Open innovation 2.0 yearbook 2016.
Date: 2016-06-16
Institutions: Directorate-General for Communications Networks, Content and Technology
Subjects: digital technology, information society, information technology, innovation, new technology, provision of services, sustainable development, yearbook

ISSN 1977-7566

Open innovation 2.0 
yearbook 2016

O

p

e

n

i

n

n

o

v

a

t

i

o

n

2

.

0

y

e

a

r

b

o

o

k

2

0

1

6

Communications
Information
Networks, Contents
Society and
and Technology
Media

 
 
 
 
EUROPEAN COMMISSION

Open innovation 2.0 
yearbook 2016

2016  Directorate-General for Communications Networks, Content and Technology

Europe Direct is a service to help you find answers 
to your questions about the European Union

Freephone number (*):

00 800 6 7 8 9 10 11

(*) Certain mobile telephone operators do not allow access to 00 800 numbers or these calls may be billed.

DISCLAIMER

The opinions expressed are those of the author(s) only and should not be considered as representative of the European 
Commission’s official position.

A great deal of additional information on the European Union is available on the internet. It can be accessed through the Europa 
server (http://europa.eu).

LEGAL NOTICE

By the European Commission, Directorate-General for Communications Networks, Content and Technology.

Neither the European Commission nor any person acting on its behalf is responsible for the use which might be made of the 
information contained in the present publication. The European Commission is not responsible for the external websites referred 
to in the present publication.

Disclaimer: This report represents the views of the authors, and is not the official position of the European Commission services.

This work is licensed under a Creative Commons Attribution — Non-commercial — Share Alike 3.0 Unported licence, available at 
www.creativecommons.org.

You are free to share — to copy, distribute and transmit the work, and to remix — to adapt the work, under the following 
conditions:

Attribution. You must attribute this work to the author, but not in any way that suggests that they endorse you or your use of 
the work.

Non-commercial. You may not use this work for commercial purposes.
Share alike. If you alter, transform or build upon this work, you may distribute the resulting work only under the same or similar 
licence to this one.

•  For any reuse or distribution, you must make clear to others the licence terms of this work. The best way to do this is with a 

link to this web page.

•  Any of the above conditions can be waived if you get permission from the copyright holder.

Layout: European Commission

Concept and reproduction: Luxembourg: Publication Office of the European Union, 2016

Print 

Web 

ISBN 978-92-79-53365-5 

doi:10.2759/061731  

ISSN 1977-7558 

KK-AI-15-001-EN-C

ISBN 978-92-79-53366-2 

doi:10.2759/0306 

ISSN 1977-7566 

KK-AI-15-001-EN-N

Reproduction is authorised provided the source is acknowledged.

© European Union 2016

Printed in Luxembourg

Printed on white chlorine-free paper

Contents

FOREWORD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

ACKNOWLEDGEMENTS . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

EXECUTIVE SUMMARY  . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

CHAPTER I
ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENTS . . . . . . 9

Engagement platforms and European innovation systems ............................................................................................................................................................9

A new mode of technical and societal innovation .............................................................................................................................................................................16

Challenges of open innovation ......................................................................................................................................................................................................................22

Open Innovation 2.0 calls for magnetic organisations ...................................................................................................................................................................28

Open data for open innovation ......................................................................................................................................................................................................................35

Thought piece on societal innovation and futurising ....................................................................................................................................................................... 41

Open Innovation 2.0 and higher education ............................................................................................................................................................................................46

CHAPTER II
INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.0 . . . . . . . . . . . . . . . . 49

When large companies build ecosystems, should small companies join? A role for open innovation ...............................................................49

Open Innovation 2.0 and the digital single market ...........................................................................................................................................................................54

Power of user communities affecting decision-making in innovation ecosystems .......................................................................................................59

The role of experimentation facilities in open innovation ecosystems for the future internet .............................................................................64

Trends in the innovation ecosystem, startups and the industrial renaissance ................................................................................................................71

CHAPTER III
FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.0 . . . . . . . . . . . . . . . . . . . . . . . . . . . 79

Smarter cities in the cognitive era...............................................................................................................................................................................................................79

Designing a smart society ................................................................................................................................................................................................................................87

World cities that need transformation ......................................................................................................................................................................................................93

Smart city network boosting open innovation ..................................................................................................................................................................................103

The Smart Countries and Cities Congress ...........................................................................................................................................................................................105

4

Foreword

Dear reader,

Dear colleagues in Open Innovation 2.0,

I am delighted to write the foreword for the 2016 
edition of the Open Innovation 2.0 (OI2) yearbook 
especially  because  we  have  all  seen  in  the  past 
year a lot of very positive developments in the open 
innovation sphere!

Open innovation, coined by Henry Chesbrough, is 
a phenomenon which was growing simultaneously 
with the living labs concept, and the European Net-
work  of  Living  Labs  (ENoLL)  was  established  in 
2006 to be a new innovation policy instrument in 
Europe. These two phenomena interlink strongly in 
the OI2 where the ‘people’ component in the qua-
druple helix innovation approach is highlighted.

In  2015  the  message  ‘Open  science,  open  in-
novation, open to the world’ gained popularity in 
a speech given by Commissioner for Research, Sci-
ence and Innovation Carlos Moedas. This new drive 
will also strongly reflect the European policies on 
innovation,  both  strategically  and  operationally, 
through e.g. the mid-term review of the Horizon 
2020 programme. The commissioner has called for 
input to the European Innovation Council processes, 
contents and operations. In parallel, openness and 
co-creativity is also launched in the horizontal Eu-
ropean actions proposed by the senior adviser for 
innovation in the European Political Strategy Centre 
(EPSC), Robert Madelin.

spirit appears to be crucial in the process of making 
Europe more innovation-friendly and trying to make 
investments in innovation actions and infrastruc-
tures more impactful.

The technology and societal transformations we 
are in the middle of (clouds, Internet of Things (IoT), 
open data, big data, 5G), together with important 
political initiatives, like the digital single market 
strategy, are creating entirely new opportunities for 
new value creation in the shape of new markets, 
new  services  and  new  products  in  a  co-creative 
manner  where  the  users/citizens,  industry,  pub-
lic sector and academia all have their role in this 
seamless collaboration.

I am happy to see that in this yearbook we have 
not only further developed our understanding on 
OI2, but we are also showing a wide range of prac-
tical examples where OI2 works. Despite all this, 
what is still in the core is the change of mindset 
for openness and curiosity and letting the innov-
ation happen in the real world. Brainstorming, ignit-
ing new experiments and prototypes, fast scaling 
up,  orchestrating,  bridging  and  curating  are  the 
new approaches we all need to try, experience and 
analyse.

Wishing you all interesting reading in the company 
of Open Innovation practitioners!

These  examples  manifest  the  extremely  strong 
drivers showing in everyday life when new innov-
ation paradigms step aboard. This new collaborative 

Bror Salmelin
Advisor for Innovation Systems, 
DG CONNECT, European Commission

OPEN INNOVATION YEARBOOK 20165

Acknowledgements

Last name

First name

Company/Organisation

E-mail

Alavaikko

Mika

Diaconia University of Applied Sciences

mika.alavaikko@diak.fi

Ali-Vehmas

Timo

Nokia Technologies

timo.ali-vehmas@nokia.com

Boniface

Michael

IT Innovation Centre, University of 
Southampton

mjb@it-innovation.soton.ac.uk

Çakır

Curley

Yilmaz

Başakşehir Living Lab

y.cakir@superonline.com

Martin

Intel. Labs Europe and National University 
of Ireland, Maynooth, Innovation Value 
Institution

martin.g.curley@intel.com

den Ouden

Elke

Eindhoven University of Technology

E.d.Ouden@tue.nl

Di Minin

Alberto

Scuola Superiore Sant’Anna

a.diminin@sssup.it

Euzen

Jean-Pierre

European Commission

europa@euzen.eu

Edvinsson

Leif

New Club of Paris

leifedvinsson@gmail.com

Gabison

Garry A.

Institute for Prospective Technological 
Studies

garry.gabison@ec.europa.eu

Istrat

Višnja

Rapporteur Open Innovation Strategy and 
Policy Group

Visnja.istrat@gmail.com

Keeling

Mary

IBM

mary.keeling@ie.ibm.com

Kirkpatrick

Scott

Hebrew University of Jerusalem

skirkp1@gmail.com

Kulkki

Seija

Aalto School of Business

seija.kulkki@aalto.fi

Lin

Carol Yeh-Yun

National Chengchi University, Taiwan

yehyunln@nccu.edu.tw

Marullo

Cristina

Scuola Superiore Sant’Anna

c.marullo@sssup.it

Meijer

Geleyn R.

Amsterdam University of Applied Science

g.r.meijer@hva.nl

Nicholson

Artemus E.

PA Consulting Group

artemus.nicholson@paconsulting.com

Pesole

Annarosa

Institute for Prospective Technological 
Studies

annarosa.pesole@ec.europa.eu

Priester

Ruurd

Amsterdam University of Applied Science

r.priester@hva.nl

Rantakokko

Mika

The Six City Strategy

mika.rantakokko@ouka.fi

Salmelin

Bror

European Commission

Bror.Salmelin@ec.europa.eu

Sargsyan

Gohar

CGI Group Inc.

gohar.sargsyan@cgi.com

Schaffers

Hans

Saxion University of Applied Sciences

j.w.m.schaffers@saxion.nl

Schreurs

Mary Ann

City of Eindhoven

m.schreurs@eindhoven.nl

Turkama

Petra

Aalto School of Business

petra.turkama@aalto.fi

Valkenburg

Rianne

The Hague University of Applied Sciences

a.c.valkenburg@tue.nl

6

Executive summary

This year the Open Innovation 2.0 (OI2) yearbook 
focuses much on the operational aspect of showing 
how OI2 is done in practice, and how benchlearning 
can be used to cross-pollinate the impact of this 
new paradigm. The yearbook is divided into three 
main parts: engagement platforms and European 
innovation systems; innovation ecosystems and liv-
ing labs challenged by OI2; and future cities and 
regions in the context of OI2 taking advantage of 
the open innovation approach in practice.

Chapter I. Engagement platforms 
and European innovation systems
The article by Bror Salmelin builds on the work 
which is being done in the European Commission 
on European innovation systems. The focus of his 
reasoning  is  on  the  case  of  platforms  and  their 
governance to achieve the environments for value 
creation  innovation  and  business  model  innov-
ation in a sustainable manner. The role of the dif-
ferent stakeholders in the innovation ecosystem is 
described in a new way illustrating the short, rapid 
innovation cycles needed to create new markets, 
and the longer cycles which design the necessary 
infrastructures and enablers.

The article by Professor Martin Curley is based 
on the 20 snapshots of OI2, a concept published 
for the first time in the first whitepaper on OI2. To 
make the OI2 concept easier to implement in prac-
tice, he introduces a design pattern where the most 
important processes and functionalities in OI2 are 
described, also by examples.

The transformation of the open innovation para-
digm itself is described in the article by Dr Petra 
Turkama  and  Dr  Seija  Kulkki.  Open  innovation 
has matured to a mainstream innovation process 
for major companies and the public sector. Lead-
ing companies actively engage their customers and 
stakeholders in a co-creation process, while open 
consultations are becoming a norm in the public 
sector. The recent term ‘Open Innovation 2.0’ on 
the one hand highlights the advances in open in-
novation, and on the other makes a separation from 
the early open innovation concepts by von Hippel 
and Chesbrough that no longer explain the market 
nuances. The drivers for this transition and critical 
elements in the modern view for open innovation 
are elaborated in this article.

innovation  and  magnetic  organisations  on  the 
transformation  of  organisation  structures  and 
behaviour. The text elaborates on the elementary 
conditions and drivers for large- and medium-sized 
organisations to be effective in OI2. The authors 
introduce the notion of magnetic organisations and 
argue that a right mixture of internal initiatives, 
entrepreneurship and a compelling attractive goal 
are needed to move ahead. Physics is used as an 
inspiration source for describing two conditions that 
can be analysed and used for organisational design. 
Theory of organisation entropy is used to develop 
the freedom to act and connect to the outside while 
the principles of magnetism are employed to focus 
on goal orientation and convergence.

Dr Timo Ali-Vehmas focuses on the data-driven 
innovation in his article. He draws an interesting 
parallel between traditional raw materials and data 
by claiming that life in general, and business life is 
no exception, has always focused on the new raw 
materials which can be transformed to valuable 
products and services to customers. The new raw 
material of the data age is the data. Therefore, it is 
not enough to complement the world we know with 
an additional data element but rather we need to 
place the data in the centre. Similarly, as our soci-
ety is becoming more and more data driven and 
a larger share of our decisions, including also finan-
cial decisions, is based on the digital information we 
have available.

Professor Leif Edvinsson describes a new approach 
to societal innovation 3.0 and beyond. He sets the 
context in societal innovation at national level as 
well as how to progress with big issues on a glob-
al scale with open innovation. Societal in novation 
refers to a systemic change in the interplay of the 
state and of civil society. It is a relative of social in-
novation, but differs from it by considering the state 
to be an important co-creator in achieving sustain-
able systemic change. The prototyping might take 
place with impact investing models, circular econ-
omy,  sharing  economy  and  working  together  for 
the  environment  and  the  economy.  A whole  new 
prototyping paradigm, a glossary or taxonomy and 
metrics/key performance indicators (KPI) might be 
in progress for the innovation work of new ways of 
shaping and sharing the wealth creation.

Professor Geleyn Meijer, Artemus E. Nicholson 
and Ruurd Priester focus in their article on open 

Mika Alavaikko describes how a higher education 
institution (the University of Applied Sciences in Fin-
land) is reforming the curricula and collaborative 

OPEN INNOVATION YEARBOOK 2016E X E C U T I V E   S U M M A R Y

7

environments both internally and externally using 
open  innovation  principles.  The  institution  has 
developed blogging as the collaborative and sharing 
platform which has proven to be simple and also 
seamless enough for successful joint undertakings. 
As a consequence, the platform has also changed 
the teaching method and learning processes in the 
institution.

Chapter II. Innovation ecosystems 
and living labs challenged 
by Open Innovation 2.0
Garry A. Gabinson, Annarosa Pesole, Professor 
Alberto Di Minin, and Cristina Marullo tackle the 
problematic balance of small and large enterprises 
in innovation ecosystems and platforms. The rise 
of the open innovation paradigm has encouraged 
the creation of innovation networks (ecosystems) 
involving a mix of partners: universities, research 
laboratories, start-up companies, small- and me-
dium-sized enterprises (SMEs), multinationals and 
governments.  Physical  proximity  is  an  essential 
driver of open innovation effectiveness. It enables 
the exchange of ideas and inside/outside exploita-
tion  of  knowledge  and  resources.  This  paper  in-
vestigates how some large companies invested in 
key relationships with external innovation partners 
through the creation and the orchestration of open 
ecosystems (e.g. open research campuses). By con-
trast, small companies cannot afford to create and 
orchestrate their own local research ecosystem, but 
they do have the option to join or co-locate within 
existing ecosystems. This paper draws lessons from 
two of 13 case studies the authors collected, and 
compares and contrasts the experience of ecosys-
tem builders and ecosystem joiners.

In the article ‘Open innovation and the digital sin-
gle market’ Dr Gohar Sargsyan focuses on the fu-
ture cities and how open innovation can accelerate 
and focus the development. Her focusing sentence 
is  ‘Think  big,  start  small,  accelerate  fast’,  which 
captures  well  the  spirit  of  experimentation  and 
prototyping in OI2. The approach suggests the im-
portance of open innovation ecosystems and close 
and seamless involvement of citizens in the sus-
tainable development of future cities.

Visnja Istrat elaborates on the power of crowds 
and communities in open innovation ecosystems, 
and  on  how  the  communities  can  be  increas-
ingly engaged in business model/value creation 
development. Networking and collaboration tech-
nologies are extremely effective ways of bringing 
experts together to perform new processes and 
to share experiences — both the success stories 
and the possible setbacks. People, also stakehold-
ers, with common interests or related roles can 
form communities to learn from and support one 

another. Social media can also help in cases where 
creating  a more  collaborative  culture  is  one  of 
the major objectives of the change management. 
The subject is about the crowd of user commu-
nities that affects decision-making in innovation 
ecosystems.

Dr Hans Schaffers, Michael Boniface and Scott 
Kirkpatrick  build  their  article  on  the  success  of 
FIRE  platform  and  experimental  approach.  He 
argues that the approach is useful and needs to 
be further expanded to cover the new technology 
developments,  but  also  to  address  the  societal 
changes from an application perspective. Increas-
ing focus on ‘complex smart systems of networked 
infrastructures and applications’ within the FIRE 
programme, the unique and most valuable contri-
bution of FIRE should ‘bridge’ and ‘accelerate’: cre-
ate the testing, experimenting and innovation envi-
ronment which enables linking networking research 
to business and societal impact. FIRE’s test beds 
and experiments are tools to address research and 
innovation in ‘complex smart systems’, in different 
environments such as cities, manufacturing indus-
try and data-intensive services sectors.

The article by Ylimaz Cakir describes the devel-
opment and transformations in the Turkish innov-
ation ecosystem, taking the Başakşehir living lab as 
a focal point and as driver for the new ecosystems. 
He further elaborates that, where open innovation 
is foreseen, living labs have a central role in the 
Turkish strategic goals on innovation policy. The 
article also argues that living labs methodology, 
together with open innovation, is the transforma-
tive engine for industry and society.

Chapter III. Future cities and regions in 
the context of Open Innovation 2.0
Dr Mary Keeling is touching upon open innovation 
from  a very  interesting  and  important  perspec-
tive. Cognitive technology brings new capabi lities 
that  offer  the  potential  to  transform  the  way 
work is done, the way services are provided, the 
way products are made and the way businesses 
and organisations of all sizes and in all sectors 
are run. Organisations can enable and accelerate 
innovation and growth as part of open innovation 
activities by pulling in capabilities from outside 
the organisation, and by active participation and 
engagement in cognitive ecosystems and collab-
orative networks. Cognitive capabilities are needed 
by businesses and organisations to make sense of 
the large and rapidly growing amounts of unstruc-
tured data and to shine a light on ‘dark’ data. In 
open innovation platforms, the open and big data, 
for example, will be the challenge to be used ef-
fectively for new markets, products and services 
creation.  The  article  illustrates  with  concrete 

8

examples how cognitive capabilities are used suc-
cessfully in creating value for all stakeholders in 
the innovation ecosystems.

hubs of the world. There are abundant clues from 
the figures and tables presented in this paper.

Drir. Rianne  Valkenburg, Drir.  Elke  Den  Ouden, 
and Drs. Mary Ann Schreurs outline the challenges 
of modern co-creation with citizens and the new 
design approach which is needed when applying 
OI2. Smart solutions enable citizens to become an 
active producer of societal value, instead of a pas-
sive consumer of government services. Redefining 
smart cities to a focus on quality of life for their 
citizens  implies  creating  a  smart  society.  In  this 
transformation lies the design challenge of how 
to enable and engage all citizens to make use of 
the new possibilities and employ themselves. To 
really become a resilient city, a different approach 
is needed to engage the people.

Professor Carol Yeh-Yun Lin expands the previous 
work on national intellectual capital to city level. 
This is extremely important when setting regional 
and  local  development  goals  and  measures,  as 
structural intellectual capital seems to be the driver 
for the competitiveness and value creation also on 
city level. In the article the measures are discussed 
on a very practical level, opening a lot of opportu-
nities to reinforce the most important drivers for 
value creation and well-being in society. Cities will 
become the unit of competition rather than nation 
states  in  the  future.  Attending  to  the  intangible 
assets development may decide the future talent 

In  the  article  by  Dr  Mika  Rantakokko  a  six-city 
collaboration network is described: a strategy for 
sustainable urban development carried out by the 
six largest cities in Finland: Helsinki, Espoo, Vantaa, 
Tampere, Turku and Oulu. By building the national 
network of open innovation platforms, driving new 
competence development, business and jobs cre-
ation will become more efficient. Utilising the wide 
variety of knowledge and specialisation in different 
cities, the best practices and concepts will be col-
lected to form an excellent basis for a new type of 
city business modelling.

Jean-Pierre Euzen describes in his article the think-
ing and action behind the new birth of Paris to be 
one of the leading hubs of innovation in Europe. The 
regional approach is very interesting, and builds on 
a wide variety of physical spaces dealing with in-
novation already existing: living labs, fab labs, hack-
erspaces, digital factories, microfactories, co-work-
ing  spaces,  TechShop,  makerspaces,  etc.  Their 
common objective is to promote innovation and en-
trepreneurship by leveraging collective intelligence 
and collaborative dynamics on the territories and 
form an essential part of the open innovation eco-
system. Integrating the activities under one umbrel-
la makes the collaboration of these entities easier 
and we are getting closer to seamless infrastructure 
services for new entrepreneurship.

OPEN INNOVATION YEARBOOK 2016CHAPTER I

Engagement platforms 
and business modelling 
in Open Innovation 
2.0 environments

Engagement platforms and European innovation systems

Abstract

This article highlights some recent innovation trends through the lens of open innovation and impact 
of innovation investments. Open Innovation 2.0 (OI2) stresses the importance of all stakeholders in the 
innovation: the users/citizens, the industry, the public sector and academia. In this article I elaborate 
the role of the stakeholders to achieve the boiling kettle of innovation ecosystems.

I focus on the case of platforms and their governance to achieve the environments for value creation 
innovation and business model innovation in a sustainable manner. The technology development is 
extremely rapid towards new technology platforms, but what is needed is the integration of them to 
enablers for new value creation.

Each of the stakeholders has their distinctive role in creating the critical enablers and fluidity of suc-
cessful ecosystems. The focus in this paper is on creating the new industrial era with new kinds of 
products, services and entirely new industries too, rather than improving the old paradigm. We in 
Europe need to have an entirely new approach to value creation for all based on our industries, leading 
to the creation of new products and services in modern innovation ecosystems.

We have some conceptual forward-looking elements in the European innovation landscape, but now 
is the time to put that into practice. Only by looking at the innovation governance as enabler for the 
seamless interaction across the disciplines and different stakeholders can we move fast enough to 
respond to the challenges we face in societal and technological transformation. Or actually instead of 
challenges we should see this transition as a golden opportunity to reinforce the European approach!

The  digitalisation  also  enables  the  creation  of 
engagement platforms for new value creation for 
all  stakeholders  through  new  business  models 
where the driving force is to win together. This also 
links to sharing economy developments, and even 
more  importantly  to  issues  the  new  technology 
brings forward through the societal change. Are we 
solving the right problems with our current actions?

Importance of online 
engagement platforms
Digital is the key driving the creation of the new: 
merging digital into tangible economy like in Industry 
2.0, but also creating entirely new digital en ablers 
based on the current technology transformation to-
wards future internet, 5G communications, clouds, 
IoT and, last but not least, massive and open data. 
If this transformation is looked at in a compartmen-
talised technology-oriented way we miss the oppor-
tunity to create a holistic perspective of the trans-
formative power of these technologies in all industry 
and society. We see a new set of en ablers to more 
concretely build our OI2 approach in Europe.

10

As Commissioner for Digital Economy and Society 
Günther Oettinger says:

‘Online platforms are playing an ever-more central 
role in the digital economy in a wide range of areas 
and are rapidly and profoundly challenging tradi-
tional business models. Some of these platforms 
can control access to online markets and can exer-
cise significant influence. This raises important regu-
latory questions we will answer in a comprehensive 
assessment of the role of platforms in 2016’ [1].

Can we use experimentation in the real world as 
the approach to see which aspects of the platforms 
and their functionalities are to be regulated, and 
where the markets can take the lead?

Taking the lessons when creating the mobile com-
munications industry in Europe in the late 1980s 
into  consideration,  it  is  critical  to  share  the  basic 
technological  developments  on  open  platforms 
(where  e.g.  cross-licencing  of  the  essential  pat-
ents is fair/shared) and where standardisation on 
the functional level happens across the technology 

silos mentioned before. Functional integration is im-
portant across the technologies as modern applica-
tions are increasingly based on this new technology 
space.

Modular and functional approach: 
overarching the transformation 
of technologies and society
Functional integration leads to important issues on 
how to create the consensus for open platforms and 
environments in and for Europe. Technology inter-
operability is not an issue, but rather the creation 
of the open ecosystems and platforms in an inte-
grated, holistic manner on functional level. What 
I mean by ‘functional’ is well explained in a report 
by Myriam Corral [2], published in the Open Innov-
ation Strategy and Policy Group (OISPG) publication 
series, where OISPG elaborated, based on the pub-
lic services structure, a meta-architecture of those 
functionalities  which,  like  LEGO  building  blocks, 
could  be  configured  to  any  service  needed.  The 
building blocks were functional, based on functional 
interoperability, and had no predefined technology 
base.

Figure 1: The modular structure for services of public interest. Each module is part of the 
functional interoperability scheme but the technology realisation is not defined

Services Components

Document store

Searches

Digital
Trust

Electronic
Identity

Personal data

Information
Exchange

Address Manager

Personalisation

Tagging

Online Help

Multilingualism

Alerts and
scheduling

Social
Collaboration
Tools

Notiﬁcations

Mobility

Multichannel

Privacy
Manager

Electronic
Invoicing

Context
Information

Electronic
Signatures

Spatial
Information

Payment
System

Figure  1  illustrates  the  functional  structure  of 
building blocks based on which services for citi-
zens can be configured. The functional interoper-
ability is essential as then we do not need to pay 
too much attention to the underlying technology 

base. When looking at these building blocks we can 
also observe that many of them are essential com-
ponents in the digital single market actions. Exam-
ples that can be mentioned are identity manage-
ment, security, privacy, electronic commerce, etc.

OPEN INNOVATION YEARBOOK 201611

The recent technology development enables the 
realisation  of  those  functions  more  easily  than 
before; e.g. the cloud enables global accessibility to 
the roaming data needed for service integration, IoT 
enables the integration of multilevel sensory data 
to automate some of the features in the functional 
modules, etc. Open data is also important when we 
develop these modules further. What we see today 
is the platforms being dominated by large players 
creating (closed) platforms for their own ecosys-
tems. Good examples of these are e.g. companies 
like Apple and Google but also many players in the 
sharing economy like Airbnb, Uber, BlaBlaCar, etc. 
In this game the platform is integrating the con-
tent/service providers to their own ecosystem. This 
is also seen in the development of the platform-
dominating companies being valued to several bil-
lion euros, and the number of these unicorns grow 
very fast, from a few to more than a hundred in 
2015. One can justifiably ask if these platforms and 
unicorns have any analogy to the e-commerce bub-
ble we had in the beginning of the century where 
empty expectations collapsed very fast.

E-platforms: part of the creative 
and shared commons in Europe?
Can  and  should  the  European  approach  be  dif-
ferent? Can we see the platforms as part of the 

creative and shared commons in Europe as we did 
with  the  mobile  communications  basis?  Can  we 
build on platforms being closer to cooperatives for 
their collaboration partners sharing the wealth and 
success to the users and content providers? What 
is  the  sustainable  European  approach  to  plat-
forms? How can block chain technology be used to 
increase the very important peer-to-peer trust in 
open platforms?

What I see as a challenge is to combine the new 
technological  driver  with  the  changing  societal 
needs to create innovative, even disruptive, solu-
tions  based  on  the  new  enablers.  Can  new  ser-
vice and platform architectures be developed fast 
enough, and how can the full benefit of the digital 
single market be captured with the new functional, 
open approaches?

When  further  elaborating  this  approach  from 
a societal context we can identify the social col-
laboration toolset — modules which compose add-
itional functionalities when co-creativity, collabora-
tion and community building are needed. This leads 
to the need of new modules focusing on collabora-
tive and participative innovation aspects as shown 
in Figure 2.

Figure 2: Collaborative modules are added for co-creativity and innovation

Services 
Components

Information
Exchange

Mobility

Document store

Searches

Electronic
Identity

Personalisation

Address Manager

Notiﬁcations

Multilingualism

Digital
Trust

Tagging

Payment
System

Alerts and
scheduling

Social
Collaboration
Tools

Multichannel

Privacy
Manager

Personal data

Context
Information

Spatial
Information

Online Help

Electronic
Invoicing

Electronic
Signatures

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT12

It is noteworthy that this basic, conceptual user-
driven approach stems from the report by OISPG 
in 2010 [3] where the user/citizen-centric perspec-
tive of new business models was described by the 
reverse innovation pyramid [4]. Again, and repeat-
edly, I need to highlight that these platforms are 
technology agnostic, and therefore the interoper-
ability  enables  all  sizes  of  companies  and  even 
individuals  to  operate  in  this  innovation  sphere. 
There are no lock-in technologies one dominating 
company could use, as today is still sadly the case.

Governance of platforms and 
environments for innovation
Europe has huge potential to use the technology 
transformation  of  digital  technologies,  if  at  the 
same time it takes on board the quadruple helix-
user  co-creative  approach  for  new  markets  and 
services. I firmly believe that the user co-creativity 
is increasing in importance, especially when we are 
creating the ‘new’, as mentioned in the introduction. 
In the traditional triple helix approach we too eas-
ily fall into the win-lose game against the existing 
competitors. However, in Europe we need to pro-
gress in areas where we do not have any competi-
tors yet.

Common vision is needed to make the synergies 
between the actions across stakeholders and eco-
systems. Strong vision requires a wide set of inter-
related actions driving to the same direction, but 
also having competition among themselves. Here 
the OI2 approach steps in. Based on common goals, 
different approaches in various contexts are experi-
mented, and from those the most successful ones 
are rapidly scaled up, to be built upon in the next 
phases.

A good illustration of this can be seen, for example, 
in the Future Internet governance where the basic 
technologies develop quite independently and the 
governance  on  the  upper  layers  determines  the 
functionalities and ways of application of the single 
building blocks. This is well illustrated in Figure 3 
displayed in Francesca Bria’s article [5]. The digital 
single market actions of the European Commission 
reinforce this kind of coordinated governance inte-
grating the technological and policies development 
for entirely new types of services, products and 
foremost value creation processes in and for the 
society.

Figure 3: Future internet as an example needs several layered governance processes from technical and 
functional interoperability to the mastering of the internet as an omnipresent platform for value creation

This approach could also lead to purpose-driven 
companies  rather  than  money-driven  ones  only; 
in purpose-driven companies the societal impact 
and  longevity  of  the  life  span  is  increasingly 
important and is leading to societal and business 
sustainability.

The rules of the game are designed based on the 
values driving the society on the highest govern-
ance  level  of  these  platform  ecosystems.  One 
strong  option  to  consider  is  collaborative  coop-
eratives as intermediaries instead of the current 
money-driven ones.

OPEN INNOVATION YEARBOOK 201613

A concrete example of emerging platform consoli-
dation can be seen in recent developments around 
Fiware.

• 

• 

Fiware and the European Data Portal [6] will 
collaborate  to  bring  free  data  to  the  grow-
ing  open  community  of  thousands  of  Fiware 
developers, startups and new users in Europe 
and worldwide. These open more than 250 000 
datasets available through a multilingual inter-
face  of  the  European  Data  Portal  and  come 
from public organisations in the EU, and it is 
available for use and reuse for commercial or 
non-commercial purposes.
Fiware and TM Forum [7], the global industry 
association  for  digital  business,  have  joined 
forces  to  speed  up  the  development  of  new 
smart  city  applications.  This  partnership  will 

• 

enable more efficient management of municipal 
services in areas such as mobility, water, waste, 
energy and environmental management, and 
will also pave the way for the development of 
smart applications by third parties.
The Things Network [8] and Fiware Lab NL [9] 
have  recently  announced  the  creation  of  an 
open IoT platform. The two initiatives will cre-
ate together an open IoT platform so developers 
will have meaningful sensor data to work with 
in the Fiware Lab to create new solutions for 
smart cities, healthcare, agrifood and more.

Short and long innovation cycle
The  role  of  the  different  stakeholders  to  create 
these environments and processes for creating new 
markets, value and services can also be illustrated 
with the following picture.

Figure 4: The short innovation cycle with experimentation enables the creation of new markets 
and extended products (product and services integrated) and the long innovation cycle creates the 
framework for creating new seed and the infrastructures needed for innovation ecosystems.

The  research  institutions/community  is  bringing 
new seed into the innovation system which inter-
acts with the real world (users) via Research and 
Technology Development, and Innovation (RTDI). 
The users based on this interaction act as a pilot-
ing  and  experimentation  environment  creating 
new markets for policies, products and services. 
The cyclic innovation can also be initiated by co-
creativity of the users. What is important is that we 
have the fast cycle of new market creation where 
users and the industry are key. In addition, we have 
longer cycles where infrastructures (conditions for 

innovation) are created, where the public sector has 
an important role to foster new seed to grow, to 
do infrastructure investments and to create favour-
able  conditions  for  frictionless  processes  in  the 
faster innovation cycle.

Focus  in  this  diagram  is  on  the  creation  of  the 
‘new’, but of course the users’ behaviour is strongly 
affecting the old existing markets in their renewal.

In Figure 4 I also explain that depending on the 
sector the balance between the various quadruple 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT14

helix players is different, especially when we see 
the Research and Technology Development (RTD) 
component in creating the new (industries, services, 
products).

This kind of division of roles and identifying long 
and short innovation cycles helps us also to better 
consider the short-term operative objectives from 
the long-term challenges and opportunities. It leads 
to the question of balance between these two.

Shorter-term  policy  goals  lead  to  rather  well-
defined innovation agendas, like in Horizon 2020. 
The  key  questions,  however,  are  if  we  can  have 
enough  serendipity  in  these  operational  pro-
grammes  and  if  we  can  properly  take  on  board 
longer-term trends at an early enough stage.

Are we solving the right 
issues? Long-term cycles
The new platform economy leads to new oppor-
tunities for the various stakeholders due to the new 
enabling digital technologies. The technology pal-
ette has a transformative power beyond the mod-
ernisation of current services and structures.

The digital single market, platforms and rapid tech-
nology development are all simultaneously leading 
to new, disruptive problem settings in the long-term 
innovation cycle.

A smart cities example
It is said that digital connectivity kills cities. The 
impact of connectivity replacing physical mobility 
leads to new city structures and new models for 
city planning. In the discussion we increasingly hear 
about edge cities replacing megacities. Edge cities 
are 60 000-100 000 population cities which are 
well  connected  and  self-sustained.  In  the  vision 
of Garreau [10], megacities will break into smaller 
cities. In Tokyo, an example told by the largest local 
construction companies, the change of job nature 
will likely need the mixed use of high-rise office 
buildings and the establishment of several edge 
cities within the metropolitan area. E-commerce, 
local service accessibility, goods delivery based on 
drones or nearby 3D printing are all information 
and communications technology-related technolo-
gies shaping modern cities and must be taken into 
account when designing future actions. Serendipity 
and disruptions characterise future city develop-
ments more than we now see in our programmes. 
Topics  like  autonomous  or  self-driving  cars  will 
make rapid progress but will only likely be very par-
tial solutions in the radically changing city-planning 
landscape.  Communications  infrastructures  will 
likely be much more important than mobility infra-
structures. Infomobility solves the mobility issues 
we have in the current mobility landscape.

Do  we  have  enough  of  ‘against  the  mainstream 
research’?  Do  we  have  the  courage  to  face  the 
unexpected? We need to have new design in the 
research and innovation landscape where projects 
are allowed to have uncertainty, and not only lin-
ear extrapolations of the past with well-defined 
roadmaps.

Conclusion
It is important to build the innovation capability in 
Europe based on OI2 and functional interoperability 
of integrated technological platforms such as IoT, 
clouds, open data and 5G. The joint undertakings 
in these areas are ensuring a strong foundation. 
Integrating these transformative technologies en-
ables new value-creation models for businesses 
and society.

A new European innovation governance structure is 
needed, with an open and exploratory mindset open 
for challenges and disruptions.

In order to fully achieve this, a strong joint move-
ment  is  needed  to  create  the  open  innovation 
ecosystems  based  on  common  architectural 
approaches on meta-level, enabling fast develop-
ment and experimentation of the emerging solu-
tions, in turn making a fast scale-up of possible 
successes. As indicated before, all the stakeholders 
have an important role in creating these environ-
ments and making them feed new ideas, concepts, 
products and services — all in a co-creative mode.

A good and recent development of embracing the 
innovation aspects in Horizon 2020 are the innov-
ation radar activities where the innovation aspects 
of  the  Horizon  2020  projects  are  assessed  by 
independent experts during the project, and not 
only ex post. Lessons learnt can be fed into exist-
ing projects but especially into new programmes 
to  increase  their  impact.  Due  to  its  methodical 
approach,  OI2  will  likely  increase  in  importance 
when the impact is measured.

We are on a very good path integrating the pan-
European,  regional,  national  and  local  activities 
with  a common  vision  for  the  future  of  Europe. 
Thinking in innovation systems is taking on board 
the newest developments as well as policies and 
funding instruments.

References
[1]  http://neurope.eu/article/
europes-digital-challenges-in-2016/

[2; 3]  Corral, M., Put user in the centre for services — 
A reference model, DG Communications Networks, 
Content and Technology of the European Commission, 
Luxembourg, 2010.

OPEN INNOVATION YEARBOOK 201615

[4]  https://ec.europa.eu/digital-agenda/en/news/osi-
socioeconomic-impact-open-service-innovation-smart-
20090077-study

[5]  Bria, F., ‘New governance models towards an open 
internet ecosystem for smart connected European cities 
and regions’, Open Innovation 2.0 — Yearbook 2012, 
European Commission, Luxembourg, 2012, pp. 62-71.

[6]  http://www.europeandataportal.eu/

[7]  https://www.tmforum.org/

[8]  http://thethingsnetwork.org/

[9]  http://fiware-lab.nl/

[10]  Garreau, J., Edge city: life on the new frontier, 
Anchor Books, New York, 1991.

Contact

Bror Salmelin
Adviser for Innovation Systems
DG Communications Networks, 
Content and Technology
European Commission
Bror.Salmelin@ec.europa.eu

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT16

A new mode of technical and societal innovation
Open Innovation 2.0

Abstract

A new mode of technical and societal innovation is emerging, with blurred lines between universities, 
industry, governments and also featuring users and indeed communities as innovators. For example in 
Brixton, United Kingdom, a broad set of stakeholders including Lambeth Council, Transport for London, 
companies and most importantly schools and children are fusing participatory design, data and play to 
co-design urban services that approach sustainability through community sensing, data visual isation, 
behaviour change and ambient technology in what is an illustration of Open Innovation 2.0 (OI2) in 
action. OI2 is a new mode of innovation based on principles of integrated collaboration, co-created 
shared value, cultivated innovation ecosystems, unleashed exponential technologies, experimentation 
and focus on adoption and sustainability. OI2 is rooted in a vision of sustainable intelligent living where 
smart solutions are developed and diffused meeting needs while being resource- and environmentally 
efficient. OI2 also promises significant improvements in the pace, productivity, predictability and profit-
ability of our collective innov ation efforts.

Figure 1: OI2 — a new milieu

Enabling forces
The collision of three mega trends, Moore’s law, 
mass  collaboration  and  sustainability,  each  of 
which are mutually reinforcing, is creating a unique 
opportunity for us to leverage our collective intel-
ligence and energies. Here the nature of innovation 
changes from a linear to a non-linear process to 
drive innovation and deliver structural outcomes 
far beyond the scope of what any one organisation 
or individual could achieve on their own. Significant 
technological innovation has ensured that Moore’s 
law continues to hold true to essentially deliver the 
doubling of compute performance delivered at less 
or equal cost every two years or so. The new in-
novation revolution is enabled by increasing levels 
of connectivity and catalysed by the emergence of 
exponential technologies such as Internet of Things 
(IoT), clouds and open data. Thus, ordinary things 
from dishwashers to cars become smart, connected 
and collaborative. When smart things and indeed 
people are connected the intrinsic intelligence and 

our  collective  execution  capability  is  multiplied 
exponentially.

Not only is there great opportunity to create and 
extract  value,  particularly  of  challenges  when 
data is shared, aggregated and analysed across 
domains,  but  a transformation  opportunity  also 
exists to create new high-frequency, high-preci-
sion management control circuits in societal level 
systems, where previously only open-loop control 
was possible. A simple example is a gully signal-
ling to a city management system that it is blocked, 
whereas  a more  complex  example  is  a dynamic 
congestion-based charging system which automa-
tically adjusts, changes traffic flow and offers park-
and-ride incentives based on parameters such as 
levels of traffic and air quality in a city.

The European Internet Foundation (EIF) has pro-
posed for the next decades a paradigm of a world 
driven  by  mass  collaboration,  enabled  by  the 

OPEN INNOVATION YEARBOOK 201617

ubiquitous availability of high-speed, high-capacity 
digital networks and services. The EIF predicts the 
inexorable spread of purpose-driven online collab-
oration as the role of networks evolves from ena-
bling not just communication and transactions, but 
also value creation through collaboration. We have 
all witnessed the phenomenon of ‘social produc-
tion’, whereby people contribute to generate eco-
nomic value and where there are few or no mon-
etary incentives involved with the ongoing evolution 
of Wikipedia and the development of Linux being 
primary examples.

We will see mass people-to-people, machine-to-
machine  and  machine-to-people  collaboration. 
Sometimes  this  collaboration  will  be  proactive 
creative collaboration, where individuals as part of 
a community or as part of more formal innovation 
configurations will co-design and co-create solu-
tions such as a new city services or the transform-
ation of an electrical grid. At other times we will 
give  permission  to  our  devices  to  collaborate 
together  to  figure  out  an  optimum  solution  to 
a given scenario, for example real-time car-to-car 
communication and collaboration to determine the 
best sequencing of traffic at an upcoming junction 
to minimise transit times. The EU FP7 total elas-
tic adaptive mobility project (TEAM) is focused on 
developing cooperative systems for energy-efficient 
and sustainable mobility, with drivers, travellers 
and infrastructure acting as a team — adapting to 
each other and to the situation and creating opti-
mised mobility conditions. The TEAM solutions are 
currently being piloted in several European cities 
including Athens and Turin, with players such as 
BMW, FIAT, Volvo and Intel involved, as well as the 
municipalities and citizens, naturally.

With  the  adoption  of  the  new  UN  sustainable 
development goals, the recent Paris COP21 agree-
ment and the increasing trend of extreme weather 
events, individuals and communities are becom-
ing more sustainability focused. In parallel, there 
is a slow but growing recognition of the need to 
move  from  the  ‘take,  make,  dispose’  mode  of 
today’s linear economy to a circular economy that 
preserves and enhances natural capital. The nir-
vana  of  sustainability  is  the  ability  to  decouple 
growth from resource consumption and environ-
mental impact, and knowledge-driven entrepre-
neurship provides a potential pathway to achieve 
this. Former EU Commissioner for Research Máire 
Geoghegan-Quinn’s statement that ‘knowledge is 
the crude oil of the 21st century’ aptly describes 
the opportunity. By leveraging the astonishing pos-
sibilities enabled by Moore’s law and harnessing 
the collective intelligence and energy of people and 
machines worldwide through mass collaboration 

focused on new solutions which are intrinsically 
sustainable, we may be about to witness some-
thing akin to a pre-Cambrian explosion of impact-
ful innovations.

Similar to the Gutenberg invention of the printing 
press, the invention and evolution of modern com-
puting and communications technology is a funda-
mental disruptor to the fabric and nature of soci-
ety. We have all witnessed how industries such as 
the music- and book-selling industries have been 
transformed  through  ICT  led  by  companies  such 
as Apple and Amazon. This is Schumpeter’s ‘cre-
ative destruction’ at work, or it could alternatively be 
termed ‘digital Darwinism’. However, the next phase 
of digital transformations will deliver significantly 
more value, will be more difficult orders of magni-
tude and will require significant citizen involvement 
to maximise the chances of success. Transformation 
of our cities, energy grids and healthcare systems 
will ultimately evolve through a process of emer-
gence; however, the opportunity exists to proactively 
take charge and move much more quickly to the 
benefits promised by these transformations. OI2 is 
an emerging innovation mode which is based on an 
evolving set of design patterns, i.e. general reusable 
solutions to commonly occurring problems which 
can accelerate the delivery of innovation benefits.

