene therapy oversight. N Engl J Med. Retrieved from https://www.nejm.org/doi/pdf/10.1056/NEJMp1810628
European Commission. (2018). 2018 reform of EU data protection rules.
Retrieved from https://ec.europa.eu/commission/priorities/justice-and-fundamental-rights/data-protection/2018-reform-eu-data-protection-rules_en
Linnstaedt, S. D., Riker, K. D., Rueckeis, C. A., Kutchko, K. M., Lackey, L.
et al. (2018, August 27). A functional riboSNitch in the 3’UTR of
FKBP5 alters microRNA-320a binding efficiency and mediates
vulnerability to chronic posttraumatic pain. J Neurosci. Retrieved
from http://www.jneurosci.org/content/38/39/8407.long
Lu, D., Edgerton, R., Modaber, M., AuYong, N., Morikawa, E. et al. (2016,
May 18). Engaging cervical spinal cord networks to reenable volitional control of hand function in tetraplegic patients.
Neurorehabilitation and Neural Repair. Retrieved from https://journals.sagepub.com/doi/full/10.1177/1545968316644344
National Institutes of Health, United States of America. (n.d.-a) All of Us
Research Program. Retrieved from https://allofus.nih.gov/——— . (n.d.-b). The BRAIN Initiative®. Retrieved from https://www.braininitiative.nih.gov/——— . (n.d.-c). The Division of Neuroscience of the National Instituteon Aging. AMP – AD Biomakers Project, Accelerating Medicines
Partnership (AMP) for Alzhemiers Disease. Retrieved fromhttps://www.nia.nih.gov/research/dn/amp-ad-biomarkers-project——— . (n.d.-d). Regenerative Medicine Innovation Project. Retrieved fromhttps://www.nih.gov/research-training/medical-research-initiatives/rmi——— . (2014, April 8). The National Institute of Biomedical Imaging andBioengineering. Spinal stimulation helps four patients with paraplegia
regain voluntary movement. Retrieved from https://www.nih.gov/
news-events/news-releases/spinal-stimulation-helps-four-patients-paraplegia-regain-voluntary-movement——— . (2018a, May 4). National Institute of Allergy and Infectious Diseases.
Universal Influenza Vaccine Research. Retrieved from https://www.
niaid.nih.gov/diseases-conditions/universal-influenza-vaccine-research——— . (2018b, July 24). Office of Strategic Coordination, The Common
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gov/singlecell——— . (2018d, November 27). Office of Extramural Research. Enhancing
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2018 [News Release]. Retrieved from https://www.nih.gov/newsevents/news-releases/nih-statement-world-aids-day-december-1-2018——— . (2019a, January). NIH Health Initiative. Retrieved from https://www.
nih.gov/research-training/medical-research-initiatives/heal-initiative

——— . (2019b, January 29). Office of Strategic Coordination, The Common
Fund. Somatic Cell Genome Editing Program. Retrieved fromhttps://commonfund.nih.gov/editing
Novartis (2017, August 30). Novartis receives first ever FDA approval
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media-releases/novartis-receives-first-ever-fda-approval-car-t-cell-therapy-kymriahtm-ctl019
Russell, S. J., El-Khatib, F. H., Sinha, M., Magyar, K. L., McKeon, K. et al.
(2014, June 15). Outpatient Glycemic Control with a Bionic Pancreas
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Takahshi, Y., Sekine, K., Kin, T., Takebe, T., & Taniguchi, H. (2018, May 8).
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CH AP T E R 5

APPLICATION OF ARTIFICIALINTELLIGENCE AND
BIG DATA IN CHINA’SHEALTHCARE SERVICES
Ma Huateng, Tencent

In recent years, with a flourishing economy and the continuous
progress of medical reform, China’s healthcare system has
experienced rapid expansion and significant service improvements.
Today, there are over one million medical institutions in China.1
Medical insurance covers more than 95% of the Chinese
population.2 Life expectancy has reached 76.4 years, an average
higher than that of some high-income countries.3
However, population aging has put enormous pressure on
China’s healthcare system. To relieve this pressure, we consider
how technology could help improve healthcare efficiency, andhow solutions could be integrated into the healthcare system
to help relieve the pain of patients and reduce the financial
and psychological burden on their families.
The next generation of information technology (IT) represented
by artificial intelligence (AI) and big data analytics could offer
new tools to address China’s healthcare challenges. Medical AI
has the potential to complement doctor resources and enablebroader access to high-quality medical services. This is of greatsignificance for China where the current supply of healthcare
services falls short of the growing demand from an aging
population of 1.4 billion.

Impetus: potential of IT integrationand innovation in China’s healthcare
services
The integration of IT into China’s healthcare services is aninexorable trend and will unleash great potential. Growing
demand for healthcare services, a favorable policy environment,
surging capital investment, and emerging technology are four

driving factors. Combined, they bring new opportunities for
IT integration and innovation to the healthcare system andfacilitate innovative applications on a global scale.
1. Demand: growing healthcare demand creates opportunities
for technological innovation
China’s large healthcare sector is in the process of rapid
expansion. Total national health expenditures exceeded 5 trillion
yuan in 2017, accounting for 6.2% of the gross domestic
product (GDP).4 This number will reach 16 trillion yuan by 2030,
according to the Healthy China 2030 Planning Outline.5
This growth in national health expenditures is creating opportunities
for medical AI in China. According to Tractica’s forecast, China’s
AI medical market is developing rapidly, with the market size
soaring from 9.661 billion yuan in 2016, and 13.65 billion yuan
in 2017, to 20.4 billion yuan in 2018, maintaining a compound
annual growth rate of more than 40%.6 At the same time,
Chinese medical institutions and businesses are taking aproactive attitude towards AI. Nearly 80% of hospitals andmedical companies are planning to, or already have, carried out
medical AI applications and more than 75% of hospitals believethat such applications will become popular in the future.7
2. Technology: increasing standards and patents
safeguard innovation
In recent years, AI technologies have flourished globally, andparticularly in China. According to the Derwent World Patents
Index (DWPI), global annual AI patent applications have surged
since 2010. China contributed the highest number with a total

Chapter 5103

of 76,876 applications from 1985 to 2017 (Figure 5.1). According
to the China Patent Abstract Database (CNABS), the top fivepatent applicants in China were Baidu, Chinese Academy of
Sciences (CAS), Microsoft, Tencent, and Samsung.8
According to the Patentics database, in the field of healthcare,keyword analysis of global AI patents indicates two features.9
During the period 1985 to 2017, China ranked fourth in the total
number of healthcare AI patent applications filed, contributing
to 12% of the total. This implies that China’s technologicalinnovation has been comparatively less active in the fieldof healthcare AI compared to overall AI activity. In this same
period, China rapidly increased patent applications from 2010and surpassed Japan and the European Union to become theworld’s second largest healthcare AI applicant in 2016, whichreflects the strong momentum of medical technology innovationin China (Figure 5.2).10
Also in the Patentics database, China’s healthcare AI patents
are classified into five categories: medical diagnostics,
nursing/caring, medical devices, data and archiving, andpharmaceuticals. Among them, patents for AI in medical
diagnostics and nursing/caring account for 29% and 28%
respectively, far more than any other category, making these
the two most active fields of healthcare AI innovation in China(Figure 5.3).
3. Capital: accelerating capital investment fuels innovation
Healthcare AI is drawing the attention of investors, which isbringing capital to the field and accelerating technologicalinnovation. According to third-party statistics, global healthcare
AI start-ups have raised US$4.3 billion through 576 deals
since 2013. China overtook the United Kingdom in the first halfof 2018 to become the second most active country in termsof capital investment in healthcare AI.11

Innovation: emergence of AI
and big data applications in China’s
healthcare
Under favorable market and policy environments, healthcare
AI and big data have developed more quickly in recent years.
From 2007 to 2017, more than 100 companies dedicated tohealthcare AI emerged in China. Since 2014, a surge in companies
entering the space has caused innovation to accelerate.12
Many types of businesses and institutions have participated in
the development of healthcare AI in China. Representative
participants range from established Internet companies totechnology start-ups, from healthcare software companies to
medical device manufacturers, and from pharmaceuticalcompanies to hospitals, universities, and research institutions.
Attempts to apply AI to over 20 types of diseases have beenmade. Lung cancer diagnosis and diabetic retinopathy are
the most popular applications and are attracting the moststart-ups. Many companies are also exploring AI applications
in cardiovascular diseases.13

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AI has already been extensively integrated into several sub-fieldsof the healthcare sector. In addition to medical services andhospital management and administration, applications arealso deployed in fields such as pharmaceutical research anddevelopment, cost control for payers, and health management
for individual consumers.
1. Smart doctors: leveraging medical imaging
Medical imaging has become the leading and most popular field
for AI application in China’s healthcare sector, having benefited
from the mature technology found in machine learning-based
image recognition and from the availability of massive medical
imaging data. A wide range of products targeting cancers
and chronic diseases have entered the clinical validation
phase. These products focus on areas such as disease
screening, target volume delineation for radiation therapy,
and three-dimensional reconstruction.
In disease screening, AI-enabled software automatically marks
lesions so that doctors can improve their focus and efficiency
when reading medical images by referencing these marks.
Clinical Target Volume (CTV) delineation, mainly used inradiotherapy, employs AI to automatically delineate target
volumes based on medical images generated from computed
tomography and/or magnetic resonance imaging machines.14
The results are then subject to use and correction by doctors.
The application can significantly shorten the time required bytraditional manual delineation and accelerate the implementationof radiotherapy. Three-dimensional reconstruction refers to theautomatic creation of 3D models of human organs by machines,
from which realistic physical models can be obtained to facilitate
high-quality surgical procedures and other medical treatments.
For example, Tencent AI Medical Imaging, developed in 2017,is a system used for screening several diseases such as diabetic
retinopathy, lung cancer, and esophageal cancer. The system isundergoing clinical validation in more than 100 major hospitals
in China. It has assisted doctors in reading over 100 million medical
images and served nearly one million patients cumulatively.
With the advancement of image recognition technologies,
diagnostic precision has reached new levels. For example,
data from Tencent shows that recognition accuracy reaches
90% for esophageal cancer, 97% for diabetic retinopathy,
and 97.2% for colorectal cancer, making disease screening
highly effective.
2. Smart doctors: leveraging diagnosis support
Healthcare services involve extensive and varied text datasuch as consultation records, medical records, and researchstudies. Using AI to comprehensively mine and analyze
text data will help doctors improve diagnostic efficiency andcreate significant opportunities for AI and big data applications
throughout healthcare. Specific applications include:• Intelligent triage: Patients can quickly and accurately
obtain triaging information by entering symptoms and otherrequired information in mobile apps and robotic devices
that guide patients in hospitals.

FIGURE 5.1

Top ﬁve countries/regions for AI patent applications, 1985 to 2017

90,00080,00076,87670,00067,27660,00050,00044,75540,00030,00020,00020,18018,631

10,0000China

United Statesof America

Japan

Republic of Korea

European Union

Source: Patent Protection Association of China, 2018.
Note: Analysis report based on data sourced from China Patent Abstract Database (CNABS).

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105

FIGURE 5.2

Healthcare AI patent applications in major countries and regions,1985 to 2017

4,000

3,500

3,000

2,500

2,000

1,500

1,000

500

0

1985 1987 1989

India

1993 1995 1997 1999 2001 2003 2005 2007 2009 2011

Republic of Korea

Source: Patentics Database.
Note: Data analyzed by Tencent.

106

1991

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China

Japan

European Union2013 2015 2017

United States of America

FIGURE 5.3

Healthcare AI patent categories in China

Data and archiving
1,551 patents

Nursing/caring
3,410 patents

13%
28%

22%

Medical device
2,724 patents

Pharmaceuticals
1,039 patents

8%

29%

Medical diagnostics
3,601 patents

Source: Patentics Database.
Note: Data analyzed by Tencent.

Chapter 5107• Intelligent medical record management: Medical records
retain essential information for medical services, but it ischallenging to manage and utilize medical records because
the data are primarily recorded as unstructured, free-form text.
Text recognition and natural language processing not only
improves the efficiency of medical record processing but also
supports the extraction and analysis of disease characteristics,
improving follow-up diagnosis and scientific research.
• Intelligent risk monitoring: AI helps doctors monitor andadjust their diagnosis and treatment plans and further reduces
the risk of missed diagnosis and misdiagnosis.
At the level of implementation, the concept of enabling clinicaldecision support systems (CDSS) with AI is drawing more
attention. AI-enabled CDSS is expected to provide doctors withefficient decision support throughout a patient’s continuum ofcare. Several national projects are underway including projects
jointly conducted by Tencent, CAS Institute of Automation, andmultiple medical institutions such as the People’s Hospital of
Peking University. These projects have already shown promisingoutcomes. For cardiovascular and cerebrovascular diseases,
an intelligent analysis system for electrocardiogram has
been introduced. For Parkinson’s disease, intelligent
assessment of motor function has been enabled by applying
AI-based video analysis technologies. For head and neckradiotherapy, an innovative rapid organ guidance technique
has been developed.
3. Intelligent hospitals: boosting management andoperational efficiency through mobile Internet
One primary reason that Chinese hospitals adopted IT applications
was to improve the efficiency of management and operations.
At present, most hospitals are in the process of migrating tomobile Internet services, that is, digitalizing hospital services,management, and operation procedures through mobile
applications. The use of mobile apps is greatly improving theefficiency of hospitals and is emerging as a distinct featureof some forward-thinking hospitals in China. Exploration isextending to the automation of administrative tasks with thehelp from AI technologies and intelligent decision support
based on big data analytics.
4. Intelligent pharmaceuticals: exploring digital andintelligent pharmaceutical research & development
The environment for innovation in pharmaceutical researchand development (R&D) improved significantly in China overthe past few years. The Opinions on Deepening the Reformof Review and Approval System to Encourage the Innovationof Drugs and Medical Devices, issued by the State Council
in 2017, noted that China’s pharmaceutical and medical device
industries have developed rapidly amid ascending innovationand entrepreneurship, medical review reform, and approvalsystem advances. China has independently researched anddeveloped new drugs in recent years that have contributed
about 4% to the global novel drug market, approximately
one-twelfth of the contribution from that of the United Statesof America.15 Digital modeling and simulation will facilitate
independent drug R&D in China by effectively reducing costand accelerating development. A group of Chinese emerging

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The Global Innovation Index 2019

start-ups, including Deep Intelligent Pharma (compound
synthesis), XtaiPi (crystal structure prediction), and LinkDoc(recruitment of clinical trial participants), are at the forefrontof exploration.
5. Smart users: expanding from medical knowledge tohealth management
For individuals, medical care is only a means, while health isthe end goal. As the standard of living improves, people
become more proactive about preventing and treating healthissues. In this context, health management has become an
emerging field for IT application. AI and big data technologies
can be applied in two ways:• Making specialized healthcare knowledge accessible to the
public: Knowledge and information can be more accurately
disseminated to users from content databases that integrate
AI and big data technologies. For example, Tencent Medipedia
provides users with information based on content frominternationally acclaimed medical information providers—such as WebMD or Healthline—and leading hospitals in China.
• Managing and monitoring personal health data: AI and
big data technologies are also used to monitor users’ healthconditions with the help of intelligent wearables that provide
personalized health advice.

Future: fostering synergies to makehealthcare more intelligent in China
New technologies, such as artificial intelligence and big data
analytics, have been innovatively applied in China’s medical
service sector and exhibit great potential for further development.
Looking ahead, joint efforts are needed to advance theseapplications toward Tech for Social Good.16
First, data governance should be strengthened. Using digitaltechnologies such as cloud computing and big data, appropriate
rules and processes should be established for data collection,utilization, and protection among healthcare institutions.
Data sharing and circulation mechanisms should be secured
to achieve standardized collection, integration, sharing, andcompliant application of healthcare big data.
Second, collaboration should be encouraged. Open platforms
of innovation in the field of healthcare should be built throughjoint efforts, which could strengthen the sharing of maturetechnologies and expertise to solve common problems andlower the technical threshold for large-scale application ofdigital technology.
Finally, coordinated security assurance should be established.
A sound and coordinated system that covers network security,
system security, and data security for healthcare institutions
should be established. The principles and requirements of
security assurance should be clearly defined for involved parties
to ensure privacy and prevent unintended disclosure.

Notes:from http://www.xinhuanet.com//2017-08/14/c_1121481192.htm——— . (2017, July 20). The New Generation Artificial Intelligence
Development Plan. Retrieved from http://www.gov.cn/zhengce/
content/2017-07/20/content_5211996.htm

1

National Health Commission of People’s Republic of China, 2018a.

2

Xinhuanet, 2018.

3

World Health Organization, 2018.

4

National Health Commission of People’s Republic of China, 2018b.

——— . (2018, April 28). The Opinions of the State Council on Promoting
the Development of Internet Plus Healthcare. Retrieved fromhttp://www.gov.cn/zhengce/content/2018-04/28/content_5286645.htm

5Xinhua News Agency, 2017.

Tencent. (2019). Global Statistical Analysis of Healthcare AI Patents.

6

iResearch, 2019.

7

HC3i, 2017.

VCbeat. (2018, September 27). Healthcare AI Report 2018. Retrieved
from https://vcbeat.net/MjliNzEwOGY0M2M4YTlhM2IyOTdhZjA2MTBhNDA1Yjg=

8

Patent Protection Association of China, 2018.

9

Patentics database, n.d.

10Tencent, 2019. New patent applications are usually not publishedin 18 months, therefore part of the applications in the late 2017
are not included.

11

CB Insights, 2018.

12

EO Intelligence, 2017.

13

VCbeat, 2018.

14

In radiotherapy, Clinical Target Volume (CTV) refers to a tissue
volume that contains the Gross Tumor Volume and/or subclinicalmalignant disease at a certain probability level. It is a proxy of theextent of tumor spread, plus a margin of safety.

15

Wu et al., 2017.

16

Tencent upgraded it’s mission and vision to Tech for Social Good
recently, aiming to harness technology for the benefit of mankind.

World Health Organization. (2018). World Health Statistics 2018: Monitoring
health for the SDGs, 60. Retrieved from https://apps.who.int/iris/
bitstream/handle/10665/272596/9789241565585-eng.pdf?ua=1
Wu, L., & Chen, Y. (2017). Novel Drug Research and Development Ability
in China: An International Comparison and Analysis. Chinese
Journal of Health Policy, 2017, 10(8): 23-28. Retrieved from http://
journal.healthpolicy.cn/html/20170805.htm
Xinhuanet. (2018, February 12). National Health Commission: China’s
Basic Medical Insurance Covered 1.35 Billion People. Retrieved
from http://www.xinhuanet.com/2018-02/12/c_1122407264.htm.
Xinhua News Agency. (2017, August 14). National Health Commission:
China’s Healthcare Industry to Reach 16 Trillion Yuan in 2030.
Retrieved from http://www.xinhuanet.com//2017-08/14/c_1121481192.htm.

References:
CB Insights. (2018, September 13). The AI Industry Series: Top Healthcare
AI Trends To Watch. Retrieved from https://www.cbinsights.com/
research/report/ai-trends-healthcare/
EO Intelligence. (2017, August 25). Research Report on AI Enabling the
Healthcare Industry. Retrieved from https://www.iyiou.com/intelligence/reportPreview?id=85323&&did=530
HC3i. (2017, June 27). AI in Healthcare Market Analysis and Trend Report(2016–2017). Retrieved from http://news.hc3i.cn/art/201706/39588.htm.
iResearch. (2019, January 25). Global Artificial Intelligence Empowerment
China Summit 2019 will be held in Shanghai on March 28th.
Retrieved from http://news.iresearch.cn/content/2019/01/282947.shtml
National Health Commission of People’s Republic of China. (2018a,
January 23). Number of National Healthcare Institutions by the
End of November 2018. Retrieved from http://www.nhc.gov.cn/
mohwsbwstjxxzx/s7967/201901/94fcf9be64b84ccca2f94e3efead7965.shtml——— . (2018b, June 12). Statistical Communiqué on China’s Healthcare
Development in 2017. Retrieved from http://www.nhc.gov.cn/guihuaxxs/s10743/201806/44e3cdfe11fa4c7f928c879d435b6a18.shtml
Patent Protection Association of China. (2018, November 12). In-depth
Analysis Report of AI Patents 2018. Retrieved from img.ppac.org.
cn/attachments/2018/11/1542002367d9905c035a6e00a5.doc
Patentics database. (n.d.). Retrieved from http://patentics.com/web/en/
database/
The State Council of the People’s Republic of China. (2016, June 24).
The Guiding Opinions of the State Council on Promoting andRegulating the Application of Big Data in Healthcare. Retrieved

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CH AP T E R 6

REACHING NEW FRONTIERSFOR ALZHEIMER’S
THROUGH RESEARCH
AND INNOVATIONDavid Ricks and Brandy Matthews, Eli Lilly and Company

Alzheimer’s is one of the most feared diseases in the world—
for good reason. No other disease takes from its victims boththeir pasts and their futures. No other disease among the top
10 causes of death worldwide lacks a treatment to slow it down.
We see Alzheimer’s both personally and professionally. One
of us has a close relative with Alzheimer’s disease who lives ina nursing home. One of us treats patients in a dementia clinic,
where many suffer from Alzheimer’s without the hope of aneffective treatment. Our pharmaceutical company has been
trying to develop an Alzheimer’s medicine for over three
decades—so far without success.
The Alzheimer’s challenge is a window into the future. Aging
populations will continue to strain budgets for health services—
whether that’s care for Alzheimer’s, cancer, diabetes, heartdisease, or other conditions that increase with age. The only
viable solution is to stimulate innovation to produce therapies
that delay disease and lessen the need for expensive services.
In this chapter, we describe the current state of Alzheimer’s andthe challenges of Alzheimer’s drug development, which havecontributed to longer development timelines for Alzheimer’s andhigher failure rates for clinical trials. We suggest policy solutions
that could lower these barriers—helping deliver treatments thatgive hope to patients and the health systems that care for them.

The state of Alzheimer’s
Alzheimer’s disease (AD) is a chronic, progressive illness, whichmostly affects people over the age of 65. Symptoms typicallybegin with subjective concerns related to memory and thinking,followed by more objective deficits in cognition and behavior.
Eventually, patients’ daily activities become impaired. They lose
the ability to care for themselves and typically spend the lastyears of their lives receiving care in nursing homes, which isalso highly expensive (Figure 6.1).1
Across the globe, 50 million people are living with dementia;
Alzheimer’s is the most common form. The estimated yearly costto treat and care for people with dementia is US$1 trillion. That’s
equal to the total amount spent each year on all pharmaceuticals
globally.2 But Alzheimer’s costs are expected to double in a
decade as the prevalence rises to 82 million people in 2030.
By 2050, as populations age significantly in numerous countries,
the prevalence is expected to triple from today’s levels.3
A delay in progression of only one year could reduce the total
number of patients with Alzheimer’s by more than 9 million by
2050.4 Delaying the onset of symptoms for individuals over
70 by one year could reduce healthcare payments by 14%, withlonger delays saving even more.5
Alzheimer’s appears in the brain 10-20 years before patients
experience any change in thinking or memory. The telltale
signs under the miscroscope are clumps of misfolded proteins,

Chapter 6111

FIGURE 6.1

Progression of Alzheimer’s disease

THEORETICAL TIME (YEARS)FROM SYMPTOM ONSET> - 20 YRSRISK FACTORS+ Genetic alterations+ Time (aging)+ Environmental factors?
+ Other?

Amyloid-betaclumping> - 15 YRS

Complex cellular
dysfunction

Tau tangles> - 10 YRS
Degeneration(death of neurons)> O YRSSYMPTOMS FIRST SEEN
Localized brainorgan failure+ 10 YRSSYMPTOM PROGRESSION
Widespread brainorgan failure

Source: Golde et al., 2018.

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inflammation, loss of function in the synapses between neurons,
and, ultimately, the death of neurons—called neurodegeneration.
One estimate suggests that eight times more people haveundetected buildup of misfolded proteins or neurodegeneration
than have observable Alzheimer’s symptoms.6
Targeting the following pathological proteins is a major focus ofattempts to develop a disease-modifying therapy for Alzheimer’s.
Amyloid
The foundation of attempts to treat Alzheimer’s is the amyloidcascade hypothesis. This hypothesis suggests that a protein
called amyloid-beta slowly accumulates into clumps, which
triggers a complicated cascade of events: the pathologicalmisfolding and spread of another brain protein, tau; the activationof inflammatory pathways in the central nervous system; andeventually the death of neurons.
Tau
The second hallmark of Alzheimer’s is clumps of misfolded tau
protein inside neurons. These clumps, called neurofibrillarytangles, correlate with the clinical symptoms of Alzheimer’s
based on autopsy studies and, more recently, based on molecularimaging of living patients’ brains. Efforts to reduce the load oftau still lag behind the anti-amyloid approaches.
Additional targets
Other potentially disease-modifying approaches currently in clinicaltesting target inflammation, neurotransmission, and vascularand metabolic contributions to Alzheimer’s. Others attempt topromote growth of neurons and synapses, to protect neurons
from damage, or to reverse brain damage via stem cell therapy(Figure 6.2).

Challenges of development
Attempting to impact the trajectory of decline in a chronic andslowly progressive disease is inherently time-consuming.
In Alzheimer’s, Phase 1 human testing takes about 13 months tocomplete; Phase 2 lasts approximately 28 months; and Phase
3 takes about 51 months, followed by an 18-month regulatory
review. The process involves a commitment of nearly 10 years
from bench to bedside—in addition to more than 4 years of
preclinical discovery and testing. That’s about one more year
than average drug development—when everything works asplanned. In Alzheimer’s, it rarely does.7 Development failure
rates have been higher in Alzheimer’s than in almost any otherdisease—99.6% from 2002 to 2012, compared with 81% incancer.8 And there have been many late-stage failures in
Alzheimer’s since then, including two—crenezumab andaducanumab—this year alone.
Future research will likely continue to drive disease-modifying
therapeutics to earlier stages of the disease process—especiallygiven the initial 10-20 year stage of Alzheimer’s in which

pathological proteins are active but there are no clinical symptoms.
However, such trials will require an even greater investment oftime and money.
The development challenges of Alzheimer’s start in the discovery
phase with pre-clinical models. Although several transgenic
mouse models of Alzheimer’s develop clumps of protein, or
plaques, to serve as a target for amyloid-beta therapies, thesemouse models differ from humans in significant ways. They do
not develop the full spectrum of the human disease. They are
missing tau deposition and loss of neurons, and have only alimited inflammatory response. A further challenge for Alzheimer’sis that small molecules—chemical drugs, rather than complex
protein-based drugs—must penetrate the blood-brain barrier,and a molecule that does so in a mouse model does not always
do the same in humans.
The challenges continue in human testing. There is a mismatch
between the progression of the disease, based on the buildup of
pathological proteins in the brain, and the symptoms describedby patients and observed by clinicians. Clearly delineating
the stages of disease progression is still imprecise and potentially
inaccurate, yet has been required to define groups for standard
clinical trials. This mismatch is further complicated because therates of decline among individual patients span a wide range—
due to differences in genetics, experiences, exposures, andthe presence or absence of other maladies of the aging brain.
Some patients present with amyloid, but then never develop
the symptoms of Alzheimer’s. Others develop dementia, but not
Alzheimer’s dementia. These variations among patients makeit difficult to see clearly whether a treatment is having a desired
effect in the right set of patients.
A key part of the solution to these challenges is biomarkers.
They could stand in for, and even predict the progressionof, Alzheimer’s—in the same way blood pressure measurement
is a biomarker for hypertension and hemoglobin A1C is abiomarker for diabetes.
Potential biomarkers for Alzheimer’s are now routinely integrated
into clinical trials, including brain imaging agents visible withpositron emission tomography (PET) scans or measurements of
cerebrospinal fluid (CSF) ratios. However, finding a biomarker
that conveniently allows clinicians to track patients’ response
to a treatment has proved elusive. Yet this last use may be
the most critical in such a slowly progressive and individuallyvariable disease.
Negative clinical trial findings exemplify the importance ofusing biomarkers to select trial participants. In some studies,approximately 25% of participants clinically diagnosed withmild Alzheimer’s and selected for clinical trial participation werelater shown by amyloid imaging not to have brain amyloid
consistent with Alzheimer’s.9 Still, some trials that have usedamyloid biomarkers have also failed, suggesting other factors
may be contributing—such as lack of adequate engagement
between the experimental drug and its intended target in thebrain or failure to identify the maximum tolerated dose.

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113

FIGURE 6.2

Pipeline of experimental Alzheimer’s medicines99

Molecules
in Phase 2 & 3

22

13

39

25

Amyloid

Tau

Otherdisease-modifying
therapies*

Symptomatic

Source: ResearchersAgainstAlzheimer’s, 2018.
*Includes therapies that target inﬂammation, neurotransmission, and vascular and metabolic contributions to Alzheimer’s disease.
Other therapies attempt to promote growth of neurons and synapses, to protect neurons from damage, or to reverse brain damage via stem cell therapy.

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Until a disease-modifying therapy demonstrates a significant
slowing of the decline of Alzheimer’s, the interpretation of
biomarkers will likely remain challenging. This presents achicken-and-egg problem. To prove a biomarker works requires
testing a drug over many years to show it successfully slows thedecline of Alzheimer’s. Yet the expense and practical realities
of Alzheimer’s testing make such a long trial difficult, if not
impossible, without an accepted biomarker.
This will likely not be a one-time problem. Researchers now
generally expect that successful treatment of Alzheimer’s will
come through a combination of therapies—as is the casewith the cocktail treatment for HIV. A successful combination
for Alzheimer’s could pair a molecule that blocks amyloid
formation with an agent that removes amyloid plaques.
Or multiple molecules that function as anti-amyloid, anti-tau,
and anti-inflammatory agents could be deployed simultaneously,
or in series, depending on the stage of the disease. Any trialsof combination therapies will be considerably more complex
than trials with a single agent.
Overcoming the increasing length and complexity of Alzheimer’s
clinical trials requires innovative policy responses. Breakthroughsin therapy in the past have almost always been coupled withbreakthroughs in regulatory standards. That was true whendeveloping medicines for oncology, AIDS, and other diseases.
It is needed now in Alzheimer’s.

The need for policy innovation
Innovation can change the math of Alzheimer’s that challenges
governments around the world. But to do that, governments
need to change the math for innovators. Currently, the extra
time and high failure rate for Alzheimer’s medicines make thecosts of bringing one through the regulatory process more thandouble the highest estimate for overall drug development.10
Yet current policy offers a relatively fixed period during which
an innovator can recoup those costs. Innovators are incentivized
to focus their investments elsewhere—in disease areas withfaster clinical trials and lower failure rates.
Pharmaceutical companies are studying more than 20 times
as many drugs for cancer than for Alzheimer’s, even though
the global societal costs of each disease are about the same.11
Empirical analysis of clinical trials has shown that private
funding flows to cancers, and stages of cancer, where potential
survival times are shorter—because the longer trials neededfor earlier interventions or for slower-progressing cancers
consume too much of a drug’s patent life.12
Various solutions have been put forward to address the
problematic math of Alzheimer’s drug development.
Below we describe five categories of policies that could
make a difference.

funded research often produces insights into biology that create
the conditions for the development of new medicines.13 So
governments should maintain or even increase their funding for
research for Alzheimer’s.14
Start-up companies and private investors, along with large
pharmaceutical companies, are also critical in this ecosystem.
The vast majority of new drugs are discovered and developedby private efforts.15 So governments should also take greatcare to create the best environment to enable private efforts toadvance drug development.
One Alzheimer’s drug tested by our company, Eli Lilly andCompany, shows this ecosystem in action. The protein, called
solanezumab, was discovered via a collaboration with Lilly
scientists at a university that receives both private and publicresearch funding. When Lilly moved solanezumab into Phase
3 testing, it helped fund those studies via a partnership with anoutside hedge fund. Later studies of solanezumab relied ona brain imaging biomarker developed by a small biotech firm,
which Lilly has since acquired. Solanezumab showed small
effects but not enough to be clinically meaningful. We are now
working with public partners to test solanezumab at four times
the previous dose.
Innovative funding
There is a need for innovative funding approaches—especiallyin the earliest and riskiest phases of drug discovery research.
Public-private partnerships and open innovation can help inprecompetitive areas, such as biomarker development, bettermodels of Alzheimer’s disease, and big data analytics to identify
and stratify patients. Other possibilities include crowd-funding,patient advocacy group funding, prizes and government R&D
contracting. Governments can help to integrate the disparate
set of current funding sources—perhaps, as some havesuggested, creating mega funds to advance research.16 Somehave even proposed advance market commitments, in which
innovators promise to offer a new drug at a lower price while
donors make a long-term contractual pledge to pay a “top-up”
price. We concur with various scholars that these efforts, ona voluntary basis, are welcome additions to the search for aneffective therapy.17
However, with biopharmaceutical companies sponsoring or
co-sponsoring more than 70% of Alzheimer’s clinical trials,18
the biggest thing governments can do is change the math forthese companies. The next three categories aim at that goal.
Faster testing
In recent years, biopharmaceutical companies have worked toreduce clinical development periods through gains in operational
efficiency and statistical methodologies that permit shorterand smaller trials.19 But these efforts are inadequate in the faceof Alzheimer’s because of two major challenges.

Research
Drug development has always operated in an ecosystem of
researchers in public and private organizations, both large andsmall, sustained by a mix of public and private funds. Publicly

First, a constant challenge in clinical trials of Alzheimer’s therapies
is getting patients enrolled. There are significant barriers—bothscientific and psychosocial—to diagnosing patients. Half or moreof dementia patients are not clinically diagnosed—far higher

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than other diseases.20 Because existing biomarkers such as PET
imaging are not widely available—or widely reimbursed—diagnosis
in the pre-symptomatic phase can be especially difficult. Also,
doctors are reluctant to commit to a diagnosis of Alzheimer’s
when they can offer no effective treatment.
In response to the challenge of patient enrollment, governments
and other groups could help by organizing advanced patientregistries of well-characterized candidates for clinical trials.
As it becomes ever clearer that Alzheimer’s begins damaging
people’s brains years before symptoms show up, it is morecritical that public and private health plans offer coverage fordiagnostic tests that do exist. It may not be prudent to open
coverage to everyone. But the willingness of health plans to
pay for tests at the earliest signs of cognitive change would
provide a significant stimulus to the makers of medical anddigital technologies to push for even better and easier-to-use
diagnostic tools.
The second big challenge in Alzheimer’s clinical trials is theendpoints required by regulators. The ultimate goal is to finda disease-modifying therapy that changes clinical symptoms—
slowing the decline in thinking and daily functioning. But to getto that point, it may be necessary for regulators to experimentwith surrogate endpoints of Alzheimer’s. In cancer, regulators
have long accepted progression-free survival as a surrogate
endpoint for new drugs—even though the ultimate goal isalways overall survival for patients. Alzheimer’s trials need similar
flexibility from regulators. The field may not yet know what
the Alzheimer’s version of “progression-free survival” is. But
regulators could approve a new Alzheimer’s medicine that provessafe and shows progress against a surrogate endpoint—andthen require a pharmaceutical company to gather the real-world
evidence and long-term data necessary to see if the surrogate
endpoint successfully predicted improvement in later symptoms.
In the United States of America (U.S.), the Food and Drug
Administration (FDA) has this kind of accelerated approvalauthority—which was granted in the early 1990s to find solutions
to the HIV/AIDS crisis. Former President Obama’s Council ofAdvisors on Science and Technology recommended that the
FDA use this authority broadly by approving more drugs basedon surrogate endpoint results.21 Such policies, if adopted byregulators worldwide, would encourage innovators to keep
working on slow-progressing diseases, like Alzheimer’s.
Intellectual property
Patents provide 20 years of protection for a new medicine.
But that 20-year clock starts years before a medicine is approvedfor sale. Patents are necessarily filed before any public disclosure,which typically is before human testing begins. The result isthat every extra year of clinical testing means one less year
in patent-protected sales. Over the past two decades, averagepost-approval patent life in the U.S. and Europe has fallen to
13 years—even including the impact of patent-term extension
policies.22 The combination of lengthening development
timelines and fixed patent terms creates a perverse incentive
for innovators to give high priority to molecules with fasterdevelopment times, rather than to the medicines patientsneed most.

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For this reason, the single best thing governments can do to
incentivize development of a drug that will slow Alzheimer’s isto create more uniform and sufficiently long periods of data
exclusivity. There is a patchwork of terms of data exclusivity
around the world—with protection running from as high as
12 years to as low as zero. Many countries also have shorter
periods of data exclusivity for traditional small molecule drugs
than for biologics.23 These inconsistent terms mean a drug thattakes a long time to develop—running out most of the years
on its patent—must rely on data exclusivity in fewer countries
to recoup the capital and risk expended to develop it. It also
skews research arbitrarily toward biologic drugs—even though
they may not be the best way to treat a disease. In short,weaker data exclusivity policies mean less money invested in
fewer medicines for difficult and slow-progressing diseases
like Alzheimer’s.
Lilly has experienced this dynamic first hand with solanezumab,
which we continue to test in Alzheimer’s patients. The U.S.
patent on solanezumab will expire in 2021. Yet Lilly continues tomanufacture and test this molecule because the data exclusivity
we have—12 years in the U.S. and 10 years in Europe—offerssome potential to recoup our continued investment. Without
data exclusivity, solanezumab—and many other promising
compounds without adequate patent protection—would havealmost no hope of reaching patients.
We recognize that extending data exclusivity is an unpopular
idea to many who believe the key to pharmaceutical affordability
is to reduce the duration of intellectual property (IP) protection.
We believe, however, that an appropriate period of data
exclusivity is essential to generate the investment necessary
to create a sufficient supply of disease-modifying Alzheimer’s
medicines to begin with. A strong IP system, in the long run,produces more breakthroughs today and provides morebargains tomorrow. Even a disease-modifying therapy for
Alzheimer’s would, after about 13 years, be sold for a small
fraction of its initial price and would continue delivering value
to patients and health systems for decades. In our view, nothingin healthcare is more productive.
Reimbursement
It is always healthy to ask for proof that any healthcare service isworth its cost. The evidence for pharmaceuticals is encouraging.
An analysis of 15 developed countries found that those that
introduced the newest medicines soonest saved the most on
hospital costs—US$2.50 saved for every US$1.00 extra spenton the latest pharmaceuticals.24 In addition, a recent analysis of
the U.S. Medicare health plan for seniors found that growth inother healthcare spending slowed significantly after Medicare
started paying for prescription medicines.25
The problem is that few, if any, government-funded healthprograms financially reward a pharmaceutical that enables
reduced spending in other areas—such as, lower hospital costs
or doctor fees. Funding for pharmaceuticals is typically separate
from hospital and doctor care, which is separate from nursing
home care. Government officials that oversee these funding
streams work separately to control costs, without trying tocalculate how spending in one stream might save money inanother. To prepare for the arrival of a disease-modifying
therapy for Alzheimer’s, governments should create mechanisms
to connect these disparate funding streams.
Mechanisms could include better horizon scanning by government
health programs, followed by restructuring of health systems.
This is what the Government of Australia did in the 1990s and2000s—gradually shrinking the infrastructure and workforce
needed to conduct traditional Pap smear tests for cervicalcancer screening, and shifting resources to simpler and cheaper
polymerase chain reaction (PCR) testing.26
Mechanisms could also include outcome-based contracts.
Because the clinical and economic value of a disease-modifying
therapy for Alzheimer’s may not be completely clear at launch,
it may make sense for governments to pay a portion of a drug’s
cost up front, with additional payments made over time only
if patients taking the drug show slower disease progression.
Other innovative payment models that could work in Alzheimer’s
are prices that vary based on patient severity; a “Netflix” modelof pricing that smooths out costs to payers; or, in the case ofmultiple therapies, combination pricing.27
Funding streams could even be connected via the sale ofsocial impact bonds, which have been used to fund recidivism
programs in the U.S. and the United Kingdom. In the case of a
successful disease-modifying therapy for Alzheimer’s, sellingsuch bonds could raise private money to enable a government
to fund payments for the new medicine. The government
would repay bondholders only if, years later, savings on
nursing home care materialize, freeing up the funds needed
to repay bondholders.

Conclusion
Governments face a clear choice today. Unless public policies
steer private funding to difficult diseases with long development
times and high failure rates—and do so strongly enough togenerate multiple successful therapies—Alzheimer’s will likely
remain an ongoing health and budgetary challenge. If, instead,governments around the world act to change the mathfor innovators—by accelerating testing and strengthening
incentives—they will provide the certainty that drug developers
need to take on the biggest and broadest challenges society
faces, including Alzheimer’s.

7

Cummings, Lee, Ritter et al., 2018; DiMasi et al., 2016.

8

Cummings et al., 2014.

9

Cummings, 2018.

10

Cummings, Reiber et al., 2018.

11

Long, 2017.

12

Budish et al., 2015.

13

Cleary, 2018.

14

Grabowski et al., 2015.

15

Chakravarthy et al., 2016; Kneller, 2010 (76% of new drugs
approved from 1998 to 2007 were discovered inside drug companies,
compared with 24% by university researchers); Sampat et al.,2011 (of drugs approved from 1988 to 2005, 9% had public-sector
patents; 48% had some public-sector influence).

16

Cummings, Reiber et al., 2018.

17

Cummings, Reiber et al., 2018; Kremer, 2010.

18

Cummings et al., 2017.

19

Morgan et al., 2018.

20

Eichler et al., 2014.

21

President’s Council, 2012.

22

Grabowski et al., 2014; Copenhagen Economics, 2018.

23

The U.S. offers 12 years for biologic medicines but five years forchemical, or small molecule, medicines. The EU and Canada offer
10 years for both kinds of drugs. Japan offers roughly eight years.
Australia and Mexico offer five years—although Mexico recently
agreed to 10 years as part of a pending trade deal with the U.S.
and Canada. India offers none, and China offers practically none—
although China has recently proposed adopting a policy of up to
12 years.

24

Lichtenberg, 2018.

25

Cutler et al., 2019.

26

Kearney, 2018; Oortwijn et al., 2018.

27

Multi-year payments and the “Netflix” model have been proposedby the Massachusetts Institute of Technology’s New Drug
Development Paradigms Initiative.

References:
Aitken, M., Kleinrock, M., Simorellis, A., & Nass, D. (2019). The Global Useof Medicine in 2019 and Outlook to 2023: Forecasts and Areas toWatch. Parsippany, NJ: IQVIA Institute for Human Data Science.
Brookmeyer, R., Abdalla, N., Kawas, C. H., & Corrada, M. M. (2018).
Forecasting the Prevalence of Preclinical and Clinical Alzheimer’s
Disease in the United States. Alzheimer’s & Dementia, 14(2), 121–129.

Notes:
1

Jack et al., 2018.

2

Aitken et al., 2019.

3

Patterson, 2018.

4

Brookmeyer et al., 2007.

5

Zissimopoulos et al., 2014.

6

Brookmeyer et al., 2018.

Brookmeyer, R., Johnson, E., Ziegler-Graham, K., & Arrighi, H. M. (2007).
Forecasting the Global Burden of Alzheimer’s Disease. Alzheimer’s& Dementia, 3(3), 186-91.
Budish, E., Roin, B. N., & Williams, H. (2015). Do Firms Underinvest inLong-Term Research? Evidence from Cancer Clinical Trials.
American Economic Review, 105(7), 2044-2085.
Chakravarthy, R., Cotter, K., DiMasi, J., Milne, C., & Wendel, N. (2016).
Public and Private Sector Contributions to the Research &Development of the Most Transformational Drugs of the Last
25 Years: From Theory to Therapy. Therapeutic Innovation& Regulatory Science, 50(6), 759-768.

Chapter 6117

Cleary, E. G., Beierlein, J. M., Khanuja, N. S., McNamee, L. M., & Ledley,
F. D. (2018). Contribution of NIH Funding to New Drug Approvals
2010–2016. Proceedings of the National Academy of Sciences of
the United States of America, 115(10), 2329-2334.

Morgan, P. et al. (2018). Impact of a Five-Dimensional Framework
on R&D Productivity at AstraZeneca, Nature Reviews: Drug
Development, 17(3), 167-181.

Copenhagen Economics. (2018). Study on the Economic Impact ofSupplementary Protection Certificates, Pharmaceutical Incentives
and Rewards in Europe: Final Report. Brussels, Belgium:
European Commission.

Oortwijn, W., Sampietro-Colom, L., Habens, F., & Trowman, R. (2018).
How Can Health Systems Prepare for New and Emerging
Health Technologies? The Role of Horizon Scanning Revisited.
International Journal of Technology Assessment in Health Care,
34(3), 254-259.

Cummings, J. (2018). Lessons Learned from Alzheimer Disease: Clinical
Trials with Negative Outcomes. Clinical and Translational Science,11(2), 147-152.

Patterson, C. (2018). World Alzheimer’s Report 2018: The State of the
Art of Dementia Research: New Frontiers. London, England:
Alzheimer’s Disease International.

Cummings, J., Lee, G., Mortsdorf, T., Ritter, A., & Zhong, K. (2017). Alzheimer’s
Disease Drug Development Pipeline. Alzheimer’s & Dementia:
Translational Research & Clinical Interventions, (3), 367–384.

President’s Council of Advisors on Science and Technology. (2012).
Report to the President on Propelling Innovation in Drug
Discovery, Development and Evaluation. Washington, DC:
Executive Office of the President.

Cummings, J., Lee, G., Ritter, A., & Zhong, K. (2018). Alzheimer’s Disease
Drug Development Pipeline. Alzheimer’s & Dementia: Translational
Research & Clinical Interventions, 4, 195-214.
Cummings, J. L., Morstorf, T., & Zhong, K. (2014). Alzheimer’s Disease
Drug Development Pipeline: Few Candidates, Frequent Failures.
Alzheimer’s Research & Therapy, 6(4), 37.
Cummings, J., Reiber, C., & Kumar, P. (2018). The Price of Progress:
Funding and Financing Alzheimer’s Disease Drug Development.
Alzheimer’s and Dementia: Translational Research & ClinicalInterventions, 4, 330–343.
Cutler, D. M., Ghosh, K., Messer, K. L., Raghunathan, T. E., Stewart, S.
T., & Rosen, A. B. (2019). Explaining The Slowdown In Medical
Spending Growth Among The Elderly, 1999–2012. Health Affairs,
38(2), 222-229.
DiMasi, J. A., Grabowski, H. G., & Hansen, R. A. (2016). Innovation in the
Pharmaceutical Industry: New Estimates of R&D Costs. Journal of
Health Economics, 47, 20-33.
Eichler, T., Thyrian, J., Hertel, J., Köhler, L., Wucherer, D., & Dreier, A.
(2014) Rates of Formal Diagnosis in People Screened Positive for
Dementia in Primary Care: Results of the DelpHi-Trial. Journal of
Alzheimer’s Disease, 42(2), 451–458.
Golde, T., DeKosky, S., & Galasko, D. (2018). Alzheimer’s Disease:
The Right Drug, the Right Time. Science 362(6420), 1250-1251.
Grabowski, H. G., DiMasi, J. A., & Long, G. (2015). The Roles of Patents
and Research and Development Incentives in BiopharmaceuticalInnovation. Health Affairs, 34(2), 302–310.
Grabowski, H., Long, G., & Mortimer, R. (2014). Recent Trends in
Brand-Name and Generic Drug Competition. Journal of Medical
Economics, 17(3), 207-214.
Jack Jr., C. R. et al. (2018). NIA-AA Research Framework: Toward a
Biological Definition of Alzheimer’s Disease. Alzheimer’s &Dementia, 14(4), 535-562.
Kearney, B. (2018). Cervical Cancer Screening Australia. Presentation to
the HTAi Global Policy Forum.
Kneller, R. (2010). The Importance of New Companies for Drug
Discovery: Origins of a Decade of New Drugs. Nature Reviews
Drug Discovery, 9, 867-882.
Kremer, M., & Williams, H. (2010). Incentivizing Innovation: Adding to the
Tool Kit. Innovation Policy and the Economy, 10(1), 1-17.
Lichtenberg, F. R. (2018). The Impact of New Drug Launches on
Hospitalization for 106 Medical Conditions in 15 OECD Countries,
2002-2015: A Triple-Differences Analysis. Presentation to theAmerican Society of Health Economists 7 th Annual Conference:
Economics and Public Health.
Long, G. (2017). The Biopharmaceutical Pipeline: Innovative Therapies
in Clinical Development. Boston, MA: The Analysis Group.

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ResearchersAgainstAlzheimer’s. (2018). The Current State of Alzheimer’s
Drug Development: 2018 Alzheimer’s Drug Pipeline—Phase 2 and3. Chevy Chase, MD: UsAgainstAlzheimer’s.
Sampat, B.N., & Lichtenberg, F.R. (2011). What Are the Respective Rolesof the Public and Private Sectors in Pharmaceutical Innovation?
Health Affairs, 30(2), 332-339.
Zissimopoulos, J., Crimmins, E., & St. Clair, P. (2014). The Value of
Delaying Alzheimer’s Disease Onset. Forum for Health Economics& Policy, 18(1), 25-39.

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CH AP T E R 7

IMPROVING PATIENTHEALTHCARE THROUGH
VIRTUAL PLATFORMS
Claire Biot, Patrick Johnson, Sébastien Massart, and Nicolas Pécuchet, Dassault Systèmes

It is expected that by 2030, the healthcare system will be
proactive and benefit from knowledge and know-how thatcreate sustainable innovation. The health experience of patients
will be fluid and continuous. Virtual models will represent thehuman body and help in handling diseases. The whole healthecosystem will be oriented towards long-term prevention andpersonalized care.1 These transformations are necessary, butthey cannot happen without digital platforms. How will thesenew platforms change the relationship between patients andphysicians? How will these platforms influence pharmaceuticalresearch and the production of drugs? How will society handle
health in this new era of connectivity? Based on the strong
belief that virtual universes extend and improve the real world,
this article describes the current challenges of the health systemand shows how digital platforms can bridge these frontiers andpromote a more sustainable environment for healthy citizens.

Proactive medicine: from cure to care
Health is a highly precious state of life, which enables individuals
to fulfill themselves, unlimited by anything but their will andenvironment. Maintenance of health is a costly pursuit, as
healthcare spending is projected to reach over US$10 trillion,
nearly 10% of global GDP, by 2022.2 A swift upward trajectoryin global health spending is particularly noticeable in lowand middle-income countries, where health spending iscurrently growing, on average, 6% annually compared with 4%
in high-income countries (Figure 7.1).3
A series of innovations have driven better health for people,
including hygiene, infectious disease prevention, precision
diagnostics, therapeutic devices, biological pharmaceuticalcompounds, and minimally invasive surgical procedures.

However, chronic diseases have never been so common.
Globally, the number of people living with diabetes has risen
from 108 million in 1980 to 422 million in 2014 and is now risingeven more rapidly in low- to middle-income countries.4 Vasculardiseases are the number one cause of death: 17.9 million people
die annually from cardiovascular diseases, representing 31%
of all deaths globally, and over three-quarters of these deaths
occur in low- to middle-income countries.5 In high-income
countries, nearly 50% of citizens suffer from chronic disease
while the other half are diagnosed with cancer during their
lifetime. The current rise of non-communicable diseases (NCDs)
is associated with lifestyle choices—tobacco use, unhealthy
diet, obesity, physical inactivity, and harmful use of alcohol—andenvironmental factors, yet NCDs could be largely prevented byearly detection and appropriate counseling and management.
To face this challenge, healthcare stakeholders—individuals,
physicians, payers, policymakers, and health technology
companies—must converge on digital platforms to connect,
combine and share data, which will allow for global innovationof care that includes social and environmental determinantsof health. Such platforms will allow stakeholders to capitalize
on knowledge about health factors both at the individualand population-level. These data-based approaches will leadto a new human-centered view of healthcare that includes
personalized prevention and support. “Knowledge is the only
good that multiplies, when you share it” and sharing among
patients, caregivers, payers, and regulators will not only provide
information to support better decision-making and service, butwill also expand global knowledge of health and life science—leading to sustainable and accelerated progress.6 By 2030,
the life sciences industry will increasingly shift from reactive toproactive medicine, enabled by personalized health. This new
era will encompass a holistic view of the citizen, where healthwill become a core value of daily life and cities. Digital platforms
will play a key role in this transformation.

Chapter 7

121

FIGURE 7.1

Healthcare spending in 2017 and 2022
GlobalNorth America
Western Europe
Asia & Australasia
Latin America
Middle East and Africa
Transition economies

0■■⊲ Healthcare spending,billion US$

2,000

4,000

6,000

8,000

10,00012,0002022
2017

Source: The Economist Intelligence Unit, data tool accessed on August 16, 2018.

FIGURE 7.2

Top beneﬁts of healthcare technology, top 3 rankings

16%
17%
17%

16%

15%

17%

23%
15%

15%

29%

13%

11%
9%

16%

Quality of life—
living longer &with better health■

Rank 114%

Prevention—being
More accessible
able to prevent
information—giving
disease with nutrition
doctors more
and activity
information to makerecommendations
better decisions■

Rank 2

■

13%

12%

Safety—erasing
human errors
anytime, anywhere

Personalization—
being able tocustomize healthplans for my own
needs

7%

8%

Portability—
being able todispense
medications
without goingto the hospitalNoneof the above

Rank 3

Source: Frost & Sullivan Report in partnership with Dassault Systèmes, 2019.
Notes: Participants were asked to select the top 3 beneﬁts of having technology integrated into the healthcare system in the year 2030. Interestingly, portability ismore important to younger respondents: 37% of 18- to 34-year-olds say that portability is a one of the top three beneﬁts. Quality of life is especially important tothose 55 years of age or older: 36% of the 55+ group rank this as the #1 beneﬁt.

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The Global Innovation Index 2019

Healthy living and quality of life
In a fast-growing technology era, quality of life is the mostimportant benefit citizens expect from healthcare technology
breakthroughs: it is acknowledged as top 1 priority for 29% of
respondents and top 3 for 62% of respondents.7 Preventionis among the top ranking expectations as well, identified as top 3priority for 56% of respondents. Preventive health plans areperceived as having the highest direct impact on people’s health.
Patients also expect higher autonomy through better informationand the ability to dispense treatments at home (Figure 7.2).
This builds a strong link between health and cities. More andmore cities in the world are moving towards a new “cityexperience”, where the interactions between citizens andcity services are transformed. These cities will enter into theplatform era by leveraging data and technology to create more
efficient living environments, improve sustainability, connect
citizens to decisions by sharing information with the public,
and improving the quality of government services. Achieving
this goal requires a harmonious development in all dimensionsof city experience: governance, education, housing, mobility,
infrastructure, connectivity, innovation, energy, and healthcare—a core part of this holistic city experience. The quality, reliability,
and completeness of healthcare infrastructure will be afundamental factor for the global development of cities. As smart
cities create a more valuable citizen experience, “cities of health”
will become more and more attractive. In Virtual Singapore,
intelligent 3D models were set up to improve the experienceof residents, businesses, and government by capturing all
aspects of the city.8 By connecting the dots across citizens,
thinking about experiences, and connecting the virtual andreal world, smart cities reveal sustainable urban solutions tomaintain the health of their growing and aging population.
A new approach will be required to the design of cities
with a new mindset for operating these cities. Mobility andtransportation will be planned to preserve the health of theresidents, social services will be sized based on neighborhood
health indicators, and environmental exposure and air quality
will be crossed with patient health to generate new insights
into emerging risk factors and to trigger personalized
prevention recommendations. Emerging diseases aremonitored continuously to detect clusters of cases and theirlink with infectious agents or pollutants.

Continuous, contextual, andconnected journeys
The fragmentation of the patient journey among different
physicians and professionals, split across disease areas andterritories, leads to “stacking” many disconnected healthservices to provide care to a single person. With the advent of
the experience economy, value is now centered on the patient.
The health industry network—from pharma to healthcaredelivery—is focused on delivering effective and direct outcome
for people’s health. Platform approaches become necessary
to solve the complexity of this health journey. The holistic
model of care for citizen health will provide stakeholders witha sustainable and cost-effective model for development andinnovation. The value of their collaboration on platforms of care
will be patient health, rather than products. These platforms
will connect physicians and care professionals to provide
patient-centered experiences that are fluid and convenient.
The Internet of Experiences (IoE) connects experiences worldwide,
making them accessible everywhere and anytime. This will
enable a shift to remote care and monitoring, leading tomore proactive therapeutic solutions with personalizedrecommendations. For example, healthcare-related smart homedevices are designed to track and manage health at home,allowing savings of healthcare expenditures. A home healthnetwork can include services—that track vital signs, sleep
quality, and other health parameters via wearables, sensors,and devices—or telehealth, which includes information services,education, and care delivery. Wearables will not only be used
for continuous monitoring of health, but they will also serve as
treatment dispensers. The IoE will reshape the care delivery
experience through ambulatory care, telehealth, wearable
devices that monitor vital signs, at-home drug delivery devices
reducing in-hospital treatments, and a wide panel of online
services around prevention and behavior change. Citizens will
increasingly be empowered to monitor and manage their own
health, reaching a new level of autonomy and harmony in theirrelationship with their body.

Personal and collective data
intelligence
Security and privacy of health information are a top priority.
Regulations on personal health data will be progressively
harmonized worldwide. As the patient is positioned at thecore of their own health journey, the right to access and control
personal data becomes more crucial than ever.9 At the sametime, healthcare stakeholders require increased sharing ofhealth data to build collaborative intelligence and to expand
their understanding of healthcare activities. Data is shifting fromthe care of an individual to the care of a population and offers
new opportunities for service and quality improvements.
A data-enhanced platform of care enables siloed data sources
to be integrated and contextualized within the healthenvironment. Platforms, therefore, catalyze collaboration
amongst diverse stakeholders and allow the setup of human
patrimony in every country. Different approaches have been
undertaken to collect patient data at the scale of a population.
In Denmark, the entire country is a cohort scrutinized byintegration of health information sources from claims, electronic
health records, or genomic analysis.10 In the US, the largest evercohort—called “All of Us”—has been launched to gather data
about more than one million people, in order to explore thepotential of precision medicine while taking into accountindividual differences in lifestyle, environment, and biology.11
Anonymization of data has been a key enabler for data sharing
and will contribute to opening the data economy. There areno commonly accepted data sharing standards at this stage,
although these will be required to build the needed trust ata societal level. A first meaningful step in this direction has been
made in Europe with the European General Data Protection
Regulation, which frames the definition of anonymization to

Chapter 7123reduce the risk of reidentification. Technical solutions, such as
blockchain, exist but they are not sufficient by themselves tobuild trust. New processes and institutional approaches areneeded to allow sharing of highly-sensitive data. While modelsof data sharing have yet to be developed, collective data
intelligence will become a cornerstone for continuous learningand an improving healthcare system.

New experiences of healthAs technologies will illuminate new dimensions of patient health,they create new approaches to pre-symptomatic prevention,
early diagnosis, personalized treatment, and home monitoring(Figure 7.3). Invisible factors and hidden causes become more andmore apparent in the routine practice of care. However, to prevent
disease, virtual models and simulation are required to help
practitioners turn complex data into actionable information.
New ways to prevent: While traditional decision models requirea high level of expertise and include only a few clinical factors,
recent advances in machine learning—when associated withproper scientific knowledge and good medical understanding—
support the use of prediction models based on numerous
factors, such as those generated with recent imaging and genomics.
These new models may guide personalized recommendations
for patients that take into account their individual risk ofdeveloping specific diseases.
New ways to diagnose: The convergence of high-definition
technologies is leveraged in neurosurgery, where brain imaging
is coupled with functional electro-physiology and per-surgery
investigation in the operating room. Anatomic models enrichedby simulation help define the pathologic zone to be resected,
for instance in the case of epilepsy patients. Virtual twins ofpatients may help guide the surgical plan in orthopedics by
predicting the functional outcome. This new way of prescribing
based on a predicted patient outcome—which is nearly
impossible today—will increase safety and help patients better
understand medical decisions before they undergo surgery.
New ways to cure: Virtual reality is advancing as a new treatment
modality—evidenced by 3D printing, which is developing toprovide a range of personalized applications in the healthcare
sector. Applications are currently limited to prosthetics,
pre-surgery anatomical models, and custom surgical tools
manufacturing. However, by 2030, the technology could be
used to print prescription drugs or 3D print new tissues ororgans based on a 3D model of a patient’s own organs.12
Based in Paris and Boston, Biomodex already exemplifies thesenew possibilities: this start-up company provides 3D printed
anatomical models to help surgeons prepare for complex anddifficult surgeries. The idea is that personalized 3D printed
models enable physicians to gain a better understanding of thepatient’s unique anatomy and better plan complex procedures.
Organ imaging, via an MRI or scanner, generates data that isused to create a virtual 3D model of that organ, which can thenbe printed using a 3D printer. While bio-printed 3D organs may
emerge as a future game changer, 3D printing will first be used
for the personalization of implanted medical devices, such as

124

The Global Innovation Index 2019dental and orthopedic prostheses. The technology is not yet
mature to produce an entire organ, but 3D bio-printers that use
nanotechnology can already print live skin-based organs within
hours and opens to powerful skin care applications. A survey
shows that 71% of citizens think that on-demand 3D printedorgans will directly impact their health.13
New ways for care at home: Patient benefits may be maximized
at home by reducing the risk of various hospital-related
complications, such as infection decubitus complications andloneliness. Home care delivery requires a complex infrastructureand network more easily organized in new healthcare platforms
able to collect patient data, diagnose, link patients and medical
professionals, and monitor treatments for safety and efficacy.
The “Living Heart” project provides a powerful example of how
virtual universes will allow the radical improvement of the healthexperience.14 When Dassault Systèmes’ Living Heart Project was
launched nearly five years ago, it was founded on the belief thata digital health transformation must have the patient playing
the central role. The company reimagined a healthcare system
far beyond today’s paper and electronic records—instead taking
the power of the virtual world to capture the best understandingof the body and combining it with a finely tuned ability toperceive subtle details in a 3D world. The project has connectedleading researchers worldwide to create digital twins of acomplete, beating, human heart. The model has already beenused around the world to test a range of medical devices andto reproduce known disease conditions, blood flow disorders,and adverse drug effects. Combining 3D models with real-world
medical data yields a powerful foundation for guiding new
device designs and optimizing complex surgical procedures.
The United States Food and Drug Administration (FDA) has set
a goal to create a population of 3DEXPERIENCE twins—models
which replicate the real-world experiences of a population andreveal how a group of patients will react to new devices. The
hope is that, linked with a comprehensive digital assessment ofsafety and performance outcomes, innovation will accelerate
and regulatory burden will lessen. One day, this approach may
be translated into a patient record where the complexity of yourclinical data is seamlessly combined with accurate virtual reality
representations of your body. This data will be hosted in thecloud, securely under your control, and accessible anywhere—
from your mobile phone to the offices and surgical suites of yourhealthcare team.

New business model calling for a
new platform“I will prevent disease whenever I can, for prevention is preferable
to cure.”15 Health systems are shifting from curative medicine
to preventive approaches, by enrolling citizens and professionals
in value-based economic models instead of volume-based
funding. The value is now the patient experience. A value-based
approach requires reforming an entire model of regulation andevaluation where payments are made for activity to a system
where payments are tied to patient-centered value and quality.
Europe is leading this new model adoption; Sweden and theFIGURE 7.3

PR

RE

E

VE

CA

Creating the continuum of careNT
ION

CITIZEN HEALTH

A

GN

RE

DI

OS

IS

CU
Source: Dassault Systèmes.

Chapter 7125United Kingdom are the only countries with high alignment
between payments and value.16 Until now, the value of healthproducts had to be demonstrated by means of clinical trials
in a pre-specified patient population. This process is long andexpensive and is challenged by a high risk of failure in real life
conditions. The current paradigm of clinical trials is expected
to become more decentralized, more inclusive to diverse
populations, and more able to rapidly adapt in real time during
trials so that the right population—even in the case of small
cohorts—is rapidly identified in order to deliver the highest
benefit. Clinical trials are also expected to increase their validity
in the real world. Real-world evidence is the clinical evidence
regarding the usage and potential benefits or risks of a medical
product derived from analysis of real-world data, as promotedby the U.S. FDA.17 Real-world data are collected from various
sources including, but not limited to, clinical trials, prospective
and/or retrospective observational studies, medical healthrecords, claims, and mobile and wearable devices. These
data have the potential to complement clinical trials; increaseknowledge for therapeutic innovations, pragmatic care, andprevention practices; lead to better designed and conductedclinical trials; and measure the real-world efficacy of a drug or
a prevention. Payers will become more capable of setting pricebased on patient efficacy.
As precision medicine is delivered on platforms of care,
individual patient value can be assessed and used to support
policymaker decisions and payer engagement, leading to a
new value-based model of care that moves from product tooutcomes and holistic care.

Workforce of the future
The physicians, nurses, and professionals who provide direct
patient care are essential to the success of the healthcare
system. While nations and policymakers are developing
educational programs to maintain the right number of skilled
people, practicing is a key aspect of healthcare training.
Pragmatic and manual skills are learned by experience,
therefore, 3D and virtual worlds could play a role in scaling
and extending current capacities. The increase in, and rapid
evolution of, knowledge are less compatible with traditional
learning materials, such as textbooks, which are being replacedby online knowledge services to access the right information at
the right time. Professionals are facing less time with patients,
more time for bureaucracy, and more complex care activities
for dependent and aging populations with multiple concurrent
pathologies. One measure of these changes is the average
duration of a consultation, which is constantly decreasing.
In 18 countries representing about 50% of the global population,
patients spend five minutes or less with their primary care
physician.18 Fragmentation of the care processes across multiple
organizations and professionals requires enablers of goodcommunication. On the new collaborative platforms of care,every caretaker can share a holistic vision of their patients,
create a relationship of listening and trust with patients, sharepatient-defined objectives of care, and make ethical decisions
collectively. Healthcare is thus becoming a continuous and fluid
journey, empowering practitioners and professionals to deliver

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The Global Innovation Index 2019the best health experience to patients and citizens.

Notes:
1

Hood et al., 2012.

2

Deloitte, 2019.

3

World Health Organization (WHO), 2018.

4

World Health Organization (WHO), 2018.

5

World Health Organization (WHO), 2018.

6

Quote by Marie Freifrau von Ebner-Eschenbach.

7

Frost & Sullivan Report, 2019.

8

The “Virtual Singapore” project is championed by the National Research
Foundation (NRF); the Prime Minister’s Office, Singapore; the Singapore
Land Authority (SLA); and the Government Technology Agency ofSingapore (GovTech). It aims to transform Singapore into a “platformcity” in all its dimensions. See: https://www.nrf.gov.sg/programmes/virtual-singapore

9Mikk, 2017.

10

See for instance the “Data Saves Lives” initiative:
http://www.cphhealthtech.com/data-saves-lives

11

See https://allofus.nih.gov/

12

Murphy, 2014.

13

Frost & Sullivan Report, 2014.

14

Further information about the Living Heart project is available at https://www.3ds.com/products-services/simulia/solutions/life-sciences/the-living-heart-project/

15

Hippocratic Oath. See for instance here: https://www.nlm.nih.gov/hmd/
greek/greek_oath.html

16

The Economist Intelligence Unit, 2016.

17

Further information about how the FDA develops an innovative
approach and policy in this domain is available at https://www.fda.gov/
ScienceResearch/SpecialTopics/RealWorldEvidence/default.htm

18

Irving, 2017.

References:
Deloitte. (2019). Global healthcare outlook, Shaping the future. Retrieved
from https://www2.deloitte.com/global/en/pages/life-sciences-and-healthcare/articles/global-health-care-sector-outlook.html
The Economist Intelligence Unit. (2016). Value-based healthcare: A global
assessment. Retrieved from http://vbhcglobalassessment.eiu.com/
Frost & Sullivan Report in partnership with Dassault Systèmes. (2019, January).
Experiencing city life in 2030: trends & perspectives. Retrieved
from https://discover.3ds.com/experiencing-city-life-2030-reportHood, L., & Flores, M. A. (2012, September 5). Personal view on systems
medicine and the emergence of proactive P4 medicine: predictive,
preventive, personalized and participatory. N Biotechnol. 29(6), 613-624.
Irving, G. et al. (2017, November 8). International variations in primary care
physician consultation time: a systematic review of 67 countries. BMJ
Open. 7(10), e017902.
Mikk, K. A., Sleeper, H. A., & Topol, E. J. (2017). Patient Data Ownership. JAMA,
318, 1433-1434. https://jamanetwork.com/journals/jama/article-abstract/2673960
Murphy, S. V., & Atala, A. (2014). 3D bioprinting of tissues and organs. Nature
Biotechnology, 32(8), 773–785.
Sherman, R. E. et al. (2016, December). Real-World Evidence — What Is It andWhat Can It Tell Us? The New England Journal of Medicine, 2293-2297.
https://www.nejm.org/doi/full/10.1056/NEJMsb1609216
World Health Organization (WHO). (2018). Global Health Expenditure
Report. Retrieved from: https://www.who.int/health_financing/topics/
resource-tracking/ghed-update/en/

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CH AP T E R 8

HOW DATA WILL IMPROVEHEALTHCARE WITHOUTADDING STAFF OR BEDS
Kieran Murphy, GE Healthcare

Few other industries are as complex, comprehensive, andfascinating as healthcare. Three major forces are impacting
the sector today: cost, which is skyrocketing at a time when
governments are facing budgetary pressures; access,with 5.8 billion people unable to receive affordable healthcare
across the world; and quality, which global providers havestruggled to consistently offer.
A key ingredient to address all of these challenges is healthcare
data, which exists in abundance. Today, hospitals are producing
50 petabytes of data per year.1 This includes clinical notes,
lab tests, medical images, sensor readings, genomics, andoperational and financial data. Yet 97% of this information
goes unanalyzed or unused. Too often, important patient data
is siloed in different departments, devices, medical records
or even hospitals and, as a result, the care team lacks a fully
informed clinical picture.
The wealth of untapped data has created a path for precision
health—an emerging approach to healthcare that is integrated,highly personalized to each patient, and that reduces waste
and inefficiency.
More effectively integrating data and analytics across the carepathway can better support medical professionals and careproviders with insights that enable predictive, individualized,
and efficient care. Below I’ve outlined key examples of how theeffective utilization of data is improving healthcare outcomes.

Improving the quality of imaging
diagnosis
A staggering 90% of all healthcare data comes from imaging
technology. Hospitals store hundreds of millions of digital
images, and their numbers are growing as imaging scanners
such as MRIs and CTs become better at capturing thinner
and thinner slices of the body, and as 3D and 4D imaging
become the norm.
Humans alone cannot analyze and convert that much data into
useful information. Artificial Intelligence (AI)-powered medical
imaging systems can help radiologists diagnose earlier and treat
patients with emerging or serious conditions sooner.
Let’s look at the potential of harnessing data derived from theoldest form of medical imaging, the X-ray. Just like first
impressions with people, the first clinical image taken helps
set the path going forward. Chest X-rays represent 40% of the
3.6 billion imaging procedures performed worldwide every
year.2 But X-ray “reject rates”, the number of images that cannot
be used due to poor image quality or patient positioning, canapproach 25%.3
To address this, software engineers have developed an
application that helps clinicians pinpoint the root causes ofrejected images.
The app was piloted at the University of Washington Medical
Center and has automated a process that once required
230 mouse clicks and nearly seven hours of work.4 Reducing
these reject rates saves time and resources while putting
patients on the right path sooner.

Chapter 8129

X-rays also provide the first indicator of a potentially collapsed
lung, clinically known as a pneumothorax, a life-threatening
condition that strikes nearly 74,000 Americans each year,5
which can be deadly if not diagnosed quickly and accurately.6
A pneumothorax occurs when air leaks into the space
between the lung and chest wall. This air pushes on the outsideof the lung and makes it collapse. It can be caused by trauma,
cigarette smoking, drug abuse, certain lung diseases, or bycomplications from surgery.
Today, patients who present with symptoms associated withthis condition receive a chest X-ray, which can take anywhere
between two and eight hours for a radiologist to read.7
Clinicians are looking for ways to read chest X-rays faster andin a more prioritized manner to enable a quicker diagnosis.
A new X-ray algorithm uses data to identify potential
pneumothorax cases at the point-of-care to enable prioritizationof image review. Through simple red and green lights thatflag critical cases, technologists taking the scan know whether
this is a patient whose images need to be read immediately.
When a suspected pneumothorax condition is identified,
the point-of-care notification alerts the clinical team, enablingprioritization of image review and potentially changing the
trajectory of the patient.

Helping doctors make clinicaldecisions across specialties
According to the International Agency for Research on Cancer,
an estimated 18.1 million new cancer cases were diagnosed
globally in 2018, and 9.6 million people died from the disease.8
In oncology, speeding up diagnosis, improving accuracy,and enabling more individualized treatments offers great clinicalpotential for doctors, researchers, and patients.
Yet, reports show that the process of preparing for, conducting,and documenting tumor board meetings is frequently
suboptimal and non-standardized,9 with each specialist
aggregating data in a silo. As a result, clinicians can develop
perspectives based on an incomplete view of a patient, andmeetings are spent switching back and forth between
different systems and portable technologies used across eachdiscipline. These inconsistencies and inefficiencies can leadto wasted time, decreased engagement, and could evennegatively impact patient outcomes.10
An alliance between Roche Diagnostics and GE Healthcare
aims to combine and analyze patients’ in vitro diagnostic data—
including genomics, tissue pathology, and biomarkers—with
their in vivo medical imaging and monitoring data. When
combined with the increasing availability of big data andadvanced analytics, a patient can be placed quickly within thecontext of a broader evidence base.
Co-developed tools present a patient’s in vivo and in vitro
information alongside not only patient records but also medical
best practices and the latest research outcomes, helping

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physicians make more informed, earlier, and faster diagnoses
and helping them determine the most appropriate, individualized
treatment for a specific patient.
Among the tools in development is cloud-based software thatwould fundamentally change the process of tumor board
meetings that bring together clinicians from multiple disciplines
to discuss the diagnosis and treatment plan for cancer patients.
Lack of effective data integration can also prevent cliniciansfrom understanding the root cause of an illness and may hinder
informed decision making when it is most crucial, including inacute situations, such as identifying the onset of sepsis. Without
quick treatment, sepsis—a common but serious complication
arising from an infection—can cause multiple organ failure.
It is estimated to affect more than 30 million people worldwide
each year, claiming the lives of 6 million patients.11
Roche and GE Healthcare are working to create an AI-enabled“virtual collaborator” to integrate data from electronic medical
records with other hospital systems to provide insights into thestatus and trends of patients who are at-risk for sepsis-related
deterioration. The virtual collaborator aims to highlight andintegrate the detectable, but potentially undetected, data.
Giving providers the ability to access and analyze patient
information across specialties through a single solution,in their existing workflow, empowers them to deliver the kindof care that is expected today—precise, data-driven, andevidence-based.

Using data to individualize
precision therapies
Integrating valuable data can have transformative effects not
only in a hospital or patient-facing setting but across thehealthcare ecosystem. We have recently begun a partnershipwith Vanderbilt University Medical Center (VUMC), essentiallydrawing on data to enable safer, more-precise immunotherapies.
Immunotherapies use the immune system to recognize
and attack cancer cells and can be more effective than traditional
treatments, but response rates are often low and side effects
can be severe.
Together, we will retrospectively analyze and correlate theimmunotherapy treatment response of thousands of
VUMC cancer patients with their anonymized demographic,
genomic, tumor, cellular, proteomic, and imaging data.
We will then develop AI-powered apps that draw on this datato help physicians identify the most suitable treatment foreach individual patient.
Not only will these techniques help predict the efficacy of an
immunotherapy treatment but also its adverse effects for a
specific patient, before the therapy is administered. This would
allow physicians to better target immunotherapies to the rightpatients and avoid potentially damaging, ineffective, and costly
courses of treatments.

Addressing capacity, safety,
and quality

Catalyzing the transformationof healthcare

In the 1960s, airports started using air traffic control technologythat allowed them to swiftly transition from scheduling a few
hundred flights a day to managing thousands. Now, many
airports handle millions of passengers every day. Despite thevast complexity of such a logistical challenge, the airline industry
also became significantly safer and more efficient along the way.

Even though these techniques will change the interaction
between doctors and patients and change how care is delivered,they should not be overtly noticed but rather they should
seamlessly integrate the existing care continuum—embedded
into workflows, processes, applications, and devices alreadyin use today.

This “air traffic control” concept soon spread to other industries.
Online retailers use data and technology to predict whencustomers need their next batch of vitamins. Brick-and-mortar
businesses and restaurants use it to track busy times andappropriately staff those periods.

This won’t happen overnight, but opportunities to deliver
precision health already exist throughout the global healthcare
ecosystem, from integrated digital diagnostics and AI-based
clinical decision support to precision therapeutics likeimmunotherapies and 3D printing for treatment planning,telehealth, and remote patient monitoring. These are justthe beginning.

Now the healthcare industry is implementing its own “air traffic
control”. A small but growing number of hospitals are
implementing NASA-style Command Centers, designed toserve as a central mission control across a hospital’s functions
and services. The goal: address the capacity, safety, quality,
and wait-time issues that have plagued healthcare.
A Command Center constantly pulls in streams of data frommultiple systems at a hospital. Using simulation, algorithms, andAI, the system will generate predictive analytics that will help
staff recognize patterns in real-time and predict what will
happen in the next 24 to 48 hours. Advanced algorithms help
staff anticipate and resolve bottlenecks in care-delivery before
they occur, recommending actions to enable faster, more
responsive patient care and better allocation of resources.
The data is displayed not only on the Command Center screens
but also on tablets and mobile devices. All of this allows thestaff to prioritize and focus on delivering care rather thanorganizing it.
Johns Hopkins Hospital in Baltimore, Maryland was an early
adopter of the Command Center, which helped themtransfer patients to other hospitals 60% faster, reduce wait
times in the Emergency Department by 25%, and decreasetime spent waiting in the operating room for a post-surgicalbed by 70%.
Industry experts say that this type of digitization is not only
inevitable but is just the beginning. Deloitte’s Center for Health
Solutions report cites centralized digital centers to enabledecision-making as one of the major changes the hospital of the
future will need to implement to function in a world of evolving
technologies, demographic shifts, and economic changes.12
According to the report, AI can continuously monitor the data toalert hospital operators and caregivers, enabling more efficient
care and better outcomes. Through big-data analytics, machinelearning, and AI, patient harm—or unintended consequences—can be predicted before it occurs and suggested interventions
can be fed to caregivers. For example, using data on admissions,inter-facility transfers, and predictive analytics on possibledays for discharge, command centers can help staff manage
patient flow and improve care delivery, better manage lengthsof stay, and enhance the discharge process.

These tools will quickly feel natural, making way for a more
personal doctor-to-patient experience.

Conclusion
To deliver better quality healthcare at a lower cost to more
people, healthcare needs to become more personalized,
more digitally integrated, and more collaborative. Effective
integration of useful data is the key to this transformation.
Advanced analytics teams have made significant progressover the past few years, and we are already seeing the impact
in pockets of healthcare. The potential is exciting, but there
is a lot of work to be done.
Harnessed effectively, data and analytics can increase theefficiency of health systems, offer insights to support clinicaldecisions, better organize care, and even help to predict future
health events. Ultimately this all means more effective, precise,and individualized healthcare with better outcomes for patients,
providers, physicians, and healthcare staff.

Notes:1

EMC MC with Research & Analysis by IDC, 2014.

2

World Health Organization, 2016.

3

Little et al., 2017.

4

GE Healthcare, 2018.

5

Bintcliffe et al., 2014.

6

Morjaria et al., 2014.

7

Rachh et al., 2017.

8

Bray et al., 2018.

9

Patkar et al., 2011.

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10

Foster et al., 2016.

11

Fleischmann et al., 2016.

12

Deloitte Center for Health Solution, 2017.

References:
Bintcliffe, O., & Maskell, N. (2014). Spontaneous pneumothorax. The
BMJ. Retrieved from https://www.bmj.com/content/348/bmj.g2928
Bray, F. et al. (2018). Global cancer statistics 2018: GLOBOCAN
estimates of incidence and mortality worldwide for 36 cancers in
185 countries. Retrieved from https://dx.doi.org/10.3322/caac.21492
Deloitte Center for Health Solution. (2017). The digital hospital of the
future. Retrieved from https://www2.deloitte.com/us/en/pages/lifesciences-and-health-care/articles/global-digital-hospital-of-the-future.html?id=us:2el:3pr:chs3959:awa:chs:100217
EMC MC with Research & Analysis by IDC. (2014). The Digital Universe
Driving Data Growth in Healthcare. Retrieved from https://www.
emc.com/analyst-report/digital-universe-healthcare-vertical-report-ar.pdf
Fleischmann, C. et al. (2016). Assessment of Global Incidence andMortality of Hospital-treated Sepsis. Current Estimates andLimitations. American Journal of Respiratory and Critical Care
Medicine. Retrieved from https://doi.org/10.1164/rccm.201504-0781OC
Foster, T. J., Bouchard-Fortier, A., Olivotto, I. A., & Quan, M. L. (2016).
Effect of Multidisciplinary Case Conferences on Physician
Decision Making: Breast Diagnostic Rounds. Cureus, 8(11): e895.
Retrieved from https://dx.doi.org/10.7759%2Fcureus.895
Little, K. J. et al. (2017). Unified database for rejected image analysis
across multiple vendors in radiography. Journal of the American
College of Radiology. Retrieved from https://doi.org/10.1016/j.
jacr.2016.07.011
Morjaria, J. B., Lakshminarayana, U. B., Liu-Shiu-Cheong, P., & Kastelik J.
A. (2014). Pneumothorax: a tale of pain or spontaneity. Therapeutic
Advances in Chronic Disease. Retrieved from https://dx.doi.
org/10.1177%2F2040622314551549
Patkar, V. et al. (2011). Cancer Multidisciplinary Team Meetings: Evidence,
Challenges, and the Role of Clinical Decision Support Technology.
International Journal of Breast Cancer. Retrieved from http://dx.doi.
org/10.4061/2011/831605
Rachh, P., Ferlay, J., Soerjomataram, I., Siegel, R. L., Torre, L. A., & Jemal, A.
(2017). Reducing STAT Portable Chest Radiograph Turnaround Times:
A Pilot Study. Current problems in diagnostic radiology. Retrieved fromhttps://doi.org/10.1067/j.cpradiol.2017.05.012
The Pulse. (2018). X-Ray marks the spot: Reinventing the world’s oldest
imaging scanner. Retrieved from http://newsroom.gehealthcare.com/xray-marks-the-spot-reinventing-the-worlds-oldest-imaging-scannerhimss18/
World Health Organization. (2016). Communicating radiation risks in pediatricimaging. Retrieved from https://www.who.int/ionizing_radiation/pub_meet/radiation-risks-paediatric-imaging/en/

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Chapter 8

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CH AP T E R 9

CASE OF IAMYIAM—INNOVATING IN PREVENTIVEHEALTH DELIVERY
Lorena Puica, iamYiam
Jack Bauersachs, University of Applied Sciences Deggendorf

Innovation in health delivery has long been associated withtechnical advances in curative care. While this has brought
improvements in treatment outcomes, it has yet to deliver
meaningful progress in mitigating the rapid growth in preventablenon-communicable diseases (NCDs)—which reflect global
trends in the way we work, eat, and live.1
Not only are lifestyle diseases the leading cause of death indeveloping countries, but they also account for, including
mental health, 90% of public and private health expendituresin developed economies.2 Moreover, they reduce themeaningfulness of progress made in increasing life expectancy.
Half of a retiree’s remaining years of life will be significantly
impacted by one or more lifestyle-related illnesses, reducing
the quality of life and adding treatment costs.3
To address this growing issue, lifestyle enhancement andprevention research has expanded and matured significantly
over the last three decades. There are now over 1.8 million
published studies evaluating the effects of lifestyle, diet,traditional therapies, and personal biology on health outcomes.4
With an emphasis on daily lifestyle interventions, thesesustainable health approaches are proven to reduce disease
burden, resulting in lower overall costs and higher impact.5
Over the past decade, this research has translated intoa call for action in medical and health provider communities
and also spawned over 300,000 start-ups focused on
prevention by enhancing lifestyle.6
These include preventive activity booking platforms, such as
BookRetreats; interpreters of biological wellness markers fromsaliva and blood samples, such as 23&me and WellnessFX;
and digital engagement gadgets, such as fitness watches andphone apps that influence behavior by providing real-time
feedback about miles walked, calories burned, or sleep quantity
and inferred quality. There are also digital coaching platforms,
like Omada, that seek to prevent pre-diabetics from requiring
medical interventions.
Growing recognition that prevention is the key instrument for
tackling health care costs is driving governments, insurers,
corporations, and healthcare providers to actively seek newframeworks, as well as innovations and partnerships to foster
widespread adoption of healthier lifestyles. In the United
Kingdom (U.K.), the Department of Health and Social Care has
prioritized spending on new approaches to prevention in orderto reach the government’s mission of enabling its people toenjoy five additional, healthy, and independent years of life.7
An Asian insurance company, AIA, introduced a platform tocreate incentives for members via product discounts andother rewards to engage in preventive activities such as
quitting smoking.8 Fullerton Healthcare has made a long-term
commitment to bring prevention innovations to its millionsof members across Asia Pacific through its recent partnershipwith iamYiam. Moreover, Discovery Health Medical Scheme
offers its South African members a gamified prevention program
called Vitality,9 using inputs from fitness wearables, while
Bupa healthcare targets corporate culture in Australia with its
multipronged wellness programs.10
Nevertheless, prevention is still viewed mainly through the lensof curative medicine. For many, the entry point for engagementwith preventive measures follows a medical diagnosis of
mental or physical symptoms. As a consequence, the medical
community has been the primary recipient of health policy
initiatives focused on prevention, even though there may be

Chapter 9135more effective channels. Institutions that already seek toinfluence the actions of their constituencies, like schools,
employers, and social communities,11 may be in a better position
to promote activities associated with a healthier lifestyle.
Moreover, investment capital earmarked for “preventive”
innovations flows primarily toward technologies that aim to
reduce or revert the progression of chronic disease andpre-morbidity conditions—such as elevated blood sugar, bloodpressure, or cholesterol—rather than toward technologies thatsustain health in the broader, asymptomatic population.
Viewing health as merely the absence of ailments continues todrive the “repair shop” model that dominates institutionalized
health delivery—fixing what is broken. At its core, this paradigm
is reactive, allocating substantial resources to finding fixes
for problems when their burden becomes unmanageable forthe individual and the system itself. Nearly a century ago
smoking was linked by researchers to disease, yet restrictions
on advertising, sales to minors, and product warnings were
initiated decades later—after the burden on public health could
no longer be ignored.12 Similarly, mental health has become
a focus of health policy now that costs from treatment andlost productivity are skyrocketing; by 2030 depression is
expected to be the leading cause of the global disease
burden.13 Centered on medical treatment rather than theindividual’s lifestyle and environment, reactive healthcare has
proven itself unsustainable as it fails to keep pace with thealarming growth in chronic and debilitating diseases linked
directly to unhealthy lifestyles.
This suggests the need for a pre-emptive model that focuseson enhancing an individual’s lifestyle and environment tosupport health in a sustainable manner—every day and lifelong.
Such a model would align with what was commonly considered
preventive for most of written history. Prior to the antiseptic
and public hygiene revolutions in the late 19th century and thedevelopment of antibiotics in the early 20th century, models for
obtaining and maintaining health were holistic and, by necessity,
activity-based—eating, exercising, resting, and thinking right.14
Building on this view, this chapter focuses on how a creative
start-up designed a framework for prevention that leverages
both the time-tested preventive model of health delivery
and cutting edge artificial intelligence (AI) technology toprovide an accessible, sustainable, and affordable solution.
This example traces the development of iamYiam and thechallenges faced in designing and bringing to life thisframework. Following an overview of the vision and conceptbehind creating and delivering scalable prevention, we discuss
how advances in machine learning, genomics, plus heightened
privacy concerns led to essential shifts in iamYiam’s market
development strategy, delivery platform, and business model.
We extend the discussion to look at the impact of regulation
on health delivery start-ups. In the final segment, we reflect
on the key lessons for entrepreneurs and policymakers
engaging with preventive health.

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Necessity—the mother of invention
iamYiam was launched in 2016 to provide the most efficient path
for achieving optimal health—personalized to the individual.
The idea for the company grew out of the experience of thefounder, Lorena Puica, in overcoming her own debilitating
health condition: “Doctors in Germany, as well as in the U.K.,
recommended a course of action—thyroidectomy—that
I disagreed with due to the severity of the implications for myoverall wellbeing. I started researching what the most effective
courses of non-medical action for my condition were and,after a year and a half of experimenting with everything fromyoga, meditation, acupuncture, massage, nutrition, etc.,
I achieved a sustainable state of health without any medicationor other form of medical intervention. What baffled me wasthat, while the path to a science-based medical solution wasstraightforward, an analogous approach to non-medical,
preventive alternatives for my challenges did not yet exist.
I decided to get involved so that no one else would need totake a random walk among anecdotal advice, internet searches,and experimentation to find the best preventive solution.”
Lorena learned through her research that emotions, social
connections, career success, financial security, purposefulaction, and environmental impact are interrelated with biologicaland mental health and—for health to be sustainable—must be
integrated into a new framework. As a former investment
industry professional, she viewed health as an optimization
problem analogous to portfolio theory and investment
decision-making. Just as an optimal investment portfolio
achieves its goals by allocating capital efficiently among a
mix of asset classes, optimal health is the result of an efficient
allocation of time, energy, and nutrients based on an individual’s
biological, environmental, and psychological idiosyncrasies.
Prevention stems mainly from how one allocates the hoursof the day to various activities ranging from sleep to mental
processes and physical exertion, as well as how one thinks,
eats, and acts. At the same time, active measures—including
traditional and modern nonmedical interventions, such asacupuncture and cognitive behavioral therapy—can also be
regarded as preventive activities.
To implement this concept, a team was formed to develop
a research base and build a digital platform to provide
evidence-based recommendations personalized to one’s
biology and preferences. A marketplace was also offered
where vetted practitioners and nutrition providers could offer
members access to tools, therapies, classes, meal plans,
and other resources that appear in some recommendations—such that individual health information, personalizedrecommendations, and resources are accessible in one
health account with lifetime access.

A technical approach toquality of life
The key technological innovation the company developed is acomprehensive framework for understanding an individual’s life
context and goals. It combines biological (genetic), behavioral,
and environmental factors in a predictive model that guides
members to their maximum potential by tracking their progress
toward optimizing the quality of their life. This is modeled by alife quality index (LQI) composed of nine interrelated dimensions,
ranging from the environment to physical health.
At the heart of the platform is an AI agent referred to as See
Yourself Differently (Syd), which acts as an optimal controller.
Syd estimates the current state of being of a person in relation
to their goals and uses platform-wide observations to optimize
specific guidance for reaching one’s desired outcomes. Over200,000 published research papers were referenced to create
the baseline for the predictions that Syd continuously improves
upon via its internal model and interactions with all members.
Progress in an individual’s journey to better health is tracked
and displayed in the member’s LQI as Syd becomes a life
partner—and an accurate, adaptive representation of themember’s state of being.
For example, an individual with a goal of better sleep may havegenetic traits that predict poor caffeine metabolism. Throughanalysis of the behavioral, environmental and biological data
across the platform, Syd might determine that others with similar
genetics, environmental, and personal characteristics—suchas the same postal code, satisfaction with their careers, andlow screen time—might sleep better if caffeine consumption
is followed by five minutes of brisk walking. The individual’s
response to this guidance updates the LQI score and serves as
input for Syd to further personalize recommendations.

Challenges of going to market
A key challenge of bringing this innovation to market was the
product’s complexity. While there had been rapid growth in
the number of adults engaging in preventive activities, few
were actively seeking an all-encompassing system fordelivering qualified guidance on activities tied to their biology
and personality. The goal was to target the market segmentthat most severely felt the need for timely and effective advice
on what steps to take and how to easily access what would
work best for them.
iamYiam.com was launched with a focus on professionals
who were aware of, or had already previously engaged with,preventive practices. The messaging initially focused on theplatform’s efficiency: “We believe that experiencing natural
health must be simpler.” Subsequent customer feedback
pointed toward highlighting evidence-based guidance andother benefits. During the first year, a significant increase in
consumer-oriented genetic testing websites offering ancestry,health risks, and other tests went to market. This exacerbatedthe need for a sharper positioning of iamYiam as an adaptivemodel for preventive health delivery—especially to limit comparison
with genetic testing companies.
This same messaging challenge also applied to fundraising.
The amount of time to develop and test the AI-driven algorithms
meant the company was similar to a pharma start-up—requiring
substantial investment for testing and development before theproduct was complete. Accordingly, market penetration and
ROI were expected to lag the development phase. Venture
capitalists tended to relegate the company to a predefinednarrow category for lack of one with a better fit—either a genetics
services business, a digital health application, or a two-sided
marketplace. Anticipating this challenge, the company aimed its
capital raising efforts at investment angels with a shared passion
for the company’s mission.
To smooth the market penetration strategy, the product was
positioned as an everyday, lifelong companion to support one’s
health, offering evidence-based guidance at every step of theway. A broader market analysis also revealed that employers
would respond favorably to the company’s offering, as many
were actively seeking a single comprehensive preventive
solution for their rising healthcare costs.

Market expansion intobusiness-to-consumer (B2C)
During 2017, iamYiam laid the groundwork for taking its offering
directly to corporations. Employers were becoming acutely
aware that rising rates of obesity and impaired mental healthwere dragging down productivity and raising health insurance
premiums. Depression, which the platform addresses, wasincreasingly becoming a significant cause of absenteeism andlost productivity.
While most corporations that were approached had already
implemented one or several preventive programs, thesewere not tailored to the specific health issues individual
employees faced. Moreover, the expected results were neither
based on scientific evidence nor measured in a way that aided
decision-making. Companies were interested in assessing
the health risks they faced and getting an overall pictureof the state of health of their employees. An executive
dashboard was developed to demonstrate the potential risk
mitigation and return on investment (ROI) from deploying
the platform. Besides calculating ROI, it presented insights
and risks for employee health as a group by pairing preventive
activities with productivity, absenteeism, and other outcomes.
What initially began as a means to demonstrate theplatform’s effectiveness became key features within theiamYiam corporate offering: custom dashboards, employee
memberships, and member support.

Chapter 9137

Regulatory impact
The platform’s AI engine does not perform disease diagnosis.
This allows the company to operate in the prevention spacerather than the medical industry, enabling a faster path tomarket. Such an approach is efficient for addressing the current
market while remaining open to future collaborations with
innovators in disease treatment if, as anticipated, the prevailing
medical model becomes more integrated. Recent researchsupports the view that preventive activities play an importantrole in life quality during and after treatment for disease.15
A new emphasis in medicine on life quality over disease
treatment may lead to innovations in treatment models thatcombine a patient’s historical lifestyle data with treatment
protocols to deliver better health risk predictions and a higher
quality of life. The personalized analysis provided by Syd could
well become a useful input for collaborators developing new
diagnostic methods or treatments that adjust medical measures
to LQI scores or other information from the platform’s data
analysis. In such a case, the genetic tests that many members
undertake to further personalize the guidance they receive
about their activities may trigger more intense regulation as thedata use crosses the line between wellness and clinical use.
Regulation proves to be more of a challenge for dataprotection—however, not for the reasons one would expect.
Coinciding with the product launch, new data protection
requirements were being planned by European and U.K.
policymakers. From inception, personal privacy has been an
overarching goal in developing the iamYiam and Syd platform.
The company made extensive efforts to find the most reliable
technologies available to protect the privacy of personal
data and formed a board composed of thought leaders in ethics
to provide oversight on the collection and use of data. As
a result, the company has been well positioned to meet thechallenge of navigating a continuously changing landscapeof regulation leading up to the recently issued General Data
Protection Regulation (GDPR) and the U.K. Data Protection Act.

Lessons learned
The unpredictability of how policymakers will interpret what isin the best interests of consumers results in resources wasted
on contingency planning. Health start-ups, in particular, must not
only comply with established medical regulations and new interpretations—driven by genetics evaluation and other evolving
methodologies—but also predict the impact of recent regional
directives in data privacy and copyright protections. Local
differences in regulations compel start-ups to weigh possible
compliance stumbling blocks when choosing whether to relocate operations to maintain their speed of development. Ideally,
policymakers will not only consider the intent of the regulations
but the long-term implications for innovators in the digital healthspace. Addressing their concerns early on would avoid
penalizing them with excessive costs and delays in delivering
impact in their markets.
Start-ups can also prepare for changes in rules governing dataand privacy protection by not second-guessing regulators.

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A better strategy is to keep the interests of their customers—therightful owners of data and intellectual property—in mind by
putting themselves in their customers’ shoes at every step of
the product development process. If there is something you
would not enjoy in terms of security, privacy, or data sharing,your customers will reach the same conclusion sooner or later.

Lessons for policymakers:
sustainable health vs. early diagnosis
Prevention strategies and digital technologies need to be at theforefront of long-term planning. Some national health agencies,
such as those in Singapore and the U.K., are focusing theirstrategies on these two areas. Singapore is also an example ofa country ready to partner with health innovators. For instance,
the Singapore Ministry of Health partnered with the U.K. start-up
Tictak to motivate its citizens to improve their lifestyles byinterpreting information collected from fitness wearables, suchas Apple Watch.16
In the U.K., the National Health Service (NHS) is taking the leadin partnering with digital health start-ups to accelerate theinnovation process.17 In that role, the NHS actively solicits the
input of innovators, like iamYiam, on the future of prevention
and how to deliver affordable, accessible health outcomes.
Much more attention is still needed to create innovative
public policies that target prevention where it is mosteffective—before one requires medical diagnosis or treatment.
Public policy would benefit from being primarily directed atsustainable health. This translates into teaching people andproviding the means for them to access activities that enhancetheir lifestyle and environment—as well as rewarding innovators
who create the tools and systems for this purpose. One
example of an agency that directly targets sustainability is
Singapore’s Health Promotion Board, which rewards employers,builders, and landlords for finding innovative ways to prevent
obesity in young workers before it creates serious health issues.18
Rising costs have pushed large corporations to try new models
that more effectively deliver health to their employees. One
prominent example of an innovative model is the cooperative
arrangement formed by JP Morgan, Amazon, and Berkshire
Hathaway to self-insure. This nonprofit venture focuses on
improving care for its one million employees—and eventually
making their innovations available to the 150 million Americans
who get their health insurance through work.19 However, policies
that nudge companies to create new models for healthier work
environments are still needed, which means addressing all
dimensions of their employees’ lifestyle, ranging from financial
security to social interactions.
In closing, although lifestyle improvement is where the highest
return on expenditures is possible, nearly all preventive
initiatives by government services still focus on the “repair shop”
medical model of health delivery—taking action after one isdiagnosed to be at risk for diabetes, heart disease, depression,etc. Preventive technologies have become increasingly
sophisticated for addressing health issues at the pre-chronicand treatment stages, yet they are more burdensome inmonetary and societal terms than other approaches aimed
at root causes. Policymakers who make a concerted effort
to reposition the fundamental health delivery model as anintegrated model with a core focus on the relationship between
health and lifestyle can also effect an improved social climate,beyond the substantial cost savings. Technologies are rapidly
evolving to support this model with tools and systems to guideindividuals to make healthier choices. To ensure that policies
do not hamper innovation, greater dialogue is needed between
governments and those in the vanguard of innovation. Policies
that promote long-term investments encourage innovation insystemic solutions that have long development cycles.
The potential benefits of getting prevention policy right far
outweigh the costs of promoting innovation. Poor lifestylechoices drive health risks that drive chronic disease andhealth care costs. Governments are uniquely positioned toencourage change by shining a light on unhealthy behaviors
and empowering the innovators of tomorrow to bring theirsolutions to global audiences.

References:
Bachinger, E., & McKee, M. (2007). Tobacco policies in Austria during theThird Reich. The International Journal of Tuberculosis and Lung
Disease, 11(9).
Centers for Disease Control and Prevention. (2019). National Center for
Chronic Disease Prevention and Health Promotion (NCCDPHP).
Health and Economic Costs of Chronic Disease. Retrieved fromhttps://www.cdc.gov/chronicdisease/about/costs/index.htm#ref1
Global Entrepreneurship Monitor (GEM). (2019). Global Report
2018/2019. Retrieved from https://www.gemconsortium.org/report
Google Scholar. (2019). Search result information. Retrieved fromhttps://scholar.google.deHealth Promotion Board. (2019). Healthy Workplace Ecosystem.
Retrieved from https://www.hpb.gov.sg/workplace/healthy-workplace-ecosystem
Ivbijaro, G. (2012). System Strengthening Across the Healthcare Sector
to Promote Resilience in a Time of Economic Hardship. World
Federation for Mental Health, 19-22. Retrieved fromhttps://www.who.int/mental_health/management/depression/
wfmh_paper_depression_wmhd_2012.pdf
McEleny, C. (2018, March 5). How a British start-up got involved in
Singapore’s diabetes prevention campaign [Interview]. The Drum.
Minich, D., & Bland, J. (2013). Personalized Lifestyle Medicine: Relevancefor Nutrition and Lifestyle Recommendations. The Scientific World
Journal.

Notes:
1

World Health Organization, 2018.

2

Centers for Disease Control and Prevention, 2019.

3

Salive, 2013.

4

Google Scholar, 2019.

5

Minich et al., 2013.

6

Global Entrepreneurship Monitor (GEM), 2019. The authors madetheir own estimates based on the data in the GEM Global Report.

7

UK Department for Business, Energy, and Industrial Strategy, 2018.

8

Further information about AIA’s corporate wellness program isavailable at https://vitality.aia.com.sg/en/vitality/home.html

9Further information about Discovery’s Vitality application is available at https://www.discovery.co.za/vitality/vitality-active

10

Further information about Bupa’s workplace programs is available
at https://www.bupahealthierworkplaces.com.au/solution/creating-healthier-cultures-social-connection-packs/

11

Ivbijaro, 2012.

12

Bachinger et al., 2007.

13

World Health Organization (WHO), 2011.

14

Petersen et al., 1996.

15

Segal et al., 2017.

16

McEleny, 2018.

17

UK Department of Health and Social Care, 2018.

18

Health Promotion Board, 2019.

19

Tracer, 2018.

Petersen, A., & Lupton, D. (1996). The new public health: health and self
in the age of risk. London: Sage.
Salive, M. E. (2013). Multimorbidity in older adults. Epidemiol Rev, 35, 75-83.
Segal, R., Zwaal, C., Green, E., Tomasone, J. R., Loblaw, A. et al. (2017,
August 31). Exercise for People with Cancer Guideline: A Systematic
Review. Curr Oncol. 24(4), 290–315. doi: 10.3747/co.24.3619.
Tracer, Z. (2018, June 24). Amazon-Berkshire-JPMorgan Health Venture
Takes Aim at Middlemen. Bloomberg LP. Retrieved fromhttps://www.bloomberg.com/news/articles/2018-06-24/amazon-berkshire-jpmorgan-health-venture-takes-aim-at-middlemen
UK Department for Business, Energy, and Industrial Strategy. (2018,
December 13). The Grand Challenge missions. Retrieved fromhttps://www.gov.uk/government/publications/industrial-strategy-the-grand-challenges/missions
UK Department of Health and Social Care. (2018, October 17). The
future of healthcare: our vision for digital, data and technology inhealth and care. Retrieved from https://www.gov.uk/government/
publications/the-future-of-healthcare-our-vision-for-digital-dataand-technology-in-health-and-care/the-future-of-healthcare-ourvision-for-digital-data-and-technology-in-health-and-care
World Health Organization (WHO). (2011, December 01). Global burdenof mental disorders and the need for a comprehensive, coordinatedresponse from health and social sectors at the country level.
Retrieved from http://apps.who.int/gb/ebwha/pdf_files/eb130/
b130_9-en.pdf
World Health Organization (WHO). (2018, June 1). Noncommunicable
Diseases Factsheets. Retrieved from https://www.who.int/en/newsroom/fact-sheets/detail/noncommunicable-diseases

Chapter 9

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The Global Innovation Index 2019

CH AP T E R 10

HOW PARTICLE PHYSICSRESEARCH AT CERNCONTRIBUTES TO MEDICALINNOVATION
Giovanni Anelli, Manuela Cirilli, and Anais Rassat, European Organization
for Nuclear Research (CERN)

Since the discovery of X-rays at the end of the 19th century,
physics has been having a tremendous impact on modern
medicine. Physics phenomena underpin many advanced
techniques and technologies that are routinely used in hospitals
for both diagnosis and treatment of diseases. Radiotherapy forcancer treatment, radiopharmaceuticals, magnetic resonanceimaging (MRI), and positron emission tomography (PET) imaging
are just some examples. In addition, many of the state-of-the-art
technologies behind these healthcare innovations were initiallydeveloped for particle physics research. Some have been
pushed well beyond the industrial know-how by the stringent
requirements of frontier instruments, like the particle accelerator
Tevatron at Fermilab,1 or the Large Hadron Collider (LHC) at
CERN,2 as well as the detectors used in these machines. Particle
detectors and particle accelerators are not only found at CERN
and other particle physics laboratories but are ubiquitous in
hospitals. Accelerators are the core of radiotherapy devices,while PET scanners contain photon detectors. Computer
simulations of how particles interact with matter are also widelyused to model the effects of radiation on biological tissues.
More recently, the healthcare sector has become interested
in artificial intelligence techniques. Personalized medicine, anincreasingly data-hungry discipline, is a major driver of thistrend, which in turn is triggering an interest in the data analytics
techniques being developed by particle physicists to deal with
their large data sets.
There is a giant leap between a bespoke 27-kilometer longaccelerator like the LHC and an off-the-shelf room-sized medical
accelerator. Understanding how the transfer of technologies andknow-how from particle physics to the medtech industry andmedical research happens is a challenge. This knowledge canoffer keys to improve the process and to maximize the impactof basic science on societally relevant topics, such as healthcare.

This article mainly focuses on the example of knowledgetransfer from CERN, the world’s largest particle physics laboratory.
Some of the strategic issues described are relevant for thebroad community of particle physics research and for “bigscience” in general. However, CERN also faces some specificchallenges due to it being a publicly funded internationalorganization with a core mission of fundamental research.

The impact of basic research
Beyond scientific achievements, the search for answers tofundamental questions often leads to major technologicalbreakthroughs. However, measuring the worth of basic research
is not a simple cost-benefit analysis. Often, the impact of basic
research on the medtech market is indirect and difficult to track.
One such case is particle physics’ contribution to modern
medical imaging technology. Today, MRI scanners deliveramazingly detailed images of the human body thanks topowerful magnets engineered with coils of a superconducting
material called niobium-titanium. In the early seventies when the
MRI technique was in its infancy, this material was industriallyavailable only in small quantities, so the first scanners were built
using conventional magnets. At the same time, particle physics
was in dire need of niobium-titanium to build the strong magnets
necessary for the Tevatron particle accelerator at Fermilab.3
This is where the role of big science in pushing technologies
beyond state-of-the-art becomes manifest: Fermilab bought the
raw material in quantities that were orders of magnitude larger
than standard orders for niobium-titanium and worked alongside
manufacturers to achieve the perfect coils for the Tevatron.
This paved the way for commercial use of niobium-titanium in
MRI machines and, later, in medical accelerators.

Chapter 10141

A similar pattern can be found in the history of technology for
PET scanners, often quoted as the epitome of the cross-fertilization
between particle physics detectors and imaging tools.
Experiments at the Stanford Linear Accelerator Center and
CERN pioneered the large-scale use of detectors that are
now ubiquitous in PET scanners. The mammoth scale of thesenext-generation experiments fueled the development ofstate-of-the-art photon-sensitive devices—which are used in thelatest commercial PET scanners.
In some cases, there can be a direct transfer of a technology
developed for particle physics research to medical applications.
A recent successful example is a breakthrough applicationof a chip developed at CERN by the Medipix3 Collaboration
for LHC experiments. Members of the Medipix3 collaboration
founded a company, MARS Bioimaging Ltd., which has been
granted a license to exploit the chip for spectral computed
tomography imaging—X-Ray imaging in color. In 2018, thecompany developed a scanner based on the Medipix3 technology
and managed to take the first 3D color X-ray images of humanbody parts.4 However, such a direct transfer is not common—
particularly in laboratories or institutions like CERN, which havea mandate of pure basic research. In such places, technologies
are developed to satisfy the needs of upcoming or on-goingprojects and are often tailored to the end use in a particle
physics environment.
International collaborations play a vital role also in providing
fertile ground for the application of technologies developedfor basic research to other fields. For example, the Geant4
computing simulation toolkit is developed and maintained by aworld-wide collaboration of scientists and software engineers.5
Today it is adopted by thousands of users worldwide forapplication in a variety of domains, including the study of theradiation environment on the International Space Station as
well as radiation effects on possible future manned space
missions to the Moon or Mars.

Success stories of medtech
applications of CERN technology
CERN is the world’s largest particle physics laboratory, locatedat the border between France and Switzerland. Its core mission
is fundamental research in particle physics. As a publicly fundedlaboratory, it also has a remit to ensure that its technology andexpertise deliver immediate and tangible benefits to society
wherever possible. Other physics research laboratories andinstitutes were early adopters of CERN technologies, thanks
to the highly collaborative nature of particle physics. Since its
creation in 1954, CERN has also been active in transferring
its technology and expertise outside particle physics. The most
known example is the invention of the World Wide Web by
CERN scientist Tim Berners-Lee in 1989, but the laboratory has
contributed to applications in many other fields, from medical
and biomedical technologies to aerospace applications, safety,“Industry 4.0”, cultural heritage, and emerging technologies(Figure 10.1).

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The Global Innovation Index 2019

Applications of CERN technologies and know-how to the healthdomain represent one of the most relevant knowledge transfer
opportunities in terms of potential impact on society.
At CERN, early activities with pertinence to medical applications
date back to the 1970s. At that time, knowledge transfer
happened—mostly serendipitously—through specific initiativesof individual researchers. CERN physicist Georges Charpak notonly opened a new era for particle physics with the detector
he conceived in 1968, for which he earned the 1992 Nobel Prizein Physics, but also strived to ensure that his invention could
be applied in medicine. Charpak’s detector has found important
applications in biology, radiology, and nuclear medicine.
He was a firm believer in entrepreneurship as a tool to transfer
technologies from basic research to society—the company
he founded in 1989 is still active in the field of medical imaging,with a system based on his original detector.6
In 1975, CERN physicists David Townsend and Alan Jeavons
had the idea of using a version of Charpak’s detector for PET
imaging, by looking at the work of a group in Berkeley andUniversity of California, San Francisco (UCSF). Townsend
developed software to reconstruct the data from Jeavons’detectors and, in 1977, they took the first mouse image, with theparticipation of radiobiologist Marilena Streit-Bianchi. PET was
not invented at CERN, but the work carried out by Jeavons andTownsend made a major contribution to its early development.7
After these individual efforts, CERN acted in the 1990s as acatalyst for collaborative endeavors spanning beyond particle
physics: the Crystal Clear and Medipix international collaborations
aimed at developing particle physics detectors and exploring
their applications to other fields, including healthcare.8 Suchcollaborative efforts often provide the much-needed support
to bridge the gap between CERN R&D and the end-user
application. Given CERN’s focus on fundamental research, it is
not surprising that there are a limited number of cases of directtransfer to the healthcare sector, where a technology developed
for particle physics is used “as-is” in a medical device. One
example is the color X-ray scanner mentioned above. Anotherrecent case is a compact, modular, low-cost linear accelerator
manufactured by CERN, which capitalizes on the skills andexpertise developed while designing the laboratory’s latest
linear accelerator.9 The compact accelerator is suitable for
medical applications and has been licensed to a company,
ADAM, that is building a next-generation machine for hadron
therapy, an advanced form of cancer radiation therapy thatuses protons or other ions to treat cancer. Simulation codes
initially developed for particle physics have also become crucial
to modeling the effects of radiation on biological tissues for avariety of applications in the medical field. The FLUKA simulation
package, jointly developed by CERN and the Istituto Nazionale di
Fisica Nucleare (INFN), is licensed to various medtech companies.
A major asset to institutions like CERN is their human capital—
scientists, engineers, and technicians who have the expertise
to develop and maintain innovative technologies and complex
technical systems. For example, in the 1990s, CERN leveraged
this expertise by contributing to a collaborative design study
for a next-generation cancer treatment center that would use

FIGURE 10.1

From CERN knowledge to society

Particle acceleration& control
Cooling & ventilation
Cryogenics
Digital sciences
High & ultra-highvacuum systems
Industrial controls
Magnet technology
Manufacturing& mechanical processes
Material science

MEDICAL& BIOMEDICALTECHNOLOGIESAEROSPACEAPPLICATIONSSAFETY

Metrology
Particle tracking& calorimetry
Power electronics,
optoelectronics& microelectronics
Radiation protection& monitoring
Radio frequency
technology

INDUSTRY 4.0
CULTURAL HERITAGE
EMERGINGTECHNOLOGIES

Robotics
Sensors
Superconductivity
Testing facilities

Source: CERN/Geoﬀrey Dorne.
Notes: Through the laboratory’s main technology pillars—Accelerators, Detectors, and Computing—CERN has developed expertise (left) that have foundapplications in many ﬁelds outside particle physics (right). These represent ﬁelds where a meaningful knowledge transfer has happened.

Chapter 10143both protons and carbon ions.10 This study provided thetechnical background for building two of the four European
centers providing cancer therapy with protons and carbon
ions—the National Centre of Oncological Hadrontherapy(CNAO), Italy,11 and MedAustron, Austria.12 CNAO’s design was
based on the original study, improved by the Foundation forOncological Hadrontherapy (TERA foundation) and realizedwith seminal contributions from the INFN—all based in Italy.
MedAustron was later constructed using the CNAO design.
Beyond the initial design study, CERN had an ongoing agreementwith both treatment centers to provide expertise in accelerators,
magnets, and training of personnel.
CERN also has unique infrastructures that attract the interest of
medtech companies and medical researchers. One example is
the CERN-MEDICIS facility that, since 2018, has been producing
innovative isotopes for medical and biomedical research byhospitals and other institutes.13

Challenges of knowledge transferfrom fundamental researchParticle physics has an important role to play in contributing to
medical innovation and healthcare technologies. Maximizing
the societal impact of basic research requires setting up a
number of knowledge transfer strategies and being aware of
the challenges ahead. Many of the hurdles faced when trying toapply CERN technologies to the medical and biomedical fields
provide important clues for how to optimize these strategies
in other application domains, as well as in other fundamental
research environments.
As discussed earlier, basic research centers develop technologies
primarily for their internal needs. Such technologies are honed
and fine-tuned to meet demanding specifications and adapting
them to a different application is often not straightforward—andmight even require rolling back to an earlier, less customized
version. These adaptions may require collaboration withvisionary companies who are willing to engage in medium- tolong-term partnerships. Even companies with the right mindset
and spirit might have difficulty funding such endeavors—when
the technology is so disruptive that the market application won’t
be realized for years and hence does not fit the current market
strategy. Funding schemes to bridge the gap between in-housedevelopment and market application would catalyze public-private
collaborations. Most of the available schemes either fundthe initial R&D (proof-of-concept and first prototyping) or thedevelopment of a market-ready medical device. However,between prototype and final product, several years of technicaldevelopments in close collaboration with clinicians and industry
are often needed, and more funding should be made available
for this stage. One pioneering initiative is the ATTRACT funding
scheme, which is supported by the European Commission’s
Horizon 2020 Programme and aimed at creating a co-innovation
ecosystem for fundamental research and industrial communities
to develop breakthrough detection and imaging technologies
for scientific and commercial uses.14

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The Global Innovation Index 2019

There is also a need to bridge the cultural gap between companies
and the particle physics community. For example, companies
do not always know what to expect from a collaboration with
scientists and engineers working in big-science endeavors likethe Large Hadron Collider. Scientists and engineers not only
develop innovative technologies but also have an in-depth
understanding of how these technologies work and can beadapted to harsh and challenging environments—ultra-highvacuum, high radiation exposure, superconductivity, superfluidity,
and other extreme phenomena. In addition, they are familiar withfacing complex problems related to integrating technologies
and systems. This unique blend of technical competences andexperience in a highly collaborative and interactive environment
would be ideal for assisting companies in overcoming theirtechnical challenges.
At the same time, the particle physics community needs to
sharpen its efforts: when a potential application for a technology
is identified, it is essential to evaluate whether this development
would fill an existing need in the medical market or whether
the application is trying to solve a problem that is not perceived
as such by healthcare professionals. While blue-sky R&D iswhat drives basic research forward and allows building theexperiments of the future, it is important to understand market
needs when trying to adapt a given technology to a medical
application. A dialogue with all the relevant players on thehealthcare side—doctors, medical physicists, and medtech
companies—is key to properly assess the potential of a given
technology for a specific application, and hence to be able tofocus the efforts on the most promising cases. A particularly
relevant example is CERN’s competences in the data analytics
and machine learning domains; as discussed earlier, thesecompetences are essential to harness the full potential of large
data sets for personalized medicine. While the LHC experiments
generate a vast amount of data, the technical challenges
are not the same as those of the healthcare communities.
In addition, the computing tools developed at CERN are often
highly specialized and only usable by highly skilled scientists.
The expectations of end users, such as medical researchers andcompanies operating in medical and biomedical technologies,
may be far from the reality of the computing tools developedat CERN. It would be unrealistic to expect turnkey solutions
without further technical developments due to the very different
nature of the data sets available in high-energy physics and themedtech field. This makes it crucial to ensure an early dialogue
between CERN and potential external partners, as realistic
expectations are more likely to result in effective collaborations.

Knowledge transfer at CERN
While a lot of the above can be applied, with some variations,
to most laboratories dedicated to fundamental research, a setof challenges is explicitly connected to the CERN environment.
For example, the industrial culture at CERN is not as strong
as in other research institutions, and therefore it is not always
easy to motivate busy scientists to work with a company on thedevelopment of a medical device. The nature of CERN as aninternational organization that is funded by 23 Member States
also has implications for the knowledge-transfer process. CERN

is bound by its mandate of basic research and cannot become
an applied laboratory, meaning that its technologies must be
brought to the market by industrial partners. At the same time,
CERN being publicly funded implies that companies from all
Member States should be given equal opportunities to exploit
CERN’s technologies. A strategy document outlining knowledgetransfer from CERN for the benefit of medical applications sets
clear boundaries for these activities.
The knowledge created by CERN’s community has the potential
to lead to innovation in fields beyond particle physics. This
innovation can happen organically, as proved by the early examplesof transfer from CERN to medical technologies, but actively
investing in the process can also boost its impact and reach.
The CERN Knowledge Transfer (KT) group provides advice,support, training, networks and infrastructure to ease the transfer
of CERN’s know-how to industry and society.15
Intellectual property (IP) lies at the core of successful knowledgetransfer at CERN. It enables CERN to claim being at the originof a novel technology, making it possible to share its knowledge
and create societal impact. CERN’s policy is to disseminate its
technologies as widely as possible to industrial and institutional
partners within its Member States, however, patenting represents
only a tiny part of CERN’s approach to IP. CERN will only
consider patenting where it might help mitigate the financial
risks of investing further in the development of a technology.
CERN’s patent portfolio currently comprises 34 patent families,
a number significantly lower than organizations of a similar size.
In addition to its technology portfolio, CERN also has a wealthof scientific and technical competence across areas of expertise,
which is accessible through collaboration and consultancy
agreements.
Open innovation has been part of CERN’s DNA since its
inception. Several CERN software technologies are developedwith open collaboration in mind. The CERN laboratory is also
contributing to many open source projects, small and large, that
promote collaboration within the larger community, not only
the scientific world. The CERN Open Hardware License, draftedand published by the CERN KT group, was born out of the wish
to openly disseminate CERN’s hardware designs. The license
fosters the dissemination of schematics, hardware documentation,and improvements made to the hardware. The license itself
can be used by anyone and is a good example of how
CERN’s work can have surprising benefits for society—even
the availability of open hardware worldwide.
One of the main challenges in the knowledge-transfer sphere is
to make it as easy as possible for scientists and other specialists
to turn their research into innovations, and CERN invests much
effort in such activities. Launched in 2011, the CERN KT Fundbridges the gap between research and industry by awarding
grants to projects proposed by CERN personnel where there isa high potential for positive impact on society. Since its creation,
40 projects have been funded, each receiving grants with avalue between 15,000 and 240,000 Swiss francs (CHF) over one
or several years. In 2016, two European Commission funded
projects, AIDA-2020 and ARIES, incorporated a proof-of-concept
fund modeled on CERN’s KT Fund. CERN also provides a limited

amount of seed funding for projects aimed at transferring its
technologies and know-how to the medical field. Between 2014
and 2017, 25 projects have been funded with an average grantof about CHF 64,000 per project.
Since the early days of technology transfer at CERN, one main
focus has been on knowledge transfer through people—especially
early career scientists who work in industry following theircontracts at CERN or who start their own company. Over the last
20 years, CERN has continued to build a general culture ofentrepreneurship within the organization through many avenues.
There are currently over 20 start-ups and spin-offs that use
CERN technologies in their business. To assist entrepreneurs
and small technology businesses in taking CERN technologies
and expertise to the market, the CERN laboratory has alsoestablished a network of ten Business Incubation Centres (BICs)
throughout its Member States where companies can directly
express their interest in adopting a CERN technology. The BIC
managers provide office space, expertise, business support,
access to local and national networks, and support in accessing
funding. Every year since 2008, students from the School of
Entrepreneurship (NSE) at the Norwegian University of Scienceand Technology (NTNU) spend a week at CERN to evaluate
the business potential of CERN technologies. Three of thestudents attending the CERN-NTNU screening week in 2012
started TIND, a spin-off based on CERN’s open-source
software, Invenio.
Getting the next generation of scientists into the habit of thinking
about their research in terms of impact is vital for knowledgetransfer to thrive. In 2015, the CERN KT group launched a seriesof Entrepreneurship Meet-Ups (EM-Us) to foster entrepreneurshipwithin the CERN community. The CERN KT group, with thesupport of the CERN & Society foundation, also launched the
CERN Entrepreneurship Student Programme (CESP), bringing
together graduate students from all around the world for
5-weeks of practical and theoretical training at CERN. In 2018,
CERN organized the CERN Medical Technology Hackathon(CERN MedTech:Hack) to explore new ways of developing
viable applications of CERN technologies in the medical field.
The CERN MedTech:Hack took place over three days, during
which international teams of students competed to solve topicalproblems pitched by healthcare organizations and industry
partners in the medical field.

Conclusions
Basic research in particle physics is an effective driving force
for major technological advances. Bringing such disruptive
technologies on the medtech scene is a non-trivial exercise,often because the actual market needs are too far away in timeand it is difficult for companies to invest resources in developments
outside of their current business plan. CERN and other basic
research laboratories should hone their tools and strategies tomaximize the impact of their technologies and expertise onsocietally relevant topics such as healthcare. Understanding
what challenges are involved in transferring knowledge fromparticle physics to the medical field and what lies behind
successful cases can offer keys to improving and streamlining
the process.

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Projects like the LHC can only happen through large-scaleinternational cooperation based on mutual trust. This successfulmodel should be of inspiration when it comes to knowledgetransfer, where it is essential for different communities ofexperts—from academia, industry, and other disciplines—to be
in contact and to know and trust each other. When a possible
application of a technology is identified, it is essential toevaluate whether this development would fill an existing needin the medical market or whether one is trying to solve a problem
that is not perceived as such by healthcare professionals. The
scale, complexity, and unprecedented technology needs ofsuch basic science projects require human capital with uniquecompetences. Scientists and engineers from CERN and otherresearch institutes are at the heart of knowledge transfer, as
they collaborate with industry while remaining involved infundamental research, move to the private sector, or start theirown business. Getting the next generation of scientists into
the habit of thinking about their research in terms of impact isvital for knowledge transfer to thrive.
Fundamental research has a priceless goal: knowledge for thesake of knowledge. Even though the lead times from basic
scientific discoveries to practical applications are often long,
it is thanks to knowledge that humankind has got to where it
stands today. The theories of relativity and quantum mechanics
were considered abstract and almost esoteric when they weredeveloped; a century later, we owe them, respectively, theremarkable precision of GPS systems and the transistors thatare the foundation of the electronics-based world we live in.
Beyond this, particle physics research acts as a trailblazer for
disrupting technologies in the fields of particle accelerators,
detectors, and computing; these technologies have alreadygreatly contributed to the advances of modern medicine,although their impact is often difficult to track as it is indirect anddiffused over time. Supporting the knowledge-transfer processfrom particle physics to medical research and the medtech
industry is a promising avenue to boost healthcare innovationand provide solutions to present and future health challenges.
CERN will certainly continue its efforts to maximize the impactof our laboratory’s know-how and technologies on society,including—but not limited to—the medical sector.

Notes:
1

Further information about Fermilab is available at www.fnal.gov/

2

Further information about CERN is available at https://home.cern

3

Cofield, 2008.

4

Muller, 2018.

5

Further information about Geant4 is available at http://cern.ch/geant4

6

Illés et al., 2012.

7

Raynova, 2017; Bressan, 2005.

8

Further information is available about the Crystal Clear Collaboration
at http://cern.ch/crystalclear and about Medipix at http://cern.ch/medipix

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Del Rosso, 2015.

10

Bryant, 2000.

11

Further information about CNAO is available at http://fondazionecnao.it

12

Further information about MedAustron is available at https://www.
medaustron.at/en

13

CERN, 2017.

14

Further information about ATTRACT is available at https://attract-eu.com

15

Further information about the CERN Knowledge Transfer group isavailable at http://kt.cern

References:
Bressan, B. (2005). PET and CT: a perfect fit. Retrieved from https://cerncourier.com/pet-and-ct-a-perfect-fit/
Bryant, P. (2000). PIMMS: Proton-ion medical machine study. Retrieved
from https://cds.cern.ch/record/448963
CERN. (2017). New CERN facility can help medical research into cancer.
Retrieved from https://home.cern/news/press-release/cern/
new-cern-facility-can-help-medical-research-cancer
Cofield, C. (2008). Magnetic Resonance Imaging. Retrieved fromhttps://www.symmetrymagazine.org/article/december-2008/deconstruction-mri
Del Rosso, A. (2015). The miniature accelerator. Retrieved fromhttp://cds.cern.ch/journal/CERNBulletin/2015/26/News%20Articles/2026007
Illés, T., & Somoskeöv, S. (2012). The EOS imaging system and its uses
in daily orthopaedic practice. Retrieved from https://www.ncbi.nlm.
nih.gov/pmc/articles/PMC3385897/
Muller, R. (2018). First 3D colour X-ray of a human using CERN technology.
Retrieved from https://home.cern/news/news/knowledge-sharing/first-3d-colour-x-ray-human-using-cern-technology
Raynova, I. (2017). Forty years since the first PET image at CERN.
Retrieved from https://home.cern/news/news/knowledge-sharing/
forty-years-first-pet-image-cern

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CH AP T E R 11

OVERCOMING BARRIERSTO MEDICAL INNOVATIONSFOR LOW-RESOURCESETTINGSDavid C. Kaslow, PATH

Advancing health equity by improving health outcomes of
those living in the lowest resource settings is a defining moral
imperative of our current epoch. By identifying and overcoming
barriers to health equity, individuals, families, and communities
benefit from lifelong opportunities to improve well-being andincrease economic development and security. A key determinant
in achieving health equity in low- and middle-income countries
is the successful development, introduction, and uptake ofessential biologics, drugs, and vaccines—referred to herein
as essential medicines—as well as diagnostics, devices, andhealth systems and services designed for the specificcontexts and needs of those living in low-resource settings.
Developing and increasing access to health technologies foruse in low-resource settings presents multi-dimensional
challenges. For the subset of health innovations known asessential medicines, these challenges are even greater,
and additional interventions are required due to the lack ofrobust and compelling market-based financial incentives that
historically drive innovation and uptake of new technologies.
Despite clear and present unmet health needs, innovationin essential medicines and other health technologies fordisenfranchised populations has historically remained stagnant.
Evolving traditional models of—and/or creating new paradigms
for—product development, approval, and access are criticalto reduce uncertainties and risks and to create sustainable
incentives for public, private, and local stakeholders tosignificantly improve the pace of development and impact of
new health technologies.

Three types of challenges toinnovation
Challenges to product development for low-resource settings
present in myriad ways throughout the product life cycle.
Often, analyses of these challenges focus disproportionately
on intellectual property and price, while important drivers ofaccess, affordability, and availability of generic options alone are
not sufficient to ensure widespread access and uptake of newhealth products.
A more holistic and systematic approach to identifying barriers
and solutions to innovation and successful multisector
collaboration reveals diverse opportunities to develop new
products or significantly improve access to health technologies
in low- and middle-income countries (LMICs). These barriers
can be divided into three main categories.
1. Biological uncertainties: include biological hurdles or host
response limitations imposed by the target disease or
population that create uncertainties or currently insurmountablebarriers to the development of new health technologies.
For example, available scientific evidence may suggest it
is biologically implausible to develop a universal, durably
protective vaccine of sufficient safety and efficacy for agiven disease. Increased investment in product development
activities or changes to regulations or policies will havelittle to no impact on traversing these biological barriers
absent further scientific advances or insights.

Chapter 11149

2. Technical uncertainties or risks: refer to challenges related
to processes and/or attributes of health technologies indevelopment or inherent in existing products that limit theirproduction, safety, efficacy, or quality. Such issues include,
but are not limited to, manufacturing, formulation, productanalytics, stability, bioavailability, or half-life of a productcandidate as well as dosing schedules and processes for
conducting clinical trials. For example, an effective
compound may have a complex and costly synthesis
process, rendering production expensive and presenting
a barrier for uptake in low-resource settings.
Some technical challenges can be overcome with increased
investment. In many cases, effective therapies exist for
diseases present in low-resource settings, but in formulations
that are resource intensive or burdensome to store or
administer. For example, pulmonary surfactant for thetreatment of infant respiratory distress syndrome (IRDS) is
generally affordable and available. But it requires advanced
healthcare infrastructure, such as ventilation equipment,
to administer and monitor the treatment, which limits its
suitability in low-resource settings. In such cases, reformulations
or innovations to existing products may be the optimal
investment to overcome an access barrier.
3. Human-controlled uncertainties and risks: relate torecommendations and decisions that drive approvals,
investments, or allocation of resources that support productdevelopment, accessibility, availability, affordability,
acceptability, or sustainability of health technologies. Suchdecisions can significantly create or overcome barriers to
medical innovations in all settings. Political will, appropriate
and relevant incentives, sufficient or insufficient allocationof financial and human resources, cost- and risk-sharing—or lack thereof—and favorable or unfavorable ethical,
regulatory, and policy decisions can either advance orstall innovation. Evidence-driven shifts in the collective
understanding of what is truly impeding access in low-resource
settings today and more comprehensive analyses of thevalue proposition that a particular health technology brings
to advancing health equity are needed to overcome thesehuman-controlled uncertainties and risks.

Understanding human-controlled
uncertainties and risks
Human-controlled factors act as barriers to innovation andaccess to new health products—especially those consideredessential medicines—throughout the various stages of the
product life cycle.
Meta challenges
While some challenges to innovation or access are primarily
present at a particular point in the life cycle of a product, thissection highlights two challenges—funding and political will—that are omnipresent, manifesting in various ways at each stage.

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Funding
Funding for product research and development, implementationand outcomes research, and market analyses for uses of healthtechnologies in low-resource settings remain insufficient.
Global funding for basic research and product development forneglected diseases in 2017 was just below US$3.6 billion, withover two-thirds directed to HIV/AIDS, malaria, and tuberculosis(TB),1 leaving roughly $1 billion remaining for product development
for all other neglected diseases. It is estimated that the funding
gap between current investment and what is needed to launch
one of each of 18 key missing neglected disease essential
medicine products in the next five years is at least $1.5 to$2.8 billion annually.2 This shortage of funding creates andexacerbates challenges throughout every stage of the productdevelopment life cycle.
Weak or absent profit incentives for new products for use in
LMICs make it difficult to engage private-sector partners
and secure their financial investment, capital infrastructure,and human resource capabilities for these products. Productdevelopers are often able to secure partners who provide
expertise and resources for work early in the product development
life cycle. However, as a product progresses into later andmore expensive stages of development and introduction, it
becomes harder to secure private-sector funding to advance
products. For context, a phase 3 vaccine trial conducted tostandards that would suffice for WHO Listed Authorities
who perform at a Maturity Level 3 or 4 (WLA-ML 3-4)3 can cost$200 million or more.4
Funding to develop products for low-resource settings comesprimarily from a rather short list of donor governments andfoundations, such as the Bill & Melinda Gates Foundation(Gates Foundation). This puts product development for specificuse in low-resource settings at a severe resource disadvantage
as compared to for-profit product development. For perspective,
in 2017, the Gates Foundation invested nearly $1.3 billion on
global health,5 but for-profit pharmaceutical developers now
spend an average of $2.6 billion per drug.6
The complexity of challenges related to supporting productdevelopment for use in low-resource settings is further
complicated by nuanced, but important, differences in thebusiness cases for those products. For example, a productmay have use in dual markets—both LMICs and high-income
countries (HICs) and both private and public markets—or may
have use only in LMIC public markets. Depending on thebusiness case, different solutions have been, or could be,applied to provide sufficient incentives to drive development
and introduction investments. Figure 10.1 illustrates thesedifferences. The type of intervention and the epidemiology ofthe disease also can significantly impact the types of challenges
and incentives most applicable to a particular product.
Insufficient donor and health-related funding also impacts healthsystems and creates challenges specific to research, evaluation,
procurement, and administration of health technologies.
For example, a consortium of research and development

FIGURE 11.1

Four vaccine business cases
Compelling—Uncertain—Assistance—No

Low-income public market onlyNo

Assistancedependent

Dual market

Uncertain

Development
risk

Compelling

Potential returns

0
Opportunity cost

Assistance-dependent

Uncertain(LMIC only; Outbreak)(LMIC ←→ HIC)

(HIC → LMIC)(e.g., LMIC: cholera, malaria,
meningitis A, Shigella; Outbreak:Ebola, MERS, Nipah, Lassa fever)(e.g., group A strep, group B strep, TB)(e.g., HBV, HiB, HPV, PCV, RSV,
rotavirus)

Solutions:Public funding
Priority review vouchers
LMIC manufacturers
Push and pull mechanisms

Solutions:
Reverse tiered pricing
Push and pull mechanisms

Solutions:Tiered pricing
Push and pull mechanisms

business casebusiness caseCompellingbusiness case

Source: PATH/David Kaslow.
Note: Four vaccine business cases determine the types of incentives and partners most appropirate to advance a product.

Chapter 11151

organizations, including PATH, identified the lack of support for
implementation research as a formidable barrier which reduces
access to and impact of new health technologies.7
At the same time, government budgets and healthcare systems
may not have sufficient funds to procure or administer all the
drugs on Essential Medicines Lists (EMLs), nor to train local
healthcare providers to use new technologies, nor to provide
the infrastructure needed to maintain supply and delivery of
products—all of which impact access.
Political Will
The challenge of building political will to fully recognize healthinequity as both a moral imperative and a barrier to socialand economic development also impacts many facets of accessto health technologies at the global and local level. Whenassessing competing funding priorities, both donors andgovernments may operate in an evidence- or awareness-scarcespace on health’s broader impact on national and global
economies, security, and stability. This scarcity isolates andrestricts resources, and it limits potential for innovative
cross-sector collaboration to overcome challenges to productdevelopment and access.

Pre-approval challenges
This section focuses on the many challenges that exist in theprocess of developing and getting new health technologies
approved for use in a particular market. Developing products
designed specifically for use in LMICs poses unique research,development, regulatory, policy and financing challenges.
Regulatory practice
When developing or reformulating health technologies, strong
regulatory systems are integral to protect patient safety andprivacy and to ensure favorable benefit-risk profiles and qualityof interventions. Challenges—related to consistency andsuitability of regulatory practice for products designed specificallyfor LMICs—manifest in several ways that cause delays andincrease the cost of product development.
Undefined regulatory or impractical development pathways
Registering a product for dual use (i.e., HIC and LMIC) often
begins with regulatory approval from an influential WLA-ML 4
regulatory authority, most commonly the United States Foodand Drug Administration (FDA) or the European Medicines
Agency (EMA). Development of a product for low-resource
setting use only, may also start with regulatory review (e.g., U.S.
FDA review of an investigational new drug (IND) application)
by a prominent WLA-ML 4 regulatory authority, and may also
include a comprehensive evaluation of the quality, safety,
and efficacy of certain medicinal products for use intended
exclusively for markets outside their jurisdiction—for example,
the EMA Article 58 procedural advice. Reviews by these orother WLA-ML 3 or 4 authorities significantly assist approval inmany low-income countries that lack the capacity and resources
to conduct comprehensive independent regulatory reviews.

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While WLA-ML 4 regulatory authorities may assist other countries’
registration and adoption of new products, the WLA-ML 4
regulatory authority’s mandates are typically legislated to ensure
quality, safety, and efficacy of products to be used in their own
jurisdiction. Although there are mechanisms for evaluation ofcandidates in other jurisdictions (e.g., see U.S. FDA Guidancefor Industry: General Principles for the Development of Vaccines
to Protect Against Global Infectious Diseases8), HIC national
regulatory authority standards may not reflect the specificpopulation needs, local infrastructural and administration
limitations, or various other context-specific dynamics of products
designed for use in LMICs. As noted above, EMA’s scientificopinion procedure was designed to apply EMA’s scientificreview capabilities and the local epidemiology and disease
expertise of WHO and national regulators to provide adevelopment and assessment pathway for products intended
for use in LMICs. This procedure facilitates both WHO
Prequalification (PQ) and local approval.9 Yet challenges remain.
As an example, during the development of tribendimidine (TrBD)
to control soil-transmitted helminth (STH) infections in LMICs,
FDA registration standards originally called for the productto be evaluated for efficacy against the U.S. approved standardof care—which is a multi-dose, multi-day, licensed productregimen designed for individual-based treatment of active
gastrointestinal infection. This is feasible to implement in HICs,
however, TrBD is intended for use in LMICs where single-dose,mass drug administration for periodic presumptive treatment(PPT) is the most feasible approach for treating and controlling
STH infections in an entire population. A mass drug administration
campaign is not a licensed regimen in the United States.
After a specific request to re-evaluate the acceptability of a
PPT indication, U.S. FDA did recognize PPT as a new indication
acceptable for approval. However, the development pathway
for a registration of a PPT indication was complex from financial,
regulatory, and scientific perspectives, which placed the project
goal out of reach.
Multiple national regulatory authorities withdiffering regulations
Each regulatory system presents distinct logistical and technicalrequirements. The need for researchers and manufacturers tonavigate multiple systems to register the same health products
across multiple countries results in delays and increased cost to
product access.
Gaps in regulatory capacity in LMICs
Gaps in regulatory capacity in many LMICs can lead to delays inaccessing new health technologies. In situations where a productis intended solely for use in LMICs, first-in-human studies areoften conducted in the United States or the European Union,
with subsequent research often conducted locally. Reduced
regulatory capacity means reviews may be longer and/or
iterative, and the development pathway may be delayed or
require more trials than in WHA-ML 3 or 4 settings. Somenational regulatory authority (NRA) systems have insufficient
capacity to efficiently regulate across all phases of development
and licensure and provide adequate pharmacovigilance,or quality assurance, for products once marketed.

Resource-limited NRAs result in delays in other ways as well.
For example, WHA-ML 4 NRAs have created mechanisms
whereby product candidates for certain indications can obtain:
1) Accelerated approval based on a surrogate or intermediate
clinical endpoint reasonably likely to predict a clinical benefit,
followed by post-approval phase 4 confirmatory trials to verify
clinical benefit (e.g., U.S. FDA accelerated approval pathway); or
2) Conditional approval, renewable annually, based on meetingcertain specific requirements, including that the benefit to publichealth of the immediate availability of the product outweighs
the risks due to a need for further data. This later pathway
requires completion of ongoing or new studies and, in somecases, additional activities to provide comprehensive data
confirming that the benefit-risk balance is positive.
Many LMIC NRAs do not have similar mechanisms and/or theirhealthcare systems are not able to provide the monitoring andstandards stipulated as required for earlier access to essential
medicines and health technologies. For products with markets
and use cases in both HICs and LMICs, LMICs may have to
wait for the confirmatory studies in HICs to be completed before
LMICs approve access to these new health technologies.

Post-approval challenges
Once a product is developed, it must reach those it is intended
to benefit to have an impact. This section highlights challenges
that exist in the process of ensuring a newly developed andapproved product achieves optimal use at scale.
Appropriate essential medicines lists at local levels
The WHO EML serves as a model for the development of
national and institutional essential medicines lists. The mostcurrent WHO EML includes 433 products deemed essential for
addressing the most important public health needs globally.
Most countries have national lists and some have provincial orstate lists as well. National lists of essential medicines guidethe procurement and supply of medicines in the public sector,
schemes that reimburse medicine costs, medicine donations,and local medicine production.10
Given the realities of budget limitations, it is often not possible
for national or district health systems to procure an adequate
supply of all medicines with WHO EML designation. Countries
also may lack the data or expertise to assess their needs andprioritize their lists and supply accordingly.
Lack of workforce capacity and training
Widespread and responsible implementation of health technologies
requires local healthcare providers who accept the value of
new products and are appropriately trained and licensed in theiruse. Local healthcare workers may not have the specializedskills or licenses to administer the product. For example, local
regulations in some countries preclude classes of healthworkers from administering injections. Program resources

needed to support local capacity, product acceptance, andtraining around new products can be large and expensive.
The process of scaling such programs can be lengthy, slowing
uptake of new products.
Fragile markets
Market dynamics for many health technologies, particularly
essential medicines, are not driven by traditional market
forces and therefore may be fragile and require considerable
additional efforts and interventions to shape and sustain them.
The long-term availability of health technologies relies onsustainable markets for product manufacturers.
A product’s price must be low enough to be affordable to thehealth system(s) or patients who must purchase it. However,
if prices are pushed too low, manufacturers will exit the market,
reducing competition and threatening supply security.
In the case of the live Japanese encephalitis vaccine (JEV), which
PATH contributed to bringing to market, a single manufacturer,
Chengdu Institute of Biological Products, is responsible for overthree-quarters of the JEV global supply. The product is currently
affordable and available, but any significant disruption in JEV
supply from one manufacturer, including force majeure, could
threaten global availability of this product, negatively impacting
public health and increasing the threat of outbreaks of Japanese
encephalitis.
Infrastructure maintenance
An often-neglected component of sustainable supply for
essential medicines and other health technologies is ongoing
maintenance and quality improvement in the infrastructure
and capacity for production. Facilities that produce, store, andtransport existing and future products must be rigorously
maintained and routinely updated to new and evolving quality
standards. Manufacturing facilities that produce low-margin
essential medicines for low-resource settings face constantthreats to their long-term sustainability. Without sufficientmargins or other mechanisms to ensure access to low-cost
capital and resources for maintaining or replacing aging
facilities, sustainable supply and administration of healthproducts is threatened.

Policy recommendations
Addressing barriers to access of health technologies, including
essential medicines, in low-resource settings requires innovationand strengthening of systems throughout the product life cycle,
as well as engagement from stakeholders at all levels and fromvarious sectors and governmental agencies. The following is
a list of recommendations to support and accelerate access toinnovative health technologies for use in low-resource settings
and further enable the multisector collaboration needed totackle the complex and diverse challenges previously discussed.