The importance and 
evolution of innovation
It is easy to see why many people are drawn to 
technical innovation, as according to the Organ-
isation  for  Economic  Cooperation  and  Develop-
ment,  it  is  the  leading  contributor  to  growth  in 
developed countries. In the United States 75 % of 
the GDP growth since World War Two has come 
from technological-based innovation, according 
to the United States Department of Commerce. 
In the last century it was often a brilliant scien-
tist at Bell Laboratories or an IBM lab which drove 
new inventions and subsequent innovations. Then 
along came Open Innovation, which was neatly 
conceptualised by Henry Chesbrough and is about 
a systematic process where ideas can pass to and 
from different organisations and travel on differ-
ent exploitations vectors for value creation. Open 
Innovation was based on the idea that not all of 
the smart people in the world can work for your 
company or organisation and that you have to also 
look outside the organisation for ideas. Procter 
and Gamble are frequently referenced as a role 
model  for  practicing  open  innovation  and  their 
‘connect and develop’ open innovation strategy 
has resulted in almost 50 % of their new products 
coming from ideas and innovations which started 
outside of the company.

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT18

Figure 2: The evolution of innovation. Source: Salmelin, EU Open Innovation Strategy and Policy Group

The discipline of innovation is constantly evolving 
and now the combination of exponential technolo-
gies,  together  with  participation  of  actors  from 
across value chains, is creating a new primordial 
soup which creates an environment to yield ever-
more complex and compelling innovations. Indeed 
the unit of competition is changing in that it is no 
longer how good an individual company or organ-
isation  is,  but  the  strength  of  the  ecosystem  in 
which they participate in is often the differentiating 
factor for great success, mediocrity or even failure. 
Witness the decline of once-leading mobile phone 
handset companies like Nokia and Blackberry, and 
the  unprecedented  success  of  the  Apple  iPhone 
and various Android-based handsets. A key differ-
entiator has been the strength, incentivisation and 
nurture of the ecosystem developing and using the 
products. Organisations can no longer afford to do 
it all on their own as innovations are so intercon-
nected and are often composed of intelligent com-
binations of emerging and existing solutions and 
building blocks.

OI2 — A new mode of technical 
and societal innovation and an 
emerging pattern language
OI2 is a new mode of technical and societal innov-
ation. The notion of a community or ecosystem co-
innovating together is central to the new mode of 
innovation. The Innovation Value Institute at May-
nooth University and the Alcatel-Lucent-led Green 
Touch consortium are two examples where a global 
community innovating together has driven strong 
results. The metaphor of linear momentum applies 
well here, being the product of mass by velocity, so 
the ecosystem with the greatest number of partici-
pants who are co-innovating the fastest will likely 
ultimately be the most successful. Implicit within is 
the recognition of the power of the crowd and the 

growth of both crowdsourcing and crowdfunding 
as a leading indicator for the future importance of 
mass collaboration.

Given the array of opportunities that is available, 
how can these opportunities be most efficiently and 
effectively harnessed? Innovation itself is a risky 
business with high failure rates; however, the ap-
plication of innovation design patterns can substan-
tially improve the productivity of collective innov-
ation efforts. The EU Open Innovation Strategy and 
Policy group has been studying, practicing and pub-
lishing an annual open innovation summary for over 
five years and is attempting to codify this new mode 
of innovation into a new emergent pattern language, 
i.e. a series of design patterns. Design patterns are 
nuggets of knowledge and help us remember in-
sights about design and can be used in combin ation 
to help in novate solutions. The goal of this effort is 
for open innovation to become a discipline practised 
by many rather than an art mastered by few.

This new era of co-innovation requires a culture 
shift with a requirement to move somewhat away 
from Adam Smith’s ‘invisible hand’ where the self-
interest  of  actors  in  an  economy  leads  to  some 
common benefits and more to a ‘sharing economy’ 
perspective based on a principle of shared value 
where actors proactively collaborate and innovate 
based on a common purpose. Having a shared pur-
pose is the foundational pattern of the new mode 
of innovation whereby shared vision and shared 
value underpinned by shared values is at the core 
of successful large-scale innovation. Where efforts 
are  aligned  using  a  compelling  shared  vision, 
people’s efforts and intellect are harnessed through 
commitment rather than compliance, resulting in 
strong synergies. Synergy is simply the cooperation 
or interaction of a number of organisations that 

OPEN INNOVATION YEARBOOK 201619

results in an effect or impact greater than the sum 
of the individual efforts, and this is a core goal of 
the OI2 approach.

The  following  table  shares  10  of  the  elemental 
design patterns that are distilled from our observa-
tions, research and practice in open innovation.

Table 1: 10 elemental design patterns in open innovation

Number Pattern

Characteristics

1

2

3

4

5

6

7

8

9

Purpose

Shared Vision, Value and Values

Partnering/Participative Innovation

Platform

Community, ecosystem-centric collaboration based on longer term 
win-win relationship based on shared risk and reward. User-led Inno-
vation, All innovating together to achieve synergies

Foundation for co-innovation, enable network effects, both technol-
ogy platforms (e.g. Cloud, IOT etc) and Business platforms (e.g. Apps 
economy etc) 

Innovation Possibilities and Discov-
ery Driven Planning – 10 types of 
Innovation

10 core types of innovation from business model innovation to prod-
uct, process, user experience innovation etc. Planning when there is 
much uncertainty, Adapting plan in real-time to new learnings

Proactively Design for Adoption

Design for adoption, User/Citizen led Innovation, models for imitation, 
(Utility, ease of Use, User Experience, Ubiquity)

Prototyping

Early sample or model, rapid iteration and experimentation

Pilots/Proof of Concepts

Experimenting in the wild with test deployments in living labs, evalua-
tions scale, parallel, non-linear innovation

Productization

Converting prototypes into viable commercial product/services, scaling 
and providing infrastructure to enable robust global operation

Product Service Systems/Servitisation

Extending products to services for sustainability and profitability, 
Designing solutions which are better, easier to use and more resource 
efficient that prior solutions, towards the circular economy

Having repeatable processes for innovation rather than ad-hoc, view-
ing innovation as a capability, delivering innovation results which are 
more predictable, probable and profitable

10

Processes

These  are  evolving  elemental  design  patterns 
which we believe will prove to be useful in helping 
ensuring the effectiveness and efficiency of col-
lective innovation efforts using the OI2 mode. They 
encompass many of the key characteristics of OI2, 
which we have described in previous OI2 yearbooks 
and papers, and will evolve and can be defined with 
more precision in the future. We would like to pre-
sent these as early design patterns of an emergent 
pattern language for OI2. A pattern language is 
a method of describing good design practices within 
a particular field of expertise and is often presented 
as a network of patterns that call upon one another 
to add synergistic value.

Designing for adoption
Innovation can be defined as the creation and adop-
tion of something new for the organisation or indi-
vidual that adopts it. Solutions that are designed to 
provide utility and to be easy to use while provid-
ing a great user experience are much more likely to 
be adopted, e.g. the Apple iPod. Many companies 
including Intel had MP3 players in the market well 
before Apple but were not successful.

By using a platform which allows easy co-innov-
ation and is subject to a network effect, one can sig-
nificantly increase the rate of adoption and hence 
the rate of value creation for everyone, with the 
Apple iPhone and App Store being examples of this.

Designing for sustainability
Developing  a  product  service  system  is  a core 
OI2 pattern to support sustainability. Product ser-
vice systems are a new innovation pattern which 
looks to move organisations from delivering prod-
ucts to delivering products/services and have more 
sustainable  consumption  and  supply.  The  IoT  is 
a fundamental enabler of this pattern which is also 
sometimes called servitisation. Rolls-Royce’s ‘Power 
by the hour’, whereby the company sells hours of 
flight  time  rather  than  jet  engines,  enabled  by 
advanced telematics, is the most commonly refer-
enced example of this pattern.

Some auto companies are looking to see how to 
change their business models. Daimler’s ‘car2go’ 
car service is an example of when the motivation of 
the business changes from maximising sales and 
thereby the consumption of physical resources to 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT20

maximising the utilisation and the longevity of the 
assets, thereby also minimising the consumption 
of non-renewable resources. In the case of car2go 
the vehicles are also often electric vehicles. Broader 
adoption of this model requires buy-in from con-
sumers that a car is no longer something that we 
need to own but that we could instead buy mobility 
as a service.

High-frequency, high-precision control 
systems for societal-level systems
Our ever-increasing connectivity, the ever-increas-
ing power of compute and the emergence of the IoT, 
with everything from cars to electrical substations 
to washing machines, is creating the opportunity to 
introduce high-frequency and high-precision closed 
control systems into societal systems which were 
previously  in  Open  Loop.  For  example,  the  elec-
trical grid has been designed as a one-way linear 
system  where  energy  is  generated  in  bulk  cap-
acity and then distributed (quite inefficiently) through 
high-voltage, medium-voltage and low-voltage dis-
tribution systems. With the increasing availability 
of local renewable energy (wind, solar, etc.), smart 
home systems and smart heat-storage systems, 
the opportunity exists to redesign the grid creating 
value for all participants, lowering costs and mak-
ing the overall solution more sustainable. One Hori-
zon 2020 project with a set of stakeholders from 
across  the  energy  value  chain,  from  generators 
to consumers, called ‘real value’ will research and 
demonstrate this across 1 250 homes in Germany, 
Ireland and Latvia. This model is an example of the 
emerging concept of collaborative consumption.

At the core of these kinds of innovations are the 
twin ideas of systems of systems and closed-loop 
control through enabling functions of acquisition, 
analytics and actuation. Data are acquired from 
a thing or system, and then analytics are performed 
to provide decision support which can then drive 
actuation to change parameters to effect service 
improvements  or  efficiencies.  The  integration  of 
these three capabilities enables the creation and 
operation  of  high-frequency  and  high-precision 
management control circuits. An example of such 
a system of systems would be a dynamic conges-
tion-charging system in a city which dynamically 
updates congestion charging based on parameters 
such as localised air pollution and weather and traf-
fic measurements to help optimise real-time traffic 
flows and improve commute times while minimis-
ing  the  environmental  impact.  The  operation  of 
such a system will also create a lot of big data, and 
the use of machine learning and offline analytics 

can  create  a second-order  feedback  loop  which 
can drive further system improvements based on 
insights garnered.

Conclusion
According to Steven Carter, author of ‘Where good 
ideas  come  from?’,  the  great  driver  of  scientific 
and technological innovation has been the historic 
increase in connectivity. Indeed, we are witnessing 
what Kurzweil called the law of accelerating returns 
with each new innovation building on prior innov-
ations and also often becoming infrastructure for 
future innovations. The OI2 innovation paradigm 
is based on extensive networking and co-creative 
collaboration between all actors in society, span-
ning organisational boundaries well beyond normal 
licensing and collaboration schemes.

Looking forward, we need to collectively adopt the 
mindset of shared vision and share value, and build 
innovation strategies and ecosystems to tackle the 
major  societal  problems.  For  example,  we  could 
agree to strive to create and build the equivalent of 
a Moore’s law and an ecosystem to deliver health-
care transformation — systematically and continu-
ously finding technology interventions which will 
improve the quality of life and the quality of care 
which, when cumulatively added, help create longer 
and healthier lives — a key role of the citizen would 
be taking more individual responsibility for their 
health. In parallel, there will be difficult challenges 
to solve in areas such as security, standards, trust 
and privacy as more and more systems are open 
and interconnected. However, this should not stop 
us making progress.

Ultimately it is not just about open innovation, but 
openness to innovation. Peter Drucker wrote that 
culture eats strategy for breakfast every time, high-
lighting the importance of culture to the success of 
any strategy. Fostering a culture which is open to 
innovation and risk-taking is important. Increasingly 
it seems there is a growing appetite for citizens to 
be involved in larger innovation efforts, as exem-
plified by more citizen science initiatives. In a Dub-
lin City Council survey of visitors to a future cities 
exhibition in Dublin in 2013, over 90 % of respond-
ents felt that Dublin should be used as a venue for 
testing experimental solutions and would be will-
ing to participate in the experiments themselves. 
The United Kingdom government’s whitepaper on 
community engagement ‘Communities in control: 
real people, real power’ also indicates that there is 
a desire from the top for more community and per-
sonal engagement.

OPEN INNOVATION YEARBOOK 201621

Denis and Donella Meadows wrote in 1972 that

‘Man possesses, for a small moment in time, the 
most powerful combination of knowledge, tools 
and resources the world has ever known. He has 
all that is physically necessary to create a totally 
new form of human society — one that would be 
built to last for generations. The missing ingredi-
ents are a realistic long-term goal that can guide 
mankind to the equilibrium society and the human 
will to achieve that goal’.

Strange that this statement seems even truer today 
and yet the progress made has been disappoint-
ing. We have the technology and now we have an 
emerging innovation methodology. We have to take 
the opportunity of a lifetime, in the lifetime of this 
opportunity. The technology is certainly ready — are 
we?

References
Alexander, T. et al., A pattern language, towns, buildings, 
construction, Oxford University Press, 1977.

Andersson, T., Curley, M. and Formica, P., Knowledge-
driven entrepreneurship — The key to social and 
economic transformation, Springer, 2010.

Baldwin, E. and Curley, M., Managing IT innovation for 
business value, Intel Press, 2007.

Johnson, S., Where good ideas come from — The natural 
history of innovation, Riverhead Books, 2011.

Chesbrough, H., Open innovation — The new imperative 
for creating and profiting from technology, Harvard 
Business School Press, 2003.

Curley, M. and Salmelin, B., Open Innovation 2.0: a new 
paradigm, EU Open Innovation Strategy and Policy 
Group, 2013.

Gawer, A., Platforms, markets and innovation, Edward 
Elgar, 2011.

Kiely, K. and Pham, H., Brixton listening lab: 
moving communities forward, 2014 — http://www.
adjacentgovernment.co.uk/lg-edition-001/brixton-
listening-lab-moving-communities-forward/3311/

Linton, P. et al., The digital world in 2025 — Indicators 
for European action, European Internet Foundation, 
2009.

Meadows, D. et al., The limits to growth, Universe Books, 
1972.

Nolan, P., ‘Transforming the usage of ICT’, Open 
Innovation 2.0: Sustainable Economy and Society 
Conference, 2013.

Pham, H. et al., Designed to evolve with cities: urban 
IoT for sensing to sense-making, Intel Collaborative 
Research Institute for Sustainable Cities, 2015.

Van Landegem, T., Open Innovation 2.0 — An example 
in action: GreenTouch, 2014 — http://www.greentouch.
org/uploads/documents/Open_Innovation_2_0_An_
Example_in_Action_GREENTOUCH_Thierry_Van_
Landegem_October_2014.pdf

Stahel, W., The performance economy, Palgrave-
MacMillan, London, 2010.

Contact

Martin Curley
Vice-president and director
Intel Labs Europe, Intel Corporation
Chair
Open Innovation Strategy and Policy Group
martin.g.curley@intel.com

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT22

Challenges of open innovation

Abstract

Throughout its short history, open innovation has created enthusiasm, setbacks and certainly many valu-
able experiences from numerous reference cases around Europe and beyond. The opportu nities and limi-
tations of the concept are well known, and the attitudes toward openness are becoming increasingly prag-
matic and realistic after the initial hype and excitement. However, we argue that despite best intentions, 
open innovation remains mostly technology driven and emphasise research, development and innovation 
(RDI) around individual technologies and their functionalities. The open innovation is still ‘half-a-way’ from 
being open in terms of understanding human and social behaviour. With human and societal challenges in 
mind, the chapter suggests that with the aid of advanced digital technologies we can elevate the level of 
open innovation projects to thoroughly resonate with the needs and the consumption patterns of the citi-
zens and societies, and thus enable a significant impact on societal transformation and industrial renewal.

Introduction

Open innovation concepts and methodologies have evolved significantly in the recent decade. This can be 
accounted for in significant investments in open innovation research and policies as well as new enabling 
technologies and tools. Open innovation is broadly accepted as a major driver for improved customer 
value and choice, adaptation of new technologies and processes and a means to democratise decision-
making and societies. Numerous new, sophisticated innovation models, concepts and communities of 
research and practice have sprung from the original concept of open innovation and continue to shape our 
conceptualisation of relationships between companies, the public sector, citizens and other institutions.

We argue for ‘the second wave’ of open innovation that is facilitated by ongoing digitalisation, cloud 
technologies and consequent new capabilities. They provide significant opportunities for stronger demand 
and market-driven approaches; we may create, in collaboration with people, citizens, users and customers, 
new market dynamism and experiences that can be ‘individualised’ and socially patterned. Consequently, 
the technologies — especially their design rules for integration — are created downstream from market 
knowledge, not only the other way around.

That is why we propose this open innovation concept of being: (i) relational (human, social, institutional 
and firm-to-firm); (ii) around ecosystems of industries, cities and regions or institutional, developer and 
social networks; and (iii) challenge driven aiming at solving major economic and social challenges of our 
time. One of the challenges is the speed of development; technologies, markets and industries change 
their relations, offerings, structure and processes very dynamically. Open innovation should be sensitive 
to the time dimension of the initiatives, when to launch the strategic RDI for systemic transformation, 
how to manage the RDI process to ‘fit the cause of events’, and how to implement the outcomes in 
a timely manner. The issue is to facilitate the renewal of markets, industries and societies in a way that 
it improves even the life of human beings and the development of all-inclusive, participative, open and 
reflective societies.

The paper also contributes to the existing know ledge base of service innovation processes, draws atten-
tion to the time dimension and relationships between institutions, individuals and open innovation com-
munities, and supports the design of sustainable next-generation open innovation ecosystems.

Evolution of open innovation in Europe
In the late 1990s, the phenomenon of open innov-
ation emerged simultaneously with the spreading 
of internet and mobile technologies. The new digi-
tal technologies created need and inspiring oppor-
tunities for new value creation — after decades of 
closed science and corporate research and devel-
opment (R & D) — and for opening the innovation 
and development processes to the public. In the 
beginning,  the  opening  referred  to  collaboration 
with business-to-business or lead customers in the 
development of new products, technologies and 
services. It also meant gathering direct feedback 

from markets, customers and users of the usability 
and experience of products and services, especially 
in the early phases of innovation and market adap-
tation. So what is the relation between the diffusion 
of internet technologies and open innovation today? 
Co-creation and innovation takes place on technol-
ogy  platforms  that  bring  together  technologies, 
developer communities and customers. Develop-
ing such platforms requires thorough understand-
ing of industrial, organisational, social, institutional 
and  human  behaviour  that  relate  to  processing 
knowledge and information. These platforms have 
been understood not only as technologies but as 

OPEN INNOVATION YEARBOOK 201623

facilitators of human and social interactions, know-
ledge creation and innovation.

Firstly, the opening of R & D took place between 
companies; it became a process of co-creation of 
products  and  technologies  [1,  2],  but  soon  after 
we saw the opening of broader RDI processes with 
lead-user communities and consumers [3]. In the 
early 2000s, open innovation became included in 
policy processes. In addition to traditional tech-
nology-related innovation policies, cities, regions, 
nations  and  even  the  EU  promoted  wider  social 
and economic transformation through innovation 
policies that addressed society- and industry-level 
renewal through engagement of firms, public agen-
cies and citizens.

These innovation policies emphasised demand and 
user-driven, open and participatory RDI with real-
life experimentation and piloting with citizens. In 
addition, globalisation and European single market 
development created a need to conduct wide-scale 
RDI for scalable solutions over many markets and 
industries, with unified standards and regulations 
for volumes of scale; this gave a strong stimulus 
for launching international networks such as In-
novative Regions, Smart Cities and the European 
Network of Living Labs (ENoLL). The idea was to 
develop, ‘from the very beginning and by their very 
DNA’,  markets,  industries  and  societies  that  are 
locally anchored but both international and glob-
ally connected. Currently, the open innovation has 
matured into a mainstream innovation process for 
both corporate and public sectors. Leading com-
panies actively engage their customers and stake-
holders in the co-creation process, while the public 
sector has adopted open consultations as part of 
regular policy cycles.

Digital transformation and 
open innovation
The  ongoing  digital  transformation  offers  great 
opportunities to renew dynamism in European soci-
eties and economies. Digitalisation has properties 
of being instrumental in changing the underlying 
foundations and structures of industries, economic 
activities and societies. It offers Europe an oppor-
tunity to develop a new globally competitive indus-
trial dominant design [4] that is human centric, sys-
temic and even socioeconomic by nature.

Digitalisation is not only related to individual prod-
ucts,  devices  or  technologies;  it  is  about  shared 
systems or integrated infrastructures, i.e. how prod-
ucts, technologies, economic and social activities, 
organisations and institutions collaborate and relate 
to  each  other.  Digitalisation  is  about  underlying, 

enabling technologies, like cloud computing, that 
foster industrial, social and economic transform-
ation through new virtual platforms that bring about 
new digital value creation processes as well. This 
strengthens  generative  capacities  between  and 
within organisations, human and social networks for 
communication and collaboration in knowledge and 
information production and transfer.

We argue that the digitalisation brings about a new 
open innovation model that lets us separate and 
integrate in a new way (in cloud) virtual and phys-
ical interaction layers, where the interactions and 
co-creation  follow  different  logic  and  rationale. 
That  is  why  we  propose  re-conceptualising  the 
drivers,  actors,  critical  incidents  and  impacts  of 
physical and virtual ecosystems and open innova-
tion interventions, and noting the special charac-
teristics of virtual ecosystems. So the digitalisation 
creates two inspiring, powerful, parallel and inter-
related ‘dynamic platforms’ for open innovation: (a) 
a technology-enabled virtual platform where firms, 
cities, regions, public agencies and other ‘platform 
providers’ may co-create dynamic new ecosystems 
for value creation; and (b) a service and content 
creation and delivery-driven platforms of citizens 
as co-creators or ‘users’ who in addition to firms, 
cities, regions and other players can participate in 
value creation — also for themselves.

Furthermore,  in  today’s  economies  and  global 
marketplace, megatrends and transitions occur in 
months rather than years. New, ever-more complex 
and  connected  product  introductions  are  intro-
duced at an accelerated rate, leading to a highly 
volatile technology landscape. An example of this 
is  the  estimate  that  Facebook  today  would  cost 
only about EUR 500 000 to make. Thus the value 
is  not  with  the  technology  of  the  company,  but 
with the users and business models [5]. Value net-
works are ambiguous, with low entry barriers and 
industrial symbiosis, which leads to a continuous 
re-configuration of industry segments and chang-
ing  market  dynamics  and  revenue  models.  The 
recommendation is to adopt a ‘holonomic’ way of 
thinking, a dynamic and authentic understanding of 
the relationships within a business system, and an 
appreciation of the whole.

The  following  table  details  the  main  drivers  for 
the new open innovation era. The drivers are inter-
twined,  e.g.  with  consumption  patterns  changed 
radically since the 1990s with the adaptation of 
mobile internet technologies, and markets trans-
formed following the new forms of consumerism 
[6]. This, in turn, has steered technological develop-
ment to better respond to customer needs.

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT24

Table 1: Drivers for the new open innovation paradigm

Drivers

Concepts

Elements

Societal Drivers

Servitisation

Share economy, as a service consumption

Sustainability

Globalisation

Circular Economy, resource efficient, resilient economy

Mobility, competition, economic interdependency

Technical

Digitalisation

Cloud, IoT, mobility, virtualisation

Price of technologies

Affordable, ubiqenous solutions

Mobility

Mobile access, new consumption patterns

Market

Ecosystem-based services

Collaborative development, business models

Platform-based technologies

Dominant standards, interoperability

Shortening life cycles

Intensified competition, continuous improvements

Cultural

Social media

New connectivity, perception of privacy, opinion shapers

Customer driven development

Co-creation with customers

Political

Inclusive regulatory process

Citizen empowerment, participatory consultations

Demand side instruments

Drive adaptation, sustainability, innovation

Strong interventions

Incentives for renewal, shared vision

We have learned that RDI of ICT-based infrastruc-
tures [7] or platforms often emphasise design rules 
that integrate industrial activities or technologies 
and operate on different layers and specifications 
of platforms. If the underlying virtual platforms are 
‘the shared capacity and capabilities’ of companies, 
other organisations, social networks and people to 
collaborate, we argue that especially those layers 
of platforms that are close to services and busi-
ness  models  may  benefit  from  specifications  or 
design rules derived from market, user, human and 
social behaviour. There are many cases where new 

digital infrastructures or platforms benefit from 
deep ‘internal’ structural and processual integra-
tion that reflects human, user and market behav-
iour. Today, with social media and other means of 
public participation and crowdsourcing, this would 
be a natural path to follow.

The parallel virtual and physical open innovation 
processes have much of the same characteristics, 
but the critical success factors somewhat vary. The 
following table highlights the differences between 
the processes.

Table 2: Actors, relationships and activities in physical and virtual co-creation arenas

Ecosystem Characteristics

Physical

Virtual

Venue

Living Lab , real life environment

Technology Platforms

Methodologies

Actors

Relationships

Activities

Applications

Outcomes

Focus Groups, Ideation Workshops, Use of Props, 
User Observations, Makers Spaces, Fab labs,..

APIs, Apps, GUIs on technology 
platforms, on cloud, social media

Orchestrator, developer, user, technology and service 
provider, public sector, property owner,  limited 
number of actors

Platform owner, developers, users, 
broad communities

Medium to long term, clear roadmaps and 
sustainability plans

Ad Hoc

Experimentation

Configuration

Smart City, business networking

IoT, open source development, cloud

Improved physical service, product, policy 
recommendations, business models

New services, enabling technologies

Critical Success Factors

Interactions, integration to legacy systems, shared 
vision, policy support, user acceptance

Interoperability, standards

OPEN INNOVATION YEARBOOK 201625

The presented table highlights the added complex-
ity of open innovation in a physical context, where 
the number of actors and relationships is higher 
and the investment is heavy. In the emerging new 
open innovation paradigms, the virtual and phys-
ical interaction layers can benefit from two-way 
dialogue and closed-loop learning. Physical prod-
ucts and assets can be augmented with virtuali-
sation and life cycles prolonged with supporting 
services  and  new  business.  Virtual  development 
processes, in turn, can apply learnings from the 
user-driven service development, and thus reduce 
the gap of virtual and physical service experiences. 
The needs and expectations of the users or con-
tributor are still the same regardless of the point 
of delivery.

If we cultivate the thinking even further, we may 
distinguish virtual layers that are mainly created 
through designs’ rules related to technology and 
virtual layers that are created on human and social 
behaviour. What an opportunity to have an inte-
grated ‘sphere of RDI’ where these two collabora-
tive dynamics for value creation merge!

Value creation through 
collaborative platforms
We have argued that digital transformation opens 
new  avenues  also  for  perceiving  the  value  cre-
ation; the value is created through parallel interac-
tive ‘platforms’ and their integrated systemic-level 
solutions, as well as through accumulated value in 
relationships and their constitution, in addition to 
functionalities of technologies and services. Oppor-
tunities for value creation are offered by dynamic 
constellations  for  collaboration  both  at  physical 
(technology-provided) and consequent virtual lay-
ers as well as at socially and institutionally consti-
tuted ‘layers for open innovation’; consequently, the 
value is increasingly created in virtual networks, 
where  physical  objects  connect  seamlessly  and 
can  be  re-configured  to  serve  customer-specific 
contexts and needs. These technology translation 
processes — guided partly by human and social 
behaviour — in the virtual world follow different 
laws from the ecosystems in a physical context, 
and thus should be studied with different assump-
tions, heuristics and methodologies.

We argue that the tipping point of technology dom-
inance and virtualisation has been reached, and 
the new communities of users prefer customised 
experiences and relationships. These trends create 
friction in service design and business models, and 
again open up opportunities for open and shared 
service  models.  The  categorisation  and  roles  of 
users and developers need to be defined in more 
detail  and  distinct  models  developed  for  each 
group depending on their expectations, maturity 

and willingness to engage in open innovation. Fur-
thermore, with increased valuation of support and 
customer  service,  we  witness  also  the  return  of 
human-to-human services, instead of automated or 
self-services. As today the consumption is increas-
ingly based on economies of functionality in rent, 
rather than ownership, we need to reconsider our 
perception of value creation based on contracts 
(like the much-published Airbnb concept). Customer 
needs may be fulfilled by ‘as a service’ rental or 
pay-per-use consumption models, which are more 
sustainable and scalable.

By and large the dynamic interaction between tech-
nology-driven platforms and human- and socially 
driven platforms of collective co-creation represent 
a new dynamism in value creation. This calls for 
rethinking the sources and sustainability, efficiency, 
productivity and also new discovery-driven meth-
odologies  for  managing  the  new  cyber-physical 
ecosystems [8].

Role of cities and regions
In Europe, the openness of RDI and the participation 
of cities, regions and citizens into the development 
of better societies and economies has stimulated 
shared visions of socioeconomic development for 
the well-being of human beings, that is by its very 
nature  knowledge  and  innovation  driven,  trans-
formative and participative [9]. The ideal is to cre-
ate human-centric reflective societies and econ-
omies that promote an all-inclusive engagement of 
private and public stakeholders as well as citizens, 
improve participative democracy and reflect these 
properties even in their very core activities such as 
research and innovation. These qualities would give 
Europe a unique profile on the global innovation 
map where the United States competes through 
corporate-driven RDI, science and technology and 
China has a mixed open/controlled model of cen-
tral  government-driven  science,  technology  and 
corporate RDI aiming at sustainable growth after 
a period of sustained growth [10]. Open innovation 
is in the heart of this process and therefore it is 
essential to understand the extended opportunities 
that advanced technologies have opened for the 
concept.

We  proposed  that  the  open  RDI  around  societal 
challenges starts with open, society-wide dialogue 
for shared challenge definition and vision creation. 
We have also proposed that the process continues 
with open experimentation of potential solutions. 
We deploy open, dialogical, participative, big data, 
design and large-scale experimentation and pilot-
ing methodologies. While applying this approach 
we also promote open economy and society devel-
opment  and  forms  of  participative  democracy. 
People and organisations learn from each other, 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT26

share views and visions of challenges ahead and 
strengthen  the  sphere  of  economic  and  social 
choice. People become subjects, not objects, of their 
lives. As Sen [11] argues:

experience and sustainability in a scale that ena-
bles residents to gain an extra hour of their own 
time  every  day.  The  development  is  challenge 
driven and open for all contributors.

‘What choices one can make in life is 
dependent on the society we live in’.

We may even turn the argument of Perez [12] that 
technological advances drive societal development 
the ‘other way around’. We may learn to bring about 
societal challenge-driven industries, technologies, 
firms and jobs.

We  argue  that  cities  and  regions  are  ‘best  pos-
itioned for RDI in this regard’ and could be the open 
ecosystems that solve societal challenges and cre-
ate new forms of value creation and scalability of 
social, economic and industrial activities. As inter-
nationally networked, they could also create new 
social  and  economic  dynamism,  well-being  and 
wealth and value creation — locally and globally. 
However, this may call for greater independence 
for cities to create their own international, public 
services, technology, industry and innovation pol-
icies. They also need organisational, institutional 
and funding arrangements of their own to fulfil the 
tasks related to solving societal challenges through 
participative and open innovation.

One  highly  visible  example  of  the  open  innov-
ation community is the international network of 
smart  cities,  and  consequent  emergence  of  the 
term human smart cities. The concept highlights 
challenge-driven innovation, where the initiatives 
should build on shared values and jointly created 
visions  for  the  cities.  Decisions  and  choices  for 
technologies and processes are driven by sustain-
ability, convenience, economic growth, stability and 
quality of life for all demographic groups. Focus is 
on lean innovations that can be scaled on different 
application areas and context with little effort. This 
transition is enabled by changed mindset, roles and 
enabling technologies [13].

The new Kalasatama (fish harbour) area of Helsinki 
is a representative example of a human smart city 
innovation platform. The Kalasatama neighbour-
hood  is  designed  as  an  experimental  innovation 
platform for co-creating smart urban infrastruc-
tures  and  services.  This  old  harbour  area  was 
transformed into a modern housing area through 
open  consultations  and  piloting  with  all  quad-
ruple helix stakeholders in an open living lab set-
up. By 2030 Kalasatama will serve as a home to 
20 000 residents and offer jobs for 8 000 people 
with advanced smart infrastructure and pioneer-
ing  concepts  for  open  data-based  services.  The 
vision for Kalasatama is to add to the convenience, 

Smart  Kalasatama  is  funded  by  the  European 
Regional Development Fund, the City of Helsinki 
and the Ministry of Employment and the Economy. 
The project is coordinated by Forum Virium Helsinki. 
Experiments include electric car-charging stations, 
a solar power plant, a pop-up library, maker spaces, 
smart  containers,  smart  home  concepts,  heat 
pumps for ICT server rooms and vacuum waste dis-
posals. Kalasatama is a longitudinal commitment 
to co-creation from quadruple stakeholders. With 
true  citizen-driven  development  goals,  applica-
tions of open data, open technology standards and 
sustainable solutions it represents the new open 
innovation concept at its best on both virtual and 
physical layers.

Conclusion
We have argued that the digitalisation opens new 
platforms for both technology-driven and socially 
driven open innovation. We have also argued that 
there are new opportunities for open innovation to 
balance and integrate these approaches and offer 
opportunities for new value creation, global com-
petitiveness and scalability, as well as all-inclusive 
development  towards  open  economic  and  social 
dynamism  that  promotes  participative  democ-
racy. We also discussed new platforms of virtual 
co-creation as ecosystems that would benefit from 
human-, social-, market-, user- and customer-driven 
approaches and specifications applied in physical 
co-creation initiatives as well. The increased migra-
tion of physical and virtual worlds also calls for new 
policy instruments for providing incentives for open 
processes  and  interfaces.  This  is  an  area  where 
the open innovation community can make a sig-
nificant contribution in the coming years in continu-
ing to shape our conceptualisation of relationships 
between companies, the public sector, citizens and 
other institutions, and build stability and quality of 
life for all demographic groups.

Europe has the opportunity to transform the foun-
dations  of  its  industrial  dynamics  towards  new 
dominant  designs  that  are  globally  competitive, 
human centric, systemic and even socioeconomic 
by nature. This is possible through digitalisation — 
perhaps for the first time in economic history. One 
may argue that until now the industries did emerge, 
evolve and change through introducing new inno-
vative products or technologies that did spread, 
scale up and diffuse over time — through a kind of 
natural, evolutionary and adaptive process. Today, 
we have the opportunity — through a wide-scale 
experimentation,  collaboration  and  ecosystem 

OPEN INNOVATION YEARBOOK 201627

approach — to make society-wide economic, indus-
trial or other system-level changes. Today, we can 
transform industries almost consciously! However, 
we do that by engaging our people and societies 
into knowledgeable and dynamic co-creation that 
has the potential to transform our economic and 
social dynamism as well.

This has a major impact on our industrial, technol-
ogy, urban and innovation policies, as well as on 
open RDI itself.

References
[1]  Chesbrough, H., Open innovation: the new imperative 
for creating and profiting from technology, Harvard 
Business School Press, Boston, Massachusetts, 2003.

[2]  Chesbrough, H., ‘Open innovation: a new paradigm 
for understanding industrial innovation’ in Chesbrough, 
H., Vanhaverbeke, W. and West, J., eds., Open innovation: 
researching a new paradigm, Oxford University Press, 
2006, pp. 1-12.

[3]  von Hippel, E., Democratising innovation, Creative 
Commons, 2005.

[4]  Kulkki, S., ‘A digital transformation’, Horizon 2020 
projects, 2015 — www.horizon2020projects.com

[5]  Pine, B.G. and Gilmore, J.H., The experience economy, 
Harvard Business Review Press, Boston, Massachusetts, 
2011.

[6]  Kulkki, S., ‘Getting competitive’, Pan European 
networks: science and technology, 2011 — www.
paneuropeannetworks.com

[7]  Kulkki, S., ‘Revisiting RDI design rules’, Pan European 
Networks: Science and Technology, 2015 — www.
paneuropeannetworks.com

(8)  McGrath, R. and MacMillan, I. C., Discovery-driven 
growth: a breakthrough process to reduce risk and seize 
opportunity, Harvard Business School Press, Boston, 
Massachusetts, 2009.

[9]  Hämäläinen, T., Towards a sustainable well-being 
society: building blocks for a new socioeconomic model, 
Sitra, 2013.

[10]  Kulkki, S., ‘Europe on global innovation map: 
human-centric RDI for solving major societal challenges 
of our time’, Public service review: European science and 
technology, 2011.

[11]  Sen, A., Foundations of social choice theory: 
an epilogue in Elster Jon and Hylland Aanund — 
Foundations of social choice theory, Cambridge 
University Press, 1986.

[12]  Perez, C., Technological revolutions and financial 
capital: the dynamics of bubbles and golden ages, 
Edward Elgar, 2002.

[13]  Faems, D., de Visser, M., Andries, P. and Van 
Looy, B., ‘Technology alliance portfolios and financial 
performance: value-enhancing and cost-increasing 
effects of open innovation’, Journal of Product Innovation 
Management, 2010, pp. 785-796.

Contact

Seija Kulkki
Professor, founder
Centre for Knowledge and 
Innovation Research
Aalto School of Business
Finland
seija.kulkki@aalto.fi

Petra Turkama
Director
Centre for Knowledge and 
Innovation Research
Aalto School of Business
Finland
petra.turkama@aalto.fi

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT28

Open Innovation 2.0 calls for magnetic organisations

Abstract

A globalised economy, digitisation and disruptive competition from unexpected actors — private and 
public organisations — result in high pressure to change. There are plenty of dramatic examples of 
once-proud brands that have disappeared and many calls for action for those that are still around. 
But changing an organisation is a challenging task in practice. External developments are moving fast 
while internal inertia of people and processes seems to slow down any capacity to adapt.

Open Innovation 2.0 (OI2) is a paradigm strongly rooted in our 21st century society and will affect 
all of our 20th century organisations, both private and public. It is essential that these organ isations 
appreciate the disruptive capacity of OI2 and understand the elementary conditions that are needed 
to adapt, to reap the benefits of OI2 and to be a leading brand in the 21st century.

Introduction

This contribution focuses on the elementary conditions and drivers for large and medium-sized 
organisations to be effective in OI2. The authors introduce the notion of magnetic organisations and 
argue that the right mixture of internal initiatives, entrepreneurship and a compelling attractive goal 
is needed to move ahead. Physics is used as a source of inspiration for describing two conditions that 
can be analysed and used for organisational design. The theory of organisation entropy is used to 
develop the freedom to act and connect externally, while the principles of magnetism are employed to 
focus on goal orientation and convergence. Practical implementations of these principles are given to 
illustrate how a balance in entropy and attractiveness helps these magnetic organisations to flourish 
and contribute in an OI2 society.

Figure 1: Magnetic organisations as a metaphoric formula

A renewed interest in corporate innovation
What innovation is, how it functions and how it can 
be stimulated has been fundamental to organisa-
tion theory, business schools and policymaking.

Nowadays, a wealth of ideas and initiatives focus 
on startups and greenfield innovation; how busi-
nesses can be set up and supported and how they 
can grow. This is not, however, the subject of this 
study. We focus on the stage at which a business is 
mature, when, from a start-up, an organisation has 
been formed with people, processes, ways of work-
ing and culture. A corporation can thus be a com-
mercial corporation or a public one.

This may not be the most attractive topic in the 
public space nowadays. For many years (from the 
early 1990s onwards) the leading theme in renew-
ing  our  society  and  keeping  our  economy  com-
petitive has been focused on renewing our large 
industries, stimulating their research and devel-
opment (R & D) capacity and aligning our univer-
sities to that end. A typical career for graduates 
has primarily been to seek employment in these 

large corporations and from there to contribute to 
society. Starting a new business did not rank very 
highly.

This trend changed with the rupture of the internet 
bubble in the early part of the 21st century and 
following the financial and economic crisis. Gain-
ing employment in large corporates was difficult to 
achieve and corporations did not prove to be the 
society renewals that were hoped for. As a result 
of this, starting a new business became the credo. 
And with good reason: Microsoft, Apple and later 
Facebook showed that entrepreneurial spirit and 
a  garage  were  all  that  was  needed.  We  are  in 
a phase now where focus on entrepreneurship and 
a start-up mentality are peaking.

But small companies get bigger: just as we have 
seen  with  Microsoft,  Apple  and  Facebook.  They 
become the new corporations. So the question of 
how to innovate within our corporate is back. For 
instance Google, another new corporation, intro-
duced an often quoted 1 day a week free research 
as innovation methodology, whereas Apple started 

OPEN INNOVATION YEARBOOK 201629

a religion to keep its market share. The new cor-
porations also operate in an open innovation soci-
ety: they keep a close look on innovations outside 
their corporate wall and absorb new acquisitions 
within their own services and brand.

In a way, the new corporations are all representing 
an IT-intensive sector and since our whole society 
is  becoming  a digital  one,  the  new  corporations 
may pioneer the guiding principles that underpin 
the innovation processes. Looking for sustainable 
innovation models in corporate settings is becoming 
a trending topic once again.

This study focuses on the following two types of 
corporate innovation.

1.  Industrial corporations with an R & D culture. 
This is the world of Unilever, pharmaceutical, 
car and aerospace industry. The leading trend 
here is to move from closed innovation to open 
innovation [1]. Make the shift from R & D in iso-
lation and secrecy to embracing the customer 
as co-developer. Models to describe this open 
innovation  shift  are  provided  by  Curley  and 
Salmelin [2].

2.  Professional services organisations with strong 
individual-led  innovation  culture.  This  is  the 
world of hospitals, financial services firms, en-
gineering, media, education and IT services. The 
individual professional leads innovation and its 
practices. Although innovative on an individual 
scale, the organisation as a whole is often con-
servative and immobile. The consultancy sector 
in particular is suffering from a lack of a sus-
tainable innovation model.

This study focuses primarily on the latter, the pro-
fessional service organisations. In earlier papers [3], 
the characteristics of the IT-based services firms 
have been identified and the need for a sustainable 
innovation model described.

The innovation pyramid is upside 
down; a new role for corporations
Throughout recent decades the role of capital and 
infrastructure in driving innovation has decreased 
to make room for the role of ‘the ideas’ and the 
‘knowledge to realise it’ as leading differentiators.

Ideas and knowledge are linked to people, not to 
organisations.  People  that  have  ideas  and  know 
how to realise them have a competitive advantage. 
Organisations no longer make the difference. In the 
growing service industry of digital design agencies, 
for instance, the brands that are ‘hot’ one day will 
typically only remain as such for a limited time; per-
haps for as little as one or two years. A hot new 
brand with a unique proposition will replace them 

soon enough. What is interesting to see, however, 
is  that  the  people  behind  these  brands,  the  key 
designers and producers, are often the same. They 
mix in different circles and settings, but are united 
by their shared knowledge and ideas and not by the 
brands they work for at any given time.

Does this then mean that there is no role for the 
corporate organisations in realising consistent in-
novations anymore? Yes, there is. Corporations must 
now take on a new role. After the reversal of the 
innovation pyramid [4], the role of the organisation 
has changed from initiator and producer of innov-
ations to being the up-scaling partner for services 
and products that individual people have conceived. 
It is the powerhouse that allows small innovations 
to be amplified and made available to many to cre-
ate a wide-scale impact.

From  the  perspective  of  the  organisation,  the 
creators of these innovations consist of their own 
employees, those working at partner organisations, 
university associates from a collaborative project 
and  notably  the  same  people  that  used  to  con-
sume the end products. It is the critical mass the 
crowd creates that leads corporations to react and 
renew. The organisation is the breeding ground for 
this crowdsourcing and, importantly, it provides the 
scale to make investments in time and infrastruc-
ture to realise ideas.

The new corporation plays a further role here too. 
It can provide an inspiring environment for these 
people  to  create  and  share  knowledge.  This  en-
vironment can provide meaning to ideas and can 
give a common drive to the people associated (not 
necessarily as employees, but the crowds) with the 
organisation. This unleashes a drive to apply their 
creativity and energy to serve a cause that they 
would not be able to serve on their own. Creating 
better medical services for all, reinventing educa-
tion for a new generation, growing socioeconomic 
wealth  or  making  better  product  services  in  our 
daily life are good examples.

The  innovation  sourced  by  a  crowd  associated 
with an organisation is an instance of OI2. And the 
question  is:  what  does  corporate  crowd-sourced 
innovation look like? How can it be described and 
modelled?

Characteristics of a future-ready 
Open Innovation 2.0 organisation
Given  that  innovation  in  an  organisation  that 
embraces OI2 and displays many characteristics of 
crowdsourcing, it is challenging to look for models 
that describe these crowdsourcing mechanisms — 
a model that identifies the dominant mechanisms 
and  describes  their  relationships.  Other  issues 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT30

relate to how these mechanisms interact, which 
ones add to a more productive innovation outcome 
and which ones work the other way round.

Innovation modelling has a long tradition and, as 
with many organisation theories, it is the readiness 
for  practical  application  that  contributes  to  the 
body of knowledge and adoption by practitioners.

First, let us focus on the state of the art and dis-
tinguish  four  types  of  approaches  in  innovation 
practice:

1. 
innovation initiatives as separate programmes;
2.  the set-up of a new organisation entity focused 

• 

• 

• 

entrepreneurship (strive to be a pioneer, be will-
ing to take high risks, challenge your current 
business model and be disruptive yourself);
right leadership (be good at encouraging and 
nurturing  innovation  and  remove  the  ele-
ments that kill innovative processes within your 
organisation);
customer centricity (put the customer at the 
heart of everything you do).

All of these elements are worthwhile and certainly 
true in becoming ready for the future. But we do 
think there is more to a future-proof organisation 
than the following commonly found items.

on innovation;

• 

3.  a  top-down  or  bottom-up  reorganisation  to 

innovate the organisation;

4.  acquisition  of  startups  or  innovative  niche 

players.

These approaches are found in common practice in 
many corporations and, interestingly, in their cur-
rent form provide a disturbing picture. Recent sur-
veys [5] confirm this. The majority of organisations 
are not capable of becoming future-proof. Even if 
they are capable to a certain degree in doing so, 
they fail to deliver results fast enough [6].

In short, all of the mentioned approaches are too 
one sided. They have the following few things in 
common.

• 

• 

• 

They  do  not  look  into  their  organisation  and 
identify where the right energy is present and 
how best to tap into it.
They seem to have a specific innovation in scope, 
instead of growing the organisation. For instance 
the digital savviness of experts and managers 
on various levels is crucial for future success.
They do not consider the customer to be com-
pletely central. At most, a business case per-
spective is taken, but the results for all innov-
ations cannot be predicted upfront.

There are several characteristics mentioned in con-
temporary management literature [7] that apply to 
future-ready organisations. They stress:

• 

• 

flexibility  (learn  quickly  from  mistakes  and 
be able to adjust and adapt along the way to 
changing circumstances or different customer 
needs);
create openness (co-create with different mar-
ket players like customers, partners, suppliers 
or other complementary organisations that add 
value to the offered products and services; so 
decrease your organisation boundaries and let 
other insights and ideas in);

The current wave of the agile way of working 
proves to be successful in solving long-lasting 
change initiatives or IT programmes. One ele-
ment in particular which is very important is 
to be more agile, that is to form multidiscip-
linary teams that combine the expertise and 
competences of various people to work closely 
together and come up with solutions that other-
wise — in traditional functional teams — would 
not have come up.

• 

•  Organisations  need  to  become  digital  savvy 
on  various  levels  —  in  particular  the  senior 
management. They must be sufficiently savvy 
to truly understand the challenges and possi-
bilities that innovative, digital technology rep-
resents. And to act accordingly to shape the 
innovative organisation.
In every organisation change happens where 
the  energy  of  the  people  is  high  and  the 
momentum is right. Those are the conditions 
to realise change, but they often quickly fade 
because  of  an  organisation’s  structures  and 
old traditions. What companies need to do is 
focus on an energy-driven environment. They 
need to think outside organisational structures 
and  give  space  to  employees  to  be  creative 
and resourceful without dealing with too many 
organisation boundaries.

The magnetic organisation
All of these characteristics come together in the 
concept of the magnetic organisation. We describe 
this  new  organisation  model  with  two  dominant 
phenomena inspired by physics, namely ‘entropy’ 
and ‘magnetism’.

Innovation entropy
Entropy is a measure of disorder within a system. 
High  entropy  indicates  lots  of  disorder  in  a sys-
tem, as opposed to low entropy, which indicates 
rigid structures. The notion of ‘entropy’ stems from 
thermophysics where it is, among others, applied to 
explain the behaviour of heat flow between objects, 
stating that heat will flow from warm objects to 

OPEN INNOVATION YEARBOOK 201631

colder objects, increasing the total disorder of the 
system. In information theory, entropy is a measure 
of information. Albeit with an inverse relationship: 
the more entropy, the more disorder and thus less 
information. Many scholars have also applied the 
notion of entropy to describe phenomena in human 
organisations [8]. This is a challenging field and has 
led to various uses of the term.

In  this  paper  the  notion  ‘innovation  entropy’  is 
introduced. It is a measure for the inherent innov-
ation behaviour of people or groups of people. Low 
innovation entropy means that people are stuck to 
what their job description or task tells them to do 
and have little or no intrinsic drive to try something 
else. The organisation does what it did yesterday. 
No risks are taken nor improvements sought. A high 
degree of order is observed.

High  innovation  entropy  means  a lot  of  drive  to 
change individual or group behaviour and many ini-
tiatives to try something else. People act and cre-
ate, but in no particular direction. There is a high 
degree of disorder.

There is no prescription of the amount of innovation 
entropy that an organisation needs. Too little of it is 
no good, but too much is equally damaging.

The second thermophysics law states that entropy 
will at best stay what it is, or an increase can be 
translated to organisations as well. It then states 

that  people  or  groups  of  people  will  effectively 
always  tend  to  increase  disorder.  It  is  up  to  the 
organisation to accommodate this tendency. Put 
in a different way, people will act, either inside or 
outside the organisation, either with it or against it.

For an organisation to be effective in open innov-
ation, the innovation entropy needs to be managed. 
It needs to break down inhibitors that keep people 
in  their  cubicles  or  rooms  with  doors  closed.  An 
organisation must ensure a lively debate on what 
can  be  changed  and  stimulate  experimentation, 
whilst being able to manage a cooldown if experi-
mentation is uncontrolled. This happens when the 
amount of initiatives and autonomous behaviour 
is accelerating beyond control. Typically, a happy 
medium is reached when there is a spontaneous 
formation of teams that formulate project ideas 
and initiate experiments. These teams are formed 
of people across the internal and external bound-
aries of the organisation and accept responsibil-
ity for spending their own and the organisations 
resources. They are willing to explain their findings 
and accept that there may be an end to their team 
effort if there is no greater benefit for others out-
side their own group.

Managing the innovation entropy is a process of 
give and take. At times the organisation needs to 
free up energy and create more disorder, followed 
by periods of ‘cooling down’ when ideas and experi-
mental results are evaluated and pruned.

Figure 2: Open innovation requires open team interactions instead of walls and closed doors

What is needed next is a mechanism by which the 
innovation entropy of people or teams becomes 
directed instead of a random movement that may 
produce a lot of ‘heat’ but leaves the organisation 
as a whole stuck in the middle.

Magnetism to describe the attraction
Magnetism is a class of physical phenomena that is 
mediated by magnetic fields. A magnetic field cre-
ates a well-defined attractive force on objects that 
are susceptible to magnetism, like many metals. 
The  magnetic  field  can  be  created  and  main-
tained  by  an  electrical  current  through  a coiled 
wire or by a permanent magnet — so-called fer-
romagnetism. The force of the magnetic field can 

be very powerful, like in electric motors, magnetic 
resonance  imaging  scanners  or  household  per-
manent magnets. The force reduces quickly, typi-
cally in the order of the square distance or faster, 
and  is  effective  on  short  distances  up  to  centi-
metres for practical use in attracting and moving 
objects with a mass of several grams or more.

The effect can be felt on larger distances too, albeit 
on a subatomic scale, in moving electrons in an 
electromagnetic field (radio). On a terrestrial scale, 
it is our Earth’s magnetic field.

The magnetic field and its attractive force form 
a powerful  model  of  the  attractive  force  that  is 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT32

needed in an organisation to get people in motion 
and to direct this motion towards a common goal. 
This is illustrated with a metaphor.

Suppose the people in an organisation that move by 
themselves or are latent movers — the organisa-
tional units (OUs) — are represented by metal balls. 
Each ball can move on a flat surface freely. The sur-
face can be the bottom of a box, representing the 
organisation boundaries when we think of closed 
innovation within a corporation, or the surface can 
be a large table in case of OI2.

What are the effects of the attractive force and 
how does it translate to an organisation?

• 

• 

The attractive force results in a real change 
in the orientation of the individual OU. If they 
move already, their direction is diverted towards 
the magnet. If they were still inert, they may 
come into motion. In organisation terms this 
means that an attractive vision will ‘pull’ the 
OUs in a given direction.
The attractive force can be amplified to have 
greater reach by applying a stronger magnet. 
This means by making the already attractive 
vision more compelling and/or communicating 
the vision more powerfully, it will have a direct 
effect.

• 

• 

The attractive force can be induced in other OUs 
so that they too execute an attractive force on 
yet other OUs (this is because a magnet induces 
a magnetic field in the metal balls themselves. 
They  provide  an  attractive  force  on  others 
again). In an organisation this means that the 
vision  is  further  distributed  by  ambassadors 
who pull others in the same direction.
The attractive force can travel towards the OUs 
(moving the magnet closer to the metal balls). 
By bringing the attractive vision close enough, 
OUs  will  experience  the  attraction.  Manag-
ing communication in intensity, frequency and 
clearness varies the effect of the attraction.
•  Some  negative  effects  can  be  identified  too. 
Exerting the attractive force too close to the 
metal balls will make them accelerate towards 
the magnet and get stuck to it. This stops all 
free motion of the OUs. The entropy is zero and 
no innovation can be expected.
Likewise, a magnet applied at too large a dis-
tance or infrequently has no effect on the metal 
balls at all. Although there is an attractive vision 
represented by a magnetic field, the effect on 
the OUs is zero. They either move freely around 
like before (innovation takes place in all direc-
tions), or they do not move at all (no innovation 
takes place).

• 

Figure 3: Open innovation needs to be pull driven instead of driven by top-down push

In  an  OI2  organisation,  innovation  entropy  and 
magnetic attraction are the two controls that mat-
ter the most. It is the task and challenge of people 
in leadership positions to make use of these con-
trols and balance their adjustments. This is not an 
easy task and it is one which requires a new look 
on what leadership is. The good news is that it is 
already happening, as is demonstrated with the fol-
lowing practices.

The magnetic organisation in practice

Magnetism explained
The  magnetic  field  and  its  attractive  force  as 
a model for understanding the innovation behaviour 
in an Open Innovation 2.0 setting, finds strong prac-
tical support from recent marketing and innovation 
diffusion theory [9].

Inspired by Simon Sinek’s TED Talk [10] about the 
‘Golden  Circle’,  many  organisation  have  come  to 
understand  that  people  ide  strongly  identify  with 
the purpose of an organisation than with the actuals 
products or services it brings to the market. In his 
famous talk Sinek introduced a simple model of three 
concentric circles with the Why at the centre and the 
How and What in the second and third circle. Sinek:

‘Every single person and organisation in the planet 
knows what they do 100 %. Some know how they do 
it, whether you call it your differentiating proposition 
or proprietary process or USP. But very few people 
and organisations know why they do what they do. 
And by why I don’t mean to make a profit — that’s 
a result. It’s always a result. By why I mean, what’s 
your purpose? What’s your cause? What’s your 
belief? Why does your organisation exist?’ [11]

OPEN INNOVATION YEARBOOK 201633

Sinek argues that the strength of an organisational 
‘Why?’ defines the level of identification with the 
organisation amongst internal and external target 
groups. The golden circle model [12] has gained 
much popularity over the last few years. Within the 
Netherlands  the  model  has  become  a dominant 
branding workshop methodology.

The  magnetic  organisation  model  explains  the 
underlying mechanism for this popularity because 
the  ‘Why?’  is  a  practical  implementation  of  the 
attractive force. It provides direction for people in 
what they do and how they do it.

from  the  systems  design  and  creative  thinking 
community.  Bud  Cadell  [13]  proposed  a model 
for  systems  design  by  placing  design  thinking, 
lean start-up and agility into one process model. 
It  links  the  recursive  and  iterative  functions  of 
these methods to each other. At any given time, 
divergence (disorder) and convergence (order) are 
alternating.

In summary, the two practices can be combined into 
one another: Sinek’s ‘Why?’ serves as an attrac-
tive force, while Cadell’s process model manages 
entropy on the ‘How?’ level within Sinek’s model.

Entropy explained
In addition, the concept of entropy has also been 
translated into practical terms. One example is 

The figure below depicts this combination and illus-
trates  the  implementation  in  the  case  of  Apple 
computers.

Figure 4: A practical implementation of the metaphor

Conclusions and Outlook
To understand the workings of products and ser-
vices  creation  in  an  OI2  network  of  small-  and 
medium  sized  enterprises,  knowledge  institutes 
and  citizens,  the  magnetic  organisation  model 
is presented. It fills the void in innovation model-
ling  frameworks  stemming  from  the  fact  that 
in OI2 networks there is an absence of hierarch-
ical structures, checks, balances and control flow. 
These  structures  are  the  underlying  organisa-
tional principle of a classic corporation. The idea 
of  a ‘corporation’  gets  a new  meaning  in  OI2.  It 
serves  to  provide  up-scaling,  critical  mass  and 
focus. It acts as a breeding ground for renewal and 
entrepreneurship.

Practical support for this applicability is found in 
the  approaches  of  Sinek  in  the  why-what-how 
organisational  drivers  and  Cadell’s  construct  of 
iterative systems design.

It is the ambition of the research collaboration of 
the authors to formulate an organisation model 
with characteristics, variables and constants that 
can be interpreted in terms of measurable quan-
tities within the organisation. Such quantities are 
those that can be determined by means of observ-
ing,  measuring,  interviewing  and  analysing  the 
organisation data and their behaviour. This will aid 
the organisations leadership to balance the two 
controls and perform well in an OI2 setting.

Innovation in the context of the new corporation 
is described by the notion of innovation entropy 
and  attractive  field.  These  two  measures  act 
directly upon people and fit well with the reverse 
innovation pyramid that is characteristic for OI2 
organisations.

Three  case  studies  are  to  be  executed  in  2016 
to validate the expressive power of the magnetic 
organisation model and to illustrate how a balance 
in  entropy  and  attractiveness  would  help  these 
magnetic organisations to flourish and contribute 
in an OI2 society. A workshop methodology is under 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT34

construction to make these insights available in 
training and consultancy.

References
[1]  Downes, L. and Nunes, P., Big bang disruption, 
Portfolio Penguin, 2014.

[2]  Curley, M. and Salmelin, B., ‘Open Innovation 2.0: 
a new paradigm’, European Union conference paper, 
2013.

[3]  Meijer, G. R. and Nicholson, A. E., Management 
consulting in the IT revolution — The rise of 3rd 
generation management consultants, Logica, 2010.

[4]  Sargsyan, G., Meijer, G. R. and Open Source 
Initiative consortium, ‘Revered innovation pyramid’ in 
Socioeconomic impact of open service innovation, Editor 
Connect, 2010, p. 166 — https://ec.europa.eu/digital-
agenda/en/news/socioeconomic-impact-open-service-
innovation-smart-20090077

[5]  PA Consulting Group, ‘Innovation as unusual’, 2015.

[6]  Examples from The Netherlands in the Dutch paper 
Volkskrant, 8.8.2015.

[7]  Capgemini Consulting, ‘Digital transformation: 
a roadmap for billion-dollar organisations’, MIT Centre 
for Digital Business, 2011, among others.

[8]  Martínez-Berumen, H. A., López-Torres, G. C. and 
Romo-Rojas, L., ‘Developing a method to evaluate 

entropy in organisational systems’, Conference on 
Systems Engineering Research, 2014.

[9]  Moore, G., Crossing the chasm, Harper Collins, 2014.

[10], [11], [12]  Sinek, S., 9.5.2012 — https://www.
youtube.com/watch?v=l5Tw0PGcyN0

[13]  Courtesy of Cadell, B. — http://budcaddell.com/

Contact

Geleyn R. Meijer
Dean of the Faculty of Digital 
Media and Creative Industries
Amsterdam University of Applied Science
g.r.meijer@hva.nl

Artemus E. Nicholson
Managing Consultant
PA Consulting Group
artemus.nicholson@paconsulting.com

Ruurd Priester
Research Fellow
Amsterdam University of Applied Science
r.priester@hva.nl

OPEN INNOVATION YEARBOOK 201635

Open data for open innovation

Abstract

Quadruple helix and Open Innovation 2.0 (OI2) are powerful concepts to describe the role of actors and 
their behaviours in a modern knowledge-based society. The importance of data is recognised widely 
but further work is needed to make the innovation pipeline utilising the data broadly accepted. New 
value creation will not take place in an optimum way unless a holistic, systemic understanding of the 
process is available. Trust is a fundamental element in our monetary system. Similarly, trust is a fun-
damental element in an emerging datumtary () system. Models of innovation processes deriving new 
value from data as the critical resource are discussed.

The data age has started
Information and communication technologies (ICT) 
have developed over the last 40 years, driven mainly 
by internal innovation responding to internal needs 
of the ICT industries. The global telecommunication 
network has been designed and developed almost 
only for telecom-specific services. The current main-
stream telecom service based on 4G technologies, 
specifically long-term evolution (LTE) of the radio and 
system architecture evolution (SAE) of core network 
has  adopted  a high-throughput  packet  radio  and 
a flat architecture to better support the fast-growing 
internet traffic. But the overall penetration of full dig-
ital services beyond telecom is only taking its early 
steps. The European Union is taking advantage of 
ICT-enabled opportunities slower than its main global 
competitors such as the United States and China.

Today  almost  all  existing  information  has  been 
digitised, as Nicholas Negroponte predicted some 
20 years ago [1]. He did not, however, predict that 
digitalisation will take place also for material things, 
a transition which is currently shaping all industries 
in several fundamental ways. The Internet of Things 
and the industrial internet are shining dots on the 
hype curve, while too little system-level thinking has 
been applied to understand the deep behavioural 
changes that impact each and every traditional sec-
tor  of  our  society.  Observing  clustering  of  actors 
and stakeholders is not enough. Understanding the 
importance of the true common aims and the role 
of interdependences as the drivers and constraints 
in ecosystem formations is needed. The difference 
between a random group of companies and ecosys-
tems is like that between correlation and causality.

much more versatile. In casual terms, we all will 
have our ‘web presence’ in the cloud, including web 
pages of our wallets and pockets, as well as our 
livers and other organs. Digitalisation will only be 
complete when there is nothing left without aug-
menting digital data. The data age has started.

Life in general always develops towards new raw 
materials as they become available. The new raw 
material  of  the  data  age  is  data  itself.  It  is  not 
enough to think just of complementing the world 
we know with some additional data, but rather we 
need to place data at the centre. We should not just 
add intelligence to our products but redesign our 
products to be added to the vast emerging cloud of 
intelligence. Peter Diamandis describes the impacts 
of  scarce  resource  becoming  abundant  by  mak-
ing a difference between 10 % and 10 times the 
growth opportunities [2]. The question today is how 
we should deal with data to enable the 10-time 
growth, rather than be happy with the limping sin-
gle-digit growth that we experience in the European 
Union today.

Data and trust
If we look at the history of gold as a raw material, 
a valuable metal and later as the reference value 
for money, we might be able to identify some useful 
analogies. During the years of uncertainty, gold was 
used directly to bring stability to economies in each 
country. Only after World War Two was the Bret-
ton Woods system created, and today the credibility 
and the final value of money are based on trust in 
the responsible organisations and processes, rather 
than the value of the printed paper.

Our challenge is to extend Negroponte’s observa-
tion to cover not only information but also all ma-
terial aspects of our life, including our gadgets, our 
vehicles, our homes and finally also the material 
aspects of ourselves. Not only atoms but even elec-
trons will have their primary existence augmented 
by bits. As an example, electrical energy will carry 
information of its origin, price and on other aspects 
which  can  add  value  to  plain  old  electricity.  For 
material ‘things’, the added value can be obviously 

Big raw data is mined, processed and packetised 
using deep learning and other artificial intelligence 
methods to provide more and more valuable know-
ledge, and 1 day even wisdom for society [3]. The 
raw material will be there but we must pay more 
attention to the ways it is processed. We must have 
complete trust in how this process works. We know 
the enrichment process of gold and we know we 
can trust it. We need to learn how to deal with the 
enrichment process of data. We have already seen 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT36

some small incidents where trust in data enrich-
ment has been compromised. As a broader phe-
nomenon this may seriously jeopardise the value 
creation opportunities of the data age. Data with-
out trust has no value. Therefore further work is 
needed  to  define  the  relevant  trust  models  and 
processes for data, regardless of whether we talk 
about big data, small data or any derived informa-
tion based on the data. Trust is needed to make the 
data valuable.

where trust is not maintained. This is why we have 
courts of law.

The other strong idea seems to be based on social 
loyalty. There are numerous groups based on vari-
ous ideas of common purpose and principles with-
out any solid contractual arrangements. If trust is 
broken people typically just leave the group and 
ultimately this may lead to the decomposition of 
the whole group.

Trust is not a simple concept. Just a quick look at 
a dictionary can give 20 or more different inter-
pretations or aspects of trust.

‘Trust is both an emotional and logical act’. ‘Trust 
may be based on law or in some cases trust can 
be a much more complex construct’.

A neutral way to address the question is to look at 
the structures that emerge from the data itself. To 
get started we can use mankind as a heuristic com-
puting machine and observe if there are any general 
intuitive principal components that can be observed 
in  the  way  we  have  been  dealing  with  data.  Key 
words such as predictability, value exchange meth-
ods, reciprocity and vulnerability or recovery mech-
anisms can be used to test the hypothesis.

It seems that four intuitive principal ideas of trust 
can  be  identified.  The  first  of  the  two  strongest 
ideas seems to be where there is some kind of con-
tractual trust in place. There are numerous mech-
anisms in our society to maintain trust this way and 
there are numerous ways to deal with situations 

Both  of  these  trust  models  are  open  based  and 
rather transparent mechanisms. Contractual trust 
has a more ridged and centralised approach, while 
social  trust  is  originally  rather  distributed,  each 
group having its own trust asset. In the data age, 
digital mechanisms enable very large, even global, 
social systems to emerge. We may need to con-
sider whether such large, often less transparent 
and rather centralised systems will maintain the 
expectations  of  the  distributed  and  open  social 
trust models of, for example, a local football team 
or a student choir.

The behaviours of these global networks lead us 
to look at trust models which are characteristically 
centralised and closed. Access to the data is lim-
ited and enrichment of the data is in the hands of 
the owners of the platforms. Some governments 
in less democratic countries drive a similar trust 
model towards their citizens. One common behav-
iour in very large social constructs seems to be the 
tendency towards a centralised attempt to act on 
behalf of their members. Trust is neither contracted 
nor socially fully accepted.

Figure 1: Fundamental trust models using centralisation and openness as principal dimensions

OPEN INNOVATION YEARBOOK 201637

For completion of the 2 x 2 matrix using heuristic 
dimensions of openness and centralisation there is 
one corner where the trust model is also closed but 
not centralised. As an extreme case this is an en-
vironment where there is no trust whatsoever and the 
actors are working alone. One consequence of such 
a model is that identities are not needed and the data 
is fully anonymous. Data with this kind of trust model 
are not usable for any common activities but may still 
be valuable for each of those actors locally.

Innovation and trust
There  are  good  reasons  to  believe  that  open  in-
novation is the most competitive approach for value 
creation and also the best way to share the value 
among all the stakeholders, but at the same time 
we need to acknowledge the merits of closed innov-
ation models. It is not by accident that the innovation 
models as defined by the Open Innovation Strategy 
and Policy Group (OISPG) are very similar to the trust 
models  discussed  here.  The  dimensions  of  open-
ness and centralisation span the ecosystem space 
similarly independently of what the perspective is. 
Therefore a rational question arises: the Open In-
novation 2.0 (OI2) model calls for open and active 
collaboration  of  all  the  possible  parties,  but  has 
there been enough consideration of the prerequisites 
such as mutual trust between the stakeholders for 
a successful collaboration to really happen?

The quadruple helix (QH) used as the framework 
in the OI2 was introduced by Christer Asplund and 
Jörgen Eriksson [4] and can be seen as an evolution 
of the older triple helix thinking originally proposed 
by Henry Etzkowitz and Loet Leyderdorf [5].

The high-level innovation modelling in the OISPG 
follows the QH thinking by pointing out the four dif-
ferent segments being civil, business, academia and 
government. Asplund and Eriksson, however, argue 
that:

‘The role of strong individuals who are resourceful, 
not in their capacity as legitimised role players in 
either of the three other (triple helix) organisa-
tions, but rather as resourceful individuals who are 
less well organised and normally not appointed by 
at least the classical institutions’.

This can be interpreted as an introduction of the 
fourth innovation model, decentralised closed in-
novation, in addition to the already well-defined 
centralised but closed innovation, (centralised) open 
innovation and (decentralised) innovation networks 
ecosystems. At least in this context we can call it 
random innovation. This way we will get a strong 
motivation  to  align  the  models  of  trust  to  the 
models of QH and OI2.

Figure 2: The four innovation models inspired by the QH model, completed

Centralized
inward looking
innovation

CLOSED
INNOVATION

Externally focused,
collaborative
innovation

Ecosystem centric, 
cross-organisational
innovation

Random individual
innovation

OPEN INNOVATION

INNOVATION
NETWORKS
ECOSYSTEMS

RANDOM
INNOVATION

Separately from triple and quadruple helixes there 
is a third helix model which should not be confused 
with the two already mentioned. Charles Fine [6] 
proposed a double helix model to explain the eter-
nal oscillation of the different value chain models 
between centralised and decentralised behaviours. 
Fine is indicating that there is no global optimum 
point in this oscillation but rather that the opti-
mum point is moving forward as technologies and 
businesses gain maturity within their current oper-
ating point. Even if today’s business thinking has 

developed from ‘simple’ supply chains to complex 
‘ecosystems’  models,  the  role  of  openness  and 
centralisation,  periodic  cycling  between  vertical 
products and horizontal platforms seems to repeat 
itself in a fractal way.

As  a  synthesis,  the  double  helix  oscillation  can 
explain the eternal movement through the tem-
porary leading roles of each of the four different 
corner points and lead actors of the quadruple helix. 
The double helix oscillation is driven by emerging 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT38

powers of technology and market innovations as 
counter  measures  to  customers’  dissatisfaction 
and stagnation. This is an important observation, 
since it raises the following question: is it possible 
in reality to have a fruitful collaboration between 
all the four stakeholder groups focusing on different 
innovations models all at the same time? Or, more 

optimistically, what are the ground rules we need to 
define for such a collaboration to happen? The criti-
cal testing point of that question could be the level 
of compatibility between the different trust models 
related to the data used and shared by the different 
QH stakeholders.

Figure 3: Double helix illustrates the oscillations in the supply chain between 
vertical/integral and horizontal/modular according to Charles Fine

Eternal evolution of innovations ideas
By noting the fourth innovation model as indicated 
by the QH, we avoid linear thinking towards any 
permanent end state. Random innovation may be 
seen as a smallest form of innovation, which nor-
mally is also the first early approach before more 
advanced innovation models are needed. However, 
recognising the fourth innovation model may help 
in our overall quest for seeking the viable combin-
ations towards one fully holistic innovation frame-
work. This approach also makes the QH and OISPG 
thinking fully aligned. Finally, we can also add to 
the discussion the different trust models of data-
enrichment processes relevant for open as well as 
closed innovation concepts. Furthermore, we can 
add one more post-it note on trust to the 20 exist-
ing characteristics of OI2 as discussed in the 2015 
OISPG yearbook [7].

In the context of vertical and horizontal business 
models,  there  is  a need  to  look  at  the  different 
clusters in ICT-driven industries. The double helix 
oscillation  as  defined  by  Fine  takes  place  syn-
chronously when there are strong ties and depend-
encies between the actors. If the ties are weaker 

or deliberately limited, for instance by regulation 
or open standards, the interrelation becomes asyn-
chronous. There are needs to clarify the clusters for 
the data age especially because the role of con-
sumers  and  their  augmented  digital  presence  is 
becoming one of the clusters on the same level as 
the currently, rather well-defined clusters of con-
tent, network and consumer devices. This need has 
been  recognised  but  further  work  is  needed  [8]. 
Trust is also one of the critical factors to be consid-
ered for cross-cluster innovations. The clusters and 
their interaction become sustainable ecosystems 
only when all relevant interdependences including 
trust are fully understood and appreciated. Vertical 
bundling over regulatory borderlines is not going to 
be any easier issue in the future. Communications 
network technologies are already moving towards 
the 5G paradigm. This will create needs for other 
ICT clusters to follow, if not synchronously then at 
least asynchronously.

Innovation and data
The discussion on very fundamental aspects of life 
and business such as trust is useful when a suitable 
level of abstraction is chosen.

OPEN INNOVATION YEARBOOK 201639

Figure 4: Innovations are needed to create value using raw material

The previous growth cycle in ICT can also be defined 
as an enrichment process of a raw material through 
extensive multiple innovations to valuable services 
for consumers. Value creation in telecommunica-
tions services is fundamentally an abstract enrich-
ment process of radio spectrum. To bridge the gap 
between historical developments and the current 
topic, data-driven ecosystems can be seen more 
clearly if data is considered as a scarce resource 
like radio spectrum.

The current assumption is that there are lots and 
lots  of  data  available.  There  are  many  plans  to 
open even more, e.g. public data, to be available for 
anybody to create new businesses. As an example, 
significant publicly owned cartography databases 
are  already  open  for  anybody  to  create  mobile 
applications in Finland. When there is such a large 
amount of data available and all that data can also 
be copied easily, how can we talk about data being 
a scarce resource?

In  the  early  days  of  radio  communication  there 
was no scarcity of radio spectrum either, but as in-
novations open new opportunities, the availability 
of the raw material also becomes an issue, either 
because of the laws of physics or because of the 
issues within collaboration of the people. Tragedies 
of commons or anti-commons have been observed 
many times. When more and more valuable ser-
vices are needed in real time, availability of the 
data as well as the speed of the enrichment pro-
cess of the real-time data is not a trivial problem 
to be solved using the laws of physics. The scarcity 
is hiding in the first and higher derivatives of the 
data. What are the implications then for trust? Do 
we need to conceptually derivate trust too?

The scarcer a raw material is the more there are 
value  creation  opportunities  through  innovation. 
Complex value creation aims to exceed the arith-
metic sum of the separate value propositions. These 
kinds  of  honeypots  may  be  available  when  sev-
eral  innovation  processes  deal  with  several  sep-
arate scarce resources at the same time. One such 
example is the emerging new mobility as a service 
(MaaS) paradigm, where scarce resources such as 
consumers’ (mobility) data, road capacity and radio 

spectrum for mobile radio communications are all 
ingredients of the same converging innovation pro-
cess.  This  observation  easily  leads  to  a question 
about the applicability of complex value generation 
in case the fundamentals of the separate innovation 
processes, for instance related to trust, are strongly 
misaligned. We cannot expect a guaranteed quality 
of service from self-driving cars if trust in the quality 
of data communications is best effort or the enrich-
ment process for critical traffic data is not transpar-
ent [9]. Should this also require road capacity to be 
available on a commercial basis is a good question. 
Or even a broader question is whether the manage-
ment processes of all scarce resources in the data 
age should be revisited. Should licences to scarce 
resources  be  aligned  for  a  successful  systemic 
business?

This may sound rather radical and liberal, or on the 
other hand even a rather old-fashioned, regula-
tive-oriented approach. Obviously it is both. How-
ever, observations are derived from dependencies 
as must be done in case of ecosystems, and not 
only by accidental clustering where two or more 
assets happen to be at the same place at the same 
time.  Causality  is  needed  and  correlation  is  not 
enough. And we might consider keeping the innov-
ation models originally separate and invite them to 
converge only where appropriate.

The ubiquitous connectivity provided by different 
types of networking services makes all data tech-
nically  available  globally,  but  because  of  differ-
ent ecosystem constraints, especially the trust in 
data and the different business models developing 
knowledge based on the data, value creation and 
innovation on data is a far more complicated mat-
ter. Following the concept for radio spectrum man-
agement, this leads to a consideration of whether 
there should be one international management sys-
tem for data with the following four separate initial 
domains.

1.  Data for governmental use only. Example: data 
for military and national security purposes.
2.  Licensed  data  for  commercial  use.  Example: 
traffic data about autonomous driving. Data is 
owned by the consumer but a commercial traffic 

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT40

operator is licensed to manage it. Data portabil-
ity between the operators.

age. We deserve a solid, rigid, flexible and efficient 
way to manage our key new raw material — data.

3.  Unlicensed data for social use. Example: social 
wellness data shared though the social wellness 
application within the community for the benefit 
of all the participants in the community.

4.  Anonymous data. Example: data collected with-

out any consent by the observed objects.

Conclusions
Four different types of innovation models are dis-
cussed in the context of four different trust levels. 
Mixing different innovation models can be done but 
it will require a careful approach to deal with the 
different requirements and expectations in each of 
the approaches. This is clearly valid for aspects of 
trust but should be considered in case of any other 
aspects of ownership and control. The challenges 
in  making  the  different  innovation  models  work 
together  is  not  just  a challenge  for  open  innov-
ation promoters. Similar challenges in different ways 
have been a hot potato in collaboration between 
different standardisation organisations for years. 
There are many examples of failure, but also some 
successes in how different approaches have been 
integrated into one functional setup. The recent 
European Telecommunications Standards Institute 
Summit  on  Standardisation  and  Open  Source  is 
a good example of practical work towards the OI2 
environment, at least for Europe [10].

It is far too easy to assume that there is only one 
way of dealing with the data. Today the data age is 
only taking its first steps and it will take time to find 
broadly accepted agreements on how to deal with 
the data and with all the dimensions such as trust 
globally. We have some earlier examples where we 
have been able to develop working collaborative 
models to deal with such sensitive and abstract 
issues. There is no other way forward in the data 

References
[1]  Negroponte N., Being digital, Vintage Books, 1995.

[2]  Diamandis P. and Kotler S., Abundance, Free Press, 
2012.

[3]  Thomson R., Lebiere C. and Bennati S., ‘Human, 
model and machine: a complementary approach to big 
data’, HCDBR ‘14, ACM, 2014.

[4]  Etzkowitz H., Leydesdorff L., ‘The triple helix — 
University-industry-government relations: a laboratory 
for knowledge-based economic development’ EASST 
Review 14, 1995.

[5]  Asplund C., Eriksson J. ‘Beyond “triple helix” — 
Towards “quad helix”. The bearing wave’, Bearing 
Consulting, 2012.

[6]  Fine C., ‘Clockspeed-based strategies of supply chain 
design’, Production and Operations Management, 2000.

[7]  Open Innovation Strategy and Policy Group, 
‘Yearbook 2015’, European Union, 2015.

[8]  Fransman, M., The new ICT ecosystem, implications 
for policy and regulation, Cambridge University Press, 
2010.

[9]  Ali-Vehmas, T. and Casey, T., ‘Examining possible 
value system transitions: the case of smart mobility 
services’, 48th Hawaii International Conference on 
System Sciences, 2015.

[10]  European Telecommunications Standards Institute, 
Summit on Standardisation and Open Source, 2015 — 
http://www.etsi.org/news-events/events/979-2015-11-
summit-standardization-and-open-source

Contact

Timo Ali-Vehmas
Head of Ecosystem Research
Nokia Technologies 
timo.ali-vehmas@nokia.com

OPEN INNOVATION YEARBOOK 201641

Thought piece on societal innovation and futurising

Context

One of the milestones in open innovation collab orations, on the macrolevel, took place in December 
2015 in Paris — COP21. A global agreement was reached among 196 parties as consensus on limiting 
global warming to less than 2 °C, compared to earlier escalating levels [1].

This agreement is said to be both an industrial as well as a societal challenge for planet Earth. Hope-
fully we will see a stream of eco-innovation, not only innovative household Tesla batteries, but also 
policy innovations on various organisational levels.

The further societal prototyping might take place with different impact investing models, e.g. circular 
economy, sharing economy, cross-disciplinary and cross-organisational, working together for the en-
vironment and the economy. As an initial outcome might we see a whole new glossary or taxonomy 
and metrics/key performance indicators for this emerging eco-paradigm? This will be a critical input 
for the innovation work of new ways of shaping and sharing the wealth creation.

Societal innovation
Societal  innovation  (SocInn)  refers  to  a  systemic 
change  in  the  interplay  of  the  state  and  civil  so-
ciety.  It  is  a relative  of  social  innovation,  but  dif-
fers from it by considering the state to be an im-
portant co-creator in achieving sustainable systemic 
change. In this sense, the term’s origins lie beyond 
the traditional Anglo-Saxon understanding for the 
concept of social innovation [2]. A starting point is 
often the observation that the institutional systems 
of societies are obsolete in relation to its emerging 
societal and geopolitical context.

SocInn  might  be  viewed  in  different  perspectives, 
beyond social innovation:

• 

• 

• 

• 

as a Lumification process or signal process for 
SocInn from knowledge navigators for sustain-
ability navigation like in Ragusa (see later on in 
the article);
as triggering reduced friction or peace innovation 
among citizens, by innovative harmonising of citi-
zens’ relational interaction, such as a knowledge 
café, the Aalto camp for societal innovation [3] or 
the BMW-Guggenheim Lab [4];
as new societal rulemaking for a joint co-cre ative 
thrust, as COP21, or as civil rights innovations, 
like with MindLab in Denmark, pioneering spe-
cific e-lawmaking in Malaysia, the new business 
hybrid form the United States called Low-Profit 
Limited Liability company, Social Benefit Com-
pany in Australia or the legal reframing case by 
the Nobel Peace Prize awardees as a National 
Dialogue Quartet in Tunisia;
as a usage of information and communications 
technology  (ICT)  and  networking  technologies 
for new types of democracy engagements, such 
as voting kiosks or distributed online community 
dialogues.

A learning case on a macrolevel might be the process 
behind and the construction of the European Union 
and the European Commission. It can be related to 
the  four  pillars  of  learning  principles  of  its  initial 
chairman Jacques Delors: learning to know, learning 
to do, learning to live together and learning to be [5].

Another pioneering case outside of Europe might be 
the Multimedia Super Corridor, initiated by the former 
prime minister to encourage the internet entrepre-
neurship and digitalisation of Malaysia, and the rel-
evant rulemaking [6].

In Finland, after the collapse of the Soviet Union, 
there was a huge need for renewal and institutional 
refraining at many levels. As a critical driving force 
was the creation of a committee for the future, to 
address the societal thrust across political parties 
and old institutions to shape actions [7].

In Denmark some society leaders realised the need 
for  Cabinet  process  renewal.  Inspired  by  Skandia 
Future Centre, Rosted initiated the MindLab [8] as 
a collaborative thrust between the Ministry of Busi-
ness and Growth, the Ministry of Education and the 
Ministry of Employment [8].

A recent experiment in progress is the cross-national 
science construct —European Spallation Lab in Lund 
[9] — for high acceleration research in physics. It is 
a cross-disciplinary lab as well as a cross-national 
funding together with the European Commission.

The above examples relate to the bullet points as an 
illustration of seeing the need for renewal (lumifica-
tion) as a proactive reduction of tentative society 
friction by users’ and citizens’ involvement and usage 
of ICT to smartening, as well as reforming rulemak-
ing in different contexts.

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT42

Open innovation of nations
Open innovation as a model developed by Henry 
Chesbrough [10] might be considered not only for 
enterprising, but also for nations to collaborate. 
The COP21 might be an illustration. We still have 
to explore the work model of open innovation for 
nations.  Such  macrolevel  perspectives  might  be 
supported  by  navigational  data  in  the  work  of 

national intellectual capital (NIC) as initiated within 
the New Club of Paris.

Now available through the New Club of Paris are 
databases for deepening the review of the progress 
of data of more than 50 countries, with more than 
50 indicators, grouped into the NIC model. This is 
also referred to as the Edvinsson, Lin, Stahle, Stahle 
(ELSS) model model in Figure 1.

Figure 1: ELSS model of NIC

In these unique databases of the performance and 
development on the subject of NIC, it shows that 
in  advanced  economies,  almost  75  %  of  growth 
and  development  can  be  traced  back  to  NIC  per-
formance.  NIC  impact  on  GDP  can  vary  from 
16-72 % of GDP growth. It can also be observed that 
one of the critical dimensions is the renewal and 
innovation, not only of enterprises but of society as 
a whole. The fabric of society and its systems needs 
continuous renewal, not only maintenance.

Leading nations of NIC might be seen from maps 
of NIC [11]; [12]. A further look indicates the follow-
ing top list: United States, Finland, Israel, Sweden, 
Denmark, Japan, Taiwan, Germany, Switzerland and 
Singapore. A more recent and detailed NIC research 
update on the renewal of capital of nations will be 
found in the continuously refined database.

Figure 2: NIC renewal

OPEN INNOVATION YEARBOOK 201643

The most innovative nations reported by Bloom-
berg are South Korea, Germany, Sweden, Japan and 
Switzerland [13]. What is the implication outlook for 
Europe?

Historical  research  also  indicates  that  national 
economy and well-being also go through cycles, 
as Dr Jay Forrester from Massachusetts Institute 
of Technology (MIT) documented in his book World 
dynamics. Combinatory insights also point out that 
the societal eroding catalyst might be in the intan-
gibles or components of NIC. Cultural erosion and 
failing citizen dialogue systems might be some of 
them.

However, this is also a quest for more refined indi-
cators than traditional economic perspectives. We 
still have to wait for such indicators from the shar-
ing  economy,  circular  economy,  and  so  on.  New 
eco-metrics for eco-mapping will emerge. Among 
those, trust-bridging relations capital metrics will 
be critical.

One of the pioneering eco-researchers is Profes-
sor  Johan  Rockström  at  Stockholm  Resilience 
Centre  [14],  which  was  established  in  2007  as 
part of Stockholm University. Stockholm Resilience 
Centre advances research on the governance of 
social-ecological systems with a special emphasis 

on resilience — the capacity to deal with change 
and  continue  to  develop.  Resilience  has  several 
distinctions, but the core might be in the ability to 
swiftly return to a previous healthy condition and 
to recover. Pioneering eco-metrics might be refined, 
such as in a SocInn index.

Another  such  societal  leader  who  is  said  to  be 
a man of extraordinary societal resilience was Nel-
son Mandela. In his legacy we might find a deeper 
dimension of collaborative and persistent models of 
societal cultivation and innovative policymaking for 
justice. A new important job function will be in the 
role of planet cultivators for the custody, preserva-
tion and navigational policymaking for futurising.

Societal innovation fabric 
and societal learning
One of the early pioneers with another perspec-
tive for its citizens is to be found in the old city 
of Dubrovnik, once also called Ragusa. There, for 
around 600 years, the citizens were living in peace, 
with a continuously growing economy. Its lumifi-
cation  intelligence  was  based  on  dragomans  as 
knowledge navigators and diplomacy. Now, for the 
last 10 years, the e-students of Zagreb, together 
with New Club of Paris, have organised a summer 
school [15] to search for further insights into this 
unique societal construct.

Figure 3: Map of old Ragusa city with its intelligence fleet, by A. Dvir, 2015

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT44

In  Ragusa,  the  societal  fabric  system  was  very 
much based on societal learning. There was a sys-
tem for survival and defence based on diplomacy 
and societal intelligence, with special-knowledge 
navigators called dragomans stationed around the 
Mediterranean. There was also a specific educa-
tional system, amplified by the taxonomy of hav-
ing the city mayor called rector/dean. This system 
gave the society a continuous well-being for around 
600 years, up until the year 1806.

For the process of societal fabric weaving it has 
to be appealing, innovative, solid and continuously 
renewing. Unfortunately, the present situation in 
many leading economies seems to be character-
ised by what the founder of the Visa, Dee W. Hock, 
phrased as institutional failure.

This  is  a very  serious  alert  for  increasing  social 
unrest, unemployment, financial debt burden on 
different levels and growing opportunity costs for 
future generations. SocInn might also be looked 
upon as a topic of justice for its citizens! Might the 
challenge be to find the ways to cross the chasm by 
new societal bridging systems?

In Tunisia this has been a process for 11 years, and 
with  a pioneering  National  Dialogue  Quartet  of, 
among others, four thought leaders who were given 
the Nobel Peace Prize in December 2015 [16] ‘for 
its decisive contribution to the building of a pluralis-
tic democracy in Tunisia in the wake of the Jasmine 
Revolution of 2011’.

Peace Innovation Lab
In  the  quest  for  SocInn,  a  recently  developed 
approach  can  be  found  in  the  Stanford  Peace 
Innovation Lab [17] with several labs in Denmark 
as well as its spin-off into the Berlin Peace Innov-
ation Lab. It has similarities to the early pioneering 
work in Skandia Future Centre, followed by MindLab 
in Copenhagen and now Future Centre Alliance in 
Japan. MindLab in Denmark has been evaluated to 
add to both the speed of policymaking as well as to 
the innovative content dimensions [18].