Chapter 11153

1. Resources and commitment: Increase financial investment
and political will to prioritize global health productdevelopment and access
The lack of adequate financial resources to drive the productdevelopment and access pipelines for new health technologies
for poverty-related and neglected diseases impacts every
challenge discussed. Unlocking greater funding for this workrequires innovations to be valued not just on their direct, individual
health benefits but also on indirect, population-based social andeconomic benefits. Funding to support this work must breakout of silos, such as solely Ministry of Health or Department of
Health budgets. A more holistic approach could enable new
resource streams to sustainably fund innovation. Activities tosupport this shift include:• Existing funders should continue to support research tofurther establish the evidence base and business casefor investment in innovation of health technologies. This
research should include cross-disciplinary work that frames
the value of new products beyond individual health benefits
and presents evidence of the positive impact healthtechnology investment can have on other priorities likepoverty prevention, security, global development, agriculture,
education, and technology. Funders and thought leaders
should highlight this research using high-visibility platforms
to build political will and cultivate champions.
• More fit-for-purpose incentives and innovative financing
mechanisms to support product development and provide
incentives for private-sector participation are needed
throughout the product life cycle. To ensure impact, each ofthese mechanisms need a focused and clearly understood
scope to accomplish stated goals and limit unintended
outcomes. Mechanisms should be deliberately coordinatedsuch that there is a clear line-of-sight across development
and introduction, with minimal gaps or delays during transitions
in financing mechanisms. Both push (funding greater input)
and pull (rewarding output) mechanisms are needed.
2. Regulatory affairs: expand efforts to converge regulatory
standards across agencies and regions and support
innovative initiatives to strengthen regulatory capacity in LMICs
Addressing regulatory challenges could simplify and clarify thedevelopment and regulatory pathways required for registrationof health technologies (including essential medicines), facilitating
quicker adoption and uptake, and increasing public healthimpact. A more convergent and/or integrated regional or evenglobal regulatory system would reduce the cost and time of
product development, as fewer country-specific clinical studies
or chemistry, manufacturing, and control activities would haveto be performed.
Efforts across regions to pool resources and expertise is a
critical way to strengthen capacity and converge/integrate
standards and processes. A recent PATH report, Making theCase: How Regulatory Harmonisation Can Save Lives in Africa,shows that harmonization of regulatory approvals for just two
medicines could contribute to more than 23,000 lives savedin eastern and southern Africa. Initiatives such as the African

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The Global Innovation Index 2019

Medicines Regulatory Harmonisation (AMRH) are advancing
these goals and having an impact.11 However, these efforts have
only been piloted at a small scale and require further support.
Activities to support strengthening regulatory systems include:• Regulatory agencies should clearly and consistently
communicate regulatory and licensure requirements to help
clarify paths for developers and manufacturers.
• Regulatory convergence and ongoing harmonization
initiatives should receive financial and political support,with a focus on building capacity and streamlining
processes in LMICs.
• Regulatory convergence should create opportunities forthird parties with experience developing and evaluatingproducts in low-resource settings to help facilitate regional
regulatory convergent/integrated processes. These
opportunities include, but are not limited to, standardizing
methodologies for evaluation, forms and filing protocol,
review scheduling, and decision reporting systems.
3. Local capacity: Invest in growing local capacity to support
the introduction, appropriate and responsible use, andsustainable supply of the most impactful health technologies
Public health impact is not achieved until those in need ofinterventions receive and benefit from them. Ensuring medical
products are reliably delivered, consistently available, andappropriately and responsibly administered requires reliable
and robust health systems. These health systems must include
informed decision-makers, well-trained and resourced careproviders, and anti-fragile infrastructure to support manufacturing,storage, and delivery. Activities to strengthen the capacity of
local workforces, and systems to implement innovative healthsolutions, must include sufficient resources from donors andnational governments to:• Strengthen public health systems and aspire to achieve
universal healthcare, which will enable widespread andresponsible use of new health technologies.
• Develop national and provincial Essential Medicines
Lists that ensure countries are selecting, prioritizing, andprocuring the products necessary and appropriate for theirhealth context and making these decisions based on current
relevant evidence from real-life implementation of statedtreatment standards.
• Address issues of deteriorating manufacturing infrastructureof legacy essential medicines (e.g., vaccine factories that arereaching the end of their useful life) and ensure the supplyof essential medicines—particularly those with two or fewer
manufacturers—remains secure. To stimulate competitionand provide incentives or funding for the maintenance ofinfrastructure needed for manufacture, storage, and delivery,
products in need of manufacturer diversity and repair ofmarkets should be proactively identified. Such efforts should
include actively seeking and supporting local manufacturers
and investing in their capacity to produce essential medicines,
to increase local product acceptance, promote consistentand sustainable local product supply, and achieve sustainable
and affordable product prices.

Innovation is critical to driving gains in health equity and socialand economic development around the world. However,product development is only the first step. A holistic approachthat creates and supports the financial, economic, regulatory,
and human resources to create an anti-fragile environmentis needed to sustainably advance the development, approval,
widespread adoption, and effective and responsible use ofhealth technologies in LMICs.

World Health Organization (WHO). (n.d.-a.) WHO Global Benchmarking Tool
(GBT) for evaluation of national regulatory systems. Retrieved fromhttps://www.who.int/medicines/regulation/benchmarking_tool/en/——— . (n.d.-b.) WHO Model List of Essential Medicines. Retrieved from https://www.who.int/selection_medicines/list/en/
Young, R., Bekele, T., Gunn, A. et al. (2018). Developing new health technologies
for neglected diseases: a pipeline portfolio review and cost model[version 2; referees: 3 approved]. Gates Open Research. Retrieved fromhttps://doi.org/10.12688/gatesopenres.12817.2

Notes:
1

Chapman et al., 2019.

2Young et al., 2018.

3

World Health Organization (WHO), n.d.-a.

4Young et al., 2018.

5

Bill & Melinda Gates Foundation, 2017.

6

DeMasi, 2018.

7

PATH, 2018.

8

United States Food and Drug Administration (FDA), 2011.

9

European Medicines Agency (EMA), n.d.

10World Health Organization (WHO), n.d.-b.

11

New Partnership for Africa’s Development (NEPAD), n.d.

References:
Bill & Melinda Gates Foundation. (2017). Who We Are: Annual Report 2017.
Retrieved from https://www.gatesfoundation.org/Who-We-Are/Resources-and-Media/Annual-Reports/Annual-Report-2017
Chapman, N., Doubell, A., Oversteegen, L. et al. (2019). Neglected Disease
Research and Development: Reaching New Heights. Surry Hills NSW,
Australia: Policy Cures Research; 2019. Retrieved from https://www.
policycuresresearch.org/wp-content/uploads/Y11_G-FINDER_Full_report_Reaching_new_heights.pdf
DeMasi, J.A. (2018). Assessing pharmaceutical research and development
costs. JAMA Internal Medicine, 178(4), 587. Retrieved from https://doi.
org/10.1001/jamainternmed.2017.8703
European Medicines Agency (EMA). (n.d.) Medicines for use outside theEuropean Union. Retrieved from https://www.ema.europa.eu/en/
human-regulatory/marketing-authorisation/medicines-use-outside-european-union
New Partnership for Africa’s Development (NEPAD). (n.d.) African Medicines
Regulatory Harmonisation (AMRH). Retrieved from https://www.nepad.
org/programme/african-medicines-regulatory-harmonisation-amrh
PATH. (2018). Investigating a Second Valley of Death in Malaria R&D: How Is“Research for Implementation” Funded? Seattle, WA: PATH 2018.
Retrieved from https://www.malariavaccine.org/sites/www.malariavaccine.org/files/content/resource/files/Malaria_R&D_Funding_Report.pdf
United States Food and Drug Administration (FDA). (2011).
Guidance for Industry: General Principles for the Development of
Vaccines to Protect Against Global Infectious Diseases. Rockville, MD:
FDA. Retrieved from https://www.fda.gov/downloads/BiologicsBloodVaccines/GuidanceComplianceRegulatoryInformation/Guidances/Vaccines/
UCM282995.pdf

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CH AP T E R 12

LIFE IS TOO SHORTWITH HCV AND NCDS—
100 MILLION HEALTHYLIVES INITIATIVE
Hala Zaid, Aysam Salaheldein, Mostafa Monier Othman, and Mohamed Hassany, Ministry of
Health and Population, Egypt
Ahmed Sorour, Egypt Country Office, World Health Organization

Global healthcare is moving towards implementing medical
innovations through automation and digital transformation ofe-health strategies and applications. Digital health supports theapplication of universal health coverage (UHC), which ensures
no one is excluded from obtaining health and medical services
due to financial hardship.1 Strengthening information andcommunication technologies (ICT) changes the shape of service
delivery and improves individual and public health. E-healthhelps to ensure that health information is provided to the right
person at the appropriate time and place.2
Leadership enables these changes—especially on the national
level—ensuring alignment with strategic health goals. In 2018,
Egypt’s highest level of authority started to show commitment
towards digital health by establishing automation and digitaltransformation units in all ministries. Shortly thereafter, the Ministryof Health and Population (MoHP) started addressing andenhancing the health information system (HIS) through assessment
and definition of specific objectives. The primary focus of the
MoHP is to assess health risks using population surveys. Using
these evidence-based surveys ensures that resources areallocated efficiently and allows for effective decision-making.
The two main health risks in need of assessment in Egypt are
hepatitis C virus (HCV) and non-communicable diseases (NCDs).
An estimated 84% of all deaths in Egypt are NCD-related.
Statistics from 2008 show that Egypt had the highest HCV
prevalence worldwide,3 with an estimated 6.8 million patients
between the ages of 15 and 59 diagnosed with the virus.4 The
prevalence of HCV decreased by 30% from 2008 to 2015 but,
despite this decrease,5 Egypt still had the highest prevalence
globally—a reported 7% or roughly 4.5 million patients.6 The
use of population surveys as an assessment tool for health risks
has yielded moderate results. To strengthen the influence andimpact of these surveys, further action needs to be taken to
improve data governance, transparency, population coverage,
fraud detection, and instant monitoring. These matters can only
be enhanced through digital technologies.

Methodology
From October 2018 to April 2019, the MoHP ran a large-scale
HCV and NCD screening and treatment program for Egyptians
aged 18 years and older. Egypt is known to be the country withthe highest prevalence of HCV and the highest number ofmortalities due to the complications of NCDs. Despite this, the
MoHP did not have precise records for the incidence andprevalence of HCV and NCDs. In addition, the MoHP had neither
comparison with other countries nor the peripheral distribution
between provinces. This initiative—named 100 Million Healthy
Lives—was launched under the patronage of the Egyptianpresident. The aim of this program is to eliminate hepatitis C by
2020 and to assess the prominence of NCDs in the country.
It includes early detection, referral, and treatment for HCV and
NCDs. The cross-sectional screening had three phases andcovered 27 governorates representing the country. Over sevenmonths, screening teams consisting of 60,057 medical
professionals and data entry staff worked in 5,716 screening
sites, such as primary healthcare (PHC) units, government
hospitals, mobile clinics, and youth centers.7 Over 49.8 million
people were screened and tested for NCDs and HCV, 2.2 million
were referred for polymerase chain reaction (PCR) tests, and 0.9
million started their first dose of HCV treatment. Monitoring andevaluation of the program, in collaboration with the World HealthOrganization (WHO) Egypt Country Office, took place in two
parts—field visits during the screening and a verification process
to ensure the quality of the screened data.8

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The process flow of the patient cycle was divided into technicaland medical. The technical side of the cycle focused on datacollection to create patient profiles at the beginning of theprocess and to record medical results and assessments at theend of the process. Based on the personal data collected at the
beginning of the cycle, the system determined whether tests for
NCDs and/or HCV were required. Trained health professionals—
mainly physicians, dentists, and/or pharmacists—performed thenecessary medical tests following pre-defined standards.
The health professionals were also responsible for completingthe technical side of the cycle by providing medical data as
input for the system. In the case of negative results, the patient
file was closed. If results were positive, the patient proceeded
to a second phase where further testing was conducted andmedical professionals established patient specific treatment
plans.

Findings
1. Instant monitoring of the process
The MoHP developed software solution offers a holistic approachto the screening, referral, and treatment process. It provides
instant reports derived from the data entries at every registeredsite. The system updates every ten minutes. It is able to detect
which screening units did not make any data entries for patients
within the last fifteen minutes. This enables monitoring officers
to overcome any obstacle or challenge that may be faced
within these locations, such as technical issues related to the
database, code debugging, internet accessibility, or even lackof workforce motivation. All of these challenges can be solved
once detected.
Between 2011 and 2015, rapid political changes affected thehealth system. Short-term wins were created to demonstrate
power, while long-term programs lacked political commitment.
This eventually led to duplication of services through parallel
programs. Now the system enables standardization between
different entities, centralized around the patient. This systemenables the medical team to determine—during the screening
process—whether the patient is insured or not. If possible, thepatient is referred directly to a nearby hospital that belongs
to their health insurance organization (HIO). If not insured,
the patient is referred to a hospital with administrative ties tothe curative sector in the MoHP. In this case, the patient getsfinancial coverage from another insurance scheme. The referralplace and time of the patient’s next visit are provided during thescreening, enabling the patient to understand the next steps
before leaving the screening site. Having the system accessibleat each referral site enables all patient information—fromscreening, treatment, and results—to be entered, stored, andeasily tracked.9
The software produces updates every ten minutes and canprovide instant reports about screenings across the country.
The system generates a targeted number of screenings foreach site per day and compares that to the actual screened
population. It also analyzes the population per gender, shows
the highest contribution by age group, and is capable ofidentifying the peak screening time within a day or peak times

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throughout the screening process. Its enormous capacity allows
access to 20,000 users at the same time, captures 750,000
screening transactions per day, and captures 47 screening
transactions per second.
2. Evidence-based decision-making
Limited resources are usually the main challenge facing publichealth interventions. Resource mobilization driven by data is the
optimum solution to overcome this obstacle. A well-developed
software solution offers multilayer output. This approach starts
from a national level and narrows to regions, governorates,
districts, cities, and villages—eventually reaching a population
covered by a primary healthcare unit. This multilayer approachclarifies which screening centers have covered the targeted
population numbers and which centers have not. This targeting
is followed by behavioral change and awareness campaigns,
using messages sent to targeted citizens in a specific geographicalarea to motivate them to undertake the screening.
The system produces data, such as the total number ofscreened cases and their results, on all layers from the national
level to villages and specific areas. This aids in placing targetedinterventions in the needed areas. The system also shows
correlation between diseases and related risk factors. For example,
the data shows a strong correlation between hypertension
and obesity, a decrease in the incidence of hypertension withincreased physical activity and lifestyle management, a higher
prevalence of hypertension in males, and a higher prevalenceof diabetes in females.
3. Data governance and transparency
Lack of data governance can raise security and management
issues, while lack of transparency may decrease trust and cause
decisions based on incomplete information. Data governanceaims to establish evidence-based decision-making. It aims to
distribute responsibility and authority across the Ministry of Health.
The system effectively connects campaign senior management,
tactical teams, and operational managers. Policies and rules forthe medical and technical teams are utilized to ensure the best
governance. The system has built-in data validation rules toensure the integrity and consistency of all data. This createsa closed-loop system for the screening process that includes
data security, privacy, operation, analysis, and decision-making.
The system encapsulates processes and procedures anddefines them as implementable operational steps. It promotes
consistency, data flows, data analytics, and data mining. Training
for operational teams, managerial teams, and steering committees
enabled each group to understand the system, manage
data, and make decisions. Finally, audits are in place to ensure
data quality.
Transparency was achieved through a verification report on
the data quality, performed by WHO, Egypt. Data verificationand transparency strengthened the results from the population
surveys. Results of the screening are displayed on public
billboards for citizens and other parties to see. Reports areunder development to share the results of this large-scale
screening. Media campaigns are also being used to communicate
why the general public should undertake the screening.

4. Population coverage and health mapping
Population coverage—using a multilayer approach—is a key
measure that defines the success of Egypt’s population-based
survey. Data mining and analytics based on the most criticalcases, such as hypertension over 180/110 mmHg and diabetes
over 600mg/dL, will lead to a health map matrix that can inform
communication campaigns and treatment. The data will beanalyzed for correlations between the screened diseases andgeographical areas. For instance, four governorates from phase
one have double the prevalence of hypertension comparedto the rest of the governorates. This enables defining the risk
factors by governorates and narrowing further to focus on
small areas and villages. Other risk factors are also taken into
consideration, such as gender, age group, distribution between
rural and urban, and profession. In addition to the healthmapping matrix, the analytics will be used to produce various
reports and research articles. Finally, the software produces adashboard that offers a strategic overview of the mass screening.
5. Cost-effective approaches, fraud detection, and financial
sustainability
The economic burden of diseases is critical, as it increases outof pocket and catastrophic health expenditures. Wise decisions
must be adopted to decrease the financial load on the population.
The fragmentation of the Egyptian health system makes it
difficult to detect service duplication, standardize services
across different entities, or stabilize pricing for services. However,
the technology system has capabilities that enable integrating
the different entities, detecting fraud, and ensuring efficientinterventions.
The National Committee for Control of Viral Hepatitis (NCCVH)
is the governmental entity that develops strategy for thescreening, prevention, and treatment process. In the past, thiswas a long process, which included time-consuming and costly
paperwork and accounted for 65% of the out of pocket costto patients. Now, the process of approval is completely
electronic and confirms the treatment regimen with no financial
burden on the patient. The screening is free of charge and has
eliminated out of pocket and catastrophic expenditures.

Conclusion and recommendations
The case study of the Egyptian presidential initiative, called
100 Million Healthy Lives, set a few goals, which include improving
the public health status of 100 million Egyptians, eliminating
HCV from Egypt by 2030, and assessing the situation of NCDs.
The objective of this mass screening was to screen 50 million
citizens above 18 years old and connect them to treatment
through a proper referral system. This initiative was successful
due to the digital health application. It generated an enormous
amount of data that can be easily transformed into useful
information for wise decision-making.
Automation and digital transformation of public health interventions
ensure prompt evaluation and provide clear evidence fordecision-making, governance modalities, health metrics, andthe best economic approaches. The health system in Egypt isfragmented due to unintegrated health services and complex
vertical programs and silos. The only solution for fixing thisissue is through connecting all the services and the institutions
together to prohibit duplication of services, define the needed
services, and ensure transparency. Data mining and analytics
are cost-effective approaches to mobilizing resources toward
the most crucial health needs.
Egypt is the chair of the African Union in 2019. The sister countries
have similar health system challenges regarding healthinformatics. This has motivated policymakers to support othercountries through knowledge and technology transfer. Currently,
some countries are adopting the lessons learned and buildingon Egypt’s experience, according to their status and needs.
Requirements for each of the nominated member states iscurrently being assessed through field visits. The approach
will then be modified and tailored to satisfy the specific needsof member states.
There is a critical need in science and public health in Egypt
to develop more effective medicines and medical devices andto ensure that they are available and accessible for all who
need them. A solution to this problem is under development
through enterprise resource planning (ERP)—business process
management software that includes supply chain management,
inventory management, documentation management, and humanresources management. This system will integrate various
applications that digitize back-office processes and procedures
and will be utilized for all governmental bodies, not only MoHP.

Notes:
1

WHO, 2016.

2

WHO, 2012.

3

WHO, 2017.

4

Kandeel et al., 2017.

5

Talaat et al., 2019.

6

Kouyoumjian et al., 2018.

7

WHO, 2019.

8

WHO, 2019.

9

Additional information is available at http://stophcv.eg/upload/endnote-weblink-2-pager.pdf

References:
Kandeel A., Genedy M., et al. (2017, June 30). The prevalence of hepatitis C
virus infection in Egypt 2015: implications for future policy on prevention
and treatment. Liver Int. 37(1), 45–53.
Kouyoumjian, S., Chemaitelly, H., Abu-Raddad, L. (2018, January). Characterizing
hepatitis C virus epidemiology in Egypt: systematic reviews,
meta-analyses, and meta-regression. Nature, scientific reports 8,1661(26). Retrieved from https://www.nature.com/articles/s41598-01717936-4.

Chapter 12159

Talaat, M., Afifi, S. et al. (2019, February 14). Evidence of sustained reductionsin the relative risk of acute hepatitis B and C virus infections, and theincreasing burden of hepatitis a virus infection in Egypt: comparisonof sentinel acute viral hepatitis surveillance results, 2001-17. BMC
Infectious Diseases 2019 19(1).
World Health Organization (WHO). (2016). From Innovation to implementation:eHealth in the WHO European Region. Retrieved from http://www.euro.
who.int/__data/assets/pdf_file/0012/302331/From-Innovation-to-Implementation-eHealth-Report-EU.pdf
World Health Organization (WHO) and International Telecommunication Union(ITU). (2012). National eHealth strategy Toolkit. Retrieved fromhttps://www.itu.int/dms_pub/itu-d/opb/str/D-STR-E_HEALTH.05-2012PDF-E.pdf
World Health Organization (WHO) and Ministry of Health and Population(MoHP), Egypt. (2017). Egypt National STEPwise Survey For
Noncommunicable Diseases Risk Factors Report 2017. Retrieved fromhttps://www.who.int/ncds/surveillance/steps/Egypt_National_STEPwise_
Survey_For_Noncommunicable_Diseases_Risk_Factors_2017_Report.
pdf?ua=1.
World Health Organization (WHO) and Ministry of Health and Population(MoHP), Egypt. (2019). National HCV/ NCD screening verification
report draft.

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CH AP T E R 13

INNOVATIONS IN HEALTHCARE AFFORDABILITY
AND DELIVERY—AN INDIANPERSPECTIVE
Devi Shetty, Narayana HealthWith a population of more than 1.3 billion,1 just a shade less thanChina’s 1.4 billion, India faces enormous challenges ensuring
quality healthcare for all of its citizens. Although a relatively
young nation, with 50% of the population below 25 years of age
and 65% below 35 years,2 India still has a large aging population
which needs access to medical facilities to lead a healthy life.
Improvement in life expectancy over the years, which is 69.04
years as of 2018,3 implies that the types of healthcare challenges
faced by the country today are quite different from what they
were thirty or forty years back. In earlier years, high rates of
infant mortality, infectious diseases, and population control
were the major concerns. Today, healthcare problems—suchas hypertension, diabetes, and coronary heart disease, which
has emerged as the leading cause of death in India—are more
related to lifestyle.4
In this chapter we focus on healthcare in India, innovatingin healthcare delivery, and increasing healthcare affordability
through increased capacity.

Healthcare in India—an overview
Indian healthcare has made substantial progress, especially inthe last decade. The Government of India has been trying to
improve public health delivery through significant investmentsin the healthcare infrastructure. With limited resources and alarge population to take care of, the Indian government requires
innovative ways to provide quality healthcare facilities for all. It
spends roughly 1.15% of gross domestic product (GDP) on the
public healthcare system,5 which badly suffers from an insufficientnumber of trained health professionals. In addition, disparity
in healthcare coverage between urban and rural areas does

not meet the needs of the population. The private sector has
stepped in to fill this gap in India, but healthcare facilities remainbeyond the reach of a large percentage of the population
due to their prohibitive costs. Although the government has
primary, secondary, and tertiary care facilities, it is the private
sector that runs a majority of super specialty hospitals—hospitals
with expertise in multiple specialized areas. However, private
facilities are concentrated in and around tier 1 and 2 cities. The
healthcare market in India is expected to reach US$372 billion
by 2022.6 India has attracted foreign direct investment (FDI)
worth US$6 billion in the healthcare sector between April 2000
and June 2018.7 However, there is great disparity in the availabilityof skilled resources between rural and urban areas. On thepositive side, India is currently among the top 20 global medical
device markets and the 4th largest medical device market in
Asia. Medical tourist arrivals in India have also increased byover 50% to 200,000 in 2016 from 130,000 in 2015—and are
expected to double in the near future.
Across the world, government spending on healthcare is expected
to reach US$10 trillion by 2022,8 which is the largest expense
for any service in the world. Even today, less than 20% of theworld’s population has access to secondary and tertiary level
healthcare.9 In order to meet the healthcare needs of citizens
and increase access to affordable healthcare, the Indian government
created the centrally sponsored Ayushman Bharat scheme.
Ayushman Bharat initiative by the government promises toprovide affordable access to healthcare services. Launched in2018, the scheme is the world’s largest universal health coverage
program with a goal to provide medical insurance worth
US$7,100 each to 100 million families every year.10 While it issimilar to other health insurance schemes, the Indian government
pays the insurance premium to health insurance providers on

Chapter 13163

behalf of its citizens. The entire healthcare infrastructure is now
being geared up to meet the demands and massive scale of
Ayushman Bharat. India’s medical educational infrastructure
has grown rapidly in the last 26 years: the number of medicalcolleges in India has increased from 314 in FY11 to 476 in FY18.
The government has increased health expenditure by 370%
between 2000 and 2014, making the efficient managementof expenditures and the creation of mechanisms that ensure
benefits reach the needy essential.

Healthcare delivery—the need forinnovation
While developing countries continue to focus on controlling
malaria, tuberculosis, and HIV, which combined kill 3.8 million
people annually,11 adequate attention is needed to save nearly
17 million lives lost due to the absence of proper facilities forbasic procedures and surgeries. The statistics reveal that outof the 313 billion surgeries done across the world, only 6% areperformed in the areas where nearly half the world population
lives. These are not complex surgeries of the heart, brain,
or for cancer but basic surgeries, called bellwether procedures,that include an emergency cesarean section for obstructeddelivery, laparotomy for a burst appendix, and surgery forcompound fractures.
The infrastructure created for malaria, tuberculosis, and HIV
cannot be used to perform surgeries, but the infrastructure andexpertise built for performing surgeries can be used to treat
malaria, tuberculosis, and HIV with virtually no additional cost.
Essentially, what is needed is investment in innovations aimed
at the delivery of healthcare.
Indian healthcare organizations are gradually increasing
investment in artificial intelligence (AI), the internet of things(IoT), and robotics. With telemedicine becoming a fast-growing
sector in India, major hospitals adopting telemedicine services,and hospitals entering into public-private partnerships (PPPs),
the telemedicine market in India is expected to reach US$32
million by 2020. This would help bridge the rural-urban dividein terms of medical facilities, extending low-cost consultationand diagnostic facilities to the remotest of areas via high-speed
communication links.
As hospitals “go paperless”—by digitizing and relaying informationelectronically rather than on paper—consultations, access to
inpatient reports, and communication within and outside thehospitals can be revolutionized. The impact of technology canbe much more significant than any pill or medical equipment
in reducing preventable deaths in the country. Adoption oftechnologies, such as less invasive diagnostics, patient-centric
mobile apps, remote monitoring solutions, digital platform
integration, surgical robotic tools, smaller implants, AI, and 3D
printing, shall provide the necessary impetus towards achieving
the vision of a connected healthcare ecosystem.

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One of the first steps towards this transformation will be to use
technology to leverage a digital healthcare ecosystem. Rising
adoption of AI-based applications will ensure better connectivity
among physicians, patients, hospitals, and the overall healthcare
industry. Developments in information technology and integration
with medical electronics have made it possible to provide
high-quality medical care at home—at affordable prices—enabling
consumers to save from 20 to 50 percent of the cost.

Capacity building—critical aspects
Rural Health Statistics 2017 show that there is an 81.6% shortageof medical specialists in government-run hospitals in India.12
We do not have adequate specialists to fill the vacant positions
in government-run hospitals. Infectious diseases are no longer
a cause for concern, as they can be treated by doctors with
undergraduate degrees. But degenerative diseases, which areresponsible for most illnesses, cannot be treated legally bya doctor with only an undergraduate degree. It is essential fora doctor to have a graduate qualification to treat such illnesses.
According to the Medical Council of India, while 63,850 seats
are offered for undergraduate admissions in medical colleges
across India, availability of seats for graduate studies numbers
only 25,000.13 Of this, admissions for clinical specialties arearound 14,500 and the rest are for paraclinical specialties.
This gap between undergraduate and graduate seats hascreated 200,000 undergraduate, or MBBS, doctors who areeither unutilized or underutilized in the nation’s healthcaredelivery. The problem can be addressed by equalizing thenumber of seats at the undergraduate and graduate levels
in medical colleges. This will also ensure the availability of
specialists in the rural and remote areas.
Over the years, education in the healthcare sector in India has
become an elitist affair. It costs over US$60 million to build
a medical college that can train 100 doctors per year. In thisprocess, the cost of education has increased beyond themeans of the working class and the poor. Interestingly, many
esteemed doctors across the world generally come fromdeprived backgrounds. In India, the problem could be addressedby converting 763 district hospitals into medical, nursing, andparamedical institutions,14 which will cost roughly US$15 million.
About 5% of the seats in these colleges could be reserved for
local students, which would enable them to study in their own
region and improve the quality of service in their home districts.
Across the world, especially in the United States of America(U.S.) and Europe, any practicing medical specialist withover five years of experience is able to become a medical
teacher who can train doctors, nurses, and paramedics.
As per guidelines from the Medical Council of India, a medical
practitioner must work for more than 10 years in a medicalcollege hospital to be considered as a medical teacher.
There are medical colleges in the Caribbean region that have
low overhead costs using small rental spaces to train medical
students that will work in the United States. Many pre-medical
students and medical residents undergoing specialist training
programs in the United States are from one of these Caribbean

medical colleges. If India adopts these norms for training
medical students, the overall cost of medical education will
decrease significantly.
Healthcare is poised to become one of the largest employers
and carries huge potential for foreign exchange earnings
through medical tourism. With a large youth population, India
could also become a skilled health workforce provider forthe aging and shrinking population of the developed countries.
Policymakers must carefully consider all of these aspects tobuild a balanced program for education.

Healthcare—improving affordability
in India
While a heart surgery in India used to cost US$3,500 about
30 years ago, it is performed for less than US$1,500 today.
This drastic cost reduction has been possible because ofphysician and hospital entrepreneurship. To achieve further
reductions in the cost of healthcare, we need to dramaticallychange the way doctors, nurses, and medical technicians aretrained and also how hospitals are built and managed.
While the developed world focuses more on cutting-edge
research, we in India have a unique opportunity to develop
innovative processes to democratize healthcare.
To foster a culture of research and excellence, specialized
research—in robotics-led remote surgeries, basic medicine,and provisions—should be encouraged and incentivized to
reward innovators for their time and effort.
More than innovation in products, India needs process innovations
and a major change in regulations to embrace technology inhealthcare. Technology enables a specialist anywhere in theworld to instantly access patient reports, view monitors attachedat the patient’s bedside, and take clinical decisions immediately.
Despite the benefits that the adoption of technology offers,
there are additional costs that will extend the time it takes
for these technologies to become a reality. There are noclear-cut guidelines related to technology-led healthcaredelivery in India. For example, a doctor cannot issue anelectronic medical prescription because they are limited byregulations. Updating regulations, encouraging technology
adoption, and mandating minimum standards for healthcaredelivery, electronic medical records, and exchange of clinicaldata are some of the important changes needed in the country.
Once technology adoption becomes widespread, remotemonitoring of patients using telehealth devices will become
the norm. Hospitals will do away with wards and have 90%of beds for intensive care and 10% of beds for emergency
or trauma. The healthcare delivery model will undergo a change
where patients who would have otherwise been in hospitals
will be tended to in patient care centers by nurses and remotely
monitored by specialists.

Conclusion
Like Uber and Airbnb, information technology enabled services(ITES) will become the largest healthcare provider. There isalready Microsoft’s Kaizala platform, which allows patients tosave their medical records on their phone and to have a Skypeconversation with a doctor from any part of the world. Suchplatforms can dramatically change the way patient-doctor
interaction happens, resulting in a significant cost reductionof healthcare.
Adoption of such technologies will lead to better care, which
will not only reduce re-admissions but also improve the average
length of stay. Due to the volume of patients that a healthcaredelivery center can handle, enhanced efficiency in the system
will bring down the costs.
The Government of India has embarked on an ambitious target
of providing broadband connectivity to every village. Suchhigh-speed data links would revolutionize the communication
process—patients’ pathological, radiographic, and other test
data collected at primary health centers could be quickly
shared with super specialty hospitals to enable the specialists
to decide on diagnosis and treatment protocol. The aforesaid
tech-enabled healthcare delivery models would transform thehealthcare services sector in the country. In addition, the Indian
Government’s health coverage program will boost healthcare
services. Such initiatives will pave the way for better accessand affordability of quality care—the grand vision of any universal
healthcare program.

Notes:
1

United Nations, n.d.

2

Government of India,Vice President’s Secretariat, 2018.

3

Knoema, n.d.

4World Health Organization, 2018.

5

National Health Systems Resource Centre, 2016.

6

India Brand Equity Foundation, 2018.

7

India Brand Equity Foundation, 2019.

8

Deloitte, 2019.

9

Meara et al., 2015.

10

National Portal of India, n.d.

11

Meara et al., 2015.

12

Ministry of Health and Family Welfare, 2018.

13

Seats offered for undergraduate admissions are 63,850 whereas
graduate admissions are 25,000 across India. Further information about
the number of seats for the said admissions is available at https://www.
mciindia.org/CMS/information-desk/college-and-course-search

14

Ministry of Health and Family Welfare, 2016.

Chapter 13

165

References:
Deloitte. (2019). Global Health Care Outlook: Shaping the Future.
Retrieved from https://www2.deloitte.com/global/en/pages/life-sciences-and-healthcare/articles/global-health-care-sector-outlook.html
India Brand Equity Foundation. (2018, October). Growth of Healthcare Industry
in India–Infographic. Retrieved from https://www.ibef.org/industry/healthcare-india/infographic——— . (2019, March). Healthcare Industry in India. Retrieved from https://www.
ibef.org/industry/healthcare-india.aspx
Knoema. (n.d). India–Life expectancy at birth. Retrieved from https://knoema.
com/atlas/India/topics/Demographics/Age/Life-expectancy-at-birth
Meara, J. G., Leather, A. J. M., Hagander, L., Alkire, B. C., Alonso, N. et al.
(2015, August 08). Global Surgery 2030: evidence and solutions forachieving health, welfare, and economic development. The Lancet
Commissions, 386(9993), 596-624. https://doi.org/10.1016/S01406736(15)60160-X
Ministry of Health and Family Welfare. (2016, July 22). Functioning District
Hospitals as on 31st March 2015. Ministry of Health and Family Welfare.
Retrieved from https://community.data.gov.in/functioning-district-hospitals-as-on-31st-march-2015/
Ministry of Health and Family Welfare. (2018, February 12). Rural Health
Statistics–2017. Retrieved from https://data.gov.in/resources/state-utwise-total-specialists-community-health-centres-chcs-surgeons-ob-and-gy
National Health Systems Resource Centre. (2017, February). Government
Health Expenditures in India (2013-14). New Delhi: Ministry of Healthand Family Welfare, Government of India. Retrieved from http://nhsrcindia.org/sites/default/files/practice_file/Final%20Government%20
Health%20Expenditure%20Report%20-%20Web%20Optimized%20
Version%20-%2020.06.17%20%282%29.pdf
National Portal of India. (n.d). Ayushman Bharat–National Health Protection
Mission. Retrieved from https://www.india.gov.in/spotlight/ayushman-bharat-national-health-protection-mission
Government of India, Vice President’s Secretariat. (2018, October 10). Skilldevelopment should be a continuous process [Press release]. Retrieved
from http://pib.nic.in/Pressreleaseshare.aspx?PRID=1549166
United Nations. (n.d). Global Issues, Population. Retrieved fromhttps://www.un.org/en/sections/issues-depth/population/
World Health Organization (2018, June 1). Noncommunicable diseases.
Retrieved from https://www.who.int/news-room/fact-sheets/detail/noncommunicable-diseases

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CH AP T E R 14

A BRAZILIAN OUTLOOKON HEALTH AND MEDICALINNOVATION
Robson Braga de Andrade, National Confederation of Industry–Brazil (CNI)
Carlos Melles, Brazilian Micro and Small Business Support Service (SEBRAE)

This chapter looks at the challenges and opportunities for Brazil
in the health sector—one of the most thriving sectors in theworld. First, we consider global health trends in innovation and
how Brazil is performing. Second, we outline the role of the
National Confederation of Industry–Brazil (CNI), Social Service
of Industry (SESI), National Service for Industrial Training (SENAI),
Euvaldo Lodi Institute (IEL), and the Brazilian Micro and Small
Business Support Service (SEBRAE) in shaping the futureof health innovation in the country. Finally, we present
recommendations for the Brazilian government to build a moreinnovative ecosystem in the country.

Global health trends and theBrazilian outlook
Global health trends
One of the main factors driving health innovations worldwide
is an aging population. This has led to increased research
into diseases that most commonly affect the elderly, such asneurodegenerative diseases like Parkinson’s and Alzheimer’s.
Another effect of population aging is the increase in healthcosts. Health spending as a share of global GDP has steadilygrown in recent years, from 8.6% to almost 10% between
2000 and 2015; in higher income economies it reaches up to
17% of GDP.1
However, the growing availability of health data may help
mitigate rising health costs and increase the potential for using
information and communication technologies (ICT), which
can revolutionize health services.2 The application of ICT tohealthcare ranges from telemedicine to the use of artificial

intelligence (AI) as an auxiliary tool in diagnosing diseases
and the development of medicines through the managementof health systems. Several ICT-based technologies areamong recent significant innovations in health.3 Among them
are telemedicine, artificial intelligence, the increased useof monitoring devices, virtual reality, and the use of social
networks to improve health services. Specialists also mention
immunotherapy—the activation or suppression of the immune
system—as a tool to combat certain diseases and as one of themost promising new technologies for the treatment of cancer.4
A recent study by IEL, 2027 Industry: Risks and Opportunities
for Brazil in the Face of Disruptive Innovations, mentions
several of these trends as relevant for Brazilian Industry.5
The novelties are numerous, but the scope of these changes
is still unclear. However, the conditions for the developmentof new technologies have not changed as much as thetechnologies themselves. In any field, innovating requires
qualified people, adequate infrastructure for conducting
research and product development, and a stimulating environment.
In addition to this, innovation in healthcare and medicine has
specific and more complex characteristics than any other sector.6
Creating new health products—especially medicine—requires
more scientific research than practically any other sector of
economic activity. Before developing medicine, medical
equipment, or medical devices, it is necessary to understandthe human body in relation to how diseases affect the individual—
namely its mechanisms, causes, and effects. This is usually the
purpose of scientific research conducted in universities andresearch institutions. Health innovations are also typicallyexpensive and take time to reach patients. The developmentof a new drug, for example, can take about 10 years fromthe basic research stage to preclinical and clinical tests. Even

Chapter 14

169

TABLE 14.1

Participation (% of total scientific publications) of health-related scientificareas in Brazilian and worldwide scientific publications (2017)
Academic field

Health-related publications
as a percent of Brazilianscientific publications

Health-related publications
Brazil’s health-related
as a percent of worldwide
publications as a percent
scientific publicationsof worldwide health-related
publications

Biology and agriculture

11.6%

4.4%

Biochemistry, genetics, and molecular biology

6.8%

6.4%

6.5%
2.6%

Odontology

1.6%

0.3%

11.8%

Immunology and microbiology

2.5%

1.5%

4.0%

Medicine

17.9%

16.9%

2.6%

Neuroscience

1.6%

1.5%

2.6%

Nursing

1.3%

1.0%

3.1%

Pharmacology, toxicology, and pharmaceutics

2.2%

1.8%

3.1%

45.3%

33.7%

2.4%

Total

Source: Ministry of Science, Technology, Innovation and Communications (MCTIC).
Notes: This table shows the participation of scientific areas related to health in Brazilian and world publications, as well as the participation of Brazilianscience in the world. When the participation of the area in Brazilian publications is greater than its respective participation in world publications, it meansthat Brazil has advantages in these areas.

innovation in software, equipment, and devices take time tomeet regulatory requirements before they are released to patients.
Furthermore, the development of a new health product is arisky activity. Estimates indicate that the percent of drugs
that reach the market after starting clinical trials vary between
6% and 13.8%.7

health-related scientific areas detailed in the table, Brazil’s
participation is 2.4% overall and much greater in specific areas.
For example, Brazil accounts for almost 7% of worldwide
scientific publications in biological and agrarian sciences, close
to 12% in odontology, and precisely 4% in immunology andmicrobiology. This shows that Brazil has important scientificexpertise in these areas (Figure 14.1).

Brazilian outlook
Brazil has over 200 million inhabitants and one of the largest
public healthcare systems in the world, called the UnifiedHealth System (SUS). The SUS provides healthcare, from basic
treatments to complex transplants, to over 100 million people,
free of charge. According to the Brazilian Institute of Geography
and Statistics (IBGE), in 2015 the total costs of health-related
goods and services in Brazil amounted to around 9.1% of GDP,approximately US$180 billion today.8 These numbers showthat Brazil has a significant market for health. Rising healthcosts, together with the fiscal problems faced by the country,
also make the SUS an excellent pilot to test technologies
capable of reducing health costs, especially through ICTs.
While the size of the market is an important advantage forthe development of new technologies in health and medicine,
it is also important to note that Brazil has pertinent scientificcompetences in health-related areas as shown in Table 14.1.
Across all scientific areas, not just health-related areas, Brazil
accounts for 1.8% of worldwide scientific publications. In the

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The Global Innovation Index 2019

When it comes to translating research into new drug production,
however, there is room for the country to move forward.
Evidence of this is Brazil’s participation in clinical trials, thefinal stage of a long research and developmnet (R&D) processthat starts in the laboratory of a university or research centerand ends with testing on humans. At this stage, fundamental
research from universities and research institutions moves
to the laboratories of large pharmaceutical companies, which
are primarily responsible for conducting clinical trials. Brazil
accounts for less than 3% of worldwide clinical trials, and thisparticipation is lower in phases 0, I, and II, which are the mostknowledge intensive. An increase in clinical trials will help
establish the country within global networks of knowledge
production in medicines and health products, especially in areas
where Brazilian comparative advantages are relevant.
This is the case for biopharmaceuticals, an area that has grown
the most in recent years and accounts for about 20% of theworld’s pharmaceutical market. A recent study conductedby researchers from the Massachusetts Institute of Technology(MIT), as part of a program sponsored by SENAI, argues

F IGU RE 14.1

South American and Brazilian share in worldwide clinical trials(phases 0 to IV) initiated between January 2000 and January 2018

8.0%

7.2

7.0%

6.0%

5.0%

4.8
4.0%

4.2

3.0%

2.8
2.0%

2.2
1.4

1.0%

0.0%

Phases 0, I, II

South America

Phases III, IV

Total

BrazilSource: De Negri, 2018.

Chapter 14

171that Brazil has the conditions to be more than a follower inbiopharmaceuticals because of its scientific competences
and the potential of its biodiversity.9 The 2027 Industry study
conducted by IEL has reached the same conclusions.10
However, biopharmaceuticals—which are more expensive thanpharmochemicals—can burden health systems. For this reason,a resolution of the National Health Surveillance Agency (Anvisa)
regulated the biosimilar market—drugs that are the equivalent
to approved, but not patented, biopharmaceuticals—in 2010.
By regulating this market, it is possible to increase patients’
access to biological drugs without causing significant increases
in drug costs. Nevertheless, according to the MIT study,
by focusing solely on biosimilars, Brazil risks falling further
behind the rapidly expanding science-based innovation frontier,meaning that the regulation of biosimilars is not enough to put
Brazil on the path of innovative countries in biopharmaceuticals.
By choosing the path of biosimilars and generics, Brazil hastaken an important step towards facilitating access to cheaper
medicines, but this is not enough for the country to be morethan follower in this field. Pursuing a leadership strategy
requires larger R&D investments from businesses in the healthsector. Today, the Brazilian pharmaceutical industry invests
around 2.4% of its revenues on R&D, according to the IBGE’s
Technological Innovation Survey (PINTEC).11 This level ofinvestment makes the sector one of the most R&D intensive inthe country. However, this is far from worldwide R&D investmentin the pharmaceutical sector, which is 10% to 15% of revenues.12
Yet, health innovation does not only relate to medicines. Thereis potential for Brazil to use ICT in health, since there is asignificant ecosystem of start-ups and researchers in this area.13
In addition, the SUS, one of the largest public health systems
in the world, could improve management and efficiency using
ICTs. A recent study has mapped out about 200 start-ups thatoffer solutions in ICTs applied to health, all of which are in
operation and own proprietary technologies.14 These companies
are involved in telemedicine, wearables, internet of things (IoT),
medical devices, electronic medical records management,
AI, and big data. A significant Brazilian medical innovation is anapplication developed by researchers at the Federal Universityof Rio Grande de Norte who, through analysis of a user’s
speech, help in the diagnosis of patients with schizophrenia.15
Brazil is just beginning to participate in other technologicaltrends, such as precision medicine. Nevertheless, important
initiatives—such as the Brazilian Initiative on Precision Medicine(BIPMed), which brings together five research centers supportedby the São Paulo Research Foundation (FAPESP)—facilitate thesharing of a genomic database. The Albert Einstein Hospitalin São Paulo, in partnership with a genomics company, hascreated a center for personalized medicine. This center aims touse genetics to improve the diagnostic accuracy of serious andcomplex diseases while administering an assertive prevention
plan and adopting an individualized approach for each patient.

Prognosis and the role of the CNI,SESI, SENAI, IEL, and SEBRAE
Despite the challenges, the prospects for Brazil in terms ofinnovation in health and medicine are promising. SEBRAE,
SENAI, SESI, IEL, and CNI all play a relevant role in the health area.
The role of SENAISENAI has contributed significantly to innovation in Brazil, throughtraining and the provision of technical services. To address
innovation challenges, SENAI has created a network ofinnovation centers called the SENAI Innovation Institutes (ISI),
equipped to develop innovative projects in several transversal
areas, including health and medicine. To date, 10 of the
26 ISIs have developed over 43 R&D projects related to health,in partnership with companies and other research institutions.
Some examples are:
1. The ISI for Microelectronics, in Manaus, Brazil, is leading
R&D of medical devices, in partnership with the Oswaldo
Cruz Research Foundation (Fiocruz) based in Rio de Janeiro,
Brazil. The first project aimed to design and produce a
low-cost device capable of conducting isothermal reactions
to assist in the diagnosis of infections such as tuberculosis,
leprosy, malaria, and dengue.
2. In Pernambuco, Brazil, the ISI for Information and Communication
Technologies is focusing R&D on a radiology imaging
transmission system, a virtual reality solution to train
Paralympic athletes, and portable equipment to use forretinal diagnosis.
3. The ISI specializing in polymer engineering, in Rio Grande
do Sul, Brazil, tests materials, orthoses, and breast prostheses,
in addition to developing health instruments.
Several additional SENAI Innovation Institutes undertake R&D
in health and medicine, such as the ISIs for Advanced Materials
and Nanocomposites, Advanced Manufacturing in São Paulo,
Microfabrication in São Paulo, Byosinthetics in Rio de Janeiro,
and Automation of Production in Bahia. Before the end of 2019,
SENAI expects to launch the ISI for Biotechnology in São Paulo,
whose R&D efforts will focus on the development and optimizationof bioprocesses and biomolecules, engineering genetics, andthe development of intelligent products with a biological basis.
The role of SEBRAESEBRAE aims to foster development and to support micro andsmall companies in areas such as technological prospection,
intellectual property consulting, business modeling, market
positioning, investor relations, consulting, and business andfinancial management. One SEBRAE initiative, for example, is topromote events where inventors and investors present market
trends and business opportunities to small companies.
In the health sector, SEBRAE initiates participation from innovation
professionals in areas such as biotechnology, nanotechnology,
bioinformatics, and artificial intelligence. For example, through
SEBRAE, start-ups and innovators have the opportunity to present
their solutions to solve specific health challenges to investors.

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The Global Innovation Index 2019

The role of SESISESI focuses on, and promotes innovation in, health and safety
at work. This contributes to business competitiveness by
reducing costs, reducing work-related accidents, and improving
workers’ well-being. To face the challenges of safety andhealth at work, SESI has implemented nine innovation centers
aimed at identifying challenges and developing solutions inseveral areas: prevention of disability, health and safety
economics, ergonomics, lifestyle and health, longevity andproductivity, health and safety management systems, psychosocial
factors, occupational hygiene, and healthcare technologies.
For example, the SESI Innovation Center for Health Care
Technologies developed a gamification solution to encourage
users to adopt healthy habits. The solution facilitates monitoringand data visualization of personal habits that need to change
for a healthier lifestyle. This and other examples of innovations
developed by the SESI Innovation Centers are publicly available
on the web in the National Platform of Innovations.16
The role of CNI and IEL
CNI manages SENAI, SESI, and IEL. Together, state federations
and employers’ trade unions form the Industry System,a national private network responsible for initiatives to support
the Brazilian industrial sector.
From the demands identified in the companies by the industrial
federations and unions, the System offers basic education,
professional training, business training, and technical andtechnological solutions to industries. It also develops
socio-educational programs that contribute in an effective way
to improve safety and health conditions in the workplace.
The Innovation Directory of CNI/IEL also supports innovative
companies in the health and medical sector throughmanagement consulting and training. The program Inova
Talentos, in partnership with the National Council for Scientificand Technological Development (CNPq), encourages fellows
to participate in innovation projects, such as validating biomarkers
discovered through metabolomics and development, or
validating tools to aid molecular diagnosis in precision oncology.
Finally, CNI hosts the Entrepreneurial Mobilization for Innovation(MEI) in Brazil. One of MEI’s initiatives—carried out through anagreement between CNI, SESI, SENAI, and SEBRAE—is the
publication Business Innovation Cases, which aims to inspirecompanies to innovate.
These are just a few examples of how the CNI, SENAI, SESI, IEL,
and SEBRAE can collaborate in the development of newtechnologies in health and medicine in Brazil. Brazil has enormous
opportunities ahead, and the research and business support
infrastructures provided by the aforementioned institutions willplay an essential role in realizing these opportunities.

Key challenges and recommendations
for health innovation in Brazil
Despite the country’s scientific expertise and potential in some
aspects of healthcare and medicine, developing more technologies
in these areas requires us to overcome regulatory, financial,and institutional constraints.
One significant constraint is the discontinuity in public policies
and research funding, which undermines the country’s scientificinfrastructure and expertise. Although companies account fora significant portion of R&D investment in health, public investment
is still the primary source of scientific research in the area
worldwide. In Brazil, discontinuities in public funding for scienceand technology (S&T) lead to brain drain—training gaps for
qualified staff—and obsolescence of equipment and laboratories,
which need to be continuously updated if the country wishes to
produce relevant scientific knowledge in this area.
Therefore, one of the most important recommendations for
Brazilian government is to set up a transparent and stablestrategy for innovation in healthcare and medicine, which should
consist of long-term investments in infrastructure and research.
This strategic plan should also address institutional constraints
that hamper innovation in the country.
Regulation is one constraint that partially explains the low
participation of the country in world clinical trials. According tocompanies, the time required by ANVISA to approve clinical
trials is one of the regulatory problems, and a study by theBrazilian Development Bank (BNDES) showed that these timerequirements are higher than the world average.17 Since manystudies are conducted concomitantly in several countries,
delays in the approval process may limit Brazilian participationin those studies.
One reason for this delay may be the existence of multiple
requests for approval for clinical trials. Each research institution
has its own research ethics committee, which is not always
expeditious in analyzing tests. In some cases, this approval stillneeds to go to the National Ethics Research Council, where theprocess can take up to six months to complete.18
In addition, entrepreneurs and studies point out that the cost ofclinical research in Brazil as an impediment to growth.19 This costcomes, in part, from regulatory standards, such as the need tosupply medicine to trial participants after the study ends.
One possible solution to these issues lies in a bill currently
under discussion in the Congress. This bill establishes standards
for clinical research in human beings and creates a national
system of ethics and research, which will improve and giveconsistency to the regulation of clinical research in the country.
Intellectual property is also a major challenge for innovation in
Brazilian industry. Specifically, in the health sector, intellectual
property rights are the main tool to reward the innovator for therisk incurred in innovating. In Brazil, the registration of a patent

Chapter 14173can take up to 11 years, which hampers innovation in the country.
Therefore, one important recommendation of CNI is to increase
the efficiency of the National Patent Office (INPI) in evaluating
patents, which requires more evaluators, better management,
and the use of international collaborative schemes.

8IBGE, 2017.

9

Reynolds et al., 2016.

10

Instituto Euvaldo Lodi, 2018.

11

IBGE, 2016.

12

OECD, 2015.

13

Revista Exame, 2018.

14

Distrito, 2018.

15Prêmio Abril Dasa de Inovação Médica, 2018.

16

Plataforma Nacional de Soluções SESI, 2019.

With regard to advancing the use of ICT in health, there aresome relevant bottlenecks related to legislation and theavailability of information. One example is the adoption of
the electronic medical record in the Unified Health System
network. For this to be feasible, it is necessary to provide
basic infrastructure for public health units across the country
and to establish interoperability protocols among several healthservice providers. Government and regulatory agencies
need to develop standards and protocols for medical records
to widen its use, which could benefit both the public andprivate health system and its patients.

17

Gomes et al., 2012.

18

Gomes et al., 2012.

19

Reynolds et al., 2016.

The recently passed General Data Protection Act, due to comeinto force in 2020, introduces a new element to this scenario.
From this, any use of personal data—especially sensitive
information such as health—will require the consent of theowner. Two factors requiring clarification are whether the law is
expected to protect people and their personal information fromindiscriminate and unauthorized use, and if the Act will impact
health research, especially using big data and AI. Therefore,
the CNI will follow the developments of this law and its impact
on innovation in health in Brazil.

Deloitte. (2016). Analysis: Top 10 health care innovations – More value, better
outcomes, for less. Retrieved from https://www2.deloitte.com/us/en/
pages/life-sciences-and-health-care/articles/top-10-health-care-innovations.html

An example of a good international collaborative scheme is
the Budapest treaty, aimed at advancing the protection of
microorganisms, which allows deposits of microorganisms
at an international depositary authority for patent procedure.
CNI considers that Brazil becoming a member of the Budapest
treaty would be an important step for the development of thebiopharma industry in the country.

Brazil has immense potential to innovate in health and medicine.
These are merely a few recommendations that could help thecountry overcome challenges and build a more dynamic healthinnovation ecosystem, thus benefiting Brazilian society withimproved and more affordable healthcare. The Brazilian industry
is committed to these ideas and to the goal of transforming thecountry into a hub of innovation in health.

References:
Cross, R. (2018). Drug development success rates are higher than previously
reported. Chemical and Engineering News, 96(7), 10. Retrieved from:https://cen.acs.org/content/cen/articles/96/i7/Drug-development-success-rates-higher.html

De Negri, F. (2018). Novos caminhos para a inovação no Brasil. Washington:
Wilson Center, Ipea.
DiMasi, J. A., Grabowski, H. G., & Hansen, R. W. (2016). Innovation in the
Pharmaceutical Industry: New Estimates of R&D Costs. Journal of
Health Economics, 47, 20–33. Retrieved from https://doi.org/10.1016/j.
jhealeco.2016.01.012
Distrito. (2018). Healthtech Mining Report: Primeiro semestre 2018. Retrieved
from https://conteudo.distrito.me/data-miner-healthtech
The Economist. (2018, February 1). Data and medicine: A revolution in healthcare is coming. Retrieved from https://www.economist.com/leaders/2018/02/01/a-revolution-in-health-care-is-coming
Gomes, R. P., Pimentel V. P., Landim, A. B., & Pieroni, J. P. (2012). Ensaios
Clínicos No Brasil: Competitividade Internacional E Desafios. BNDES
Setorial, 36, 45-84.
Herzlinger, R. E. (2006). Why Innovation in Health Care Is so Hard. Harvard
Business Review 84(5), 58.
IBGE. (2016). Pesquisa de Inovação Tecnológica (PINTEC): 2014. Rio de Janeiro:
IBGE. https://biblioteca.ibge.gov.br/visualizacao/livros/liv99007.pdf

Notes:
1

The World Bank, 2019.

2

The Economist, 2018.

3

Deloitte, 2016.

4

Deloitte, 2016.

5

Instituto Evaldo Lodi, 2018.

6

De Negri, 2018.

7

Cross, 2018

174

The Global Innovation Index 2019——— . (2017). Conta-satélite de saúde, Brasil: 2010-2015. Rio de Janeiro: IBGE.
Retrieved from: https://biblioteca.ibge.gov.br/visualizacao/livros/liv101437.pdf
Instituto Euvaldo Lodi, Núcleo Central (2018). Estudo de sistema produtivo
farmacêutica, Instituto Euvaldo Lodi, Pedro Palmeira. (Indústria 2027:
riscos e oportunidades para o Brasil diante de inovações disruptivas)
Brasília, 98. http://www.portaldaindustria.com.br/cni/canais/industria-2027/publicacoes/
MCTIC. (2018). Indicadores Nacionais de Ciência, Tecnologia e Inovação.
Retrieved from https://www.mctic.gov.br/mctic/opencms/indicadores/
detalhe/Producao_Cientifica/Producao_Cientifica_5.7.html.
OECD. (2015). OECD Indicators. Health at a Glance 2015. Paris: OECD Publishing.
Retrieved from http://dx.doi.org/10.1787/health_glance-2015-en

Plataforma Nacional de Soluções SESI. (2019). Retrieved from http://www.
inovacaosesi.org.br
Politi, F.A.S., Majerowicz, J., Cardoso, T.A.O., Pietro, R.C.L.R., Salgado, H.R.N.
(2009). Caracterização de Biotérios, Legislação E Padrões deBiossegurança. Revista de Ciências Farmacêuticas Básica E Aplicada,29(1), 17–28.
Prêmio Abril Dasa de Inovação Médica. (2018). Retrieved from http://premiodeinovacaomedica.com.br/os-campeoes-da-primeira-edicao-do-premio/
Revista Exame. (2018). HealthTechs alavancam mercado de saúde no Brasil.
Retrieved from https://exame.abril.com.br/negocios/dino/healthtechs-alavancam-mercado-de-saude-no-brasil/
Reynolds, E. B., Zylberberg, E. & Del Campo, M. V. (2016). Brazil’s Role in the
Biopharmaceutical Global Value Chain. Working papers. MIT-IPC.
Retrieved from https://ipc.mit.edu/sites/default/files/documents/16-004.pdf.
The World Bank. (2019, January). Current health expenditure (% of GDP).
Retrieved from https://data.worldbank.org/indicator/SH.XPD.CHEX.
GD.ZS

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CH AP T E R 15

INTEGRATION OF HEALTH
AND MEDICAL INNOVATIONSIN RWANDA TO PROMOTEHEALTH EQUITY
Parfait Uwaliraye, Patrick Ndimubanzi, Andrew Muhire, and Valencia Lyle, Ministry of Health, Rwanda

While ministries and health departments around the globe facedisparate health concerns, they often share a vision of improving
equitable access to quality healthcare—particularly from agender and age-specific lens—for their constituents. Although
this vision is ubiquitous, the procedures involved in bringing
it to fruition remain arcane. Nevertheless, Rwanda has madetremendous progress in the area of universal health coverage,advancing the county’s health equity agenda.
One of the key catalysts propelling Rwanda’s progress in providing
equitable access to healthcare is the country’s eagerness toadopt technological innovations and swiftly integrate them into
the health system. Innovations range from utilizing drones todeliver blood to citizens in the most remote corners of thecountry to using mobile phones to transmit critical healthinformation collected at the community level to a central database.
The innovations in Rwanda’s health system ensure the equitable
distribution of health services, as well as consistent and reliable
information about critical health information at all levels of
the health system. Many health policy experts suggest thatthe synergy of political will and the aforementioned healthinnovations have fostered Rwanda’s health sector achievements.

Health innovations
1. Drones
In Rwanda, as well as many other parts of the world, a considerable
portion of the population living in rural areas have limited accessto essential medical products, such as blood and vaccines,
due to onerous landscapes and gaps in infrastructure.1 In past
years, when essential medical supplies were required to save

lives, healthcare providers would either dispatch an ambulance
to transport the patient to a health facility with higher capacity or
dispatch a car and driver to the central blood bank to retrieve
blood. These processes are especially precarious in situations
where the central blood bank is five hours from the health facility.
The protracted process of awaiting land vehicles to transportvital medical supplies to patients in critical condition hampered
doctors’ abilities to save the lives of those patients. The
ineffectiveness of this approach encouraged health policymakers
to create a novel strategy to quickly deliver lifesaving medical
supplies to patients in critical condition.
Through an emphasis on building strong public-private partnerships,
the Rwanda Ministry of Health has begun using medical drones
to supply lifesaving medical supplies to 21 district hospitals
throughout the country. These medical drones ensure thatblood products are instantly accessible to the nearly 12 million
citizens of Rwanda.2
Since October 2016, the Rwanda Ministry of Health has
collaborated with Zipline to integrate drones into the
medical-supply infrastructure. Before drones were integrated
into the health system, donated blood stored in blood banks
in Rwanda would often expire. Rwanda was likely spending
over US$50,000 for the disposal of blood products annually.
As a result of this new, comprehensive blood-delivery
system, medical doctors are now able to place orders
online and receive blood from the distribution center within 30
minutes.3 According to Zipline, blood deliveries to hospitals
by drone resulted in blood banks having zero units of expired
blood. This highlights several benefits of integrating drones
into Rwanda’s medical-supply infrastructure.

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2. Mobile health (mHealth) as a digital health solution
In addition to the integration of cutting-edge technology topromote health equity, phones are also used as an alternativetechnological innovation to provide quick, affordable, quality
resolutions to ailing citizens. With over 2 million registeredusers—roughly 30% of the adult population in Rwanda—andover 280,000 consultations performed, digital healthcare throughBabyl Rwanda is expanding the provision of healthcare services
to individuals throughout the country. Clients must follow three
simple steps to access heathcare through Babyl: 1) send an
SMS to a specific phone number to request an appointment,2) transmit a payment using e-transactions with mobile money
services, and 3) complete a short consultation with a triage
nurse before scheduling a follow-up appointment with the
Babyl senior nurse or general practitioner. This digital healthsolution offered through Babyl Rwanda is promoting access tohealthcare in a convenient and cost-effective system.
With an average waiting time to see an emergency center
physician of 30-60 minutes in Rwanda, Babyl Rwanda diminishes
the time wasted in long queues by providing immediate accessto healthcare professionals.4 The long waiting times are,in part, a result of the doctor to patient ratios that lie below
international recommendations. Given these low ratios, theartificial intelligence (AI) component of Babyl Rwanda becomes
extremely valuable. Babyl Rwanda is integrating AI into the
Babyl call center, health posts, and health centers. The AI
system will serve as a commensurable substitute to in-person
consultations with physicians given AI will have the capacityof an expert medical doctor’s brain.5 The development andexpansion of AI technology will serve as an extraordinary tool
to support the task sharing and task shifting approaches
that are in place to mitigate the shortage of highly skilled healthprofessionals. In addition to reducing time wasted awaiting
consultations and assuaging congested waiting areas, Babyl
Rwanda will also ensure that healthcare services are affordable
to the Rwandan population. As Babyl Rwanda’s consultations
are quick and convenient, illnesses can be diagnosed andtreated earlier—before the patient’s symptoms worsen andcreate a need for extensive and costly medical treatment.
While Babyl Rwanda predominantly promotes healthcare-seeking
behaviors in patients, RapidSMS serves as another mHealthinnovation that, in contrast, focuses on health service outreach.
In 2010, Community Health Workers (CHWs) adopted RapidSMS,
a mobile-based process for transferring vital health information
about vulnerable community members to a central database to
be monitored by doctors and central level staff. ThroughRapidSMS, the 58,298 CHWs in Rwanda ensure that community
members, pregnant women, and infants, in particular, receive
the swift healthcare services they require. Additionally, RapidSMS
serves as a notification system to ensure that medical
professionals are immediately alerted when life-threatening
complications arise. With the recent upsurge of malaria cases,
severe malaria was added to the RapidSMS system to acceleratereferral processes and reduce mortality. Malaria alerts
demonstrate that RapidSMS has the flexibility to accommodate
conditions that require a specific focus.

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The Global Innovation Index 2019

Some of the most significant barriers to achieving optimum
maternal and child health indexes point to the low reach,quality, and utilization of services. Low reach is largely due to ashortage of human resources needed to expand the coverageof health services. Low coverage for maternal and child healthservices results in late identification of pregnancy and laborcomplications, slow response to poor newborn health, andinadequate monitoring of child development.6 The integrationof the RapidSMS into CHWs’ daily work facilitates the expeditious
communication between CHWs and medical professionals.
This ensures that CHWs can access the clinical informationneeded to increase the effectiveness of their work, expedite
the interventions they are implementing, and improve theirconfidence in securing the health of their community members(Figure 15.1).
3. Online learning
As the health sector is ever evolving with innovative tools andpolicies to expand access to high-quality care, there is aneed to provide standardized, high-quality trainings to thehealth workforce to ensure they are prepared to adopt these
innovations. To address this need, the Rwandan Ministry of
Health developed the health sector e-learning system inJanuary 2018, which combines online distance learning withcurtailed virtual face-to-face sessions to offer learners the
optimal learning experience.7 The online learning affords thehealth sector workforce the flexibility to build their skills andknowledge at home, during breaks at work, or anywhere an
individual has an internet connection, as courses can be takeneven on smartphones.
Online training—which offers flexibility in the time, location,and pace that health workers consume new information—
averts the absenteeism that is typically associated with healthworkers’ attendance at traditional face-to-face training. A study
examining the causes of low health worker performanceand outputs in low-income countries recognized that traditional,
in-service training was associated with reduced productivity
because it served as an authorized absence for staff.8
Furthermore, e-learning aims to ensure that the entire population
is afforded high-quality health services by providing training tohealthcare workers in even the most remote areas of the country.
The most recently launched e-learning course was offered to
district and private hospital data managers. Data managers,
monitoring staff, and evaluation staff—representing all public
and several private hospitals throughout the country—enrolled
in the course. Through this online training, the Rwanda Ministryof Health was able to ensure that all 60 participants received
consistent, high-quality training and were equipped to integrate
leading data quality mechanisms into their daily work practices.
A meta-analysis conducted by the United States Department of
Education discovered that e-learning users performed modestly
better, on average, than students learning the same material
through traditional face-to-face instruction.9 This improvement inlearning outcomes and evidence regarding the cost-effectivenessof online learning have encouraged policymakers to integratee-learning into their educational initiatives.10

FIGURE 15.1

RapidSMS Rwanda information ﬂowchart• Easy remote web access by all stakeholders• Provides countrywide data on maternal and child health

Ministry of Healthuser interface

Ministry of Health
RapidSMS
central server

HealthcenterCHW
sends
messages

Automated
response
to CHW

District
hospital

Ministry of
Health(central level)

RED ALERT EMERGENCIES••••

Ambulance dispatched
Nearest relevant health center notiﬁed
District hospital notiﬁed
Supervisor notiﬁed

Community healthworker (CHW)

Umudugudu

Source: Scaling Up Nutrition, 2016.

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Impact of innovations on the qualityof health services
The aforementioned innovations propel the continued
strengthening of healthcare services offered in the country.
Rwanda is a country that promotes evidence-based innovationand is eager to adopt blockchain, genomics, and precision
medicine. The country’s leadership ensures that all of these
innovations serve the common denominator of equitable accessto high-quality healthcare for the entire population. The
integration of blood and vaccine delivering drones, mHealth,and online learning into the health system have served to
expand equitable access to healthcare across the Rwandan
population in the most cost-effective manner.
The blood and vaccine delivering drones, for example, are not
only cost-effective in preventing the wastage of blood supplies,
but a study found that emergency shipments by drones
could be more cost-effective than the use of common transportmeans (ground ambulances and motorcycles). The analysis
not only includes cost savings but also suggests that there
is a time-saving element to using drones.11 Rwanda’s blooddelivering drones also contribute to the country’s aspirationsof providing healthcare services to the population as thecold-chain capabilities of the drones preserve the quality ofvaccines and blood that reach their intended clients.
RapidSMS is the most well-documented innovation becauseof its contribution to improving the quality of health services
in Rwanda. As one of mHealths’ digital health solutions,
the RapidSMS has contributed to the country’s improvements
in maternal and child healthcare. As postnatal care is essential
for safeguarding the health of newborns and mothers, theintroduction of RapidSMS has led to an increase in the total
number of postnatal care visits.12 This increase is significant
given that over 50% of pregnant women had not received
postnatal care checkups according to the 2014/2015 Demographicand Health Survey.13 As RapidSMS assists in the expansionof healthcare services, several stakeholders also suggest thatthe system contributed to improvements in the quality ofservices provided both in the community and in health facilities.14
One example of this includes the testimonies received from
district- and community-level healthcare personnel who foundthat RapidSMS helped them reach their targets for careprovision.15 A less studied mHealth solution is Babyl—Rwanda’s
largest health service provider.16 While this innovation is fairly
new, the formative evaluations that have been conductedsuggest that this innovation is a time-saving solution for boththe individuals seeking care and the health system. Mobile
consultations are afforded to thousands of Babyl Rwanda users
through the medical AI agent that mimics the thought processesof an expert medical doctor’s brain which enables it to provide
quick and reliable healthcare to Babyl Rwanda’s clients.17
The last health innovation which contributes to health service
quality improvement is Rwanda’s Health Sector e-Learning
System. This system safeguards the equitable distributionof high-quality training to healthcare workers throughout

180

The Global Innovation Index 2019the country. Preliminary results from course evaluations andpre- and post-training assessments completed by e-learning
participants suggest that a majority of participants gain criticalknowledge and skills upon completion of these courses andgain confidence in their ability to carry out their daily work
responsibilities. As healthcare providers acquire new skills andknowledge through standardized training and experience aboost in confidence in their ability to provide quality healthcare,
the healthcare services offered throughout the country will
similarly improve.

Main challenges and opportunities
While e-learning has it’s benefits—such as ensuring the healthworkforce is properly trained on innovations integrated into thehealth system—the blended learning approach that is used in
the health sector e-learning system may still increase the time
healthcare workers spend away from their patients. Additionally,
capacity building in areas, such as service delivery, requires
numerous practical sessions. These sessions should becomplemented through—not replaced by—e-learning courses.
The integration of technology into the health system also requires
greater investment in infrastructure. As new systems—suchas the delivery of medical supplies by drones—are integrated
into the health infrastructure, new policies must be developed
to regulate the services and maintain a standard of quality inservice delivery. Additionally, the health system in Rwanda
must continue to foster strong partnerships with private sector
experts to ensure that technology interventions are effectively
integrated into health service delivery.
Finally, given the increasing cost of healthcare—caused byan increase in healthcare utilization, life expectancy, andnon-communicable diseases—it is of paramount importanceto find cost effective ways of providing the best and safest care
to all. For example, the Joint United Nations Programme on
HIV and AIDS (UNAIDS) noted a substantial decrease in AIDS
funding from 13 governments in 2016.18 Several innovations havebeen integrated into health systems around the world to reduce
the transmission of HIV, such as pre-exposure prophylaxis andHIV self-sampling kits. It is essential that these efforts continue
to be funded to ensure countries that have been successful
in reducing the incidence of HIV transmission, such as Rwanda,
can reach the goal of ending AIDS as a public health threatby 2030.

Conclusion
Rwanda’s receptiveness to, and interest in, the adoption of
innovative solutions to public health challenges has led to thecountry’s remarkable progress—both in enhancing health equity
and towards achieving universal health coverage. As one of
the first countries in the world to utilize drones as a methodof equitably distributing health products to citizens throughout
the country, Rwanda has embraced the idea of integrating

technology into the health system to provide high-quality,
equitable services to the population.

Notes:
1

Zipline, n.d.

2

Ackerman et al, 2018.

3

Glauser, 2018.

4

Pascasie et al., 2013.

5

Kantengwa, 2017.

6

Mwendwa, 2016.

7

Lyle et al., 2018.

8

Dovlo, 2005.

9

U.S. Department of Education, 2010.

10

Bartley et al., 2014.

11

Würbel, 2017.

12

Würbel, 2017.

13

National Institute of Statistics Rwanda, 2016.

14

Ruton et al., 2016.

• collaboration with the Republic of Rwanda Ministry of
Infrastructure, which includes the civil aviation mandate toensure the availability of well-established regulations forblood and vaccine delivering drones to operate in Rwanda;• the country’s mobile phone penetration, which crept up to
76.1% in February 2018, driving the expansion and successof mHealth services;19 and• significant investment in expanding internet connectivity,
especially fiber optic telecommunication networks acrossthe country, ensuring the feasibility of the e-learning system.

15

Musabyimana et al., 2018.

16

Babyl, n.d.

17

Rwanda Guide, 2018.

18

UNAIDS, 2016.

19

The New Times, 2018.

Beyond the technological innovations, the contributions fromother sectors suggest that health technology is not the soleforce driving the expansion of health equity throughout thecountry. The Ministry of Health’s appetite for reaching acrosssectors to improve collaboration, coordination, and communication
has made immeasurable contributions to the health sector’s
success in implementing these technological innovations. The
commitment of CHWs and the private sector to use technology
to reach citizens in even the most remote areas of the country
suggests that partnerships between internal and external actors
are essential to providing affordable, effective, and high-quality
health care to the population.

Ackerman, E., & Strickland, E. (2018). Medical delivery drones take flight in East
Africa. IEEE Spectrum, 55(1), 120-125. Retrieved from https://ieeexplore.
ieee.org/abstract/document/8241731

Furthermore, the country’s adoption of mHealth—to deliver
quick and effective health services, reduce waiting room
congestion at health facilities, and communicate the healthemergencies which occur in the community to medical experts
in the capital—safeguards the equitable distribution of high-quality
services to the entire population. As the health sector’s effective
use of drones and mobile devices are used for deliveringhigh-quality services, the proper uses of these health innovations
require high-quality training. The adoption of innovations suchas an e-learning system targeting the health workforce ensuresthat healthcare professionals are proficient in utilizing these
innovations countrywide.
While the health sector may encounter challenges in theimplementation of these health innovations, the amalgamationof strong political will and good governance involving thecontributions of other sectors in Rwanda enables the healthsector to push forward and find solutions to those challenges.
Some of the contributions from other sectors include:

The Government of Rwanda’s readiness to partner withtechnology experts from the private sector further propels theirsuccess in integrating technology innovations into the healthsystem. Technological progress does not always equate tohealth equity; however, the Government of Rwanda remained
mindful of its intention to integrate technology that furthers
equitable access to high-quality services into the health system.
This has driven its success in using technological innovations
to achieve inclusive and equitable health for the population.

References:Babyl. (n.d.). Retrieved from http://www.babyl.rw/
Bartley, S. J., & Golek, J. H. (2014). Evaluating the Cost Effectiveness of Online
and Face-to-Face Instruction. Educational Technology & Society, 7(4),167-175.
Dovlo, D. (2005). Wastage in the health workforce: some perspectives
from African countries. Human Resources for Health, 3(6). Retrieved
from https://human-resources-health.biomedcentral.com/articles/10.1186/1478-4491-3-6
Glauser, W. (2018). Blood-delivering drones. CMAJ, 190(3), E88-E89. Retrieved
from https://europepmc.org/articles/pmc5780273
Kantengwa, S. (2017). Babyl Rwanda on providing digital healthcare. The New
Times. Retrieved from https://www.newtimes.co.rw/section/read/222717
Lyle, V., & Muhire, A. (2018). With high costs and worker absenteeism
associated with in-person trainings of health workers, can eLearning be
the remedy? eLearning Africa. Retrieved from https://ela-newsportal.
com/with-high-costs-and-worker-absenteeism-associated-with-in-person-trainings-of-health-workers-can-elearning-be-the-remedy/
Musabyimana, A., Ruton, H., Gaju, E., Berhe, A., Grépin, K. A. et al. (2018).
Assessing the perspectives of users and beneficiaries of a community
health worker mHealth tracking system for mothers and children in
Rwanda. PLoS One, 13(6). Retrieved from https://www.ncbi.nlm.nih.gov/
pmc/articles/PMC5991741/

Chapter 15181

Mwendwa, P. (2016). Assessing the fit of RapidSMS for maternal and new-born
health: perspectives of community health workers in rural Rwanda.
Development in Practice. Retrieved from https://www.researchgate.
net/profile/Purity_Mwendwa/publication/287375589_Assessing_the_fit_of_RapidSMS_for_maternal_and_new-born_health_perspectives_of_community_health_workers_in_rural_Rwanda/
links/5b5a02d20f7e9bc79a6684e6/Assessing-the-fit-of-RapidSMS-formaternal-and-new-born-health-perspectives-of-community-health-workers-in-rural-Rwanda.pdf
National Institute of Statistics Rwanda (2016). Rwanda Demographic and
Health Survey 2014-15. Retrieved from http://www.statistics.gov.rw/publication/demographic-and-health-survey-20142015-final-report
Pascasie, K. & Mtshali, N. G. (2013). A descriptive analysis of Emergency
Department overcrowding in a selected hospital in Kigali, Rwanda.
African Journal of Emergency Medicine, 4(4), 178-183. Retrieved fromhttps://www.sciencedirect.com/science/article/pii/S2211419X14000044
Ruton, H. & Musabyimana, A. (2016). 2016 Rwanda: Rwanda RapidSMS impact
evaluation. Retrieved from https://www.unicef.org/evaldatabase/index_95032.html
Rwanda Guide. (2018). Babyl’s chatbot to enhance digital healthcare platform.
Retrieved from https://rwandaguide.info/post-details/babyls-chatbot-to-enhance-digital-healthcare-platform
Scaling Up Nutrition. (2016). How Rwanda Rapid SMS Works Illustration.
Retrieved from https://scalingupnutrition.org/news/monitoring-performance/photo-4-how-rwanda-rapid-sms-works-illustration-02/
The New Times. (2018). Rwanda’s mobile telephone penetration rate rises to76.1%.Retrieved from https://www.newtimes.co.rw/section/read/231156
UNAIDS. (2016). The collapse of global AIDS funding. Retrieved fromhttp://www.unaids.org/en/resources/presscentre/featurestories/2016/
july/20160719_funding
U.S. Department of Education. (2010). Evaluation of Evidence-Based Practices
in Online Learning. Retrieved from https://www2.ed.gov/rschstat/eval/tech/evidence-based-practices/finalreport.pdf
Würbel, H. (2017). Framework for the evaluation of cost-effectiveness of drone
use for the last-mile delivery of vaccines. Retrieved from https://logcluster.org/sites/default/files/gm_files/master_final_project_heike_wurbel_13_jun2017_003.pdf
Zipline. (n.d.). Our Progress, Daily Deliveries Across Rwanda & Ghana.
Retrieved from http://www.flyzipline.com/

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The Global Innovation Index 2019

CH AP T E R 16

IRAN’S EXPERIENCE IN
DEVELOPING HIGH-TECH
MEDICAL INNOVATIONSAND THE PATH AHEAD
Kiarash Fartash, Shahid Beheshti University
Mahdi Elyasi, Allameh Tabataba’i University

Over the last two decades, the Islamic Republic of Iran has
made significant progress in the health and medical sector,
expanding both in market size and coverage. The ever-growing
medical innovation ecosystem is supported by ongoing policy
framework developments, incentives, and regulatory bodies.
In addition, the emergence and development of the biopharma
sector in Iran, which is a complex, high-tech sector, hosts
several successful local export firms.

From a science, technology, and innovation (STI) perspective,
Iran has boosted scientific production in areas such as
nano-tech, biotechnology (biotech), biomedical engineering,bioengineering, biomaterials, and biophysics. For instance,
rankings have improved from either non-existent or around60th position in the late 20th century to 4th in nano-tech,
12th in biomedical engineering, 9th in bioengineering, and8th in biomaterials, in 2017.2

The focus of this chapter is the evolving pro-innovation ecosystemof the health sector in Iran. This ecosystem has achieved
effective policy and regulatory synergies and has supported the
supply- and demand-side of medical innovation. Demand-side
innovation has paved the way for advanced endogenous
medical innovations in Iran while, historically, conventional
medical solutions were not easily accessible due to sanctions
or affordability.

STI efforts to transform the medical and health sector resulted
in synergies between human capital supply, technological regime,
and the innovation ecosystem. In addition, state-of-the-art
medical innovation continues to advance through expanding
medical education, support for university- and firm-levelresearch and development (R&D), and the creation of anevolving pro-innovation, medical policy framework. The medical
innovation ecosystem—supported by over 19,300 faculty
members from medical universities and research institutes,
and responsible for roughly 37,450 scientific papers and 1,589
patent applications in 2018—has the capacity to host various
research activities.3

The chapter provides policy- and firm-level recommendations
to highlight common success factors of medical innovation,
based on the mentioned case studies and field interviews
conducted with firms and policymakers. In addition, we discuss
ways to mitigate impediments to further innovation.

Advancing health coverage,
research, and innovation
Iran’s improvement in health-related indicators has been
consistent and promising. According to the Human Development
Index (HDI), the mean years of life expectancy in Iran has
increased dramatically from 51.1 in 1980 to 76.2 in 2018, anapproximate 25-year increase over the past three decades.1

In 2018, the National Medical Device Directorate (NMDD)
reported that the Iranian medical equipment market was worth
US$2.5 billion, of which 30% belonged to over 1,000 domestic
firms.4 On a global scale, 56% of 500,000 medical equipment
items available in the world market have Iranian-made versions.5
In pharmaceuticals, around 70% of Iran’s US$4.5 billion market
is domestic products and, in 2018, 97% of pharmaceuticals
consumed in the country were manufactured locally.6 Furthermore,in 2018, 67% of the active pharmaceutical ingredients (APIs)
used to produce drugs in Iran were made locally.7

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185

Boosting the medical innovation
ecosystem through policy framework

expenses for these products.11 Supporting the local productionof drugs has successfully promoted domestic product sharein the national pharmaceutical market, from 63.4% in 2009 to
78.6% in 2018.12

Medical innovation policy framework
Iran has integrated its healthcare system with medical education
to improve health conditions. Sixty-five medical universities,
responsible for both health services and medical higher education,
constitute a decentralized network of provincial healthcare
bodies that are managed centrally by the Ministry of Health(MOH). This network has contributed to the creation of a strong
healthcare system characterized by extensive and convenient
access to medical services, both in rural and urban areas.
In each province, public medical universities provide medical
services, administer vaccinations, and assist in fighting local
diseases. Because of countrywide distribution, the network
has the ability to undertake endogenous research andinnovation and train medical cadres based on local demands
and epidemic situations.
Since the early 1990s, the MOH has followed a five-year national
development plan (FYDP), revised in five-year intervals, as theprincipal policy framework for enhancing Iran’s health sector.8
In 2014, during the 5th FYDP, the MOH initiated and fundedthe Health Transformation Plan (HTP), which has resulted ina sharp decrease in the share of medical expenses paid by
patients—from an initial out-of-pocket expense of 37% of overallpatient health costs to 5% for rural citizens and 10% for urban
citizens. The key health policy for the 6th FYDP (2016 to 2021),
is dedicated to providing universal health coverage using
coordinated public insurance schemes governed by the MOH.
According to the MOH, 100% of urban and 98% of rural areas in
Iran now have access to at least primary medical services.9
Policies supporting the supply side of medical innovations:
In the 1980s, lack of access to foreign drugs and medical
equipment became a threat to national health and well-beingin Iran. For this reason, Iran adopted import substitution policies
and promoted local production. In 2011, the Food and Drug
Administration of Iran, under the MOH, introduced a set of
regulations to support the supply of local medical equipment
and pharmaceutical products. These regulations ban or limit
the import of foreign drugs and medical equipment to 10%
of market share when a similar local product becomes available.
When local products are available, public health insurances
do not cover the costs of foreign drugs for patients, but they
do cover from 90 to 100 percent of the total cost of thedomestic equivalent.10
Imposing high tariffs on foreign drugs and/or medical equipment,
when an equivalent is locally produced and developed to meetdomestic demand, is also a tool to support medical innovation.
In cases where the domestic equivalent is not available, lowtariffs of 4% are set on foreign products. However, when thedomestic equivalent is available and verified by the MOH, thesetariffs increase from 4 percent to between 32 to 45 percent, andpublic health insurances will no longer cover patient medical

186

The Global Innovation Index 2019

But, this approach will not guarantee the success of medical
innovations in the long run. Policymakers and firms are awareof the possible harmful consequences of import substitution
on future medical innovation.13 Hence, exporting medical
innovations is strongly encouraged by recent policies, suchas the law for supporting knowledge-based firms (KBFs). Thislaw, approved by Parliament in 2010, was introduced as amechanism to encourage the supply side of technology andinnovation in high-tech firms, benefitting the health sector.14
The Vice-Presidency for Science and Technology (VPST)
administers this law and the Innovation and Prosperity Fund
(IPF) channels funds to the innovative and technologicalactivities of eligible KBFs. Eligible firms include private entities
that produce high-tech products, require in-house R&D
and skilled employees, are high value-added, and are difficult
to imitate. In early 2019, US$85 million had been allocatedin the form of low-interest rate loans to fund 474 medical
innovation projects by the IPF. Additionally, the VSPT supports
4,300 KBFs, of which approximately 1,100 KBFs are private
health and medical sector firms.15
Policies supporting the demand side of medical innovations:
Policy efforts are also in play to push medical innovation on the
demand side (Figure 16.1). One example is the Iran Lab Expo
(ILE), initiated by the VPST in 2012 to promote technology &innovation (T&I) development by private firms.16 Depending on
the depth of domestic capabilities to design and manufacture
independently as well as the technological complexities of thelab equipment and/or device, public buyers, such as universities
and hospitals, are entitled to a VPST subsidy of between 10 and
40 percent of total cost. To encourage and stimulate demand
from private buyers, the ILE grants low-rate, medium-term loansof up to US$120,000.17 In addition, the Heyat Omana Arzi (HOA)
plays a critical role, on behalf of the MOH, to procure and supply
medical disposables, devices, and equipment to public hospitals
and medical centers. The HOA also provides patients withprerequisites for domestic treatment, minimizing dependency
on foreign treatment and medical expenditure.18
Medical innovation ecosystem and its key actors
A community of vibrant young entrepreneurs in Iran has
pioneered state-of-the-art medical innovations. Their efforts
are reinforced by evolving government support in the formof tariff barriers, tax exemption, and guaranteed purchase.
The law for supporting KBFs has played a key role in empowering
the medical innovation ecosystem. There are 4 dedicated
S&T parks, 78 incubators, and 739 research centers in a variety
of medical fields affiliated with the MOH.19 Furthermore,
68 incubators and 27 S&T parks, under the supervision of
the Ministry of Science Research and Technology (MSRT),
specialize in supporting medical and pharmaceutical sectors.20
As of February 2019, medical related KBFs—approximately 1,100

F IGU RE 16.1

Key policies and actors supporting medical innovation in Iran

• Food and Drug Administration—
certiﬁes all foods and drugs
for consumers• National Medical Device
Directorate—responsible forcertifying local and imported
medical equipment/devices• Iranian National Standards
Organization—certifying all
foods, medical equipment
when applicable• Ministry of Health
Health Technology Council—
supports technology andinnovation development inhealth sector
Food and Drug Administration—
sets high tariﬀs and limits market
share of imported drug andmedical equipment whendomestically produced options
are available• Vice-Presidency for Scienceand Technology—supports
knowledge-based ﬁrms byoﬀering instruments such as tax
and duty exemptions; funding
and supporting major healthsector innovative projects
called mega projects• Ministry of Industry, Mines
and Trade—imposes importtariﬀs on drugs and medical
equipment in coordination
with Ministry of Health, upon
availability of domestic
products• Research and technology
funds and VCs—21 S&T funds
and 9 VCs such as Innovation
and Prosperity Fund; Biotech
Fund; Medical Equipment Fund;
Tehran Health Fund
• CVCs—PersisGen in biopharmafounded by CinnaGen• National IP oﬃce; IP oﬃces
in universities• Innovation centers—79 centers• Accelerators—29 accelerators• S&T parks and incubators• Health techmarts• Medical equipment &pharmaceutical ﬁrms—
about 1100 ﬁrms
• Commercial ﬁrms—importing
drugs and medical
equipment and providing
after-sale customer services• Research centers—such as
Pasteur Institute, Razi Institute,
National Institute of Genetic
Engineering and Biotechnology;
739 university research centers• Universities—such as biotech,pharmacy, science, medical
engineering, chemistry, andother relevant faculties in both
medical and conventional
universities• Ministry of Health
Health Technology Council—
strengthening university-industry
collaborations in health sector
Heyat Omana Arzi—procuring
aggregated medical equipment
and drugs for MOH leveraged
to support medical innovationand made-in-Iran products• Vice-Presidency for Scienceand Technology—subsidizes
lab equipment/devices for
public hospitals and universities
and grants loan to private buyers
by Iran Lab Expo initiative
Biotech Council—coordinatesand supports development ofbiotech-related technologies
and products, including
biopharma• National Medical Device
Directorate—encourages
export of medical equipment;
pushing local ﬁrms to acquire
local and international
standards such as CE/ISO■ Regulators■ Supply side

■ Intermediaries■ Demand side

Sources: Ministry of Health and Medical Education, 2019; Institute for Trade Studies and Research, 2017a,b; UNCTAD, 2016.
Note: Data extracted from information provided by actors on their websites and available periodical reports.

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FIGU RE 16.2

Iran’s biopharma evolution and key products

2003

CinnaGen started collobaration with Fraunhofer to develop interferon beta-1a

2006

Production of CinnoVex® (interferon beta-1a) by CinnaGen for MS treatment(3rd country in the world to produce); Introduction of PDpoetin® (erythropoietin)
by Pooyesh Darou for hemodialysis patients

2008

ReciGen® (interferon beta-1a) produced by CinnaGen for enhancing immune
cell activities; γ-Immunex® (interferon gamma-1b) by ExirPharma for improving
immune system produced

2012

Production of CinnoRA® (adalimumab) by CinnaGen for rheumatology treatment;
recombinant activated human blood coagulation factor VIIa, with the trade nameAryoSeven™, developed by AryoGen for hemophilia treatment; Herceptin (trade namefor trastuzumab) introduced for ﬁghting breast cancer

2013

Production of PegaGen® (pegylated ﬁlgrastim) by CinnaGen forﬁghting cancer

2014

Glatiramer (trade name Osvimer®) and deferasirox (trade name Osveral®)developed by Osvah Pharma for multiple sclerosis treatment

2016

CinnaGen produced: CinnoPar® (teriparatide) for osteoporosis treatment;
CinnaTropin® (somatropin) to enhance growth of bones and muscles andincrease metabolism; Cinnal-f® (follitropin alfa) for infertility treatment; CinnoRA®
(adalimumab) for autoimmune diseases

2019

Saman daroo 8 produced human recombinant factor VIII (hr FVIII) under tradename Safacto (SD8) for hemophilia patients

Source: Institute for Trade Studies and Research, 2017a.
Note: Data in this ﬁgure have been partially extracted from the information provided on websites and periodical reports of Iranian biopharma ﬁrms.

188

The Global Innovation Index 2019firms—are engaged in T&I development, including 200 biotech
firms, 255 advanced pharmaceutical firms, and 175 medical
equipment firms.
Accelerators and innovation centers are the most recent
mechanisms used by the government and, in particular, the
VPST to expand and increase the efficiency of KBFs. To date,29 accelerators and 79 innovation centers are operationaland open to medical innovators and entrepreneurs. PersisGen,
established in 2016 by CinnaGen, is an example of a medical
accelerator—perhaps the most successful and prominent
in Iran—which provides corporate venture capital (CVC).21
As of February 2019, PersisGen had hosted 15 teams towork on 20 advanced biopharma innovations, of which 4 teams
had reached the final product.
The major funding institution, IPF, supports medical innovation
mainly by granting loans—US$85 million to date—to facilitate
KBF efforts in developing medical equipment, biotech, andadvanced drugs. Another active funding body, the Iran Biotech
Fund (IBT), was founded in 2015 by the Biotech Development
Council, an affiliate to VPST, and is supported by joint investment
from the private sector.22 At the end of 2017, IBT had invested
US$4 million in venture capital (VC) in 24 innovative ideas
and, from its inception, has granted 350 loans—total of US$11.7
million—to a wide range of innovative biotech ideas and projects.
Biopharma in Iran: a unique and advanced sector
Over the last two decades, Iran’s STI efforts, accompaniedby policy support, in biotechnology and pharmaceuticals
has resulted in a rapid increase in biotechnology scientificpublications—ranking 9th in bioengineering, 9th in applied
microbiology and biotechnology, and 13th in biotechnology
in 2017.23
Iran’s history in biopharma dates back to the 1920s when the
Pasteur and Razi Institutes, initially specializing in producing
vaccines and then biotechnology, gradually diversified into
biopharma. In the 1980s, the National institute of Genetic
Engineering and Biotechnology and the Iranian Red Crescent
boosted biopharma development. The turning point, in the
1990s, came when the government supported and collaborated
with foreign countries, including Cuba, to train Iranian scientists
and researchers. Shortly after, trainees, along with otherambitious scientists and researchers, formed an inner circleof Iranian biotechnology and biopharma pioneers thatrevolutionized biopharma in Iran by founding firms such as
CinnaGen, ExirPharma,24 Ronak Daru,25 Pooyesh Darou,26Osvah Pharmaceutical,27 Saman daroo 8,28 Zist Daru Danesh,29
and AryoGen.30 International collaboration and STI linkages
in biopharma have been instrumental to the success of medical
innovation in this sector, but global collaboration barriers,
such as sanctions, remain a challenge. Key events in the courseof biopharma development in Iran are shown in Figure 16.2.
Currently, there are 20 Iranian biopharma firms, 7 of which are
KBFs supported by the VPST. Of the 22 drugs that these firms
produce, at least 10 are considered state of the art. The

local development of biopharma products has resulted insavings of US$980 million annually, created over 4000 quality
jobs for Iranian scientist and researchers, and is accountable
for roughly US$60 million of Iran’s pharmaceutical exports—of
which a sizeable share is exported to Europe.31
Although the quantity of biopharma products sold in the local
market is not comparable to conventional drugs, three of the
top five pharmaceutical manufacturers—in terms of total sales
in 2017—are CinnaGen, ExirPharma, and AryoGen. These threemanufacturers hold 11.2% of the pharmaceutical market share.
In the same vein, AryoTrust™ (Trastuzumab for breast cancer
treatment), Cinnovex® (interferon beta-1a for multiple sclerosis
treatment),32 and ZytuxTM (Rituximab for fighting cancer andautoimmune diseases developed by AryoGen) are among the
top 10 drugs sold in 2017.33
Cases of advanced medical innovations in Iran
The increasing and developing market for pharmaceuticals
and medical equipment—fueled by local technological andinnovative efforts, continued public support, and an influx ofinterested young medical entrepreneurs—reflects the dynamics
of medical innovation in Iran. Three noteworthy cases ofadvanced medical innovations are explored below, whilst
looking at the main drivers of success and challenges as wellas the barriers to further innovation.
Medical devices and equipment incubator (MDEI)34: The
MDEI, based at the Imam Khomeini hospital in Iran, hosts several
promising firms that are equipped to design and manufactureadvanced medical equipment and develop cutting-edge
technologies.35 One of these firms, Sina Robotics and Medical
Innovators Co, a KBF, develops Sina—a robotic telesurgery
system which assists surgeons in sophisticated surgeries.36
A guaranteed purchase order by the government in 2009 drove
Sina’s development, which had commenced in the early 2000s,
and by 2013, the first generation of Sina became available.37
The improved Sina, equipped with added force feedback
capability and more, has advantages over similar products on
the market and has gained significant international interest.
With over 30 patents registered on Sina, the drivers of its
success include: the government order, which overcame
sanctions that had made the system locally inaccessible; internal
R&D capabilities; the availability and dedication of qualified
and talented human resources; and the proximity to clinicalpractice. Sina creators have faced lack of interest from private
investors and delays in allocating public support funds.38
Tanin Pardaz Pasargad (TPP)39: TPP, a KBF, specializes indesigning and manufacturing the external unit of the cochlear
implant system (CDS) called TAPPS+.40 Established as acompany in 2013, the founders began research efforts almost
two decades earlier. After several generations of prototypes,
TAPPS+ was introduced in 2016 with the expectation of releaseto the public in 2019. TPP is one of five firms in the world
offering a similar product and interest from leading firms tocollaborate on TAPPS+ is growing.

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One complementary asset to TAPPS+ is executing the transtympanic
promontory stimulation test (TPST) using the ETT device.41
TPST is a tool used to evaluate the effectiveness of cochlear
implant surgeries, especially in patients with weak auditory
nerves and those who have been deaf for a prolonged period.
Another significant innovative product by TPP uses deafness
recognition by baby crying, which offers free and efficientevaluation of infant cry signals to detect deafness in babies.42
Although TPP provides a number of innovative products, a few
challenges inhibit TPP’s ability to realize its efforts. For example,
complying with local standards is a complicated and lengthy
process. Moreover, there is a need to implement a proactive
marketing strategy and to increase stakeholder involvement—in particular, sales representatives of foreign CDSs.43
Behyaar Sanaat Sepahan (Behyaar)44: Behyaar, founded in
2003, is a KBF specializing in radiotherapy and radiography
solutions.45 In 2010, the founder—a young engineer activein linear accelerator (LINAC) maintenance in Isfahan hospitals—
decided to build a locally made LINAC. Given Iran’s need to
produce 240 LINACs by 2025—almost three times the available
amount—it was a wise decision. In 2017, relying on in-house
R&D, Behyaar built the OMID 6MV, a medical linear accelerator
which puts Iran among roughly 10 countries involved in building
medical LINACs. Furthermore, LINAC design and development
led Behyaar to develop the first Iranian-made cargo inspection
system, called Sayyad, designed to inspect loaded trucks,
containers, and vehicles at ports, airports, and borders.
It uses a dual energy LINAC that penetrates up to 320
millimeters in steel.
Despite numerous failed attempts owing to product complexityand lack of available expertise, Behyaar transformed froma company that used to build simple hospital beds to one
designing optical lenses, 3D water phantoms, X-ray systems,
image viewing systems, and U-arm ceiling radiology systems.
Overcoming these challenges required persistence, risk-taking
and in-house R&D. Yet, Behyaar faces a barrier to further
innovation and commercialization—the prolonged process toacquire approvals for equipment using radiation. This process
can be longer than the product development period itself.46

Conclusions and policy
recommendation to strengthen
medical innovations
Over the past two decades, several domestic firms have pursued
medical innovations, some of which are more advanced anduser-friendly than world-leading products—particularly in thebiopharma and medical equipment sectors. These innovations
were driven by the necessity to fulfill local demand for drugs
and medical equipment when international solutions wereneither accessible nor affordable. Providing all citizens withaffordable universal healthcare and medical services that arerecognized by government and firms encourages the realizationof medical innovations.

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National necessity, foreign currency saving, self-reliance,
ambition, public incentives, and public policies have afforded
Iranian medical researchers and entrepreneurs the opportunity
to design and develop medical equipment and advanced drugs.
Despite the sizeable share of local medical products in the
Iranian market, further domestic innovation requires economies
of scale that cannot be attained solely by tariff barriers andmarket protection. To achieve economies of scale, local firms
must export their products. It is imperative that the government
systematically continues to facilitate and monitor the exportof medical products.47
Even with many successes, Iranian firms face barriers tocontinued innovation, such as lack of customized public
support, branding, international acceptance, and standards.
Overcoming these barriers would require establishing acoordinated policy framework and creating synergies between
current policies. Several policy recommendations to strengthen
medical innovation and increase economic impact include:• The scale of the domestic health market is not large enoughto justify the development of costly and long-lasting medical
innovations. To deter exclusive reliance on the domestic
market, strong policy measures should be established toencourage local firms to export their products. The export
process can be lengthy, which suggests that enhancing
accreditation infrastructure and standardization facilities
would encourage exports more than, for example, accessto low-rate loans.
• Government support of local firms has proved to bebeneficial; therefore, government should increasingly trustand encourage local firms to engage in high-end medical
innovations.
• As leading firms play an important role in the economy,
the government should adequately support them in thedevelopment of medical innovations and the creation ofa dynamic knowledge regime. This would entail enforcing
fewer formalities on leading firms, facilitating medical
exports, and assisting with the import of raw materials andproduction equipment. To this end, the Vice-Presidency
for Science and Technology has devised Pioneer KBFs,
a direct communication line to gather information about
the needs and challenges of leading firms and to addressthese in the shortest time possible. The Ministry of Healthis encouraged to adopt a similar approach to facilitateand support leading firms.
• According to local firms, some foreign firms that import
medical equipment do not face the same difficulties
experienced by locals, specifically in obtaining permissions
and certifications needed to launch their product in themarket. Giving procurement and tender priority to domestic
products and firms over the foreign equivalent should be
reinforced by the Ministry of Health. In other words,
government should take measures to limit foreign medical
imports, especially products of lower quality, as a means toencourage local firms to engage in medical research andinnovation, as is the case with many other countries.
• Current funding systems that support medical innovation arelargely risk-averse. Although institutional mechanisms—

such as the Iran Biotech Fund and the Innovation and
Prosperity Fund—have helped to mitigate innovation risks,
there is a need to enhance efficiency and availabilityof funding, particularly venture capital. Formulating acomprehensive technology and innovation funding systemin the health sector by socializing some of the inherent risks—
for example, through guaranteed public procurements
and grants in the medical innovation process—could be
the starting point to attract more private funding.48

24

More information can be found at http://www.exir.co.ir/index.php/en/25

More information can be found at http://ronakpharm.com/

26

More information can be found at https://pooyeshdarou.com/

27

More information can be found at http://www.osvahpharma.com/en

28

More information can be found at http://samandaroo.com/english/

29

More information can be found at http://zistdaru.ir/?lang=en

30

More information can be found at http://www.aryogen.com/EN/index.html

31

Institute for Trade Studies and Research, 2017a.

32

Multiple sclerosis, or MS, is a long-lasting disease that can affect brain,
spinal cord, and the optic nerves in eyes. It can cause problems withvision, balance, muscle control, and other basic body functions. MS
insulates covers of nerve cells in the brain and spinal cord are damaged.

33

Food and Drug Organization, 2017; Food and Drug Organization, 2018.

34

More information on the incubator activities can be found at http://icmed.tums.ac.ir/

35

Imam Khomeini hospital is a medical institution affiliated to Tehran
University of Medical Sciences

36

More information about Sina Robotics and Medical Innovators can befound at http://sinamed.ir/

37

PARSISS Integrated Company, established in 2006, is anothercompetent firm located at the MDEI. PARSISS has successfully
developed the Parseh surgical navigation system (SNG) that was
introduced in 2011. Thanks to Parseh, Iran is among only sevencountries in the world manufacturing SNG. Parseh market share in Iranis about 80 percent and its market price is between 30 and 50 percent
of foreign SNGs. The main success factors of Parseh are building trust
between PARSISS team and surgeons, mastering SNG core technologies
by in-house R&D, and proximity to clinical practice; based on Interview
with PARSISS business development manager, Mr. Javad Hasani,
conducted by authors in 30 January 2019.

38

Interview with the CEO of Sina Robotics and Medical Innovators,
Mr. Alireza Mirbagheri, conducted by authors in 27 January 2019.

39

More information about TPP can be found at http://taninpardazco.com/
en-us/

40

More details on TAPPS+ can be found at http://taninpardazco.com/enus/Products/Tapps

41

More details on ETT can be found at http://taninpardazco.com/en-us/
Products/ETT

42

More information on baby crying test can be found at http://taninpardazco.com/en-us/Activities/Hearing-Detection/BabyCrying

43

Interview with Tanin Pardaz Pasargad CEO, Ms. Samira Kooshkestani,
conducted by authors in 28 January 2019;. Interview with Tanin Pardaz
Pasargad founder, Mr. Hamed Sajedi, conducted by authors in 28
January 2019.

44

More information about Behyaar is available at http://www.behyaar.com/en/

45

More details on Behyaar products is available at http://www.behyaar.
com/?page_id=3299

46

Interview with Behyaar’s CEO, Mr. Navid Nejatbakhs, conducted byauthors in 23 January 2019.

47

Masaeli, 2018b.

48

Mazzucato, 2015.

Notes:
1

United Nations Development Programme, 2018.

2

StatNano, 2019; Scimago, 2017.

3

Ministry of Health and Medical Education, 2019.

4

Masaeli, 2018a.

5

Masaeli, 2019.

6

Food and Drug Organization, 2017; Food and Drug Organization, 2018;
Pirsalehi, 2019.

7

Pirsalehi, 2019.

8

The five-year development plan (FYDP), revised in five-year intervals, isthe main national policy to steer Iran’s economic development, involving
all national sectors, including the health sector.

9

Ministry of Health and Medical Education, 2019.

10

Institute for Trade Studies and Research, 2017a; Institute for Trade
Studies and Research, 2017b.

11

Institute for Trade Studies and Research, 2017a; Institute for Trade
Studies and Research, 2017b.

12

Jahanpoor, 2019.

13

Negotiation for ascension to the WTO is in progress; Iran may eventually
have to let go its support for import substitution by wall of tariffs according
to page 49 of UNCTAD, 2016.

14

UNCTAD, 2016.

15

Information on KBFs and their fields of activity can be found athttps://pub.daneshbonyan.ir/ (Accessed in March 2019; In Persian)

16

More information about ILE procedures and statistics can be found at
http://iranlabexpo.ir/index.php?lang=2

17

Iran Vice-Presidency for Science and Technology, 2019.

18

More information can be found at http://hoa-ir.com/en/Page/2677/
About-Us.html

19

Vatanpour, 2017.

20

Ministry of Science, Research and Technology, 2018. By February 2019,
195 incubators and 44 S&T parks are under the supervision of the
Ministry of Science, Research and Technology.

21

More information about CinnaGen and PersisGen can be found at
http://persisgen.com/en and https://www.cinnagen.com/

22

More information on IBT approach and initiatives can be found at
http://en.biotechfund.ir/

23

Scimago, 2017.

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References:
Food and Drug Organization. (2017). The annual pharmaceutical statistics ofIran in 2017, Data extracted from the annual pharmaceutical statistics
of Iran in 2017, released by the Food and Drug Organization of I.R
Iran. Retrieved from: http://fda.gov.ir/item/4423; http://www.fda.gov.ir/
item/3814——— . (2018). The annual pharmaceutical statistics of Iran in 2018, Data
extracted from the annual pharmaceutical statistics of Iran in 2018,
released by the Food and Drug Organization of I.R Iran. Retrieved from:http://aphm.ir/images/pdf/xls/ad8.xlsx
Institute for Trade Studies and Research. (2017a). Integration of Iran biopharmaceutical sector Industrial, trade and technology policy, research
project funded by Iran Vice-Presidency for Science and Technology[in Persian].
——— . (2017b). Integration of Iran medical equipment sector Industrial, trade
and technology policy, research project funded by Iran Vice-Presidency
for Science and Technology [in Persian].
Iran Vice-Presidency for Science and Technology. (2019). Report on the performance Iran Lab Expo, limited publication [in Persian]. Retrieved from:http://iranlabexpo.ir/index.php?lang=2
Jahanpoor, K. (2019). 23.9 percent increase in the contribution of local madedrugs in Iran, speaker of Food and Drug Organization statement in
February 2019 [in Persian]. Retrieved from http://iraneconomist.com/fa/
news/280058
Masaeli, R. (2018a). Provision of 30 percent value of the medical equipment
market by domestic firms, head of the National Medical Device Directorate statement in June 2018 [in Persian]. Retrieved from http://imed.ir/
Default.aspx?PageName=News&ID=2961——— . (2018b). Setting the goal of tenfold increase in medical equipment
exports, head of the National Medical Device Directorate statement inAugust 2018 [in Persian]. Retrieved from http://imed.ir/Default.aspx?PageName=News&ID=3179——— . (2019). Challenges of medical equipment export in 2019, head of the
National Medical Device Directorate statement in January 2019 [inPersian]. Retrieved from http://www.mehrnews.com/news/4517136
Mazzucato, M. (2015). The entrepreneurial state: Debunking public vs. private
sector myths. United States: Public Affairs publication.
Ministry of Health and Medical Education. (2019). Report of Ministry of Healthand Medical Education key actions from 1979 to 2019 (forty years after
the Islamic Revolution) [in Persian]. Retrieved from http://www.behdasht.
gov.ir/uploads/gozaresh_288616.pdf
Ministry of Science, Research and Technology. (2018). List of Iran’s S&T parks,
incubator and innovation center [in Persian]. Retrieved from https://techno.msrt.ir/fa/page/640/
Pirsaleh, M. (2019). 67 percent of active pharmaceutical ingredient usedin Iran is produced locally, head of Food and Drug Organization in
January 2019 [in Persian]. Retrieved from https://www.asriran.com/fa/
news/652084/67
Scimago. (2017). Scimago Journal & Country Rank database. Retrieved fromhttps://www.scimagojr.com/countryrank.php
StatNano. (2019). ISI indexed nano-articles. Retrieved from https://statnano.
com/report/s29
UNCTAD. (2016). Science, Technology and Innovation Policy Review of theIslamic Republic of Iran, Published in December 2016 Retrieved fromhttp://unctad.org/en/pages/PublicationWebflyer.aspx?publicationid=1679.
United Nations Development Programme. (2018). Human Development
Reports. Human Development Indicators for Iran (Islamic Republic of).
Retrieved from http://hdr.undp.org/en/countries/profiles/IRN.
Vatanpour, H. (2017). Health Sciences Technology Development in IRAN
during last decade. Iranian Journal of Pharmaceutical Research, 16(4),
1272.

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CH AP T E R 17

SOCIAL AND ECONOMICASPECTS OF HEALTH AND
MEDICAL INNOVATION IN
THAILAND
Krithpaka Boomfueng and Chaiyatorn Limapornvanich, National Innovation Agency (NIA), Thailand
Thanaphan Suksaard, Ministry of Public Health, Thailand

Innovation has long been recognized as a driving engine of
economic growth. After the global financial crisis, Thailand
turned its attention to an innovation-driven growth strategy,
instead of an export-oriented growth strategy—and recently
became an upper-middle-income economy. According to theTenth National Economic and Social Development Plan, which
covers the period from 2007 to 2011, the strategy was deployednationwide with a focus on economic development andcompetitiveness. Since adopting this strategy, the concept ofinnovation has evolved and been broadly adopted as a means
toward sustainable development. Presently the focus has been
expanded in the Twelfth Plan, covering the period from 2017
to 2021, to include all aspects of development. Health andmedical innovation are playing a crucial role.
As the country is experiencing transitions in demography
and epidemiology—with an increase in life expectancy and adecrease in fertility—the health and medical system has had
profound impacts on economic, social, and health service
development. At a glance, Thailand’s life expectancy has
increased steadily, from 71.1 years in 2000 to 75.5 years in 2016.1
Also, the rate of fertility and mortality is declining. In 2010, it wasreported that around 11.9% of the Thai population, or 68 million
people, are aging over 60 years; this is expected to reach 25%
in 2030.2 Moreover, the population—which was predominantly
rural and poor—has recently changed to the one that is almost
equally balanced between urban and rural populations. Whileurbanization offers many opportunities, including potential
access to better health service, it also introduces healthchallenges relating to the environment, non-communicablediseases (NCDs), unhealthy diets, and physical inactivity.
On the other hand, Thai medical services are recognizedglobally as having an outstanding medical foundation, including
premium medical services, qualified healthcare specialists,and various internationally accredited medical facilities. With
over 50,573 well-trained physicians and more than 1,000
public and 300 private hospitals nationwide, a diverse rangeof treatments and world-class facilities are offered.3 Thailand
was ranked first in top destinations for medical tourism, andthe number of foreign patients receiving treatment reached2.35 million people in 2014.4 This is the result of long-term
developments in medical education. Nevertheless, the demandfor doctors, medical personnel, and healthcare service in the
country still cannot be met.
Given these challenges and opportunities, innovation isconsidered to be a means toward sustainable health andmedical transformations. However, a broad range of benefits
and impacts of innovation could be induced in two main
aspects—social and economic. Various forms of innovation havebeen introduced into the health and medical system, ranging
from policy innovation to technological innovation. In order todevelop a comprehensive understanding of how innovation
has affected the reform of the Thai health and medical system,
we will focus on two aspects of innovation—health policies
and the medical industry.

Innovation in health policies
Demographic changes, through an aging population, affected
the rising cost of medical care, the quality of care, and healthsecurity for individuals;5 consequently, the health systemneeded to be reformed. Through government policies, thereforms aimed to shape the context of the health systemin terms of efficiency, effectiveness, quality, safety, andaffordability—which is not only limited to healthcare services but
also extends to processes, systems, policies, and organizational
structures for the purpose of creating new value for patients.

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The health system reform in Thailand has employed the conceptof a Participatory Public Policy Process (PPPP). Three main
sectors were identified to participate in the reform to promotehealthy public policy:6
1. Knowledge or technical sectors, which includes scholars,
professionals, and policy researchers in all relevant areas ofboth public and private institutes;
2. Social sectors that open opportunities for everyone,from individuals, groups, civil society organizations, mass
media, non-governmental organizations, and private sector
agencies; and3. Political and civil service sectors, which includes stateagencies, political organizations, and local governmentorganizations.
The fundamentals of health reform have started with reframing
the health system from “ill-health oriented” to “good-healthoriented”.7 The concepts of health promotion and healthprevention have become part of the reforms to the Thai healthsystem.8 Also, healthcare financing must be developed toensure accessibility to adequate and quality healthcare forall. All of these concepts lead to innovation in Thailand healthpolicies such as financing for health promotion, universal healthcoverage providing all Thai people access to health services,and participation from related sectors to develop public healthpolicies in the National Health Assembly.

Financing for health promotion—
ThaiHealthIn the last few decades, Thailand has been facing the double
burden of communicable and non-communicable diseases.
NCDs—such as cardiovascular disease, cancer, diabetes, andchronic respiratory diseases—have emerged as a leading
cause of disease burden. Fundamentally, these diseases sharesimilar risk factors to tobacco use, alcohol consumption, dietaryimbalances, and insufficient physical activity. Although healthpromotion and disease prevention have been recognized
as cost-effective investments that can improve lifestyles andsociety, the majority of health expenditures from the Ministry of
Public Health focus on curative services. Therefore, the concept
of innovative and sustainable funding for health promotion has
been explored and implemented.9
After the long process of national policy development andhealth system reform, Thai parliament enacted the Health
Promotion Foundation Act in 2001. This act established theThai Health Promotion Foundation (ThaiHealth) as a stateagency with annual revenue around US$120 million—derived
from a “sin tax” or excise tax of 2% on tobacco and alcohol.10
ThaiHealth was established to manage the health promotion
fund and to support health promotion activities at both theindividual and organizational level in all areas relevant to healthpromotion, including a healthy society and environment. As
an autonomous agency, ThaiHealth coordinates with partners
in both public and private sectors. ThaiHealth also provides a

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dedicated infrastructure for health promotion, offering several
advantages such as flexibility, financial security, and effective
strategy. ThaiHealth employs a “Tri-Power Model”—which not
only supports direct activities but also supports knowledge
development related to evidence-based action and policy, thesocial movement to raise public awareness and action, and thegoal of fortifying political authority involvement (Figure 17.1).11
Achievement and challenges—The initiation of ThaiHealthis regarded as the most important landmark signifying thestrength of health promotion in Thailand. For example, one of
the campaigns against smoking, conducted during the previous
decade, changed the perception and social norm related tosecondhand smoke. Additionally, there have been several
successful campaigns to promote physical activity and improve
emotional and spiritual health, such as the “Bike for Mom”
project and the campaign to stop drunk-driving. ThaiHealthintroduced an innovative and sustainable financing system for
health promotion. This system provides sustainable financial
resources and also accelerates, supports, and promotes healthpromotion activities.
However, this financing system still has some challenges. As
a new concept, it took time to build up a clear understandingof the concept and its indirect benefits to the public andkey stakeholders. Furthermore, some campaigns for healthpromotion might be against some industries and businesses,
which makes it challenging to secure political support to counterany opposition. To overcome the challenges, ThaiHealth must
develop an understanding of health promotion to the public andkey stakeholders at large, as well as improve the evaluationand effectiveness of health promotion at project, program,and strategic levels.

Universal health coverage for
Thailand’s health security
Thailand has been recognized as a developing country thathas been successful in implementing universal health coverage(UHC). In 2002, the National Health Security Act establishedthe National Health Security Office (NHSO). Universal healthcoverage contributes to the health security of the Thai
population, allowing access to necessary health services
without catastrophic healthcare expenditures—particularly forpoor people or vulnerable groups. In other words, the UHC
provides public health security to the Thai people who do
not have coverage from any health insurance scheme. As
a result, more than 90% of the Thai population is presently
covered by three public health insurance schemes—the Civil
Servant Medical Benefit Scheme (CSMBS) for civil servants
and their dependents, the Social Health Insurance Scheme(SHI) for private sector employees, and UHC for the rest of the
population.
Achievement and challenges—Apart from improving healthsecurity for Thai people, the UHC also contributes to the qualityof healthcare services because of the scale of the program.
The purchaser, in particular the NHSO, can negotiate with theservice providers on both price and quality of care. StrategicFIGURE 17.1

“Tri-Power Model” of ThaiHealth
Policy and system

ADVOCACYFOR
POLICY ANDSYSTEM
CHANGE

THAIHEALTHRESEARCH &EVIDENCE

PUBLIC
AWARENESS

Knowledge

Social mobilization

Source: Adapted from Wasi, 2000 and Sopitarchasak et al., 2017.

FIGURE 17.2

Timeline of innovation in health policies

HealthPromotion
Foundation
Act.
B.E. 2544

2001

National
HealthSecurityAct.
B.E. 2545

2002

National Health
Security Oﬃce
Thai Health
Promotion
Foundation

Universal
HealthCoverage

National
HealthAct.
B.E. 2550

Statute of
National
Health System
B.E.2552

2007

2008

National
HealthCommission
Oﬃce

1st National
HealthAssembly

2009

Source: Adapted from Rajan et al., 2017.

Chapter 17

197

purchasing by NHSO resulted in improved and equitable
access to certain high cost interventions, such as open-heart
surgery, renal replacement therapy, and antiretroviral therapy.
Improvement in the quality of hospital care is indicated by anincrease in the number of hospitals that meet the standard
requirements for hospital accreditation and a reduction in
hospital standardized mortality ratio. However, there area couple of future challenges for the UHC, for example,
harmonizing the three public health insurance schemes andthe equitable distribution of financial and human resources.12
To overcome these challenges, policy recommendations
have been suggested for future development. For example,
on the issue of harmonizing the three public health insurance
schemes, the government needs to streamline operations bystandardizing common features—for example, the benefits
package, the information system, and the payment method.
At the same time, inequities in benefits and level of expenditureneed to be reduced and inefficiencies across the schemes
addressed.13 Working towards achieving a more equitable
distribution of human resources across the country must beplanned and developed—and include capacity developmentin the health workforce.

Sectors driving public health policies
in the National Health Assembly
The National Health Assembly (NHA) is a platform for public
policy development. The platform encourages participation of
public and key stakeholders throughout the process of healthpolicy development—including agenda setting, resolution
drafting, stakeholder and public consultation, resolution
adoption, implementation, monitoring, and evaluation. It is ayear-round policy process, not just a onetime event, to assurethat public health policies will be developed sustainably.
In Thailand, there are three types of health assemblies:
area-based health assemblies, issue-based health assemblies,
and the National Health Assembly (NHA). The health assemblies
emphasize participatory democracy and promote active
multisectoral involvement in the formulation of public healthpolicies. At the provincial and regional level, area-based healthassemblies identify local health issues and concerns and raisethem to the national level. Issue-based health assemblies
convene on topics based on specific health issues andconcerns. All concerns and comments from area-based healthassemblies and issue-based health assemblies are collected
and drafted into NHA resolutions. The NHA encourages
the engagement of representatives from the government,
academia, and local communities, in order to finalize and bring
the resolution to actions.
Achievement and challenges—The NHA has an impact
on public policymaking in Thailand. The consensus-based
resolutions of the NHA are submitted to the National HealthCommission and further to the Cabinet of Thailand. Presently,
81 resolutions from 11 assemblies have been implemented,
including resolutions on NCDs, such as childhood obesity
management; national strategies on antibacterial resistance;
health promotion, such as illegal advertisement of drugs and

198

The Global Innovation Index 2019health products; daily cycling; waste management; and housing.
Moreover, six issues have been generated by the issue-based
health assemblies: development of the national healthinformation system, a bill on reproductive health protection,
traditional medicine strategy, nanotechnology strategy for safety
and ethics, health workforce educational reform, and a national
strategic plan on health promotion at the end of life.14
With regard to the achievements above, there are a couple ofchallenges that need to be explored and addressed. Although
the NHA is open for all sectors to participate, it is limited toactive groups, rather than the whole society. In this sense,
the question of whether the voices of participants—groups or
networks—adequately reflect the real needs of the country has
been raised. In addition, due to the nature of the resolutions
implemented—which are voluntary rather than compulsory—it isdifficult to evaluate the outcome and impact of the resolutions.
In conclusion, the reform of Thailand’s health system has beensignificantly impacted by innovation in health policies. The mostinfluential aspect of reform has been the public participation
concept—where civil society organizations have been
participating in health issues and learning about resolutions andinitiatives implemented. The Health Promotion Foundation Act,
enacted in 2001, led to establishing the Thai Health Promotion
Foundation. This extended the concept of health beyond thephysical to also include mental, social, and spiritual aspectsof health. Additionally, innovation health financing has been
introduced to build sustainable funding to support healthpromotion. In 2002, the National Health Security Act was
legislated and universal health coverage (UHC) implemented,
which contributed to health security and access to necessary
services for the Thai population—particularly poor people andvulnerable groups. Moreover, one year after the National Health
Act was legislated in 2007, formal “space” for the public toparticipate was introduced. The National Health Act conceived
the National Health Commission Office (NHCO) with a mandate
to convene the National Health Assembly, which is a healthpolicy platform for the public—from the grass roots to civilsociety, academic institutions, departments, and ministries—toengage in the same place (Figure 17.2).15

Innovation in Thailand’s medical
industry
Thailand has given the medical industry top priority as one ofthe driving engines for economic development. A range ofpolicies have been deployed to utilize the existing medical
foundation to its highest potential, strengthen competitivenessof the industry, and improve the quality of life for Thai citizens.
Innovation is considered as a means towards these goals.
Support and incentives are provided to create opportunities
for continual success in related fields, including medical
technologies, digitalization in healthcare services, andinvestment incentives.

Medical technologies
The medical device sector in Thailand is considered a high-value
industry. Despite unfavorable economic conditions, thesector gains advantages from a national medical hub policythat encourages foreigners to travel to Thailand for medical
purposes. Since 2003, this medical hub policy has helped tosupport continuous growth in medical tourism. The number offoreign patients arriving in Thailand has soared to 2.5 million
patients annually—and is continuing to grow.16 Additionally, theThai medical device industry has expanded continuously—both
domestically and internationally. Although there are a wide
variety of medical devices being manufactured domestically,
concentration is on relatively low-end product categories, while
a substantial number of high-end and sophisticated medical
devices are being imported.17 To upgrade the local production of
medical devices, long-term and systematic development of local
capabilities, knowledge, and innovation are required.
To accelerate the growth of the sector, the Thai government
provides investment and support through research funding,public-private partnerships, and granting for prototype
development. As a result, the technological progress inacademic research creates tremendous opportunities for
new investment in the medical device sector, such as medical
diagnosis kits, medical robotics, and implanted medical devices.
The following are examples of how the support could be used
for leveraging the sector’s transformation:18• The Biomedical Technology Research Unit of the Facultyof Associated Medical Sciences, Chiang Mai Universities,
developed a more convenient, less expensive, and highly
accurate test kit for alpha thalassemia carrier screening.
The device has been licensed to a private company forcommercialization.
• The Thailand Center of Excellence for Life Sciences (TCELS)
has established the Center for Advanced Medical Robotics,
to broaden Thailand’s research base through advanced
medical robotics projects. With an extensive networkof researchers, the sector is able to develop their own
technological capabilities. Specialized medical robots havebeen prototyped and commercialized, including Dindow,
an elderly care robot by CT Asia Robotics, Co., Ltd., andSensible Tab, an arm rehabilitation robot by TMGO Co., Ltd.

of digital transformation and digital literacy. Moreover, accessto medical records and data is important for enabling
effective collaboration between patients and healthcare providers.
With awareness of these challenges, the Ministry of Public
Health (MoPH) deployed the eHealth Strategy in 2017 to serve
as a mechanism for the development of the national healthsystem. The strategy includes reform of digital technology
operations, innovation in medical product manufacturing,and innovation in health services. However, this strategy is along-term development plan that needs to be coordinated withThailand’s digital landscape and digital development plan.
The case of Bangkok Metropolitan Administration (BMA) highlights
the impact of digitalization on healthcare service. BMA is using
technology to enable the elderly to have more convenient
access to healthcare. Similar to many other cities across theregion, Bangkok is facing an increasing number of elderly
people and a declining birth rate; among Bangkok’s registered
10 million people, around 16% are over 60 years old.
The growing elderly population is increasing the burden on
the city’s working population, as people must juggle full-timejobs with caring for their elderly relatives. In addition, Bangkok
is a large and crowded city with traffic conditions that makehospital visits inconvenient.
One solution is to bring care to the homes of the elderly. The
Home Ward Referral Center, a new BMA unit, has been set up inorder to provide home care for the elderly, improve the utilizationof digital technology in public hospitals, and improve theaccessibility of healthcare services to patients with difficulties
in mobilization. Utilization of technologies is at the center ofthis innovative healthcare service, as sharing patients’ medical
records and personal data could enhance the capability of thecenter to provide healthcare staff and healthcare volunteers tocheck on elderly and disabled patients. Additionally, the updated
data from the visits can also be shared with public hospitals
so that doctors and nurses can better coordinate care. This
could improve the patient experience, as patients don’t have torepeatedly provide the same information to doctors—whether athome visits or hospitals. The BMA has also launched a pilot to
introduce electronic patient records in 10 public hospitals. Thisis a crucial platform that is required for the city’s public healthsystem to use more advanced technologies, like analytics andartificial intelligence, in the future.
Investment incentives• Chulalongkorn University and TCELS have completed thedevelopment of a unipolar modular hip prosthesis, which ismore compatible with the anatomy of Asians, and they havesecured funding to undergo standard testing in accordancewith ISO 7206, ASTM 2009, ASTM 1875 and ISO 10993.
Digitalization in healthcare services
There are great challenges and opportunities for digital technologies
in the healthcare system. On the one hand, digital technologies
will improve equality and convenience of Thai people in getting
healthcare services. On the other hand, adoption of digitaltechnologies to the healthcare system, in particular at a national
level, is very challenging for the country—for example, in terms

As government support of knowledge and innovation increases
the potential growth of the sector, it seems that foreign direct
investment in manufacturing facilities, global supply chain,and knowledge is required to strengthen linkages to the global
market. To encourage foreign investment and business
partnerships, the Board of Investment (BOI) offers various typesof investment incentives, including import duty exemption,
tax breaks, and land ownership rights to both foreign andThai investors seeking to manufacture medical equipment inThailand. On top of that, the manufacture of medical equipment
receives the maximum 8-year corporate income tax exemption,
regardless of location.19

Chapter 17

199

Alongside investment incentives, several types of support arealso provided by other government agencies to encourage
collaboration in research and development (R&D) of new
medical technologies, medical products, and services. Agencies
include the:• National Science and Technology Development Agency(NSTDA), a leading public research institute which provides
channels of communication between Thai research
institutions and the private sector;• Thailand Science Park (TSP), a technology and innovation
hub that includes R&D and innovation development for
private sectors, providing services ranging from technology
transfer to financial assistance and business incubation; and• National Innovation Agency (NIA), a granting agency forinnovation development, which supports up to 75% funding
for prototype or pilot scale projects, and which also
provides interest-free loans for up to 3 years to assist in
the commercial operations of innovation projects.
In summary, Thailand’s medical industry has responded to theeconomic development policy to strengthen the competitivenessof Thailand in this high-value sector. As the industry advances
through knowledge and technologies, bridging the supply-side
knowledge and the demand-side market becomes very
important. Supports and incentives also need to be in place
to facilitate the flow of technical knowledge from research
institutes to innovative companies—and to encourage
investments and partnerships. Digitalization is a crucial enabling
tool for the effective collaboration between stakeholders andpartners. Its deployment at the national level would significantly
enhance the transformation of healthcare services at large.
To elevate the medical industry, the government plays acrucial role in boosting knowledge creation and stimulating
collaboration between supply-side and demand-side partners,
through the provision of supports and incentives.

Conclusion and policy
recommendations
With regard to the two different aspects of health and medical
innovation in Thailand, which are health policies and the
medical industry, it is noticeable that innovation has a crucialrole in health and medical transformations of the country.
The health and medical system serve the country—as a profoundpublic service for society and a growth engine for the economy.
Innovation, therefore, requires integration of broad andcomprehensive viewpoints, especially from policymakers, civilsociety, industries, entrepreneurs, and technology providers.
On the one hand, innovation at the policy level is necessary for
preparing the country to deal with structural reforms and futurechanges. In essence, it shifts the paradigm of thought, which
greatly affects society. On the other hand, the developmentof health- and medical-related industries could strengthen
Thailand’s competitiveness and bring opportunities for economic
growth. The support of the government makes Thailand fertile
ground for medical industry investment. Yet, technological andknowledge infrastructure—both medical and digital—require

200

The Global Innovation Index 2019

investment. The health and medical system is driven byknowledge-intensive activities and reliable services.
Contextualization and inclusive engagement are imperative tothe success of both upstream and downstream development.

Notes:
1

World Health Organization, 2018.

2

Tejativaddhana et al., 2018.

3

Tejativaddhana et al., 2018.

4

Thailand Board of Investment, 2019.

5

Wasi, 2000; Bureau of Policy and Strategy, 2011.

6

Wasi, 2000; Bureau of Policy and Strategy, 2011.

7

Adulyanon, 2012.

8

Wasi, 2000; Bureau of Policy and Strategy, 2011.

9

Damrongplasit and Melnick, 2009.

10

ThaiHealth.

11

Adulyanon, 2012.

12

Evans et al., 2012.

13

Evans et al., 2012.

14

Rajan et al., 2017.

15

Rajan et al., 2017.

16

Hanvoravongchai, 2013.

17

Tunpaiboon, 2018.

18

Thailand Board of Investment, 2019.

19

Thailand Board of Investment, 2019.

References:
Adulyanon, S. (2012). Funding health promotion and disease prevention
programmes: an innovative financing experience from Thailand. WHO
South-East Asia Journal of Public Health, 1(2), 201.
Bureau of Policy and Strategy. (2011). Thailand Health Profile Report 20082010. Ministry of Public Health.
Damrongplasit, K., & Melnick, G. A. (2009). Early results from Thailand’s 30
Baht. Health Reform: something to smile about. Health Affairs, 28(3),w457-w466.
Evans, T. G. et. al. (2012). Thailand’s universal coverage scheme: achievements
and challenges. An independent assessment of the first. 10.
Hanvoravongchai, P. (2013). Health financing reform in Thailand: toward
universal coverage under fiscal constraints.
Hughes, D., & Leethongdee, S. (2007). Universal coverage in the land ofsmiles: lessons from Thailand’s 30 Baht health reforms. Health Affairs,
26(4), 999-1008.

McCoy, D., & Brikci, N. (2010). Taskforce on innovative international financing
for health systems: what next?. Bulletin of the World Health Organization,
88, 478-480.
Rajan, D. et al. (2017). The triangle that moves the mountain: nine yearsof Thailand’s National Health Assembly. (No. WHO/UHC/HGF/
HGS/2017.1). World Health Organization.
Rasanathan, K., Posayanonda, T., Birmingham, M. et al. (2012). Innovation andparticipation for healthy public policy: the first National Health Assemblyin Thailand. Health Expectations, 15(1), 87-96.
Silva, H. P., Lehoux, P., Miller, F. A. et al. (2018). Introducing responsible
innovation in health: a policy-oriented framework. Health researchpolicy and systems, 16(1), 90.
Sopitachasak, S., Adulyanon, S., & Lorthong, L. (2015). Thai Health Promotion
Foundation: innovative enabler for health promotion. World Health
Popul, 16(1), 62-71.
Tejativaddhana, P., Briggs, D., Singhadej, O., & Hinoguin, R. (2018). Developing
primary health care in Thailand: Innovation in the use of socio-economic
determinants, Sustainable Development Goals and the district healthstrategy. Public Administration and Policy, 21(1), 36-49.
Thailand Board of Investment. (2019). Thailand’s Medical Hub. Retrieved fromhttps://www.boi.go.th/index.php?page=business_opportunities_detail&topic_id=117526
Tunpaiboon, N. (2018). Thailand Industry Outlook 2018-20 – Medical Devices.
Wasi, P. (2000). Triangle that moves the mountain and health systems reformmovement in Thailand. Health Systems Research Institute (HSRI).
Watabe, A., Wongwatanakul, W., Thamarangsi, T. et al. (2016). Analysis ofhealth promotion and prevention financing mechanisms in Thailand.
Health promotion international, 32(4), 702-710.
World Health Organization (WHO). (2016). Tobacco taxation and innovative
health-care financing. New Delhi, India: World Health Organization.
World Health Organization (WHO). (2018). 2018 Health SDG Profile: Thailand.
Yamwong, P. (2006). The Medical Education System in Thailand. Asia Pacific
Biotech News, 10(15), 815-817.

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202

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APPENDICES

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204

The Global Innovation Index 2019

A P P E NDIX I

THE GLOBAL INNOVATION INDEX (GII)CONCEPTUAL FRAMEWORKThe rationale for the Global
Innovation Index
The Global Innovation Index (GII) project was launched byProfessor Dutta in 2007 during his tenure at INSEAD. The goal
was to find and determine metrics and methods that could
better capture the richness of innovation in society, going
beyond the traditional measures of innovation such as
the number of research articles and the level of research anddevelopment (R&D) expenditures.1
There were several motivations for setting this goal. First,
innovation is important for driving economic progress andcompetitiveness—both for developed and developing economies.
Many governments are putting innovation at the center of their
growth strategies. Second, the definition of innovation has
broadened—it is no longer restricted to R&D laboratories andto published scientific papers. Innovation could be and is moregeneral and horizontal in nature, including social, businessmodel, and technical innovation. Last, but foremost, recognizing
and celebrating innovation in emerging markets is critical for
inspiring people—especially the next generation of entrepreneurs
and innovators.
Now in its 12th edition, the GII helps to create an environment
in which innovation factors are under continual evaluation. It
provides a key tool for decision-makers and a rich database ofdetailed metrics for refining innovation policies.
The GII is not meant to be the ultimate and definitive rankingof economies with respect to innovation. Measuring innovation
outputs and its impact remains difficult, hence great emphasis
is placed on measuring the climate and infrastructure forinnovation and on assessing related outcomes.
Although the end results take the shape of several rankings,
the GII is more concerned with improving the “journey” to bettermeasurement, understanding innovation, and in identifying
targeted policies, good practices, and other levers that foster
innovation. The rich data metrics, at index, sub-index, orindicator level, can be used to monitor performance over time
and to benchmark developments against economies within
the same region or income group classification.

Drawing on the expertise of the GII’s Knowledge Partners andits prominent Advisory Board, the GII model is continually
updated to reflect the improved availability of statistics and ourunderstanding of innovation. This year the model continues
to evolve, although its mature state now requires only minor
updates (Appendix IV).

An inclusive perspective on innovation
The GII adopts a broad notion of innovation, originally elaborated
in the Oslo Manual developed by the European Communities
and the Organisation for Economic Co-operation and Development(OECD). In its fourth edition, the Oslo Manual 2018 introduces
a more general definition of innovation:2
An innovation is a new or improved product or process(or combination thereof) that differs significantly from the unit’s
previous products or processes and that has been madeavailable to potential users (product) or brought into useby the unit (process).
This update of the Oslo Manual also introduces a series ofdefinitions associated with innovation in business activities andfor different types of innovation firms.3 In this context, innovationtranslates as improvements made to outcomes in the formof either new goods or services or any combination of these.
While the GII focuses on a more general definition of innovation,
it is important to highlight how these definitions capture theevolution of the way innovation has been perceived andunderstood over the last two decades.4
Economists and policymakers previously focused on R&D-based
technological product innovation, largely produced in-houseand mostly in manufacturing industries. Innovation of this nature
was executed by a highly educated labor force in R&D-intensive
companies. The process leading to such innovation wasconceptualized as closed, internal, and localized. Technologicalbreakthroughs were necessarily “radical” and took place atthe “global knowledge frontier”. This characterization implied
the existence of leading and lagging economies, with low- or
middle-income economies only playing “catch up”.

Appendix I

205Today innovation capability is increasingly seen as the ability
to exploit new technological combinations; it embraces
the notion of incremental innovation and “innovation without
research”. Non-R&D innovative expenditure is an importantcomponent of reaping the rewards of technological innovation.
Interest in understanding how innovation evolves in low- andmiddle-income economies is increasing, along with anawareness that incremental forms of innovation can impact
development. Furthermore, the process of innovation itself
has changed significantly. Investment in innovation-related
activity has consistently intensified at the firm, economy, andglobal levels, adding both new innovation actors from outside
high-income economies and non-profit actors. The structureof knowledge production activity is more complex andgeographically dispersed than ever.
A key challenge is to find metrics that capture innovation as it
actually happens in the world today.5 Direct official measuresthat quantify innovation outputs remain extremely scarce.6
For example, there are no official statistics on the amount ofinnovative activity—defined as the number of new products,
processes, or other innovations—for any given innovation actor,
let alone for any given country (GII 2013, Chapter 1, Annex 1,
Box 1). Most measurements also struggle to appropriately
capture the innovation outputs of a wider spectrum of innovation
actors, such as the services sector or public entities. This
includes innovation surveys, which have contributed greatly tothe measurement of innovation activities, but that fail to provide
a good and reliable sense of cross-economy innovation output
performance, and that are often not applicable to developing
economies where innovation is often informal.7
The GII aims to move beyond the mere measurement of such
simple innovation metrics. To do so will require the integrationof new variables, with a trade-off between the quality of thevariable on the one hand and achieving good economy coverageon the other. A key priority is to improve the measurement ofinnovation in the field of knowledge-intensive services, user andpublic sector innovation, including policy support to innovative
entrepreneurship and venture capital, innovation linkages(in particular international ones) and innovation outputs andimpacts more generally.8
The timeliest possible indicators are used for the GII: 37.3% ofdata obtained are from 2018, 33.3% are from 2017, 9.3% arefrom 2016, 4.8% from 2015, and the small remainder of 5.3%
from earlier years.9

The GII conceptual framework
The GII is an evolving project that builds on its previous editions,while incorporating newly available data, and is inspired by thelatest research on the measurement of innovation. This year the
GII model includes 129 countries/economies, which represent
91.8% of the world’s population and 96.8% of the world’s GDP
in purchasing power parity current international dollars. The
GII relies on two sub-indices—the Innovation Input Sub-Index
and the Innovation Output Sub-Index—each built around pillars.
Three measures are calculated (Figure A-I.1):10

206

The Global Innovation Index 2019

Innovation Input Sub-Index: Five input pillars capture elementsof the national economy that enable innovative activities.
Innovation Output Sub-Index: Innovation outputs are the resultof innovative activities within the economy. Although the Output
Sub-Index includes only two pillars, it has the same weight incalculating the overall GII scores as the Input Sub-Index.
The overall GII score is the average of the Input and Output
Sub-Indices.
Each pillar is divided into three sub-pillars, each of which iscomposed of individual indicators, a total of 80 this year (Figure
A-I.1). The GII pays special attention to presenting a scoreboard
for each economy that includes strengths and weaknesses
and makes the data series accessible (Appendix II); providing
data sources and definitions (Appendix III); and providing detailed
technical notes and adjustments to the GII framework, including
a detailed analysis of the factors influencing year-on-yearchanges (Appendix IV). In addition, since 2011 the GII has
undergone an independent statistical audit performed by the
Joint Research Centre of the European Union (Appendix V).

The Innovation Input Sub-Index
The first sub-index of the GII, the Innovation Input Sub-Index,
has five enabler pillars: Institutions, Human capital and research,
Infrastructure, Market sophistication, and Business sophistication.
Enabler pillars define aspects of the environment conducive toinnovation within an economy.
Pillar 1: Institutions
Nurturing an institutional framework that attracts business andfosters growth by providing good governance and the correct
levels of protection and incentives is essential to innovation.
The Institutions pillar captures the institutional framework ofan economy.
The Political environment sub-pillar includes two indices: the firstis the political, legal, operational or security risk index that
replaces the political stability and safety indicator, reflecting
more on the likelihood and severity of political, legal, operationalor security risks impacting business operations; the second
reflects the quality of public and civil services, policy formulation,and implementation.
The Regulatory environment sub-pillar draws on two indicesaimed at capturing perceptions on the ability of the government
to formulate and implement cohesive policies that promote thedevelopment of the private sector and at evaluating the extent
to which the rule of law prevails (in aspects such as contract
enforcement, property rights, the police, and the courts).
The third indicator evaluates the cost of redundancy dismissal
as the sum, in salary weeks, of the cost of advance noticerequirements added to severance payments due when terminatinga redundant worker.

FIGURE A-I.1

Framework of the Global Innovation Index 2019

INSTITUTIONSPolitical environment
Regulatory environment
Business environment

HUMAN CAPITAL AND RESEARCH
Education
Tertiarty education
Research & development (R&D)

INFRASTRUCTURE

Innovation
Input
Sub-Index

ICTs
General infrastructure
Ecological sustainability

MARKET SOPHISTICATION
CreditInvestment
Trade, competition, & market scale

GLOBALINNOVATION
INDEX

BUSINESS SOPHISTICATION
Knowledge workers
Innovation linkages
Knowledge absorption

KNOWLEDGE ANDTECHNOLOGY OUTPUTS
Knowledge creation
Knowledge impact
Knowledge difusion

Innovation
OutputSub-Index

CREATIVE OUTPUTS

Intangible assets
Creative goods and services
Online creativity

Source: Global Innovation Index Database, Cornell, INSEAD, and WIPO, 2019.

Appendix I

207

The Business environment sub-pillar expands on two aspects
that directly affect private entrepreneurial endeavors by using
the World Bank indices on the ease of starting a businessand the ease of resolving insolvency (based on the recovery
rate recorded as the cents on the dollar recouped by creditors
through reorganization, liquidation, or debt enforcement/foreclosure
proceedings).
Pillar 2: Human capital and research
The level and standard of education and research activity in an
economy are prime determinants of the innovation capacity of anation. This pillar tries to gauge the human capital of economies.
The first sub-pillar includes a mix of indicators aimed at capturing
achievements at the elementary and secondary educationlevels. Education expenditure and school life expectancy aregood proxies for coverage. Government funding per pupil,
secondary, gives a sense of the level of priority given tosecondary education by the state (excluding funding fromabroad). The quality of education is measured through theresults to the OECD Programme for International Student
Assessment (PISA), which examines 15-year-old students’performances in reading, mathematics, and science, as well as
the pupil-teacher ratio.
Higher education is crucial for economies to move up the value
chain beyond simple production processes and products.
The sub-pillar on tertiary education aims at capturing coverage(tertiary enrolment); priority is given to the sectors traditionallyassociated with innovation (with a series on the percentageof tertiary graduates in science, engineering, manufacturing, andconstruction); and the inbound and mobility of tertiary students,
which plays a crucial role in the exchange of ideas and skills
necessary for innovation.
The last sub-pillar, on R&D, measures the level and quality of
R&D activities, with indicators on researchers (full-time equivalence),gross expenditure, the R&D expenditures of top global R&D
spenders, and the quality of scientific and research institutions
as measured by the average score of the top three universities
in the QS World University Ranking of 2018. The R&D
expenditures of the top three firms in a given economy looks
at the average expenditure of these three firms that are partof the top 2,500 R&D spenders worldwide. The QS university
rankings indicator gives the average scores of the economy’s
top three universities that belong to the top 700 universities
worldwide. These indicators are not aimed at assessing the
average level of all institutions within an economy.
Pillar 3: Infrastructure
The third pillar includes three sub-pillars: Information andcommunication technologies (ICTs), General infrastructure, andEcological sustainability.
Good and ecologically friendly communication, transport, andenergy infrastructures facilitate the production and exchange ofideas, services, and goods and feed into the innovation system

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The Global Innovation Index 2019

through increased productivity and efficiency, lower transaction
costs, better access to markets, and sustainable growth.
The ICTs sub-pillar includes four indices, each on ICT access,use, online service by governments, and online participationof citizens.
The sub-pillar on general infrastructure includes the average ofelectricity output in GWh per capita; a composite indicator on
logistics performance; and gross capital formation, which
consists of outlays on additions to the fixed assets and net
inventories of the economy, including land improvements(fences, ditches, drains); plant, machinery, and equipment
purchases; and the construction of roads, railways, and the like,including schools, offices, hospitals, private residential dwellings,
and commercial and industrial buildings.
The sub-pillar on ecological sustainability includes three indicators
GDP per unit of energy use (a measure of efficiency in theuse of energy), the Environmental Performance Index of
Yale and Columbia Universities, and the number of certificatesof conformity with standard ISO 14001 on environmental
management systems issued.
Pillar 4: Market sophistication
The availability of credit and an environment that supports
investment, access to the international market, competition,and market scale are all critical for businesses to prosper
and for innovation to occur. The Market sophistication pillar
has three sub-pillars structured around market conditions
and the total level of transactions.
The Credit sub-pillar includes a measure on the ease of getting
credit aimed at measuring the degree to which collateraland bankruptcy laws facilitate lending by protecting the rights
of borrowers and lenders, as well as the rules and practices
affecting the coverage, scope, and accessibility of credit
information. Transactions are given by the total value of domestic
credit and, to make the model more applicable to emerging
markets, by the gross loan portfolio of microfinance institutions.
The Investment sub-pillar includes the ease of protecting
minority investors index as well as two indicators on the levelof transactions. The Investment sub-pillar includes the ease ofprotecting minority investors index as well as two indicators on
the level of transactions. These two indicators look at whether
market size is matched by market dynamism and provide a hard
data metric on venture capital deals.
The last sub-pillar tackles trade, competition, and market scale.
The market conditions for trade are given in the first indicatormeasuring the average tariff rate weighted by import shares.
The second indicator is a survey question that reflects theintensity of competition in local markets. Efforts made at finding
hard data on competition remain unsuccessful so far. Domestic
market scale, as measured by an economy’s GDP, wasincorporated in 2016, so the last sub-pillar takes into consideration
the impact that the size of an economy has on its capacity
to introduce and test innovations in the marketplace.