Soon, there will be a request for especially designed 
spaces  for  collaborative  and  thought  leadership 
dialogues for fail-safe rapid prototyping. In Japan 
this is being pioneered by the Ministry of Economy, 
Trade and Industry as well as, among others, Pro-
fessor  Noburo  Konno  and  his  pioneering  work, 
together with Professor Ikujiro Nonaka [19]. In their 
work on knowledge innovation management they 
are drawing upon the insights of both Asian and 
Western thought processing. Perhaps this would 
add to the resilience and peace innovation dimen-
sions beyond the traditional management paradigm 
of competitive models. The peace innovation labs 

might be very instrumental for further prototyping 
of SocInn.

National open innovation and futurising 
steps on societal innovation
In the extension of COP21 combined with societal 
modelling of diplomacy and luminary intelligence, 
how do we take the next steps? Perhaps by look-
ing into new digital social media models for cross-
generational  collaborations.  Another  exploration 
area  might  be  a super-forecasting  approach,  as 
researched by Professor Philip E. Tetlock on the art 
and science of prediction from the University of 
California, Berkeley and the University of Pennsyl-
vania [19]. It is about metrics for probability judg-
ments on geopolitical predictions similar to weather 
predictions and improved probability scoring based 
on skilful/swift collective intelligence.

For societal leaders it is of the utmost urgency to 
address a  process of reframing the institutional 
fabric  of  the  knowledge  economy.  This  will  call 
for thought leadership, by the key work of future 
centres, among others, in the Netherlands. There, 
the innovating collaborative space was labelled LEF 
[20], which in English translates to courage. This is 
a pioneering space for the government on infra-
structure challenges of The Netherlands with penta 
helix collaborations. This is very much highlighted 
in the abovementioned SocInn cases from differ-
ent parts of the world. For the futurising of soci-
etal fabrics it is essential, along with institutional 
reframing, to address the not knowing — societal 
ignorance!

Pioneering steps for such an approach of SocInn 3.0 
might include:

• 

• 

• 

• 

• 

refined and acknowledged unorthodox metrics 
for the societal navigation;
cross-cultural appreciative inquiry for thought 
leadership and benchlearning;
externalised innovation prototyping places, e.g. 
MindLab, peace innovation labs;
leveraging the digital economy to shape new 
parallel hybrid parliamentary systems across 
generations,  across  institutions  and  across 
culture;
prototyping  the  power  of  new  digital  cur-
rency, its implications for welfare and citizen 
well-being.

References
[1]  http://www.cop21.gouv.fr/en/

[2]  Lehtola, V. and Ståhle, P., ‘Societal innovation at the 
interface of the state and civil society’, The European 
Journal of Social Science Research, 2014, pp. 152-174.

[3]  Aalto camp on societal innovation — https://
ec.europa.eu/digital-agenda/en/news/acsi-espoo-2015

OPEN INNOVATION YEARBOOK 201645

[4]  BMW Guggenheim Lab — http://www.
bmwguggenheimlab.org/

[5]  Leonardo Learning Award, see http://www.leonardo-
award.eu/content/index_eng.html

[6]  Multimedia Super Corridor, established in 
1996 as a special zone, Malaysia — http://nitc.
kkmm.gov.my/index.php/key-ict-initiatives/
multimedia-super-corridor-msc-malaysia

[7]  http://www.fdsd.org/ideas/
the-committee-for-the-future-finnish-parliament/

[8]  http://mind-lab.dk/en/

[9]  A cross-nation collaborative, special high-tech 
impact centre in progress in Lund, Sweden — https://
europeanspallationsource.se/

[14]  http://www.stockholmresilience.org/21/about.html

[15]  https://www.estudent.hr/category/international/
dubrovnik-summer-school/; https://en.m.wikipedia.org/
wiki/Republic_of_Ragusa

[16]  Nobel Peace Prize 2015 —http://www.nobelprize.
org/nobel_prizes/peace/laureates/2015/

[17]  http://peaceinnovation.stanford.edu/

[18]  http://future-center.org/

[19]  Tetlock on super forecasting — http://longnow.org/
seminars/02015/nov/23/superforecasting/

[20]  Governmental future centre for infrastructure 
in The Netherlands — http://www.rijkswaterstaat.nl/
english/index.aspx

[10]  Open innovation pioneer, see https://en.m.wikipedia.
org/wiki/Open_innovation

Contact

[11]  www.NIC40.org; www.nic4nations.com

[12]  http://bimac.fi/#StartTop1; methodology based 
on Ståhle, P., Ståhle, S. and Lin, C., ‘Intangibles and 
national economic wealth — a new perspective on how 
they are linked’, Journal of Intellectual Capital, 2015 — 
http://www.emeraldinsight.com/doi/abs/10.1108/
JIC-02-2014-0017

[13]  http://www.bloomberg.com/news/
articles/2016-01-19/these-are-the-world-s-most-
innovative-economies#media-4

Leif Edvinsson
The world’s first professor 
on intellectual capital
Co-founder and initial chairman for the New 
Club of Paris — www.new-club-of-paris.org
Luminary Awardee 2013 for thought 
leadership by the European Commission, 
Intel and the Peter Drucker Foundation

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT46

Open Innovation 2.0 and higher education
A case of thesis process in social and healthcare education

Abstract

Principles regarding Open Innovation 2.0 (OI2) have been widely recognised [1]. Still, OI2 is mainly 
applied to areas such as industries and economics [2; 3].

Traditional models of providing education are being challenged by possibilities provided by new forms 
of learning. These issues relate to innovation [4] and development of work practices [5]. Innov ation 
pedagogy serves as a wide concept bringing together different practices and ideals in pedagogy [6; 7].

Diak and the traditional thesis method
Diaconia University of Applied Sciences (Diak) is 
a Finnish institution of higher education. We train 
professionals in healthcare and social work, both 
domestically and globally. The Diak curriculum was 
reformed from January 2015 onwards. As part of 
that process, the thesis method was reformed as 
well.

Diak has bachelor’s programmes in social work and 
healthcare, and a bachelor’s programme in social 
services taught in English. The university also pro-
vides one master’s-level programme taught in Eng-
lish. In Finnish, Diak has masters’ programmes in 
both social work and healthcare.

Before these reforms, Diak’s thesis procedure fol-
lowed the traditional form. Students had to take 
a series of courses on the basics of research meth-
odologies.  These  included  observation,  different 
kinds of interviews and survey methods. In fact, 
the thesis methods within the framework of Finnish 
universities of applied sciences should focus on the 
development of work processes and other practical 
development aims, rather than on ‘pure’ academic 
research.  This  means  the  research  methods  are 
applied to practical tasks such as finding out what 
is actually wrong in the working process of a certain 
clinic or finding out the views of parents and profes-
sionals on the development of preschool education 
in a certain community.

Despite this, the thesis followed the traditional pat-
tern where a student or a pair of students plan, 
execute and evaluate a series of actions. Then, this 
process and the results are reported as a mono-
graph type of the report [8; 9; 10; 11; 12].

New ideas for thesis process
During  the  reform  of  the  thesis  process  princi-
ples of OI2 were applied, Diak wanted to form an 
open  platform  for  innovation  and  development. 
This platform has to be able to serve businesses’, 

governments’  and  civil  societies’  interests.  The 
problem with virtual learning environments is that 
they are closed, where access is usually limited to 
the teachers and students. Representatives of busi-
nesses, governments or civil society cannot be eas-
ily integrated into these environments. They are not 
open for comments. This also means that they do 
not really serve needs of processes based on OI2. 
If an idea for a new project, service or business is 
presented on a traditional course, the only possible 
commentators are the teachers and students on 
that same course. Imagine if any expert could be 
invited to comment on the student’s idea? What if 
this idea could then be developed in a direct contact 
with relevant business, government and civil society 
organisations?

It was our aim to develop an open platform to make 
this possible. In Diak there were earlier experiences 
to build upon [13]. Apart from the question of open-
ness, there was another challenge. While Diak has 
a project portfolio (projects with domestic and EU 
funding), these projects had not been duly linked 
and integrated into the student’s thesis processes. 
We needed a way to open thesis process to those 
outside  the  Diak  organisation  as  well  (projects, 
partners), and interlink our own project organisa-
tion into this open thesis process.

In order to serve the aforementioned aims, a tech-
nical solution had to be selected. Instead of this 
closed  learning  environment,  we  created  a blog 
which inherently is an open platform. This blog cre-
ates what Salmelin [1] has called an engagement 
platform. It creates a possibility to publish and test 
ideas — with zero marginal costs.

Since  Diak  is  an  institution  of  higher  education, 
the  innovation  process  has  to  be  articulated  as 
syllabus. In the Diak model as shown in Table 1, 
the innovation cycle is understood as consisting of 
three stages: (i) innovation and planning; (ii) deploy-
ment; and (iii) evaluation and reporting.

OPEN INNOVATION YEARBOOK 201647

Table 1: Stages of the Diak model

Innovation and planning

Deployment

Evaluation and reporting

Two semesters in student process

Two semesters in student process

Two semesters in student process

Students (i)  get familiar with Diak part-
ners and projects; (ii) produce ideas; (iii) 
plan their execution.

Students (i) work on different courses 
(ii) deploy ideas developed earlier; (iii) 
apply different  methods of material 
gathering and development work; (iv) 
report on writing, statistics, videos and  
photographs.

Students (i) evaluate the outcome of 
the earlier stages; (ii) write further 
contributions if needed; (iii) write the 
summary report of the process.

Diak RDI –team integrated in the 
process

Ideas are deployed in co-operation with 
Diak partners and projects.

Reports and products are published 
with partners and projects.

Each stage is articulated into courses in the Diak 
curriculum.  The  process  starts  from  the  second 
semester  and  goes  on  through  the  rest  of  the 
studies.

Blog serves as an open platform
The blog for testing one’s ideas is central during the 
first stage: innovation and planning. It consists of 
two courses, one focused purely on innovation and 
the other focused on creating a plan for executing 
and documenting one’s idea. Students’ ideas are 
based on the earlier Diak projects with domestic 
or EU funding and/or ongoing cooperation with our 
partners. These ideas are published in the blog. This 
means that ideas can be commented on by ‘outsid-
ers’; outsiders referring here to representatives of 
projects and organisations outside of Diak.

Apart from these comments from the outsiders, the 
Diak research, development and innovation (RDI) 
team is integrated into this stage. They comment 
on the ideas and connect and combine them into 
concepts  and  processes  that  already  exist.  Also, 
these ideas remain in the blog for the next gener-
ation of students to use. This creates a possibility for 
an accumulation of knowledge and understanding.

Then, during the deployment stage, students work 
with different organisations and deploy their plans 
and ideas. Despite the fact that the last stage is 
called evaluation and reporting, the latter takes 
place throughout the whole process. Students write 
shorter reports on each course  — these reports 
are  then  evaluated  at  the  beginning  of  the  last 
stage of the process. The question is whether these 
reports make up a thesis that is coherent enough. 
Then a summary report is written and the thesis is 
published.

Conclusion
Since  the  new  Diak  curriculum  has  been  active 
only since January 2015, one year later, in January 
2016, students are only at the first stages of the 
process. For the blog, a beta version is employed. 
The deployment stage has not yet started with any 

of the groups. This means that a wider evaluation 
of the model is not yet available.

From the first experiences it is possible to conclude 
that  students  work  eagerly  in  the  process.  Stu-
dents produce ideas worth considering and devel-
oping further, also by professional Diak RDI staff. 
The model is flexible and provides possibilities to 
combine work and studies. As for the ecosystem, 
whether this kind of practice can stimulate or even 
create one remains an open question. Examples 
of  online  platforms  used  as  a core  for  develop-
ment processes do exist [5]. Discussion on innov-
ation pedagogy [6, 7] provides conceptual tools for 
development.

The next step is to collect empirical data from the 
different  points  of  views  (students,  staff,  part-
ners, etc.). Also, different practices that reach out 
towards  our  partners  need  to  be  remodelled  to 
serve the current situation. All this will give a pos-
sibility for further development and also for more 
precise conceptual definitions within the model.

References
[1]  Salmelin, B., ‘Open Innovation 2.0 creates new 
innovation space’, Open Innovation 2.0 — Yearbook 
2015, 2015.

[2]  Lappalainen, P., Markkula, M. and Kune, H., 
Orchestrating regional innovation systems, Otavan 
Kirjapaino, 2015.

[3]  Kärkkäinen, H., Jussila, J. and Erkinheimo, P., ‘The 
new era of crowdsourcing — Industrial crowdsourcing’, 
Open Innovation 2.0 — Yearbook 2015, 2015.

[4]  de Langen, F. and van den Bosch, H., ‘Massive open 
online courses: disruptive innovations or disturbing 
inventions?’, Open Learning, 2013.

[5]  Mendizabal Galder, A., Nuño-Solinis, R. and Zaballa, 
G., ‘HOBE+, a case study: a virtual community of practice 
to support innovation in primary care in Basque public 
health service’, BMC Family Practice, 2013.

[6]  Sharples, M., McAndrew, P., Weller, M., Ferguson, 
R., FitzGerald, E., Hirst, T. et al., Innovating pedagogy 
2013, Open University Innovation Report 2, The Open 
University, 2013.

ENGAGEMENT PLATFORMS AND BUSINESS MODELLING IN OPEN INNOVATION 2.0 ENVIRONMENT48

[7]  Kettunen, J., Kairisto‐Mertanen, L. and Penttilä, T., 
‘Innovation pedagogy and desired learning outcomes in 
higher education’, On the Horizon, 2013.

[8]  Borisov, B., The Bulgarian Roma in Helsinki, Diaconia 
University of Applied Sciences, 2013 — www.theseus.fi

[9]  Khatiwada, P., Social entrepreneurship as an 
approach to community development, Diaconia 
University of Applied Sciences, 2014 — www.theseus.fi

[10]  Kinnunen, L., Using cooperation forums in 
developing a culture- and gender-sensitive integration 
path, Diaconia University of Applied Sciences, 2014 — 
www.theseus.fi

[11]  de Oliveira Fernandes, T., Team sports, martial arts 
and combat sports as preventive social work, Diaconia 
University of Applied Sciences, 2014 — www.theseus.fi

[12]  Wainaina, B., Quality of prenatal care at Baraton 
maternal child clinic, Diaconia University of Applied 
Sciences, 2015 — www.theseus.fi

[13]  Alavaikko, M., ‘Blogi-pohjaisen verkkojulkaisun 
käyttö ammattikorkeakouluopetuksessa’, 
Hankekirjoittaminen Välineitä hanketoimintaan ja 
opinnäytetyöhön, Haaga-Helia, 2010.

Contact

Mika Alavaikko
Master of social science, 
lecturer in social sciences
Diaconia University of Applied 
Sciences Finland
mika.alavaikko@diak.fi

OPEN INNOVATION YEARBOOK 2016CHAPTER II

Innovation ecosystems 
and living labs challenged 
by Open Innovation 2.0

When large companies build ecosystems, should small 
companies join? A role for open innovation

Abstract

The rise of the open innovation paradigm has encouraged the creation of innovation networks (ecosystems) 
involving a mix of partners: universities, research laboratories, start-up companies, small and medium-
sized enterprises (SMEs), multinationals and governments. Physical proximity is an essential driver of open 
innovation effectiveness. It enables the exchange of ideas and inside/outside exploitation of knowledge and 
resources. This paper investigates how some large companies invested in key relationships with external 
innovation partners through the creation and the orchestration of open ecosystems (e.g. open research 
campuses). By contrast, small companies cannot afford to create and orchestrate their own local research 
ecosystem, but they do have the option to join or co-locate within existing ecosystems. This paper draws 
lessons from two of 13 case studies we collected, and compares and contrasts the experience of ecosystem 
builders and ecosystem joiners.

Introduction

Innovation ecosystem often refers to the combin ation of policies, ideas, institutions and regulations 
that shape the innovation framework of the European Union. In this paper, we specifically refer to the 
local physical ecosystem that surrounds in novators. One of the EU’s targets is to improve competitiveness, 
increase employment and promote sustainable growth [1]. Innovation policies are seen as essential tools 
to fulfil these targets; however, to make innovation policies work effectively, an interactive system for value 
creation involving EU institutions, governments, firms and society at large needs to be promoted.

In this context, open innovation could help creating the optimal synergies necessary to prompt the shift 
from a traditional model of innovation — based on linear and vertically integrated research and develop-
ment (R & D) — towards a more complex innovation system — based on interactions and knowledge flows. 
The innovation models that companies deploy affect the competiveness of innov ation investments and, in 
general, the outcome.

The role of open innovation has been recently widely studied for both business and societal impact [2]. 
A prerogative of open innovation is the inclusion of different actors in innovation development; such as 
universities, industries, governments and civil societies recalling the quadruple helix innovation system [3].

Scholars generally agree that open innovation strategies (OIS) advance the exchange and integration of 
knowledge beyond the boundaries where it originates. The physical proximity of companies at different 
stages of the innovation process enables these companies to cooperate and share their scientific, techno-
logical and market knowledge to help the innovation process. Open innovation strategies encourage the 
improvement of technological capabilities within an ecosystem and also expand an ecosystem to reach 
a pareto superior outcome.

This process requires multiple players to implement OIS and requires these participants to apply mecha-
nisms to distribute their spillovers. Only with cooperative implementation and incentive alignment can 
these participants reach a win-win scenario. This is particularly true in the case of interactions in open 
environments between large and small companies.

50

Open innovation in SMEs and large firms
Open innovation may encounter different obstacles 
and have different impacts when implemented by 
large firms or by SMEs. In general, large firms are 
thought to be more effective when implementing 
OIS as they are better positioned to orchestrate 
research partnerships and can exercise more power 
in (i) setting the agenda of large consortia; (ii) iden-
tifying clear benefits for partners; and (iii) boost-
ing and spreading the OIS attitude throughout the 
industry [4]. Furthermore, large companies are more 
likely  to  give  a  central  role  to  human  resources 
management in order to achieve OIS goals and to 
adopt a long-term perspective, focusing on both the 
short-term benefits of technology alliances and the 
future objectives. Large companies may, however, 
face  substantial  managerial  challenges  to  keep 
complex OIS under control and reap the benefits 
while ensuring business continuity.

On the opposite side, SMEs, given their structure and 
organisation, might lack the managerial and techni-
cal skill to successfully implement OIS. In particu-
lar, structural limitations (the so-called liability of 
smallness), such as the lack of financial resources, 
low market influence, less formalised R & D pro -
cedures, small innovation portfolio and shortness 
of ability in R & D planning and management with 
respect to large firms constituting an obstacle for 
the  implementation  of  OIS.  Moreover,  the  exist-
ence of less developed internal capabilities (e.g. the 
capabilities necessary to transform inventions into 
innovative products and processes) and the absence 
of a multidisciplinary competence base may lead 
SMEs to perform rather unstructured approaches 
in  the  organisation  of  the  innovation  processes 
with respect to large firms [5]. On the other hand, 
the lighter structure of SMEs increases their abil-
ity to fast reacting, to changing environment and to 
quickly adapting to new business models.

Taking into account these structural differences, 
the implementation of OIS in SMEs may prove to 
be beneficial and could help to overcome the lim-
itation related to their size. In this perspective, the 
full integration of SMEs in open ecosystems set by 
large firms could come as an opportunity for SMEs.

In  particular,  innovation  partnership  with  large 
firms can allow SMEs to access external knowledge 
to develop new technologies, explore new business 
ideas and commercialise new products. An open 
ecosystem can provide SMEs with financial support, 
protection from competitors through the enforce-
ment  of  intellectual  property  (i.e.  appropriation 
strategies), access to complementary assets such 
as  production  facilities,  complementary  market 
knowledge and new distribution channels (i.e. busi-
ness model innovation).

On  the  other  side,  collaboration  between  large 
firms  and  SMEs  could  develop  into  the  depend-
ence of SMEs on large companies to generate value 
from their technologies. This strategic dependence 
together with SMEs’ limited ability to profit from 
their intellectual property may raise issues of tech-
nology and value appropriability. SMEs that collab-
orate with large companies may become locked in. 
In other words, the profitability of an SME that col-
laborates and/or licenses its technology to a large 
company  may  depend,  to  a  large  extent,  on  the 
strategic decisions of the latter.

In light of this, for open innovation to succeed it 
is important to create an ecosystem able to grant 
benefits to both SMEs and large firms.

The following conversation rests upon case studies 
collected for a larger study entitled ‘European in-
novation policies for the digital shift’ [3]. The follow-
ing paper discusses two of these case studies in de-
tail: (i) Royal Philips of the Netherlands (Philips) as 
an example of a large company that created its own 
ecosystem (an open research campus) in order to 
evolve from a closed R & D setting to a more open 
one; (ii) Primo1D, an SME born within the ecosys-
tem of a large entity. Primo1D benefited from being 
part of a larger ecosystem before it could develop 
its own. Open innovation allowed for both of these 
experiences to ever occur and be successful.

The case of Philips
Philips  epitomises  the  open  innovation  principle 
because of the way it fully embraced the open in-
novation  paradigm  since  its  inception.  As  such, 
Philips has been one of the most studied open in-
novation implementer [6].

Since 2003, Philips has adopted an open innova-
tion  strategy  and  opened  its  High  Tech  Campus 
Eindhoven to external companies [7]: the Philips 
research lab literally and figuratively tore down its 
walls to other technological companies, universities, 
research institutions and talents. Philips describes 
this move as part of an evolution from a closed 
innovation approach to the establishment of dif-
ferent partnerships to an open innovation model of 
strategic joint research programmes [8].

Companies came to use the facilities but also to 
be close to one of the largest Dutch multination-
als. Beyond private actors, Philips attracted public 
actors and helped create the Holst Centre, an inde-
pendent open innovation R & D centre and a Bel-
gian–Dutch partnership on the Eindhoven campus 
which now encompasses over 160 employees [9].

Philips has proactively orchestrated these changes 
and put itself at the centre of these interactions.

OPEN INNOVATION YEARBOOK 201651

Figure 1: Actions taken by Philips

Invite
companies

Invite
governments

Open its
research
campus

Involve
universities

Incubate and
accelerate
companies

A research programme manager at Philips respon-
sible for public–private partnership and Ph.D. and 
European projects stated:

‘Open innovation for Philips meant open innovation 
in the research complex, involving SMEs, spin-offs 
and suppliers connected to the company’ [10].

While  open  innovation  does  not  require  a  local 
ecosystem, the case of Philips suggests that geo-
graphic proximity plays an important role for better 
relationships and allows for direct communication. 
Having a physical campus has undeniably helped 
Philips in their application of open innovation and, 
in particular, to benefit from results of the activities 
shared among partners.

Open innovation is helping Philips in the present but 
also for the future. Specifically, Philips has opened 
its research campus to universities in what they see 
as a win-win relationship. Philips created Ph.D. pro-
grammes where students would use the facilities 
and learn from Philips staff, and in return Philips 
could  train  ‘people  with  skills  and  abilities  that 
Philips needs’ in the hope of ‘hiring [them] after the 
four years of the programmes.’ This strategy put 
a strong emphasis on the attraction and retention 
of talented individuals.

Primo1D
Primo1D is a French start-up that was born and 
incubated on the Grenoble research campus of the 
Commissariat à l’énergie atomique et aux énergies 
alternatives (CEA). Central to its innovation devel-
opment  was  the  use  of  the  CEA  Laboratory  for 
Electronics and Information Technology (CEA-Leti) 

[11]. CEA-Leti is one part of a larger research cam-
pus, the Minatec Technology Campus [12]. Minatec 
boasts  10 000 m 2  of  clean  rooms,  initially  cost 
close  to  EUR  200  million  [13]  and  has  already 
received additional assets upward of EUR 150 mil-
lion [14].

As a CEA employee, one of the Primo1D founders 
created this new company as a technology spin-off 
of CEA in order to commercialise the technology 
outside the research ecosystem. Primo1D has an 
exclusive licence on the technology developed and 
patented inside CEA.

Primo1D benefited from continuous access to the 
R  &  D  and management department of a  larger 
entity. In exchange, CEA took 15 % of the spin-off 
share and Primo1D also pays the intellectual prop-
erty licence through a mix of fixed fees and royal-
ties on the future turnovers.

Since  its  inception,  Primo1D  partnered  in  an  EU 
framework programme entitled the platform for 
advanced smart textile applications (PASTA) pro-
ject.  The  PASTA  project  has  16  other  members 
and extended Primo1D’s network beyond CEA and 
Minatec [15].

On the one hand, opening up to its local ecosystem 
and participating in the EU framework programme 
allowed Primo1D to refine its technological cap-
abilities;  on  the  other  hand,  its  interaction  with 
different open ecosystems (such as Techtera Lyon 
cluster specialised in textiles) enabled Primo1D to 
refine its business model by accessing key market 
knowledge.

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.052

Implications
It is difficult to go past the fact that Philips’s OIS 
evolved around the opening up of its research cam-
pus.  Opening  its  campus  allowed  Philips  to  pull 
other  companies —  large  and  small —  into  the 
same physical ecosystem. A wide range of com-
panies joined HTCE, including multinationals such 
as IBM and Intel. Others were born on the campus 
through collaborations or spin-offs.

Since this opening, Philips has decided to divest its 
interest in the research park and to become just 
‘another tenant’ to further open this environment 
[16]. Philips, however, retains the largest presence 
on campus [17]. Divesting its ownership allowed the 
campus to become even more open and welcom-
ing to companies sceptic about Philips’s intents (e.g. 
was Philips inviting them to learn its trade secret?).

SMEs do not have the scale to create, manage and 
ultimately open their own research facilities and 
they  usually  lack  the  pull  to  attract  other  com-
panies. SMEs can, however, join these types of facil-
ities and become a node in a large open innovation 
hub, as was the case of Primo1D.

Becoming a node often means giving up some free-
dom of operation. These open innovation physical 
clusters often are specialised. For instance, CEA-
Leti is a specialised research facility within a larger 
specialised research park. Picking up the correct 
open innovation clusters can lead to intricate path-
dependency  implications.  It  will  dictate  who  the 
other nodes will be, what nodes end up interacting, 
and from whom they can benefit. If an SME evolves 
across fields, it must make a difficult decision. While 
Primo1D was born within a nanotech lab, it evolved 
across  industries,  through  microelectronics  to 
‘smart’ textiles.

However, through other open innovation methods, 
these SMEs can become more than a node. Instead, 
these SMEs can build their own (virtual) ecosys-
tem and become the entry to other contributors. 
Primo1D showed that, through its framework pro-
gramme participation, it was able to join a consor-
tium of companies and universities far and away. 
Open innovation goes beyond the local ecosystem.

These clusters can also be supported by govern-
mental entities. As with the case of CEA-Leti, the 
public–private partnership has led to one of the 
largest and most modern research facilities. The 
extensive fixed cost to build these open innovation 
clusters can be led by private entities like Philips, 
but they can also be created by governmental en-
tities like CEA-Leti. With larger fixed costs, the future 
seems that it will require further cooperation. Bet-
ter understanding the intricacies of open innovation 

can  only  lead  public  and  private  participants  to 
a win-win scenario.

Conclusion
Open ecosystems may act as a stepping stone for 
SMEs  with  growth  ambitions.  They  may  provide 
the necessary tools for SMEs to outgrow their size, 
put them on a sustainable growth path and secure 
new sources of competitive advantages (e.g. iden-
tify new interesting markets to apply their compe-
tences). However, at a later stage SMEs cannot rely 
only on the ecosystem offered by other individuals 
but need to start creating their own. In the case 
of Primo1D, the SME went outside its ecosystem. 
A company, whether large or small, that wants to 
grow needs to do the same.

Large  companies  have  enough  pull  to  create 
a physical ecosystem that resembles their network-
ing ecosystem. SMEs cannot create this physical 
environment; to be close to other members of their 
ecosystem, they must rely on other means such as 
virtual meetings and consortia.

From our case studies, open innovation principles 
offer some guidance on how to create a valuable 
ecosystem. First, companies ought to focus their 
efforts on their ecosystem. If they develop tech-
nologies  that  are  not  central  to  their  business 
model,  they  may  benefit  from  licensing  out  the 
ideas; or they may develop a new business model 
to accommodate this new technology and identify 
new avenues for sustainable future growth. Having 
an ecosystem where a company can safely share 
their ideas and advances can help them decide how 
to exploit unused (non-core) technologies through 
open business models.

Second, companies ought to find ways to benefit 
from their ecosystem. Companies need profits to 
survive. Therefore, appropriability inside ecosys-
tems is an issue both for SMEs and for large com-
panies.  Intellectual  property  protections  allow 
companies  to  monetise  some  of  the  ideas  they 
give away and send outside their own value chain. 
Selecting an ecosystem and its members becomes 
crucial: even with the correct protection, enforcing 
its right can be costly and counterproductive, which 
lead some companies to rely on trade secrets; hav-
ing trustee ecosystem partners avoids having to 
wonder about these protections.

Third, companies ought to give and take. Creating 
an ecosystem around itself does not signify that the 
company must only receive information. Instead, 
open innovation functions better when the nodes 
of the ecosystem actively participate. For instance, 
lately the focus has been on user involvement: their 
involvement means that they recognise the creation 

OPEN INNOVATION YEARBOOK 201653

as their own and are more likely to adopt it. Key 
challenges for OI2 are (1) the efficient inclusion of 
users to ecosystems in order to exchange relevant 
ideas, knowledge and technologies; and (2) to iden-
tify the right appropriation mechanisms that ensure 
return on investments and keep users engaged.

For a full analysis of the 13 case studies, refer to 
the forthcoming Euripidis report.

References
[1]  Priorities of the European Commission — http://
ec.europa.eu/priorities/index_en.htm

[2]  See, for example, Gabison, G. A. and Pesole, A., 
An overview of models of distributed innovation: open 
innovation, user innovation and social innovation, 
European Commission, 2015.

[3]  Curley, M. and Salmelin, B., Open Innovation 2.0: 
a new paradigm, Open Innovation Strategy and Policy 
Group, 2013 — http://ec.europa.eu/information_society/
newsroom/cf/dae/document.cfm?doc_id=2182

[4]  This paper draws lessons from 13 case studies 
gathered for the European innovation policies for 
the digital shift project, which is jointly funded by DG 
Communications, Networks, Content and Technology 
and Joint Research Council (JRC) Institute for 
Prospective Technological Studies (IPTS) of the European 
Commission. IPTS is one of the seven research institutes 
of the European Commission’s JRC. For more information 
and the complete list of cases, please refer to our 
webpage: http://is.jrc.ec.europa.eu/pages/ISG/EURIPIDIS/
EURIPIDIS.index.html

[5]  Di Minin, A., Marullo, C. and Piccaluga, A., 
‘Heterogeneous determinants of SMEs growth. 
A comparative look at open, closed and user-led 
innovation strategies in technology-based firms’, 1st 
World Open Innovation Conference, 2014.

[6]  See, for example, Chesbrough, H. W. and Garman, 
A. R., ‘Use open innovation to cope in a downturn’, 
Harvard Business Review, 2009; Viskari, S., Salmi, P. and 
Torkkeli, M., (2007). ‘Implementation of open innovation 
paradigm — Cases: Cisco Systems, DuPont, IBM, Intel, 
Lucent, P&G, Philips and Sun Microsystems’, Research 
Report, Lappeenranta University of Technology, 2007.

[7]  Philips website, ‘Our history’ — http://www.research.
philips.com/about/history.html

[8]  van den Bisen, J., ‘Open innovation’, Philips Research, 
Business Symposium ‘Open innovation in global 
networks’, 2008 — http://www.oecd.org/innovation/
inno/40206366.pdf; Wolf, R. M., ‘The future of 
innovation, a Philips research perspective’, Interpleader 
Conference, 2010 — http://www.interleader.cz/Portals/1/

Open %20Innovation %20Philips %20Research %20
(Praag, %20Sept %202010).pdf

[9] Holst Centre — https://www.tno.nl/en/collaboration/
expertise/technical-sciences/holst-centre/

[10]  All quotes can be found in the full report. See 
note 3.

[11]  Primo1D — http://primo1d.com/applications/
general/

[12]  Micro- and nanotechnologies: Minatec, Alliance 
Crolles 2, Biochips — http://www.cea.fr/english-portal/
technologies/micro-and-nanotechnologies-minatec-
alliance-c; Minatec — http://www.minatec.org/en/
minatec

[13]  Mennessier, M., ‘Minatec: Grenoble parie sur 
les nanotechnologies’, Le Figaro, 2006 — http://
www.lefigaro.fr/sciences/2006/06/02/01008-
20060602ARTFIG90202-minatec_grenoble_parie_sur_
les_nanotechnologies.php

[14]  Minatec, ‘150 millions d’euros de 
nouveaux bâtiments pour Minatec’ — http://
www.minatec.org/vie-de-campus/minanews/
breve/150-millions-deuros-nouveaux-batiments-minatec

[15]  PASTA project, ‘The partners of the consortium’ — 
https://projects.imec.be/pasta/node/17

[16]  High Tech Campus Eindhoven, ‘Campus history’ — 
http://www.hightechcampus.com/who-we-are/
campus-history

[17]  Philips Research Eindhoven — http://www.research.
philips.com/locations/eindhoven.html

Contact

Garry A. Gabison
Research fellow
Institute for Prospective Technological Studies
garry.gabison@ec.europa.eu

Annarosa Pesole
Research fellow
Institute for Prospective Technological Studies
annarosa.pesole@ec.europa.eu

Alberto Di Minin
Associate professor
Scuola Superiore Sant’Anna
a.diminin@sssup.it

Cristina Marullo
Ph.D. candidate
Scuola Superiore Sant’Anna
c.marullo@sssup.it

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.054

Open Innovation 2.0 and the digital single market

Abstract

To write this article I was inspired by the feedback to my recent blog post: ‘Open Innovation 2.0 (OI2) for 
future cities’ [1] and my professional visits to different stakeholders representing government, business, 
research, SMEs and citizens promoting and expanding the Open Innovation Strategy and Policy Group’s 
(OISPG) [2] activities at a global level, in particular my visit to CGI Group, Inc. in Montreal, Canada, and 
meeting regional government and other stakeholders. The responses I received on the OI2 vision I saw 
as a timely alarm to apply the OI2 approaches into the real world.

In this article I elaborate on the establishment of an effective OI2 ecosystem and scaling it up from 
a city level into a regional level and beyond. I also discuss arguments and analysis of OI2 considering 
the ‘Think big, start small, accelerate fast’ approach. Finally, I explain one of the ten EU Commission’s 
priorities, digital single market (DSM), and how combining OI2 approaches into it can contribute in mul-
tiplying the social and economic values for all stakeholders involved.

Introduction

Recently I published a blog post ‘Open Innovation 2.0 (OI2) for future cities’ [1]. The text was targeted 
to the business readers, which is usually the most challenging participant group in the OI2 ecosystem 
in terms of accepting and understanding the direct business values of OI2. To my surprise, I got a lot of 
feedback on my blog post, most of which expressing high interest in the topic as potential value propo-
sition to clients, asking clarifications on specific details of how it works, even making appointments with 
me to better understand how we can incorporate OI2 into industrial or business strat egies and how the 
stakeholders can gain maximum value and tangible results.

I also had a professional visit to the CGI Group, Inc. head office in Canada (Montreal, Quebec) to contrib-
ute to a smart cities high-level conference organised by Les affaires [3] where I introduced the European 
Commission’s digital agenda, smart cities’ programmes, Horizon 2020, public–private people partner-
ship (PPPP) and the OISPG’s activities as ways of supporting the operationalisation of the concepts. 
Here I had opportunities to meet different stakeholders (government officials, businesses both large and 
small, researchers and citizens) who also quickly embraced the OI2 philosophy and shared their vision 
on efficient collaboration among the stakeholders in such an ecosystem.

It was energising and exciting to receive the aforesaid feedback, which I viewed as a sign that it is now 
time to make it happen! I have been contributing in a number of innovations, including open in novation 
(OI) topics, and based on my experience the time an innovative idea comes into realisation and adoption 
by application areas and the market might take approximately 8 to 10 years. Then I looked back and 
realised that it was exactly about a decade since I had been contributing to the topic. So, is now really 
the time to put it into practice?

Then I looked back to my publications on the topic and the activities of OISPG [4] and thought about 
the right timing of turning OI2 values and approaches into tangible outcomes for all the stakeholders 
(government, businesses, academia and citizens).

So, I started to visualise the next steps and how we can make the ecosystem even more efficient and 
operational.

OI2 has drawn considerable attention in the last years, recognised by some of the world leaders [5] [6] 
and now we see growing trends to experience it in practice. This is an opportunity which we need to 
take advantage of now.

Think big, start small, accelerate fast
Referring  to  the  concluding  sentence  ‘Think  big, 
start  small,  accelerate  fast!’  in  my  paper  ‘Open 
innovation in smart cities: the rise of digital entre-
preneurs’ [7], I would like to apply this approach in 
this paper to further elaborate on OI2.

quadruple helix model where government, industry, 
academia and civil participants work together to 
co-create the future and drive structural changes 
far beyond the scope of what any one organisation 
or person could do alone. We take this as our vision, 
big thinking, and see how we can achieve it.

Let us start with ‘think big’. Thinking big can be 
considered as the core of OI2 itself laying in the 

Now let us see what ‘start small’ means in this 
context.  There  can  be  several  answers  to  this. 

OPEN INNOVATION YEARBOOK 201655

However, I suggest starting OI2 approaches in a city 
context. I perceive a city as a small environment 
and, therefore, a small element in the process. If 
we understand the challenges of OI2 in a city con-
text  and  are  able  to  identify  ways  to  create  an 
efficient ecosystem in a city environment, then we 
will be able to replicate the successful methods in 
a regional level and beyond.

Finally, ‘accelerate fast’, which in this context I sug-
gest understanding the following: we need to be able 
to rapidly scale up the effective approaches of OI2 
from a city to regions, from regions to countries, 
from countries to the European Union and beyond. 
The speed is critically important nowadays because 
we are living a permanent digital revolution and digi-
tal transformation is happening very fast. If we are 
slow, we will miss considerable opportunities and we 
will fail in achieving our big thinking objectives.

Figure 1: Visualising the term ‘accelerate fast’

What is OI2 for future cities?
During  the  last  years  several  studies  have  sug-
gested methods for smart, sustainable cities and 
citizen collaboration with the goal of social benefit. 
Leading companies have offered ways to implement 
different sustainable city or regions solutions with 
the aim of gaining maximum value for all stake-
holders involved. Engaging citizens in this process 
is another challenge and, to date, there is no clear 
method for effectively engaging citizens in the OI 
process and using social capital as a key factor.

Let us try to understand what OI2 is for stakehold-
ers, for future cities and from there we can zoom 
into regions and even further.

The future cities vision is about the effective inte-
gration of physical, digital and human systems to 
deliver a sustainable, prosperous and inclusive life 
for citizens. OI2 for cities is about extensive col-
laboration among local government, businesses, 
researchers and citizens — where all participants 
jointly create the future city vision. It is about shar-
ing ideas, results and intellectual creativity to max-
imise economic and social impact.

Collaborative skills and open data, as well as shared 
ideas, values and processes: all of these are needed 
to generate a wealth of benefits for  future cities 
and their citizens.

The  future  cities  ecosystem  is  becoming  more 
complex due to evolving factors influencing each 
stakeholder group. Businesses want to make more 

money, researchers seek new scientific advance-
ments, citizens want inclusive society and a better 
life, and governments want to create a sustainable 
environment.

New  methods  are  needed  to  empower  citizen 
engagement through technology-intensive, user-
driven  services.  Moving  from  theory  to  practice 
and creating a functional OI ecosystem requires 
that such methods need to be tested in practice, 
not just studied academically. This experimentation 
should take place in cities with different attributes 
(e.g., size, geography, climate, culture, etc.) to under-
stand how to scale based on a common, truly effec-
tive and valuable representation of a future cities 
ecosystem. Involving citizens in the innovation pro-
cess will allow for rapid prototyping that can foster 
entrepreneurship, create jobs and boost sustainable 
growth.

Then  we  move  to  the  next  challenge.  Assuming 
that  we  succeeded  to  create  an  effective  future 
city ecosystem as we defined above, then we need 
to  be  able  to  replicate  the  method  in  as  many 
cities as possible to make other cities also smart 
and embrace the OI2 values, social and economic 
growth, scientific development and value (co-)cre-
ation for all.

Cities, even situated in the same country, can be 
very different by their nature, culture, diversity and 
societal capital. For instance, there is a big differ-
ence between Amsterdam and Groningen, London 
and  Preston,  Stockholm  and  Kiruna,  Milan  and 

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.056

Palermo, Helsinki and Oulu, Montreal and Calgary, 
New York City and Los Angeles, etc. Therefore, in 
order to be able to replicate an effective model for 
all cities we need to carefully analyse the common-
alities, peculiarities and eventual trends for each of 
the cities to create a model which will work for all.

citizens want a better life, and governments want 
to support well-being and sustainability and secure 
a better place for all stakeholders.

I am convinced the success of future cities requires 
these three things:

If we look into all participants in a smart city eco-
system (government, business, academia/research 
and citizens) in all types of cities, there is a com-
mon trend: businesses want to make (more) money, 
researchers  seek  novel  scientific  breakthroughs, 

1.  an effective, open innovation ecosystem;
2.  sustainability;
3.  collaboration  with  citizens  based  on  social 

capital.

Figure 2: Digital future city, citizens’ collaboration

What is OI2 for future regions?
Now let us try to zoom out from cities to regions. 
Regions consist of cities of different characteristics. 
If we extend the vision of the future cities, we can 
conclude that the future regions are about effec-
tive integration of smart cities into a more efficient 
ecosystem  containing  the  elements  of  future 
cities: physical, digital and human systems, deliv-
ering a sustainable and inclusive life for citizens. 
The role of the people participating in the process 
is again crucial.

Scaling up OI2 from cities into regions, we need to 
create a combined vision of an effective OI2 ecosys-
tem in the context of future regions. If we look only 
into the regions of the European Union, there are 
about 360 regions consisting of more than 100 000 
cities, each of them having different characteristics.

EU regional innovation must unite public, private 
and  third  sectors  and  Europe  needs  methodolo-
gies that mobilises PPPP and encourages people 
participation through user-driven OI and living labs, 

OPEN INNOVATION YEARBOOK 201657

argues Markku Markkula, the President of the Euro-
pean Committee of the Regions [8].

Agreeing with Markku Markkula and further elab-
orating the OI2 in the context of regions, in my view, 
OI2 for future regions is not only about effective 
integration of future cities vision, but also about 
collaboration, co-creation and sharing among the 
regional government, industry, researchers and citi-
zens of the region, all contributing to a creation of 
common values.

One important aspect is ‘the speed’ of integration, 
co-creation and collaboration. We must accelerate 
fast to sustain a place in the current, rapidly grow-
ing digital world, and only then can we gain leader-
ship in the global market.

OI2 for beyond the future 
cities and regions
To  continue  the  line  of  thinking  from  a  city  to 
a region, let us now try to zoom further. Each Mem-
ber State of the European Union consists of number 
of regions. From regions, if we scale up into a coun-
try level, we need to look into the meaning of OI2 
from each country perspective. For example, in The 
Netherlands there are 12 provinces (regions) with 
different characteristics and socioeconomic values. 
We need to combine them and find the common-
alities of these 12 provinces to be able to create 
efficient ecosystem. I believe that OI2 in each Mem-
ber State is about effective integration of their own 
regional  values  and  ecosystems,  together  with 
extensive collaboration, co-creation and sharing of 
ideas and values among them to create a better 
country for all stakeholders.

There are 28 states in Europe which are members 
of the European Union. Europe’s societal capital is 
unique in terms of diversity. Collaboration, co-cre-
ation and sharing values of diverse countries are 
challenging tasks. On the other hand, the maximum 
value for all stakeholders in the ecosystem can be 
earned in the multicultural and diverse environment 
as there is always another or complementary point 
of view on the same idea/solution, which will allow 
enriching  the  horizon  of  understanding  of  com-
plexity and seeing new added value. If all Member 
States extensively collaborate, co-create and share 
values  together,  then  we  can  consider  that  OI2 
has been successful. Some models and methods 
are offered within ‘Socioeconomic impact of open 

service innovation’ [9] which are useful. There is still 
much that needs to be done to properly establish 
OI2 in Europe.