Pillar 5: Business sophistication
The last enabler pillar tries to capture the level of businesssophistication to assess how conducive firms are to innovation
activity. The Human capital and research pillar (pillar 2) made thecase that the accumulation of human capital through education,
particularly higher education and the prioritization of R&D
activities, is an indispensable condition for innovation to occur.
That logic is taken one step further here with the assertion
that businesses foster their productivity, competitiveness,and innovation potential with the employment of highly qualified
professionals and technicians.
The first sub-pillar includes four quantitative indicators on
knowledge workers: employment in knowledge-intensive
services; the availability of formal training at the firm level; R&D
performed by business enterprise (GERD) as a percentage ofGDP (i.e., GERD over GDP); and the percentage of total grossexpenditure of R&D that is financed by business enterprise.
In addition, the sub-pillar includes an indicator related to thepercentage of females employed with advanced degrees.
This indicator, in addition to providing a glimpse into the genderlabor distributions of nations, offers more information about thedegree of sophistication of the local human capital currently
employed.
Innovation linkages and public/private/academic partnerships
are essential to innovation. In emerging markets, pockets ofwealth have developed around industrial or technologicalclusters and networks, in sharp contrast to the poverty thatmay prevail in the rest of the territory. The Innovation linkages
sub-pillar draws on both qualitative and quantitative data
regarding business/university collaboration on R&D, theprevalence of well-developed and deep clusters, the level ofgross R&D expenditure financed by abroad, and the numberof deals on joint ventures and strategic alliances. In addition,
the total number of Patent Cooperation Treaty (PCT) andnational office published patent family applications filed byresidents in at least two offices proxies for international linkages.
The GII team has been evaluating various hard data-based
indicators to measure innovation linkages in an economy.
Measuring innovation linkages adequately remains challenging,
if not to say, impossible based on existing innovation metrics.
In broad terms, pillar 4 on Market sophistication makes thecase that well-functioning markets contribute to the innovation
environment through competitive pressure, efficiency gains,and economies of transaction and by allowing supply to meetdemand. Markets that are open to foreign trade and investment
have the additional effect of exposing domestic firms to bestpractices around the globe, which is critical to innovation
through knowledge absorption and diffusion, which are consideredin pillars 5 and 6. The rationale behind sub-pillars 5.3 onKnowledge absorption (an enabler) and 6.3 on Knowledge
diffusion (a result)—two sub-pillars designed to mirror eachother as much as possible—is precisely that together they
will reveal how good economies are at absorbing and diffusing
knowledge.

Sub-pillar 5.3 includes five metrics that are linked to sectors
with high-tech content or are key to innovation: intellectual
property payments as a percentage of total trade (three-year
average); high-tech imports as a percentage of total imports;
imports of communication, computer and information services
as a percentage of total trade; and net inflows of foreign direct
investment (FDI) as a percentage of GDP (three-year average).
To strengthen the sub-pillar, the percentage of research talent
in business was added in 2016 to provide a measurement ofprofessionals engaged in the conception or creation of new
knowledge, products, processes, methods and systems, including
business management.

The Innovation Output Sub-Index
Innovation outputs are the results of innovative activities within
an economy. Although the Output Sub-Index includes only
two pillars, it has the same weight in calculating the overall GII
scores as the Input Sub-Index. There are two output pillars:
Knowledge and technology outputs and Creative outputs.
Pillar 6: Knowledge and technology outputs
This pillar covers all those variables that are traditionally thought
to be the fruits of inventions and/or innovations. The first sub-pillar
refers to the creation of knowledge. It includes five indicatorsthat are the result of inventive and innovative activities: patentapplications filed by residents both at the national patent office
and at the international level through the PCT; utility model
applications filed by residents at the national office; scientificand technical published articles in peer-reviewed journals;
and an economy’s number of articles (H) that have received
at least H citations.
The second sub-pillar, on Knowledge impact, includes statistics
representing the impact of innovation activities at the micro- andmacro-economic level or related proxies: increases in laborproductivity (three-year average), the entry density of new firms,
spending on computer software, the number of certificatesof conformity with standard ISO 9001 on quality management
systems issued, and the measure of high- and medium-high-techindustrial output over total manufactures output.
The third sub-pillar, on Knowledge diffusion, mirrors the Knowledge
absorption sub-pillar of pillar 5, except for indicators 5.3.2(no longer net imports) and 5.3.5 (on research talent). It includes
four statistics all linked to sectors with high-tech content or thatare key to innovation: intellectual property receipts as a percentage
of total trade (three-year average); high-tech net exports asa percentage of total exports; exports of ICT services as apercentage of total trade; and net outflows of FDI as a percentage
of GDP (three-year average).

Appendix I

209

Pillar 7: Creative outputs

or services and that has been introduced on the market. A businessprocess innovation is a new or improved business process for one ormore business functions that differs significantly from the firm’s previous
business processes and that has been brought into use in the firm.

The role of creativity for innovation is still largely underappreciatedin innovation measurement and policy debates. Since its
inception, the GII has always emphasized measuring creativity
as part of its Innovation Output Sub-Index. The last pillar, on
Creative outputs, has three sub-pillars.
The first sub-pillar on intangible assets includes statistics on
trademark applications by residents at the national office;industrial designs included in applications at a regional or
national office; and two survey questions regarding the useof ICTs in business and organizational models—new areas thatare increasingly linked to process innovations in the literature.
The second sub-pillar on Creative goods and services includes
proxies to get at creativity and the creative outputs of an
economy. In 2014, to include broader sectoral coverage,a global entertainment and media output composite was added.
In addition, that same year, the indicator on audio-visual andrelated services exports was renamed Cultural and creative
services exports, and expanded to include information services,
advertising, market research and public opinion polling, andother, personal, cultural and recreational services (as apercentage of total trade). These two indicators complement
the remainder of the sub-pillar, which measures national featurefilms produced in a given economy (per capita count), printing
and other media output (as a percentage of total manufactures
output), and creative goods exports (as a percentage of total
trade), all of which are aimed at providing an overall senseof the international reach of creative activities in an economy.
The third sub-pillar on Online creativity includes four indicators:
generic and economy/country-code top level domains, average
yearly edits to Wikipedia, all scaled by population aged 15
through 69 years old and mobile app creation, which is scaled
by GDP (bn PPP US$). The indicator on mobile app creation was
improved this year to capture more precisely the downloads ofapps by origin of the headquarters of the developer/firm. This
improvement aims to offer more insight into how innovation,
production and trade of digitized creative products and services
are evolving in an innovation-based economy.

The innovation status of a firm is defined based on its engagement ininnovation activities and its introduction of one or more innovations
over the observation period of a data collection exercise. There arethree categories of innovative and innovation-active firms: innovative,
non-innovative, and innovation-active firms.
4OECD, 2010; INSEAD, 2011; and WIPO, 2011.

5

INSEAD, 2011; OECD Scoreboard, 2013; WIPO, 2011

6

INSEAD, 2011; OECD, 2011; WIPO, 2011.

7

Elahi et al, 2013.

8

See OECD Blue Sky Forum on Science and Innovation Indicators.
http://www.oecd.org/innovation/blue-sky.htm

9

For completeness, 1.6% of data points are from 2014, 1.4% from 2013,
0.4% from 2012, 0.6% from 2011, 0.7% from 2010, 0.3% from 2009
and 2008, and a few exceptions from 2007 (0.01%), 2006 (0.03%),
2003 (0.01%), and 2002 (0.01%). In addition, the GII is calculated based
on 9,300 data points (compared to 10,320 with complete series),
implying that 9.9% of data points are missing. The Data Tables(Appendix II) include the reference year for each data point and markmissing data as not available (n/a).

10This year the GII introduces an alternative to study of the connection
between innovation inputs and outputs replacing the Efficiency Ratio(see Chapter 1, Figure 1.8 and relevant segment).

References:
Cornell University, INSEAD, and WIPO (World Intellectual Property Organization).
(2013). In S. Dutta and B. Lanvin (Eds.), Global Innovation Index 2013:
The Local Dynamics of Innovation. Geneva, Ithaca, and Fontainebleau:Cornell, INSEAD, and WIPO.
Elahi, S., de Beer, J., Kawooya, D., Oguamanam, C., and Rizk, N. (2013). Knowledge and innovation in Africa: scenarios for the future. Cape Town: Open
A.I.R. Network.
Eurostat and OECD (Organisation for Economic Co-operation and Development).
(2005). Oslo Manual: Guidelines for Collecting and Interpreting
Innovation Data, 3rd edition. Paris: OECD.
INSEAD. (2011). In S. Dutta (Ed.), Global Innovation Index 2011: Accelerating
Growth and Development. Fontainebleau: INSEAD.
OECD (Organisation for Economic Co-operation and Development). (2010).
The OECD Innovation Strategy: Getting a Head Start on Tomorrow.
Paris: OECD.
——— . (2011). OECD Science, Technology and Industry Scoreboard 2011.
Paris: OECD.

Notes:
1

For a detailed introduction to the Global Innovation Index, see theGII 2011.

2

Eurostat and OECD, 2018.

3

The manual uses the term “innovation activities” to refer to processes
while the term “innovation” is limited to outcomes. Business innovation
is defined as a new or improved product or business process (orcombination thereof) that differs significantly from the firm's previous
products or business processes and that has been introduced on themarket or brought into use by the firm. Business processes include allcore activities by the firm to produce products as well as all auxiliaryor supporting activities. A product innovation is a new or improved
good or service that differs significantly from the firm’s previous goods

210

The Global Innovation Index 2019——— . (2013). OECD Science, Technology and Industry Scoreboard 2013.
Paris: OECD.
WIPO (World Intellectual Property Organization). (2011). The Changing Natureof Innovation and Intellectual Property. In World Intellectual Property
Report 2011: The Changing Face of Innovation. Geneva: WIPO. Retrieved from https://www.wipo.int/publications/en/details.jsp?id=227

Appendix I

211

212

The Global Innovation Index 2019

A P P E NDIX I I

ECONOMY PROFILES & DATA TABLES

Economy profiles
The following tables provide detailed profiles for each of the
129 economies in the Global Innovation Index 2019. They are
constructed around three sections.

The 2019 GII includes 80 indicators and three types of data.
Composite (or index) indicators are identified with an asterisk ( ),survey questions from the World Economic Forum’s Executive
Opinion Survey are identified with a dagger ( ), and the remaining
indicators are all hard data series.

*†

The top section provides the overall Global Innovation
Index (GII) rank for each economy.
The next section provides eight key metrics to put
the economy into context. They present the Innovation
Output Sub-Index rank,
Innovation Input Sub-Index rank, the
ALBANIA
income group to which the economy
1belongs, its geographical region,
population in millions,2 GDP in billion
PPP US$, and GDP per capita in PPP
US$.3 The last metric provides the GII2018 rank for the economy.
Output rank

Input rank

Income9370

Upper middle

For hard data, the original value is provided (except for indicators
in sub-pillar 7.3, for which the raw data were provided under thecondition that only the normalized scores be published). Normalized
scores in the 0 to 100 range are provided
for everything else (index and survey
data, sub-pillars, pillars, and indices).
83
GII 2019 rank

RegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

EUR

2.9

38.3

13,344.5

83

Score/Value Rank

Because of economies dropping
or entering the GII, and because ofadjustments made to the GII frameworkand other technical factors not directly
related to actual performance (missing
data, updates of data, etc.), the GII
rankings are not directly comparablefrom one year to the next. Please refer
to Appendix IV for details.


INSTITUTIONS………………………………….…….…..
65.8

56

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
56.8

73.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
48.4

63
50
66

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

79
60
85
88

1.3
1.3.1
1.3.2


79.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
91.6

Ease of resolving insolvency*……………………………….….
67.4

35 ● ◆
44
36 ●

61.1
47.9
35.7
20.8


22.7
HUMAN CAPITAL & RESEARCH………………...

88

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


40.1
Education…………………………………………………………..……

4.0
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 9.8
School life expectancy, years……………….…………….…….
15.2
PISA scales in reading, maths, & science…………......…
415.2
Pupil-teacher ratio, secondary…………………………......….
11.6

85
80
98 ○ ◇
48
57
45

2.2
2.2.1
2.2.2
2.2.3


26.7
Tertiary education……………………………………….……..….

57.0
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
19.2

Tertiary inbound mobility, %.......................................
….
1.5

76
51
69
81

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.2 103🕘🕘
Researchers, FTE/mn pop……………………………..…...……
156.1 82🕘🕘Gross expenditure on R&D, % GDP………….………..……
94
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……
43 ○ ◇
QS university ranking, average score top 3*……………
0.0
78 ○ ◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4


46.2
INFRASTRUCTURE……………………………….......

66

Information & communication technologies(ICTs) 63.8

ICT access*………………………………………………………….…….
53.1

ICT use*…………………………….....................................…….
52.8

73.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
75.8

72
82
69
57
59



3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 26.6
2,702.1
Electricity output, kWh/mn pop………………………..…….

Logistics performance*……………………………………………..
27.9

Gross capital formation, % GDP………………………….…….
21.7

94
67
85
78

3.3
3.3.1
3.3.2
3.3.3


48.2
Ecological sustainability………………………………………..

14.1
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
65.5
ISO 14001 environmental certificates/bn PPP$ GDP..  1.9

38 ● ◆
16 ● ◆
36 ● ◆
48

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
30.9
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
35.0
🕘🕘Microfinance gross loans, % GDP……………………….…….
0.5

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 71.7
Ease of protecting minority investors*…………..………….
71.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a[8]
24 ●
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
57.6
Applied tariff rate, weighted avg., %………………………….
0.9
Intensity of local competition†……………………………………
67.4
Domestic market scale, bn PPP$………………………………
38.3

77
7 ●
72
107 ◇


MARKET SOPHISTICATION..………….…………… 53.4 42 ●



89
40
88
31

All scores at the sub-index, pillar,
sub-pillar, and indicator level arenormalized in the 0 to 100 range. The
Innovation Input Sub-Index score is the average of the scores in
the first five pillars, while the Innovation Output Sub-Index is theaverage of the scores in the last two pillars. Each sub-index rank
is computed based on these scores for each economy.

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
24.0 105

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
24.5 97
Knowledge-intensive employment, %...........................
17.4 85
Firms offering formal training, % firms…………………………
23.8 66
GERD performed by business, % GDP…………………..……
n/a n/a🕘🕘
GERD financed by business, %……………………………........
3.3 85Females employed w/advanced degrees, %……………..
9.9 66

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


17.9 108
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
38.8 73◇State of cluster development†.……..………..…………………..
34.3 112🕘🕘
GERD financed by abroad, %.........................................
7.4 53JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 68
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
29.5 85
0.5 66
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
1.5 128 ○ ◇
1.5 42 ●ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
8.4 16 ● ◆Research talent, % in business enterprise……..…………..
n/a n/a◇ 12.2 114
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 2.2 121 ○
0.6 75
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0 99 ○ ◇
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.0 62 ○
Scientific & technical articles/bn PPP$ GDP….…..…..….
3.2 98Citable documents H-index…………………….……….……..….
1.5 122 ○

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


23.3 109
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-1.6 104◇
New businesses/th pop. 15-64………………….…....………….
1.4 62Computer software spending, % GDP…………..……………
0.1 88

ISO 9001 quality certificates/bn PPP$ GDP…………..……
7.8 39 ●
High- & medium-high-tech manufactures, %………………
0.0 99 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


10.9 99
Knowledge diffusion……………………………………..…..…….

0.1 53
Intellectual property receipts, % total trade……………….

0.0 125 ○High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.0 56

FDI net outflows, % GDP…………………………….………….......
0.0 116

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
30.1 107Trademarks by origin/bn PPP$ GDP…………..……….….….
34.2
71
🕘🕘
Industrial designs by origin/bn PPP$ GDP…………..……..
0.4 87

ICTs & business model creation†………………………....…….
51.3 100

ICTs & organizational model creation†……………………....
39.5 113

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
30.7 29 ● ◆Cultural & creative services exports, % total trade…....
1.2 22 ●🕘🕘National feature films/mn pop. 15-69………………….………
3.3 54Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
3.4
5 ● ◆
🕘🕘
Creative goods exports, % total trade………………………..
0.2 89

7.3
7.3.1
7.3.2
7.3.3
7.3.4


6.6
Online creativity………………………………………..……….…….

6.6
Generic top-level domains (TLDs)/th pop. 15-69……….

2.4
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
16.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a


24.4
CREATIVE OUTPUTS…….…………………….…………

74

59
48
63
57
n/a

◇

When data are either not available orout of date, ‘n/a’ is used. (see Appendix
IV for more details). The year used foreach data point is indicated in the Data
Table (Appendix II). To the right of theindicator title, a clock symbol indicatesthat the economy’s data for thatindicator are older than the base year.
(Appendix II)
For further details, see Appendix III,
Sources and Definitions, and Appendix IV,
Adjustments to the Global Innovation Index
Framework, Year-on-Year Comparabilityof Results, and Technical Notes.

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.

Pillars are identified by an icon, sub-pillars by two-digit
numbers, and indicators by three-digit numbers.
For example, indicator: 1.3.1 Ease of starting a businessappears under sub-pillar: 1.3, Business environment, which inturn appears under pillar: 1 Institutions.
Throughout thereport the pillars are identified by their respective icons or
names, and the sub-pillars and indicators by their respective
numbers.

To the far right of each column,
strengths of the economy
in question are indicated by a solid circle (●), weaknesses bya hollow circle ( ). Strengths within the economy’s income groupare indicated with a solid diamond (♦), weaknesses by a hollow
diamond ( ). The only exceptions to the income group strengths
and weaknesses are the top 25 high-income economies,
where these strengths and weaknesses are computed within the
top 25 group.4
All ranks of 1, 2, and 3 are highlighted as strengths, except
in particular instances at the sub-pillar level where strengths
and weaknesses are not signaled when the desired minimum
indicator coverage (DMC) is not met for that sub-pillar.5 For theremaining indicators, strengths and weaknesses of a particular
economy are based on the percentage of economies withscores that fall below its score (i.e., percent ranks).

Appendix II213

• For a given economy, strengths (●) are those scores withpercent ranks greater than the 10th largest percent rank
among the 80 indicators in that economy.
• For that economy, weaknesses ( ) are those scores withpercent ranks lower than the 10th smallest percent rank
among the 80 indicators in that economy.
• Similarly, for a given economy, income group strengths (♦)
are those scores that are above the income group averageplus the standard deviation within the group.
• For an economy, weaknesses ( ) are those scores thatare below the income group average minus the standard
deviation within the group.

The sub-heading text provides a detailed description of eachindicator and includes information on the units of each variable,
the scaling factor (if any), the question asked (for survey questions),
and the most frequent year for which data were available

In addition, economies with a sub-pillar that does not meetthe DMC will show the score for that sub-pillar within brackets.
Those that have more than one sub-pillar that fails to meet the
DMC in the same pillar will also show the ranks of the pillar
where these are located within brackets. For these pillars andsub-pillars, strengths/weaknesses are not signaled.

A total of 57 variables are hard data. A total of 18 variables arecomposite indicators and 5 are survey questions from the World
Economic Forum’s Executive Opinion Survey.

Percent ranks embed more information than ranks and allow
for comparisons of ranks of series with missing data and ties
in ranks. Examples from the Russian Federation and Zambia
illustrate this point:

Explanation of scores

1. Strengths for Russia are all indicators with percent ranks
equal to or above 0.83 (10th largest percent rank for Russia);
weaknesses are all indicators with percent ranks equal to or
below 0.27 (Russia’s 10th smallest percent rank).
2. Russia ranks 22nd out of 129 economies in 6.1.5, Citable
documents H-Index, with a percent rank of 0.84; thisindicator is a strength for Russia.
3. Russia ranks 29th in 1.3.1, Ease of starting a business, but witha percent rank of 0.78, this indicator is not a strength for Russia.
4. The rank of 77 (percent rank of 0.01) in 4.2.3, Venture capitaldeals loans, is a weakness for Russia. By contrast, the similarrank of 78 for Zambia in 1.3.1, Ease of starting a businessis a strength for Zambia (with a percent rank of 0.40, this is
above the cut-off for strengths for Zambia, which is 0.37).
Percent ranks are not reported in the Economy Profiles but they
are presented in the Data Tables (Appendix II).

Data tables
This appendix provides a description of the tables for each of the
80 indicators that make up the Global Innovation Index 2019.
These can be found online at https://globalinnovationindex.org.

Structure
Each table is identified by indicator number, with the first digit
representing the pillar, the second representing the sub-pillar,
and the final digit representing the indicator within that particular
sub-pillar. For example, the table for indicator shows results forindicator 5.1.4, GERD financed by business enterprise, which isthe fourth indicator of sub-pillar 5.1, Knowledge workers, withinpillar 5, Business sophistication.

214

The Global Innovation Index 2019For each indicator for each economy, the most recent value within
the period 2009 to 2018 was used (with a few exceptions, which
are further explained in Appendix III). In instances where this baseyear does not correspond to the most frequent year reported in the
sub-heading, the year of the value appears in parentheses after the
economy name. These instances are noted in the Economy
Profiles after the indicator name with a clock symbol.

The source of each indicator is indicated at the bottom of the page;details for each can be found in Appendix III: Sources and Definitions.

The tables list the economies by their rank order, with the best
performers at the top. After the rank comes the economy name,the original value of the specific indicator for that economy (inthe units specified in the sub-heading), the normalized scorein the 0 to 100 range, and the percentage of economies withscores that fall below the normalized score (i.e., percent ranks).
To the far right of each column, a solid circle indicates that anindicator is a strength for the economy in question, and a hollow
circle indicates that it is a weakness.
• Strengths (●) are all ranks of 1, 2, and 3, as well as all scoreswith percent ranks greater than the 10th highest percent
rank among the 80 indicators in a specific economy.
• Weaknesses ( ) are all scores with percent ranks lower than
the 10th smallest percent rank among the 80 indicators in a
specific economy.
For four hard data series (7.3.1, 7.3.2, 7.3.3, and 7.3.4), the raw
data were provided under the condition that only the normalized
scores be published and therefore the original value equals thenormalized score. For indicators 1.3.1, 1.3.2, 2.3.4, 3.3.2, 4.1.1, and4.2.1, the range for both measures is the same, 0 to 100, andtherefore both measures are also identical.
Details on the computation methodology can be found in
Appendix IV.

Notes:1

Countries/economies are classified according to the World Bank Income
Group (July 2018; see https://datahelpdesk.worldbank.org/knowledgebase/articles/906519-world-bank-country-and-lending-groups) andspecial classification based on the online version of the United Nations
publication Standard Country or Area Codes for Statistical Use, originallypublished as Series M, No. 49, and now commonly referred to as theM49 standard (April 2018; see https://unstats.un.org/unsd/methodology/m49/). These are: EUR = Europe; NAC = Northern America; LCN = Latin
America and the Caribbean; CSA = Central and Southern Asia; SEAO =South East Asia, East Asia, and Oceania; NAWA = Northern Africa andWestern Asia; SSF = Sub-Saharan Africa.

2

Data are from the United Nations, Department of Economic andSocial Affairs, Population Division, World Population Prospects:
The 2017 Revision.

3

Data for GDP and GDP per capita are from the International Monetary
Fund World Economic Outlook 2018 database.

4

As the only non-high-income economy in the top 25, China’s income
group strengths and weaknesses are computed within the non-top
25 group.

5

Data stringency requirements are used in the attribution of strengths
and weaknesses at the sub-pillar level. These levels were revised in
2019. When economies do not meet a data minimum coverage (DMC)
requirement at the sub-pillar level (for sub-pillars with two indicators, theDMC is 2; for three it is 2; for four it is 3; and for five it is 4), they are not
attributed a strength or weakness at the sub-pillar either. Furthermore,
if the economy in question does not meet the DMC requirements at the
sub-pillar level, but it still obtains a ranking higher than or equal to 10 ora ranking equal to or lower than 100 at the sub-pillar level, for caution
this rank is put in brackets. This procedure is to ensure that incomplete
data coverage does not lead to erroneous conclusions about strengths
or weaknesses, or particularly about strong or weak sub-pillar rankings.

Appendix II

215

216

The Global Innovation Index 2019

Index of economy profiles
EconomyPage

EconomyPage

EconomyPage

Albania

218

Greece261

Norway304

Algeria

219

Guatemala

262

Oman

305

Argentina

220

Guinea263

Pakistan

306

Armenia

221

Honduras

264

Panama307

Australia

222

Hong Kong, China

265

Paraguay

308

Austria

223

Hungary

266

Peru

309

Azerbaijan

224

Iceland267

Philippines

310

Bahrain

225

India

268

Poland311

Bangladesh

226

Indonesia

269

Portugal

312

Belarus227

Iran (Islamic Republic of)

270

Qatar

313

Belgium

228

Ireland271

Republic of Korea

314

Benin

229

Israel272

Republic of Moldova

315

Bolivia (Plurinational State of)

230

Italy

273

Romania

316

Bosnia and Herzegovina

231

Jamaica

274

Russian Federation

317

Botswana

232

Japan

275

Rwanda318

Brazil233

Jordan276

Saudi Arabia

319

Brunei Darussalam234

Kazakhstan

277

Senegal320

Bulgaria

235

Kenya

278

Serbia321

Burkina Faso

236

Kuwait279

Singapore

322

Burundi237

Kyrgyzstan

280

Slovakia

323

Cambodia

238

Latvia281

Slovenia

324

Cameroon

239

Lebanon282

South Africa

325

Canada240

Lithuania

283

Spain

326

Chile

241

Luxembourg

284

Sri Lanka

327

China

242

Madagascar

285

Sweden328

Colombia

243

Malawi

286

Switzerland

329

Costa Rica

244

Malaysia

287

Tajikistan

330

Côte d'Ivoire

245

Mali

288

Thailand331

Croatia

246

Malta

289

Togo

332

Cyprus247

Mauritius

290

Trinidad and Tobago

333

Czech Republic

248

Mexico291

Tunisia334

Denmark

249

Mongolia

292

Turkey335

Dominican Republic

250

Montenegro

293

Uganda336

Ecuador251

Morocco294

Ukraine

337

Egypt

252

Mozambique

295

United Arab Emirates

338

El Salvador

253

Namibia296

United Kingdom

339

Estonia

254

Nepal

297

United Republic of Tanzania

340

Ethiopia

255

Netherlands

298

United States of America

341

Finland256

New Zealand

299

Uruguay

342

France257

Nicaragua

300

Viet Nam

343

Georgia

258

Niger

301

Yemen

344

Germany259

Nigeria302

Zambia

345

Ghana

260

North Macedonia

303

Zimbabwe

346

Appendix II

217

ALBANIA

GII 2019 rank

83

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

93

70

Upper middle

EUR

2.9

38.3

13,344.5

83

Score/Value Rank

INSTITUTIONS………………………………….…….…..
65.8

56

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
56.8

73.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 48.4

63
50
66

1.2
1.2.1
1.2.2
1.2.3


61.1
Regulatory environment……………………………..………..

47.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
35.7

20.8
Cost of redundancy dismissal, salary weeks…………..

79
60
85
88

1.3
1.3.1
1.3.2


79.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
91.6

Ease of resolving insolvency*……………………………….…. 67.4

35 ● ◆
44
36 ●


22.7
HUMAN CAPITAL & RESEARCH………………...

88

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


40.1
Education…………………………………………………………..……

4.0
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 9.8
School life expectancy, years……………….…………….……. 15.2

PISA scales in reading, maths, & science…………......…
415.2
Pupil-teacher ratio, secondary…………………………......….
11.6

85
80
98 ○ ◇
48
57
45

2.2
2.2.1
2.2.2
2.2.3


26.7
Tertiary education……………………………………….……..….

57.0
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
19.2

Tertiary inbound mobility, %.......................................….
1.5

76
51
69
81

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.2 103🕘🕘
Researchers, FTE/mn pop……………………………..…...……
156.1 82🕘🕘Gross expenditure on R&D, % GDP………….………..……
94
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……
43 ○ ◇
QS university ranking, average score top 3*……………
0.0
78 ○ ◇
46.2
INFRASTRUCTURE……………………………….......

66

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 63.8

ICT access*………………………………………………………….…….
53.1

ICT use*…………………………….....................................…….
52.8

73.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
75.8

72
82
69
57
59

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
26.6
 …………………..…….
Electricity output, GWh/mn pop……
2,702.1
Logistics performance*…………………………………………….. 27.9
Gross capital formation, % GDP………………………….…….
21.7

94
67
85
78

3.3
3.3.1
3.3.2
3.3.3


48.2
Ecological sustainability………………………………………..

14.1
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
65.5
ISO 14001 environmental certificates/bn PPP$ GDP..
1.9

38 ● ◆
16 ● ◆
36 ● ◆48


MARKET SOPHISTICATION..………….…………… 53.4 42 ●

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
30.9
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...…… 35.0🕘🕘Microfinance gross loans, % GDP……………………….……. 0.5

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 71.7
Ease of protecting minority investors*…………..………….
71.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a[8]
24 ●
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
57.6
Applied tariff rate, weighted avg., %………………………….
0.9
Intensity of local competition†…………………………………… 67.4
Domestic market scale, bn PPP$……………………………… 38.3

77
7 ●
72
107 ◇



89
40
88
31

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
24.0 105

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
24.5 97
Knowledge-intensive employment, %...........................
17.4 85
Firms offering formal training, % firms………………………… 23.8 66

GERD performed by business, % GDP…………………..…… n/a n/a🕘🕘
GERD financed by business, %……………………………........
3.3 85Females employed w/advanced degrees, %……………..
9.9 66

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


17.9 108
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
38.8 73◇State of cluster development†.……..………..…………………..
34.3 112🕘🕘
GERD financed by abroad, %.........................................
7.4 53JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 68
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
29.5 85
0.5 66
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
1.5 128 ○ ◇
1.5 42 ●ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
8.4 16 ● ◆Research talent, % in business enterprise……..………….. n/a n/a 12.2 114
KNOWLEDGE & TECHNOLOGY OUTPUTS....


2.2 121 ○
0.6 75
0.0 99 ○ ◇
0.0 62 ○
3.2 98
1.5 122 ○

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


23.3 109
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-1.6 104◇
New businesses/th pop. 15-64………………….…....………….
1.4 62Computer software spending, % GDP…………..…………… 0.1 88
ISO 9001 quality certificates/bn PPP$ GDP…………..……
7.8 39 ●
High- & medium-high-tech manufactures, %………………
0.0 99 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


10.9 99
Knowledge diffusion……………………………………..…..…….

0.1 53
Intellectual property receipts, % total trade……………….

0.0 125 ○High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.0 56

FDI net outflows, % GDP…………………………….………….......
0.0 116


24.4
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4

74


Intangible assets…………………………………….………………..
30.1 107Trademarks by origin/bn PPP$ GDP…………..……….….….
34.2
71
🕘🕘
Industrial designs by origin/bn PPP$ GDP…………..……..
0.4 87
†
ICTs & business model creation ………………………....……. 51.3 100

ICTs & organizational model creation†……………………....
39.5 113

The Global Innovation Index 2019

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5

Creative goods & services……………………….…….……….. 30.7 29 ● ◆Cultural & creative services exports, % total trade…....
1.2 22 ●🕘🕘National feature films/mn pop. 15-69………………….………
3.3 54Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
3.4
5 ● ◆
🕘🕘
Creative goods exports, % total trade……………………….. 0.2 89

7.3
7.3.1
7.3.2
7.3.3
7.3.4


6.6
Online creativity………………………………………..……….…….

6.6
Generic top-level domains (TLDs)/th pop. 15-69……….

2.4
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
16.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

59
48
63
57
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
218◇ALGERIA

GII 2019 rank

113

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

118

100

Upper middle

NAWA

42.0

660.8

15,439.9110

Score/Value Rank

INSTITUTIONS………………………………….…….…..

51.1 106

Score/Value Rank

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
38.3

Political and operational stability*……………..………….….
50.9
Government effectiveness*…………………………..…………. 32.1

111
121
103

1.2
1.2.1
1.2.2
1.2.3


51.2
Regulatory environment……………………………..………..

9.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
23.5

17.3
Cost of redundancy dismissal, salary weeks…………..

◇
109
126 ○ ◇
116
◇
71

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
63.7
Ease of starting a business*………………………………..……
78.1

Ease of resolving insolvency*……………………………….…. 49.2

88
112
68


27.9
HUMAN CAPITAL & RESEARCH………………...

74

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


37.7
Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
4.3
Government funding/pupil, secondary, % GDP/cap… n/a🕘🕘
School life expectancy, years……………….…………….……. 14.3

PISA scales in reading, maths, & science…………......…
361.7
Pupil-teacher ratio, secondary…………………………......….
n/a

[90]
69
n/a
65
69 ○
n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
40.6
Tertiary enrolment, % gross………………………….….……….
47.7
Graduates in science & engineering, %……………….….
31.1
Tertiary inbound mobility, %.......................................
….
0.6

36 ●
62 ●
9 ●◆
94

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
5.3
Researchers, FTE/mn pop……………………………..…...……
820.8
Gross expenditure on R&D, % GDP………….………..……
0.5

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

78
54 ●
58 ●
43 ○ ◇78 ○ ◇
INFRASTRUCTURE……………………………….......
42.1

81

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 35.3

ICT access*………………………………………………………….…….
53.1

ICT use*…………………………….....................................…….
46.3

21.5
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
20.2

115
◇
83
75
125 ○ ◇
123 ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
54.8
Electricity output, GWh/mn pop………………………..…….
1,748.3
Logistics performance*…………………………………………….. 18.0
Gross capital formation, % GDP………………………….…….
50.6

10 ● ◆
82
107 ◇
2 ●◆

3.3
3.3.1
3.3.2
3.3.3


36.1
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
10.3
Environmental performance*…….………………………………
57.2
ISO 14001 environmental certificates/bn PPP$ GDP..
0.1

74
47 ●
77
123



MARKET SOPHISTICATION..………….…………… 34.1 122


BUSINESS SOPHISTICATION..……….……………
18.1 126 ○ ◇

◇
◇
◇
◇

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
9.8 125 ◇Ease of getting credit*…………………………………..…………..
10.0 126 ○ ◇
Domestic credit to private sector, % GDP…………...……
24.8 107Microfinance gross loans, % GDP……………………….…….
n/a n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 35.0Ease of protecting minority investors*…………..………….
35.0

Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[99]
123
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
57.6
Applied tariff rate, weighted avg., %………………………….
9.4
†Intensity of local competition …………………………………… 55.0
Domestic market scale, bn PPP$……………………………… 660.8

78
110 ◇
121 ◇
34 ●

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
19.0 110Knowledge-intensive employment, %...........................
17.9 81Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..…… 0.0 75

GERD financed by business, %……………………………........ 6.7 77
Females employed w/advanced degrees, %……………..
8.1 79

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


◇
Innovation linkages…………..……………………………………..
13.8 122
◇
University/industry research collaboration †………………..
26.9 117State of cluster development†.……..………..…………………..
40.6 91

GERD financed by abroad, %.........................................
0.0 102 ○ ◇
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 94
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 89

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


◇
Knowledge absorption……………………………………..……..
21.4 117
0.4 73
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.3 53 ●
ICT services imports, % total trade…………..………………...
0.7 91◇
FDI net inflows, % GDP…………………………….………………….
0.5 120◇
Research talent, % in business enterprise……..…………..
0.5 82◇◇

 12.3 113
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 6.0

Patents by origin/bn PPP$ GDP……………….…………..….…
0.2

0.0
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
4.6
Citable documents H-index…………………….……….……..….
8.0

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


24.5 107
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.5 50 ●🕘🕘
New businesses/th pop. 15-64………………….…....………….
0.6 82Computer software spending, % GDP…………..……………
0.0 125 ○ ◇
ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.7 115🕘🕘
High- & medium-high-tech manufactures, %……………… 0.0 94
◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


Knowledge diffusion……………………………………..…..…….
Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………

FDI net outflows, % GDP…………………………….………….......

90
91
87
n/a
83
79

6.4 126 ○ ◇0.0 100◇
0.0 126 ○
0.3 109
0.0 107
14.3 117
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
27.8
Trademarks by origin/bn PPP$ GDP…………..……….….….
12.9
Industrial designs by origin/bn PPP$ GDP…………..……..
1.9

ICTs & business model creation†………………………....…….
46.7

ICTs & organizational model creation †…………………….... 41.3

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.8 102
Online creativity………………………………………..……….…….

0.5 108
Generic top-level domains (TLDs)/th pop. 15-69……….

0.1 116
Country-code TLDs/th pop. 15-69…………………..………….

3.7 90
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.0 94

◇

111
◇
99
53 ●
114
◇
110
◇

1.0 125◇
0.0 108
0.4 97
1.3 55◇
0.3 99 ○ ◇0.0 124

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

219

ARGENTINA

GII 2019 rank

73

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

75

72

High

LCN

44.7

918.6

20,537.1

80

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
56.7

86

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
57.0
Political and operational stability*……………..………….….
70.2
Government effectiveness*…………………………..…………. 50.4

62
61
61

◇
◇
◇

1.2
1.2.1
1.2.2
1.2.3


51.5
Regulatory environment……………………………..………..

34.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
39.9

30.3
Cost of redundancy dismissal, salary weeks…………..

106 ○ ◇92◇75
◇116 ○ ◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
61.6

Ease of starting a business*………………………………..……
82.0
Ease of resolving insolvency*……………………………….….
41.2

95
99
92


38.7
HUMAN CAPITAL & RESEARCH………………...

42

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.9
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.6
Government funding/pupil, secondary, % GDP/cap… 21.8
School life expectancy, years……………….…………….……. 17.6

PISA scales in reading, maths, & science…………......…
468.9
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.2

31
25 ●
42
15 ●
39
50

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
29.7
🕘🕘Tertiary enrolment, % gross………………………….….……….
89.1
Graduates in science & engineering, %……………….….
16.1
Tertiary inbound mobility, %....................................... ….
2.5

70
◇
7 ●
81 ○ ◇
70

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
28.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
1,232.6
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.5

46.3
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*…………… 41.9

38
47 ◇
59
34
29 ●
INFRASTRUCTURE……………………………….......
45.8

69

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  68.1

ICT access*………………………………………………………….…….
73.1

ICT use*…………………………….....................................…….
61.8
Government’s online service*…………………………….……. 75.0E-participation*…………………………………………………….…….
62.4

62
55
53
56
84

◇
◇
◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
32.1
Electricity output, GWh/mn pop………………………..…….
3,346.1
Logistics performance*……………………………………………..
38.5

Gross capital formation, % GDP………………………….…….

◇

23.7

75
59
60
57

3.3
3.3.1
3.3.2
3.3.3


37.3
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.2
Environmental performance*…….……………………………… 59.3
ISO 14001 environmental certificates/bn PPP$ GDP..
1.6

69
62
65
54

◇
◇
◇


BUSINESS SOPHISTICATION..……….……………
32.6

57

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
41.2

Knowledge-intensive employment, %...........................
17.6
🕘🕘Firms offering formal training, % firms………………………… 63.6
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
18.2
Females employed w/advanced degrees, %……………..
14.2

53
84
◇
5 ● ◆
58
◇
◇
69
44

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
18.0 106 ○ ◇◇University/industry research collaboration †………………..
37.6 83◇State of cluster development†.……..………..………………….. 39.1 95

GERD financed by abroad, %......................................... 6.3 57
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 96 ○ ◇
Patent families 2+ offices/bn PPP$ GDP……………………..
0.1 62

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
38.4

2.9
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
12.1

ICT services imports, % total trade…………..………………...
1.5

FDI net inflows, % GDP…………………………….………………….
1.5🕘🕘Research talent, % in business enterprise……..………….. 8.1

42
7 ●◆
18 ●
39
97
65
◇

 19.2KNOWLEDGE & TECHNOLOGY OUTPUTS....

78



Knowledge creation………………………………………........... 13.2
Patents by origin/bn PPP$ GDP……………….…………..….…
0.4

n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.2
Scientific & technical articles/bn PPP$ GDP….…..…..….
6.8
Citable documents H-index…………………….……….……..….
26.2

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


28.0 101
Knowledge impact………………………………………..............
◇
Growth rate of PPP$ GDP/worker, %……………..…....…….
-1.2 102 ○ ◇🕘🕘New businesses/th pop. 15-64………………….…....…………. 0.4 89 ○Computer software spending, % GDP…………..……………
0.2 78◇
ISO 9001 quality certificates/bn PPP$ GDP…………..……
7.0 47High- & medium-high-tech manufactures, %……………… n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


16.3
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

1.8
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..……… 2.5

FDI net outflows, % GDP…………………………….…………....... 0.2

73
33
56
41
87

◇


24.0
CREATIVE OUTPUTS…….…………………….…………

77

◇

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
37.9

Trademarks by origin/bn PPP$ GDP…………..……….….….
64.7
Industrial designs by origin/bn PPP$ GDP…………..……..
1.1

◇


ICTs & business model creation†………………………....…….
53.0

ICTs & organizational model creation †……………………....
50.6

80
32
65
93
79

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
14.6
Cultural & creative services exports, % total trade…....
1.1
National feature films/mn pop. 15-69………………….………
7.4
Entertainment & Media market/th pop. 15-69……………. 10.2
🕘🕘Printing & other media, % manufacturing…...................
1.0
Creative goods exports, % total trade………………………..
0.1

69
◇
24 ●
24 ●
35
◇
67
98

7.3
7.3.1
7.3.2
7.3.3
7.3.4


5.4
Online creativity………………………………………..……….…….

3.0
Generic top-level domains (TLDs)/th pop. 15-69……….

4.5
Country-code TLDs/th pop. 15-69…………………..………….

12.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
5.8

63
62
55
61
48

◇

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
20.1
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...…… 16.1

Microfinance gross loans, % GDP……………………….…….
0.0

117 ○ ◇
77
113 ○ ◇
75 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 32.2
Ease of protecting minority investors*…………..………….
61.7

Market capitalization, % GDP………………………………...….
12.7
Venture capital deals/bn PPP$ GDP……………….……....
0.0

111 ○ ◇
54
68 ○
59

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
61.3
Applied tariff rate, weighted avg., %………………………….
7.9
Intensity of local competition†…………………………………… 55.4
Domestic market scale, bn PPP$……………………………… 918.6

61
103 ○ ◇120 ○ ◇
28 ●

60
78
n/a
43
65
36

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
The Global Innovation Index 2019

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5


37.9 111 ○ ◇MARKET SOPHISTICATION..………….……………

220

◇

◇

◇
◇

◇
◇
◇

ARMENIA

GII 2019 rank

64

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

50

85

Upper middle

NAWA

2.9

30.7

10,176.1

68

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
26.3

INSTITUTIONS………………………………….…….…..
63.2

64

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
50.5

Political and operational stability*……………..………….….
63.2
Government effectiveness*…………………………..…………. 44.2

81
86
77

1.2
1.2.1
1.2.2
1.2.3


69.1
Regulatory environment……………………………..………..

49.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
42.3

13.0
Cost of redundancy dismissal, salary weeks…………..

55
57
69
42

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
70.1
Ease of starting a business*………………………………..……
96.2
Ease of resolving insolvency*……………………………….…. 44.0

65
8 ●◆
85


16.9 107
HUMAN CAPITAL & RESEARCH………………...

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


26.9 [112]
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
2.8 1 1 1 ○ ◇🕘🕘Government funding/pupil, secondary, % GDP/cap… 14.5
85
🕘🕘School life expectancy, years……………….…………….……. 13.0
81

PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
n/a n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
22.1
Tertiary enrolment, % gross………………………….….……….
52.2
Graduates in science & engineering, %……………….…. 14.7
Tertiary inbound mobility, %.......................................
….
4.3

87
54
88 ○ ◇
48

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

97
n/a
86
43 ○ ◇78 ○ ◇

1.6
n/a
0.2
0.0
0.0


INFRASTRUCTURE……………………………….......
40.2

85

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  60.1

ICT access*………………………………………………………….…….
76.7

ICT use*…………………………….....................................…….
50.7

56.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
56.7

78
36 ● ◆
70
95
97

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
26.7
Electricity output, GWh/mn pop………………………..…. 2,496.6
Logistics performance*…………………………………………….. 25.4
Gross capital formation, % GDP………………………….…….
22.5

93
71
87
68

3.3
3.3.1
3.3.2
3.3.3


33.9
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
7.8

Environmental performance*…….……………………………… 62.1
ISO 14001 environmental certificates/bn PPP$ GDP..
0.1

82
80
56
120 ○



MARKET SOPHISTICATION..………….…………… 50.1


55

4.1
4.1.1
4.1.2
4.1.3

Credit……………………………………………………….……………… 31.2
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
51.5

Microfinance gross loans, % GDP……………………….……. 0.0

86
40
66
60

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 63.3
Ease of protecting minority investors*…………..………….
63.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[17]
48
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
55.9
Applied tariff rate, weighted avg., %………………………….
2.2
Intensity of local competition†…………………………………… 73.6
Domestic market scale, bn PPP$……………………………… 30.7

86
56
36
113 ○ ◇

89

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
36.5 [66]Knowledge-intensive employment, %...........................
29.4 46
Firms offering formal training, % firms………………………… 16.2 82 ○ ◇
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
14.9 42

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
20.0
University/industry research collaboration †………………..
36.3
State of cluster development†.……..………..………………….. 46.0

GERD financed by abroad, %......................................... 1.7

JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a
Patent families 2+ offices/bn PPP$ GDP……………………..
0.2

88
89
69
82
n/a
47

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
22.4
🕘🕘
0.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.8

ICT services imports, % total trade…………..………………... 0.5

FDI net inflows, % GDP…………………………….…………………. 2.4

Research talent, % in business enterprise……..…………..
n/a

114 ○ ◇
120 ○ ◇
109
102
74
n/a

 25.0 54
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 22.6

Patents by origin/bn PPP$ GDP……………….…………..….…
3.9

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 1.4
Scientific & technical articles/bn PPP$ GDP….…..…..….
25.2
Citable documents H-index…………………….……….……..….
9.8

37
29 ●
50
18 ●
13 ● ◆
69

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


35.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
6.2
New businesses/th pop. 15-64………………….…....………….
1.7
Computer software spending, % GDP…………..…………… 0.1

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.0
High- & medium-high-tech manufactures, %………………
0.0

70
2 ●◆
55
84
107
96 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.2 67
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0 109 ○ ◇Intellectual property receipts, % total trade……………….

0.6 77High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.3
15 ● ◆
FDI net outflows, % GDP…………………………….…………....... 0.3 77


32.2
CREATIVE OUTPUTS…….…………………….…………

48

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
43.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
94.7
Industrial designs by origin/bn PPP$ GDP…………..…….. 1.9

ICTs & business model creation†………………………....……. 54.2

ICTs & organizational model creation †……………………....
52.8

55
18 ●
52
88
67

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
22.4 49
Cultural & creative services exports, % total trade…....
0.6 41National feature films/mn pop. 15-69………………….………
12.5 1 1 ● ◆Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.5 33Creative goods exports, % total trade……………………….. 0.6 55

7.3
7.3.1
7.3.2
7.3.3
7.3.4


19.8
Online creativity………………………………………..……….…….

3.0
Generic top-level domains (TLDs)/th pop. 15-69……….

4.6
Country-code TLDs/th pop. 15-69…………………..………….

102.5
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
2.5

34 ● ◆
64
53
6 ●◆
60

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

221

AUSTRALIAGII 2019 rank

22

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

31

15

High

SEAO

24.8

1,318.6

52,373.5

20

Score/Value Rank

INSTITUTIONS………………………………….…….…..

88.8

13

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
85.7

Political and operational stability*……………..………….….
89.5
Government effectiveness*…………………………..………….
83.8

14
15
15

1.2
1.2.1
1.2.2
1.2.3


93.1
Regulatory environment……………………………..………..

93.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
90.9

12.0
Cost of redundancy dismissal, salary weeks…………..

12
5 ●
13
38

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
87.7

96.5
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….….
78.9

11
7 ●
19


57.7
HUMAN CAPITAL & RESEARCH………………...

10 ●

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


61.0
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.3
Government funding/pupil, secondary, % GDP/cap… 17.2
School life expectancy, years……………….…………….……. 22.1

PISA scales in reading, maths, & science…………......…
502.3
Pupil-teacher ratio, secondary…………………………......….
n/a

19
32
69 ○ ◇
1 ●◆
19
n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
50.6
Tertiary enrolment, % gross………………………….….……….
113.8
🕘🕘
Graduates in science & engineering, %……………….….
17.6
Tertiary inbound mobility, %.......................................
…. 17.5

13
2 ●◆76 ○ ◇
9

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
61.4
🕘🕘
Researchers, FTE/mn pop ……………………………..…...……
4 ,539.5
🕘🕘Gross expenditure on R&D, % GDP………….………..……
1.9

68.1
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
80.9

14
16
18
20
5 ●
INFRASTRUCTURE……………………………….......
60.9

19

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 89.0

80.4
ICT access*………………………………………………………….…….

ICT use*…………………………….....................................…….
80.2

97.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

13
26
15
7 ●
5 ●

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
49.1
Electricity output, GWh/mn pop………………………..…. 10,432.2
Logistics performance*…………………………………………….. 79.0
Gross capital formation, % GDP………………………….…….

20
13
18
50

3.3
3.3.1
3.3.2
3.3.3


44.5
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
8.5
Environmental performance*…….………………………………
74.1
ISO 14001 environmental certificates/bn PPP$ GDP.. 3.2

45
67 ○
21
30


68.3
MARKET SOPHISTICATION..………….……………

8 ●

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
79.5
Ease of getting credit*…………………………………..…………..
90.0
🕘🕘Domestic credit to private sector, % GDP…………...……
142.5

Microfinance gross loans, % GDP……………………….…….
n/a

5●◆
7 ●◆
13
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 46.4
Ease of protecting minority investors*…………..………….
60.0

Market capitalization, % GDP………………………………...….
102.3
Venture capital deals/bn PPP$ GDP……………….……....
0.1

51
61 ○
11
19

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
78.9

Applied tariff rate, weighted avg., %………………………….
0.9
†Intensity of local competition …………………………………… 79.2

Domestic market scale, bn PPP$……………………………… 1,318.6

10 ●
9 ●
11
20

98.3

24.3

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
46.1

26

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
67.5
🕘🕘
Knowledge-intensive employment, %...........................
46.0

Firms offering formal training, % firms…………………………
n/a🕘🕘GERD performed by business, % GDP…………………..…… 1.0
🕘🕘
GERD financed by business, %……………………………........ 61.9
🕘🕘Females employed w/advanced degrees, %……………..
22.6

11
14
n/a
21
11
17

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
34.6
University/industry research collaboration †………………..
53.1
State of cluster development†.……..………..…………………..
53.8
🕘🕘GERD financed by abroad, %.........................................
1.6
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.2
Patent families 2+ offices/bn PPP$ GDP…………………….. 1.0

39
◇
◇
35
40
◇
84 ○
7 ●
28
◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
36.2

1.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.5
ICT services imports, % total trade…………..………………...
1.0

FDI net inflows, % GDP…………………………….………………….
3.3
🕘🕘Research talent, % in business enterprise……..…………..
27.9

◇
50
24
26
71 ○ ◇
5044◇ 31.6 36
KNOWLEDGE & TECHNOLOGY OUTPUTS....
The Global Innovation Index 2019

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 38.0
Patents by origin/bn PPP$ GDP……………….…………..….…
2.0

1.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.8
Scientific & technical articles/bn PPP$ GDP….…..…..…. 26.9
Citable documents H-index…………………….……….……..….
65.2

21
43
◇
26
◇
29
10 ●
10 ●

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


44.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.4
New businesses/th pop. 15-64………………….…....………….
15.5
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
9.7
High- & medium-high-tech manufactures, %……………… 0.3

30
77 ○
7 ●◆
53
◇
32
39

6.3
6.3.1
6.3.2
6.3.3
6.3.4


12.6
Knowledge diffusion……………………………………..…..…….

0.3Intellectual property receipts, % total trade……………….

1.7
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.0

FDI net outflows, % GDP…………………………….………….......
0.1

88 ○ ◇
29◇
58◇
83 ○
97 ○ ◇
41.1
CREATIVE OUTPUTS…….…………………….…………

29

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
48.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
64.3
Industrial designs by origin/bn PPP$ GDP…………..……..
2.3

ICTs & business model creation†………………………....…….
70.7

ICTs & organizational model creation †……………………....
67.3

40
33
48
30
25

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
27.5
Cultural & creative services exports, % total trade…....
0.4
National feature films/mn pop. 15-69………………….………
3.2
Entertainment & Media market/th pop. 15-69…………….
67.0

Printing & other media, % manufacturing…...................
2.3

Creative goods exports, % total trade………………………..
0.6

35
56
56 ○
7
14
◆
54

7.3
7.3.1
7.3.2
7.3.3
7.3.4


39.5
Online creativity………………………………………..……….…….

63.1
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 50.9

47.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
12.1

16
10 ●
14
28
37

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
222

◇

◇
◇

AUSTRIA

GII 2019 rank

21

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

25

19

High

EUR

8.8

464.0

52,137.4

21

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
86.0

17

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
83.9

Political and operational stability*……………..………….….
87.7
Government effectiveness*…………………………..…………. 82.0

17
18
16

1.2
1.2.1
1.2.2
1.2.3


93.7
Regulatory environment……………………………..………..

80.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
94.3

8.0
Cost of redundancy dismissal, salary weeks…………..

10 ●
18
9 ●
1 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
80.3
Ease of starting a business*………………………………..……
83.2

Ease of resolving insolvency*……………………………….…. 77.5

32
91 ○ ◇
20


60.2
HUMAN CAPITAL & RESEARCH………………...

8 ●

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


60.7
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.5
Government funding/pupil, secondary, % GDP/cap… 27.3

School life expectancy, years……………….…………….……. 16.3

PISA scales in reading, maths, & science…………......…
492.2
Pupil-teacher ratio, secondary…………………………......….
9.3

22
28
17
28
25
20

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
61.7
Tertiary enrolment, % gross………………………….….……….
86.3
Graduates in science & engineering, %……………….….
30.3
Tertiary inbound mobility, %.......................................
…. 16.3

3 ●◆
12 ●
12
◆
10 ●

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
58.1
Researchers, FTE/mn pop……………………………..…....… 5,439.8
Gross expenditure on R&D, % GDP………….………..……
3.2

55.4
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
42.0

18
9 ●
6 ●
25
28


INFRASTRUCTURE……………………………….......
61.4

17

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 82.3

ICT access*………………………………………………………….…….
85.2

ICT use*…………………………….....................................…….
74.7

86.8
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

26
13
29
32
45

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
51.3
Electricity output, GWh/mn pop………………………..…….
7,666.0
Logistics performance*…………………………………………….. 91.8
Gross capital formation, % GDP………………………….…….

25.6

14
27
4 ●
41

3.3
3.3.1
3.3.2
3.3.3


50.5
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
11.5
Environmental performance*…….………………………………
79.0
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.6

28
37
8 ●
37

82.6

◆


BUSINESS SOPHISTICATION..……….……………
53.8

18

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
65.0Knowledge-intensive employment, %...........................
41.6
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… 2.2

GERD financed by business, %……………………………........
54.0

Females employed w/advanced degrees, %……………..
17.2

17
25
n/a
6 ●
21
35
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
50.8
University/industry research collaboration †………………..
65.2
State of cluster development†.……..………..…………………..
66.7
GERD financed by abroad, %.........................................
16.0
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 4.5

11 ●
16
14
24
31
◇
12 ●

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
45.6 26
0.8 49Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.2 54 ○
ICT services imports, % total trade…………..………………...
2.3 18
FDI net inflows, % GDP…………………………….………………….
-1.9 127 ○
9Research talent, % in business enterprise……..…………..
62.2

◆

◇

◇


52.8
MARKET SOPHISTICATION..………….……………

44

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
47.3
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...……
84.1

Microfinance gross loans, % GDP……………………….…….
n/a

39
77 ○
34
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 38.8
Ease of protecting minority investors*…………..………….
68.3
Market capitalization, % GDP………………………………...….
30.8
Venture capital deals/bn PPP$ GDP……………….……....
0.0

81 ○ ◇30
48 ○ ◇
38 ○ ◇

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
72.4
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 78.8
Domestic market scale, bn PPP$……………………………… 464.0

28
23
13
43

◇

 36.7 25
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 41.3
Patents by origin/bn PPP$ GDP……………….…………..….…
9.7

3.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
1.0

Scientific & technical articles/bn PPP$ GDP….…..…..….
22.0
Citable documents H-index…………………….……….……..…. 43.4

18
13
11
23
20
17

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.6
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.9
New businesses/th pop. 15-64………………….…....………….
0.6

Computer software spending, % GDP…………..……………
0.6
ISO 9001 quality certificates/bn PPP$ GDP…………..……
8.4
High- & medium-high-tech manufactures, %……………… 0.4

33
65 ○
80 ○ ◇
15
36
15

6.3
6.3.1
6.3.2
6.3.3
6.3.4


25.1
Knowledge diffusion……………………………………..…..…….

0.6Intellectual property receipts, % total trade……………….

7.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.0

FDI net outflows, % GDP…………………………….………….......
-1.2

◇
40
24
21
33
124 ○ ◇


41.4
CREATIVE OUTPUTS…….…………………….…………

25

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
51.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
53.3
🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
7.3

ICTs & business model creation†………………………....…….
72.6

ICTs & organizational model creation †…………………….... 64.9

30
45
17
27
29

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5



Creative goods & services……………………….…….……….. 27.1
Cultural & creative services exports, % total trade…....
1.2
National feature films/mn pop. 15-69………………….………
7.1
Entertainment & Media market/th pop. 15-69…………….
65.3
Printing & other media, % manufacturing…...................
1.3
Creative goods exports, % total trade………………………..
0.9

38
23
28
8
42 ○
45

7.3
7.3.1
7.3.2
7.3.3
7.3.4


36.2
Online creativity………………………………………..……….…….

36.0
Generic top-level domains (TLDs)/th pop. 15-69……….

57.9
Country-code TLDs/th pop. 15-69…………………..………….

54.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
14.4

22
19
1 1 ●
20
33

◇

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

223

AZERBAIJAN

GII 2019 rank

84

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

90

77

Upper middle

NAWA

9.9

178.5

18,075.982

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
24.5 103
INSTITUTIONS………………………………….…….…..
64.5

59

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
51.2

Political and operational stability*……………..………….….
68.4
Government effectiveness*…………………………..…………. 42.6

77
71
82

1.2
1.2.1
1.2.2
1.2.3


62.4
Regulatory environment……………………………..………..

35.4
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
31.7

13.7
Cost of redundancy dismissal, salary weeks…………..

73
89
96
53

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
80.0
Ease of starting a business*………………………………..……
96.1
Ease of resolving insolvency*……………………………….…. 63.8

33 ● ◆
9 ●◆42


17.0 106
HUMAN CAPITAL & RESEARCH………………...

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


21.1 [123]Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
2.9 103
Government funding/pupil, secondary, % GDP/cap… n/a n/a
School life expectancy, years……………….…………….……. n/a n/a
PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
n/a n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
27.5
Tertiary enrolment, % gross………………………….….……….
27.1
Graduates in science & engineering, %……………….…. 23.6

Tertiary inbound mobility, %....................................... ….
2.1

74
87
38
74

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

90
n/a
90
43 ○ ◇
72

2.5
n/a
0.2
0.0
3.7


INFRASTRUCTURE……………………………….......
45.3

70

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 65.9

ICT access*………………………………………………………….…….
67.0

ICT use*…………………………….....................................…….
55.5

72.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
68.0

68
64
63
63
77

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
30.8
Electricity output, GWh/mn pop………………………..…….
2,556.7
Logistics performance*……………………………………………..
n/a
Gross capital formation, % GDP………………………….…….
25.0

83
70
n/a
45

3.3
3.3.1
3.3.2
3.3.3


39.3
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
10.8

Environmental performance*…….……………………………… 62.3
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.4

61
44
52
92



MARKET SOPHISTICATION..………….…………… 56.5

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
29.4

Knowledge-intensive employment, %...........................
23.3
Firms offering formal training, % firms………………………… 20.2

GERD performed by business, % GDP…………………..…… 0.0

GERD financed by business, %……………………………........
32.0
🕘🕘
Females employed w/advanced degrees, %……………..
12.9

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
21.4 79
University/industry research collaboration †………………..
54.2 32 ● ◆State of cluster development†.……..………..…………………..
55.7 33 ● ◆
GERD financed by abroad, %.........................................
0.1 100 ○
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 84
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 79

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
22.9
🕘🕘
0.1
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
2.8

ICT services imports, % total trade…………..………………... 0.5

FDI net inflows, % GDP…………………………….………………….
8.8

Research talent, % in business enterprise……..…………..
n/a

83
62
74
◇
82 ○
56
52

◇
113
105
124 ○ ◇
106
15 ● ◆n/a

 14.9 101
KNOWLEDGE & TECHNOLOGY OUTPUTS....

◇

31 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
29.5 95
Ease of getting credit*…………………………………..…………..
80.0 20 ●Domestic credit to private sector, % GDP…………...…… 22.2 109 ◇Microfinance gross loans, % GDP……………………….……. 0.0 66

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 81.7
Ease of protecting minority investors*…………..………….
81.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
58.4 74
🕘🕘
Applied tariff rate, weighted avg., %………………………….
5.2 89
Intensity of local competition†…………………………………… 61.3 102
Domestic market scale, bn PPP$……………………………… 178.5 66

[1]
2 ●◆
n/a
n/a



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 3.9 109
🕘🕘Patents by origin/bn PPP$ GDP……………….…………..….…
1.1 60
0.1 67
PCT patents by origin/bn PPP$ GDP…………..….…….……
🕘🕘
Utility models by origin/bn PPP$ GDP……………...…..…… 0.1 53
Scientific & technical articles/bn PPP$ GDP….…..…..….
3.5 96
Citable documents H-index…………………….……….……..….
3.9 104

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


21.4 1 1 1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-1.6 105 ○ ◇New businesses/th pop. 15-64………………….…....………….
1.0 70Computer software spending, % GDP…………..…………… 0.1 95
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.2 104
High- & medium-high-tech manufactures, %………………
0.1 79

6.3
6.3.1
6.3.2
6.3.3
6.3.4


19.4
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0Intellectual property receipts, % total trade……………….

0.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.4

FDI net outflows, % GDP…………………………….…………....... 6.4

51
108 ○ ◇
115 ○107
10 ● ◆


22.8
CREATIVE OUTPUTS…….…………………….…………

84

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
38.7
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
16.7
🕘🕘Industrial designs by origin/bn PPP$ GDP…………..…….. 0.1

ICTs & business model creation†………………………....……. 65.9

ICTs & organizational model creation †……………………....
63.4

76
91
110 ○
48 ◆
35 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


5.0
Online creativity………………………………………..……….…….

1.0
Generic top-level domains (TLDs)/th pop. 15-69……….

1.2
Country-code TLDs/th pop. 15-69…………………..………….

26.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.0

8.7 92
0.1 75
7.2 27 ● ◆n/a n/a0.7 82
0.0 122 ○

66
94
76
41 ●
93 ○◇NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
224

The Global Innovation Index 2019

BAHRAIN

GII 2019 rank

78

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

87

69

High

NAWA

1.6

75.2

50,056.5

72

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
66.0

54

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
57.4

Political and operational stability*……………..………….….
70.2
Government effectiveness*…………………………..…………. 51.0

60
61
60

◇
◇
◇

1.2
1.2.1
1.2.2
1.2.3


73.5
Regulatory environment……………………………..………..

53.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
58.2

13.6
Cost of redundancy dismissal, salary weeks…………..

39 ●
53
◇
44
◇
51

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
67.1
Ease of starting a business*………………………………..……
89.6

Ease of resolving insolvency*……………………………….…. 44.6

75
56
83

◇


24.4
HUMAN CAPITAL & RESEARCH………………...

85

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


40.5
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
2.3
Government funding/pupil, secondary, % GDP/cap… 17.5
School life expectancy, years……………….…………….……. 15.3

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
10.1

83
◇
115 ○ ◇
66
46
n/a
32 ●

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
30.1
Tertiary enrolment, % gross………………………….….……….
45.5
Graduates in science & engineering, %……………….…. 15.6
Tertiary inbound mobility, %.......................................
….
13.1

67
◇
65
◇
85
◇
12 ●

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
2.7
🕘🕘Researchers, FTE/mn pop……………………………..…...……
368.9
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
4.5

89
◇
72
◇
107 ○ ◇
43 ○ ◇70 ◇


INFRASTRUCTURE……………………………….......
51.6

45

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 78.8

ICT access*………………………………………………………….…….
82.5

ICT use*…………………………….....................................…….
73.2

79.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 79.8

34 ●
19 ●
30 ●
45
53

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
47.7
Electricity output, GWh/mn pop………………………..…….
19,937.1
Logistics performance*…………………………………………….. 40.8
Gross capital formation, % GDP………………………….…….
24.0

27 ●
3 ● ◆
58
◇
54

3.3
3.3.1
3.3.2
3.3.3


28.2 106
Ecological sustainability………………………………………..
◇
GDP/unit of energy use…………………………………………….
4.3 114 ○ ◇
Environmental performance*…….……………………………… 55.2
81
◇
ISO 14001 environmental certificates/bn PPP$ GDP..
1.9 50◇

MARKET SOPHISTICATION..………….…………… 45.3

79

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
39.7
Ease of getting credit*…………………………………..…………..
45.0
🕘🕘
Domestic credit to private sector, % GDP…………...…… 73.7

Microfinance gross loans, % GDP……………………….…….
n/a

56
94
43
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 43.9
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
61.2
Venture capital deals/bn PPP$ GDP……………….……....
0.1

60
35
28
24 ●

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
52.4 100Applied tariff rate, weighted avg., %………………………….
7.8 102
Intensity of local competition†…………………………………… 70.1 60
Domestic market scale, bn PPP$……………………………… 75.2 88◇
BUSINESS SOPHISTICATION..……….……………
27.1

83

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
26.0 [96]🕘🕘Knowledge-intensive employment, %...........................
21.9 69
Firms offering formal training, % firms………………………… n/a n/a🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 79
🕘🕘
GERD financed by business, %……………………………........
21.8 64
Females employed w/advanced degrees, %……………..
n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
37.7
University/industry research collaboration †………………..
45.4
†State of cluster development .……..………..………………….. 60.3
🕘🕘
GERD financed by abroad, %......................................... 12.4
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.2
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
17.7 127 ○ ◇
n/a n/aIntellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
4.7 110◇
ICT services imports, % total trade…………..………………...
0.4 1 1 1

FDI net inflows, % GDP…………………………….…………………. 0.8 109
🕘🕘Research talent, % in business enterprise……..………….. 0.4 83 ○ ◇◇◇

33 ●
50
26 ●
34
6 ● ◆
75

 15.9 92
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇

◇

2.1 123 ○ ◇0.2 100
0.0 92◇n/a n/a1.8 114 ○ ◇2.4 116 ○ ◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


35.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.6
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 5.7
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

6.3
6.3.1
6.3.2
6.3.3
6.3.4


9.8 103◇
Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….
🕘🕘
0.1 110High-tech net exports, % total trade……………….….…......
◇
ICT services exports, % total trade……………..……..………
3.0 32 ●
FDI net outflows, % GDP…………………………….…………....... -2.7 125 ○ ◇

69
72
n/a
39
54
85

◇


22.8
CREATIVE OUTPUTS…….…………………….…………

83

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
3.6
Industrial designs by origin/bn PPP$ GDP…………..…….. 0.4

ICTs & business model creation†………………………....…….
66.8

ICTs & organizational model creation †……………………....
58.2

90
◇
119 ○ ◇
90
42
51

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
14.8
Cultural & creative services exports, % total trade…....
n/aNational feature films/mn pop. 15-69………………….………
n/aEntertainment & Media market/th pop. 15-69…………….
9.3
Printing & other media, % manufacturing…................... n/a🕘🕘
Creative goods exports, % total trade………………………..
1.5

[67]
n/a
n/a
37
◇
n/a
35 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


4.0
Online creativity………………………………………..……….…….

4.7
Generic top-level domains (TLDs)/th pop. 15-69……….

0.4
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
16.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.1

69
◇
55
96
◇
55
87 ○

◇

◇
◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

225

BANGLADESH

GII 2019 rank

116

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

108

117

Lower middle

CSA

166.4

758.2

4,619.8

116

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
20.0 120


INSTITUTIONS………………………………….…….…..
45.5 124 ○ ◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
37.2
Political and operational stability*……………..………….….
54.4
Government effectiveness*…………………………..…………. 28.7

116
111
115

1.2
1.2.1
1.2.2
1.2.3


44.7
Regulatory environment……………………………..………..

20.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
28.6

31.0
Cost of redundancy dismissal, salary weeks…………..

118
116
102
118

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
54.5
Ease of starting a business*………………………………..……
80.8

Ease of resolving insolvency*……………………………….…. 28.2

119
◇
105
123 ○ ◇


HUMAN CAPITAL & RESEARCH………………...

◇
◇
◇

8.8 127 ○ ◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


15.9
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
1.5
Government funding/pupil, secondary, % GDP/cap… 10.2

School life expectancy, years……………….…………….……. 11.2

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
34.0

127 ○ ◇
118 ○ ◇
97
98
n/a
110 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
🕘🕘
Tertiary inbound mobility, %.......................................
….

6.6
17.6
11.3
0.1

118
◇
97
98 ○ ◇
109 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

4.0
n/a
n/a
0.0
8.0

[81]
n/a
n/a
43 ○ ◇66


INFRASTRUCTURE……………………………….......
40.0

86

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 53.3

ICT access*………………………………………………………….…….
35.7

ICT use*…………………………….....................................…….
18.7

78.5
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 80.3

90
109 ◇
1 1 1 ◇
51 ● ◆
51 ● ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
36.6
Electricity output, GWh/mn pop………………………..…….
394.8
Logistics performance*…………………………………………….. 24.0
Gross capital formation, % GDP………………………….…….
33.7

58 ●
109
94
14 ●

3.3
3.3.1
3.3.2
3.3.3


30.0
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
13.3
Environmental performance*…….……………………………… 29.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.2

96
19 ● ◆126 ○ ◇
113



MARKET SOPHISTICATION..………….…………… 41.1 96
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
32.7
Ease of getting credit*…………………………………..…………..
25.0
Domestic credit to private sector, % GDP…………...…… 47.6

Microfinance gross loans, % GDP……………………….……. 3.0

78
122 ○ ◇
73
9 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 31.0
Ease of protecting minority investors*…………..………….
55.0

Market capitalization, % GDP………………………………...….
34.5
Venture capital deals/bn PPP$ GDP……………….……....
0.0

117
84
43
73

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
59.5
🕘🕘Applied tariff rate, weighted avg., %………………………….
10.7
Intensity of local competition†…………………………………… 67.5
Domestic market scale, bn PPP$……………………………… 758.2

70116 ◇
71
30 ●

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
15.7 [116]Knowledge-intensive employment, %...........................
8.3 102Firms offering formal training, % firms………………………… 21.9 72

GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
1.3 105

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
21.0 82University/industry research collaboration †………………..
26.5 120 ○State of cluster development†.……..………..…………………..
46.8 60 ●
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 78
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
23.3

0.1
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
8.0

ICT services imports, % total trade…………..………………... 0.2

FDI net inflows, % GDP…………………………….………………….
1.1
Research talent, % in business enterprise……..…………..
n/a

111
103
58 ●
120
◇
104
n/a

 16.1KNOWLEDGE & TECHNOLOGY OUTPUTS....

91



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 6.7 [86]Patents by origin/bn PPP$ GDP……………….…………..….…
0.1 1 1 1
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
2.2 110
Citable documents H-index…………………….……….……..….
10.4 63

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


32.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
4.5
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.1
Computer software spending, % GDP…………..…………… 0.2

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.6
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

6.3
6.3.1
6.3.2
6.3.3
6.3.4


8.6 114Knowledge diffusion……………………………………..…..…….

0.0 103
Intellectual property receipts, % total trade……………….
🕘🕘
0.2 93High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.1 78
FDI net outflows, % GDP…………………………….………….......
0.0 10683
12 ●
101
75
117
◇
81


15.0 115
CREATIVE OUTPUTS…….…………………….…………

The Global Innovation Index 2019

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
29.4 108Trademarks by origin/bn PPP$ GDP…………..……….….….
13.4 98Industrial designs by origin/bn PPP$ GDP…………..…….. 2.3 49 ●
ICTs & business model creation†………………………....……. 50.2 103

ICTs & organizational model creation †……………………....
42.1 107

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.4
Online creativity………………………………………..……….…….

0.4
Generic top-level domains (TLDs)/th pop. 15-69……….

0.1
Country-code TLDs/th pop. 15-69…………………..………….

1.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.5

0.8 126 ○ ◇0.1 86
0.3 101n/a n/a0.2 101 ○ ◇0.1 107

110
112
117
104
68

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
226◇

BELARUS

GII 2019 rank

72

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

95

50

Upper middle

EUR

9.5

190.8

20,003.0

86

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

57.7

83

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
48.8

Political and operational stability*……………..………….….
70.2
Government effectiveness*…………………………..………….
38.1

87
61
91

1.2
1.2.1
1.2.2
1.2.3


51.3
Regulatory environment……………………………..………..

22.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
24.7

21.7
Cost of redundancy dismissal, salary weeks…………..

107 ○ ◇
113 ○ ◇
112 ○ ◇
92

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
73.0

93.4
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….….
52.6

54
26
66


41.6
HUMAN CAPITAL & RESEARCH………………...

39

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


60.8
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.8
Government funding/pupil, secondary, % GDP/cap… 35.9
School life expectancy, years……………….…………….……. 15.4

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
8.2

20
◆
53
8 ●◆
43
n/a
11 ● ◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
54.8
Tertiary enrolment, % gross………………………….….……….
86.7
Graduates in science & engineering, %……………….….
33.2
Tertiary inbound mobility, %.......................................
….
4.2

9 ●◆
11 ● ◆
6 ●◆
51

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

61
n/a
54
43 ○ ◇
57

9.1
n/a
0.6
0.0
14.8

◆


INFRASTRUCTURE……………………………….......
48.2

60

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  77.9

ICT access*………………………………………………………….…….
80.8

ICT use*…………………………….....................................…….
68.8

73.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
88.2

37
23
37
57
33

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
31.7
Electricity output, GWh/mn pop………………………..…….
3,529.5
Logistics performance*…………………………………………….. 23.9
Gross capital formation, % GDP………………………….…….

79
57
97
36

3.3
3.3.1
3.3.2
3.3.3


35.2
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
6.2
Environmental performance*…….………………………………
65.0
ISO 14001 environmental certificates/bn PPP$ GDP..
1.9

78
99 ○ ◇
40
◆
51

26.6

◆
◆
◆


BUSINESS SOPHISTICATION..……….……………
32.6

56

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
61.3

Knowledge-intensive employment, %...........................
39.2
Firms offering formal training, % firms…………………………
51.1
GERD performed by business, % GDP…………………..……
0.4

GERD financed by business, %……………………………........ 43.0
Females employed w/advanced degrees, %…………….. 32.6

23
◆
27
◆
19
41
41
1 ●◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
11.4 [126]University/industry research collaboration †………………..
n/a n/a
State of cluster development†.……..………..…………………..
n/a n/a
GERD financed by abroad, %.........................................
14.1 29JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 100 ○
Patent families 2+ offices/bn PPP$ GDP……………………..
0.1 60

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
25.1 101
0.4 70Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.1 104

ICT services imports, % total trade…………..………………...
0.7 93

FDI net inflows, % GDP…………………………….………………….
2.6 63Research talent, % in business enterprise……..…………..
n/a n/a 25.5KNOWLEDGE & TECHNOLOGY OUTPUTS....

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
21.8
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...……
26.4

Microfinance gross loans, % GDP……………………….…….
0.0

115 ○ ◇
77
104 ○
81 ○ ◇

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 63.3
Ease of protecting minority investors*…………..………….
63.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[17]
48
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
64.8

Applied tariff rate, weighted avg., %………………………….
1.5
†Intensity of local competition ……………………………………
n/a
Domestic market scale, bn PPP$……………………………… 190.8

54
15 ●
n/a
64

51

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 17.5
Patents by origin/bn PPP$ GDP……………….…………..….…
3.1

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
2.2
Scientific & technical articles/bn PPP$ GDP….…..…..….
5.3
Citable documents H-index…………………….……….……..…. 9.7

52
30
61
10 ●
78
70

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


40.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.5
New businesses/th pop. 15-64………………….…....………….
1.1
Computer software spending, % GDP…………..……………
0.0
ISO 9001 quality certificates/bn PPP$ GDP…………..……
22.2
High- & medium-high-tech manufactures, %………………
0.3

48
35
69
107 ○ ◇
14 ● ◆
45

6.3
6.3.1
6.3.2
6.3.3
6.3.4


18.7
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

1.8
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.0

FDI net outflows, % GDP…………………………….………….......
0.2

55
59
57
19 ● ◆89
10.8 126 ○ ◇CREATIVE OUTPUTS…….…………………….…………

◇
50.0 56
MARKET SOPHISTICATION..………….……………



7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
8.0 [127]
Trademarks by origin/bn PPP$ GDP…………..……….….….
24.8
81

Industrial designs by origin/bn PPP$ GDP…………..……..
1.0 68
ICTs & business model creation†………………………....…….
n/a n/a
ICTs & organizational model creation †……………………....
n/a n/a

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


22.1
Online creativity………………………………………..……….…….

1.7
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 5.2

22.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
66.5

5.0 101◇
0.2 690.1 105 ○ ◇n/a n/a0.5 90 ○
0.4 63

31
◆
83
47
47
6 ●◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

227

BELGIUM

GII 2019 rank

23

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

24

21

High

EUR

11.5

549.7

48,244.7

25

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
82.0

21

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
77.0
Political and operational stability*……………..………….….
80.7
Government effectiveness*…………………………..…………. 75.2

28
35
24

1.2
1.2.1
1.2.2
1.2.3


80.4
Regulatory environment……………………………..………..

75.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
81.9

19.7
Cost of redundancy dismissal, salary weeks…………..

30
24
21
81 ○

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
88.5
Ease of starting a business*………………………………..……
93.0
Ease of resolving insolvency*……………………………….…. 83.9

9 ●
30
8 ●


55.0
HUMAN CAPITAL & RESEARCH………………...

13 ●

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


68.6
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
6.6
🕘🕘Government funding/pupil, secondary, % GDP/cap… 24.5
School life expectancy, years……………….…………….……. 19.7

PISA scales in reading, maths, & science…………......…
502.5
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
9.1

5 ●◆
14
26
2 ● ◆
18
18
◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
37.2
🕘🕘Tertiary enrolment, % gross………………………….….……….
75.9
Graduates in science & engineering, %……………….….
17.1
Tertiary inbound mobility, %.......................................
…. 12.044
2278 ○ ◇
13

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
59.2
Researchers, FTE/mn pop……………………...………..…... 4,905.5
Gross expenditure on R&D, % GDP………….………..……
2.6

66.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
54.2

16
14
11 ●
21
16


INFRASTRUCTURE……………………………….......
57.2

29

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 77.1

ICT access*………………………………………………………….…….
81.5

ICT use*…………………………….....................................…….
75.6

75.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
75.8

38
◇
21
27
55 ◇
59 ○ ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
50.5
Electricity output, GWh/mn pop………………………..…….
7,496.2
Logistics performance*…………………………………………….. 92.4
Gross capital formation, % GDP………………………….…….
24.9

16
29
3 ●
47

3.3
3.3.1
3.3.2
3.3.3


44.1
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
8.5
Environmental performance*…….………………………………
77.4
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.0

46
68 ○
15
47



◇
◇
◇

◇

MARKET SOPHISTICATION..………….…………… 55.3

37

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
47.8
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...……
66.3

Microfinance gross loans, % GDP……………………….…….
n/a

36
54 ○
46 ◇
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 45.0
Ease of protecting minority investors*…………..………….
61.7

Market capitalization, % GDP………………………………...….
86.9
Venture capital deals/bn PPP$ GDP……………….……....
0.1

56
54
17
21

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
73.2
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 78.6

Domestic market scale, bn PPP$……………………………… 549.7

25
23
14
37


BUSINESS SOPHISTICATION..……….……………
54.1

17

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
73.1

Knowledge-intensive employment, %...........................
47.6

Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..……
1.8
🕘🕘
GERD financed by business, %……………………………........
58.6
Females employed w/advanced degrees, %……………..
25.0

7 ●
9 ●
n/a
11
12
1 1 ●

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
46.0
University/industry research collaboration †………………..
68.7
State of cluster development†.……..………..…………………..
64.9
🕘🕘GERD financed by abroad, %.........................................
16.5
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 2.8

19
12 ●
16
22
26
16

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
43.2 31
0.8 46
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.4 67 ○
ICT services imports, % total trade…………..………………...
2.3 20
FDI net inflows, % GDP…………………………….………………….
-1.3 126 ○
Research talent, % in business enterprise……..…………..
54.1 21

 40.8KNOWLEDGE & TECHNOLOGY OUTPUTS....


21

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 49.1
Patents by origin/bn PPP$ GDP……………….…………..….…
6.0

2.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 23.1
Citable documents H-index…………………….……….……..….
53.4

14 ●
19
15
n/a
18
14 ●

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.2
New businesses/th pop. 15-64………………….…....………….
3.7
Computer software spending, % GDP…………..……………
0.7
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 5.9
High- & medium-high-tech manufactures, %………………
0.4

39
83 ○
34
7 ●
53
29

6.3
6.3.1
6.3.2
6.3.3
6.3.4


30.2
Knowledge diffusion……………………………………..…..…….

0.9Intellectual property receipts, % total trade……………….

8.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.0

FDI net outflows, % GDP…………………………….………….......
-0.1

31
20
20
34
119 ○ ◇


38.5
CREATIVE OUTPUTS…….…………………….…………

33

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
49.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
45.8
Industrial designs by origin/bn PPP$ GDP…………..……..
2.4

ICTs & business model creation†………………………....…….
74.9

ICTs & organizational model creation †…………………….... 72.2

38
55
47
18
16

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
30.9
Cultural & creative services exports, % total trade…....
1.4
National feature films/mn pop. 15-69………………….………
10.9
Entertainment & Media market/th pop. 15-69…………….
53.9
🕘🕘Printing & other media, % manufacturing…...................
1.3
Creative goods exports, % total trade………………………..
1.6

27
18
14
14
38
34

7.3
7.3.1
7.3.2
7.3.3
7.3.4


24.9
Online creativity………………………………………..……….…….

21.2
Generic top-level domains (TLDs)/th pop. 15-69……….

56.0
Country-code TLDs/th pop. 15-69…………………..………….

30.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
1.8

29
◇
27
13 ●
39
62 ○ ◇NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
228

The Global Innovation Index 2019

◇

BENINGII 2019 rank

123

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

125

114

Low

SSF

11.5

27.5

2,426.5

n/aScore/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
19.9 [121]
INSTITUTIONS………………………………….…….…..
56.6

87

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
42.3
Political and operational stability*……………..………….….
64.9
Government effectiveness*…………………………..…………. 30.9

98
79
109

1.2
1.2.1
1.2.2
1.2.3


62.0
Regulatory environment……………………………..………..

29.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
29.8

11.6
Cost of redundancy dismissal, salary weeks…………..

74 ●
102
98
37 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
65.6
Ease of starting a business*………………………………..……
90.6

Ease of resolving insolvency*……………………………….…. 40.7

80
52 ●
97
21.1
HUMAN CAPITAL & RESEARCH………………...

92

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


36.8
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.0
Government funding/pupil, secondary, % GDP/cap… 10.8
School life expectancy, years……………….…………….……. 12.6

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.0

96
79
93
85
◆
n/a
38 ● ◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
26.4
🕘🕘Tertiary enrolment, % gross………………………….….……….
12.9
🕘🕘Graduates in science & engineering, %……………….…. 20.7

Tertiary inbound mobility, %....................................... ….
8.3

78
◆
101
59 ●
24 ● ◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

◆

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
INFRASTRUCTURE……………………………….......
27.7 118

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 31.1

ICT access*………………………………………………………….…….
31.4

ICT use*…………………………….....................................…….
8.9

47.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 37.1

118
115
124 ○ ◇
108
114

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
32.5
Electricity output, GWh/mn pop………………………..…….
32.7
Logistics performance*……………………………………………..
32.1
Gross capital formation, % GDP………………………….…….
28.4

72 ●
119 ○
75 ● ◆
25 ●

3.3
3.3.1
3.3.2
3.3.3


19.5 125
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
4.8 110
Environmental performance*…….……………………………… 38.2 120
ISO 14001 environmental certificates/bn PPP$ GDP..
0.1 126 ○

MARKET SOPHISTICATION..………….…………… 32.1 124
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
25.7 106Ease of getting credit*…………………………………..…………..
30.0 115Domestic credit to private sector, % GDP…………...…… 22.7 108
Microfinance gross loans, % GDP……………………….……. 2.2
11 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.0
Ease of protecting minority investors*…………..………….
40.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
30.7 126 ○ ◇Applied tariff rate, weighted avg., %………………………….
17.8 128 ○ ◇
Intensity of local competition†…………………………………… 63.2 89Domestic market scale, bn PPP$……………………………… 27.5 117

[72]
114
n/a
n/a

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
15.2

Knowledge-intensive employment, %...........................
n/a
Firms offering formal training, % firms………………………… 20.0

GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/a🕘🕘Females employed w/advanced degrees, %……………..
0.8

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
19.5 [90]University/industry research collaboration †………………..
30.8 104State of cluster development†.……..………..…………………..
33.4 114
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP………………….. n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
24.9 104
0.0 118 ○Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
3.6 121

1.1 63 ●ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.8 87
Research talent, % in business enterprise……..………….. n/a n/a

[118]
n/a
75
n/a
n/a
109

 5.6 126 ○ ◇KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 6.2 89
Patents by origin/bn PPP$ GDP……………….…………..….…
0.1 108
0.0 99 ○ ◇PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
8.6 55 ● ◆
Citable documents H-index…………………….……….……..….
3.5 109

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


6.6 125
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0 107
Intellectual property receipts, % total trade……………….

0.1 105
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.1 120

FDI net outflows, % GDP…………………………….…………....... 0.3 82

3.9 [124]
n/a n/an/a n/a0.1 100
1.6 95n/a n/a
13.1 124
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
26.0 118

Trademarks by origin/bn PPP$ GDP…………..……….….….
7.0 109Industrial designs by origin/bn PPP$ GDP…………..…….. 0.2 107

ICTs & business model creation†………………………....……. 49.9 105

ICTs & organizational model creation †……………………....
39.2 114

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
🕘🕘
Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.4
Online creativity………………………………………..……….…….

0.6
Generic top-level domains (TLDs)/th pop. 15-69……….

0.0Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.9
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a0.1 [128]
0.0 1 1 1n/a n/an/a n/an/a n/a0.0 128 ○ ◇

111
103
125
106
n/a

◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

229

BOLIVIA (PLURINATIONAL
STATE OF)OF)

GII 2019 rank

110

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

113

102

Lower middle

LCN

11.2

89.4

7,476.9

117

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
24.1 104
INSTITUTIONS………………………………….…….…..
36.8 128 ○ ◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...

Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….

41.1
49.1
37.1

100
122 ○ ◇
94

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

16.1
17.8
14.4
n/a

129 ○ ◇
122 ○ ◇
124 ○ ◇
n/a

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
53.3

64.3
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….…. 42.3

121◇
127 ○ ◇
90


HUMAN CAPITAL & RESEARCH………………...
26.5 [79]

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


51.7
Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
7.3
🕘🕘Government funding/pupil, secondary, % GDP/cap… 18.1
School life expectancy, years……………….…………….……. n/a
PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
20.6

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.2
🕘🕘Researchers, FTE/mn pop……………………………..…...……
166.0
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

[54]
8 ●◆
61
n/a
n/a
91

n/a [n/a]n/a n/an/a n/an/a n/a101
81
93
43 ○ ◇78 ○ ◇
INFRASTRUCTURE……………………………….......
35.1 102

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)

ICT access*………………………………………………………….…….

ICT use*…………………………….....................................…….

Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

51.1
48.4
42.0
56.3
57.9

93
92
85
95
93

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
21.2
Electricity output, GWh/mn pop………………………..…….
864.0

Logistics performance*…………………………………………….. 13.8
Gross capital formation, % GDP………………………….…….
21.5

114
98
115
80

3.3
3.3.1
3.3.2
3.3.3


32.9
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
8.1
Environmental performance*…….………………………………
56.0
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.7

84
75
79
77



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
34.7 71
Knowledge-intensive employment, %...........................
15.8 89Firms offering formal training, % firms………………………… 49.9 21 ●
GERD performed by business, % GDP…………………..…… n/a n/a🕘🕘
GERD financed by business, %……………………………........
5.2 80
Females employed w/advanced degrees, %……………..
8.5 77

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
12.3 125 ○ ◇
University/industry research collaboration †………………..
27.0 116◇State of cluster development†.……..………..…………………..
31.1 118🕘🕘
GERD financed by abroad, %.........................................
1.9 78JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 93
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
25.3

0.9
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.1

ICT services imports, % total trade…………..………………...
0.9

FDI net inflows, % GDP…………………………….………………….
1.5🕘🕘Research talent, % in business enterprise……..…………..
0.4

 14.5 105
KNOWLEDGE & TECHNOLOGY OUTPUTS....

MARKET SOPHISTICATION..………….…………… 49.7

59Credit……………………………………………………….………………
54.9
Ease of getting credit*…………………………………..…………..
35.0
Domestic credit to private sector, % GDP…………...…… 64.5

Microfinance gross loans, % GDP……………………….……. 28.2

26 ● ◆110 ◇49 ●
1●◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.0
Ease of protecting minority investors*…………..………….
40.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[72]
114
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
54.1
Applied tariff rate, weighted avg., %………………………….
6.1
Intensity of local competition†…………………………………… 63.8
Domestic market scale, bn PPP$……………………………… 89.4

91
95
85
83

◇



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 3.8

Patents by origin/bn PPP$ GDP……………….…………..….…
0.7

n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.1
Scientific & technical articles/bn PPP$ GDP….…..…..….
1.6

Citable documents H-index…………………….……….……..….
5.8

110
71
n/a
51
118
91

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


30.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.8
New businesses/th pop. 15-64………………….…....………….
0.5
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..……
2.8
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

93
45 ●
83
51 ●
79
89

6.3
6.3.1
6.3.2
6.3.3
6.3.4


9.2 108
Knowledge diffusion……………………………………..…..…….

0.2 34 ●Intellectual property receipts, % total trade……………….

0.2 100
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.6 94

FDI net outflows, % GDP…………………………….………….......
0.2 92


15.7
CREATIVE OUTPUTS…….…………………….…………

111

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
25.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
41.7
Industrial designs by origin/bn PPP$ GDP…………..……..
0.2

ICTs & business model creation†………………………....……. 39.0

ICTs & organizational model creation †…………………….... 31.7

121
◇
62
103
122 ○ ◇
122 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
11.7 79
Cultural & creative services exports, % total trade…....
0.1 89
National feature films/mn pop. 15-69………………….………
0.9 84Entertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
1.0 64Creative goods exports, % total trade………………………..
1.3 39 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

◇

4.1
4.1.1
4.1.2
4.1.3

99
40 ● ◆
41 ●78
96
84 ○

1.2 100
1.8 800.5 95
3.5 92
0.1 88NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
230

The Global Innovation Index 2019

BOSNIA AND HERZEGOVINAGII 2019 rank

76

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

79

71

Upper middle

EUR

3.5

47.3

13,491.0

77

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
26.5 88


INSTITUTIONS………………………………….…….…..
58.9

79

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
44.3
Political and operational stability*……………..………….….
63.2
Government effectiveness*…………………………..…………. 34.9

94
86
96

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

68.7
37.9
40.8
9.2

59
82
73
24 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
63.7
Ease of starting a business*………………………………..……
59.6

Ease of resolving insolvency*……………………………….…. 67.8

87
128 ○ ◇
34 ● ◆


42.0
HUMAN CAPITAL & RESEARCH………………...

37

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


92.2
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
n/aGovernment funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. n/a
PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
9.3

[1]
n/a
n/a
n/a
n/a
21 ●

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
29.7
Tertiary enrolment, % gross………………………….….……….
n/a
Graduates in science & engineering, %……………….….
20.3

Tertiary inbound mobility, %.......................................
….
7.1

71
n/a
64
31

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
4.1
Researchers, FTE/mn pop……………………………..…...……
463.9
Gross expenditure on R&D, % GDP………….………..……

79
70
89
43 ○ ◇67


Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.2
0.0
7.0


INFRASTRUCTURE……………………………….......
35.3 100

◇
◇

◆

◆

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  50.1

ICT access*………………………………………………………….…….
65.8

ICT use*…………………………….....................................…….
48.1

43.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
43.3

95
66
74
112 ○ ◇
109 ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
25.5
Electricity output, GWh/mn pop………………………..…….
5,047.4
Logistics performance*…………………………………………….. 34.8
Gross capital formation, % GDP………………………….…….

17.2

99
43
71
108 ○

3.3
3.3.1
3.3.2
3.3.3


30.4
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
5.6

Environmental performance*…….………………………………
41.8
ISO 14001 environmental certificates/bn PPP$ GDP.. 5.592◇
102 ◇
117 ○ ◇
20 ●


49.3
MARKET SOPHISTICATION..………….……………

62

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
34.3
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...……
54.4

Microfinance gross loans, % GDP……………………….…….
0.8

71
54
59
25

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 58.3
Ease of protecting minority investors*…………..………….
58.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[22]
68
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
55.1
Applied tariff rate, weighted avg., %………………………….
2.5
†Intensity of local competition …………………………………… 61.9
Domestic market scale, bn PPP$……………………………… 47.3

88
60
97
97

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
37.8
Knowledge-intensive employment, %...........................
22.1
Firms offering formal training, % firms………………………… 52.4

GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
29.1
Females employed w/advanced degrees, %……………..
6.9

59
68
16 ●
67
62
81

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
21.9
University/industry research collaboration †………………..
27.2
State of cluster development†.……..………..…………………..
37.4

GERD financed by abroad, %.........................................
16.4
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

72
114 ○ ◇
97
23 ●
58
93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
19.8 125 ○ ◇
0.1 97
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.0 106

ICT services imports, % total trade…………..………………...
0.6 101
FDI net inflows, % GDP…………………………….………………….
2.2 79Research talent, % in business enterprise……..…………..
7.2 66

 21.8 65
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 8.2

Patents by origin/bn PPP$ GDP……………….…………..….…
1.9

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
8.0

Citable documents H-index…………………….……….……..…. 3.3

79
46
66
n/a
58
1 1 1 ○

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


42.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.7
New businesses/th pop. 15-64………………….…....………….
1.1
Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 25.4
High- & medium-high-tech manufactures, %………………
0.2

41
15 ●
67
92
8 ●◆
64

6.3
6.3.1
6.3.2
6.3.3
6.3.4


15.3
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

2.4
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.8

FDI net outflows, % GDP…………………………….………….......
0.4

76
42
50
60
75


19.0
CREATIVE OUTPUTS…….…………………….…………

99

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
27.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
16.5
Industrial designs by origin/bn PPP$ GDP…………..……..
2.4

ICTs & business model creation†………………………....…….
44.0
ICTs & organizational model creation †…………………….... 39.0

115 ○ ◇
92
46
116 ○ ◇
115 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
13.2 74

Cultural & creative services exports, % total trade…....
0.0 96
National feature films/mn pop. 15-69………………….………
7.3 26 ● ◆Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.2 53Creative goods exports, % total trade………………………..
0.4 67

7.3
7.3.1
7.3.2
7.3.3
7.3.4


8.3
Online creativity………………………………………..……….…….

2.7
Generic top-level domains (TLDs)/th pop. 15-69……….

2.3
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
41.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.1

◆

56
69
64
34 ● ◆
80◇NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

231

BOTSWANA

GII 2019 rank

93

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

117

80

Upper middle

SSF

2.3

41.8

17,965.4

91

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
65.7

58

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
66.0
Political and operational stability*……………..………….….
84.2
Government effectiveness*…………………………..…………. 56.8

43
◆
25 ● ◆
◆
46

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

56
47
41
85

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
62.1
Ease of starting a business*………………………………..……
76.2

Ease of resolving insolvency*……………………………….…. 48.0

93
116 ○
73


28.2
HUMAN CAPITAL & RESEARCH………………...

73

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


67.5
Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
9.6
🕘🕘Government funding/pupil, secondary, % GDP/cap… 36.4
🕘🕘School life expectancy, years……………….…………….……. 12.2

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
n/a

[7]
1 ●◆
6 ●◆
89
◇
n/a
n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
13.8 102

Tertiary enrolment, % gross………………………….….……….
23.0
89

Graduates in science & engineering, %……………….….
n/a n/a
Tertiary inbound mobility, %....................................... ….
2.7
69

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
3.4
🕘🕘Researchers, FTE/mn pop……………………………..…...……
179.5
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.5

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

69.0
54.4
60.0
20.6

◆

◇
◇

85
80
57
43 ○ ◇78 ○ ◇
INFRASTRUCTURE……………………………….......
35.2 101

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 32.4

ICT access*………………………………………………………….…….
52.5

ICT use*…………………………….....................................…….
36.8

20.8
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
19.7

116 ○ ◇
8494
◇126 ○ ◇
125 ○ ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
34.0
Electricity output, GWh/mn pop………………………..…….
1,194.7
Logistics performance*……………………………………………..
n/a
Gross capital formation, % GDP………………………….…….
28.3

68
91 ◇
n/a
26 ●

3.3
3.3.1
3.3.2
3.3.3


39.2
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
13.3
Environmental performance*…….………………………………
51.7
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.4

62
19 ●
92
◇
93



MARKET SOPHISTICATION..………….…………… 49.0

63

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
34.0
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...…… 31.4

Microfinance gross loans, % GDP……………………….…….
n/a

73
77
93
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 56.7
Ease of protecting minority investors*…………..………….
56.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[27]
79
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
56.3
Applied tariff rate, weighted avg., %………………………….
1.1
Intensity of local competition†…………………………………… 61.7
Domestic market scale, bn PPP$……………………………… 41.8

85
11 ●
100 ◇
104


BUSINESS SOPHISTICATION..……….……………
26.2

91

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
34.4
🕘🕘
Knowledge-intensive employment, %...........................
17.8
🕘🕘Firms offering formal training, % firms………………………… 51.9
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1
🕘🕘
GERD financed by business, %……………………………........
17.7
🕘🕘Females employed w/advanced degrees, %……………..
9.1

73
82
17 ●
61
71
71

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
24.3 68

University/industry research collaboration †………………..
34.7 94◇State of cluster development†.……..………..…………………..
34.5 108🕘🕘
GERD financed by abroad, %.........................................
17 ● ◆
21.7
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 67
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
19.8 123 ○ ◇
0.1 94
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
3.6 122 ○
ICT services imports, % total trade…………..………………...
1.0 70
FDI net inflows, % GDP…………………………….………………….
2.6 66🕘🕘◇
Research talent, % in business enterprise……..………….. 1.0 76

 13.7 107
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


25.9 [105]Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
n/a n/a
New businesses/th pop. 15-64………………….…....………….
18.4
3 ● ◆

Computer software spending, % GDP…………..…………… 0.1 85
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.5 121 ○High- & medium-high-tech manufactures, %………………
n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


11.0
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

0.8
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.3

FDI net outflows, % GDP…………………………….………….......
1.7

4.1 105
0.1 117 ○
0.0 99 ○ ◇0.1 525.9
71
4.5 98

98
93
71
110
36 ●


14.3 118 ○ ◇CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
27.4 114
Trademarks by origin/bn PPP$ GDP…………..……….….….
11.9 100🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.3 93
†
ICTs & business model creation ………………………....……. 49.4 107

ICTs & organizational model creation †…………………….... 41.9 108

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
🕘🕘
Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.8
Online creativity………………………………………..……….…….

1.1
Generic top-level domains (TLDs)/th pop. 15-69……….

1.2
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

1.6 [118]
0.0 106
n/a n/an/a n/an/a n/a0.2 86

101
93
77
110
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
232

The Global Innovation Index 2019

◇

◇
◇

BRAZILGII 2019 rank

66

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

67

60

Upper middle

LCN

210.9

3,370.6

16,154.3

64

Score/Value Rank

INSTITUTIONS………………………………….…….…..

58.9

80

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
48.6

Political and operational stability*……………..………….….
66.7
Government effectiveness*…………………………..………….
39.6

88
74
87

1.2
1.2.1
1.2.2
1.2.3


63.8
Regulatory environment……………………………..………..

38.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
38.9

15.4
Cost of redundancy dismissal, salary weeks…………..

72
76
78
62

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
64.4

80.2
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….….
48.5

83
106 ○
69


36.0
HUMAN CAPITAL & RESEARCH………………...

48

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


50.1
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
6.2
Government funding/pupil, secondary, % GDP/cap… 21.7
🕘🕘
School life expectancy, years……………….…………….……. 15.3

PISA scales in reading, maths, & science…………......…
395.0
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
16.6

59
18 ● ◆
44
44
64 ○
73

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
22.3
🕘🕘Tertiary enrolment, % gross………………………….….……….
50.5
Graduates in science & engineering, %……………….….
17.7
Tertiary inbound mobility, %.......................................
….
0.2

85
56
75
105 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
35.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
881.4
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
1.3

61.5
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
43.0

32
◆
53
28 ● ◆
22 ● ◆
25 ● ◆
INFRASTRUCTURE……………………………….......
46.8

64

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  77.9

ICT access*………………………………………………………….…….
61.9

ICT use*…………………………….....................................…….
60.2

92.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

36
◆
72
57
22 ● ◆
12 ● ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
24.4
Electricity output, GWh/mn pop………………………..…….
2,787.8
Logistics performance*…………………………………………….. 43.1
Gross capital formation, % GDP………………………….…….

3.3
3.3.1
3.3.2
3.3.3


38.2
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
10.0

Environmental performance*…….………………………………
60.7
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.9

65
52
62
68


44.2
MARKET SOPHISTICATION..………….……………

84

97.2

102 ○
64
55
16.1 115 ○ ◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
25.8 105 ○Ease of getting credit*…………………………………..…………..
50.0 87Domestic credit to private sector, % GDP…………...……
59.7 56
Microfinance gross loans, % GDP……………………….…….
0.0 74 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.8
Ease of protecting minority investors*…………..………….
65.0

Market capitalization, % GDP………………………………...….
38.6
Venture capital deals/bn PPP$ GDP……………….……....
0.0

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
70.1 33
Applied tariff rate, weighted avg., %………………………….
8.6 104 ○ ◇Intensity of local competition†……………………………………
68.2 67
8 ●◆Domestic market scale, bn PPP$………………………...… 3,370.6

91
45
40
61 ○

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
37.6

40

◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
46.3 42Knowledge-intensive employment, %...........................
23.1 65🕘🕘Firms offering formal training, % firms…………………………
42.2 30
GERD performed by business, % GDP…………………..……
n/a n/a
GERD financed by business, %……………………………........
45.0 35
Females employed w/advanced degrees, %…………….. 12.5 55

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
25.0

University/industry research collaboration †………………..
42.5
State of cluster development†.……..………..…………………..
49.7
GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

66
58
50
n/a
82
55

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
41.7

2.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.1

ICT services imports, % total trade…………..………………...
1.6

FDI net inflows, % GDP…………………………….………………….
4.0
🕘🕘
Research talent, % in business enterprise……..…………..
26.6

◆
36
10 ● ◆
28 ●
35
41
45

 23.0 58
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 19.8
Patents by origin/bn PPP$ GDP……………….…………..….…
1.7

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.9
Scientific & technical articles/bn PPP$ GDP….…..…..….
9.7
Citable documents H-index…………………….……….……..…. 36.3

47
50
53
25
50
24 ● ◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


31.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.3
New businesses/th pop. 15-64………………….…....………….
0.1
Computer software spending, % GDP…………..……………
0.2
ISO 9001 quality certificates/bn PPP$ GDP…………..……
5.4
🕘🕘High- & medium-high-tech manufactures, %………………
0.3

86
96 ○
98 ○
74
58
32

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.4
Knowledge diffusion……………………………………..…..…….

0.3Intellectual property receipts, % total trade……………….

4.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.9

FDI net outflows, % GDP…………………………….………….......
0.6

66
31
32
84
63


22.8
CREATIVE OUTPUTS…….…………………….…………

82

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
38.9
Trademarks by origin/bn PPP$ GDP…………..……….….….
49.0
Industrial designs by origin/bn PPP$ GDP…………..……..
1.1

ICTs & business model creation†………………………....…….
61.1

ICTs & organizational model creation †……………………....
52.6

73
50
64
57
69

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

94
50
81
39
◆
86 ○
77

7.3
7.3.1
7.3.2
7.3.3
7.3.4


6.4
Online creativity………………………………………..……….…….

1.5
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 7.2

6.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
12.7

7.0
0.5
1.0
8.5
0.6
0.2

◆

61
87
44
71
36

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

233

BRUNEI DARUSSALAM

GII 2019 rank

71

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

120

35

High

SEAO

0.4

35.5

79,529.967

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
36.0 45
INSTITUTIONS………………………………….…….…..
78.9

27

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
80.5

Political and operational stability*……………..………….….
93.0
Government effectiveness*…………………………..…………. 74.3

21 ●
7 ● ◆
26 ●

1.2
1.2.1
1.2.2
1.2.3


81.2
Regulatory environment……………………………..………..

61.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
63.5

8.0
Cost of redundancy dismissal, salary weeks…………..

27
38
37
1 ●◆

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
75.0
Ease of starting a business*………………………………..……
94.9
Ease of resolving insolvency*……………………………….…. 55.1

45
14 ●
59
33.3
HUMAN CAPITAL & RESEARCH………………...

55

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


50.2
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.4
Government funding/pupil, secondary, % GDP/cap… 23.8
School life expectancy, years……………….…………….……. 14.4

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
8.7

58
63
30
64
◇
n/a
13 ●

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
39.8
Tertiary enrolment, % gross………………………….….……….
32.9
🕘🕘Graduates in science & engineering, %……………….….
30.5
Tertiary inbound mobility, %....................................... ….
3.8

39
79
◇
11 ● ◆
56

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

[57]
n/a
n/a
43 ○ ◇
53

9.8
n/a
n/a
0.0
19.6

◇


INFRASTRUCTURE……………………………….......
50.4

52

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 69.9

ICT access*………………………………………………………….…….
76.6

ICT use*…………………………….....................................…….
70.3

72.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
60.7

58
39
33
67
92

◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
41.9
Electricity output, GWh/mn pop………………..……..……. 10,166.7

Logistics performance*…………………………………………….. 30.1
Gross capital formation, % GDP………………………….…….
29.1

41
14 ●
79◇
23 ● ◆

3.3
3.3.1
3.3.2
3.3.3


39.3
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
10.1
Environmental performance*…….………………………………
63.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.8

60
49
48
71



◇
◇

◇

MARKET SOPHISTICATION..………….…………… 60.1

17 ●

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
58.5
Ease of getting credit*…………………………………..…………..
100.0

Domestic credit to private sector, % GDP…………...…… 39.5

Microfinance gross loans, % GDP……………………….…….
n/a

20 ●
1 ●◆
84 ◇
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 65.0Ease of protecting minority investors*…………..………….
65.0

Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[15]
45
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
56.7
Applied tariff rate, weighted avg., %………………………….
0.0
Intensity of local competition†…………………………………… 61.2
Domestic market scale, bn PPP$……………………………… 35.5

84
◇
2●◆
104 ◇
110 ○ ◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
60.1

Knowledge-intensive employment, %...........................
40.6
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..……
n/a
GERD financed by business, %……………………………........
n/aFemales employed w/advanced degrees, %……………..
12.0

[24]
26
n/a
n/a
n/a
59

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
21.7
University/industry research collaboration †………………..
37.3
State of cluster development†.……..………..…………………..
41.5
GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

76
◇
◇
86
◇
87
n/a
60
93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
26.3

0.5
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.1

ICT services imports, % total trade…………..………………...
0.8

FDI net inflows, % GDP…………………………….………………….
1.3
Research talent, % in business enterprise……..…………..
n/a

97
68
92
86
99
n/a

The Global Innovation Index 2019◇ 8.9 120 ○ ◇KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

2.7 117 ○ ◇0.2 92
0.0 83◇n/a n/a3.1 102◇
1.9 119 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……
🕘🕘
High- & medium-high-tech manufactures, %………………

6.2 [119]n/a n/a2.5 44n/a n/a3.2 76
0.0 101 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.7
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….

3.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.0

FDI net outflows, % GDP…………………………….………….......
1.6

62
n/a
44
128 ○ ◇39

17.0 107
CREATIVE OUTPUTS…….…………………….…………

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
30.4 105◇
Trademarks by origin/bn PPP$ GDP…………..……….….….
5.2 116 ○ ◇Industrial designs by origin/bn PPP$ GDP…………..……..
0.0 117 ○ ◇
ICTs & business model creation†………………………....…….
58.0
74 ◇

ICTs & organizational model creation †…………………….... 47.5 89
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


4.0
Online creativity………………………………………..……….…….

7.5
Generic top-level domains (TLDs)/th pop. 15-69……….

0.8
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
5.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

3.3 [109]
0.0 119 ○ ◇n/a n/an/a n/a0.5 93 ○ ◇0.2 91

68
45
83
79
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
234

◇

◇
◇
◇

BULGARIA

GII 2019 rank

40

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

38

45

Upper middle

EUR

7.0

162.7

23,155.6

37

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
68.3

48

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
58.1

68.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 52.9

59
71
52

1.2
1.2.1
1.2.2
1.2.3


75.5
Regulatory environment……………………………..………..

58.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
45.3

8.6
Cost of redundancy dismissal, salary weeks…………..

◆
37
43
◆
66
17 ●

1.3
1.3.1
1.3.2


71.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
85.4

Ease of resolving insolvency*……………………………….…. 57.5

60
76
51


30.6
HUMAN CAPITAL & RESEARCH………………...

62

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


47.0
Education…………………………………………………………..……
🕘🕘
4.1
Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 21.7

School life expectancy, years……………….…………….……. 14.8

PISA scales in reading, maths, & science…………......…
439.6
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.6

68
77 ○
43
56
45 ○
52

2.2
2.2.1
2.2.2
2.2.3


33.1
Tertiary education……………………………………….……..….
🕘🕘
71.2
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
19.7
Tertiary inbound mobility, %.......................................….
4.6

58
26
◆
67 ○
44

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
11.7
………………………..…....…… 2,130.5
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
0.8

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
4.7

51
38
◆
47
43 ○ ◇68


53.7
INFRASTRUCTURE……………………………….......

39

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  74.9

ICT access*………………………………………………………….…….
70.3

ICT use*…………………………….....................................…….
65.8

76.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
87.1

45
62
42
54
35

◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
33.9
 …………………..…….
Electricity output, GWh/mn pop……
6,262.4
Logistics performance*…………………………………………….. 45.4
Gross capital formation, % GDP………………………….…….
21.5

69
33 ◆
51
82 ○

3.3
3.3.1
3.3.2
3.3.3


52.2
Ecological sustainability………………………………………..

6.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
67.9
ISO 14001 environmental certificates/bn PPP$ GDP.. 11.9

21 ● ◆88 ○29 ◆
2 ● ◆



MARKET SOPHISTICATION..………….…………… 47.5 66
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
31.8
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...…… 50.6
Microfinance gross loans, % GDP……………………….…….
0.4

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 47.1
Ease of protecting minority investors*…………..………….
68.3
🕘🕘Market capitalization, % GDP………………………………...….
15.2
Venture capital deals/bn PPP$ GDP……………….……....
n/a

46
30
64 ○
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
63.7
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 65.1
Domestic market scale, bn PPP$……………………………… 162.7

56
23
81 ○
69



84 ○
54
67
32


BUSINESS SOPHISTICATION..……….……………
40.3

34

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
48.9
Knowledge-intensive employment, %...........................
31.4
Firms offering formal training, % firms………………………… 42.7

GERD performed by business, % GDP…………………..…… 0.5

GERD financed by business, %……………………………........
43.6
Females employed w/advanced degrees, %……………..
19.2

39
42
29
38
39
26

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


36.3
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
40.2
State of cluster development†.……..………..…………………..
46.8
GERD financed by abroad, %......................................... 34.2
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP……………………..
0.2

◆
37
69
61
10 ● ◆
35
◆
44

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
35.7

0.5
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.7

1.1
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….…………………. 4.0
Research talent, % in business enterprise……..………….. 43.4

52
60
78 ○
65
42
29
◆

 31.4KNOWLEDGE & TECHNOLOGY OUTPUTS....

37



◆
◆

◆

◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 17.8

1.5
Patents by origin/bn PPP$ GDP……………….…………..….…

0.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 1.7
Scientific & technical articles/bn PPP$ GDP….…..…..….
10.0

Citable documents H-index…………………….……….……..….
14.4

51
54
41
14 ●
49
50

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


54.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.9
New businesses/th pop. 15-64………………….…....………….
10.9
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..……
35.3
High- & medium-high-tech manufactures, %………………
0.2

9 ● ◆
26
11 ● ◆54
2 ● ◆
48

6.3
6.3.1
6.3.2
6.3.3
6.3.4


21.7
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

3.8
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.0

FDI net outflows, % GDP…………………………….………….......
1.1

44
44
38
31
51


33.8
CREATIVE OUTPUTS…….…………………….…………

41

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
49.9
Trademarks by origin/bn PPP$ GDP…………..……….….….
98.6
Industrial designs by origin/bn PPP$ GDP…………..……..
8.1

ICTs & business model creation†………………………....……. 58.0

ICTs & organizational model creation†…………………….... 53.7

37
12 ●
15 ● ◆75 ○
64

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
19.3 57

Cultural & creative services exports, % total trade…....
1.4 19 ●
National feature films/mn pop. 15-69………………….………
4.8 44Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.2 48Creative goods exports, % total trade……………………….. 0.8 49

7.3
7.3.1
7.3.2
7.3.3
7.3.4


16.0
Online creativity………………………………………..……….…….

22.9
Generic top-level domains (TLDs)/th pop. 15-69……….

3.3
Country-code TLDs/th pop. 15-69…………………..………….

46.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
7.0

◆

◆

40
◆
25 ● ◆
59
30
◆
45

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

235

BURKINA FASO

GII 2019 rank

117

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

115

111

Low

SSF

19.8

38.8

1,996.1

124

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
23.3 111
INSTITUTIONS………………………………….…….…..
56.4

88

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
40.2

56.1
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 32.3

103
105
102

1.2
1.2.1
1.2.2
1.2.3


64.5
Regulatory environment……………………………..………..

30.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
35.7

10.5
Cost of redundancy dismissal, salary weeks…………..

68 ●
100
86
33 ●

1.3
1.3.1
1.3.2


64.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
88.2

Ease of resolving insolvency*……………………………….…. 40.9

81
64 ●
94
14.4 110
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


29.4 109
Education…………………………………………………………..……

4.2
73 ●
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 17.6 65
School life expectancy, years……………….…………….……. 8.9 112 ○
PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
23.3 95

2.2
2.2.1
2.2.2
2.2.3


12.6 105
Tertiary education……………………………………….……..….

6.0 116 ○Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
15.4
87
🕘🕘
Tertiary inbound mobility, %.......................................
….
2.9 65 ●

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.2 102🕘🕘Researchers, FTE/mn pop……………………………..…...……
91
47.6
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
87
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……
43 ○ ◇
QS university ranking, average score top 3*……………
0.0
78 ○ ◇
31.2 110INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 40.8 103

ICT access*………………………………………………………….…….
32.4 114

ICT use*…………………………….....................................…….
14.9 116
53.5 101
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
62.4 84

◆



3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 23.8 106
 …………………..…….
Electricity output, GWh/mn pop……
n/a n/a
Logistics performance*……………………………………………..
26.1 86Gross capital formation, % GDP………………………….……. 16.3 114

3.3
3.3.1
3.3.2
3.3.3


29.0 104
Ecological sustainability………………………………………..
n/a n/aGDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
42.8 116
ISO 14001 environmental certificates/bn PPP$ GDP..  0.2 117


MARKET SOPHISTICATION..………….…………… 36.2 116

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
24.9 108Ease of getting credit*…………………………………..…………..
30.0 115Domestic credit to private sector, % GDP…………...……
31.3 94Microfinance gross loans, % GDP……………………….…….
14 ●
1.8

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.0
Ease of protecting minority investors*…………..………….
40.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
43.7 122 ○
Applied tariff rate, weighted avg., %………………………….
9.1 108
†
Intensity of local competition …………………………………… 57.7 116Domestic market scale, bn PPP$………………………………
38.8 106

[72]
114 ○
n/a
n/a

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
18.1 [111]Knowledge-intensive employment, %...........................
n/a n/a🕘🕘
Firms offering formal training, % firms…………………………
24.8 65
GERD performed by business, % GDP…………………..…… n/a n/a🕘🕘
GERD financed by business, %……………………………........
◆
11.9 72
🕘🕘Females employed w/advanced degrees, %……………..
0.5 112 ○

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.1 105
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
31.9 99State of cluster development†.……..………..…………………..
33.3 115🕘🕘
GERD financed by abroad, %.........................................
1.5 86
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 86

Patent families 2+ offices/bn PPP$ GDP…………………….. n/a n/a

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
33.8

0.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.4

2.2
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.3
Research talent, % in business enterprise……..…………..
n/a

63 ●
117 ○
112
21 ●
51 ●
n/a

 15.1 98
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 4.9 100

0.2 103
Patents by origin/bn PPP$ GDP……………….…………..….…
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……
🕘🕘
Utility models by origin/bn PPP$ GDP……………...…..……
0.1 50
Scientific & technical articles/bn PPP$ GDP….…..…..…. 5.5 75 ●
Citable documents H-index…………………….……….……..…. 4.8 95

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


31.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.5
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.2
Computer software spending, % GDP…………..……………
0.0
ISO 9001 quality certificates/bn PPP$ GDP…………..……
1.6
High- & medium-high-tech manufactures, %……………… n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


9.3 106
Knowledge diffusion……………………………………..…..…….

0.0 80Intellectual property receipts, % total trade……………….

0.1 106
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.2 74 ●
FDI net outflows, % GDP…………………………….………….......
0.3
81

90
36 ●
95
114
93
n/a


13.5 120
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
26.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
5.7
Industrial designs by origin/bn PPP$ GDP…………..……..
0.5

ICTs & business model creation†………………………....…….
50.0

ICTs & organizational model creation†……………………....
39.5

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.0
Online creativity………………………………………..……….…….

0.1
Generic top-level domains (TLDs)/th pop. 15-69……….

0.0Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

117
114
84
104
112

1.2 [122]
0.1 790.5 95n/a n/an/a n/a0.0 119
127 ○
124 ○
124 ○
125 ○
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
236

The Global Innovation Index 2019

◇

BURUNDI

GII 2019 rank

128

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

126

128

Low

SSF

10.9

8.0

735.2

n/a

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
45.6 123
BUSINESS SOPHISTICATION..……….……………
29.3 74

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
22.8

40.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 14.1

128 ○ ◇128 ○128 ○ ◇

1.2
1.2.1
1.2.2
1.2.3


51.2
Regulatory environment……………………………..………..

19.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
9.5

15.9
Cost of redundancy dismissal, salary weeks…………..

108
118
128 ○ ◇
66 ●

1.3
1.3.1
1.3.2


62.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
94.8

Ease of resolving insolvency*……………………………….…. 30.6

92
15 ● ◆117◇
17.7 103
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


38.7
Education…………………………………………………………..……

4.3
Expenditure on education, % GDP………………….…….….
🕘🕘 28.0
Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….……. 11.3

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
28.0

88
68
15 ●
95
n/a
103

2.2
2.2.1
2.2.2
2.2.3


13.8
Tertiary education……………………………………….……..….

6.2
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
16.2
Tertiary inbound mobility, %.......................................
….
2.9

101
115
80
66

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.8 109n/a n/a0.1 100
0.0
43 ○ ◇
0.0
78 ○ ◇
14.0 129 ○ ◇
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 22.9 126

ICT access*………………………………………………………….…….
24.0 122
ICT use*…………………………….....................................…….
6.1 126 ○ ◇
30.6 119Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
30.9 119

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
 …………………..…….
Electricity output, GWh/mn pop……

Logistics performance*……………………………………………..

Gross capital formation, % GDP………………………….…….

3.3
3.3.1
3.3.2
3.3.3


18.9 128 ○
Ecological sustainability………………………………………..
n/a n/aGDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
27.4 127 ○ ◇ISO 14001 environmental certificates/bn PPP$ GDP..  0.2 108

0.2 129 ○ ◇n/a n/a0.0 122 ○ ◇
6.0 124 ◇

MARKET SOPHISTICATION..………….…………… 26.1 129 ○ ◇
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
6.1 128 ○ ◇Ease of getting credit*…………………………………..…………..
10.0 126 ◇Domestic credit to private sector, % GDP…………...……
15.5 115🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.2 42 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 43.3 [61]Ease of protecting minority investors*…………..………….
43.3 105Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
28.8 128 ○ ◇🕘🕘Applied tariff rate, weighted avg., %………………………….
5.9 94
†
Intensity of local competition …………………………………… 48.5 124◇Domestic market scale, bn PPP$……………………………… 8.2 129 ○ ◇



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
16.0 [115]Knowledge-intensive employment, %...........................
2.3 114Firms offering formal training, % firms…………………………
32.0 47 ●
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %……………..
0.2 116

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


38.7 30 ●Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
33.8 96State of cluster development†.……..………..…………………..
35.1 106🕘🕘
7 ●GERD financed by abroad, %.........................................
39.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.5 33 ● ◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
33.1

0.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.0

1.6
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
0.5
Research talent, % in business enterprise……..………….. n/a

65 ●
116
44 ●
37 ●
118n/a

 4.8 [127] ◇
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 3.8 [112]
n/a n/aPatents by origin/bn PPP$ GDP……………….…………..….…
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
4.3 89
Citable documents H-index…………………….……….……..…. 0.0 128 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……
🕘🕘
High- & medium-high-tech manufactures, %………………

3.6 [126]n/a n/an/a n/a0.1 96
0.5 120
0.0 97

6.3
6.3.1
6.3.2
6.3.3
6.3.4


Knowledge diffusion……………………………………..…..…….
Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………

FDI net outflows, % GDP…………………………….………….......

7.1 122
0.0 980.0 120
0.6 96
0.0 113
12.7 125
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
24.0 123
Trademarks by origin/bn PPP$ GDP…………..……….….….
6.6 1 1 1
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a n/a
ICTs & business model creation†………………………....…….
37.3 123
ICTs & organizational model creation†…………………….... 33.3 121

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.1 126
Online creativity………………………………………..……….…….

0.0 127
Generic top-level domains (TLDs)/th pop. 15-69……….

0.1 114
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.1 122
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a◇

2.6 [112]
0.3 66 ●
0.8 89n/a n/an/a n/a0.1 109

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

237

CAMBODIAGII 2019 rank

98

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

84

104

Lower middle

SEAO

16.2

70.3

4,334.7

98

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
49.6 112
BUSINESS SOPHISTICATION..……….……………
23.5 109

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
45.0

73.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 30.7

93
50 ● ◆
110

1.2
1.2.1
1.2.2
1.2.3


53.1
Regulatory environment……………………………..………..

28.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
18.4

19.4
Cost of redundancy dismissal, salary weeks…………..

104
104
122
80

1.3
1.3.1
1.3.2


50.6
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
52.8
Ease of resolving insolvency*……………………………….…. 48.4

125 ○ ◇
129 ○ ◇71


11.2 120
HUMAN CAPITAL & RESEARCH………………...

◇

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


17.8 [126]
Education…………………………………………………………..……
🕘🕘
1.9
117 ○ ◇
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a n/a🕘🕘
School life expectancy, years……………….…………….……. 10.6 101
PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
n/a n/a

2.2
2.2.1
2.2.2
2.2.3


15.2 100
Tertiary education……………………………………….……..….

13.1 100
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….
15.4 86

Tertiary inbound mobility, %.......................................
….
n/a n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
30.4
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

113
100 ○
102
43 ○ ◇78 ○ ◇
26.5 123 ○ ◇
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 29.5

ICT access*………………………………………………………….…….
41.6

ICT use*…………………………….....................................…….
34.1

25.0
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
17.4

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
23.9 105
 …………………..…….
Electricity output, GWh/mn pop……
354.9 1 1 1
Logistics performance*…………………………………………….. 24.1 93
Gross capital formation, % GDP………………………….…….
22.0 76

3.3
3.3.1
3.3.2
3.3.3


26.0
Ecological sustainability………………………………………..

7.0
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
43.2
ISO 14001 environmental certificates/bn PPP$ GDP..  0.7

121 ◇
102
96
123 ○ ◇126 ○ ◇

112
85
115
78


MARKET SOPHISTICATION..………….…………… 56.8 30 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
73.6
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...……
86.7

Microfinance gross loans, % GDP……………………….…….
7.5

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 50.0 [39]Ease of protecting minority investors*…………..………….
50.0 93Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
46.7 114
🕘🕘
111
Applied tariff rate, weighted avg., %………………………….
9.8

†Intensity of local competition …………………………………… 59.6 108
Domestic market scale, bn PPP$………………………………
91
70.3

8 ● ◆
20 ●32 ● ◆
1 ● ◆



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
13.2 120🕘🕘
Knowledge-intensive employment, %...........................
5.3 107
Firms offering formal training, % firms…………………………
22.2 70🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 81🕘🕘
GERD financed by business, %……………………………........
19.4 67
🕘🕘Females employed w/advanced degrees, %……………..
1.1 107

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


36.9
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
37.4
State of cluster development†.……..………..…………………..
52.2
🕘🕘GERD financed by abroad, %.........................................
34.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


◇
Knowledge absorption……………………………………..……..
20.4 122
0.1 102Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
2.7 125 ○ ◇
0.6 97
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
11.7 10 ● ◆🕘🕘Research talent, % in business enterprise……..…………..
4.3 7235 ● ◆85
44 ●
9 ● ◆
33 ●
93 ○ ◇ 19.6 [75]KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
🕘🕘
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


46.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
4.9
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..……………
0.0
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 2.4
High- & medium-high-tech manufactures, %………………
n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


9.1 109
Knowledge diffusion……………………………………..…..…….

0.0 92
Intellectual property receipts, % total trade……………….
🕘🕘
1.1 65High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.4 105

FDI net outflows, % GDP…………………………….………….......
0.5 693.6 [114]
0.0 121 ○n/a n/an/a n/a2.3 109
4.3 99[25]
9 ● ◆
n/a
115
◇
82
n/a


19.8
CREATIVE OUTPUTS…….…………………….…………

97

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
37.1
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
23.4
🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.2

ICTs & business model creation†………………………....…….
60.1

ICTs & organizational model creation†……………………....
60.6

83
83
106
66
41 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
🕘🕘
Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.6 107
Online creativity………………………………………..……….…….

0.8 99Generic top-level domains (TLDs)/th pop. 15-69……….

0.0 121
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
1.8 100
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.3 744.4 [105]
0.0 112
3.2 55n/a n/an/a n/a0.3 76◇◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
238

The Global Innovation Index 2019◇◇

CAMEROON

GII 2019 rank

115

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

106

112

Lower middle

SSF

24.7

95.1

3,828.2

111

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
23.9 106
INSTITUTIONS………………………………….…….…..
49.6

111

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
36.5

56.1
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 26.7

118
105
118

1.2
1.2.1
1.2.2
1.2.3


50.8
Regulatory environment……………………………..………..

19.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
19.3

19.9
Cost of redundancy dismissal, salary weeks…………..

110
117
120
82

1.3
1.3.1
1.3.2


61.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
86.3

Ease of resolving insolvency*……………………………….…. 36.6

98
73 ●
108


18.8
HUMAN CAPITAL & RESEARCH………………...

98

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


34.5
Education…………………………………………………………..……

3.1
Expenditure on education, % GDP………………….…….….
🕘🕘 17.4
Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….……. 12.7

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
19.3

98
102
68
82
n/a
85

2.2
2.2.1
2.2.2
2.2.3


21.9
Tertiary education……………………………………….……..….
🕘🕘
19.2
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….
21.3
🕘🕘
Tertiary inbound mobility, %.......................................
….
1.1

88
95
54 ●
86

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

◇
◇
◇

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
29.9 113
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

◇

Information & communication technologies(ICTs)  31.7

ICT access*………………………………………………………….…….
34.6

ICT use*…………………………….....................................…….
13.7

45.8
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

◇

32.6

117 ◇
112 ◇
119 ○ ◇
110
116
◇

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 31.8
 …………………..…….
Electricity output, GWh/mn pop……
357.0
Logistics performance*……………………………………………..
24.9

Gross capital formation, % GDP………………………….……. 29.1

77
110
90
24 ●

3.3
3.3.1
3.3.2
3.3.3


26.3
Ecological sustainability………………………………………..

8.3
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
40.8
ISO 14001 environmental certificates/bn PPP$ GDP..  0.2

111
71
119 ○ ◇114




MARKET SOPHISTICATION..………….…………… 36.4 115

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
22.4 114

Ease of getting credit*…………………………………..…………..
60.0 66Domestic credit to private sector, % GDP…………...……
14.5 117
Microfinance gross loans, % GDP……………………….…….
0.2 47

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 41.7 [65]Ease of protecting minority investors*…………..………….
41.7 108
Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
45.1 117◇🕘🕘Applied tariff rate, weighted avg., %………………………….
12.7 125 ○ ◇†Intensity of local competition …………………………………… 63.2 88
Domestic market scale, bn PPP$………………………………
95.1 79

◇



◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
26.3
🕘🕘
Knowledge-intensive employment, %...........................
10.9
Firms offering formal training, % firms………………………… 37.6

GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/a🕘🕘Females employed w/advanced degrees, %……………..
2.0

[94]
98
37 ●
n/a
n/a
100

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.3
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
38.4
State of cluster development†.……..………..…………………..
35.3

GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

102
77
104
n/a
103 ○
93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
27.0 94◇
0.1 106
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.4 101
1.1 67 ●ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.2 78Research talent, % in business enterprise……..…………..
n/a n/a 15.7 93
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.5
0.3
0.0
n/a
6.8
6.0

87
83
94
n/a
64 ●
89

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


29.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.0

New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..……………
0.2
ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.7
🕘🕘High- & medium-high-tech manufactures, %……………… 0.0

94
62 ● ◇
n/a
76
116
◇
103 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


10.6 100
Knowledge diffusion……………………………………..…..…….

0.0 89Intellectual property receipts, % total trade……………….

0.2 95High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.9 57 ●
FDI net outflows, % GDP…………………………….………….......
0.0 105
16.5 109
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
27.6 113Trademarks by origin/bn PPP$ GDP…………..……….….….
5.9 113Industrial designs by origin/bn PPP$ GDP…………..……..
0.3 95

ICTs & business model creation†………………………....…….
52.0 99

ICTs & organizational model creation†…………………….... 42.4 106

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
10.4 84

Cultural & creative services exports, % total trade…....
0.3 61 ●🕘🕘
National feature films/mn pop. 15-69………………….………
1.9 68
Entertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
1.3 40 ●
Creative goods exports, % total trade………………………..
0.0 121 ○

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.5 108
Online creativity………………………………………..……….…….

0.2 117◇Generic top-level domains (TLDs)/th pop. 15-69……….

1.3 75Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.1 119 ○
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

239

CANADAGII 2019 rank

17

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

22

9

High

NAC

37.0

1,852.5

49,651.2

18

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

92.3

4 ●

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
92.0

93.0
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
91.5

6 ●
7
6 ●

1.2
1.2.1
1.2.2
1.2.3


95.1
Regulatory environment……………………………..………..

92.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
94.0

10.0
Cost of redundancy dismissal, salary weeks…………..

8
6 ●
10
29

1.3
1.3.1
1.3.2


89.8
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
98.2
Ease of resolving insolvency*……………………………….….
81.5

4 ●
3 ● ◆
12


50.9
HUMAN CAPITAL & RESEARCH………………...

19

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


51.9
Education…………………………………………………………..……
🕘🕘
5.3
Expenditure on education, % GDP………………….…….….
🕘🕘 18.3
Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….…….
16.1

PISA scales in reading, maths, & science…………......…
523.3
Pupil-teacher ratio, secondary…………………………......…. n/a

51
◇
33
58 ○ ◇
33
5
n/a

2.2
2.2.1
2.2.2
2.2.3


41.2
Tertiary education……………………………………….……..….
🕘🕘
67.0
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
21.3

Tertiary inbound mobility, %.......................................
….
11.9

32
33
55 ○
14

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
59.5
🕘🕘Researchers, FTE/mn pop……………………………..…...……
4,274.7
🕘🕘Gross expenditure on R&D, % GDP………….………..……
1.7

69.6
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
80.2

15
22
21
19
6 ●


58.5
INFRASTRUCTURE……………………………….......

27

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 85.0

ICT access*………………………………………………………….…….
80.0

ICT use*…………………………….....................................…….
76.1

93.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

21
29
25
17
27

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
55.4
…………………..….... 18,368.9
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 77.8
Gross capital formation, % GDP………………………….…….
23.8

8
4 ● ◆
20
56

3.3
3.3.1
3.3.2
3.3.3


35.1
Ecological sustainability………………………………………..

5.5
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
72.2
ISO 14001 environmental certificates/bn PPP$ GDP..  0.7

79 ○ ◇103 ○ ◇24
76 ○ ◇91.0



MARKET SOPHISTICATION..………….…………… 80.4

◇

2 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
85.0
Ease of getting credit*…………………………………..…………..
85.0
Domestic credit to private sector, % GDP…………...……
n/a
Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 77.7
Ease of protecting minority investors*…………..………….
78.3
Market capitalization, % GDP………………………………...….
125.1
Venture capital deals/bn PPP$ GDP……………….……....
0.5

4 ● ◆
10 ◆
7
1 ● ◆

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
78.6
Applied tariff rate, weighted avg., %………………………….
1.5
†Intensity of local competition …………………………………… 74.5
Domestic market scale, bn PPP$…………………………..… 1,852.5

13
16
31
17



[4]
11
n/a
n/a

◆


BUSINESS SOPHISTICATION..……….……………

49.9 22

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
56.4 28🕘🕘
Knowledge-intensive employment, %...........................
43.7 19
Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..……
0.8 24
GERD financed by business, %……………………………........ 40.9 43
Females employed w/advanced degrees, %……………..
17.6 31

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


48.4
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
63.0

State of cluster development†.……..………..…………………..
62.0
GERD financed by abroad, %.........................................
10.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.3
Patent families 2+ offices/bn PPP$ GDP…………………….. 2.1

15
20
22
36
1 ● ◆
20

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
44.9

2.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.0

0.9
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.6
🕘🕘
Research talent, % in business enterprise……..…………..
56.7

28
11
30
77 ○ ◇6418

 41.3KNOWLEDGE & TECHNOLOGY OUTPUTS....

19



The Global Innovation Index 2019

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 50.5

2.3
Patents by origin/bn PPP$ GDP……………….…………..….…

1.3
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 20.6
Citable documents H-index…………………….……….……..….
80.0

13
38
◇
27
◇
n/a
22
4 ● ◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


41.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.7
New businesses/th pop. 15-64………………….…....………….
0.1
Computer software spending, % GDP…………..……………
0.7
ISO 9001 quality certificates/bn PPP$ GDP…………..……
3.4
High- & medium-high-tech manufactures, %………………
0.4

43
68 ○
104 ○ ◇
5 ●
73 ○ ◇
24

6.3
6.3.1
6.3.2
6.3.3
6.3.4


32.0
Knowledge diffusion……………………………………..…..…….

0.8Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 4.9

ICT services exports, % total trade……………..……..………
1.5

FDI net outflows, % GDP…………………………….………….......
5.0

27
21
31
68 ○
12


41.4
CREATIVE OUTPUTS…….…………………….…………

27

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
50.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
58.5
Industrial designs by origin/bn PPP$ GDP…………..……..
0.5

ICTs & business model creation†………………………....…….
75.7

ICTs & organizational model creation†……………………....
77.0

31
37
86 ○ ◇
16
11

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
24.7
Cultural & creative services exports, % total trade…....
0.8
National feature films/mn pop. 15-69………………….………
3.5
Entertainment & Media market/th pop. 15-69…………….
59.4
Printing & other media, % manufacturing…...................
1.5
Creative goods exports, % total trade………………………..
1.0

45
34
53
10
34
43

7.3
7.3.1
7.3.2
7.3.3
7.3.4


39.4
Online creativity………………………………………..……….…….

76.5
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 29.4

49.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
18.8

17
6 ● ◆
19
25
24

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
240◇CHILEGII 2019 rank

51

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

62

43

High

LCN

18.2

481.0

25,978.3

47

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
33.1 53


INSTITUTIONS………………………………….…….…..
73.0

39

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
71.7

80.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 67.2

37
35
36

1.2
1.2.1
1.2.2
1.2.3


72.9
Regulatory environment……………………………..………..

77.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
73.1

27.4
Cost of redundancy dismissal, salary weeks…………..

41
21 ●
29
107 ○ ◇

1.3
1.3.1
1.3.2


74.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
89.1
Ease of resolving insolvency*……………………………….…. 59.9

50
58
46


32.5
HUMAN CAPITAL & RESEARCH………………...

57

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


49.8
Education…………………………………………………………..……

5.4
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 18.2
School life expectancy, years……………….…………….……. 16.5

PISA scales in reading, maths, & science…………......…
442.7
Pupil-teacher ratio, secondary…………………………......….
18.4

60
30
59
20 ●
44
79 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


34.3
Tertiary education……………………………………….……..….

91.5
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….…. 20.5

Tertiary inbound mobility, %.......................................….
0.4

56
5 ● ◆
62
100 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
13.3
🕘🕘Researchers, FTE/mn pop……………………………..…...……
502.1
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.4

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
39.5

◇
49
67
◇
71
◇
43 ○ ◇32


51.0
INFRASTRUCTURE……………………………….......

50

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  76.1

ICT access*………………………………………………………….…….
72.8

ICT use*…………………………….....................................…….
66.3

83.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
82.0

41
57
41
37
46

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
36.5
 …………………..…….
Electricity output, GWh/mn pop……
4,262.7
Logistics performance*…………………………………………….. 58.6
Gross capital formation, % GDP………………………….…….
22.4

59
51
33
71

3.3
3.3.1
3.3.2
3.3.3


40.3
Ecological sustainability………………………………………..

10.1
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 57.5

ISO 14001 environmental certificates/bn PPP$ GDP..
3.1

53
49
73
31

◇

◇

◇

◇



MARKET SOPHISTICATION..………….…………… 51.7 49
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
41.4
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...…… 112.6
Microfinance gross loans, % GDP……………………….…….
0.9

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.3
Ease of protecting minority investors*…………..………….
60.0

Market capitalization, % GDP………………………………...….
89.8
Venture capital deals/bn PPP$ GDP……………….……....
0.0

71
61
15 ●
53

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
73.3
Applied tariff rate, weighted avg., %………………………….
0.5
Intensity of local competition†…………………………………… 74.5
Domestic market scale, bn PPP$……………………………… 481.0

24 ●
4 ● ◆
30
42



51
77
19 ●
21
◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
44.4

Knowledge-intensive employment, %...........................
26.4
🕘🕘Firms offering formal training, % firms………………………… 57.5
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
35.8
Females employed w/advanced degrees, %……………..
8.8

47
53
◇
10 ● ◆
57
52
75
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.7
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
43.8
†State of cluster development .……..………..………………….. 44.1

GERD financed by abroad, %.........................................
1.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.2

96 ○ ◇55◇
77
77 ○ ◇85 ○ ◇
42

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
36.3

2.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.5
ICT services imports, % total trade…………..………………... 0.7

FDI net inflows, % GDP…………………………….…………………. 5.3
🕘🕘
Research talent, % in business enterprise……..…………..
29.5

49
12 ●
50
88 ○
2842

 22.9 61
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 14.6

0.9
Patents by origin/bn PPP$ GDP……………….…………..….…

0.5
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.2
Scientific & technical articles/bn PPP$ GDP….…..…..…. 13.2
Citable documents H-index…………………….……….……..….
22.5

56
64
35
41
40
37

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


38.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.7
New businesses/th pop. 15-64………………….…....………….
8.9
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..……
9.4
🕘🕘High- & medium-high-tech manufactures, %………………
0.2

56
67
15 ●
43
33
62

6.3
6.3.1
6.3.2
6.3.3
6.3.4


15.8 74
Knowledge diffusion……………………………………..…..…….

0.1 65
Intellectual property receipts, % total trade……………….

0.8 72High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.5 102 ○
FDI net outflows, % GDP…………………………….………….......
3.8
16 ●


27.2
CREATIVE OUTPUTS…….…………………….…………

66

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
45.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
70.2
Industrial designs by origin/bn PPP$ GDP…………..…….. 0.2

ICTs & business model creation†………………………....……. 72.1

ICTs & organizational model creation†……………………....
57.8

48
28
105 ○
28
54

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
10.9
Cultural & creative services exports, % total trade…....
0.3
National feature films/mn pop. 15-69………………….………
3.7
Entertainment & Media market/th pop. 15-69…………….
13.5
🕘🕘Printing & other media, % manufacturing…...................
1.1
Creative goods exports, % total trade………………………..
0.2

80
◇
65
49
31
◇
59
90 ○

7.3
7.3.1
7.3.2
7.3.3
7.3.4


6.9
Online creativity………………………………………..……….…….

2.2
Generic top-level domains (TLDs)/th pop. 15-69……….

12.2
Country-code TLDs/th pop. 15-69…………………..………….

16.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
2.4

58
76
37
56
61

◇

◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

241

CHINAGII 2019 rank

14

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

526Upper middle

SEAO

1,415.0

25,313.3

18,109.8

17

Score/Value

Rank


INSTITUTIONS………………………………….…….…..
64.1

60

1.1
1.1.1
1.1.2

Political environment……………………………………….…...

Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….

63.0
75.4
56.8

47
46
47

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

54.6
38.0
39.4
27.4

100 ○
81
77
107 ○

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….

Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….….