OI2 and the DSM
Let us recall what OI2 means as defined by the 
OISPG  group.  OI2  is  a  new  paradigm  based  on 
a quadruple helix model where government, indus-
try, academia and civil participants work together 
to co-create the future and drive structural changes 
far beyond the scope of what any one organisation 
or person could do alone. This model also encom-
passes (citizen/)user-oriented innovation models 
to take full advantage of ideas’ cross-fertilisation 
leading to experimentation and prototyping in real-
world setting [2] [10].

In response to the global crisis of 2008, the Europe 
2020 [11] strategy was created in 2010 with the 
aim of Europe becoming a smart, sustainable and 
inclusive economy by 2020. As one of the seven pil-
lars of the Europe 2020 agenda, the digital agenda 
for Europe was created [12], which is the European 
Commission’s action plan to speed up the economic 
recovery.  The  main  objective  of  digital  agenda 
Europe is to develop a DSM [13] as a key enabler to 
reach the Europe 2020 strategy.

Why  DSM?  As  the  internet  and  digital  technolo-
gies are developing rapidly and transforming our 
world, there are online barriers which do not allow 
citizens to take maximum benefits on goods and 
services. Companies cannot expand their horizon 
of doing business, focusing only on local markets, 
businesses and governments are not able to fully 
benefit from digital tools which they need. In add-
ition, there are 28 national markets with their own 
regulations which make cross-border activities very 
complex and inefficient. The DSM aims at tearing 
down regulatory walls and moving from 28 national 
markets to a single one. However, it is moving quite 
slowly and we need to act urgently.

I strongly believe that the DSM can be achieved 
faster and in a more efficient way if the core values 
of OI2 are embraced.

On the other hand, the DSM can speed up the cre-
ation of OI2 effective ecosystems, turning Europe 
into a powerful economy, an exclusive place to live 
and work and a bearer of societal excellence.

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.058

Figure 3: New illustration of the DSM with OI2

I propose a new illustration of the DSM combined 
with OI2 approaches as shown above in Figure 3.

If  the  framework  supporting  OI2  approaches  is 
strengthened by European policymakers, I believe 
the  DSM,  combined  with  OI2  approaches,  can 
contribute in multiplying the social and economic 
values for all stakeholders involved and can create 
hundreds of thousands of new jobs, which Europe 
desperately needs today. It is time to act urgently.

References
[1]  Sargsyan, G., ‘Open Innovation 2.0 for future cities’, 
29.7.2015 —

http://www.cgi.com/en/blog/government/
open-innovation-2dot0-for-future-cities

[2]  Open Innovation Strategy and Policy 
Group — https://ec.europa.eu/digital-agenda/en/
open-innovation-strategy-and-policy-group

[3]  ‘Villes intelligentes’, Les affaires, 23.10.2015 —

[7]  Sargsyan, G., ‘Open innovation in smart cities: the 
rise of digital entrepreneurs’, Open Innovation 2.0 — 
Yearbook 2013, DG Communications Networks, Content 
and Technology, European Commission.

[8]  Markkula, M., ‘EU regional innovation must unite 
public, private and third sectors’, EU Parliament 
Magazine, 4.6.2015 —

https://www.theparliamentmagazine.eu/articles/opinion/
eu-regional-innovation-must-unite-public-private-and-
third-sectors

[9]  Sargsyan, G., ‘Socioeconomic impact of open service 
innovation’, OSI Consortium, 2011 — https://ec.europa.
eu/digital-agenda/en/news/socioeconomic-impact-open-
service-innovation-smart-20090077

[10]  Curley, M. and Salmelin, B., ‘Open Innovation 2.0: 
a new milieu’, Open Innovation 2.0 — Yearbook 2014, 
2014.

[11]  Europe 2020 — http://ec.europa.eu/europe2020/
index_en.htm

[12]  Digital agenda for Europe — https://ec.europa.eu/
digital-agenda/en

http://www.lesaffaires.com/evenements/conferences/
villes-intelligentes—2e-edition/579392

[13]  Digital single market — http://ec.europa.eu/
digital-agenda/en/digital-single-market

[4]  Service innovation yearbooks 2009-2010 and 2010-
2011; Open innovation yearbooks 2012 and 2013; Open 
Innovation 2.0 yearbooks 2013, 2014 and 2015, OISPG 
publications, European Commission. In all yearbooks 
Sargsyan has individual or joint papers on (open) 
innovation.

[5]  Kroes, N., Vice-President of the European 
Commission responsible for the digital agenda, 
‘Unlocking the digital future though open innovation’, 
speech during the 4th pan-European Intellectual 
Property Summit.

[6]  Obama, B., ‘A strategy for American innovation: 
driving towards sustainable growth and quality jobs’, 
Economic report from the White House, Washington, 
2009.

Contact 

Dr Gohar Sargsyan, MBA
Partner, ICT Innovation Lead
CGI Group Inc.
OISPG member
gohar.sargsyan@cgi.com

OPEN INNOVATION YEARBOOK 201659

Power of user communities affecting decision-making in 
innovation ecosystems

Abstract
Achieving success in a lot of businesses requires more than simply telling everyone about the new 
way that things are going to be done. Acceptance of change — processes, services, working relation-
ships, policies and more — can be accelerated across the organisation through the real-time sharing 
of experiences. Networking and collaboration technologies are extremely effective ways of bringing 
experts together to perform new processes and to share experiences — both the success stories and 
the possible setbacks. Citizens, also business stakeholders, with common interests or related roles can 
form communities to learn from and support one another. Social media can also help in cases where 
creating a more collaborative culture is one of the major objectives of the change management. The 
subject is about the crowd of user communities that affects decision-making in innovation ecosystems.

Creation of strong users’ community 
culture via social media
The online collaboration and networking platforms 
are empowering experts, customers and partners to 
be active participants in global terms. New business 
models should be created based on collaboration 
and networking platforms where all engaged stake-
holders can participate in the creation of final prod-
ucts or services [1]. Crowdsourcing of knowledge 
based on Social Media Technologies (SMTs) can be 
the future of creating successful companies with 
a large share at the market due to the co-develop-
ment of ideas co-creation of products/services. Col-
laborative culture incorporated into business is one 
of the basic characteristics that determine the suc-
cessful positioning of the company at the market.

USTRANSCOM, a company from the United States, 
has launched several social media initiatives includ-
ing an executive blog and a Q & A blog hosted on 
the command’s intranet, as well as a public pres-
ence on Facebook and Twitter. The executive blog 
(which has been recognised by the United States 
Department of Defence as a best practice) enables 
executives to hear from staff directly, without hav-
ing messages filtered through intermediate man-
agement levels. These social media tools — which 
quickly  generated  more  than  5  million  impres-
sions — have flattened the organisational hierar-
chy and driven positive corporate culture shifts, as 
measured by an annual staff survey.

Figure 1: Crowd of the users’ community [7]

A  critical  issue  for  ecosystems  that  should  be 
addressed is trust building. All actors involved in 
the communication should be secured via suitable 
social media platforms [2]. This would require dif-
ferent rules for social platforms in the future. There 
is a need for researchers to elaborate more on the 
issue of providing safe ecosystems to address the 
needs of all participants in the communication pro-
cess. Trust is the precondition to build an effective 
working environment that can contribute to suc-
cessful business projects.

Informal communication is also one of the means for 
creating a successful business. Networks of profes-
sionals sharing information online should be ensured 
to  have  stable  platforms  that  work  successfully. 
Informal communication among experts should be 
supported by various online tools [2]. Cross-discip-
linary communication is also very important; per-
sonal or profiled contacts from different fields shar-
ing their knowledge and experience via SMTs could be 
the starting point for many new ideas that improve 
state-of-the-art science. At a later phase, projects in 

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.060

real-term settings could develop. Such environments 
should be created by the SMTs. Social media tools 
provide an effective communications medium — for 
the core change programme teams and across the 
organisation as a whole—as a large-scale change 
initiative proceeds. In addition, by monitoring and 
participating  in  online  discussions,  managers  can 
more readily see where any misunderstandings exist 
across  the  enterprise  and  take  steps  to  address 
them. For example, one global resources company 
recently established a presence on Yammer, a secure 
and enterprise-strength social network that enables 
co-workers to communicate and share information 
with one another. Seventy per cent of the company’s 
team members signed up for Yammer after its ini-
tial launch and 25 groups were created to discuss 
work-related issues. Today, about 2 000 messages 
are posted each month.

Team leaders’ presence in social media-based col-
laboration  platforms  is  essential.  Collaboration 
tools can actually undermine change effectiveness 
if they merely cause confusion and discontent to 
multiply across social networking sites. Manage-
ment must establish a mechanism for delivering 
the ‘voice of truth’ — an authoritative, trusted and 
believable source of information. The input should 
be easy to use, contribute to and trace if being used 
as part of future innovation. When there is a busi-
ness idea at the beginning, team leaders should 
ensure that there is the encouragement in the form 
of a reward already at the start of the process of 
innovation. This idea reinforces that social media 
can be used by employees not only to voice ideas 
and concerns but also to get accurate and credible 
answers regarding the company’s change effort.

Effective two-way communication is very important 
for companies to get feedback from the employ-
ees and consumers so that it can help improving 
business processes or end-products and services. 
Involvement of users from the beginning in the pro-
cess of product/service development creates new 
market in order to satisfy users’ needs. The quad-
ruple helix open innovation model is showing the 
importance of engaging users in order to make the 
competitive advantage of companies at the market.

Improvement of community 
engagement via the OI2 paradigm
One of the critical success factors for managing 
large-scale change in the organisation is engaging 
employees in the change — helping them to feel 
ownership in the initiative and let them use their 
energy to resolve issues and advance the business. 

Collaboration solutions allow information to flow 
in multiple directions rather than just top-down. 
For example, using wikis and microblogs — appli-
cations for sharing short bursts of information in 
Twitter-like fashion — organisations can ‘crowd-
source’ ideas and involve employees more directly 
in the change programme. Organisations can build 
greater internal loyalty by actively soliciting con-
tinuous feedback on issues related to the change. 
One United States bank initiated a major change 
programme to improve the customer experience as 
a means of gaining market share. The bank lever-
aged a crowdsourcing tool to tap into its workforce 
for ideas about how to improve customer service. 
Therefore, open engagement platforms are critical 
enablers for the OI2 paradigm, beyond the usual 
social media. It is evident especially in affordable 
prototyping and scale-up, e.g. the mobile applica-
tion development. The key to success is providing 
such open engagement platforms that foster in-
novation ecosystems for creating jobs and growth. 
In the first use of the tool, more than 250 employ-
ees submitted 50 separate ideas resulting in seven 
high-quality innovations for the company — many 
of which resulted in programmes that have gener-
ated value for the bank. There is the strong link of 
users’ community engagement and the success of 
the OI2 paradigm applied to new business models. 
It should be ensured that various channels of com-
munication stay open as well as that of the OI en-
vironment that fosters creation of jobs and growth.

Creating OI culture
OI is a process designed to accelerate innovation 
through collaboration [3]. Traditionally companies 
create  value  by  internal  available  resources.  OI 
involves external partners to the process of devel-
oping  new  business  opportunities.  Products  and 
services created in an OI environment better fit the 
customer’s needs since they are engaged in shaping 
the outcome of the idea.

The  OI  environment  represents  the  most  suit-
able ecosystem for creating value at the market. 
It is a challenge for traditional companies to cre-
ate them because moving from something already 
established and familiar to the new concept always 
represents  stress  to  the  people.  The  success  is 
dependent on all engaged stakeholders and there-
fore  the  special  attention  should  be  paid  to  the 
people whose creativity, skills and knowledge cre-
ate the core of every successful market realisa-
tion. Thus the OI environment has to be stimulat-
ing, easy to use, challenging and fun for the people 
involved. More on OI in [4], [5], [6].

OPEN INNOVATION YEARBOOK 201661

Figure 2: The relation between community and budget [8]

The  following  are  some  of  the  issues  that  need 
to  be  considered  carefully  when  creating  OI 
environment.

•  Overcoming the scepticism of the employees 
if new OI environment will really work. Change 
managers together with HR services should take 
care of this issue using available motivational 
tools. Motivation is a precondition for success.
•  Engaging all stakeholders in creating value at 
the market through products or services that 
are important for all of them. Creating the win-
win situation is very important as an incentive 
for people to really try to put the effort, know-
ledge and passion for success into the business.
•  Being careful about intellectual property right 
(IPR) issues at the early stages. As seen from 
various  innovation  projects,  IPR  issues  are 
nowadays more in compliance with traditional 
linear innovation [11]. Rules should be changed 
regarding  IPR,  especially  about  fair  share  in 
crowdsourcing  or  co-creation.  Since  IPRs  are 
important in creating open engagement plat-
forms  and  keeping  software  and  data  open, 
a new approach on IPR issues is necessary on 
data sharing, creative commons, etc.

•  Stimulating creativity, experimentation and pro-
totyping creating the competition environment 
where best ideas are realised into projects. OI 
competitions are highly important to show to 
the engaged that only the best ideas with the 
strongest impact to the society will be realised 
into the project. The same business conditions 
for all create the message that it is worth trying 
to get the optimal business position for achiev-
ing the targets.

•  Networking  and  collaboration  should  be 
strongly present in the OI environment; thus, 
stimulating  communication  and  sharing  of 

knowledge should be one of the priorities. Now-
adays success in entrepreneurship is desirable; 
if it is not connected with users, buyers, sup-
pliers,  competitors  and  others  than  it  fades 
away. Long-term success without networking 
and collaboration is impossible.

• 

•  Stimulating  people  to  create  and  use  plat-
forms where trials, experimentations and pro-
totyping with new products and services are 
possible without any big loss if the attempt is 
unsuccessful. Courage is a crucial component 
that converts potential success into a real one. 
Keeping  up  the  enthusiasm  from  the  begin-
ning to the very end of a project is important. 
Engagement to deliver results throughout the 
whole process (even when failures occur) is the 
key to success. The same goes for social plat-
forms and community engagement to participa-
tory innovation.
Fostering result-oriented, innovative and crea-
tive thinking which creates new kinds of entre-
preneurship. Traditional business ecosystems 
and rules of current entrepreneurship should 
be upgraded to more flexible, stimulating plat-
forms where entrepreneurs should more easily 
change the form of organising a business or 
create the new form themselves.
Taking  initiatives  in  the  area  of  law.  Current 
legal economic framework is too narrow to be 
able to address upcoming challenges of how 
the EU should enhance its competitiveness. Pro-
posing initiatives at national level and involving 
different think tanks and specialised groups to 
suggest the guidelines to the European Com-
mission  in  order  to  make  directives  on  new 
entrepreneurship.  Also  proposing  an  experi-
mental approach for policymaking; then it could 
be seen when and where policy measures are 
necessary.

• 

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.062

Prototyping platforms that improve 
decision-making in the OI environment
In the information society, information itself pre-
sents  the  most  important  resource  which  cre-
ates competitiveness. Knowledge society is more 
advanced  and  it  combines  information  together 
with knowledge to create value. Wisdom society 
combines  experiences  of  different  stakeholders, 
intangible assets that are necessary for success, 
knowledge and information to make value aggre-
gation at the market.

The  new  wisdom  society  ahead  of  us  demands 
different  rules  and  business  environments  that 
bridge the gap between the idea and its realisa-
tion at the market. Policymakers should create the 
business platforms where prototyping and experi-
mentation are available and easy to use. Small and 
fast failures and errors should be allowed with the 
idea that eventually they lead to big success. Risk 
should be reduced to minimal, unlike the traditional 
approach where one of the biggest obstacles was 
a high level of risk to the entrepreneur property or 
rights. Writing the apps and putting them in the 
platform to see if they work in the market should 
create the comfortable OI environment where inno-
vation is in the hotspot of making the entrepreneur-
ship successful.

The collective awareness platforms (CAPS) for sus-
tainability and social innovation are information 
and communications technology (ICT) systems lev-
eraging the emerging ‘network effect’ by combin-
ing open online social media, distributed knowledge 
creation and data from real environments (Internet 
of Things) in order to create new forms of social 
innovation. They are expected to support environ-
mentally aware grassroots processes and practices 
to share knowledge, to achieve changes in lifestyle, 
production and consumption patterns, and to set 
up  more  participatory  democratic  processes  [9]. 
These kinds of platforms should be modified and 
upgraded to include a permissible degree of errors. 
Entrepreneurs should have the freedom to use eas-
ily accessible open engagement platforms as the 
hotspot for their applications and projects to see 
if it really works at the market. Social innovation 
leads to meeting social needs of different kinds: 
education, health, etc.

Entrepreneurship by user 
communities of the future
Young people want to actively participate in the 
society. They want to help in developing different 
perspectives of the society: culture, sport, educa-
tion, environment, civil protection, etc. The outcome 
of involving the young in participating in societal 

challenges is raising their self-confidence, acquiring 
new and diverse skills, creating identity and a better 
relationship with the society. There is a big potential 
among the young that should be stimulated in the 
right direction to foster societal growth.

ICT  as  a  significant  economy  driver  will  be  even 
more important in the future for entrepreneurship. 
ICT is playing an extraordinary role in how organ-
isations interact with their customers. It is predicted 
that the Europe 2020 strategy will follow the deep-
ening trend towards personalisation in the field of 
business [10]. Technology will have its most positive 
impact on organisations enabling managers and 
other employees to react much faster to markets 
and customers. ICT will enable widening the target 
customers base to anywhere in the world as well 
as simplifying business processes. Therefore, it is 
essential that more attention be paid to the devel-
oping ICT skills and literature among the young in 
the future. ICT will have a significantly important 
role  also  among  business-to-business  environ-
ments. Rapid growth of smart systems and devices 
will play an important role in this context. Crucial 
ICT  skills  that  successful  entrepreneurs  should 
master in the future are the following.

•  Understanding how to market, sell and manage 

customers online.

•  Mastering issues about data privacy.
•  Building and mining open data in order to create 
a value in an effective way. In order to apply the 
OI2 paradigm, certain conditions, such as open 
data, should ensure that the innovation ecosys-
tem is functioning.

It is interesting to analyse, from a psychological 
point  of  view,  enterprises  and  businesses  in  the 
future. When we are talking about Maslow’s hier-
archy  of  needs  and  humans,  we  notice  that  the 
lower level of the pyramid is connected with phys-
iological needs for food, water, sleeping, etc. The 
upper  levels  present  more  psychological  needs 
related to self-esteem, respect and self-actualisa-
tion. The lower the level is achieved, the upper tends 
to be as well. It describes the well-being of humans. 
When Maslow’s hierarchy of needs is transferred to 
companies we can see that the lower levels of the 
pyramid, such as cost revenue and customer satis-
faction, are not so difficult to achieve. The real value 
and success of the organisation are the upper lev-
els of the pyramid: innovation culture and organisa-
tional agility. These are the most important indica-
tors that determine the well-being and success of 
the company. Each successful company should have 
open, experimental and sharing innovation culture 
on what the further progress depends. Based on 

OPEN INNOVATION YEARBOOK 201663

the innovation culture, a company creates organisa-
tional agility that determines the position and the 
respect of the company in the society.

Conclusion
In fulfilling the Europe 2020 strategy’s targets, new 
kinds of entrepreneurship based on ICT change will 
have an immensely important role. Businesses are 
affected by technological change and new ways 
of entrepreneurship will require new sets of busi-
ness  skills.  A  more  virtual  working  environment 
could reduce teamworking which is, traditionally, 
the most effective way of organising work. Busi-
ness  processes  and  structures  will  also  need  to 
change in order to act on the opportunities cre-
ated by technology. The human side is also very 
important, meaning that cultural change should 
be  appropriately  managed.  Human  resistance  is 
often an obstacle to the adapting new technologies 
and  ways  of  doing  businesses.  Business  leaders 
and entrepreneurs should pay attention to remove 
obstacles  from  creating  smart,  sustainable  and 
inclusive growth in Europe.

A new approach to business will consist of a mash-
up  of  societal  drivers,  value  drivers  and  ICT  en-
ablers. Open platforms provide a user-centric and 
co-creative process that provides better leaps from 
the idea to the market value. Wisdom society, along 
with its societal dimension, should be in the middle 
of policymakers’ attention, in order to create better 
platforms for new kinds of entrepreneurship. An OI 
environment with ICT-enabled drivers will foster en-
trepreneurship and reach Europe 2020 targets. New 
entrepreneurial forms are emerging based on open 
platforms and open data. Europe needs to foster 
innovation towards new business models and en-
trepreneurship, especially with its new instruments 

like Horizon 2020 and CEF research programmes. 
The power of users’ community makes the most 
successful way of creating jobs and growth in in-
novation ecosystems.

References
[1]  https://ec.europa.eu/digital-agenda/en/
open-innovation-strategy-and-policy-group

[2]  Istrat, V., ‘New entrepreneurship as challenge in 
achieving Europe 2020 targets’, 25th Bled e-conference, 
e-dependability, reliable and trustworthy e-structures, 
e-processes, e-operations and e-services for the future, 
Bled, Slovenia, 17-20.6.2012.

[3]  www.ifm.eng.cam.ac.uk/ctm/teg/openinnovation.html

[4]  http://openinnovation.berkeley.edu/what_is_oi.html

[5]  http://ec.europa.eu/research/horizon2020/
index_en.cfm

[6]  https://sites.google.com/site/openinnovationplatform/
open-innovation

[7]  http://www.crowdsourcing-blog.org/donde-esta-mi-
multitud-lecciones-aprendidas-ii/?lang=en

[8]  http://headrush.typepad.com/creating_passionate_
users/2007/03/user_community_.html

[9]  http://ec.europa.eu/information_society/activities/
collectiveawareness/index_en.htm

[10]  http://ec.europa.eu/europe2020/index_en.htm

[11]  Keynote speech of Mr Bror Salmelin from DG 
Communications Network, Content and Technology, 
European Commission, at the MIST 2015 Conference in 
Portugal.

Contact

Višnja Istrat
Rapporteur
Open Innovation Strategy and Policy Group
Visnja.istrat@gmail.com

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.064

The role of experimentation facilities in open innovation 
ecosystems for the future internet

Introduction

The future internet research and experimentation (FIRE) [1] initiative is evolving towards a dynamic, 
sustainable and large-scale European experimental infrastructure, connecting and federating exist-
ing and next generation testbeds for future internet technologies. FIRE offers wide-scale testing and 
experimentation resources demanded by competitive research organisations, industry and small and 
medium-sized enterprises (SMEs) to speed up the time-to-market for innovative technologies, services 
and solutions. Gradually, FIRE’s original focus on advanced networking technologies and service para-
digms has expanded to new areas of technological innovation, such as the Internet of Things (IoT), 
and to application domains and user environ ments such as for networked media and smart cities. 
This raises the issue of how FIRE experimental facilities could further evolve as core resources of an 
innovation ecosystem and accelerator platform for FIRE and innovation.

The research and experimentation landscape shaping the future internet is undergoing a major 
transformation. Service and application developers (including SMEs) make use of advanced network-
ing, communication and software concepts. Smart city initiatives and technology-intensive domains 
such as healthcare, manufacturing, e-government and financial services present new challenges to 
such developers. European-wide initiatives have emerged where FIRE’s experimental facilities may 
bring added value, such as advanced networking (5G public–private partnership (PPP)), big data, the 
IoT and cyber-physical systems. Traditional boundaries between facility developers, researchers and 
experimenters, and end users in vertical application domains start blurring, giving rise to experimen-
tation and innovation-based platform ecosystems which bring together a wide range of stakeholders 
to collaborate on innovation opportunities driven by future internet technologies. Correspondingly, 
the demands of experimenters and researchers serving those users and developers are changing, 
pushing for the development of new types of experimental facilities and experimentation methods 
and tools.

In this context the AmpliFIRE project [2], running from 2013-2015, has developed a future vision 
concerning the potential of FIRE’s testbed facilities and experimentally driven research for the coming 
decade. In this vision, FIRE’s federated facilities fulfil a key role within the currently evolving innovation 
ecosystem for the future internet.

The evolving role of FIRE testbeds 
and experimentation
There  have  been  considerable  changes  in  FIRE 
throughout the 7th framework programme and now 
in Horizon 2020, as a consequence of the Commis-
sion’s evolving FIRE vision and the needs and inter-
ests of the FIRE community. Originally established 
from a core of networking testbeds and aimed at 
investigating  fundamental  issues  of  networking 
infrastructure, FIRE’s mission has changed to deliver 
widely reusable facilities for the future internet com-
munity, resulting in the current emphasis on federa-
tion. Figure 1 provides an overview of testbeds par-
ticipating in the FED4FIRE federation project.

New  domains  are  coalescing  within  future  net-
works, such as the IoT, internet of services, cyber-
physical systems, big data and other areas, giving 
rise to new research and innovation challenges and 
demands to experimentation facilities. Interactions 
with communities such as smart cities, cloud com-
puting and IoT already brought new perspectives 
into FIRE’s portfolio. To some extent this is visible in 
the new work programme 2016-2017, in particular 

in relation to the IoT, where FIRE testbeds are con-
sidered  to  support  technology  validation  before 
deployment in field trials. AmpliFIRE identifies sev-
eral key trends, such as the integration of a broad 
range of systems (cloud services, wireless sensor 
networks,  content  platforms  and  mobile  users) 
within future internet systems in large-scale, highly 
heterogeneous  systems,  to  support  increasingly 
connected and networked applications. This new 
emphasis calls for looser forms of federation of 
cross-domain resources.

Whereas FIRE has become meaningful in the con-
text of the future internet and its research commu-
nity, FIRE also increasingly addresses the demand 
side of experimentation, the need to engage users 
and  to  support  innovation  processes.  This  way 
FIRE’s  evolution  must  find  a  balance  between 
coherence and fragmentation in shaping the rela-
tion between facility-building projects and research 
and  experimentation  —  and  increasingly  innov-
ation — projects. In this respect a specific develop-
ment is how FIRE is increasingly shaped by new, 
flexible demand-oriented instruments such as open 

OPEN INNOVATION YEARBOOK 201665

Figure 1: Testbeds participating to the FED4FIRE federation project (source: FED4FIRE)

calls and open access, which demonstrates how 
customer ‘pull’ is increasingly supplementing and 
balancing technology ‘push’.

• 

As  experimenter  needs  and  requirements  are 
becoming more demanding, expectations are rising 
as regards how FIRE should anticipate the needs 
and requirements from SMEs, industry, smart cities, 
and from other initiatives in the scope of future 
internet such as IoT and 5G. New types of service 
concepts, for example experimentation-as-a-ser-
vice,  aim  at  making  experimentation  more  sim-
ple, efficient, reliable, repeatable and easy to use. 
These new concepts affect the methods and tools, 
the channels for offering services to new categories 
of users, and the collaborations to be established 
with infrastructure and service partners to deliver 
the services.

Thus it is expected that FIRE will increasingly be 
shaped by demand-pull factors in the period 2015-
2020. These user demands will be based on the fol-
lowing four main trends.

ever-increasing amounts and combining data to 
generate new content.
The internet of people: people-to-people net-
working, where users will become the centre 
of internet technology — indeed the bound-
aries between systems and users will become 
increasingly blurred.

In order to contribute to these four fast-moving 
areas, the FIRE ecosystem must grow in its tech-
nical capabilities. New networking protocols must 
be introduced and managed, both at the physical 
layer where every higher wireless bandwidth tech-
nologies  are  being  offered,  and  in  the  software 
interfaces,  which  (software  defined  networks)  is 
opening up. Handling data at medium (giga to tera) 
to large (petabyte) scale is becoming a critical part 
of the applications that impact people’s lives. Min-
ing such data, combining information from sepa-
rated archives, filtering and transmitting efficiently 
are key steps in modern applications, and the inter-
net testbeds of this decade will be used to develop 
and explore these tools.

• 

• 

• 

The IoT: a global, connected network of prod-
uct tags, sensors, actuators and mobile devices 
that interact to form complex, pervasive sys-
tems that autonomously pursue shared goals 
without direct user input. A typical application 
of this trend is automated retail stock control 
systems.
The internet of services: internet/scaled service-
oriented  computing,  such  as  cloud  software 
(software as a service) or platforms (platform 
as a service).
The internet of information: sharing all types of 
media, data and content across the internet in 

Future internet systems will integrate a broad range 
of systems such as cloud services, sensor networks 
and  content  platforms  into  large-scale  hetero-
geneous systems of systems. There is a growing 
need for integration, for example the integration 
of multipurpose, multiapplication wireless sensor 
networks with large-scale data processing, analy-
sis, modelling and visualisation along with the inte-
gration of next-generation human-computer inter-
action methods. This will lead to complex large-scale 
networked  systems  that  integrate  the  four  pil-
lars:  things,  people,  content  and  services.  Com-
mon research themes include scalability solutions, 

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.066

interoperability, new software and service engineer-
ing methods, optimisation, energy awareness and 
security, privacy and trust solutions. To validate the 
research themes, federated experimented facilities 
are required that are large scale and highly het-
erogeneous. Testbeds that bridge the gap between 
infrastructure,  applications  and  users  and  allow 
the exploration of the potential of large-scale sys-
tems which are built upon advanced networks, with 
real users and in realistic environments, will be of 
considerable value. This will also require the devel-
opment  of  new  methodological  perspectives  for 
FIRE, including how to experiment and innovate in 
a framework of collaboration among researchers, 
developers and users in real-life environments.

As we emphasise a focus on ‘complex smart sys-
tems of networked infrastructures and applications’ 
within the FIRE programme, the unique and most 
valuable contribution of FIRE should be to ‘bridge’ 
and ‘accelerate’: create the testing, experimenting 
and  innovation  environment  which  enables  link-
ing networking research to business and societal 
impact. FIRE’s testbeds and experiments are tools 
to  address  research  and  innovation  in  ‘complex 
smart systems’, in different environments such as 
cities, manufacturing industry and data-intensive 
services sectors. In this way, FIRE widens its pri-
mary focus from testing and experimenting, build-
ing the facilities, tools and environments towards 
closing the gap from experiment to innovation for 
users and markets.

Positioning of FIRE
This leads to the issue of how to position FIRE in 
relation to other initiatives in the future internet 
landscape. FIRE is one among a number of initia-
tives in the future internet research and innovation 
ecosystem. FIRE seeks a synergetic and value-add-
ing relationship with other initiatives and players 
such as GÉANT/NRENs and the FI-PPP initiatives 
related to IoT and smart cities, EIT Digital, the new 
5G PPP and big data PPP initiatives, the evolving 
area  of  cyber-physical  systems,  and  others.  For 
the  future,  we  foresee  a layered  future  internet 
infrastructural and service provision model, where 
a diversity of actors gather together and ensure 
interoperability  for  their  resources  and  services 
such as provision of connectivity, access to testbed 
and experimentation facilities, offering of research 
and  experimentation  services,  business  support 
services,  and  more.  Bottom-up  experimentation 
resources are part of this, such as crowdsourced 
or  citizen/community-provided  resources.  Each 
layer  is  transparent  and  offers  interoperability. 
Research networks (NRENs) and GÉANT are provid-
ing the backbone networks and connectivity to be 
used by FIRE facilities and facilities offered by other 
providers.

FIRE’s core activity is to provide and maintain sus-
tainable, common facilities for FIRE, and to provide 
customised experimentation and research services. 
In addition, given the relevance of experimentation 
resources for innovation, and given the potential 
value and synergies which FIRE offers to other ini-
tiatives, FIRE should assume a role in supporting 
experimentally driven research and innovation of 
technological systems. For this to become a real-
ity, FIRE and other initiatives related to the future 
internet, such as 5G, should ensure sharing and 
reusing experimentation resources. FIRE should also 
consider opening up to (other) public and private 
networks, providing customised facilities and ser-
vices to a wide range of users and initiatives in both 
public and private spheres. FIRE’s core activity and 
longer-term orientation requires the ability to mod-
ernise and innovate the experimental infrastructure 
and service orientation for today’s and tomorrow’s 
innovation  demands.  Really  innovative  contribu-
tions may come from smaller, more aggressive and 
riskier projects. Large-scale European Commission 
initiatives such as the 5G PPP, big data PPP and the 
IoT should have an influence on their selection and 
justification. Early engagement and dialogue among 
concerned communities is essential to accomplish 
this goal.

Envisioning FIRE’s evolution 
into the future
For setting out a transition path from the current 
FIRE facilities towards FIRE’s role within a ‘future 
internet ecosystem’, AmpliFIRE has proposed four 
alternative future development patterns for FIRE 
which equally represents the spectrum of forces 
acting upon FIRE’s evolution:

• 

• 

• 

• 

competitive testbed as a service: FIRE as a set 
of individually competing testbeds offering their 
facilities as a pay-per-use service;
industrial cooperative: FIRE becomes a resource 
where experimental infrastructures (testbeds) 
and  future  internet  services  are  offered  by 
cooperating commercial and non-commercial 
stakeholders;
social innovation ecosystem: FIRE as a collec-
tion  of  heterogeneous,  dynamic  and  flexible 
resources offering a broad range of facilities, 
e.g.  service-based  infrastructures,  network 
infrastructure, smart city testbeds, support to 
user-centred living labs, and other;
resource-sharing collaboration: federated infra-
structures provide the next generation of test-
beds, integrating different types of infrastruc-
ture within a common architecture.

These future scenarios aim at stretching our think-
ing  about  how  FIRE  must  choose  its  operating 
points  and  desired  evolution  in  relation  to  such 
forces. Simplifying the argument, FIRE evolution 

OPEN INNOVATION YEARBOOK 201667

proceeds  along  two  dimensions.  One  dimension 
ranges  from  a  coherent,  integrated  portfolio  of 
FIRE activities on the one hand to individual, inde-
pendent projects (the traditional situation) selected 
solely for their scientific and engineering excellence 
on the other. A second dimension reflects both the 
scale of the funded projects and the size of the 
customer or end user set that future FIRE projects 
will reach out to and be visible to, ranging from sin-
gle entities to community initiatives.

Some broad lines of FIRE’s future evolution can be 
sketched as follows in Figure 2. In the short term, 
FIRE’s mission and unique value is to offer an effi-
cient  and  effective  federated  platform  of  facil-
ities as a common research and experimentation 

infrastructure related to the future internet that 
delivers innovative and customised experimenta-
tion capabilities and services not achievable in the 
commercial market. FIRE should expand its facil-
ity offers to a wider spectrum of technological in-
novations in European Commission programmes, 
e.g. in relation to smart cyber-physical systems, 
smart  networks  and  internet  architectures,  ad-
vanced cloud infrastructure and services, 5G net-
work infrastructure for the future internet, IoT and 
platforms for connected smart objects. In this role, 
FIRE  delivers  experimental  testing  facilities  and 
services at low cost, based upon federation, ex-
pertise and tool sharing, and offers all necessary 
expertise and services for experimentation on the 
future internet part of Horizon 2020.

Figure 2: FIRE evolution longer-term vision 2020

For the medium term, around 2018, FIRE’s mission 
and added value is to support the future internet 
ecosystem in building, expanding and continuously 
innovating the testing and experimenting facilities 
and tools for future internet technological innov-
ation. FIRE continuously includes novel cutting-edge 
facilities into this federation to expand its service 
portfolio, targeting a range of customer needs in 
areas  of  technological  innovation  based  on  the 
future internet. FIRE assumes a key role in offer-
ing facilities and services for 5G. In addition, FIRE 
deepens its role in experimentally driven research 
and innovation for smart cyber-physical systems, 
cloud-based systems and big data. This way FIRE 
could also support technological innovation in key 
sectors such as smart manufacturing and smart 
cities. FIRE will also include ‘opportunistic’ experi-
mentation resources, e.g. crowdsourced or citizen-/
community-provided resources.

In this time frame, FIRE establishes cutting-edge net-
worked media and possibly big data facilities rele-
vant to research and technology demands to support 
industry and the solving of societal challenges. Fed-
eration activities to support the operation of cross-
facility experimentation are continued. A follow-up 
activity of Fed4FIRE is needed which also facilitates 
coordinated open calls for cross-FIRE experimenta-
tion using multiple testbeds. Additionally, a broker 
service is provided to attract new experimenters and 
support SMEs. This period ensures that openly acces-
sible FIRE federations are aligned with 5G architec-
tures that simplify cross-domain experimentation. 
Second, via the increased amount of resources dedi-
cated to Open Calls, FIRE will create an accelerator 
functionality to support product and service innov-
ation of startups and SMEs. For this, FIRE will estab-
lish cooperation models with regional players and 
other  initiatives.  FIRE  continues  to  implement 

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.068

professional practices and establishes a legal entity 
which can engage in contracts with other players and 
supports pay-per-use usage of testbeds.

In summary, some of the key strategic objectives 
for FIRE proposed by AmpliFIRE are the following.

For the longer term, by 2020, our expectation is 
that internet infrastructures, services and applica-
tions form the backbone of connected regional and 
urban innovation ecosystems. People, SMEs and 
organisations collaborate seamlessly across bor-
ders to experiment on novel technologies, services 
and business models to boost entrepreneurship and 
new ways of value creation. In this context, FIRE’s 
mission is to become the research, development 
and innovation environment, or ‘accelerator’, within 
Europe’s  future  internet  innovation  ecosystem, 
providing the facilities for research, early testing 
and experimentation for technological innovation 
based on the future internet. FIRE, in cooperation 
with other initiatives, drives research and innov-
ation cycles for advanced internet technologies that 
enable business and societal innovations and the 
creation of new business-helping entrepreneurs to 
take novel ideas closer to market.

In this timeframe it is envisaged that FIRE continues 
to add new resources that match advanced experi-
menter  demands  (5G,  large-scale  data-oriented 
testbeds, large-scale IoT testbeds, cyber-physical 
systems) and offers services based on experimen-
tation-as-a-service.  The  services  evolve  towards 
experiment-driven innovation. More and more FIRE 
focuses  on  the  application  domain  of  innovative, 
large-scale  smart  systems.  Implementing  secure 
and  trustworthy  services  becomes  a  key  priority, 
also  to  attract  industrial  users.  Responsive  SME-
tailored open calls are implemented to attract SMEs. 
FIRE continues the accelerator activity by providing 
dedicated start-up accelerator funding. FIRE also 
takes new steps towards (partial) sustainability by 
experimenting with new funding models. Sustain-
able facilities are supported with continued minimum 
funding after the project’s lifetime. FIRE community 
has achieved a high level of professional operation. 
FIRE contributes to establishing a network of future 
internet  initiatives  which  works  towards  sharing 
resources, services, tools and knowledge and which 
is supported by the involved Commission units.

Around 2020, FIRE thus may have evolved towards 
a  core  infrastructure  for  Europe’s  open  lab  for 
future internet research, development and innov-
ation and FIRE has evolved into a technology accel-
erator within Europe’s innovation ecosystem for the 
future internet. Clearly this implies that FIRE should 
achieve a considerable level of sustainability, pos-
sibly as (part of) the core infrastructure of a thriv-
ing  platform  ecosystem  which  creates  techno-
logical innovations addressing business and societal 
challenges.

• 

• 

• 

For  2016:  to  increase  its  relevance  and 
impact  primarily  for  European-wide  technol-
ogy  research,  but  also  to  increase  its  global 
relevance.
For 2018: to create substantial business and 
societal  impact  through  addressing  techno-
logical  innovations  related  to  societal  chal-
lenges. To become a sustainable and open fed-
eration that allows experimentation on highly 
integrated future internet technologies; sup-
porting networking and cloud pillars of the net 
futures community.
For 2020: to become a research, development 
and innovation space that is attractive to both 
academic researchers, SME technology devel-
opers and industrial research and development 
(R & D) companies, with emphasis on key Euro-
pean initiatives such as 5G, big data, IoT and 
cyber-physical systems domains.

Conclusions and recommendations
FIRE has evolved into a diverse portfolio of experi-
mental facilities, increasingly federated and sup-
ported by tools, and responding to the needs and 
demands of a large scientific experimenter com-
munity. Issues that require attention include the 
sustainability of facilities after the project’s termi-
nation, the engagement of industry and SMEs, and 
the continued development of FIRE’s ecosystem to 
remain  relevant  to  changing  research  demands. 
A more strategic issue is to develop a full service 
approach addressing the gaps between ecosystem 
layers as well as integration issues that are only 
now coming up in other future internet-funded pro-
jects. A related challenge is to expand the nature of 
FIRE’s ecosystem from an offering of experimen-
tal  facilities  towards  the  creation  of  an  ecosys-
tem platform capable of attracting market parties 
from different sides that benefit from mutual and 
complementary interests. Additionally, FIRE should 
anticipate  the  shifting  focus  of  future  internet 
innovation areas towards connecting users, sen-
sor networks and heterogeneous systems, where 
data, heterogeneity and scale will determine future 
research and innovation in areas such as big data, 
5G and IoT. Such demands lead to the need for FIRE 
to focus on testbeds, experimentation and innova-
tion support in the area of ‘smart systems of net-
worked infrastructures and applications’.

To address the viewpoints identified by the FIRE 
community,  the  FIRE  initiative  should  support 
actions  that  keep  pace  with  the  changing  state 
of the art in terms of technologies and services, 
able to deal with current and evolving experiment-
er  demands.  Such  actions  must  be  based  upon 

OPEN INNOVATION YEARBOOK 201669

a co-creation strategy, interacting directly with the 
experimenters, collecting their requirements and 
uncovering potential for extensions. FIRE must also 
collaborate globally with other experimental test-
bed initiatives to align with trends and share ex-
pertise and new facilities. Where major new tech-
nologies emerge, these should be funded as early 
as possible as new experimental facilities in the 
FIRE ecosystem.

This  analysis  leads  to  some  recommendations 
regarding  the  future  direction  of  FIRE,  concisely 
summarised below.

• 

• 

• 

• 

FIRE’s  strategic  vision  for  2020  is  to  be  the 
research, development and innovation environ-
ment for the future internet, creating business 
and  societal  impact  and  addressing  societal 
challenges. Adding to FIRE’s traditional core in 
networking technologies is the shift of focus in 
moving upwards to experimenting and innovat-
ing on connected smart systems which are en-
abled by advanced networking technologies.
FIRE  must  forcefully  position  the  concept  of 
experimental testbeds driving innovation at the 
core of the experimental large-scale trials of 
other future internet initiatives and of selected 
thematic domains of Horizon 2020. Relevant 
initiatives  suitable  for  co-developing  and 
exploiting testbed resources include the 5G PPP, 
IoT large-scale pilots and e-infrastructures.
FIRE should help establish a network of open, 
shared experimental facilities and platforms 
in cooperation with other future internet ini-
tiatives. Experimental facilities should become 
easily  accessible  for  any  party  or  initiative 
developing innovative technologies, products 
and services building on future internet tech-
nologies. For this to happen, actions include the 
continuing federation of facilities to facilitate 
the sharing of tools and methods, and providing 
single access points and support cross-domain 
experimentation. Facilities should also employ 
recognised  global  standards.  At  the  level  of 
facilities,  open  access  structures  should  be 
implemented  as  a fundamental  requirement 
for any FIRE facility. To extend open facilities 
beyond FIRE, for example with 5G PPP or GÉANT 
and NRENs, cooperation opportunities can be 
grounded in clear value propositions, for exam-
ple based on sharing technologies and experi-
ment resources.
FIRE should establish ‘technology accelerator’ 
functionality,  by  itself  or  in  cooperation  with 
other  future  internet  initiatives,  to  boost  SME 
research and product innovation and facilitate 
start-up creation. The long-term goal of FIRE is 
to realise a sustainable, connected network of 
internet experimentation facilities providing easy 

access for experimenters and innovators across 
Europe and globally, offering advanced experi-
mentation  and  proof-of-concept  testing.  The 
number of SMEs and startups leveraging FIRE 
can be increased by offering professional highly 
supported facilities and services such as experi-
mentation-as-a service, shortening learning time 
and decreasing time-to-market for experimenta-
tion. A brokering initiative should provide broker 
services across the FIRE portfolio or via exploit-
ation partnerships. Additionally, community appli-
cation programming interfaces should be offered 
to make FIRE resources more widely available.
FIRE’s  core  expertise  and  know-how  must 
evolve: from offering facilities for testing net-
working technologies to offering and co-devel-
oping the methodologies, tools and processes 
for research, experimentation and proof-of-con-
cept testing of complex systems. FIRE should 
establish a lively knowledge community to cre-
ate innovative methodologies and learn from 
practice.
FIRE should ensure longer-term sustainability 
building  upon  diversification,  federation  and 
professionalisation.  FIRE  should  support  the 
transition from research and experimentation 
to innovation and adoption, and evolve from 
single area research and experiment facilities 
towards cross-technology, cross-area facilities 
which can support the combined effects and 
benefits of novel infrastructure technologies 
used together with emerging new service plat-
forms enabling new classes of applications.
FIRE should develop and implement a service 
provisioning approach aimed at customised ful-
filment of a diverse range of user needs. Mov-
ing from offering tools and technologies, FIRE 
should offer a portfolio of customised services 
to address industry needs. FIRE should estab-
lish clear channels enabling interaction among 
providers, users and service exploitation by col-
laboration partners.

• 

• 

• 

FIRE should become part of a broader future inter-
net value network, by pursuing cooperation strat-
egies at multiple levels. Cooperation covers different 
levels: federation and sharing of testbed facilities, 
access to and interconnection of resources, joint 
provision of service offerings, and partnering with 
actors  in  specific  sectoral  domains.  In  this  FIRE 
should target both strong and loose ties of oppor-
tunistic collaboration. Based on specific cases in 
joint projects, cooperation with 5G and IoT domains 
could be strengthened.

Finally, FIRE should evolve towards an open access 
platform ecosystem. Platform ecosystem building is 
now seen as critical to many networked industries as 
parties are brought together who establish mutually 

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.070

beneficial relations. Platforms bring together and 
enable direct interactions within a value network of 
customers, technology suppliers, developers, facility 
providers and others. Developer communities may 
use the FIRE facilities to directly work with business 
customers and facility providers. Orchestration of 
the FIRE platform ecosystem is an essential condi-
tion. Steps towards forming a platform ecosystem 
include the encouragement of federation, the setting 
up of open access and open call structures, and the 
stimulation of developer activities.

References
[1]  FIRE portal — http://www.ict-fire.eu/home.html

[2]  AmpliFIRE website and downloads — http://www.
ict-fire.eu/home/amplifire.html

Acknowledgment
The authors gratefully acknowledge the contribu-
tion of AmpliFIRE partners to the ideas and recom-
mendations presented in this paper. For detailed 
information we refer to AmpliFIRE deliverables and 
white papers made available on its website [2].

Contact

Hans Schaffers
Research professor
Saxion University of Applied Sciences
The Netherlands
j.w.m.schaffers@saxion.nl

Michael Boniface
Technical director
IT Innovation Centre, University 
of Southampton
The United Kingdom
mjb@it-innovation.soton.ac.uk

Scott Kirkpatrick
Professor of engineering and 
computer science
Hebrew University of Jerusalem
Israel
skirkp1@gmail.com

OPEN INNOVATION YEARBOOK 201671

Trends in the innovation ecosystem, startups and the 
industrial renaissance
A look into innovation and startups in Turkey

Introduction

The world is going through the fourth industrial revolution which is about to be as and even more dis-
ruptive as the previous ones. It is proposed that the fourth revolution will not only affect the systems 
governing global production, transportation and consumption of goods, but it will have consequences 
reaching far into every aspect of our lives. The message that echoes around the globe is clear: ‘You have 
not seen anything yet!’ If you will allow me to point out the obvious, I will just say that the aftermath of 
this wave — no, tsunami — will be an industrial and culture renaissance, and we will be one step closer 
to being a global civilisation.

The fourth industrial revolution is different from the previous ones in three ways: first, it is evolving at 
a far greater pace than anything previously experienced. Second, it affects an incredibly broad range of 
technologies — 3D printing, sensors, nanotech, brain research, etc. Consequently, it opens the possibility 
for large leaps in knowledge. Third, it allows for holistic optimisations of complex services as opposed to 
the fine-tuning of individual products.

Opportunities of the fourth 
industrial revolution
Digitalisation: software and cloud-based services 
are multiplying. This leads to the possibility of com-
mercialisation with low capital costs and this is con-
siderably empowering.

Ownership: the concept of ownership is changing; 
collaborative  consumption  is  becoming  more  and 
more prominent.

Talent: talent and ‘the team’ are becoming more val-
uable. Microentrepreneurship is gaining importance, 
and entrepreneurial quotient (EQ) is already a taking-
shape term. Large companies are progressively com-
peting for the privilege of breathing life into pioneer-
ing projects. Consequently, the global competition 
among ‘ecosystem players’ is growing to be more 
acute. The ‘million-dollar laboratory’ of the old now 
stands in stark contrast to research and development 
(R & D) making its way into the primary and second-
ary school curricula. Therefore, finding metrics for 
innovative talent is something to ponder on.

Transformations in the marketplace: as the mar-
ketplace defines the investment strategy, changes 
in  demographics  have  to  be  tracked.  On  a  local 
level, if we look from a vantage point in Turkey, for 
instance, we differentiate two growing markets on 
which to focus innovation: one which caters to the 
large proportion of the younger generation, and one 
that focuses on creating services that are sensitive 
to social conservatism (the latter trend is not only 
limited within the confines of Turkey).

Transformations in market segments: as market 
segments are further subdividing, large companies 

are afforded a chance to go more local, and small 
companies are able to thrive.

Entrepreneurial spirit: Turkish startups are entering 
a new and promising period in 2016 which will posi-
tively affect European startups.

Where does Turkey stand?
Turkey, with its population of 82 million, is the sec-
ond largest country in Europe after Germany, and 
half of its population is below the age 25. Out of the 
82 cities in Turkey, 29 have a status of ‘metropolitan 
municipalities’. In those cities, regional municipal-
ities are also active alongside the larger metropolitan 
municipality. Istanbul is, of course, the largest city 
in Europe being situated on two continents. Istanbul 
can be surely considered as a country; having 16 mil-
lion people, a population number bigger than in 131 
countries in the world.

Turkey is one of the world’s leading countries in terms 
of urban growth. Consequently, the municipalities 
are in competition with one another towards mak-
ing cities ‘smarter’. Başakşehir is one of the regional 
municipalities of Istanbul and its population is pro-
jected to reach one million by 2020. Başakşehir has 
successfully established a living lab and innovation 
centre which focuses on information and communi-
cations technology. The living lab is creating a new 
ecosystem for 30 000 SMEs located in Başakşehir 
and affects 400 000 citizens. The living lab’s focal 
areas  are  industrial  design  area,  user  experience 
centre,  startups  space,  smart  home  prototype, 
healthcare and education rooms. In the municipality 
region of Başakşehir every business and apartment 
building has 1 GB internet connection.

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.072

Cities as open living labs
Once,  cities  were  the  centres  of  imperial  empires 
where  local  governance  was  usually  undertaken 
by  members  of  the  conquering  nation  who  would 
be placed over the local elite. In the industrial era 
cities became factories; they became the engines of 
national economies. Now, we witness them becoming 
innovation hubs. In the digital era, step by step, cities 
are transforming into living labs, as a living lab pro-
vides an innovation ecosystem model that best fits 
the complexity of a city organisation.

The  European  Network  of  Living  Labs  (ENoLL) 
offers local governments and municipalities a clear 
message:

‘Every city needs an open living lab strategy 
because this citizen-based approach is the ulti-
mate innovation model’ [1].

Of course, cities need to digitalise urban infrastruc-
tures by installing sensors and making data available. 
This will lead to advanced services for citizens. And 
yet, this is only a small detail of the transformation of 
the city. If a city is to lead other cities in a certain area, 
it should embrace open living lab strategies, based 

Table 1: Components of the entrepreneurial ecosystem

on the Open Innovation 2.0 ‘quadruple helix’ para-
digm: cities to be transformed into citizen-driven liv-
ing labs, where local governments and municipalities 
will partner with thousands of companies, hundreds 
of research centres and millions of citizens in order to 
build a real innovation ecosystem that is much more 
comprehensible than any smart city strategy.

As Artur Serra Hurtado (the director of İ2Cat Living 
Lab/ Barcelona) said:

‘Cities are becoming too complex to be managed like 
factories of the industrial era. We need to manage 
them like we manage the internet; putting our trust 
on the network, in the citizens, in the entrepreneurs 
and in the neighbourhoods, thus relying on the peer-
to-peer model. The key issue: increase talent and 
desire of the citizen to innovate. Open living labs are 
the new ‘school of innovation’. They are the places 
where the new generations feel free to develop their 
own dreams, projects and jobs in cooperation with 
their peers. Leaders of the regional governments 
and municipalities who believe that they have the 
ability to make change are limited without the help 
of citizens. Therefore, their ultimate role should be 
to empower everyone to be innovative’ [2].

The regional innovation ecosystem
The innovative entrepreneurial ecosystem is a broad 
field that is fed by a varied policy landscape. In the 
past the innovative entrepreneurial ecosystem was 
considered an appendage to the policies governing 
SMEs, which were a product of industrialisation. But 
today, it is acknowledged that the favourable condi-
tions for the growth of SMEs and innovative entre-
preneurship  are  quite  different,  so  the  innovative 
entrepreneurial ecosystem is increasingly becoming 
an independent policy field. Reports and documents 
such as the Global entrepreneurship monitor (GEM), 
the EU Progress report, the European SME law and 
the entrepreneurship 2020 action plan make a strong 
emphasis on new strategies for innovation.

In parallel to these developments, Turkey has decided 
to author a plan that is separate from the SME strat-
egy and action plan. Thus a new plan called the Turkish 
innovation ecosystem action plan (GISEP), which cov-
ers the time span of 2015-2018, has been prepared. 
The general purpose of GISEP is to make the innovative 
culture in Turkey more widespread, and to create an 
ecosystem which will support entrepreneurship. The six 
goals that make up the plan are the following:

1.  to develop an entrepreneur-friendly regulatory 

framework;

2.  to support innovative entrepreneurship;
3.  develop sustainable thematic frameworks such 
as woman entrepreneurs, eco-entrepreneurship, 

OPEN INNOVATION YEARBOOK 201673

young entrepreneurship, social entrepreneurship 
and global entrepreneurship;

4.  to develop a culture that embraces the entrepre-

neur and entrepreneurship;

5.  to extend formal and informal innovation edu-
cation,  and  to  develop  consulting  services  for 
entrepreneurs;

6.  to facilitate the entrepreneur’s access to financial 

instruments.

Table 2: Policies of SMEs and entrepreneurial ecosystems

The strengths and weaknesses of the 
innovation ecosystem and risks in Turkey

• 

The strengths
•  Market advantage: Turkey’s demographics, its 
geographic location and its proximity to differ-
ent types of markets; Istanbul’s attractiveness 
and consumerist tendencies.
The young population: the strong numbers of 
the Y generation that wants to work in the fields 
of technology, science and media and the posi-
tive view of entrepreneurship among university 
students.

• 

• 

• 

•  Skilled workforce: the fact that the people who 
will be the architects, builders and leaders of 
the future are currently being educated.
Incentives: the fact that investors receive incen-
tives for R & D, patenting, design, marketing and 
investing.
Trendy: the fact that innovation and startups are 
openly supported by the public and that they are 
the order of the day; collaborations are visibly 
strengthening, as are the pools of funding; the 
government, endowed universities, technoparks, 
chambers of industry and some large munici-
palities are offering space and funds to startups.
•  World brands and the diaspora: the fact that 
a will to create world brands through collabor-
ation between the industry and startups exists; 
the strategy to access the global halal market 
with the help of the diaspora.

The level of R & D capacity: the small market 
share of R & D in Turkey; the difficulty in offer-
ing incentives for patenting and copyrighting; 
the lack of industrial experience, and the lack of 
industry-university collaboration.

•  Non-supportive education: the shortcomings of 
the education system in teaching analytic skills 
and teamwork. Lack of English-language com-
petency, which is crucial to entrepreneurship; the 
lack of computer programming education before 
university level is an indicator of how the educa-
tion system does not support innovation in Turkey.
The weakness of the entrepreneurial culture and 
mindset: original and commercially viable ideas 
are not produced at a redundant rate; ideas that 
come out do not get the support that they need; 
income  inequality,  and  the  lack  of  an  honour 
system.

• 

•  Metrics: the lack of reliable statistical reports on 

• 

a lot of important phenomena.
The lack of interest in the public and private sec-
tors: public companies have a hard time manag-
ing even public projects; the reputation-based 
leadership model and lack of synergetic collabo-
ration between corporations; positive discrimin-
ation of foreign companies.

•  Role models: the small number of serial entre-
preneurs, the difficulty of finding employees for 
startups because there are not enough success 
stories.
The shallow talent pool.

• 

The weaknesses
• 

The  lack  of  early-stage  funds:  investors  are 
inclined to support startups in the growth stage 
as opposed to in the beginning; the missing links 
in the investment chain.

Risks
•  Contradictions  in  understanding:  the  lack  of 
a startup handbook, the dangers of bureaucratic 
confusion  about  the  differences  of  particular 
entrepreneurship models.

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.074

• 

Falling behind: the middle income trap makes it 
difficult to catch the crests of the waves of tech-
nological change.

•  Attraction  of  talent:  brain  drain  is  a  familiar 

problem in many countries.

• 

Education: the enormous task of educational 
reform in a country with 25 million students.
•  Cultural obstacles: the social and psychological 
pressures that startups face; the risk of falling 
behind because of slow cultural transformation.

Table 3: 10th development plan: developments and targets in entrepreneurship and SMEs

Table 4: Statistics of incorporated and terminated companies (between 2010-2014)

Turkey’s innovation and 
entrepreneurship goals for 2023
The  Organisation  for  Economic  Cooperation  and 
Development defines the entrepreneur as some-
body who can shape new business opportunities 
and use sources efficiently. It is somebody who can 
identify new products, processes and markets and 

creates value by establishing new commercial pro-
cesses or improving on current ones. Accordingly, 
the entrepreneur is not evaluated by his actions, 
but by the outcomes of these actions. The entre-
preneur invests his time, creativity, network and 
other resources to begin processes working within 
an environment that contains uncertainty and risk. 

Figure 1: ENoLL open living lab days 2015, Istanbul

OPEN INNOVATION YEARBOOK 201675

As  these  processes  mature,  they  should  lead  to 
economic and social value as well as to dissolving 
values that were in place before.

Vision and goals
In order to become one of the ‘regional hubs’ in 
Europe and the Middle East for an innovation and 
entrepreneurship ecosystem, Turkey needs to have 
an overarching vision as well as specific goals, to 
suggest legislative steps, to have a clear idea of 
marketplace, define financial initiatives, understand 
human capital, networking opportunities and desir-
able cultural transformations.

Vision

•  Be located in Istanbul.
•  Be  protected  by  law  that  is  integrated  with 

global regulations.

•  Be completely independent.

Goals

On the path that this vision guides Turkey, the coun-
try envisages:

• 

• 

• 
• 

• 

• 
• 

• 

• 

to give rise to multiple Unicorn companies by 
2023;
to reach two-digit percentages of the national 
export produced by startups;
to attract foreign and global entrepreneurs;
to be instrumental in establishing a ministry of 
enterprise and innovation;
in  order  to  boost  the  exit  performance  of 
entrepreneurs:
to lower the cost of entry to the market,
to connect various kinds of reachable markets 
for easy reach;
to  create  special  incentives  for  ‘born  global’ 
ventures;
to influence entrepreneur-friendly legislation.

Figure 2: Social innovation atelier in Başakşehir Living Lab

Legislative steps

Finance

•  Startups should be allowed to receive benefits 
from a credit guarantee fund trust; they should 
benefit from breaks in sales, withholding and 
dividend tax as well as receive temporary social 
insurance tax exemption.

• 
• 

Local investment should be facilitated.
Local banks and companies should be allowed 
a  fair  opportunity  to  support  and  purchase 
startups.

•  Crowdfunding  and  co-investment  platforms 

•  Revisions should be made in incentives for angel 

should be established.

• 

investors.
Intellectual property rights of startups should 
be protected.

•  Cooperation between venture capital and accel-

erators/incubators should be facilitated.

•  Early-stage and corporate enterprise-funding 

• 

projects should be established.
Legislative steps to draw foreign investment 
should be made.

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.076

Human capital
•  Coding and computer-aided design (CAD) should 
be included in early education. Design thinking 
should be emphasised, and maker labs should 
be established.

•  Gender equality in employment should be in the 

• 

forefront.
The causes of brain drain should be probed and 
radical steps be taken to prevent it.

Figure 3: Global startup ecosystem

Networking
•  National and international ‘mentoring ecosys-

tem’ should be incentivised.

•  Clustering should be encouraged in cities other 

• 

than Istanbul.
Technoparks and incubators should receive well-
defined benefits.

•  Amateur interest groups should be rewarded to 

provide cooperative outreach.

Culture and communication
•  Hands-on project-based education should be 

organised.

•  A culture of ‘do it yourself’ should be embraced.
• 
•  Experienced role models should appear on the 

Financial literacy should be boosted.

media.

To understand what is happening and what is going 
to happen in Turkey, we need to look at the world. 
The two horses that pull this carriage forward are 
enterprise and venture capital. Some of this belongs 
to early-stage seed funds, and others to growth 
stages. It is also crucial to spread the risk in the 
investments that are made. Invested funds should 
be  collected  in  a  pool  and  invested  at  multiple 
stages of startups.

According to the global innovation index that is pub-
lished through collaboration by Cornell University, 
Insead and the World Intellectual Property Organ-
isation, Turkey ranks 68th among 142 countries. The 
global creativity index that is published by Martin 
Prosperity Institute under the University of Toronto 
defines three pillars of economic growth: technol-
ogy, talent and startups. In this index, Turkey ranks 
as 37th among 82 countries in R & D investments, 

OPEN INNOVATION YEARBOOK 201677

44th in research, 54th in innovation and 51st in 
technology.

To  combine  the  two  wings  of  the  star tup 
machine — technology and business — under one 
body  is  uncommon  but  not  impossible.  For  this 
reason, the symbiotic interaction between techno-
crats and startups is very important. Therefore, it is 
paramount to establish innovation ecosystems that 
bring together finance and mentorship structures. 
Technocrats came into existence as a logical con-
tinuation of an occupational group of the industrial 
society. The same thing is not valid yet for startups. 
The industrial society has turned professional man-
agement into an occupation, but not startups. Now 
the information society is trying to achieve this, and 
it will probably take another five years.

The World Economic Forum asked 800 profession-
als in the information technologies sector for their 
predictions about the near future. Their responses 
are documented in the report titled ‘Technology 
tipping points and social impact’ [3]. What sorts 
of transformations are possible until 2025? 86 % 
agrees that we will see a drugstore that is entirely 
operated by robots, 84 % agree that we will see 
3D-printed cars, 91 % agree that our clothes will 

be connected online, 78 % agree that the num-
ber of cars will reach 10 % of today’s numbers, 
76 % agree that we will see the first 3D-printed 
kidney, 69 % agree that half of internet traffic will 
be between devices and 45 % agree that we will 
see  some  form  of  artificial  intelligence  in  man-
agerial boards. The last one of these, and the least 
likely  one  to  become  reality,  was  implemented 
by a start-up in Hong Kong by the name of Deep 
Knowledge. They officially assigned an algorithm 
to  help  the  board  make  better  decisions  about 
investment strategies. The algorithm is a product 
of a biotechnology firm called Aging Analytics. This 
software is called Vital, and it is designed to detect 
early investment opportunities in biotechnology. 
This will make it possible for the algorithm to ana-
lyse advances in subjects like renewable medicine, 
cancer treatment, bioinformatics, drug development 
and personalised medicine, and will have a vote in 
the administrative body.

These  innovations  fall  under  the  umbrella  of 
‘Thingalytics’. The article titled ‘Here’s how manag-
ers can be replaced by software’ by Devin Fidler and 
published in the Harvard business review is neither 
the first or last place where such ideas are explored 
[4]. Thus, the i-CEO concept is emerging.

Figure 4: A city innovation system model (i2Cat Catalonia Digital Lab)

INNOVATION ECOSYSTEMS AND LIVING LABS CHALLENGED BY OPEN INNOVATION 2.078

How should startups be?
The startups in Turkey follow the news in the world 
and have parallels to examples in Europe. Following 
their path is undeniably good, but to reach Silicon 
Valley levels requires efforts far beyond the current 
ones.

References
[1]  ENoLL meetings: in Barcelona 18.11.2015 and in 
Brussels 20.1.2016.

[2]  İ2Cat Living Lab Barcelona, 18.11.2015.

[3]  Dünya daily economic newspaper, 18.12.2015.

[4]  Dünya daily economic newspaper, 19.12.2015.

Contact

Yılmaz Çakır
Chairman of Başakşehir Living Lab/Istanbul
Vice Chairman of StartersHub/Istanbul
y.cakir@superonline.com

Startups in Turkey need to be on top of their field, 
follow the advances in their domains closely, ful-
fil the basic requirement of 10 000 man hours, be 
sharp and have faith. They need real muscles, men-
tal and physical fitness. They need to be good with 
the books, and if they are not, they should team 
up with such people. In fact, this is nothing but the 
definition of a modern-day gladiator. Turkey has the 
potential to enter the global arena among European 
and American startups in as much as it is able to 
produce gladiators.

The Slush event organised in Helsinki every Novem-
ber that cringed together 17 000 people in 2015 
is planned to be organised in Istanbul during June 
2016 by the most important local start-up ecosys-
tem, StartersHub. 3 000 participants from five con-
tinents are expected to attend the event. With this 
event, Turkey is taking a big step towards establish-
ing its position in the global start-up environment.

OPEN INNOVATION YEARBOOK 2016CHAPTER III

Future cities and regions 
in the context of Open 
Innovation 2.0

Smarter cities in the cognitive era

Introduction

A new technological age is upon us — the cognitive era. Cognitive technology brings new capabilities that 
offer the potential to transform the way work is done, the way services are provided, the way products are 
made, and the way businesses and organisations of all sizes and in all sectors are run. It offers a real and 
tangible opportunity to fundamentally improve every aspect of how cities function, from the core public 
services provided by cities or private sector entities to the products and services produced by private 
sector businesses for citizens and businesses. Existing challenges can be addressed in entirely new ways 
and new opportunities can be seized. Organisations can enable and accelerate innovation and growth as 
part of open innovation activities by pulling in cap abilities from outside the organisation, and by active 
participation and engagement in cognitive ecosystems and collaborative networks.

What is cognitive computing?
The history of information technology can be bro-
ken down into two distinct eras [1]. The first, the 
tabulating era, covered the period from 1900 to 
the 1940s. This technology comprised of machines 
designed to perform a specific job, such as count-
ing, and they enabled large-scale data inputting 
and calculations. Applications of this technology 

included population censuses in the United States 
as well as the control of industrial machines. The 
programmable era emerged in the 1940s and still 
forms the basis of much of the technology in use 
today. This instruction-led computing involves pro-
gramming  computers  with  logical  sequences  of 
instructions coded in software to conduct specific 
tasks such as analysing, processing and performing 

Figure 1: Cognitive computing capabilities

80

calculations  on  structured  data  —  that  is,  data 
organised, entered and stored in a record or file [2].

The  dawn  of  the  cognitive  era  began  in  2011, 
although the potential for surpassing the limitations 
of programming were raised many decades before 
this, and some of the key capabilities of cognitive 
emerged from work undertaken in earlier decades, 
such as that on artificial intelligence [3]. Yet this era 
is distinct due to the combination of the capabilities 
that cognitive brings. Some of these capabilities are 
outlined below [4].

•  Natural language processing is the ability to 
interpret  and  process  language  in  the  same 
way as humans [5]. This includes analysing and 
understanding the tone and context of language 
to derive meaning from it as well as being able 
to generate natural language. This means that 
anything written in natural language, such as in 
books, articles, newspapers, websites and social 
media, can be analysed and understood.

•  Reasoning  relates  to  the  probabilistic  nature 
of cognitive systems. While programmed sys-
tems were based on predetermined processes 
and rules applied to structured data, cognitive 
systems do not offer definitive answers. Instead, 
they analyse, weigh and interpret large amounts 
of information from structured and unstructured 
sources, and generate hypotheses and answers 
with supporting evidence and confidence levels 
assigned to answers [6].

•  Questioning and answering is the ability for 
users or systems to use questions or inquiries 
in natural language [7]. It goes beyond a search 
on Google, for example, that produces a list of 
results.  Instead  it  can  go  through  large  sets 
of  documents  or  data  and  pick  out  a person, 
place or thing that answers a question and thus 
reduces the time between answering a question 
and getting an answer [8].

•  Machine learning enables computer systems to 
learn, discover and predict automatically with-
out having to be explicitly programmed [9]. This 
means that systems have the ability to improve 
their own performance [10]. Machine learning 
also covers data-analysis capabilities including 
predictive analytics and data mining that can 
make connections, discover trends, patterns and 
relationships between datasets, with cognitive 
analytics bringing faster processing and better 
algorithms.

•  Computer vision is the ability to analyse and 
understand the content of an image and return 
the objects, people and text found within the 
image [11]. This can help with analysing online 
photos and videos to extract insights, for exam-
ple, related to customer interests, hobbies or life 
events.

•  Speech recognition converts speech into text 
[12]. It can be used wherever voice interactivity 
is needed, for example transcribing media files 
or converting sound to text to then make data 
searchable.

All of these capabilities help support and extend 
human expertise in decision-making. The cognitive 
era is not about replacing humans with machines 
but offers the chance to augment human decision-
making to produce better outcomes and results. The 
cognitive era will thus provide new ways for infor-
mation technology to continue its role as a critical 
enabler of economic growth and development [13]. 
The next section outlines some of the key drivers 
for why these capabilities are increasingly needed.

Why we need cognitive

The growth in big data
The  volume  of  data  being  created  is  exploding; 
90  %  of  all  data  has  been  created  in  the  past 
2 years [14], with 294 billion emails sent every day, 
1 billion Google searches performed and more than 
230 million tweets made [15]. In 2015, there were 
almost 4.1 billion social media accounts [16]. Face-
book users send on average over 31 million mes-
sages and view 2.8 million videos every minute [17].

The rate at which data volumes are growing is also 
increasing  faster  than  ever  before.  By  the  year 
2020, about 1.7 megabytes of new information will 
be created every second for every person [18]. To 
put that amount into perspective, data creation will 
be 44 times greater in 2020 than it was in 2009 
[19]. Social media accounts will reach 4.8 billion by 
2017 — a 50 % rise on 2013 levels [20].

The variety of data is also growing, with increas-
ing amounts of video and photo data being created. 
In 2014, 300 hours of video are uploaded to You-
Tube alone every minute, increasing to 400 hours in 
2015 and is expected to grow to 700 hours by the 
beginning of 2016 [21]. In 2015, 1 trillion photos 
will be taken and billions of them will be shared 
online — by 2017, this will increase by 30 % to 
1.3 trillion [22]. This year, over 1.4 billion smart-
phones will be shipped — up from just 173 million 
in 2009 — and this is expected to rise to almost 
1.9 billion in 2019 [23]. By 2020 there will be over 
6.1 billion smartphone users globally [24]. These 
phones are packed with sensors that can collect all 
kinds of data and result in the creation of data by 
their users. While sensors are not new, the declining 
size and cost means that they are being put into 
more types of devices than ever before [25]. This 
growth  in  data  is  creating  an  Internet  of  Things 
(IoT) and 6.4 billion ‘things’ will be connected to the 
internet in 2016, up 30 % from 2015 [26].

OPEN INNOVATION YEARBOOK 201581

Figure 2: Why we need cognitive: the growth in big data

Extracting meaningful insight in a timely manner 
from this data offers a huge challenge for organisa-
tions. But it also offers a huge opportunity — what 
IBM’s chief executive officer Ginny Rometty called 
the world’s new natural resource [27]. It holds tre-
mendous potential to generate insights that result 
in huge improvements and transformations in the 
way services are delivered and how work is done, 
and  to  drive  innovation  and  foster  growth.  Yet, 
despite  the  rapid  growth  in  the  amount  of  data 
that organisations have available to them and the 
potential it holds, it is estimated that businesses 
use just 20 % of it — the remaining 80 % being 
‘dark data’. This ‘dark data’ is unstructured data, 
such as complex human voice, image, video and 
natural-language data, but it is wasted as existing 
systems cannot process it. And, while more than 
70 % of data is generated by individuals, enter-
prises have responsibility for the storage, protection 
and management of 80 % of it [28].

These  are  some  of  the  key  reasons  why  organ-
isations are starting to leverage the capabilities 
of  cognitive  computing  and  this  is  driving  rapid 
spending growth in this market from an estimated 
USD 2.5 billion in 2014 to almost USD 12.6 billion 
by 2019 representing a compound annual growth 
rate of 38 % from 2014 to 2019 [29]. With many of 
these capabilities available through internet-based 
services via the cloud, this enables organisations 
to take advantage of cognitive as well as all the 
benefits that cloud brings, such as greater flexibil-
ity, shifting from capital expenditure to operational 
expenditure, and the ability to work from anywhere. 

Cognitive capabilities are needed by businesses and 
organisations to make sense of the large and rap-
idly growing amounts of unstructured data and to 
shine a light on ‘dark’ data. Cognitive systems will 
generate new and improved insights from existing 
data sources and new sources of information, such 
as sensors [30].

Scale of challenges in Europe
The scale and magnitude of the economic, social and 
environmental challenges facing Europe is another 
key reason why public and private sector organisa-
tions should take advantage and make greater use 
of cognitive capabilities as part of open innovation. 
This can help to find new approaches to utilising the 
data within and between systems to help solve the 
challenges and issues in these systems.

In  health,  for  example,  Europe’s  aging  popula-
tion  will  result  in  increasing  demands  being  put 
on already strained services. Between 2014 and 
2020 the number of people over 65 will increase 
by 10 million from 94 million to 104 million people, 
and growing by a further 20 million to 124 million 
by 2030. [31]. Over one third of those above the 
age of 15 in Europe have a chronic disease and 
two thirds of those reaching 65 will have at least 
two chronic conditions. [32]. This will increase the 
burden chronic diseases place on already strained 
budgets given chronic diseases currently account 
for 70-80 % of healthcare spending in the Euro-
pean Union [33]. New ways are needed to more rap-
idly and cost-effectively prevent, correctly diagnose 
and treat patients to improve the health of citizens.

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.082

In education, the Europe 2020 strategy set a target 
for 40 % of 30- to 34-year-olds to have a higher 
education qualification by 2020 [34]. While there 
has  been  substantial  progress  towards  this  tar-
get, there is still a need to help improve student 
engagement and performance to reduce dropouts 
and improve completion rates. This need also exists 
at second level where over 11 % of 18- to 24-year-
olds were early leavers from education and train-
ing with at most a lower secondary education [35]. 
There  were  more  than  22 million  people  unem-
ployed in the European Union in November 2015 
and the youth unemployment rate was at 20 %. 
Improving educational attainment using cognitive 
technologies  offers  a  new  way  to  help  improve 
employment opportunities for citizens, reduce the 
economic and social costs of unemployment, and 
support growth as the educational system provides 
graduates that are suited to the needs of growing 
businesses [36].

In terms of innovation, in 2014 R & D investment 
was 2 % of GDP, up from 1.85 % of GDP in 2008 but 
still below the 3 % target set in the Europe 2020 
strategy [37]. The latest figures available show that 
almost half of all enterprises in the EU-28 reported 
some  type  of  innovation  activity  between  2010 
and 2012, but this actually declined by almost 4 % 
compared with 2008-2010 [38]. 27.5 % reported 
organisational innovation, 24 % implemented some 
form of marketing innovation, the same proportion 
were engaged in some form of innovation related 
to developing new products or services, and 21 % 
of  enterprises  implemented  process  innovations 
[39].  With  Europe’s  strong  focus  on  innovation, 
there is substantial scope to leverage cognitive as 
part of these existing innovation activities and to 
help increase the scale and magnitude of innov-
ation within enterprises. Capabilities, such as rapidly 
and accurately analysing large bodies of informa-
tion to generate insights, can accelerate all kinds 
of research discoveries and support innovation. For 
example, IBM’s Watson cognitive system can ana-
lyse over 800 million pages per second. There is also 
scope to leverage cognitive to help drive improve-
ments in the efficiency of all kinds of agricultural, 
industrial  and  service  activities  to  foster  labour 
productivity growth in the European Union, which 
is currently growing at about 0.5 % annually, well 
down from the 2 % growth in the 1980s [40].

Good examples of those who are already 
leveraging it
This section outlines some examples where these 
capabilities  are  already  being  used  and  applied 
to a range of economic activities to provide bet-
ter services for citizens and businesses, accelerate 
the pace of innovation and discoveries, and support 
revenue and other aspects of business growth.

Health
•  Memorial Sloan Kettering, a cancer centre in 
New York, uses natural language-reading tools 
and machine learning to manage and rapidly 
analyse the massive amount of data collected. 
This results in a decrease in time for the latest 
research and evidence to influence clinical prac-
tice  for  the  oncology  community  and  deliver 
evidence-based  medicines  and  therapies  to 
patients [41].

• 

•  Bumrungrad  Hospital  in  Bangkok,  Thailand, 
analyses patients’ data against thousands of 
cases, medical journals, textbooks and 12 mil-
lion pages of text to reduce the time to develop 
treatment plans for cancer patients from weeks 
or months to just minutes [42].
The Mayo Clinic in the United States uses nat-
ural-language processing and powerful data-
analytics capabilities to help its clinicians sift 
through millions of pages of clinical trial and 
patient data and build a clinical trial-matching 
solution to increase the speed of new discover-
ies while offering patients more treatment pos-
sibilities [43].

•  GenieMD,  an  application  developer  based  in 
California,  developed  a  predictive  analyt-
ics  tool  to  provide  users  with  a holistic  view 
of their health while collecting their medical 
records.  GenieMD  gives  answers  to  personal 
health questions, offers periodic and highly tar-
geted health recommendations, reduces medi-
cal errors, increases patients engagement and 
satisfaction,  improves  patient  outcomes  and 
reduces the cost of healthcare [44].

Education
•  Deakin University in Australia is using a 24/7, 
always  on,  personalised  student  advisor  to 
improve  student  engagement.  Using  natural 
language  and  machine-learning  capabilities, 
the  solution  provides  students  with  tailored 
answers  to  their  specific  questions  to  help 
improve engagement and student satisfaction 
by 20 % and boost the ability to attract new 
students [45].

•  Gwinnett County Public Schools in the United 
States uses machine learning, predictive mod-
elling,  deep  content  analytics  and  advanced 
case management to identify learning needs of 
students and recommend personalised learn-
ing pathways to move from a ‘one size fits all’ 
model to a personalised approach that moti-
vates and engages learners, reduces dropout 
rates, improves academic performance and col-
lege readiness, increases student engagement 
and enhances teacher effectiveness [46].

•  More than 100 Kenyan schools are leveraging 
cognitive,  mobile  and  analytics  technologies 
to capture data to track and reduce students’ 

OPEN INNOVATION YEARBOOK 201583

underperformance and have a complete over-
view on the resources available as well as the 
school conditions. This helps to create an early 
warning system that can help identify school 
needs and students who are at particular risk of 
failing [47].

Services
•  DBS bank in Singapore is using cognitive com-
puting  solutions  to  transform  customer  ex-
perience and shape the future of banking. Large 
volumes of complex unstructured and struc-
tured data can be analysed, including research 
reports,  product  information  and  customer 
profiles, to help identify connections between 
customers’  needs.  This  helps  advisors  weigh 
various financial options available to custom-
ers and gives DBS data-driven insights that can 
personalise the client experience [48].
Thomson Reuters, the world’s leading source of 
intelligent information for businesses and pro-
fessionals, is leveraging deep content analytics, 
natural language processing, decision support 
and evidence-based learning to enable Thom-
son Reuters’ customers to derive greater insight 
and  workflow  efficiency.  Applying  cognitive 
capabilities to the company’s vast trove of data 
on science, law, tax and finance helps accelerate 
discoveries and brings new levels of speed and 
precision to important decisions [49].

• 

• 

•  Alpha Modus Corp., a financial services technol-
ogy company in the United States, uses a cloud-
based platform and ecosystem for developing 
next-generation  investment  tools,  reducing 
deployment cycles by 80 % [50].
Trisept  Solutions  is  a  travel  company  in  the 
United  States  that  leverages  cognitive  cap-
abilities to generate personalised travel recom-
mendations from natural language queries to 
enable travel agents to make better decisions 
more quickly and provide highly personalised 
holiday recommendations to their clients [51].

Manufacturing
•  Sanofi,  the  French  pharmaceutical  company, 
is using cognitive capabilities to speed up the 
discovery of alternate uses for existing drugs 
by  analysing  and  extracting  key  information 
from millions of pages of scientific literature 
and  visualising  relationships  between  drugs 
and other potential diseases. It is also being 
used to understand, extract and organise tox-
icological information to enable researchers to 
make better decisions on candidate progression 
to improve drug safety and toxicity in clinical 
development and trials, and to improve the suc-
cess rate of drug R & D [52].

•  PhotonStar LED Group, a designer and manu-
facturer of smart LED lighting solutions in the 

United Kingdom, is using cognitive capabilities 
to  enable  the  company  to  build  new  innov-
ations. This is helping the company to uncover 
opportunities, find new avenues of growth and 
be better positioned to fulfil client requirements 
for  innovative,  end-to-end  solutions  for  the 
commercially built environment [53].

•  Media Control Gmbh, a media and entertain-
ment company in Germany, uses sophisticated 
algorithms to continuously sift through reviews, 
blogs and other content on over 100 000 web-
sites to create a sentiment index and a first-of-
a-kind social media analysis service. This has 
helped the company strengthen relationships 
with existing customers and attract new cus-
tomers, improving the company’s competitive 
position and increasing its market share [54].
Inno360  is  an  enterprise  research  and  in-
novation management company in the United 
States. It uses sentiment tracking and machine 
learning to provide advanced analysis to clients 
for their R & D data to resolve product issues 
quickly and bring new products to the market 
more rapidly, thereby enhancing client return on 
investment, and increasing Inno360’s revenue 
[55].

• 

Conclusion
The cognitive era and cognitive technology clearly 
offer an opportunity to radically improve how cities 
operate and function, how services are delivered, 
how  products  are  made,  how  new  services  and 
products are developed, and how to accelerate the 
discovery  of  solutions  and  answers  to  our  most 
pressing challenges and problems. This applies not 
just to the public sector or local government organ-
isations  in  cities,  but  also  to  any  private  sector 
business providing goods or services to citizens and 
businesses in cities. And, of course, there is consid-
erable scope for central and national governments 
to take advantage of these capabilities in driving 
innovation in any of the services they deliver for 
citizens and businesses — internal and back-office 
government  processes  can  be  transformed,  and 
governments can make more informed and better 
policy decisions and better predict the impact of 
their decisions.

Open  innovation  will  play  a  critical  role  in  this 
process.  Cognitive  capabilities  go  beyond  the 
cap abilities  of  most  companies  relying  on  their 
internal resources and activities, as in a closed innov-
ation model. Integrating cognitive ideas, solutions, 
resources and capabilities into internal innovation 
activities  and  processes  enables  improvements 
that are simply not possible for many firms to do 
themselves.  While  organisations  can  start  now 
to  take  full  advantage  of  these  capabilities,  as 
time goes on, cognitive will become essential for 

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.084

organisations  to  stay  competitive  and  grow  as 
existing systems hit the limits of their abilities due 
to the ever-expanding sea of unstructured data. It 
is time for smarter cities to become cognitive cities.

References
[1]  Kelly, J. E., Computing, cognition and the future of 
knowing — How humans and machines are forging 
a new age of understanding, IBM Global Services, 
2015 — http://www.research.ibm.com/software/
IBMResearch/multimedia/Computing_Cognition_
WhitePaper.pdf

[2]  For definitions of structured data see, for example, 
‘structured data’, Webopedia, 2016 — http://www.
webopedia.com/TERM/S/structured_data.html

[3]  See, for example, Langley, P., Artificial intelligence 
and cognitive systems, Arizona State University, 
Arizona, 2011 — http://www.isle.org/~langley/papers/
cogsys.aisb12.pdf; Licklider, J. C. R., ‘Man-computer 
symbiosis — Ire transactions on human factors 
in electronics’, MIT Computer Science and Artificial 
Intelligence Laboratory, 1960 — http://worrydream.com/
refs/Licklider %20- %20Man-Computer %20Symbiosis.
pdf

[4]  This list is not exhaustive given the constantly 
evolving nature of the capabilities being developed. 
For example, in less than two years between 2013 
and 2015, IBM’s Watson platform evolved from 
one application programming interface (API) and 
a limited set of application-specific deep question-
and-answering capabilities to more than 25 
APIs powered by over 50 technologies. See, for 
example, ‘IBM extends industry’s largest portfolio 
of cognitive APIs’, Scientific Computing, 2015 — 
http://www.scientificcomputing.com/news/2015/09/
ibm-extends-industrys-largest-portfolio-cognitive-apis

[5]  Russell, S. and Norvig, P., Artificial intelligence: 
a modern approach, Pearson, London, 2009.

[6]  Kelly, J. E., Computing, cognition and the future of 
knowing: how humans and machines are forging a new 
age of understanding, IBM Global Services, 2015 — 
http://www.research.ibm.com/software/IBMResearch/
multimedia/Computing_Cognition_WhitePaper.pdf

[7]  Hurwitz, J., Kaufman, M. and Bowles, A., Cognitive 
computing and big data analytics, Wiley, New York, 2015.

[8]  ‘Cognitive insights: question answering’, 
AlchemyAPI, 2015 — http://blog.alchemyapi.com/
cognitive-insights-question-answering

[9]  ‘Machine learning’, Stanford online, Stanford 
University, 2016 — http://online.stanford.edu/course/
machine-learning-1

[10]  ‘Machine learning and cognition’, A preparatory 
workshop for EU seventh research framework 
programme, Europa, Luxembourg, 2005 — http://
cordis.europa.eu/pub/ist/docs/dir_e/machine_learning_
cognition_workshop20051219.pdf

[11]  Russell, S. and Norvig, P., Artificial intelligence: 
a modern approach, Pearson, London, 2009.

[12]  ‘Cognitive computing in the enterprise’, 
Business World, 2015 — http://www.businessworld.
in/article/Cognitive-Computing-In-The-
Enterprise/17-11-2015-87608/

[13]  For evidence on the importance of information 
and communications technology (ICT) as a driver 
of growth see, for example, Khuong, M. Vu., ‘ICT 
as a source of economic growth in the information 
age: empirical evidence from the 1996-2005 
period’, Telecommunications Policy, 2011 — 
http://www.sciencedirect.com/science/article/pii/
S030859611100022X;

Sang-Yong, T. L., Gholamib, R. and Yit Tong, T., ‘Time 
series analysis in the assessment of ICT impact at the 
aggregate level — Lessons and implications for the 
new economy’, Information & Management, 2005 — 
http://www.sciencedirect.com/science/article/pii/
S0378720604001569;

Cortada, J. W., The digital hand: how computers changed 
the work of American manufacturing, transportation 
and retail industries, Oxford University Press, Oxford, 
2003; Cortada, J. W., The digital hand, Volume 2: how 
computers changed the work of American financial, 
telecommunications, media and entertainment 
industries, Oxford University Press, Oxford, 2005.