74.7
93.5
55.8

48
25
56


HUMAN CAPITAL & RESEARCH………………...
47.6

25

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


Education…………………………………………………………..……
63.4

Expenditure on education, % GDP………………….…….….
n/aGovernment funding/pupil, secondary, % GDP/cap…
n/a🕘🕘School life expectancy, years……………….…………….…….
13.5
PISA scales in reading, maths, & science…………......… 514.3
Pupil-teacher ratio, secondary…………………………......….
13.3

[13]
n/a
n/a
74
8
59

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................….

94 ○
55
n/a
101 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
58.8
1,234.8
Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……
2.1
Global R&D companies, avg. exp. top 3, mn US$……
91.7

QS university ranking, average score top 3*……………
82.5

◆
17
46
15
◆
6 ◆
3 ●◆
INFRASTRUCTURE……………………………….......
58.7

26

Information & communication technologies(ICTs)  74.5

ICT access*………………………………………………………….…….
60.0

ICT use*…………………………….....................................…….
61.5

46
75
55
34
29

3.1
3.1.1
3.1.2
3.1.3
3.1.4


Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

20.6
51.0
n/a
0.4

86.1
90.5

Score/Value Rank

BUSINESS SOPHISTICATION..……….………… 55.4
◆
◆

◆

◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
63.8

4,487.7
Electricity output, GWh/mn pop………………………..…….

Logistics performance*……………………………………………..

Gross capital formation, % GDP………………………….…….

72.1
44.2

2●◆
48
26 ◆
4●◆

3.3
3.3.1
3.3.2
3.3.3

Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
ISO 14001 environmental certificates/bn PPP$ GDP..

37.9
6.6
50.7
7.1

67
94 ○
97 ○ ◇
14◆

MARKET SOPHISTICATION..………….………… 58.6

21

4.1
4.1.1
4.1.2
4.1.3

Credit……………………………………………………….………………
45.3
Ease of getting credit*…………………………………..…………..
60.0
Domestic credit to private sector, % GDP…………...……
155.8

Microfinance gross loans, % GDP……………………….…….
0.0

◆
43
66
◆
7
69 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..……….
Ease of protecting minority investors*…………..………….

Market capitalization, % GDP………………………………...….
Venture capital deals/bn PPP$ GDP……………….……....

64
61
22
22

4.3
4.3.1
4.3.2
4.3.3

Trade, competition, & market scale………..…………….
88.2
Applied tariff rate, weighted avg., %………………………….
3.8

†Intensity of local competition ……………………………………
74.4
Domestic market scale, bn PPP$………………………..… 25,313.3

42.2
60.0
70.2
0.1

◆

◆


Knowledge workers…………………………………………….…..
84.9 [1]Knowledge-intensive employment, %...........................
n/a n/a🕘🕘
Firms offering formal training, % firms…………………………
79.2
1 ●◆

GERD performed by business, % GDP…………………..……
12
1.7
◆

GERD financed by business, %……………………………........ 76.5
2 ●◆
Females employed w/advanced degrees, %…………….. n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5

Innovation linkages…………..…………………………………….. 27.2

56.5
University/industry research collaboration † ………………..

State of cluster development†.……..………..…………………..
59.6

GERD financed by abroad, %.........................................
0.6
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0
Patent families 2+ offices/bn PPP$ GDP……………………..
1.0

58
◆
27
28
◆
93 ○
57
27
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
54.1

1.1
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
23.3

ICT services imports, % total trade…………..………………...
0.8

FDI net inflows, % GDP…………………………….………………….
1.7
Research talent, % in business enterprise……..………….. 60.7

13
◆
30
4 ●◆
85
88 ○
12
◆

KNOWLEDGE & TECHNOLOGY OUTPUTS... 57.2

5

The Global Innovation Index 2019

◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……
Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

68.1
53.7
2.1
72.4
11.9
54.2

4 ●◆
1 ●◆
◆
17
1 ●◆
42
13
◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5

Knowledge impact……………………………………….............. 66.6
Growth rate of PPP$ GDP/worker, %……………..…....…….
7.1
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..……………
0.4
ISO 9001 quality certificates/bn PPP$ GDP…………..……
16.9
🕘🕘High- & medium-high-tech manufactures, %………………
0.5

1 ●◆
1 ●◆
n/a
◆
24
20
◆
12

6.3
6.3.1
6.3.2
6.3.3
6.3.4


Knowledge diffusion……………………………………..…..…….
37.0

0.1
Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…......
27.9
ICT services exports, % total trade……………..……..………
1.2

FDI net outflows, % GDP…………………………….………….......
1.4

◆
22
56
1 ●◆
75
42

CREATIVE OUTPUTS…….…………………….……… 48.3

12

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
77.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
238.7
Industrial designs by origin/bn PPP$ GDP…………..……..
26.3

ICTs & business model creation † ………………………....…….
61.7

ICTs & organizational model creation † …………………….... 59.7

1 ●◆
1 ●◆
1 ●◆
56
46
◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5

Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

35.2
0.5
0.8
6.9
0.8
11.9

◆
15
49
87 ○
42
79 ○
1 ●◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….

Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

2.7
2.4
5.4
0.3
n/a

79
75
46
111 ○
n/a

2●◆
73
32
1 ●◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. S quare brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
242

◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

◆

◆

14

◆

COLOMBIA

GII 2019 rank

67

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

7658

Upper middle

LCN

49.5

748.6

14,943.5

63

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
64.0

61

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
50.4

61.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 44.9

82
91 ○
74

1.2
1.2.1
1.2.2
1.2.3


65.4
Regulatory environment……………………………..………..

51.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
36.9

16.7
Cost of redundancy dismissal, salary weeks…………..

66
55
83
69

1.3
1.3.1
1.3.2


76.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
85.3
Ease of resolving insolvency*……………………………….…. 67.4

41
77
37


27.0
HUMAN CAPITAL & RESEARCH………………...

78

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


38.8
Education…………………………………………………………..……

4.4
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 17.5
School life expectancy, years……………….…………….……. 14.6

PISA scales in reading, maths, & science…………......…
410.1
Pupil-teacher ratio, secondary…………………………......….
26.0

87
64
67
59
59 ○
98 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


32.5
Tertiary education……………………………………….……..….

60.4
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
23.7
Tertiary inbound mobility, %.......................................….
0.2

60
44
37
106 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
9.8
🕘🕘Researchers, FTE/mn pop……………………………..…...……
88.5
Gross expenditure on R&D, % GDP………….………..……
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
33.2

58
88 ○
85
43 ○ ◇34


51.3
INFRASTRUCTURE……………………………….......

47

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  71.4

ICT access*………………………………………………………….…….
61.3

ICT use*…………………………….....................................…….
44.2

88.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
92.1

55
74
79
30
◆
23 ● ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
28.7
 …………………..…….
Electricity output, GWh/mn pop……
1,580.8
Logistics performance*…………………………………………….. 41.1
Gross capital formation, % GDP………………………….…….
21.5

88
87
57
79

3.3
3.3.1
3.3.2
3.3.3


53.8
Ecological sustainability………………………………………..

15.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
65.2
ISO 14001 environmental certificates/bn PPP$ GDP.. 4.2

13 ● ◆
10 ● ◆
38 ◆
27 ●

◆

MARKET SOPHISTICATION..………….…………… 50.4 53
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
39.7
Ease of getting credit*…………………………………..…………..
95.0
Domestic credit to private sector, % GDP…………...…… 49.4

Microfinance gross loans, % GDP……………………….…….
0.1

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 41.2
Ease of protecting minority investors*…………..………….
75.0

Market capitalization, % GDP………………………………...….
34.9
Venture capital deals/bn PPP$ GDP……………….……....
0.0

70
14 ● ◆
42
66 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
70.2
Applied tariff rate, weighted avg., %………………………….
4.4

Intensity of local competition†…………………………………… 75.0Domestic market scale, bn PPP$……………………………… 748.6

32
78
28 ● ◆31



55
3 ● ◆
70
53


BUSINESS SOPHISTICATION..……….……………
32.6

58

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
46.8
🕘🕘Knowledge-intensive employment, %...........................
16.7
🕘🕘Firms offering formal training, % firms………………………… 65.1

GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
49.3
Females employed w/advanced degrees, %……………..
13.7

41
86
4 ● ◆
60
29
49

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


17.7 109 ○Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
41.9 60
State of cluster development†.……..………..…………………..
45.1 75

GERD financed by abroad, %.........................................
0.5 96 ○
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 75
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1 59

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
33.1

0.9
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
13.2

1.4
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
4.4
🕘🕘Research talent, % in business enterprise……..………….. 2.4

64
44
16 ●
51
37
75 ○ ◇ 19.5 76
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 8.6

0.8
Patents by origin/bn PPP$ GDP……………….…………..….…

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.3
Scientific & technical articles/bn PPP$ GDP….…..…..….
4.5
Citable documents H-index…………………….……….……..….
15.8

75
66
48
39
85
46

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


37.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.5
New businesses/th pop. 15-64………………….…....………….
2.3
Computer software spending, % GDP…………..…………… 0.2

ISO 9001 quality certificates/bn PPP$ GDP…………..……
16.1
High- & medium-high-tech manufactures, %………………
0.2

60
51
45
73
21 ●
53

6.3
6.3.1
6.3.2
6.3.3
6.3.4


12.5
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

1.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.7

FDI net outflows, % GDP…………………………….………….......
1.4

90
55
64
92
44


22.3
CREATIVE OUTPUTS…….…………………….…………

85

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.8

Trademarks by origin/bn PPP$ GDP…………..……….….….
33.4
Industrial designs by origin/bn PPP$ GDP…………..……..
0.4

ICTs & business model creation†………………………....……. 60.3

ICTs & organizational model creation†…………………….... 54.5

86
73
92 ○
65
62

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

87
68
73
47
43
79

7.3
7.3.1
7.3.2
7.3.3
7.3.4


6.0
Online creativity………………………………………..……….…….

2.8
Generic top-level domains (TLDs)/th pop. 15-69……….

17.4
Country-code TLDs/th pop. 15-69…………………..………….

4.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.4

9.9
0.3
1.4
5.5
1.3
0.2

62
66
29 ●
84
72

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

243

COSTA RICA

GII 2019 rank

55

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

48

68

Upper middle

LCN

5.0

88.7

17,559.1

54

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
61.9

68

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
58.4

70.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 52.5

58
61
56

1.2
1.2.1
1.2.2
1.2.3


69.9
Regulatory environment……………………………..………..

54.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
58.4

18.7
Cost of redundancy dismissal, salary weeks…………..

54
48
43
76

1.3
1.3.1
1.3.2


57.2
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
79.9

Ease of resolving insolvency*……………………………….…. 34.5

110 ○ ◇108
1 1 1 ○ ◇28.5
HUMAN CAPITAL & RESEARCH………………...

72

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.5
Education…………………………………………………………..……

7.4
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 23.9
School life expectancy, years……………….…………….……. 15.4

PISA scales in reading, maths, & science…………......…
415.8
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.7

36
7 ● ◆
28
41
54
55

2.2
2.2.1
2.2.2
2.2.3


19.6
Tertiary education……………………………………….……..….

55.6
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
14.4

Tertiary inbound mobility, %.......................................
….
1.3

95
52
90 ○ ◇
84

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
8.3
🕘🕘Researchers, FTE/mn pop……………………………..…...……
529.9
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.5

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
17.1

64
66
66
43 ○ ◇54

47.0
INFRASTRUCTURE……………………………….......

63

Information & communication technologies(ICTs)  68.7

ICT access*………………………………………………………….…….
65.6

ICT use*…………………………….....................................…….
64.8

67.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

59
67
46
74
57

3.1
3.1.1
3.1.2
3.1.3
3.1.4

77.0

◆

◆



3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 23.4 108
 …………………..…….
Electricity output, GWh/mn pop……
2,238.973
Logistics performance*……………………………………………..
72
34.1

Gross capital formation, % GDP………………………….……. 17.8 105 ○

3.3
3.3.1
3.3.2
3.3.3


49.0
Ecological sustainability………………………………………..

14.5
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
67.9
ISO 14001 environmental certificates/bn PPP$ GDP..  1.4

34 ◆
15 ● ◆29 ◆
59MARKET SOPHISTICATION..………….…………… 44.2 85

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
37.8
Ease of getting credit*…………………………………..…………..
85.0
Domestic credit to private sector, % GDP…………...……
62.0
🕘🕘Microfinance gross loans, % GDP……………………….…….
0.0

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 32.2
Ease of protecting minority investors*…………..………….
48.3
Market capitalization, % GDP………………………………...….
4.6
Venture capital deals/bn PPP$ GDP……………….……....
n/a

112 ○
99
74 ○ ◇
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
62.4
🕘🕘Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 72.9
Domestic market scale, bn PPP$……………………………… 88.7

58
22 ●
39
84



60
1 1 ● ◆
53
71 ○


BUSINESS SOPHISTICATION..……….……………
33.2

52

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
37.0Knowledge-intensive employment, %...........................
24.4
🕘🕘Firms offering formal training, % firms………………………… 54.7
🕘🕘
GERD performed by business, % GDP…………………..…… 0.2

GERD financed by business, %……………………………........
2.8
Females employed w/advanced degrees, %……………..
10.5

65
58
14 ●
54
87 ○ ◇
63

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.8 95
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
45.1 51
State of cluster development†.……..………..…………………..
49.6 51
GERD financed by abroad, %.........................................
1.3 88 ○
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 109 ○ ◇Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 70

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
43.8

2.8
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.1

1.4
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
5.0

Research talent, % in business enterprise……..………….. n/a◆
29
8 ● ◆
43
50
30
n/a

 24.3 56
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

5.9
0.2
0.1
0.1
5.0
10.1

91
94
57
49
81
66

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


36.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.3
New businesses/th pop. 15-64………………….…....………….
2.1
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 3.6
High- & medium-high-tech manufactures, %………………
0.3

62
38
49
46
67
41

6.3
6.3.1
6.3.2
6.3.3
6.3.4


30.2
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

5.7
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
6.1

FDI net outflows, % GDP…………………………….………….......
0.7

◆
30
79
28
7 ● ◆
60


34.3
CREATIVE OUTPUTS…….…………………….…………

39

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
48.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
94.1
Industrial designs by origin/bn PPP$ GDP…………..……..
0.1

ICTs & business model creation†………………………....…….
68.3

ICTs & organizational model creation†…………………….... 63.0

41
19 ●
113 ○
34
◆
36
◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
34.8 16 ● ◆Cultural & creative services exports, % total trade…....
4.2
1 ● ◆

National feature films/mn pop. 15-69………………….………
3.7 50Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
2.2 15 ●
Creative goods exports, % total trade……………………….. 0.4 65

7.3
7.3.1
7.3.2
7.3.3
7.3.4


5.1
Online creativity………………………………………..……….…….

11.3
Generic top-level domains (TLDs)/th pop. 15-69……….

1.4
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
11.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.4

65
37
70
62
73

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
244

The Global Innovation Index 2019◆◆CÔTE D'IVOIRE

GII 2019 rank

103

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

91

110

Lower middle

SSF

24.9

106.8

4,177.6

123

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
26.1 [94]
INSTITUTIONS………………………………….…….…..
57.5

84

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
40.1

63.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 28.6

105
86
116

1.2
1.2.1
1.2.2
1.2.3


61.6
Regulatory environment……………………………..………..

32.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
29.7

13.1
Cost of redundancy dismissal, salary weeks…………..

77
96
99
48 ●

1.3
1.3.1
1.3.2


70.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
93.7
Ease of resolving insolvency*……………………………….…. 48.0

63
23 ● ◆72◇
13.6 113
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


33.7
Education…………………………………………………………..……

4.4
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 23.5
School life expectancy, years……………….…………….……. 9.6

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
26.3

101
65
33 ●
◇
108
n/a
100

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

7.2
9.2
n/a
2.1

116
110
n/a
73

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
28.1 117
INFRASTRUCTURE……………………………….......

◇
◇

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  27.4 122 ○ ◇
ICT access*………………………………………………………….…….
37.0 107

ICT use*…………………………….....................................…….
32.9 98
22.2 124 ○ ◇Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
17.4 126 ○ ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
31.7
 …………………..…….
Electricity output, GWh/mn pop……
432.6
Logistics performance*…………………………………………….. 47.6
Gross capital formation, % GDP………………………….…….
23.7

78
108
49 ● ◆
58

3.3
3.3.1
3.3.2
3.3.3


25.3
Ecological sustainability………………………………………..

6.4
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 45.3

ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

115
95
108
96



MARKET SOPHISTICATION..………….…………… 36.7 113

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
31.2 87
Ease of getting credit*…………………………………..…………..
70.0 40 ●Domestic credit to private sector, % GDP…………...…… 26.5 102
Microfinance gross loans, % GDP……………………….…….
0.8 27 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 28.2 123 ○Ease of protecting minority investors*…………..………….
40.0 114 ○ ◇Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.0 43

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
50.8 105
Applied tariff rate, weighted avg., %………………………….
10.3 114

Intensity of local competition†…………………………………… 70.2 57
Domestic market scale, bn PPP$……………………………… 106.8 76



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
28.8
Knowledge-intensive employment, %...........................
n/a
Firms offering formal training, % firms………………………… 35.5

GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/a🕘🕘Females employed w/advanced degrees, %……………..
0.8

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


17.4 [113]Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
22.1 124 ○ ◇◇State of cluster development†.……..………..…………………..
32.5 116
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP………………….. n/a n/a
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
32.1

0.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.6

ICT services imports, % total trade…………..………………... 1.9

FDI net inflows, % GDP…………………………….…………………. 1.6

Research talent, % in business enterprise……..…………..
n/a72
114 ○ ◇
96
29 ● ◆94n/a

 19.7KNOWLEDGE & TECHNOLOGY OUTPUTS....

74



[85]
n/a
39 ●
n/a
n/a
108

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

3.3
0.2
0.0
n/a
1.9
5.3

115
97
99 ○ ◇
n/a
113
94

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


45.8
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
5.1
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..…………… 0.0

ISO 9001 quality certificates/bn PPP$ GDP…………..……
2.1
High- & medium-high-tech manufactures, %………………
n/a

[26]
7 ● ◆
n/a
121 ○ ◇
86
n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


10.1 102
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0
91
Intellectual property receipts, % total trade……………….

1.1 66High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.2 76

FDI net outflows, % GDP…………………………….………….......
0.1 103
17.6 105
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
34.5 97
Trademarks by origin/bn PPP$ GDP…………..……….….….
9.5 106
Industrial designs by origin/bn PPP$ GDP…………..…….. 1.5 58

ICTs & business model creation†………………………....……. 63.7 53 ● ◆ICTs & organizational model creation†……………………....
50.3 80

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.3 116
Online creativity………………………………………..……….…….

0.5 109
Generic top-level domains (TLDs)/th pop. 15-69……….

0.2 108
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.5 108
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a1.1 [124]
0.1 93n/a n/an/a n/an/a n/a0.1 103◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

245

CROATIA

GII 2019 rank

44

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

52

46

High

EUR

4.2

107.4

26,221.4

41

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
69.3

45

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
66.7

78.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 60.5

42
42
41

1.2
1.2.1
1.2.2
1.2.3


71.7
Regulatory environment……………………………..………..

53.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
55.2

15.1
Cost of redundancy dismissal, salary weeks…………..

46
49
48
61

1.3
1.3.1
1.3.2


69.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
82.6

Ease of resolving insolvency*……………………………….…. 56.2

68
95 ○ ◇54


35.6
HUMAN CAPITAL & RESEARCH………………...

50

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


59.1
Education…………………………………………………………..……
🕘🕘
4.6
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. 15.0

PISA scales in reading, maths, & science…………......…
475.4
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
6.7

28 ●
60
n/a
54
34
1 ● ◆

2.2
2.2.1
2.2.2
2.2.3


36.4
Tertiary education……………………………………….……..….
🕘🕘
67.5
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
25.3
Tertiary inbound mobility, %.......................................
….
0.4

48
32
28
98 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
11.5
Researchers, FTE/mn pop……………………………..…...……
1,865.4
Gross expenditure on R&D, % GDP………….………..……
0.9

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
4.7

◇
52
42
41
43 ○ ◇
68
◇


51.6
INFRASTRUCTURE……………………………….......

46

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 71.1

ICT access*………………………………………………………….…….
75.8

ICT use*…………………………….....................................…….
63.4

68.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
77.0

57
40
49
73
57

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
30.7
 …………………..…….
Electricity output, GWh/mn pop……
3,025.2
Logistics performance*…………………………………………….. 48.7
Gross capital formation, % GDP………………………….…….
20.4

85 ◇
63
48
90 ○

3.3
3.3.1
3.3.2
3.3.3


52.9
Ecological sustainability………………………………………..

10.1
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
65.5
ISO 14001 environmental certificates/bn PPP$ GDP..  9.5

19 ●
48
37
6 ● ◆



◇
◇

◇
◇
◇

MARKET SOPHISTICATION..………….…………… 46.0

71

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
40.6
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...……
57.4

Microfinance gross loans, % GDP……………………….……. n/a

53
77
58
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 38.3
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
39.2
Venture capital deals/bn PPP$ GDP……………….……....
0.0

84
35
38
44

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
59.2
🕘🕘Applied tariff rate, weighted avg., %………………………….
2.0

†Intensity of local competition …………………………………… 57.1
Domestic market scale, bn PPP$……………………………… 107.4

71
53
117 ○ ◇75




BUSINESS SOPHISTICATION..……….……………
34.3

49

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
52.3
Knowledge-intensive employment, %...........................
36.3
Firms offering formal training, % firms………………………… 49.3

GERD performed by business, % GDP…………………..…… 0.4

GERD financed by business, %……………………………........
42.9
Females employed w/advanced degrees, %……………..
16.8

33
34
22 ●
40
42
37

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.5
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
27.7
State of cluster development†.……..………..…………………..
30.4

GERD financed by abroad, %.........................................
10.8
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

99 ○ ◇1 1 1 ○ ◇
119 ○ ◇
37
46
56

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
32.2

1.1
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.1

1.5
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.5
Research talent, % in business enterprise……..………….. 21.3

70
31
91 ○
43
70
56
◇

 25.6 49
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 17.9

1.5
Patents by origin/bn PPP$ GDP……………….…………..….…

0.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.5
Scientific & technical articles/bn PPP$ GDP….…..…..….
22.7
Citable documents H-index…………………….……….……..…. 15.9

50
53
40
34
19 ●
45

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


40.4
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.4
New businesses/th pop. 15-64………………….…....………….
5.0

Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..……
23.3
High- & medium-high-tech manufactures, %……………… 0.2

46
53
27 ●
99 ○ ◇
12 ● ◆
51

6.3
6.3.1
6.3.2
6.3.3
6.3.4


18.5
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

3.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.8

FDI net outflows, % GDP…………………………….………….......
0.2

56
38
42
36
88 ○


31.0
CREATIVE OUTPUTS…….…………………….…………

51

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
40.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
46.8
Industrial designs by origin/bn PPP$ GDP…………..……..
4.9

ICTs & business model creation†………………………....…….
57.9

ICTs & organizational model creation†…………………….... 51.9

65
◇
54
27 ●
76
◇
72
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
30.1 31 ●
Cultural & creative services exports, % total trade…....
1.9
7 ● ◆

National feature films/mn pop. 15-69………………….………
2.0 64◇Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
2.7
9 ● ◆

Creative goods exports, % total trade………………………..
0.8 50

7.3
7.3.1
7.3.2
7.3.3
7.3.4


12.6
Online creativity………………………………………..……….…….

14.2
Generic top-level domains (TLDs)/th pop. 15-69……….

9.7
Country-code TLDs/th pop. 15-69…………………..………….

33.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
4.3

46
32 ●
40
37
53

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
246

The Global Innovation Index 2019

CYPRUSGII 2019 rank

28

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

23

28

High

NAWA

1.2

33.8

39,973.2

29

Score/Value Rank

INSTITUTIONS………………………………….…….…..

80.3

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

25

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
72.8

80.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
68.8

34
35
33

1.2
1.2.1
1.2.2
1.2.3


84.8
Regulatory environment……………………………..………..

69.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..… 69.8

8.0
Cost of redundancy dismissal, salary weeks…………..

21
31
33
1 ● ◆

1.3
1.3.1
1.3.2


83.3
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
91.2

Ease of resolving insolvency*……………………………….….
75.5

24
46
24


35.8
HUMAN CAPITAL & RESEARCH………………...

49

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


63.4
Education…………………………………………………………..……

6.4
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 39.4
🕘🕘School life expectancy, years……………….…………….…….
14.6

PISA scales in reading, maths, & science…………......…
437.5
🕘🕘
Pupil-teacher ratio, secondary…………………………......…. 10.4

12
16
3 ● ◆
◇
62
46
33

2.2
2.2.1
2.2.2
2.2.3


37.5
Tertiary education……………………………………….……..….
🕘🕘
60.1
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
15.9
🕘🕘Tertiary inbound mobility, %.......................................
…. 17.5

42
45
82 ○ ◇
8
◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
6.5
Researchers, FTE/mn pop……………………………..…...……
1,174.4
Gross expenditure on R&D, % GDP………….………..……
0.6

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*…………… 0.0

◇
71
49
◇
55
43 ○ ◇78 ○ ◇
55.9
INFRASTRUCTURE……………………………….......

34

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  79.9

ICT access*………………………………………………………….…….
79.7

ICT use*…………………………….....................................…….
79.6

78.5
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

32
31
18
51
46

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
29.9
 …………………..…….
Electricity output, GWh/mn pop……
5,749.4
Logistics performance*…………………………………………….. 50.9
Gross capital formation, % GDP………………………….…….
17.0

86 ◇
36
44
1 1 1 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


57.8
Ecological sustainability………………………………………..

12.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
72.6
ISO 14001 environmental certificates/bn PPP$ GDP..  8.5

11
28
23
9

82.0

◆


MARKET SOPHISTICATION..………….…………… 58.2 24

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
78.8
Ease of getting credit*…………………………………..…………..
60.0
Domestic credit to private sector, % GDP…………...……
199.1

Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 38.0
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
12.9
Venture capital deals/bn PPP$ GDP……………….……....
0.1

86
35
66 ○
25

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
57.7
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†……………………………………
76.0
Domestic market scale, bn PPP$……………………………… 33.8

76
◇
23
20
1 1 1 ○ ◇

6 ● ◆
66
2 ● ◆
n/a

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

47.6

24



Knowledge workers…………………………………………….….. 49.9 38
Knowledge-intensive employment, %...........................
35.3 37
Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..……
0.2 52
GERD financed by business, %……………………………........ 34.9 53
Females employed w/advanced degrees, %……………..
24.6 14


◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5

Innovation linkages…………..…………………………………….. 36.4
University/industry research collaboration†………………..
39.2
State of cluster development†.……..………..…………………..
46.3

GERD financed by abroad, %.........................................
18.6
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 1.7

36
72
67
20
17
23

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
56.3

1.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..……………….. 4.6

8.1
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
43.8
Research talent, % in business enterprise……..…………..
25.6

◆
9
36
1 1 1 ○ ◇
1 ● ◆
2 ● ◆
47◇ 41.2 20
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 24.6

1.9
Patents by origin/bn PPP$ GDP……………….…………..….…

1.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
25.6
Citable documents H-index…………………….……….……..….
10.4

35
47
28
n/a
12
63

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


48.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.1
New businesses/th pop. 15-64………………….…....…………. 16.6
Computer software spending, % GDP…………..……………
0.2
ISO 9001 quality certificates/bn PPP$ GDP…………..……
29.6
High- & medium-high-tech manufactures, %………………
0.2

19
84 ○
5 ● ◆
71
4 ● ◆
60

6.3
6.3.1
6.3.2
6.3.3
6.3.4


50.6
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 0.4

ICT services exports, % total trade……………..……..………
14.6

FDI net outflows, % GDP…………………………….………….......
48.5

10
82 ○86◇
1 ● ◆
1 ● ◆


41.1
CREATIVE OUTPUTS…….…………………….…………

28

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
44.2
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
97.0
Industrial designs by origin/bn PPP$ GDP…………..……..
3.4

52
17
37
73
92

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
22.4 50
Cultural & creative services exports, % total trade…....
0.1 88 ○ ◇National feature films/mn pop. 15-69………………….……… 6.8 32
Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
2.4 12◆
Creative goods exports, % total trade………………………..
0.5 59

7.3
7.3.1
7.3.2
7.3.3
7.3.4


53.6
Online creativity………………………………………..……….…….

75.2
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 4.7
🕘🕘
51.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
100.0


ICTs & business model creation†………………………....…….
58.1

ICTs & organizational model creation†……………………....
47.3

◆
◇
◇

9
◆
7 ● ◆
52
23
1 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

247

CZECH REPUBLIC (THE)GII 2019 rank

26

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

21

29

High

EUR

10.6

396.4

37,371.0

27

Score/Value Rank

INSTITUTIONS………………………………….…….…..
78.6

29

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
75.6

84.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 71.3

31
25
30

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

78.4
75.0
75.9
20.2

33
25
26
83 ○

1.3
1.3.1
1.3.2


81.8
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
83.6

Ease of resolving insolvency*……………………………….…. 80.1

29
89 ○ ◇
14 ●


43.4
HUMAN CAPITAL & RESEARCH………………...

34

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


59.7
Education…………………………………………………………..……

5.8
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 23.7
School life expectancy, years……………….…………….……. 16.8

PISA scales in reading, maths, & science…………......…
490.8
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.5

26
23
31
19
28
44

2.2
2.2.1
2.2.2
2.2.3


43.2
Tertiary education……………………………………….……..….
🕘🕘
63.7
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
23.5
Tertiary inbound mobility, %.......................................
….
11.5

26
38
39
15

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
27.3
………………………..….....… 3,689.9
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
1.8

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
25.4

40
25
20
43 ○ ◇42

56.4
INFRASTRUCTURE……………………………….......

32

Information & communication technologies(ICTs)  67.3

ICT access*………………………………………………………….…….
71.9

ICT use*…………………………….....................................…….
70.0

65.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

64 ◇
60 ◇
34
82 ○ ◇88 ○ ◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

61.8



3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 48.6
 …………………..…….
Electricity output, GWh/mn pop……
8,107.8
Logistics performance*……………………………………………..
75.6

Gross capital formation, % GDP………………………….……. 26.5

22
21
22
37

3.3
3.3.1
3.3.2
3.3.3


53.4
Ecological sustainability………………………………………..

7.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
67.7
ISO 14001 environmental certificates/bn PPP$ GDP..  11.7

16 ●
79 ○
32
3 ● ◆


MARKET SOPHISTICATION..………….…………… 52.4 46

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
46.6
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
51.6

Microfinance gross loans, % GDP……………………….……. n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 39.2
Ease of protecting minority investors*…………..………….
58.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.0

80 ○
68 ○
n/a
70 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
71.5
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 78.2
Domestic market scale, bn PPP$……………………………… 396.4

31
23
16
46



41
40
65
n/a

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
46.3

25

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
55.2

Knowledge-intensive employment, %...........................
38.0

Firms offering formal training, % firms………………………… 55.1

GERD performed by business, % GDP…………………..……
1.1

GERD financed by business, %……………………………........
39.3
Females employed w/advanced degrees, %……………..
12.2

30
31
13
19
46
58

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


34.5
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
50.9
State of cluster development†.……..………..…………………..
50.5
GERD financed by abroad, %.........................................
25.0
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP……………………..
0.7

40
39
46
13 ● ◆
62 ○
30

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
49.1

0.8
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
17.4

1.3
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.6

Research talent, % in business enterprise……..………….. 51.6

21
47
8 ● ◆
55
47
23

 43.8KNOWLEDGE & TECHNOLOGY OUTPUTS....

16 ●



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 35.1

2.7
Patents by origin/bn PPP$ GDP……………….…………..….…

0.5
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
3.2
Scientific & technical articles/bn PPP$ GDP….…..…..….
23.4
Citable documents H-index…………………….……….……..…. 28.8

24
34
37
6 ● ◆
17
31

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


54.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.7
New businesses/th pop. 15-64………………….…....………….
4.0

Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
29.7
High- & medium-high-tech manufactures, %……………… 0.6

10 ● ◆
47
31
35
3 ● ◆
5 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


41.7
Knowledge diffusion……………………………………..…..…….

0.3Intellectual property receipts, % total trade……………….

17.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.3

FDI net outflows, % GDP…………………………….………….......
1.7

19
30
1 ● ◆
45
35


43.1
CREATIVE OUTPUTS…….…………………….…………

21

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
50.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
61.9
Industrial designs by origin/bn PPP$ GDP…………..……..
6.5

ICTs & business model creation†………………………....…….
65.7

ICTs & organizational model creation†…………………….... 66.3

36
34
21
49
26

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
42.2
Cultural & creative services exports, % total trade…....
0.5
National feature films/mn pop. 15-69………………….………
7.1
Entertainment & Media market/th pop. 15-69…………….
22.2
Printing & other media, % manufacturing…...................
1.0
Creative goods exports, % total trade………………………..
10.1

6 ● ◆
47
29
26
66 ○
1 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


30.1
Online creativity………………………………………..……….…….

17.1
Generic top-level domains (TLDs)/th pop. 15-69……….

48.5
Country-code TLDs/th pop. 15-69…………………..………….

56.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
17.2

26
30
15 ●
18
27

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
248

The Global Innovation Index 2019

◇

DENMARK

GII 2019 rank

7

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

12

5

High

EUR

5.8

300.3

52,120.5

8Score/Value Rank

INSTITUTIONS………………………………….…….…..
91.7

6 ●

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
91.1

93.0
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 90.1

10
7
9

1.2
1.2.1
1.2.2
1.2.3


95.3
Regulatory environment……………………………..………..

85.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
95.7

8.0
Cost of redundancy dismissal, salary weeks…………..

7
16
6 ●
1 ●

1.3
1.3.1
1.3.2


88.8
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
92.5

Ease of resolving insolvency*……………………………….…. 85.1

8
38
6 ●


63.1
HUMAN CAPITAL & RESEARCH………………...

4 ● ◆

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


73.5
Education…………………………………………………………..……
🕘🕘
7.6
Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 31.1
School life expectancy, years……………….…………….……. 19.1

PISA scales in reading, maths, & science…………......…
504.3
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.3

2 ● ◆
3 ● ◆
11◆
5 ●
16
41

2.2
2.2.1
2.2.2
2.2.3


42.6
Tertiary education……………………………………….……..….
🕘🕘
81.1
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….…. 21.0
Tertiary inbound mobility, %.......................................…. 10.8

29
18
58 ○
17

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
73.3
………………………..….....… 7,923.2
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
3.1

72.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*…………… 57.1

8
2 ● ◆
7
16
15


65.8
INFRASTRUCTURE……………………………….......

6 ●

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  93.1

ICT access*………………………………………………………….…….
82.5

ICT use*…………………………….....................................…….
90.0

100.0
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
100.0

2 ● ◆
18
1 ● ◆
1 ● ◆
1 ●

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
44.1
 …………………..…….
Electricity output, GWh/mn pop……
5,273.1
Logistics performance*…………………………………………….. 90.2
Gross capital formation, % GDP………………………….…….
21.4

33
40
8
83 ○

3.3
3.3.1
3.3.2
3.3.3


60.1
Ecological sustainability………………………………………..

15.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 81.6

ISO 14001 environmental certificates/bn PPP$ GDP.. 3.9

7
13
3 ●
28



MARKET SOPHISTICATION..………….…………… 66.9

9

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
75.3
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...…… 165.4

Microfinance gross loans, % GDP……………………….……. n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 57.1
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.1

26
35
n/a
12

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
68.2
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 70.9Domestic market scale, bn PPP$……………………………… 300.3

41
23
50
56 ○



740
6 ●
n/a

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
59.1

9

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


8
Knowledge workers…………………………………………….…..
71.6

Knowledge-intensive employment, %...........................
46.3 13Firms offering formal training, % firms………………………… n/a n/a
9
GERD performed by business, % GDP…………………..……
2.0

GERD financed by business, %……………………………........
58.5 13Females employed w/advanced degrees, %……………..
22.2 18

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


56.4
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
64.0
†State of cluster development .……..………..………………….. 63.9

GERD financed by abroad, %......................................... 8.9

JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP……………………..
5.8

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
49.3 20

1.0 39Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.7 94 ○
9
3.0
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.3 102 ○
13
Research talent, % in business enterprise……..………….. 60.5

 46.4KNOWLEDGE & TECHNOLOGY OUTPUTS....


7
19
19
46 ○
14
10

14

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 52.0

12.5
Patents by origin/bn PPP$ GDP……………….…………..….…

4.8
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.3
Scientific & technical articles/bn PPP$ GDP….…..…..…. 35.6
Citable documents H-index…………………….……….……..….
50.2

12
8
8
37 ○
1 ● ◆
15

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


48.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.3
New businesses/th pop. 15-64………………….…....………….
9.9

Computer software spending, % GDP…………..…………… 0.6

ISO 9001 quality certificates/bn PPP$ GDP…………..……
9.2
High- & medium-high-tech manufactures, %………………
0.4

16
81 ○
13
12
34
16

6.3
6.3.1
6.3.2
6.3.3
6.3.4


38.4
Knowledge diffusion……………………………………..…..…….

1.7Intellectual property receipts, % total trade……………….

5.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.7

FDI net outflows, % GDP…………………………….………….......
3.5

21
13
30
38
18


48.6
CREATIVE OUTPUTS…….…………………….…………

11

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
54.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
44.7
Industrial designs by origin/bn PPP$ GDP…………..…….. 6.8

ICTs & business model creation†………………………....……. 74.4

ICTs & organizational model creation†……………………....
78.9

23
57 ○
20
20
7

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
30.7
Cultural & creative services exports, % total trade…....
0.6
National feature films/mn pop. 15-69………………….………
13.5
Entertainment & Media market/th pop. 15-69…………….
78.0

Printing & other media, % manufacturing…...................
1.0
Creative goods exports, % total trade………………………..
1.6

28
44
9
4
69 ○
33

7.3
7.3.1
7.3.2
7.3.3
7.3.4


55.3
Online creativity………………………………………..……….…….

48.7
Generic top-level domains (TLDs)/th pop. 15-69……….

91.9
Country-code TLDs/th pop. 15-69…………………..………….

48.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
48.5

8
16
4 ● ◆
26
11

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

249

DOMINICAN REPUBLIC (THE)GII 2019 rank

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

88

90

Upper middle

LCN

10.9

188.3

18,424.6

87

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
54.3

94

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
47.5

66.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 38.0

89
74
92

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

54.9
39.8
35.3
26.2

98
74
91
103

1.3
1.3.1
1.3.2


60.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
83.4

Ease of resolving insolvency*……………………………….…. 37.5

103
90
106

◇


18.0 101
HUMAN CAPITAL & RESEARCH………………...

◇


37.3
Education…………………………………………………………..……

n/a
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 19.1

School life expectancy, years……………….…………….……. 14.2

PISA scales in reading, maths, & science…………......…
339.0

Pupil-teacher ratio, secondary…………………………......….
18.6

91
n/a
54
69
70 ○
82

2.2
2.2.1
2.2.2
2.2.3


16.9
Tertiary education……………………………………….……..….

59.9
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
11.6
Tertiary inbound mobility, %.......................................
….
1.7

98
◇
46 ●
97 ○ ◇
79

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

3.1
3.1.1
3.1.2
3.1.3
3.1.4

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇73

Information & communication technologies(ICTs). 55.8

ICT access*………………………………………………………….…….
46.1

ICT use*…………………………….....................................…….
43.0

66.0
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

83
96
82
79
77

68.0



◇

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 28.7
 …………………..…….
Electricity output, GWh/mn pop……
1,822.9
Logistics performance*……………………………………………..
28.0

Gross capital formation, % GDP………………………….……. 24.3

89
80
84
52 ●

3.3
3.3.1
3.3.2
3.3.3


49.4
Ecological sustainability………………………………………..

16.7
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
64.7
ISO 14001 environmental certificates/bn PPP$ GDP..  0.1

32 ● ◆
8 ● ◆
42 ● ◆118 ○

MARKET SOPHISTICATION..………….…………… 46.1

70

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
19.2 119 ○ ◇Ease of getting credit*…………………………………..…………..
45.0 94 ◇Domestic credit to private sector, % GDP…………...……
28.7 98
Microfinance gross loans, % GDP……………………….…….
0.1 57

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 56.7
Ease of protecting minority investors*…………..………….
56.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[27]
79
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
62.3
Applied tariff rate, weighted avg., %………………………….
4.2
†Intensity of local competition …………………………………… 70.3
Domestic market scale, bn PPP$……………………………… 188.3

59
75
56 ●
65


BUSINESS SOPHISTICATION..……….……………
26.3 [90]

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


44.6
INFRASTRUCTURE……………………………….......

87

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
27.1 [89]Knowledge-intensive employment, %...........................
16.0 88Firms offering formal training, % firms…………………………
23.4 68
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
9.4 70

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


25.2 [64]Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
31.8 101State of cluster development†.……..………..…………………..
46.9 59GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 85

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
26.5 95

0.5 62
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.5 83

0.5 107
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.8 44 ●
Research talent, % in business enterprise……..…………..
n/a n/a 15.6 95
KNOWLEDGE & TECHNOLOGY OUTPUTS....


0.9 129 ○ ◇
0.1 109
0.0 890.1 59 ○
0.3 128 ○ ◇
2.0 118 ○

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


31.8 87
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.5
31 ●
New businesses/th pop. 15-64………………….…....………….
1.5
61
Computer software spending, % GDP…………..……………
0.0 118 ○ ◇
ISO 9001 quality certificates/bn PPP$ GDP…………..……
1.0 106
High- & medium-high-tech manufactures, %……………… n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


14.1
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….

2.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.7

FDI net outflows, % GDP…………………………….………….......
0.1

81
n/a
52 ●
87
101


22.9
CREATIVE OUTPUTS…….…………………….…………

81

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
46.8
Industrial designs by origin/bn PPP$ GDP…………..……..
0.2

ICTs & business model creation†………………………....…….
59.3

ICTs & organizational model creation†……………………....
48.9

88
53 ●
101
68
84

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
16.9 [63]Cultural & creative services exports, % total trade…....
0.2 74
National feature films/mn pop. 15-69………………….………
3.5 52Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
n/a n/a
Creative goods exports, % total trade………………………..
2.2 25 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.9
2.5
1.1
5.7
0.0

86
71
78
78
92 ○NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
250

The Global Innovation Index 2019ECUADOR

GII 2019 rank

99

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank9898

Upper middle

LCN

16.9

199.7

11,718.1

97

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
24.6 102
INSTITUTIONS………………………………….…….…..
44.7 125 ○ ◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
43.4

52.6
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 38.8

◇95
118 ○ ◇
90

1.2
1.2.1
1.2.2
1.2.3


42.6
Regulatory environment……………………………..………..

15.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
27.8

31.8
Cost of redundancy dismissal, salary weeks…………..

◇
119
123 ○ ◇106
◇119 ○ ◇

1.3
1.3.1
1.3.2


48.0
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
70.6

Ease of resolving insolvency*……………………………….…. 25.4

126 ○ ◇121 ○ ◇126 ○ ◇

21.1
HUMAN CAPITAL & RESEARCH………………...

91

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


37.3
Education…………………………………………………………..……

5.0
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 5.3
🕘🕘School life expectancy, years……………….…………….……. 15.4

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
21.9

92
49 ●
104 ○ ◇
42 ●
n/a
92
◇

2.2
2.2.1
2.2.2
2.2.3


19.1
Tertiary education……………………………………….……..….
🕘🕘
45.5
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
15.8
🕘🕘Tertiary inbound mobility, %.......................................
….
0.8

97
64
83
92

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
6.9
🕘🕘Researchers, FTE/mn pop……………………………..…...……
400.7
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.4

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
13.6

70
71
68
43 ○ ◇
59 ●


43.4
INFRASTRUCTURE……………………………….......

78

Information & communication technologies(ICTs) 58.4

ICT access*………………………………………………………….…….
51.0

ICT use*…………………………….....................................…….
42.4

72.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

80
86
83
63
79

3.1
3.1.1
3.1.2
3.1.3
3.1.4

67.4



◇

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 32.2
 …………………..…….
Electricity output, GWh/mn pop……
1,666.5
Logistics performance*……………………………………………..
38.3

Gross capital formation, % GDP………………………….……. 25.3

73
84
61
44 ●

3.3
3.3.1
3.3.2
3.3.3


39.6
Ecological sustainability………………………………………..

11.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
57.4
ISO 14001 environmental certificates/bn PPP$ GDP..  1.0

57 ●
34 ●
76
64

MARKET SOPHISTICATION..………….…………… 43.3 89

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
24.7 109
Ease of getting credit*…………………………………..…………..
45.0 94 ◇Domestic credit to private sector, % GDP…………...……
91
32.3

Microfinance gross loans, % GDP……………………….…….
19 ●
0.9

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 46.7 [48]Ease of protecting minority investors*…………..………….
46.7 101Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
58.5
Applied tariff rate, weighted avg., %………………………….
7.0

†Intensity of local competition …………………………………… 69.8
Domestic market scale, bn PPP$……………………………… 199.7



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
37.4

Knowledge-intensive employment, %...........................
13.4
Firms offering formal training, % firms………………………… 73.7
🕘🕘
GERD performed by business, % GDP…………………..…… 0.2
🕘🕘
GERD financed by business, %……………………………........
0.1
Females employed w/advanced degrees, %……………..
8.8

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


14.9 119
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
34.5 95
State of cluster development†.……..………..…………………..
36.5 103🕘🕘
GERD financed by abroad, %.........................................
2.5 74JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 97
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 83

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


◇
Knowledge absorption……………………………………..……..
21.6 115
0.2 83
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.1 55 ●
0.0 127 ○ ◇
ICT services imports, % total trade…………..………………...
◇
FDI net inflows, % GDP…………………………….………………….
0.9 105🕘🕘Research talent, % in business enterprise……..…………..
15.0 61

6193◇
2 ● ◆
53
96 ○ ◇76◇◇

 15.0 100
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


29.7 95
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-2.0 108 ○ ◇
New businesses/th pop. 15-64………………….…....………….
n/a n/aComputer software spending, % GDP…………..……………
0.2 64

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 6.1
51 ●

High- & medium-high-tech manufactures, %………………
0.1 74

6.3
6.3.1
6.3.2
6.3.3
6.3.4


9.5 104
Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

0.4 84High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.2 116

FDI net outflows, % GDP…………………………….………….......
0.3 83

5.8
0.1
0.2
0.2
5.9
8.0

93
114
56
45
70
79


20.4
CREATIVE OUTPUTS…….…………………….…………

93

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
35.9

Trademarks by origin/bn PPP$ GDP…………..……….….….
42.8
Industrial designs by origin/bn PPP$ GDP…………..……..
1.0

ICTs & business model creation†………………………....…….
53.3

ICTs & organizational model creation†…………………….... 52.9

94
61
67
92
66

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

8.1 93
0.1 85
2.1 62n/a n/a
1.1 600.1 110

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.7
2.1
1.1
5.0
0.4

88
77
79
82
70

73
98 ◇
62
60 ●NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

251

EGYPTGII 2019 rank

92

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

74

106

Lower middle

NAWA

99.4

1,297.0

13,366.5

95

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
21.2 116 ○ ◇
INSTITUTIONS………………………………….…….…..
47.9 118 ○

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
39.7

56.1
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 31.5

106
105
104

1.2
1.2.1
1.2.2
1.2.3


40.8
Regulatory environment……………………………..………..

18.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
32.2

36.8
Cost of redundancy dismissal, salary weeks…………..

120 ○
120 ○ ◇95
121 ○

1.3
1.3.1
1.3.2


63.2
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
84.1

Ease of resolving insolvency*……………………………….…. 42.3

90
84
89


19.7
HUMAN CAPITAL & RESEARCH………………...

96

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


37.0
Education…………………………………………………………..……
🕘🕘
3.8
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 14.0
School life expectancy, years……………….…………….……. 13.1

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
15.2

94
89
86
80
n/a
68

2.2
2.2.1
2.2.2
2.2.3


11.4 108
Tertiary education……………………………………….……..….
🕘🕘
34.4
Tertiary enrolment, % gross………………………….….……….
77Graduates in science & engineering, %……………….….
11.2 99 ○ ◇Tertiary inbound mobility, %.......................................
….
1.8
77

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
10.7
Researchers, FTE/mn pop……………………………..…...……
669.4
Gross expenditure on R&D, % GDP………….………..……
0.6

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
21.9

55
61
51
◆
43 ○ ◇48 ● ◆
36.8
INFRASTRUCTURE……………………………….......

94

Information & communication technologies(ICTs) 49.4
ICT access*………………………………………………………….…….
55.6

ICT use*…………………………….....................................…….
34.7

53.5
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

96
78
95
101
100

3.1
3.1.1
3.1.2
3.1.3
3.1.4

53.9



3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 21.1
 …………………..…….
Electricity output, GWh/mn pop……
2,030.8
Logistics performance*……………………………………………..
35.6

Gross capital formation, % GDP………………………….……. 15.5

116 ○
76 ◆
66
118 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


39.9
Ecological sustainability………………………………………..

11.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
61.2
ISO 14001 environmental certificates/bn PPP$ GDP..  0.6

55 ◆
39 ●
59 ◆
81



MARKET SOPHISTICATION..………….…………… 41.0

97

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
25.8 103Ease of getting credit*…………………………………..…………..
65.0 54Domestic credit to private sector, % GDP…………...……
28.5 99Microfinance gross loans, % GDP……………………….…….
0.1 58

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 30.8
Ease of protecting minority investors*…………..………….
58.3
Market capitalization, % GDP………………………………...….
15.5
Venture capital deals/bn PPP$ GDP……………….……....
0.0

119 ○
68
63
63

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
66.4
Applied tariff rate, weighted avg., %………………………….
7.4
†Intensity of local competition …………………………………… 65.7
Domestic market scale, bn PPP$……………..……………… 1,297.0

48 ●
101
77
21 ● ◆



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
21.1 106
Knowledge-intensive employment, %...........................
30.3 43 ● ◆Firms offering formal training, % firms…………………………
10.0 89 ○ ◇
GERD performed by business, % GDP…………………..……
0.0 76
GERD financed by business, %……………………………........ 5.4 79
Females employed w/advanced degrees, %…………….. 5.5 89

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


17.5 110
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
30.0 106State of cluster development†.……..………..…………………..
53.9 38 ● ◆
GERD financed by abroad, %.........................................
0.0 101 ○
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 98 ○
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 88

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
24.9 103
71
0.4Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.8 73
1.1 68
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.6 69Research talent, % in business enterprise……..…………..
6.5 69

 22.1 64
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 11.1
🕘🕘
0.8
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
7.1
Citable documents H-index…………………….……….……..…. 15.5

66
68
81
n/a
61
48 ●

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.5
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..……………
0.4
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.8
🕘🕘High- & medium-high-tech manufactures, %………………
0.2

32 ●
32 ●
n/a
21 ● ◆
89
52

6.3
6.3.1
6.3.2
6.3.3
6.3.4


11.6 94
Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

0.1 113High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.2 73

FDI net outflows, % GDP…………………………….………….......
0.1 102
21.1
CREATIVE OUTPUTS…….…………………….…………

89

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
35.8
🕘🕘
Trademarks by origin/bn PPP$ GDP…………..……….….….
11.2
Industrial designs by origin/bn PPP$ GDP…………..……..
1.7

ICTs & business model creation†………………………....…….
61.0

ICTs & organizational model creation†……………………....
56.0

95
104
56
59
57

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
12.1
Cultural & creative services exports, % total trade…....
0.1
🕘🕘National feature films/mn pop. 15-69………………….………
0.6
Entertainment & Media market/th pop. 15-69…………….
0.5
🕘🕘
Printing & other media, % manufacturing…...................
1.4

Creative goods exports, % total trade………………………..
1.1

77
80
93
61 ○
35 ●
41 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.7 103
Online creativity………………………………………..……….…….

1.2
91
Generic top-level domains (TLDs)/th pop. 15-69……….

0.0 123 ○Country-code TLDs/th pop. 15-69…………………..………….

2.5 97
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.1 82NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
252

The Global Innovation Index 2019

EL SALVADORGII 2019 rank

108

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

116

97

Lower middle

LCN

6.4

53.7

8,041.2

104

Score/Value Rank

INSTITUTIONS………………………………….…….…..
53.9

95

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
45.6

61.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 37.7

92
91
93

1.2
1.2.1
1.2.2
1.2.3


54.1
Regulatory environment……………………………..………..

37.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
23.7

22.9
Cost of redundancy dismissal, salary weeks…………..

101
83
114
95

1.3
1.3.1
1.3.2


62.0
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
78.4

Ease of resolving insolvency*……………………………….…. 45.6

94
111
80


18.3
HUMAN CAPITAL & RESEARCH………………...

99

Score/Value Rank

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


29.7 108
Education…………………………………………………………..……

3.8 90
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 15.1
84

School life expectancy, years……………….…………….……. 11.7 92

PISA scales in reading, maths, & science…………......… n/a n/a
Pupil-teacher ratio, secondary…………………………......….
27.8 102

2.2
2.2.1
2.2.2
2.2.3


24.4
Tertiary education……………………………………….……..….

28.7
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
22.3
Tertiary inbound mobility, %.......................................
….
0.4

82
84
48
99

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.9
🕘🕘Researchers, FTE/mn pop……………………………..…...……
65.9
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

107
89
96
43 ○ ◇78 ○ ◇
35.7
INFRASTRUCTURE……………………………….......

98

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 52.2
ICT access*………………………………………………………….…….
48.3

ICT use*…………………………….....................................…….
33.0

62.5
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
65.2

92
93
97
89
80

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
17.9
 …………………..……. 942.4
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 23.9
Gross capital formation, % GDP………………………….…….
16.1

121
95
95
116

3.3
3.3.1
3.3.2
3.3.3


36.8
Ecological sustainability………………………………………..

11.4
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
53.9
ISO 14001 environmental certificates/bn PPP$ GDP..  0.4

70
38 ●
87
94




BUSINESS SOPHISTICATION..……….……………
25.5

97

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
33.0Knowledge-intensive employment, %...........................
10.6
Firms offering formal training, % firms………………………… 53.8
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
40.2
Females employed w/advanced degrees, %……………..
3.5

79
99
15 ● ◆
69
◆
44
95

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


12.4 124 ○ ◇Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
27.6 113State of cluster development†.……..………..…………………..
29.7 122 ○ ◇71
GERD financed by abroad, %.........................................
3.0
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 107 ○
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.1 81
1.3 25 ● ◆Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.7 47 ●
0.6 100
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.8 84
Research talent, % in business enterprise……..…………..
n/a n/a◇ 7.9 121KNOWLEDGE & TECHNOLOGY OUTPUTS....

◇



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 0.9 128 ○
0.1 116
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0
91
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.1 56

Scientific & technical articles/bn PPP$ GDP….…..…..…. 0.5 126 ○Citable documents H-index…………………….……….……..….
1.4 123 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.9 60
Knowledge diffusion……………………………………..…..…….

0.5 26 ● ◆Intellectual property receipts, % total trade……………….

2.7 47 ●High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.2 50 ●
FDI net outflows, % GDP…………………………….………….......
-0.3 122 ○ ◇

5.1 [121]n/a n/a0.5 86
0.0 105
4.0 64n/a n/a◇◇◇

MARKET SOPHISTICATION..………….…………… 44.8

81

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
36.7
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...……
51.7

Microfinance gross loans, % GDP……………………….…….
0.4

63
20 ●
64
34

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 38.3 [85]Ease of protecting minority investors*…………..………….
38.3 122 ○ ◇Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
59.2
Applied tariff rate, weighted avg., %………………………….
2.1
†Intensity of local competition …………………………………… 72.8
Domestic market scale, bn PPP$……………………………… 53.7




20.4
CREATIVE OUTPUTS…….…………………….…………

94

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
38.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
98.2
Industrial designs by origin/bn PPP$ GDP…………..……..
0.2

ICTs & business model creation†………………………....…….
49.3

ICTs & organizational model creation†……………………....
42.7

79
15 ●
102
108
102

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

4.0 [107]
0.0 113
0.3 102 ○n/a n/an/a n/a0.7 53

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.6
2.5
0.5
4.8
0.0

92
73
◆
92
83
95 ○

7255 ◆
40 ● ◆95

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

253

ESTONIA

GII 2019 rank

24

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

19

27

High

EUR

1.3

44.2

34,095.8

24

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
81.7

23

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
78.3

87.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 73.6

25
18
27

1.2
1.2.1
1.2.2
1.2.3


87.8
Regulatory environment……………………………..………..

86.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
80.3

12.9
Cost of redundancy dismissal, salary weeks…………..

18
14
22
39

1.3
1.3.1
1.3.2


78.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
95.3

Ease of resolving insolvency*……………………………….…. 62.5

36
13
44

◇


42.1
HUMAN CAPITAL & RESEARCH………………...

36

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


56.9
Education…………………………………………………………..……

5.2
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 18.1
School life expectancy, years……………….…………….……. 16.1

PISA scales in reading, maths, & science…………......…
524.3
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
8.8

40
41
60
◇
34
4 ●
16
◆

2.2
2.2.1
2.2.2
2.2.3


46.0
Tertiary education……………………………………….……..….
🕘🕘
71.4
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
27.5
Tertiary inbound mobility, %.......................................
….
6.8

20
25
21
33

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
23.4
………………………....…...… 3,568.9
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
1.3

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
21.6

◇
44
26
◇
27
◇
43 ○ ◇
49
◇


61.5
INFRASTRUCTURE……………………………….......

16

Information & communication technologies(ICTs).  85.7

ICT access*………………………………………………………….…….
81.6

ICT use*…………………………….....................................…….
79.9

90.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
91.0

20
20
16
26
27

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 45.8
 …………………..…….
Electricity output, GWh/mn pop……
9,962.1
Logistics performance*……………………………………………..
58.4

Gross capital formation, % GDP………………………….……. 26.4

30
15
35
38

3.3
3.3.1
3.3.2
3.3.3


53.1
Ecological sustainability………………………………………..

6.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
64.3
ISO 14001 environmental certificates/bn PPP$ GDP..  13.5

18
90 ○
44 ◇
1 ● ◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4



◇
◇

◇

28

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
57.4

Knowledge-intensive employment, %...........................
45.5
Firms offering formal training, % firms………………………… 35.2

GERD performed by business, % GDP…………………..…… 0.6

GERD financed by business, %……………………………........
48.2
Females employed w/advanced degrees, %……………..
25.9

26
◇
15
40
34
◇
31
8 ● ◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


30.3
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
46.4
State of cluster development†.……..………..…………………..
45.6
GERD financed by abroad, %.........................................
13.6
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.8

◇
46
◇
48
73 ○ ◇
31
24
29
◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
40.0

0.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.6

2.2
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.3
Research talent, % in business enterprise……..………….. 33.9

◇
40
81 ○ ◇
36
23
75 ○
39◇ 36.0 26
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇
33
40
◇
29
◇
21
9 ●
47
◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


53.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.6
New businesses/th pop. 15-64………………….…....………….
20.8
Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..……
25.2
High- & medium-high-tech manufactures, %……………… 0.2

1230
2 ● ◆
79 ○ ◇
10 ● ◆
◇
55

6.3
6.3.1
6.3.2
6.3.3
6.3.4


28.3
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

8.6
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.6

FDI net outflows, % GDP…………………………….………….......
0.4

34
64 ○ ◇
19
22
72 ○


51.7
CREATIVE OUTPUTS…….…………………….…………

8 ●

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
58.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
81.1
Industrial designs by origin/bn PPP$ GDP…………..……..
6.4

ICTs & business model creation†………………………....…….
75.2

ICTs & organizational model creation†…………………….... 79.3

11
25
22
17
5 ●

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
38.6 10 ●
Cultural & creative services exports, % total trade…....
1.6
11

National feature films/mn pop. 15-69………………….………
19.8
4 ● ◆

Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
2.1 16Creative goods exports, % total trade………………………..
1.4 3844
79 ○ ◇
n/a
16

7.3
7.3.1
7.3.2
7.3.3
7.3.4


50.6
Online creativity………………………………………..……….…….

9.8
Generic top-level domains (TLDs)/th pop. 15-69……….

36.6
Country-code TLDs/th pop. 15-69…………………..………….

133.5
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
66.0

◇

◇


Credit……………………………………………………….………………
50.3
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
66.4

Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 47.3
Ease of protecting minority investors*…………..………….
56.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.1

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
60.2 67◇Applied tariff rate, weighted avg., %………………………….
1.8 23
†
10
Intensity of local competition …………………………………… 79.7
Domestic market scale, bn PPP$………………………………
44.2 100 ○ ◇

31
40
45
n/a

12
40
◇
17
2 ● ◆
7 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
The Global Innovation Index 2019◇

Knowledge creation………………………………………........... 26.0

2.2
Patents by origin/bn PPP$ GDP……………….…………..….…

1.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
1.3
Scientific & technical articles/bn PPP$ GDP….…..…..…. 28.7
Citable documents H-index…………………….……….……..….
15.8

4.1
4.1.1
4.1.2
4.1.3

254

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5


MARKET SOPHISTICATION..………….…………… 52.6 45


BUSINESS SOPHISTICATION..……….……………
42.6

ETHIOPIA

GII 2019 rank

111

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

80

124

Low

SSF

105.0

195.8

2,160.8

n/a

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
47.5 119
BUSINESS SOPHISTICATION..……….……………
20.2 118

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
37.9

54.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 29.6

114
111
113

1.2
1.2.1
1.2.2
1.2.3


53.8
Regulatory environment……………………………..………..

15.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
34.4

19.1
Cost of redundancy dismissal, salary weeks…………..

103
124
93
79 ●

1.3
1.3.1
1.3.2


50.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
70.8
Ease of resolving insolvency*……………………………….…. 30.5

124
120
118

◇
◇
◇


10.6 124
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


22.7
Education…………………………………………………………..……

4.7
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 16.6
🕘🕘
School life expectancy, years……………….…………….……. 8.4

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
40.4

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
3.3
🕘🕘Researchers, FTE/mn pop……………………………..…...……
45.0
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.6

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

◆
86
92
52 ● ◆43 ○ ◇78 ○ ◇
35.6
INFRASTRUCTURE……………………………….......

99

121
57 ●
74
115
n/a
113 ○ ◇

5.8 [119]8.1 112n/a n/an/a n/a

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 38.5 108

ICT access*………………………………………………………….…….
22.5 124
ICT use*…………………………….....................................…….
10.9 122
63.2
Government’s online service*…………………………….…….
87E-participation*…………………………………………………….…….
57.3 95

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
48.9
 …………………..…….
Electricity output, GWh/mn pop……
109.6

Logistics performance*…………………………………………….. n/a
Gross capital formation, % GDP………………………….…….
39.5

3.3
3.3.1
3.3.2
3.3.3


19.4 126
Ecological sustainability………………………………………..

3.1 116
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
44.8 109
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.0 127◇◆

21 ● ◆118
n/a
7 ● ◆



MARKET SOPHISTICATION..………….…………… 27.3 128

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
7.7 127
Ease of getting credit*…………………………………..…………..
15.0 124
Domestic credit to private sector, % GDP…………...……
n/a n/a
Microfinance gross loans, % GDP……………………….…….
0.0 62

◇
◇

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 28.3 [122]Ease of protecting minority investors*…………..………….
28.3 127 ○ ◇Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
45.8 116🕘🕘Applied tariff rate, weighted avg., %………………………….
12.1 120

Intensity of local competition†…………………………………… 45.6 125 ○ ◇Domestic market scale, bn PPP$……………………………… 220.7 59 ● ◆



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
8.5 124🕘🕘
Knowledge-intensive employment, %...........................
4.5 108

Firms offering formal training, % firms………………………… 20.8 73
🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 84
🕘🕘
GERD financed by business, %……………………………........
0.7 92
🕘🕘Females employed w/advanced degrees, %……………..
0.3 115

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


17.4 112
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
43.9 54 ●
State of cluster development†.……..………..…………………..
42.7 83🕘🕘
GERD financed by abroad, %.........................................
◇
2.1 75
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 99
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
34.7 58 ●
0.0 109
Intellectual property payments, % total trade………….....
🕘🕘
6 ● ◆
High-tech imports, % total trade………………..………………..
21.8

0.7 89ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
4.8 32 ●🕘🕘
Research talent, % in business enterprise……..…………..
0.5 81

 17.0 88
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 9.0n/a
Patents by origin/bn PPP$ GDP……………….…………..….…
n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
4.9
Citable documents H-index…………………….……….……..….
7.0

[73]
n/a
n/a
n/a
82
83

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


39.8
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
5.5New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..…………… 0.0

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.3
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

49 ● ◆
5 ● ◆
n/a
127 ○ ◇
125
70

6.3
6.3.1
6.3.2
6.3.3
6.3.4


2.1 129 ○ ◇Knowledge diffusion……………………………………..…..…….

0.0 105
Intellectual property receipts, % total trade……………….
🕘🕘
0.1 114High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.6 97

FDI net outflows, % GDP…………………………….………….......
n/a n/a◆
23.2 [80]
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
39.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
n/aIndustrial designs by origin/bn PPP$ GDP…………..……..
n/a
ICTs & business model creation†………………………....……. 40.6

ICTs & organizational model creation†……………………....
38.2

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
14.2 [71]🕘🕘Cultural & creative services exports, % total trade…....
0.0 100National feature films/mn pop. 15-69………………….………
n/a n/aEntertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
1.8 21 ●🕘🕘
Creative goods exports, % total trade………………………..
0.0 115

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

[70]
n/a
n/a
119
116

0.0 129 ○
0.0 129 ○ ◇
0.0 129 ○ ◇
0.0 123
0.0 98 ○ ◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

255

FINLANDGII 2019 rank

6

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

7

7

High

EUR

5.5

257.2

46,429.5

7

Score/Value Rank

INSTITUTIONS………………………………….…….…..
93.6

3 ● ◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
92.2

89.5
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 93.5

5
15
4 ●

1.2
1.2.1
1.2.2
1.2.3


96.1
Regulatory environment……………………………..………..

90.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
100.0

10.1
Cost of redundancy dismissal, salary weeks…………..

5
8
1 ●
31

1.3
1.3.1
1.3.2


92.6
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
92.4

Ease of resolving insolvency*……………………………….…. 92.8

1 ● ◆
39
2 ● ◆


63.4
HUMAN CAPITAL & RESEARCH………………...

2 ● ◆

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


69.9
Education…………………………………………………………..……

7.1
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 25.8
School life expectancy, years……………….…………….……. 19.3

PISA scales in reading, maths, & science…………......…
522.7
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
13.2

4 ● ◆
10◆
22
3 ● ◆
6
58 ○

2.2
2.2.1
2.2.2
2.2.3


53.0
Tertiary education……………………………………….……..….
🕘🕘
87.0
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….…. 29.5
Tertiary inbound mobility, %.......................................….
7.8

10
10
15
29

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
67.3
……………………..…........… 6,707.5
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
2.8

79.7
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
48.0

10
6
10
11
19


62.1
INFRASTRUCTURE……………………………….......

12

Information & communication technologies(ICTs).  87.5

ICT access*………………………………………………………….…….
73.9

ICT use*…………………………….....................................…….
79.7

96.5
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 100.0

16
52 ◇
17
8
1 ●

3.1
3.1.1
3.1.2
3.1.3
3.1.4



3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 51.7
………………….……. 12,236.8
Electricity output, GWh/mn pop……

Logistics performance*……………………………………………..
89.1
Gross capital formation, % GDP………………………….…….
22.9

13
10
10
66 ○

3.3
3.3.1
3.3.2
3.3.3


47.0
Ecological sustainability………………………………………..

6.3
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 78.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 6.0

42
96 ○
1018

MARKET SOPHISTICATION..………….…………… 57.3

27

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
54.9
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...…… 94.5

Microfinance gross loans, % GDP……………………….……. n/a25
54 ○
29
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 51.7
Ease of protecting minority investors*…………..………….
58.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.2

34
68 ○
n/a
11

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
65.2
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 61.7
Domestic market scale, bn PPP$……………………………… 257.2

52
23
99 ○ ◇58

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
63.9

5

◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


6
Knowledge workers…………………………………………….…..
74.0Knowledge-intensive employment, %...........................
47.4 10Firms offering formal training, % firms………………………… n/a n/a
GERD performed by business, % GDP…………………..……
1.8 10
GERD financed by business, %……………………………........
57.0 15
Females employed w/advanced degrees, %……………..
27.2
5

◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


62.6
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
74.7
†State of cluster development .……..………..………………….. 64.9

GERD financed by abroad, %......................................... 12.1
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP……………………..
6.5

4 ● ◆
51735
10
3 ● ◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
54.9

1.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.7
ICT services imports, % total trade…………..………………... 3.7

FDI net inflows, % GDP…………………………….………………….
4.9
Research talent, % in business enterprise……..…………..
55.5

12
37
60 ○
4 ● ◆
31
20

 55.1KNOWLEDGE & TECHNOLOGY OUTPUTS....

9



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 58.5

13.1
Patents by origin/bn PPP$ GDP……………….…………..….…

7.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 2.0
Scientific & technical articles/bn PPP$ GDP….…..…..…. 30.9
Citable documents H-index…………………….……….……..….
42.9

9
7
1 ● ◆
11
6
◆
19

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


44.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.3
New businesses/th pop. 15-64………………….…....………….
4.0

Computer software spending, % GDP…………..…………… 0.6

ISO 9001 quality certificates/bn PPP$ GDP…………..……
10.8
High- & medium-high-tech manufactures, %………………
0.3

28
57 ○
32
17
29
34

6.3
6.3.1
6.3.2
6.3.3
6.3.4


61.9
Knowledge diffusion……………………………………..…..…….

3.3
Intellectual property receipts, % total trade……………….

4.4
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
8.1

FDI net outflows, % GDP…………………………….………….......
4.0

7
6
34
5
14


48.1
CREATIVE OUTPUTS…….…………………….…………

13

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
55.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
44.7
Industrial designs by origin/bn PPP$ GDP…………..…….. 3.9

ICTs & business model creation†………………………....……. 84.4

ICTs & organizational model creation†……………………....
80.4

19
58 ○
32
2 ● ◆
3 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
24.7
Cultural & creative services exports, % total trade…....
1.0National feature films/mn pop. 15-69………………….………
10.7
Entertainment & Media market/th pop. 15-69…………….
57.5
Printing & other media, % manufacturing…...................
1.1
Creative goods exports, % total trade……………………….. 0.5

44
29
15
13
58 ○
56

7.3
7.3.1
7.3.2
7.3.3
7.3.4


57.3
Online creativity………………………………………..……….…….

29.2
Generic top-level domains (TLDs)/th pop. 15-69……….

34.0
Country-code TLDs/th pop. 15-69…………………..………….

98.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
100.0

6
21
18
8
1 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
256

The Global Innovation Index 2019

◆◆

FRANCEGII 2019 rank

16

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

14

16

High

EUR

65.2

2,968.5

45,775.1

16

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
53.3

INSTITUTIONS………………………………….…….…..
83.2

19

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
80.4

82.5
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 79.3

22
32
21

1.2
1.2.1
1.2.2
1.2.3


85.5
Regulatory environment……………………………..………..

73.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
84.4

13.0
Cost of redundancy dismissal, salary weeks…………..

20
26
19
41

1.3
1.3.1
1.3.2


83.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
93.3

Ease of resolving insolvency*……………………………….…. 74.1

21
27
26


55.8
HUMAN CAPITAL & RESEARCH………………...

11

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.8
Education…………………………………………………………..……

5.5
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 26.5
School life expectancy, years……………….…………….……. 15.5

PISA scales in reading, maths, & science…………......…
495.7
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.9

32
27
19
◆
38
24
57 ○

2.2
2.2.1
2.2.2
2.2.3


44.8
Tertiary education……………………………………….……..….
🕘🕘
64.4
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
25.6
Tertiary inbound mobility, %.......................................
….
9.9

25
37
26
20

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
64.6
Researchers, FTE/mn pop……………………………..…...……
4,441.1
Gross expenditure on R&D, % GDP………….………..……
2.2

87.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
69.3

11
18
12
7 ●
10 ●


62.3
INFRASTRUCTURE……………………………….......

11

Information & communication technologies(ICTs) 89.6
ICT access*………………………………………………………….…….
83.4

ICT use*…………………………….....................................…….
80.3

97.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
96.6

10 ●
16
14
4 ●
13

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 47.5
 …………………..…….
Electricity output, GWh/mn pop……
8,177.3
Logistics performance*……………………………………………..
83.3
Gross capital formation, % GDP………………………….……. 23.7

29
20
16
59 ○

3.3
3.3.1
3.3.2
3.3.3


49.9
Ecological sustainability………………………………………..

10.3
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
84.0
ISO 14001 environmental certificates/bn PPP$ GDP..  2.2

31
46
2 ● ◆
46

3.1
3.1.1
3.1.2
3.1.3
3.1.4





◇

MARKET SOPHISTICATION..………….…………… 62.9

12

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
49.2
Ease of getting credit*…………………………………..…………..
50.0
Domestic credit to private sector, % GDP…………...……
101.6

Microfinance gross loans, % GDP……………………….…….
n/a33
87 ○
26
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 57.5
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
93.2
Venture capital deals/bn PPP$ GDP……………….……....
0.2

25
35
14
5 ●

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
81.9
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 80.0
Domestic market scale, bn PPP$…………………………… 2,968.5

6 ●
23
8 ●
10 ●



19

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
66.2 15
Knowledge-intensive employment, %...........................
45.1 16
Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..…… 1.4 13
🕘🕘
GERD financed by business, %……………………………........ 54.0 20
Females employed w/advanced degrees, %……………..
21.6 21

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


41.6
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
54.6
State of cluster development†.……..………..…………………..
63.2
🕘🕘
GERD financed by abroad, %.........................................
7.6
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 3.5

26
◇
30
20
51 ○
30
14

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
52.1

1.9
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.8

2.2
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.8
Research talent, % in business enterprise……..………….. 60.3

17
14
23
22
85 ○
14

 45.0KNOWLEDGE & TECHNOLOGY OUTPUTS....

15



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 42.7

8.8
Patents by origin/bn PPP$ GDP……………….…………..….…

2.7
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.1

Scientific & technical articles/bn PPP$ GDP….…..…..…. 15.8
Citable documents H-index…………………….……….……..…. 79.2

16
15
13
57 ○
33
5 ● ◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


44.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.7
New businesses/th pop. 15-64………………….…....………….
1.8

Computer software spending, % GDP…………..……………
0.6
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 7.6
High- & medium-high-tech manufactures, %………………
0.5

29
69 ○
52 ○
10 ●
41
13

6.3
6.3.1
6.3.2
6.3.3
6.3.4


47.7
Knowledge diffusion……………………………………..…..…….

2.0Intellectual property receipts, % total trade……………….

12.8
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.2

FDI net outflows, % GDP…………………………….………….......
2.4

13
12
10 ●
51 ○
27


45.0
CREATIVE OUTPUTS…….…………………….…………

16

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
58.8
Trademarks by origin/bn PPP$ GDP…………..……….….….
97.9
Industrial designs by origin/bn PPP$ GDP…………..……..
6.3

ICTs & business model creation†………………………....…….
77.2

ICTs & organizational model creation†…………………….... 70.9

10 ●
16
24
13
19

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
26.6
Cultural & creative services exports, % total trade…....
1.3
National feature films/mn pop. 15-69………………….………
6.8
Entertainment & Media market/th pop. 15-69…………….
52.3
Printing & other media, % manufacturing…...................
1.0
Creative goods exports, % total trade………………………..
1.7

39
20
31
15
61 ○
32

7.3
7.3.1
7.3.2
7.3.3
7.3.4


35.7
Online creativity………………………………………..……….…….

40.9
Generic top-level domains (TLDs)/th pop. 15-69……….

20.7
Country-code TLDs/th pop. 15-69…………………..………….

64.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
37.7

23
18
28
15
14

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

257

GEORGIA

GII 2019 rank

48

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

60

44

Lower middle

NAWA

3.9

43.0

11,485.4

59

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
74.3

36

◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
64.2

71.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 60.4

45
58
42

◆
◆
◆

1.2
1.2.1
1.2.2
1.2.3


80.8
Regulatory environment……………………………..………..

70.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
55.1

8.6
Cost of redundancy dismissal, salary weeks…………..

◆
28
30
◆
49
◆
17 ● ◆

1.3
1.3.1
1.3.2


77.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
99.3
Ease of resolving insolvency*……………………………….…. 56.0

◆38
2 ● ◆
55
◆


30.5
HUMAN CAPITAL & RESEARCH………………...

63

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


51.5
Education…………………………………………………………..……

3.8
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. 15.4

PISA scales in reading, maths, & science…………......…
405.4
Pupil-teacher ratio, secondary…………………………......….
7.4

55
85
n/a
◆
39
61 ○
5 ● ◆

2.2
2.2.1
2.2.2
2.2.3


34.3
Tertiary education……………………………………….……..….

57.5
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
21.9
Tertiary inbound mobility, %.......................................….
5.6

57
50
52
38

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
5.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
1,336.6
🕘🕘Gross expenditure on R&D, % GDP………….………..……

75
45
◆
79
43 ○ ◇78 ○ ◇Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.3
0.0
0.0

◆
◆


44.7
INFRASTRUCTURE……………………………….......

72

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 64.3

ICT access*………………………………………………………….…….
72.1

ICT use*…………………………….....................................…….
53.3

69.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
62.4

71
59
67
70
84

◆
◆
◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
39.2
 …………………..…….
Electricity output, GWh/mn pop……
3,111.3
Logistics performance*…………………………………………….. 17.7
Gross capital formation, % GDP………………………….…….
35.2

46
61 ◆
109 ○
1 1 ● ◆

3.3
3.3.1
3.3.2
3.3.3


30.5
Ecological sustainability………………………………………..

7.0
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
55.7
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

91
86
80
98



MARKET SOPHISTICATION..………….…………… 62.1

15 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
47.1
Ease of getting credit*…………………………………..…………..
85.0
Domestic credit to private sector, % GDP…………...…… 62.5
Microfinance gross loans, % GDP……………………….…….
1.6

40
1 1 ●
52
15

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 81.7
Ease of protecting minority investors*…………..………….
81.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
57.4 79🕘🕘
5 ● ◆
Applied tariff rate, weighted avg., %………………………….
0.7
Intensity of local competition†…………………………………… 62.7 94
Domestic market scale, bn PPP$……………………………… 43.0 102 ○ ◇

[1]
2 ● ◆
n/an/aBUSINESS SOPHISTICATION..……….……………
29.5

70

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
32.1 [81]Knowledge-intensive employment, %...........................
25.3 54
Firms offering formal training, % firms………………………… 10.5 88 ○ ◇
GERD performed by business, % GDP…………………..……
n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
17.6 32
◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


25.0 65
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
32.0 98State of cluster development†.……..………..…………………..
34.8 107 ○🕘🕘
GERD financed by abroad, %.........................................
14.7 28
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.1 19◆
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.2 48
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.4

0.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.5

0.7
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….…………………. 11.6
Research talent, % in business enterprise……..…………..
n/a

78
88
63
90
1 1 ● ◆n/a

 22.5 62
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 16.1

1.9
Patents by origin/bn PPP$ GDP……………….…………..….…

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 1.4
Scientific & technical articles/bn PPP$ GDP….…..…..….
14.1
Citable documents H-index…………………….……….……..….
9.4

55
48
59
19
37
73

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


38.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
5.0
New businesses/th pop. 15-64………………….…....………….
8.4
Computer software spending, % GDP…………..…………… 0.1

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 3.3
High- & medium-high-tech manufactures, %………………
0.1

55
8 ● ◆
17◆
89
74
91 ○

6.3
6.3.1
6.3.2
6.3.3
6.3.4


12.9
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

0.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.1

FDI net outflows, % GDP…………………………….………….......
2.2

86
90 ○
90
80
28
◆


29.1
CREATIVE OUTPUTS…….…………………….…………

58

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
44.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
68.8
Industrial designs by origin/bn PPP$ GDP…………..……..
11.8

ICTs & business model creation†………………………....……. 52.1

ICTs & organizational model creation†…………………….... 43.6

50
29
12 ● ◆
97
99 ○

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
16.9 62
Cultural & creative services exports, % total trade…....
0.5 51National feature films/mn pop. 15-69………………….………
6.6 33Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.6 29Creative goods exports, % total trade………………………..
0.1 97

7.3
7.3.1
7.3.2
7.3.3
7.3.4


9.9
Online creativity………………………………………..……….…….

1.8
Generic top-level domains (TLDs)/th pop. 15-69……….

3.4
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
44.5
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
4.3

53
82
57
31
52

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
258

The Global Innovation Index 2019

◆

◆

◆
◆
◆

GERMANYGII 2019 rank

9

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

9

12

High

EUR

82.3

4,379.1

52,558.7

9Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
56.1

INSTITUTIONS………………………………….…….…..
86.4

16

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
88.1

87.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 88.2

13
18
11

1.2
1.2.1
1.2.2
1.2.3


84.4
Regulatory environment……………………………..………..

89.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
88.9

21.6
Cost of redundancy dismissal, salary weeks…………..

23
11
16
89 ○ ◇

1.3
1.3.1
1.3.2


86.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
83.6

Ease of resolving insolvency*……………………………….…. 90.1

15
88 ○ ◇
4 ● ◆


63.2
HUMAN CAPITAL & RESEARCH………………...

3 ● ◆

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.8
Education…………………………………………………………..……

4.8
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 23.0
School life expectancy, years……………….…………….……. 17.1

PISA scales in reading, maths, & science…………......…
508.1
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.0

33
55 ○
34
17
11
48

2.2
2.2.1
2.2.2
2.2.3


58.6
Tertiary education……………………………………….……..….
🕘🕘
68.3
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….…. 36.0
Tertiary inbound mobility, %.......................................….
8.0

5 ● ◆
31
4 ● ◆
28

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
73.4

Researchers, FTE/mn pop……………………………..…...……
5,036.2
Gross expenditure on R&D, % GDP………….………..……
3.0

97.2
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
69.1

7
12
8
2 ● ◆
11


62.0
INFRASTRUCTURE……………………………….......

13

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 88.2
ICT access*………………………………………………………….…….
90.3

ICT use*…………………………….....................................…….
77.2

93.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 92.1

15
6 ●
22
17
23

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
47.8
 …………………..…….
Electricity output, GWh/mn pop……
7,849.4
Logistics performance*…………………………………………….. 100.0Gross capital formation, % GDP………………………….…….
20.4

26
22
1 ● ◆
91 ○

3.3
3.3.1
3.3.2
3.3.3


50.1
Ecological sustainability………………………………………..

11.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 78.4
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.4

29
34
13
41


Knowledge workers…………………………………………….…..
67.1 13
17Knowledge-intensive employment, %...........................
44.7
Firms offering formal training, % firms………………………… n/a n/a
7
GERD performed by business, % GDP…………………..…… 2.1

GERD financed by business, %……………………………........
65.2
7

Females employed w/advanced degrees, %……………..
13.2 51

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


53.9
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
72.8
†State of cluster development .……..………..………………….. 75.4

GERD financed by abroad, %......................................... 5.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
5.9

10
6
2 ● ◆
60 ○
32
◇
9

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
47.5

0.8
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.6

2.1
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….…………………. 1.8

Research talent, % in business enterprise……..………….. 59.7

22
51
37
25
86 ○
15

 52.7KNOWLEDGE & TECHNOLOGY OUTPUTS....

10



◇

Knowledge creation………………………………………........... 66.6

17.5
Patents by origin/bn PPP$ GDP……………….…………..….…

4.5
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 2.3
Scientific & technical articles/bn PPP$ GDP….…..…..…. 15.7
Citable documents H-index…………………….……….……..….
87.9

6 ●
1 ● ◆
9935
3 ● ◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


48.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.6
New businesses/th pop. 15-64………………….…....………….
1.3
Computer software spending, % GDP…………..…………… 0.6

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 15.4
High- & medium-high-tech manufactures, %………………
0.6

17
73 ○
64 ○
18
22
6

6.3
6.3.1
6.3.2
6.3.3
6.3.4


42.7
Knowledge diffusion……………………………………..…..…….

1.2Intellectual property receipts, % total trade……………….

11.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.3

FDI net outflows, % GDP…………………………….………….......
3.3

17
17
14
46
22


49.6
CREATIVE OUTPUTS…….…………………….…………

10

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
63.8

Trademarks by origin/bn PPP$ GDP…………..……….….….
65.2
Industrial designs by origin/bn PPP$ GDP…………..……..
14.5

ICTs & business model creation†………………………....……. 78.4

ICTs & organizational model creation†…………………….... 78.0

5 ● ◆
30
6
◆
12
8

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
26.3
Cultural & creative services exports, % total trade…....
0.9
National feature films/mn pop. 15-69………………….………
4.1
Entertainment & Media market/th pop. 15-69…………….
58.7
Printing & other media, % manufacturing…...................
1.0
Creative goods exports, % total trade………………………..
2.2

41
33
47
12
63 ○
26

7.3
7.3.1
7.3.2
7.3.3
7.3.4


44.4
Online creativity………………………………………..……….…….

52.9
Generic top-level domains (TLDs)/th pop. 15-69……….

77.6
Country-code TLDs/th pop. 15-69…………………..………….

52.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
11.9

14
14
6 ● ◆
22
40

MARKET SOPHISTICATION..………….…………… 58.6 20
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
53.2
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...…… 77.7

Microfinance gross loans, % GDP……………………….……. n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 39.7
Ease of protecting minority investors*…………..………….
58.3
Market capitalization, % GDP………………………………...….
53.9
Venture capital deals/bn PPP$ GDP……………….……....
0.1

79 ○ ◇
68 ○
31
20

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
82.9
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 76.3
Domestic market scale, bn PPP$………………………………4,379.1

4 ●
23
18
5 ● ◆



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5



28
40
39
n/a

12

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

259

GHANAGII 2019 rank

106

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

97

109

Lower middle

SSF

29.5

145.8

6,451.7

107

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
26.6

INSTITUTIONS………………………………….…….…..
48.9 115

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
52.0

68.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 43.8

74
71
78

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

40.2
38.3
49.8
49.8

121
79
53
◆
123 ○ ◇

1.3
1.3.1
1.3.2


54.6
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
84.3

Ease of resolving insolvency*……………………………….…. 24.9

◇
117
83
128 ○ ◇

19.2
HUMAN CAPITAL & RESEARCH………………...

97

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


43.6
Education…………………………………………………………..……

4.5
Expenditure on education, % GDP………………….…….….
🕘🕘 26.2
Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….……. 11.5

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
16.0

75
62
21 ●
94
n/a
72

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

107
99
93
64

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
2.1
🕘🕘Researchers, FTE/mn pop……………………………..…...……
38.4
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.4

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

11.8
16.2
13.4
2.9

◇

93
96
70
43 ○ ◇78 ○ ◇
35.0 103
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 54.5
ICT access*………………………………………………………….…….
45.6

ICT use*…………………………….....................................…….
40.0

69.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
62.9

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
14.9 125 ○ ◇
 …………………..…….
Electricity output, GWh/mn pop……
461.6 106
Logistics performance*…………………………………………….. 23.5 99
Gross capital formation, % GDP………………………….…….
13.8 119 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


35.7
Ecological sustainability………………………………………..

11.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
49.7
ISO 14001 environmental certificates/bn PPP$ GDP..  0.3

86
97
89
70
82

75
33 ●
99
102


MARKET SOPHISTICATION..………….…………… 34.3 121

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
25.8 104Ease of getting credit*…………………………………..…………..
60.0 66Domestic credit to private sector, % GDP…………...……
13.9 120 ○ ◇Microfinance gross loans, % GDP……………………….…….
0.8 24 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 26.7 127 ○ ◇Ease of protecting minority investors*…………..………….
51.7 89🕘🕘Market capitalization, % GDP………………………………...….
8.8
71 ○

Venture capital deals/bn PPP$ GDP……………….……....
0.0 64

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
50.3 107
Applied tariff rate, weighted avg., %………………………….
10.6 115
†
Intensity of local competition …………………………………… 63.4 87
Domestic market scale, bn PPP$……………………………… 145.8 70



86

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
20.7 108🕘🕘
Knowledge-intensive employment, %...........................
11.6 95
Firms offering formal training, % firms…………………………
40.1 35🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 91 ○🕘🕘
GERD financed by business, %……………………………........
0.1 97 ○ ◇🕘🕘Females employed w/advanced degrees, %……………..
3.4 97

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


36.1
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
47.3
State of cluster development†.……..………..…………………..
52.9
🕘🕘GERD financed by abroad, %.........................................
31.2
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
23.0 [112]
n/a n/aIntellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
3.7 119
n/a n/aICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
6.1 25 ●🕘🕘
Research talent, % in business enterprise……..…………..
1.0 7738 ● ◆
44 ● ◆
42 ● ◆
11 ● ◆
42 ●
82

 16.6 89
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 4.4 103

0.1 110
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0 99 ○ ◇
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.1 58

Scientific & technical articles/bn PPP$ GDP….…..…..….
5.2 79
Citable documents H-index…………………….……….……..…. 7.3 82

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


33.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.6
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.9
Computer software spending, % GDP…………..……………
0.0
ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.5
High- & medium-high-tech manufactures, %……………… n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


12.3 [92]Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

0.2 97High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
n/a n/a
FDI net outflows, % GDP…………………………….………….......
0.2
91

81
17 ●
73
124 ○ ◇
119
◇
n/a


18.9[100]
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
35.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
6.9
Industrial designs by origin/bn PPP$ GDP…………..……..
5.5

ICTs & business model creation†………………………....…….
56.0

ICTs & organizational model creation†……………………....
49.7

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.3 [114]
Online creativity………………………………………..……….…….

0.6 102
Generic top-level domains (TLDs)/th pop. 15-69……….

0.0 122
Country-code TLDs/th pop. 15-69…………………..………….
n/a n/aWikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a96
110
25 ●
84
83

5.1 [100]n/a n/an/a n/an/a n/a0.6 85
0.0 117◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
260

The Global Innovation Index 2019

GREECEGII 2019 rank

41

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

54

40

High

EUR

11.1

312.5

29,123.042

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
67.2

51

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
59.5

70.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 54.1

53
61
50

◇
◇
◇

1.2
1.2.1
1.2.2
1.2.3


68.2
Regulatory environment……………………………..………..

48.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
48.6

15.9
Cost of redundancy dismissal, salary weeks…………..

60
58
57
67

◇
◇
◇

1.3
1.3.1
1.3.2


73.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
92.4

Ease of resolving insolvency*……………………………….…. 55.4

53
40
57


49.5
HUMAN CAPITAL & RESEARCH………………...

20 ●

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


61.9
Education…………………………………………………………..……

n/a
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 22.6

School life expectancy, years……………….…………….……. 17.9

PISA scales in reading, maths, & science…………......…
458.5
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
8.4

16 ●
n/a
38
12 ●
42
12 ●

2.2
2.2.1
2.2.2
2.2.3


54.8
Tertiary education……………………………………….……..….
🕘🕘
126.4
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
28.2
Tertiary inbound mobility, %.......................................
….
3.3

8 ● ◆
1 ● ◆
19 ●
60

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
31.7
Researchers, FTE/mn pop……………………………..…...……
3,152.8
Gross expenditure on R&D, % GDP………….………..……
1.1

41.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
21.9

36
28
32
41
47


51.7
INFRASTRUCTURE……………………………….......

43

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs).  78.2

ICT access*………………………………………………………….…….
79.8

ICT use*…………………………….....................................…….
63.2

81.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
87.6

35
30
50
41
34

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
25.5 100 ○ ◇
 …………………..…….
Electricity output, GWh/mn pop……
5,479.7 38
Logistics performance*…………………………………………….. 53.4
41

Gross capital formation, % GDP………………………….…….
12.6 121 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


51.5
Ecological sustainability………………………………………..

11.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
73.6
ISO 14001 environmental certificates/bn PPP$ GDP..
5.1

◇

25
39
22 ●
22 ●



MARKET SOPHISTICATION..………….…………… 50.3 54
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
48.9
Ease of getting credit*…………………………………..…………..
50.0
Domestic credit to private sector, % GDP…………...……
100.4

Microfinance gross loans, % GDP……………………….……. n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 34.2 103 ○ ◇Ease of protecting minority investors*…………..………….
63.3 48
Market capitalization, % GDP………………………………...….
22.0 59 ○
Venture capital deals/bn PPP$ GDP……………….……....
0.0 57

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
67.7
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 67.9
Domestic market scale, bn PPP$……………………………… 312.5

34
87
27
n/a




BUSINESS SOPHISTICATION..……….……………
32.4

59

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
46.1 43Knowledge-intensive employment, %...........................
29.8 45
Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..……
0.6 36
GERD financed by business, %……………………………........ 44.8 36
Females employed w/advanced degrees, %……………..
17.9 29

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


◇
21.5 77
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
25.6 122 ○ ◇State of cluster development†.……..………..…………………..
32.3 117 ○ ◇
GERD financed by abroad, %.........................................
14.9 27
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 37
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.3 39

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


◇
Knowledge absorption……………………………………..……..
29.5 86
0.5 67
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.4 100 ○
1.1 69ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.3 101 ○
41
Research talent, % in business enterprise……..…………..
30.3

 25.1 53
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 19.9

2.0
Patents by origin/bn PPP$ GDP……………….…………..….…

0.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.0
Scientific & technical articles/bn PPP$ GDP….…..…..…. 20.5
Citable documents H-index…………………….……….……..….
31.9

46
44
42
61 ○
23 ●
29

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


42.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.2
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.8

Computer software spending, % GDP…………..…………… 0.6

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 25.7
High- & medium-high-tech manufactures, %………………
0.1

40
93 ○
77
14 ●
7 ● ◆
69

6.3
6.3.1
6.3.2
6.3.3
6.3.4


13.2 84◇Knowledge diffusion……………………………………..…..…….

0.1 54
Intellectual property receipts, % total trade……………….

2.0 54High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.6 64

FDI net outflows, % GDP…………………………….………….......
0.1 104 ○
30.1
CREATIVE OUTPUTS…….…………………….…………

53

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
42.9
Trademarks by origin/bn PPP$ GDP…………..……….….….
n/aIndustrial designs by origin/bn PPP$ GDP…………..……..
3.6
†
ICTs & business model creation ………………………....……. 52.7

ICTs & organizational model creation†……………………....
44.6

57
n/a
34
96 ○ ◇96 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
22.5
Cultural & creative services exports, % total trade…....
0.7
National feature films/mn pop. 15-69………………….………
11.2
Entertainment & Media market/th pop. 15-69…………….
19.7
Printing & other media, % manufacturing…...................
1.4

Creative goods exports, % total trade………………………..
1.1

48
38
13 ●
27
36
42

7.3
7.3.1
7.3.2
7.3.3
7.3.4


12.0
Online creativity………………………………………..……….…….

12.0
Generic top-level domains (TLDs)/th pop. 15-69……….

16.3
Country-code TLDs/th pop. 15-69…………………..………….

24.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
3.4

48
35
31
43
57

43
23
69
53

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

261

GUATEMALA

GII 2019 rank

107

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

102

105

Upper middle

LCN

17.2

145.2

8,436.4

102

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
48.1

117

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
38.2

52.6
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 31.0

113
118
108

◇
◇
◇

1.2
1.2.1
1.2.2
1.2.3


48.9
Regulatory environment……………………………..………..

35.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
18.3

27.0
Cost of redundancy dismissal, salary weeks…………..

112
91
123
104

◇

1.3
1.3.1
1.3.2


57.2
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
86.7

Ease of resolving insolvency*……………………………….…. 27.6

112
71
124

◇


11.1 121
HUMAN CAPITAL & RESEARCH………………...

◇

◇
◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


26.2
Education…………………………………………………………..……

2.8
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap…
5.1
🕘🕘
School life expectancy, years……………….…………….……. 10.8

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
10.5

115
◇
108
◇
105 ○ ◇◇
100n/a
36 ●

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

6.9
21.8
9.8
n/a

117
◇
90
◇
100 ○ ◇
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.1
🕘🕘Researchers, FTE/mn pop……………………………..…...……
22.2
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.0

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

117
103
◇
112
◇
43 ○ ◇78 ○ ◇
30.6 112
INFRASTRUCTURE……………………………….......

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 49.0

ICT access*………………………………………………………….…….
48.7

ICT use*…………………………….....................................…….
20.8

64.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
61.8

◇
◇
◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
11.6 127 ○ ◇
 …………………..…….
Electricity output, GWh/mn pop……
750.9 99 ◇Logistics performance*…………………………………………….. 16.4 112 ◇
Gross capital formation, % GDP………………………….…….
12.1 122 ◇

3.3
3.3.1
3.3.2
3.3.3


31.2
Ecological sustainability………………………………………..

8.5
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
52.3
ISO 14001 environmental certificates/bn PPP$ GDP..
0.1



98
91
107
83
88

89
69
90
121

◇
◇

MARKET SOPHISTICATION..………….…………… 43.2

93

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
32.3
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...…… 33.3
Microfinance gross loans, % GDP……………………….……. 0.2

82
20 ●
90
45

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 31.7 [113]Ease of protecting minority investors*…………..………….
31.7 126 ○ ◇Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
65.5
🕘🕘
Applied tariff rate, weighted avg., %………………………….
1.4
Intensity of local competition†…………………………………… 72.8
Domestic market scale, bn PPP$……………………………… 145.2


BUSINESS SOPHISTICATION..……….……………
33.7

50 ●

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
27.2 88
Knowledge-intensive employment, %...........................
◇
9.1 101🕘🕘Firms offering formal training, % firms………………………… 51.9
17 ●
🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 93 ○ ◇
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
2.2 99
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


39.4
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
41.6
State of cluster development†.……..………..…………………..
42.9
🕘🕘GERD financed by abroad, %......................................... 49.0
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
0.0

29 ● ◆
62
82
4 ● ◆
101
93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
34.4

1.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.9

0.9
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.6

Research talent, % in business enterprise……..………….. n/a

59
27 ●
31 ●
75
91
n/a

 12.5 111
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 1.3 126
0.0 125 ○
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0 96
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.1 60
Scientific & technical articles/bn PPP$ GDP….…..…..….
0.5 127 ○ ◇Citable documents H-index…………………….……….……..….
3.6 108

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


24.7 106
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.5 99🕘🕘
New businesses/th pop. 15-64………………….…....………….
0.5 83Computer software spending, % GDP…………..…………… 0.0 122

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.5 96
High- & medium-high-tech manufactures, %………………
n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


11.6 95
Knowledge diffusion……………………………………..…..…….

0.0 70Intellectual property receipts, % total trade……………….

1.4 62High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.5 70
FDI net outflows, % GDP…………………………….………….......
0.1 100


21.1
CREATIVE OUTPUTS…….…………………….…………

90

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
39.8
Trademarks by origin/bn PPP$ GDP…………..……….….….
45.0
Industrial designs by origin/bn PPP$ GDP…………..……..
0.1

ICTs & business model creation†………………………....……. 64.4

ICTs & organizational model creation†…………………….... 57.0

69
56
112
52 ●
56 ●

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

2.9 [110]
0.0 94
1.2 77n/a n/an/a n/a0.3 74

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.8
4.1
0.5
3.9
0.0

87
59
93
88
97 ○

50 ●
14 ●
41 ●
71

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
262

The Global Innovation Index 2019

◇

GUINEA

GII 2019 rank

125

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

124

127

Low

SSF

13.1

30.3

2,309.6

n/aScore/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
50.6 108
BUSINESS SOPHISTICATION..……….……………
23.3 [110]

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
33.4

57.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 21.2

122
101
123

1.2
1.2.1
1.2.2
1.2.3


56.8
Regulatory environment……………………………..………..

19.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
13.9

10.1
Cost of redundancy dismissal, salary weeks…………..

93
119
125
30 ●

1.3
1.3.1
1.3.2


61.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
83.9

Ease of resolving insolvency*……………………………….…. 39.1

96
86 ●
102


HUMAN CAPITAL & RESEARCH………………...

6.5 128 ○ ◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


13.8 128 ○ ◇
Education…………………………………………………………..……

2.2 116
Expenditure on education, % GDP………………….…….….
◇🕘🕘Government funding/pupil, secondary, % GDP/cap… 8.7 100◇🕘🕘School life expectancy, years……………….…………….……. 9.1 109
PISA scales in reading, maths, & science…………......…
n/a n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
33.1 108

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
🕘🕘
Tertiary inbound mobility, %.......................................
….

5.8 120
11.3 105n/a n/a0.9 88

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
27.0 121
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  27.1 123

ICT access*………………………………………………………….…….
29.8 118
ICT use*…………………………….....................................…….
12.0 121
31.3 118
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 35.4 115

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
22.4
 …………………..…….
Electricity output, GWh/mn pop……
n/a
Logistics performance*…………………………………………….. 6.4

Gross capital formation, % GDP………………………….…….
19.8

111
n/a
119
94

3.3
3.3.1
3.3.2
3.3.3


31.4
Ecological sustainability………………………………………..

n/a
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 46.6
ISO 14001 environmental certificates/bn PPP$ GDP..
0.1

88
n/a
106
119



MARKET SOPHISTICATION..………….…………… 31.4 125
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
11.8 123Ease of getting credit*…………………………………..…………..
30.0 115🕘🕘Domestic credit to private sector, % GDP…………...…… 9.6 125 ○🕘🕘Microfinance gross loans, % GDP……………………….…….
0.2 43 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.0
Ease of protecting minority investors*…………..………….
40.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
42.3 125
Applied tariff rate, weighted avg., %………………………….
12.3 121
21 ● ◆
Intensity of local competition†…………………………………… 75.9
Domestic market scale, bn PPP$……………………………… 30.3 115



[72]
114
n/a
n/a

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
16.6 [114]Knowledge-intensive employment, %...........................
n/a n/a
Firms offering formal training, % firms………………………… 16.0 83

GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


33.5 [42]Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
67.2 14 ● ◆State of cluster development†.……..………..…………………..
50.3 47 ● ◆
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


◇
Knowledge absorption……………………………………..……..
19.8 124🕘🕘
0.0 115
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
2.0 126 ○ ◇◇
0.2 119
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
8.2 18 ●
Research talent, % in business enterprise……..………….. n/a n/a◇ 2.9 129 ○ ◇
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 1.1 127 ○ ◇
0.0 122
Patents by origin/bn PPP$ GDP……………….…………..….…
◇
0.0 99 ○ ◇
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
1.1 121◇Citable documents H-index…………………….……….……..….
1.4 123
◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
🕘🕘New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


5.9 128 ○
Knowledge diffusion……………………………………..…..…….
🕘🕘-0.1 109 ○ ◇Intellectual property receipts, % total trade……………….
🕘🕘
0.1 108
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.0 127 ○
FDI net outflows, % GDP…………………………….………….......
0.1 991.6 [128]n/a n/a0.1 980.0 106
0.4 123n/a n/a
19.6
CREATIVE OUTPUTS…….…………………….…………

98

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
38.6 77 ● ◆Trademarks by origin/bn PPP$ GDP…………..……….….….
8.4 108

Industrial designs by origin/bn PPP$ GDP…………..…….. 1.7 55 ●
ICTs & business model creation†………………………....……. 68.2 35 ● ◆ICTs & organizational model creation†……………………....
60.0 45 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

1.2 [123]
0.1 900.8 85n/a n/an/a n/a0.0 120

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

0.0
0.0
0.0
0.0
n/a

128 ○
126
128 ○
126 ○
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

263

HONDURAS

GII 2019 rank

104

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

104

101

Lower middle

LCN

9.4

49.0

5,212.0105

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
28.9 76


INSTITUTIONS………………………………….…….…..
46.9 121 ○

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
40.9

Political and operational stability*……………..………….….
54.4
Government effectiveness*…………………………..…………. 34.1

101
111
98

1.2
1.2.1
1.2.2
1.2.3


45.2
Regulatory environment……………………………..………..

30.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
18.7

30.3
Cost of redundancy dismissal, salary weeks…………..

117
99
121 ○ ◇
116

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
54.6
Ease of starting a business*………………………………..……
77.1

Ease of resolving insolvency*……………………………….…. 32.1

118
115
114

◇
◇


18.3 100
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


42.1
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
6.0
🕘🕘Government funding/pupil, secondary, % GDP/cap… 20.0
🕘🕘School life expectancy, years……………….…………….……. 10.2

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
16.7

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
12.6 106🕘🕘
Tertiary enrolment, % gross………………………….….……….
20.8
91
🕘🕘
Graduates in science & engineering, %……………….…. 14.7
89🕘🕘
Tertiary inbound mobility, %....................................... ….
0.8
93

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.0🕘🕘Researchers, FTE/mn pop……………………………..…...……
22.8
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.0

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*…………… 0.0

78
21 ● ◆
50
105
◇
n/a
74

119
102 ○
113 ○ ◇43 ○ ◇78 ○ ◇
INFRASTRUCTURE……………………………….......
32.5 109

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  41.7

ICT access*………………………………………………………….…….
40.7

ICT use*…………………………….....................................…….
20.3

51.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
54.5

101
103
108
104
98

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
27.0
Electricity output, GWh/mn pop………………………..…….
964.1
Logistics performance*…………………………………………….. 25.3
Gross capital formation, % GDP………………………….…….
24.1

91
93
88
53 ●

3.3
3.3.1
3.3.2
3.3.3


28.8 105
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
6.7
91
Environmental performance*…….……………………………… 51.5 93
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.6
79



◇

MARKET SOPHISTICATION..………….…………… 45.7

75

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
38.7
Ease of getting credit*…………………………………..…………..
85.0
Domestic credit to private sector, % GDP…………...…… 57.4

Microfinance gross loans, % GDP……………………….……. 0.3

58 ●
1 1 ●
57 ●
40

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 41.7 [65]Ease of protecting minority investors*…………..………….
41.7 108
Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
56.9
🕘🕘Applied tariff rate, weighted avg., %………………………….
2.8

Intensity of local competition†…………………………………… 69.5
Domestic market scale, bn PPP$……………………………… 49.0

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
33.5 [77]Knowledge-intensive employment, %...........................
12.2 94Firms offering formal training, % firms………………………… 47.7 24 ●
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
3.5 96

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
21.8 74

University/industry research collaboration †………………..
37.9 81State of cluster development†.……..………..…………………..
46.0 68
GERD financed by abroad, %......................................... n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 106 ○
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.5

0.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.5

ICT services imports, % total trade…………..………………... 0.8

FDI net inflows, % GDP…………………………….…………………. 5.7

Research talent, % in business enterprise……..…………..
n/a

76
56 ●
64
82
27 ●
n/a

 12.9 110
KNOWLEDGE & TECHNOLOGY OUTPUTS....

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5


Knowledge creation………………………………………........... 1.8 124 ○
Patents by origin/bn PPP$ GDP……………….…………..….…
0.1 112
0.0 99 ○ ◇
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.2 46
Scientific & technical articles/bn PPP$ GDP….…..…..….
1.5 120 ○Citable documents H-index…………………….……….……..….
1.6 121 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


15.1 [114]Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
n/a n/a
New businesses/th pop. 15-64………………….…....………….
n/a n/aComputer software spending, % GDP…………..…………… 0.3 60
ISO 9001 quality certificates/bn PPP$ GDP…………..……
3.7 66
High- & medium-high-tech manufactures, %………………
n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


21.6
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….

0.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.0

FDI net outflows, % GDP…………………………….………….......
1.3

45 ●
n/a
78
29 ●
47 ● ◆


20.2
CREATIVE OUTPUTS…….…………………….…………

96

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
38.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
49.5
Industrial designs by origin/bn PPP$ GDP…………..…….. 0.1

ICTs & business model creation†………………………....……. 60.3

ICTs & organizational model creation †……………………....
55.3

75
49 ●
1 1 1 ○
64
59

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

2.4 [114]
0.0 107
2.2 61n/a n/an/a n/a0.1 108

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

0.7 104
0.6 106
0.4 98
2.9 95
0.1 86

81
62
63
96

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
264

The Global Innovation Index 2019

HONG KONG, CHINA

GII 2019 rank

13

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

16

8

High

SEAO

7.4

484.0

64,215.7

14

Score/Value Rank

INSTITUTIONS………………………………….…….…..

91.1

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

7

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
93.4
Political and operational stability*……………..………….….
94.7
Government effectiveness*…………………………..………….
92.7

4
4
5

1.2
1.2.1
1.2.2
1.2.3


98.0
Regulatory environment……………………………..………..

100.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
91.8

8.0
Cost of redundancy dismissal, salary weeks…………..

3 ●
1 ● ◆
12
1 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
81.9
Ease of starting a business*………………………………..……
98.2
Ease of resolving insolvency*……………………………….….
65.7

28
5
41

◆
◇


46.1
HUMAN CAPITAL & RESEARCH………………...

28

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


53.6
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.3
Government funding/pupil, secondary, % GDP/cap… 22.2

School life expectancy, years……………….…………….…….
16.5
PISA scales in reading, maths, & science…………......…
532.6
Pupil-teacher ratio, secondary…………………………......…. 11.5

48
96 ○ ◇
40
21
2 ●◆
43

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
50.0

Tertiary enrolment, % gross………………………….….……….
73.8
Graduates in science & engineering, %……………….….
n/aTertiary inbound mobility, %.......................................
….
11.4

15
23
n/a
16

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
34.7
Researchers, FTE/mn pop……………………………..…...……
3,411.7
Gross expenditure on R&D, % GDP………….………..……
0.8

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
80.1

33
◇
27
◇
43
◇
43 ○ ◇7


INFRASTRUCTURE……………………………….......
67.9

4

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  87.3

ICT access*………………………………………………………….…….
91.4

ICT use*…………………………….....................................…….
83.2

n/a
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

[18]
4
8
n/a
n/a

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
44.1
Electricity output, GWh/mn pop………………………..…….
5,205.2
Logistics performance*…………………………………………….. 86.8
Gross capital formation, % GDP………………………….…….
22.2

34
41
12
74 ○

3.3
3.3.1
3.3.2
3.3.3


72.2
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
27.0
Environmental performance*…….………………………………
n/a
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.2

2 ●◆
1●◆
n/a
44

n/a

◆

◆


77.3
MARKET SOPHISTICATION..………….……………

3●◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
87.5
Ease of getting credit*…………………………………..…………..
75.0
🕘🕘Domestic credit to private sector, % GDP…………...……
203.8

Microfinance gross loans, % GDP……………………….…….
n/a

2●◆
29
1●◆
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 67.7
Ease of protecting minority investors*…………..………….
78.3
Market capitalization, % GDP……………………………...…. 1,099.6
Venture capital deals/bn PPP$ GDP……………….……....
0.1

11
◆
10 ◆
1●◆
26

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
76.8

Applied tariff rate, weighted avg., %………………………….
0.0
Intensity of local competition†……………………………………
85.6
Domestic market scale, bn PPP$……………………………… 484.0

16
1●◆
2●◆
41

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

51.1

20

Knowledge workers…………………………………………….….. 51.9
🕘🕘Knowledge-intensive employment, %...........................
39.0

Firms offering formal training, % firms…………………………
n/aGERD performed by business, % GDP…………………..……
0.4

GERD financed by business, %……………………………........ 50.0
🕘🕘Females employed w/advanced degrees, %…………….. 15.9

35
29
n/a
43
26
41





◇
◇
◇
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5

Innovation linkages…………..…………………………………….. 44.7

University/industry research collaboration †………………..
66.4
State of cluster development†.……..………..…………………..
72.6

GERD financed by abroad, %.........................................
4.4
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.2
Patent families 2+ offices/bn PPP$ GDP……………………..
1.1

21
15
6
◆
65 ○
4
◆
25
◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
56.6

0.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
49.8
ICT services imports, % total trade…………..………………...
0.3

FDI net inflows, % GDP…………………………….………………….
45.3
Research talent, % in business enterprise……..…………..
37.3

876 ○ ◇
1 ●◆112 ○ ◇1 ●◆34◇

 32.9 33
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 21.5
Patents by origin/bn PPP$ GDP……………….…………..….…
0.7

n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
1.1

Scientific & technical articles/bn PPP$ GDP….…..…..….
n/a
Citable documents H-index…………………….……….……..…. 35.5

[39]
70
n/a
22
n/a
25

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


50.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.1
New businesses/th pop. 15-64………………….…....………….
27.3
Computer software spending, % GDP…………..……………
0.4
ISO 9001 quality certificates/bn PPP$ GDP…………..……
5.7
High- & medium-high-tech manufactures, %……………… 0.1

14
41
1 ●◆
27
55
82 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


27.0
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….
🕘🕘
High-tech net exports, % total trade……………….….…...... 0.1

ICT services exports, % total trade……………..……..………
0.4

FDI net outflows, % GDP…………………………….………….......
26.2

36
52
◇
104 ○ ◇
103 ○ ◇
1 ●◆


55.9
CREATIVE OUTPUTS…….…………………….…………

3●◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
50.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
64.8
Industrial designs by origin/bn PPP$ GDP…………..……..
2.7

35
31
44
19
23

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5



Creative goods & services……………………….…….……….. 70.5
Cultural & creative services exports, % total trade…....
0.1
🕘🕘National feature films/mn pop. 15-69………………….………
10.4
Entertainment & Media market/th pop. 15-69…………….
50.9

Printing & other media, % manufacturing…...................
4.8
Creative goods exports, % total trade………………………..
9.9

1 ●◆
76 ○ ◇
17
16
1 ●◆
1 ●◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


52.8
Online creativity………………………………………..……….…….

71.9
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 12.3

84.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
70.2

10
8
36
11
5


ICTs & business model creation†………………………....…….
74.6

ICTs & organizational model creation †……………………....
67.6

◇

◇

◇
◆

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

265

HUNGARYGII 2019 rank

33

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

26

39

High

EUR

9.7

308.2

31,902.7

33

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
71.6

41

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
67.4

Political and operational stability*……………..………….….
84.2
Government effectiveness*…………………………..…………. 59.0

41
25
43

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

75.8
59.4
60.4
13.4

36
42
40
50

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
71.5
Ease of starting a business*………………………………..……
87.9
Ease of resolving insolvency*……………………………….…. 55.0

59
66
60


41.0
HUMAN CAPITAL & RESEARCH………………...

41

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


51.8
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.6
Government funding/pupil, secondary, % GDP/cap… 21.2

School life expectancy, years……………….…………….……. 15.1

PISA scales in reading, maths, & science…………......…
474.4
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
10.0

52
59
45
49
36
30

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
36.8
🕘🕘Tertiary enrolment, % gross………………………….….……….
48.0
Graduates in science & engineering, %……………….….
22.8
Tertiary inbound mobility, %....................................... ….
8.9

47
59
45
22

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
34.4
Researchers, FTE/mn pop…………………………….........… 2,924.0
Gross expenditure on R&D, % GDP………….………..……
1.4

52.5
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
20.5

34
31
25
27
50


INFRASTRUCTURE……………………………….......
52.7

40

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  71.5

ICT access*………………………………………………………….…….
77.9

ICT use*…………………………….....................................…….
63.6

73.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
70.8

54
◇
34
48 ◇
57 ◇
67 ○ ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
37.8
Electricity output, GWh/mn pop………………………..…….
3,354.0
Logistics performance*…………………………………………….. 63.4
Gross capital formation, % GDP………………………….…….
23.3

52
58
30
62

3.3
3.3.1
3.3.2
3.3.3


48.9
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.4
Environmental performance*…….………………………………
65.0
ISO 14001 environmental certificates/bn PPP$ GDP..
7.6

35
61
39
11 ● ◆

◇

MARKET SOPHISTICATION..………….…………… 45.7

76 ○

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
44.5
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...…… 33.4
Microfinance gross loans, % GDP……………………….…….
n/a

46
29
89 ○ ◇
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 27.1 124 ○ ◇
Ease of protecting minority investors*…………..………….
50.0 93 ○ ◇
Market capitalization, % GDP………………………………...….
18.3 62 ○
Venture capital deals/bn PPP$ GDP……………….……....
0.0 56 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
65.5

Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 59.3
Domestic market scale, bn PPP$……………………………… 308.2


BUSINESS SOPHISTICATION..……….……………
40.8

33

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
42.1
Knowledge-intensive employment, %...........................
34.3
Firms offering formal training, % firms………………………… 15.8

GERD performed by business, % GDP…………………..…… 1.0

GERD financed by business, %……………………………........
56.4
Females employed w/advanced degrees, %……………..
14.4

51
38
84 ○ ◇
22
17
43

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
27.3
University/industry research collaboration †………………..
44.4
State of cluster development†.……..………..…………………..
46.8
GERD financed by abroad, %.........................................
16.6
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.4

57
53
62
21
73 ○
35

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
53.0

1.5
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
13.2

ICT services imports, % total trade…………..………………...
1.3

FDI net inflows, % GDP…………………………….………………….
13.6
Research talent, % in business enterprise……..………….. 61.7

16 ●
22
17 ●
58
9 ●
1 1 ●

 42.8KNOWLEDGE & TECHNOLOGY OUTPUTS....

17 ●



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 20.3

Patents by origin/bn PPP$ GDP……………….…………..….…
2.0

0.5
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.7
Scientific & technical articles/bn PPP$ GDP….…..…..….
15.8
Citable documents H-index…………………….……….……..….
28.3

43
42
36
31
34
33

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


49.6
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.4
New businesses/th pop. 15-64………………….…....………….
3.4
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..……
20.5
High- & medium-high-tech manufactures, %………………
0.6

15 ●
54
37
36
16 ●
8 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


58.4
Knowledge diffusion……………………………………..…..…….

1.6Intellectual property receipts, % total trade……………….

12.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.9

FDI net outflows, % GDP…………………………….………….......
11.6

8 ●◆
16 ●
1 1 ● ◆
58
1 ●◆


34.6
CREATIVE OUTPUTS…….…………………….…………

38

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
43.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
40.5
Industrial designs by origin/bn PPP$ GDP…………..……..
3.2
†
ICTs & business model creation ………………………....……. 65.5

ICTs & organizational model creation †…………………….... 60.3

56
64 ○
40
50
42

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
31.6
Cultural & creative services exports, % total trade…....
0.8
National feature films/mn pop. 15-69………………….………
5.2
Entertainment & Media market/th pop. 15-69…………….
14.1
Printing & other media, % manufacturing…...................
0.8
Creative goods exports, % total trade………………………..
6.1

24
36
42
29
◇
75 ○
9 ●◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


20.6
Online creativity………………………………………..……….…….

10.4
Generic top-level domains (TLDs)/th pop. 15-69……….

29.1
Country-code TLDs/th pop. 15-69…………………..………….

53.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
6.7

32
39
20
21
46

51
23
110 ○ ◇54

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
266

The Global Innovation Index 2019

ICELANDGII 2019 rank

20

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

18

22

High

EUR

0.3

19.3

55,917.3

23

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
86.8

15

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
85.5

Political and operational stability*……………..………….….
93.0
Government effectiveness*…………………………..…………. 81.7

15
7
17

1.2
1.2.1
1.2.2
1.2.3


88.5
Regulatory environment……………………………..………..

80.4
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
88.9

13.0
Cost of redundancy dismissal, salary weeks…………..

16
19
17
42

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
86.3
Ease of starting a business*………………………………..……
90.7
Ease of resolving insolvency*……………………………….…. 81.9

16
50
11


45.4
HUMAN CAPITAL & RESEARCH………………...

30

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


64.4
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
7.7
Government funding/pupil, secondary, % GDP/cap… 20.8
School life expectancy, years……………….…………….……. 19.2

PISA scales in reading, maths, & science…………......…
480.9
Pupil-teacher ratio, secondary…………………………......….
n/a

9
2 ●◆
46
4 ●
33
◇
n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
30.0
🕘🕘Tertiary enrolment, % gross………………………….….……….
73.6
🕘🕘Graduates in science & engineering, %……………….….
15.7
Tertiary inbound mobility, %.......................................
….
6.8

68
◇
24
84 ○ ◇
34

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
41.7
Researchers, FTE/mn pop……………………………..…...……
6,118.9
Gross expenditure on R&D, % GDP………….………..……
2.2

45.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

24
◇
8
14
36
78 ○ ◇
INFRASTRUCTURE……………………………….......
59.2

24

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 80.7

ICT access*………………………………………………………….…….
92.9

ICT use*…………………………….....................................…….
88.2

72.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
68.5

30
◇
2●◆
3 ●◆
63 ◇
73 ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
57.3
Electricity output, GWh/mn pop………………………....… 56,585.3
Logistics performance*…………………………………………….. 54.3
Gross capital formation, % GDP………………………….…….
23.1

6
1 ● ◆
39
◇
64

3.3
3.3.1
3.3.2
3.3.3


39.5
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
2.7
Environmental performance*…….………………………………
78.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 5.0

58 ◇
118 ○ ◇
11
23


56.0
MARKET SOPHISTICATION..………….……………

35

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
51.2
Ease of getting credit*…………………………………..…………..
60.0
Domestic credit to private sector, % GDP…………...……
89.8

Microfinance gross loans, % GDP……………………….…….
n/a

29
66
30
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 64.2
Ease of protecting minority investors*…………..………….
70.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.2

16
27
n/a
6

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
52.6
Applied tariff rate, weighted avg., %………………………….
1.6

†Intensity of local competition …………………………………… 70.0Domestic market scale, bn PPP$……………………………… 19.3

98 ○ ◇
1761 ◇
126 ○ ◇

◇


BUSINESS SOPHISTICATION..……….……………
48.0

23

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
66.8
Knowledge-intensive employment, %...........................
50.0

Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… 1.4

GERD financed by business, %……………………………........
36.4
Females employed w/advanced degrees, %……………..
24.4

14
6
n/a
14
51
15

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
47.7
University/industry research collaboration †………………..
59.7
State of cluster development†.……..………..…………………..
52.6
GERD financed by abroad, %.........................................
24.5
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 3.9

16
24
43
14
41
13

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
29.5 84 ○ ◇
1.1 33
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.1 105 ○ ◇
ICT services imports, % total trade…………..………………...
2.3 19
FDI net inflows, % GDP…………………………….………………….
-9.3 129 ○ ◇
Research talent, % in business enterprise……..…………..
42.7 30

◇

◇

◇
◆
◇

 37.6 23
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 40.0Patents by origin/bn PPP$ GDP……………….…………..….…
5.1

2.5
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
32.6
Citable documents H-index…………………….……….……..…. 18.6

19
24
14
n/a
5 ● ◆
40
◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


39.6
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.3
New businesses/th pop. 15-64………………….…....………….
12.1
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
7.3
High- & medium-high-tech manufactures, %……………… 0.1

51
◇
56
10
44
43
73 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


33.2
Knowledge diffusion……………………………………..…..…….

2.4
Intellectual property receipts, % total trade……………….

1.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.7

FDI net outflows, % GDP…………………………….………….......
n/a

26
10
60
37
n/a


50.4
CREATIVE OUTPUTS…….…………………….…………

9

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
54.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
93.8
Industrial designs by origin/bn PPP$ GDP…………..……..
0.8

ICTs & business model creation†………………………....…….
72.8

ICTs & organizational model creation †…………………….... 75.5

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
30.9 25

Cultural & creative services exports, % total trade…....
0.6 40🕘🕘National feature films/mn pop. 15-69………………….………
98.5
1 ●◆

Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.7 24Creative goods exports, % total trade………………………..
0.1 105 ○ ◇

7.3
7.3.1
7.3.2
7.3.3
7.3.4


62.5
Online creativity………………………………………..……….…….

100.0
Generic top-level domains (TLDs)/th pop. 15-69……….

78.2
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
104.8
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
1.2

24
20
74 ○
26
13

4 ● ◆
1 ●◆
5 ●◆
4 ●◆
64 ○ ◇NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

267

INDIAGII 2019 rank

52

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

51

61

Lower middle

CSA

1,354.1

10,401.4

7,873.7

57

Score/Value Rank

INSTITUTIONS………………………………….…….…..
59.5

77

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
53.0
Political and operational stability*……………..………….….
61.4
Government effectiveness*…………………………..…………. 48.8

71
91
65

1.2
1.2.1
1.2.2
1.2.3


64.5
Regulatory environment……………………………..………..

35.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
46.5

15.8
Cost of redundancy dismissal, salary weeks…………..

69
90
64
63

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
60.9
Ease of starting a business*………………………………..……
81.0
Ease of resolving insolvency*……………………………….…. 40.8

101
104
95

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
31.0

◆

◆


33.5
HUMAN CAPITAL & RESEARCH………………...

53

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


28.0
Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
3.8
🕘🕘Government funding/pupil, secondary, % GDP/cap… 16.8
School life expectancy, years……………….…………….……. 12.3
🕘🕘
PISA scales in reading, maths, & science…………......…
336.0
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
28.5

110 ○
84
72
87
71 ○ ◇104 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
38.4
Tertiary enrolment, % gross………………………….….……….
27.5
Graduates in science & engineering, %……………….….
32.6
Tertiary inbound mobility, %....................................... ….
0.1

40
◆
86
7 ●◆
107 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
34.2
🕘🕘Researchers, FTE/mn pop……………………………..…...……
216.2
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.6

73.9
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
47.3

35
◆
77
50
◆
15 ● ◆
21 ● ◆
INFRASTRUCTURE……………………………….......
43.0

79

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 62.5

ICT access*………………………………………………………….…….
38.5

ICT use*…………………………….....................................…….
20.8

95.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
95.5

75
105 ○
106 ○
9●◆15 ● ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
41.9
Electricity output, GWh/mn pop………………………..…….
1,115.8
Logistics performance*…………………………………………….. 52.1
Gross capital formation, % GDP………………………….…….
31.5

42
◆
92
43
◆
17 ●

3.3
3.3.1
3.3.2
3.3.3


24.7
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.2
Environmental performance*…….………………………………
30.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.8

117 ○
62
125 ○ ◇
70

◆


56.3
MARKET SOPHISTICATION..………….……………

33

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
38.7
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...…… 49.7
Microfinance gross loans, % GDP……………………….……. 0.8

57
20
69
23

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 50.8
Ease of protecting minority investors*…………..………….
80.0
Market capitalization, % GDP………………………………...….
76.9

Venture capital deals/bn PPP$ GDP……………….……....
0.0

37
6●◆
20 ◆
30 ◆

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
79.4
Applied tariff rate, weighted avg., %………………………….
5.8

Intensity of local competition†…………………………………… 67.6
Domestic market scale, bn PPP$………………………..… 10,401.4

9 ●◆
93
70
3●◆

◆

65

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
24.1 99🕘🕘Knowledge-intensive employment, %...........................
14.2 91Firms offering formal training, % firms………………………… 35.9 38
🕘🕘
GERD performed by business, % GDP…………………..…… 0.3 49◆
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %……………..
1.6 103 ○

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
33.6
University/industry research collaboration †………………..
60.1
State of cluster development†.……..………..…………………..
60.4

GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.2

41
23
25
n/a
48
46

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
35.4

56
29
27
62
83
46


1.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.3

ICT services imports, % total trade…………..………………...
1.2

FDI net inflows, % GDP…………………………….………………….
1.9
🕘🕘Research talent, % in business enterprise……..………….. 26.4

 33.5 32
KNOWLEDGE & TECHNOLOGY OUTPUTS....
The Global Innovation Index 2019

◆
◆

◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 20.9

Patents by origin/bn PPP$ GDP……………….…………..….…
1.6

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
5.3
Citable documents H-index…………………….……….……..….
38.9

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.4 35
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
5.9
4 ●◆

New businesses/th pop. 15-64………………….…....………….
0.1 100 ○
Computer software spending, % GDP…………..…………… 0.2 65
ISO 9001 quality certificates/bn PPP$ GDP…………..……
3.8 65🕘🕘High- & medium-high-tech manufactures, %………………
0.3 33
◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


36.1
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

2.8
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
10.4

FDI net outflows, % GDP…………………………….………….......
0.3

◆
23
50
46
1 ● ◆
76


23.5
CREATIVE OUTPUTS…….…………………….…………

78

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
37.8

Trademarks by origin/bn PPP$ GDP…………..……….….….
25.6
Industrial designs by origin/bn PPP$ GDP…………..……..
0.8

ICTs & business model creation†………………………....…….
61.1

ICTs & organizational model creation †…………………….... 59.6

81
79
77
58
47

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5



Creative goods & services……………………….…….……….. 15.2
Cultural & creative services exports, % total trade…....
0.7
🕘🕘National feature films/mn pop. 15-69………………….………
2.2
Entertainment & Media market/th pop. 15-69…………….
0.5
🕘🕘
Printing & other media, % manufacturing…...................
0.6
Creative goods exports, % total trade……………………….. 2.7

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.2 76
Online creativity………………………………………..……….…….

0.9 98Generic top-level domains (TLDs)/th pop. 15-69……….

0.6
91Country-code TLDs/th pop. 15-69…………………..………….

1.0 105
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
10.7 42

42
52
51
◆
n/a
77
21 ● ◆

◆

66
39
◆
60
60 ○
88 ○
22

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
268

◆
◆
◆

INDONESIA

GII 2019 rank

85

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

78

87

Lower middle

SEAO

266.8

3,495.9

13,229.5

85

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
25.7

INSTITUTIONS………………………………….…….…..
53.2

99

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
53.9

Political and operational stability*……………..………….….
66.7
Government effectiveness*…………………………..…………. 47.5

68
74
68

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

31.1
39.1
37.2
57.8

128 ○ ◇
75
82
125 ○ ◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
74.6

Ease of starting a business*………………………………..……
81.2

Ease of resolving insolvency*……………………………….…. 67.9

49
◆
102
33 ● ◆


21.3
HUMAN CAPITAL & RESEARCH………………...

90

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


33.9
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.6
Government funding/pupil, secondary, % GDP/cap… 10.5
School life expectancy, years……………….…………….……. 13.4

PISA scales in reading, maths, & science…………......…
395.5
Pupil-teacher ratio, secondary…………………………......….
15.3

99
92
94 ○
78
63
69

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
21.5
Tertiary enrolment, % gross………………………….….……….
36.3
Graduates in science & engineering, %……………….….
19.4

Tertiary inbound mobility, %.......................................
….
0.1

89
74
68
110 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
8.4
🕘🕘Researchers, FTE/mn pop……………………………..…...……
89.2
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
31.3

63
86
109 ○ ◇43 ○ ◇
36 ● ◆
INFRASTRUCTURE……………………………….......
44.2

75

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  53.7

ICT access*………………………………………………………….…….
51.4

ICT use*…………………………….....................................…….
44.8

56.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

88
85
77
92
88

◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
43.5
Electricity output, GWh/mn pop………………………..…….
952.1
Logistics performance*…………………………………………….. 50.8
Gross capital formation, % GDP………………………….…….

33.4

35 ● ◆9445◆
15 ●

3.3
3.3.1
3.3.2
3.3.3


35.4
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
11.9
Environmental performance*…….………………………………
46.9
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.7

76
30 ●
105
75


48.8
MARKET SOPHISTICATION..………….……………

64

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
29.0
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
38.7

Microfinance gross loans, % GDP……………………….…….
0.0

96
40
85
61

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.8
Ease of protecting minority investors*…………..………….
63.3
Market capitalization, % GDP………………………………...….
46.0

Venture capital deals/bn PPP$ GDP……………….……....
0.0

90
48
32
60

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
80.6

Applied tariff rate, weighted avg., %………………………….
2.1
†Intensity of local competition …………………………………… 73.2
Domestic market scale, bn PPP$…………………………… 3,495.9

7 ●◆
54 ◆
37 ◆
7 ●◆

61.8

◆
◆

95

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
10.9 122 ○ ◇Knowledge-intensive employment, %...........................
10.9 97
Firms offering formal training, % firms…………………………
7.7 90 ○ ◇🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 78

GERD financed by business, %……………………………........ n/a n/aFemales employed w/advanced degrees, %……………..
6.0 85

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
29.4
University/industry research collaboration †………………..
53.8
State of cluster development†.……..………..…………………..
60.0
GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

50
34 ● ◆
27 ● ◆
n/a
92
91

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
36.7

1.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.5
ICT services imports, % total trade…………..………………...
1.3

FDI net inflows, % GDP…………………………….………………….
1.6
🕘🕘
Research talent, % in business enterprise……..………….. 35.5

48
35
49
54
90
37

◆

◆

 17.6 82
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 4.6 101
Patents by origin/bn PPP$ GDP……………….…………..….…
0.7 72

0.0 97 ○PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.1 54

Scientific & technical articles/bn PPP$ GDP….…..…..….
0.6 125 ○Citable documents H-index…………………….……….……..…. 12.7 55

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


36.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.3
New businesses/th pop. 15-64………………….…....………….
0.3
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
2.2
🕘🕘High- & medium-high-tech manufactures, %……………… 0.3

64
37
91
33 ● ◆
85
37
◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


11.5
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

3.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.5

FDI net outflows, % GDP…………………………….………….......
0.0

96
76
43
101
112 ○


24.0
CREATIVE OUTPUTS…….…………………….…………

76

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
40.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
16.0
Industrial designs by origin/bn PPP$ GDP…………..……..
0.7

ICTs & business model creation†………………………....…….
67.1

ICTs & organizational model creation †…………………….... 65.4

68
93
80
40
◆
27 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
13.9
Cultural & creative services exports, % total trade…....
0.0🕘🕘National feature films/mn pop. 15-69………………….………
0.5
Entertainment & Media market/th pop. 15-69…………….
2.2
🕘🕘Printing & other media, % manufacturing…...................
0.8
Creative goods exports, % total trade……………………….. 2.9

73
99
96 ○
52◆
77
19 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


2.0
Online creativity………………………………………..……….…….

1.5
Generic top-level domains (TLDs)/th pop. 15-69……….

0.4
Country-code TLDs/th pop. 15-69…………………..………….

2.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
4.8

83
88
97
99
49

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

269

IRAN (ISLAMIC REPUBLIC OF)

GII 2019 rank

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

47

86

Upper middle

CSA

82.0

1,652.9

19,556.6

65

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
22.6 113 ○ ◇
INSTITUTIONS………………………………….…….…..
48.8 116 ○ ◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
46.7

Political and operational stability*……………..………….….
56.1
Government effectiveness*…………………………..…………. 41.9

90
105
85

1.2
1.2.1
1.2.2
1.2.3


48.0
Regulatory environment……………………………..………..

9.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
28.3

23.1
Cost of redundancy dismissal, salary weeks…………..

115 ○ ◇
127 ○ ◇
105
96

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
51.7
Ease of starting a business*………………………………..……
67.8
Ease of resolving insolvency*……………………………….…. 35.6

123 ○ ◇
123 ○ ◇
109
◇


37.6
HUMAN CAPITAL & RESEARCH………………...

43

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


41.0
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.8
Government funding/pupil, secondary, % GDP/cap… 17.7
School life expectancy, years……………….…………….……. 14.9

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
19.0

80
87
63
55
n/a
84

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
62.6
🕘🕘Tertiary enrolment, % gross………………………….….……….
68.8
Graduates in science & engineering, %……………….….
43.9
Tertiary inbound mobility, %....................................... ….
0.4

2 ●◆
30 ●
3 ● ◆
97 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
9.1
🕘🕘Researchers, FTE/mn pop……………………………..…...……
671.0
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.3

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
23.4

59
60
83
43 ○ ◇45


INFRASTRUCTURE……………………………….......
46.0

68

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 59.6

ICT access*………………………………………………………….…….
72.7

ICT use*…………………………….....................................…….
49.8

63.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
52.8

79
58
71
87
102

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
48.6
Electricity output, GWh/mn pop………………………..…….
3,601.1
Logistics performance*…………………………………………….. 36.9
Gross capital formation, % GDP………………………….…….
39.1

23 ● ◆
56
63
8 ●◆

3.3
3.3.1
3.3.2
3.3.3


29.8
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
5.9

Environmental performance*…….………………………………
58.2
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.4

97
101
70
88



MARKET SOPHISTICATION..………….…………… 40.0 100

61

◇

◇
◇

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
40.2
Ease of getting credit*…………………………………..…………..
50.0
🕘🕘Domestic credit to private sector, % GDP…………...…… 66.1

Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 25.2 128 ○ ◇
Ease of protecting minority investors*…………..………….
33.3 125 ○ ◇
Market capitalization, % GDP………………………………...….
24.6 53Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
54.7
🕘🕘Applied tariff rate, weighted avg., %………………………….
15.2
Intensity of local competition†…………………………………… 58.0
Domestic market scale, bn PPP$…………………………… 1,652.9

54
87
47
n/a

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
26.3 [93]Knowledge-intensive employment, %...........................
18.7 76Firms offering formal training, % firms………………………… n/a n/a🕘🕘
GERD performed by business, % GDP…………………..…… 0.1 65
🕘🕘
GERD financed by business, %……………………………........
30.9 57
Females employed w/advanced degrees, %……………..
n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
20.3
University/industry research collaboration †………………..
33.6
State of cluster development†.……..………..…………………..
43.9
GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
21.1 120 ○ ◇🕘🕘
0.2 92
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.9 107
🕘🕘
ICT services imports, % total trade…………..………………...
0.5 104
◇
FDI net inflows, % GDP…………………………….………………….
0.8 108🕘🕘Research talent, % in business enterprise……..…………..
15.0 60

84
97
78
n/a
110 ○ ◇
78

 27.2 46
KNOWLEDGE & TECHNOLOGY OUTPUTS....


32 ● ◆
14 ● ◆
64
n/a
27 ● ◆
41

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 27.9
Patents by origin/bn PPP$ GDP……………….…………..….…
9.3

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 17.6
Citable documents H-index…………………….……….……..….
17.6

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


46.3 23 ● ◆
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.4
18 ●

New businesses/th pop. 15-64………………….…....………….
n/a n/aComputer software spending, % GDP…………..…………… 0.3 59
ISO 9001 quality certificates/bn PPP$ GDP…………..……
1.5 100
🕘🕘High- & medium-high-tech manufactures, %………………
0.4 30 ●

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.5
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0Intellectual property receipts, % total trade……………….

0.3
High-tech net exports, % total trade……………….….…......
🕘🕘ICT services exports, % total trade……………..……..………
0.6
🕘🕘
FDI net outflows, % GDP…………………………….………….......
0.0

116 ○ ◇
86
91
95
108


32.5
CREATIVE OUTPUTS…….…………………….…………

45

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
62.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
200.7
Industrial designs by origin/bn PPP$ GDP…………..……..
10.9

ICTs & business model creation†………………………....…….
57.6

ICTs & organizational model creation †…………………….... 47.4

6 ●◆
4 ●◆
13 ● ◆
78
91

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.2
Online creativity………………………………………..……….…….

1.8
Generic top-level domains (TLDs)/th pop. 15-69……….

4.7
Country-code TLDs/th pop. 15-69…………………..………….

9.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.0

1.4 120 ○ ◇n/a n/a
1.7
71
1.7 54◇
0.2 102 ○ ◇0.1 1 1 1

77
79
50
64
96 ○

90
127 ○ ◇
113 ○ ◇
18 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
270

The Global Innovation Index 2019

IRELANDGII 2019 rank

12

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

10

20

High

EUR

4.8

378.5

78,784.8

10

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
85.5

18

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
81.7

Political and operational stability*……………..………….….
89.5
Government effectiveness*…………………………..…………. 77.8

18
15
23

1.2
1.2.1
1.2.2
1.2.3


87.3
Regulatory environment……………………………..………..

84.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
84.2

14.3
Cost of redundancy dismissal, salary weeks…………..

19
17
20
56 ○

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
87.5
Ease of starting a business*………………………………..……
95.9
Ease of resolving insolvency*……………………………….…. 79.1

12
10
17


48.4
HUMAN CAPITAL & RESEARCH………………...

22

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


49.7
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.8
Government funding/pupil, secondary, % GDP/cap… 16.5
School life expectancy, years……………….…………….……. 18.8

PISA scales in reading, maths, & science…………......…
509.0

Pupil-teacher ratio, secondary…………………………......….
n/a

61 ○ ◇
88 ○ ◇
75 ○ ◇
9 ●
10
n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
45.4
🕘🕘Tertiary enrolment, % gross………………………….….……….
77.6
Graduates in science & engineering, %……………….…. 25.2

Tertiary inbound mobility, %....................................... ….
8.2

23
21
29
26

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
50.0
Researchers, FTE/mn pop…………………………….…...…… 4,288.6
Gross expenditure on R&D, % GDP………….………..……
1.0

78.4
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*…………… 47.0

20
21
34
12
22


INFRASTRUCTURE……………………………….......
66.3

◇

5 ● ◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 83.8

ICT access*………………………………………………………….…….
81.3

ICT use*…………………………….....................................…….
77.9

82.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
93.3

23
22
20
39
22

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
45.7
Electricity output, GWh/mn pop………………………..…….
6,394.0
Logistics performance*…………………………………………….. 67.7
Gross capital formation, % GDP………………………….…….
27.1

32
32
28
34

3.3
3.3.1
3.3.2
3.3.3


69.6
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
23.3
Environmental performance*…….……………………………… 78.8
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.8

4 ●◆
3●◆
9 ●
34



◇


BUSINESS SOPHISTICATION..……….……………
55.8

13

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
62.1

Knowledge-intensive employment, %...........................
42.5
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… 0.7

GERD financed by business, %……………………………........
49.0

Females employed w/advanced degrees, %……………..
25.6

22
21
n/a
27
◇
30
9 ●◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
46.2
University/industry research collaboration †………………..
69.9
†State of cluster development .……..………..………………….. 60.8

GERD financed by abroad, %......................................... 23.6

JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP……………………..
1.8

17
11
23
16
18
22

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
59.1

22.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.1

ICT services imports, % total trade…………..………………...
1.5

FDI net inflows, % GDP…………………………….…………………. 35.3
Research talent, % in business enterprise……..………….. 53.3

5 ●
1 ● ◆
56 ○
46
4 ●◆
22

 56.9KNOWLEDGE & TECHNOLOGY OUTPUTS....

6 ●

39

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
44.8
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...…… 44.4
Microfinance gross loans, % GDP……………………….…….
n/a

44
◇
40
76 ○ ◇
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 50.1
Ease of protecting minority investors*…………..………….
75.0

Market capitalization, % GDP………………………………...….
42.4
Venture capital deals/bn PPP$ GDP……………….……....
0.1

38
14
34 ○ ◇
14

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
69.0

Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 69.4
Domestic market scale, bn PPP$……………………………… 378.5

3723
64 ○ ◇
48

◇
◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 28.7
Patents by origin/bn PPP$ GDP……………….…………..….…
2.2

1.6
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 13.2
Citable documents H-index…………………….……….……..….
33.2

31
39
22
n/a
39
28

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


58.6
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.8
New businesses/th pop. 15-64………………….…....………….
6.7
Computer software spending, % GDP…………..…………… 0.8

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 7.3
🕘🕘High- & medium-high-tech manufactures, %………………
0.7

3 ● ◆
28
◆
21
2 ●◆
44
2 ●◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


83.4
Knowledge diffusion……………………………………..…..…….

2.8Intellectual property receipts, % total trade……………….