[14]  ‘Bringing big data to the enterprise’, IBM, 2016 — 
http://www-01.ibm.com/software/data/bigdata/what-is-
big-data.html

[15]  ‘Quick facts and stats on big data’, IBM, 
2016 — http://www.ibmbigdatahub.com/gallery/
quick-facts-and-stats-big-data

[16]  Radicati, S. and Levenstein, J., Email statistics 
report, 2013-2017, The Radicati Group, Inc., California, 
2013 — http://www.radicati.com/wp/wp-content/
uploads/2013/04/Email-Statistics-Report-2013-2017-
Executive-Summary.pdf

[17]  Kapko, M., ‘7 staggering social media use by-the-
minute stats’, CIO, 2015 — http://www.cio.com/
article/2915592/social-media/7-staggering-social-
media-use-by-the-minute-stats.html

[18]  Gantz, J. and Reinsel, D., The digital universe study: 
big data, bigger digital shadows, and biggest growth in 
the Far East, IDC, 2012 — http://www.whizpr.be/upload/
medialab/21/company/Media_Presentation_2012_
DigiUniverseFINAL1.pdf

[19]  ‘Big data just beginning to explode’, CSC, 2016 — 
http://www.csc.com/big_data/flxwd/83638-big_data_
just_beginning_to_explode_interactive_infographic

[20]  Radicati, S. and Levenstein, J., Email statistics 
report, 2013-2017, The Radicati Group, Inc., California, 
2013 — http://www.radicati.com/wp/wp-content/
uploads/2013/04/Email-Statistics-Report-2013-2017-
Executive-Summary.pdf

[21]  Robertson, M. R., ‘500 hours of video 
uploaded to YouTube every minute [Forecast]’, 
ReelSEO, 2015 — http://www.reelseo.com/
hours-minute-uploaded-youtube/

[22]  G4Developer, ‘Research triangle: one trillion 
photos in 2015: InfoTrends’, Digital Imaging 
Reporter, 2015 — http://www.direporter.com/article/
one-trillion-photos-2015-infotrends/

[23]  ‘Global smartphone shipments forecast 
from 2010 to 2019 (in million units)’, Statista, 
2015 — http://www.statista.com/statistics/263441/
global-smartphone-shipments-forecast/

[24]  Lunden, I., ‘6.1B smartphone users 
globally by 2020, overtaking basic fixed phone 

OPEN INNOVATION YEARBOOK 201585

subscriptions’, TechRunch, 2015 — http://techcrunch.
com/2015/06/02/6-1b-smartphone-users-globally-by-
2020-overtaking-basic-fixed-phone-subscriptions/#.
tbnx8uv:RPIH

[25]  Greenough, J., ‘Here are the four key 
elements that will make the ‘Internet of Things’ 
an absolutely massive market’, Business Insider 
UK, 2014 — http://uk.businessinsider.com/
four-elements-driving-iot-2014-10

[26]  van der Meulen, R., ‘Gartner says 6.4 billion 
connected ‘things’ will be in use in 2016, up 30 per cent 
from 2015’, Gartner, 2015 — http://www.gartner.com/
newsroom/id/3165317

[27]  Akhtar, O., ‘‘Big data is the world’s natural 
resource for the next century’ — IBM CEO Ginni 
Rometty’, The Hub, the marketing technology 
resource, 2014 — http://www.thehubcomms.com/
news/big-data-is-the-worlds-natural-resource-
for-the-next-century—ibm-ceo-ginni-rometty/
article/346991/

[28]  ‘Big data just beginning to explode’, CSC, 2016 — 
http://www.csc.com/big_data/flxwd/83638-big_data_
just_beginning_to_explode_interactive_infographic

[29]  ‘Cognitive computing market by technology (natural 
language processing, machine learning, automated 
reasoning), by deployment model (on-premises, cloud) 
and by regions — Global forecast to 2019’, Markets 
and Markets, 2015 — http://www.marketsandmarkets.
com/Market-Reports/cognitive-computing-
market-136144837.html

[30]  Kelly III, J. E. and Hamm, S., Smart Machines: IBM’s 
Watson and the era of cognitive computing, Columbia 
University Press, 2013.

[31]  ‘Population structure by major age groups, EU-28, 
2014-2080’, Eurostat, 2015 — http://ec.europa.eu/
eurostat/statistics-explained/index.php/File:Population_ 
structure_by_major_age_groups,_EU-28,_2014 %E2 % 
80 %9380_ %28 %C2 %B9 %29_ %28 %25_of_total_ 
population %29_YB15.png

domestic expenditure on R & D (GERD)’, Eurostat, 
2015 — http://ec.europa.eu/eurostat/tgm/table.do?tab=t
able&init=1&language=en&pcode=t2020_20&plugin=1

[38]  ‘Innovation statistics’, Eurostat, 2015 — http://
ec.europa.eu/eurostat/statistics-explained/index.php/
Innovation_statistics

[39]  Ibid.

[40]  Heise, M., ‘What are Europe’s twin growth 
challenges?’, World Economic Forum, 2015 — 
http://www.weforum.org/agenda/2015/12/
what-are-europes-twin-growth-challenges/

We mention agriculture here to highlight that all of the 
capabilities of cognitive computing can be applied to 
agricultural activities, for example to help improve and 
optimise planting, harvesting and distribution. See, for 
example, ‘Precision agriculture: using predictive weather 
analytics to feed future generations’, IBM — http://www.
research.ibm.com/articles/precision_agriculture.shtml

[41]  ‘Watson oncology’, Memorial Sloan Kettering 
Cancer Centre, 2016 — https://www.mskcc.org/about/
innovative-collaborations/watson-oncology; ‘IBM 
Watson for oncology’, IBM, 2016 — http://www.ibm.com/
smarterplanet/us/en/ibmwatson/watson-oncology.html

[42]  ‘Bumrungrad Hospital Public Company Limited — 
Cognitive solution for doctors added to plan treatments 
for patients with cancer’, IBM, 2015 — http://www-
03.ibm.com/software/businesscasestudies/hk/en/
corp?synkey=E805024R41013W85

[43]  ‘IBM Watson Health, Epic and Mayo Clinic to 
unlock new insights from electronic health records’, 
IBM, 2015 — https://www-03.ibm.com/press/us/en/
pressrelease/46768.wss;

‘Mayo Clinic and IBM task Watson to improve clinical trial 
research’, IBM, 2014 — https://www-03.ibm.com/press/
us/en/pressrelease/44754.wss

[44]  ‘The most comprehensive, IBM Watson-powered 
patient engagement solution’, GenieMD, 2016 — http://
geniemd.com/

[32]  Spongenberg, H., ‘Chronic diseases — The biggest 
killer in Europe’, EUobserver, 2014 — https://euobserver.
com/chronic-diseases/125636

[45]  ‘IBM Watson adoption accelerates globally’, 
IBM, 2014 — http://www-03.ibm.com/press/au/en/
pressrelease/45059.wss;

[33]  Ibid.

[34]  ‘Tertiary educational attainment by sex, age group 
30-34’, Eurostat, 2015 — http://ec.europa.eu/eurostat/
tgm/table.do?tab=table&init=1&language=en&pcode=t2
020_41&plugin=1

[35]  ‘School enrolment and early leavers from education 
and training’, Eurostat, 2015 — http://ec.europa.
eu/eurostat/statistics-explained/index.php/School_
enrolment_and_early_leavers_from_education_and_
training

[36]  ‘Unemployment rate by sex and age — monthly 
average, %’, Eurostat, 2016 — http://appsso.eurostat.
ec.europa.eu/nui/show.do?dataset=une_rt_m&lang=en;

‘Euro area unemployment rate at 10.5 %’, 
Eurostat, 2015 — http://ec.europa.eu/eurostat/
documents/2995521/7121195/3-07012016-AP-EN.pdf/
d0073836-6df2-4d38-9bcd-a326ec1ecbf5

[37]  ‘Europe 2020 indicators — Research and 
development’, Eurostat, 2014 — http://ec.europa.eu/
eurostat/statistics-explained/index.php/Europe_2020_
indicators_-_research_and_development; ‘Gross 

Eassom, S., ‘IBM Watson for education’, 
IBM Insights on business, 2015 — http://
insights-on-business.com/education/
ibm-watson-for-education-sector-deakin-university/

[46]  ‘IBM and Georgia’s largest school system bring 
personalized learning to life’, IBM, 2013 — https://www-
03.ibm.com/press/us/en/pressrelease/42759.wss

[47]  Warner, B., ‘How African schools are using cognitive 
systems to help shape the future of education’, 
IBM Big Data & Analytics Hub, 2015 — http://www.
ibmbigdatahub.com/blog/how-african-schools-are-
using-cognitive-systems-help-shape-future-education

[48]  ‘DBS bank engages IBM’s Watson to achieve next 
generation client experience’, IBM, 2014 — https://www-
03.ibm.com/press/us/en/pressrelease/42868.wss

[49]  ‘Thomson Reuters and IBM collaborate to 
deliver Watson cognitive computing technology’, 
IBM, 2015 — https://www-03.ibm.com/press/us/en/
pressrelease/47794.wss

[50]  ‘Alpha Modus reinvents investing with 
IBM Bluemix’, IBM, 2016 — http://www-03.

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.086

ibm.com/software/businesscasestudies/us/en/
corp?synkey=E224227U13112J55

[51]  ‘It’s all about Watson’, WayBlazer, 2016 — 
http://wayblazer.com/ibm-watson?cm_mc_
uid=29795784869214495199847&cm_mc_
sid_50200000=1449591758; ‘WayBlazer Taps IBM 
Watson to personalize travel booking, Trisept Solutions 
first to adopt WayBlazer cognitive conversion platform 
for travel agents powered by Watson’, WayBlazer Press, 
2015 — http://wayblazer.com/media/docs/WayBlazer-
and-Trisept-Announcement-Dec-2015.pdf

[52]  Taylor, N. P., ‘J&J, Sanofi apply IBM’s Watson to 
R & D’, FierceBiotech, 2014 — http://www.fiercebiotechit.
com/story/jj-sanofi-apply-ibms-watson-rd/2014-09-02

[53]  Halper, M., ‘British LED specialist teams with 
IBM Watson for IoT’, LEDs Magazine, 2015 — http://
www.ledsmagazine.com/articles/2015/12/british-led-
specialist-teams-with-ibm-watson-for-iot.html

[54]  ‘Media control GmbH — Social media 
analytics used to discover early signs of tomorrow’s 
bestsellers’, IBM, 2015 — http://www-03.
ibm.com/software/businesscasestudies/us/en/
corp?synkey=G062294K93544K86

[55]  Schaedler, D., ‘The Watson ecosystem: bringing 
smart software to market fast’, A Smarter Planet, 
2015 — http://asmarterplanet.com/blog/2015/09/
watson-ecosystem-smart-software-speed-market.
html; ‘IBM Watson ecosystem partners in market 
building businesses, PR Newswire, 2015 — http://www.
prnewswire.com/news-releases/ibm-watson-ecosystem-
partners-in-market-building-businesses-300148376.
html

Contact

Dr Mary Keeling
Manager economic analysis, smarter cities
IBM
mary.keeling@ie.ibm.com

Acknowledgements
The author would like to thank Emma Feerick and 
Celeste Bonanno for research assistance for this 
paper.

OPEN INNOVATION YEARBOOK 201587

Designing a smart society

From smart cities to smart societies
The  awareness  that  cities  need  to  react  to  new, 
disruptive  transformations  and  become  smart 
and  sustainable  is  being  put  into  practice.  More 
and more cities are applying the Open Innovation 
2.0 (OI2) principles as a new approach to today’s 
innovation challenges [1]. These are caused by the 
digitisation of society and the associated disruptive 
technology solutions, forcing us to reconsider how 
technology can best be applied to create a better 
quality of life. Redesigning the city for the digital 
era means redesigning society at large, engaging 
citizens and other stakeholders in innovation, and 
actively seeking new connections between sectors 
[2]. In brief, this means redesigning in co-creation, 
going far beyond technical solutions alone.

Redefining ‘smart’
‘Smart’ is not just about technology. Although tech-
nological development enables new facilities that 
were  not  available  before,  smart  solutions  also 
improve liveability and contribute to a vibrant and 
sustainable city for citizens. But most of all, smart 
solutions enable citizens themselves to actively pro-
duce societal value, instead of simply being passive 
consumers of services provided by the government. 
Redefining smart cities with a focus on creating qual-
ity of life for and by citizens implies creating a smart 
society. This transformation poses a new design chal-
lenge: how to engage all citizens so they use the new 
facilities and actively take part in creating a higher 
quality of life for themselves and others?

Resilience is an important factor in the smart city 
philosophy. Instead of believing that everything can 
be engineered and controlled, we have to accept 
uncertainty.  This  affects  the  (new)  solutions  and 
systems that we design, but it also affects the citi-
zens themselves. Future city residents have to be 
prepared to deal with unexpected, disruptive events; 
they must be able to consciously adapt their behav-
iour, and they must value personal development. 
The challenge lies in giving  participating citizens 
the  space  and  opportunities  to  become  enthusi-
astic, and to be involved. This requires smart sys-
tems,  offering  and  co-creating  human-centred, 
personalised services. These should meet people’s 
needs, using a shared platform that contributes to 
economic resilience. But it also requires rethinking 
the participation process, to ensure the support and 
active involvement of all citizens in the transform-
ation process.

Redesigning the ‘rules of the game’
To  make  sure  the  new  technology  solutions  are 
people  centric  and  technology  enabled,  and  not 

just technology driven, we need to define the ‘rules 
of the game’. When the digital and real world are 
blended, with the aim of improving the quality of 
life for citizens, we need to reconsider issues like 
standardisation,  handling  of  data,  privacy  and 
openness  in  the  public  space  from  the  perspec-
tive of societal value and ethics. We will need new 
instruments and frameworks to link the digital and 
physical spaces. In the same way as municipalities 
are responsible for safety in the public space, the 
new virtual layer on the public space also has to be 
designed with the principles of inclusiveness, open-
ness, safety and accessibility in mind, to ensure 
the public interest, and at the same time as a pre-
requisite for active citizen participation.

In brief, the aim is a future scenario in which citi-
zens  live  together  well  and  unwanted  develop-
ments are avoided. But how can we achieve this? 
How can we safeguard public interests? How can 
we deal with resistance to new technology, and pro-
tect people from undesirable commercial interests? 
How can we drive innovation and build an attrac-
tive economic climate in smart cities? And how can 
we achieve shared, efficient use of resources in the 
public domain to create higher societal value?

Redesign the approach
Nobody knows what the future will look like, but it 
will most probably be disruptively different. We are 
going through a change process in which the trad-
itional control changes from leadership to orches-
tration [3]. It may be tempting to wait until we have 
more clarity on the new solutions and the required 
approaches. In the city of Eindhoven we do not want 
to wait until things are clear, because by then, con-
sciously or unconsciously, the rules of the game will 
have been set. This is urgent, because experiments 
have already started. So we have decided for col-
laborative  experimentation.  We  believe  that  the 
path to the desired future can be reached by mix-
ing innovative technology with creative design. So 
we adopt a design approach; starting from a basic 
vision, experimenting in different settings and col-
laborating with a number of stakeholders. This is 
what we mean by iterative co-design of the smart 
society.

In the Open Innovation 2.0 — Yearbook 2015 we 
describe the practical challenges in the paradigm 
shift  to  OI2  based  on  experience  gained  in  real 
smart city projects [4]. This year our contribution — 
again in a cooperation between Eindhoven Univer-
sity of Technology (TU/e) and the Municipality of 
Eindhoven — continues along the bumpy path of 
innovation towards a smart and resilient society.

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.088

The transition: from hardware 
to services via data
In earlier contributions we emphasised that smart 
solutions use technology to create new applications. 

These then become meaningful only if they address 
relevant societal needs. To explain the architecture 
of such smart systems, we introduced a four-lay-
ered model (Figure 1) [5; 6].

Figure 1: A four-layered model of smart systems [6]

Societal Needs

Meaningful 
applications

Services: for societal stakeholders

ICT: data & applications

Devices: sensors, lights

Infrastructure: dense network

Technology
enablers

We  argued  that  in  the  coming  years  innovation 
will take place at all four levels of this model (see 
Figure 2). Innovation can take place in the separate 
layers, but each layer also enables innovation in 
the levels above. To ensure innovation through the 
entire system, two aspects need to be addressed.

• 

• 

The openness of the system (the left column in 
Figure 2) to ensure transparency and safeguard 

public interest at all levels of the system. This 
requires innovation beyond contemporary busi-
ness models, which in many cases are based on 
ownership of (parts of) the system.
The orchestration of innovation (the right col-
umn in Figure 2) by organising the collaboration 
in the quadruple helix structure (consisting of 
citizens, industry, knowledge institutions and 
municipalities).

Figure 2: Prerequisites of innovation [5]

Guarding public interest

Innovation in quadruple helix

Creating conditions to safeguarding the public interest 
and availability of basic services by providing open access
 to the system at all levels.

System
architecture

Ensuring continuous innovation and co-creation
with citizens by organising the quadruple helix

Open knowledge
Providing access to acquire knowledge 
of proven user profiles for co-creation partners

Open data
Providing access for involved parties to data
for general/public interest

Services

Data

Social innovation
Continuous monitoring of societal issues 
to priorities innovation

Services innovation
Stimulating application development to ensure 
the ambition is realised, within code of conduct

Open access
Providing access for modules to the systems (the ‘lego’ lampost)

Devices

System innovation
Organising development of a standard interface between systems

Open connectivity

Infrastructure

Providing access for public services to the infrastructure

Structure innovation
Continuous monitoring alignment of shorter and 
longer term decisions in infrastructure with vision 
and roadmap to avoidconflicts and mismatches

OPEN INNOVATION YEARBOOK 201589

In the context of smart society innovation, munici-
palities have an important role in establishing the 
preconditions for innovation. By setting the right 
criteria in tenders for solutions to be implemented 
in the public space, they can safeguard public inter-
est, cyber-safety and the availability of the basic 
services  by  providing  open  system  access  at  all 
levels:  connectivity  to  the  public  services  infra-
structure and access to the devices, to the data for 
public interest and to acquired knowledge. Munici-
palities can also decide not to invite tenders based 
on available solutions, but instead to use innova-
tions or even a continuous innovation process in co-
creation with citizens. By using the quadruple helix 
structure, innovation can be ensured at all levels of 
the system, together with the development of solu-
tions for societal challenges that citizens regard as 
important.

In last year’s contribution [4], we described sev-
eral  smart  city  projects  and  indicated  the  chal-
lenges in the transition to open innovation start-
ing from societal needs. During 2015 we continued 
these  projects  and  identified  the  crucial  role  of 
data. Measuring and monitoring systems in public 
spaces or social contexts generate data in the pub-
lic space, which is not in itself a new phenomenon; 
traffic counts have been used for years. What is 
new is that intelligent technology enables applica-
tions beyond the specific goal for which the data 
is  gathered.  Secondly,  until  now  data  collection 
was limited to actions taken for public purposes, 
whereas nowadays public parties initiate sensoring 
in public space. And yet, this data plays a vital role 
in the transition to a smart society. So far, there 
has been little regulation of data collected in the 
public space. As a result, many companies design 
their business models around the collection and 
ownership of data, just as they do in other domains. 
But the public space is a different context in which 
people  do  not  have  an  ‘opt  out’,  and  privacy  is 
a major concern. New business models are needed 
that respect privacy and give users of public spaces 
control of their own data.

Several studies of the future of smart and sustain-
able cities of 2050 [7; 8] indicate a desired future 
scenario in which ambient networks provide con-
nectivity for (wireless) access to data and energy. 
These  studies  emphasise  that  citizens  should 
be  able  to  choose  freely  from  a range  of  avail-
able options. The system ensures the privacy and 
security of users, who are always in control. Those 
systems are user focused: that means users can 
understand  how  the  systems  work,  and  there  is 
a range of available solutions that plug in directly 
to the city’s open platform. Cities offer a good bal-
ance in the quality of neighbourhoods and infra-
structure, with affordable services for all income 

levels. Experts interviewed in these studies indi-
cate the need for democratised systems based on 
open data. Democratised means that the systems 
are open, bidirectional, multipurpose platforms on 
which (renewable) energy and energy management 
services are available to all.

Smart cities need a smart infrastructure. This ‘Inter-
net of Things’-like infrastructure serves a range of 
functions and aims. It enables the development of 
new services and empowers people as owners of 
data. But unfortunately we encounter challenges in 
current projects. These mean the roles and respon-
sibilities of all the innovation partners are chang-
ing, so we have to redefine the rules of the game 
together while we are playing it. We recognise the 
need for a shared framework, and especially for 
data to ensure open, multipurpose, democratised 
platforms.

Creating new frameworks: 
open data principles
Because developments in (open) data are still very 
new, regulations at national or European level are 
not yet available or are still insufficiently detailed. 
Most commercial companies now focus primarily 
on gaining ownership of data as a new business 
model. Most people are not yet aware of how this 
strategy will affect their privacy, and how it will 
limit the availability of services in their daily lives. 
Achieving Eindhoven’s ambition of co-designing an 
open, multipurpose, democratised platform requires 
a clear position in relation to the ownership, open-
ness and use of data gathered in the public domain. 
The aim is to safeguard public interest and to max-
imise value for society as a whole, rather than for 
individuals or companies.

The Municipality of Eindhoven has developed a set 
of  open  data  principles,  which  serve  as  a  first 
attempt  to  deal  sensibly  with  data  in  the  public 
space (see Table 1) [9]. These principles follow the 
policy that all data collected (unconsiously from 
the people), generated or monitored in the public 
space remains public property, and they prevent 
that data from being monopolised by any party or 
parties. Clear agreements about how data is man-
aged benefit trust, transparency and acceptance of 
new technologies by citizens and businesses in the 
city. In this way, citizens are assured that their data 
will not be misused, and that the public interest is 
safeguarded.

Opening up data aims to promote innovation and 
to help create an attractive economic climate in 
the new smart society. The essence is that every-
one can make money by using data from the public 
domain, but the data itself remain in public owner-
ship, so that other parties (both public and private) 

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.090

can use and re-use it. The open data of the City of 
Eindhoven is freely available [10]. Innovative appli-
cations  of  data  and  healthy  competition  should 
ensure a sustainable and self-sustaining ecosys-
tem. The sharing of data aims at more efficient use 
of the city infrastructure, for example in terms of 
network capacity and sensors. The (literal) physical 
space is limited, and opening it encourages shared 
use of the facilities that are already there. By keep-
ing data as public property, the city aims to secure 
the (yet unknown) added value of data for the pub-
lic interest.

The city is currently working on embedding the prin-
ciples in legislation to create a legal structure, in 
which undesired developments in the use of (open) 
data can be prevented. Defining the principles is 
a step in the iterative design process; we expect 
that by applying the principles in practice we will 
be confronted by new and unexpected situations, 
and that we will gain progressive insights that will 
require us to review the principles. These principles 
provide a start for constructive dialogue with the 
quadruple helix partners, and they will be adjusted 
as and when necessary in the course of the design 
process.

Table 1: Open data principles by the city of Eindhoven [9]

a.

b.

c.

d.

e.

f.

g.

h.

Data residing in the public space (further on: data) belong to everyone. These data are an asset of the public. Data 
that are collected, generated or measured (for example by sensors that are placed in the public space) should be 
opened up such that everyone can make use of it for commercial and non-commercial purposes. While doing so, 
privacy and security aspects should be taken into consideration.

Data may contain personal information. These data can therefore impact the private life of individuals. The rules 
specified in the Personal Data Protection Act are applicable here. These data may only be opened up after they 
have been processed (for example, by anonymization or aggregation) such that there are no privacy threats 
anymore.

Data which do bring privacy or security risks along may only be used according to the privacy legislation. Storage 
and processing of these data should be performed according to the existing legislation.

Data that do not contain personal information (anymore) should be placed such that everyone can access these 
data in an equal manner (for example, through an Open Data portal). We call this “opening up” the data. There 
should be no technical or juridical obstacles that limit, discriminate or block access to data.

Data are always opened up free of charge, without unnecessary processing (as much as possible in a raw form) 
and according to the functional and technical requirements that are yet to be defined.

A distinction is made with regard to personal data (such as an e-mail address or payment information) that are 
collected with full awareness and after an explicit consent of the individuals. Use of these data is defined by 
an agreement between the parties involved according to the rules of privacy legislation (such as an end user 
agreement).

The city authorities always have an insight into which data is collected in the public space, independently of 
whether these data can or cannot be opened up.

The city authorities keep an ongoing dialogue with the parties that contribute to the development of data infra-
structure in the city and strive to create earning opportunities and a fruitful economic climate.

Next steps for Eindhoven in 
becoming a smart society
The challenge on the path to a smart society is to 
(re-)design the game and the rules of the game. 
The open data principles are a first effort to do this. 
These principles should be reviewed in use to see 
if they actually lead to more innovation and have 
the ability to prevent undesired business models in 
public spaces.

At  the  same  time  this  is  a  huge  opportunity  to 
develop local solutions that answer questions with 
a global impact. The municipalities, the companies 
and the knowledge institutions have the ambition 
to not only regard solutions as a ‘local pilot project’, 
but also to seek ways to increase their scale. This 
is needed to enable companies to develop sustain-
able businesses, but also to speed up the develop-
ment of the platform and smart society services. 

Given its size, Eindhoven would not be an attractive 
market on its own, but can serve as a front-runner. 
Solutions that work for Eindhoven cannot simply 
be transferred to other contexts: they need to be 
tuned to meet the new and specific local needs. But 
a smart platform will enable added-value services 
in different contexts, using similar hardware mod-
ules but with different services, settings and usage 
scenarios. This also makes it possible to adjust the 
services and solutions over time.

In  Eindhoven,  stakeholders  are  already  used  to 
working together in ‘living labs’, which allow innov-
ative  solutions  to  be  designed  and  tested.  To 
actively seek entirely new connections and solu-
tions,  and  to  scale  solutions  across  sectors,  all 
parties are willing to look beyond the pilot stage. 
Living labs are the ideal context in which to jointly 
practice design: to prototype, to test, to learn and 

OPEN INNOVATION YEARBOOK 201591

to discover step by step which elements work. The 
next challenge for living labs will also be to learn 
about the concepts and requirements that facilitate 
success (the rules of the game) and to facilitate 
the adjustment and enrolment in new contexts, in 
a continuing iterative process. This aims at eventu-
ally up-scaling the solutions, creating a larger mar-
ket and speeding the development of the platform 
and services.

Redesigning the city to become sustainable for the 
digital era indeed requires a shift from leadership 
to orchestration. In a quadruple helix collaboration, 
innovation is turned into a process of participation. 
This aims to create shared value by making the 
lives of citizens more enjoyable, with sustainable 
business  propositions  by  existing  and  new  com-
panies. The municipality takes responsibility not 
only to promote and facilitate living labs, but also 
to ensure that this happens safely and inclusively, 
in the same way that security in public spaces is 
ensured. The virtual layer on the public space — 
the public data layer — has to be considered in the 
same way: dealing with openness, accessibility and 
security.

Conclusion
The transition to smart cities is in full swing. To 
really  become  a  smart  society,  we  need  to  put 
citizens at centre stage. To really become a city 
with resilient citizens, we need to truly empower 
people. And to really get there, we need a different 
approach: a design approach.

Data  play  a  vital  role  in  the  transition  towards 
a  smart  society.  We  believe  that  if  an  open, 
multipurpose democratised platform is applied in the 
public domain, data can empower people to become 
active producers of societal value. And to ensure 
a strong foundation on which to built the smart soci-
ety, we need to regulate at different levels.

Locally, the rules of the game need to be designed 
to facilitate innovation to the maximum possible 
extent. We need to avoid data monopoly and lock-
in business models in the (virtual) public space, as 
well as safeguard the public interest and maximise 
social value over individual or commercial profit. 
Issues  of  ownership  and  privacy  must  be  safe-
guarded, and cities must be aware of their public 
responsibility to facilitate and orchestrate the basic, 
local infrastructure to enable these processes in 
the best possible way. Eindhoven has developed 
open data principles as a first attempt to sensibly 
deal with data in the public domain. But this is still 
only a first step. How this will enable new business 
development and economic prosperity at the same 
time will also need to become clear in the follow-
ing steps.

Collaboration with other European cities is neces-
sary to ensure a market that enables sustainable 
development  of  the  platform,  the  smart  society 
services and the necessary frameworks and regu-
lations. Dealing with open data in particular is still 
very new, and regulations at national or European 
level are not yet available or are still insufficiently 
detailed.  A lot  of  progress  has  been  made  with 
the living labs in Eindhoven, but it is only through 
cooperation that we can learn which way is best 
and achieve the scale needed to guide the trans-
formation process in the right direction. In the EU 
frameworks, regulations can be designed to pro-
mote a vibrant society and at the same time build 
a thriving economy.

In Europe we value human rights and have firmly 
secured a number of issues, such as openness, pri-
vacy and security. It is only through cooperation 
that Europe can compete with other international 
economic  power  blocs.  The  views,  concepts  and 
activities in Eindhoven as described in this chap-
ter depend greatly on good contextual frameworks. 
EU citizens as well as local and national author-
ities have to be alert to maintain and promote their 
values.

For instance, the currently negotiated Transatlan-
tic Trade and Investment Partnership (TTIP) [11] 
may underpin some of our European rights. TTIP 
does not cover data, although this will form the 
main basis for new business models. Critics have 
expressed  concerns  about  a  number  of  issues, 
including data protection and privacy [12]. In the 
current proposal, for instance, personal data of EU 
citizens could be transferred to any country trump-
ing the EU data protection framework. There are 
also negotiations dealing with issues like mass sur-
veillance and encryption. In its current form, this 
may subvert the democracy of actions and conse-
quently directly limit potential local opportunities 
and solutions. We should prevent any provisions on 
data protection, any lock-in of existing data trans-
fer agreements, and any form of standardisation of 
encryption or interoperability of encryption stand-
ards that could lead to a possible lock-in of those 
standards [12]. Although the protection of personal 
data now seems to be covered, the collection of 
other data in public space still seems to be poorly 
regulated.

Finally, we also recognise that we are exploring 
new territory on the path to the desired future, 
and we will have to constantly adapt to new and 
changing insights. The smart society will not hap-
pen  by  itself.  Municipalities,  institutions,  com-
panies and engaged citizens need to be involved 
and inspired to participate. In Eindhoven, we will 
continue with new forms of collaboration in our 

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.092

current and future living labs. By integrating our 
visions and strategies, all the actors and stake-
holders in the cities will contribute in some way 
(through regulation, knowledge, funding and feed-
back) to the city’s power to innovate.

[8]  Sashinskaya, M. and Schilze, C., ‘Open data — the 
new oil for smarter EU cities’, Open Innovation 2.0 — 
Yearbook 2013, European Commission, 2013.

[9]  Raadsinformatiebrief — Openbaarheid van data in 
de openbare ruimte (Council information letter in Dutch), 
Municipality of Eindhoven, 2015.

References
[1]  Salmelin, B., ‘Open Innovation 2.0 creates new 
innovation space’, Open Innovation 2.0 — Yearbook 
2015, European Commission, 2015.

[2]  Salmelin, B., ‘Open Innovation 2.0: a new milieu’, 
Open Innovation 2.0 — Yearbook 2014, European 
Commission, 2014.

[3]  Salmelin, B., ‘European Commission innovation 
strategies and support for innovation — why and how’, 
Open Innovation 2.0 — Yearbook 2013, European 
Commission, 2013.

[4]  Den Ouden, E., Valkenburg, R., Schreurs, M. and Aarts, 
E., ‘Smart lighting solutions as a catalyst for smart 
cities: practical challenges of ambitious innovation 
partners’, Open Innovation 2.0 — Yearbook 2015, 
European Commission, 2015.

[5]  Den Ouden, E., Valkenburg, R. and Aarts, E., 
‘Participative innovation in smart urban lighting’, Open 
Innovation 2.0 — Yearbook 2013, European Commission, 
2013.

[6]  Den Ouden, E., Valkenburg, R., and Aarts, E., ‘Service 
design based on smart urban lighting’, Open Innovation 
2.0 — Yearbook 2014, European Commission, 2014.

[7]  Den Ouden, E. and Valkenburg, R., Future telling 
2050 — D2.1 report — Drivers for change, R4E, 2015 — 
www.RoadmapsforEnergy.eu

[10]  https://data.eindhoven.nl/

[11]  ‘About TTIP’, DG Trade, European Commission — 
http://ec.europa.eu/trade/policy/in-focus/ttip/about-ttip/

[12]  Ferdández Pérez, M., TTIP and digital rights, EDRi, 
2015.

Contact

Drir. Rianne Valkenburg
Value producer LightHouse, Eindhoven 
University of Technology
Professor of designerly innovation, The 
Hague University of Applied Sciences
a.c.valkenburg@tue.nl

Drir. Elke den Ouden
Fellow new business development in 
public–private value networks
Strategic director LightHouse, 
Eindhoven University of Technology
e.d.ouden@tue.nl

Drs. Mary Ann Schreurs
Vice mayor/executive councillor for innovation
City of Eindhoven
m.schreurs@eindhoven.nl

OPEN INNOVATION YEARBOOK 201593

World cities that need transformation
Intellectual capital of 36 cities

Abstract

Today half the world’s population lives in cities. Cities have been recognised as centres for the production 
of knowledge, culture, information and innovation. Thus, metropolitan areas, rather than nation states, 
will shape the world’s social, cultural, technological and economic agendas in this century. National gov-
ernments are aware of the significant impact of city competitiveness, resulting in increasing investments 
in building unique city characteristics to boost city as well as national economic development.

In the past, cities generally set their visions and goals by considering tangible assets as the main driver 
of a city’s prosperity. In the knowledge economy, the role of intangible assets has become fundamental 
to wealth creation. As a result, an intangible assets framework that allows navigation from the present 
reality to the future vision has become an urgent need for all cities [3].

Although there is an awareness of the role a city plays in sustaining a country’s competitiveness, a well-
accepted city-level intangible asset model and ranking is still lacking. This paper introduces a city-level 
intellectual capital (CIC) covering human capital, market capital, process capital, renewal capital and 
financial capital. The top six CIC cities are Paris, London, New York, Stockholm, Copen hagen and Helsinki.

Introduction

After the dawning of the knowledge economy, how intangible assets affects competitiveness has 
increasingly caught worldwide attention. The concept of intellectual capital was the product of such 
a trend. Intellectual capital originated at the organisational level and was gradually applied to regional 
and national level, ever since Edvinsson and Malone [6] proposed the Skandia model. Intellectual capital 
(IC) includes not only knowledge, competence, skills, culture, employee motivation, working methods and 
systems, but also customer relationships, partner relationships and other processes to leverage these 
assets. Although hard to grasp, IC could mainly be represented by three distinct components, namely 
human capital, structural (organisational) capital and relational (social, customer) capital [6]; [15]; [37].

Over the past 15 years, some researchers have extended the concept and its application to the national 
level, such as Bontis [1], Pasher and Shachar [33], and Lin and Edvinsson [18]. Among various national-level 
IC researchers, the author of this article continuously conducted a large-scale national intellectual capital 
(NIC) study and published a series of 12 booklets for 48 countries [19]-[29]. This paper attempts to extend 
my past national-level research to the city level, mainly because of the rising of the borderless global 
economy.

Since the ‘city’ is gradually becoming the source of future competitiveness in any country, this CIC 
research reports the relative position of 36 world cities. Hopefully, city governments and relevant poli-
cymakers can learn from examples of globally competitive cities to gather essential resources to build 
facilitating environments for future city development.

Background
Nowadays,  cities  and  regions  all  over  the  world 
devote a large amount of resources, encouraging 
and cultivating the collective knowledge or IC to 
shape future competitiveness [3]. Since half the 
world’s population lives in cities [35], cities have 
been recognised as centres for the production of 
knowledge,  culture,  information  and  innovation 
[32]. In addition, the increasing growth of mega-
cities, particularly in the emerging economies, adds 
further importance to this perspective [38].

City Mayors (an international think tank for urban 
affairs)  believes  that  metropolitan  areas,  rather 
than nation states, will shape the world’s social, cul-
tural, technological and economic agendas in this 
century [38]. The Lisbon strategy on sustainable 

European cities also recognises that cities are the 
centres of knowledge and sources of growth and 
innovation.  The  strategy  promotes  a process  to 
make  the  European  Union  the  most  competitive 
and dynamic economy in the world, leading to more 
and better jobs with greater social cohesion [32]. 
For example, Amsterdam becomes the hub of city 
networks in Europe; Barcelona is known as the ‘city 
of knowledge’ and the best place for know ledge 
workers [10]; and Rotterdam has retained its role 
as a transit hub in Europe by providing new trans-
portation knowledge and capability [39]. In addition, 
Poitiers  in  France  utilised  information  and  com-
munications technology, multimedia and a high-
tech work team to transform itself from a barren 
rural location to a learning city with research and 
development (R & D), education and a recreation 

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.094

future  scope  theme  park.  Such  transformation 
has attracted global tourists as well as 70 compa-
nies, thus creating 1 500 jobs inside the park and 
12 000 job opportunities in the vicinity [17].

In the United States, New York is the global eco-
nomic  centre  and  Silicon  Valley  is  the  base  of 
emerging  industries.  Similarly,  Austin,  Texas  is 
another city known for its so-called wired for tal-
ent strategy that is designed to attract talent from 
around  the  country  [38].  In  Canada,  Edmonton, 
Alberta  is  pursuing  a  vision  for  an  international 
smart city through ‘smart research, smart workforce 
and a smart culture’. These cases clearly explain the 
value of creating an environment in which people 
and businesses can succeed and thrive in cities.

Literature review reveals that urban planning is cur-
rently the main stream in this field of study. A small 
percentage  of  city  studies  include  liveable  cities, 
sustainable cities, knowledge cities, intelligent cities, 
smart cities and creative cities. Yet few studies par-
ticularly focus on CIC [29]; [12]; [35]; [32], and most 
of CIC publications are conceptual papers. For the 
studies that have real city data, generally they report 
status of a limited number of cities or one city only. 
For example, Rodrigues and Tomé [35] studied three 
cities — Braga, Luxembourg and Ruse; Hyrkas, Kianto 
and Rings [12] studied four municipalities located in 
southeastern Finland — Lappeenranta, Joutseno, 
Lemi and Taipalsaari; and Maria and Marti [30] used 
one city, Mataro in Spain, to illustrate their model. 
The book Intellectual capital for communities: nations, 
regions, and cities, published by Bounfour and Edvins-
son [2], only described a small portion of CIC.

For non-academic literature, world organisations, 
governments  and  private  organisations  showed 
interest in evaluating cities from different perspec-
tives. For example, the European Union regularly 
ranks European cities based on six defining char-
acteristics, namely smart economy, smart mobility, 
smart governance, smart environment, smart living 
and smart people (www.smart-cities.eu) [38].

Based on 39 indicators, every year Mercer reports 
the results of Mercer quality of living survey for 
221  cities  and  the  world’s  ‘greenest’  cities.  The 
Economist  retrieved  some  of  Mercer's  results 
and published ‘The world’s most ‘liveable’ cities’. 
From 2010, a private company in Australia named 
2thinknow started to collect data of 162 indicators 
and reports an ‘innovative cities’ ranking for around 
300  cities,  covering  architecture,  art,  business, 
economy, education, environment, food and health.

In  addition  to  the  above  efforts,  Table  1  sum-
marises eight city-level models for assessing IC, 
smart cities or cities with quality of life.

CIC — Navarro and associates
Navarro  and  associates  [32]  propose  that  CIC 
should cover human capital, process capital, com-
mercial capital, communication capital, R & D and 
innov ation  capital,  and  environmental  capital. 
They advocate that IC is essential for the economic 
growth of cities and local IC provides a measure of 
hidden wealth of the city.

CIC — Viedma
Hyrkas, Kianto and Rings [12] regard municipalities 
as non-profit organisations with the main task to 
produce services to their citizens’ needs. And ser-
vices are essentially intangible. To meet this chal-
lenge most effectively and professionally, IC is the 
foundation [12]. Although it is difficult to quantify 
IC, especially in the public sector, they proposed to 
use Viedma’s [40] model consisting of human cap-
ital, market capital, process capital and renewal and 
development capital to define and measure CIC.

CIC — Maria and Marti
Maria and Marti [30] proposed a CIC benchmark-
ing system based on the IC navigator model (Skan-
dia model). According to the model, there are four 
areas of focus with regard to IC: human capital, 
customer and market capital, process capital, and 
renewal and development capital.

CIC — Hsu
As a master thesis from National Chengchi Univer-
sity, Taiwan, my student Ms. Hsu and myself worked 
together to come up with 29 CIC indicators, cover-
ing human capital, market capital, process capital, 
renewal capital and financial capital, comparing 
four major cities in Taiwan.

PricewaterhouseCoopers city of opportunity 
indicators
PricewaterhouseCoopers, together with New York 
City, has been researching cities of opportunity for 
five consecutive years and particularly highlighted 
the  importance  of  IC  in  city  development.  The 
2010 results include that Stockholm was named 
the ‘green capital’ of Europe, Chicago was the best 
business city with a high quality of living, and Syd-
ney was renowned for its landscape with visionary 
city policies. In its most recent 2011 version, 60 
indicators were used to rank cities of opportunity.

Features of smart cities
Rodrigues and Tomé [34] studied smart or know-
ledge  cities  and  reported  the  need  for  a radical 
reformulation when entering the knowledge-based 
economy. Based on these two researchers, smart 
cities score high in smart economy, smart mobility, 
smart living, smart governance, smart environment 
and smart people.

OPEN INNOVATION YEARBOOK 201595

Features of cities with quality of life
Donald [5] identifies eight features of cities with qual-
ity of life, including social cohesion, human services, 
learning, community safety, affordable housing, public 
transportation, environmental quality and culture.

Features of creative cities
According to Cabrita and Cabrita [3], there is a high 
demand for new approaches to IC assessment and 
valuation, including services, information, technol-
ogy and intellectual property. Generally speaking, 
the  quantity  and  quality  of  human  capital  and 
derived creativity will determine the parameters 
for success. These two scholars provide four dimen-
sions to explain and develop creative cities, includ-
ing scientific creativity, economic creativity, cultural 
creativity and technological creativity.

As  mentioned  earlier,  the  nexus  of  competitive 
advan tage has shifted from nation states to those 

cities and regions that can generate, retain and at-
tract the best talent. Accordingly, future competitive 
cities should have a high degree of knowledge and in-
novation; that is, intangible assets. This trend will lead 
to increased competition for human, intellectual and 
material resources but will also force cities to cooper-
ate with and learn from one another [38].

The CIC ranking reported in this paper enables a city 
to locate its relative position for benchmarking and 
coping strategies. Measuring CIC enables cities to 
determine  what  they  must  take  into  account  to 
make  them  a  source  of  wealth,  prosperity,  wel-
fare and future growth. Given that the measure-
ment  and  management  of  the  IC  of  cities  has 
great similarities to that of countries, the advances 
made in the management of the IC of nations can 
be extrapolated to the case of cities [30]. In what 
follows, the definition and components of CIC are 
briefly introduced.

Table 1: Eight studies about CIC, cities with quality of life and creative cities

Viedma (2004)

Maria and Marti 

HSU (2008)

PwC - Cities of 

Rodrigues and 

Donald (2001) 

Cabrita and 

(2003)

Opportunity

Tomé (2011)

Cities with quality 

Cabrita (2010)

of life

Creative cities

Human capital

Human capital

Human capital

60 indicators

smart economy

Social cohesion

Scientific creativity

Market capital

Customer  &  Market 
capital

Market capital

smart mobility

Human services

Economic creativity

Process capital

Process capital

Process capital

smart living

Learning

Cultural creativity

Renewal and devel-
opment capital

Renewal  and  devel-
opment capital

Renewal capital

smart Governance

Community safety

technological 
creativity

Financial capital

smart Environment

Affordable housing

smart people

Public 
transportation

Environmental 
quality

Culture

CIC
City competitiveness is the reflection of CIC. CIC 
development  can  also  be  based  on  the  Skandia 
model [6] and national IC model [18]. The compo-
nent capitals may include city human capital, mar-
ket capital, process capital, renewal capital and 
financial capital, briefly explained hereunder.

City human capital
City human capital consists of knowledge about 
facts, laws and principles relating to city interac-
tions  and  other  specialised  and  communication 
skills. It may include knowledge, wisdom, expertise, 
vision and individual capability to accomplish city 
goals. Relevant indicators include population with 
higher education, internet subscribers and percent-
age of knowledge workers.

City market capital
City market capital is similar to external relational 
networking and social capital in a microsetting in 
that it represents a city’s capabilities and successes 
in  providing  an  attractive  and  competitive  incen-
tive in order to meet the needs of its partners, while 
also sharing knowledge with other cities. It includes 
a relationship with other local as well as inter national 
cities, such as strategic partners, city loyalty, city sat-
isfaction, city branding and city export and import.

City process capital
City  process  capital  comprises  the  non-human 
sources of knowledge in a city. Embedded in a city’s 
infrastructure, these sources facilitate the creation, 
accessibility and dissemination of information, and 
infrastructures needed for collaboration, knowledge 

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.096

flow and better outputs, such as information tech-
nology system, hardware, software, database, labo-
ratories and organisational structure.

City renewal capital
City renewal capital is a city’s future intellectual 
wealth and the capability to utilise city resources 
for  innovation  and  renewal,  such  as  investment 
in R & D, patent and trademark development, and 
a number of new companies that sustain a city’s 
competitive advantage.

City financial capital
City  financial  capital  is  the  wealth  of  a city  and 
reflects  the  ‘outcomes’  of  city  governance,  such 
as disposable household income and city GDP. In 
this study, city financial capital is the city’s GDP per 
capita (ppp) in US dollars transformed to a score 
between 1 and 10.