9.9
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
22.7

FDI net outflows, % GDP…………………………….…………....... 28.7

1 ●◆
7 ●
16
1 ● ◆
1 ●◆
43.3
CREATIVE OUTPUTS…….…………………….…………

19

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
60.5

Trademarks by origin/bn PPP$ GDP…………..……….….….
n/aIndustrial designs by origin/bn PPP$ GDP…………..…….. 1.4

ICTs & business model creation†………………………....……. 76.5

ICTs & organizational model creation †……………………....
70.8

8 ●
n/a
59 ○
14
20

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
18.4
Cultural & creative services exports, % total trade…....
0.2
🕘🕘National feature films/mn pop. 15-69………………….………
8.9
Entertainment & Media market/th pop. 15-69…………….
49.6
Printing & other media, % manufacturing…................... 0.5
Creative goods exports, % total trade………………………..
1.3

59 ○ ◇
72 ○ ◇
21
18
94 ○ ◇
40

7.3
7.3.1
7.3.2
7.3.3
7.3.4


33.7
Online creativity………………………………………..……….…….

61.0
Generic top-level domains (TLDs)/th pop. 15-69……….

22.1
Country-code TLDs/th pop. 15-69…………………..………….

49.5
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
18.3

24
11
26
24
25

◇

MARKET SOPHISTICATION..………….…………… 54.6



◆

◇

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

271

ISRAELGII 2019 rank

10

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

8

17

High

NAWA

8.5

336.1

37,972.0

11

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

77.9

31

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
78.6

Political and operational stability*……………..………….….
75.4
Government effectiveness*…………………………..………….
80.1

24
46
20

◇

1.2
1.2.1
1.2.2
1.2.3


72.6
Regulatory environment……………………………..………..

76.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
73.4

27.4
Cost of redundancy dismissal, salary weeks…………..

◇
44
23
28
◇
111 ○ ◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
82.5

92.4
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….….
72.7

26
41
27


54.5
HUMAN CAPITAL & RESEARCH………………...

14

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


55.6
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.9
Government funding/pupil, secondary, % GDP/cap… 18.7
School life expectancy, years……………….…………….……. 16.0

PISA scales in reading, maths, & science…………......…
471.7
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
9.8

42
22
56 ○
35
38 ○ ◇
26

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
29.7
Tertiary enrolment, % gross………………………….….……….
62.7
Graduates in science & engineering, %……………….….
n/a🕘🕘Tertiary inbound mobility, %.......................................
….
2.8

72 ○ ◇
42n/a
67 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
78.2
🕘🕘
Researchers, FTE/mn pop……………………………..…...……
8,250.5
Gross expenditure on R&D, % GDP………….………..……

4.6

70.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
42.6

2 ●◆
1 ●◆
1 ●◆
17
27


INFRASTRUCTURE……………………………….......
56.1

33

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 80.6

80.3
ICT access*………………………………………………………….…….

ICT use*…………………………….....................................…….
76.2

82.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
83.2

31
27
24
39
43

◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
37.9
Electricity output, GWh/mn pop………………………..…….
7,791.4
Logistics performance*…………………………………………….. 58.2
Gross capital formation, % GDP………………………….…….
20.9

51
◇
24
36
◇
89 ○

3.3
3.3.1
3.3.2
3.3.3


50.0
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
12.0
Environmental performance*…….………………………………
75.0
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.8

30
29
19
35


61.4
MARKET SOPHISTICATION..………….……………

16

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
47.7
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...……
66.0
Microfinance gross loans, % GDP……………………….…….
n/a

37
54
48
n/a

4.2
4.2.1
4.2.2
4.2.3
4.3
4.3.1
4.3.2
4.3.3


BUSINESS SOPHISTICATION..……….……………
66.5

3 ● ◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
63.4

Knowledge-intensive employment, %...........................
48.4
Firms offering formal training, % firms…………………………
18.6
GERD performed by business, % GDP…………………..…… 3.9

GERD financed by business, %……………………………........ 34.7
🕘🕘Females employed w/advanced degrees, %……………..
28.4

19
8
76 ○ ◇1 ●◆54 ○ ◇
3 ●◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
82.5
University/industry research collaboration †………………..
79.4
State of cluster development†.……..………..…………………..
58.5
GERD financed by abroad, %.........................................
49.8
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 6.9

1 ●◆
2 ●◆
30
3 ●◆
8
2 ●◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
53.7

0.5
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.0

ICT services imports, % total trade…………..………………...
2.1

FDI net inflows, % GDP…………………………….………………….
4.2
🕘🕘Research talent, % in business enterprise……..…………..
83.7

15
65 ○ ◇
45
24
40
1 ●◆

 56.9KNOWLEDGE & TECHNOLOGY OUTPUTS....

7



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 56.7
Patents by origin/bn PPP$ GDP……………….…………..….…
4.5

5.7
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 24.2
Citable documents H-index…………………….……….……..….
47.1

10
25
7
n/a
14
16

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


48.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.2
New businesses/th pop. 15-64………………….…....………….
3.4
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
27.1
🕘🕘High- & medium-high-tech manufactures, %……………… 0.4

21
59
36
57
5
19

6.3
6.3.1
6.3.2
6.3.3
6.3.4


65.9
Knowledge diffusion……………………………………..…..…….

1.7Intellectual property receipts, % total trade……………….

11.9
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
12.2

FDI net outflows, % GDP…………………………….………….......
3.3

◆
4
14
13
1 ● ◆
21


46.3
CREATIVE OUTPUTS…….…………………….…………

14

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
49.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
11.8
Industrial designs by origin/bn PPP$ GDP…………..……..
3.4

ICTs & business model creation†………………………....…….
81.5

ICTs & organizational model creation †……………………....
77.0

39
101 ○ ◇
38
5
12

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
28.4
Cultural & creative services exports, % total trade…....
2.5
🕘🕘National feature films/mn pop. 15-69………………….………
5.7
Entertainment & Media market/th pop. 15-69…………….
35.8
🕘🕘
Printing & other media, % manufacturing…...................
1.1
Creative goods exports, % total trade………………………..
1.7

34
4
◆
38
21
◇
57 ○
31

Investment……………………………………………………..………. 66.5
Ease of protecting minority investors*…………..………….
73.3
Market capitalization, % GDP………………………………...….
71.6
Venture capital deals/bn PPP$ GDP……………….……....
0.4

14
21
21
3●◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


58.8
Online creativity………………………………………..……….…….

22.4
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 12.7

148.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
100.0

5
26
35
◇
1 ●◆
1 ●◆


Trade, competition, & market scale………..…………….
69.8
Applied tariff rate, weighted avg., %………………………….
1.9

†Intensity of local competition …………………………………… 75.4
Domestic market scale, bn PPP$……………………………… 336.1

34
50
24
50

◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
272

The Global Innovation Index 2019

◆

◇
◆

ITALYGII 2019 rank

30

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

29

30

High

EUR

59.3

2,398.2

39,637.0

31

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
75.3

34

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
63.7

Political and operational stability*……………..………….….
73.7
Government effectiveness*…………………………..…………. 58.7

46
50
44

1.2
1.2.1
1.2.2
1.2.3


79.0
Regulatory environment……………………………..………..

60.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
55.0

8.0
Cost of redundancy dismissal, salary weeks…………..

31
39
50
◇
1 ●◆

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
83.4

Ease of starting a business*………………………………..……
89.5
Ease of resolving insolvency*……………………………….…. 77.3

23
57
21


45.4
HUMAN CAPITAL & RESEARCH………………...

31

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


53.6
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.1
Government funding/pupil, secondary, % GDP/cap… 22.9
School life expectancy, years……………….…………….……. 16.2

PISA scales in reading, maths, & science…………......…
485.0
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
10.0

49
75 ○
37
30
31
31

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
37.0
🕘🕘
Tertiary enrolment, % gross………………………….….……….
63.0
Graduates in science & engineering, %……………….….
23.3
Tertiary inbound mobility, %.......................................
….
5.1

46
40
42
39

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
45.5
Researchers, FTE/mn pop……………………………..…...… 2,294.5
Gross expenditure on R&D, % GDP………….………..……
1.4

77.2
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
47.6

22
37
24
13 ●
20


INFRASTRUCTURE……………………………….......
59.4

22

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 82.6

ICT access*………………………………………………………….…….
74.3

ICT use*…………………………….....................................…….
65.3

95.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
95.5

24
48 ◇
44
9 ●
15 ●

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
37.2
Electricity output, GWh/mn pop………………………..…….
4,845.3
Logistics performance*…………………………………………….. 78.4
Gross capital formation, % GDP………………………….…….
18.1

55
46
19
103 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


58.3
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
13.5
Environmental performance*…….………………………………
77.0
ISO 14001 environmental certificates/bn PPP$ GDP.. 6.3

9 ●
18
16 ●
17

◇
◇
◇



MARKET SOPHISTICATION..………….…………… 51.4 50
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
41.7
Ease of getting credit*…………………………………..…………..
45.0

Domestic credit to private sector, % GDP…………...……
81.7

Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 34.0 104 ○ ◇Ease of protecting minority investors*…………..………….
58.3 68 ○🕘🕘Market capitalization, % GDP………………………………...….
26.5
51 ○

Venture capital deals/bn PPP$ GDP……………….……....
0.0 33

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
78.7
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 71.4
Domestic market scale, bn PPP$…………………………… 2,398.2

50
94 ○
35n/a
BUSINESS SOPHISTICATION..……….……………
42.2

29

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
50.7
Knowledge-intensive employment, %...........................
36.1
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… 0.8

GERD financed by business, %……………………………........
52.1
Females employed w/advanced degrees, %……………..
12.6

36
36
n/a
23
23
54

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
37.6
University/industry research collaboration †………………..
49.5
State of cluster development†.……..………..…………………..
74.5

GERD financed by abroad, %.........................................
9.8
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 2.0

34
41
4 ●◆
44
61 ○
21

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
38.2

0.9
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.7

ICT services imports, % total trade…………..………………...
1.7

FDI net inflows, % GDP…………………………….………………….
0.8
Research talent, % in business enterprise……..………….. 42.6

43
45
77 ○
32
114 ○
31

 38.9 22
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 38.0
Patents by origin/bn PPP$ GDP……………….…………..….…
5.6

1.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.8
Scientific & technical articles/bn PPP$ GDP….…..…..…. 16.9
Citable documents H-index…………………….……….……..….
69.2

23
21
25
30
30
7 ●◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


55.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.1
New businesses/th pop. 15-64………………….…....………….
2.7
Computer software spending, % GDP…………..……………
0.6
ISO 9001 quality certificates/bn PPP$ GDP…………..……
42.2
High- & medium-high-tech manufactures, %……………… 0.4

6 ● ◆
85 ○41
13 ●
1 ●◆
26

6.3
6.3.1
6.3.2
6.3.3
6.3.4


23.1
Knowledge diffusion……………………………………..…..…….

0.7Intellectual property receipts, % total trade……………….

5.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.6

FDI net outflows, % GDP…………………………….………….......
0.8

42
22
29
67
56


36.8
CREATIVE OUTPUTS…….…………………….…………

37

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
53.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
47.3
Industrial designs by origin/bn PPP$ GDP…………..……..
16.6

ICTs & business model creation†………………………....…….
66.0

ICTs & organizational model creation †…………………….... 54.6

28
52
5 ●◆
47
61
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
21.7
Cultural & creative services exports, % total trade…....
0.4
National feature films/mn pop. 15-69………………….………
4.2
Entertainment & Media market/th pop. 15-69…………….
29.4
Printing & other media, % manufacturing…...................
1.3
Creative goods exports, % total trade………………………..
2.2

51
60
46
23
44
24

7.3
7.3.1
7.3.2
7.3.3
7.3.4


19.4
Online creativity………………………………………..……….…….

23.2
Generic top-level domains (TLDs)/th pop. 15-69……….

21.5
Country-code TLDs/th pop. 15-69…………………..………….

44.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
3.4

36
24
27
32
58 ○

12 ● ◆
23
47
12 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

273

JAMAICAGII 2019 rank

81

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

69

84

Upper middle

LCN

2.9

27.0

9,446.6

81

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
71.3

42

◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
62.9

Political and operational stability*……………..………….….
71.9
Government effectiveness*…………………………..…………. 58.4

48
58
45

◆

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

63
64
70
54

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
83.6

Ease of starting a business*………………………………..……
97.4
Ease of resolving insolvency*……………………………….…. 69.8

22 ● ◆
6 ●◆
31
◆


24.4
HUMAN CAPITAL & RESEARCH………………...

86

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


52.4
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.3
Government funding/pupil, secondary, % GDP/cap… 26.7

School life expectancy, years……………….…………….……. n/a
PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
15.5

[50]
34
18 ● ◆
n/a
n/a
71

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
20.8
🕘🕘
Tertiary enrolment, % gross………………………….….……….
26.9
Graduates in science & engineering, %……………….….
n/aTertiary inbound mobility, %....................................... ….
n/a

[93]
88
n/a
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

67.4
45.8
42.2
14.0

◆

◇

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
INFRASTRUCTURE……………………………….......
33.7 105

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 38.5

ICT access*………………………………………………………….…….
53.6

ICT use*…………………………….....................................…….
37.1

31.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
31.5

107
◇
81
93
◇
117 ○ ◇
118 ○ ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
23.1
Electricity output, GWh/mn pop………………………..…….
1,468.8
Logistics performance*…………………………………………….. 21.3
Gross capital formation, % GDP………………………….…….
21.0

110 ○
89
104 ○ ◇
88

3.3
3.3.1
3.3.2
3.3.3


39.4
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
7.9
Environmental performance*…….………………………………
58.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 4.6

59
76
68
25 ●



MARKET SOPHISTICATION..………….…………… 36.4 114 ○ ◇
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
33.8
Ease of getting credit*…………………………………..…………..
85.0
🕘🕘Domestic credit to private sector, % GDP…………...…… 32.0
Microfinance gross loans, % GDP……………………….……. 0.2

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 32.9 109
Ease of protecting minority investors*…………..………….
55.0 84🕘🕘Market capitalization, % GDP………………………………...….
32.1 46Venture capital deals/bn PPP$ GDP……………….……....
0.0 34

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
42.5 124 ○ ◇🕘🕘
Applied tariff rate, weighted avg., %………………………….
10.8 117 ○ ◇
Intensity of local competition†…………………………………… 72.1 45
Domestic market scale, bn PPP$……………………………… 27.0 120 ○ ◇74
11 ● ◆
92
44


BUSINESS SOPHISTICATION..……….……………
31.5

64

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
33.6

Knowledge-intensive employment, %...........................
21.7
🕘🕘Firms offering formal training, % firms………………………… 25.9

GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/aFemales employed w/advanced degrees, %……………..
n/a

[75]
70
61
n/a
n/a
n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
28.8
University/industry research collaboration †………………..
47.1
State of cluster development†.……..………..…………………..
48.2

GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

52
◆
45
55
n/a
25 ● ◆
69

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
32.2

0.9
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.4

ICT services imports, % total trade…………..………………...
1.3

FDI net inflows, % GDP…………………………….………………….
6.4
Research talent, % in business enterprise……..………….. n/a

71
43
113 ○
57
21 ● ◆
n/a

 15.7 94
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


28.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-1.9
New businesses/th pop. 15-64………………….…....………….
1.3
Computer software spending, % GDP…………..…………… 0.4

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.5
High- & medium-high-tech manufactures, %………………
n/a97
107 ○ ◇63
25 ● ◆
98
n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


12.7
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

0.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.1

FDI net outflows, % GDP…………………………….………….......
0.8

87
58
124 ○
53
57


28.6
CREATIVE OUTPUTS…….…………………….…………

60

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
50.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
105.9
Industrial designs by origin/bn PPP$ GDP…………..……..
4.9

ICTs & business model creation†………………………....…….
63.6

ICTs & organizational model creation †…………………….... 55.2

33
10 ●
26 ●
54
60

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
12.4
Cultural & creative services exports, % total trade…....
1.3
National feature films/mn pop. 15-69………………….………
n/aEntertainment & Media market/th pop. 15-69…………….
n/a
Printing & other media, % manufacturing…...................
n/aCreative goods exports, % total trade……………………….. 0.2[76]
21 ●
n/a
n/a
n/a
84

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

98
81
81
98
n/a

5.7 [94]
0.4 79n/a n/an/a n/a
4.6 844.2 100

1.4
1.8
1.0
2.3
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
274

The Global Innovation Index 2019

JAPANGII 2019 rank

15

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

17

14

High

SEAO

127.2

5,632.5

44,227.2

13

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
56.5

INSTITUTIONS………………………………….…….…..
89.9

10

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
88.2

Political and operational stability*……………..………….….
93.0
Government effectiveness*…………………………..…………. 85.7

12
7
13

1.2
1.2.1
1.2.2
1.2.3


91.7
Regulatory environment……………………………..………..

78.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
87.8

8.0
Cost of redundancy dismissal, salary weeks…………..

15
20
18
1 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
89.8
Ease of starting a business*………………………………..……
86.1

Ease of resolving insolvency*……………………………….…. 93.5

5 ●
74 ○ ◇1 ●◆
49.1
HUMAN CAPITAL & RESEARCH………………...

21

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.3
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.5
Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. 15.2

PISA scales in reading, maths, & science…………......…
528.9
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.2

37
95 ○ ◇
n/a
47 ◇
3 ●◆
40

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
13.6 [103]Tertiary enrolment, % gross………………………….….……….
n/a n/a
Graduates in science & engineering, %……………….….
n/a n/a
Tertiary inbound mobility, %.......................................
….
3.7
57

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

◇

76.3
Researchers, FTE/mn pop………………………………...…… 5,304.9
Gross expenditure on R&D, % GDP………….………..……
3.2

92.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
79.2

5 ●
10
55 ●
8

INFRASTRUCTURE……………………………….......
64.0

9

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 90.3

ICT access*………………………………………………………….…….
86.3

ICT use*…………………………….....................................…….
81.3

95.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
98.3

7
11
12
9
5

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
50.7
Electricity output, GWh/mn pop………………………..…….
8,500.2
Logistics performance*…………………………………………….. 91.8
Gross capital formation, % GDP………………………….…….
24.5

15
19
5
48

3.3
3.3.1
3.3.2
3.3.3


50.9
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
11.2
Environmental performance*…….………………………………
74.7
ISO 14001 environmental certificates/bn PPP$ GDP..
4.4

27
39
20
26


65.8
MARKET SOPHISTICATION..………….……………

10

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
68.5
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...……
168.2

Microfinance gross loans, % GDP……………………….…….
n/a

12
77 ○
5●◆
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 42.9
Ease of protecting minority investors*…………..………….
60.0

Market capitalization, % GDP………………………………...….
113.1
Venture capital deals/bn PPP$ GDP……………….……....
0.0

63
◇
61 ○
8
51 ○ ◇

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
85.9

Applied tariff rate, weighted avg., %………………………….
2.5
Intensity of local competition†…………………………………… 87.2
Domestic market scale, bn PPP$………………………...… 5,632.5

3 ●◆
59
1●◆
4●◆

11

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
63.1

Knowledge-intensive employment, %...........................
25.2
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..……
2.5

GERD financed by business, %……………………………........
78.3
🕘🕘Females employed w/advanced degrees, %……………..
21.0

21
56
◇
n/a
3 ●◆
1 ●◆
22

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
50.2
University/industry research collaboration †………………..
64.5
State of cluster development†.……..………..…………………..
72.3

GERD financed by abroad, %.........................................
0.6
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 13.2

12
18
7
94 ○ ◇
36
◇
4
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
56.2

2.4
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
13.8
ICT services imports, % total trade…………..………………...
1.7

FDI net inflows, % GDP…………………………….………………….
0.4
Research talent, % in business enterprise……..………….. 73.7

10
9
14
34
121 ○
3 ●◆ 50.8KNOWLEDGE & TECHNOLOGY OUTPUTS....

12



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 56.1
Patents by origin/bn PPP$ GDP……………….…………..….…
47.8

8.8
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.8
Scientific & technical articles/bn PPP$ GDP….…..…..…. 9.2
Citable documents H-index…………………….……….……..….
71.0

11
1 ●◆
1 ●◆
28
53
◇
6

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


39.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.0
🕘🕘
New businesses/th pop. 15-64………………….…....………….
0.2
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 8.9
🕘🕘High- & medium-high-tech manufactures, %……………… 0.550◇
89 ○
95 ○ ◇
47
35
9

6.3
6.3.1
6.3.2
6.3.3
6.3.4


56.4
Knowledge diffusion……………………………………..…..…….

4.8
Intellectual property receipts, % total trade……………….

12.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.6

FDI net outflows, % GDP…………………………….………….......
3.4

9
1 ●◆
12
98 ○
20


37.9
CREATIVE OUTPUTS…….…………………….…………

35

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
54.5
Trademarks by origin/bn PPP$ GDP…………..……….….….
91.1
Industrial designs by origin/bn PPP$ GDP…………..……..
4.5
†
ICTs & business model creation ………………………....……. 73.2

ICTs & organizational model creation †…………………….... 67.8

22
21
29
25
22

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5



Creative goods & services……………………….…….……….. 30.9
Cultural & creative services exports, % total trade…....
0.4
National feature films/mn pop. 15-69………………….………
7.0
Entertainment & Media market/th pop. 15-69…………….
67.1
🕘🕘Printing & other media, % manufacturing…...................
1.7
Creative goods exports, % total trade………………………..
2.0

26
55
30
6
26
27

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….

Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

49
31
48
50
35

11.6
15.4
5.1
18.6
13.2

◇
◇
◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

275

JORDANGII 2019 rank

86

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

71

91

Upper middle

NAWA

9.9

93.2

9,433.5

79

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
16.9 128 ○ ◇
INSTITUTIONS………………………………….…….…..
62.1

67

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
54.5

Political and operational stability*……………..………….….
64.9
Government effectiveness*…………………………..…………. 49.4

67
79
64

1.2
1.2.1
1.2.2
1.2.3


74.5
Regulatory environment……………………………..………..

44.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
53.3

8.0
Cost of redundancy dismissal, salary weeks…………..

38 ● ◆66
51◆
1 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
57.4

84.4
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….…. 30.3

109 ○ ◇
81
120 ○ ◇


29.4
HUMAN CAPITAL & RESEARCH………………...

68

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


37.3
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.6
Government funding/pupil, secondary, % GDP/cap… 17.0
School life expectancy, years……………….…………….……. n/a
PISA scales in reading, maths, & science…………......…
399.0

Pupil-teacher ratio, secondary…………………………......….
11.4

93
91
71
n/a
62 ○
42

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
43.2
Tertiary enrolment, % gross………………………….….……….
31.7
🕘🕘Graduates in science & engineering, %……………….…. 26.4

Tertiary inbound mobility, %....................................... …. 13.9

27 ●
82
24 ●
11 ● ◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
7.8
Researchers, FTE/mn pop……………………………..…...……
601.1
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.3

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
17.1

66
64
75
43 ○ ◇55


INFRASTRUCTURE……………………………….......
38.2

91

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 54.2

61.5
ICT access*………………………………………………………….…….

ICT use*…………………………….....................................…….
57.5

49.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
48.3

87
73
60
105
105

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
23.9 104Electricity output, GWh/mn pop………………………..…….
2,085.7
75

Logistics performance*…………………………………………….. 29.2 82
Gross capital formation, % GDP………………………….…….
19.4 96

3.3
3.3.1
3.3.2
3.3.3


36.6
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
8.7
Environmental performance*…….……………………………… 62.2
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.9



73
66
55
69

MARKET SOPHISTICATION..………….…………… 38.9 106

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
25.5 107Ease of getting credit*…………………………………..…………..
35.0 110 ○ ◇🕘🕘
Domestic credit to private sector, % GDP…………...……
41 ●
75.1

Microfinance gross loans, % GDP……………………….……. 0.4 36

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 31.3
Ease of protecting minority investors*…………..………….
46.7
Market capitalization, % GDP………………………………...….
63.7
Venture capital deals/bn PPP$ GDP……………….……....
0.0

116 ○ ◇
101
25
42

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
59.8

Applied tariff rate, weighted avg., %………………………….
4.4

Intensity of local competition†…………………………………… 76.0Domestic market scale, bn PPP$……………………………… 93.2

69
79
19 ● ◆
81

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
0.0 [129]
Knowledge-intensive employment, %...........................
n/a n/a
Firms offering formal training, % firms………………………… 3.4 91 ○ ◇
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
26.7
University/industry research collaboration †………………..
40.6
†State of cluster development .……..………..………………….. 57.7

GERD financed by abroad, %......................................... n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
23.9 106
0.1 98Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.6 79

ICT services imports, % total trade…………..………………...
0.2 118 ○ ◇
FDI net inflows, % GDP…………………………….………………….
4.4 36 ●Research talent, % in business enterprise……..………….. n/a n/a59
66
31 ● ◆n/a
9071

 17.4 84
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 14.4

Patents by origin/bn PPP$ GDP……………….…………..….…
0.3

n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 14.1
Citable documents H-index…………………….……….……..….
8.4

[57]
88
n/a
n/a
36 ●
77

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


30.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.2
New businesses/th pop. 15-64………………….…....………….
0.6

Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 4.2
High- & medium-high-tech manufactures, %………………
0.2

91
94 ○
80
49
63
50

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.3
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

0.4
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.1

FDI net outflows, % GDP…………………………….………….......
0.0

117 ○ ◇
48
82
123 ○
1 1 1 ○
26.8
CREATIVE OUTPUTS…….…………………….…………

67

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
37.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
34.7
Industrial designs by origin/bn PPP$ GDP…………..……..
0.8

ICTs & business model creation†………………………....……. 63.5

ICTs & organizational model creation †…………………….... 52.6

82
70
76
55
68

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
23.1 46

Cultural & creative services exports, % total trade…....
0.3 64
National feature films/mn pop. 15-69………………….………
n/a n/aEntertainment & Media market/th pop. 15-69…………….
1.9 53 ○ ◇
Printing & other media, % manufacturing…................... 2.4 13 ● ◆🕘🕘Creative goods exports, % total trade………………………..
1.5 36 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


8.9
Online creativity………………………………………..……….…….

5.2
Generic top-level domains (TLDs)/th pop. 15-69……….

0.2
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
21.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
15.6

54
54
107
48
32 ●NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
276

The Global Innovation Index 2019

KAZAKHSTAN

GII 2019 rank

79

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

9264

Upper middle

CSA

18.4

507.6

27,549.874

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
68.3

49

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
54.6

Political and operational stability*……………..………….….
70.2
Government effectiveness*…………………………..…………. 46.8

66
61
69

1.2
1.2.1
1.2.2
1.2.3


70.0
Regulatory environment……………………………..………..

46.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
35.5

8.7
Cost of redundancy dismissal, salary weeks…………..

53
62
87
19 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
80.4

Ease of starting a business*………………………………..……
93.0
Ease of resolving insolvency*……………………………….…. 67.8

31 ● ◆
33 ●34 ● ◆


29.8
HUMAN CAPITAL & RESEARCH………………...

67

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


44.3
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
2.9
Government funding/pupil, secondary, % GDP/cap… 20.2

School life expectancy, years……………….…………….……. 15.3
🕘🕘
PISA scales in reading, maths, & science…………......…
416.4
Pupil-teacher ratio, secondary…………………………......….
7.0

72
105
◇
49
45
53
2 ● ◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
34.5
Tertiary enrolment, % gross………………………….….……….
53.3
Graduates in science & engineering, %……………….…. 24.8
Tertiary inbound mobility, %....................................... ….
2.2

54
53
31
72

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
10.7
🕘🕘Researchers, FTE/mn pop……………………………..…...……
687.6
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*…………… 31.7

56
59
97
43 ○ ◇35 ●
INFRASTRUCTURE……………………………….......
46.1

67

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 76.2

ICT access*………………………………………………………….…….
75.4

ICT use*…………………………….....................................…….
58.9

86.8
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
83.7

40
◆
41 ◆
58
32 ● ◆
42

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
35.4
Electricity output, GWh/mn pop………………………..…….
5,990.3
Logistics performance*…………………………………………….. 34.9
Gross capital formation, % GDP………………………….…….
25.5

63
34
70
42

3.3
3.3.1
3.3.2
3.3.3


26.7 109
Ecological sustainability………………………………………..
◇
GDP/unit of energy use…………………………………………….
5.0 109 ○ ◇
Environmental performance*…….……………………………… 54.6 85
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3 99


BUSINESS SOPHISTICATION..……….……………
28.1

78

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
41.2
🕘🕘
Knowledge-intensive employment, %...........................
33.3
Firms offering formal training, % firms………………………… 28.3
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
39.6
🕘🕘Females employed w/advanced degrees, %……………..
17.5

54
39
54
68
45
33

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
15.6 118 ○ ◇
University/industry research collaboration †………………..
40.5 67◇State of cluster development†.……..………..…………………..
34.4 110
GERD financed by abroad, %.........................................
1.5 85
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 74
Patent families 2+ offices/bn PPP$ GDP……………………..
0.1 54

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
27.6

0.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.5

ICT services imports, % total trade…………..………………... 0.6

FDI net inflows, % GDP…………………………….…………………. 6.2

Research talent, % in business enterprise……..…………..
n/a

92
80
84
99
22 ● ◆
n/a

 18.2KNOWLEDGE & TECHNOLOGY OUTPUTS....

81

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 10.6

Patents by origin/bn PPP$ GDP……………….…………..….…
2.4

0.0
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 1.6
Scientific & technical articles/bn PPP$ GDP….…..…..….
1.8

Citable documents H-index…………………….……….……..….
3.5

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


29.5 96
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.1 23 ●
New businesses/th pop. 15-64………………….…....………….
2.2 47Computer software spending, % GDP…………..…………… 0.0 120 ○ ◇
ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.8 113High- & medium-high-tech manufactures, %………………
0.1 84

6.3
6.3.1
6.3.2
6.3.3
6.3.4


14.7
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

3.6
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.2

FDI net outflows, % GDP…………………………….…………....... 1.6◆

MARKET SOPHISTICATION..………….…………… 46.3 69
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
26.8 102
Ease of getting credit*…………………………………..…………..
65.0 54Domestic credit to private sector, % GDP…………...…… 29.9 95
Microfinance gross loans, % GDP……………………….……. 0.2 46

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 44.9
Ease of protecting minority investors*…………..………….
85.0

Market capitalization, % GDP………………………………...….
25.4
Venture capital deals/bn PPP$ GDP……………….……....
0.0

57
1●◆
52
75 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
67.3
Applied tariff rate, weighted avg., %………………………….
2.4
Intensity of local competition†…………………………………… 60.0Domestic market scale, bn PPP$……………………………… 507.6

45
58
107
40



◆

68
36
80
16 ●
116 ○
110

78
99 ○ ◇
41
115 ○
38
18.4 102
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
31.5
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
18.8
Industrial designs by origin/bn PPP$ GDP…………..…….. 0.2

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.8
Online creativity………………………………………..……….…….

0.3
Generic top-level domains (TLDs)/th pop. 15-69……….

3.2
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
17.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.0

◇

103
90
98

ICTs & business model creation†………………………....……. 54.7 87
ICTs & organizational model creation †……………………....
48.2
87
6.8 96
0.1 91
6.0 37n/a n/a0.5 92 ○
0.1 9371
114 ○
60
52
90 ○◇NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

277

KENYAGII 2019 rank

77

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

64

89

Lower middle

SSF

51.0

177.4

3,690.978

Score/Value Rank

INSTITUTIONS………………………………….…….…..
59.2

78

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
45.9

Political and operational stability*……………..………….….
59.6
Government effectiveness*…………………………..…………. 39.0

91
98
88

1.2
1.2.1
1.2.2
1.2.3


61.9
Regulatory environment……………………………..………..

35.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
35.5

15.8
Cost of redundancy dismissal, salary weeks…………..

76
88
88
63

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
69.9
Ease of starting a business*………………………………..……
82.4

Ease of resolving insolvency*……………………………….…. 57.4

67
97
52

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
32.2 61◆17.5 104
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


33.8 [100]Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.2
39
Government funding/pupil, secondary, % GDP/cap… n/a n/a🕘🕘
School life expectancy, years……………….…………….……. 10.5 102 ○
PISA scales in reading, maths, & science…………......…
n/a n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
33.4 109 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
13.4 104
🕘🕘
Tertiary enrolment, % gross………………………….….……….
11.7 104
Graduates in science & engineering, %……………….….
16.5
79

Tertiary inbound mobility, %....................................... ….
0.9 89

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
5.5
🕘🕘Researchers, FTE/mn pop……………………………..…...……
225.0
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.8

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
2.5

76
76
45
◆
43 ○ ◇77


INFRASTRUCTURE……………………………….......
29.6 116 ○ ◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 43.3 100

ICT access*………………………………………………………….…….
39.6 104

ICT use*…………………………….....................................…….
17.6 112 ○ ◇
62.5 89
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
53.4 101

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
20.9
Electricity output, GWh/mn pop………………………..…….
201.2
Logistics performance*…………………………………………….. 35.1
Gross capital formation, % GDP………………………….…….
16.8

117 ○
113 ○ ◇67
112 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


24.5
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
5.3
Environmental performance*…….………………………………
47.3
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.4

118 ○
104
103
91



MARKET SOPHISTICATION..………….…………… 51.8

48

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
58.1
Ease of getting credit*…………………………………..…………..
90.0
Domestic credit to private sector, % GDP…………...…… 29.3

Microfinance gross loans, % GDP……………………….…….
4.2

21 ● ◆
7 ●◆
97
6●◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 46.3
Ease of protecting minority investors*…………..………….
78.3
🕘🕘Market capitalization, % GDP………………………………...….
30.0

Venture capital deals/bn PPP$ GDP……………….……....
0.1

52
10 ● ◆
49
23 ◆

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
51.2 103🕘🕘Applied tariff rate, weighted avg., %………………………….
12.3 121 ○ ◇Intensity of local competition†…………………………………… 72.0 46 ◆Domestic market scale, bn PPP$……………………………… 177.4 67

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
26.3 [92]Knowledge-intensive employment, %...........................
n/a n/a
Firms offering formal training, % firms………………………… 40.6 34
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1 66
🕘🕘
GERD financed by business, %……………………………........
4.3 83
Females employed w/advanced degrees, %……………..
n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
45.0
University/industry research collaboration †………………..
55.1
State of cluster development†.……..………..…………………..
55.4
🕘🕘
GERD financed by abroad, %.........................................
47.1
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
25.2 100
1.2 26 ● ◆Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.1 42
ICT services imports, % total trade…………..………………...
0.3 116 ○ ◇
FDI net inflows, % GDP…………………………….………………….
0.8 1 1 1 ○🕘🕘Research talent, % in business enterprise……..…………..
11.4 63

 20.1KNOWLEDGE & TECHNOLOGY OUTPUTS....


20 ● ◆
29 ● ◆
◆
34
5 ●◆
50
77

72

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

11.3
0.8
0.0
0.9
6.0
14.3

65
67
76
24
68
52

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


30.4
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.1
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.8

Computer software spending, % GDP…………..…………… 0.2

ISO 9001 quality certificates/bn PPP$ GDP…………..……
3.6
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

92
43
75
77
69
77

6.3
6.3.1
6.3.2
6.3.3
6.3.4


18.5
Knowledge diffusion……………………………………..…..…….

0.6Intellectual property receipts, % total trade……………….

0.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.3

FDI net outflows, % GDP…………………………….………….......
0.3

57
25 ● ◆
88
26 ●
80


28.3
CREATIVE OUTPUTS…….…………………….…………

61

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
41.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
32.5
Industrial designs by origin/bn PPP$ GDP…………..……..
0.9
ICTs & business model creation†………………………....…….
68.9

ICTs & organizational model creation †…………………….... 60.0

64
74
70
33 ● ◆
44
◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
30.6 30 ● ◆Cultural & creative services exports, % total trade…....
0.0 98
National feature films/mn pop. 15-69………………….………
n/a n/aEntertainment & Media market/th pop. 15-69…………….
2.4 51◆🕘🕘Printing & other media, % manufacturing…...................
4.2
3 ●◆
🕘🕘
Creative goods exports, % total trade……………………….. 0.3 75

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.6 106
Online creativity………………………………………..……….…….

1.0 97
Generic top-level domains (TLDs)/th pop. 15-69……….

0.8 84
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
1.0 103
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.0 89 ○NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
278

The Global Innovation Index 2019

◆

KUWAITGII 2019 rank

60

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

56

75

High

NAWA

4.2

303.3

67,000.2

60

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
55.6

90

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
49.4

Political and operational stability*……………..………….….
63.2
Government effectiveness*…………………………..…………. 42.5

85
86
83

◇
◇
◇

1.2
1.2.1
1.2.2
1.2.3


57.0
Regulatory environment……………………………..………..

40.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
49.1

28.1
Cost of redundancy dismissal, salary weeks…………..

◇
92
73
◇
55
◇
113 ○ ◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
60.3
Ease of starting a business*………………………………..……
81.4

Ease of resolving insolvency*……………………………….…. 39.3

105
101
101

◇
◇
◇


25.5 [81]
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


48.2
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
n/a🕘🕘Government funding/pupil, secondary, % GDP/cap… 17.6
🕘🕘School life expectancy, years……………….…………….……. 13.6

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
7.6

[67]
n/a
64
73
◇
n/a
6 ●◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
25.3
🕘🕘Tertiary enrolment, % gross………………………….….……….
32.6
Graduates in science & engineering, %……………….….
n/aTertiary inbound mobility, %....................................... ….
n/a

[79]
80
n/a
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
2.9
Researchers, FTE/mn pop……………………………..…...……
491.8
Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
4.5

87
◇
68
◇
110 ○ ◇
43 ○ ◇71 ◇


INFRASTRUCTURE……………………………….......
50.2

53

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  73.7

78.3
ICT access*………………………………………………………….…….

ICT use*…………………………….....................................…….
68.2

79.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
69.1

48 ●
33 ●
38 ●
48 ●
70 ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
42.5
Electricity output, GWh/mn pop………………………..…….17,307.2
Logistics performance*…………………………………………….. 37.3
Gross capital formation, % GDP………………………….…….
22.2

39 ●
5 ● ◆
62
◇
75

3.3
3.3.1
3.3.2
3.3.3


34.4
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
7.6

Environmental performance*…….……………………………… 62.3
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.5

80
82
54
83



◇

◇

◇
◇
◇

MARKET SOPHISTICATION..………….…………… 53.5

41 ●

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
41.1
Ease of getting credit*…………………………………..…………..
35.0
Domestic credit to private sector, % GDP…………...…… 99.2

Microfinance gross loans, % GDP……………………….…….
n/a52
110 ○ ◇
28 ●
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 58.3
Ease of protecting minority investors*…………..………….
58.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[22]
68
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
61.0

Applied tariff rate, weighted avg., %………………………….
4.3
Intensity of local competition†…………………………………… 56.0
Domestic market scale, bn PPP$……………………………… 303.3

6477
119 ○ ◇
55


BUSINESS SOPHISTICATION..……….……………
24.7 [100] 

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
26.6
🕘🕘
Knowledge-intensive employment, %...........................
22.7
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… n/a🕘🕘
GERD financed by business, %……………………………........
1.0

Females employed w/advanced degrees, %……………..
n/a

[91]
66
◇
n/a
n/a
90 ○ ◇
n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
19.6
University/industry research collaboration †………………..
40.2
†State of cluster development .……..………..………………….. 49.9
🕘🕘
GERD financed by abroad, %.........................................
1.2
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

89
68
49
90
56
81

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
28.1 [91]
n/a n/aIntellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.8 76◇
ICT services imports, % total trade…………..………………...
0.7 92
FDI net inflows, % GDP…………………………….………………….
0.2 122 ○
Research talent, % in business enterprise……..………….. n/a n/a◇◇ 25.2 52
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 6.8 [85]Patents by origin/bn PPP$ GDP……………….…………..….…
n/a n/an/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
2.1 112
Citable documents H-index…………………….……….……..….
7.6
81

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


33.4
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-1.5
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..…………… 0.4

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.5
High- & medium-high-tech manufactures, %………………
0.2

79
103 ○ ◇
n/a
26 ●
101
◇
54

6.3
6.3.1
6.3.2
6.3.3
6.3.4


35.4
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….

0.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.9

FDI net outflows, % GDP…………………………….………….......
5.5

24 ●
n/a87◇
20 ●
1 1 ●


29.2
CREATIVE OUTPUTS…….…………………….…………

56

◇
◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
53.7 [25]Trademarks by origin/bn PPP$ GDP…………..……….….….
n/a n/a
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a n/a
ICTs & business model creation†………………………....……. 56.6 82
ICTs & organizational model creation †…………………….... 50.9
78

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


4.9 67
Online creativity………………………………………..……….…….
◇
7.6 44 ●
Generic top-level domains (TLDs)/th pop. 15-69……….

0.3 100
Country-code TLDs/th pop. 15-69…………………..………….
◇🕘🕘
16.3 54
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.7 67◇◇

4.6 103◇
0.0 110 ○ ◇1.9 67◇
11.3 34◇
0.4 97 ○ ◇0.2 78NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

279

KYRGYZSTAN

GII 2019 rank

90

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

111

78

Lower middle

CSA

6.1

24.4

3,843.6

94

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
54.6

92

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
37.0
Political and operational stability*……………..………….….
52.6
Government effectiveness*…………………………..…………. 29.2

117
118
114

1.2
1.2.1
1.2.2
1.2.3


56.5
Regulatory environment……………………………..………..

32.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
21.9

17.3
Cost of redundancy dismissal, salary weeks…………..

96
95
118
71

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
70.3
Ease of starting a business*………………………………..……
93.0
Ease of resolving insolvency*……………………………….…. 47.6

64
32 ●
74
31.7
HUMAN CAPITAL & RESEARCH………………...

60

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


64.1
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
7.2
Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. 13.4

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
10.4

[11]
9 ●◆
n/a
77
n/a
35 ● ◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
30.4

Tertiary enrolment, % gross………………………….….……….
43.7
Graduates in science & engineering, %……………….….
20.5
Tertiary inbound mobility, %.......................................
….
6.4

65
67
63
36

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

111
n/a
104
43 ○ ◇78 ○ ◇


Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.7
n/a
0.1
0.0
0.0

◇

◇

◆

◆


INFRASTRUCTURE……………………………….......
38.8

89

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 55.0

ICT access*………………………………………………………….…….
47.1

ICT use*…………………………….....................................…….
39.7

64.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
68.5

85
95
91
83
73

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
34.6
Electricity output, GWh/mn pop………………………..…….
2,181.3
Logistics performance*…………………………………………….. 22.6
Gross capital formation, % GDP………………………….…….
30.7

66
74 ◆
100
19 ●

3.3
3.3.1
3.3.2
3.3.3


26.7
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
5.1
Environmental performance*…….………………………………
54.9
ISO 14001 environmental certificates/bn PPP$ GDP..
0.1

110
108 ◇
83
124 ○ ◇


55.6
MARKET SOPHISTICATION..………….……………

36 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
51.2
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...……
21.8

Microfinance gross loans, % GDP……………………….…….
4.1

30 ●
29 ●
110
7 ●◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 66.7
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

[12]
35
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
49.0

Applied tariff rate, weighted avg., %………………………….
2.9

†Intensity of local competition …………………………………… 56.5
Domestic market scale, bn PPP$……………………………… 24.4

110
63
118
122


BUSINESS SOPHISTICATION..……….……………
26.7

84

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
37.3

Knowledge-intensive employment, %...........................
18.5
Firms offering formal training, % firms………………………… 62.7

GERD performed by business, % GDP…………………..…… 0.0

GERD financed by business, %……………………………........
6.4
🕘🕘Females employed w/advanced degrees, %……………..
10.8

62
78
6 ● ◆
77
78
61

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
13.9 121

University/industry research collaboration †………………..
27.6 112State of cluster development†.……..………..…………………..
29.1 123 ○ ◇
GERD financed by abroad, %.........................................
3.1 70
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
28.9

0.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.1

0.6
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
8.3
Research talent, % in business enterprise……..…………..
n/a

88
91
70
95
17 ●
n/a

 17.3 85
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 10.3 70
Patents by origin/bn PPP$ GDP……………….…………..….…
6.0
18 ● ◆

0.0 99 ○ ◇PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.9 26

Scientific & technical articles/bn PPP$ GDP….…..…..….
3.2 99
Citable documents H-index…………………….……….……..…. 1.4 125 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


28.3 98
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.9 25 ●
New businesses/th pop. 15-64………………….…....………….
1.3 65Computer software spending, % GDP…………..……………
0.1 90
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.3 124 ○ ◇
High- & medium-high-tech manufactures, %………………
0.0 100 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


13.2
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

2.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.0

FDI net outflows, % GDP…………………………….………….......
0.7

83
66
51
82
58


13.3 122
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
23.1 125 ○ ◇Trademarks by origin/bn PPP$ GDP…………..……….….….
22.4 84
Industrial designs by origin/bn PPP$ GDP…………..……..
0.5 85

ICTs & business model creation†………………………....…….
36.5 124 ○ ◇
ICTs & organizational model creation †…………………….... 34.8 120
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

5.5 990.4 590.3 103 ○n/a n/a0.7 81
0.1 99

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.5
0.2
0.8
7.3
0.1

95
116
86
69
85

◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
280

The Global Innovation Index 2019

◇◇

LATVIAGII 2019 rank

34

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

34

36

High

EUR

1.9

57.3

29,901.3

34

Score/Value Rank

INSTITUTIONS………………………………….…….…..

77.2

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
37.4

32

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
72.5

Political and operational stability*……………..………….….
80.7
Government effectiveness*…………………………..………….
68.5

36
35
34

1.2
1.2.1
1.2.2
1.2.3


82.2
Regulatory environment……………………………..………..

72.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
71.0

13.0
Cost of redundancy dismissal, salary weeks…………..

26
28
32
42

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
76.9
Ease of starting a business*………………………………..……
94.1

Ease of resolving insolvency*……………………………….….
59.6

39
21
49


36.9
HUMAN CAPITAL & RESEARCH………………...

44

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


59.0
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.3
Government funding/pupil, secondary, % GDP/cap… 24.8
School life expectancy, years……………….…………….…….
16.2

PISA scales in reading, maths, & science…………......…
486.8
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
8.1

29
31
25
32
30
10 ● ◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
40.4

Tertiary enrolment, % gross………………………….….……….
88.1
Graduates in science & engineering, %……………….….
20.5
Tertiary inbound mobility, %.......................................
….
7.7

38
9 ●
60
30

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
11.4
Researchers, FTE/mn pop……………………………..…..…… 1,785.9
Gross expenditure on R&D, % GDP………….………..……
0.5

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
13.1

53
◇
43
62
43 ○ ◇60


INFRASTRUCTURE……………………………….......
50.5

51

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  71.3

ICT access*………………………………………………………….…….
74.5

ICT use*…………………………….....................................…….
75.4

66.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

56
46
28
75
73

◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
31.1
Electricity output, GWh/mn pop………………………..…….
3,882.0
Logistics performance*…………………………………………….. 34.9
Gross capital formation, % GDP………………………….…….
23.3

82 ○ ◇
52
69
◇
63

3.3
3.3.1
3.3.2
3.3.3


49.1
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.9

Environmental performance*…….………………………………
66.1
ISO 14001 environmental certificates/bn PPP$ GDP.. 6.9

33
54
35
15 ●


54.4
MARKET SOPHISTICATION..………….……………

40

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
56.3
Ease of getting credit*…………………………………..…………..
85.0
Domestic credit to private sector, % GDP…………...……
60.2

Microfinance gross loans, % GDP……………………….…….
n/a

23
11
54
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 46.6
Ease of protecting minority investors*…………..………….
63.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.1

49
48
n/a
27

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
60.4
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†……………………………………
74.3
Domestic market scale, bn PPP$……………………………… 57.3

66
23
33
94 ○ ◇

68.5

◇
◇

◆



41

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

Knowledge workers…………………………………………….….. 44.8
Knowledge-intensive employment, %...........................
42.1
Firms offering formal training, % firms…………………………
25.2
GERD performed by business, % GDP…………………..……
0.1

GERD financed by business, %……………………………........
21.6
Females employed w/advanced degrees, %…………….. 24.8

46
2364 ○
56
65 ○ ◇
13 ● ◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
32.0
University/industry research collaboration †………………..
38.3
State of cluster development†.……..………..…………………..
46.0
GERD financed by abroad, %.........................................
27.8
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.4

44
78 ○ ◇
70
12 ● ◆
65
36

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
35.5

0.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
11.9
ICT services imports, % total trade…………..………………...
1.7

FDI net inflows, % GDP…………………………….………………….
2.6

Research talent, % in business enterprise……..…………..
18.6

54
84 ○ ◇
19
33
68
58 ○ ◇

 27.5 45
KNOWLEDGE & TECHNOLOGY OUTPUTS....

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5



Knowledge creation………………………………………........... 13.0
Patents by origin/bn PPP$ GDP……………….…………..….…
1.9

0.5
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
10.2

Citable documents H-index…………………….……….……..…. 8.4


61
45
34
n/a
47
77

◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5

Knowledge impact……………………………………….............. 41.9
Growth rate of PPP$ GDP/worker, %……………..…....…….
3.4
New businesses/th pop. 15-64………………….…....………….
8.0

Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..……
17.8
High- & medium-high-tech manufactures, %……………… 0.1

42
20
◆
20
86 ○ ◇
19
80 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


27.8
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 7.4

ICT services exports, % total trade……………..……..………
3.8

FDI net outflows, % GDP…………………………….………….......
1.0

35
69 ○
22
21
52


42.8
CREATIVE OUTPUTS…….…………………….…………

22

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
48.0
Trademarks by origin/bn PPP$ GDP…………..……….….….
72.3
Industrial designs by origin/bn PPP$ GDP…………..……..
3.5

44
27
35
46
37

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
46.9
3 ●◆

Cultural & creative services exports, % total trade…....
1.5 13 ●National feature films/mn pop. 15-69………………….………
15.4
7 ● ◆

Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
2.8
8 ●◆

Creative goods exports, % total trade………………………..
3.1 18 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


28.3
Online creativity………………………………………..……….…….

9.5
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 25.6
🕘🕘
99.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
10.9

ICTs & business model creation†………………………....…….
66.1

ICTs & organizational model creation †……………………....
62.7

27
41
24
7 ●◆
41

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

281

LEBANON

GII 2019 rank

88

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank82

92

Upper middle

NAWA

6.1

91.2

14,684.1

90

Score/Value Rank

INSTITUTIONS………………………………….…….…..
51.8 102

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
29.3

75

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
30.6

Knowledge-intensive employment, %...........................
n/a
Firms offering formal training, % firms…………………………
26.6
GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/aFemales employed w/advanced degrees, %……………..
n/a

[82]
n/a
58
n/a
n/a
n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
25.6
University/industry research collaboration †………………..
41.1
State of cluster development†.……..………..…………………..
47.4

GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

63
65
56
n/a
44
61

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.6

0.1
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
3.8

ICT services imports, % total trade…………..………………...
1.8

FDI net inflows, % GDP…………………………….………………….
4.7
Research talent, % in business enterprise……..………….. n/a

75
96
118 ○
31 ● ◆
33
n/a

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
37.3
Political and operational stability*……………..………….….
43.9
Government effectiveness*…………………………..………….
34.1

115 ○ ◇
127 ○ ◇
◇
99

1.2
1.2.1
1.2.2
1.2.3


64.1
Regulatory environment……………………………..………..

33.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
24.6

8.7
Cost of redundancy dismissal, salary weeks…………..

71
93
113 ○ ◇
21 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
54.1
Ease of starting a business*………………………………..……
78.6

Ease of resolving insolvency*……………………………….…. 29.6

120 ○ ◇
110
121 ○ ◇


25.3
HUMAN CAPITAL & RESEARCH………………...

82

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


26.5
Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
2.5
Government funding/pupil, secondary, % GDP/cap…🕘🕘 5.8
School life expectancy, years……………….…………….……. 11.3

PISA scales in reading, maths, & science…………......…
376.4
Pupil-teacher ratio, secondary…………………………......….
7.9

113 ○ ◇
114 ○ ◇
103 ○ ◇
96◇
66 ○
8 ●◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
35.7
Tertiary enrolment, % gross………………………….….……….
38.1
🕘🕘Graduates in science & engineering, %……………….….
23.4

Tertiary inbound mobility, %.......................................
….
8.9

51
73
40
21 ● ◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
13.8
Researchers, FTE/mn pop……………………………..…...……
n/aGross expenditure on R&D, % GDP………….………..……
n/a

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
27.6

[48]
n/a
n/a
43 ○ ◇40


INFRASTRUCTURE……………………………….......

37.1

93

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 53.0

ICT access*………………………………………………………….…….
65.3

ICT use*…………………………….....................................…….
55.0

47.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
44.4

91
68
64
108
107

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
20.8
Electricity output, GWh/mn pop………………………..…….
3,109.8
Logistics performance*…………………………………………….. 30.6
Gross capital formation, % GDP………………………….…….
n/a

119 ○ ◇
62
78
n/a

3.3
3.3.1
3.3.2
3.3.3


37.6
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
10.0

Environmental performance*…….………………………………
61.1
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.4

68
52
60
87

◇

◇
◇


41.8 95
MARKET SOPHISTICATION..………….……………

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
30.9
Ease of getting credit*…………………………………..…………..
40.0
Domestic credit to private sector, % GDP…………...……
105.5

Microfinance gross loans, % GDP……………………….…….
0.1

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 33.3 106Ease of protecting minority investors*…………..………….
41.7 108 ○ ◇
Market capitalization, % GDP………………………………...….
22.6 57

Venture capital deals/bn PPP$ GDP……………….……....
9●◆
0.2

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
61.3
Applied tariff rate, weighted avg., %………………………….
3.8

†Intensity of local competition …………………………………… 79.0
Domestic market scale, bn PPP$……………………………… 91.2

90104 ◇
23 ● ◆50

KNOWLEDGE & TECHNOLOGY OUTPUTS....
13.5 [109]


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 14.3 [58]🕘🕘Patents by origin/bn PPP$ GDP……………….…………..….…
1.3 55
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
10.3 46
Citable documents H-index…………………….……….……..…. 10.6
61

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.2
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

1.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.5

FDI net outflows, % GDP…………………………….………….......
1.8

68
63
68
40
34


26.5
CREATIVE OUTPUTS…….…………………….…………

68

9.2 [116]n/a n/an/a n/a0.1 102
6.1 50n/a n/a

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
30.3 106🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
15.1 96Industrial designs by origin/bn PPP$ GDP…………..……..
n/a n/a
ICTs & business model creation†………………………....…….
43.2 117 ○ ◇
ICTs & organizational model creation †…………………….... 42.4 105
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
34.6
Cultural & creative services exports, % total trade…....
1.7
🕘🕘National feature films/mn pop. 15-69………………….………
3.6
Entertainment & Media market/th pop. 15-69…………….
3.3
🕘🕘Printing & other media, % manufacturing…...................
4.1

Creative goods exports, % total trade……………………….. 0.5

7.3
7.3.1
7.3.2
7.3.3
7.3.4


10.7
51
Online creativity………………………………………..……….…….

6.5 49Generic top-level domains (TLDs)/th pop. 15-69……….

0.3 105
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
7.5 68
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
31.1
16 ● ◆

17 ● ◆
9 ●◆
51
49
4 ●◆
57

62
72
12 ● ◆
82

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
282

The Global Innovation Index 2019◇

LITHUANIA

GII 2019 rank

38

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

40

38

High

EUR

2.9

96.9

34,825.8

40

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
76.0

33

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
75.5

Political and operational stability*……………..………….….
86.0

Government effectiveness*…………………………..…………. 70.3

32
21 ●
32

1.2
1.2.1
1.2.2
1.2.3


82.6
Regulatory environment……………………………..………..

73.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
72.6

13.0
Cost of redundancy dismissal, salary weeks…………..

25
27
31
42

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
70.0Ease of starting a business*………………………………..……
93.2

Ease of resolving insolvency*……………………………….…. 46.9

66
28
77


36.3
HUMAN CAPITAL & RESEARCH………………...

47

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


51.7
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.2
Government funding/pupil, secondary, % GDP/cap… 17.1
School life expectancy, years……………….…………….……. 16.5

PISA scales in reading, maths, & science…………......…
475.4
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
7.7

53
72
70 ○
22 ●
35
7 ● ◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
38.4
🕘🕘Tertiary enrolment, % gross………………………….….……….
71.1
Graduates in science & engineering, %……………….….
23.8
Tertiary inbound mobility, %....................................... ….
4.1

41
27
35
53

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
18.9
Researchers, FTE/mn pop……………………………..…...… 3,013.2
Gross expenditure on R&D, % GDP………….………..……
0.9

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
19.8

46
29
39
43 ○ ◇52


INFRASTRUCTURE……………………………….......
51.7

44

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  75.4

ICT access*………………………………………………………….…….
73.7

ICT use*…………………………….....................................…….
67.8

79.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
80.3

43
54
39
45
51

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
25.8
Electricity output, GWh/mn pop………………………..…….
1,280.8
Logistics performance*…………………………………………….. 44.6
Gross capital formation, % GDP………………………….…….
18.3

97 ○ ◇
90 ○ ◇53◇
101 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


53.7
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
10.5
Environmental performance*…….………………………………
69.3
ISO 14001 environmental certificates/bn PPP$ GDP.. 8.5

14 ●
45
28
10 ● ◆◇◇
BUSINESS SOPHISTICATION..……….……………
38.0

39

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
56.2

Knowledge-intensive employment, %...........................
41.8
Firms offering formal training, % firms………………………… 42.0

GERD performed by business, % GDP…………………..…… 0.3

GERD financed by business, %……………………………........
39.0

Females employed w/advanced degrees, %……………..
27.9

29
24
31
47
47
4 ●◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
29.2

University/industry research collaboration †………………..
51.4
State of cluster development†.……..………..…………………..
41.3
GERD financed by abroad, %.........................................
19.2
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP……………………..
0.3

51
37
90 ○ ◇
19 ●
39
37

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
28.6

0.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.5

ICT services imports, % total trade…………..………………...
0.8

FDI net inflows, % GDP…………………………….…………………. 2.4

Research talent, % in business enterprise……..………….. 29.0

89 ○ ◇
90 ○ ◇
85 ○84 ○
7343

 24.4 55
KNOWLEDGE & TECHNOLOGY OUTPUTS....

Knowledge creation………………………………………........... 16.7
Patents by origin/bn PPP$ GDP……………….…………..….…
1.1

0.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
17.2
Citable documents H-index…………………….……….……..….
11.3

53
59
39
n/a
29
58

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


36.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.5
New businesses/th pop. 15-64………………….…....………….
3.3
Computer software spending, % GDP…………..…………… 0.1

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 14.1
High- & medium-high-tech manufactures, %………………
0.2

61
34
◆
38
97 ○ ◇
25
59

6.3
6.3.1
6.3.2
6.3.3
6.3.4


19.6
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

5.9
High-tech net exports, % total trade……………….….…......
🕘🕘ICT services exports, % total trade……………..……..………
1.0

FDI net outflows, % GDP…………………………….………….......
1.2

50
60
26
81
50


40.3
CREATIVE OUTPUTS…….…………………….…………

30

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
48.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
53.7
Industrial designs by origin/bn PPP$ GDP…………..……..
3.5
†
ICTs & business model creation ………………………....……. 69.8

ICTs & organizational model creation †…………………….... 68.4

42
44
36
31
21 ●


Creative goods & services……………………….…….………..
20.8 56

Cultural & creative services exports, % total trade…....
0.6 43
National feature films/mn pop. 15-69………………….………
5.5 40Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.2 49Creative goods exports, % total trade……………………….. 2.0 29

43.5
Online creativity………………………………………..……….…….

13.1
Generic top-level domains (TLDs)/th pop. 15-69……….

26.3
Country-code TLDs/th pop. 15-69…………………..………….

54.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
98.0

MARKET SOPHISTICATION..………….…………… 50.9

51

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
44.0
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...…… 41.4

Microfinance gross loans, % GDP……………………….…….
n/a

47
40
80
n/a

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 45.3
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.0

55
35
n/a
55 ○

7.3
7.3.1
7.3.2
7.3.3
7.3.4

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
63.4
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 75.1
Domestic market scale, bn PPP$……………………………… 96.9

57
23
26
77





6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

15 ●
34
22 ●
19 ●4 ●◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

283

LUXEMBOURG

GII 2019 rank

18

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

11

23

High

EUR

0.6

66.1

106,704.9

15

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
60.7

INSTITUTIONS………………………………….…….…..
80.7

24

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
90.4

Political and operational stability*……………..………….….
96.5
Government effectiveness*…………………………..…………. 87.3

11
2 ●◆
12

1.2
1.2.1
1.2.2
1.2.3


84.5
Regulatory environment……………………………..………..

87.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
92.3

21.7
Cost of redundancy dismissal, salary weeks…………..

22
13
11
91

◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
67.1
Ease of starting a business*………………………………..……
88.7
Ease of resolving insolvency*……………………………….…. 45.5

74
59
81

◇
◇
◇


41.7
HUMAN CAPITAL & RESEARCH………………...

38

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


48.3
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.9
Government funding/pupil, secondary, % GDP/cap… 19.2

School life expectancy, years……………….…………….……. 14.2

PISA scales in reading, maths, & science…………......…
483.3
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
8.8

66
82
52
68
32
17

◇
◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
41.1
🕘🕘Tertiary enrolment, % gross………………………….….……….
19.6
Graduates in science & engineering, %…………….….…. 17.9
Tertiary inbound mobility, %........................................…. 47.0

34
94 ○ ◇
74 ○
1●◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
35.6
Researchers, FTE/mn pop…………….…....……………..….. 4,682.5
Gross expenditure on R&D, % GDP………….………..……
1.3

58.7
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

31
◇
15
29
◇
23
78 ○ ◇
INFRASTRUCTURE……………………………….......
58.7

25

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)

ICT access*………………………………………………………….…….

ICT use*…………………………….....................................…….

Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

90.7
94.2
82.4
92.4
93.8

5 ●
1 ● ◆
10
22
19

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
32.2
Electricity output, GWh/mn pop………………………..…….
1,480.0
Logistics performance*…………………………………………….. 73.3
Gross capital formation, % GDP………………………….…….
17.4

74
◇
88 ○ ◇
24
106 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


53.3
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
13.9
Environmental performance*…….………………………………
79.1
ISO 14001 environmental certificates/bn PPP$ GDP..
1.9

17
17
7
49



◇
◇
◆

◇

MARKET SOPHISTICATION..………….…………… 46.9

68

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
32.8
Ease of getting credit*…………………………………..…………..
15.0
Domestic credit to private sector, % GDP…………...…… 105.9
Microfinance gross loans, % GDP……………………….…….
n/a

77 ◇
124 ○ ◇
21
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 47.2
Ease of protecting minority investors*…………..………….
48.3
Market capitalization, % GDP………………………………...….
98.5
Venture capital deals/bn PPP$ GDP……………….……....
0.2

45
99 ○ ◇
12
8

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
60.7
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 72.4
Domestic market scale, bn PPP$……………………………… 66.1

65
23
43
92

◇

8

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
66.1

Knowledge-intensive employment, %...........................
55.9
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..……
0.7
🕘🕘
GERD financed by business, %……………………………........
47.1
Females employed w/advanced degrees, %……………..
17.7

16
2 ●◆
n/a
28
◇
32
30

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
56.8
University/industry research collaboration †………………..
68.2
State of cluster development†.……..………..…………………..
67.0
🕘🕘GERD financed by abroad, %.........................................
3.4
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 8.2

6 ●
13
13
69
11
4
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


4 ●
Knowledge absorption……………………………………..……..
59.1

1 ●◆
4.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
1.9 127 ○ ◇
8◆ICT services imports, % total trade…………..………………...
3.1

3 ●◆
FDI net inflows, % GDP…………………………….………………….
35.7
Research talent, % in business enterprise……..………….. 41.9 32

 42.2KNOWLEDGE & TECHNOLOGY OUTPUTS....


18

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 43.5
Patents by origin/bn PPP$ GDP……………….…………..….…
11.5

5.9
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 12.1
Citable documents H-index…………………….……….……..….
9.1

15
9
1 ●◆
n/a
41
◇
74
◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


34.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.9
New businesses/th pop. 15-64………………….…....………….
15.4
Computer software spending, % GDP…………..…………… 0.2

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 3.4
High- & medium-high-tech manufactures, %………………
0.1

74
◇
101 ○ ◇
8
◆
69
◇
72
◇
68
◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


48.0
Knowledge diffusion……………………………………..…..…….

2.0Intellectual property receipts, % total trade……………….

0.6
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.5

FDI net outflows, % GDP…………………………….………….......
63.5

11
11
76
◇
24
1 ●◆


56.2
CREATIVE OUTPUTS…….…………………….…………

2●◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
59.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
102.9
Industrial designs by origin/bn PPP$ GDP…………..……..
4.6

ICTs & business model creation†………………………....…….
80.3

ICTs & organizational model creation †…………………….... 72.2

9
11
28
9
15

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
38.6
9

Cultural & creative services exports, % total trade…....
4.0
1 ●◆
🕘🕘
National feature films/mn pop. 15-69………………….………
42.4
1 ●◆

Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
0.9 73Creative goods exports, % total trade………………………..
0.1 100 ○ ◇

7.3
7.3.1
7.3.2
7.3.3
7.3.4


67.6
Online creativity………………………………………..……….…….

90.8
Generic top-level domains (TLDs)/th pop. 15-69……….

63.3
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
87.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
57.2

1 ● ◆
4 ●◆
9
9
9

◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
284

The Global Innovation Index 2019

MADAGASCAR

GII 2019 rank

121

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

109

122

Low

SSF

26.3

42.8

1,630.2

n/aScore/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
18.4 [125] 
INSTITUTIONS………………………………….…….…..
49.9 109

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
31.9

57.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 19.0

123101
126 ○

1.2
1.2.1
1.2.2
1.2.3


56.7
Regulatory environment……………………………..………..

23.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
23.7

14.7
Cost of redundancy dismissal, salary weeks…………..

94
110
115
58

1.3
1.3.1
1.3.2


61.2
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
88.1

Ease of resolving insolvency*……………………………….…. 34.2

100
65
112


15.3 109
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


23.5
Education…………………………………………………………..……
🕘🕘
2.8
Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 8.4
School life expectancy, years……………….…………….……. 10.4

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
20.0

118
109
101
103
n/a
88

2.2
2.2.1
2.2.2
2.2.3


22.2
Tertiary education……………………………………….……..….
🕘🕘
4.8
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
23.3
Tertiary inbound mobility, %.......................................….
1.7

86
◆
118
41 ●
80

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.1
Researchers, FTE/mn pop……………………………..…...……
30.6
Gross expenditure on R&D, % GDP………….………..……
0.0

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

118
99
114 ○ ◇43 ○ ◇78 ○ ◇◇◇
22.6 126 ○INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 23.3 125 ○
ICT access*………………………………………………………….…….
22.3 125 ○ ◇
ICT use*…………………………….....................................…….
7.6 125 ○ ◇
30.6 119Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
32.6 116

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
21.4
 …………………..…….
Electricity output, GWh/mn pop……
n/a
Logistics performance*…………………………………………….. 15.2
Gross capital formation, % GDP………………………….……. 17.1

113
n/a
113
110

3.3
3.3.1
3.3.2
3.3.3


23.0
Ecological sustainability………………………………………..

n/a
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
33.7
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.2

121n/a
123 ○ ◇109

MARKET SOPHISTICATION..………….…………… 40.3 98
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
23.2 112
Ease of getting credit*…………………………………..…………..
40.0 104Domestic credit to private sector, % GDP…………...……
13.6 122 ○Microfinance gross loans, % GDP……………………….…….
16 ●
1.5

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 51.7 [35]Ease of protecting minority investors*…………..………….
51.7 89Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
46.1 115
Applied tariff rate, weighted avg., %………………………….
5.7 92

Intensity of local competition†…………………………………… n/a n/a
Domestic market scale, bn PPP$……………………………… 42.8 103



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
7.6 [126]
🕘🕘Knowledge-intensive employment, %...........................
3.4 113Firms offering formal training, % firms………………………… 12.7 86

GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %……………..
1.9 101

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


10.1 [128]Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
n/a n/a
State of cluster development†.……..………..…………………..
n/a n/a🕘🕘
GERD financed by abroad, %.........................................
10.6 40 ●
JV-strategic alliance deals/bn PPP$ GDP………………….. n/a n/a
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
37.6

0.4
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.1

2.5
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
4.3
Research talent, % in business enterprise……..…………..
n/a◇

45 ● ◆
72
116
14 ● ◆39 ●n/a

 15.4 96
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


28.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.1
New businesses/th pop. 15-64………………….…....………….
0.1
Computer software spending, % GDP…………..…………… 0.0

ISO 9001 quality certificates/bn PPP$ GDP…………..……
1.9
High- & medium-high-tech manufactures, %………………
n/a

99
60
103 ○
116
87
n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


14.4
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

0.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.3

FDI net outflows, % GDP…………………………….………….......
0.9

79
37 ● ◆112
48 ●
55

3.7 113
0.2 95
0.0 88n/a n/a3.6 95
3.8 105
15.5 113
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
23.8 [124]Trademarks by origin/bn PPP$ GDP…………..……….….….
60.4 35 ● ◆Industrial designs by origin/bn PPP$ GDP…………..……..
4.1
31 ● ◆
†
ICTs & business model creation ………………………....……. n/a n/a
ICTs & organizational model creation†…………………….... n/a n/a

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
14.3 70◆
Cultural & creative services exports, % total trade…....
0.1 82
National feature films/mn pop. 15-69………………….………
0.8 88
Entertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
2.0 20 ● ◆Creative goods exports, % total trade………………………..
0.1 95

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.2 120
Online creativity………………………………………..……….…….

0.1 122
Generic top-level domains (TLDs)/th pop. 15-69……….

0.1 118
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.4 109
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/aNOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

285

MALAWI

GII 2019 rank

118

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

112

119

Low

SSF

19.2

23.7

1,199.4

114

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
51.3 105
BUSINESS SOPHISTICATION..……….……………
29.5 [72]

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
40.7

61.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 30.3

102
91
111

1.2
1.2.1
1.2.2
1.2.3


58.0
Regulatory environment……………………………..………..

21.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
36.6

16.7
Cost of redundancy dismissal, salary weeks…………..

89
114
84
68

1.3
1.3.1
1.3.2


55.2
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
77.2

Ease of resolving insolvency*……………………………….…. 33.3

116
114
113


10.8 122
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


30.1 107
Education…………………………………………………………..……

4.0
78
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 25.2
24 ●
🕘🕘
School life expectancy, years……………….…………….……. 10.4 104
PISA scales in reading, maths, & science…………......…
n/a n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
37.9 112 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
🕘🕘
Tertiary inbound mobility, %.......................................
….

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.1
🕘🕘Researchers, FTE/mn pop……………………………..…...……
48.3
Gross expenditure on R&D, % GDP………….………..……
n/a

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

2.0 125 ○ ◇
0.8 123 ○ ◇n/a n/a
1.1 85116
90n/a
43 ○ ◇78 ○ ◇
23.5 125
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 20.4

ICT access*………………………………………………………….…….
22.6

ICT use*…………………………….....................................…….
13.1

25.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
20.2

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
16.7 122
 …………………..…….
Electricity output, GWh/mn pop……
n/a n/a
Logistics performance*…………………………………………….. 24.4 92
Gross capital formation, % GDP………………………….……. 11.8 123 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


33.2
Ecological sustainability………………………………………..

n/a
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
49.2
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.2

127 ○ ◇123 ○ ◇
120
122
123
◇

83
n/a
101
115

◆



MARKET SOPHISTICATION..………….…………… 38.8 107
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
32.0
Ease of getting credit*…………………………………..…………..
90.0
🕘🕘Domestic credit to private sector, % GDP…………...…… 10.5

Microfinance gross loans, % GDP……………………….……. 0.2

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.8
Ease of protecting minority investors*…………..………….
50.0

Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.0

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
47.4 113🕘🕘Applied tariff rate, weighted avg., %………………………….
4.8 82

Intensity of local competition†…………………………………… 61.1 105Domestic market scale, bn PPP$……………………………… 23.7 123



83
7 ● ◆
124 ○
41
89
93
n/a
31 ●

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
17.8 [112]🕘🕘Knowledge-intensive employment, %...........................
3.8 110Firms offering formal training, % firms………………………… 32.9 45 ●
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
0.6 111

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


33.0
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
28.7
State of cluster development†.……..………..…………………..
35.2

GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. n/a

[43]
110
105
n/a
n/a
n/a

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
37.7

0.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.5

1.5
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
6.2
Research talent, % in business enterprise……..………….. n/a

44 ● ◆87
25 ●
47 ●
24 ●
n/a

 15.0 99
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 8.3 78
🕘🕘
0.1 105
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0 99 ○ ◇
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
9.7
51 ● ◆
Citable documents H-index…………………….……….……..….
7.0 83
◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


22.1 110
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.4 98🕘🕘New businesses/th pop. 15-64………………….…....………….
0.1 102Computer software spending, % GDP…………..…………… 0.0 109

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.8 112
🕘🕘High- & medium-high-tech manufactures, %………………
0.1 83

6.3
6.3.1
6.3.2
6.3.3
6.3.4


14.8
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….

0.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.1

FDI net outflows, % GDP…………………………….………….......
-0.1

77
n/a
81
◆
52 ●
117
15.5 114
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
25.9
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
23.6
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a
†
ICTs & business model creation ………………………....……. 40.0
ICTs & organizational model creation†…………………….... 28.7

119
82
n/a
121
124 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
10.0
Cultural & creative services exports, % total trade…....
0.1
National feature films/mn pop. 15-69………………….………
n/aEntertainment & Media market/th pop. 15-69…………….
n/a🕘🕘
Printing & other media, % manufacturing…...................
1.2
Creative goods exports, % total trade………………………..
0.1

[85]
81
n/a
n/a
46 ●
104

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.1 121
Online creativity………………………………………..……….…….

0.2 118
Generic top-level domains (TLDs)/th pop. 15-69……….

0.3 104
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.0 124 ○
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
286

The Global Innovation Index 2019

MALAYSIAGII 2019 rank

35

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

39

34

Upper middle

SEAO

32.0

999.8

30,859.935

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
71.6

40

◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
72.6

84.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 66.9

35
25
37

◆
◆
◆

1.2
1.2.1
1.2.2
1.2.3


67.3
Regulatory environment……………………………..………..

60.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
57.3

23.9
Cost of redundancy dismissal, salary weeks…………..

64
40
◆
46
◆
100 ○

1.3
1.3.1
1.3.2


75.0
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
82.8

Ease of resolving insolvency*……………………………….…. 67.2

46
94 ○
38
44.2
HUMAN CAPITAL & RESEARCH………………...

33

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


46.1
Education…………………………………………………………..……

4.7
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 23.0
School life expectancy, years……………….…………….……. 13.5
🕘🕘
PISA scales in reading, maths, & science…………......…
412.7
Pupil-teacher ratio, secondary…………………………......….
12.3

70
56
35
76 ○
58 ○
51

2.2
2.2.1
2.2.2
2.2.3


47.8
Tertiary education……………………………………….……..….

41.9
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
32.1
Tertiary inbound mobility, %.......................................
….
8.1

18
◆
68
8 ● ◆
27
◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
38.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
2,357.9
🕘🕘Gross expenditure on R&D, % GDP………….………..……
1.4

44.3
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
50.6

◆
27
36
◆
23
◆
37
◆
17 ● ◆
51.8
INFRASTRUCTURE……………………………….......

42

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  79.4

ICT access*………………………………………………………….…….
75.0

ICT use*…………………………….....................................…….
64.8

88.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
88.8

33
43
47
27
32

◆
◆
◆
◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
38.1
 …………………..…….
Electricity output, GWh/mn pop……
5,022.8
Logistics performance*…………………………………………….. 54.1
Gross capital formation, % GDP………………………….…….
24.3

50
45
40
51

3.3
3.3.1
3.3.2
3.3.3


37.9
Ecological sustainability………………………………………..

8.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
59.2
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.4

66
65
66
42



◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
38.1
🕘🕘
Knowledge-intensive employment, %...........................
27.3
Firms offering formal training, % firms………………………… 18.5
🕘🕘
GERD performed by business, % GDP…………………..…… 0.8

GERD financed by business, %……………………………........
56.9
🕘🕘Females employed w/advanced degrees, %……………..
12.5

58
50
77 ○ ◇
25
◆
◆
16
56

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


30.2
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
72.0
State of cluster development†.……..………..…………………..
71.1

GERD financed by abroad, %.........................................
0.9
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP……………………..
0.2

◆
47
8 ● ◆
8 ● ◆
91 ○
34
◆
50

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
49.5

0.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
26.4

1.4
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.6
🕘🕘
Research talent, % in business enterprise……..………….. 21.9

◆
19
53
3 ● ◆
48
46
53

 32.1 34
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◆

◆

Knowledge creation………………………………………........... 9.9

1.2
Patents by origin/bn PPP$ GDP……………….…………..….…

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.1
Scientific & technical articles/bn PPP$ GDP….…..…..….
8.0

Citable documents H-index…………………….……….……..….
17.0

71
57
58
48 ○
59
43

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


46.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.3
New businesses/th pop. 15-64………………….…....………….
2.3
Computer software spending, % GDP…………..…………… 0.4

ISO 9001 quality certificates/bn PPP$ GDP…………..……
11.1
🕘🕘High- & medium-high-tech manufactures, %………………
0.4

24
21
46
29
27
17

6.3
6.3.1
6.3.2
6.3.3
6.3.4


40.0
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

34.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.3

FDI net outflows, % GDP…………………………….………….......
2.9

◆
20
62
1 ● ◆
72
23
◆


32.8
CREATIVE OUTPUTS…….…………………….…………

44

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
44.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
20.9
Industrial designs by origin/bn PPP$ GDP…………..……..
0.6
†
ICTs & business model creation ………………………....……. 74.4

ICTs & organizational model creation†…………………….... 71.9

51
87 ○
83 ○
21◆
17 ● ◆

◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
37.1
Cultural & creative services exports, % total trade…....
0.3
National feature films/mn pop. 15-69………………….………
3.8
Entertainment & Media market/th pop. 15-69…………….
9.7
🕘🕘
Printing & other media, % manufacturing…...................
0.9
Creative goods exports, % total trade……………………….. 9.8

1 1 ● ◆
67
48
36
◆
72 ○
1 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


5.2
Online creativity………………………………………..……….…….

6.2
Generic top-level domains (TLDs)/th pop. 15-69……….

4.0
Country-code TLDs/th pop. 15-69…………………..………….

9.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
4.2

64
51
56
65
54

◆

◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
44.8
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...……
118.8
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.1

◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 55.9
Ease of protecting minority investors*…………..………….
81.7
Market capitalization, % GDP………………………………...….
131.7

Venture capital deals/bn PPP$ GDP……………….……....
0.0

29
2 ● ◆
6 ● ◆
48

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
72.6
🕘🕘Applied tariff rate, weighted avg., %………………………….
4.0

†Intensity of local competition …………………………………… 76.7
Domestic market scale, bn PPP$……………………………… 999.8

27
74
17 ● ◆
25



36

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

MARKET SOPHISTICATION..………….…………… 57.8 25
45
29
18
52


BUSINESS SOPHISTICATION..……….……………
39.3

◆

◆
◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

287

MALI

GII 2019 rank

112

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

100

120

Low

SSF

19.1

44.3

2,384.0112

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
30.1

INSTITUTIONS………………………………….…….…..
51.4 103

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
31.7

47.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 23.8

124 ○
123 ○
121

1.2
1.2.1
1.2.2
1.2.3


58.8
Regulatory environment……………………………..………..

26.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
25.8

13.7
Cost of redundancy dismissal, salary weeks…………..

85
105
110
52 ●

1.3
1.3.1
1.3.2


63.8
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
84.1

Ease of resolving insolvency*……………………………….…. 43.5

85
85
86


10.7 123 ○HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


27.1
Education…………………………………………………………..……

3.1
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 20.3
🕘🕘
School life expectancy, years……………….…………….……. 7.3

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
17.4

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
🕘🕘
Tertiary inbound mobility, %.......................................
….

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.6
Researchers, FTE/mn pop……………………………..…...……
32.8
Gross expenditure on R&D, % GDP………….………..……
0.3

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

111
101
48 ●
117 ○ ◇n/a77

3.4 122 ○ ◇
5.5
117 ○
n/a n/a0.9 9096
98
80
43 ○ ◇78 ○ ◇
27.5 119INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 25.2 124 ○
ICT access*………………………………………………………….…….
35.7 110
ICT use*…………………………….....................................…….
14.6
117

26.4 121
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
24.2 121
◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
27.8
 …………………..…….
Electricity output, GWh/mn pop……
n/a
Logistics performance*…………………………………………….. 24.6
Gross capital formation, % GDP………………………….……. 19.4

90
n/a
91
98

3.3
3.3.1
3.3.2
3.3.3


29.6
Ecological sustainability………………………………………..

n/a
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
43.7
ISO 14001 environmental certificates/bn PPP$ GDP..  0.2

98
n/a
112
116



MARKET SOPHISTICATION..………….…………… 33.9 123 ○
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
18.3 120
Ease of getting credit*…………………………………..…………..
30.0 115Domestic credit to private sector, % GDP…………...……
27.1 101Microfinance gross loans, % GDP……………………….…….
0.8 22 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.0
Ease of protecting minority investors*…………..………….
40.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
43.3 123 ○
Applied tariff rate, weighted avg., %………………………….
10.0 112
†
Intensity of local competition …………………………………… 58.3 112

Domestic market scale, bn PPP$……………………………… 44.3 98



[72]
114
n/a
n/a

68

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
8.1 125 ○🕘🕘
Knowledge-intensive employment, %...........................
3.7 111Firms offering formal training, % firms…………………………
17.7 80

GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
0.8 91🕘🕘Females employed w/advanced degrees, %……………..
0.3 114 ○

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


41.3
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
39.8
State of cluster development†.……..………..…………………..
46.5

GERD financed by abroad, %.........................................
50.2
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
41.1 39 ● ◆🕘🕘
0.1 107
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.6 81
7 ● ◆
3.1
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.1 80
Research talent, % in business enterprise……..…………..
31.4 40 ● ◆

 20.5KNOWLEDGE & TECHNOLOGY OUTPUTS....


27 ● ◆7066◆
2 ● ◆
77
93 ○ ◇

[71]

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


38.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.8
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..……………
0.0
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.2
High- & medium-high-tech manufactures, %………………
n/a

[53]
29 ●
n/a
113
127 ○
n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


18.8
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

0.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
5.0

FDI net outflows, % GDP…………………………….………….......
0.6

53 ● ◆
95
116
9 ● ◆
64 ●

3.8 [111]
0.2 96n/a n/an/a n/a2.3 108
4.0 102

The Global Innovation Index 2019◇
14.2 119
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
27.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
5.3
Industrial designs by origin/bn PPP$ GDP…………..……..
0.2

ICTs & business model creation†………………………....…….
48.6

ICTs & organizational model creation†……………………....
45.0

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


2.3
Online creativity………………………………………..……….…….

0.1
Generic top-level domains (TLDs)/th pop. 15-69……….

6.7
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

116
115
99
111
95

0.2 [127]
0.0 103
0.1 107 ○ ◇n/a n/an/a n/a0.0 11881◆
121
45 ● ◆121 ○n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
288◆MALTAGII 2019 rank

27

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

20

32

High

EUR

0.4

20.8

45,605.9

26

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
54.9

INSTITUTIONS………………………………….…….…..
75.2

35

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
75.9

86.0
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 70.9

30
21
31

1.2
1.2.1
1.2.2
1.2.3


88.2
Regulatory environment……………………………..………..

76.4
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
76.6

8.0
Cost of redundancy dismissal, salary weeks…………..

17
22
24
1 ● ◆

1.3
1.3.1
1.3.2


61.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
84.9

Ease of resolving insolvency*……………………………….…. 38.1

97 ○ ◇79◇
105 ○ ◇

36.6
HUMAN CAPITAL & RESEARCH………………...

45

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


60.0
Education…………………………………………………………..……

5.3
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 29.9
School life expectancy, years……………….…………….……. 15.9

PISA scales in reading, maths, & science…………......…
463.4
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
7.2

24
35
13
◆
36
40
4 ● ◆

2.2
2.2.1
2.2.2
2.2.3


29.9
Tertiary education……………………………………….……..….
🕘🕘
48.8
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
18.0
Tertiary inbound mobility, %.......................................
….
8.4

69
◇
58
72 ○
23

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
19.8
……………………….…....…… 2,075.0
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
0.5

42.5
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

45
40
56
39
78 ○ ◇
INFRASTRUCTURE……………………………….......

18

3.1
3.1.1
3.1.2
3.1.3
3.1.4

61.1

Information & communication technologies(ICTs) 84.6

ICT access*………………………………………………………….…….
91.3

ICT use*…………………………….....................................…….
78.1

84.0
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
84.8

22
5 ● ◆
19
36
39

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 25.8
 …………………..…….
Electricity output, GWh/mn pop……
1,945.5
Logistics performance*……………………………………………..
35.1

Gross capital formation, % GDP………………………….……. 19.9

98 ○ ◇78 ◇
68 ◇
93 ○

3.3
3.3.1
3.3.2
3.3.3


72.8
Ecological sustainability………………………………………..

25.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
80.9
ISO 14001 environmental certificates/bn PPP$ GDP..  1.8

1 ● ◆
2 ● ◆
4 ● ◆
52


MARKET SOPHISTICATION..………….…………… 45.2 80

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
36.2
Ease of getting credit*…………………………………..…………..
35.0
Domestic credit to private sector, % GDP…………...……
79.6

Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 44.0
Ease of protecting minority investors*…………..………….
61.7

Market capitalization, % GDP………………………………...….
40.8
Venture capital deals/bn PPP$ GDP……………….……....
0.1

59
54
36
13

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
55.5
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 80.4
Domestic market scale, bn PPP$……………………………… 20.8

87
◇
23
7
◆
125 ○ ◇

65
110 ○ ◇
37
n/a

15

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
53.8 31
Knowledge-intensive employment, %...........................
42.5 22Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..…… 0.3 44

GERD financed by business, %……………………………........ 54.5 18

13.3 50
Females employed w/advanced degrees, %……………..

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


55.8
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
48.8
State of cluster development†.……..………..…………………..
53.8
GERD financed by abroad, %.........................................
10.7
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.3
Patent families 2+ offices/bn PPP$ GDP…………………….. 5.3

◆
8
42
41
38
1 ● ◆
11
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
55.1

3.6
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
8.4

1.2
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
25.9
Research talent, % in business enterprise……..………….. 57.0

11
4 ● ◆
51
61
6
◆
16

 31.9 35
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 21.0
🕘🕘
5.2
Patents by origin/bn PPP$ GDP……………….…………..….…

2.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
10.0

Citable documents H-index…………………….……….……..…. 5.4

41
23
16
n/a
48
93 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.4
New businesses/th pop. 15-64………………….…....………….
17.9
Computer software spending, % GDP…………..……………
0.4
ISO 9001 quality certificates/bn PPP$ GDP…………..……
9.9
🕘🕘High- & medium-high-tech manufactures, %……………… 0.1

37
78 ○
4 ● ◆
30
31
76 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


31.5 28
Knowledge diffusion……………………………………..…..…….

2.5
9Intellectual property receipts, % total trade……………….
◆🕘🕘
3.8 37High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.5 100 ○
FDI net outflows, % GDP…………………………….………….......
n/a n/a
55.0
CREATIVE OUTPUTS…….…………………….…………

4 ● ◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
64.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
119.8
🕘🕘
Industrial designs by origin/bn PPP$ GDP…………..……..
12.4

ICTs & business model creation†………………………....…….
76.1

ICTs & organizational model creation†…………………….... 64.4

4 ● ◆
8
◆
10
◆
15
31

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
54.2
Cultural & creative services exports, % total trade…....
5.9
National feature films/mn pop. 15-69………………….………
16.4
Entertainment & Media market/th pop. 15-69…………….
12.1
🕘🕘Printing & other media, % manufacturing…...................
22.4
🕘🕘
Creative goods exports, % total trade……………………….. 0.2

2 ● ◆
1 ● ◆
6◆
32◇
1 ● ◆
81

7.3
7.3.1
7.3.2
7.3.3
7.3.4


37.3
Online creativity………………………………………..……….…….

93.7
Generic top-level domains (TLDs)/th pop. 15-69……….

15.6
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
41.9
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
11.9

20
3 ● ◆
33
33
39

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

289

MAURITIUS

GII 2019 rank

82

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

96

67

Upper middle

SSF

1.3

30.1

23,699.5

75

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
27.9

INSTITUTIONS………………………………….…….…..
63.6

62

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
76.0

91.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 68.3

◆
29
12 ● ◆
35
◆

1.2
1.2.1
1.2.2
1.2.3


33.3
Regulatory environment……………………………..………..

68.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
64.4

73.6
Cost of redundancy dismissal, salary weeks…………..

126 ○ ◇
33
◆
36
◆
127 ○ ◇

1.3
1.3.1
1.3.2


81.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
94.3

Ease of resolving insolvency*……………………………….…. 69.1

◆30
18 ● ◆
32
◆


27.1
HUMAN CAPITAL & RESEARCH………………...

77

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


56.5
Education…………………………………………………………..……

5.0
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 32.0
School life expectancy, years……………….…………….……. 15.0

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
12.7

41
47
10 ● ◆
53
n/a
53

2.2
2.2.1
2.2.2
2.2.3


23.5
Tertiary education……………………………………….……..….

38.8
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
n/aTertiary inbound mobility, %.......................................….
4.5

84
71
n/a
45

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.4 100🕘🕘Researchers, FTE/mn pop……………………………..…...……
79
181.8
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
91
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……
43 ○ ◇
QS university ranking, average score top 3*…………… 0.0
78 ○ ◇
44.2
INFRASTRUCTURE……………………………….......

76

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 66.3
ICT access*………………………………………………………….…….
74.3

ICT use*…………………………….....................................…….
49.0

72.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
69.1

66
49
73
63
70

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
20.8
 …………………..…….
Electricity output, GWh/mn pop……
2,414.3
Logistics performance*…………………………………………….. 31.3
Gross capital formation, % GDP………………………….…….
15.8

118 ○ ◇
72
77
117 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


45.4
Ecological sustainability………………………………………..

15.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 56.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.8

44
10 ● ◆
78
72



MARKET SOPHISTICATION..………….…………… 53.4


◆

43

4.1
4.1.1
4.1.2
4.1.3

Credit……………………………………………………….……………… 56.9
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...……
102.3

Microfinance gross loans, % GDP……………………….……. n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 46.4
Ease of protecting minority investors*…………..………….
75.0

Market capitalization, % GDP………………………………...….
65.7
Venture capital deals/bn PPP$ GDP……………….……....
0.0

50
14 ● ◆
24
36

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
56.8

Applied tariff rate, weighted avg., %………………………….
0.9
Intensity of local competition†…………………………………… 70.5
Domestic market scale, bn PPP$……………………………… 30.1

82
8 ●
54
116 ○ ◇



22 ● ◆
54
25 ● ◆
n/a

79

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
27.9 87Knowledge-intensive employment, %...........................
24.0 60🕘🕘Firms offering formal training, % firms………………………… 25.6 62

GERD performed by business, % GDP…………………..…… n/a n/a🕘🕘
GERD financed by business, %……………………………........
0.3 95 ○ ◇Females employed w/advanced degrees, %……………..
8.4 78

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


24.2
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
35.7
†State of cluster development .……..………..………………….. 51.2
🕘🕘
GERD financed by abroad, %......................................... 6.4

JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
0.2

69
90
45
56
29
45

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.6

0.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.5

ICT services imports, % total trade…………..………………... 1.6

FDI net inflows, % GDP…………………………….………………….
2.3
Research talent, % in business enterprise……..…………..
n/a

74
78
97
36
76
n/a

 11.0 116 ○ ◇
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 4.0 [106]
0.0 123 ○
Patents by origin/bn PPP$ GDP……………….…………..….…
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 4.1 92
Citable documents H-index…………………….……….……..….
2.4 116 ○

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


17.8
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
n/a
New businesses/th pop. 15-64………………….…....………….
9.8

Computer software spending, % GDP…………..…………… 0.2

ISO 9001 quality certificates/bn PPP$ GDP…………..……
7.2
High- & medium-high-tech manufactures, %………………
0.0

113
◇
n/a
14 ● ◆
72
45
98 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


11.2
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….
🕘🕘
0.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.0

FDI net outflows, % GDP…………………………….…………....... 0.3

9778
127 ○
54
78


24.9
CREATIVE OUTPUTS…….…………………….…………

73

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
36.6
🕘🕘Industrial designs by origin/bn PPP$ GDP…………..…….. 0.4

ICTs & business model creation†………………………....……. 57.4

ICTs & organizational model creation†……………………....
53.2

92
69
89
79
65

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
21.3 53

Cultural & creative services exports, % total trade…....
0.1 78
National feature films/mn pop. 15-69………………….………
9.3 20 ● ◆Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.8 22 ●
Creative goods exports, % total trade……………………….. 0.9 47

7.3
7.3.1
7.3.2
7.3.3
7.3.4


6.5
Online creativity………………………………………..……….…….

13.2
Generic top-level domains (TLDs)/th pop. 15-69……….

2.2
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
5.9
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

60
33
66
75
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
290

The Global Innovation Index 2019◆◆

MEXICOGII 2019 rank

56

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

55

59

Upper middle

LCN

130.8

2,575.2

20,601.7

56

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

62.8

66

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
51.1

61.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
45.9

78
91
72

1.2
1.2.1
1.2.2
1.2.3


59.0
Regulatory environment……………………………..………..

47.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
31.4

22.0
Cost of redundancy dismissal, salary weeks…………..

84
61
97
94

1.3
1.3.1
1.3.2


78.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
85.9
Ease of resolving insolvency*……………………………….….
70.8

37
75
30


33.4
HUMAN CAPITAL & RESEARCH………………...

54

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


43.5
Education…………………………………………………………..……

5.2
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 15.6
School life expectancy, years……………….…………….…….
14.3

PISA scales in reading, maths, & science…………......…
415.7
Pupil-teacher ratio, secondary…………………………......…. 16.9

76
38
79
66
55
75

2.2
2.2.1
2.2.2
2.2.3


30.7
Tertiary education……………………………………….……..….

38.2
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
25.5
Tertiary inbound mobility, %.......................................
….
0.3

64
72
27
102 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
25.8
🕘🕘Researchers, FTE/mn pop……………………………..…...……
244.2
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.5

49.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
41.2

42
74
65
29
30


48.3
INFRASTRUCTURE……………………………….......

59

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  72.8

ICT access*………………………………………………………….…….
54.9
ICT use*…………………………….....................................…….
49.6

92.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

51
79
72
22 ● ◆
17 ● ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
31.9
 …………………..…….
Electricity output, GWh/mn pop……
2,586.2
Logistics performance*…………………………………………….. 46.2
Gross capital formation, % GDP………………………….…….
22.5

76
69
50
70

3.3
3.3.1
3.3.2
3.3.3


40.1
Ecological sustainability………………………………………..

11.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
59.7
ISO 14001 environmental certificates/bn PPP$ GDP..  0.7

54
34
64
74

94.4



◆

◆
◆

MARKET SOPHISTICATION..………….…………… 49.9

57

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
37.3
Ease of getting credit*…………………………………..…………..
90.0
Domestic credit to private sector, % GDP…………...……
35.5
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.4

62
7 ● ◆
87
35

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 32.8 110 ○Ease of protecting minority investors*…………..………….
58.3 68Market capitalization, % GDP………………………………...….
34.4 44Venture capital deals/bn PPP$ GDP……………….……....
0.0 69 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
79.5
Applied tariff rate, weighted avg., %………………………….
1.2
Intensity of local competition†……………………………………
70.1
Domestic market scale, bn PPP$……………………..……… 2,575.2



29.4

73

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
35.7

Knowledge-intensive employment, %...........................
19.9
🕘🕘Firms offering formal training, % firms…………………………
50.8
🕘🕘GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
20.7
Females employed w/advanced degrees, %……………..
8.8

68
74
20 ●
55
66
74

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


20.0
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
43.7
State of cluster development†.……..………..…………………..
53.8
GERD financed by abroad, %.........................................
0.6
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

87
56
◆
39
95 ○
81
63

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
32.6 67
0.1 104 ○Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
17.0 10 ● ◆
0.0 125 ○ ◇
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.1 54
🕘🕘Research talent, % in business enterprise……..…………..
24.5 50

 25.5 50
KNOWLEDGE & TECHNOLOGY OUTPUTS....

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5



Knowledge creation………………………………………........... 11.0
0.5
Patents by origin/bn PPP$ GDP……………….…………..….…

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.2
Scientific & technical articles/bn PPP$ GDP….…..…..…. 4.3
Citable documents H-index…………………….……….……..….
27.4


67
76
65
42
88
34

◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5

Knowledge impact……………………………………….............. 36.7
Growth rate of PPP$ GDP/worker, %……………..…....…….
0.3
New businesses/th pop. 15-64………………….…....………….
0.5
Computer software spending, % GDP…………..……………
0.2
ISO 9001 quality certificates/bn PPP$ GDP…………..……
2.9
High- & medium-high-tech manufactures, %……………… 0.5

6.3
6.3.1
6.3.2
6.3.3
6.3.4


28.7 33◆
Knowledge diffusion……………………………………..…..…….

0.0 102 ○ ◇Intellectual property receipts, % total trade……………….

9 ● ◆
High-tech net exports, % total trade……………….….…...... 15.0

ICT services exports, % total trade……………..……..………
0.0 126 ○
FDI net outflows, % GDP…………………………….………….......
0.7
61

65
82
83 ○
66
77
1 1 ● ◆


29.2
CREATIVE OUTPUTS…….…………………….…………

55

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
41.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
44.1
Industrial designs by origin/bn PPP$ GDP…………..……..
0.7

ICTs & business model creation†………………………....…….
67.6

ICTs & organizational model creation†……………………....
57.9

62
59
82
37
53

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
32.1
Cultural & creative services exports, % total trade…....
0.0National feature films/mn pop. 15-69………………….………
2.0
Entertainment & Media market/th pop. 15-69…………….
7.5

Printing & other media, % manufacturing…...................
0.4
Creative goods exports, % total trade………………………..
9.6

22 ● ◆
118 ○66
40
96 ○ ◇
1 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


2.2
Online creativity………………………………………..……….…….

2.5
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 3.3

3.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.7

82
72
58
93
66

◆

8 ● ◆
12 ●59
11 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

291

MONGOLIA

GII 2019 rank

53

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

44

73

Lower middle

SEAO

3.1

43.2

13,446.5

53

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
23.5 108
INSTITUTIONS………………………………….…….…..
59.8

76

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
52.5

77.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 40.2

73
44
86

1.2
1.2.1
1.2.2
1.2.3


68.8
Regulatory environment……………………………..………..

38.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
38.4

8.7
Cost of redundancy dismissal, salary weeks…………..

◆
58
77
80
19 ● ◆

1.3
1.3.1
1.3.2


58.1
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
86.9

Ease of resolving insolvency*……………………………….…. 29.4

108
70
122 ○ ◇

24.6
HUMAN CAPITAL & RESEARCH………………...

84

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


41.9
Education…………………………………………………………..……

4.1
Expenditure on education, % GDP………………….…….….
🕘🕘 15.4
Government funding/pupil, secondary, % GDP/cap…
🕘🕘School life expectancy, years……………….…………….……. 14.6

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
14.5

79
76
81
61
n/a
65

2.2
2.2.1
2.2.2
2.2.3


31.1
Tertiary education……………………………………….……..….

64.8
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
21.6
Tertiary inbound mobility, %.......................................
….
1.0

63
36
53
87

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

3.1
3.1.1
3.1.2
3.1.3
3.1.4

◆

◆

84

Information & communication technologies(ICTs) 55.6

ICT access*………………………………………………………….…….
49.1

ICT use*…………………………….....................................…….
40.0

59.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

84
89
88
91
63

73.6



◆

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 36.8
 …………………..…….
Electricity output, GWh/mn pop……
1,870.3
Logistics performance*……………………………………………..
14.5

Gross capital formation, % GDP………………………….……. 34.8

57
79
114 ○ ◇
12 ● ◆

3.3
3.3.1
3.3.2
3.3.3


30.6
Ecological sustainability………………………………………..

6.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
57.5
ISO 14001 environmental certificates/bn PPP$ GDP..  0.1

90
89
72
122 ○



MARKET SOPHISTICATION..………….…………… 62.2

13 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
68.0
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...……
53.0
Microfinance gross loans, % GDP……………………….…….
18.5

14 ● ◆
20
61
1 ● ◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 68.3
Ease of protecting minority investors*…………..………….
68.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
50.4 106

91
Applied tariff rate, weighted avg., %………………………….
5.5

†Intensity of local competition …………………………………… 61.9 98
Domestic market scale, bn PPP$……………………………… 43.2 101Knowledge workers…………………………………………….…..
42.4

Knowledge-intensive employment, %...........................
23.7
Firms offering formal training, % firms………………………… 60.9

GERD performed by business, % GDP…………………..…… 0.0

GERD financed by business, %……………………………........
4.6
Females employed w/advanced degrees, %……………..
18.5

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


13.8 123 ○Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
26.6 119 ○State of cluster development†.……..………..…………………..
30.2 120 ○ ◇
GERD financed by abroad, %.........................................
2.1 76
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1 65

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
14.4 129 ○ ◇
0.3 75
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.3 114
1.1 66
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
-7.8 128 ○ ◇Research talent, % in business enterprise……..…………..
n/a n/a49◆
61
7 ● ◆
86 ○
82
27
◆

 17.2 86
KNOWLEDGE & TECHNOLOGY OUTPUTS....

0.9 108n/a n/a0.1 990.0
43 ○ ◇
0.0
78 ○ ◇
41.0
INFRASTRUCTURE……………………………….......

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

[9]
30
n/a
n/a



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 34.0 26 ● ◆
3.1
Patents by origin/bn PPP$ GDP……………….…………..….…
31◆
0.0 75
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
6.4
1 ● ◆

Scientific & technical articles/bn PPP$ GDP….…..…..….
4.4 87

Citable documents H-index…………………….……….……..…. 3.7 106

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


10.6
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
n/a🕘🕘
New businesses/th pop. 15-64………………….…....………….
6.3
Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.8
High- & medium-high-tech manufactures, %……………… 0.1

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.2 120 ○
Knowledge diffusion……………………………………..…..…….

0.0 73
Intellectual property receipts, % total trade……………….

0.1 118
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.4 106

FDI net outflows, % GDP…………………………….………….......
0.2 86115◇
n/a
23 ● ◆
81
114
92


43.5
CREATIVE OUTPUTS…….…………………….…………

18 ● ◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
68.5
Trademarks by origin/bn PPP$ GDP…………..……….….….
229.1
Industrial designs by origin/bn PPP$ GDP…………..……..
17.9

ICTs & business model creation†………………………....…….
51.3

ICTs & organizational model creation†……………………....
42.8

2 ● ◆
2 ● ◆
4 ● ◆
101
101

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
33.4 19 ● ◆Cultural & creative services exports, % total trade…....
0.2 73
National feature films/mn pop. 15-69………………….………
26.3
1 ● ◆

Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
2.4 1 1 ● ◆Creative goods exports, % total trade………………………..
0.0 125 ○

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.4
Online creativity………………………………………..……….…….

0.6
Generic top-level domains (TLDs)/th pop. 15-69……….

2.2
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
15.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.1

75
101
65
58
83

◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
292

The Global Innovation Index 2019

◆

MONTENEGRO

GII 2019 rank

45

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

46

55

Upper middle

EUR

0.6

11.8

19,043.3

52

Score/Value Rank

INSTITUTIONS………………………………….…….…..
68.9

46

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
58.7

75.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 50.3

56
46
62

1.2
1.2.1
1.2.2
1.2.3


71.7
Regulatory environment……………………………..………..

50.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
46.7

11.2
Cost of redundancy dismissal, salary weeks…………..

47
56
63
35

1.3
1.3.1
1.3.2


76.3
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
86.7

Ease of resolving insolvency*……………………………….…. 66.0

42
72
40

Score/Value Rank


33.0 [56]
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


49.3
Education…………………………………………………………..……

n/a
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. 15.0

PISA scales in reading, maths, & science…………......…
418.7
Pupil-teacher ratio, secondary…………………………......….
n/a

[62]
n/a
n/a
51
52
n/a

2.2
2.2.1
2.2.2
2.2.3


45.7
Tertiary education……………………………………….……..….

58.2
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
n/aTertiary inbound mobility, %.......................................
….
n/a

[22]
48
n/a
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
3.8
🕘🕘Researchers, FTE/mn pop……………………………..…...……
714.3
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.3

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

83
57
76
43 ○ ◇78 ○ ◇
48.8
INFRASTRUCTURE……………………………….......

56

Information & communication technologies(ICTs) 68.3

ICT access*………………………………………………………….…….
74.4

ICT use*…………………………….....................................…….
58.1

66.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

61
47
59
75
62

3.1
3.1.1
3.1.2
3.1.3
3.1.4

74.2



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
39.9
Knowledge-intensive employment, %...........................
37.6

Firms offering formal training, % firms………………………… 23.7
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1
🕘🕘
GERD financed by business, %……………………………........
29.8
Females employed w/advanced degrees, %……………..
17.5

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


21.1 80
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
41.6 61State of cluster development†.……..………..…………………..
41.8 86
🕘🕘
GERD financed by abroad, %.........................................
5.9 60
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
35.5

0.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.5

2.6
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
11.3
🕘🕘Research talent, % in business enterprise……..…………..
12.2

57
32
◆
67
71 ○
61
34

53
85
98 ○
13 ● ◆
12 ● ◆62

 18.5 79
KNOWLEDGE & TECHNOLOGY OUTPUTS....

◆

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 39.0
 …………………..…….
Electricity output, GWh/mn pop……
5,066.1
Logistics performance*……………………………………………..
31.9

Gross capital formation, % GDP………………………….……. 30.2

47
42
76
22 ●

3.3
3.3.1
3.3.2
3.3.3


39.0
Ecological sustainability………………………………………..

9.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
61.3
ISO 14001 environmental certificates/bn PPP$ GDP..  1.5

63
56
58
56


MARKET SOPHISTICATION..………….…………… 44.4 83

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
36.5
Ease of getting credit*…………………………………..…………..
85.0
🕘🕘Domestic credit to private sector, % GDP…………...……
48.9

Microfinance gross loans, % GDP……………………….…….
0.1

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 52.8
Ease of protecting minority investors*…………..………….
61.7
🕘🕘
Market capitalization, % GDP………………………………...….
82.6
Venture capital deals/bn PPP$ GDP……………….……....
n/a

33
54
19
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
43.9

Applied tariff rate, weighted avg., %………………………….
3.1
†Intensity of local competition …………………………………… 62.9
Domestic market scale, bn PPP$……………………………… 11.8

121 ○ ◇
64
92
128 ○ ◇


BUSINESS SOPHISTICATION..……….……………
32.2 62◆

64
1 1 ● ◆
71
48



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 12.9
🕘🕘
1.0
Patents by origin/bn PPP$ GDP……………….…………..….…

0.7
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
16.8
Citable documents H-index…………………….……….……..…. 0.6

62
62
33
◆
n/a
31
◆
127 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


33.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.0

New businesses/th pop. 15-64………………….…....………….
6.7
Computer software spending, % GDP…………..……………
0.4
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 4.6
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

80
86 ○
22 ●
23 ● ◆59
88 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


9.3 107 ○
Knowledge diffusion……………………………………..…..…….

0.0 77
Intellectual property receipts, % total trade……………….

0.2 96High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.4 43

FDI net outflows, % GDP…………………………….………….......
-1.2 123 ○ ◇
41.4
CREATIVE OUTPUTS…….…………………….…………

26 ● ◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
45.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
n/a🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.8

ICTs & business model creation†………………………....…….
58.6

ICTs & organizational model creation†……………………....
52.6

49
n/a
79
71
70

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
35.8 14 ● ◆🕘🕘Cultural & creative services exports, % total trade…....
1.5 14 ● ◆🕘🕘National feature films/mn pop. 15-69………………….………
13.2 10 ● ◆Entertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
3.0
6 ● ◆

Creative goods exports, % total trade………………………..
0.1 94

7.3
7.3.1
7.3.2
7.3.3
7.3.4


39.3
Online creativity………………………………………..……….…….

1.5
Generic top-level domains (TLDs)/th pop. 15-69……….

100.0Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
24.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

18 ● ◆89
1 ● ◆
44
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

293

MOROCCO

GII 2019 rank

74

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

66

83

Lower middle

NAWA

36.2

315.4

8,932.6

76

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

61.1

72

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
50.7

66.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 42.7

79
74
81

1.2
1.2.1
1.2.2
1.2.3


59.7
Regulatory environment……………………………..………..

35.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
41.7

20.7
Cost of redundancy dismissal, salary weeks…………..

82
86
71
86

1.3
1.3.1
1.3.2


72.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
93.0
Ease of resolving insolvency*……………………………….…. 52.8

◆
55
31 ●
65


27.8
HUMAN CAPITAL & RESEARCH………………...

75

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


54.0
Education…………………………………………………………..……
🕘🕘
5.3
Expenditure on education, % GDP………………….…….….
🕘🕘 36.5
Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….……. 13.5

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
20.3

47 ●
36 ●
5 ● ◆
75
n/a
90 ○

2.2
2.2.1
2.2.2
2.2.3


21.5
Tertiary education……………………………………….……..….

33.8
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
18.4

Tertiary inbound mobility, %.......................................
….
2.0

90
78
71
75

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
7.9
🕘🕘Researchers, FTE/mn pop……………………………..…...……
1,069.0🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.7

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
3.5

65
51
◆
49
◆
43 ○ ◇73


48.0
INFRASTRUCTURE……………………………….......

61

Information & communication technologies(ICTs) 62.5

ICT access*………………………………………………………….…….
63.6

ICT use*…………………………….....................................…….
42.2

66.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

74
70
84
75
56

3.1
3.1.1
3.1.2
3.1.3
3.1.4

77.5



◆

◆

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 37.5
 …………………..…….
Electricity output, GWh/mn pop……
899.5
Logistics performance*……………………………………………..
22.3

Gross capital formation, % GDP………………………….……. 34.4

53
96
101 ○
13 ● ◆

3.3
3.3.1
3.3.2
3.3.3


43.9
Ecological sustainability………………………………………..

13.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
63.5
ISO 14001 environmental certificates/bn PPP$ GDP..  0.6

47 ● ◆
23 ● ◆49 ◆
82

MARKET SOPHISTICATION..………….…………… 42.9 94

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
26.8 101Ease of getting credit*…………………………………..…………..
45.0 94 ○Domestic credit to private sector, % GDP…………...……
51
63.0

Microfinance gross loans, % GDP……………………….…….
0.4 37

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.3
Ease of protecting minority investors*…………..………….
60.0

Market capitalization, % GDP………………………………...….
54.1
Venture capital deals/bn PPP$ GDP……………….……....
0.0

96
61
30
52

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
65.6

Applied tariff rate, weighted avg., %………………………….
3.2
†Intensity of local competition …………………………………… 67.2
Domestic market scale, bn PPP$……………………………… 315.4

49
66
73
52




BUSINESS SOPHISTICATION..……….……………
19.8 122 ○ ◇

◆
5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
20.9 107 ○🕘🕘
Knowledge-intensive employment, %...........................
6.9 105 ○ ◇Firms offering formal training, % firms…………………………
26.3 60🕘🕘
GERD performed by business, % GDP…………………..…… 0.2 51◆🕘🕘
GERD financed by business, %……………………………........
29.9 60

Females employed w/advanced degrees, %…………….. n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


16.9 114 ○Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
31.2 103 ○State of cluster development†.……..………..…………………..
45.9
71
🕘🕘
GERD financed by abroad, %.........................................
1.7 81
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 80
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 80

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
21.5 116 ○
0.3 82
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.5 86
0.5 103 ○ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.6 62
🕘🕘Research talent, % in business enterprise……..…………..
7.0 67

 20.7 69
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 8.4

0.7
Patents by origin/bn PPP$ GDP……………….…………..….…

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
5.8
Citable documents H-index…………………….……….……..…. 10.0

77
74
55
n/a
72
67

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


36.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.3
New businesses/th pop. 15-64………………….…....………….
1.7
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 2.9
🕘🕘High- & medium-high-tech manufactures, %………………
0.3

67
39 ●
59
58
78
38 ●

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.6
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

1.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.4

FDI net outflows, % GDP…………………………….………….......
0.7

64
88 ○
61
25 ●
59


26.0
CREATIVE OUTPUTS…….…………………….…………

69

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
48.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
56.9
Industrial designs by origin/bn PPP$ GDP…………..……..
12.4

ICTs & business model creation†………………………....…….
60.4

ICTs & organizational model creation†…………………….... 51.3

43 ● ◆39 ●9 ● ◆
63
76

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

5.6
0.4
1.5
0.8
0.7
0.1

98
53
72
58 ○
84 ○
101

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.6
1.6
0.8
5.2
0.4

91
86
85
81
71

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
294

The Global Innovation Index 2019

MOZAMBIQUE

GII 2019 rank

119

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

114

118

Low

SSF

30.5

39.3

1,291.4

n/aScore/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
43.7 126
BUSINESS SOPHISTICATION..……….……………
25.1 98

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
35.9

57.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 24.9

119
101
120

1.2
1.2.1
1.2.2
1.2.3


38.0
Regulatory environment……………………………..………..

22.4
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
19.8

37.5
Cost of redundancy dismissal, salary weeks…………..

123
112
119
122

1.3
1.3.1
1.3.2


57.2
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
67.6

Ease of resolving insolvency*……………………………….…. 46.9

110
124
◇
76 ● ◆◇◇
17.4 105
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


48.9
Education…………………………………………………………..……
🕘🕘
6.5
Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 44.0
School life expectancy, years……………….…………….……. 9.7

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
36.5

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

1.5 126 ○ ◇
6.9 114
9.0 101 ○ ◇
0.3 103

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
🕘🕘
Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

1.9
41.5
0.3
0.0
0.0

64 ● ◆
15 ● ◆
2 ● ◆
107
n/a
1 1 1 ○ ◇

94
93
74
43 ○ ◇78 ○ ◇
33.6 107
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 30.8

ICT access*………………………………………………………….…….
20.8

ICT use*…………………………….....................................…….
15.6

42.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
44.4

119
126 ○ ◇
115
113
107

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
50.4
 …………………..…….
Electricity output, GWh/mn pop……
649.7
Logistics performance*…………………………………………….. n/a
Gross capital formation, % GDP………………………….…….
40.0

17 ● ◆103
n/a
6 ● ◆

3.3
3.3.1
3.3.2
3.3.3


19.6 124
Ecological sustainability………………………………………..

2.4 120 ○GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
46.4 107
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.5 86

MARKET SOPHISTICATION..………….…………… 34.8 120
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
11.8 124
Ease of getting credit*…………………………………..…………..
25.0 122Domestic credit to private sector, % GDP…………...……
25.6 106Microfinance gross loans, % GDP……………………….…….
0.0 68

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 41.7 [65]Ease of protecting minority investors*…………..………….
41.7 108
Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
50.9 104
🕘🕘Applied tariff rate, weighted avg., %………………………….
3.6 70 ● ◆Intensity of local competition†…………………………………… 54.9 122Domestic market scale, bn PPP$……………………………… 39.3 105



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
2.5 128 ○ ◇🕘🕘Knowledge-intensive employment, %...........................
3.9 109
Firms offering formal training, % firms………………………… n/a n/a🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 88◇🕘🕘
GERD financed by business, %……………………………........
0.5 93
🕘🕘Females employed w/advanced degrees, %……………..
0.7 110

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


44.4 22 ● ◆
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
37.2 87State of cluster development†.……..………..…………………..
36.5 102🕘🕘
8 ●GERD financed by abroad, %.........................................
39.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 87
Patent families 2+ offices/bn PPP$ GDP…………………….. n/a n/a

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
28.5 90
0.3 77
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
3.7 120

1.5 44 ●ICT services imports, % total trade…………..………………...

7 ● ◆
FDI net inflows, % GDP…………………………….………………….
24.3
🕘🕘Research talent, % in business enterprise……..………….. 0.3 85 ○ 14.7 104
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
🕘🕘
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……
🕘🕘
Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


33.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.4
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..…………… 0.0

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.6
High- & medium-high-tech manufactures, %………………
n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.3 118
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0 97
Intellectual property receipts, % total trade……………….

0.5 79High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.3 1 1 1

FDI net outflows, % GDP…………………………….………….......
0.2 903.9 108
0.4 77◆
0.0 99 ○ ◇
0.2 444.2
91
4.1 101
[82]
79
n/a
117
94
n/a

◆


14.9 116
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
28.8 109🕘🕘
Trademarks by origin/bn PPP$ GDP…………..……….….….
36.8 68 ● ◆🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.8 73
†
ICTs & business model creation ………………………....……. 48.4 113

ICTs & organizational model creation†…………………….... 35.8 119

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.1 124
Online creativity………………………………………..……….…….

0.0 128 ○Generic top-level domains (TLDs)/th pop. 15-69……….

0.1 110
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.2 116
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a1.9 [117]
0.0 104
2.0 65 ● ◆n/a n/an/a n/a0.0 127 ○NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

295

NAMIBIA

GII 2019 rank

101

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

103

99

Upper middle

SSF

2.6

27.5

11,228.8

93

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
24.7 101
INSTITUTIONS………………………………….…….…..
61.2

71

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
59.4

75.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 51.4

54
46 ●
58

1.2
1.2.1
1.2.2
1.2.3


71.1
Regulatory environment……………………………..………..

36.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
52.7

9.7
Cost of redundancy dismissal, salary weeks…………..

48 ●
8452◆
28 ●

1.3
1.3.1
1.3.2


53.0
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
69.1

Ease of resolving insolvency*……………………………….…. 37.0

122 ○ ◇122 ○ ◇107◇


13.9 112 ○ ◇
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


23.5 [119]Education…………………………………………………………..……
🕘🕘
3.1 100
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a n/a
School life expectancy, years……………….…………….……. n/a n/a
PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
n/a n/a

2.2
2.2.1
2.2.2
2.2.3


15.9
Tertiary education……………………………………….……..….
🕘🕘
20.6
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
13.0
Tertiary inbound mobility, %.......................................
….
7.1

99
◇
92
◇
96 ○ ◇
32 ● ◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
2.2
🕘🕘Researchers, FTE/mn pop……………………………..…...……
143.3
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.3

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

91
83
73
43 ○ ◇78 ○ ◇
34.9 104
INFRASTRUCTURE……………………………….......

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 40.5

ICT access*………………………………………………………….…….
45.4

ICT use*…………………………….....................................…….
32.3

45.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
24.5
 …………………..…….
Electricity output, GWh/mn pop……
573.0
Logistics performance*…………………………………………….. n/a
Gross capital formation, % GDP………………………….…….
22.3

101
105 ○ ◇
n/a
73

3.3
3.3.1
3.3.2
3.3.3


39.6
Ecological sustainability………………………………………..

11.9
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
58.5
ISO 14001 environmental certificates/bn PPP$ GDP..  0.4

56
30 ●
69
89

104 ◇
98 ◇
99 ◇
1 1 1 ○ ◇
39.3 1 1 1 ○ ◇
MARKET SOPHISTICATION..………….…………… 40.2 99

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
29.9
Ease of getting credit*…………………………………..…………..
60.0
Domestic credit to private sector, % GDP…………...……
63.8
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.0

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.7
Ease of protecting minority investors*…………..………….
51.7

Market capitalization, % GDP………………………………...….
19.7
Venture capital deals/bn PPP$ GDP……………….……....
n/a

93
89
61
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
54.1
Applied tariff rate, weighted avg., %………………………….
0.9
†Intensity of local competition …………………………………… 62.0Domestic market scale, bn PPP$……………………………… 27.5

92
10 ●
96◇
118 ○ ◇



93
66
50
59

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
22.9 101🕘🕘Knowledge-intensive employment, %...........................
18.7 75Firms offering formal training, % firms…………………………
25.4 63🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 73
🕘🕘
GERD financed by business, %……………………………........
11.1 73🕘🕘Females employed w/advanced degrees, %……………..
7.7 80

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


26.1
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
37.5
State of cluster development†.……..………..…………………..
42.2
🕘🕘GERD financed by abroad, %.........................................
15.8
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
25.1 102
0.1 101
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.4 65
0.9 76
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
5.9 26 ●🕘🕘
Research talent, % in business enterprise……..…………..
6.9 6862
84
84
25 ●
28 ● ◆93 ○ ◇

 6.0 124 ○ ◇
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 5.4 95

0.4
Patents by origin/bn PPP$ GDP……………….…………..….…
81
0.1 63
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
5.9 69
Citable documents H-index…………………….……….……..…. 3.7 106

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
🕘🕘New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……
🕘🕘
High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.1
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

0.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.7

FDI net outflows, % GDP…………………………….………….......
-0.1

121 ○ ◇94
121 ○
88
118 ○


27.5
CREATIVE OUTPUTS…….…………………….…………

64

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
51.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
128.7
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a
ICTs & business model creation†………………………....…….
55.0

ICTs & organizational model creation†…………………….... 46.7

29 ●
5 ● ◆
n/a
86
94

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.9
Online creativity………………………………………..……….…….

8.5
Generic top-level domains (TLDs)/th pop. 15-69……….

0.7
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
3.6
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

5.3 120 ○ ◇n/a n/a0.9 74
0.1 82
1.5 97
0.0 95 ○ ◇

2.8 [111]
0.0 95n/a n/an/a n/an/a n/a0.3 6970
42 ●
87
91
n/a

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
296

The Global Innovation Index 2019

NEPALGII 2019 rank

109

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

119

93

Low

CSA

29.6

86.1

2,904.9

108

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

49.8 110

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
35.5

56.1
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
25.2

120
105
119

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

48.2
22.7
28.5
27.2

114
111
104
105

◇

1.3
1.3.1
1.3.2


65.8
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
84.4

Ease of resolving insolvency*……………………………….….
47.2

79
82
75

◆


12.9 115
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


32.3 104
Education…………………………………………………………..……

5.1 45 ●Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 11.0
91

School life expectancy, years……………….…………….…….
12.2 90◆
PISA scales in reading, maths, & science…………......… n/a n/a
Pupil-teacher ratio, secondary…………………………......…. 28.8 105

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
🕘🕘
Tertiary inbound mobility, %.......................................
….

4.4
11.8
n/a
0.0

121 ○
103
n/a
1 1 1 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

2.1
n/a
0.3
0.0
0.0

92
n/a
77
43 ○ ◇78 ○ ◇
42.2
INFRASTRUCTURE……………………………….......

80

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 53.6

ICT access*………………………………………………………….…….
42.0

ICT use*…………………………….....................................…….
25.5

68.8
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
78.1

89 ◆
101 ◆
100 ◆
72◆
55 ● ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
55.4
 …………………..…….
Electricity output, GWh/mn pop……
146.4

Logistics performance*…………………………………………….. 21.0
Gross capital formation, % GDP………………………….…….
51.8

9 ● ◆
116 ○105
1 ● ◆

3.3
3.3.1
3.3.2
3.3.3


17.6 129 ○ ◇
Ecological sustainability………………………………………..

5.1 107
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
31.4 124 ○ ◇ISO 14001 environmental certificates/bn PPP$ GDP..  0.3 107

◆

MARKET SOPHISTICATION..………….…………… 45.9

72

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
34.3
Ease of getting credit*…………………………………..…………..
50.0
Domestic credit to private sector, % GDP…………...……
79.8

Microfinance gross loans, % GDP……………………….…….
0.9

70
87
36 ● ◆
20 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 58.3 [22]Ease of protecting minority investors*…………..………….
58.3 68Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
45.0
🕘🕘
Applied tariff rate, weighted avg., %………………………….
12.4
Intensity of local competition†……………………………………
63.1
Domestic market scale, bn PPP$……………………………… 86.1

◆



◆

32.8

54 ● ◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
37.6

Knowledge-intensive employment, %...........................
n/a
Firms offering formal training, % firms…………………………
31.9
GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/aFemales employed w/advanced degrees, %……………..
n/a

[60]
n/a
49 ●
n/a
n/a
n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


29.6
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
30.1
State of cluster development†.……..………..…………………..
38.0
GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. n/a

[49]
105
96
n/a
54 ●
n/a

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..

ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….

Research talent, % in business enterprise……..…………..

31.1 [80]n/a n/a11.5 21 ●
0.2 121 ○ ◇
0.5 119n/a n/a 10.4 [118]KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 7.3

0.3
Patents by origin/bn PPP$ GDP……………….…………..….…
n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 5.7
Citable documents H-index…………………….……….……..….
6.3

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……
🕘🕘
High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


20.3 [49]Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 0.1 1 1 1
ICT services exports, % total trade……………..……..………
4.2
17 ● ◆
FDI net outflows, % GDP…………………………….………….......
n/a n/a

[81]
89
n/a
n/a
73
87

3.7 125 ○ ◇n/a n/a
1.0 72
0.0 119 ○
0.9 109
0.1 90
15.5 112
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
28.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
50.6
Industrial designs by origin/bn PPP$ GDP…………..……..
0.2

ICTs & business model creation†………………………....…….
40.4

ICTs & organizational model creation†……………………....
37.9

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


1.7
Online creativity………………………………………..……….…….

0.5
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 0.9
🕘🕘
6.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
1.2

110
47 ● ◆104
120 ○
117 ○

4.0 [106]n/a n/an/a n/an/a n/a0.4 95
0.2 80
89
110
82
73
65

◇
◆
◆
◆
◆

118
124 ○
91
85

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

297

NETHERLANDS (THE)GII 2019 rank

4

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

2

11

High

EUR

17.1

972.5

56,383.2

2

Score/Value Rank

INSTITUTIONS………………………………….…….…..
90.9

8

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
91.4

91.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 91.4

8
12
7

1.2
1.2.1
1.2.2
1.2.3


91.9
Regulatory environment……………………………..………..

96.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
94.8

15.8
Cost of redundancy dismissal, salary weeks…………..

14
4 ●
7
65 ○

1.3
1.3.1
1.3.2


89.3
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
94.3

Ease of resolving insolvency*……………………………….…. 84.3

7
19
7


52.4
HUMAN CAPITAL & RESEARCH………………...

17

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


60.1
Education…………………………………………………………..……

5.4
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 22.9
School life expectancy, years……………….…………….……. 18.0

PISA scales in reading, maths, & science…………......…
507.9
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
14.4

23
29
36
11
12
64 ○

2.2
2.2.1
2.2.2
2.2.3


32.8
Tertiary education……………………………………….……..….
🕘🕘
80.4
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….
14.1
Tertiary inbound mobility, %.......................................
…. 10.7

59 ○
19
91 ○ ◇
18

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
64.4
………………………..…...…… 5,007.1
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
2.0

85.4
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
68.1

12
13
17
9
13


61.8
INFRASTRUCTURE……………………………….......

14

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 91.1

ICT access*………………………………………………………….…….
87.5

ICT use*…………………………….....................................…….
84.8

93.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
98.9

4 ●
8
7
17
4 ●

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
45.7
 …………………..…….
Electricity output, GWh/mn pop……
6,805.9
Logistics performance*…………………………………………….. 91.5
Gross capital formation, % GDP………………………….…….
21.3

31
31
6
85 ○

3.3
3.3.1
3.3.2
3.3.3


48.5
Ecological sustainability………………………………………..

10.9
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
75.5
ISO 14001 environmental certificates/bn PPP$ GDP.. 3.0

36
42
18
33



MARKET SOPHISTICATION..………….…………… 58.2

23

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
49.3
Ease of getting credit*…………………………………..…………..
45.0

Domestic credit to private sector, % GDP…………...……
111.9

Microfinance gross loans, % GDP……………………….……. n/a32
94 ○ ◇
20
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 48.8
Ease of protecting minority investors*…………..………….
58.3
Market capitalization, % GDP………………………………...….
111.0

Venture capital deals/bn PPP$ GDP……………….……....
0.1

42
68 ○
9
15

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
76.5
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 80.5
Domestic market scale, bn PPP$……………………………… 972.5

18
23 ○
5 ●
26



Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
63.7

6

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
64.6 18
Knowledge-intensive employment, %...........................
46.8 12Firms offering formal training, % firms…………………………
n/a n/a
17
GERD performed by business, % GDP…………………..…… 1.2

GERD financed by business, %……………………………........ 52.0 24
Females employed w/advanced degrees, %……………..
19.7 24

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


59.0
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
75.5
State of cluster development†.……..………..…………………..
72.8
GERD financed by abroad, %.........................................
13.9
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 6.0

5 ●
4 ● ◆
5 ● ◆
30
23
8

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
67.6

8.1
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
11.5

2.3
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
27.7
Research talent, % in business enterprise……..………….. 62.7

2 ● ◆
1 ● ◆
22
17
5 ● ◆
7

 61.8KNOWLEDGE & TECHNOLOGY OUTPUTS....

3 ● ◆



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 65.0
10.0
Patents by origin/bn PPP$ GDP……………….…………..….…

4.3
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 20.8
Citable documents H-index…………………….……….……..….
68.8

7
12
10
n/a
21
8

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


45.4
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.6
New businesses/th pop. 15-64………………….…....………….
6.1
Computer software spending, % GDP…………..…………… 0.6

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 10.9
High- & medium-high-tech manufactures, %………………
0.3

27
70 ○
24
8
28
36

6.3
6.3.1
6.3.2
6.3.3
6.3.4


75.0
Knowledge diffusion……………………………………..…..…….

7.0Intellectual property receipts, % total trade……………….

11.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.6

FDI net outflows, % GDP…………………………….………….......
36.3

2 ● ◆
1 ● ◆
15
23
1 ● ◆


53.2
CREATIVE OUTPUTS…….…………………….…………

5 ● ◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
56.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
53.9
Industrial designs by origin/bn PPP$ GDP…………..……..
3.8

ICTs & business model creation†………………………....…….
84.0

ICTs & organizational model creation†…………………….... 80.2

16
43 ○
33
3 ● ◆
4 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
37.1
Cultural & creative services exports, % total trade…....
1.7
National feature films/mn pop. 15-69………………….………
7.6
Entertainment & Media market/th pop. 15-69…………….
50.4
Printing & other media, % manufacturing…...................
1.2
Creative goods exports, % total trade………………………..
4.1

12
10
23
17
51 ○
14

7.3
7.3.1
7.3.2
7.3.3
7.3.4


63.3
Online creativity………………………………………..……….…….

78.9
Generic top-level domains (TLDs)/th pop. 15-69……….

100.0Country-code TLDs/th pop. 15-69…………………..………….

86.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
16.3

2 ● ◆
5 ● ◆
1 ● ◆
10
28

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
298

The Global Innovation Index 2019◆NEW ZEALAND

GII 2019 rank

25

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

32

18

High

SEAO

4.7

199.3

40,135.4

22

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
92.1

5 ●

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
91.7

96.5
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 89.4

7 ●
2 ● ◆
10 ●

1.2
1.2.1
1.2.2
1.2.3


98.8
Regulatory environment……………………………..………..

98.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
97.2

8.0
Cost of redundancy dismissal, salary weeks…………..

1 ●
3 ● ◆
5 ●
1 ●

1.3
1.3.1
1.3.2


85.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
100.0Ease of resolving insolvency*……………………………….…. 71.8

18
1 ● ◆
29


52.6
HUMAN CAPITAL & RESEARCH………………...

16

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


63.0
Education…………………………………………………………..……

6.3
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 20.8
School life expectancy, years……………….…………….……. 18.8

PISA scales in reading, maths, & science…………......…
505.9
Pupil-teacher ratio, secondary…………………………......….
13.6

15
17
47
7 ●
14
61 ○

2.2
2.2.1
2.2.2
2.2.3


51.3
Tertiary education……………………………………….……..….

82.0
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
21.2

Tertiary inbound mobility, %.......................................
…. 19.8

12
15
56 ○
5 ● ◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
43.4
🕘🕘Researchers, FTE/mn pop……………………………..…...……
4,052.4
🕘🕘Gross expenditure on R&D, % GDP………….………..……

1.2

47.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
50.1

23
24
30
32
18


60.9
INFRASTRUCTURE……………………………….......

20

Information & communication technologies(ICTs) 90.5

ICT access*………………………………………………………….…….
86.2

ICT use*…………………………….....................................…….
82.3

95.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

6 ●
1211
9
5 ●

3.1
3.1.1
3.1.2
3.1.3
3.1.4

98.3



◇
◇

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 50.4
 …………………..…….
Electricity output, GWh/mn pop……
8,935.3
Logistics performance*……………………………………………..
84.8

Gross capital formation, % GDP………………………….……. 25.4

18
18
15
43

3.3
3.3.1
3.3.2
3.3.3


41.8
Ecological sustainability………………………………………..

7.9
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
76.0
ISO 14001 environmental certificates/bn PPP$ GDP..  1.5

49
77 ○
17
57



MARKET SOPHISTICATION..………….…………… 68.5

6 ●

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
87.2
Ease of getting credit*…………………………………..…………..
100.0

Domestic credit to private sector, % GDP…………...……
152.9

Microfinance gross loans, % GDP……………………….…….
n/a

3 ● ◆
1 ● ◆
8 ●
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 51.5
Ease of protecting minority investors*…………..………….
81.7
Market capitalization, % GDP………………………………...….
43.4
Venture capital deals/bn PPP$ GDP……………….……....
0.1

36
2 ● ◆
33 ◇
18

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
66.7
Applied tariff rate, weighted avg., %………………………….
1.4
†Intensity of local competition …………………………………… 70.8Domestic market scale, bn PPP$……………………………… 199.3

46
13
52
61




BUSINESS SOPHISTICATION..……….……………
41.4

31

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
43.8 [48]Knowledge-intensive employment, %...........................
n/a n/a
Firms offering formal training, % firms…………………………
n/a n/a🕘🕘
GERD performed by business, % GDP…………………..…… 0.6 33
🕘🕘
GERD financed by business, %……………………………........ 43.8 38
🕘🕘Females employed w/advanced degrees, %……………..
19.5 25

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


40.2
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
62.7
State of cluster development†.……..………..…………………..
55.2
🕘🕘
GERD financed by abroad, %.........................................
7.8
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 2.2

28
21
35
◇
50 ○
15
19

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
40.0

1.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.0

1.4
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
0.7
🕘🕘Research talent, % in business enterprise……..………….. 36.9

◇
41
17
29
49
115 ○
36◇ 29.8 42
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 39.1

5.4
Patents by origin/bn PPP$ GDP……………….…………..….…

1.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 26.4
Citable documents H-index…………………….……….……..….
33.9

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


36.8 63◇
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.6 100 ○ ◇
New businesses/th pop. 15-64………………….…....………….
14.5
9Computer software spending, % GDP…………..……………
0.3 56◇
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 5.5 57
🕘🕘High- & medium-high-tech manufactures, %……………… 0.1 66 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


13.6
Knowledge diffusion……………………………………..…..…….

0.7Intellectual property receipts, % total trade……………….

1.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.1

FDI net outflows, % GDP…………………………….………….......
-0.3

82 ○ ◇
23
69 ○ ◇77 ○121 ○ ◇


42.2
CREATIVE OUTPUTS…….…………………….…………

23

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
53.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
90.5
Industrial designs by origin/bn PPP$ GDP…………..……..
1.8

ICTs & business model creation†………………………....…….
73.5

ICTs & organizational model creation†…………………….... 71.3

27
22
54
23
18

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
24.8
Cultural & creative services exports, % total trade…....
0.5
National feature films/mn pop. 15-69………………….………
6.2
Entertainment & Media market/th pop. 15-69…………….
59.0
🕘🕘
Printing & other media, % manufacturing…...................
1.8
Creative goods exports, % total trade………………………..
0.5

43
52
36
11
23
61

7.3
7.3.1
7.3.2
7.3.3
7.3.4


37.1
Online creativity………………………………………..……….…….

32.5
Generic top-level domains (TLDs)/th pop. 15-69……….

59.7
Country-code TLDs/th pop. 15-69…………………..………….

59.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
15.9

21
20
10 ●
16
31

20
22
24
n/a
11
27

◇

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

299

NICARAGUAGII 2019 rank

120

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

122

108

Lower middle

LCN

6.3

35.8

5,682.7

n/aScore/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
27.9

INSTITUTIONS………………………………….…….…..
52.5 101

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
38.8

54.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 31.1

109
111
107

1.2
1.2.1
1.2.2
1.2.3


58.0
Regulatory environment……………………………..………..

23.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
29.3

14.9
Cost of redundancy dismissal, salary weeks…………..

88
108
100
60 ●

1.3
1.3.1
1.3.2


60.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
79.8

Ease of resolving insolvency*……………………………….…. 41.1

104
109
93


11.7 [118]
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


22.8 [120]Education…………………………………………………………..……

4.3
67
Expenditure on education, % GDP………………….…….….
🕘🕘 7.3 102 ○ ◇Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….……. n/a n/a
PISA scales in reading, maths, & science…………......…
n/a n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
30.8 107 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

n/a [n/a]n/a n/an/a n/an/a n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.7
n/a
0.1
0.0
0.0

112
n/a
106
43 ○ ◇78 ○ ◇
33.6 106INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 36.0

ICT access*………………………………………………………….…….
43.6

ICT use*…………………………….....................................…….
21.3

40.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
38.8

113
99
105
114
112

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
33.1
 …………………..…….
Electricity output, GWh/mn pop……
746.3
Logistics performance*…………………………………………….. n/a
Gross capital formation, % GDP………………………….…….
28.1

70
100
n/a
29 ●

3.3
3.3.1
3.3.2
3.3.3


31.7
Ecological sustainability………………………………………..

7.9
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
55.0
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.4

87
78
82
90

◇
◇
◇



MARKET SOPHISTICATION..………….…………… 39.1 105
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
29.0
Ease of getting credit*…………………………………..…………..
50.0
Domestic credit to private sector, % GDP…………...……
42.6

Microfinance gross loans, % GDP……………………….…….
1.1

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 35.0 [99]Ease of protecting minority investors*…………..………….
35.0 123 ○ ◇Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
53.3 95
Applied tariff rate, weighted avg., %………………………….
2.3 57 ● ◆†Intensity of local competition …………………………………… 60.3 106 ◇Domestic market scale, bn PPP$……………………………… 35.8 109 ◇

97
87
78
18 ●



80

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
41.3 [52]🕘🕘Knowledge-intensive employment, %...........................
13.8 92
Firms offering formal training, % firms…………………………
57.3 1 1 ● ◆
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %……………..
6.1 84

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


15.9 116
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
27.1 115State of cluster development†.……..………..…………………..
33.7 113GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 102
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
26.5

0.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.1

0.3
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
6.9
Research talent, % in business enterprise……..…………..
n/a

96
111
◇
57 ●
117◇
19 ●
n/a

 7.9 122 ○ ◇
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
🕘🕘
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

1.7 125 ○
0.0 124 ○
0.0 84n/a n/a1.1 122 ○
2.9 113

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

4.6 [122]n/a n/an/a n/a0.1 98
1.7 90n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.5
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….

0.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.6

FDI net outflows, % GDP…………………………….………….......
0.5

65 ●
n/a
99
39 ●
67 ●


16.3 [110]CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
30.8 104🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
40.2 65🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.0 116 ○†
ICTs & business model creation ………………………....……. 48.9 110

ICTs & organizational model creation†…………………….... 43.0 100

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
🕘🕘
Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

2.1 [115]
0.0 970.3 100 ○n/a n/an/a n/a
0.3
71

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….

Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.6 [90]
2.8 68 ● ◆
0.5 94n/a n/an/a n/aNOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
300

The Global Innovation Index 2019

NIGERIA

GII 2019 rank

114

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

105

116

Lower middle

SSF

195.9

1,169.1

6,027.2

118

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
26.7

INSTITUTIONS………………………………….…….…..
49.3 114

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
30.7

45.6
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 23.3

126 ○ ◇125 ○ ◇
122
◇

1.2
1.2.1
1.2.2
1.2.3


60.4
Regulatory environment……………………………..………..

18.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
23.5

8.0
Cost of redundancy dismissal, salary weeks…………..

81
121
◇
117
1 ● ◆

1.3
1.3.1
1.3.2


56.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
83.0
Ease of resolving insolvency*……………………………….…. 30.4

113
92
119

◇


11.3 119
HUMAN CAPITAL & RESEARCH………………...

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


26.4 [114]
Education…………………………………………………………..……
n/a n/aExpenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a n/a🕘🕘
School life expectancy, years……………….…………….……. 8.7 113 ○ ◇
PISA scales in reading, maths, & science…………......…
n/a n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
23.2
94

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

7.5 [114]
10.2 107n/a n/an/a n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇◇
26.6 122
INFRASTRUCTURE……………………………….......

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  36.7

ICT access*………………………………………………………….…….
29.9

ICT use*…………………………….....................................…….
15.9

52.8
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
48.3

◇
◇
◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
14.1 126 ○ ◇
 …………………..……. 166.1
115 ◇
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 21.9 102Gross capital formation, % GDP………………………….……. 13.6 120 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


29.1 103
Ecological sustainability………………………………………..

6.6 93GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
54.8 84

ISO 14001 environmental certificates/bn PPP$ GDP..
0.1 125 ○ ◇

111
117
114
103
105



MARKET SOPHISTICATION..………….…………… 43.4 88
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
34.2
Ease of getting credit*…………………………………..…………..
85.0
Domestic credit to private sector, % GDP…………...……
14.2

Microfinance gross loans, % GDP……………………….……. 0.8

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 34.8 101Ease of protecting minority investors*…………..………….
66.7 35 ●
Market capitalization, % GDP………………………………...….
9.1 70
Venture capital deals/bn PPP$ GDP……………….……....
0.0 47

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
61.2
🕘🕘Applied tariff rate, weighted avg., %………………………….
11.3
†Intensity of local competition …………………………………… 68.7
Domestic market scale, bn PPP$……………………………… 1,169.1

72
1 1 ●
119◇
26 ●



85

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
37.2 [64]🕘🕘Knowledge-intensive employment, %...........................
28.4 49 ● ◆Firms offering formal training, % firms…………………………
30.7 50
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........ n/a n/a🕘🕘Females employed w/advanced degrees, %……………..
5.0 90

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.4 100
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
23.7 123 ○ ◇State of cluster development†.……..………..…………………..
41.5 88

GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 89
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 92

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
24.6 105
0.5 64 ●Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.0 117
0.9 81ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
0.9 106Research talent, % in business enterprise……..…………..
n/a n/a 14.0 106
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 5.0
🕘🕘
0.1
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
1.8

Citable documents H-index…………………….……….……..….
10.3

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


26.9 102
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.1
91
◇

New businesses/th pop. 15-64………………….…....………….
0.8 78Computer software spending, % GDP…………..…………… 0.1 83
ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.2 126 ○ ◇High- & medium-high-tech manufactures, %………………
n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


10.1 101
Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

0.0 122 ○High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.6 99
FDI net outflows, % GDP…………………………….………….......
0.3 79

99
119
98
n/a
115
65 ●


18.8 101
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
32.0 102🕘🕘
Trademarks by origin/bn PPP$ GDP…………..……….….….
19.8 89🕘🕘
Industrial designs by origin/bn PPP$ GDP…………..……..
0.8 72†
ICTs & business model creation ………………………....……. 55.1 85
ICTs & organizational model creation†…………………….... 47.5 88

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
10.8
Cultural & creative services exports, % total trade…....
n/a🕘🕘National feature films/mn pop. 15-69………………….………
11.2
Entertainment & Media market/th pop. 15-69…………….
0.6

Printing & other media, % manufacturing…...................
n/a🕘🕘Creative goods exports, % total trade………………………..
0.0

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.3 117
Online creativity………………………………………..……….…….

0.5 107
Generic top-level domains (TLDs)/th pop. 15-69……….

0.3 102
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.3 112
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.1
81

[81]
n/a
12 ● ◆59
n/a
126 ○

63 ●
118 ◇
66 ●
23 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

301

NIGER (THE)GII 2019 rank

127

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

127

125

Low

SSF

22.3

23.5

1,216.8

n/a

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
22.8 [112]
INSTITUTIONS………………………………….…….…..
54.4

93

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
38.3

54.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 30.2

112
111
112

1.2
1.2.1
1.2.2
1.2.3


58.5
Regulatory environment……………………………..………..

23.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
28.5

14.0
Cost of redundancy dismissal, salary weeks…………..

86
109
103
55 ●

1.3
1.3.1
1.3.2


66.6
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
93.7
Ease of resolving insolvency*……………………………….…. 39.4

76
24 ● ◆100


HUMAN CAPITAL & RESEARCH………………...

9.9 126

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


19.2 124
Education…………………………………………………………..……
◇
3.5 93
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 16.077
School life expectancy, years……………….…………….…….
6.5 118 ○ ◇
PISA scales in reading, maths, & science…………......… n/a n/a
Pupil-teacher ratio, secondary…………………………......….
29.7 106

2.2
2.2.1
2.2.2
2.2.3


10.4
Tertiary education……………………………………….……..….

4.0
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
13.2
Tertiary inbound mobility, %.......................................
….
4.3

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

110
120
94
47 ●

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
25.5 124
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  18.7 [128]
ICT access*………………………………………………………….…….
n/a n/a
ICT use*…………………………….....................................…….
n/a n/a
16.0 127 ○ ◇Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
21.4 122
◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
35.6
 …………………..…….
Electricity output, GWh/mn pop……
25.4
Logistics performance*…………………………………………….. 0.3
Gross capital formation, % GDP………………………….……. 38.5

3.3
3.3.1
3.3.2
3.3.3


22.3 122
Ecological sustainability………………………………………..

6.3 96
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
35.7 122 ◇
ISO 14001 environmental certificates/bn PPP$ GDP..  1.0 65 ● ◆

62 ●
121 ○ ◇
121 ◇
9 ● ◆



MARKET SOPHISTICATION..………….…………… 27.3 127
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
12.5 122Ease of getting credit*…………………………………..…………..
30.0 115Domestic credit to private sector, % GDP…………...……
15.7 114
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.1 49

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.0
Ease of protecting minority investors*…………..………….
40.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
29.4 127
Applied tariff rate, weighted avg., %………………………….
11.9 119†Intensity of local competition …………………………………… n/a n/a
Domestic market scale, bn PPP$……………………………… 23.5 124



◇

[72]
114
n/a
n/a

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
21.2 [105]Knowledge-intensive employment, %...........................
n/a n/a
Firms offering formal training, % firms…………………………
27.5 57
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %……………..
0.2 117 ○ ◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..

State of cluster development†.……..………..…………………..

GERD financed by abroad, %.........................................
JV-strategic alliance deals/bn PPP$ GDP…………………..

Patent families 2+ offices/bn PPP$ GDP……………………..

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
47.1
🕘🕘
0.0
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
7.2

3.5
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
5.2
Research talent, % in business enterprise……..…………..
n/a0.0 [129]n/a n/an/a n/an/a n/an/a n/a0.0 93 ○ ◇
24 ● ◆
110
69 ●
5 ● ◆
29 ●
n/a

 16.1 90
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
🕘🕘
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


28.1 100
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.1
61 ●
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.0 106 ○ ◇Computer software spending, % GDP…………..……………
0.0 1 1 1

ISO 9001 quality certificates/bn PPP$ GDP…………..……
1.6 92High- & medium-high-tech manufactures, %……………… n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


16.9 70 ●
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0 106
Intellectual property receipts, % total trade……………….
🕘🕘
0.1 103
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.3
14 ● ◆
FDI net outflows, % GDP…………………………….………….......
0.5 68 ●

3.2
0.3
0.0
n/a
3.3
2.6

116
84
77
n/a
97
114


0.4 [129]
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..

Trademarks by origin/bn PPP$ GDP…………..……….….….
🕘🕘
Industrial designs by origin/bn PPP$ GDP…………..……..

ICTs & business model creation†………………………....…….

ICTs & organizational model creation†……………………....

0.0 [129]
2.8 121 ○ ◇
0.0 114n/a n/an/a n/a

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

1.3 [121]
0.1 87
0.7 91n/a n/an/a n/a0.0 113

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.3
Online creativity………………………………………..……….…….

1.0
Generic top-level domains (TLDs)/th pop. 15-69……….

0.0Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

115
96
◆
127
127 ○ ◇n/a◇NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
302

The Global Innovation Index 2019◆◆

NORTH MACEDONIA

GII 2019 rank

59

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

63

52

Upper middle

EUR

2.1

32.3

15,709.5

84

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
69.7

43

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
56.7

70.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 49.9

64
61
63

1.2
1.2.1
1.2.2
1.2.3


70.1
Regulatory environment……………………………..………..

55.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
40.0

13.0
Cost of redundancy dismissal, salary weeks…………..

52
45
74
42

1.3
1.3.1
1.3.2


82.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
92.1

Ease of resolving insolvency*……………………………….…. 72.7

27 ● ◆
42
28 ● ◆
26.4
HUMAN CAPITAL & RESEARCH………………...

80

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


48.7
Education…………………………………………………………..……

n/a
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… n/a🕘🕘
School life expectancy, years……………….…………….……. 13.3

PISA scales in reading, maths, & science…………......…
368.9
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
9.4

[65]
n/a
n/a
79
68 ○
22 ●

2.2
2.2.1
2.2.2
2.2.3


26.5
Tertiary education……………………………………….……..….
🕘🕘
41.1
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….
20.0
🕘🕘Tertiary inbound mobility, %.......................................….
3.5

77
69
66
58

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
4.0
Researchers, FTE/mn pop……………………………..…...……
729.2
Gross expenditure on R&D, % GDP………….………..……
0.4

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

80
55
72
43 ○ ◇78 ○ ◇
44.9
INFRASTRUCTURE……………………………….......

71

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 66.6
ICT access*………………………………………………………….…….
68.3

ICT use*…………………………….....................................…….
56.3

71.5
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
70.2

65
63
62
69
69

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
19.8 120 ○ ◇
 …………………..…….
Electricity output, GWh/mn pop……
2,706.3 66
Logistics performance*…………………………………………….. 30.0 80
Gross capital formation, % GDP………………………….…….
n/a n/a

3.3
3.3.1
3.3.2
3.3.3


48.2
Ecological sustainability………………………………………..

10.1
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
61.1
ISO 14001 environmental certificates/bn PPP$ GDP.. 7.5

37 ◆
49
61
12 ● ◆

MARKET SOPHISTICATION..………….…………… 57.1 28 ● ◆
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
37.6
Ease of getting credit*…………………………………..…………..
85.0
Domestic credit to private sector, % GDP…………...……
50.0
Microfinance gross loans, % GDP……………………….……. 0.3

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 80.0Ease of protecting minority investors*…………..………….
80.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a[3]
6 ● ◆
n/a
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
53.8

Applied tariff rate, weighted avg., %………………………….
1.9

Intensity of local competition†…………………………………… 62.5
Domestic market scale, bn PPP$……………………………… 32.3

93
52
95
112 ○ ◇


BUSINESS SOPHISTICATION..……….……………
30.5

66

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
42.2
Knowledge-intensive employment, %...........................
29.0

Firms offering formal training, % firms………………………… 46.9

GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
27.4
Females employed w/advanced degrees, %……………..
13.8

50
47
25 ●
62
63
47

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.0 107 ○Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
29.2 108 ○ ◇State of cluster development†.……..………..…………………..
37.0 99

GERD financed by abroad, %.........................................
5.9 59JV-strategic alliance deals/bn PPP$ GDP………………….. n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.2 79
41
0.9Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.4 102 ○
1.4 52
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.8 43Research talent, % in business enterprise……..………….. 21.5 55◆61
1 1 ● ◆68
39

 21.6 66
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 8.8
🕘🕘
1.6
Patents by origin/bn PPP$ GDP……………….…………..….…

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
8.1

Citable documents H-index…………………….……….……..….
4.7

74
51
52
n/a
57
96

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


39.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.0

New businesses/th pop. 15-64………………….…....………….
3.9

Computer software spending, % GDP…………..…………… 0.1

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 14.3
🕘🕘High- & medium-high-tech manufactures, %………………
0.4

52
90 ○
33
80
24 ●
20 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


16.8
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

1.1
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.5

FDI net outflows, % GDP…………………………….………….......
1.4

71
46
67
42
45


28.1
CREATIVE OUTPUTS…….…………………….…………

62

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
39.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
n/aIndustrial designs by origin/bn PPP$ GDP…………..……..
3.2
†
ICTs & business model creation ………………………....……. 48.4

ICTs & organizational model creation†……………………....
41.1

72
n/a
39
112 ○ ◇1 1 1 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
21.0 55

Cultural & creative services exports, % total trade…....
0.8 35
National feature films/mn pop. 15-69………………….………
5.1 43Entertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
2.1 18 ●
Creative goods exports, % total trade………………………..
0.2 85

7.3
7.3.1
7.3.2
7.3.3
7.3.4


12.7
Online creativity………………………………………..……….…….

6.7
Generic top-level domains (TLDs)/th pop. 15-69……….

4.9
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
47.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
7.5

45
47
49
29 ● ◆44

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

303

NORWAY

GII 2019 rank

19

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

27

13

High

EUR

5.4

398.3

74,356.1

19

Score/Value Rank

INSTITUTIONS………………………………….…….…..
93.9

2 ● ◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
94.7

94.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 94.6

3 ● ◆
4 ●3 ● ◆

1.2
1.2.1
1.2.2
1.2.3


97.1
Regulatory environment……………………………..………..

90.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
99.8

8.7
Cost of redundancy dismissal, salary weeks…………..

4 ●
92 ●
21

1.3
1.3.1
1.3.2


89.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
94.3

Ease of resolving insolvency*……………………………….…. 85.4

3 ●
19
5 ●


53.9
HUMAN CAPITAL & RESEARCH………………...

15

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


70.1
Education…………………………………………………………..……

7.6
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 26.4

School life expectancy, years……………….…………….……. 18.1

PISA scales in reading, maths, & science…………......…
504.5
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
8.7

3 ● ◆
4 ● ◆
20
◆
10
15
14
◆

2.2
2.2.1
2.2.2
2.2.3


35.8
Tertiary education……………………………………….……..….

82.0
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….…. 20.5

Tertiary inbound mobility, %.......................................….
3.9

50
16
61 ○
55

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
55.8
Researchers, FTE/mn pop……………………………..…...……
6,407.5
Gross expenditure on R&D, % GDP………….………..……
2.1

57.2
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
42.9

19
7
16
24
26


69.9
INFRASTRUCTURE……………………………….......

1 ● ◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 89.6
ICT access*………………………………………………………….…….
77.6

ICT use*…………………………….....................................…….
88.1

95.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 97.8

935
5 ● ◆
9
11

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
68.5
…………………...…… 28,078.2
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 76.4
Gross capital formation, % GDP………………………….…….
28.2

1 ● ◆
1 ● ◆
21
27

3.3
3.3.1
3.3.2
3.3.3


51.5
Ecological sustainability………………………………………..

11.8
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 77.5

ISO 14001 environmental certificates/bn PPP$ GDP.. 3.5

24
32
14
29



MARKET SOPHISTICATION..………….…………… 58.6 22
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
63.0
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...…… 146.3

Microfinance gross loans, % GDP……………………….……. n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 45.3
Ease of protecting minority investors*…………..………….
75.0

Market capitalization, % GDP………………………………...….
61.5

Venture capital deals/bn PPP$ GDP……………….……....
0.0

54
14
27
40 ○ ◇

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
67.4
Applied tariff rate, weighted avg., %………………………….
3.1
Intensity of local competition†…………………………………… 69.3
Domestic market scale, bn PPP$……………………………… 398.3

44
65 ◇
65 ○ ◇45



18
77 ○
10
n/a

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
50.2

21

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
69.4 10
4 ●
Knowledge-intensive employment, %...........................
52.5
Firms offering formal training, % firms………………………… n/a n/a
GERD performed by business, % GDP…………………..……
1.1 20
GERD financed by business, %……………………………........
◇43.2 40
Females employed w/advanced degrees, %……………..
25.2 10

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


38.3
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
61.7
†State of cluster development .……..………..………………….. 64.6

GERD financed by abroad, %......................................... 9.5

JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP……………………..
1.7

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
42.7 33
0.4 69 ○ ◇Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.6 80 ○
2.8 10
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
-0.9 125 ○
Research talent, % in business enterprise……..………….. 48.1 26

31
22
18
45
22
24

 33.7 30
KNOWLEDGE & TECHNOLOGY OUTPUTS....
The Global Innovation Index 2019

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 38.0

4.4
Patents by origin/bn PPP$ GDP……………….…………..….…

1.9
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 19.3
Citable documents H-index…………………….……….……..….
39.3

22
26
18
n/a
26
20

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


41.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.6
New businesses/th pop. 15-64………………….…....………….
8.2
Computer software spending, % GDP…………..…………… 0.6

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 6.5
High- & medium-high-tech manufactures, %………………
0.2

45
71 ○
18
16
48
58 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


22.1
Knowledge diffusion……………………………………..…..…….

0.4Intellectual property receipts, % total trade……………….

3.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.7

FDI net outflows, % GDP…………………………….………….......
2.8

43
28
45
63
26


43.2
CREATIVE OUTPUTS…….…………………….…………

20

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
48.0
Trademarks by origin/bn PPP$ GDP…………..……….….….
33.9
Industrial designs by origin/bn PPP$ GDP…………..…….. 1.5

ICTs & business model creation†………………………....……. 73.2

ICTs & organizational model creation†……………………....
77.4

45
◇
72 ○
57
24
10

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
28.5
🕘🕘Cultural & creative services exports, % total trade…....
0.6
National feature films/mn pop. 15-69………………….………
10.1
Entertainment & Media market/th pop. 15-69…………….
92.3
Printing & other media, % manufacturing…...................
1.2
Creative goods exports, % total trade………………………..
0.5

33
45
18
3 ● ◆
52
60

7.3
7.3.1
7.3.2
7.3.3
7.3.4


48.4
Online creativity………………………………………..……….…….

50.7
Generic top-level domains (TLDs)/th pop. 15-69……….

56.5
Country-code TLDs/th pop. 15-69…………………..………….

104.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
16.0

13
15
12
5 ● ◆
30

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
304

◇

◇
◇

OMAN

GII 2019 rank

80

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

101

57

High

NAWA

4.8

198.2

46,584.0

69

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
61.5

69

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
61.3

80.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 51.6

49
35
57

◇

1.2
1.2.1
1.2.2
1.2.3


55.5
Regulatory environment……………………………..………..

53.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
57.8

n/a
Cost of redundancy dismissal, salary weeks…………..

97
50
45
n/a

1.3
1.3.1
1.3.2


67.6
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
92.9
Ease of resolving insolvency*……………………………….…. 42.3

◇72
34 ●
88
◇


43.3
HUMAN CAPITAL & RESEARCH………………...

35

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


64.4
Education…………………………………………………………..……

6.7
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 34.9
School life expectancy, years……………….…………….……. 14.7

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
10.0

10 ●
12 ● ◆
9 ● ◆
58
n/a
29 ●

2.2
2.2.1
2.2.2
2.2.3


61.4
Tertiary education……………………………………….……..….
🕘🕘
44.6
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
44.8
Tertiary inbound mobility, %.......................................
….
2.9

4 ● ◆
66◇
1 ● ◆
63

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
4.0
Researchers, FTE/mn pop……………………………..…...……
244.0

Gross expenditure on R&D, % GDP………….………..……
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
8.6

◇
82
75
◇
88
◇
43 ○ ◇
65
◇


51.3
INFRASTRUCTURE……………………………….......

48

Information & communication technologies(ICTs)  75.8

ICT access*………………………………………………………….…….
76.6

ICT use*…………………………….....................................…….
62.2

81.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

42
38
52
43
43

3.1
3.1.1
3.1.2
3.1.3
3.1.4

83.2



◇
◇
◇
◇

◇

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 48.0
 …………………..…….
Electricity output, GWh/mn pop……
7,722.3
Logistics performance*……………………………………………..
53.0

Gross capital formation, % GDP………………………….……. 31.5

24 ●
25 ●
42
16 ● ◆

3.3
3.3.1
3.3.2
3.3.3


30.0
Ecological sustainability………………………………………..

7.0
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
51.3
ISO 14001 environmental certificates/bn PPP$ GDP..  1.2

95
84
94
62

◇

MARKET SOPHISTICATION..………….…………… 45.5

78

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
35.0
Ease of getting credit*…………………………………..…………..
35.0
🕘🕘Domestic credit to private sector, % GDP…………...……
75.0
Microfinance gross loans, % GDP……………………….…….
n/a

67
◇
110 ○ ◇
42
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.6
Ease of protecting minority investors*…………..………….
46.7
Market capitalization, % GDP………………………………...….
41.3
Venture capital deals/bn PPP$ GDP……………….……....
n/a

94
101
35
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
65.0

Applied tariff rate, weighted avg., %………………………….
1.7
†Intensity of local competition …………………………………… 66.2
Domestic market scale, bn PPP$……………………………… 198.2

53
21 ●
76
62





◇

◇


BUSINESS SOPHISTICATION..……….……………
23.8 107

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
28.7 [86]🕘🕘Knowledge-intensive employment, %...........................
18.5 77
Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..…… 0.1 64

GERD financed by business, %……………………………........ 38.5 49
Females employed w/advanced degrees, %……………..
n/a n/a

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


24.9
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
51.0

State of cluster development†.……..………..…………………..
60.5
GERD financed by abroad, %.........................................
0.1
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
18.0 126 ○ ◇n/a n/aIntellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.9 108
0.3 114 ○ ◇
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.4 98Research talent, % in business enterprise……..…………..
0.8 79 ○ ◇

◇
◇

67
38
24 ●
99 ○ ◇
27 ●
86

 12.3 112 ○ ◇
KNOWLEDGE & TECHNOLOGY OUTPUTS....
◇
4.2 104
0.0 120 ○
0.1 70n/a n/a2.9 105◇
6.1 88
◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


20.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-3.8
New businesses/th pop. 15-64………………….…....………….
2.1
Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 3.5
High- & medium-high-tech manufactures, %………………
0.2

6.3
6.3.1
6.3.2
6.3.3
6.3.4


12.6 89◇
Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

0.1 109 ○ ◇High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.3 108

FDI net outflows, % GDP…………………………….………….......
1.5
41

112 ○ ◇110 ○ ◇
48
101
◇
71
61


21.5
CREATIVE OUTPUTS…….…………………….…………

88

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
38.8

Trademarks by origin/bn PPP$ GDP…………..……….….….
59.5
Industrial designs by origin/bn PPP$ GDP…………..……..
0.1

ICTs & business model creation†………………………....…….
59.2

ICTs & organizational model creation†…………………….... 52.5

74
◇
36
109 ○ ◇
70
◇
71
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

6.2 97◇n/a n/a
1.1 79◇
5.4 48◇
0.6 89 ○
0.5 58

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.9 85
1.7 840.2 106
5.7 77n/a n/a

◇

◇
◇
◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

305

PAKISTAN

GII 2019 rank

105

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

89

113

Lower middle

CSA

200.8

1,148.3

5,679.8

109

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
25.5

INSTITUTIONS………………………………….…….…..
53.1 100

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
39.7

Political and operational stability*……………..………….….
54.4
Government effectiveness*…………………………..…………. 32.4

107
111
101

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

113
107
109
105

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
70.9
Ease of starting a business*………………………………..……
81.9

Ease of resolving insolvency*……………………………….…. 59.9

48.7
26.0
27.2
27.2

62
100
48 ● ◆

12.5 116
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


21.6 122 ○ ◇Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
2.8 110 ○
Government funding/pupil, secondary, % GDP/cap… 10.9
92

School life expectancy, years……………….…………….……. 8.5
114 ○ ◇PISA scales in reading, maths, & science…………......… n/a n/a
Pupil-teacher ratio, secondary…………………………......…. 19.4
86

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
8.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
293.6
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.2

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
25.7

7.4
10.1
n/a
n/a

[115]
108
n/a
n/a

◇
◇

62
73
84
43 ○ ◇
41 ● ◆
INFRASTRUCTURE……………………………….......
27.3 120 ○ ◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 38.5 109

ICT access*………………………………………………………….…….
35.1 1 1 1◇
ICT use*…………………………….....................................…….
13.9 118 ○ ◇
54.9 100Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
50.0 104

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
16.2 123 ○ ◇
Electricity output, GWh/mn pop………………………..…….
590.1 104

Logistics performance*…………………………………………….. 16.6 110◇Gross capital formation, % GDP………………………….…….
16.4 113
◇

3.3
3.3.1
3.3.2
3.3.3


27.4 108
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.6 60
Environmental performance*…….………………………………
37.5 121 ○ ◇ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3
97
39.6 102
MARKET SOPHISTICATION..………….……………

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
20.1
Ease of getting credit*…………………………………..…………..
45.0

Domestic credit to private sector, % GDP…………...……
17.0
Microfinance gross loans, % GDP……………………….…….
0.6

118 ◇
94
112 ◇
28 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 38.8
Ease of protecting minority investors*…………..………….
71.7
🕘🕘Market capitalization, % GDP………………………………...….
29.2
Venture capital deals/bn PPP$ GDP……………….……....
0.0

83
24 ● ◆
50
72 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
60.0
🕘🕘
Applied tariff rate, weighted avg., %………………………….
10.1
†Intensity of local competition …………………………………… 57.7
Domestic market scale, bn PPP$……………………………… 1,148.3

68
113 ◇
115 ◇
24 ● ◆

96

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
23.6 [100]Knowledge-intensive employment, %...........................
11.6 96Firms offering formal training, % firms…………………………
32.0 47
GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a
Females employed w/advanced degrees, %……………..
1.6 104

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
20.4
University/industry research collaboration †………………..
44.5
State of cluster development†.……..………..…………………..
49.2
🕘🕘
GERD financed by abroad, %.........................................
2.7
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

83
52
52
72
59
90

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
32.5

0.5
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
10.6

0.9
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
0.8
Research talent, % in business enterprise……..………….. n/a

68
63
24 ●
73
110
n/a

 20.6 70
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 13.3 [59]Patents by origin/bn PPP$ GDP……………….…………..….…
0.2 101
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 8.5 56
Citable documents H-index…………………….……….……..….
14.4 50 ●

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


36.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.9
New businesses/th pop. 15-64………………….…....………….
0.1
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.7
High- & medium-high-tech manufactures, %………………
n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


12.3 91
Knowledge diffusion……………………………………..…..…….

0.0 75
Intellectual property receipts, % total trade……………….

0.8 73High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.2 49 ●
FDI net outflows, % GDP…………………………….………….......
0.0 10968
27 ●
104 ○
52 ●
91n/a
17.6 104
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
33.5
Trademarks by origin/bn PPP$ GDP…………..……….….….
28.9
Industrial designs by origin/bn PPP$ GDP…………..……..
0.4

ICTs & business model creation†………………………....…….
53.8

ICTs & organizational model creation †…………………….... 51.6

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

2.0 116
0.1 770.1 106 ○
0.4 62 ○ ◇0.3 100 ○
0.3 72

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….

Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.5 960.6 105
0.2 109
1.6 101
4.2 55

98
77
91
89
75

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
306

The Global Innovation Index 2019

PANAMA

GII 2019 rank

75

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

72

79

High

LCN

4.2

111.4

25,674.570

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
62.9

65

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
55.7

Political and operational stability*……………..………….….
73.7
Government effectiveness*…………………………..…………. 46.7

65
50
70

◇
◇
◇

1.2
1.2.1
1.2.2
1.2.3


67.2
Regulatory environment……………………………..………..

52.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
47.4

18.1
Cost of redundancy dismissal, salary weeks…………..

65
54
62
75

◇
◇
◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
65.8
Ease of starting a business*………………………………..……
92.1

Ease of resolving insolvency*……………………………….…. 39.6

78
43
99

◇


20.2
HUMAN CAPITAL & RESEARCH………………...

95

◇

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


31.7 106
Education…………………………………………………………..……
◇🕘🕘
Expenditure on education, % GDP………………….…….….
3.2
98
◇
Government funding/pupil, secondary, % GDP/cap…🕘🕘 9.2
99 ○ ◇
🕘🕘
School life expectancy, years……………….…………….……. 12.7
84 ◇

PISA scales in reading, maths, & science…………......…
n/a n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......…. 14.5
66
◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
27.6
🕘🕘Tertiary enrolment, % gross………………………….….……….
47.3
🕘🕘Graduates in science & engineering, %……………….….
17.2
Tertiary inbound mobility, %.......................................
….
n/a

73
63
77
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
🕘🕘
Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

1.2
39.1
0.1
0.0
3.4

104
◇
95
◇
111 ○ ◇
43 ○ ◇74 ◇


INFRASTRUCTURE……………………………….......
57.2

30 ●

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  61.7

ICT access*………………………………………………………….…….
63.5

ICT use*…………………………….....................................…….
45.6

66.0
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

76
71
76
79
64

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
57.6
Electricity output, GWh/mn pop………………………..…….
2,701.2
Logistics performance*…………………………………………….. 56.7
Gross capital formation, % GDP………………………….…….

43.5

5 ●◆
68 ◇
37 ●
5 ●◆

3.3
3.3.1
3.3.2
3.3.3


52.3
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
18.9
Environmental performance*…….………………………………
62.7
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

20 ●
7●◆
50
104 ◇


45.9
MARKET SOPHISTICATION..………….……………

73

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
42.3
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...……
87.1

Microfinance gross loans, % GDP……………………….…….
0.3

49
20 ● ◆
31 ●
38

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 37.3
Ease of protecting minority investors*…………..………….
51.7

Market capitalization, % GDP………………………………...….
24.0

Venture capital deals/bn PPP$ GDP……………….……....
n/a

88
89
54
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
58.0
🕘🕘
Applied tariff rate, weighted avg., %………………………….
5.4
†Intensity of local competition …………………………………… 70.7
Domestic market scale, bn PPP$……………………………… 111.4

75
90
53
74

71.9

◇
◇

◇
◇
◇
◇
◇

◇


BUSINESS SOPHISTICATION..……….……………
19.1 123 ○ ◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
◇
21.7 104Knowledge-intensive employment, %...........................
24.7 57◇🕘🕘
Firms offering formal training, % firms…………………………
11.0 87 ○ ◇🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 90 ○ ◇🕘🕘
GERD financed by business, %……………………………........
10.8 74◇Females employed w/advanced degrees, %……………..
10.5 62
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


◇
Innovation linkages…………..……………………………………..
18.3 103◇
University/industry research collaboration †………………..
35.5 91State of cluster development†.……..………..…………………..
46.6 65🕘🕘
GERD financed by abroad, %.........................................
0.3 97 ○ ◇
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 47
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1 66

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
17.4 128 ○ ◇◇
0.2 89Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
2.9 123 ○ ◇
◇
ICT services imports, % total trade…………..………………...
0.3 113
14 ●
FDI net inflows, % GDP…………………………….………………….
8.9
🕘🕘
◇
Research talent, % in business enterprise……..…………..
0.9 78

 10.6 117
KNOWLEDGE & TECHNOLOGY OUTPUTS....

◇



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

◇
Knowledge creation………………………………………........... 8.5 76
Patents by origin/bn PPP$ GDP……………….…………..….…
0.3 85
1.7
21 ●
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.0 64 ○ ◇
Scientific & technical articles/bn PPP$ GDP….…..…..…. 3.1 100◇
Citable documents H-index…………………….……….……..….
10.9 59

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

7.0
n/a
0.8
0.2
1.9
0.0

118
n/a
75
70
88
93

6.3
6.3.1
6.3.2
6.3.3
6.3.4


16.3
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….
🕘🕘
3.6
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.1

FDI net outflows, % GDP…………………………….………….......
1.3

72
81
40
79
46


33.3
CREATIVE OUTPUTS…….…………………….…………

43

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
40.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
41.4
Industrial designs by origin/bn PPP$ GDP…………..……..
0.0

ICTs & business model creation†………………………....…….
67.5

ICTs & organizational model creation †…………………….... 57.4

67
◇
63
118 ○ ◇
38
55

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
32.2 21 ●
Cultural & creative services exports, % total trade…....
0.5 48🕘🕘
National feature films/mn pop. 15-69………………….………
0.4 98 ○ ◇
Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
3.0
7 ●◆
🕘🕘
Creative goods exports, % total trade……………………….. 2.5 23 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


20.2
Online creativity………………………………………..……….…….

66.4
Generic top-level domains (TLDs)/th pop. 15-69……….

1.1
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
14.6
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
3.5

◇

◇
◇

33 ●
9 ● ◆
80
◇
59
◇
56

◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

307

PARAGUAY

GII 2019 rank

95

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

94

95

Upper middle

LCN

6.9

95.0

13,395.3

89

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
49.4 113

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
39.0
Political and operational stability*……………..………….….
63.2
Government effectiveness*…………………………..…………. 26.8

108
86
117

◇

1.2
1.2.1
1.2.2
1.2.3


49.9
Regulatory environment……………………………..………..

35.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
29.2

29.4
Cost of redundancy dismissal, salary weeks…………..

111
87
101
114

◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
59.4
Ease of starting a business*………………………………..……
77.5

Ease of resolving insolvency*……………………………….…. 41.3

107
113
91


22.0
HUMAN CAPITAL & RESEARCH………………...

89

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


37.7
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.5
Government funding/pupil, secondary, % GDP/cap… 15.5
🕘🕘School life expectancy, years……………….…………….……. 12.3

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
18.4

89
61 ●
80
88 ◇
n/a
80

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
27.3
🕘🕘Tertiary enrolment, % gross………………………….….……….
35.1
Graduates in science & engineering, %……………….….
n/aTertiary inbound mobility, %....................................... ….
n/a

[75]
76
n/a
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.1 105🕘🕘Researchers, FTE/mn pop……………………………..…...……
122.1
84
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.2
95

0.0
Global R&D companies, avg. exp. top 3, mn US$……
43 ○ ◇
QS university ranking, average score top 3*……………
0.0
78 ○ ◇◇
INFRASTRUCTURE……………………………….......
38.4

90

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 49.2
ICT access*………………………………………………………….…….
43.5

ICT use*…………………………….....................................…….
40.3

55.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
57.3

97
100
87
98
95

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
31.6
Electricity output, GWh/mn pop………………………..…….
9,475.6
Logistics performance*…………………………………………….. 33.6
Gross capital formation, % GDP………………………….…….
19.4

80
16 ● ◆
73
97

3.3
3.3.1
3.3.2
3.3.3


34.4
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.9

Environmental performance*…….………………………………
53.9
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

81
54 ●
86
100



◇
◇
◇

MARKET SOPHISTICATION..………….…………… 43.2

91

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
31.3
Ease of getting credit*…………………………………..…………..
40.0
Domestic credit to private sector, % GDP…………...…… 40.0Microfinance gross loans, % GDP……………………….…….
2.1

85
104 ◇
82
12 ● ◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 41.7 [65]Ease of protecting minority investors*…………..………….
41.7 108
Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
56.7
Applied tariff rate, weighted avg., %………………………….
4.8

Intensity of local competition†…………………………………… 65.6
Domestic market scale, bn PPP$……………………………… 95.0

◇
BUSINESS SOPHISTICATION..……….……………
26.6

87

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
29.0Knowledge-intensive employment, %...........................
17.7
Firms offering formal training, % firms………………………… 46.4
🕘🕘
GERD performed by business, % GDP…………………..…… 0.0

GERD financed by business, %……………………………........
0.4
Females employed w/advanced degrees, %……………..
9.6

84
83
26 ●
92 ○
94 ○ ◇
68

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
18.5
University/industry research collaboration †………………..
26.4
State of cluster development†.……..………..…………………..
34.3

GERD financed by abroad, %.........................................
13.0
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

98
121 ○ ◇
◇
111
33 ●
91
93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
32.3 69
0.2 93
Intellectual property payments, % total trade………….....

11 ● ◆High-tech imports, % total trade………………..………………..
16.7
ICT services imports, % total trade…………..………………...
0.0 128 ○ ◇
◇
FDI net inflows, % GDP…………………………….………………….
1.3 100Research talent, % in business enterprise……..…………..
n/a n/a 6.4 123
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 2.2 [120]🕘🕘Patents by origin/bn PPP$ GDP……………….…………..….…
0.3 86
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 0.6 124 ○ ◇Citable documents H-index…………………….……….……..….
3.1 112

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……
🕘🕘
High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


9.4 105
Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

0.5 80High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.1 124 ○
FDI net outflows, % GDP…………………………….………….......
0.3 84

7.5
n/a
0.1
0.0
3.6
0.1

117
n/a
97
104
68
67

The Global Innovation Index 2019

◇

◇


30.1
CREATIVE OUTPUTS…….…………………….…………

52 ●

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
55.0
🕘🕘
Trademarks by origin/bn PPP$ GDP…………..……….….….
220.4
🕘🕘
Industrial designs by origin/bn PPP$ GDP…………..……..
2.0

ICTs & business model creation†………………………....…….
52.8

ICTs & organizational model creation †…………………….... 41.8

21 ● ◆
3 ●◆
50 ●
94
109
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

9.1 890.0 116 ○
1.3 75n/a n/a
1.3 37 ●
0.0 114

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.5
1.7
1.3
4.2
0.0

97
85
74
86
91

83
83
78
80

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
308

◇

PERU

GII 2019 rank

69

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

86

48

Upper middle

LCN

32.6

458.4

14,224.3

71

Score/Value Rank

INSTITUTIONS………………………………….…….…..
61.2

70

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
50.6

Political and operational stability*……………..………….….
64.9
Government effectiveness*…………………………..………….
43.4

80
79
79

1.2
1.2.1
1.2.2
1.2.3


69.0
Regulatory environment……………………………..………..

53.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
33.1

11.4
Cost of redundancy dismissal, salary weeks…………..

57
52
94
36 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
64.1
Ease of starting a business*………………………………..……
82.4

Ease of resolving insolvency*……………………………….…. 45.7

84
96
79


30.4
HUMAN CAPITAL & RESEARCH………………...

66

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


39.7
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.9
Government funding/pupil, secondary, % GDP/cap… 15.3
School life expectancy, years……………….…………….……. 14.6

PISA scales in reading, maths, & science…………......…
393.6
Pupil-teacher ratio, secondary…………………………......….
14.2

86
81
82
60
65 ○
63

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
45.8
🕘🕘Tertiary enrolment, % gross………………………….….……….
69.6
Graduates in science & engineering, %……………….….
23.8
Tertiary inbound mobility, %.......................................
….
n/a

21 ● ◆
28 ● ◆
36
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

73
n/a
101 ○
43 ○ ◇
56

5.7
n/a
0.1
0.0
14.8


INFRASTRUCTURE……………………………….......
46.7

65

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 65.2

ICT access*………………………………………………………….…….
50.8

ICT use*…………………………….....................................…….
41.6

81.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

70
87 ◇
86
41
36 ●

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
26.7
Electricity output, GWh/mn pop………………………..…….
1,634.3
Logistics performance*…………………………………………….. 29.5
Gross capital formation, % GDP………………………….…….

92
86
81
72

3.3
3.3.1
3.3.2
3.3.3


48.1
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
15.6
Environmental performance*…….………………………………
61.9
ISO 14001 environmental certificates/bn PPP$ GDP..
1.2

39 ● ◆
10 ● ◆
57
63


57.6
MARKET SOPHISTICATION..………….……………

26 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
64.5
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...……
42.3

Microfinance gross loans, % GDP……………………….…….
5.8

17 ● ◆
29 ●79
1 ● ◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.2
Ease of protecting minority investors*…………..………….
63.3
Market capitalization, % GDP………………………………...….
39.7
Venture capital deals/bn PPP$ GDP……………….……....
0.0

97
48
37
54

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
72.1
Applied tariff rate, weighted avg., %………………………….
0.8

†Intensity of local competition …………………………………… 72.5
Domestic market scale, bn PPP$……………………………… 458.4

30 ●
6 ●
42
44

86.5

22.3

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
36.6

43

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
56.8 [27]Knowledge-intensive employment, %...........................
24.4 59
🕘🕘
Firms offering formal training, % firms…………………………
60.1
8 ● ◆

GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........ n/a n/aFemales employed w/advanced degrees, %……………..
16.3 38 ●

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
18.8 94

University/industry research collaboration †………………..
31.9 100 ○State of cluster development†.……..………..…………………..
39.5 94
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 104 ○ ◇Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 72

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
34.2

0.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.4

ICT services imports, % total trade…………..………………...
1.2

FDI net inflows, % GDP…………………………….………………….
3.7
Research talent, % in business enterprise……..………….. n/a

62
57
52
59
45
n/a

 15.3KNOWLEDGE & TECHNOLOGY OUTPUTS....

97



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 7.1

Patents by origin/bn PPP$ GDP……………….…………..….…
0.2

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.6
Scientific & technical articles/bn PPP$ GDP….…..…..…. 1.6
Citable documents H-index…………………….……….……..….
12.6

82
93
68
33
117 ○
56

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


31.6
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.3
New businesses/th pop. 15-64………………….…....………….
3.6

Computer software spending, % GDP…………..……………
0.2
ISO 9001 quality certificates/bn PPP$ GDP…………..……
3.2
High- & medium-high-tech manufactures, %……………… 0.1

88
55
35
67
75
75

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.3
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

0.4
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.3

FDI net outflows, % GDP…………………………….………….......
0.1

119 ○ ◇
74
83
112 ○
98 ○


23.4
CREATIVE OUTPUTS…….…………………….…………

79

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
50.0
Industrial designs by origin/bn PPP$ GDP…………..……..
0.2

ICTs & business model creation†………………………....…….
59.3

ICTs & organizational model creation †…………………….... 48.6

87
48
100 ○
69
85

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
17.5
Cultural & creative services exports, % total trade…....
0.1
National feature films/mn pop. 15-69………………….………
1.1
Entertainment & Media market/th pop. 15-69…………….
7.4
Printing & other media, % manufacturing…...................
2.5
Creative goods exports, % total trade………………………..
0.3

61
84
80
41
10 ● ◆
70

7.3
7.3.1
7.3.2
7.3.3
7.3.4


2.6
Online creativity………………………………………..……….…….

5.2
Generic top-level domains (TLDs)/th pop. 15-69……….

1.3
Country-code TLDs/th pop. 15-69…………………..………….

5.8
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.1

80
53
73
76
84 ○NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

309

PHILIPPINESGII 2019 rank

54

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

42

76

Lower middle

SEAO

106.5

956.0

8,935.973

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
56.0

89

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
49.9

Political and operational stability*……………..………….….
59.6
Government effectiveness*…………………………..…………. 45.0

84
98
73

1.2
1.2.1
1.2.2
1.2.3


54.6
Regulatory environment……………………………..………..

42.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
35.4

27.4
Cost of redundancy dismissal, salary weeks…………..

99
69
90
1 1 1 ○

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
63.6
Ease of starting a business*………………………………..……
72.0
Ease of resolving insolvency*……………………………….…. 55.2

89
119 ○ ◇
58
◆


24.6
HUMAN CAPITAL & RESEARCH………………...

83

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


33.3 [102]
Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
2.7
112 ○
Government funding/pupil, secondary, % GDP/cap… n/a n/a🕘🕘
School life expectancy, years……………….…………….……. 12.7
83

PISA scales in reading, maths, & science…………......…
n/a n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......…. 23.5
96

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
34.5
Tertiary enrolment, % gross………………………….….……….
35.3
Graduates in science & engineering, %……………….….
28.7
🕘🕘Tertiary inbound mobility, %.......................................
….
0.1

55
75
18 ●
108 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
6.2
🕘🕘Researchers, FTE/mn pop……………………………..…...……
187.7
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
19.9

72
78
98
43 ○ ◇51 ◆


INFRASTRUCTURE……………………………….......
48.5

58

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 68.5

ICT access*………………………………………………………….…….
47.5

ICT use*…………………………….....................................…….
44.7

88.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
93.8

60
◆
94
78 ◆
30 ◆
19 ● ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
34.2
Electricity output, GWh/mn pop………………………..…….
878.8
Logistics performance*…………………………………………….. 39.3
Gross capital formation, % GDP………………………….…….
27.5

67
97
59
31

3.3
3.3.1
3.3.2
3.3.3


42.8
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
13.3
Environmental performance*…….………………………………
57.7
ISO 14001 environmental certificates/bn PPP$ GDP..
1.2

48
19
71
61

◆

◆
◆
◆


38.3 110
MARKET SOPHISTICATION..………….……………

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
8.8 126 ○ ◇Ease of getting credit*…………………………………..…………..
5.0 128 ○ ◇
Domestic credit to private sector, % GDP…………...……
47.8 72Microfinance gross loans, % GDP……………………….…….
0.0 76 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 30.9
Ease of protecting minority investors*…………..………….
43.3
Market capitalization, % GDP………………………………...….
84.3
Venture capital deals/bn PPP$ GDP……………….……....
0.0

118 ○
105 ◇
18 ◆
68 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
75.2
Applied tariff rate, weighted avg., %………………………….
1.7
†Intensity of local competition …………………………………… 75.0Domestic market scale, bn PPP$……………………………… 956.0

20 ● ◆
18 ● ◆27 ◆
27
BUSINESS SOPHISTICATION..……….……………
40.9

32

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
46.1
Knowledge-intensive employment, %...........................
25.2
Firms offering formal training, % firms………………………… 59.8
🕘🕘
GERD performed by business, % GDP…………………..……
0.0
🕘🕘
GERD financed by business, %……………………………........
36.9
🕘🕘Females employed w/advanced degrees, %……………..
12.4

44
◆
55
9 ● ◆
72
50
57

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
22.6
University/industry research collaboration †………………..
57.5
State of cluster development†.……..………..…………………..
50.0
🕘🕘GERD financed by abroad, %.........................................
1.8
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

71
25
48
80
43
76

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
54.1

0.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
23.2

ICT services imports, % total trade…………..………………...
0.8

FDI net inflows, % GDP…………………………….………………….
2.6
🕘🕘
Research talent, % in business enterprise……..………….. 63.2

14 ● ◆
55
5 ●◆
83
65
6 ●◆

 33.7KNOWLEDGE & TECHNOLOGY OUTPUTS....

31

The Global Innovation Index 2019

◆

◆



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 11.5 64
Patents by origin/bn PPP$ GDP……………….…………..….…
0.4 82

0.0 90
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
1.6
15
Scientific & technical articles/bn PPP$ GDP….…..…..….
0.9 123 ○Citable documents H-index…………………….……….……..…. 13.4 54

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
4.9
New businesses/th pop. 15-64………………….…....………….
0.3
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
4.4
🕘🕘High- & medium-high-tech manufactures, %……………… 0.4

38
10 ● ◆
91 ○
55
61
25
◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


46.5
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

32.7
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
5.5

FDI net outflows, % GDP…………………………….………….......
1.3

14 ● ◆87
1 ●◆8 ● ◆
48
◆


27.7
CREATIVE OUTPUTS…….…………………….…………

63

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
41.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
30.7
Industrial designs by origin/bn PPP$ GDP…………..……..
0.9
ICTs & business model creation†………………………....…….
68.9

ICTs & organizational model creation †…………………….... 61.7

63
75
71
32
39

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
26.6
Cultural & creative services exports, % total trade…....
0.1
🕘🕘National feature films/mn pop. 15-69………………….………
0.8
Entertainment & Media market/th pop. 15-69…………….
2.6
🕘🕘
Printing & other media, % manufacturing…...................
0.6
Creative goods exports, % total trade……………………….. 7.0

40
◆
92
86
50
◆
87
8 ●◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….

Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

99
92
101
89
63

1.4
1.1
0.3
3.8
1.4

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
310

◆

◆
◆

POLAND

GII 2019 rank

39

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

41

37

High

EUR

38.1

1,201.9

31,938.7

39

Score/Value Rank

INSTITUTIONS………………………………….…….…..
73.6

37

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
68.2

Political and operational stability*……………..………….….
80.7
Government effectiveness*…………………………..…………. 61.9

39
35
40

1.2
1.2.1
1.2.2
1.2.3


72.9
Regulatory environment……………………………..………..

65.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
58.9

18.8
Cost of redundancy dismissal, salary weeks…………..

42
36
42
77 ○

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
79.7
Ease of starting a business*………………………………..……
82.9
Ease of resolving insolvency*……………………………….…. 76.5

34
93 ○ ◇
23 ●
41.2
HUMAN CAPITAL & RESEARCH………………...

40

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.0
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.8
Government funding/pupil, secondary, % GDP/cap… 22.1
School life expectancy, years……………….…………….……. 16.4

PISA scales in reading, maths, & science…………......…
503.9
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
9.2

39
54
41
23 ●
17
19 ●

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
35.5
🕘🕘Tertiary enrolment, % gross………………………….….……….
66.6
Graduates in science & engineering, %……………….….
22.9
Tertiary inbound mobility, %....................................... ….
3.4

52
34
44
59

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
31.0
Researchers, FTE/mn pop……………………………..…..…… 3,001.9
Gross expenditure on R&D, % GDP………….………..……
1.0

39.9
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
25.4

37
30
35
42
42


INFRASTRUCTURE……………………………….......
53.8

38

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  81.5

ICT access*………………………………………………………….…….
74.0

ICT use*…………………………….....................................…….
69.8

93.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
89.3

28
50 ◇
35
17 ●
31

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
38.2
Electricity output, GWh/mn pop………………………..…….
4,421.3
Logistics performance*…………………………………………….. 69.0
Gross capital formation, % GDP………………………….…….
21.5

49
50
27
81 ○

3.3
3.3.1
3.3.2
3.3.3


41.5
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.7

Environmental performance*…….………………………………
64.1
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.6

50
57
46
39



MARKET SOPHISTICATION..………….…………… 47.9

65

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
33.5
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...…… 52.5
🕘🕘Microfinance gross loans, % GDP……………………….…….
0.1

75 ○ ◇
29
63
54 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 35.3
Ease of protecting minority investors*…………..………….
61.7

Market capitalization, % GDP………………………………...….
32.2
Venture capital deals/bn PPP$ GDP……………….……....
0.0

98 ○
54
45 ○
41

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
75.0

Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 70.2
Domestic market scale, bn PPP$……………………………… 1,201.9

21 ●
23
58
22 ●

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
38.4

38

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
52.3
Knowledge-intensive employment, %...........................
38.6
Firms offering formal training, % firms………………………… 34.6

GERD performed by business, % GDP…………………..…… 0.7

GERD financed by business, %……………………………........
53.1
Females employed w/advanced degrees, %……………..
20.4

32
30
42
30
22
23 ●

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
21.7
University/industry research collaboration †………………..
35.1
State of cluster development†.……..………..…………………..
46.6

GERD financed by abroad, %.........................................
5.5
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.4

75 ○ ◇
92 ○ ◇
64
63 ○
52
34

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
41.2

1.1
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.3

ICT services imports, % total trade…………..………………...
1.3

FDI net inflows, % GDP…………………………….………………….
3.0

Research talent, % in business enterprise……..………….. 47.1

37
32
40
56
56
28

 30.9 39
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 24.3

Patents by origin/bn PPP$ GDP……………….…………..….…
3.9

0.3
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.8
Scientific & technical articles/bn PPP$ GDP….…..…..….
16.5
Citable documents H-index…………………….……….……..….
35.5

36
28
45
27
32
25

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.6
New businesses/th pop. 15-64………………….…....………….
1.7
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 10.5
High- & medium-high-tech manufactures, %………………
0.3

36
16 ● ◆
58
42
30
35

6.3
6.3.1
6.3.2
6.3.3
6.3.4


25.1
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

6.5
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.3

FDI net outflows, % GDP…………………………….………….......
1.6

39
41
25 ●
47
40


32.4
CREATIVE OUTPUTS…….…………………….…………

46

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
42.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
38.2
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a
†
ICTs & business model creation ………………………....……. 60.8

ICTs & organizational model creation †…………………….... 51.9

58
67 ○
n/a60◇
73 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
27.2
Cultural & creative services exports, % total trade…....
1.1
National feature films/mn pop. 15-69………………….………
1.8
Entertainment & Media market/th pop. 15-69…………….
11.5
Printing & other media, % manufacturing…...................
1.2
Creative goods exports, % total trade……………………….. 4.4

37
25
69 ○ ◇
33◇
54
12 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


17.4
Online creativity………………………………………..……….…….

6.9
Generic top-level domains (TLDs)/th pop. 15-69……….

25.7
Country-code TLDs/th pop. 15-69…………………..………….

34.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
13.8

38
46
23 ●
36
34

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

311

PORTUGAL

GII 2019 rank

32

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

35

31

High

EUR

10.3

328.8

32,006.4

32

Score/Value Rank

INSTITUTIONS………………………………….…….…..
81.8

22

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
81.2

Political and operational stability*……………..………….….
86.0

Government effectiveness*…………………………..…………. 78.8

19 ●
21
22

1.2
1.2.1
1.2.2
1.2.3


78.8
Regulatory environment……………………………..………..

66.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
76.3

17.0
Cost of redundancy dismissal, salary weeks…………..

32
35
25
70 ○

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
85.5
Ease of starting a business*………………………………..……
90.9
Ease of resolving insolvency*……………………………….…. 80.0

19 ●
49
15 ●


47.7
HUMAN CAPITAL & RESEARCH………………...

24

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


59.4
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.9
Government funding/pupil, secondary, % GDP/cap… 27.7
School life expectancy, years……………….…………….……. 16.3

PISA scales in reading, maths, & science…………......…
497.0
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
9.6

27
52
16 ●
27
22
24

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
44.9
🕘🕘Tertiary enrolment, % gross………………………….….……….
62.9
Graduates in science & engineering, %……………….…. 29.0
🕘🕘Tertiary inbound mobility, %....................................... ….
5.0

24
41
16 ●
41

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
38.8
Researchers, FTE/mn pop…………………………..…...…… 4 ,350.5
Gross expenditure on R&D, % GDP………….………..……
1.3

43.1
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
30.3

26
20
26
38
38


INFRASTRUCTURE……………………………….......
56.8

31

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 82.5

ICT access*………………………………………………………….…….
80.3

ICT use*…………………………….....................................…….
66.8

93.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 89.9

25
28
40
17
30

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
35.9
Electricity output, GWh/mn pop………………………..…….
5,592.2
Logistics performance*…………………………………………….. 73.9
Gross capital formation, % GDP………………………….…….
17.3

60
37
23
107 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


52.0
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
12.3
Environmental performance*…….……………………………… 71.9
ISO 14001 environmental certificates/bn PPP$ GDP..
4.7

23
27
25
24



MARKET SOPHISTICATION..………….…………… 49.8

58

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
47.4
Ease of getting credit*…………………………………..…………..
45.0

Domestic credit to private sector, % GDP…………...…… 104.1

Microfinance gross loans, % GDP……………………….…….
n/a

38
94 ○
24
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 33.5 105 ○ ◇Ease of protecting minority investors*…………..………….
61
60.0

Market capitalization, % GDP………………………………...….
30.9 47 ○
Venture capital deals/bn PPP$ GDP……………….……....
0.0 58 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
68.5
Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†…………………………………… 70.3
Domestic market scale, bn PPP$……………………………… 328.8

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
37.3

42

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
50.0Knowledge-intensive employment, %...........................
36.1
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… 0.7

GERD financed by business, %……………………………........
44.4
Females employed w/advanced degrees, %……………..
16.1

37
35
n/a
29
37
40

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
27.7
University/industry research collaboration †………………..
54.5
†State of cluster development .……..………..………………….. 54.4

GERD financed by abroad, %......................................... 8.0
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
0.7

53
31
37
48
64 ○
31

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
34.3

0.9
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.9

ICT services imports, % total trade…………..………………...
1.1

FDI net inflows, % GDP…………………………….…………………. 3.5

Research talent, % in business enterprise……..………….. 34.3

61
42
72 ○
64
48
38

 29.8KNOWLEDGE & TECHNOLOGY OUTPUTS....

43



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 25.3

Patents by origin/bn PPP$ GDP……………….…………..….…
2.5

0.8
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.2
Scientific & technical articles/bn PPP$ GDP….…..…..….
29.3
Citable documents H-index…………………….……….……..….
30.4

34
35
30
40 ○
8 ●◆
30

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


47.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.1
New businesses/th pop. 15-64………………….…....………….
5.0

Computer software spending, % GDP…………..…………… 0.6

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 22.8
High- & medium-high-tech manufactures, %………………
0.3

22
92 ○
26
9 ●
13 ● ◆
42

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.1
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

2.7
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.7

FDI net outflows, % GDP…………………………….………….......
1.3

69
47
48
61
49


39.4
CREATIVE OUTPUTS…….…………………….…………

32

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
58.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
98.4
Industrial designs by origin/bn PPP$ GDP…………..……..
7.2

ICTs & business model creation†………………………....……. 78.6

ICTs & organizational model creation †…………………….... 64.8

13 ● ◆
14 ● ◆
18 ●1 1 ●
30

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
21.4
Cultural & creative services exports, % total trade…....
0.6
National feature films/mn pop. 15-69………………….………
5.2
Entertainment & Media market/th pop. 15-69…………….
35.5
Printing & other media, % manufacturing…...................
1.2
Creative goods exports, % total trade………………………..
1.5

52
42
41
22
45
37

7.3
7.3.1
7.3.2
7.3.3
7.3.4


19.8
Online creativity………………………………………..……….…….

18.8
Generic top-level domains (TLDs)/th pop. 15-69……….

41.7
Country-code TLDs/th pop. 15-69…………………..………….

23.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
2.8

35
29
16 ●
46
59 ○

40
23
55
51

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
312

The Global Innovation Index 2019

QATAR

GII 2019 rank

65

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

70

53

High

NAWA

2.7

356.7

130,475.1

51

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
66.2

53

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
67.6

Political and operational stability*……………..………….….
73.7
Government effectiveness*…………………………..…………. 64.5

40
50
39

◇

1.2
1.2.1
1.2.2
1.2.3


68.1
Regulatory environment……………………………..………..

53.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
65.5

23.2
Cost of redundancy dismissal, salary weeks…………..

62
51
35
97

◇
◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
62.9

87.7
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….…. 38.1

91
68
104

◇


28.9
HUMAN CAPITAL & RESEARCH………………...

70

◇

◇

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


31.9 105
Education…………………………………………………………..……
◇
Expenditure on education, % GDP………………….…….….
2.9 106 ○ ◇🕘🕘Government funding/pupil, secondary, % GDP/cap… 10.5
95 ○ ◇

School life expectancy, years……………….…………….…….
11.9
91
◇

PISA scales in reading, maths, & science…………......…
407.3 60
Pupil-teacher ratio, secondary…………………………......….
10.4
34

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
47.5
Tertiary enrolment, % gross………………………….….……….
16.4
Graduates in science & engineering, %……………….….
22.9
Tertiary inbound mobility, %....................................... …. 35.3

19 ●
98
◇
43
1●◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
7.2
🕘🕘Researchers, FTE/mn pop……………………………..…...……
603.8
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.5

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
10.7

68
◇
63
◇
63
43 ○ ◇62


INFRASTRUCTURE……………………………….......
58.0

28 ●

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 75.0

ICT access*………………………………………………………….…….
78.9

ICT use*…………………………….....................................…….
70.7

79.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
71.4

44
32
32
48
65

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
62.3
Electricity output, GWh/mn pop………………………..…….
16,461.9
Logistics performance*…………………………………………….. 66.0
Gross capital formation, % GDP………………………….…….

n/a

3 ●◆
6●◆
29 ●
n/a

3.3
3.3.1
3.3.2
3.3.3


36.8
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
7.0
Environmental performance*…….………………………………
67.8
ISO 14001 environmental certificates/bn PPP$ GDP..
1.3

72
◇
86
31 ●
60

◇

MARKET SOPHISTICATION..………….…………… 44.7

82

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
38.1
Ease of getting credit*…………………………………..…………..
40.0
Domestic credit to private sector, % GDP…………...…… 77.3

Microfinance gross loans, % GDP……………………….…….
n/a

59
104 ○ ◇
40
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 31.6
Ease of protecting minority investors*…………..………….
28.3
Market capitalization, % GDP………………………………...….
89.5
Venture capital deals/bn PPP$ GDP……………….……....
n/a

114 ○ ◇
127 ○ ◇
16 ●
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
64.4
Applied tariff rate, weighted avg., %………………………….
4.2
Intensity of local competition†…………………………………… 65.6
Domestic market scale, bn PPP$……………………………… 356.7

55
76
79
49

◇


BUSINESS SOPHISTICATION..……….……………
30.2

67

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
17.3 113 ○ ◇Knowledge-intensive employment, %...........................
18.1 80◇Firms offering formal training, % firms………………………… n/a n/a🕘🕘
GERD performed by business, % GDP…………………..…… 0.1 63◇🕘🕘
GERD financed by business, %……………………………........
7.1 76◇🕘🕘Females employed w/advanced degrees, %……………..
4.5 92
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
27.6
University/industry research collaboration †………………..
64.8
†State of cluster development .……..………..………………….. 65.4
🕘🕘
GERD financed by abroad, %.........................................
1.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

54
17 ●
15 ●
79
◇
38
68

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
45.7

n/a
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
6.6
ICT services imports, % total trade…………..………………...
3.9

FDI net inflows, % GDP…………………………….………………….
0.6
🕘🕘
Research talent, % in business enterprise……..………….. 18.6

25 ●
n/a82
3 ● ◆
116 ○
57◇

 18.4 80
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇

◇
97
115 ○
78
◇
n/a
90
◇
85
◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


32.3 84
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-1.8 106 ○ ◇🕘🕘New businesses/th pop. 15-64………………….…....………….
1.7 56Computer software spending, % GDP…………..…………… 0.3
31 ●

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 2.3 84◇
High- & medium-high-tech manufactures, %……………… 0.4 23 ●

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.9
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….
🕘🕘
0.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.8

FDI net outflows, % GDP…………………………….………….......
2.9

59
n/a
128 ○ ◇
85
24 ●


25.8
CREATIVE OUTPUTS…….…………………….…………

70

5.1
0.1
0.0
n/a
4.2
6.6

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
43.6 54Trademarks by origin/bn PPP$ GDP…………..……….….….
3.3 120 ○ ◇
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a n/a†
ICTs & business model creation ………………………....……. 66.7 44
ICTs & organizational model creation †…………………….... 63.9 33

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
13.1 75

Cultural & creative services exports, % total trade…....
0.3 62
National feature films/mn pop. 15-69………………….………
n/a n/aEntertainment & Media market/th pop. 15-69…………….
25.7 25Printing & other media, % manufacturing…...................
1.2 55🕘🕘Creative goods exports, % total trade………………………..
0.2 88

◇

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.0
Online creativity………………………………………..……….…….

3.7
Generic top-level domains (TLDs)/th pop. 15-69……….

2.4
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
8.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.3

◇
◇

78
60
61
66
78

◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

313

REPUBLIC OF KOREA (THE)GII 2019 rank

11

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

13

10

High

SEAO

51.2

2,139.7

41,350.6

12

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
79.7

26

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
77.2

Political and operational stability*……………..………….….
86.0

Government effectiveness*…………………………..…………. 72.8

27
21
28

◇

1.2
1.2.1
1.2.2
1.2.3


72.4
Regulatory environment……………………………..………..

71.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
77.2

27.4
Cost of redundancy dismissal, salary weeks…………..

◇
45
29
◇
23
107 ○ ◇

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
89.4

95.8
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….…. 83.0

6
11
10


66.5
HUMAN CAPITAL & RESEARCH………………...

1●◆

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


60.8
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
5.3
Government funding/pupil, secondary, % GDP/cap… 28.5
School life expectancy, years……………….…………….……. 16.4

PISA scales in reading, maths, & science…………......…
519.1
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
13.8

21
37
14
◆
24
7
62 ○

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
49.4
🕘🕘Tertiary enrolment, % gross………………………….….……….
93.8
Graduates in science & engineering, %……………….….
29.9
Tertiary inbound mobility, %....................................... ….
1.9

16
4
◆
14
◆
76 ○ ◇

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
89.3
Researchers, FTE/mn pop……………………………..…...……
7,514.4
Gross expenditure on R&D, % GDP………….………..……
4.6

92.6
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
74.1

1 ●◆
3 ●◆
2 ●◆
4●
9


INFRASTRUCTURE……………………………….......
61.6

15

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 94.0

ICT access*………………………………………………………….…….
90.0

ICT use*…………………………….....................................…….
88.1

97.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
100.0

1 ●◆
7
4 ●◆
4
1 ●

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
55.4
Electricity output, GWh/mn pop………………………..…….
10,910.4
Logistics performance*…………………………………………….. 72.4
Gross capital formation, % GDP………………………….…….
31.2

7
11
25
18

3.3
3.3.1
3.3.2
3.3.3


35.4
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
6.3
Environmental performance*…….………………………………
62.3
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.6

77 ○ ◇
98 ○
53
◇
38



MARKET SOPHISTICATION..………….…………… 64.3

11

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
67.6
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...…… 144.8

Microfinance gross loans, % GDP……………………….…….
n/a

15
54
11
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 48.7
Ease of protecting minority investors*…………..………….
73.3
Market capitalization, % GDP………………………………...….
97.8
Venture capital deals/bn PPP$ GDP……………….……....
0.0

43
21
13
39

4.3
4.3.1
4.3.2
4.3.3



Trade, competition, & market scale………..……………. 76.7
Applied tariff rate, weighted avg., %………………………….
5.1
Intensity of local competition†……………………………………
83.9
Domestic market scale, bn PPP$………………………………2,139.7

◇

◆

◇


BUSINESS SOPHISTICATION..……….……………
57.6

10

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
75.3

Knowledge-intensive employment, %...........................
39.1
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… 3.6

GERD financed by business, %……………………………........
76.2
🕘🕘Females employed w/advanced degrees, %……………..
16.2

5
28
◇
n/a
2 ●◆
3 ●◆
39
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
46.1
University/industry research collaboration †………………..
56.5
†State of cluster development .……..………..………………….. 59.6

GERD financed by abroad, %.........................................
1.3
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 14.4

18
◇
26
29
89 ○
40
◇
4
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
51.5 18

19
1.6
Intellectual property payments, % total trade………….....

13
High-tech imports, % total trade………………..………………..
15.2
ICT services imports, % total trade…………..………………...
0.5 105 ○ ◇
FDI net inflows, % GDP…………………………….………………….
0.8 113 ○
2 ●◆Research talent, % in business enterprise……..…………..
81.3

 50.2KNOWLEDGE & TECHNOLOGY OUTPUTS....


13

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 63.1
Patents by origin/bn PPP$ GDP……………….…………..….…
78.2

8.0
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 3.2
Scientific & technical articles/bn PPP$ GDP….…..…..…. 20.4
Citable documents H-index…………………….……….……..….
43.3

8
1 ●◆
1 ●◆
7
24
18

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.8
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.1
New businesses/th pop. 15-64………………….…....………….
2.6

Computer software spending, % GDP…………..…………… 0.2

ISO 9001 quality certificates/bn PPP$ GDP…………..……
6.2
High- & medium-high-tech manufactures, %………………
0.6

31
42
43
62
49
7

6.3
6.3.1
6.3.2
6.3.3
6.3.4


43.8
Knowledge diffusion……………………………………..…..…….

1.1Intellectual property receipts, % total trade……………….

26.4
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.7

FDI net outflows, % GDP…………………………….………….......
2.0

16
18
1 ●◆
90 ○
29


44.1
CREATIVE OUTPUTS…….…………………….…………

17

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
65.8

Trademarks by origin/bn PPP$ GDP…………..……….….….
89.1
Industrial designs by origin/bn PPP$ GDP…………..……..
29.7

ICTs & business model creation†………………………....……. 79.7

ICTs & organizational model creation †……………………....
64.0

3 ●◆
23
1 ●◆
10
32
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
25.7
Cultural & creative services exports, % total trade…....
0.4
🕘🕘National feature films/mn pop. 15-69………………….………
8.7
Entertainment & Media market/th pop. 15-69…………….
47.8

Printing & other media, % manufacturing…...................
0.3
Creative goods exports, % total trade………………………..
3.6

42
54
22
19
98 ○ ◇
16

7.3
7.3.1
7.3.2
7.3.3
7.3.4


19.0
Online creativity………………………………………..……….…….

8.1
Generic top-level domains (TLDs)/th pop. 15-69……….

9.6
Country-code TLDs/th pop. 15-69…………………..………….

17.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
46.6

37
43
41
51
12

17
88 ○ ◇4 ◆14

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
314

The Global Innovation Index 2019

◇

◇
◇
◇
◇

REPUBLIC OF MOLDOVA (THE)GII 2019 rank

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

45

81

Lower middle

EUR

4.0

25.2

7,304.548

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
58.4

82

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
43.2
Political and operational stability*……………..………….….
61.4
Government effectiveness*…………………………..…………. 34.2

96
91
97

1.2
1.2.1
1.2.2
1.2.3


57.1
Regulatory environment……………………………..………..

40.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
35.4

23.7
Cost of redundancy dismissal, salary weeks…………..

91
72
89
98

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
74.8
Ease of starting a business*………………………………..……
95.6

Ease of resolving insolvency*……………………………….…. 54.1

47
◆
12 ● ◆
63
30.4
HUMAN CAPITAL & RESEARCH………………...

64

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.2
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
6.7
Government funding/pupil, secondary, % GDP/cap… 36.3
School life expectancy, years……………….…………….……. 11.6

PISA scales in reading, maths, & science…………......…
421.3
Pupil-teacher ratio, secondary…………………………......….
9.9

38
◆
11 ● ◆
7 ●◆
93
51
28
◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
30.3
Tertiary enrolment, % gross………………………….….……….
41.1
🕘🕘Graduates in science & engineering, %……………….….
22.3
Tertiary inbound mobility, %.......................................
….
4.1

66
70
47
52

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
3.7
Researchers, FTE/mn pop……………………………..…...……
723.9
Gross expenditure on R&D, % GDP………….………..……

84
56
78
43 ○ ◇78 ○ ◇


Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.3
0.0
0.0

◆


INFRASTRUCTURE……………………………….......
39.4

88

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  72.3

ICT access*………………………………………………………….…….
72.8

ICT use*…………………………….....................................…….
53.4

77.1
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
86.0

52
56
66
53
37

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………

21.2
1,641.4
Electricity output, GWh/mn pop………………………..…….

Logistics performance*…………………………………………….. 18.4
Gross capital formation, % GDP………………………….…….
19.8

115 ○
85
106 ○
95

3.3
3.3.1
3.3.2
3.3.3


24.8
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
4.5
Environmental performance*…….………………………………
52.0
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.2

116 ○
112 ○ ◇91
1 1 1 ○

MARKET SOPHISTICATION..………….…………… 49.5

58

◆
◆
◆

◆

60

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
29.8 94Ease of getting credit*…………………………………..…………..
70.0 40Domestic credit to private sector, % GDP…………...……
27.1 100
Microfinance gross loans, % GDP……………………….…….
0.5 29

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 68.3
Ease of protecting minority investors*…………..………….
68.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
50.2 108 ○🕘🕘
Applied tariff rate, weighted avg., %………………………….
3.5 69
Intensity of local competition†…………………………………… 63.8 86
Domestic market scale, bn PPP$……………………………… 25.2 121 ○ ◇

[9]
30
n/a
n/a


BUSINESS SOPHISTICATION..……….……………
26.1

93

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
33.6

Knowledge-intensive employment, %...........................
26.5
Firms offering formal training, % firms………………………… 32.4

GERD performed by business, % GDP…………………..…… 0.1

GERD financed by business, %……………………………........
17.9
Females employed w/advanced degrees, %……………..
13.7

76
52
46
70
70
48

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
14.8 120 ○
University/industry research collaboration †………………..
29.1 109 ○State of cluster development†.……..………..…………………..
28.2 124 ○ ◇
GERD financed by abroad, %.........................................
3.7 67
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1 51
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
30.0

0.5
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.4

ICT services imports, % total trade…………..………………...
1.9

FDI net inflows, % GDP…………………………….………………….
2.2
Research talent, % in business enterprise……..………….. 6.4

82
61
66
28 ● ◆
77
70 ○

 28.7 44
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◆

◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 33.2
Patents by origin/bn PPP$ GDP……………….…………..….…
3.1

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 5.9
Scientific & technical articles/bn PPP$ GDP….…..…..….
6.7
Citable documents H-index…………………….……….……..….
4.7

28 ● ◆
32◆
49◆
4 ● ◆
66
96

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


35.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
4.2
New businesses/th pop. 15-64………………….…....………….
1.8

Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 4.6
High- & medium-high-tech manufactures, %……………… 0.1

72
13 ●
54
87
60
71

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.9
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

0.7
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.2

FDI net outflows, % GDP…………………………….………….......
0.1

61
45
74
18 ●
93
31.8
CREATIVE OUTPUTS…….…………………….…………

49

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
53.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
127.1
Industrial designs by origin/bn PPP$ GDP…………..……..
12.2

ICTs & business model creation†………………………....…….
52.1

ICTs & organizational model creation †…………………….... 48.3

26 ● ◆
7 ●◆11 ● ◆
98
86

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
10.5 83
Cultural & creative services exports, % total trade…....
0.9 31◆🕘🕘
National feature films/mn pop. 15-69………………….………
0.3 99 ○Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.0 68Creative goods exports, % total trade……………………….. 0.2 83

7.3
7.3.1
7.3.2
7.3.3
7.3.4


9.9
Online creativity………………………………………..……….…….

2.0
Generic top-level domains (TLDs)/th pop. 15-69……….

2.0
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
17.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
24.3

◆

52
◆
78
67
53
20 ● ◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

315

ROMANIA

GII 2019 rank

50

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

53

54

Upper middle

EUR

19.6

514.2

26,446.7

49

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
67.1

52

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
51.6

Political and operational stability*……………..………….….
70.2
Government effectiveness*…………………………..…………. 42.3

75
61
84

1.2
1.2.1
1.2.2
1.2.3


77.9
Regulatory environment……………………………..………..

55.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
56.6

8.0
Cost of redundancy dismissal, salary weeks…………..

◆
35
46
47
◆
1 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
71.9
Ease of starting a business*………………………………..……
83.9

Ease of resolving insolvency*……………………………….…. 59.9

57
86
47


29.1
HUMAN CAPITAL & RESEARCH………………...

69

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


40.5
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.1
Government funding/pupil, secondary, % GDP/cap… 16.2

School life expectancy, years……………….…………….……. 14.3

PISA scales in reading, maths, & science…………......…
437.5
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.1

82
99 ○
76
67
47
49

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
41.4
🕘🕘Tertiary enrolment, % gross………………………….….……….
48.0
Graduates in science & engineering, %……………….….
28.8
Tertiary inbound mobility, %.......................................
….
4.8

31
60
17 ●
43

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
5.3
Researchers, FTE/mn pop……………………………..…...……
890.2
Gross expenditure on R&D, % GDP………….………..……
0.5

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

77
52
64
43 ○ ◇78 ○ ◇
INFRASTRUCTURE……………………………….......
54.5

35

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 67.6
ICT access*………………………………………………………….…….
71.4

ICT use*…………………………….....................................…….
62.4

66.0
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

◆

70.8

63
61
51
79
67

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
35.4
Electricity output, GWh/mn pop………………………..…….
3,277.3
Logistics performance*…………………………………………….. 49.3
Gross capital formation, % GDP………………………….…….

64
60
47
49

3.3
3.3.1
3.3.2
3.3.3


60.6
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
13.0
Environmental performance*…….………………………………
64.8
ISO 14001 environmental certificates/bn PPP$ GDP.. 11.7

6 ●◆
25 ●
41
◆
4 ●◆


43.2
MARKET SOPHISTICATION..………….……………

92

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
30.2
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...……
26.4
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.0

92
20
103 ○
72 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 30.4 120 ○ ◇Ease of protecting minority investors*…………..………….
61
60.0
🕘🕘
Market capitalization, % GDP………………………………...….
7.9 72 ○
Venture capital deals/bn PPP$ GDP……………….……....
0.0 76 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
68.9
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 62.9
Domestic market scale, bn PPP$……………………………… 514.2

24.3

BUSINESS SOPHISTICATION..……….……………
33.6

51

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
40.4

Knowledge-intensive employment, %...........................
23.3
Firms offering formal training, % firms………………………… 40.7

GERD performed by business, % GDP…………………..…… 0.3

GERD financed by business, %……………………………........
49.4
Females employed w/advanced degrees, %……………..
11.0

56
63
33
48
27
60

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
19.2 92

University/industry research collaboration †………………..
38.7 74State of cluster development†.……..………..…………………..
34.5 109 ○ ◇
GERD financed by abroad, %.........................................
9.9 43JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 70Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1 64

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
41.1

1.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.8
ICT services imports, % total trade…………..………………...
2.3

FDI net inflows, % GDP…………………………….………………….
2.9
Research talent, % in business enterprise……..………….. 25.5

◆
38
34
34
16 ● ◆
5948

 30.3KNOWLEDGE & TECHNOLOGY OUTPUTS....

41



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 10.5
Patents by origin/bn PPP$ GDP……………….…………..….…
2.4

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.1

Scientific & technical articles/bn PPP$ GDP….…..…..…. 10.6
Citable documents H-index…………………….……….……..….
13.9

69
37
73
55 ○
43
53

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


55.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
4.7
New businesses/th pop. 15-64………………….…....………….
5.6

Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
25.2
High- & medium-high-tech manufactures, %……………… 0.4

8 ● ◆
11 ● ◆
2545
9 ●◆22 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


25.1
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

4.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.9

FDI net outflows, % GDP…………………………….………….......
0.5

38
57
35
10 ● ◆66


25.8
CREATIVE OUTPUTS…….…………………….…………

71

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
38.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
43.1
Industrial designs by origin/bn PPP$ GDP…………..……..
2.6

ICTs & business model creation†………………………....…….
60.8

ICTs & organizational model creation †…………………….... 50.0

78
60
45
61
81

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
14.7
Cultural & creative services exports, % total trade…....
1.5
National feature films/mn pop. 15-69………………….………
2.0
Entertainment & Media market/th pop. 15-69…………….
5.9

Printing & other media, % manufacturing…...................
1.0
Creative goods exports, % total trade……………………….. 0.7

68
15 ● ◆
63
45
65
52

7.3
7.3.1
7.3.2
7.3.3
7.3.4


11.2
Online creativity………………………………………..……….…….

4.6
Generic top-level domains (TLDs)/th pop. 15-69……….

15.8
Country-code TLDs/th pop. 15-69…………………..………….

12.5
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
16.1

50
56
32
60
29

38
23
93 ○
39

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
316

The Global Innovation Index 2019

RUSSIAN FEDERATION (THE)GII 2019 rank

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

59

41

Upper middle

EUR

144.0

4,179.6

29,266.9

46

Score/Value Rank

46

Score/Value Rank


INSTITUTIONS………………………………….…….…..
60.9

74

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
50.2
Political and operational stability*……………..………….….
61.4
Government effectiveness*…………………………..…………. 44.7

83
91 ○
76

1.2
1.2.1
1.2.2
1.2.3


56.5
Regulatory environment……………………………..………..

29.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
25.4

17.3
Cost of redundancy dismissal, salary weeks…………..

95 ○
103 ○
1 1 1 ○ ◇
73

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
75.8
Ease of starting a business*………………………………..……
93.0
Ease of resolving insolvency*……………………………….…. 58.6

43
29
50


48.3
HUMAN CAPITAL & RESEARCH………………...

23

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.6
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.8
Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. 15.5

PISA scales in reading, maths, & science…………......…
491.8
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
8.8

35
86
n/a
37
26
◆
15 ● ◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
50.3
🕘🕘Tertiary enrolment, % gross………………………….….……….
81.8
Graduates in science & engineering, %……………….….
30.9
Tertiary inbound mobility, %.......................................
….
3.9

14 ● ◆
17 ● ◆
10 ● ◆
54

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
36.9
Researchers, FTE/mn pop……………………………..…...……
2,851.7
Gross expenditure on R&D, % GDP………….………..……
1.1

42.3
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
46.7

30
33
33
40
24


INFRASTRUCTURE……………………………….......

47.1

62

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 80.7

ICT access*………………………………………………………….…….
74.0

ICT use*…………………………….....................................…….
64.9

91.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
92.1

29
51
45
25
23

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
31.5

7,544.3
Electricity output, GWh/mn pop………………………..…….

Logistics performance*…………………………………………….. 32.4
Gross capital formation, % GDP………………………….…….
21.2

81
28
74
86

3.3
3.3.1
3.3.2
3.3.3


29.2
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
4.3
Environmental performance*…….………………………………
63.8
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.2

101 ○ ◇
113 ○ ◇
47
112 ○


49.4
MARKET SOPHISTICATION..………….……………

61

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
34.6
Ease of getting credit*…………………………………..…………..
80.0
Domestic credit to private sector, % GDP…………...……
52.7

Microfinance gross loans, % GDP……………………….…….
0.0

69
20
62
73 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 34.7 102 ○Ease of protecting minority investors*…………..………….
61.7 54Market capitalization, % GDP………………………………...….
38.9 39Venture capital deals/bn PPP$ GDP……………….……....
77 ○
0.0

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
78.8

Applied tariff rate, weighted avg., %………………………….
3.6

†Intensity of local competition …………………………………… 70.9Domestic market scale, bn PPP$…………………………… 4,179.6

◆

◆
◆
◆
◆
◆

◆
◆
◆
◆
◆


BUSINESS SOPHISTICATION..……….……………
40.0

35

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
58.0Knowledge-intensive employment, %...........................
44.3
🕘🕘Firms offering formal training, % firms………………………… 46.2

GERD performed by business, % GDP…………………..…… 0.7

GERD financed by business, %……………………………........
30.2
Females employed w/advanced degrees, %……………..
26.3

25
◆
18 ● ◆
27
31
◆
58
7 ●◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
19.1

University/industry research collaboration †………………..
49.6
State of cluster development†.……..………..…………………..
41.4
GERD financed by abroad, %.........................................
2.6
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

93
40
89
73
69
52

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
42.7

1.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.3

ICT services imports, % total trade…………..………………...
1.5

FDI net inflows, % GDP…………………………….………………….
1.6

Research talent, % in business enterprise……..………….. 47.1

◆
32
18 ● ◆
39
45
92
27
◆

 27.1KNOWLEDGE & TECHNOLOGY OUTPUTS....

47



◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 29.9
Patents by origin/bn PPP$ GDP……………….…………..….…
5.8

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 2.5
Scientific & technical articles/bn PPP$ GDP….…..…..….
6.9
Citable documents H-index…………………….……….……..….
37.4

◆
30
20 ● ◆
47
8 ●◆63
22 ● ◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


33.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.0

New businesses/th pop. 15-64………………….…....………….
4.3
Computer software spending, % GDP…………..……………
0.2
ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.9
High- & medium-high-tech manufactures, %……………… 0.3

77
63
29
63
1 1 1 ○
43

6.3
6.3.1
6.3.2
6.3.3
6.3.4


17.6
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

2.6
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.3

FDI net outflows, % GDP…………………………….………….......
1.9

63
39
49
71
30


25.1
CREATIVE OUTPUTS…….…………………….…………

72

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
39.4
Trademarks by origin/bn PPP$ GDP…………..……….….….
58.1
Industrial designs by origin/bn PPP$ GDP…………..……..
0.9
ICTs & business model creation†………………………....…….
53.3

ICTs & organizational model creation †…………………….... 58.4

71
38
69
91 ○
49

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

88
27
76
43
78 ○
68

7.3
7.3.1
7.3.2
7.3.3
7.3.4


12.1
Online creativity………………………………………..……….…….

3.5
Generic top-level domains (TLDs)/th pop. 15-69……….

13.3
Country-code TLDs/th pop. 15-69…………………..………….

19.7
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
18.1

◆

9.8
1.0
1.2
6.5
0.8
0.3

◆

47
61
34
49
26

11 ● ◆
71
51
6●◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

317

RWANDAGII 2019 rank

94

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

123

65

Low

SSF

12.5

27.1

2,280.1

99

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

68.1

50 ● ◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
59.8

Political and operational stability*……………..………….….
73.7
Government effectiveness*…………………………..………….
52.9

51 ● ◆◆
50
53 ● ◆

1.2
1.2.1
1.2.2
1.2.3


70.1
Regulatory environment……………………………..………..

45.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
49.8

13.0
Cost of redundancy dismissal, salary weeks…………..

51 ● ◆63◆
54◆
40 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
74.3

91.4
Ease of starting a business*………………………………..……

Ease of resolving insolvency*……………………………….….
57.2

52 ● ◆
45 ●53 ● ◆

17.8 102
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


43.9
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.2
Government funding/pupil, secondary, % GDP/cap… 38.0

School life expectancy, years……………….…………….……. 11.2

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
20.1

74
◆
97
4 ●◆
99
n/a
89

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

9.5
7.6
13.8
1.7

112
113 ○
92
78

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
🕘🕘
Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.0 120 ○ ◇
12.3 105 ○ ◇n/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
INFRASTRUCTURE……………………………….......
40.0

87

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  48.7

ICT access*………………………………………………………….…….
27.8

ICT use*…………………………….....................................…….
19.0

72.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
75.8

99 ◆
119 ○
110
67 ◆
59 ◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
42.0
Electricity output, GWh/mn pop………………………..…….
n/a
Logistics performance*…………………………………………….. 42.6
Gross capital formation, % GDP………………………….…….

40 ●
n/a56◆
46 ●

3.3
3.3.1
3.3.2
3.3.3


29.1 102
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
n/a n/a
Environmental performance*…….………………………………
43.7 113
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.0 128 ○ ◇

25.0

◆


55.2
MARKET SOPHISTICATION..………….……………

38 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
67.6
Ease of getting credit*…………………………………..…………..
95.0
Domestic credit to private sector, % GDP…………...……
20.9

Microfinance gross loans, % GDP……………………….…….
6.7

16 ● ◆
3●◆
111
1●◆

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 54.2
Ease of protecting minority investors*…………..………….
76.7

Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.0

31 ● ◆
13 ● ◆
n/a
35

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
44.0 120 ○🕘🕘
Applied tariff rate, weighted avg., %………………………….
7.3 99
Intensity of local competition†……………………………………
57.9 114Domestic market scale, bn PPP$………………………………
27.1 119 ○
BUSINESS SOPHISTICATION..……….……………
36.2

[44]

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
34.8
Knowledge-intensive employment, %...........................
8.2
🕘🕘Firms offering formal training, % firms…………………………
55.4
GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/aFemales employed w/advanced degrees, %……………..
3.7

[69]
103
12 ● ◆
n/a
n/a
94
◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
44.4 [23]University/industry research collaboration †………………..
41.5 63State of cluster development†.……..………..…………………..
45.8 72

GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. n/a n/a

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
29.4
🕘🕘
0.1
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
9.8
ICT services imports, % total trade…………..………………...
0.6

FDI net inflows, % GDP…………………………….………………….
3.0

Research talent, % in business enterprise……..…………..
n/a

87
99
35 ●
96
57
n/a

 5.7 125 ○ ◇KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 4.6 102
Patents by origin/bn PPP$ GDP……………….…………..….…
0.1 107
0.0 79PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
0.4 36

Scientific & technical articles/bn PPP$ GDP….…..…..….
5.5 76
Citable documents H-index…………………….……….……..…. 2.6 114

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


8.6
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0Intellectual property receipts, % total trade……………….
🕘🕘
0.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.8

FDI net outflows, % GDP…………………………….………….......
0.4

3.9 [123]n/a n/a2.051◆
0.0 103
0.4 122 ○n/a n/a
113
85
94
86
74


16.9 108
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
33.0 100
Trademarks by origin/bn PPP$ GDP…………..……….….….
10.3 105🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.2 97

ICTs & business model creation†………………………....…….
60.8 62
ICTs & organizational model creation †……………………....
51.0
77

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

1.5 [119]
0.0 105n/a n/an/a n/an/a n/a0.2 87

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

0.1 123 ○
0.1 120 ○
0.1 1130.2 117 ○n/a n/aNOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
318

The Global Innovation Index 2019

◆

◆
◆

SAUDI ARABIAGII 2019 rank

68

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

85

49

High

NAWA

33.6

1,856.9

55,943.9

61

Score/Value Rank

INSTITUTIONS………………………………….…….…..
51.3 104

Score/Value Rank

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
53.2

Political and operational stability*……………..………….….
54.4
Government effectiveness*…………………………..…………. 52.5

◇70
111 ○ ◇
◇
55

1.2
1.2.1
1.2.2
1.2.3


60.7
Regulatory environment……………………………..………..

41.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
49.0

23.7
Cost of redundancy dismissal, salary weeks…………..

80
71
56
99

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
40.0
Ease of starting a business*………………………………..……
80.1

Ease of resolving insolvency*……………………………….…. 0.0

129 ○ ◇
107 ○ ◇
129 ○ ◇


45.5
HUMAN CAPITAL & RESEARCH………………...

29 ●

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


63.2
Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
5.1
Government funding/pupil, secondary, % GDP/cap… n/a🕘🕘
School life expectancy, years……………….…………….……. 16.9

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.0

[14]
43
n/a
18 ●
n/a
37

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
36.1
Tertiary enrolment, % gross………………………….….……….
68.9
Graduates in science & engineering, %……………….….
21.9
Tertiary inbound mobility, %.......................................
….
4.9

49
29 ●
51
42

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
37.3
Researchers, FTE/mn pop……………………………..…...……
n/a🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.8

53.4
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
40.9

29 ●
n/a
42
26 ●
31 ●
INFRASTRUCTURE……………………………….......
48.9

55

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 71.7

ICT access*………………………………………………………….…….
74.8

ICT use*…………………………….....................................…….
61.6

79.2
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
71.4

53
44
54
48
65

◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………

43.2
10,681.8
Electricity output, GWh/mn pop………………………..…….

Logistics performance*…………………………………………….. 44.3
Gross capital formation, % GDP………………………….…….
26.6

37
12 ●
54
◇
35

3.3
3.3.1
3.3.2
3.3.3


31.9
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
7.6

Environmental performance*…….………………………………
57.5
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.2

86 ◇
83
75
◇
110 ○ ◇




BUSINESS SOPHISTICATION..……….……………
34.3 [48]

◇

◇
◇
◇
◇

◇

◇

MARKET SOPHISTICATION..………….…………… 51.9

47

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
34.7
Ease of getting credit*…………………………………..…………..
45.0

Domestic credit to private sector, % GDP…………...……
54.1

Microfinance gross loans, % GDP……………………….…….
n/a

68
94
60
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 47.0
Ease of protecting minority investors*…………..………….
80.0
Market capitalization, % GDP………………………………...….
66.6
Venture capital deals/bn PPP$ GDP……………….……....
0.0

47
6●◆
23
74 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
74.0

Applied tariff rate, weighted avg., %………………………….
4.9

Intensity of local competition†…………………………………… 74.8
Domestic market scale, bn PPP$…………………………..… 1,856.9

23 ●
84 ◇
29 ●
16 ● ◆

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
37.3
🕘🕘
Knowledge-intensive employment, %...........................
27.3
Firms offering formal training, % firms………………………… n/a
GERD performed by business, % GDP…………………..…… n/a
GERD financed by business, %……………………………........
n/a🕘🕘Females employed w/advanced degrees, %……………..
5.5

[63]
51
n/a
n/a
n/a
88

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
30.3

University/industry research collaboration †………………..
48.0
State of cluster development†.……..………..…………………..
62.1

GERD financed by abroad, %.........................................
n/aJV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

45
43
21 ●
n/a
72
53

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
35.4 [55]n/a n/aIntellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
7.6 62
ICT services imports, % total trade…………..………………...
1.4 53

FDI net inflows, % GDP…………………………….………………….
0.9 107 ○
Research talent, % in business enterprise……..…………..
n/a n/a 17.0KNOWLEDGE & TECHNOLOGY OUTPUTS....


87

◇

◇

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 12.8
Patents by origin/bn PPP$ GDP……………….…………..….…
0.7

0.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
6.2

Citable documents H-index…………………….……….……..….
18.7

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


26.5 104
Knowledge impact………………………………………..............
◇
Growth rate of PPP$ GDP/worker, %……………..…....…….
-4.0 1 1 1 ○ ◇New businesses/th pop. 15-64………………….…....………….
0.4 88 ○Computer software spending, % GDP…………..……………
0.4 28 ●
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.3 103◇
High- & medium-high-tech manufactures, %……………… 0.4
31

6.3
6.3.1
6.3.2
6.3.3
6.3.4


11.8
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….
🕘🕘
0.6
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.2

FDI net outflows, % GDP…………………………….………….......
1.0

◇
93
n/a
75
◇
118 ○ ◇54


21.9
CREATIVE OUTPUTS…….…………………….…………

86

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.9
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
4.3
Industrial designs by origin/bn PPP$ GDP…………..……..
0.3

ICTs & business model creation†………………………....…….
66.5

ICTs & organizational model creation †……………………....
61.5

84
◇
118 ○ ◇
96
45
40

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
11.7 78◇🕘🕘
Cultural & creative services exports, % total trade…....
0.0 115 ○ ◇
National feature films/mn pop. 15-69………………….………
n/a n/aEntertainment & Media market/th pop. 15-69…………….
13.9 30◇Printing & other media, % manufacturing…...................
1.3 39🕘🕘Creative goods exports, % total trade……………………….. 0.4 66

7.3
7.3.1
7.3.2
7.3.3
7.3.4


2.0
Online creativity………………………………………..……….…….

2.8
Generic top-level domains (TLDs)/th pop. 15-69……….

0.6
Country-code TLDs/th pop. 15-69…………………..………….

6.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.3

63
73
43
n/a
67
39

84
67
90
74
77

◇

◇

◇
◇
◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

319

SENEGALGII 2019 rank

96

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

81

103

Low

SSF

16.3

60.0

3,651.2

100

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
60.4

75

◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
49.3

Political and operational stability*……………..………….….
70.2
Government effectiveness*…………………………..…………. 38.8

86
61
89

◆
◆
◆

1.2
1.2.1
1.2.2
1.2.3


64.9
Regulatory environment……………………………..………..

38.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
42.4

14.8
Cost of redundancy dismissal, salary weeks…………..

67
80
68
59

◆
◆

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
67.1
Ease of starting a business*………………………………..……
89.9
Ease of resolving insolvency*……………………………….…. 44.3

73
54
84


20.6
HUMAN CAPITAL & RESEARCH………………...

93

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


36.8
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
6.2
Government funding/pupil, secondary, % GDP/cap… 15.2
School life expectancy, years……………….…………….……. 9.0

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
18.9

97
19 ● ◆
83
1 1 1 ○
n/a
83

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
19.4

Tertiary enrolment, % gross………………………….….……….
11.2
Graduates in science & engineering, %……………….….
n/aTertiary inbound mobility, %.......................................
….
8.3

96
106
n/a
25 ● ◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
5.7
🕘🕘Researchers, FTE/mn pop……………………………..…...……
549.3
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.8

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

74
◆
65
◆
48 ◆
43 ○ ◇78 ○ ◇
INFRASTRUCTURE……………………………….......

111

31.1

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 39.0 106

ICT access*………………………………………………………….…….
38.4 106
ICT use*…………………………….....................................…….
19.2 10947.9 106Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
50.6 103

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
24.2 103
289.2 112
Electricity output, GWh/mn pop………………………..…….

Logistics performance*…………………………………………….. 8.8 118 ○Gross capital formation, % GDP………………………….…….
25.9 40 ●

3.3
3.3.1
3.3.2
3.3.3


30.1
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
8.3
Environmental performance*…….………………………………
49.5
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

94
70
100
105

◆

◆



MARKET SOPHISTICATION..………….…………… 35.6 118
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
20.7
Ease of getting credit*…………………………………..…………..
30.0
Domestic credit to private sector, % GDP…………...……
29.5

Microfinance gross loans, % GDP……………………….…….
1.2

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 41.7 [65]Ease of protecting minority investors*…………..………….
41.7 108
Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
44.3
Applied tariff rate, weighted avg., %………………………….
12.3
†Intensity of local competition …………………………………… 68.0
Domestic market scale, bn PPP$……………………………… 60.0

116
115 ○
96
17 ●


BUSINESS SOPHISTICATION..……….……………
20.2 119

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
9.1 123 ○🕘🕘
Knowledge-intensive employment, %...........................
6.4 106Firms offering formal training, % firms…………………………
17.4 81🕘🕘
GERD performed by business, % GDP…………………..……
0.0 87 ○🕘🕘
GERD financed by business, %……………………………........
2.1 88🕘🕘Females employed w/advanced degrees, %……………..
1.8 102

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
21.5
University/industry research collaboration †………………..
39.8
State of cluster development†.……..………..…………………..
40.3
🕘🕘
GERD financed by abroad, %.........................................
7.9
JV-strategic alliance deals/bn PPP$ GDP………………….. n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

78
71
92
49
n/a
93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
29.9

0.1
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.9

ICT services imports, % total trade…………..………………...
2.6

FDI net inflows, % GDP…………………………….………………….
2.4
🕘🕘Research talent, % in business enterprise……..………….. 0.1

83
95
93
12 ● ◆
71
86 ○ ◇

 19.4KNOWLEDGE & TECHNOLOGY OUTPUTS....

77



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


34.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.4
New businesses/th pop. 15-64………………….…....………….
0.4
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.9
🕘🕘High- & medium-high-tech manufactures, %……………… 0.2

75
19 ●
90
40 ● ◆
108
63
◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


18.3
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

0.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.4

FDI net outflows, % GDP…………………………….………….......
0.5

◆
58
61
89
◆
12 ● ◆65


20.8
CREATIVE OUTPUTS…….…………………….…………

92

5.1
0.4
0.1
n/a
4.0
5.9

96
80
71
n/a
93
90

The Global Innovation Index 2019

◆
◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.9 85
Trademarks by origin/bn PPP$ GDP…………..……….….….
11.4 103Industrial designs by origin/bn PPP$ GDP…………..……..
0.8 75

ICTs & business model creation†………………………....…….
65.3
51 ● ◆
ICTs & organizational model creation †…………………….... 58.1 52
◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.4 109
Online creativity………………………………………..……….…….

1.0 95Generic top-level domains (TLDs)/th pop. 15-69……….

0.1 1 1 1
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.2 114
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a9.0 900.9 30 ● ◆0.2 104 ○ ◇n/a n/a0.8 74◇
0.1 102119
123 ○
68 ◆
93

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
320

◆

◆

SERBIAGII 2019 rank

57

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

57

62

Upper middle

EUR

8.8

112.5

17,555.2

55

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
68.7

47

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
58.7

Political and operational stability*……………..………….….
73.7
Government effectiveness*…………………………..…………. 51.2

55
50
59

1.2
1.2.1
1.2.2
1.2.3


70.9
Regulatory environment……………………………..………..

42.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
41.3

8.0
Cost of redundancy dismissal, salary weeks…………..

49
70
72
1 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
76.7
Ease of starting a business*………………………………..……
92.6

Ease of resolving insolvency*……………………………….…. 60.8

40
37
45


32.4
HUMAN CAPITAL & RESEARCH………………...

59

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


43.3
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
3.9
Government funding/pupil, secondary, % GDP/cap… 11.9

School life expectancy, years……………….…………….……. 14.8
🕘🕘
PISA scales in reading, maths, & science…………......…
446.6
Pupil-teacher ratio, secondary…………………………......….
8.1

77
83
89 ○
57
43
9 ●◆

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
41.7
Tertiary enrolment, % gross………………………….….……….
66.5
Graduates in science & engineering, %……………….….
26.6
Tertiary inbound mobility, %.......................................
….
4.4

30
35
22
46

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
12.0
Researchers, FTE/mn pop……………………………..…..…… 2,079.1
Gross expenditure on R&D, % GDP………….………..……
0.9

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
2.9

50
39
◆
38
43 ○ ◇76


INFRASTRUCTURE……………………………….......
49.9

54

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  73.2

ICT access*………………………………………………………….…….
76.6

ICT use*…………………………….....................................…….
61.0

73.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
81.5

50
37
56
57
48

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
30.8

5,469.4
Electricity output, GWh/mn pop………………………..…….

Logistics performance*…………………………………………….. 36.4
Gross capital formation, % GDP………………………….…….
21.3

84
39
64
84

3.3
3.3.1
3.3.2
3.3.3


45.6
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
6.0
Environmental performance*…….………………………………
57.5
ISO 14001 environmental certificates/bn PPP$ GDP..
11.1

43
100 ○ ◇73
5 ●◆


BUSINESS SOPHISTICATION..……….……………
31.9

63

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
36.4

Knowledge-intensive employment, %...........................
28.5
Firms offering formal training, % firms………………………… 37.8

GERD performed by business, % GDP…………………..…… 0.3

GERD financed by business, %……………………………........
10.0
Females employed w/advanced degrees, %……………..
14.2

67
48
36
45
75 ○
45

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
26.5
University/industry research collaboration †………………..
38.5
State of cluster development†.……..………..…………………..
42.9
GERD financed by abroad, %.........................................
19.9
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

61
76
81
18 ●
63
57

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
32.9

1.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.4

ICT services imports, % total trade…………..………………...
2.1

FDI net inflows, % GDP…………………………….………………….
6.5
Research talent, % in business enterprise……..………….. 10.6

66
38
99 ○
26 ● ◆
20 ● ◆
64 ○

◆

◆

 26.7 48
KNOWLEDGE & TECHNOLOGY OUTPUTS....

Knowledge creation………………………………………........... 21.0
Patents by origin/bn PPP$ GDP……………….…………..….…
1.7

0.2
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 0.7
Scientific & technical articles/bn PPP$ GDP….…..…..….
33.1
Citable documents H-index…………………….……….……..….
10.8

40
49
54
32
4 ●◆
60

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


37.8
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.0

New businesses/th pop. 15-64………………….…....………….
1.8

Computer software spending, % GDP…………..……………
0.0
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 27.0
High- & medium-high-tech manufactures, %………………
0.2

59
87 ○
53
108 ○ ◇
6 ●◆
47

6.3
6.3.1
6.3.2
6.3.3
6.3.4


21.1
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

1.6
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.3

FDI net outflows, % GDP…………………………….………….......
0.6

48
36
◆
59
13 ● ◆62


27.2
CREATIVE OUTPUTS…….…………………….…………

65

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.0

Trademarks by origin/bn PPP$ GDP…………..……….….….
29.1
Industrial designs by origin/bn PPP$ GDP…………..……..
2.0

ICTs & business model creation†………………………....…….
57.7

ICTs & organizational model creation †…………………….... 51.7

93
76
51
77
74

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
22.7 47

Cultural & creative services exports, % total trade…....
1.4 17 ● ◆National feature films/mn pop. 15-69………………….………
5.7 39Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.6 28Creative goods exports, % total trade……………………….. 0.7 51

7.3
7.3.1
7.3.2
7.3.3
7.3.4


14.2
Online creativity………………………………………..……….…….

1.4
Generic top-level domains (TLDs)/th pop. 15-69……….

4.5
Country-code TLDs/th pop. 15-69…………………..………….

40.2
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
23.6

◆



MARKET SOPHISTICATION..………….…………… 39.6 103 ○ ◇
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
28.0
Ease of getting credit*…………………………………..…………..
65.0
Domestic credit to private sector, % GDP…………...……
43.0
Microfinance gross loans, % GDP……………………….……. 0.0

98 ○
54
77
65 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 38.8
Ease of protecting minority investors*…………..………….
56.7
🕘🕘Market capitalization, % GDP………………………………...….
11.5
Venture capital deals/bn PPP$ GDP……………….……....
n/a

82
79
69 ○
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
52.0

Applied tariff rate, weighted avg., %………………………….
n/a
†Intensity of local competition …………………………………… 64.1
Domestic market scale, bn PPP$……………………………… 112.5

101 ○ ◇
n/a
84
73



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

42
90
54
35
21

◆
◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

321

SINGAPORE

GII 2019 rank

8

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

15

1

High

SEAO

5.8

556.2

100,344.7

5

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
94.9

1 ● ◆

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
100.0

100.0
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 100.0

1 ● ◆
1 ● ◆
1 ● ◆

1.2
1.2.1
1.2.2
1.2.3


98.3
Regulatory environment……………………………..………..

98.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
94.6

8.0
Cost of redundancy dismissal, salary weeks…………..

2 ●
2 ● ◆
8
1 ●

1.3
1.3.1
1.3.2


86.3
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
98.2
Ease of resolving insolvency*……………………………….…. 74.3

17
3 ● ◆
25


63.0
HUMAN CAPITAL & RESEARCH………………...

5

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


50.3
Education…………………………………………………………..……
🕘🕘
2.9
Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 16.7

School life expectancy, years……………….…………….……. 16.3

PISA scales in reading, maths, & science…………......…
551.6
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.7

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
61.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
6,729.7
🕘🕘Gross expenditure on R&D, % GDP………….………..……
2.2

48.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
68.9

13
5
13
30
12


65.4
INFRASTRUCTURE……………………………….......

7

3.1
3.1.1
3.1.2
3.1.3
3.1.4

77.1
83.9
34.5
27.2

Information & communication technologies(ICTs) 89.6
ICT access*………………………………………………………….…….
87.2

ICT use*…………………………….....................................…….
75.8

98.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
96.6



◆

57 ○ ◇104 ○ ◇73 ○ ◇26
1 ● ◆
47 ○1 ● ◆
135◆
1 ● ◆

11
926
2 ●
13

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 54.7
 …………………..…….9,209.8
Electricity output, GWh/mn pop……

Logistics performance*……………………………………………..
90.4

Gross capital formation, % GDP………………………….…….
27.8

11
17
7
30

3.3
3.3.1
3.3.2
3.3.3


52.1
Ecological sustainability………………………………………..

16.4
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
64.2
ISO 14001 environmental certificates/bn PPP$ GDP..  2.4

22
9
45 ○ ◇43



MARKET SOPHISTICATION..………….…………… 73.6

5

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
68.4
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...……
128.2

Microfinance gross loans, % GDP……………………….…….
n/a

13
29
17
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 76.7
Ease of protecting minority investors*…………..………….
80.0
Market capitalization, % GDP………………………………...….
220.1
Venture capital deals/bn PPP$ GDP……………….……....
0.2

5
6
4
7

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
75.6

Applied tariff rate, weighted avg., %………………………….
0.1
†Intensity of local competition …………………………………… 78.4

Domestic market scale, bn PPP$……………………………… 556.2

19
3 ● ◆
15
35



◆

◆
◆
◆


BUSINESS SOPHISTICATION..……….……………
63.9

4 ● ◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


9
Knowledge workers…………………………………………….…..
71.0

1 ● ◆
Knowledge-intensive employment, %...........................
56.1
Firms offering formal training, % firms…………………………
n/a n/a🕘🕘
GERD performed by business, % GDP…………………..…… 1.3 16
🕘🕘
GERD financed by business, %……………………………........
54.1 19Females employed w/advanced degrees, %……………..
17.1 36
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


49.3
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
70.0

State of cluster development†.……..………..…………………..
68.6
🕘🕘
GERD financed by abroad, %.........................................
6.8
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.2
Patent families 2+ offices/bn PPP$ GDP…………………….. 2.2

14
10
11
54 ○
1 ● ◆
18

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
71.3

3.3
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
21.2

2.7
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
22.3
🕘🕘Research talent, % in business enterprise……..………….. 50.5

1 ● ◆
5
◆
7
◆
11
8
◆
24

 50.9KNOWLEDGE & TECHNOLOGY OUTPUTS....

11Knowledge creation………………………………………........... 33.4

3.0
Patents by origin/bn PPP$ GDP……………….…………..….…

1.7
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 17.5
Citable documents H-index…………………….……….……..….
36.5

27
33
20
n/a
28
23

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


53.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.5
New businesses/th pop. 15-64………………….…....………….
8.6
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 7.0
High- & medium-high-tech manufactures, %……………… 0.8

11
33
16
41
46 ○
1 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


65.2
Knowledge diffusion……………………………………..…..…….

1.6Intellectual property receipts, % total trade……………….

27.4
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.4

FDI net outflows, % GDP…………………………….………….......
9.0

◆
5
15
1 ● ◆
44
8
◆


38.3
CREATIVE OUTPUTS…….…………………….…………

34

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
47.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
20.1
Industrial designs by origin/bn PPP$ GDP…………..……..
1.1

ICTs & business model creation†………………………....…….
80.4

ICTs & organizational model creation†…………………….... 74.6

46 ○ ◇88 ○ ◇
62 ○
7
14

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
32.2
Cultural & creative services exports, % total trade…....
1.9
National feature films/mn pop. 15-69………………….………
2.9
Entertainment & Media market/th pop. 15-69…………….
42.3
Printing & other media, % manufacturing…...................
0.7
Creative goods exports, % total trade……………………….. 4.4

20
8
57 ○
20
80 ○
11

7.3
7.3.1
7.3.2
7.3.3
7.3.4


26.4
Online creativity………………………………………..……….…….

25.6
Generic top-level domains (TLDs)/th pop. 15-69……….

11.2
Country-code TLDs/th pop. 15-69…………………..………….

23.8
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
52.9

28
23
38
◇
45 ○ ◇10

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
322

The Global Innovation Index 2019

◇
◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

◇

SLOVAKIA

GII 2019 rank

37

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

33

42

High

EUR

5.4

191.1

35,129.8

36

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
73.1

38

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
71.6

82.5
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 66.1

38
32
38

1.2
1.2.1
1.2.2
1.2.3


73.2
Regulatory environment……………………………..………..

64.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
61.5

18.8
Cost of redundancy dismissal, salary weeks…………..

40
37
39
78

1.3
1.3.1
1.3.2


74.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
82.0
Ease of resolving insolvency*……………………………….…. 66.9

51
98 ○ ◇39
32.4
HUMAN CAPITAL & RESEARCH………………...

58

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


48.9
Education…………………………………………………………..……

4.6
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 19.2

School life expectancy, years……………….…………….……. 14.5

PISA scales in reading, maths, & science…………......…
462.8
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.2

63
58
53
63
41
39

2.2
2.2.1
2.2.2
2.2.3


31.8
Tertiary education……………………………………….……..….
🕘🕘
47.8
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….
21.1
Tertiary inbound mobility, %.......................................
….
6.0

61
61
57
37

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
16.7
………………………..….....… 2,795.0
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
0.9

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
13.8

47
34
40
43 ○ ◇58

54.2
INFRASTRUCTURE……………………………….......

36

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  74.4

ICT access*………………………………………………………….…….
73.9

ICT use*…………………………….....................................…….
69.1

73.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

80.9

47
53
36
57
50

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
34.7
 …………………..…….
Electricity output, GWh/mn pop……
4,843.8
Logistics performance*…………………………………………….. 45.1
Gross capital formation, % GDP………………………….…….
23.5

65
47
52
60

3.3
3.3.1
3.3.2
3.3.3


53.5
Ecological sustainability………………………………………..

9.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
70.6
ISO 14001 environmental certificates/bn PPP$ GDP..  9.0

15 ●
59
27 ●
8 ● ◆



◇

◇

46

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
47.3
Knowledge-intensive employment, %...........................
32.0

Firms offering formal training, % firms………………………… 43.5

GERD performed by business, % GDP…………………..…… 0.5

GERD financed by business, %……………………………........
46.2
Females employed w/advanced degrees, %……………..
13.9

40
41
28
39
34
46

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


23.4
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
38.3
State of cluster development†.……..………..…………………..
46.6

GERD financed by abroad, %.........................................
10.7
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.3◇70
79 ○ ◇
63
38
71 ○
38

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
35.9

0.8
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
13.4

1.0
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
4.4
Research talent, % in business enterprise……..………….. 21.9

51
50
15 ●
72
38
54 ○

 34.0 29
KNOWLEDGE & TECHNOLOGY OUTPUTS....

◇
◇

67

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
48.7
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
59.9

Microfinance gross loans, % GDP……………………….…….
n/a

35
40
55
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 27.0 125 ○ ◇Ease of protecting minority investors*…………..………….
53.3 87 ○🕘🕘Market capitalization, % GDP………………………………...….
5.1 73 ○
Venture capital deals/bn PPP$ GDP……………….……....
0.0 67 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
66.6
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 73.7
Domestic market scale, bn PPP$……………………………… 191.1



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 20.2

1.2
Patents by origin/bn PPP$ GDP……………….…………..….…

0.3
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
1.9
Scientific & technical articles/bn PPP$ GDP….…..…..….
13.6
Citable documents H-index…………………….……….……..…. 16.3

44
58
46
12 ● ◆
38
44

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


51.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.2
New businesses/th pop. 15-64………………….…....………….
4.7
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
21.6
High- & medium-high-tech manufactures, %……………… 0.6

13 ●
58
28
37
15 ● ◆
4 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


30.3
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

9.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.7

FDI net outflows, % GDP…………………………….………….......
3.5

29
71 ○
17 ●
62
19 ●


37.1
CREATIVE OUTPUTS…….…………………….…………

36

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
46.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
55.7
Industrial designs by origin/bn PPP$ GDP…………..……..
3.1

ICTs & business model creation†………………………....…….
66.9

ICTs & organizational model creation†…………………….... 65.0

47
41
41
41
28

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
41.0
7 ● ◆

Cultural & creative services exports, % total trade…....
0.4 57National feature films/mn pop. 15-69………………….………
6.6 34Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
0.5 91 ○ ◇Creative goods exports, % total trade……………………….. 8.5
7 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


14.4
Online creativity………………………………………..……….…….

3.0
Generic top-level domains (TLDs)/th pop. 15-69……….

26.6
Country-code TLDs/th pop. 15-69…………………..………….

26.8
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
10.1

◇

MARKET SOPHISTICATION..………….…………… 47.4




BUSINESS SOPHISTICATION..……….……………
35.6

41
65
◇
21 ●
40
43

47
23
35
63

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

323

SLOVENIA

GII 2019 rank

31

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

30

33

High

EUR

2.1

76.1

36,745.930

Score/Value Rank

INSTITUTIONS………………………………….…….…..

82.3

20

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
78.0
Political and operational stability*……………..………….….
84.2
Government effectiveness*…………………………..………….
74.9

26
25
25

1.2
1.2.1
1.2.2
1.2.3


80.7
Regulatory environment……………………………..………..

57.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
73.5

10.7
Cost of redundancy dismissal, salary weeks…………..

29
44
27
34

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
88.3
Ease of starting a business*………………………………..……
92.9
Ease of resolving insolvency*……………………………….….
83.7

10 ●
35
9 ●


46.6
HUMAN CAPITAL & RESEARCH………………...

27

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


60.0
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
4.9
Government funding/pupil, secondary, % GDP/cap… 23.9
School life expectancy, years……………….…………….…….
17.4

PISA scales in reading, maths, & science…………......…
509.3
🕘🕘
Pupil-teacher ratio, secondary…………………………......…. 9.7

25
51
29
16
9 ●
25

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
40.7
🕘🕘Tertiary enrolment, % gross………………………….….……….
77.6
Graduates in science & engineering, %……………….….
25.0
Tertiary inbound mobility, %.......................................
….
3.3

35
20
30
61

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
39.3
Researchers, FTE/mn pop……………………………......…… 4,467.8
Gross expenditure on R&D, % GDP………….………..……
1.9

52.3
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
10.5

25
17
19
28
63


INFRASTRUCTURE……………………………….......
53.9

37

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 76.9

ICT access*………………………………………………………….…….
80.6

ICT use*…………………………….....................................…….
65.7

79.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

39
24
43
45
48

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
37.2
Electricity output, GWh/mn pop………………………..…….
7,721.7
Logistics performance*…………………………………………….. 58.5
Gross capital formation, % GDP………………………….…….
20.3

56
26
34
92 ○

3.3
3.3.1
3.3.2
3.3.3


47.5
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
9.1
Environmental performance*…….………………………………
67.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 6.3

41
64
33
16


43.6
MARKET SOPHISTICATION..………….……………

87 ○ ◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
32.4
Ease of getting credit*…………………………………..…………..
45.0

Domestic credit to private sector, % GDP…………...……
44.8
Microfinance gross loans, % GDP……………………….…….
n/a

81 ○ ◇
94 ○75 ○ ◇
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.7
Ease of protecting minority investors*…………..………….
70.0
Market capitalization, % GDP………………………………...….
12.9
Venture capital deals/bn PPP$ GDP……………….……....
0.0

92 ○
27
67 ○
50 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
61.6

Applied tariff rate, weighted avg., %………………………….
1.8

Intensity of local competition†……………………………………
73.0
Domestic market scale, bn PPP$……………………………… 76.1

60
23
38
87 ○ ◇

81.5

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
44.1


27

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

Knowledge workers…………………………………………….….. 63.3
Knowledge-intensive employment, %...........................
43.1
Firms offering formal training, % firms…………………………
41.5
GERD performed by business, % GDP…………………..……
1.4

GERD financed by business, %……………………………........
69.2
Females employed w/advanced degrees, %…………….. 21.8

20
20
32
15
6 ● ◆
20

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
27.4
University/industry research collaboration †………………..
47.1
State of cluster development†.……..………..…………………..
47.3

GERD financed by abroad, %.........................................
10.2
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
1.1

56
46
57
41
66 ○
26

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
41.7 35
0.7 58Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.4 103 ○
41
ICT services imports, % total trade…………..………………...
1.5

FDI net inflows, % GDP…………………………….………………….
3.2 53Research talent, % in business enterprise……..…………..
61.8 10 ● 30.7 40
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 31.8
🕘🕘Patents by origin/bn PPP$ GDP……………….…………..….…
10.2

1.5
PCT patents by origin/bn PPP$ GDP…………..….…….……
🕘🕘
Utility models by origin/bn PPP$ GDP……………...…..……
0.2
Scientific & technical articles/bn PPP$ GDP….…..…..….
35.4
Citable documents H-index…………………….……….……..….
17.5

29
1 1 ●
23
47 ○
2 ●◆
42

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


41.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.5
New businesses/th pop. 15-64………………….…....………….
3.1
Computer software spending, % GDP…………..……………
0.1
ISO 9001 quality certificates/bn PPP$ GDP…………..……
24.1
High- & medium-high-tech manufactures, %………………
0.3

44
49
40
91 ○ ◇
11 ● ◆
46

6.3
6.3.1
6.3.2
6.3.3
6.3.4


19.3
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 4.5

ICT services exports, % total trade……………..……..………
1.6

FDI net outflows, % GDP…………………………….………….......
1.0

52
40
33
66
53


42.1
CREATIVE OUTPUTS…….…………………….…………

24

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
55.3
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
111.2
🕘🕘
Industrial designs by origin/bn PPP$ GDP…………..……..
6.4

18
9 ●◆
23
36
38

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
27.3 36Cultural & creative services exports, % total trade…....
0.9 32
National feature films/mn pop. 15-69………………….………
14.2
8 ●

Entertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.7 27Creative goods exports, % total trade………………………..
1.0 44

7.3
7.3.1
7.3.2
7.3.3
7.3.4


30.3
Online creativity………………………………………..……….…….

21.0
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 24.5
🕘🕘
83.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
19.9

ICTs & business model creation†………………………....…….
68.0

ICTs & organizational model creation †……………………....
61.9

25
28
25
12 ●
22

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
324

The Global Innovation Index 2019

SOUTH AFRICA

GII 2019 rank

63

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

68

51

Upper middle

SSF

57.4

790.9

13,675.3

58

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
65.9

55

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
57.2

Political and operational stability*……………..………….….
64.9
Government effectiveness*…………………………..…………. 53.3

61
79
51

1.2
1.2.1
1.2.2
1.2.3


72.6
Regulatory environment……………………………..………..

48.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
46.1

9.3
Cost of redundancy dismissal, salary weeks…………..

◆
43
59
65
25 ●

1.3
1.3.1
1.3.2


Business environment……………………………..…..……….
67.9
Ease of starting a business*………………………………..……
81.2

Ease of resolving insolvency*……………………………….…. 54.5

70
102 ○
61


30.4
HUMAN CAPITAL & RESEARCH………………...

65

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


44.4
Education…………………………………………………………..……

Expenditure on education, % GDP………………….…….….
6.1
Government funding/pupil, secondary, % GDP/cap… 19.5
School life expectancy, years……………….…………….……. 13.7

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
26.8

71
20 ● ◆
51
71
n/a
101 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
21.0
🕘🕘Tertiary enrolment, % gross………………………….….……….
20.5
Graduates in science & engineering, %……………….….
18.5
Tertiary inbound mobility, %.......................................
….
4.3

92
93
70
49

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
25.8
🕘🕘Researchers, FTE/mn pop……………………………..…...……
473.1
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.8

46.6
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
33.6

43
69
44
33
33


INFRASTRUCTURE……………………………….......

41.1

83

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 66.3
ICT access*………………………………………………………….…….
53.8

ICT use*…………………………….....................................…….
43.1

83.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
84.8

67
80
81
37
39

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
32.6
Electricity output, GWh/mn pop………………………..…….
4,461.7
Logistics performance*…………………………………………….. 61.4
Gross capital formation, % GDP………………………….…….
18.1

71
49
32
◆
102 ○

3.3
3.3.1
3.3.2
3.3.3


24.4
Ecological sustainability………………………………………..

GDP/unit of energy use…………………………………………….
4.8

Environmental performance*…….………………………………
44.7
ISO 14001 environmental certificates/bn PPP$ GDP..
1.6

119 ○ ◇
111 ○ ◇
110 ○ ◇
53


58.6
MARKET SOPHISTICATION..………….……………

19 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
44.0
Ease of getting credit*…………………………………..…………..
60.0
Domestic credit to private sector, % GDP…………...……
147.7
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.0

48
66
9●◆
64 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 62.7
Ease of protecting minority investors*…………..………….
73.3
Market capitalization, % GDP………………………………...….
302.1
Venture capital deals/bn PPP$ GDP……………….……....
0.0

19 ● ◆
21 ●1 ● ◆
46

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
69.2
Applied tariff rate, weighted avg., %………………………….
4.6

†Intensity of local competition …………………………………… 71.2
Domestic market scale, bn PPP$……………………………… 790.9

36
80
48
29 ●


BUSINESS SOPHISTICATION..……….……………
32.7

55

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
33.9
Knowledge-intensive employment, %...........................
23.2
Firms offering formal training, % firms………………………… n/a🕘🕘
GERD performed by business, % GDP…………………..…… 0.3
🕘🕘
GERD financed by business, %……………………………........
38.9
Females employed w/advanced degrees, %……………..
10.2

74
64
n/a
46
48
64

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


Innovation linkages…………..……………………………………..
29.9
University/industry research collaboration †………………..
54.2
State of cluster development†.……..………..…………………..
56.4
🕘🕘
GERD financed by abroad, %.........................................
13.0
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.3

48
33
32
32
45
40

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
34.4

2.0
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.9

1.2
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
0.5
🕘🕘Research talent, % in business enterprise……..………….. 17.7

60
13 ● ◆
32 ●60
117 ○ ◇
59

KNOWLEDGE & TECHNOLOGY OUTPUTS... 23.9


◆
◆
◆

57

◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 19.3

Patents by origin/bn PPP$ GDP……………….…………..….…
0.9

0.3
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 10.3
Citable documents H-index…………………….……….……..….
28.4

48
63
44
n/a
45
32 ● ◆

◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


37.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.4
New businesses/th pop. 15-64………………….…....………….
10.2
Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
5.5
🕘🕘High- & medium-high-tech manufactures, %……………… 0.3

58
97 ○
12 ● ◆
48
56
40

6.3
6.3.1
6.3.2
6.3.3
6.3.4


14.4
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

2.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.7

FDI net outflows, % GDP…………………………….………….......
1.8

80
49
55
91
32


20.8
CREATIVE OUTPUTS…….…………………….…………

91

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
20.9
Industrial designs by origin/bn PPP$ GDP…………..……..
1.3

ICTs & business model creation†………………………....…….
57.2

ICTs & organizational model creation †…………………….... 58.7

89
86
60
80
48

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
🕘🕘
Cultural & creative services exports, % total trade…....
🕘🕘
National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

6.9 95
0.2 700.8 90 ○
8.8 38◆n/a n/a0.8 48

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

3.7
3.0
8.6
4.2
0.3

73
63
42
87
75 ○NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

325

SPAINGII 2019 rank

29

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

28

25

High

EUR

46.4

1,867.9

40,138.8

28

Score/Value Rank

INSTITUTIONS………………………………….…….…..
78.1

30

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
73.5

77.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 71.6

33
44
29

1.2
1.2.1
1.2.2
1.2.3


77.9
Regulatory environment……………………………..………..

67.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
73.1

17.4
Cost of redundancy dismissal, salary weeks…………..

34
34
30
74 ○

1.3
1.3.1
1.3.2


83.0
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
86.9

Ease of resolving insolvency*……………………………….…. 79.1

25
69 ○
18


47.0
HUMAN CAPITAL & RESEARCH………………...

26

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


54.3
Education…………………………………………………………..……

4.3
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 18.5
School life expectancy, years……………….…………….……. 17.9

PISA scales in reading, maths, & science…………......…
491.4
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
11.6

46
71 ○
57 ○
13 ●
27
46

2.2
2.2.1
2.2.2
2.2.3


41.2
Tertiary education……………………………………….……..….
🕘🕘
91.2
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
23.9
Tertiary inbound mobility, %.......................................
….
2.7

33
6 ● ◆
34
68 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
45.5
………………………..…........ 2,873.4
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
1.2

74.2
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
47.0

21
32
31
14 ●
23

63.1
INFRASTRUCTURE……………………………….......

10 ●

Information & communication technologies(ICTs)  87.4

ICT access*………………………………………………………….…….
80.5

ICT use*…………………………….....................................…….
77.2

93.8
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
98.3

17
25
23
16
5 ● ◆

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 43.2
 …………………..…….5,853.6
Electricity output, GWh/mn pop……

Logistics performance*……………………………………………..
82.7

Gross capital formation, % GDP………………………….…….
21.8

36
35
17
77 ○

3.3
3.3.1
3.3.2
3.3.3


58.8
Ecological sustainability………………………………………..

12.5
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
78.4
ISO 14001 environmental certificates/bn PPP$ GDP..  7.3

8 ●
26
12 ●
13 ● ◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4





MARKET SOPHISTICATION..………….…………… 59.5

18

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
55.3
Ease of getting credit*…………………………………..…………..
60.0
Domestic credit to private sector, % GDP…………...……
105.7

Microfinance gross loans, % GDP……………………….……. n/a

24
66 ○
22
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 44.6
Ease of protecting minority investors*…………..………….
70.0
Market capitalization, % GDP………………………………...….
63.5
Venture capital deals/bn PPP$ GDP……………….……....
0.0

58
27
26
29

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
78.6
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 75.8
Domestic market scale, bn PPP$………………………………1,867.9

14 ● ◆
23
22
15 ● ◆

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
38.7

37

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
52.1 34Knowledge-intensive employment, %...........................
33.2 40Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..…… 0.7 32

GERD financed by business, %……………………………........ 46.7 33
Females employed w/advanced degrees, %……………..
22.1 19

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


26.5
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
42.2
State of cluster development†.……..………..…………………..
54.4
GERD financed by abroad, %.........................................
8.1
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.6

60
59
36
47
55
32

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
37.5

1.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.8

1.6
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.9
Research talent, % in business enterprise……..………….. 37.2

46
28
74 ○
38
81 ○
35

KNOWLEDGE & TECHNOLOGY OUTPUTS... 37.2 24


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 34.2

2.2
Patents by origin/bn PPP$ GDP……………….…………..….…

0.8
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
1.3
Scientific & technical articles/bn PPP$ GDP….…..…..….
20.0

Citable documents H-index…………………….……….……..…. 59.3

25
41
31
20
25
12 ●

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


48.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.5
New businesses/th pop. 15-64………………….…....………….
3.2
Computer software spending, % GDP…………..……………
0.7
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 18.0
High- & medium-high-tech manufactures, %……………… 0.4

18
74 ○
39
6 ● ◆
18
28

6.3
6.3.1
6.3.2
6.3.3
6.3.4


28.9
Knowledge diffusion……………………………………..…..…….

0.5Intellectual property receipts, % total trade……………….

3.9
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
2.9

FDI net outflows, % GDP…………………………….………….......
3.7

32
27
36
35
17


39.7
CREATIVE OUTPUTS…….…………………….…………

31

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
56.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
52.8
Industrial designs by origin/bn PPP$ GDP…………..……..
14.2

ICTs & business model creation†………………………....…….
74.3

ICTs & organizational model creation†…………………….... 63.4

14 ●
46
7 ● ◆
22
34

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
21.2
Cultural & creative services exports, % total trade…....
1.0National feature films/mn pop. 15-69………………….………
7.3
Entertainment & Media market/th pop. 15-69…………….
28.2
Printing & other media, % manufacturing…...................
1.3
Creative goods exports, % total trade……………………….. 0.9

54
28
25
24
41
46

7.3
7.3.1
7.3.2
7.3.3
7.3.4


24.0
Online creativity………………………………………..……….…….

28.0
Generic top-level domains (TLDs)/th pop. 15-69……….

16.4
Country-code TLDs/th pop. 15-69…………………..………….

58.8
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
12.0

30
22
30
17
38

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
326

The Global Innovation Index 2019SRI LANKA

GII 2019 rank

89

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

77

94

Lower middle

CSA

21.0

292.8

13,397.5

88

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
28.5

77

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
26.2

Knowledge-intensive employment, %...........................
20.4
🕘🕘Firms offering formal training, % firms………………………… 18.4
🕘🕘
GERD performed by business, % GDP…………………..…… 0.0
🕘🕘
GERD financed by business, %……………………………........
34.4
Females employed w/advanced degrees, %……………..
9.6

95
73
78 ○ ◇
74
55
67

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


21.8
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
37.9
†State of cluster development .……..………..………………….. 47.1
🕘🕘
GERD financed by abroad, %......................................... 1.5

JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0

73
82
58
87 ○
20 ● ◆
73

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
37.4 47 ●
n/a n/aIntellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.6 61
2.0 27 ● ◆
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.2 103🕘🕘
Research talent, % in business enterprise……..…………..
22.5 52


INSTITUTIONS………………………………….…….…..
50.7 107

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
52.6

71.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 42.9

72
58
80

1.2
1.2.1
1.2.2
1.2.3


33.1
Regulatory environment……………………………..………..

38.4
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
47.8

58.5
Cost of redundancy dismissal, salary weeks…………..

127 ○ ◇7860
◆126 ○ ◇

1.3
1.3.1
1.3.2


66.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
87.9
Ease of resolving insolvency*……………………………….…. 45.1

77
67
82


14.0
HUMAN CAPITAL & RESEARCH………………...

111 ○

◆

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


32.3 103
Education…………………………………………………………..……

2.8 107 ○
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 10.4 96 ○
School life expectancy, years……………….…………….……. 14.0
70

PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
17.4
78

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

8.0
19.0
n/a
0.5

113 ○ ◇
96n/a
96 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.6
🕘🕘Researchers, FTE/mn pop……………………………..…...……
107.0
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.1

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
3.2

95
85
105 ○
43 ○ ◇75

48.5
INFRASTRUCTURE……………………………….......

57

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 50.3

ICT access*………………………………………………………….…….
49.7

ICT use*…………………………….....................................…….
22.1

66.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 62.9

94
88
103
75
82

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
40.5
 …………………..…….
Electricity output, GWh/mn pop……
673.8
Logistics performance*…………………………………………….. 25.0
Gross capital formation, % GDP………………………….…….
36.8

43 ● ◆
102
89
10 ● ◆

3.3
3.3.1
3.3.2
3.3.3


54.7
Ecological sustainability………………………………………..

20.4
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 60.6
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.8

12 ● ◆
5 ● ◆
63 ◆
73

◆



MARKET SOPHISTICATION..………….…………… 38.7 108
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
22.5
Ease of getting credit*…………………………………..…………..
40.0
🕘🕘Domestic credit to private sector, % GDP…………...…… 45.7
Microfinance gross loans, % GDP……………………….……. 0.4

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 36.5
Ease of protecting minority investors*…………..………….
66.7
Market capitalization, % GDP………………………………...….
23.5
Venture capital deals/bn PPP$ GDP……………….……....
0.0

95
35 ●
55
45

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
57.0

Applied tariff rate, weighted avg., %………………………….
8.7
Intensity of local competition†…………………………………… 65.3
Domestic market scale, bn PPP$……………………………… 292.8

80
107
80
57



113 ○
104 ○ ◇
74
33 ●

 19.9KNOWLEDGE & TECHNOLOGY OUTPUTS....


73

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 5.9

1.0
Patents by origin/bn PPP$ GDP……………….…………..….…

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
2.2
Citable documents H-index…………………….……….……..….
8.7

92
61
72
n/a
1 1 1 ○
75

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


32.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.2
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.5
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..……
2.4
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

85
40 ●
87
32 ● ◆
83
87

6.3
6.3.1
6.3.2
6.3.3
6.3.4


21.6
Knowledge diffusion……………………………………..…..…….
n/aIntellectual property receipts, % total trade……………….

0.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
4.2

FDI net outflows, % GDP…………………………….………….......
0.1

46 ●
n/a
92
16 ●
95


21.8
CREATIVE OUTPUTS…….…………………….…………

87

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
33.5
🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
26.3
Industrial designs by origin/bn PPP$ GDP…………..…….. 1.0

ICTs & business model creation†………………………....……. 56.9

ICTs & organizational model creation†……………………....
47.5

99
78
66
81
90

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
18.8 [58]Cultural & creative services exports, % total trade…....
n/a n/a🕘🕘
National feature films/mn pop. 15-69………………….………
1.0 82Entertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
2.1
17 ●

Creative goods exports, % total trade………………………..
0.4 64

7.3
7.3.1
7.3.2
7.3.3
7.3.4


1.5 94
Online creativity………………………………………..……….…….

0.8 100
Generic top-level domains (TLDs)/th pop. 15-69……….

0.6 89Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
6.2 72
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.5 69NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

327

SWEDEN

GII 2019 rank

2

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

3

4

High

EUR

10.0

542.8

52,984.1

3

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
90.1

9

1.1
1.1.1
1.1.2


Political environment……………………………………….…...

Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….

9
12
8

1.2
1.2.1
1.2.2
1.2.3


92.0
Regulatory environment……………………………..………..

90.2
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
97.6

14.4
Cost of redundancy dismissal, salary weeks…………..

13
10
3 ●
57 ○

1.3
1.3.1
1.3.2


87.1
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
94.7
Ease of resolving insolvency*……………………………….…. 79.5

14
16
16


62.1
HUMAN CAPITAL & RESEARCH………………...

6

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


67.8
Education…………………………………………………………..……

7.6
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 23.6

School life expectancy, years……………….…………….……. 18.8

PISA scales in reading, maths, & science…………......…
495.8
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.9

6
◆
5
◆
32
8
23
56 ○

2.2
2.2.1
2.2.2
2.2.3


43.1
Tertiary education……………………………………….……..….
🕘🕘
63.5
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
26.6
Tertiary inbound mobility, %.......................................
….
6.6

28
39
23
35

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
75.3
Researchers, FTE/mn pop……………………………..…...……
7,268.2
Gross expenditure on R&D, % GDP………….………..……
3.4

80.2
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
59.1

6
4 ● ◆
3 ●
10
14


69.1
INFRASTRUCTURE……………………………….......

2 ● ◆

Information & communication technologies(ICTs) 89.5

ICT access*………………………………………………………….…….
82.7

ICT use*…………………………….....................................…….
87.1

94.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

12
17
6
14
19

3.1
3.1.1
3.1.2
3.1.3
3.1.4

91.1
91.2
91.1

93.8



◆

◆

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 59.8
………………….....…. 15,902.8
Electricity output, GWh/mn pop……

Logistics performance*……………………………………………..
93.1
Gross capital formation, % GDP………………………….…….
26.4

4 ● ◆
7
2 ●
39

3.3
3.3.1
3.3.2
3.3.3


58.1
Ecological sustainability………………………………………..

9.7
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
80.5
ISO 14001 environmental certificates/bn PPP$ GDP..  9.3

1057 ○
5 ●
7 ◆MARKET SOPHISTICATION..………….…………… 62.1

14

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
59.4
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...……
132.2

Microfinance gross loans, % GDP……………………….…….
n/a

19
77 ○
15
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 54.6
Ease of protecting minority investors*…………..………….
68.3
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.1

30
30
n/a
17

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
72.3
Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 75.1
Domestic market scale, bn PPP$……………………………… 542.8

29
23 ○
25
38




BUSINESS SOPHISTICATION..……….……………
68.8

1 ● ◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
81.8

Knowledge-intensive employment, %...........................
52.3
Firms offering formal training, % firms………………………… 70.3

GERD performed by business, % GDP…………………..……
2.4
🕘🕘
GERD financed by business, %……………………………........
57.3
Females employed w/advanced degrees, %…………….. 24.8

2 ● ◆
5
3 ●
4
14
12

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


66.1
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
71.8
State of cluster development†.……..………..…………………..
67.6
🕘🕘
GERD financed by abroad, %.........................................
6.7
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.2
Patent families 2+ offices/bn PPP$ GDP…………………….. 7.2

2 ● ◆
9
12
55 ○5◆
1 ● ◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
58.4

1.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.8

3.3
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.0

Research talent, % in business enterprise……..………….. 72.0

6
16
59 ○
6◆
55 ○
4◆

 61.8KNOWLEDGE & TECHNOLOGY OUTPUTS....

2 ● ◆



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 73.5

11.2
Patents by origin/bn PPP$ GDP……………….…………..….…

7.7
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 30.2
Citable documents H-index…………………….……….……..….
59.5

2 ● ◆
10
1 ● ◆
n/a
7
◆
11

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


48.0
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.4
New businesses/th pop. 15-64………………….…....………….
8.1
Computer software spending, % GDP…………..……………
0.6
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 7.9
High- & medium-high-tech manufactures, %………………
0.5

20
80 ○
19
11
38
14

6.3
6.3.1
6.3.2
6.3.3
6.3.4


63.9
Knowledge diffusion……………………………………..…..…….

3.7Intellectual property receipts, % total trade……………….

7.3
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
6.2

FDI net outflows, % GDP…………………………….………….......
3.9

◆
6
1 ● ◆
23
6
◆
15


51.9
CREATIVE OUTPUTS…….…………………….…………

7

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
56.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
55.6
Industrial designs by origin/bn PPP$ GDP…………..……..
4.1

ICTs & business model creation†………………………....…….
81.9

ICTs & organizational model creation†…………………….... 82.7

15
42
30
4 ●
2 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
31.8
Cultural & creative services exports, % total trade…....
1.1
National feature films/mn pop. 15-69………………….………
10.1
Entertainment & Media market/th pop. 15-69…………….
71.8

Printing & other media, % manufacturing…...................
1.2
Creative goods exports, % total trade………………………..
1.8

23
26
19
5
47 ○
30

7.3
7.3.1
7.3.2
7.3.3
7.3.4


62.5
Online creativity………………………………………..……….…….

43.2
Generic top-level domains (TLDs)/th pop. 15-69……….

70.9Country-code TLDs/th pop. 15-69…………………..………….

106.6
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
64.2

3 ● ◆
17
8
3 ● ◆
8

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
328

The Global Innovation Index 2019

SWITZERLAND

GII 2019 rank

1

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

1

2

High

EUR

8.5

551.4

64,649.1

1

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
67.5

INSTITUTIONS………………………………….…….…..
89.1

12

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
95.8

94.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 96.4

2 ● ◆
4
2 ● ◆

1.2
1.2.1
1.2.2
1.2.3


95.9
Regulatory environment……………………………..………..

92.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
97.4

10.1
Cost of redundancy dismissal, salary weeks…………..

6
7
4
31

1.3
1.3.1
1.3.2


75.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
88.4

Ease of resolving insolvency*……………………………….…. 62.7

◇44
62 ○ ◇
43
◇


61.9
HUMAN CAPITAL & RESEARCH………………...

7

◆

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


58.8
Education…………………………………………………………..……

5.1
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 24.5
School life expectancy, years……………….…………….……. 16.2

PISA scales in reading, maths, & science…………......…
506.3
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
9.8

30
44 ○
27
31
13
27

2.2
2.2.1
2.2.2
2.2.3


49.2
Tertiary education……………………………………….……..….
🕘🕘
57.9
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….…. 24.5
Tertiary inbound mobility, %.......................................…. 17.6

1749 ○
32
7

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
77.9
🕘🕘Researchers, FTE/mn pop……………………………..…...……
5,257.4
🕘🕘Gross expenditure on R&D, % GDP………….………..……
3.4

92.6
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*…………… 81.6

◆
4
11
4
3 ●
4

68.2
INFRASTRUCTURE……………………………….......

3 ● ◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 86.5

ICT access*………………………………………………………….…….
87.1

ICT use*…………………………….....................................…….
89.7

84.7
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
84.3

19
10
2 ● ◆
35
41
◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
47.6
 …………………..…….7,096.9
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 86.0
Gross capital formation, % GDP………………………….…….
24.0

28
30
13
55 ○

3.3
3.3.1
3.3.2
3.3.3


70.5
Ecological sustainability………………………………………..

19.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 87.4

ISO 14001 environmental certificates/bn PPP$ GDP.. 5.5

3 ● ◆
6 ◆
1 ● ◆
21



MARKET SOPHISTICATION..………….…………… 68.4

7

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
72.8
Ease of getting credit*…………………………………..…………..
60.0
🕘🕘Domestic credit to private sector, % GDP…………...…… 175.3

Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 59.9
Ease of protecting minority investors*…………..………….
50.0

Market capitalization, % GDP………………………………...….
227.3
Venture capital deals/bn PPP$ GDP……………….……....
0.2

21
93 ○ ◇
1 ● ◆
10

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
72.6
Applied tariff rate, weighted avg., %………………………….
1.7
Intensity of local competition†…………………………………… 75.5
Domestic market scale, bn PPP$……………………………… 551.4

26
20
23
36



9
66 ○
4◆
n/a

2 ● ◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


3 ● ◆
Knowledge workers…………………………………………….…..
77.4

3 ● ◆
Knowledge-intensive employment, %...........................
52.9
Firms offering formal training, % firms………………………… n/a n/a🕘🕘
5
GERD performed by business, % GDP…………………..…… 2.4
🕘🕘
GERD financed by business, %……………………………........
63.5 10
18.5 28
Females employed w/advanced degrees, %……………..

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


63.0
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
79.1
State of cluster development†.……..………..………………….. 74.8
🕘🕘
GERD financed by abroad, %......................................... 10.2
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP……………………..
9.6

3 ● ◆
3 ● ◆
3 ● ◆
41 ○
13
4
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
62.2

3.1
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.1

ICT services imports, % total trade…………..………………... 4.2

FDI net inflows, % GDP…………………………….………………….
10.6
🕘🕘
Research talent, % in business enterprise……..…………..
50.1

3 ● ◆
6◆
90 ○
1 ● ◆
1325

 70.3KNOWLEDGE & TECHNOLOGY OUTPUTS....

1 ● ◆



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 84.7

16.5
Patents by origin/bn PPP$ GDP……………….…………..….…

8.3
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 34.1
Citable documents H-index…………………….……….……..….
66.6

1 ● ◆5◆
1 ● ◆
n/a
3 ● ◆
9

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


57.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.8
New businesses/th pop. 15-64………………….…....………….
4.3
Computer software spending, % GDP…………..…………… 0.8

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 19.7
High- & medium-high-tech manufactures, %………………
0.6

4
◆
66 ○
30
3 ● ◆
17◆
3 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


68.6
Knowledge diffusion……………………………………..…..…….

5.2
Intellectual property receipts, % total trade……………….

7.2
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.3

FDI net outflows, % GDP…………………………….…………....... 9.6

3 ● ◆
1 ● ◆
24
27
1 ● ◆


56.6
CREATIVE OUTPUTS…….…………………….…………

1 ● ◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
62.2
Trademarks by origin/bn PPP$ GDP…………..……….….….
80.3
Industrial designs by origin/bn PPP$ GDP…………..…….. 8.2

ICTs & business model creation†………………………....……. 84.7

ICTs & organizational model creation†……………………....
77.4

7
26
14
1 ● ◆
9

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
45.5
Cultural & creative services exports, % total trade…....
0.8
National feature films/mn pop. 15-69………………….………
19.4
Entertainment & Media market/th pop. 15-69……………. 94.1
🕘🕘Printing & other media, % manufacturing…...................
1.2
Creative goods exports, % total trade………………………..
3.8

4
◆
37
5
◆
2 ● ◆
50 ○
15

7.3
7.3.1
7.3.2
7.3.3
7.3.4


56.4
Online creativity………………………………………..……….…….

59.2
Generic top-level domains (TLDs)/th pop. 15-69……….

100.0Country-code TLDs/th pop. 15-69…………………..………….

47.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
34.4

7
13
1 ● ◆
27
15

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

329

TAJIKISTANGII 2019 rank

100

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

83

107

Low

CSA

9.1

30.5

3,415.8

101

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
46.0 122
BUSINESS SOPHISTICATION..……….……………
22.2 114

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
31.6

56.1
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 19.4

125 ○
105
124

1.2
1.2.1
1.2.2
1.2.3


45.6
Regulatory environment……………………………..………..

13.5
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
10.5

21.7
Cost of redundancy dismissal, salary weeks…………..

◇
116
125 ○
126 ○ ◇
92

1.3
1.3.1
1.3.2


60.8
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
90.7
Ease of resolving insolvency*……………………………….…. 30.9

102
51 ●
116


24.0
HUMAN CAPITAL & RESEARCH………………...

87

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


46.3
Education…………………………………………………………..……

5.2
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a🕘🕘
School life expectancy, years……………….…………….……. 11.2

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......….
15.4

[69]
40 ●
n/a
97
n/a
70
◆

2.2
2.2.1
2.2.2
2.2.3


24.9
Tertiary education……………………………………….……..….

30.9
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
22.0
Tertiary inbound mobility, %.......................................
….
0.8

80
83
49
91

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

110
n/a
103
43 ○ ◇78 ○ ◇

0.7
n/a
0.1
0.0
0.0

◆

◆
◆


29.8 115
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 36.4 [112]
ICT access*………………………………………………………….…….
n/a n/a
ICT use*…………………………….....................................…….
n/a n/a
34.0 115
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
38.8 112

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
23.4 109
 …………………..…….
Electricity output, GWh/mn pop……
1,971.6
77

Logistics performance*…………………………………………….. 12.9 116Gross capital formation, % GDP………………………….……. 22.8 67

3.3
3.3.1
3.3.2
3.3.3


29.5
Ecological sustainability………………………………………..

8.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
47.9
ISO 14001 environmental certificates/bn PPP$ GDP..  0.5

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
24.4 98🕘🕘
Knowledge-intensive employment, %...........................
◆16.1 87Firms offering formal training, % firms…………………………
33.1 44 ●
GERD performed by business, % GDP…………………..…… n/a n/a🕘🕘
GERD financed by business, %……………………………........
1.6 89🕘🕘Females employed w/advanced degrees, %……………..
4.0 93
◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.2 104
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
46.5 47 ●
State of cluster development†.……..………..…………………..
40.2 93🕘🕘
GERD financed by abroad, %.........................................
◇
0.2 98JV-strategic alliance deals/bn PPP$ GDP…………………..
n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
23.9 [107]
0.0 119 ○Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
n/a n/a◇
0.2 122
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.5 49 ●
Research talent, % in business enterprise……..…………..
n/a n/a 21.4 68
KNOWLEDGE & TECHNOLOGY OUTPUTS....

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 20.0 45 ● ◆🕘🕘
0.1 113
Patents by origin/bn PPP$ GDP……………….…………..….…
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……
🕘🕘
Utility models by origin/bn PPP$ GDP……………...…..……
3.7
5 ● ◆

Scientific & technical articles/bn PPP$ GDP….…..…..….
1.6 119◇Citable documents H-index…………………….……….……..…. 0.0 128 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


31.2 89
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
5.1
6 ● ◆
New businesses/th pop. 15-64………………….…....………….
0.2 94Computer software spending, % GDP…………..……………
0.1 93

ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.1 128 ○ ◇🕘🕘High- & medium-high-tech manufactures, %……………… 0.0 102 ○ ◇

6.3
6.3.1
6.3.2
6.3.3
6.3.4


13.0
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0Intellectual property receipts, % total trade……………….
n/aHigh-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.3

FDI net outflows, % GDP…………………………….………….......
1.7

◆

99
73
102
85


MARKET SOPHISTICATION..………….…………… 43.7 86

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
15.4 121Ease of getting credit*…………………………………..…………..
40.0 104Domestic credit to private sector, % GDP…………...……
13.7 121
Microfinance gross loans, % GDP……………………….…….
51
0.1

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 66.7 [12]
Ease of protecting minority investors*…………..………….
66.7 35 ● ◆Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
48.9 1 1 1
Applied tariff rate, weighted avg., %………………………….
5.0 85
†Intensity of local competition …………………………………… 61.2 103
Domestic market scale, bn PPP$……………………………… 30.5 114



85
83
n/a
113
37 ●

18.1 103
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
27.6 112🕘🕘Trademarks by origin/bn PPP$ GDP…………..……….….….
6.1 112🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.0 115 ○
ICTs & business model creation†………………………....…….
50.7 102

ICTs & organizational model creation†……………………....
44.4 97

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
16.5
Cultural & creative services exports, % total trade…....
0.0🕘🕘National feature films/mn pop. 15-69………………….………
1.8
Entertainment & Media market/th pop. 15-69…………….
n/a🕘🕘
Printing & other media, % manufacturing…...................
1.5
Creative goods exports, % total trade………………………..
n/a

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.7 105
Online creativity………………………………………..……….…….

0.1 125 ○Generic top-level domains (TLDs)/th pop. 15-69……….