Methods
For city-level analysis, it is very hard to get longitu-
dinal data for world cities. Eurostat has quite a com-
prehensive database; however, it is for cities in Europe 
only. Different databases have different focus, such 
as PricewaterhouseCoopers on cities of opportunities, 
Rodrigues and Tomé [34] on smart cities, Donald [5] on 
cities with quality of life and Cabrita and Cabrita [3] 
on creative cities. Based on the literature review, we 
first select relevant indicators in Eurostat, Pricewater-
houseCoopers and the Global Urban Competitiveness 
Research Centre for City and Competitiveness in China. 
The greatest number of cities with the largest amount 
of required data is 36. They cover 15 cities in Europe, 
11 in North America, seven in Asia, two in Australia 
and one in the Middle East. Due to a large amount of 
missing values, we have to supplement data in ‘search 
global city data,’ ‘Numbeo’ and ‘international city indi-
cators database from Taipei City Government’.

After  several  rounds  of  model  validation,  Table  2 
shows the best possible CIC model with limited data. 
Due to a large amount of city-level missing values, 
some indicators in human capital and renewal capital 
use national-level indicators from the IMD database. 
The assumption is that some national systems apply 
to all cities in the nation, such as public education 
investment,  gender  equality,  human  development 
index, years of education and intellectual rights pro-
tection. In this model, there are six indicators for each 
of the component capitals, except process capital 
which has seven and financial capital which is a sin-
gle indicator of city ppp. This paper describes intel-
lectual capital of 36 cities over a period of six years, 
from 2007 to 2012.

The model consists of two different types of data: 
data with an absolute value, such as ‘years of edu-
cation’, and data with a qualitative rating based on 
a scale of 1 to 10, such as ‘attracting foreign direct 
investment (FDI)’. Although subjective, qualitative 
rating on the degree or magnitude of certain vari-
ables is unavoidable, as evaluating intangible assets 
cannot  be  fully  represented  by  merely  adding  up 
absolute numbers. For a meaningful integration of 
the quantitative score and qualitative rating, the ratio 
of the absolute value relative to the highest value of 
each quantitative variable was calculated and multi-
plied by 10 to transform the number into a 1-to-10 
score. The data transformation procedures have been 
repeated for all numerical indicators of human cap-
ital, market capital, process capital, renewal capital 
and financial capital. The overall city intellectual cap-
ital ranking, as shown in Table 3, includes the mean 
scores of the five types of capital and the total score 
of city intellectual capital for each city.

Table 2: Indicators of human capital, market capital, process capital and renewal capital

Human Capital

Market Capital

Process Capital

H1

H2

H3

H4

H5

H6

M1

M2

M3

M4

M5

M6

P1

P2

P3

P4

P5

X1

X2

X3

X4

X5

X6

X7

X8

X9

X10

X11

X12

X13

X14

X15

X16

X17

R&D personnel researchers

*Public Education Investment

*Gender equality

*Human Development Index

*Years of education

*Overall productivity

number of laboratory and research center

Number of Global 500 headquarters

international tourists

attracting FDI

cost of business occupancy (reverse)

city population

living quality

air quality

number of cultural and arts organizations

public transportation single ride price (reverse)

households broadband access

OPEN INNOVATION YEARBOOK 201597

P6

P7

Renewal Capital R1

R2

R3

R4

R5

R6

X18

X19

X20

X21

X22

X23

X24

X25

CPI plus Rent index (reverse)

Green spaces (%)

number of international papers

industry promoting power

patent applications

*Business R&D spending

*Intellectual rights protection

*Cooperation between universities and enterprises

Table 3: Intellectual capital score and ranking of 36 world cities

2007-2012
Mean

Human capital 
7.45

Market capital
5.15

Process capital 
6.43

Renewal capital 
5.45

Financial capital
5.46

Overall CIC 
29.83

SD

city

Amsterdam

Barcelona

Beijing

Berlin

Boston

Chicago

Copenhagen

Dubai

Frankfurt

Hamburg

Helsinki

Hong Kong

Houston

Indianapolis

London

Lyon

Melbourne

Milan

Minneapolis

Munich

New York

Paris

Philadelphia

Pittsburgh

Score

7.59

7.13

4.44

7.44

7.91

7.91

8.49

5.02

7.46

7.39

8.73

6.61

7.91

7.91

7.71

7.78

7.83

6.73

7.91

7.59

7.91

7.91

7.91

7.91

San Francisco 7.91

Seattle

Seoul

Shanghai

Singapore

Stockholm

Sydney

Taipei

Tel Aviv

Tokyo

Toronto

Vienna

7.91

7

4.44

7.02

8.5

7.83

7.59

8.61

6.86

7.71

7.64

0.99

0.94

1.31

0.93

1.42

Ranking
23

28

35

26

6

6

4

34

25

27

1

33

6

6

20

18

16

32

6

22

6

5

6

6

6

6

30

35

29

3

16

23

2

31

19

21

Score

4.96

5.09

5.58

4.99

5.2

3.03

4.76

5.19

4.43

5.05

5.23

5.87

4.5

4.92

7.85

4.96

4.81

4.95

4.69

5.16

6.18

8.56

4.97

5.03

4.45

4.73

5.23

5.68

5.07

4.61

4.24

4.45

4.92

6.35

4.88

4.76

Ranking
20

13

7

17

10

36

26

11

34

15

9

5

31

22

2

19

25

21

29

12

4

1

18

16

32

28

8

6

14

30

35

33

22

3

24

27

Score

7.2

5.68

2.95

7.14

6.7

7.17

6.78

4.11

7.33

6

6.7

4.99

6.8

6.46

8.01

6.69

6.8

5.91

6.57

6.76

8.12

8.58

5.94

6.59

7.25

6.65

4.95

3.18

5.98

7.69

8.48

4.37

6.01

6.38

7.93

6.79

Ranking
9

30

36

11

17

10

15

34

7

26

18

31

12

23

4

19

12

29

22

16

3

1

28

21

8

20

32

35

27

6

2

33

25

24

5

14

Score

5.24

4.04

3.56

5.74

6.32

6.15

6.64

4.18

5.96

5.59

6.27

4.05

6.31

6.11

4.95

4.93

5.13

3.85

6.46

5.85

6.47

4.57

6.02

5.93

6.69

6.48

4.74

3.54

5.37

6.87

5.01

4.85

5.72

5.77

5.21

5.55

Ranking
22

33

35

17

7

10

3

31

13

19

9

32

8

11

26

27

24

34

6

15

5

30

12

14

2

4

29

36

21

1

25

28

18

16

23

20

Score

5.39

4.21

1.88

3.56

5.22

5.46

6.23

5.46

5.18

6.89

5.29

5.9

5.03

5.46

7.57

5.46

5.23

5.25

5.46

5.46

6.3

9.5

4.99

5.46

5.51

5.46

3.42

2.06

8.68

5.97

5.34

5.42

5.39

6.47

5.34

5.58

Ranking
21

32

36

33

28

12

7

13

29

4

25

9

30

13

3

13

27

26

13

13

6

1

31

13

11

13

34

35

2

8

23

20

22

5

24

10

4

Score

30.37

26.15

18.4

28.87

31.35

29.72

32.9

23.95

30.35

27.4

32.21

27.4

30.55

30.86

36.1

29.8

29.8

26.69

31.07

30.82

34.97

39.11

29.83

30.91

31.8

31.22

25.33

18.89

32.12

33.64

30.9

26.68

30.65

31.83

31.06

30.31

Ranking
20

32

36

27

10

26

5

34

21

28

6

28

19

16

2

24

25

30

12

17

3

1

23

14

9

11

33

35

7

4

15

31

18

8

13

22

Findings
With respect to the 6-year data for 36 cities, the 
top 10 cities in the overall ranking list are, in order, 
Paris, London, New York, Stockholm, Copenhagen, 
Helsinki, Singapore, Tokyo, San Francisco and Bos-
ton. Among the top 10, five are in Europe, three are 
in North America and two are in Asia. Interestingly, 
the five European cities and Tokyo are all capitals 
of their country, whereas none of the three cities 

in North America is a capital. Singapore is a city 
nation. The overall results of this CIC confirm the 
general perception that the three super-large cities, 
Paris, New York and London, are the top three CIC 
cities. The capital of the three Nordic countries also 
has a high degree of CIC.

Cities ranked 11th-20th are, in order, Seattle, Min-
neapolis, Toronto, Pittsburgh, Sydney, Indianapolis, 

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.098

Munich, Tel Aviv, Houston and Amsterdam. Among 
these 10 cities, five are in the United States, one is 
in Canada, three are in Europe and one is in Aus-
tralia. Tel Aviv ranked 2nd in human capital as it has 
very high R & D researcher and overall productivity.

Cities  ranked  21st-30th  are,  in  order,  Frankfurt, 
Vienna,  Philadelphia,  Lyon,  Melbourne,  Chicago, 
Berlin, Hamburg and Hong Kong (tied) and Milan. 
Among the 10 cities, six are in Europe, two are in 
the United States, one is in Australia and one is in 
Asia. Chicago is particularly weak in market capi-
tal; raw data shows that Chicago is low in ‘number 
of laboratory and research centres’ and ‘attracting 
FDI’. Hong Kong ranked fifth in market capital but 
is relatively weak in human capital, process capital 
and renewal capital.

Cities ranked 31st-36th are, in order, Taipei, Barce-
lona, Seoul, Dubai, Shanghai and Beijing. Shanghai 
and Beijing are relatively strong in market capital, 
ranked sixth and seventh, respectively. However, 
these two cities are relatively weak in human capi-
tal, process capital and renewal capital.

In order to see the relationship between CIC and 
ppp of the 36 cities, we prepared several graphs. 
Figure 1 shows a relatively high correlation between 
overall CIC and ppp. That is, generally speaking, the 
higher the CIC the higher its ppp. Figure 2 shows 
a majority of cities cluster in the middle right of 
the graphs, indicating the competition of acquiring 
good human capital among the cities. The correl-
ation between human capital and ppp is not as high 
as that in Figure 1.

Figure 1: Scatterplot of overall CIC vs. ppp

Figure 2: Scatterplot of human capital vs. ppp

Figure 3 shows a spreading graph with low correl ation 
between market capital and ppp. Figure 4 shows two 
parallel lines. London and Singapore are on the upper 
left side. A majority of the cities fall in the middle 
part of the graph. The two lines indicate a positive 

correlation between process capital and ppp, yet with 
different degrees. Figure 5 shows two clusters. The 
large cluster indicates a positive correlation between 
renewal capital and ppp, whereas the small cluster 
shows limited correlation between the two.

Figure 3: Scatterplot of market capital vs. ppp

OPEN INNOVATION YEARBOOK 201599

Figure 4: Scatterplot of process capital vs. ppp

Figure 5: Scatterplot of renewal capital vs. ppp

In order to see the progression of the top six CIC 
cities,  scatterplots  of  human  capital  vs.  renewal 
capital and market capital vs. process capital are 
presented in Figure 6 and Figure 7. Human capital 
and renewal capital together are long-term intangi-
ble assets that cities need to possess. Figure 6 shows 
that even though the specified six cities are ranked 
as the top six CIC, New York had some progress in 
human capital and renewal capital over the years. 
Paris, London, Helsinki and Stockholm regressed in 
renewal  capital.  Copenhagen  progressed  more  in 
human capital than in renewal capital.

Figure 7 shows that, over the years, Paris increased 
a little in process capital with relatively stable mar-
ket capital. London regressed quite a bit in process 
capital, however with a little increase in market 
capital. New York had great improvement in mar-
ket capital and a little increase in process capital. 
Stockholm regressed in both market and process 
capital. Copenhagen increased market capital, how-
ever regressed in process capital. Helsinki increased 
more in market capital than in process capital.

Figure 6: Human capital vs. renewal capital of the top six cities from 2007-2012

Figure 7: Market capital vs. process capital of the top six cities from 2007-2012

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.0100

It is understandable that market capital is more 
short-term oriented and depends on the regional or 
global economic situation. As the world economy is 
still stagnant, declines in market capital after the 
2008-2009  global  financial  crisis  can  be  antici-
pated. However, city governments can continuously 
build on better process capital, such as air quality 
and living quality.

From Figure 6 and Figure 7, Paris and London need 
to  be  aware  of  losing  future  competitiveness  in 
long-term intangible assets — human capital and 
renewal capital. From the raw data, Paris declined 
in R & D researchers, public education investment, 
patent applications, business R & D spending and 
cooperation between universities and enterprises. 
London  declined  in  R  &  D  researchers,  gender 
equality, number of international papers and patent 
applications. Both Paris and London are cities with 
long histories that attract tourists. Some Nordic 
cities, such as Stockholm, Helsinki and Copenhagen, 
are becoming more and more attractive to tour-
ists. In addition, they provide a social environment 
with high degrees of freedom and equality, which 
is important to the young generation. City trans-
formation advice for Paris and London is to create 
an environment that attracts and nurtures young 
talent to stay and develop their career. R & D is 
also an area worthy of further pursuit, as renewal 
and innovation may be future determinants of city 
competitiveness.

Due to space constraint, we only plotted the top 
six CIC cities for the development paths of human 
capital vs. renewal capital and market capital vs. 
process capital over the years 2007-2012. Other 
cities can refer to Figures 1-5 and Table 3 for their 
relative position, and then compare and contrast 
with their benchmarking cities for future intangible 
assets development. For example, Shanghai and 
Beijing are at the bottom-left corner of the graphs, 
except for market capital. Human capital requires 
time to develop over the years. These two cities 
in China need to start a journey of accumulating 
human capital in order to reach the level of human 
capital in European cities and United States cities. 
The  same  situation  applies  to  renewal  capital. 
Although China is increasing its R & D investment, 
for a higher degree of renewal capital, business 
R & D spending and intellectual rights protection 
are also very important.

Conclusion
The selected 36 cities are all well known in each 
country. However, when comparing their CIC on 
a global arena, some of their rankings are not as 
good as expected. The main reason is that when 
there is fierce competition, some good cities will 
be competing down as others are stronger. The 

main  goal  of  reporting  CIC  ranking  is  for  each 
city to find its relative position for guiding future 
development. It is also important to note that the 
scores are relative. Even though Paris declined in 
R & D researchers, it does not necessarily mean 
a  reduction  in  the  number  of  R  &  D  research-
ers. It could be that other cities increased their 
R & D researchers and pushed Paris’s score of this 
particular indicator down.

For long-term intangible assets — human cap-
ital and renewal capital — for the top six cities, 
New York had a little progress in human capital 
and renewal capital over the years. Copenhagen 
progressed more in human capital than in renewal 
capital.  Paris,  London,  Helsinki  and  Stockholm 
regressed in renewal capital. For the short-term 
intangible assets — market capital and process 
capital — Paris increased a little in process cap-
ital with relatively stable market capital. London 
regressed quite a bit in process capital, however 
with a little increase in market capital. New York 
has made great improvement in market capital 
and a little increase in process capital. Stockholm 
regressed in both market capital and process capi-
tal. Copenhagen increased market capital, however 
regressed in process capital. Helsinki increased 
more in market capital than in process capital.

Although  these  six  cities  are  already  at  the  top 
of CIC, there are still signs of warning. From their 
path of development, New York is the best without 
decline in both long-term and short-term intan gible 
assets over the six  years. Copenhagen is mainly 
improving its intangible assets, except some decline 
in process capital. Helsinki has relatively large scale 
decline  in  renewal  capital.  Stockholm  needs  to 
worry about its decline in market capital, process 
capital and renewal capital.

In addition to the six top CIC cities, two more cities 
(7th and 8th CIC) are particularly weak in human 
capital. Singapore’s ranking is 29th with low scores 
in public education investment and gender equal-
ity. Tokyo lags behind in R & D researchers, public 
education investment and gender equality. These 
low-degree indicators explain why Tokyo ranked 
only 31st in human capital.

City transformation suggestions especially go to 
Stockholm, Singapore and Tokyo. Sweden used to 
be high in intangible assets [18]; [19]; [27]. Stock-
holm’s decline in three out of four CIC capitals sent 
a signal for city transformation. Two Asian cities, 
Singapore  and  Tokyo,  are  low  in  human  capital. 
Although  history  and  culture  may  play  a role  in 
explaining this outcome, higher education invest-
ment and enhancing gender equality should be the 
right direction for future development.

OPEN INNOVATION YEARBOOK 2015101

As  mentioned  previously,  cities  will  become  the 
unit of competition rather than nation states in the 
future. Attending to the intangible assets devel-
opment may decide the future talent hubs of the 
world. There are abundant clues from the figures 
and tables presented in this paper. City transform-
ation suggestions are provided using the example 
of Paris, London, Shanghai and Beijing.

This  paper  presents  a preliminary  model  of  CIC, 
with limited data from various sources. We are only 
able  to  have  an  almost  complete  dataset  of  36 
global cities. Future studies may refine the model 
when more data becomes available.

References
[1]  Bontis, N., ‘National intellectual capital index — 
A United Nations initiative for the Arab region’, Journal of 
Intellectual Capital, Vol. 5, No 1, 2004, pp. 13-39.

[2]  Bounfour, A. and Edvinsson, L., Intellectual capital for 
communities in the knowledge economy: nations, regions 
and cities, Elsevier Butterworth-Heinemann, Oxford, 
2005.

[3]  Cabrita, M. R. and Cabrita, C., ‘The role of creative 
industries in stimulating intellectual capital in cities and 
regions’, proceedings of the European Conference on 
Intellectual Capital, 2010, pp. 171-179.

[4]  Global occupancy costs — Offices, DTZ, 2011 
report — http://www.dtz.com/StaticFiles/Research/
DTZ %20Occupier %20Perspective %20Global %20
Occupancy %20Costs %20Offices %202011.pdf; 2010 
report — http://www.propertyweek.com/Journals/44/
Files/2011/3/4/DTZ %20Occupier %20Perspective %20
Global %20Occupancy %20Costs %20Offices %202011.
pdf

[5]  Donald, B. (2001). ‘Economic competitiveness and 
quality of life in city regions: Compatible concepts?’, 
Canadian Journal of Urban Research, Vol. 10, No 2, 2001, 
pp. 259-274.

[6]  Edvinsson, L. and Malone, M. S., Intellectual capital: 
Realising your company’s true value by finding its hidden 
brainpower, HarperBusiness, New York, 1997.

[7]  Eurostat database (2007-2009) — http://ec.europa.
eu/eurostat/help/new-eurostat-website

[8]  CASS (2007-2012 year books), Global Urban 
Competitiveness Research Centre for City and 
Competitiveness — http://www.gucp.org/GUCP/Main

[9]  Hoornweg, D., Nunez, F. R., Freire, M., Palugyai, N., 
Villaveces, M. and Herrera, E. W., City indicators: now to 
Nanjing, World Bank Policy Research Working Paper, No 
4114, 2007.

[10]  Hospers, G., ‘Creative cities in Europe: urban 
competitiveness in the knowledge economy’, 
Intereconomics, 2003, pp. 260-269.

[11]  Hsu, C. C., ‘Indicators and analysis of city 
intellectual capital: comparisons of Taipei, Kaohsung, 
Taichung, and Tainan’, unpublished AMBA master thesis, 
National Chengchi University, 2008.

[12]  Hyrkas, E., Kianto, A. and Rings, M., ‘IC as 
a developmental tool for municipalities’, proceedings 
of the International Conference on Intellectual Capital, 

Knowledge Management and Organisational Learning, 
2010, pp. 373-380.

[13]  IMD online database (2007-2012) — https://www.
imd.org/wcc

[14]  International city indicators database, 
Deptartment of Budget, Accounting and Statistics, 
Taipei City Government (2007-2012) (in Chinese) — 
http://163.29.37.101/pxweb2007-tp/dialog/statfile9.asp

[15]  Johnson, W. H. A., ‘An integrative taxonomy of 
intellectual capital: measuring the stock and flow of 
intellectual capital components in the firm’, International 
Journal of Technology Management, Vol. 18, 1999, 
pp. 562-575.

[16]  Landry, C., The creative city: a toolkit for urban 
innovators, Earthscan, London, 2000.

[17]  Larsen, K., ‘Learning cities: the new recipe in 
regional development’, OECD Observer, No 217/218, 
1999, pp. 73-76.

[18]  Lin, C. Y. Y. and Edvinsson, L., National intellectual 
capital — A comparison of 40 countries, Springer 
Publishing Co., New York, 2011.

[19]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, T., 
National intellectual capital and the financial crisis in 
Denmark, Finland, Iceland, Norway, and Sweden, Springer 
Publishing Co., New York, 2014.

[20]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, T., 
National intellectual capital and the financial crisis in 
Australia, Canada, Japan, New Zealand, and the United 
States, Springer Publishing Co., New York, 2014.

[21]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, T., 
National intellectual capital and the financial crisis in 
Argentina, Brazil, Chile, Colombia, Mexico, and Venezuela, 
Springer Publishing Co., New York, 2014.

[22]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, 
T., National intellectual capital and the financial crisis 
in France, Germany, Ireland, and the United Kingdom, 
Springer Publishing Co., New York, 2014.

[23]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, T., 
National intellectual capital and the financial crisis in 
Austria, Belgium, the Netherlands, and Switzerland, 
Springer Publishing Co., New York, 2014.

[24]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, T., 
National intellectual capital and the financial crisis in 
Bulgaria, Czech Republic, Hungary, Romania, and Poland, 
Springer Publishing Co., New York, 2014.

[25]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, 
T., National intellectual capital and the financial crisis 
in Israel, Jordan, South Africa, and Turkey, Springer 
Publishing Co., New York, 2014.

[26]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, 
T., National intellectual capital and the financial crisis 
in Indonesia, Malaysia, the Philippines, and Thailand, 
Springer Publishing Co., New York, 2014.

[27]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, T., 
National intellectual capital and the financial crisis in 
Brazil, Russia, India, China, Korea, and South Africa, 
Springer Publishing Co., New York, 2013.

[28]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, 
T., National intellectual capital and the financial crisis 
in China, Hong Kong, Singapore, and Taiwan, Springer 
Publishing Co., New York, 2013.

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.0102

[29]  Lin, C. Y. Y., Edvinsson, L., Chen, J. and Beding, T., 
National intellectual capital and the financial crisis in 
Greece, Italy, Portugal, and Spain. Springer Publishing Co., 
New York, 2013.

[30]  Maria, J. and Marti, V., ‘A methodology and 
a framework for measuring and managing intellectual 
capital of cities: a practical application in the city of 
Mataro’, 6th World Congress on the Management of 
Intellectual Capital and Innovation, Hamilton, Canada, 
2003.

[31]  Numbeo (2010-2012) — http://www.numbeo.com/
cost-of-living/

[32]  Navarro, J. L., Ruiz, V. R. and Peña, D. N., ‘A 
theoretical intellectual capital model applied to cities’, 
proceedings of the European Conference on Intellectual 
Capital, 2012, pp. 17-25.

[33]  Pasher, E. and Shachar, S., The intellectual capital 
of the State of Israel — 60 years of achievement, Office 
of the Chief Scientist, Jerusalem, 2007 — www.moital.
gov.il/ic

[34]  PricewaterhouseCoopers cities of opportunity 
(2008-2012) — http://www.pwc.com/us/en/cities-of-
opportunity.html

[35]  Rodrigues, K. and Tomé, E., ‘Knowledge cities: 
a Portuguese case’, proceedings of the European 
Conference on Intellectual Capital, 2011, pp. 350-358.

[36]  Search global city data (2012) — http://www.nyc.
gov/html/ia/gprb/html/global/global.shtml

[37]  Stewart, T. A., Intellectual capital: the new wealth of 
organisations, Doubleday, New York, 1997.

[38]  Thite, M., ‘Smart cities: implications of urban 
planning for human resource development’, Human 
Resource Development International, Vol. 14, No 5, 2011, 
pp. 623-631.

[39]  Van Geenhuizen, M. and Nijkamp, P., ‘Improving 
the knowledge capability of cities: the case of Mainport 
Rotterdam’, International Journal of Technology 
Management, Vol. 15, No 6/7, 1998, pp. 691-709.

[40]  Viedma Marti, J. M., ‘CICBS: a methodology and 
framework for measuring and managing intellectual 
capital of cities — A practical application in the city of 
Mataró’, Knowledge Management Research & Practice, 
Vol. 2, 2004, pp. 13-23.

Contact

Carol Yeh-Yun Lin
Professor, Department of 
Business Administration
National Chengchi University, Taiwan
yehyunln@nccu.edu.tw

OPEN INNOVATION YEARBOOK 2015103

Smart city network boosting open innovation
An open innovation platform provided by Finland’s six largest cities

Introduction

The six city strategy — open and smart services — is a strategy for sustainable urban development 
carried out by the six largest cities in Finland: Helsinki, Espoo, Vantaa, Tampere, Turku and Oulu (Figure 
1). The main objective of the strategy, which will be carried out in 2014-2020, is to create new know-
how, business and jobs in Finland. The strategy is a part of the implementation of Finland’s structural 
fund programme for sustainable growth and jobs 2014-2020, forming its integrated territorial invest-
ment (ITI) component [1].

The additional objectives of the six city strategy is to improve the services offered by cities, increase 
the competitiveness of businesses and enable more widespread participation in development work. 
City services are developed based on three focus areas: open innovation platforms, open data and 
interfaces, and open participation. The central idea is to view cities as platforms, whose operations and 
services should be developed in ways that also allow easier participation by third parties. Cooperation 
becomes easier as cities open up their processes and data, and produce tools and operating models 
that facilitate joint development.

Figure 1: The six cities network

Cities as basis for innovation platforms
In  the  six  cities  collaboration,  open  innovation 
platforms are regarded as functional elements in 
a city community that create a basis for new solu-
tion creation and from there enable new business 
creation [2]. Open innovation platforms consist of 
infrastructure, physical and virtual elements, pro-
ductised processes and members of communities to 
form a strong value-added environment.

The national open innovation platform network sup-
ports the new business development in a modern, 

international,  competitive  digitalised  world.  The 
environment  also  supports  the  development  of 
the new devices, service solutions and institutional 
research. The target is to offer a ‘one door’ solu-
tion for focus groups. The other main objective is to 
offer a structured platform for digitalisation of the 
municipality services and to involve the companies 
to create new innovative ways to implement ser-
vices and thus utilise all available local resources. 
With this model the role of the city will evolve from 
service provider to service creation enabler.

Open innovation platform collaboration
The  six  cities  open  innovation  platforms  collab-
oration is aiming to build a strong network of the 
open innovation platforms by the six biggest cities 
in Finland [3]. By building the national network of 
open  innovation  platforms,  driving  new  compe-
tence development, business and jobs creation will 
become more efficient. Utilising the wide variety 
of knowledge and specialisation in different cities, 
the best practices and concepts will be collected to 
form an excellent basis for a new type of city busi-
ness modelling (smart market creation).

The open innovation platform network will provide 
companies with a possibility to access several cities 
at the same time, instead of single cities. Besides 
the critical mass, the collaboration offers a pos-
sibility to share best practices in between the cit-
ies on how to develop new smart city innovations. 

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.0104

Six cities and their innovation platforms together 
are more competitive and attractive than separate 
platforms for six cities.

The piloting phase of the six-city open innovation 
platform collaboration consists of platforms from 
the respective six cities (Figure 2). The platforms are 

developed and tested together. The open in novation 
platform also links together the platforms working 
with the same topic, such as district development 
activities. All the platforms are going to be presented 
as a smart city portfolio to make it easier for compa-
nies and others interested to find and get access to 
relevant innovation platforms for any specific need.

Figure 2: Six cities open innovation platform

Finnish smart city open 
innovation tool for Europe
The smart city sector is a growing global business. 
The  market  for  smart  cities  will  reach  a value  of 
EUR 1.5 trillion globally by 2020 [4]. As part of the 
European Union-funded integrated territorial invest-
ment activity, the six city strategy (6Aika) collabor-
ation will provide a model for an open innovation plat-
form network which can be used to support European 
businesses to exploit this remarkable opportunity.

Conclusion
It is essential for European developments to create 
new  tools  and  environments  that  support  com-
panies to match the demand from growing, global 
smart city and digitalisation market. An important 
part  of  the  support  is  to  provide  sufficient  scale 
open innovation platforms for product and service 
development. When being able to show references 
from the world’s most advanced smart city markets, 
global success is guaranteed.

The six city strategy open innovation platform links 
Finland’s six largest cities and their innovation plat-
forms under one network. The network is now in its 

pilot phase. Defined innovation platforms are tested 
in real circumstances with real users and real mar-
ket circumstances. The experiences from the pilot-
ing will be available at the end of 2017, witnessing 
the power of smart city cooperation.

References
[1]  The six city strategy — Open and smart services, 
strategy document, 6Aika, 2014.

[2]  6Aika (2016) — http://6aika.fi

[3]  Six cities collaboration — Six cities open innovation 
platform project plan, 2014.

[4]  Frost & Sullivan, Benefits of carbon neutrality in 
a rapidly changing business environment, Sitra Studies, 
102, 2015.

Contact

Mika Rantakokko
Chief operating officer
The six city strategy, open 
innovation platforms
mika.rantakokko@ouka.fi

OPEN INNOVATION YEARBOOK 2015105

The Smart Countries and Cities Congress

Abstract

Information and communication technologies have a great impact on city and territory manage-
ment, which is quickly evolving. New interrelations between territories and knowledge have appeared, 
reshaping our environments and restructuring competency domain interactions.

A smart city has become a territory open for experimentation by startups and innovators of any kinds, 
including living labs, fab labs, media labs, making and co-working spaces. A few examples are Chicago 
(United States) with its chief data officer, Nantes (France) with its all-integrated services, Helsinki (Fin-
land) with its smart Kalasatama project, and Barcelona (Spain) with its Poblenou district ecosystem.

In this context, the following elements have been underlined.

• 
• 

• 

• 

• 

the importance of the economical stakes linked to technologies for cities and territories;
the position of large French enterprises in delivering services to local communities: Veolia, Suez 
and Vinci are world leaders;
the strength of the French innovation ecosystem: many innovation startups are offering solutions 
at the forefront in these domains;
the strong wishes from French economical partners: ‘francophonie’ and more generally French-
friendly countries are expecting support from French operators on these sensitive technologies;
the Paris situation as the ‘city of light’: a city which was at the birth of human rights, which is at 
the crossroads of Europe, and which, through its involvement in the European smart city project 
of the Horizon 2020 EU programme, is the obvious capital city of the debate related to this major 
transformation of cities.

Smart Countries and Cities 
Congress objectives
Ensuing from these findings, the Smart Countries 
and  Cities  Congress  (S3C  Paris)  was  created  as 
a global event dedicated to technologies related 
to connected cities and territories and open to all 
stakeholders in these areas. Initiated in 2014 by 
the Sikiwis company as a regional conference, S3C 
Paris changed its format and location in 2015 and 
has now taken on an international dimension with 
the support of Smart-C European hub of reflection 
on smart city and of the Territories of Tomorrow 

Foundation  [1]  dedicated  to  the  development  of 
technologies in cities and territories.

The S3C objectives are as follows:

• 

• 
• 

to  increase  economic  development  and 
productivity;
to protect the environment and climate;
to accelerate social development and improve 
quality  of  life  in  order  to  boost  ‘productive, 
green and happy cities’.

Figure 1: S3C Paris

The actors
The congress allows officials in charge of cities and 
territories  to  meet  all  innovation  actors.  Among 
them were the following.

Accenture,  Alcatel,  Alstom,  ARM,  BlaBlaCar,  Bol-
loré,  Bosch,  CapGemini,  CGI  Group,  Inc.,  Citrix, 
Congo Telecom, Deutsche Bank, EDF, ERDF, Gen-
eral Electrics, IBM, Intel, JCDecaux, L&T Infotech, 
McKinsey&Company, MERCK, Oracle, Renault, Sie-
mens,  Sikiwis,  Shell,  Sistra,  Transdev,  Vedecom, 
Veolia, etc.

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.0106

Figure 2: Participants in the congress

The S3C Paris in 2015
For its first edition, the S3C Paris 2015, located in 
the Paris Congress Centre on September 1, 2 and 3, 
run under the patronage of Mr Laurent Fabius, Min-
ister for Foreign Affairs and International Develop-
ment, and of Mrs Axelle Lemaire, Secretary of State 
for Digital Affairs from the Ministry of the Economy, 
Industry and Digital Sector. It enabled stakeholders 
of intelligent territories and cities from around the 
world to discuss the issues and discover the experi-
ments underway in the city of tomorrow.

Articulated as a centre of expertise, the congress 
was organised around 250 practical and educa-
tional  conferences,  complemented  with  an  area 
where exhibitors presented immediately applicable 
solutions to increase the intelligence of cities and 
territories.

the  human  development  index  of  their  country 
through new technologies.

S3C Paris welcomed 200 international senior gov-
ernment representatives (ministers, secretaries of 
state, governors) who were engaged in workshops 
to develop a joint statement.

250  lecturers,  all  international  experts  in  their 
fields, have joined forces to present the different 
facets  of  the  city  of  tomorrow  around  subjects 
as diverse as economics and trade, open govern-
ment, security, healthcare, smart telecommunica-
tions, environment and COP21, intelligent buildings, 
smart energy management, connected home, smart 
transportation, education and future employment, 
the  Internet  of  Things,  innovations  in  cloud  and 
mobile technologies, and big data.

The event brought together 1 650 people coming 
out of 65 countries, one third being mayors and 
elected representatives. Attendees studied together 
in situ how to speed up economic development and 

Along with the speakers, more than 150 experts 
presented  solutions  and  innovations  created  by 
their companies. 17 startups demonstrated innov-
ations which enable territories and cities to better 

OPEN INNOVATION YEARBOOK 2015107

interact with their citizens and to safeguard their 
welfare as well as that of future generations.

Congress programme
Themes were centred on digital technologies and 
equipment for countries and cities and on how they 
could contribute to economic, social and environ-
mental development.

Day 1: Ministers day — Smart government and 
augmented territories: economic, social and en-
vironmental stakes — Ministerial declaration

•  Smart economy
•  Smart security
•  Smart jobs
•  Smart education
•  Smart health

Day 2: Smart devices — Technologies for growth, 
for competitiveness and for quality of life

•  Smart equipment
•  Smart services
•  Smart arts and culture
•  Smart commerce
•  Smart operations and maintenance

Day 3: Environment technologies and COP21

•  Smart buildings
•  Smart telecommunications
•  Smart transportation
•  Smart services
•  Smart grids

Running in parallel all along the 3 days there were 
three additional topics: innovating cities in France/
living and microlabs/mobility

Congress results
The congress was a great success and some of the 
highlights were:

• 

• 

• 

• 

the opening of the congress by Mr Michel Val-
ache, from the Paris Chambre de commerce et 
d’industries, who illustrated the stakes identi-
fied by the Chamber in this technological area;
the  keynote  speech  of  Mrs  Axelle  Lemaire, 
Secretary of State in charge of digital affairs, 
demonstrating a strong position of the French 
government  on  all  technologies  related  to 
territories;
the interview Mrs Lemaire gave France 24 from 
the ‘government area’;
keynote  speeches  of  Mr  Janaillac,  Transdev 
CEO;

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 

• 
• 

• 

the number of media covering the whole spec-
trum ranging from traditional media, web and 
professional  newspapers  to  large  audience 
means;
the unanimously positive welcome of the event 
by all media;
the announcement of the creation of the Smart 
City Consortium, a grouping of more than 10 
innovating European enterprises (France, United 
Kingdom, Spain), several of them being part of 
the S3C Paris Scientific Committee (Actility, ITB, 
Sikiwis);
the speech of Mr Stéphane Beaudet, Mayor of 
Courcouronnes, vice-president of the Associ-
ation of the Mayors of the Île de France region, 
appointed at the Conseil national des villes by 
the French Prime Minister, and administrator 
of the Syndicat des transports d’Île de France, 
presenting the results of a study on territory 
responsibilities and showing smart city experi-
mentations, undergoing or under preparation, in 
more than half of the Île de France districts;
the  startups  competition  with  its  Jury  des 
maires, chaired by Mr Beaudet and incorporat-
ing the general directors of System-X, Efficacity 
and BeAngels, and the VCs jury, which includes 
large French and foreign businesses, in particu-
lar Innovacom, Elaia and Alven Capital;
competition winners have received good vis-
ibility — diffusion of the three winner names 
to 6 000 AFIC (Association Française des Inves-
tisseurs pour la Croissance) members — which 
reinforces  the  probability  for  them  to  raise 
funds even outside the S3C Paris attendees;
the visit paid by former ministers Mrs Valérie 
Pécresse and Mrs Chantal Jouanno and by Mr 
Beaudet to the main exhibition actors like Veo-
lia Environnement and to the startups in the 
‘Start-up alley’;
the attendance of a large number of high-level 
speakers from both public and private sectors, 
originating from many countries;
the declaration of ministers and government 
representatives which has been a recognised 
success due to the significance of its recom-
mendations and the extremely large consensus 
that came out;
the ‘Government — SVIP (Super Very Important 
Person) evening which gathered chairpersons 
and high-level representatives of large compa-
nies together with government officials;
the quality of speeches;
the fact that conferences went smoothly and 
on time, a great challenge due to the starting 
of four new conferences every half hour during 
3 days;
the ERDF (Electricité Réseau Distribution France) 
demonstrator visit has also been very appreci-
ated by attendees.

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.0108

The Living labs y espacios de innovación de America 
Latina y el Caribe (LEILAC) network, created in 2010 
by the Territories of Tomorrow Foundation [2] at the 
occasion of the ‘Innovation and Prospective’ semi-
nar at the Unesco headquarters in Paris, was rep-
resented by most of its 25 members from Europe 
and Latin America.

The number of industrialists who mentioned major 
contracts under negotiations should also be noted, 
confirming the relevance of having such an event 
in Paris.

Ministerial declaration
Government  representatives  (from  ministries, 
regions and cities) from 50 nations met together in 
S3C Paris to elaborate statements on the citizens’ 
rights to smart technologies. This led to the follow-
ing statements:

• 

• 

• 

• 

• 

• 

• 

cities, territories and countries should investi-
gate innovative technologies to improve life-
style, economic development and environmen-
tal protection;
innovative technologies in cities, territories and 
countries should be investigated with the per-
spective of services to citizens, not as a means 
to reduce freedom or other basic human rights;
cities and territories are to implement one or 
more initiatives to reduce carbon emissions;
cities should include energy-efficiency criteria 
for further new infrastructure development;
cities and territories should promote energy-
efficient behaviours among its citizens and its 
economic players;
cities and territories should promote environ-
mental  protection  behaviours  among  their 
citizens;
cities and territories should investigate means 
of easy access to general interest data.

NB: apart from the second statement with 79 % 
of support, all statements were endorsed by more 
than 92 % of the workshop voters.

Paris becoming the world 
capital city for innovation
In 2016, and following the lessons learnt from pre-
vious smart cities conferences like the S3C Paris 
of 2015, Paris will feature a number of important 
events related to smart cities, smart territories and 
innovation labs, having in mind that a smart ter-
ritory is first — whether related to local projects 
or to European and international programmes — 
a place of experimentation.

digital factories, microfactories, co-working spaces, 
TechShop, makerspaces, etc. Their common objec-
tive is to promote innovation and entrepreneurship 
by leveraging collective intelligence and collabor-
ative dynamics in the territories.

Initiated by the Conservatoire national des arts et 
métiers (CNAM) [3] located in Paris and by the Ter-
ritories of Tomorrow Foundation, the lab of labs 
(LDL) will identify and characterise existing labs as 
well as new emerging labs, through contacts with 
initiatives of territories.

Some of the elements to be studied by the LDL 
cover innovation management practices, mapping 
of the labs, business models related to the func-
tioning of the labs, current and future economic 
impact of the labs on the territories, success fac-
tors of innovation projects, future ‘dominant design’ 
and foreseeable developments to be expected for 
labs.  In  addition,  the  LDL  may  carry  out  ad  hoc 
studies on request.

It should be noted that the CNAM is becoming one 
of the major actors in the French living labs arena 
through the creation of a living lab related to cul-
tural heritage, with its first implementation in Lyon 
where the Maison du Chamarier, a Middle Ages his-
torical monument, will be the pole of a Lyon district 
rehabilitation.

A collaborative social network on innovation
Currently innovation actors act within ecosystems 
that are dynamic but fragmented. Following some 
meetings  and  discussions  during  the  S3C  Paris 
2015, the Centre Michel Serres on Innovation and 
the Territories of Tomorrow Foundation are jointly 
creating a new innovation project on the theme of 
a collaborative social network for innovation actors.

The objective of this project is to remove barriers 
between these ecosystems, thus facilitating the 
creation and diffusion of innovations.

Viva Technology Paris
A  large  forum  named  Viva  Technology  Paris  is 
currently  launched  in  France  aiming  at  bringing 
together about 5 000 startups, and putting them 
in a relationship with industrialists, investors and 
opinion leaders of the world.

Its first edition will take place at the exhibition park 
located  near  Porte  de  Versailles  in  the  south  of 
Paris from June 30 till July 2 2016. The last day will 
be open to the public.

Creation of a lab of labs
A wide variety of physical spaces dealing with in-
novation exists: living labs, fab labs, hackerspaces, 

Over 30 000 m2, Viva Technology Paris will feature 
a place named ‘Hack’ for exchange and collabor-
ation between startups and visitors, a conference 

OPEN INNOVATION YEARBOOK 2015109

area  called  ‘Imagine’,  and  an  ‘Experience’  area 
devoted to demonstrating new technology contri-
butions to everyday life.

The S3C Paris in 2016
Organisation

Startups  interested  in  participating  are  already 
entitled to register through the event website [4]. 
The most suitable candidates will then be selected 
from March 2016 on.

The Parisian innovation arc

Labs of any kind are booming in the eastern part 
of  Paris  thanks  to  this  innovation  arc  which  is 
a cooperative project of the greater Paris. The pro-
ject mobilises local authorities who cooperate with 
all potential actors of city innovation in order to 
develop the city of the future, smart, sustainable, 
inclusive, connected and open to citizens.

A few days after the Viva Technology event, the S3C 
Paris [5] will take place from July 12 till 17. These 
dates will conveniently allow welcoming high-level 
attendees considering the euro 2016 finale which 
will  happen  on  July  10,  and  the  French  national 
celebrations on July 14.

The 2016 congress intends to construct in 10 days 
a short-lived demonstrator having a real size. This 
demonstrator will first be presented to government 
representatives, then open to the public. Several 
high-rank  industrialists  have  already  confirmed 
their willingness to contribute to this operation, of 
which technical conditions for realisation are under 
scrutiny.

Figure 3: S3C Paris 2016

FUTURE CITIES AND REGIONS IN THE CONTEXT OF OPEN INNOVATION 2.0110

Programme
On the first day, the ‘Ministers’ day’, smart and open 
governments as well as augmented territories will 
be addressed.

References
[1]  http://www.territories-of-tomorrow.org/

[2]  Loechel, A. J.-M., ‘Living Lab, French Tech Hubs et 
Smart Cities — Et la planète devient laboratoire’, 2016.

The second day will focus on technology for trans-
portation and energy: COP21 and the sustainable 
city.

[3]  http://www.cnam.fr/

[4]  www.vivatechnologyparis.com

[5]  www.s3cparis.com

On the third day, Internet of Things, big data and 
smart services will be discussed.

Contact

Conclusion
The city of Paris has become an important place in 
the area of innovation, the S3C Paris being one of 
its main players. The latter will continue promoting 
concrete solutions as well as demonstrating their 
potentialities and their effectiveness.

Jean-Pierre Euzen
S3C committee member
Former head of sector and deputy of unit
European Commission
europa@euzen.eu

OPEN INNOVATION YEARBOOK 2015HOW TO OBTAIN EU PUBLICATIONS

Free publications:

(cid:127) 

one copy: 
via EU Bookshop (http://bookshop.europa.eu);

(cid:127)   more than one copy or posters/maps: 

from the European Union’s representations (http://ec.europa.eu/represent_en.htm);  
from the delegations in non-EU countries (http://eeas.europa.eu/delegations/index_en.htm);  
by contacting the Europe Direct service (http://europa.eu/europedirect/index_en.htm) or  
calling 00 800 6 7 8 9 10 11 (freephone number from anywhere in the EU) (*).

(*) 

The information given is free, as are most calls (though some operators, phone boxes or hotels may charge you).

Priced publications:

(cid:127) 

via EU Bookshop (http://bookshop.europa.eu).

 
K
K
-
A
I
-
1
5
-
0
0
1
-
E
N
N

-

O

p

e

n

i

n

n

o

v

a

t

i

o

n

2

.

0

y

e

a

r

b

o

o

k

2

0

1

6

Print 
Web 

ISBN 978-92-79-53365-5 
ISBN 978-92-79-53366-2 

doi:10.2759/061731
doi:10.2759/0306