0.3 103
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
2.6 96
Wikipedia edits/mn pop. 15-69……………………………………
◆
Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/a

[65]
102
70
◆
n/a
30 ●n/a◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
330

The Global Innovation Index 2019

◆

THAILAND

GII 2019 rank

43

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

43

47

Upper middle

SEAO

69.2

1,323.2

19,476.5

44

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
65.8

57

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
60.6

70.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 55.9

50
61
49

1.2
1.2.1
1.2.2
1.2.3


52.0
Regulatory environment……………………………..………..

45.7
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
47.5

36.0
Cost of redundancy dismissal, salary weeks…………..

105 ○
65
61
120 ○ ◇

1.3
1.3.1
1.3.2


84.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
92.7
Ease of resolving insolvency*……………………………….…. 76.6

20 ● ◆
36
22
◆


34.7
HUMAN CAPITAL & RESEARCH………………...

52

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


40.6
Education…………………………………………………………..……
🕘🕘
4.1
Expenditure on education, % GDP………………….…….….
🕘🕘 18.0
Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….……. 15.4

PISA scales in reading, maths, & science…………......…
415.3
Pupil-teacher ratio, secondary…………………………......….
24.2

81
74
62
40
56 ○
97 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


37.1
Tertiary education……………………………………….……..….
🕘🕘
49.3
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
27.9
Tertiary inbound mobility, %.......................................
….
1.3

45
57
20
83

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
26.4
🕘🕘Researchers, FTE/mn pop……………………………..…...……
1,210.4
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.8

46.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
28.0

41
48
46
35
39


43.6
INFRASTRUCTURE……………………………….......

77

Information & communication technologies(ICTs) 60.8

ICT access*………………………………………………………….…….
56.8

ICT use*…………………………….....................................…….
57.2

63.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
65.2

77
77
61
85
80

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 37.3
 …………………..…….
Electricity output, GWh/mn pop……
2,778.4
Logistics performance*……………………………………………..
63.0

Gross capital formation, % GDP………………………….……. 23.4

54
65
31
61

3.3
3.3.1
3.3.2
3.3.3


32.7
Ecological sustainability………………………………………..

7.6
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
49.9
ISO 14001 environmental certificates/bn PPP$ GDP..  2.8

85
81
98
36

3.1
3.1.1
3.1.2
3.1.3
3.1.4





◆
◆

60

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
32.2
🕘🕘Knowledge-intensive employment, %...........................
14.3
Firms offering formal training, % firms………………………… 18.0
🕘🕘
GERD performed by business, % GDP…………………..…… 0.6

GERD financed by business, %……………………………........
75.2
🕘🕘Females employed w/advanced degrees, %……………..
9.5

80
90
◇
79 ○ ◇35
4 ● ◆
69

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


21.0
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
52.2
State of cluster development†.……..………..…………………..
48.8

GERD financed by abroad, %.........................................
0.9
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.1

81
◆
36
53
92 ○
53
58

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


◆
Knowledge absorption……………………………………..……..
43.8 30

1.6 20 ● ◆Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
15.3 12 ● ◆

0.2 123 ○ ◇
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.6 95🕘🕘
17◆
Research talent, % in business enterprise……..…………..
56.8

 31.3 38
KNOWLEDGE & TECHNOLOGY OUTPUTS....

◇

32

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
46.6
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
143.8
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.0

42
◆
40
12 ● ◆80 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 48.9
Ease of protecting minority investors*…………..………….
75.0

Market capitalization, % GDP………………………………...….
104.2
Venture capital deals/bn PPP$ GDP……………….……....
0.0

41
14 ● ◆
10 ● ◆
71 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
74.0
🕘🕘
Applied tariff rate, weighted avg., %………………………….
3.5
†Intensity of local competition …………………………………… 74.2
Domestic market scale, bn PPP$………………………………1,323.2

22
◆
68
34
19 ●

◆



◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 16.7

0.8
Patents by origin/bn PPP$ GDP……………….…………..….…

0.1
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
1.9
Scientific & technical articles/bn PPP$ GDP….…..…..…. 4.5
Citable documents H-index…………………….……….……..….
20.2

54
69
69
13
86
38

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


43.6
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.9
New businesses/th pop. 15-64………………….…....………….
1.0
Computer software spending, % GDP…………..……………
0.2
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 7.4
🕘🕘High- & medium-high-tech manufactures, %………………
0.4

34
14 ● ◆
71
61
42
◆
18

6.3
6.3.1
6.3.2
6.3.3
6.3.4


33.8
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….
🕘🕘
15.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.2

FDI net outflows, % GDP…………………………….………….......
2.9

◆
25
72
8 ● ◆
119 ○
25
◆


30.0
CREATIVE OUTPUTS…….…………………….…………

54

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
41.5
Trademarks by origin/bn PPP$ GDP…………..……….….….
25.2
Industrial designs by origin/bn PPP$ GDP…………..……..
3.0

ICTs & business model creation†………………………....…….
67.3

ICTs & organizational model creation†……………………....
60.3

61
80
42
39
43

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
33.5
Cultural & creative services exports, % total trade…....
0.0🕘🕘National feature films/mn pop. 15-69………………….………
1.0

Entertainment & Media market/th pop. 15-69…………….
5.9
🕘🕘
Printing & other media, % manufacturing…...................
0.8
🕘🕘Creative goods exports, % total trade………………………..
8.7

18 ● ◆
117 ○
83
44
76
1 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.5
Online creativity………………………………………..……….…….

5.4
Generic top-level domains (TLDs)/th pop. 15-69……….

0.4
Country-code TLDs/th pop. 15-69…………………..………….

5.6
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
4.4

74
52
99
80
51

◆

MARKET SOPHISTICATION..………….…………… 56.5




BUSINESS SOPHISTICATION..……….……………
32.3

◆
◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

331

TOGO

GII 2019 rank

126

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

128

121

Low

SSF

8.0

13.9

1,745.6

n/aScore/Value Rank

INSTITUTIONS………………………………….…….…..

53.4

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

97

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
34.5

64.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
19.3

121
79
125 ○

1.2
1.2.1
1.2.2
1.2.3


58.1
Regulatory environment……………………………..………..

20.8
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
27.5

13.1
Cost of redundancy dismissal, salary weeks…………..

87
115
108
49 ●

1.3
1.3.1
1.3.2


67.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
88.7
Ease of resolving insolvency*……………………………….….
46.7

71
60 ●
78◆
16.0 108
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


36.9
Education…………………………………………………………..……

5.1
Expenditure on education, % GDP………………….…….….
🕘🕘 15.9
Government funding/pupil, secondary, % GDP/cap…
School life expectancy, years……………….…………….…….
12.6
PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......…. 26.2

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
1.5
Researchers, FTE/mn pop……………………………..…...……
38.3
🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.3

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

95
46 ●
78
◆
86
n/a
99

9.6 [111]12.9 102n/a n/an/a n/a99
97
82
43 ○ ◇78 ○ ◇
29.8 114
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  41.3 102

ICT access*………………………………………………………….…….
33.5 113
ICT use*…………………………….....................................…….
21.6 104
55.6 98
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
54.5 98

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
28.9
 …………………..……. 30.5
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 18.0
Gross capital formation, % GDP………………………….…….
28.2

87
120 ○
108
28 ●

3.3
3.3.1
3.3.2
3.3.3


19.2
Ecological sustainability………………………………………..

2.9
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
41.8
ISO 14001 environmental certificates/bn PPP$ GDP..  0.9

127 ○
117 ○
118
66 ◆

◆



MARKET SOPHISTICATION..………….…………… 30.6 126 ○
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
31.2
Ease of getting credit*…………………………………..…………..
30.0
Domestic credit to private sector, % GDP…………...……
39.7

Microfinance gross loans, % GDP……………………….…….
2.7

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 40.0
Ease of protecting minority investors*…………..………….
40.0
Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
20.7 129 ○ ◇Applied tariff rate, weighted avg., %………………………….
13.4 126 ○ ◇Intensity of local competition†……………………………………
n/a n/a
Domestic market scale, bn PPP$………………………………
13.9 127 ○ ◇



88
115
83 ◆
10 ● ◆
[72]
114
n/a
n/a

19.0 [124]



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5

Knowledge workers…………………………………………….….. 22.2 [103]🕘🕘Knowledge-intensive employment, %...........................
7.7 104Firms offering formal training, % firms…………………………
33.7 43
GERD performed by business, % GDP…………………..……
n/a n/a
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %…………….. 2.5 98

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


11.3 [127]Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
n/a n/a
State of cluster development†.……..………..…………………..
n/a n/a🕘🕘
GERD financed by abroad, %.........................................
5.5 62JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 51 ●
Patent families 2+ offices/bn PPP$ GDP……………………..
n/a n/a

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
23.7 109
0.0 108
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
4.3 115
0.8 87
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.7 60 ●
Research talent, % in business enterprise……..…………..
n/a n/a 10.1 119
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

2.5 1190.2 104
0.0 99 ○ ◇n/a n/a
3.8 94
0.7 126 ○ ◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
🕘🕘New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……

High- & medium-high-tech manufactures, %………………

3.5 [127]n/a n/a0.3 93
0.1 94
1.3 102n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


24.4 41 ● ◆
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0 104
Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 0.0 123 ○ ◇
ICT services exports, % total trade……………..……..………
2.0 55 ●
FDI net outflows, % GDP…………………………….………….......
6.9
9 ● ◆


4.5 [128]
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..

Trademarks by origin/bn PPP$ GDP…………..……….….….

Industrial designs by origin/bn PPP$ GDP…………..……..

ICTs & business model creation†………………………....…….

ICTs & organizational model creation†……………………....

3.8 [128]11.4 102
0.8 78n/a n/an/a n/a

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

9.9 [86]
1.5 16 ● ◆
0.7 92n/a n/an/a n/a0.0 112

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.3 118
Online creativity………………………………………..……….…….

0.6 104
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 0.1 120
🕘🕘
0.2 118
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a n/aNOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
332

The Global Innovation Index 2019

◆

TRINIDAD AND TOBAGO

GII 2019 rank

91

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

99

88

High

LCN

1.4

44.3

32,253.8

96

Score/Value Rank

INSTITUTIONS………………………………….…….…..

63.4

63

Score/Value Rank

◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
59.8

73.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 52.8

52 ● ◇
50 ● ◇
54 ● ◇

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

62.0
42.6
43.5
20.5

75
68
67
84

1.3
1.3.1
1.3.2


68.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
88.6

Ease of resolving insolvency*……………………………….….
48.5

69
61
69

◇
◇
◇


20.5 [94]
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


40.4
Education…………………………………………………………..……

n/a
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. n/a
PISA scales in reading, maths, & science…………......…
423.0

Pupil-teacher ratio, secondary…………………………......….
n/a

[84]
n/a
n/a
n/a
50
n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….

Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

n/a
n/a
n/a
n/a

[n/a]
n/a
n/a
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.6
n/a
0.1
0.0
0.0

◇
114
n/a
108 ○ ◇43 ○ ◇78 ○ ◇

92

Information & communication technologies(ICTs)  62.7

ICT access*………………………………………………………….…….
74.6

ICT use*…………………………….....................................…….
54.4

63.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

57.9

73 ◇
45 ●
65 ◇
85
◇
93
◇

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 22.1
 …………………..…….
Electricity output, GWh/mn pop……
7,819.0
Logistics performance*……………………………………………..
16.5

Gross capital formation, % GDP………………………….……. n/a

112 ◇
23 ●
111
◇
n/a

3.3
3.3.1
3.3.2
3.3.3


27.7 107 ◇
Ecological sustainability………………………………………..

2.2 121 ○ ◇GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
67.4
34 ●
ISO 14001 environmental certificates/bn PPP$ GDP..  0.5 84 ◇

MARKET SOPHISTICATION..………….…………… 45.6

77

◇

◇



4.1
4.1.1
4.1.2
4.1.3

Credit……………………………………………………….……………… 27.5 100◇
Ease of getting credit*…………………………………..…………..
65.0 54Domestic credit to private sector, % GDP…………...……
81
40.5
◇
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.0 77 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 61.7
Ease of protecting minority investors*…………..………….
61.7

Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
47.5 112
🕘🕘Applied tariff rate, weighted avg., %………………………….
8.6 106

Intensity of local competition†……………………………………
66.9 74
Domestic market scale, bn PPP$………………………………
44.3 99



26.2

92

[20]
54 ●
n/a
n/a

◇

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
◇
34.7 70🕘🕘Knowledge-intensive employment, %...........................
29.9 44 ●🕘🕘
Firms offering formal training, % firms…………………………
28.0 56🕘🕘GERD performed by business, % GDP…………………..……
0.0 89 ○ ◇
GERD financed by business, %……………………………........ n/a n/a🕘🕘Females employed w/advanced degrees, %…………….. 12.8 53 ●

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


◇
20.3 85
Innovation linkages…………..……………………………………..
◇
University/industry research collaboration†………………..
29.7 107◇State of cluster development†.……..………..…………………..
43.3 79
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0 76

Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


◇
Knowledge absorption……………………………………..……..
23.5 110
0.6 59Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
6.3 89◇
0.5 108
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
-0.4 123 ○
Research talent, % in business enterprise……..…………..
n/a n/a 14.9 103
KNOWLEDGE & TECHNOLOGY OUTPUTS....

37.5
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4


BUSINESS SOPHISTICATION..……….……………

◇



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

◇
Knowledge creation………………………………………........... 2.5 118
🕘🕘
0.1 118
Patents by origin/bn PPP$ GDP……………….…………..….…

0.1 62
PCT patents by origin/bn PPP$ GDP…………..….…….……
🕘🕘
Utility models by origin/bn PPP$ GDP……………...…..……
0.0 63 ○ ◇Scientific & technical articles/bn PPP$ GDP….…..…..…. 2.7 106◇
Citable documents H-index…………………….……….……..….
4.0 102
◇

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


35.2 [71]Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-2.0 109 ○ ◇
New businesses/th pop. 15-64………………….…....………….
n/a n/aComputer software spending, % GDP…………..……………
n/a n/a
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 2.5
81◇High- & medium-high-tech manufactures, %……………… n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


6.9 124 ○ ◇Knowledge diffusion……………………………………..…..…….

0.0 84
Intellectual property receipts, % total trade……………….
🕘🕘
0.0 119
High-tech net exports, % total trade……………….….…......
◇
ICT services exports, % total trade……………..……..………
0.1 121◇
FDI net outflows, % GDP…………………………….………….......
0.4 70
20.2
CREATIVE OUTPUTS…….…………………….…………

95

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
36.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
13.9
Industrial designs by origin/bn PPP$ GDP…………..……..
6.9

ICTs & business model creation†………………………....…….
52.7

ICTs & organizational model creation†……………………....
49.8

91
◇
97
◇
19 ●
95
◇
82
◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….
🕘🕘
Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


3.7
Online creativity………………………………………..……….…….

4.3
Generic top-level domains (TLDs)/th pop. 15-69……….

1.4
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
8.0
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

4.9 [102]
0.0 101n/a n/an/a n/a0.7 83
0.1 92

◇

◇

72
◇
58 ●
71
◇
67
◇
n/a

◇
◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II333

TUNISIA

GII 2019 rank

70

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

65

74

Lower middle

NAWA

11.7

144.2

12,371.7

66

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

61.1

73

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
51.6

64.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 44.9

76
79
75

1.2
1.2.1
1.2.2
1.2.3


59.4
Regulatory environment……………………………..………..

30.9
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
48.3

21.6
Cost of redundancy dismissal, salary weeks…………..

83
98
58
90

1.3
1.3.1
1.3.2


72.2
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
90.2

Ease of resolving insolvency*……………………………….…. 54.2

56
53
62


44.4
HUMAN CAPITAL & RESEARCH………………...

32 ● ◆

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


66.9
Education…………………………………………………………..……

6.6
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 52.8
School life expectancy, years……………….…………….……. 15.1

PISA scales in reading, maths, & science…………......…
371.4
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
13.6

8 ● ◆
13 ● ◆
1 ● ◆
◆
50
67 ○
60

2.2
2.2.1
2.2.2
2.2.3


57.3
Tertiary education……………………………………….……..….

32.1
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
44.1
Tertiary inbound mobility, %.......................................….
2.3

7 ● ◆
81
2 ● ◆
71

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
9.1
🕘🕘Researchers, FTE/mn pop……………………………..…...……
1,965.0🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.6

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

60
41
◆
53
◆
43 ○ ◇78 ○ ◇
44.2
INFRASTRUCTURE……………………………….......

74

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 65.4

ICT access*………………………………………………………….…….
57.1

ICT use*…………………………….....................................…….
44.0

80.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
79.8

69 ◆
76
80
44 ● ◆
53

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
26.2
 …………………..…….
Electricity output, GWh/mn pop……
1,737.5
Logistics performance*…………………………………………….. 23.7
Gross capital formation, % GDP………………………….…….
23.1

96
83
98
65

3.3
3.3.1
3.3.2
3.3.3


41.2
Ecological sustainability………………………………………..

10.9
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
62.4
ISO 14001 environmental certificates/bn PPP$ GDP..
1.6

51
43
51
55


BUSINESS SOPHISTICATION..……….……………
21.3 115 ○ ◇

◆

◆
◆

◆

◆
◆
◆



MARKET SOPHISTICATION..………….…………… 39.6 104
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
33.0
Ease of getting credit*…………………………………..…………..
50.0
Domestic credit to private sector, % GDP…………...…… 86.2

Microfinance gross loans, % GDP……………………….……. 0.5

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 33.2 107 ○Ease of protecting minority investors*…………..………….
56.7 79Market capitalization, % GDP………………………………...….
21.0 60
Venture capital deals/bn PPP$ GDP……………….……....
0.0 28
◆

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
52.4 99
🕘🕘Applied tariff rate, weighted avg., %………………………….
9.4 109 ○
Intensity of local competition†…………………………………… 65.0 82
Domestic market scale, bn PPP$……………………………… 144.2 72

76
87
33 ● ◆
30



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
26.7
🕘🕘
Knowledge-intensive employment, %...........................
21.0

Firms offering formal training, % firms………………………… 28.9
🕘🕘
GERD performed by business, % GDP…………………..…… 0.1
🕘🕘
GERD financed by business, %……………………………........
18.9
🕘🕘Females employed w/advanced degrees, %……………..
6.7

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


16.0 115 ○Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
38.2 80State of cluster development†.……..………..…………………..
37.0 100🕘🕘
GERD financed by abroad, %.........................................
3.9 66
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 105 ○
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 87

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
21.3 118 ○
0.1 100 ○Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.7 48
0.4 110 ○ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.9 82
🕘🕘Research talent, % in business enterprise……..………….. 4.0 73 ○

90
72
52
59
68
82

 23.0 60
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 18.7

1.2
Patents by origin/bn PPP$ GDP……………….…………..….…

0.0
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..….
23.8
Citable documents H-index…………………….……….……..….
9.6

49
56
74
n/a
15 ● ◆
71

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


34.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.4
🕘🕘New businesses/th pop. 15-64………………….…....………….
1.7
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 7.6
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

76
52
57
34 ●
40 ● ◆
65

6.3
6.3.1
6.3.2
6.3.3
6.3.4


15.8
Knowledge diffusion……………………………………..…..…….

0.1Intellectual property receipts, % total trade……………….

3.7
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.5

FDI net outflows, % GDP…………………………….………….......
0.3

75
51
39 ●
69
85


24.1
CREATIVE OUTPUTS…….…………………….…………

75

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
42.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
n/aIndustrial designs by origin/bn PPP$ GDP…………..……..
1.1
†
ICTs & business model creation ………………………....……. 59.6

ICTs & organizational model creation†…………………….... 42.7

59
n/a
63
67
104

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
10.5 82

Cultural & creative services exports, % total trade…....
0.0 109 ○🕘🕘National feature films/mn pop. 15-69………………….………
1.4 74Entertainment & Media market/th pop. 15-69…………….
0.9 57 ○
Printing & other media, % manufacturing…...................
n/a n/a
Creative goods exports, % total trade………………………..
2.0 28 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

1.6
2.7
1.4
2.9
0.2

93
70
72
94
79

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
334

The Global Innovation Index 2019

◆

TURKEY

GII 2019 rank

49

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

49

56

Upper middle

NAWA

81.9

2,314.4

27,956.1

50

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
57.4

85

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
53.8

64.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 48.2

69
79
67

1.2
1.2.1
1.2.2
1.2.3


Regulatory environment……………………………..………..

Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…

Cost of redundancy dismissal, salary weeks…………..

102 ○
67
76
115 ○

1.3
1.3.1
1.3.2


64.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
88.2

Ease of resolving insolvency*……………………………….…. 40.7

82
63
96


36.3
HUMAN CAPITAL & RESEARCH………………...

46

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


44.0
Education…………………………………………………………..……

4.3
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… 11.5
School life expectancy, years……………….…………….……. 17.7

PISA scales in reading, maths, & science…………......…
424.8
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
18.5

73
70
90 ○
14 ● ◆
49
81

2.2
2.2.1
2.2.2
2.2.3


37.3
Tertiary education……………………………………….……..….
🕘🕘
103.7
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….
20.2

Tertiary inbound mobility, %.......................................
….
1.3

43
3 ● ◆
65
82

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
27.7
……………………….....…...… 1,385.8
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……

◆

1.0

48.5
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
24.8

39
44
37
31
44


52.2
INFRASTRUCTURE……………………………….......

41

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  73.3

ICT access*………………………………………………………….…….
65.1

ICT use*…………………………….....................................…….
53.3

88.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
86.0

49
69
68
27
37

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
43.0
 …………………..…….
Electricity output, GWh/mn pop……
3,761.1
Logistics performance*…………………………………………….. 50.6
Gross capital formation, % GDP………………………….…….
30.7

38 ◆
54
46 ◆
20 ●

3.3
3.3.1
3.3.2
3.3.3


40.4
Ecological sustainability………………………………………..

13.3
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
53.0
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.9

52
19 ●
88
67

54.1
42.9
39.8
29.8

◆

◆



MARKET SOPHISTICATION..………….…………… 50.8 52
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
36.0
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...…… 70.9
🕘🕘
Microfinance gross loans, % GDP……………………….……. 0.0

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 37.9
Ease of protecting minority investors*…………..………….
71.7
Market capitalization, % GDP………………………………...….
22.9
Venture capital deals/bn PPP$ GDP……………….……....
0.0

87
24
56 ○
78 ○ ◇

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
78.5
Applied tariff rate, weighted avg., %………………………….
3.5
Intensity of local competition†…………………………………… 80.5
Domestic market scale, bn PPP$……………..……………… 2,314.4

15 ● ◆67
6 ● ◆
13 ● ◆



66
29
44
78 ○


BUSINESS SOPHISTICATION..……….……………
29.5

71

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
34.6

Knowledge-intensive employment, %...........................
21.0

Firms offering formal training, % firms………………………… 28.4

GERD performed by business, % GDP…………………..…… 0.5

GERD financed by business, %……………………………........
49.4
Females employed w/advanced degrees, %……………..
8.9

72
71
53
37
27
72

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.5
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
37.0

†State of cluster development .……..………..………………….. 44.4

GERD financed by abroad, %......................................... 3.5

JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP……………………..
0.2

97
88
76
68
95 ○
43

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
35.4 57
0.3 74
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
9.9 33
0.2 124 ○ ◇
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.6 89◆Research talent, % in business enterprise……..………….. 55.7 19

KNOWLEDGE & TECHNOLOGY OUTPUTS... 23.0 59


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 22.2

4.2
Patents by origin/bn PPP$ GDP……………….…………..….…

0.7
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… 1.5
Scientific & technical articles/bn PPP$ GDP….…..…..…. 7.8
Citable documents H-index…………………….……….……..….
26.5

38
27
32
17
60
35

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


38.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.7
New businesses/th pop. 15-64………………….…....………….
1.2
Computer software spending, % GDP…………..…………… 0.5

ISO 9001 quality certificates/bn PPP$ GDP…………..……
2.8
High- & medium-high-tech manufactures, %………………
0.3

57
46
66
20 ● ◆
80
44

6.3
6.3.1
6.3.2
6.3.3
6.3.4


8.8
Knowledge diffusion……………………………………..…..…….

0.0Intellectual property receipts, % total trade……………….

1.4
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.1

FDI net outflows, % GDP…………………………….………….......
0.4

112 ○
96 ○
63
122 ○
73


34.2
CREATIVE OUTPUTS…….…………………….…………

40

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
55.1
Trademarks by origin/bn PPP$ GDP…………..……….….….
98.5
Industrial designs by origin/bn PPP$ GDP…………..……..
18.0

ICTs & business model creation†………………………....…….
58.2

ICTs & organizational model creation†…………………….... 44.2

20 ● ◆13 ●1 ● ◆
72
98 ○

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
17.8
Cultural & creative services exports, % total trade…....
0.5
National feature films/mn pop. 15-69………………….………
2.6
Entertainment & Media market/th pop. 15-69…………….
5.8

Printing & other media, % manufacturing…...................
0.9
Creative goods exports, % total trade……………………….. 2.9

60
46
59
46
71
21 ●

7.3
7.3.1
7.3.2
7.3.3
7.3.4


8.9
Online creativity………………………………………..……….…….

11.7
Generic top-level domains (TLDs)/th pop. 15-69……….

1.9Country-code TLDs/th pop. 15-69…………………..………….

4.4
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
19.0

55
36
68
85
23

◆
◆

◆

◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

335

UGANDAGII 2019 rank

102

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

107

96

Low

SSF

44.3

96.7

2,497.6

103

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
27.3

INSTITUTIONS………………………………….…….…..
55.2

91

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
41.5

59.6
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 32.4

99
98
100

1.2
1.2.1
1.2.2
1.2.3


68.1
Regulatory environment……………………………..………..

36.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
38.5

8.7
Cost of redundancy dismissal, salary weeks…………..

61 ● ◆85◆
79
21 ● ◆

1.3
1.3.1
1.3.2


56.1
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
72.3

Ease of resolving insolvency*……………………………….…. 39.9

114
118
98

◇


13.4 114
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


18.1 [125]Education…………………………………………………………..……

2.6 113 ○ ◇Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a n/a
School life expectancy, years……………….…………….……. n/a n/a
PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
n/a n/a

2.2
2.2.1
2.2.2
2.2.3


21.2
Tertiary education……………………………………….……..….
🕘🕘
4.6
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
n/a🕘🕘Tertiary inbound mobility, %.......................................
…. 10.7

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.9 106🕘🕘Researchers, FTE/mn pop……………………………..…...……
26.5 101 ○🕘🕘Gross expenditure on R&D, % GDP………….………..……
0.2 92
0.0
Global R&D companies, avg. exp. top 3, mn US$……
43 ○ ◇
QS university ranking, average score top 3*……………
0.0
78 ○ ◇
36.6
INFRASTRUCTURE……………………………….......

91
119 ○
n/a
19 ● ◆

96

◆

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 40.5 105

ICT access*………………………………………………………….…….
26.9 120 ○
ICT use*…………………………….....................................…….
15.9 113
56.9 92
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
62.4 84
◆

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
38.9
 …………………..…….
n/aElectricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 23.9
Gross capital formation, % GDP………………………….……. 27.2

48 ●
n/a
96
33 ●

3.3
3.3.1
3.3.2
3.3.3


30.2
Ecological sustainability………………………………………..

n/a
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
44.3
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

93
n/a
111
101



MARKET SOPHISTICATION..………….…………… 45.8

74

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
32.6
Ease of getting credit*…………………………………..…………..
60.0
Domestic credit to private sector, % GDP…………...……
15.0
Microfinance gross loans, % GDP……………………….…….
1.9

80
66
116 ○
13 ●

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 50.0 [39]Ease of protecting minority investors*…………..………….
50.0 93Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
55.0
🕘🕘
Applied tariff rate, weighted avg., %………………………….
7.3
†Intensity of local competition …………………………………… 72.4
Domestic market scale, bn PPP$……………………………… 96.7

◆



82

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
19.0 109
Knowledge-intensive employment, %...........................
◆10.1 100Firms offering formal training, % firms…………………………
34.7 41 ●🕘🕘
GERD performed by business, % GDP…………………..…… 0.0 83◆🕘🕘
GERD financed by business, %……………………………........
3.4 84
Females employed w/advanced degrees, %……………..
4.6 91
◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


41.7
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
42.6
State of cluster development†.……..………..…………………..
43.1
🕘🕘GERD financed by abroad, %.........................................
52.4
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
21.2 119 ○ ◇
0.3 79Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.4 87

0.6 98
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.7 61 ●🕘🕘
Research talent, % in business enterprise……..…………..
4.0 7425 ● ◆
57 ●
80
1 ● ◆
83
93 ○ ◇ 13.6 108
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
🕘🕘
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


26.6 103
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.4 76
🕘🕘New businesses/th pop. 15-64………………….…....………….
0.7 79Computer software spending, % GDP…………..…………… 0.0 123 ○ISO 9001 quality certificates/bn PPP$ GDP…………..……
1.1 105
High- & medium-high-tech manufactures, %………………
n/a n/a

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.5 115
Knowledge diffusion……………………………………..…..…….

0.0 67
Intellectual property receipts, % total trade……………….

0.1 102
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.6 93

FDI net outflows, % GDP…………………………….………….......
0.0 114

6.8
0.2
0.0
n/a
5.1
9.5

83
99
95
n/a
80
72


17.5 106
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
32.6
Trademarks by origin/bn PPP$ GDP…………..……….….….
15.2
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a
†
ICTs & business model creation ………………………....……. 49.8

ICTs & organizational model creation†…………………….... 42.7

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.2
Online creativity………………………………………..……….…….

0.2
Generic top-level domains (TLDs)/th pop. 15-69……….

0.1
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
0.6
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

101
95
n/a
106
103

4.5 [104]
0.1 83n/a n/an/a n/an/a n/a0.5 62 ● ◆119 ○
115
119 ○
107
n/a

89
◆
99
44 ● ◆78

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
336

The Global Innovation Index 2019

◆

UKRAINE

GII 2019 rank

47

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

36

82

Lower middle

EUR

44.0

391.5

9,283.4

43

Score/Value Rank

INSTITUTIONS………………………………….…….…..

53.9

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

96

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
38.8

45.6
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
35.4

110 ○
125 ○ ◇
95

1.2
1.2.1
1.2.2
1.2.3


61.4
Regulatory environment……………………………..………..

33.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
27.6

13.0
Cost of redundancy dismissal, salary weeks…………..

78
94
107 ○
42

1.3
1.3.1
1.3.2


61.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
91.1

Ease of resolving insolvency*……………………………….….
31.7

99
48
115 ○ ◇

35.6
HUMAN CAPITAL & RESEARCH………………...

51

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


55.1
Education…………………………………………………………..……

5.0
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 25.7
🕘🕘
School life expectancy, years……………….…………….……. 15.0

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
7.2

43
◆
48
23
◆
52
n/a
3 ● ◆

2.2
2.2.1
2.2.2
2.2.3


40.6
Tertiary education……………………………………….……..….
🕘🕘
83.4
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
24.2
Tertiary inbound mobility, %.......................................
….
3.2

37
◆
14 ● ◆
33
62

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
11.2
Researchers, FTE/mn pop……………………………..…...……
1,119.5
Gross expenditure on R&D, % GDP………….………..……
0.4

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
22.0

54
50
◆
67
43 ○ ◇
46
◆


36.0
INFRASTRUCTURE……………………………….......

97

Information & communication technologies(ICTs) 58.0

ICT access*………………………………………………………….…….
66.5

ICT use*…………………………….....................................…….
39.9

56.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….

68.5

81
65
90
92
73

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 26.2
 …………………..…….
Electricity output, GWh/mn pop……
3,620.1
Logistics performance*……………………………………………..
35.9

Gross capital formation, % GDP………………………….……. 18.8

95
55
65
99

3.3
3.3.1
3.3.2
3.3.3


23.9 120 ○ ◇
Ecological sustainability………………………………………..

3.4 115 ○ ◇GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
52.9 89
ISO 14001 environmental certificates/bn PPP$ GDP..  0.6 80

3.1
3.1.1
3.1.2
3.1.3
3.1.4



◆

◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
30.5
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...……
38.4
🕘🕘
Microfinance gross loans, % GDP……………………….…….
0.0

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 31.6
Ease of protecting minority investors*…………..………….
58.3
🕘🕘Market capitalization, % GDP………………………………...….
22.2
Venture capital deals/bn PPP$ GDP……………….……....
0.0

115 ○
68
58
62 ○

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
67.8

Applied tariff rate, weighted avg., %………………………….
1.9

†Intensity of local competition …………………………………… 64.4
Domestic market scale, bn PPP$……………………………… 391.5

42
51
83
47



91
29
86
79 ○

47

◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
45.4

Knowledge-intensive employment, %...........................
36.9
Firms offering formal training, % firms…………………………
22.6
GERD performed by business, % GDP…………………..…… 0.3

GERD financed by business, %……………………………........
30.1
Females employed w/advanced degrees, %……………..
29.9

45
◆
33
◆
69
50
◆
59
2 ● ◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


27.4
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
41.3
State of cluster development†.……..………..…………………..
37.3

GERD financed by abroad, %.........................................
24.4
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.0Patent families 2+ offices/bn PPP$ GDP…………………….. 0.2

55
64
98
15 ● ◆
88 ○
41
◆

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.7

0.7
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
8.8

0.9
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
3.2
Research talent, % in business enterprise……..…………..
25.1

73
52
46
79
52
49

KNOWLEDGE & TECHNOLOGY OUTPUTS... 34.6 28


◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 42.5

6.2
Patents by origin/bn PPP$ GDP……………….…………..….…

0.4
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
24.3
Scientific & technical articles/bn PPP$ GDP….…..…..…. 9.2
Citable documents H-index…………………….……….……..….
15.0

17 ● ◆
17 ● ◆38◆
1 ● ◆
54
49

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


40.1
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.2
New businesses/th pop. 15-64………………….…....………….
1.5
Computer software spending, % GDP…………..……………
0.5
ISO 9001 quality certificates/bn PPP$ GDP…………..……
3.5
High- & medium-high-tech manufactures, %………………
0.2

47
22
60
19 ● ◆
70
56

6.3
6.3.1
6.3.2
6.3.3
6.3.4


21.3
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 2.0

ICT services exports, % total trade……………..……..………
4.8

FDI net outflows, % GDP…………………………….………….......
0.1

47
43
53
1 1 ● ◆96


33.5
CREATIVE OUTPUTS…….…………………….…………

42

◆


MARKET SOPHISTICATION..………….…………… 43.3 90

34.8

◆

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
55.8
17 ● ◆
Trademarks by origin/bn PPP$ GDP…………..……….….….
128.6
6 ● ◆
Industrial designs by origin/bn PPP$ GDP…………..……..
13.4
8 ● ◆

ICTs & business model creation†………………………....…….
49.1 109 ○
†
ICTs & organizational model creation …………………….... 55.6 58

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


13.6
Online creativity………………………………………..……….…….

4.5
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 4.7

31.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
24.3

8.8 91
0.4 58
0.6 94 ○n/a n/a
1.0 620.2 82
43
57
51
38
19

◆
◆
◆
◆
◆

◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

337

UNITED ARAB EMIRATES (THE)GII 2019 rank

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

58

24

High

NAWA

9.5

732.9

69,381.7

38

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

78.8

28

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
80.5

80.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
80.4

20
35
19

1.2
1.2.1
1.2.2
1.2.3


84.2
Regulatory environment……………………………..………..

69.1
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
67.5

8.0
Cost of redundancy dismissal, salary weeks…………..

24
32
34
1 ● ◆

1.3
1.3.1
1.3.2


71.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
94.1

Ease of resolving insolvency*……………………………….….
49.7

58
22
67


52.4
HUMAN CAPITAL & RESEARCH………………...

18

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


61.9
Education…………………………………………………………..……

n/a
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….…….
13.6

PISA scales in reading, maths, & science…………......…
474.3
🕘🕘
Pupil-teacher ratio, secondary…………………………......…. 9.5

[17]
n/a
n/a
72 ○ ◇
37
23

2.2
2.2.1
2.2.2
2.2.3


57.5
Tertiary education……………………………………….……..….
n/aTertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
22.0
Tertiary inbound mobility, %.......................................
…. 48.6

6 ● ◆
n/a
50
1 ● ◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
37.7
🕘🕘Researchers, FTE/mn pop……………………………..…...…
2,406.6
🕘🕘Gross expenditure on R&D, % GDP………….………..……
1.0

69.7
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
31.2

28
35
36
18
37


59.4
INFRASTRUCTURE……………………………….......

21

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  88.7

ICT access*………………………………………………………….…….
84.8

ICT use*…………………………….....................................…….
81.3

94.4
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
94.4

14 ●
15
13 ●
14 ●
17

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
52.7
…………………..…….. 13,980.2
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 88.5
Gross capital formation, % GDP………………………….…….
22.5

12 ●
8 ●
1 1 ● ◆
69

3.3
3.3.1
3.3.2
3.3.3


36.8
Ecological sustainability………………………………………..

8.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
58.9
ISO 14001 environmental certificates/bn PPP$ GDP..  2.5

71 ◇
72 ○
67 ◇
40



MARKET SOPHISTICATION..………….…………… 56.1

34

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
53.5
Ease of getting credit*…………………………………..…………..
70.0
Domestic credit to private sector, % GDP…………...……
78.8

Microfinance gross loans, % GDP……………………….…….
n/a

27
40
38
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 46.2
Ease of protecting minority investors*…………..………….
75.0

Market capitalization, % GDP………………………………...….
60.4
Venture capital deals/bn PPP$ GDP……………….……....
0.0

53
14
29
32

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
68.6
Applied tariff rate, weighted avg., %………………………….
4.8

†Intensity of local competition …………………………………… 71.0Domestic market scale, bn PPP$……………………………… 732.9

39
81 ○ ◇
49
32



36

◆

41.5

30

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
40.7 55
Knowledge-intensive employment, %...........................
18.4 79 ○ ◇Firms offering formal training, % firms…………………………
n/a n/a🕘🕘
GERD performed by business, % GDP…………………..……
0.7 26🕘🕘
GERD financed by business, %……………………………........ 74.3
5 ● ◆

Females employed w/advanced degrees, %…………….. 8.8 73 ○ ◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


41.9 24
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
55.7 28
State of cluster development†.……..………..…………………..
69.1 10 ● ◆
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1 16

Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 67

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
42.0

0.7
Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
9.4

0.9
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.6
🕘🕘
Research talent, % in business enterprise……..…………..
62.2

34
54
38
74
67
8 ●

 22.2 63
KNOWLEDGE & TECHNOLOGY OUTPUTS....

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5


Knowledge creation………………………………………........... 6.4 88 ○ ◇
0.1 106 ○Patents by origin/bn PPP$ GDP……………….…………..….…

0.1 60
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a n/a
Scientific & technical articles/bn PPP$ GDP….…..…..….
3.1 101 ○ ◇Citable documents H-index…………………….……….……..…. 10.5 62

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


34.9
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
1.6
New businesses/th pop. 15-64………………….…....………….
2.6

Computer software spending, % GDP…………..……………
0.3
ISO 9001 quality certificates/bn PPP$ GDP…………..……
6.0
High- & medium-high-tech manufactures, %……………… 0.2

73
48
42
50
52
57

6.3
6.3.1
6.3.2
6.3.3
6.3.4


25.2
Knowledge diffusion……………………………………..…..…….

1.0Intellectual property receipts, % total trade……………….
🕘🕘
High-tech net exports, % total trade……………….….…...... 0.1

ICT services exports, % total trade……………..……..………
1.8

FDI net outflows, % GDP…………………………….………….......
4.0

37
19
107 ○ ◇
59
13 ●


31.2
CREATIVE OUTPUTS…….…………………….…………

50

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
40.5

Trademarks by origin/bn PPP$ GDP…………..……….….….
8.7
🕘🕘Industrial designs by origin/bn PPP$ GDP…………..……..
0.1

ICTs & business model creation†………………………....…….
71.7

ICTs & organizational model creation†……………………....
67.3

66
◇
107 ○ ◇
108 ○
29
24

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
35.9 13 ●
Cultural & creative services exports, % total trade…....
n/a n/a
National feature films/mn pop. 15-69………………….………
10.6 16
Entertainment & Media market/th pop. 15-69…………….
19.5 28Printing & other media, % manufacturing…...................
1.5 32🕘🕘Creative goods exports, % total trade………………………..
4.2 13 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


7.9
Online creativity………………………………………..……….…….

10.8
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 7.3
🕘🕘
9.9
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
6.7

57
38
43
63
47

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
338

The Global Innovation Index 2019

◇◇

UNITED KINGDOM (THE)GII 2019 rank

5

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

4

6

High

EUR

66.6

3,033.7

45,704.6

4Score/Value Rank

INSTITUTIONS………………………………….…….…..

87.1

14

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
80.2

78.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
80.8

23
42 ○ ◇
18

1.2
1.2.1
1.2.2
1.2.3


93.7
Regulatory environment……………………………..………..

88.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
90.8

9.3
Cost of redundancy dismissal, salary weeks…………..

11
12
14
25

1.3
1.3.1
1.3.2


87.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
94.6

Ease of resolving insolvency*……………………………….….
80.3

13
17
13


59.3
HUMAN CAPITAL & RESEARCH………………...

9

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


57.7
Education…………………………………………………………..……

5.5
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap… 19.0
School life expectancy, years……………….…………….……. 19.0

PISA scales in reading, maths, & science…………......…
499.9
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
19.4

34
26
55 ○
6 ●
21
87 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


52.4
Tertiary education……………………………………….……..….
🕘🕘
59.4
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
26.3
Tertiary inbound mobility, %.......................................
….
18.1

11
47 ○
25
6
◆

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
67.8
………………………..…....… 4,377.0
Researchers, FTE/mn pop……

Gross expenditure on R&D, % GDP………….………..……
1.7

86.8
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
95.2

9
19
22
8
2 ● ◆


64.4
INFRASTRUCTURE……………………………….......

8

Information & communication technologies(ICTs) 93.0

ICT access*………………………………………………………….…….
92.9

ICT use*…………………………….....................................…….
82.7

97.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
98.3

3 ● ◆
3 ● ◆
94 ●
5

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 39.3
 …………………..…….
Electricity output, GWh/mn pop……
5,041.5
Logistics performance*……………………………………………..
90.0

Gross capital formation, % GDP………………………….……. 17.2

44 ○ ◇44 ○9109 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


61.0
Ecological sustainability………………………………………..

14.7
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
79.9
ISO 14001 environmental certificates/bn PPP$ GDP..  6.0

5 ● ◆
14
6 ●
19

3.1
3.1.1
3.1.2
3.1.3
3.1.4





MARKET SOPHISTICATION..………….…………… 76.0

4 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
70.4
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...……
136.2

Microfinance gross loans, % GDP……………………….…….
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 75.4
Ease of protecting minority investors*…………..………….
75.0

Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.3

6 ● ◆
14n/a
4 ● ◆

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
82.0

Applied tariff rate, weighted avg., %………………………….
1.8

†Intensity of local competition …………………………………… 79.9
Domestic market scale, bn PPP$………………………..…… 3,033.7

5 ●
23 ○
99



Score/Value Rank

BUSINESS SOPHISTICATION..……….……………

10
29
14
n/a

54.3

16

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
67.5 12
7Knowledge-intensive employment, %...........................
48.6
Firms offering formal training, % firms…………………………
n/a n/a
GERD performed by business, % GDP…………………..……
1.1 18
GERD financed by business, %……………………………........
51.8 25
Females employed w/advanced degrees, %…………….. 22.8 16

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


50.1
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
72.7
State of cluster development†.……..………..…………………..
69.8
GERD financed by abroad, %.........................................
15.6
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP…………………….. 2.3

13
7
9
26
12
17

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
45.4

1.5
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
11.9

1.8
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
4.7
Research talent, % in business enterprise……..…………..
37.9

27
23
20
30
34
33 ○ ◇ 56.6KNOWLEDGE & TECHNOLOGY OUTPUTS....

8



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 66.9

6.4
Patents by origin/bn PPP$ GDP……………….…………..….…

1.9
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……
n/a
Scientific & technical articles/bn PPP$ GDP….…..…..…. 23.8
Citable documents H-index…………………….……….……..….
100.0

5 ●
16
19
n/a
16
1 ● ◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


55.2
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.5
New businesses/th pop. 15-64………………….…....………….
15.7
Computer software spending, % GDP…………..……………
0.7
ISO 9001 quality certificates/bn PPP$ GDP…………..……
12.8
High- & medium-high-tech manufactures, %……………… 0.4

7
75 ○
6◆
4 ●
26
21

6.3
6.3.1
6.3.2
6.3.3
6.3.4


47.7
Knowledge diffusion……………………………………..…..…….

2.6Intellectual property receipts, % total trade……………….

9.0
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.2

FDI net outflows, % GDP…………………………….………….......
1.8

12
8
18
28
31


52.2
CREATIVE OUTPUTS…….…………………….…………

6 ●

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
58.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
56.2
Industrial designs by origin/bn PPP$ GDP…………..……..
7.9

ICTs & business model creation†………………………....…….
80.4

ICTs & organizational model creation†……………………....
79.1

1240 ○
16
8
6 ●

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
40.4
Cultural & creative services exports, % total trade…....
2.0
National feature films/mn pop. 15-69………………….………
6.3
Entertainment & Media market/th pop. 15-69…………….
62.0

Printing & other media, % manufacturing…...................
2.0
Creative goods exports, % total trade………………………..
2.9

8
6 ● ◆
35
9
19
20

7.3
7.3.1
7.3.2
7.3.3
7.3.4


51.6
Online creativity………………………………………..……….…….

60.7
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 73.1

69.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
25.9

11
12
7
13
18

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

339

UNITED REPUBLIC OF TANZANIA(THE)

GII 2019 rank

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

73

115

Low

SSF

59.1

175.9

3,443.7

92

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
25.1

INSTITUTIONS………………………………….…….…..
53.4

98

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
40.2

57.9
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 31.3

104
101
106

1.2
1.2.1
1.2.2
1.2.3


64.2
Regulatory environment……………………………..………..

26.4
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
34.6

9.3
Cost of redundancy dismissal, salary weeks…………..

70
106
92
25 ● ◆

1.3
1.3.1
1.3.2


55.8
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
72.7
Ease of resolving insolvency*……………………………….…. 39.0

115
117
103

◇


10.0 125
HUMAN CAPITAL & RESEARCH………………...

◇

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


24.5
Education…………………………………………………………..……
🕘🕘
3.5
Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 12.4
School life expectancy, years……………….…………….……. 7.7

PISA scales in reading, maths, & science…………......…
n/a
Pupil-teacher ratio, secondary…………………………......….
17.1

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

2.5 [124]
3.9 122 ○n/a n/an/a n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
🕘🕘
Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

2.8
18.3
0.5
0.0
0.0

117
94
87
116 ○ ◇
n/a
76

◆
88
104 ○
60 ● ◆43 ○ ◇78 ○ ◇
33.2 108INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 38.3

ICT access*………………………………………………………….…….
26.0

ICT use*…………………………….....................................…….
9.0

56.3
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
61.8

110
121
123
95
88

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
35.9
 …………………..…….
Electricity output, GWh/mn pop……
125.9

Logistics performance*…………………………………………….. n/a
Gross capital formation, % GDP………………………….…….
30.5

61 ●
117
n/a
21 ●

3.3
3.3.1
3.3.2
3.3.3


25.5
Ecological sustainability………………………………………..

5.2
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
50.8
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

114
106
96
103

◇

◆



MARKET SOPHISTICATION..………….…………… 35.7 117
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
23.6 110Ease of getting credit*…………………………………..…………..
65.0 54 ● ◆🕘🕘Domestic credit to private sector, % GDP…………...……
14.4 118

Microfinance gross loans, % GDP……………………….…….
0.1 55

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 30.4
Ease of protecting minority investors*…………..………….
45.0

Market capitalization, % GDP………………………………...….
n/a
Venture capital deals/bn PPP$ GDP……………….……....
0.0

4.3
4.3.1
4.3.2
4.3.3





121
104
n/a
65

Trade, competition, & market scale………..……………. 53.1 96
🕘🕘Applied tariff rate, weighted avg., %………………………….
8.6 105
Intensity of local competition†……………………………………
59.4 109Domestic market scale, bn PPP$……………………………… 175.9 68

97

◇
◇

99

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
13.5 119🕘🕘
Knowledge-intensive employment, %...........................
3.4 112Firms offering formal training, % firms………………………… 30.7 50

GERD performed by business, % GDP…………………..…… n/a n/a🕘🕘
GERD financed by business, %……………………………........
0.1 98 ○ ◇🕘🕘Females employed w/advanced degrees, %……………..
0.4 113

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


38.0 32 ●Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
45.7 49 ●
State of cluster development†.……..………..…………………..
48.7 54 ● ◆🕘🕘
6 ●GERD financed by abroad, %.........................................
42.0
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 108 ○
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
23.8 108
0.0 113Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.2 68
0.3 115
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
2.9 58 ●
Research talent, % in business enterprise……..…………..
n/a n/a 14.9 102
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
🕘🕘
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


33.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
3.1
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..…………… 0.0

ISO 9001 quality certificates/bn PPP$ GDP…………..……
0.9
High- & medium-high-tech manufactures, %………………
0.1

6.3
6.3.1
6.3.2
6.3.3
6.3.4


6.2 127 ○
Knowledge diffusion……………………………………..…..…….

0.0 101
Intellectual property receipts, % total trade……………….

0.2 101
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.2 117

FDI net outflows, % GDP…………………………….………….......
0.0 115

5.1 980.0 126 ○ ◇
0.0 93n/a n/a3.1 104
8.6 76◆
78
24 ●
n/a
126 ○
11086


28.7 [59]
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
50.3 [34]Trademarks by origin/bn PPP$ GDP…………..……….….….
n/a n/a
Industrial designs by origin/bn PPP$ GDP…………..……..
n/a n/a
ICTs & business model creation†………………………....……. 53.3 90
ICTs & organizational model creation†……………………....
47.2 93

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
13.9 [72]🕘🕘Cultural & creative services exports, % total trade…....
0.0 114National feature films/mn pop. 15-69………………….………
n/a n/aEntertainment & Media market/th pop. 15-69…………….
n/a n/a
Printing & other media, % manufacturing…...................
1.7 25 ●🕘🕘
Creative goods exports, % total trade………………………..
0.1 96

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

0.1 1220.1 119
0.1 1120.2 115n/a n/a◆◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
340

The Global Innovation Index 2019

UNITED STATES OF AMERICA(THE)

GII 2019 rank

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

6

3

High

NAC

326.8

20,513.0

62,605.6

6

Score/Value Rank

INSTITUTIONS………………………………….…….…..
89.7

11

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
84.2

84.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 84.2

16
25
14

1.2
1.2.1
1.2.2
1.2.3


93.9
Regulatory environment……………………………..………..

85.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
89.9

8.0
Cost of redundancy dismissal, salary weeks…………..

915
15
1 ●

1.3
1.3.1
1.3.2


91.1
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
91.2

Ease of resolving insolvency*……………………………….…. 90.9

2 ● ◆
47
3 ● ◆


55.7
HUMAN CAPITAL & RESEARCH………………...

12

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


54.5
Education…………………………………………………………..……
🕘🕘
5.0
Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 22.5
School life expectancy, years……………….…………….……. 16.3

PISA scales in reading, maths, & science…………......…
487.6
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
14.7

45
50
39
29
29
◇
67 ○ ◇

2.2
2.2.1
2.2.2
2.2.3


34.6
Tertiary education……………………………………….……..….
🕘🕘
88.8
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….…. 17.9
Tertiary inbound mobility, %.......................................….
5.0

53
8
73 ○
40

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
77.9
🕘🕘Researchers, FTE/mn pop……………………………..…...……
4,256.3
Gross expenditure on R&D, % GDP………….………..……
2.8
 100.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
99.0

3 ● ◆
23
9
1 ● ◆
1 ● ◆


59.2
INFRASTRUCTURE……………………………….......

23

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  89.7

ICT access*………………………………………………………….…….
84.8

ICT use*…………………………….....................................…….
77.2

98.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….……. 98.3

8
14
21
2 ●
5

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
49.4
…………………..……. 13,000.9
Electricity output, GWh/mn pop……

Logistics performance*…………………………………………….. 85.2
Gross capital formation, % GDP………………………….…….
21.1

19
9
14
87 ○

3.3
3.3.1
3.3.2
3.3.3


38.4
Ecological sustainability………………………………………..

8.1
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… 71.2
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.3

64 ◇
74 ○
26
106 ○ ◇



MARKET SOPHISTICATION..………….…………… 87.0

1 ● ◆

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
94.6
Ease of getting credit*…………………………………..…………..
95.0
🕘🕘Domestic credit to private sector, % GDP…………...…… 192.2
Microfinance gross loans, % GDP……………………….……. n/a

1 ● ◆
3 ● ◆
3 ● ◆
n/a

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 73.7
Ease of protecting minority investors*…………..………….
64.7
Market capitalization, % GDP………………………………...….
150.3
Venture capital deals/bn PPP$ GDP……………….……....
0.4

7
◆
47
5
1 ● ◆

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
92.7
Applied tariff rate, weighted avg., %………………………….
1.7
Intensity of local competition†…………………………………… 84.3
Domestic market scale, bn PPP$……………………...…… 20,513.0

1 ● ◆
18
3 ● ◆
2 ● ◆



3Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
62.7

7

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


4
Knowledge workers…………………………………………….…..
76.4

11
Knowledge-intensive employment, %...........................
47.3
Firms offering formal training, % firms………………………… n/a n/a
8
GERD performed by business, % GDP…………………..……
2.0

GERD financed by business, %……………………………........
63.6
9

Females employed w/advanced degrees, %……………..
26.3
6

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


54.3
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
80.9
†State of cluster development .……..………..………………….. 79.5

GERD financed by abroad, %......................................... 6.2

JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1
Patent families 2+ offices/bn PPP$ GDP……………………..
3.3

9
1 ● ◆
1 ● ◆
58 ○
9
15

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
57.3

1.8
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
17.2
ICT services imports, % total trade…………..………………... 1.5

FDI net inflows, % GDP…………………………….………………….
2.4
🕘🕘Research talent, % in business enterprise……..…………..
71.0

7
15
9
◆
40
72 ○
5◆

 59.7KNOWLEDGE & TECHNOLOGY OUTPUTS....

4



◆

◆

◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 72.3

15.1
Patents by origin/bn PPP$ GDP……………….…………..….…

2.7
PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..…… n/aScientific & technical articles/bn PPP$ GDP….…..…..…. 10.5
Citable documents H-index…………………….……….……..….
100.0

3 ● ◆
6
◆
12
n/a
44
◇
1 ● ◆

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


60.4
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.9
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..……………
1.1
ISO 9001 quality certificates/bn PPP$ GDP…………..…… 1.5
High- & medium-high-tech manufactures, %……………… 0.5

2 ● ◆
64 ○n/a
1 ● ◆
99 ○ ◇
10

6.3
6.3.1
6.3.2
6.3.3
6.3.4


46.5
Knowledge diffusion……………………………………..…..…….

5.0Intellectual property receipts, % total trade……………….

5.8
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
1.6

FDI net outflows, % GDP…………………………….………….......
1.8

15
1 ● ◆
27
65
33


45.5
CREATIVE OUTPUTS…….…………………….…………

15

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
50.3
Trademarks by origin/bn PPP$ GDP…………..……….….….
22.0
Industrial designs by origin/bn PPP$ GDP…………..…….. 1.2

ICTs & business model creation†………………………....……. 81.0

ICTs & organizational model creation†……………………....
83.7

32
85 ○ ◇
61
6
1 ● ◆

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
43.8
Cultural & creative services exports, % total trade…....
2.5
National feature films/mn pop. 15-69………………….………
2.9
Entertainment & Media market/th pop. 15-69…………….
100.0

Printing & other media, % manufacturing…...................
1.5
Creative goods exports, % total trade………………………..
3.3

5
◆
5
◆
58
◇
1 ● ◆
31
17

7.3
7.3.1
7.3.2
7.3.3
7.3.4


37.5
Online creativity………………………………………..……….…….

100.0
Generic top-level domains (TLDs)/th pop. 15-69……….

2.4
Country-code TLDs/th pop. 15-69…………………..………….

26.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
30.1

19
1 ● ◆
62
◇
42
◇
17

NOTES: ● indicates a strength; ○ a weakness; ◆ a strength relative to the other top 25-ranked GII economies; ◇ a weakness relative to the other top 25-ranked GII economies; anindex; † a survey question. 🕘🕘 indicates that the economy’s data are older than the base year; see Appendix II for details, including the year of the data, at
http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage (DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

341

URUGUAY

GII 2019 rank

62

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

61

66

High

LCN

3.5

81.6

23,274.1

62

Score/Value Rank

Score/Value Rank


INSTITUTIONS………………………………….…….…..
69.3

44

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
65.8

84.2
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 56.6

44
25 ●
48
◇

1.2
1.2.1
1.2.2
1.2.3


70.6
Regulatory environment……………………………..………..

59.6
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
61.9

20.8
Cost of redundancy dismissal, salary weeks…………..

50
41
38
87

1.3
1.3.1
1.3.2


71.4
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
89.8
Ease of resolving insolvency*……………………………….…. 53.0

61
55
64


28.7
HUMAN CAPITAL & RESEARCH………………...

71

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


54.8
Education…………………………………………………………..……
🕘🕘
4.4
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. 16.3

PISA scales in reading, maths, & science…………......…
430.0
🕘🕘
Pupil-teacher ratio, secondary…………………………......….
12.7

44
66
n/a
25 ●
48
54

2.2
2.2.1
2.2.2
2.2.3


24.1
Tertiary education……………………………………….……..….
🕘🕘
62.4
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
13.2
Tertiary inbound mobility, %.......................................
….
n/a

83
◇
43
95 ○ ◇
n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
7.1
Researchers, FTE/mn pop……………………………..…...……
667.7
🕘🕘
Gross expenditure on R&D, % GDP………….………..……
0.4

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
12.0

◇
69
62
◇
69
◇
43 ○ ◇61

51.0
INFRASTRUCTURE……………………………….......

49

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  81.7

ICT access*………………………………………………………….…….
75.1

ICT use*…………………………….....................................…….
71.4

88.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
91.6

27 ●
42
31
27 ●
26 ●

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
23.6 107 ○ ◇
 …………………..…….
Electricity output, GWh/mn pop……
3,848.3 53
Logistics performance*…………………………………………….. 29.1
83 ◇Gross capital formation, % GDP………………………….…….
17.8 104 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


47.7
Ecological sustainability………………………………………..

13.0
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
64.7
ISO 14001 environmental certificates/bn PPP$ GDP.. 3.0

◇

◇

40
24 ●
43
32



MARKET SOPHISTICATION..………….…………… 39.9 101

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
23.5 1 1 1 ○ ◇Ease of getting credit*…………………………………..…………..
60.0 66Domestic credit to private sector, % GDP…………...……
26.3 105 ○ ◇🕘🕘Microfinance gross loans, % GDP……………………….……. 0.0 67 ○

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 43.3 [61]Ease of protecting minority investors*…………..………….
43.3 105 ○ ◇Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
52.8

Applied tariff rate, weighted avg., %………………………….
6.3
Intensity of local competition†…………………………………… 61.5
Domestic market scale, bn PPP$……………………………… 81.6



97
97
101
86


BUSINESS SOPHISTICATION..……….……………
27.7

81

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
33.3

Knowledge-intensive employment, %...........................
22.2
🕘🕘Firms offering formal training, % firms………………………… 48.6
🕘🕘
GERD performed by business, % GDP…………………..…… 0.0

GERD financed by business, %……………………………........
4.6
Females employed w/advanced degrees, %……………..
10.1

78
◇
67
◇
23
80 ○ ◇81 ○ ◇
65
◇

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


18.3 101
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
34.9 93State of cluster development†.……..………..…………………..
37.0 101
GERD financed by abroad, %.........................................
7.4 52JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0 79
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.2 49

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
31.4

0.8
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
7.1

2.5
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
0.8
Research talent, % in business enterprise……..…………..
0.7

The Global Innovation Index 2019

◇
◇
◇

77
48
71
15 ●
112 ○
80 ○ ◇ 21.5 67
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


36.3
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
2.0
New businesses/th pop. 15-64………………….…....………….
2.1
Computer software spending, % GDP…………..…………… 0.2

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 14.6
🕘🕘High- & medium-high-tech manufactures, %………………
0.1

66
44
50
68
23 ●
◇
72

6.3
6.3.1
6.3.2
6.3.3
6.3.4


18.7
Knowledge diffusion……………………………………..…..…….

0.2Intellectual property receipts, % total trade……………….

0.9
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
3.0

FDI net outflows, % GDP…………………………….………….......
1.4

54
32
70
30 ●
43


29.2
CREATIVE OUTPUTS…….…………………….…………

57

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
41.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
47.4
Industrial designs by origin/bn PPP$ GDP…………..……..
0.7

ICTs & business model creation†………………………....…….
66.8

ICTs & organizational model creation†…………………….... 58.4

60
51
81
43
50

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
16.6 64Cultural & creative services exports, % total trade…....
1.6 12 ●🕘🕘
National feature films/mn pop. 15-69………………….………
4.7 45
Entertainment & Media market/th pop. 15-69…………….
n/a n/a🕘🕘
Printing & other media, % manufacturing…...................
1.1 56Creative goods exports, % total trade………………………..
0.1 106 ○

7.3
7.3.1
7.3.2
7.3.3
7.3.4


16.7
Online creativity………………………………………..……….…….

6.4
Generic top-level domains (TLDs)/th pop. 15-69……….

9.8
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
68.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
4.6

9.4
0.3
n/a
0.3
9.2
9.9

72
87
n/a
38
52
68

39
50
39
14 ●
50

◇
◇
◇

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
342◇VIET NAM

GII 2019 rank

42

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

37

63

Lower middle

SEAO

96.5

707.6

7,510.5

45

Score/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
30.0

INSTITUTIONS………………………………….…….…..
58.6

81

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
58.6

82.5
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 46.6

57
32
71

1.2
1.2.1
1.2.2
1.2.3


57.3
Regulatory environment……………………………..………..

31.3
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
48.2

24.6
Cost of redundancy dismissal, salary weeks…………..

90
97
59
◆
101 ○

1.3
1.3.1
1.3.2


59.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
84.8

Ease of resolving insolvency*……………………………….…. 34.9

106 ○
80
110 ○


31.1
HUMAN CAPITAL & RESEARCH………………...

61

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


61.2
Education…………………………………………………………..……
🕘🕘
5.7
Expenditure on education, % GDP………………….…….….

Government funding/pupil, secondary, % GDP/cap… n/a
School life expectancy, years……………….…………….……. n/a
PISA scales in reading, maths, & science…………......…
502.0

Pupil-teacher ratio, secondary…………………………......….
n/a

[18]
24
n/a
n/a
20
n/a

2.2
2.2.1
2.2.2
2.2.3


24.7
Tertiary education……………………………………….……..….
🕘🕘
28.3
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
22.7
Tertiary inbound mobility, %.......................................….
0.2

81
85
46
104 ○

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
7.4
Researchers, FTE/mn pop……………………………..…...……
700.8
Gross expenditure on R&D, % GDP………….………..……
0.5

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
9.9

67
58
61
43 ○ ◇64

42.0
INFRASTRUCTURE……………………………….......

82

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  57.5

ICT access*………………………………………………………….…….
48.8

ICT use*…………………………….....................................…….
38.7

73.6
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
69.1

82
90
92
57
70

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
39.3
 …………………..…….
Electricity output, GWh/mn pop……
1,778.1
Logistics performance*…………………………………………….. 56.6
Gross capital formation, % GDP………………………….…….
27.5

45
81
38
32

3.3
3.3.1
3.3.2
3.3.3


29.2 100
Ecological sustainability………………………………………..

6.7 92GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
47.0 104 ○
ISO 14001 environmental certificates/bn PPP$ GDP.. 2.2 45 ◆

MARKET SOPHISTICATION..………….…………… 57.0 29

◆
◆
◆

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
22.8 102 ○
Knowledge-intensive employment, %...........................
1.1 117 ○ ◇Firms offering formal training, % firms………………………… 22.2 70 ○
GERD performed by business, % GDP…………………..…… 0.4 42◆
GERD financed by business, %……………………………........
64.1
8 ● ◆

Females employed w/advanced degrees, %……………..
6.1 83

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


20.0
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
38.6
State of cluster development†.……..………..…………………..
45.2

GERD financed by abroad, %.........................................
4.5
JV-strategic alliance deals/bn PPP$ GDP………………….. 0.0
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
47.1 23 ● ◆
n/a n/aIntellectual property payments, % total trade………….....

1 ● ◆
High-tech imports, % total trade………………..………………..
26.5

0.0 126 ○ ◇
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
6.2 23 ●Research talent, % in business enterprise……..…………..
24.1 51

86
75
74
64
49
84

◆

KNOWLEDGE & TECHNOLOGY OUTPUTS... 35.6

◆

Credit……………………………………………………….………………
68.6
Ease of getting credit*…………………………………..…………..
75.0
Domestic credit to private sector, % GDP…………...……
130.7

Microfinance gross loans, % GDP……………………….……. 3.9

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 33.1 108 ○Ease of protecting minority investors*…………..………….
55.0 84Market capitalization, % GDP………………………………...….
36.9
41

Venture capital deals/bn PPP$ GDP……………….……....
0.0 37

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
69.3
Applied tariff rate, weighted avg., %………………………….
2.7
Intensity of local competition†…………………………………… 63.2
Domestic market scale, bn PPP$……………………………… 707.6

11 ● ◆29
16 ● ◆
8 ● ◆





27

◆

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


56.5
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
6.0

New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..…………… 0.3

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 8.3
High- & medium-high-tech manufactures, %………………
0.4

6.3
6.3.1
6.3.2
6.3.3
6.3.4


42.1 18 ● ◆
Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

32.9
1 ● ◆
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.1 125 ○ ◇
FDI net outflows, % GDP…………………………….………….......
0.4
71

8.1
0.9
0.0
0.4
5.6
11.7

80
65
82
35
74
57
5 ● ◆
3 ● ◆
n/a
38
37
◆
◆
27


32.3
CREATIVE OUTPUTS…….…………………….…………

47

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
43.7
Trademarks by origin/bn PPP$ GDP…………..……….….….
85.3
Industrial designs by origin/bn PPP$ GDP…………..……..
2.7
†
ICTs & business model creation ………………………....……. 56.1

ICTs & organizational model creation†…………………….... 54.4

53
24 ●
43
83
63

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..
28.8 32◆Cultural & creative services exports, % total trade…....
n/a n/a🕘🕘
National feature films/mn pop. 15-69………………….………
1.2 78
Entertainment & Media market/th pop. 15-69…………….
1.3 56 ○
Printing & other media, % manufacturing…...................
0.9 70Creative goods exports, % total trade……………………….. 5.9 10 ● ◆

7.3
7.3.1
7.3.2
7.3.3
7.3.4


13.0
Online creativity………………………………………..……….…….

2.4
Generic top-level domains (TLDs)/th pop. 15-69……….

1.8
Country-code TLDs/th pop. 15-69…………………..………….

7.1
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
42.9

◆

4.1
4.1.1
4.1.2
4.1.3

35
61
90
33

69

◆

44
◆
74
◆
69
70
13 ● ◆◆NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

343

YEMENGII 2019 rank

129

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

129

129

Low

NAWA

28.9

73.3

2,377.2

n/aScore/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
16.3 [129] 
INSTITUTIONS………………………………….…….…..
27.5 129 ○ ◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...

Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….

0.0
0.0
0.0

129 ○ ◇
129 ○ ◇
129 ○ ◇

1.2
1.2.1
1.2.2
1.2.3


36.0
Regulatory environment……………………………..………..

3.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
0.0

27.4
Cost of redundancy dismissal, salary weeks…………..

◇
124
128
◇
129 ○ ◇
107
◇

1.3
1.3.1
1.3.2


46.5
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
67.0
Ease of resolving insolvency*……………………………….…. 25.9

127
125
125

◇
◇
◇


12.5 [117]
HUMAN CAPITAL & RESEARCH………………...

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


26.0 [116]
Education…………………………………………………………..……
🕘🕘
5.2 42 ●Expenditure on education, % GDP………………….…….….
🕘🕘
Government funding/pupil, secondary, % GDP/cap… 12.0 88
🕘🕘School life expectancy, years……………….…………….……. 9.0 110

PISA scales in reading, maths, & science…………......…
n/a n/a
Pupil-teacher ratio, secondary…………………………......….
n/a n/a

2.2
2.2.1
2.2.2
2.2.3


11.4 109
Tertiary education……………………………………….……..….
🕘🕘
10.0 109
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….
n/a n/a🕘🕘
Tertiary inbound mobility, %.......................................
….
4.3 50 ●

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……

Researchers, FTE/mn pop……………………………..…...……

Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

0.0 [120]n/a n/an/a n/a0.0
43 ○ ◇
0.0
78 ○ ◇
21.5 128
INFRASTRUCTURE……………………………….......

◇

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs)  10.8 [129]
ICT access*………………………………………………………….…….
n/a n/a
ICT use*…………………………….....................................…….
n/a n/a
9.7 128 ○ ◇Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
11.8 128 ○ ◇

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
2.5 128 ◇ …………………..…….
Electricity output, GWh/mn pop……
182.9 114

Logistics performance*…………………………………………….. 9.4
117

Gross capital formation, % GDP………………………….…….
5.9 125 ○ ◇

3.3
3.3.1
3.3.2
3.3.3


51.2
Ecological sustainability………………………………………..

21.3
GDP/unit of energy use…………………………………………….

Environmental performance*…….……………………………… n/a
ISO 14001 environmental certificates/bn PPP$ GDP.. 0.0

26 ● ◆
4 ● ◆
n/a
128 ○ ◇



MARKET SOPHISTICATION..………….…………… 35.0 119
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………

Ease of getting credit*…………………………………..…………..
🕘🕘
Domestic credit to private sector, % GDP…………...……

Microfinance gross loans, % GDP……………………….…….

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 53.3 [32]Ease of protecting minority investors*…………..………….
53.3 87 ●
Market capitalization, % GDP………………………………...….
n/a n/a
Venture capital deals/bn PPP$ GDP……………….……....
n/a n/a

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
51.2 102
Applied tariff rate, weighted avg., %………………………….
5.0 87 ● ◆Intensity of local competition†…………………………………… 50.4 123 ◇Domestic market scale, bn PPP$……………………………… 73.3 89 ●

0.4 129 ○ ◇
0.0 129 ○ ◇
5.6 126 ○ ◇
0.1 56 ●



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
6.7 [127]🕘🕘
Knowledge-intensive employment, %...........................
1.6 116
Firms offering formal training, % firms………………………… 14.3 85

GERD performed by business, % GDP…………………..…… n/a n/a
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %……………..
1.1 106

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


15.8 [117]Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
19.5 125 ○ ◇◇State of cluster development†.……..………..…………………..
29.9 121
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP………………….. n/a n/a
Patent families 2+ offices/bn PPP$ GDP……………………..
0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
26.3 98
1.6 21 ● ◆Intellectual property payments, % total trade………….....
🕘🕘High-tech imports, % total trade………………..………………..
6.3 88 ●
0.4 109
ICT services imports, % total trade…………..………………...
◇
FDI net inflows, % GDP…………………………….………………….
-0.8 124
Research talent, % in business enterprise……..………….. n/a n/a 3.8 128KNOWLEDGE & TECHNOLOGY OUTPUTS....

The Global Innovation Index 2019

◇



6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………........... 2.1 122

0.2 98
Patents by origin/bn PPP$ GDP……………….…………..….…
n/a n/a
PCT patents by origin/bn PPP$ GDP…………..….…….……
🕘🕘
Utility models by origin/bn PPP$ GDP……………...…..…… 0.0 65 ○ ◇Scientific & technical articles/bn PPP$ GDP….…..…..…. 3.1 103
Citable documents H-index…………………….……….……..….
1.9 119

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
New businesses/th pop. 15-64………………….…....………….

Computer software spending, % GDP…………..……………

ISO 9001 quality certificates/bn PPP$ GDP…………..……
🕘🕘
High- & medium-high-tech manufactures, %………………

6.3
6.3.1
6.3.2
6.3.3
6.3.4


8.8 1 1 1
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.2 35 ● ◆Intellectual property receipts, % total trade……………….
🕘🕘
0.1 117
High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.7 89
FDI net outflows, % GDP…………………………….………….......
0.0 110

0.6 129 ○ ◇
-11.1 112 ○ ◇n/a n/a0.0 1100.0 129 ○ ◇
0.0 104 ○ ◇
9.0 127
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
17.9 126Trademarks by origin/bn PPP$ GDP…………..……….….….
39.9 66 ● ◆Industrial designs by origin/bn PPP$ GDP…………..…….. 0.3 94

ICTs & business model creation†………………………....…….
24.3 125 ○ ◇
ICTs & organizational model creation†……………………....
21.7 125 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................
🕘🕘
Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.4 113
Online creativity………………………………………..……….…….

0.4 113
Generic top-level domains (TLDs)/th pop. 15-69……….

0.0 126
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
1.1 102
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
0.3 76

0.0 [129]n/a n/an/a n/a
0.0 63 ○ ◇n/a n/a0.0 123

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
344◇ZAMBIAGII 2019 rank

124

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

121

126

Lower middle

SSF

17.6

73.2

4,103.5

n/aScore/Value Rank

Score/Value Rank

BUSINESS SOPHISTICATION..……….……………
17.1 127 ○ ◇
INSTITUTIONS………………………………….…….…..
47.1 120

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
43.2

66.7
Political and operational stability*……………..………….….

Government effectiveness*…………………………..…………. 31.5

97
74 ●
105

1.2
1.2.1
1.2.2
1.2.3


34.4
Regulatory environment……………………………..………..

29.4
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
37.7

50.6
Cost of redundancy dismissal, salary weeks…………..

125 ○ ◇
101
81 ●
124 ○ ◇

1.3
1.3.1
1.3.2


63.7
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
85.1

Ease of resolving insolvency*……………………………….…. 42.4

86
78 ●
87


HUMAN CAPITAL & RESEARCH………………...

1.4 [129]

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


Education…………………………………………………………..……
🕘🕘
Expenditure on education, % GDP………………….…….….
Government funding/pupil, secondary, % GDP/cap…

School life expectancy, years……………….…………….…….

PISA scales in reading, maths, & science…………......…

Pupil-teacher ratio, secondary…………………………......….

0.0 [129]
1.1 119 ○ ◇n/a n/an/a n/an/a n/an/a n/a

2.2
2.2.1
2.2.2
2.2.3


Tertiary education……………………………………….……..….
🕘🕘
Tertiary enrolment, % gross………………………….….……….

Graduates in science & engineering, %……………….….

Tertiary inbound mobility, %.......................................
….

2.6 [123]
4.0 121 ○ ◇n/a n/an/a n/a

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
🕘🕘
Researchers, FTE/mn pop……………………………..…...……
🕘🕘
Gross expenditure on R&D, % GDP………….………..……

Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………

1.5
41.0
0.3
0.0
0.0

3.1
3.1.1
3.1.2
3.1.3
3.1.4

98
94
81
43 ○ ◇78 ○ ◇
36.6
INFRASTRUCTURE……………………………….......

95

Information & communication technologies(ICTs) 35.8

ICT access*………………………………………………………….…….
31.1

ICT use*…………………………….....................................…….
24.5

47.9
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
39.9

114
116
101
106
110



◇
◇
◇

3.2
3.2.1
3.2.2
3.2.3

General infrastructure…………………………………………… 48.0
 …………………..…….
Electricity output, GWh/mn pop……
704.9
Logistics performance*……………………………………………..
21.6
Gross capital formation, % GDP………………………….……. 44.4

25 ● ◆
101
103
3 ● ◆

3.3
3.3.1
3.3.2
3.3.3


25.9
Ecological sustainability………………………………………..

5.3
GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
51.0
ISO 14001 environmental certificates/bn PPP$ GDP..  0.4

113
105
95
95


MARKET SOPHISTICATION..………….…………… 37.7 112

◇

4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
32.7
Ease of getting credit*…………………………………..…………..
95.0
Domestic credit to private sector, % GDP…………...……
11.2

Microfinance gross loans, % GDP……………………….…….
0.0

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..………. 26.8 126 ○ ◇Ease of protecting minority investors*…………..………….
50.0 93🕘🕘Market capitalization, % GDP………………………………...….
13.6 65
Venture capital deals/bn PPP$ GDP……………….……....
0.0 49 ●

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
53.5
🕘🕘Applied tariff rate, weighted avg., %………………………….
6.2
†Intensity of local competition …………………………………… 66.4
Domestic market scale, bn PPP$……………………………… 73.2

79 ●
3 ● ◆
123 ○ ◇
63



5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
◇
12.9 121

Knowledge-intensive employment, %...........................
2.0 115 ○ ◇Firms offering formal training, % firms…………………………
28.2 55 ●🕘🕘
GERD performed by business, % GDP…………………..……
0.0 85🕘🕘
GERD financed by business, %……………………………........ 3.2 86
Females employed w/advanced degrees, %…………….. 5.8 86

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


17.4 1 1 1
Innovation linkages…………..……………………………………..

University/industry research collaboration†………………..
31.6 102State of cluster development†.……..………..…………………..
42.1 85
🕘🕘
GERD financed by abroad, %.........................................
1.6 83JV-strategic alliance deals/bn PPP$ GDP………………….. n/a n/a
Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 93 ○ ◇

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
21.1 121◇
0.0 112Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
5.7 95
0.7 94
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
4.7 35 ●🕘🕘
71
Research talent, % in business enterprise……..…………..
4.9

 12.1 115
KNOWLEDGE & TECHNOLOGY OUTPUTS....


◇

6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........

Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


23.6 108
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
0.0 88New businesses/th pop. 15-64………………….…....………….
1.1 68Computer software spending, % GDP…………..……………
0.0 112

ISO 9001 quality certificates/bn PPP$ GDP…………..…… 0.6 118
🕘🕘High- & medium-high-tech manufactures, %………………
0.1 78

6.3
6.3.1
6.3.2
6.3.3
6.3.4


8.8 110Knowledge diffusion……………………………………..…..…….
n/a n/aIntellectual property receipts, % total trade……………….

0.4 85High-tech net exports, % total trade……………….….…......
ICT services exports, % total trade……………..……..………
0.4 104

FDI net outflows, % GDP…………………………….………….......
-0.2 120 ○ ◇

3.9 1070.2 102
0.0 86n/a n/a2.7 107
5.7 92◇◇◇
13.4 121
CREATIVE OUTPUTS…….…………………….…………

◇

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
25.4 120
Trademarks by origin/bn PPP$ GDP…………..……….….….
15.6 94Industrial designs by origin/bn PPP$ GDP…………..……..
0.4 88
ICTs & business model creation†………………………....…….
45.2 115

ICTs & organizational model creation†…………………….... 37.3 118

◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

2.5 [113]
0.3 63 ●n/a n/an/a n/an/a n/a0.0 116

7.3
7.3.1
7.3.2
7.3.3
7.3.4


Online creativity………………………………………..……….…….

Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..………….
🕘🕘
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..

0.1 125 ○
0.1 123 ○ ◇
0.1 115
0.1 120n/a n/a

◇
◇

94
96
75 ●
90

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
Appendix II

345

ZIMBABWE

GII 2019 rank

122

Output rank

Input rank

IncomeRegionPopulation (mn)GDP, PPP$GDP per capita, PPP$GII 2018 rank

110

123

Low

SSF

16.9

36.3

2,787.6

113

Score/Value Rank

INSTITUTIONS………………………………….…….…..

Score/Value Rank

37.6 127 ○ ◇

1.1
1.1.1
1.1.2


Political environment……………………………………….…...
27.6

47.4
Political and operational stability*……………..………….….

Government effectiveness*…………………………..………….
17.7

127 ○
123
127 ○

1.2
1.2.1
1.2.2
1.2.3


39.3
Regulatory environment……………………………..………..

0.0
Regulatory quality*…………………………………..…………….…

Rule of law*……………………………………………..……………..…
9.9

25.3
Cost of redundancy dismissal, salary weeks…………..

◇
122
129 ○ ◇127 ○ ◇
102
◇

1.3
1.3.1
1.3.2


45.9
Business environment……………………………..…..……….

Ease of starting a business*………………………………..……
66.5
Ease of resolving insolvency*……………………………….….
25.3

128 ○ ◇126
◇127 ○ ◇

27.8
HUMAN CAPITAL & RESEARCH………………...

76

2.1
2.1.1
2.1.2
2.1.3
2.1.4
2.1.5


51.4
Education…………………………………………………………..……
🕘🕘
7.5
Expenditure on education, % GDP………………….…….….
🕘🕘 31.0
Government funding/pupil, secondary, % GDP/cap…
🕘🕘School life expectancy, years……………….…………….…….
10.2

PISA scales in reading, maths, & science…………......…
n/a🕘🕘
Pupil-teacher ratio, secondary…………………………......…. 22.5

56 ● ◆
6 ● ◆
12 ● ◆
106
n/a
93

2.2
2.2.1
2.2.2
2.2.3


31.6
Tertiary education……………………………………….……..….
🕘🕘
8.5
Tertiary enrolment, % gross………………………….….……….
🕘🕘
Graduates in science & engineering, %……………….….
30.2
🕘🕘
Tertiary inbound mobility, %.......................................
….
0.5

62 ● ◆
111
13 ● ◆
95

2.3
2.3.1
2.3.2
2.3.3
2.3.4


Research & development (R&D)……….……………..……
0.3
🕘🕘Researchers, FTE/mn pop……………………………..…...……
88.7
Gross expenditure on R&D, % GDP………….………..……
n/a

0.0
Global R&D companies, avg. exp. top 3, mn US$……

QS university ranking, average score top 3*……………
0.0

115
87
n/a
43 ○ ◇78 ○ ◇◆
21.7 127 ○ ◇
INFRASTRUCTURE……………………………….......

3.1
3.1.1
3.1.2
3.1.3
3.1.4

Information & communication technologies(ICTs) 29.9 120

ICT access*………………………………………………………….…….
36.0 108ICT use*…………………………….....................................…….
23.4 102
32.6 116
Government’s online service*…………………………….…….

E-participation*…………………………………………………….…….
27.5 120

3.2
3.2.1
3.2.2
3.2.3


General infrastructure……………………………………………
15.0 124
 …………………..…….
Electricity output, GWh/mn pop……
436.8 107

Logistics performance*…………………………………………….. 2.6 120 ○ ◇Gross capital formation, % GDP………………………….…….
18.7 100

3.3
3.3.1
3.3.2
3.3.3


20.2 123
Ecological sustainability………………………………………..

2.7 119 ○GDP/unit of energy use…………………………………………….

Environmental performance*…….………………………………
43.4 114
ISO 14001 environmental certificates/bn PPP$ GDP..  1.5 58 ● ◆

◆
◆



MARKET SOPHISTICATION..………….…………… 38.4 109
4.1
4.1.1
4.1.2
4.1.3


Credit……………………………………………………….………………
27.6
Ease of getting credit*…………………………………..…………..
55.0
Domestic credit to private sector, % GDP…………...……
n/a
Microfinance gross loans, % GDP……………………….…….
0.0

4.2
4.2.1
4.2.2
4.2.3

Investment……………………………………………………..……….

Ease of protecting minority investors*…………..………….

Market capitalization, % GDP………………………………...….

Venture capital deals/bn PPP$ GDP……………….……....

4.3
4.3.1
4.3.2
4.3.3


Trade, competition, & market scale………..…………….
49.2 109
🕘🕘Applied tariff rate, weighted avg., %………………………….
5.0 86

Intensity of local competition†……………………………………
58.4 1 1 1
Domestic market scale, bn PPP$………………………………
36.3 108
BUSINESS SOPHISTICATION..……….……………

99
77
n/a
70

n/a [n/a]n/a n/an/a n/an/a n/a20.6 117

5.1
5.1.1
5.1.2
5.1.3
5.1.4
5.1.5


Knowledge workers…………………………………………….…..
15.5 [117]🕘🕘Knowledge-intensive employment, %...........................
1.1 118 ○ ◇Firms offering formal training, % firms…………………………
26.4 59GERD performed by business, % GDP…………………..……
n/a n/a
GERD financed by business, %……………………………........
n/a n/a🕘🕘
Females employed w/advanced degrees, %…………….. 5.7 87
◆

5.2
5.2.1
5.2.2
5.2.3
5.2.4
5.2.5


19.3 91
Innovation linkages…………..……………………………………..
◇
University/industry research collaboration†………………..
26.7 118State of cluster development†.……..………..…………………..
26.6 125 ○ ◇
GERD financed by abroad, %.........................................
n/a n/a
JV-strategic alliance deals/bn PPP$ GDP…………………..
0.1 21 ● ◆Patent families 2+ offices/bn PPP$ GDP…………………….. 0.0 74

5.3
5.3.1
5.3.2
5.3.3
5.3.4
5.3.5


Knowledge absorption……………………………………..……..
27.1

0.2
Intellectual property payments, % total trade………….....
High-tech imports, % total trade………………..………………..
6.8

0.9
ICT services imports, % total trade…………..………………...

FDI net inflows, % GDP…………………………….………………….
1.6

Research talent, % in business enterprise……..…………..
n/a

93
86
75
80
93
n/a

 17.5 83
KNOWLEDGE & TECHNOLOGY OUTPUTS....


6.1
6.1.1
6.1.2
6.1.3
6.1.4
6.1.5

Knowledge creation………………………………………...........
🕘🕘
Patents by origin/bn PPP$ GDP……………….…………..….…

PCT patents by origin/bn PPP$ GDP…………..….…….……

Utility models by origin/bn PPP$ GDP……………...…..……

Scientific & technical articles/bn PPP$ GDP….…..…..….

Citable documents H-index…………………….……….……..….

6.8
0.2
0.0
n/a
7.0
6.5

84
90
85
n/a
62 ● ◆
86

6.2
6.2.1
6.2.2
6.2.3
6.2.4
6.2.5


38.7
Knowledge impact………………………………………..............

Growth rate of PPP$ GDP/worker, %……………..…....…….
-0.3
New businesses/th pop. 15-64………………….…....………….
n/a
Computer software spending, % GDP…………..……………
0.4
ISO 9001 quality certificates/bn PPP$ GDP…………..……
4.3
🕘🕘High- & medium-high-tech manufactures, %………………
0.2

54 ● ◆95
n/a
22 ● ◆
62 ● ◆
49 ● ◆

6.3
6.3.1
6.3.2
6.3.3
6.3.4


7.0 123
Knowledge diffusion……………………………………..…..…….
🕘🕘
0.0 68Intellectual property receipts, % total trade……………….

High-tech net exports, % total trade……………….….…...... 0.2 98
ICT services exports, % total trade……………..……..………
0.2 114

FDI net outflows, % GDP…………………………….………….......
0.1 94
13.3 123
CREATIVE OUTPUTS…….…………………….…………

7.1
7.1.1
7.1.2
7.1.3
7.1.4


Intangible assets…………………………………….………………..
24.4 122🕘🕘
Trademarks by origin/bn PPP$ GDP…………..……….….….
4.8 117Industrial designs by origin/bn PPP$ GDP…………..……..
n/a n/a
ICTs & business model creation†………………………....…….
42.7 118

ICTs & organizational model creation†……………………....
29.7 123 ○ ◇

7.2
7.2.1
7.2.2
7.2.3
7.2.4
7.2.5


Creative goods & services……………………….…….………..

Cultural & creative services exports, % total trade…....

National feature films/mn pop. 15-69………………….………
Entertainment & Media market/th pop. 15-69…………….

Printing & other media, % manufacturing…...................

Creative goods exports, % total trade………………………..

7.3
7.3.1
7.3.2
7.3.3
7.3.4


0.4
Online creativity………………………………………..……….…….

0.4
Generic top-level domains (TLDs)/th pop. 15-69……….
Country-code TLDs/th pop. 15-69…………………..…………. 0.7
🕘🕘
0.3
Wikipedia edits/mn pop. 15-69……………………………………

Mobile app creation/bn PPP$ GDP……………..……………..
n/a

4.0 [108]0.2
71n/a n/an/a n/an/a n/a0.3 73 ● ◆
112
111
88
113
n/a

◆

NOTES: ● indicates a strength; ○ a weakness; ◆ an income group strength; ◇ an income group weakness; an index; † a survey question. 🕘🕘 indicates that the economy’s data areolder than the base year; see Appendix II for details, including the year of the data, at http://globalinnovationindex.org. Square brackets [ ] indicate that the data minimum coverage(DMC) requirements were not met at the sub-pillar or pillar level.
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Appendix II

347

348

The Global Innovation Index 2019

A P P E NDIX I I I

SOURCES AND DEFINITIONSThis appendix complements the country/economy profiles andthe online data tables by providing, for each of the 80 indicators
included in the Global Innovation Index (GII) this year, its title,
description, definition, and source.
For all 129 economies in the GII in 2019, the most recent values,
within the period 2009 to 2018, were used for each indicatorwith a few noted exceptions (see Appendix IV). The year
provided next to the indicator description corresponds to theyear when data were most frequently available for economies.
When more than one year is considered, the period is indicatedat the end of the indicators source in parentheses.
Of the 80 indicators, 57 variables are hard data, 18 are composite
indicators from third party data providers, marked with ( ),and 5 are survey questions from the World Economic Forum’s
Executive Opinion Survey (EOS), marked with ( ). In some cases,
additional markings are provided at the end of the indictor
description. Instances marked with “[a]” signal indicators thatwere assigned half weights and those marked “[b]” are indicators
where higher scores indicate poorer outcomes, commonly
known as “bads”. Details on the computation can be found in
Appendix IV.

*†

Some indicators received special treatment by way of scaling
during computation to be comparable across economies.
Scaling of indicators by other comparable indicators or throughdivision by gross domestic product (GDP) in current U.S. dollars,purchasing power parity GDP in international dollars (PPP$
GDP), population, total exports, total trade, and so on. Details
are provided in this appendix. In all cases, the scaling factor
used was the value that corresponded to the same year of
the indicator.

1 Institutions
1.1

Political environment

1.1.1

Political and operational stability
Political, legal, operational or security risk index*ab | 2018
Index that measures the likelihood and severity of political,
legal, operational or security risks impacting business
operations. Scores are annualized and standardized.
Source: IHS Markit, Country Risk Scores, aggregated forend Q1, Q2, Q3, and Q4 2018. (https://ihsmarkit.com/industry/economics-country-risk.html).

1.1.2 Government effectivenessGovernment effectiveness index* | 2017
Index that reflects perceptions of the quality of public
services, the quality of the civil service and the degree of
its independence from political pressures, the quality ofpolicy formulation and implementation, and the credibilityof the government’s commitment to such policies. Scores
are standardized.
Source: World Bank, Worldwide Governance Indicators,
2018 update. (http://info.worldbank.org/governance/
wgi/#home).

1.2 Regulatory environment
1.2.1 Regulatory quality
Regulatory quality index*a | 2017
Index that reflects perceptions of the ability of thegovernment to formulate and implement sound policies
and regulations that permit and promote private-sector
development. Scores are standardized.
Source: World Bank, Worldwide Governance Indicators,
2018 update. (http://info.worldbank.org/governance/
wgi/#home).

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1.2.2 Rule of law
Rule of law index*a | 2017
Index that reflects perceptions of the extent to which
agents have confidence in and abide by the rules of society,and in particular the quality of contract enforcement,
property rights, the police, and the courts, as well as thelikelihood of crime and violence. Scores are standardized.
Source: World Bank, Worldwide Governance Indicators,
2018 update. (http://info.worldbank.org/governance/
wgi/#home).
1.2.3 Cost of redundancy dismissal
Sum of notice period and severance pay for redundancy
dismissal (salary in weeks, averages for workers with
1, 5, and 10 years of tenure, with a minimum threshold of
8 weeks)b | 2018
Redundancy costs measure the cost of advance noticerequirements and severance payments due whenterminating a redundant worker, expressed in weeks ofsalary. The average value of notice requirements andseverance payments applicable to a worker with 1 yearof tenure, a worker with 5 years, and a worker with 10
years is also considered. One month is recorded as 4 and1/3 weeks. If the redundancy cost adds up to 8 or fewer
weeks of salary, a value of 8 is assigned but the actual
number of weeks is published. If the cost adds up to morethan 8 weeks of salary, the score is the number of weeks.
Source: World Bank, Doing Business 2019: Training for
Reform, 2019. (http://www.doingbusiness.org/en/reports/
global-reports/doing-business-2019).

1.3 Business environment
1.3.1 Ease of starting a business
Ease of starting a business (score)* | 2018
The ranking of economies on the ease of starting abusiness is determined by sorting their scores. Thesescores are the simple average of the scores for eachof the component indicators. The World Banks Doing
Business records all procedures officially required, orcommonly done in practice, for an entrepreneur to startup and formally operate an industrial or commercial
business, as well as the time and cost to complete theseprocedures and the paid-in minimum capital requirement.
These procedures include obtaining all necessary
licenses and permits and completing any required
notifications, verifications, or inscriptions for the company
and employees with relevant authorities. Data arecollected from limited liability companies based in thelargest business cities. For 11 economies, namely
Bangladesh, Brazil, China, India, Indonesia, Japan,

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Mexico, Nigeria, Pakistan, the Russian Federation,and the United States, the data are also collected for thesecond-largest business city.
Source: World Bank, Doing Business 2019: Training for
Reform, 2019. (http://www.doingbusiness.org/en/reports/
global-reports/doing-business-2019).
1.3.2 Ease of resolving insolvency
Ease of resolving insolvency (score)* | 2018
The ranking of economies on the ease of resolving
insolvency is determined by sorting their scores. Thesescores are the simple average of the scores for therecovery rate and the strength of insolvency framework
index. The recovery rate is recorded as cents on thedollar recovered by secured creditors throughreorganization, liquidation, or debt enforcement(foreclosure or receivership) proceedings. The calculation
takes into account the outcome: whether the businessemerges from the proceedings as a going concern or
the assets are sold piecemeal. Then the costs of theproceedings are deducted (1 cent for each percentage
point of the value of the debtor’s estate). Finally, the value
lost as a result of the time that the money remains tied up
in insolvency proceedings is taken into account, including
the loss of value due to depreciation of a hotel’s furniture.
Consistent with international accounting practice, theannual depreciation rate for furniture is taken to be 20%.
The furniture is assumed to account for a quarter of thetotal value of assets. The recovery rate is the present
value of the remaining proceeds, based on end-2017
lending rates from the International Monetary Fund’sInternational Financial Statistics, supplemented with datafrom central banks and the Economist Intelligence Unit.
If an economy had zero cases a year over the past
five years involving a judicial reorganization, judicial
liquidation, or debt enforcement procedure (foreclosure
or receivership), the economy receives a “no practice”
mark on the time, cost, and outcome indicators. Thismeans that creditors are unlikely to recover their money
through a formal legal process. The recovery rate for “nopractice” economies is zero. In addition, a “no practice”
economy receives a score of “zero”. on the strength of theinsolvency framework index even if its legal framework
includes provisions related to insolvency proceedings(liquidation or reorganization). The strength of theinsolvency framework index is based on four otherindices: commencement of proceedings index,
management of debtor’s assets index, reorganization
proceedings index, and creditor participation index.
Source: World Bank, Doing Business 2019: Training for
Reform, 2019. (http://www.doingbusiness.org/en/reports/
global-reports/doing-business-2019).

2 Human capital and research
2.1 Education
2.1.1 Expenditure on education
Government expenditure on education (% of GDP) | 2015
Total general (local, regional and central) government
expenditure on education (current, capital, and transfers),
expressed as a percentage of GDP. It includes expenditure
funded by transfers from international sources togovernment. Algeria Egypt, Saudi Arabia, Yemen, andZambia use data for 2008.
Source: UNESCO Institute for Statistics, UIS online
database (2008–17). (http://data.uis.unesco.org/).
2.1.2 Government funding per secondary student
Government funding per secondary student (% of GDP
per capita) | 2015
Total general (local, regional and central, current andcapital) initial government funding of education perstudent, which includes transfers paid (such as
scholarships to students), but excludes transfers received,in this case international transfers to government for
education (when foreign donors provide education
sector budget support or other support integrated in
the government budget). This is then expressed as ashare of GDP per capita, in US$.
Source: UNESCO Institute for Statistics, UIS online
database (2009-17). (http://data.uis.unesco.org/).
2.1.3 School life expectancy
School life expectancy, primary to tertiary education, both
sexes (years) | 2016
Total number of years of schooling that a child of a certain
age can expect to receive in the future, assuming thatthe probability of his or her being enrolled in school at
any particular age is equal to the current enrolment ratio
for that age. For a child of a certain age, the school life
expectancy is calculated as the sum of the age-specificenrolment rates for primary to tertiary levels of education.
The part of the enrolment that is not distributed by age
is divided by the school-age population for the primary
to tertiary level of education in which they are enrolled,
and multiplied by the duration of that level of education.
The result is then added to the sum of the age-specificenrolment rates. A relatively high value indicates a greater
probability that children will spend more years in education
and a higher overall retention within the education
system. It must be noted that the expected number ofyears spent in school does not necessarily coincide withthe expected number of grades of education completed,because of grade repetition. Botswana and Cambodia
use data for 2008.
Source: UNESCO Institute for Statistics, UIS online
database (2008–18). (http://data.uis.unesco.org).

2.1.4 Assessment in reading, mathematics, and science
PISA average scales in reading, mathematics, and sciencea| 2015The Organisation for Economic Co-operation andDevelopment (OECD) Programme for International
Student Assessment (PISA) develops triennial international
surveys that examine 15-year-old students’ performancein reading, mathematics, and science. The scores arecalculated in each year so that the mean is 500 and thestandard deviation 100.
The statistical data for Israel are supplied by and under
the responsibility of the relevant Israeli authorities. The
use of such data by the OECD is without prejudice to thestatus of the Golan Heights, East Jerusalem, and Israeli
settlements in the West Bank under the terms ofinternational law. B-S-J-G (China) refers to the fourPISA-participating China provinces: Beijing, Shanghai,
Jiangsu, and Guangdong. CABA (Argentina) refers to theadjudicated region of Ciudad Autónoma de Buenos Aires.
FYROM refers to North Macedonia. Russia refers to theRussian Federation. 2015 scores from the United ArabEmirates are from Dubai. 2010 scores from India
are from Himachal Pradesh and Tamil Nadu (average);2010 scores from the Bolivarian Republic of Venezuela
are from Miranda.
The results of adjudication and subsequent further
examinations showed that the PISA Technical Standards
were met in all countries and economies that participatedin PISA 2015 except for the following countries: In Albania,
the PISA assessment was conducted in accordance withthe operational standards and guidelines of the OECD.
However, because of the ways in which the data were
captured, it was not possible to match the data in thetest with the data from the student questionnaire. As aresult, Albania cannot be included in analyses that relate
students’ responses from the questionnaires to the test
results. In Argentina, the PISA assessment was conductedin accordance with the operational standards andguidelines of the OECD. However, there was a significant
decline in the proportion of 15-year-olds who were coveredby the test, both in absolute and relative numbers. There
had been a re-structuring of Argentina’s secondary
schools, except for those in the adjudicated region of
Ciudad Autónoma de Buenos Aires, which is likely tohave affected the coverage of eligible schools listed in
the sampling frame. As a result, Argentina’s results may
not be comparable with those of other countries or withresults for Argentina from previous years. In Kazakhstan,
the national coders were found to be lenient in marking.
Consequently the human-coded items did not meet PISA
standards and were excluded from the international data.
Since human-coded items form an important part of theconstructs that are tested by PISA, the exclusion of these
items resulted in a significantly smaller coverage of the
PISA test. As a result, Kazakhstan’s results may not becomparable with those of other countries or with resultsfor Kazakhstan from previous years. In Malaysia, the PISA

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351

assessment was conducted in accordance with theoperational standards and guidelines of the OECD.
However, the weighted response rate among the initiallysampled Malaysian schools of 51% falls well short of thestandard PISA response rate of 85%. Therefore the results
may not be comparable to those of other countries or toresults for Malaysia from previous years.
Source: OECD Programme for International Student
Assessment (PISA) (2010–15). (www.pisa.oecd.org/).
2.1.5 Pupil-teacher ratio, secondary
Pupil-teacher ratio, secondarya,b | 2017
The number of pupils enrolled in secondary school divided
by the number of secondary school teachers (regardlessof their teaching assignment). Where the data are missing
for some countries, the ratios for upper-secondary
are reported; if these are also missing, the ratios forlower-secondary are reported instead. Argentina uses
data for 2008.
Source: UNESCO Institute for Statistics, UIS online
database (2008–18). (http://data.uis.unesco.org).

2.2 Tertiary education
2.2.1 Tertiary enrolment
School enrolment, tertiary (% gross)a | 2017
The ratio of total tertiary enrolment, regardless ofage, to the population of the age group that officiallycorresponds to the tertiary level of education. Tertiary
education, whether or not at an advanced research
qualification, normally requires, as a minimum conditionof admission, the successful completion of education
at the secondary level. The school enrolment ratio can
exceed 100%
as a result of grade repetition and the inclusion ofover-aged and under-aged students because of earlyor late entrants.
Source: UNESCO Institute for Statistics, UIS online
database (2010–18). (http://data.uis.unesco.org).
2.2.2 Graduates in science and engineering
Tertiary graduates in science, engineering, manufacturing,and construction (% of total tertiary graduates) | 2016
The share of all tertiary-level graduates in natural sciences,mathematics, statistics, information and technology,
manufacturing, engineering, and construction as apercentage of all tertiary-level graduates.
Source: UNESCO Institute for Statistics, UIS online
database (2010–18). (http://data.uis.unesco.org).

2.2.3 Tertiary inbound mobility
Tertiary inbound mobility rate (%)a | 2016
The number of students from abroad studying in a given
country as a percentage of the total tertiary-level
enrolment in that country. Philippines uses data from 2008.
Source: UNESCO Institute for Statistics, UIS online
database (2008–17). (http://data.uis.unesco.org).

2.3 Research and development (R&D)
2.3.1 2.3.1 Researchers FTE
Researchers, full-time equivalent (FTE) (per million
population) | 2017
Researchers per million population, full-time equivalent.
Researchers in R&D are professionals engaged in theconception or creation of new knowledge, products,
processes, methods, or systems and in the managementof the projects concerned. Postgraduate PhD students(ISCED97 level 6) engaged in R&D are included. Special
tabulation based on UNESCO, Eurostat, and OECD data.
Albania and Zambia use data for 2008.
Source: UNESCO Institute for Statistics, UIS online database;Eurostat, Eurostat data base, 2019; OECD, Main Scienceand Technology Indicators MSTI database, 2019(2008–17). (http://data.uis.unesco.org; https://ec.europa.
eu/eurostat/data/database; https://stats.oecd.org/Index.
aspx?DataSetCode=MSTI_PUB).
2.3.2 Gross expenditure on R&D (GERD)
Gross expenditure on R&D (% of GDP) | 2017
Total domestic intramural expenditure on R&D during a given
period as a percentage of GDP. “Intramural R&D expenditure”
is all expenditure for R&D performed within a statistical unit or
sector of the economy during a specific period, whatever
the source of funds. Special tabulation based on UNESCO,
Eurostat, and OECD data. Albania and Zambia use data for 2008
Source: UNESCO Institute for Statistics, UIS online database;Eurostat, Eurostat data base, 2019; OECD, Main Science andTechnology Indicators MSTI database, 2019 (2008–17).
(http://data.uis.unesco.org; https://ec.europa.eu/eurostat/data/database; https://stats.oecd.org/Index.aspx?DataSetCode=MSTI_PUB).
2.3.3 Global R&D companies, average expenditure, top 3
Average expenditure of the top 3 global companies by
R&D, mn US$* | 2018
Average expenditure on R&D of the top three global
companies. If a country has fewer than three global
companies listed, the figure is either the average of thesum of the two companies listed or the total for a single
listed company. A score of 0 is given to countries withno listed companies.
Source: EU JRC Industrial R&D Investment Scoreboard
2018. (http://iri.jrc.ec.europa.eu/scoreboard18.html).

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2.3.4 QS university ranking average score of top 3
universities
Average score of the top 3 universities at the QS world
university ranking* | 2018
Average score of the top three universities per country.
If fewer than three universities are listed in the QS rankingof the global top 1000 universities, the sum of the scoresof the listed universities is divided by three, thus implying
a score of zero for the non-listed universities.
Source: QS Quacquarelli Symonds Ltd, QS World
University Ranking 2017/2018, Top Universities.
(https://www.topuniversities.com/university-rankings/
world-university-rankings/2018).

3 Infrastructure
3.1 Information and communication
technologies (ICTs)
3.1.1 ICT access
ICT access index* | 2018
The ICT access index, previously part of the ITU ICTDevelopment Index, is a composite index that weights
five ICT indicators (20% each): (1) Fixed telephone
subscriptions per 100 inhabitants; (2) Mobile cellular
telephone subscriptions per 100 inhabitants; (3)International Internet bandwidth (bit/s) per Internet user;(4) Percentage of households with a computer; and(5) Percentage of households with Internet access.
Source: GII calculations based on the World
Telecommunication/ICT Indicators Database​(Released
January 18, 2019) following the methodology of theInternational Telecommunication Union, ICT Development
Index 2017. (http://www.itu.int/en/ITU-D/Statistics/Pages/
publications/mis2017.aspx).
3.1.2 ICT use
ICT use index* | 2018
The ICT use index, previously part of the ITU ICTDevelopment Index, is a composite index that weights
three ICT indicators (33% each): (1) Percentage ofindividuals using the Internet; (2) Fixed (wired)-broadband
Internet subscriptions per 100 inhabitants; (3) Active
mobile-broadband subscriptions per 100 inhabitants.
Source: GII calculations based on the World
Telecommunication/ICT Indicators Database ​(Released
January 18, 2019) following the methodology of theInternational Telecommunication Union, ICT Development
Index 2017. (http://www.itu.int/en/ITU-D/Statistics/Pages/
publications/mis2017.aspx).

3.1.3 Government’s online service
Government’s online service index* | 2018
The Online Services Index component of the E-Government
Development Index is a composite indicator measuring
the use of ICTs by governments in delivering public
services at the national level. The 2018 Online Service
Questionnaire (OSQ) consists of a list of 140 questions.
To arrive at a set of Online Service Index values for 2018,a total of 206 online United Nations Volunteer (UNV)
researchers from 89 countries covering 66 languages,
assessed each country’s national website in the native
language, including the national portal, e-services portal
and e-participation portal, as well as the websites of therelated ministries of education, labour, social services,
health, finance and environment, as applicable. The total
number of points scored by each country is normalized
to a range of 0 to 1. The online index value for a given
country is equal to the actual total score less the lowest
total score divided by the range of total score values for
all countries.
Note: The precise meaning of these values varies fromone edition of the Survey to the next as understandingof the potential of e-government changes and theunderlying technology evolves. Read about the methodology
at https://publicadministration.un.org/egovkb/Portals/
egovkb/Documents/un/2018-Survey/E-Government%20
Survey%202018_Annexes.pdf .
Source: United Nations Public Administration Network,
e-Government Survey 2018. (https://publicadministration.
un.org/egovkb/en-us/About/Overview/-E-Government-Development-Index).
3.1.4 Online e-participation
E-Participation Index* | 2018
The E-Participation Index (EPI) is derived as a supplementaryindex to the United Nations E-Government Survey. It
extends the dimension of the Survey by focusing on thegovernment use of online services in providing information
to its citizens or “e-information sharing”, interactingwith stakeholders or “e-consultation” and engaging indecision-making processes or “e-decision-making.” A
country’s EPI reflects the e-participation mechanisms thatare deployed by the government as compared to all othercountries. The purpose of this measure is not to prescribe
any specific practice, but rather to offer insight into how
different countries are using online tools in promotinginteraction between the government and its citizens, aswell as among the citizens, for the benefit of all. As the EPI
is a qualitative assessment based on the availability andrelevance of participatory services available on government
websites, the comparative ranking of countries is forillustrative purposes and only serves as an indicator of thebroad trends in promoting citizen engagement. As with
the EGDI, the EPI is not intended as an absolute measurementof e-participation, but rather, as an attempt to capture the
e-participation performance of counties relative to one
another at a point in time. The index ranges from 0 to 1,
with 1 showing greater e-participation. Mathematically,

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353

the EPI is normalized by taking the total score value fora given country, subtracting the lowest total score for any
country in the Survey and dividing by the range of total
score values for all countries.
Note: The precise meaning of these values varies fromone edition of the Survey to the next as understandingof the potential of e-government changes and theunderlying technology evolves. Read about the methodology
at https://publicadministration.un.org/egovkb/Portals/
egovkb/Documents/un/2018-Survey/E-Government%20
Survey%202018_Annexes.pdf.
Source: United Nations Public Administration Network,
e-Government Survey 2018. (https://publicadministration.
un.org/egovkb/en-us/Reports/UN-E-Government-Survey-2018).

3.2 General infrastructure
3.2.1 Electricity output
Electricity output (GWh per mn population)a 2016
Electricity production, measured at the terminals of allalternator sets in a station. In addition to hydropower,
coal, oil, gas, and nuclear power generation, this indicator
covers generation by geothermal, solar, wind, and tide
and wave energy, as well as that from combustible
renewables and waste. Production includes the output
of electric plants that are designed to produce electricity
only as well as that of combined heat and power plants.
Electricity output in GWh is scaled by population.
Source: International Energy Agency (IEA) World Energy
Balances on-line data service, 2018 edition (2016–17).
(http://www.iea.org/statistics/).
3.2.2 Logistics performance
Logistics Performance Index*a | 2018
A multidimensional assessment of logistics performance,
the Logistics Performance Index (LPI) ranks 160 countries
combining data on six core performance components
into a single aggregate measure—including customs
performance, infrastructure quality, and timeliness of
shipments. The data used in the ranking comes from asurvey of logistics professionals who are asked questions
about the foreign countries in which they operate. The
LPI’s six components are: (1) the efficiency of customs andborder management clearance (“Customs”); (2) the qualityof trade and transport infrastructure (“Infrastructure”); (3)the ease of arranging competitively priced shipments(“International shipments”); (4) the competence and qualityof logistics services (“Services Quality”); (5) the ability to
track and trace consignments (“Tracking and tracing”);
and (6) the frequency with which shipments reachconsignees within scheduled or expected delivery times(“Timeliness”). The LPI consists therefore of both qualitative

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The Global Innovation Index 2019and quantitative measures and helps build profiles oflogistics friendliness for these countries.
Source: World Bank and Turku School of Economics,
Logistics Performance Index 2018; Arvis et al., 2018,
Connecting to Compete 2018: Trade Logistics in the
Global Economy–The Logistics Performance Index andits Indicators. (https://openknowledge.worldbank.org/
bitstream/handle/10986/29971/LPI2018.pdf).
3.2.3 Gross capital formation
Gross capital formation (% of GDP) | 2018
Gross capital formation is expressed as a ratio of total
investment in current local currency to GDP in current
local currency. Investment or gross capital formationis measured by the total value of the gross fixed capitalformation and changes in inventories and acquisitions
less disposals of valuables for a unit or sector, on thebasis of the System of National Accounts (SNA) of 1993.
Source: International Monetary Fund, World Economic
Outlook Database, October 2018 (PPP$ GDP). (https://www.imf.org/external/pubs/ft/weo/2018/02/weodata/index.aspx).

3.3 Ecological sustainability
3.3.1 GDP per unit of energy use
GDP per unit of energy use (2010 PPP$ per kg of oil
equivalent) | 2016
Purchasing power parity gross domestic product (PPP$
GDP) per kilogram of oil equivalent of energy use.
Total primary energy supply (TPES) is made up of
production + imports − exports − international marine
bunkers − international aviation bunkers +/– stock changes.
Source: International Energy Agency (IEA) World Energy
Balances on-line data service, 2017 edition (2016–17).
(http://www.iea.org/statistics/).
3.3.2 Environmental performance
Environmental Performance Index* | 2018
The 2018 Environmental Performance Index (EPI) ranks
180 countries on 24 performance indicators across ten
issue categories covering environmental health andecosystem vitality. These metrics provide a gauge at anational scale of how close countries are to establishedenvironmental policy goals. The EPI thus offers ascorecard that highlights leaders and laggards inenvironmental performance, gives insight on best practices,and provides guidance for countries that aspire to beleaders in sustainability. The index ranges from 0 to 100,with 100 indicating best performance.
Source: Yale University and Columbia University Environmental
Performance Index 2018. (http://epi.yale.edu/).

3.3.3 ISO 14001 environmental certificates
ISO 14001 Environmental management systems—
Requirements with guidance for use: Number ofcertificates issued (per billion PPP$ GDP)a | 2017
ISO 14001:2015 specifies the requirements for anenvironmental management system that an organization
can use to enhance its environmental performance. ISO
14001 is intended for use by an organization seeking tomanage its environmental responsibilities in a systematicmanner that contributes to the environmental pillar ofsustainability. ISO 14001 helps an organization achieve
the intended outcomes of its environmental management
system, which provide value for the environment, theorganization itself, and interested parties. Consistent withthe organization’s environmental policy, the intended
outcomes of an environmental management system
include enhancement of environmental performance,
fulfillment of compliance obligations, and achievementof environmental objectives. ISO 14001 is applicable toany organization, regardless of size, type, or nature, andapplies to the environmental aspects of its activities,
products, and services that the organization determines
it can either control or influence from a life cycle
perspective. ISO 14001 does not state specific environmental
performance criteria. ISO 14001 can be used in whole
or in part to systematically improve environmental
management. Claims of conformity to ISO 14001, however,are not acceptable unless all its requirements areincorporated into an organization’s environmental
management system and fulfilled without exclusion.
The data are reported per billion PPP$ GDP.
Source: International Organization for Standardization,
The ISO Survey of certifications to management systemstandards, 2017; International Monetary Fund, World
Economic Outlook Database, October 2018 (PPP$ GDP)
(https://www.iso.org/the-iso-survey.html ; https://www.imf.
org/external/pubs/ft/weo/2018/02/weodata/index.aspx).

4 Market sophistication
4.1 Credit
4.1.1 Ease of getting credit
Ease of getting credit* | 2018
The ranking of economies on the ease of getting credit
is determined by sorting their scores for getting credit.
These scores are the score for the sum of the strength ofthe legal rights index (range 0–12) and the depth of credit
information index (range 0–8). Doing Business measuresthe legal rights of borrowers and lenders with respect tosecured transactions through one set of indicators andthe reporting of credit information through another. The
first set of indicators measures whether certain featuresthat facilitate lending exist within the applicable collateraland bankruptcy laws. The second set measures thecoverage, scope, and accessibility of credit information
available through credit reporting service providers suchas credit bureaus or credit registries. Although Doing
Business compiles data on getting credit for public registry
coverage (% of adults) and for private bureau coverage(% of adults), these indicators are not included in the ranking.
Source: World Bank, Doing Business 2019: Training for
Reform. (http://www.doingbusiness.org/en/reports/global-reports/doing-business-2019).
4.1.2 Domestic credit to private sector
Domestic credit to private sector (% of GDP) | 2017
“Domestic credit to private sector” refers to financial
resources provided to the private sector by financial
corporations, such as through loans, purchases of non-equity
securities, and trade credits and other accounts
receivable, that establish a claim for repayment. For somecountries these claims include credit to public enterprises.
The financial corporations include monetary authorities
and deposit money banks, as well as other financial
corporations where data are available (including corporations
that do not accept transferable deposits but do incursuch liabilities as time and savings deposits). Examplesof other financial corporations are finance and leasing
companies, money lenders, insurance corporations,pension funds, and foreign exchange companies.
Source: International Monetary Fund, International
Financial Statistics and data files; and World Bank andOECD GDP estimates; extracted from the World Bank’s
World Development Indicators database (2013-2017).
(http://data.worldbank.org/).
4.1.3 Microfinance institutions gross loan portfolio
Microfinance institutions: Gross loan portfolio(% of GDP) | 2017
Combined gross loan balances of microfinance institution(current US$) in a country as a percentage of its GDP(current US$).
Source: Microfinance Information Exchange, Mix Market
database; International Monetary Fund, World Economic
Outlook Database, October 2018 (current US$ GDP)
(2011-2018). (https://reports.themix.org/; https://www.imf.
org/external/pubs/ft/weo/2018/02/weodata/index.aspx).

4.2 Investment
4.2.1 Ease of protecting minority investors
Ease of protecting minority investors* | 2018
This ranking is the simple average of the scores for theextent of conflict of interest regulation index and theextent of shareholder governance index. The extent
of conflict of interest regulation index measures theprotection of shareholders against directors’ misuseof corporate assets for personal gain by distinguishing

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three dimensions of regulation that address conflicts ofinterest: transparency of related-party transactions (extent
of disclosure index), shareholders’ ability to sue and holddirectors liable for self-dealing (extent of director liability
index), and access to evidence and allocation of legal
expenses in shareholder litiga­tion (ease of shareholder
suits index). The extent of shareholder governance index
measures shareholders’ rights in corporate governanceby distinguishing three dimensions of good governance:
shareholders’ rights and role in major corporate decisions(extent of shareholder rights index); governancesafeguards protecting shareholders from undue board
control and entrenchment (extent of ownership andcontrol index); and corporate transparency on ownershipstakes, compensation, audits, and financial prospects(extent of corporate transparency index). The index alsomeasures whether a subset of relevant rights andsafeguards are available in limited companies. The data
come from a questionnaire administered to corporate
and securities lawyers and are based on securities
regulations, company laws, civil procedure codes, andcourt rules of evidence.
Source: World Bank, Doing Business 2019: Training for
Reform. (http://www.doingbusiness.org/en/reports/global-reports/doing-business-2019).

4.2.2 Market capitalization
Market capitalization of listed domestic companies(% of GDP, three-year average)a | 2017Market capitalization (also known as “market value”) is
the share price times the number of shares outstanding(including their several classes) for listed domestic
companies. Investment funds, unit trusts, and companies
whose only business goal is to hold shares of other listedcompanies are excluded. Data are the average of theend-of-year values for the last three years with the
exception of Jamaica (averages for two years: 2010 and2011); Ukraine (2010, 2011), and Zambia (2011)
Source: World Federation of Exchanges database; extracted
from the World Bank’s World Development Indicators
database (2011–17). (http://data.worldbank.org/).
4.2.3 Venture capital deals
Venture capital per investment location: Number of deals(per billion PPP$ GDP)a | 2018
Thomson Reuters data on private equity deals, per deal,
with information on the location of investment, investmentcompany, investor firms, and funds, among other details.
The series corresponds to a query on venture capitaldeals from January 1, 2018 to December 31, 2018, with thedata collected by investment location, for a total of 14,856
deals in 78 countries in 2018. The data are reported per
billion PPP$ GDP.

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Source: Thomson Reuters, Thomson One Banker Private
Equity database; International Monetary Fund, World
Economic Outlook Database October 2018 (PPP$ GDP).
(https://www.thomsonone.com); https://www.imf.org/external/pubs/ft/weo/2018/02/weodata/index.aspx).

4.3 Trade, competition, and market scale
4.3.1 Applied tariff rate, weighted average
Tariff rate, applied, weighted average, all products(%)a,b | 2017
“Weighted mean applied tariff” is the average of effectively
applied rates weighted by the product import sharescorresponding to each partner country. Data are classified
using the Harmonized System of trade at the six- oreight-digit level. Tariff line data were matched to Standard
International Trade Classification (SITC) revision 3 codes
to define commodity groups and import weights. To theextent possible, specific rates have been converted totheir ad valorem equivalent rates and have been includedin the calculation of weighted mean tariffs. Effectively
applied tariff rates at the six- and eight-digit product level
are averaged for products in each commodity group.
When the effectively applied rate is unavailable, the mostfavoured nation rate is used instead.
Source: World Bank, based on data from United Nations
Conference on Trade and Development’s Trade Analysis
and Information System (TRAINS) database and theWorld Trade Organization’s (WTO) Integrated Data Base
(IDB) and Consolidated Tariff Schedules (CTS) database;
extracted from World Bank World Development Indicators
database (2011–17). (http://data.worldbank.org/).
4.3.2 Intensity of local competition
Average answer to the survey question: In your country,
how intense is competition in the local markets? [1 = notintense at all; 7 = extremely intense]†a | 2018
Source: World Economic Forum, Executive Opinion
Survey 2018. (https://www.weforum.org/reports/the-global-competitveness-report-2018).
4.3.3 Domestic market scale
Domestic market scale as measured by GDP,bn PPP$ | 2018
The domestic market size is measured by gross domestic
product (GDP) based on the purchasing-power-parity(PPP) valuation of country GDP, in current international
dollars (billions).
Source: World Bank, International Monetary Fund, World
Economic Outlook Database October 2018 (PPP$ GDP).
(https://www.imf.org/external/pubs/ft/weo/2018/02/weodata/index.aspx).

5 Business sophistication
5.1 Knowledge workers
5.1.1 Employment in knowledge-intensive services
Employment in knowledge-intensive services(% of workforce) | 2017
Sum of people in categories 1 to 3 as a percentage of
total people employed, according to the International
Standard Classification of Occupations (ISCO). Categories
included in ISCO-08 are: 1 Managers, 2 Professionals,
and 3 Technicians and associate professionals (years
2009–18). Where ISCO-08 data were not available,
ISCO-88 data were used. Categories included in
ISCO-88 are: 1 Legislators, senior officials and managers;
2 Professionals; 3 Technicians and associate professionals(2009–18). Nigeria uses data from 2013.
Source: International Labour Organization ILOSTAT
Database of Labour Statistics (2009–18). (http://www.ilo.
org/ilostat/).
5.1.2 Firms offering formal training
Firms offering formal training (% of firms) | 2013
The percentage of firms offering formal training programsfor their permanent, full-time employees in the sample offirms in the World Bank’s Enterprise Survey in each country.
Source: World Bank, Enterprise Surveys (2009–17).
(http://www.enterprisesurveys.org/).
5.1.3 GERD performed by business enterprise
GERD: Performed by business enterprise(% of total GDP)a | 2017
Gross expenditure on R&D performed by businessenterprise as a percentage of GDP. For the definitionof GERD see indicator 2.3.2. Islamic Republic of Iranand Zambia use data for 2008.
Source: UNESCO Institute for Statistics, UIS online
database; Eurostat, Eurostat database, 2019; OECD,
Main Science and Technology Indicators MSTI database,2019 (2008–17). (http://data.uis.unesco.org; https://ec.europa.eu/eurostat/data/database; https://stats.oecd.org/Index.
aspx?DataSetCode=MSTI_PUB).
5.1.4 GERD financed by business enterprise
GERD: Financed by business enterprise(% of total GERD)a | 2016
Gross expenditure on R&D financed by businessenterprise as a percentage of total gross expenditure
on R&D. For the definition of GERD see indicator
2.3.2. Albania, Australia, Islamic Republic of Iran, andZambia use data for 2008.

Source: UNESCO Institute for Statistics, UIS online
database; Eurostat, Eurostat database, 2019; OECD, Main
Science and Technology Indicators MSTI database, 2019(2008–17). (http://data.uis.unesco.org; https://ec.europa.
eu/eurostat/data/database; https://stats.oecd.org/Index.
aspx?DataSetCode=MSTI_PUB).
5.1.5 Females employed with advanced degrees
Females employed with advanced degrees, % total
employed (25+ years old)a | 2017
The percentage of females employed with advanced
degrees out of total employed. The employed comprise
all persons of working age who, during a specified brief
period, were in one of the following categories: (1) paid
employment (whether at work or with a job but not atwork); or (2) self-employment (whether at work or with anenterprise but not at work). Data are disaggregated bylevel of education, which refers to the highest levelof education completed, classified according to theInternational Standard Classification of Education (ISCE).
Data for Canada are based on Table 14-10-0020-01 of thecountry’s Labour Force Survey estimates.
Source: International Labour Organization, ILOSTATAnnual Indicators; Statistics Canada. Table 14-10-0020-01
Unemployment rate, participation rate and employment
rate by educational attainment, annual (x 1,000), accessed
February 21, 2019 (2009–18). (http://www.ilo.org/ilostat/;
http://www.statcan.gc.ca/).

5.2 Innovation linkages
5.2.1 University/industry research collaboration
Average answer to the survey question: In your country,
to what extent do businesses and universities collaborate
on research and development (R&D)? [1 = do not collaborate
at all; 7 = collaborate extensively]†a | 2018
Source: World Economic Forum, Executive Opinion
Survey 2018. (https://www.weforum.org/reports/the-global-competitiveness-report-2017-2018).
5.2.2 State of cluster development
Average answer to the survey question on the role ofclusters in the economy: In your country, how widespread
are well-developed and deep clusters (geographic
concentrations of firms, suppliers, producers of related
products and services, and specialized institutions in aparticular field)? [1 = non-existent; 7 = widespread in many
fields]† | 2018
Source: World Economic Forum, Executive Opinion
Survey 2018. (https://www.weforum.org/reports/the-global-competitiveness-report-2017-2018).

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5.2.3 GERD financed by abroad
GERD: Financed by abroad (% of total GERD) | 2016
Percentage of gross expenditure on R&D financed byabroad—that is, with foreign financing as a percentage
of total gross expenditure on R&D in a country. For thedefinition of GERD see indicator 2.3.2. Albania, Australia,
Burundi, and Zambia use data for 2008.
Source: UNESCO Institute for Statistics, UIS online
database; Eurostat, Eurostat database, 2019; OECD, Main
Science and Technology Indicators MSTI database, 2019(2008–18). (http://data.uis.unesco.org; https://ec.europa.
eu/eurostat/data/database; https://stats.oecd.org/Index.
aspx?DataSetCode=MSTI_PUB).
5.2.4 Joint venture/strategic alliance deals
Joint ventures/strategic alliances: Number of deals,
fractional counting (per billion PPP$ GDP)a | 2018
Thomson Reuters data on joint ventures/strategic alliances
deals, per deal, with details on the country of origin ofpartner firms, among others. The series corresponds toa query on joint venture/strategic alliance deals fromJanuary 1, 2018 to December 31, 2018, for a total of 6,880
deals announced in 2017, with firms headquartered in 110
participating economies. Each participating nation of eachcompany in a deal (n countries per deal) gets, per deal,a score equivalent to 1/n (with the effect that all country
scores add up to 6,880). The data are reported per billion
PPP$ GDP.
Source: Thomson Reuters, Thomson One Banker Private
Equity, SDC Platinum database; International Monetary
Fund World Economic Outlook Database, October 2018
(PPP$ GDP). (http://banker.thomsonib.com; https://www.imf.
org/external/pubs/ft/weo/2018/02/weodata/index.aspx).
5.2.5 Patent families filed in two offices
Number of patent families filed by residents in at least two
offices (per billion PPP$ GDP) | 2015
A “patent family” is a set of interrelated patent applications
filed in one or more countries or jurisdictions to protect
the same invention. Patent families containing applications
filed in at least two different offices is a subset of patentfamilies where protection of the same invention is sought
in at least two different countries. In this report, “patentfamilies data” refers to patent applications filed byresidents in at least two IP offices; the data are scaled by
PPP$ GDP (billions). A “patent” is a set of exclusive rights
granted by law to applicants for inventions that are new,non-obvious, and commercially applicable. A patent isvalid for a limited period of time (generally 20 years),
during which patent holders can commercially exploit
their inventions on an exclusive basis. In return, applicants
are obliged to disclose their inventions to the public in amanner that enables others, skilled in the art, to replicate
the invention. The patent system is designed to encourage

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innovation by providing innovators with time-limited
exclusive legal rights, thus enabling them to appropriate
the returns from their innovative activity.
Source: World Intellectual Property Organization, Intellectual
Property Statistics; International Monetary Fund, World
Economic Outlook Database, October 2018 (PPP$ GDP).
(http://www.wipo.int//ipstats/; https://www.imf.org/external/
pubs/ft/weo/2018/02/weodata/index.aspx).

5.3 Knowledge absorption
5.3.1 Intellectual property payments
Charges for use of intellectual property i.e., payments(%, total trade, three-year average)a | 2017
Charges for the use of intellectual property not included
elsewhere payments (% of total trade), average of threemost recent years or available data. Value according to
the Extended Balance of Payments Services Classification
EBOPS 2010—that is, code SH charges for the use of
intellectual property not included elsewhere as a percentage
of total trade. “Total trade” is defined as the sum of total
imports code G goods and code SOX commercial
services (excluding government goods and services notincluded elsewhere) plus total exports of code G goods
and code SOX commercial services (excluding
government goods and services not included elsewhere),
divided by 2. According to the sixth edition of theInternational Monetary Fund’s Balance of Payments
Manual, the item “Goods” covers general merchandise,
net exports of goods under merchanting, andnon-monetary gold. The “commercial services” category isdefined as being equal to “services” minus “government
goods and services not included elsewhere”. Receipts are
between residents and non-residents for the use of
proprietary rights (such as patents, trademarks, copyrights,
industrial processes and designs including trade secrets,
franchises), and for licenses to reproduce or distribute(or both) intellectual property embodied in produced
originals or prototypes (such as copyrights on books andmanuscripts, computer software, cinematographic works,
and sound recordings) and related rights (such as for live
performances and television, cable, or satellite broadcast).
Data for Armenia is for (2012-14), Azerbaijan and Guinea(2011, 2012, 2015), Islamic Republic of Iran (2013-15), Niger(2009, 2014-15), and Rwanda (2008).
Source: World Trade Organization, Trade in Commercial
Services database, based on the sixth (2009) edition of
the International Monetary Fund’s Balance of Payments
and International Investment Position Manual and
Balance of Payments database (2009–17). (http://stat.wto.
org/StatisticalProgram/WSDBStatProgramSeries.aspx;
http://www.oecd.org/std/its/EBOPS-2010.pdf).

5.3.2 High-tech imports
High-tech imports (% of total trade) | 2017
High-technology imports as a percentage of total trade.
High-technology exports and imports contain technicalproducts with a high intensity of R&D, defined by theEurostat classification, which is based on Standard
International Trade Classification (SITC) Revision 4 andthe Organisation for Economic Co-operation andDevelopment (OECD) definition. Commodities belong
to the following sectors: aerospace; computers & officemachines; electronics; telecommunications; pharmacy;
scientific instruments; electrical machinery; chemistry;
non-electrical machinery; and armament.
Source: World Trade Organization, United Nations,
Comtrade database; Eurostat, Annex 5: High-techaggregation by SITC Rev. 4, April 2009 (2015-2017).
(http://comtrade.un.org/; http://ec.europa.eu/eurostat/cache/metadata/Annexes/htec_esms_an5.pdf).
5.3.3 ICT services imports
Telecommunications, computers, and information services
imports (% of total trade) | 2017
Telecommunications, computer and information services
as a percentage of total trade according to the Organisation
for Economic Co-operation and Development (OECD)’s
Extended Balance of Payments Services Classification
EBOPS 2010, coded SI: Telecommunications, computerand information services. For the definition of total trade
see indicator 5.3.1.
Source: World Trade Organization, Trade in Commercial
Services database, based on the sixth (2009) edition of
the International Monetary Fund’s Balance of Payments
and International Investment Position Manual and Balanceof Payments database (2015-17). (http://stat.wto.org/StatisticalProgram/WSDBStatProgramSeries.aspx; http://www.
oecd.org/std/its/EBOPS-2010.pdf).
5.3.4 Foreign direct investment net inflows
Foreign direct investment (FDI), net inflows (% of GDP,
three-year average) | 2017
Foreign direct investment is the average of the mostrecent three years of net inflows of investment to acquirea lasting management interest (10 percent or more of
voting stock) in an enterprise operating in an economy
other than that of the investor. It is the sum of equity
capital, reinvestment of earnings, other long-term capital,and short-term capital as shown in the balance of
payments. This series shows net inflows (new investment
inflows less disinvestment) in the reporting economy
from foreign investors, and is divided by GDP.
Source: International Monetary Fund, International
Financial Statistics and Balance of Payments databases,

World Bank, International Debt Statistics, and World Bankand OECD GDP estimates; extracted from the WorldBank’s World Development Indicators database, 2019.
(http://data.worldbank.org/).
5.3.5 Research talent in business enterprise
Researchers in business enterprise per thousand
population (%) | 2017
“Full-time equivalent (FTE) researchers in the businessenterprise sector” refers to researchers as professionals
engaged in the conception or creation of new knowledge,
products, processes, methods, and systems, as well as in
the management of these projects, broken down by thesectors in which they are employed (business enterprise,government, higher education, and private non-profit
organizations). In the context of R&D statistics, the businessenterprise sector includes all firms, organizations, andinstitutions whose primary activity is the market productionof goods or services (other than higher education) for saleto the general public at an economically significant price,and the private non-profit institutions mainly serving them;the core of this sector is made up of private enterprises.
This also includes public enterprises. Oman uses datafor 2015.
Source: UNESCO Institute for Statistics, UIS online
database; Eurostat, Eurostat database, 2019; OECD, Main
Science and Technology Indicators MSTI database, 2019(2008–17). (http://data.uis.unesco.org; https://ec.europa.
eu/eurostat/data/database; https://stats.oecd.org/Index.
aspx?DataSetCode=MSTI_PUB).

6 Knowledge and technology
outputs
6.1 Knowledge creation
6.1.1 Patent applications by origin
Number of resident patent applications filed at a given
national or regional patent office (per billion PPP$ GDP)a| 2017“Patent” is defined in the description of indicator 5.2.5.
A “resident patent application” refers to an application
filed with an IP office or an office acting on behalf of thestate or jurisdiction in which the first-named applicant has
residence. For example, an application filed with theJapan Patent Office (JPO) by a resident of Japan isconsidered a resident application for Japan. Similarly, anapplication filed with the European Patent Office (EPO)
by an applicant who resides in any of the EPO member
states, for example Germany, is considered a resident
application for that member state (Germany).
Source: World Intellectual Property Organization,
Intellectual Property Statistics; International Monetary

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Fund, World Economic Outlook Database, October 2018
(PPP$ GDP) (2010–17). (http://www.wipo.int/ipstats/; https://www.imf.org/external/pubs/ft/weo/2018/02/weodata/index.aspx).
6.1.2 PCT applications by origin
Number of Patent Cooperation Treaty applications filed byresidents (per billion PPP$ GDP)a | 2018
This is the number of international patent applications
filed through the WIPO-administered Patent Cooperation
Treaty (PCT) in 2018 originating in the country. The PCT
system makes it possible to seek patent protection for an
invention simultaneously in a number of countries by filinga single international patent application. The origin of PCT
applications is defined by the residence of the first-named
applicant. Data is available only for those economies
which are PCT Contracting States.
Source: World Intellectual Property Organization, Intellectual
Property Statistics; International Monetary Fund, World
Economic Outlook Database, October 2018 (PPP$ GDP).
(http://www.wipo.int/ipstats/; https://www.imf.org/external/
pubs/ft/weo/2018/02/weodata/index.aspx).
6.1.3 Utility models by origin
Number of utility model applications filed by residents atthe national patent office (per billion PPP$ GDP) | 2017
These are the number of resident utility model applications
iled at a given national or regional patent office in 2017
A “resident UM application” refers to an application filedwith an IP office of, or an office acting on behalf of, thestate or jurisdiction in which the first-named applicant has
residence. For example, an application filed with the
IP office of Germany by a resident of Germany isconsidered a resident application for Germany. A “utility
model grant” is a special form of patent right issued
by a state or jurisdiction to an inventor or the inventor’s
assignee for a fixed period of time. The terms andconditions for granting a utility model are slightly different
from those for normal patents and include a shorter termof protection and less stringent patentability requirements.
A utility model is sometimes referred to in certain
countries as “petty patents”, “short-term patents”, or“innovation patents”. Data is available only for thoseeconomies with a utility models system.
Source: World Intellectual Property Organization, Intellectual
Property Statistics; International Monetary Fund, World
Economic Outlook Database, October 2018 (PPP$ GDP)
(2010–17). (http://www.wipo.int/ipstats/; https://www.imf.org/
external/pubs/ft/weo/2018/02/weodata/index.aspx).
6.1.4 Scientific and technical publications
Number of scientific and technical journal articles(per billion PPP$ GDP)a | 2018
The number of scientific and engineering articles
published in those fields, including: agriculture, astronomy,360

The Global Innovation Index 2019

astrophysics, automation control systems, biochemistry
molecular biology, biodiversity conservation, biotechnology
applied microbiology, cell biology, chemistry, computerscience, construction building technology, dentistry oral
surgery medicine, engineering, environmental sciences,ecology, evolutionary biology, food science technology,
general internal medicine, life sciences biomedicine andother topics, marine freshwater biology, materials science,
mathematical computational biology, mathematics,
metallurgy and metallurgical engineering, meteorology
atmospheric science, microbiology, nuclear science andtechnology, physics, plant sciences, radiology nuclear
medicine medical imaging, reproductive biology, researchexperimental medicine, science technology and othertopics, telecommunications, transportation, and veterinarysciences. Article counts are from a set of journals coveredby the Science Citation Index (SCI) and the Social Sciences
Citation Index (SSCI). Articles are classified by year of
publication and assigned to each country/economy onbasis of the institutional address(es) listed in the article.
Articles are counted on a count basis (rather than afractional basis)—that is, for articles with collaborating
institutions from multiple countries/economies, eachcountry/economy receives credit on the basis of its
participating institutions. The data are reported per
billion PPP$ GDP.
Source: Clarivate Analytics, special tabulations from
Thomson Reuters, Web of Science, Science Citation Index(SCI), and Social Sciences Citation Index (SSCI);International Monetary Fund, World Economic Outlook
Database, October 2018 (PPP$ GDP). (https://apps.webofknowledge.com; https://www.imf.org/external/pubs/ft/
weo/2018/02/weodata/index.aspx).
6.1.5 Citable documents H-index
The H-index is the economy’s number of publishedarticles (H) that have received at least H citations | 2018
The H-index expresses the journal’s number of articles (H)that have received at least H citations. It quantifies bothjournal scientific productivity and scientific impact, and isalso applicable to scientists, journals, and so on. The
H-index is tabulated from the number of citations received
in subsequent years by articles published in a given year,
divided by the number of articles published that year.
Source: SCImago (2019) SJR—SCImago Journal &Country Rank. Retrieved February 2019. (http://www.
scimagojr.com).

6.2 Knowledge impact
6.2.1 Growth rate of GDP per person engaged
Growth rate of GDP per person engaged (%, three-year
average) | 2018

Growth rate of real GDP per person employed (constant1990 PPP$), average of three last available years. Growthof gross domestic product (GDP) per person engaged
provides a measure of labour productivity (defined as
output per unit of labour input). GDP per person employed
is GDP divided by total employment in the economy. PPP$GDP is Constant 1990 in US dollar, expressed in 1990 GK
PPP, Millions. While this is a relatively robust measure,it does not correct for part-time jobs as it merely counts
people who are employed. Hence, GDP per person
employed is somewhat underestimated in countries witha higher share of part-time workers, which are mostlyOECD countries.
Source: The Conference Board Total Economy
Database™ Output, Labor and Labor Productivity,
1950–2018, November 2018. (https://www.conference-board.org/data/economydatabase/).
6.2.2 New business density
New business density (new registrations per thousand
population 15–64 years old)a | 2016
Number of new firms, defined as firms registered in thecurrent year of reporting, per thousand population aged
15–64 years old. Kenya used data for 2008
Source: World Bank, Doing Business 2018, Entrepreneurship(2008–16). (http://www.doingbusiness.org/data/exploretopics/entrepreneurship).
6.2.3 Total computer software spending
Total computer software spending (% of GDP)a | 2018
Computer software spending includes the total valueof purchased or leased packaged software such as
operating systems, database systems, programming tools,
utilities, and applications. It excludes expenditures forinternal software development and outsourced custom
software development. The data are a combination of
actual figures and estimates. Data are reported as apercentage of GDP.
Source: IHS Markit, Information and Communication
Technology Database. (https://www.ihs.com/index.html).
6.2.4 ISO 9001 quality certificates
ISO 9001 Quality management systems—Requirements:
Number of certificates issued (per billion PPP$ GDP)a |2017
ISO 9001:2015 specifies requirements for a quality
management system when an organization needs todemonstrate its ability to consistently provide products
and services that meet customer and applicable statutory
and regulatory requirements, and aims to enhancecustomer satisfaction through the effective application of
the system, including processes for improving the system
and assuring conformity to customer and applicablestatutory and regulatory requirements. All the requirementsof ISO 9001:2015 are generic and are intended to be
applicable to any organization, regardless of its type orsize, or the products and services it provides. The data
are reported per billion PPP$ GDP. Refer to indicator 3.3.3
for more details.
Source: International Organization for Standardization(ISO), The ISO Survey of certifications to management
system standards, 2017; International Monetary Fund,World Economic Outlook database, October 2018 (PPP$
GDP). (http://www.iso.org; https://www.imf.org/external/
pubs/ft/weo/2018/02/weodata/index.aspx).
6.2.5 High-tech and medium-high-tech output
High-tech and medium-high-tech output (% of total
manufactures output)a | 2016
High-tech and medium-high-tech output as a percentage
of total manufactures output, on the basis of theOrganisation for Economic Co-operation and Development(OECD) classification of Technology Intensity Definition,itself based on International Standard Industrial
Classification ISIC Revision 4 and ISIC Revision 3. ISIC
Revision 4 data were preferred; when not available or notreported for a given country, ISIC Revision 3 data wereused. For all ISIC three-digit classification codes includedin the definition of high-tech and medium-high-tech output
reported as missing for a given country, but for which
four-digit level data were available, the three-digit values
were calculated as the sum of all four-digit codes thatwere available. No data were available for Botswana or
Lebanon. Cameroon uses data for 2008.
Source: United Nations Industrial Development
Organization (UNIDO), Industrial Statistics Database,
3- and 4-digit level of International Standard Industrial
Classification ISIC Revision 4 and Revision 3 (INDSTAT42018); OECD, Directorate for Science, Technology
and Industry, Economic Analysis and Statistics Division,“ISIC Rev. 3 and Rev. 4 Technology Intensity Definition:
Classification of Manufacturing Industries into Categories
Based on R&D Intensities” (2008–16). (http://www.unido.
org/statistics.html; http://stat.unido.org/content/focus/
classification-of-manufacturing-sectors-by-technological-intensity-%2528isic-revision-4%2529;jsessionid=4DB1A3A5812144CACC956F4B8137C1CF; http://www.oecd.
org/sti/ind/48350231.pdf).

6.3 Knowledge diffusion
6.3.1 Intellectual property receipts
Charges for use of intellectual property i.e., receipts(% total trade, three-year average)a | 2017

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Charges for the use of intellectual property not included
elsewhere receipts (% of total trade), average of threemost recent years or available data. Value according
to the Extended Balance of Payments Services
Classification EBOPS 2010—that is, code SH charges forthe use of intellectual property not included elsewhereas a percentage of total trade. Receipts are between
residents and non-residents for the use of proprietary
rights (such as patents, trademarks, copyrights, industrial
processes, and designs including trade secrets,
franchises), and for licenses to reproduce or distribute(or both) intellectual property embodied in produced
originals or prototypes (such as copyrights on books andmanuscripts, computer software, cinematographic works,
and sound recordings) and related rights (such as for live
performances and television, cable, or satellite broadcast).
For definition of total trade see indicator 5.3.1. Data forArmenia is for (2015), Azerbaijan (2011-12, 2014), Benin(2014-16), Burundi (2014-15, 2017), Côte d’Ivoire (2014-16),
Guinea (2013), Islamic Republic of Iran (2013-15), Mali
(2011-12, 2017), Mozambique (2009, 2011 -12), Niger (201516), Rwanda (2009), Tajikistan (2009, 2014), Togo (2010),
Turkey (2017), and Yemen (2009, 2016).

http://www.oecd.org/std/its/EBOPS-2010.pdf).
6.3.4 Foreign direct investment net outflows
Foreign direct investment (FDI), net outflows (% of GDP,
three-year average)a | 2017
“Foreign direct investment” refers to the average of themost recent three years of direct investment equity
flows in an economy. It is the sum of equity capital,
reinvestment of earnings, and other capital. Direct
investment is a category of cross-border investment
associated with a resident in one economy having control
or a significant degree of influence on the managementof an enterprise that is resident in another economy.
Ownership of 10 percent or more of the ordinary shares ofvoting stock is the criterion for determining the existenceof a direct investment relationship. This series shows net
outflows of investment from the reporting economy to therest of the world, and is divided by GDP. The two extreme
bottom outliers in Malta and Iceland were given n/a due toa verified low quality of their time series for that indicator.
Source: International Monetary Fund, International
Financial Statistics and Balance of Payments databases,
World Bank, International Debt Statistics, and World Bankand OECD GDP estimates; extracted from the WorldBank’s World Development Indicators database (2016–17).
(http://data.worldbank.org/).

Source: World Trade Organization, Trade in Commercial
Services database, based on the sixth (2009) edition of
the International Monetary Fund’s Balance of Payments
and International Investment Position Manual and Balanceof Payments database (2009–17). (http://stat.wto.org/StatisticalProgram/WSDBStatProgramSeries.aspx; http://www.
oecd.org/std/its/EBOPS-2010.pdf).
6.3.2 High-tech exports
High-tech net exports (% of total trade)a | 2017
High-technology exports minus re-exports (% of total
trade). See indicator 5.3.2 for details.
Source: World Trade Organization, United Nations,
Comtrade database; Eurostat, Annex 5: High-techaggregation by SITC Rev. 4, April 2009 (2015–17). (http://
comtrade.un.org/; https://ec.europa.eu/eurostat/cache/
metadata/Annexes/htec_esms_an5.pdf).
6.3.3 ICT services exports
Telecommunications, computers, and information services
exports (% of total trade)a | 2017
Telecommunications, computer and information services(% of total trade) according to the Extended Balance ofPayments Services Classification EBOPS 2010, coded SI:
Telecommunications, computer and information services.
Source: World Trade Organization, Trade in Commercial
Services database, based on the sixth (2009) edition of
the International Monetary Fund’s Balance of Payments
and International Investment Position Manual and
Balance of Payments database (2015-17). (http://stat.wto.
org/StatisticalProgram/WSDBStatProgramSeries.aspx;

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7.1

Intangible assets

7.1.1

Trademark application class count by origin
Number of trademark applications issued to residents
at a given national or regional office (per billion PPP$
GDP) | 2017
The count of trademark applications is based on the
total number of goods and services classes specified inresident trademark applications filed at a given national orregional office in 2017. Data refer to trademark application
class counts—the number of classes specified in resident
trademark applications—and include those filed atboth the national office and the regional office, whereapplicable. Data are scaled by PPP$ GDP (billions).
A “trademark” is a sign used by the owner of certain
products or provider of certain services to distinguishthem from the products or services of other companies.
A trademark can consist of words and/or combinationsof words, such as slogans, names, logos, figures andimages, letters, numbers, sounds and moving images,
or a combination thereof. The procedures for registering
trademarks are governed by the legislation andprocedures of national and regional IP offices. Trademark
rights are limited to the jurisdiction of the IP office that
registers the trademark. Trademarks can be registered

by filing an application at the relevant national or regional
office(s) or by filing an international application throughthe Madrid System. A resident trademark application is
one that is filed with an IP office or an office acting on
behalf of the state or jurisdiction in which the applicant
has residence. For example, an application filed with
the Japan Patent Office (JPO) by a resident of Japan isconsidered a resident application for Japan. Similarly, anapplication filed with the Office for Harmonization in theInternal Market (OHIM) by an applicant who resides in anyof the EU member states, such as France, is considereda resident application for that member state (France).
Source: World Intellectual Property Organization, Intellectual
Property Statistics; International Monetary Fund, World
Economic Outlook Database, October 2018 (PPP$ GDP)
(2010–17). (http://www.wipo.int//ipstats/; https://www.imf.
org/external/pubs/ft/weo/2018/02/weodata/index.aspx).
7.1.2 Industrial designs by origin
Number of designs contained in industrial design
applications filed at a given national or regional office(per billion PPP$ GDP)a | 2017
This indicator refers to the number of designs contained
in industrial design applications filed at a given nationalor regional office in 2017. Data refer to industrial design
application counts—the number of designs contained inapplications—and include designs contained in resident
industrial design applications filed at both the national
office and at the regional office, where applicable.
“Resident design counts” refers to the number of designs
contained in applications filed with the IP office of or at an
office acting on behalf of the state or jurisdiction in which
the applicant has residence. For example, an application
filed with the Japan Patent Office (JPO) by a residentof Japan is considered a resident application for Japan.
Similarly, an application filed with the Office for
Harmonization in the Internal Market (OHIM) by anapplicant who resides in any of the OHIM member states,
such as Italy, is considered as a resident application
for that member state (Italy).
Source: World Intellectual Property Organization, Intellectual
Property Statistics; International Monetary Fund, World
Economic Outlook Database, October 2018 (PPP$ GDP)
(2010–17). (http://www.wipo.int//ipstats/; https://www.imf.
org/external/pubs/ft/weo/2018/02/weodata/index.aspx).
7.1.3 ICTs and business model creation
Average answer to the question: In your country, to what
extent do ICTs enable new business models? [1 = not atall; 7 = to a great extent]† | 2018

Survey 2018. (Forthcoming at https://www.weforum.org).
7.1.4 ICTs and organizational model creation
Average answer to the question: In your country, to what
extent do ICTs enable new organizational models (e.g.,
virtual teams, remote working, telecommuting) withincompanies? [1 = not at all; 7 = to a great extent]† | 2018
Source: World Economic Forum, Executive Opinion
Survey 2018. (Forthcoming at https://www.weforum.org).

7.2 Creative goods and servicesa
7.2.1 Cultural and creative services exports
Cultural and creative services exports (% of total trade)a| 2017Creative services exports (% of total exports) according
to the Extended Balance of Payments Services
Classification EBOPS 2010—that is, EBOPS code SI3
Information services; code SJ22 Advertising, market
research, and public opinion polling services; code SK1
Audiovisual and related services; and code SK24
Other personal cultural and recreational services as apercentage of total trade. See 5.3.1 for a full definition of
total trade. On the score for the United States of America(U.S.), this includes SI3 Information services; the category
Movies & TV programming from Table 2.1 (U.S. Trade inServices, BEA) is used in the absence of available data forcode SK1 Audiovisual and related services (the category
Movies & TV programming is specific to the U.S. in BPM6
statistics and does not have a code); the category Sports
and performing arts (U.S. Trade in Services, BEA) is usedinstead of code SK24; the category Advertising (U.S.
Trade in Services, BEA) is used instead of code SJ22.
Costa Rica, Cyprus, Ecuador, Guinea, Malta, Mexico,
Togo show values used in the GII 2018. Due to quality
considerations data for the United Arab Emirates is notconsidered.
Source: World Trade Organization, Trade in Commercial
Services database, based on the sixth (2009) editionof the International Monetary Fund’s Balance of Payments
and International Investment Position Manual and
Balance of Payments database; Bureau of Economic
Analysis (BEA) released October 2017. (2016-2017). (http://
stat.wto.org/StatisticalProgram/WSDBStatProgramSeries.
aspx; http://www.oecd.org/std/its/EBOPS-2010.pdf; https://www.bea.gov/iTable/iTable.cfm).
7.2.2 National feature films produced
Number of national feature films produced (per million
population 15–69 years old)a | 2017

Source: World Economic Forum, Executive Opinion
A film with a running time of 60 minutes or longer.
It includes works of fiction, animation, and documentaries.

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363

It is intended for commercial exhibition in cinemas.
Feature films produced exclusively for television
broadcasting, as well as newsreels and advertising films,
are excluded. Data are reported per million population
15–69 years old. El Salvador uses data for 2008.
Source: UNESCO Institute for Statistics, UIS online
database; United Nations, Department of Economic andSocial Affairs, Population Division, World Population
Prospects: The 2017 Revision (population) (2008-2017).
(http://data.uis.unesco.org; http://esa.un.org/unpd/wpp/).
7.2.3 Entertainment and media market
Global entertainment and media market (per thousand
population 15–69 years old)*a | 2017
The Global entertainment and media outlook (theOutlook) provides a single comparable source of five-year
forecast and five-year historic consumer and advertiser
spending data and commentary for 17 entertainment andmedia segments, across 63 countries. Two new datasets
have been added to this year’s Outlook. Podcasts arecovered for the first time, with data for both monthly
listeners and advertising revenue for 20 markets.
Additionally, the E-sports dataset has been deepened
with the addition of E-sports media rights, providing aricher picture of this fast-emerging market. A numberof changes have also been made to the segmentationof the Outlook to better reflect the shape of the modern
entertainment and media market. The Music and Radio
segments have been merged along with the new Podcasts
data to create the new Music, Radio and Podcasts
segment, reflecting the growing interconnectedness of
the audio entertainment market. And the Video games
segment has been merged with E-sports to create the
new Video games and e-sports segment, capturing theclose relationship between the two markets. The namesof a number of segments have also been changed:
OOH advertising is now simply OOH, and Internet video
is now OTT video. None of the data contained in thesesegments has been affected. Finally, Venezuela has
been removed from the Outlook for this year due to thedifficulty of accurately measuring the entertainment
and media market in that country given its current politicaland economic environment.
A total of 63 countries are represented within the Outlook
spread across North America, Western Europe, Central
Europe, the Middle East and North Africa, Latin America,and Asia Pacific. The score and rankings for the Global
Media Expenditures for the 63 countries considered in the
Outlook report are based on advertising and consumer
digital and non-digital data in US$ millions at average
2018 exchange rates for the year 2018. These results
are reported normalized per thousand population, 15–69
years old, for the year 2018. The figures for Algeria,
Bahrain, Jordan, Kuwait, Lebanon, Morocco, Oman, Qatar,
the Islamic Republic of Iran, Malta, Tunisia, and Yemen
were estimated from a total corresponding to Middle Eastand North Africa (MENA) countries using a breakdown

364

The Global Innovation Index 2019of total GDP (current US$) for the above-mentioned
countries to define referential percentages.
Source: Calculations were derived from PwC’s Global
Entertainment and Media Outlook, 2018–2022; United
Nations, Department of Economic and Social Affairs,
Population Division, World Population Prospects: The 2017
Revision (population); World Economic Outlook Database,
October 2018 (current US$ GDP); Middle East & North
Africa in the World Bank’s DataBank. (http://www.pwc.com/
outlook ; http://esa.un.org/unpd/wpp/ ; https://www.imf.org/
external/pubs/ft/weo/2018/02/weodata/index.aspx; http://
data.worldbank.org/region/middle-east-and-north-africa).
7.2.4 Printing publications and other media output
Printing publications and other media (% of manufactures
total output) | 2016
Printing, and reproduction of recorded media output(ISIC Revision 4 Division 18, group 181 with class 1811 and1812 and group 182 with class 1820) as a percentage of
total manufacturing output (ISIC Revision 4, section C).
Where data for ISIC Revision 4 were not available, datafrom ISIC Revision 3 were used (ISIC Revision 3 group
222, classes 2221, 2222, and 2230). For a more robust
coverage data for Argentina (2002), Ghana (2003),
Trinidad and Tobago (2006), Pakistan (2006), Madagascar(2006), and Lebanon (2007) is used from years prior to2008. Chile used data for 2015.
Source: United Nations Industrial Development
Organization, Industrial Statistics Database; 4-digit levelof International Standard Industrial Classification ISIC
Revision 4 (INDSTAT4 2018) and ISIC Revision 3(INDSTAT2 2018). (2002–17). (http://www.unido.org/statistics.html; http://data.un.org/).
7.2.5 Creative goods exports
Creative goods exports (% of total trade) | 2017
Total value of creative goods exports, net of re-exports(current US$) over total trade. Creative goods as definedin 2009 UNESCO Framework for Cultural Statistics,
Table 3, International trade of cultural goods and services
based on the 2007 Harmonised System (HS 2007).
For the definition of total trade see indicator 5.3.1.
Source: United Nations, Comtrade database; 2009
UNESCO Framework for Cultural Statistics, Table 3,
International trade of cultural goods and services basedon the 2007 Harmonised System (HS 2007); World Trade
Organization, Trade in Commercial Services database,itself based on the sixth (2009) edition of the International
Monetary Fund’s Balance of Payments and International
Investment Position Manual and Balance of Payments
database (2013–17). (http://comtrade.un.org/; http://www.
uis.unesco.org/culture/Documents/framework-cultural-statistics-culture-2009-en.pdf; http://stat.wto.org/StatisticalProgram/WSDBStatProgramSeries.aspx; http://www.oecd.
org/sdd/its/EBOPS-2010.pdf).

7.3 Online creativitya
7.3.1 Generic top-level domains (gTLDs)
Generic top-level domains (gTLDs) (per thousand
population 15–69 years old) | 2018
A generic top-level domain (gTLD) is one of the categories
of top-level domains (TLDs) maintained by the Internet
Assigned Numbers Authority (IANA) for use in the Internet.
Generic TLDs can be unrestricted (.com, .info, .net, and.org) or restricted—that is, used on the basis of fulfilling
eligibility criteria (.biz, .name, and .pro). Of these, thestatistic covers the five generic domains .biz, .info, .org,.net, and .com. Generic domains .name and .pro, andsponsored domains (.arpa, .aero, .asia, .cat, .coop, .edu,.gov, .int, .jobs, .mil, .museum, .tel, .travel, and .xxx) are
not included. Neither are country-code top-level domains(refer to indicator 7.3.2). The statistic represents the total
number of registered domains (i.e., net totals by December
2018, existing domains + new registrations – expired
domains). Data are collected on the basis of a 4% random
sample of the total population of domains drawn from theroot zone files (a complete listing of active domains) for
each TLD. The geographic location of a domain isdetermined by the registration address for the domainname registrant that is returned from a whois query. These
registration data are parsed by country and postal codeand then aggregated to any number of geographic
levels such as county, city, or country/economy. The
original hard data were scaled by thousand population
15–69 years old. For confidentiality reasons, only
normalized values are reported; while relative positions
are preserved, magnitudes are not.
Source: ZookNIC Inc; United Nations, Department of
Economic and Social Affairs, Population Division, World
Population Prospects: The 2017 Revision (population).
(http://www.zooknic.com; http://esa.un.org/unpd/wpp/).
7.3.2 Country-code top-level domains (ccTLDs)
Country-code top-level domains (ccTLDs) (per thousand
population 15–69 years old) | 2018
A country-code top-level domain (ccTLD) is one of thecategories of top-level domains (TLDs) maintained by theInternet Assigned Numbers Authority (IANA) for use in
the Internet. Country-code TLDs are two-letter domains
especially designated for a particular economy, country,
or autonomous territory (there are 255 ccTLDs, in various
alphabets/characters). The statistic represents the total
number of registered domains (i.e., net totals by December
2018, existing domains + new registrations – expired
domains). Data are collected from the registry responsible
for each ccTLD and represent the total number of domain
registrations in the ccTLD. Each ccTLD is assigned to thecountry with which it is associated rather than based on

the registration address of the registrant. ZookNIC reports
that, for the ccTLDs it covers, 85–100% of domains thatare registered in the same country; the only exceptions
are the ccTLDs that have been licensed for commercial
worldwide use. Data are reported per thousand
population 15–69 years old. For confidentiality reasons,only normalized values are reported; while relative
positions are preserved, magnitudes are not.
Source: ZookNIC Inc; United Nations, Department of
Economic and Social Affairs, Population Division, World
Population Prospects: The 2017 Revision (population).
(http://www.zooknic.com; http://esa.un.org/unpd/wpp/).
7.3.3 Wikipedia yearly edits
Wikipedia yearly edits by country (per million population
15–69 years old) | 2017
Data extracted from Wikimedia Foundation’s internal data
sources. For every country with more than 100,000 edit
counts in 2017, the data from 2017 are used; otherwise, forevery country with more than 100,000 edit counts in 2016,
the data from 2016 are used. For all other countries,
the data from 2014 are used. The data exclude bothcontributions to the extent that is identifiable in the data
sources. Data are reported per million population 15–69
years old.
Source: Wikimedia Foundation; United Nations,
Department of Economic and Social Affairs, Population
Division (2014–17). World Population Prospects: The 2017
Revision (population). (https://wikimediafoundation.org;
https://esa.un.org/unpd/wpp/).
7.3.4 Mobile apps creation
Global downloads of mobile apps (scaled by per billion
PPP $ GDP) | 2018
Global downloads of mobile apps, by origin of theheadquarters of the developer/firm, scaled by PPP$ GDP(billions). Global downloads are compiled by App Annie
Intelligence, public data sources, and the company’s
proprietary forecast model based on data from Google
play store and iOS App store in each country between
January 1, 2018 and December 31, 2018. Since data for
China are not available for Google play store and only
for iOS App store, data from China are treated as missing
and considered “n/a”.
Source: Source: App Annie Intelligence; International
Monetary Fund, World Economic Outlook Database,
October 2018 (PPP$ GDP) (2010–17). (https://www.
appannie.com/en/; https://www.imf.org/external/pubs/ft/
weo/2018/02/weodata/index.aspx)

Appendix III

365

366

The Global Innovation Index 2019

A P P E NDIX I V

ADJUSTMENTS TO THE GLOBALINNOVATION INDEX FRAMEWORK,YEAR-ON-YEAR COMPARABILITYOF RESULTS, AND TECHNICAL NOTES
Adjustments to the Global Innovation
Index framework
The Global Innovation Index (GII) is a cross-economy performanceassessment, compiled on an annual basis, which continuously
seeks to update and improve the way innovation is measured.
The GII report pays special attention to making the statistics
used in the Economy Profiles and Data Tables accessible
by providing data sources and definitions, and detailing thecomputation methodology (Appendix II, III, and IV). This
segment summarizes the changes made this year and provides
an assessment of the impact these changes have on thecomparability of rankings.

Centre of the European Commission (JRC). We also collaborate
with private organizations, such as the International Organizationfor Standardization (ISO), IHS Markit, Bureau van Dijk (BvD),
ZookNIC Inc, Thomson Reuters, Wikimedia Foundation, andAppAnnie to obtain the best globally available data on innovation.
Table A-IV.1 provides a summary of adjustments to the GII 2019
framework. A total of seven indicators were modified this year.
One indicator was replaced, five underwent methodologicalchanges, and one’s methodology changed at source.

Methodology and data
The nature of the 2019 adjustments are detailed below:

The GII model is revised every year in a transparent exercise.
This year no change was made at either the pillar or the
sub-pillar level.
Beyond the use of the World Intellectual Property Organization(WIPO) data, we collaborate with public international bodies,such as the International Energy Agency, the United Nations
Educational, Scientific and Cultural Organization (UNESCO), theUnited Nations Industrial Development Organization (UNIDO),
the World Trade Organization (WTO), and the Joint Research

Indicator 1.1.1: Political stability and safety from the World
Banks World Governance Indicators, which measures theperception of the likelihood of political instability and/or politicallymotivated violence, including terrorism, was replaced in 2019by the indicator Political and operational stability. The political,
legal, and operational or security risk index developed by
IHS Markit measures the likelihood and severity of these risks
in relation to their impact on business operations.

TABLE A-IV.1

Changes to the GII 2019 framework
GII 2018

Adjustment

GII 2019

1.1.1 Political stability & safety

Replaced

1.1.1 Political & operational stability

3.3.2 Environmental performance

Indicator changed at source

3.3.2 Environmental performance

5.3.1 Intellectual property payments, % total trade

Methodology change

5.3.1 Intellectual property payments, % total trade (3 year avg.)

5.3.2 High-tech imports, % total trade

Methodology change

5.3.2 High-tech imports, % total trade

6.2.1 Growth rate of PPP$ GDP/worker, %Methodology change

6.2.1 Growth rate of PPP$ GDP/worker, % (3 year avg.)

6.3.1 Intellectual property receipts, % total trade

Methodology change

6.3.1 Intellectual property receipts, % total trade (3 year avg.)

7.3.4 Mobile app creation/bn PPP$ GDP

Methodology change

7.3.4 Mobile app creation/bn PPP$ GDP

Source: Global Innovation Database, Cornell, INSEAD, and WIPO.
Notes: Refer to Appendix I and III for a detailed explanation of terminology and acronyms. Refer to Appendix III for a detailed explanation of methodologicalchanges at source.

Appendix IV

367

Indicator 3.3.2: Environmental performance is an index
produced by Yale University and Columbia University that measuresenvironmental health and ecosystem vitality. This year, themethodology changed, therefore the scores calculated under
the old methodology are not comparable to the new scores.
The methodology underpinning indicators 5.3.1 and 6.3.1,
Intellectual property payments and Receipts, respectively, wasupdated. This year, the GII considers the average of the threemost recent years in order to avoid excessive volatility.
Data for indicator 5.3.2: High-tech net imports are sourced
directly from the United Nations Comtrade rather than fromthe World Integrated Trade Solutions (WITS). The change affects
the calculation for net totals.
For indicator 6.2.1: Growth rate of GDP PPP$ per worker,
the methodology changed to capture the average of the threemost recent years to produce a more stable variable.
Indicator 7.3.4: Mobile app creation, introduced last year tomeasure the number of mobile apps created in an economy,
was adjusted this year to measure the global downloads
of mobile apps by origin of the headquarters of the developeror producing firm.

Missing values
Since its inception, one of the core missions of the GII is toincrease awareness of the importance of submitting timely data.
In recent years, the GII has had a positive influence on datacollection, helping improve the number of data points submitted
to international data agencies. In the GII 2019, with the inclusionof three economies in the GII sample, coverage remains
relatively close to the level seen last year, with 10% of data
points missing.
When it comes to economy coverage, the objective is to include
as many as possible. However, it is also important to maintaina good level of data coverage within each of these economies.
Because the GII results depend on data availability (Appendix V),
which in turn affects the overall GII rankings, the threshold rulefor economies with missing data and the minimum coverage
necessary per sub-pillar were progressively tightened in 2016
and 2017 (Appendix IV: Technical Notes ).
The motivation behind the introduction of these adjustments
is because of data availability, which, historically, was lesssatisfactory when considering innovation outputs in the GII.
For instance, this year, 13.2% of all economies show data
coverage of less than 75% but exhibit over 66% coverage in
the Output Sub-Index, while only 3.2% of these economies havethis coverage range in the Input Sub-Index.
In addition to the economies featured last year, three new
economies, Burundi, Ethiopia, and Nicaragua, are included in
the GII 2019 because data coverage has improved above the
66% threshold in the 27 variables of the Output Sub-Index.
Despite the requirement for a minimum level of coverage, forseveral economies the number of missing data points

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The Global Innovation Index 2019

remains very high. Table A-IV.2 lists the economies with thehighest number of missing data points (20 or more).
Conversely, Table A-IV.3 lists economies with the best data
coverage. These economies are missing five data points at themost while others are missing none.
For the last three years, more stringent rules were introduced,
resulting in significant data coverage improvements for various
economies. Table A-IV.4 shows economies with improved data
coverage from 2016 to 2019. At the same time, fewer economies
witnessed a decline in data coverage, as shown in Table A-IV.5.

Year-on-year comparability of results—
sources of change in the rankings
The GII compares the performance of national innovation
systems across economies, and presents the changes in
economy rankings over time.
Importantly, scores and rankings from one year to the next
are not directly comparable (see GII 2013, Annex 2, for a full
explanation). Making inferences about absolute or relative
performance based on year-on-year differences in rankings
can be misleading. Each ranking reflects the relative positioningof a particular economy based on the conceptual framework,
data coverage, and the sample of economies in a given year,
also reflecting changes in the underlying indicators at source
and in data availability.
A few factors influence year-on-year rankings of an economy:••••

the actual performance of the economy in question;
adjustments made to the GII framework;
data updates, the treatment of outliers, and missing values; andthe inclusion or exclusion of economies in the sample.

Additionally, the following characteristics complicate the time-series
analysis based on simple GII scores or rankings:• Missing values. The GII produces relative index scores,
which means that a missing value for one economy affects
the index score of other economies. Because the numberof missing values decreases every year, this problem
reduces over time.
• Reference year. The data underlying the GII do not refer toa single year but to several years depending on the latest
available year for any given variable. In addition, the reference
years for different variables are not the same for eacheconomy. The motivation for this approach is that it widens
the set of data points for cross-economy comparability.
• Normalization factor. Most GII variables are normalizedusing either GDP or population, with the intention to enablecross-economy comparability. Yet, this implies that year-onyear changes in individual variables may be driven either
by the variable’s numerator or by its denominator.
• Consistent data collection. Measuring the change ofyear-on-year performance relies on the consistent collectionof data over time. Changes in the definition of variables
or in the data collection process could create movementsin the rankings that are unrelated to performance.

TABLE A-IV.2

GII economies with the most missing values
EconomyNumber of
missing values

EconomyNumber of
missing values

EconomyNumber of
missing values

Niger

23

Guinea

21

Togo

20

Nicaragua

22

Nepal

21

Yemen

20

Trinidad and Tobago

20

Source: Global Innovation Database, Cornell, INSEAD, and WIPO.

TABLE A-IV.3

GII economies with the fewest missing values
EconomyNumber of
missing values

EconomyNumber of
missing values

EconomyNumber of
missing values

Turkey0

Bulgaria

2

Morocco3

Romania0

Argentina

2

Costa Rica

3

Thailand0Indonesia

2

Tunisia

3

Malaysia

0

Italy

2

Cyprus

4

Chile

0

Portugal

2

Lithuania

4

Mexico0Philippines

2

Luxembourg

4

Colombia0

Kazakhstan

2

United States of America

4

Russian Federation

1

Finland3

United Kingdom

4Poland1Israel3

Republic of Moldova

4

Hungary

1

Estonia3

New Zealand4

Republic of Korea

2

Sweden

3

Malta

4

France2Singapore3

Latvia4

Ukraine2

Denmark

3

Greece4

Slovenia

2

Switzerland

3

South Africa

4

Czech Republic

2

Serbia

3

Egypt

4

Austria2

Netherlands

3

Canada5

Brazil2

Norway3

Ireland

5

Spain

2

Australia

3

Japan

5

Germany

2

India

3

Panama5

Slovakia

2

Croatia

3

Kenya

5

Belgium

3

Source: Global Innovation Database, Cornell, INSEAD, and WIPO.

Appendix IV

369

TABLE A-IV.4

Indicator coverage improvement, from 2016 to 2019, in % and number
Economy2016-2019

Improvement

NumberEconomy2016-2019

Improvement

NumberBrunei Darussalam

From 30 to 18

15.7%

12

Albania

From 12 to 6

20.6%

6

Algeria

From 17 to 7

25.6%

10

El Salvador

From 14 to 8

17.0%

6

United Arab Emirates

From 17 to 8

22.2%

9

ZambiaFrom 19 to 13

11.9%

6

Mozambique

From 20 to 11

18.1%

9

Tajikistan

From 22 to 16

10.1%

6

Burkina Faso

From 23 to 14

15.3%

9

Togo

From 26 to 20

8.4%

6

Zimbabwe

From 26 to 17

13.2%

9

Trinidad and Tobago*

From 25 to 20

7.2%

5

Yemen

From 29 to 20

11.6%

9

Spain

From 7 to 2

34.1%

5

Cambodia

From 20 to 12

15.7%

8

Netherlands

From 8 to 3

27.9%

5

Honduras

From 21 to 13

14.8%

8

MoroccoFrom 8 to 3

27.9%

5

BurundiFrom 27 to 19

11.1%

8

Ghana

From 16 to 11

11.7%

5

Iran, Islamic Republic of

From 16 to 9

17.5%

7

Namibia

From 18 to 13

10.3%

5

JordanFrom 17 to 10

16.2%

7

RwandaFrom 22 to 17

8.2%

5

Bahrain

From 18 to 11

15.1%

7

Côte d'Ivoire

From 23 to 18

7.8%

5

Montenegro

From 18 to 11

15.1%

7

Malawi

From 23 to 18

7.8%

5

Tunisia

From 9 to 3

30.7%

6

Benin

From 24 to 19

7.5%

5

Malta

From 10 to 4

26.3%

6

Nicaragua

From 27 to 22

6.6%

5

2016-2019

Improvement

Number

Source: Global Innovation Database, Cornell, INSEAD, and WIPO.
Notes: Annualized growth. *Period: 2017 to 2019.

TABLE A-IV.5

Indicator coverage decline, from 2016 to 2019, in % and number
Economy2016-2019

Improvement

NumberEconomyMadagascar

From 15 to 18

6.3%

3

Japan

From 2 to 5

35.7%

3

UgandaFrom 13 to 16

7.2%

3

South Africa

From 2 to 4

26.0%

2

Source: Global Innovation Database, Cornell, INSEAD, and WIPO.
Note: Annualized growth.

370

The Global Innovation Index 2019

A detailed economy study based on the GII database and theeconomy profile over time, coupled with analytical work on
the ground, including innovation actors and decision makers,
yields the best results in terms of grasping an economy’s
innovation performance over time as well as in identifying
possible avenues for improvement.

Technical notes
Audit by the European Commission’sCompetence Centre on Composite Indicators
and Scoreboards (COIN) at the Joint
Research Centre (JRC).
The JRC-COIN has extensively researched the complexity ofcomposite indicators that rank economies’ performances alongpolicy lines. For the ninth consecutive year, the JRC-COIN
has performed a thorough “robustness” and “sensitivity” analysisof the GII to assess structural changes that are made to thelist of indicators by the GII developing team (Table A-IV.1).
The recommendations from the JRC-COIN audit on the GII2018 model were reviewed and incorporated into the GII 2019model. This year, for an economy to feature in the GII 2019, theminimum symmetric data coverage is at least 35 indicators in
the Innovation Input Sub-Index (66%) and 18 indicators in the
Innovation Output Sub-Index (66%), with scores for at least two
sub-pillars per pillar. In 2019, consideration was given to whether
scores for all sub-pillars, for all pillars, would be required for
economies to be considered in the GII. Ultimately, this rule was
not applied this year, but will be reviewed again in 2020 and
implemented if applicable.
A final audit of the GII 2019 model was performed in June 2019
(Appendix V).

Composite indicators
The GII relies on seven pillars, each divided into three sub-pillars,of which include two to five individual indicators. Sub-pillar
scores are calculated using the weighted average of its individual
indicators. Pillar scores are calculated using the weighted
average of its sub-pillar scores.
The notion of weights as important coefficients was revised
this year to ensure a greater statistical coherence of the model,
following the recommendations of the JRC-COIN.1
The GII includes three indices:
1.
		
2.
		
3.
		

The Innovation Input Sub-Index is the average of thefirst five pillar scores.
The Innovation Output Sub-Index is the average of thelast two pillar scores.
The Global Innovation Index is the average of the
Input and Output Sub-Indices.

Economy rankings are provided for indicators, sub-pillars, pillars,
and index scores.
This year, following the advice of the JRC-COIN, the GII introduceda more statistically fitting alternative to analyzing the relation
between innovation inputs and outputs. This approach replaces
the Innovation Efficiency Ratio analysis (see Chapter 1, Figure 1.8
and relevant segment).2

Individual indicators
The GII 2019 model includes 80 indicators, which fall in three
categories:
1. quantitative/objective/hard data (57 indicators),
2. composite indicators/index data (18 indicators), and3. survey/qualitative/subjective/soft data (5 indicators).
Hard data
Hard data (57 indicators) are drawn from a variety of public
and private sources. These include, among others, the United
Nations Educational, Scientific and Cultural Organization(UNESCO), the United Nations Industrial Development
Organization (UNIDO), the World Intellectual Property Organization(WIPO), the World Bank, the Joint Research Centre of theEuropean Commission (JRC), PwC, Bureau van Dijk (BvD), Thomson
Reuters, IHS Markit, Wikimedia Foundation, and AppAnnie.
Indicators are often correlated with population, gross domestic
product (GDP), or some other size-related factor; they requirescaling by a relevant size indicator for economy comparisons to
be valid. Most indicators are either scaled at source or do notneed to be scaled; for the rest, the scaling factor was chosen to
represent a fair picture of economy differences. Scaling affected
40 indicators, which can be broadly divided into four groups:
1. Indicators scaled by GDP in current US$: 2.1.1, 2.3.2, 3.2.3,
4.1.2, 4.1.3, 4.2.2, 5.1.3, 5.3.4, 6.2.3, and 6.3.4.3
2. The count variables 3.3.3, 4.2.3, 5.2.4, 5.2.5, 6.1.1, 6.1.2, 6.1.3,
6.1.4, 6.2.4, 7.1.1, 7.1.2, and 7.3.4 are scaled by GDP in purchasing
power parity current international dollars. This choice ofdenominator was dictated by a willingness to appropriately
account for differences in development stages; in addition,scaling these variables by population would improperly
bias results to the detriment of economies with a large
young or ageing population.4
3. Variables 3.2.1, 5.1.5, 6.2.2, 7.2.2, 7.2.3, 7.3.1, 7.3.2, and 7.3.3
are scaled by population. Total population for 3.2.1, population
25+ years old for 5.1.5, population 15–64 years old for 6.2.2,
and population 15–69 years old for the remaining.5
4. Sectoral indicators 5.3.1, 5.3.2, 5.3.3, 6.3.1, 6.3.2, 6.3.3, 7.2.1,
and 7.2.5 are scaled by total trade; and indicators 6.2.5 and7.2.4 by the total unit used to measure the particular statistic.6

Appendix IV

371

Indices

First rule: selection

Composite indicators are collected from a series of specialized
agencies and academic institutions, such as the World Bank,
the UN Public Administration Network (UNPAN), and Yale andColumbia Universities. Statisticians discourage the use of an“index within an index” on two main grounds: the distorting effectof the different computing methodologies used and the riskof duplicating variables. The normalization procedure partiallysolves the former (more on this below). To avoid the mistakeof including a particular indicator more than once (directly andindirectly through a composite indicator), only indices with anarrow focus (18 in total) were selected.

Problematic indicators were identified by skewness or kurtosis.
The problematic indicators had either:

Any additional disadvantage is outweighed by what is gainedwith model parsimony, acknowledgement of expert opinion,and focus on multi-dimensional phenomena that can hardly be
captured by a single indicator.7
Survey data
Survey data are drawn from the World Economic Forum’s
Executive Opinion Survey (EOS). Survey questions are draftedto capture subjective perceptions on specific topics; five EOS
questions were retained to capture phenomena strongly linked
to innovative activities for which hard data are nonexistent or
have low coverage for economies.

Economy coverage and missing data
This year the GII covers 129 economies, selected basedon the availability of data and achieves the same percentage
of indicator coverage as in the GII 2018 (Appendix IV:
Technical Notes)
For each economy, only the most recent yearly data wasconsidered. As a rule, the GII enforced the cut-off year to be2009 for considering data at the indicator level. A few
exceptions were made for years prior to the cut-off year.8
For the sake of transparency and replicability of results, noadditional effort was made to fill missing values. Missing values
are indicated with “n/a” and are not considered in the sub-pillar
score. However, the JRC-COIN audit assessed the robustnessof the GII modelling choices (i.e., no imputation of missing data,
fixed predefined weights, and arithmetic averages) by imputing
missing data, applying random weights, and using geometricaverages. Since 2012, based on this assessment, a confidence
interval has been provided for each ranking in the GII as well as
the Input and Output Sub-Indices (Appendix V).

Treatment of series with outliers
Potentially problematic indicators with outliers that could
polarize results and unduly bias the rankings were treatedaccording to the rules listed below, as per the recommendationsof the JRC-COIN. This affected 29 indicators; 27 out of the
57 hard data indicators and 2 out of the 18 composite indicators.

372

The Global Innovation Index 2019

• an absolute value of skewness greater than 2.25, or• a kurtosis greater than 3.5.9

Second rule: treatment
Series with one to five outliers (24 cases) were winsorized; thevalues distorting the indicator distribution were assigned the next
highest value, up to the level where skewness and/or kurtosis
entered within the ranges specified above.10
With two exceptions (see note 10) for series with five or more
outliers, skewness and/or kurtosis entered within the ranges
specified above after multiplication by a given factor f andtransformation by natural logs.11 Since only “goods” wereaffected (i.e., indicators for which higher values indicate better
outcomes, as opposed to “bads”), the formula used was:…where “min” and “max” are the minimum and maximum
indicator sample values.
For one case, neither winsorization nor multiplication by a given
factor plus log transformation brought the series within thedesired parameters.12 For this particular case a variant of a Box-Coxtransformation, defined as Yeo-Johnson, was applied to theentire series with a λ=0.6. The formula used was:wℎere 0 ≤ λ ≤ 2; λ ≠ 0; y ≥ 0; and yi = economy value

Normalization
The 80 indicators were then normalized into the [0, 100] range,
with higher scores representing better outcomes. Normalization
was according to the min-max method; where the min and max
values were given by the minimum and maximum indicatorsample values respectively. The exception for index and survey
data, for which the original series range of values was kept as
min and max values (for example, [0, 1] for UNPAN indices; [1, 7]
for the World Economic Forum Executive Opinion Survey
questions; [0, 100] for World Bank’s World Governance Indicators;etc.). The following formula was applied:businesses (6.2.2); Cameroon (2008) in High- & medium-high-tech
manufactures (6.2.5); El Salvador (2008) in National feature films (7.2.2);
and Argentina (2002), Lebanon (2007), Trinidad and Tobago (2006),
Pakistan (2006), Ghana (2003), Cameroon (2008), and Madagascar(2006) in Printing & other media (7.2.4).

Notes:
1

Paruolo, P. et al. (2013) show that a theoretical inconsistency exists
between the real theoretical meaning of weights and the meaning
generally attributed to them by the standard practice in constructing
composite indicators that use them as importance coefficients incombination with linear aggregation rules. The approach followed in
the GII this year, as last year, is to assign weights of 0.5 or 1.0 to eachcomponent in a composite to ensure the highest correlations between
them (i.e., indicator/sub-pillar, sub-pillar/pillar, etc.). Two sub-pillars(7.2 Creative goods and services, and 7.3 Online creativity) and 35
indicators (1.1.1, 1.2.1, 1.2.2, 2.1.4, 2.1.5, 2.2.1, 2.2.3, 3.2.1, 3.2.2,
3.3.3, 4.2.2, 4.2.3, 4.3.1, 4.3.2, 5.1.3, 5.1.4, 5.1.5, 5.2.1, 5.2.4, 5.3.1,
6.1.1, 6.1.2, 6.1.4, 6.2.2, 6.2.3, 6.2.4, 6.2.5, 6.3.1, 6.3.2, 6.3.3, 7.1.2,
7.2.1, 7.2.2, and 7.2.3) are weighted 0.5; the rest have a weight of 1.
This year the weights for three indicators were adjusted to provide
higher statistical coherence (5.2.5 Patent families 2+ offices and 6.1.5
Citable documents H-index now have a weight of 1 and 6.3.4FDI net
outflows a weight of 0.5).

2

To account for differences in development, other composite indicators
use weighting schemes differentiated by income level.

3

These indicators are expenditure on education (2.1.1); gross expenditure
on R&D (GERD) (2.3.2); gross capital formation (3.2.3); domestic credit
to private sector (4.1.2); microfinance institutions' gross loan portfolio(4.1.3); market capitalization (4.2.2); GERD performed by businessenterprise (5.1.3); foreign direct investment net inflows (5.3.4); total
computer software spending (6.2.3); and foreign direct investment net
outflows (6.3.4).

9

Based on Groeneveld and Meeden (1984), which sets the criteria ofabsolute skewness above 1 and kurtosis above 3.5. The skewness
criterion was relaxed to account for the small sample at hand(129 economies).

10

This distributional issue affects the following variables: 3.2.1, 4.2.3,
5.3.2, 5.3.3, 6.1.5, and 7.2.4 (1 outlier); 4.2.2, 5.2.4, 5.3.1, 6.1.3, 7.1.2,
7.2.1, 7.2.2, 7.3.2, and 7.3.4 (2 outliers); 2.2.3, 6.1.1, and 6.3.3 (3 outliers);
4.1.3 and 5.2.5 (4 outliers); and 6.1.2, 6.3.1, and 7.2.5 (5 outliers).
The treatment criterion was relaxed this year to allow two series (6.3.2
and 6.3.4) with 6 outliers. For two particular economies—Malta and
Iceland— values were removed for indicator 6.3.4. The reason for thiswas twofold: first, the data did not seem to capture the noted historic
trend for these economies for this variable; second, the data produced
a distortion in skewness and kurtosis for the indicator that neither
winsorization nor any transformation could adequately correct.

11

This distributional issue affects variables 2.3.3 and 4.3.3 (factor f of 1).

12

These formulas achieve two things: converting all series into “goods”
and scaling the series to the range [1, max] so that natural logs
are positive starting at 0. Where “min” and “max” are the minimum andmaximum indicator sample values.
The corresponding formula for bads is:

4

5

6

These count variables are mainly indicators that increase disproportionately
with economic growth. They include: ISO 14001 environmental
certificates (3.3.3); venture capital deals; (4.2.3) joint venture/strategic
alliance deals; (5.2.4) patent families filed in two or more offices (5.2.5);
patent applications by origin (6.1.1); PCT international applications byorigin (6.1.2); utility model applications by origin (6.1.3); scientific andtechnical publications (6.1.4); ISO 9001 quality certificates (6.2.4);
trademark application class count by origin (7.1.1); industrial designs byorigin (7.1.2); and mobile app creation (7.3.4)
These variables are electricity output (3.2.1); females employed withadvanced degrees (5.1.5); new business density (6.2.2); nationalfeature films produced (7.2.2); entertainment and media market (7.2.3);
generic (7.3.1) and country-code (7.3.2) top-level Internet domains; andWikipedia yearly edits (7.3.3).
Intellectual property payments (5.3.1); high-tech net imports (5.3.2); ICTservices imports (5.3.3); intellectual property receipts (6.3.1); high-tech
net exports (6.3.2); ICT services exports (6.3.3); cultural and creative
services exports (7.2.1); and creative goods exports (7.2.5) were scaled
by total trade; high-tech and medium-high-tech output (6.2.5) andprinting and other media (7.2.4) were scaled by total manufactures output.

7

For example, GII sub-pillar 3.1 Information and communication technologies(ICTs) is composed of four indices: ICT Access and Use sub-indices,and UNPAN’s Government Online Service and E-Participation indices.
The first two, previously part of ITU’s ICT Development Index, are now
produced by the GII independently from other components from thatoriginal index, following the methodology of the ITU’s ICT Development
Index 2017. Similarly, the Online Service Index is a component of
UNPAN’s E-Government Development Index together with two indiceson Telecommunication Infrastructure and Human Capital that were
not considered, as they duplicate GII pillars 3 and 2, respectively. The
e-Participation Index was developed separately by UNPAN in 2010.

8

A total of 37 economies in 14 indicators show data that is previous to2009. These are Saudi Arabia (2008), Egypt (2008), Algeria (2008),
Zambia (2008), Yemen (2008) in Expenditure on education (2.1.1);
Botswana (2008) and Cambodia (2008) in School life expectancy(2.1.3); Argentina (2008) in Pupil-teacher ratio (2.1.5); Philippines (2008)
in Tertiary inbound mobility (2.2.3); Albania (2008) and Zambia (2008) in
Researchers (2.3.1) and Gross expenditure on R&D (2.3.2); Iran (Islamic
Republic of) (2008), Zambia (2008) in GERD performed by business(5.1.3); Australia (2008), Iran (Islamic Republic of) (2008), Albania (2008),
Zambia (2008) in GERD financed by business (5.1.4); Australia (2008),
Albania (2008), Zambia (2008), Burundi (2008) in GERD financed byabroad (5.2.3); Iran (Islamic Republic of) (2008), Panama (2008), Ecuador(2008), Zambia (2008) in Research talent (5.3.5); Kenya (2008) in New

13This distributional issue affected variable 5.3.4 Foreign direct
investment net inflows.

14

For negative values in that series the formula used was:wℎere 0 ≤ λ ≤ 2; λ ≠ 2; y < 0; λ; and yi = economy value

References:
Groeneveld, R. A., & Meeden, G. (1984). Measuring Skewness and Kurtosis.
The Statistician, 33, 391–99.
Paruolo P., Saisana, M., & Saltelli, A. (2013). Ratings and Rankings: Voodoo
or Science?. Journal of the Royal Statistical Society, A 176(2), doi:
0964–1998/13/176000.

Appendix IV

373

374

The Global Innovation Index 2019

A P P E NDIX VJOINT RESEARCH CENTRE (JRC)
STATISTICAL AUDIT OF THE
2019 GLOBAL INNOVATION INDEX
Michaela Saisana, Marcos Domínguez-Torreiro, Daniel Vértesy, and Marcos Alvarez,
European Commission, Joint Research Centre (JRC), Ispra, Italy

Conceptual and practical challenges are inevitable when trying
to understand and model the fundamentals of innovation at thenational level worldwide. In its 12th edition, the Global Innovation
Index (GII) 2019 considers these conceptual challenges in
Chapter 1 and deals with practical challenges—related to data
quality and methodological choices—by grouping economy-level
data over 129 economies; and across 80 indicators into 21
sub-pillars, 7 pillars, 2 sub-indices and, finally, an overall index.
This appendix offers detailed insights into the practical issues
related to the construction of the GII, analysing the statisticalsoundness of the calculations and assumptions made to arriveat the final index rankings. Statistical soundness should be
regarded as a necessary but not sufficient condition fora sound GII; since the correlations underpinning the majority ofthe statistical analyses carried out herein “need not necessarily
represent the real influence of the individual indicators on thephenomenon being measured”.1 Consequently, the developmentof the GII must be nurtured by a dynamic iterative dialogue
between the principles of statistical and conceptual soundnessor, to put it another way, between the theoretical understandingof innovation and the empirical observations of the data
underlying the variables.
The European Commission’s Competence Centre on Composite
Indicators and Scoreboards (COIN) at the Joint Research Centre(JRC) in Ispra has been invited for the ninth consecutive year
to audit the GII. As in previous editions, the present JRC-COIN
audit focuses on the statistical soundness of the multi-levelstructure of the index as well as on the impact of key modelingassumptions on the results.2 The independent statistical assessmentof the GII provided by the JRC-COIN guarantees the transparency
and reliability of the index for both policy-makers and otherstakeholders, thus facilitating more accurate priority setting andpolicy formulation in the innovation field.
As in past GII reports, the JRC-COIN analysis complements the
economy rankings with confidence intervals for the GII, theInnovation Input Sub-Index, and the Innovation Output Sub-Index,
in order to better appreciate the robustness of these ranks tothe computation methodology. Finally, the JRC-COIN analysis
includes an assessment of the added value of the GII and ameasure of distance to the efficient frontier of innovation byusing data envelopment analysis.

Conceptual and statistical coherencein the GII framework
An earlier version of the GII model was assessed by the JRCCOIN in April/May 2019. Fine-tuning suggestions were taken
into account in the final computation of the rankings in an
iterative process with the JRC-COIN aimed at setting thefoundation for a balanced index. The entire process followed
four steps (Figure A-V.1).

Step 1: conceptual consistency
Eighty indicators were selected for their relevance to a specificinnovation pillar based on literature review, expert opinion,
economy coverage, and timeliness. To represent a fair pictureof economy differences, indicators were scaled either at sourceor by the GII team, as appropriate, and where needed. For
example, Expenditure on education (indicator 2.1.1) is expressed
as a percentage of GDP, while Government funding per pupil
at secondary level (indicator 2.1.2), is expressed as a percentage
of GDP per capita.

Step 2: data checks
The data, which were most recently released within the period
2008 to 2018, were used for each economy: 78% of theavailable data refer to 2017 or more recent years. The exception
are data values for six economies: Argentina, Lebanon, Trinidad
and Tobago, Pakistan, Ghana, and Madagascar, on Printing &other media, % manufacturing (indicator 7.2.4) that refer to theperiod 2002 to 2007. The JRC-COIN recommendation was tooffer an explanation behind the choice to use data that may notreflect recent advances in the relevant field in these economies(Appendix III). In past editions, until 2015, economies were
included if data availability was at least 60% across all variablesin the GII framework. More stringent criterion were adopted
in 2016, following the JRC-COIN recommendation in past GII
audits, where economies were only included if data availability
was at least 66% within each of the two sub-indices (i.e., 35 outof 53 variables within the Input Sub-Index and 18 out of the 27
variables in the Output Sub-Index) and where at least two of
the three sub-pillars in each pillar could be computed. These

Appendix V

375

FIGURE A-V.1

Conceptual and statistical coherencein the GII 2019 framework
STEP 4.
QUALITATIVE REVIEWInternal qualitative review(INSEAD, WIPO, and Cornell University)
External qualitative review(JRC-COIN, international experts)

STEP 3.
STATISTICAL COHERENCE
Treatment of pairs of highly collinear variables
as a single indicator
Assessment of grouping indicators into sub-pillars,
pillars, sub-indices, and the GII
Use of weights as scaling coeﬃcients to ensurestatistical coherence
Assessment of arithmetic average assumption
Assessment of potential redundancy of informationin the overall GII

criterion aim to ensure that economy scores for the GII and forthe two Input and Output Sub-Indices are not particularly
sensitive to missing values (as was the case for the Output
Sub-Index scores of several economies in past editions).
In practice, data availability for all economies included in the
GII 2019 is good: 80% of data is available for 87% of the economies(equivalent to 112 economies out of 129). Potentially problematic
indicators that could bias the overall results were identified on
the basis of two measures related to the shape of the distributions:skewness and kurtosis. Since 2011, and decided jointly with
the JRC-COIN, values were treated if the indicators had absoluteskewness greater than 2.0 and kurtosis greater than 3.5.
In 2017, and after having analyzed data in the GII 2011 to theGII 2017, a less stringent criterion were adopted. An indicator
was only treated if the absolute skewness was greater than
2.25 and kurtosis greater than 3.5.3 These indicators weretreated either by winsorization or by natural logarithm (in casesof more than five outliers; Appendix IV: Technical Notes). In
2018, an exceptional behaviour for FDI net outflows (indicator
6.3.4) was observed (Chapter 1, Annex 3, JRC Audit, 2018)
and from 2018 on, it was recommended to adjust the GII rule
for the treatment of outliers as follows:(a) for indicators with absolute skewness greater than 2.25
and kurtosis greater than 3.5, apply either winsorization or
the natural logarithm (in case of more than five outliers);(b) for indicators with absolute skewness of less than 2.25 andkurtosis greater than 10.0, produce scatterplots to identify
potentially problematic values that need to be consideredas outliers and treated accordingly.

Step 3: statistical coherence
STEP 2.
DATA CHECKSCheck for data recency (78% of available
data refer to 2017 and 2018)
Availability requirements per economy:
coverage ≥66% for the Input and the Output
Sub-Indices, separately and data availability forat least two sub-pillars per pillar
Check for reporting errors (interquartile range)
Outlier identiﬁcation (skewness and kurtosis)
and treatment (winsorisation or logarithmictransformation)
Direct contact with data providers

STEP 1.
CONCEPTUAL CONSISTENCY
Compatibility with existing literature on
innovation and pillar deﬁnition
Use of scaling factors (denominators) per indicator
to represent a fair picture of country
diﬀerences (e.g., GDP, population)
Source: European Commission, Joint Research Centre, 2019.

376

The Global Innovation Index 2019

Weights as scaling coefficients
Jointly decided between the JRC-COIN and the GII team in 2012,weights of 0.5 or 1.0 were to be scaling coefficients and notimportance coefficients, with the aim of arriving at sub-pillar andpillar scores that were balanced in their underlying components(i.e., that indicators and sub-pillars can explain a similar amountof variance in their respective sub-pillars/pillars). Becker, W. et al.
(2017) and Paruolo, P. et al. (2013) show that, in weighted
arithmetic averages, the ratio of two nominal weights gives
the rate of substitutability between two indicators, and hence
can be used to reveal the relative importance of individual
indicators. This importance can then be compared with ex-postmeasures of variables’ importance, such as the non-linear
Pearson correlation ratio. As a result of this analysis, 35 outof 80 indicators and two sub-pillars—7.2 Creative goods andservices and 7.3 Creation of online content—were assigned half
weights, while all other indicators and sub-pillars were assigned
a weight of 1.0. In past GII editions, despite this weighting
adjustment, a small number of indicators (seven in the GII 2017
edition) were found to be non-influential in the GII framework,
implying that they could not explain at least 9% of economy
variation in the respective sub-pillar scores.4 This year, as it was
the case also in 2018, all 80 indicators are found to be sufficiently influential in the GII framework, which is worthy highlighting asa very positive feature of this year’s GII framework.

Principal components analysis and reliability item analysis
Principal component analysis (PCA) was used to assess to what
extent the conceptual framework is confirmed by statistical
approaches. PCA results confirm the presence of a single latentdimension in each of the seven pillars (one component with an
eigenvalue greater than 1.0) that captures between close to 55%(pillar 4: Market sophistication) up to 83% (pillar 1: Institutions) of
the total variance in the three underlying sub-pillars. Furthermore,
results confirm the expectation that the sub-pillars are morecorrelated to their own pillar than to any other pillar and that all
correlation coefficients are close to or greater than 0.70. (Table A-V.1).

Finally, an important part of the analysis relates to clarifying theimportance of the Input and Output Sub-Indices with respect tovariation in the GII scores. The GII is built as a simple arithmetic
average of the five input sub-pillars and the two output sub-pillars,
which implies that the input-related pillars have a weight of 5/7
versus a weight of 2/7 for the output-related pillars. Yet this does
not imply that the Input aspect is more important than the
output aspect in determining the variation of the GII scores.
In fact, the Pearson correlation coefficient of either the Input or
the Output Sub-Index with the overall GII is 0.97 (and the two
sub-indices have a correlation of 0.89), which suggests that the
sub-indices are effectively placed on equal footing.

The five input pillars share a single statistical dimension thatsummarizes 82% of the total variance, and the five loadings(correlation coefficients) of these pillars are very similar to eachother (0.84–0.93). This similarity suggests that the five pillars
make roughly equal contributions to the variation of theInnovation Input Sub-Index scores, as envisaged by the developing
team. The reliability of the Input Sub-Index, measured by the
Cronbach alpha value, is very high at 0.94—well above the 0.70
threshold for a reliable aggregate.5

Overall, the tests so far show that the grouping of variables into
sub-pillars, pillars, and an overall index is statistically coherent
in the GII 2019 framework, and that the GII has a balanced
structure at each aggregation level. Furthermore, this year,
all 80 indicators are found to be sufficiently influential in the
GII framework, namely each indicator explains at least 9% of
countries variation in the respective sub-pillar scores, which
is worthy highlighting as a very positive feature of this year’s
GII framework.6

The two output pillars—Knowledge and technology outputs andCreative outputs—are strongly correlated to each other (0.80);
they are also both strongly correlated with the Innovation Output
Sub-index (0.94 to 0.96).

Added value of the GII
As already discussed, the Input and Output Sub-Indices correlatestrongly with each other and with the overall GII. Furthermore,
the five pillars in the Input Sub-Index have a very high statistical

TABLE A-V.1

Statistical coherence in the GII: correlations between sub-pillars and pillars
Sub-pillar

Institutions

Human
capital andresearch

Infrastructure

1.1. Political environment

0.95

0.81

0.88

0.73

0.82

0.73

0.82

1.2. Regulatory environment

0.92

0.70

0.72

0.63

0.74

0.64

0.74

1.3. Business environment

0.86

0.69

0.70

0.63

0.68

0.65

0.61

2.1. Education

0.60

0.81

0.61

0.50

0.57

0.55

0.55

2.2. Tertiary education

0.62

0.81

0.69

0.52

0.50

0.52

0.56

2.3. Research and development (R&D)

0.77

0.88

0.76

0.69

0.88

0.86

0.74

Innovation

3.1. Information and communication technologies (ICTs)

0.81

0.84

0.94

0.71

0.74

0.71

0.78

Input

3.2. General infrastructure

0.56

0.54

0.70

0.48

0.50

0.50

0.48

Sub-index

3.3. Ecological sustainability

0.64

0.56

0.75

0.44

0.61

0.56

0.69

4.1. Credit

0.70

0.62

0.61

0.88

0.62

0.55

0.62

4.2. Investment

0.35

0.26

0.21

0.63

0.28

0.23

0.21

4.3. Trade, competition, and market scale

0.53

0.68

0.71

0.68

0.61

0.66

0.59

5.1. Knowledge workers

0.79

0.83

0.79

0.69

0.89

0.78

0.75

5.2. Innovation linkages

0.63

0.57

0.53

0.52

0.81

0.67

0.66

5.3. Knowledge absorption

0.65

0.64

0.62

0.49

0.85

0.80

0.65

6.1. Knowledge creation

0.71

0.81

0.69

0.65

0.84

0.90

0.79

6.2. Knowledge impact

0.54

0.60

0.59

0.47

0.57

0.80

0.60

6.3. Knowledge diffusion

0.65

0.65

0.64

0.54

0.82

0.88

0.66

7.1. Intangible assets

0.62

0.61

0.68

0.53

0.63

0.66

0.88

7.2. Creative goods and services

0.67

0.61

0.69

0.59

0.65

0.64

0.82

7.3. Online creativity

0.80

0.72

0.73

0.59

0.82

0.76

0.84

Innovation
OutputSub-index

MarketBusiness
Knowledge
sophistication sophistication & technology
outputs

Creative
outputs

Source: European Commission Joint Research Centre, 2019.

Appendix V

377

TABLE A-V.2

Statistical coherence in the GII: correlations between sub-pillars and pillars
Innovation Input
Sub-Index
Rank differences (positions)Innovation Output
Sub-Index

Institutions%

Human capitaland research%

Infrastructure%Marketsophistication%

Businesssophistication%

Knowledge &technology
outputs%

More than 30

12.4%

10.1%

10.1%

24.0%

11.6%

10.1%

7.0%

20-29

13.2%

13.2%

10.1%

17.8%

14.0%

12.4%

10.1%

10-19

28.7%

30.2%

24.0%

30.2%

20.2%

25.6%

21.7%

10 or more*

54.3%

53.5%

44.2%

72.1%

45.7%

48.1%

38.8%

5-9

22.5%

24.0%

29.5%

7.0%

19.4%

25.6%

27.1%

Less than 5

20.9%

22.5%

25.6%

17.1%

31.0%

22.5%

30.2%

Same rank

2.3%

0.0%

0.8%

3.9%

3.9%

3.9%

3.9%

100.0%

100.0%

100.0%

100.0%

100.0%

100.0%

100.0%

0.90

0.90

0.89

0.78

0.92

0.93

0.92

Total**
Pearson correlation coefficient with the GII

Creative
outputs%

Source: European Commission Joint Research Centre, 2019.
Notes: *This column is the sum of the prior three rows. **This column is the sum of all white rows.

reliability. These results—the strong correlation between Input
and Output Sub-Indices and the high statistical reliability of
the five input pillars—may be interpreted by some as a sign ofredundancy of information in the GII. The tests conducted by the
JRC-COIN confirm that this is not the case. In fact, for more than
44% (up to 72%) of the 129 economies included in the GII 2019,
the GII ranking and any of the seven pillar rankings differ by
10 positions or more (Table A-V.2). This is a desired outcome
because it demonstrates the added value of the GII ranking,which helps to highlight other aspects of innovation that do not
emerge directly by looking into the seven pillars separately.
At the same time, this result points to the value of duly taking
into account the GII pillars, sub-pillars, and individual indicatorson their own merit. By doing so, economy-specific strengths andbottlenecks on innovation can be identified and serve as an
input for evidence-based policymaking.

Step 4: qualitative review
Finally, the GII results—including overall economy classifications
and relative performances in terms of the Innovation Input or
Output Sub-Indices—were evaluated to verify that the overall
results are, to a great extent, consistent with current evidence,existing research, and prevailing theory. Notwithstanding thesestatistical tests and the positive outcomes on the statisticalcoherence of the GII structure, the GII model is and has toremain open for future improvements as better data, morecomprehensive surveys and assessments, and new relevant
research studies become available.

378

The Global Innovation Index 2019

The impact of modeling assumptions
on the GII results
An important part of the GII statistical audit is to check the effectof varying assumptions inside plausible ranges. Modelingassumptions with a direct impact on the GII scores and rankings
relate to:• setting up an underlying structure for the index based on abattery of pillars,• choosing the individual variables to be used as indicators,• deciding whether (and how) or not to impute missing data,• deciding whether (and how) or not to treat outliers,• selecting the normalization approach to be applied,• choosing the weights to be assigned, and• deciding on the aggregation rule to be implemented.
The rationale for these choices is manifold. For instance, expert
opinion coupled with statistical analysis is behind the selectionof the individual indicators, common practice and ease ofinterpretation suggests the use of a min-max normalization
approach in the [0–100] range, the treatment of outliers is driven
by statistical analysis, and simplicity and parsimony criteria seemto advocate for not imputing missing data. The unavoidable
uncertainty stemming from the above-mentioned modelingchoices is accounted for in the robustness assessment carriedout by the JRC-COIN. More precisely, the methodology applied
herein allows for the joint and simultaneous analysis of the
impact of such choices on the aggregate scores, resulting inerror estimates and confidence intervals calculated for the GII2019 individual economy rankings.

As suggested in the relevant literature on composite indicators,7
the robustness assessment was based on Monte Carlo simulationand multi-modeling approaches, applied to “error-free” data
where potential outliers and eventual errors and typos havealready been corrected in a preliminary stage. In particular, thethree key modeling issues considered in the assessment of the
GII were the treatment of missing data, the pillar weights, andthe aggregation formula used at the pillar level.
Monte Carlo simulation comprised 1,000 runs of different sets
of weights for the seven pillars in the GII. The weights wereassigned to the pillars based on uniform continuous distributions
centered in the reference values. The ranges of simulated
weights were defined by considering both the need for a wide
enough interval to allow for meaningful robustness checks
and the need to respect the underlying principle of the GII that
the Input and the Output Sub-Indices should be placed onequal footings. As a result of these considerations, the limit
values of uncertainty for the five input pillars are between
10% and 30%; the limit values for the two output pillars are
between 40% and 60%. (Table A-V.3).
The GII developing team, for transparency and replicability, has
always opted not to estimate missing data. The “no imputation”
choice, which is common in similar contexts, might encourage
economies not to report low data values. Yet this is not the casefor the GII. After 12 editions of the GII, the index-developing
team has not encountered any intentional no-reporting strategy.
The consequence of the “no imputation” choice in an arithmetic
average is that it is equivalent to replacing an indicator’s missing
value for a given economy with the respective sub-pillar score.
Hence, the available data (indicators) in the incomplete pillar
may dominate, sometimes biasing the ranks up or down. To

test the impact of the “no imputation” choice, the JRC-COIN
estimated missing data using the Expectation Maximization (EM)algorithm that was applied within each GII pillar.8
Regarding the aggregation formula, decision-theory practitioners
challenge the use of simple arithmetic averages because of
their fully compensatory nature, in which a comparative highadvantage on a few indicators can compensate a comparative
disadvantage on many indicators.9 To assess the impact of thiscompensability issue, the JRC-COIN relaxed the strong perfect
substitutability assumption inherent in the arithmetic averageand considered instead the geometric average, which is apartially compensatory approach that rewards economies withbalanced profiles and motivates economies to improve in the GII
pillars in which they perform poorly, and not just in any GII pillar.10
Four models were tested based on the combination of no
imputation versus EM imputation, and arithmetic versus geometricaverage, combined with 1,000 simulations per model (random
weights versus fixed weights), for a total of 4,000 simulations
for the GII and each of the two sub-indices (Table A-V.3 for asummary of the uncertainties considered).

Uncertainty analysis results
The main results of the robustness analysis are shown in Figure A-V.2
with median ranks and 90% confidence intervals computed
across the 4,000 Monte Carlo simulations for the GII and the two
sub-indices. The figure orders economies inn ascending order(best to worst) according to their reference rank (black line), thedot being the median rank over the simulations.

TABLE A-V.3

Uncertainty parameters: missing values, aggregation and weights
Reference

Alternative

I. Uncertainty in the treatment of missing values 		

No estimation of missing data

Expectation Maximization (EM)II. Uncertainty in the aggregation formula at pillar level		

Arithmetic average

Geometric average

III. Uncertainty intervals for the GII pillar weights
			

GII Sub-Index
Innovation Input

Innovation Output

Pillar

Reference value for the weight

Distribution assigned forrobustness analysis

Institutions

0.2

U[0.1,0.3]

Human capital and research0.2

U[0.1,0.3]

Infrastructure0.2

U[0.1,0.3]

Market sophistication

0.2

U[0.1,0.3]

Business sophistication

0.2

U[0.1,0.3]

Knowledge and technology outputs

0.5

U[0.4,0.6]

Creative outputs

0.5

U[0.4,0.6]

Source: European Commission Joint Research Centre, 2019.

Appendix V

379

FIGURE A-V.2

Robustness analysis of the GII and Input and Output Sub-Indices
GII rank vs. median rank, 90% conﬁdence intervals
1▲

GII 2019 ranks andinterval of simulated
ranks

⊲

Countries/Economies●

Median rank

11
21
31
41
51
61
71
81

GII 2019 rank

91
101
111
121
131

Input rank vs. median rank, 90% conﬁdence intervals
1▲

GII 2019 ranks andinterval of simulated
ranks

⊲

Countries/Economies●

Median rank

11
21
31
41
51
61
71
81

GII 2019 rank

91
101
111
121
131

Output rank vs. median rank, 90% conﬁdence
1▲

GII 2019 ranks andinterval of simulated
ranks

⊲

Countries/Economies●

Median rank

11
21
31
41
51
61
71
81

GII 2019 rank

91
101
111
121
131

Source: European Commission Joint Research Centre, 2019.
Notes: Median ranks and intervals are calculated over 4,000 simulated scenarios combining simulated weights, imputation versus no imputation of missing
values, and geometric versus arithmetic average at the pillar level. The Spearman rank correlation between the median rank and the GII 2019 rank is 0.997;
between the median rank and Innovation Input 2019 rank it is 0.997; and between the median rank and the Innovation Output 2019 rank it is 0.992.

380

The Global Innovation Index 2019

All published GII 2019 ranks lay within the simulated 90%
confidence intervals, and for most economies these intervals
are narrow enough for meaningful inferences to be drawn: there
is a shift of fewer than 10 positions for 98 of the 129 economies.
However, it is also true that ranks for a few economies varysignificantly with changes in weights and aggregation formulaand because of the estimation of missing data. Nine economies,
Brunei Darussalam, Belarus, Panama, Rwanda, Paraguay,
Tajikistan, Namibia, El Salvador, and Togo have 90% confidence
interval widths of 20 positions (up to 32 positions in the caseof Rwanda and Namibia). Consequently, their GII ranks—between
the 71st ( Brunei Darussalam) and 126th position (Togo) in the
GII classification—should be interpreted cautiously and certainly
not taken at face value. This is a remarkable improvementcompared to GII versions until 2016, where more than 40 economies
had confidence interval widths of more than 20 positions.
The improvement in the confidence that one can attach to theGII 2019 ranks is the direct result of the developers’ choicesince 2016 to adopt a more stringent criterion for an economy’s
inclusion, which requires at least 66% data availability withineach of the two sub-indices. Some caution is also warrantedin the Input Sub-Index for 3 economies— Panama, Bosnia andHerzegovina, and Rwanda —that have 90% confidence interval
widths over 20 (up to 27 for Rwanda). The Output Sub-Index
is slightly more sensitive to the methodological choices: 13
economies, Mongolia, Belarus, Panama, Mauritius, Lebanon,
Trinidad and Tobago, Paraguay, the United Republic of Tanzania,
Namibia, El Salvador, Ethiopia, Togo, and the Niger, have 90%
confidence interval widths over 20 (up to 46 for Belarus). Thissensitivity is mostly the consequence of the estimation of
missing data and the fact that there are only two pillars: thismeans that changes to the imputation method, weights, oraggregation formula have a more notable impact on economy
ranks in the Innovation Output Sub-Index.

of indices, have to be approached with care. The reason wasthat the simulated 90% confidence intervals for most economies
were too wide for meaningful inferences to be drawn: there wasa shift of more than 20 positions for 50% of the economies. Hence,
whilst propagating the uncertainty in the two GII sub-indicesover to their sum the GII had a modest impact to the rankings,
this same uncertainty propagation over to their ratio had a very
high impact on the economy ranks. This is not a challenge
specific to the GII framework per se but a statistical property
that comes with ratios of composite indicators. In this present
audit, the JRC-COIN complements the GII team for having opted
to drop the Efficiency Ratio in this year’s publication, drawing
instead policy inference on the Input-Output performance in asimilar way as per the plot of GII scores against the economies’
level of economic development and commenting on thosepairs/groups of economies that have similar Innovation Input
level but very different Innovation Output level, and vice versa.

Although ranks for a few economies, in the GII 2019 overall
or in the two sub-indices, appear to be sensitive to themethodological choices, the published rankings for the vast
majority can be considered as representative of the pluralityof scenarios simulated herein. Taking the median rank as theyardstick for an economy’s expected rank in the realm of
the GII’s unavoidable methodological uncertainties, 75% of
the economies are found to shift fewer than three positions
with respect to the median rank in the GII, or in the Input and
Output Sub-Index.

All in all, the published GII 2019 ranks are reliable and for mosteconomies the simulated 90% confidence intervals are narrow
enough for meaningful inferences to be drawn. Nevertheless,the readers of the GII 2019 report should consider economy
ranks in the GII 2019 and in the Input and Output Sub-Indicesnot only at face value but also within the 90% confidence
intervals in order to better appreciate to what degree an economy’srank depends on the modeling choices. These confidence
intervals have to be taken into account also when comparing
economy rank changes from one year to another at the GII
or Innovation Sub-indices level in order to avoid drawing
erroneous conclusions on economies’ ascent or descent in theoverall classifications. Since 2016, following the JRC-COIN
recommendation in past GII audits, the developers’ choice toapply the 66% indicator coverage threshold separately to the
Input and Output Sub-Indices in the GII 2019 has led to a netincrease in the reliability of economy ranks for the GII and thetwo sub-indices. Furthermore, the adoption in 2017 of less stringent
criterion for the skewness and kurtosis (greater than 2.25 inabsolute value and greater than 3.5, respectively) has not
introduced any bias in the estimates.

For full transparency and information, Table A-V.4 reports theGII 2019 Index and Input and Output Sub-Indices economy
ranks together with the simulated 90% confidence intervals inorder to better appreciate the robustness of the results tothe choice of weights, of the aggregation formula and theimpact of estimating missing data (where applicable).
Emphasizing the identification of and relation between input andoutput indicators seems irresistible from a policy perspective
since doing so may possibly shed light on the effectiveness ofinnovation systems and policies. Yet, last year’s statistical audit
concluded that innovation efficiency ratios, calculated as ratios

Sensitivity analysis results
Complementary to the uncertainty analysis, sensitivity analysis
has been used to identify which of the modeling assumptions
have the highest impact on certain country ranks. Table A-V.5
summarizes the impact of changes of the EM imputation method
and/or the geometric aggregation formula, with fixed weights
at their reference values (as in the original GII). Similar to lastyear’s results, this year neither the GII nor the Input or Output
Sub-Index are found to be heavily influenced by the imputationof missing data, or the aggregation formula. Depending on the
combination of the choices made, only nine economies,
Belarus, Paraguay, Namibia, El Salvador, Togo, the Niger,
Brunei Darussalam, Rwanda, the United Republic of Tanzania,
shift rank by 20 positions or more.

Appendix V

381

TABLE A-V.4

GII 2019 and Input/Output Sub-Indices: ranks and 90% confidence intervals
GII 2019
Switzerland
SwedenUnited States of America
Netherlands
United Kingdom
FinlandDenmark
Singapore
Germany
IsraelRepublic of Korea
IrelandHong Kong, China
China
Japan
FranceCanadaLuxembourg
NorwayIceland
Austria
Australia
Belgium
Estonia
New ZealandCzech Republic
Malta
CyprusSpain
Italy
Slovenia
Portugal
Hungary
LatviaMalaysia
United Arab Emirates
Slovakia
Lithuania
PolandBulgaria
GreeceViet Nam
ThailandCroatia
Montenegro
Russian Federation
UkraineGeorgia
TurkeyRomania
Chile
India
Mongolia
Philippines
Costa Rica
MexicoSerbiaRepublic of Moldova
North Macedonia
KuwaitIran (Islamic Republic of)
UruguaySouth Africa
Armenia
Qatar

Input Sub-Index

Output Sub-Index

Rank

Interval

Rank

Interval

Rank

Interval

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65

[1, 1]		
[2, 2]		
[3, 6]		
[3, 5]		
[3, 5]		
[4, 6]		
[7, 9]		
[7, 11]		
[7, 9]		
[8, 10]		
[10, 12]		
[12, 16]		
[11, 17]		
[12, 17]		
[12, 16]		
[14, 16]		
[15, 19]		
[16, 18]		
[19, 23]		
[18, 20]		
[20, 21]		
[22, 26]		
[22, 26]		
[21, 25]		
[24, 29]		
[21, 27]		
[22, 28]		
[26, 29]		
[28, 29]		
[30, 30]		
[31, 32]		
[32, 33]		
[31, 33]		
[34, 35]		
[34, 36]		
[36, 41]		
[36, 37]		
[37, 39]		
[37, 39]		
[38, 40]		
[41, 45]		
[41, 51]		
[41, 43]		
[44, 48]		
[44, 60]		
[43, 48]		
[41, 50]		
[47, 59]		
[45, 51]		
[46, 52]		
[47, 56]		
[44, 53]		
[44, 61]		
[47, 57]		
[51, 57]		
[51, 56]		
[54, 58]		
[52, 60]		
[58, 65]		
[59, 79]		
[58, 66]		
[60, 66]		
[59, 66]		
[61, 67]		
[63, 72]		

2
4
3
11
6
7
5
1
12
17
10
20
8
26
14
16
9
23
13
22
19
15
21
27
18
29
32
28
25
30
33
31
39
36
34
24
42
38
37
45
40
63
47
46
55
41
82
44
56
54
43
61
73
76
68
59
62
81
52
75
86
66
51
85
53

[2, 3]		
[2, 4]		
[2, 6]		
[8, 15]		
[6, 8]		
[5, 10]		
[4, 6]		
[1, 2]		
[9, 14]		
[10, 20]		
[7, 14]		
[17, 20]		
[6, 14]		
[22, 28]		
[8, 15]		
[15, 18]		
[8, 15]		
[22, 26]		
[10, 17]		
[22, 24]		
[16, 20]		
[12, 19]		
[20, 21]		
[25, 29]		
[16, 21]		
[26, 30]		
[26, 34]		
[27, 33]		
[23, 26]		
[28, 32]		
[29, 34]		
[28, 34]		
[36, 40]		
[36, 39]		
[29, 34]		
[23, 30]		
[41, 45]		
[37, 41]		
[35, 38]		
[41, 47]		
[35, 41]		
[58, 69]		
[43, 51]		
[45, 50]		
[51, 64]		
[36, 44]		
[65, 83]		
[42, 61]		
[47, 59]		
[47, 60]		
[40, 46]		
[50, 63]		
[67, 80]		
[63, 81]		
[64, 71]		
[52, 61]		
[52, 64]		
[74, 84]		
[50, 68]		
[71, 82]		
[73, 91]		
[63, 75]		
[46, 59]		
[82, 91]		
[49, 63]		

1
3
6
2
4
7
12
15
9
8
13
10
16
5
17
14
22
11
27
18
25
31
24
19
32
21
20
23
28
29
30
35
26
34
39
58
33
40
41
38
54
37
43
52
46
59
36
60
49
53
62
51
44
42
48
55
57
45
63
56
47
61
68
50
70

[1, 1][3, 3][5, 10][2, 2][4, 5][4, 8][11, 13][14, 21][7, 9][7, 9][12, 13][10, 16][13, 20][5, 6][15, 20][14, 17][21, 24][8, 11][26, 29][15, 18][24, 26][30, 31][24, 27][17, 20][32, 36][17, 21][15, 23][22, 23][25, 28][28, 29][30, 31][34, 36][23, 28][32, 37][38, 40][55, 59][32, 34][38, 43][40, 42][37, 39][52, 57][35, 44][42, 44][49, 53][43, 60][56, 60][34, 37][59, 60][48, 52][48, 54][61, 63][46, 54][36, 57][41, 45][46, 49][53, 55][54, 58][43, 46][63, 66][55, 70][45, 47][61, 62][68, 73][47, 50][69, 84]
CONTINUED

382

The Global Innovation Index 2019

TABLE A-V.4

GII 2019 and Input/Output Sub-Indices: ranks and 90% confidence intervals,
continued
GII 2019
Rank
BrazilColombia
Saudi Arabia
Peru
Tunisia
Brunei Darussalam
BelarusArgentina
MoroccoPanamaBosnia and Herzegovina
Kenya
BahrainKazakhstan
Oman
Jamaica
Mauritius
Albania
Azerbaijan
Indonesia
JordanDominican Republic
LebanonSri Lanka
Kyrgyzstan
Trinidad and Tobago
Egypt
Botswana
RwandaParaguay
SenegalUnited Republic of Tanzania
Cambodia
EcuadorTajikistan
Namibia
UgandaCôte d'Ivoire
Honduras
Pakistan
Ghana
Guatemala
El Salvador
Nepal
Bolivia (Plurinational State of)Ethiopia
Mali
Algeria
Nigeria
Cameroon
Bangladesh
Burkina Faso
MalawiMozambique
Nicaragua
Madagascar
Zimbabwe
Benin
ZambiaGuineaTogo
Niger
Burundi
Yemen

66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129

Input Sub-Index
Interval[61, 66]		
[64, 70]		
[67, 77]		
[67, 75]		
[66, 74]		
[67, 94]		
[53, 80]		
[67, 75]		
[67, 76]		
[66, 87]		
[72, 86]		
[71, 81]		
[76, 84]		
[76, 80]		
[76, 88]		
[75, 83]		
[72, 86]		
[82, 93]		
[82, 87]		
[78, 86]		
[79, 86]		
[87, 96]		
[76, 90]		
[82, 91]		
[87, 99]		
[90, 105]		
[83, 96]		
[90, 101]		
[89, 121]		
[88, 109]		
[90, 99]		
[96, 109]		
[95, 102]		
[94, 103]		
[90, 112]		
[89, 121]		
[102, 112]		
[99, 107]		
[94, 105]		
[98, 108]		
[97, 108]		
[103, 110]		
[94, 117]		
[102, 115]		
[103, 111]		
[103, 121]		
[108, 116]		
[109, 118]		
[109, 115]		
[106, 118]		
[114, 121]		
[115, 124]		
[115, 127]		
[111, 126]		
[113, 122]		
[113, 122]		
[111, 127]		
[120, 124]		
[120, 126]		
[121, 127]		
[105, 127]		
[119, 129]		
[125, 128]		
[128, 129]		

Rank
60
58
49
48
74
35
50
72
83
79
71
89
69
64
57
84
67
70
77
87
91
90
92
94
78
88
106
80
65
95
103
115
104
98
107
99
96
110
101
113
109
105
97
93
102
124
120
100
116
112
117
111
119
118
108
122
123
114
126
127
121
125
128
129

Output Sub-Index

IntervalRank[49, 63]		
[50, 62]		
[42, 62]		
[46, 60]		
[62, 80]		
[35, 46]		
[43, 56]		
[58, 76]		
[75, 87]		
[70, 91]		
[63, 89]		
[81, 95]		
[64, 75]		
[59, 67]		
[48, 65]		
[74, 89]		
[65, 71]		
[69, 85]		
[72, 85]		
[76, 89]		
[82, 98]		
[88, 94]		
[84, 93]		
[89, 101]		
[70, 85]		
[84, 90]		
[99, 107]		
[75, 86]		
[62, 89]		
[92, 99]		
[101, 110]		
[108, 120]		
[100, 116]		
[94, 101]		
[100, 116]		
[94, 106]		
[94, 103]		
[107, 114]		
[97, 106]		
[104, 116]		
[101, 110]		
[101, 113]		
[95, 99]		
[91, 105]		
[93, 104]		
[123, 127]		
[112, 122]		
[92, 105]		
[108, 118]		
[107, 117]		
[110, 124]		
[109, 122]		
[116, 123]		
[109, 123]		
[105, 117]		
[120, 127]		
[110, 127]		
[108, 121]		
[113, 129]		
[124, 127]		
[116, 123]		
[122, 127]		
[124, 129]		
[128, 129]		

67
76
85
86
65
120
95
75
66
72
79
64
87
92
101
69
96
93
90
78
71
88
82
77
111
99
74
117
123
94
81
73
84
98
83
103
107
91
104
89
97
102
116
119
113
80
100
118
105
106
108
115
112
114
122
109
110
125
121
124
128
127
126
129

Interval[66, 68][73, 79][83, 94][84, 89][65, 73][110, 121]
[58, 104][72, 75][63, 66][62, 92][74, 82][64, 65][85, 97][90, 97][99, 116][67, 76][75, 99][92, 107][88, 93][76, 81][70, 81][87, 100][68, 89][74, 83][108, 119][95, 121][69, 82][106, 117]
[114, 124]
[72, 116][72, 82][72, 101][81, 89][94, 109][80, 98][76, 120][105, 120]
[86, 95][85, 104][83, 96][93, 103][99, 110][92, 119][103, 120]
[110, 120]
[80, 101][94, 105][115, 126]
[100, 112]
[100, 117]
[105, 115]
[113, 122]
[108, 126]
[112, 124]
[104, 122]
[90, 109][107, 123]
[123, 125]
[117, 127]
[109, 126]
[83, 128][104, 129]
[125, 128]
[128, 129]

Source: European Commission Joint Research Centre, 2019.
Notes: Confidence intervals are calculated over 4,000 simulated scenarios combining simulated weights, imputation
versus no imputation of missing values, and geometric versus arithmetic average at the pillar level.
Appendix V

383

TABLE A-V.5

Sensitivity analysis: impact of modeling choices on countries withmost sensitive ranks
Number of economies
that improve

Number of economies
that deteriorate

Spearmanrank
correlation
between thetwo series

by morethan 20
positions

between
10 and 20
positionsby morethan 20
positions

between
10 and 20
positionsGeometric vs. arithmetic average

0.991

0

1

23

2

EM imputation vs. no imputation of missing data

0.992

0

4

0

5

Geometric average and EM imputation vs. arithmetic average and missing values

0.989

0

5

0

7

Input

Geometric vs. arithmetic average

0.996

0

1

0

2

Sub-Index

EM imputation vs. no imputation of missing data

0.993

0

2

0

3

Geometric average and EM imputation vs. arithmetic average and missing values

0.990

0

3

14

6

OutputGeometric vs. arithmetic average

0.996

0

0

15

3

Sub-Index

EM imputation vs. no imputation of missing data

0.969

1

5

8

16

11

Geometric average and EM imputation vs. arithmetic average and missing values

0.969

42

9

17

15

Index orSub-Index

GII

Uncertainty tested (pillar level only)

Source: European Commission Joint Research Centre, 2019.
Notes:
1 Belarus, Paraguay, Namibia, El Salvador, Togo
2 Belarus, El Salvador, Togo, the Niger
3 Brunei Darussalam, Rwanda
4 Rwanda
5 Paraguay
6 United Republic of Tanzania
7 United Republic of Tanzania

Efficiency frontier in the GII by
Data Envelopment Analysis
Is there a way to benchmark economies’ multi-dimensional
performance on innovation without imposing a fixed andcommon set of weights that may not be fair to a particular
economy?
Several innovation-related policy issues at the national levelentail an intricate balance between global priorities andeconomy-specific strategies. Comparing the multi-dimensional
performance on innovation by subjecting economies to a fixedand common set of weights may prevent acceptance of an
innovation index on grounds that a given weighting scheme
might not be fair to a particular economy. An appealing featureof the Data Envelopment Analysis (DEA) literature applied in realdecision-making settings is to determine endogenous weightsthat maximize the overall score of each decision-making unit
given a set of other observations.
In this segment, the assumption of fixed pillar weights common
to all economies is relaxed once more; this time economy-specificweights that maximize an economies’ global innovation scoreare determined endogenously by DEA.11 In theory, eacheconomy is free to decide on the relative contribution of each384

The Global Innovation Index 2019

innovation pillar to its score, so as to achieve the best possible
score in a computation that reflects its innovation strategy. In
practice, the DEA method assigns a higher (lower) contribution
to those pillars in which an economy is relatively strong (weak).
Reasonable constraints on the weights are applied to preclude
the possibility of an economy achieving a perfect score by
assigning a zero weight to weak pillars: for each economy, theshare of each pillar score (i.e., the pillar score multiplied by the
DEA weight over the total score) has upper and lower bounds
of 5% and 20% respectively. The DEA score is then measured
as the weighted average of all seven innovation pillar scores,
where the weights are the economy-specific DEA weights,
compared to the best performance among all other economies
with those same weights. The DEA score can be interpreted asa measure of the “distance to the efficient frontier”.

Table A-V.6 presents the pie shares and DEA scores for the top
25 economies in the GII 2019, next to the GII 2019 ranks. All
pie shares are in accordance with the starting point of granting
leeway to each economy when assigning shares, while notviolating the (relative) upper and lower bounds. The pie sharesare quite diverse, reflecting the different national innovation
strategies. These pie shares can also be seen to reflecteconomies’ comparative advantage in certain GII pillars vis-à-vis

TABLE A-V.6

Pie shares (absolute terms) and efficiency scores for the top 25 economies
in the GII 2019
Input pillars
Institutions

Switzerland
SwedenUnited States of America
Netherlands
United Kingdom
FinlandDenmark
Singapore
Germany
IsraelRepublic of Korea
IrelandHong Kong, China
China
Japan
FranceCanadaLuxembourg
NorwayIceland
Austria
Australia
Belgium
Estonia
New Zealand

0.07
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.05
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20

Output pillars

Human InfrastructureMarketBusiness Knowledge
capitalsophistication sophistication
andandtechnology
research
outputs
0.17
0.20
0.20
0.05
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.05
0.05
0.05
0.10
0.20
0.20
0.05
0.20
0.10
0.20
0.20
0.20
0.10
0.20

0.12
0.20
0.10
0.20
0.20
0.20
0.20
0.20
0.20
0.10
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20
0.20

0.06
0.05
0.20
0.05
0.20
0.05
0.20
0.20
0.10
0.20
0.20
0.10
0.20
0.20
0.20
0.20
0.20
0.10
0.20
0.20
0.10
0.20
0.20
0.20
0.20

0.19
0.20
0.20
0.20
0.05
0.20
0.10
0.10
0.05
0.20
0.10
0.20
0.10
0.20
0.20
0.05
0.10
0.20
0.05
0.05
0.20
0.05
0.10
0.05
0.05

Creative
outputs

Efficient
frontier
score
(DEA)

Efficient
frontier
rank
DEA)

GII
rank

Difference
fromGII rank

0.19
0.10
0.05
0.20
0.10
0.10
0.05
0.05
0.20
0.05
0.05
0.05
0.20
0.20
0.05
0.10
0.05
0.20
0.10
0.20
0.05
0.10
0.05
0.20
0.10

1.00
0.99
0.97
0.93
0.96
0.95
0.95
0.97
0.91
0.89
0.91
0.86
0.92
0.83
0.89
0.88
0.89
0.85
0.87
0.83
0.85
0.86
0.82
0.80
0.84

1
2
3
8
5
6
6
3
10
12
10
17
9
22
12
15
12
19
16
22
19
17
24
25
21

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25

0
0
0
-4
0
0
1
5
-1
-2
1
-5
4
-8
3
1
5
-1
3
-2
2
5
-1
-1
4

0.19
0.05
0.05
0.10
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.20
0.05
0.10
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05

Source: European Commission, Joint Research Centre, 2019.
Notes: Pie shares are in absolute terms, bounded by 0.05 and 0.20 for all seven innovation pillars. In the GII 2019, however, the five input pillars each have afixed weight of 0.10; the two output pillars each have a fixed weight of 0.25. Darker colors represent higher contribution of those pillars to the overall DEA scoreas a result of a country’s stronger performance in those pillars, which may help to evidence economy-specific strategies.

all other economies and all pillars. For example, Switzerland is
the only economy this year that obtains a perfect DEA scoreof 1.00, followed closely by Sweden (DEA score of 0.99). In thecase of Switzerland this is achieved by assigning 17 to 19% of its
DEA score to a mix of input and output pillars, namely Human
capital and research, Business sophistication, Knowledge andtechnology outputs, and Creative outputs. Instead, merely 6% to
12% of Switzerland’s DEA score comes from three input pillars,
namely Institutions, Infrastructure, and Market sophistication.
Using a different mix, Sweden would assign 20% of its DEA
score to four input pillars—Institutions, Human capital andresearch, Infrastructure, and Business sophistication—while
merely 5 to 10% of its DEA score comes from the two output
pillars capturing Knowledge and technology outputs, andCreative Outputs, and from the input pillar measuring Market
sophistication. Switzerland and Sweden are closely followedby the United States of America, Singapore, United Kingdom,
Finland, and Denmark, who score between 0.95 (Denmark)and 0.97 (the United States of America and Singapore) in termsof efficiency. Figure A-V.3 shows how close the DEA scoresand the GII 2019 scores are for all 129 economies (Pearson
correlation of 0.993).

Conclusion
The JRC-COIN analysis suggests that the conceptualized
multi-level structure of the GII 2019—with its 80 indicators, 21
sub-pillars, 7 pillars, 2 sub-indices, up to an overall index—isstatistically sound and balanced: that is, each sub-pillar makes
a similar contribution to the variation of its respective pillar.
This year, the refinements made by the developing team havehelped to enhance the already strong statistical coherence in
the GII framework where for all 80 indicators their capacity
to distinguish economies’ performance is maintained at the
sub-pillar level or higher.
The no-imputation choice for not treating missing values,common in relevant contexts and justified on grounds oftransparency and replicability, can at times have an undesirable
impact on some economy scores, with the additional negativeside-effect that it may encourage economies not to report low
data values. The adoption, since 2016, by the GII team of a more

Appendix V

385

FIGURE A-V.3

GII 2019 scores and DEA “distance to the eﬃcient frontier” scores

1.0

0.8

▲

GII 2019 (rescaled) and
DEA eﬃciency⊲

Countries/Economies

0.6

DEA eﬃciency

0.4

GII 2019 (rescaled)

0.2

0.0

Source: European Commission Joint Research Centre, 2019
Note: For comparison purposes, the GII scores were rescaled by dividing them with the best performer (Switzerland) in the overall GII 2019.

stringent data coverage threshold (at least 66% for the inputand output-related indicators, separately) has notably improved
the confidence in the economy ranks for the GII and the two
sub-indices.
Additionally, the choice of the GII team, which was made in2012, to use weights as scaling coefficients during the index
development constitutes a significant departure from thetraditional, yet erroneous, vision of weights as a reflection ofindicators’ importance in a weighted average. It is hoped thatsuch a consideration will be made also by other developers ofcomposite indicators to avoid situations where bias sneaks inwhen least expected.
The strong correlations between the GII components areproven not to be a sign of redundancy of information in the GII.
For more than 44% (up to 72%) of the 129 economies includedin the GII 2019, the GII ranking and the rankings of any of theseven pillars differ by 10 positions or more. This demonstrates
the added value of the GII ranking, which helps to highlightother components of innovation that do not emerge directly bylooking into the seven pillars separately. At the same time, thisfinding points to the value of duly considering the GII pillars,
sub-pillars, and individual indicators on their own merit. By doing
so, economy-specific strengths and bottlenecks in innovation
can be identified and serve as an input for evidence-based
policy making.
All published GII 2019 ranks lie within the simulated 90% confidence intervals that consider the unavoidable uncertainties inthe estimation of missing data, the weights (fixed vs. simulated),

386

The Global Innovation Index 2019

and the aggregation formula (arithmetic vs. geometric average)at the pillar level. For the vast majority of economies theseintervals are narrow enough for meaningful inferences to be
drawn: the intervals comprise fewer than 10 positions for 76%(98 out of 129) of the economies. Some caution is needed
mainly for nine countries—Brunei Darussalam, Belarus, Panama,
Rwanda, Paraguay, Tajikistan, Namibia, El Salvador, Togo—with
ranks that are highly sensitive to the methodological choices.
The Input and the Output Sub-Indices have the same modest
degree of sensitivity to the methodological choices related tothe imputation method, weights, or aggregation formula.
Economy ranks, either in the GII 2019 or in the two sub-indices,can be considered representative of the many possible
scenarios: 75% of economies shift fewer than three positions
with respect to the median rank in the GII or either of the Input
and Output Sub-Indices.
All things considered, the present JRC-COIN audit findings
confirm that the GII 2019 meets international quality standards
for statistical soundness, which indicates that the GII index
is a reliable benchmarking tool for innovation practices at theeconomy level around the world.
Finally, the “distance to the efficient frontier” measure calculatedwith Data Envelopment Analysis can be used as a measure ofefficiency, and a suitable approach to benchmark economies’
multidimensional performance on innovation without imposing
a fixed and common set of weights that may not be fair toparticular economy. The choice of the GII team to abandon theefficiency ratio (ratio of Output to Input Sub-index) is particularly
applaudable. In fact, ratios of composite indicators (Output toInput Sub-Index in this case) come with much higher uncertainty
than the sum of the components (Input plus Output Sub-Index,
equivalent to the GII). For this reason, developers and users ofindices alike need to take efficiency ratios of this nature withgreat care. The GII should not be the ultimate and definitive
ranking of economies with respect to innovation. On the contrary,
the GII best represents an ongoing attempt by Cornell
University, INSEAD, and the World Intellectual Property Organization
to find metrics and approaches that better capture the richness
of innovation, continuously adapting the GII framework toreflect the improved availability of statistics and the theoreticaladvances in the field. In any case, the GII should be regarded
as a sound attempt, matured over 12 years of constantrefinements, to pave the way for better and more informed
innovation policies worldwide.

often, no reliable information on prices (Charnes, A. et al., 1985).
A notable difference between the original DEA question and the one
applied here is that no differentiation between inputs and outputs ismade ( Cherchye, L. et al., 2008; Melyn, W. et al., 1991). To estimate
DEA-based distance to the efficient frontier scores, we consider them = 7 pillars in the GII 2019 for n = 129 economies, with yij the value ofpillar j in economy i. The objective is to combine the pillar scores per
economy into a single number, calculated as the weighted average ofthe m pillars, where wi represents the weight of the i-th pillar. In absenceof reliable information about the true weights, the weights that maximize
the DEA-based scores are endogenously determined. This gives thefollowing linear programming problem for each economy j:							(bounding constraint)

Subject to							(non-negativity constraint)

Notes:
1

OECD/EC JRC, 2008.

2

The JRC analysis was based on the recommendations of the OECD/EC JRC (2008) Handbook on Composite Indicators and on more recent
research from the JRC. The JRC audits on composite indicators are
conducted upon request of the index developers and are available athttps://ec.europa.eu/jrc/en/coin and https://composite-indicators.jrc.
ec.europa.eu

3Groeneveld, R.A., et al., 1984: set the criteria for absolute skewness
above 1 and kurtosis above 3.5. The skewness criterion was relaxed in
the GII case after having conducted ad-hoc tests in the GII 2008-2018
timeseries.

4

An indicator can explain 9% of the economy’s variation in the GII
sub-pillar scores if the Pearson correlation coefficient between thetwo series is 0.3.

5

Nunnally, 1978.

6

See footnote 4.

7

Saisana et al., 2005; Saisana et al., 2011; Vértesy, 2016; Vértesy
et al., 2016; Montalto et al., 2019.

8

The Expectation-Maximization (EM) algorithm (Little, R.J., et al., 2002;
Schneider, T., 2001) is an iterative procedure that finds the maximum
likelihood estimates of the parameter vector by repeating two steps: (1)The expectation E-step: Given a set of parameter estimates, such as amean vector and covariance matrix for a multivariate normal distribution,
the E-step calculates the conditional expectation of the complete-data
log likelihood given the observed data and the parameter estimates.
(2) The maximization M-step: Given a complete-data log likelihood, theM-step finds the parameter estimates to maximize the complete-data
log likelihood from the E-step. The two steps are iterated until theiterations converge.

9Munda, 2008.

10

In the geometric average, pillars are multiplied as opposed to summedin the arithmetic average. Pillar weights appear as exponents in themultiplication. All pillar scores were greater than zero, hence there wasno reason to rescale them to avoid zero values that would have led tozero geometric averages.

11

A question that arises from the GII approach is whether there is a way
to benchmark economies’ multi-dimensional performance on innovation
without imposing a fixed and common set of weights that may not be
fair to an economy. The original question in the DEA literature was how
to measure each unit’s relative efficiency in production compared to asample of peers, given observations on input and output quantities and,In this basic programming problem, the weights are non-negative andan economy’s score is between 0 (worst) and 1 (best).

References:
Barbosa, N., & Faria, A. P. (2011). Innovation across Europe: How important
are institutional differences. Research Policy 40: 1157–69.
Becker, W., Saisana, M., Paruolo, P., & Vandecasteele., I. (2017). Weights
and Importance in Composite Indicators: Closing the Gap. Ecological
Indicators 80: 12–22.
Charnes, A. & Cooper, W. W. (1985). Preface to Topics in Data Envelopment
Analysis. Annals of Operations Research 2: 59–94.
Cherchye, L., Moesen, W., Rogge, N., Van Puyenbroeck, T., Saisana, M.
et al. (2008). Creating Composite Indicators with DEA and Robustness
Analysis: The Case of the Technology Achievement Index. Journal ofOperational Research Society 59: 239–51.
Groeneveld, R. A. & Meeden, G. (1984). Measuring Skewness and Kurtosis.
The Statistician 33: 391–99.
Little, R.J. A., & Rubin, D.B. (2002). Statistical Analysis with Missing Data. 2ndedition. Hoboken, NJ: John Wiley & Sons, Inc.
Melyn, W. & Moesen, W. (1991). Towards a Synthetic Indicator of
Macroeconomic Performance: Unequal Weighting when Limited
Information Is Available. Public Economics Research Paper 17.
Leuven: Centre for Economic Studies.
Montalto, V., Tacao Moura, C.J., Langedijk, S., & Saisana, M. (2019). Culture
counts: An empirical approach to measure the cultural and creative
vitality of European cities. Cities 89: 167-85.
Munda, G. 2008. Social Multi-Criteria Evaluation for a Sustainable Economy.
Berlin Heidelberg: Springer-Verlag.
Nunally, J. (1978). Psychometric Theory. New York: McGraw-Hill.
OECD/EC JRC (Organisation for Economic Co-operation and Development/
European Commission, Joint Research Centre). (2008). Handbook
on Constructing Composite Indicators: Methodology and User Guide.
Paris: OECD.
Paruolo, P., Saisana, M., & Saltelli, A. (2013). Ratings and Rankings: Voodoo or
Science? Journal of the Royal Statistical Society A 176 (3): 609–34.

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Saisana, M., D’Hombres, B., & Saltelli, A. (2011). Rickety Numbers: Volatilityof University Rankings and Policy Implications. Research Policy 40:
165–77.
Saisana, M., Saltelli, A., & Tarantola, S. (2005). Uncertainty and Sensitivity
Analysis Techniques as Tools for the Analysis and Validation ofComposite Indicators. Journal of the Royal Statistical Society A 168 (2):
307–23.
Saltelli, A., Ratto, M., Andres, T., Campolongo, F., Cariboni et al. (2008). Global
Sensitivity Analysis: The Primer. Chichester, England: John Wiley & Sons.
Schneider, T. (2001). Analysis of incomplete climate data: Estimation of meanvalues and covariance matrices and imputation of missing values.
Journal of Climate, 14, 853–871.
Vértesy, D. (2016, July). A Critical Assessment of Quality and Validity ofComposite Indicators of Innovation. Paper presented at the OECD
Blue Sky III Forum on Science and Innovation Indicators. Ghent,
19-21 Sept 2016.
Vertesy, D., & Deiss, R. (2016). The Innovation Output Indicator 2016.
Methodology Update. EUR 27880. European Commission, Joint
Research Centre.

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Appendix V

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390

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A P P E NDIX V I

ABOUT THE AUTHORS

Marcos Álvarez-Díaz is a Researcher at the European Commission’sCompetence Centre on Composite Indicators and Scoreboards(COIN) of the Joint Research Centre of the European Commission,
Italy, and Associate Professor of Economics at the Universityof Vigo, Spain. He holds a PhD, a Master of Philosophy, and a
Master of Arts in Economics from Columbia University, New Yorkin the United States of America. He has worked as Researcher
at the Economic Research Center of the savings bank Caixa
de Balears and served as Assistant Professor at the Universityof the Balearic Islands, Spain. He is the recipient of awards
and honors such as the William Vickrey prize from Columbia
University and the Alexandre Pedrós award from the Review of
Public Economics. He has coauthored and authored scientificarticles dealing with the modeling and forecasting of economic
and financial time series.
Giovanni Anelli joined CERN’s Knowledge Transfer Group in2010 as Technology Transfer Officer and was appointed Headof the Knowledge Transfer Group in August 2011. Previously, heworked for three years for LEM SA. and prior to this, he worked
for 10 years in CERN’s Microelectronics Group in the Physics
Department, where he designed several low-noise low-power
analog and mixed signal VLSI circuits for High-Energy Physics
applications. Mr. Anelli received a Master of Science in Electronics
Engineering from the Polytechnic of Milan, Italy, in 1997, a PhD
in Electronics Engineering with honors from the Polytechnic ofGrenoble, France, in 2000 and an Executive Master of Business
Administration from Ecole des Hautes Etudes Commerciales(HEC) Paris, France, in 2008. He is author and coauthor of morethan 70 publications and is an IEEE senior member.
Jack Bauersachs is Professor of Finance at Technische
Hochschule Deggendorf where he directs the International
Management Programme. Prior to joining the university, hefounded Promax Corp. and New World Cuisine, Inc., producersof sports nutritional products and organic snacks. He waspreviously Head of Corporate Finance for RAF Financial Corp.
and Associate Professor of Economics at Colorado State
University, United States of America. He earned his PhD withhonors in Econometrics at the University of Colorado and is a
Chartered Financial Analyst.

Kyle Bergquist is a Data Analyst in the Economics and Statistics
Division of the World Intellectual Property Organization (WIPO).
He holds a Master of Science in Economics from the Universityof Neuchâtel, Switzerland, and a Bachelor of Arts in Political
Science from the University of Nevada, United States of America.
Prior to working at WIPO, Mr. Bergquist was a data analyst
for the patient safety department at CRICO, the malpracticeinsurance company for the Harvard medical community, where
his research focused on the occurrence and prevention ofadverse medical events as well as risk assessment. His research
topics of interest are intellectual property, environmental policy,
and economic geography.
Claire Biot leads the Life Sciences Industry organization of
Dassault Systèmes, which aims to provide the life sciences
ecosystem with agile digital solutions to tackle main current
challenges, including personalized health, total quality,
operational excellence in development and manufacturing,knowledge capitalization, and re-inventing the value chain.
Ms. Biot holds a Master of Science in Engineering from Ecole
Polytechnique, Paris, France, and a Master of Science in
Biological Sciences from the Watson School of Biological
Sciences, Cold Spring Harbor Laboratory in New York, UnitedStates of America. She studied cancer immunotherapy at
Institut Pasteur, Paris, France, where she graduated with a
PhD in immunology in 2012. She began her career at the French
Ministry of Health as Head of Division, Health Products Pricing
and Reimbursement in 2012. She then joined Greater Paris
University Hospitals, AP-HP, Paris, France, in 2015 as Managing
Director of the Health Products and Technologies Central
Agency, allowing her to build proficiency in health products
development, manufacturing, and procurement as well as
patient care. She has been an active member in several World
Health Organization (WHO) working groups on health products.
She joined Dassault Systèmes in March 2019.

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Krithpaka Boonfueng is the Deputy Executive Director of
Innovation System at the National Innovation Agency (NIA) in
Thailand. She graduated in 1994 with a Bachelor of Laws fromThammasat University, Thailand, with second class honors; in1997 with a Master of Laws in Business Law from Chulalongkorn
University, Thailand; in 1998 as a Barrister-at-Law from the ThaiBar Association; in 1999 with a Bachelor of Laws in International
Business Law from the American University, United States ofAmerica; in 2000 with a Bachelor of Laws from the Universityof Pennsylvania, United States of America; and in 2003 as a
Doctor of Juridical Science (SJD) from the American University,
United States of America. She received the Thai Government
Scholarship to study intellectual property law in the UnitedStates of America. After graduating, she launched her careerat the National Science and Technology Development Agency(NSTDA) as an intellectual property specialist for 12 years andthen worked at the Biodiversity-Based Economy Development
Office (Public Organization) as the Director of Legal Development
and Intellectual Property Management Group from 2015 to 2018.
She was on the Board of Directors of the Defense Technology
Institute of the Ministry of Defense from 2012 to 2017. She is apart-time lecturer to Masters students at various Thai institutions,
namely the Thammasat University Graduate School ofManagement and Innovation, the King Mongkut’s University ofTechnology Thonburi, and the School of Law at Ramkhamhaeng
University and Bangkok University, Thailand. Moreover, she is
the Associate Judge of the Central Intellectual Property andInternational Trade Court in Thailand. Her expertise includes
Intellectual Property Law, Electronic Commerce and Internet
Law, and Intellectual Property and Innovation Management.
Robson Braga de Andrade is President of the National
Confederation of Industry (CNI), Director of the Social Services
for the Industry (SESI), President of the Board of the National
Service for Industrial Training (SENAI) and President of theOrteng Group, a leading company that produces equipment
for the segments of energy, oil, gas, mining, steel, sanitation,
telecommunications, and transport for over 30 years. He is amember of the Economic and Social Development Council of
the Presidency of the Republic (CDES); member of the National
Council of Industrial Development (CNDI); Vice-President of
CNI from 2002 to 2010, President of the State Federation ofIndustries of Minas Gerais (FIEMG) from 2002 to 2010; memberof Minas Gerais State Economic and Social Development
Council; Director of the Latin American Business Council (CEAL)
from 2004 to 2006; President of the Association of the Electrical
Appliances and Electronics Industry (Sinaees) from 2004 to
2010; member of the Brazilian Association of Infrastructure andBasic Industries (ABDIB) Strategic Council from 2001 to 2003; andmember of the Brazilian Association of Electric and Electronicndustry (Abinee) Board from 2001 to 2004. He graduated asa Mechanical Engineer from the Federal University of Minas
Gerais (UFMG) and has postgraduate diplomas in Strategic
Management for Business Leaders of the Dom Cabral Foundation,in Minas Gerais State, and of INSEAD, France.

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Manuela Cirilli joined CERN’s Knowledge Transfer Group in2010 as Technical Coordinator of an EU-funded project on
medical imaging, and she was appointed Section Leader for
Medical Applications in 2016. She is also Chair of CERN’s
Medical Applications Project Forum. Prior to this, she was anexperimental researcher in particle physics. She joined CERN
in 1997 as a PhD student and the ATLAS collaboration in 2001.
She has extensive experience in detector construction andcommissioning, data analysis, and databases. Ms. Cirilli holds
a PhD in Particle Physics from the Scuola Normale Superiore
in Pisa, Italy, as well as a Master of Science in Communication
and Journalism from the University of Ferrara, Italy. She iscoauthor of more than 320 peer-reviewed publications, including
the article on the discovery of the Higgs boson by the ATLAS
collaboration. In parallel to her scientific career, she has
engaged in science communication and popularization since
the early 2000s, for a variety of audiences and stakeholders of
all ages. She is a teacher and coach in science communication,science writing, and public speaking. Ms. Cirilli is also
actively involved in promoting STEM careers among young
women and girls.
Francis S. Collins, MD, PhD is the Director of the National
Institutes of Health (NIH) in the United States of America.
In this role, he oversees the work of the largest supporter ofbiomedical research in the world, spanning the spectrum frombasic to clinical research. Dr. Collins is a physician-geneticist
noted for his landmark discoveries of disease genes and hisleadership of the international Human Genome Project, which
culminated in April 2003 with the completion of a finishedsequence of the human DNA instruction book. He served as
Director of the National Human Genome Research Institute at
the NIH from 1993 to 2008. Before coming to the NIH,
Dr. Collins was a Howard Hughes Medical Institute Investigatorat the University of Michigan in the United States of America.
He is an elected member of the Institute of Medicine and the
National Academy of Sciences, was awarded the Presidential
Medal of Freedom in November 2007, and received the
National Medal of Science in 2009.
Marcos Domínguez-Torreiro is a Research Fellow at theCompetence Centre on Composite Indicators and Scoreboards(COIN) of the Joint Research Centre of the European Commission,
Italy, where he conducts research and policy support tasks inthe field of Econometrics and Applied Statistics. After his
undergraduate studies in Economics and Business Administration,
he completed his doctoral thesis in Applied Economics at the
University of Vigo, Spain. His past work experience is in theprivate sector, universities, and public administration. He hascoauthored books and research articles dealing with finance,
consumer behavior, environmental and natural resource
economics, rural development, and institutional economics.

Soumitra Dutta is Professor of Management and the former
founding dean of the Cornell SC Johnson College of Business(April 2016 to January 2018). Previously, he was the Anne andElmer Lindseth Dean of the Samuel Curtis Johnson Graduate
School of Management. Prior to coming to Cornell in 2012,he was on the faculty and leadership team of INSEAD, a leadinginternational business school in France and Singapore. He
is an authority on technology and innovation policy, is the co-editor
and author of The Global Information Technology Report,
published by the World Economic Forum and The Global
Innovation Index, published by the World Intellectual Property
Organization—two influential reports in technology and innovation
policy. Mr. Dutta is on the global boards of Sodexo and Dassault
Systèmes. He is also a member of the Shareholder Council of
Chicago-based ZS Associates. In addition, he is a member of
the advisory boards of several business schools including HEC,
Montreal; ESADE, Barcelona; and ESCP, Paris. He has co-founded
two firms, including Fisheye Analytics, which WPP groupacquired. He is currently Chair of the Board of Directors of the
Global Business School Network, a Washington, D.C. based
not-for-profit organization focused on improving management
capacity in emerging markets. He was previously the Chairof AACSB, the leading global body for the accreditation ofbusiness schools. Mr. Dutta is a member of the Davos Circle,
an association of long-time participants in the World Economic
Forum Annual Meeting in Davos, and has engaged in a numberof multi-stakeholder initiatives to shape global, regional, andindustry agendas. He is also currently the co-chair of the World
Economic Forum’s Global Future Council on Innovation
Ecosystems. Mr. Dutta received a Bachelor of Technology inElectrical Engineering and Computer Science from the Indian
Institute of Technology (IIT), New Delhi, a Master of Science inboth Business Administration and Computer Science, and a
PhD in Computer Science from the University of California at
Berkeley. In 2017, he received the Distinguished Alumnus Award
from his alma mater IIT Delhi.
Mahdi Elyasi graduated from the Sharif University of Technology
with a degree in Industrial Engineering. He obtained his PhD
in Technology Management (policymaking) from Allameh Tabataba’i
University, Tehran, Iran, and is a member of the University’s
scientific board in the fields of technology management, andscience and technology policymaking. He has over 10 yearsof experience in training, research, and executive activities ingovernmental and private bodies, is a member of the board of
directors of technology management and knowledge management
associations, and has written various research essays.
Rafael Escalona Reynoso has been Lead Researcher for
The Global Innovation Index since October 2013. His previous
professional experience was as Economic, Science andTechnology Policy Advisor to the Senate of Mexico, and as amember of the Trade and Foreign Investment Advisory Board
at the office of the President of Mexico. His research experienceat Cornell University includes comparative studies between
Mexico and Spain on the regulatory aspects of modern
biotechnology and the biosafety of genetically modified
organisms (GMOs), and on the reach of intellectual property
rights (IPRs) in the information technologies era. He holds a PhD
in Regional Planning and a Master of Public Administration from
Cornell University as well as a Bachelor of Arts in Economics
from Universidad Panamericana in Mexico.

Kiarash Fartash holds a PhD in Management of Technology
with specialization in science and technology (S&T) policymaking
from Allameh Tabataba’i University, Tehran, Iran. He has
authored more than 20 research papers and has played a majorpart in many international STI policy studies, of which his rolein the preparation of Iran Science, Technology and Innovation
Policy Review, published by UNCTAD in 2016, was instrumental.
Since 2013, he has coordinated at a national level with all key
organizations and institutions in Iran to address the country’s
challenges and deficiencies based on The Global Innovation
Index (GII) report rationales as well as improving quality, data,
and the international reporting system of Iran’s statistics relevant
to GII indicators.
Carsten Fink is the Chief Economist of the World Intellectual
Property Organization (WIPO) based in Geneva. Before joining
WIPO, he was Professor of International Economics at the
University of St. Gallen, Switzerland. He has also held thepositions of Visiting Professor at the Fondation Nationale desSciences Politiques (Sciences Po) in Paris and Visiting Senior
Fellow at the Group d’Economie Mondiale, a research instituteat Sciences Po. Prior to his academic appointments, Dr. Fink
worked for more than 10 years at the World Bank. Among otherpositions, he was Senior Economist in the International Trade
Team of the World Bank Institute, working out of the WorldBank’s office in Geneva, and Economist in the Trade Division of
the World Bank’s research department, based in Washington,
D.C. Dr. Fink’s research work—focused on intellectual property,
innovation, and international trade—has been published inacademic journals and books. He holds a Doctorate in Economics
from the University of Heidelberg in Germany and a Masterof Science in Economics from the University of Oregon in the
United States of America.
Antanina Garanasvili is a Research Economist at Bournemouth
University, the Centre for Intellectual Property Policy & Management(CIPPM). She also serves as an independent consultant toCornell University for The Global Innovation Index. Her mainarea of expertise is in applied microeconomics and industrialorganization, with a focus on innovation and intellectual property
economics. Dr. Garanasvili has previously worked witheconomist teams at EUIPO (European Union Intellectual Property
Office), EPO (European Patent Office) and WIPO (WorldIntellectual Property Office). She held the position of visiting
PhD researcher at Queen Mary University of London and holds
a PhD in Economics from the Università di Padova, Italy.
Francesca Guadagno is an Economist and International
Consultant. Her research interests cover the broad area of
innovation and development, with a focus on the role of public
policies. She has considerable experience in policy-oriented
research, working with the Asian Development Bank, theDutch Ministry of Foreign Affairs, the Gates Foundation, the E15
Initiative, ECDPM, UNIDO, UNCTAD, and WIPO. Dr. Guadagno
holds a Master of Economics and Management of Innovationfrom Bocconi University in Milan, Italy; a Master of Managementof Innovation from the Rotterdam School of Management, theNetherlands; and a PhD in Innovation Studies and Developmentfrom UNU-MERIT and Maastricht University School of Businessand Economics.

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Cashelle Hardman graduated with a Bachelor of Commercefrom the University of Pretoria, South Africa in 2014. She pursued
a career in the field of Human Resources Management
thereafter, an area in which she had worked for roughly five
years, including at the World Intellectual Property Organization(WIPO), before assuming her current role as Project Manager
for The Global Innovation Index in 2018.
Mohamed Hassany is Assistant to the Egyptian Minister of
Health and Population for public health initiatives in Egypt, andExecutive Director of the National Committee for Control ofViral Hepatitis. Previously, he was Vice-Dean of Scientific
Research and Training. He has many international peer-reviewed
publications/book chapters in the field of viral hepatitis andserves as an editorial board member and reviewer of many
international peer reviewed journals. In 2019, he was awarded
the State Encouragement Award in medical science in Egypt.
Patrick Johnson is Vice-President of Corporate Science &Research at Dassault Systèmes (3DS). His mission is to define
the scientific bases of the company’s solutions, invent new
disruptive technologies for the Industry Renaissance, andanimate the group’s global research ecosystem. Mr. Johnson
joined 3DS in 1996 and has held various positions in researchand development (R&D), from Product Lifecycle Management
infrastructure to virtual product design solutions for the CATIA
flagship brand. In 2001, he became head of the Knowledgeware
department and, convinced by the potential of artificial
intelligence and knowledge management, played a key rolewith major breakthroughs currently used in multiple industrial
sectors, such as intelligent morphing templates, and industrial
processes capitalization & reuse automation. After two years
as Executive Assistant to the CEO Bernard Charlès, he wasnamed Head of Corporate Research in 2004. Since then he haslaunched the development of multiple original technologies,
which has resulted in more than 30 innovative products
and 60 patents, transformed industry & scientific practices
and significantly grown the global innovation ecosystem that
promotes the creation of public/private partnerships withprestigious research institutes and organizations. In addition,
he launched an entirely new field of diversification for 3DS,
following ‘BioIntelligence’—a very large European research
program, resulting in a suite of collaborative applications forthe life sciences sector, the acquisition of key player and thecreation of the BIOVIA brand with a worldwide R&D lab inmodeling, simulation, and big data for life sciences. A graduateof ENSAE, Mr. Johnson is based at 3DS world headquarters near
Paris. He is or has been a member of the scientific boards of
INRIA, IMT, ARISS, International Society of Computational
Biology, IRCAM, Comité de Culture Mathematics of the Institut
Henri Poincaré, and Personnalité associée of the Economic,
Social and Environmental Council (CESE).

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David Kaslow, MD, is PATH’s Vice-President for Essential
Medicines, which includes PATH’s Drug Development Program
and the PATH Center for Vaccine Innovation and Access (CVIA).
As the Director of CVIA, he leads PATH’s work to accelerate
the development and introduction of lifesaving vaccines for themost vulnerable children and communities around the world.
Dr. Kaslow has more than 25 years of experience in vaccine
research and development. Before joining PATH in 2012 as
Director of MVI’s work to drive the development of safe andeffective vaccines against malaria, he held key advisory
positions with MVI and the Bill & Melinda Gates Foundation
related to malaria vaccines. Prior to that, he oversaw project
leadership and management of Merck Research Laboratories’
vaccine pipeline and founded the Malaria Vaccine Development
Unit at the National Institutes of Health. As a basic researchscientist, Dr. Kaslow completed the molecular cloning andcharacterization of several proteins involved in malaria parasite
sexual development. He has also directed product development,
including field studies, of several malaria vaccine candidates.
Outside the malaria field, Dr. Kaslow has contributed to thevaccine application of tools originally developed for genetherapy. He holds or co-holds more than a dozen patents andhas published more than 150 scientific papers. Dr. Kaslow
received his medical degree from the University of California,
San Francisco.
Pratap Khedkar is a Managing Principal and Global Leader for
the Biopharmaceuticals Practice at ZS Associates, a management
consulting firm focusing on healthcare. He has also been amember of the ZS Associates Board since 2012. Mr. Khedkar
has 20 years of experience in the healthcare industry, helping
multiple organizations on issues related to commercial strategy
and effectiveness. More recently, he has worked on developing
effective strategies and analytics for changing customers in the
new healthcare ecosystem. A recognized healthcare industry
expert, Mr. Khedkar regularly contributes his insights topublications including The Wall Street Journal, Bloomberg
Businessweek, Business Insider, Medical Marketing & Media,
NPR, Pharmaceutical Executive and others. Currently, histhought leadership work focuses on topics as diverse as
healthcare policy; life sciences companies’ new commercial
and organizational models; the evolving relationships between
patients, providers and payers, and the life sciences organizations
that serve them. He holds a PhD in Computer Science andArtificial Intelligence from the University of California at Berkeley,as well as a B. Tech. in Computer Science and Engineering fromthe Indian Institute of Technology, Delhi.

Bruno Lanvin is INSEAD’s Executive Director for Global Indices.
From 2007 to 2015, he was the Executive Director of INSEAD’s
eLab, managing INSEAD’s teams in Paris, Singapore and
Abu Dhabi, and then Executive Director for INSEAD’s European
Competitiveness Initiative (IECI). From 2000 to 2007, Dr. Lanvinworked for the World Bank, where he was inter alia Senior
Advisor for E-strategies and Regional Coordinator in Europe andCentral Asia for information and communication technology (ICT)and e-government issues. He also headed the Capacity Building
Practice of the World Bank’s Global ICT Department and was
Chairman of the Bank’s e-Thematic Group. From June 2001 to
December 2003, he was the Manager of the Information for
Development Program (infoDev) at the World Bank. In 2000,
Dr. Lanvin was appointed Executive Secretary of the G8-DOT
Force. Until then, he was Head of Electronic Commerce in the
United Nations Conference on Trade and Development(UNCTAD) in Geneva, and occupied various senior positions
including Chief of the Cabinet of the Director General of theUnited Nations in New York, Head of Strategic Planning,
and later Chief of the SME Trade Competitiveness Unit of
UNCTAD/SITE. He was the main drafter, team leader, and editorof Building Confidence: Electronic Commerce and Development,
published in January 2000. Since 2002, he has been
coauthoring The Global Information Technology Report (Cornell
University-INSEAD-World Economic Forum), and is currently
the co-editor of The Global Innovation Index Report (Cornell
University-INSEAD-WIPO). In 2013, he created and launched thefirst edition of the Global Talent Competitiveness Index (GTCI),
and is still the co-editor of this annual report. He holds a
Bachelor of Arts in Mathematics and Physics from the Universityof Valenciennes, France, a Masters of Business Administrationfrom Ecole des Hautes Etudes Commerciales (HEC) in Paris,
France, a PhD in Economics from the University of Paris I(La Sorbonne) in France, and is an alumnus of INSEAD (IDP-C).
A frequent speaker at high-level meetings, he advises several
global companies and governments and has been a memberof numerous boards for many years, including those of ICANN,
IDA-Infocomm, GovTech, IP-Watch, AAID, and the Bin RashidFoundation for Government Innovation.
Chaiyatorn Limapornvanich is Head of Innovation Foresightat the National Innovation Agency (NIA) in Thailand. Based on
his educational background in electrical engineering andinformation science, he started his career as a web developer
and then became a research assistant. He joined NIA in 2004
and secured a scholarship for his doctoral studies in 2009 at the
University of Surry, United Kingdom. With extensive experiencecollaboratively working with innovative companies, he decided
to conduct his doctoral research on Knowledge Management
and graduated in 2013. At present, his research focuses arein the areas of Strategic Foresight and Innovation Management,
and his professional interests have been expanded toorganizational learning and development.

Valencia Lyle received a Master’s in Public Health from Columbia
University’s Mailman School of Public Health, New York in the
United States of America. Since then, Ms. Lyle has been building
her proficiency in health system strengthening and global healthresearch. She further strengthened her expertise in theseareas after joining the Health Management Information System(HMIS) Unit of the Rwanda Ministry of Health (MOH) from
July 2017 until March 2019. As Vital Statistics Knowledge
Management Officer, she provided support to Rwanda’s
MOH/HMIS Unit staff through analyzing data, coordinatinge-learning system activities, and contributing to health system
related reporting and research. Her medley of past and current
work experiences drive her enthusiasm for integrating technology
into health systems to achieve health and gender equity.
Huateng (Pony) Ma is one of Tencent’s co-founders andcurrently serves as Chairman of the Board and Chief Executive
Officer. He oversees the strategic development, businesspositioning, and management of Tencent. In 2018, Mr. Ma
topped Fortune’s list of “China’s 50 Most Influential Business
Leaders” and was named one of the “Best-Performing CEOs in
the World 2017” by Harvard Business Review. Mr. Ma received
his Bachelor of Science in Computer Science from Shenzhen
University, China, in 1993.
Sébastien Massart is Head of Corporate Strategy at Dassault
Systèmes. Among his previous positions, he was Senior
Industrial Advisor to former French President François Hollande,
where he contributed to the definition and implementationof major orientations and policies for industry transformation at
the national level. Mr. Massart also formerly served as TechnicalAdvisor for Industrial Affairs in the private office of the French
Minister of Defense. He began his career at Deloitte Consulting
in Paris. He then became a French State civil servant, Headof Economic Development at a regional level, and then Adviser
to the Chairman of the French Financial Markets Authority (AMF),
in charge of strategic planning. At that time, he was notably
involved in European multilateral negotiations regarding the
new regulation of derivatives markets after the financial crisis.
He then joined the French State Shareholding Agency (A.P.E.) at
the French Ministry for Economy, where he oversaw a portfolioof companies including Airbus Group, Nexter, Eurenco, andMonnaie de Paris. Mr. Massart holds an engineering degreefrom Ecole Polytechnique (Paris-Saclay University) and is a
graduate of Ecole Normale Supérieure, Paris, France, in
Theoretical Physics and Philosophy.

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Brandy R. Matthews, MD, FAAN, joined Eli Lilly and Company
in 2015 after serving as Associate Professor of Clinical
Neurology and the Neurology Residency Program Director at
the Indiana University School of Medicine, Clinical AssistantProfessor at Marian University College of Osteopathic Medicine,and clinical investigator at the Indiana Alzheimer Disease
Center, United States of America. She completed a Bachelor of
Science in psychology/theatre, graduating summa cum laude
from Ball State University in 1994. She obtained her Doctorate ofMedicine at Indiana University School of Medicine in 2001 withinduction into the Alpha Omega Alpha Medical Honor Society.
Dr. Matthews was a Neurology Resident at Mayo Clinic Graduate
School of Medicine from 2002 to 2005, where she served
as Chief Neurology Resident before her National Institutes of
Health-funded research fellowship in Clinical Behavioral
Neurology at University of California, San Francisco Schoolof Medicine between 2005 and 2007. As a Clinical Instructor in
Neurology at Mayo Clinic College of Medicine and at the
University of California, San Francisco, she was active in the
education of medical students and residents before returning to
Indiana to assume a leadership role in Graduate Medical
Education. As a diplomate of the American Board of Psychiatry
and Neurology and a Fellow of the American Academy of
Neurology, she has served leadership roles in both organizations.
Dr. Matthews has published and presented nationally andinternationally on a broad range of neuroscience topics, witha focus on Alzheimer’s disease and related dementias anda special interest in the intersection of Neurology and the Arts.
During her tenure at Eli Lilly, she has been actively engaged
across the global Alzheimer’s disease effort, collaborating withmedical and non-medical colleagues while maintaining her
special interests in medical education and exploring opportunities
to prepare the external environment for new therapies forpatients with neurodegenerative diseases. She cares forpatients and families affected by neurodegenerative dementia
in her biweekly volunteer clinic at Indiana University Health.

Andrew Muhire is Sector M&E and Report Lead Specialist at
the Rwanda Ministry of Health (MoH). During his tenure,
Mr. Muhire has been dedicated to providing innovative solutions
to support health workers and improve data collection methods.
With 7 years of experience managing the Health Management
Information System (HMIS), Mr. Muhire has spearheaded several
initiatives to safeguard the collection of high quality data tobolster the effectiveness of data driven policymaking. One of
Mr. Muhire’s most notable achievements includes serving as amember of the task force that customized the first web-based
system (DHIS2) for the MoH. Additional components of his corerole include disseminating information regarding public healthtrends and best practices, using data to improve healthcaredelivery throughout Rwanda, and strategically integrating
technology into building the capacity of health workers.

Carlos Melles is an agronomist, researcher, and cooperative
executive director. He was a member of congress for six
consecutive legislatures, and throughout his career has stoodup for agribusiness, cooperatives, and micro and small businesscauses. At the lower chamber of Brazilian Congress, he waspresident of the Micro Business Special Committee, whichapproved the Micro and Small Business General Act in 2006.
It is worth noting that Mr. Melles was the reading clerk for thebills in 2018: Individual Micro Entrepreneur (MEI, in Portuguese)and Simple Credit Business (ESC, in Portuguese). In the Federal
Government, he was Minister of State of Sports and Tourism in 2000
and, in the Minas Gerais State Government, he was Secretaryof State of Transport and Public Developments in 2011.

Patrick Ndimubanzi is Minister of State for Primary Health Careof the Ministry of Health in Rwanda. Dr. Ndimubanzi is a Public
Health specialist with experience in designing and implementing
strategies to tackle the HIV/AIDS pandemic and other infectious
and non-infectious diseases. A medical doctor by profession,
he holds a Master of Science, majoring in Epidemiology fromthe University of Oklahoma, Health Sciences Center.

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Kieran Murphy is President and CEO of GE Healthcare,a $20 billion business unit of General Electric that provides
transformational medical technologies and solutions to theglobal healthcare industry. GE Healthcare supports customers
in over 100 countries with a broad range of services andsystems, from diagnostic imaging, monitoring, and digitalsolutions through to molecular diagnostics and life sciences.
Prior to this, Mr. Murphy was President and Chief Executive
Officer of GE Healthcare Life Sciences. He was appointed CEO
in May 2011 and oversaw significant revenue growth andgeographic expansion of the molecular medicine business.
Mr. Murphy joined GE Healthcare in 2008 from Whatman plc.,
a $230 million global supplier of filters and membranes forlaboratory research, life sciences, and medical diagnostic
applications. Mr. Murphy has over twenty years’ experience inthe global life sciences and biotechnology industry beginning
his career with Janssen Pharmaceuticals, a division of Johnson
and Johnson, followed by leadership roles with Mallinckrodt,
veterinary medicines provider Vericore, Novartis, Adprotech,
ML Laboratories, and Innovata plc.

Mostafa Monier Othman is Technical Officer in the Minister of
Health’s Technical Office in Egypt. He holds a Master of e-HealthManagement and two postgraduate diplomas in Public Healthand Quality Management. Prior to working in the Ministry of
Health, he was a health research consultant for WHO/EMRO.
During his seven-year experience, he worked on health systemstrengthening topics.

Nicolas Pécuchet, MD, PhD, is Head of Genomic Sciences at
Dassault Systèmes. Dr. Pécuchet’s team focuses on translating
genomic innovations and disruptive technologies into clinicalbenefit for patients. His work is based on strong interactions andpartnerships with research institutes and healthcare institutes
to build collaborative research programs. Among his previous
positions, he served as a clinical oncologist at the European
Georges Pompidou Hospital and Clinical Investigator and Directorof the clinical trial in kidney cancer. As Founding member ofAssistance Publique – Hôpitaux de Paris (AP-HP) Molecular
Tumor Board, he actively supports delivering precision medicine
to a large number of patients. His translational research on
cancer genomics and liquid biopsy have been published in
Plos Medicine, Annals of Oncology, Clinical Chemistry andClinical Cancer Research. Dr. Pécuchet is a graduate of Paris
Descartes University and Paris Descartes Medical School andwas awarded the Chancellery prize of the Universities of Paris.
Lorena Puica is an academic, investment professional, extreme
athlete, and the Founding CEO of the world leading preventive
platform iamYiam.com. Prior to founding iamYiam, Ms. Puica
achieved five degrees in mathematics, economics, and financefrom Universities in Romania, Germany, the United Kingdom,
and the United States of America, including being one of theyoungest to receive the CFA designation. She published a bookon microfinance at the age of 26 and created a decade-longcareer with Allianz SE—the global Insurer in Group Development
and Long Term Strategy, KPMG—the global consulting firm
focused on post-merger integrations, and Morningstar—the
global investment firm as Director of Strategy and Businessdevelopment working with portfolios of over £200billion. At
the same time, Ms. Puica was an extreme athlete with 2 world
record events—running 7 marathons on 7 continents in 7 days
and climbing Kilimanjaro in 2,5 days.
Anais Rassat is Communication and Marketing Officer in the
Knowledge Transfer group at CERN. She holds a PhD in
astrophysics and worked for 12 years on ground- and space-based
telescope projects at the Swiss Federal Institute of Technology
in Lausanne (EPFL), the French Alternative Energies andAtomic Energy Commission (CEA), and University College
London. During this time, she managed international science
working groups and teams, and acted as project manager ofscientific research projects. She has authored and coauthoredover 40 publications related to astrophysics, cosmology, or
cosmostatistics. She now drives the development andimplementation of the Knowledge Transfer group’s communicationand marketing strategy. She is passionate about technology,
innovation, science policy, and entrepreneurship.

David A. Ricks has served as Chief Executive Officer of Eli Lilly
and Company since January 1, 2017. He became Chairpersonof the board of directors on June 1, 2017. A 20-year Eli Lilly
veteran, Mr. Ricks served as president of Eli Lilly Bio-Medicinesfrom 2012 to 2016. Previously, he was President of Eli Lilly in the
United States of America, the company’s largest affiliate, from2009 to 2012. He served as President and General Manager of
Eli Lilly China, operating in one of the world’s fastest-growing
emerging markets, from 2008 to 2009. And he was General
Manager of Eli Lilly Canada from 2005 to 2008, after roles as
director of pharmaceutical marketing and national sales director
in that country. Mr. Ricks joined Eli Lilly in 1996 as a Business
Development Associate and held several management roles
in U.S. marketing and sales before moving to Eli Lilly Canada.
Mr. Ricks earned a Bachelor of Science from Purdue University
in 1990 and a Master of Business Administration from Indiana
University in 1996. Mr. Ricks is the President of the International
Federation of Pharmaceutical Manufacturers & Associations(IFPMA) as well as serves on the board of the Pharmaceutical
Research and Manufacturers of America (PhRMA), the Central
Indiana Corporate Partnership, the Elanco Board of Directors,
and the Adobe Board of Directors. He chairs the Riley Children’sFoundation Board of Governors.
Lorena Rivera León is the Program Officer of The Global
Innovation Index (GII) at the Economics and Statistics Divisionof the World Intellectual Property Organization (WIPO). She has
worked as a researcher, policy analyst, and consultant in thefield of research and innovation for over 13 years, including
for various services of the European Commission, UNESCO,
the OECD, and the Inter-American Development Bank. Prior tojoining WIPO, she was involved in the design and developmentof various innovation and entrepreneurship scoreboards at theEuropean level, including the Regional Ecosystems Scoreboardof the European Cluster Observatory and the Regional
Innovation Scoreboard of the European Union. At WIPO she
acts as Lead Researcher of the GII, including the review of data,
the construction and the development of the statistical model,
and the undertaking of related data computations. She also
provides ad hoc technical advice to countries on innovation
metrics and innovation policy and performance. Lorena iscurrently finalizing her PhD in Economics and Policy Studies
of Technical Change at UNU-MERIT in the Netherlands. She
received her Master of Arts jointly from the Department of
Economics, University of British Columbia, Canada and the
Université Pierre-Mendès-France in Grenoble.

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Dharmendra Sahay is a Managing Principal and Global Leader
for Analytics Practice at ZS Associates, a management consulting
firm focusing on healthcare. He has also been a member of the
ZS Associates Board since 2009. Mr. Sahay has more than 27
years of experience in the healthcare industry, helping multiple
organizations on issues related to commercial strategy andcommercial effectiveness with a focus on technology andanalytics. He has worked extensively with clients to effecttransformational changes in their commercial models with large
analytics and system programs. Mr. Sahay is currently driving
various innovations at the intersection of technology andanalytics, such as building analytics and AI organizational
capabilities, solving complex healthcare business problems
with analytics, and driving organizational change and adoption.
Mr. Sahay has authored several publications on commercial
analytics and technology and is a regular speaker at conferences
on related topics. He has a Master of Science in Computer
Science from Northwestern University and a Master of Business
Administration from the Kellogg School of Management at
Northwestern, as well as a Bachelor of Technology in ElectricalEngineering from the Indian Institute of Technology, Delhi.
Michaela Saisana leads the European Commission’s CompetenceCentre on Composite Indicators and Scoreboards (COIN) at
the Joint Research Centre in Italy. She conducts and coordinates
research on the monitoring of multidimensional phenomena thatfeed into European Union policy formulation and legislation.
She collaborates, by auditing performance indices, with over
100 international organizations and world-class universities,
including the United Nations, UNICEF, Transparency International,
the World Economic Forum, INSEAD, the World Intellectual
Property Organization, Yale University, Columbia University,and Harvard University. Her publications deal with composite
indicators, multi-criteria analysis, multi-objective optimization, dataenvelopment analysis, and sensitivity analysis (25 peer-reviewed
articles, 2 books, 100 working papers). She provides regulartrainings/seminars on composite indicators (over 40 trainings
and 80 invited lectures). In 2004, she was awarded the European
Commission’s JRC Young Scientist Prize in Statistics andEconometrics in recognition of her research on composite
indicators. In 2018, her team won the JRC Policy Award fortheir work on the Social Scoreboard for the European Pillarof Social Rights. She holds a PhD and a Master of Science in
Chemical Engineering.
Aysam Salaheldein is an eHealth Advisor to the Egyptian
Minister of Health, and is Technology Manager of the ‘One
Million Healthy Lives Initiative’. He holds a Bachelor of Business
Administration and is an EU-TDMEP registered senior IT Expert.
His fields of expertise are in digital transformation, eHealth,health insurance, and system analysis. He was honored by the
Egyptian President for his project “HIO Automation”.

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The Global Innovation Index 2019

Bhaven Sampat is an Associate Professor in the Department
of Health Policy and Management at Columbia University anda Research Associate at the National Bureau of Economic
Research. Most of his research focuses on issues at theintersection of health policy and innovation policy. His current
work includes various empirical studies of drug and life sciencepatent policy in the United States of America and developing
countries; evaluating the validity of different approaches tomeasure science, innovation, and science-technology linkages;
and measuring the social and private value of new drugs.
He has previously done empirical research on the political
economy of publicly funded research, patent examinationand patent quality, and the roles of academic patenting inuniversity-industry technology transfer.
Devi Prasad Shetty is the Chairperson and Founder ofNarayana Hrudayalaya (NH) Ltd. He graduated with a Bachelorof Medicine and Surgery from Kasturba Medical College in
Mangalore and has worked as MS (General Surgery) at Kasturba
Medical College, Mangalore; Cardiac surgeon at National HealthService, the United Kingdom; Professor of International Healthat the University of Minnesota Medical School, the UnitedStates of America; Professor at Rajiv Gandhi University of Health
Sciences, Karnataka; Fellow of Royal College of Surgeons
England (FRCS England); Former Governor at the Medical
Council of India; and Chairman, Board of Governors,
Indian Institute of Management, Bengaluru. Dr. Shetty was thefirst surgeon in India to perform heart surgery on newborn
babies and introduced minimally invasive surgery using a
microchip camera to close holes in the heart. He pioneered
operations for complex heart conditions like pulmonary
endarterectomy, redo heart surgery, valve repairs in newborn
babies, and aortic aneurysm surgeries. He also pioneered
the concept of Health City—one shared campus with a few
thousand beds, consisting of different medical specialties
sharing a common infrastructure. He launched India’s firsttelemedicine program in partnership with ISRO to offer cardiac
care across remote locations in India and Africa, which treatedover 53,000 patients free of charge. He created the world’s
first micro-health insurance called Yeshaswini, which became
the model for many state government’s health reimbursement
schemes. He is the Representative of the President of India inthe Board of Governors of Indira Gandhi National Open
University and was nominated to the Board of Governors ofMedical Council of India between 2010 and 2011. He has been
awarded the Ernst & Young Entrepreneur of the Year, 2003;
Padma Shri, 2003; Padma Bhushan, 2012; Medical Councilof India Dr. B. C. Roy Award, 2003; World Economic Forum
Social Entrepreneurship Award, 2005; The Economist Innovation
Award, 2011; and the Nikkei Innovation Award, 2014.
Ahmed Sorour is a Support Officer at the World HealthOrganization Country Office in Egypt, assigned to work in the
Egyptian Minister of Health and Population’s (MoHP) Technical
Office. He participates in planning and preparation of different
projects at the MoHP. He participated in the WHO audit mission‘One Million Healthy Lives Initiative’. He worked in medical
and management fields for more that thirteen years for bothnational and international entities.

Thanaphan Suksaard is a researcher of Health Promotion
Policy Research at the International Health Policy Program,
Ministry of Public Health, Thailand. She received her Bachelor of
Science and Master of Science in Pharmacy from Chulalongkorn
University, Thailand, and her PhD from the University of Surrey,
the United Kingdom. Since completing her PhD in 2014, she has
been working on health policy research. Her research areas
are policy research in public participation, NCDs, risk factors,
and cancer. She is currently working on the project of the Thai
National Cancer Control Program (NCCP) Evaluation.

Hala Zaid is the Minister of Health and Population in Egypt
and has more than 20 years of experience in medical practice,
health system development, planning, and evaluation. Witha Doctorate of Business Administration (DBA), among others,
paired with extensive practical experience at the Ministry of
Health and Population, she developed a deeper understandingof the current challenges and needs of the healthcare system
in Egypt. Her experience in setting and implementing effective
strategic plans, lean management, and business development
has given her the unique opportunity to lead health management
in complex environments.

Parfait Uwaliraye has served as the Director General of Planning,
Health Financing and Information System at the Rwandan
Ministry of Health since November 2012. He leads the Ministry’s
work in Planning, Monitoring & Evaluation, Health Financing,
Partners’ Coordination and Health Information Systems throughPolicy Development, Advocacy, Research and Resources
Mobilization. Dr. Uwaliraye is qualified as a medical doctor witha Master’s in Public Health/Health Workforce Development.
He worked as a Research Assistant, a District Medical Officer,
and the Director of a rural district hospital prior to joining the
Ministry. His particular focus is on health policy & planning,
health financing, private sector engagement, global health, andhealth workforce development.
Daniel Vértesy is a Research Fellow at the Competence Centre
on Composite Indicators and Scoreboards (COIN) at the Joint
Research Centre (JRC) of the European Commission, Italy. He is
conducting and coordinating econometric and applied statisticalresearch projects focusing on the measurement of scientificand technological research and innovation performance atvarious levels in support of EU policies. Prior to joining theEuropean Commission, he worked at the United Nations
University (UNU-MERIT) conducting research on sectoral
innovation system dynamics and emerging aerospace industries.
He holds a PhD in Innovation Studies and Development fromMaastricht University and UNU-MERIT, a PhD in Economics
from the Corvinus University of Budapest, and a Master’s inInternational Relations from the latter university.
Sacha Wunsch-Vincent is Head of the Composite Indicator
Research Section, Economics and Statistics Division, and co-editorof The Global Innovation Index (GII) at the World Intellectual
Property Organization (WIPO). He joined WIPO as Senior
Economist in 2010 to help set up WIPO’s economics work under
the Chief Economist, including the World Intellectual Property
Report and the GII. Before joining WIPO, he was an Economist
and Co-Leader of the Innovation Strategy Project at the OECD
Directorate for Science, Technology and Industry. Prior to that,
he was the Swiss National Science Fellow at the Berkeley
Center for Law and Technology, University of California, Berkeley
and the Peterson Institute for International Economics,
Washington, D.C. He is currently preparing Harnessing Public
Research for Innovation in the 21st Century: An International
Assessment of Knowledge Transfer Policies, a book with
Anthony Arundel and Suma Athreye for the Cambridge
University Press.

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In 2019, the Global Innovation Index (GII) presents its 12th edition dedicated to the theme
Creating Healthy Lives—The Future of Medical Innovation. This edition sheds light on therole of medical innovation as it determines the future of healthcare in the next decades.
Innovation is widely recognized as a central driver of economic growth and development.
The aim of the Global Innovation Index (GII) is to provide insightful data on innovation
and, in turn, to assist economies in evaluating their innovation performance and making
informed innovation policy considerations.
The GII has been impactful on three fronts. First, it helps place innovation firmly on
the policy map, in particular for low- and middle-income economies. As a result,leaders regularly refer to innovation and their innovation rankings as part of theireconomic policy strategies.
Second, the GII allows economies to assess the relative performance of their nationalinnovation system. Economies invest resources to analyze their GII results and metrics
in cross-ministerial task forces and then design appropriate policy reactions, such asaddressing weak R&D funding or innovation linkages.
Third, the GII continues to provide a strong impetus for economies to prioritize andcollect innovation metrics. By experimenting with new data and evaluating existing
innovation metrics, the GII also aims to shape the innovation measurement agenda.
The GII is co-published by Cornell University, INSEAD, and the World Intellectual Property
Organization (WIPO), a specialized agency of the United Nations. The 2019 edition of
the GII draws on the expertise of its Knowledge Partners: the Confederation of Indian
Industry (CII), Dassault Systèmes—The 3DEXPERIENCE Company, and the Brazilian
National Confederation of Industry (CNI) and the Brazilian Micro and Small BusinessSupport Service (SEBRAE), as well as an Advisory Board of eminent international experts.
For the ninth consecutive year, the Joint Research Centre (JRC) of the European
Commission audited the GII calculations.
The GII is concerned primarily with improving the journey towards a better way tomeasure and understand innovation and with identifying targeted policies and goodpractices that foster innovation.
The full report and the GII Mobile Apps—Android and iOS—can be downloaded athttps://globalinnovationindex.org.