5-Year
Pre-Doctoral
Report2004-2008

Noritomo Ouchi

WATANABE

Chaojung Chen

WATANABE

Kwok L Shum

Shanyu Lei

Akihisa Yamada

Xuening Yao

Weilin Zhao

WATANABE

WATANABE

WATANABE

WATANABE

WATANABE

Contents
An Elucidation of Canon’s High Profitability Mechanism
Vol. 3, No. 1 Spring 2007
The Effect of Technology on Diffusion Mechanism of Music Market- An
Empirical Analysis of CD Singles Market of Japan
Vol. 1,No1 Fall 2005
The Co-evolution Process of Technological Innovation - A Perspective from theRelationship between Mobile Phone Vendors and Telecommunication Service
Operators in Japan
Vol. 2, No. 1 Spring 2006
Similarity and Disparity between Mobile Phone and Automotive Industry ofJapan: Resilient Business Strategy toward a Ubiquitous SocietyVol. 2, No. 2 Fall 2006
An Empirical Analysis of Institutional Co-evolution in the Productizing of Solar
Photovoltaic – A Comparison between Japan and the USA
Vol. 1, No.1 Fall 2005
Technological Trajectory and Its Implications to Digital Convergence- the Case of Smart Solar Photovoltaic (PV)Vol. 2, No.1 Spring 2006
Government’s Role in Managing Disruptive Innovation – Lessons Learned fromthe Case of Electric Vehicle in Japan
Vol. 2, No. 2 Fall 2006
An Empirical Analysis of Dynamic Co-evolution between GDP, Education and
PCs Diffusion Focusing on China’s Unique Institutional Systems
Vol. 2, No. 1 Spring 2006
The Role of Market Learning as a Coordinator of Techno-CountervailingPower-An Empirical Analysis of Canon Printers Based on Optimal Theory
Vol. 2, No. 2 Fall 2006
Fusing Indigenous Technology Development and Market Learning for Higher
Functionality Development
Vol. 3, No. 1 Spring 2007
The Influence of Institutions on Strategic Alliances: The Case of
The Semiconductor Industry (in Japanese)Vol. 1, No1 Fall 2005
Dynamism between Adaptability and Diversification of R&D: An Introduction (inJapanese)
Vol. 2, No. 1 Spring 2006
The Role of Informatization in Inducing Coevolution between Educational
Development, Urbanization and Economic GrowthVol. 2, No. 1 Spring 2006
Sustainable Economic Development with Inter-regional Heterogeneity in China
Vol. 3, No. 1 Spring 2007
Co-evolutionary Dynamism between Innovation and Institutional Systems in the
BRICs
Vol. 3, No. 2 Fall 2007
Co-evolutionary Dynamism between Japan and China in Software Outsourcing
Vol. 3, No. 1 Spring 2007
Risk Management in Outsourcing Service Industry - Suggestions from a Portfolio
Analysis of India’s Case
Vol. 3, No. 2 Fall 2007
An Exploration of Competitive Advantages in an Industry Cluster within Local
Institutional Systems: The Case of Dalian Software Park in China
Vol. 4, No. 1 Spring 2008
An Empirical Analysis of the Development Trajectory of Chinese Software
Industry: Focusing on Outsourcing and Industry Clusters
Vol. 4, No. 2 Fall 2008

i

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….074

Koji Moriyama

Jae-Ho ShinWATANABE

WATANABE

Nazrul IslamMIYAZAKI

Seunghye Hong

MIYAZAKITomonari Kitahara

Tien-Fang Kuo

MIZUNOYAJIMAR&D and Profitability: R&D as a Turbulence Role to Profitability
Vol. 4, No. 1 Spring 2008
Decisive Factors for Firms’ Sustainable Functionality Development
Vol. 5, No. 1 Spring 2009
<poster> Tripolarization of R&D Profitability Structure in Japan’s
High-technology Firms - Co-evolutionary Domestication Leads a Way to
Sustainable Functionality Development (in Japanese)
5th Annual SIMOT Symposium
The Analysis on the Bipolarization of Profitability in Japanese High-technology
firms -Substitutions and Complement of Input for Output in Research andDevelopment (in Japanese)Vol. 2, No. 2 Fall 2006
The Analysis of the Bipolarization of Profitability amongst Japanese
Hi-technology Firms (in Japanese)Vol. 3, No. 1 Spring 2007
The Analysis of the Bipolarization of Profitability amongst Japanese
Hi-technology Firms: The Disparity of Effort for External Acquisition (inJapanese)
Vol. 3, No. 2 Fall 2007
Comparative Analysis of Diffusion Trajectory of Plasma TV between Japan, Korea
and Taiwan’s Companies
Vol. 2, No. 2 Fall 2006
Patent Analysis of Plasma TV between Japanese and Korean Companies
Vol. 3, No. 1 Spring 2007
Transition Dynamism in Web 2.0: Emerging Dynamism of New Functionality
Vol. 3, No. 2 Fall 2007
Earlier Emergence of Functionality Development in a Diffusion TrajectoryVol. 4, No. 1 Spring 2008
Nanotechnology Innovation System: An Analysis of Technology Fusion Strategy
Vol. 3, No. 2 Fall 2007
Comments on poster and reports in SIMOT program<poster>“The Diffusion of Mobile Broadband Services and the Role of Standards in the
Mobile Sector Ecosystem” 5th Annual SIMOT Symposium<reports>“Continuous Improvement and Innovation in Manufacturing Firms” Vol. 4, No.
2 Fall 2008
“Mobile Sector Ecosystem - Actor Networks as the Key to Innovation and
Diffusion of Mobile Services” Vol. 5, No. 1 Spring 2009
<poster> SIMOT and Optimization
5th Annual SIMOT Symposium
An analysis of classification rules under the minimax criterion (in Japanese)Vol. 3, No. 1 Spring 2007
Generalized Chebyshev bound and its applications to optimization (in Japanese)Vol. 3, No. 2 Fall 2007
An analysis of the weighted least squares method and the layered least squares
method using the basis block lower triangular matrix form (in Japanese)Vol. 4, No. 1 Spring 2008
A theoretical analysis of the interior point method for linear programming and its
impacts to SIMOT (in Japanese)Vol. 4, No. 2 Fall 2008
Robust optimization and SIMOT (in Japanese)
V ol. 5, No. 1 Spring 2009
Ranking and Selecting Terms for Text Categorization via SVM Discriminate
BoundaryVol. 1, No.1 Fall 2005
The Application of Feature Selection for SIMOT (in Japanese)Vol. 2, No. 1 Spring 2006

ii

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….107
….408

Mizuho Ogikubo

ENKAWA

Masaomi Ikeshoji

KorrakotYaibuathet

BjoernFrank

ChristianTanyanuparb
Anantana

Gulimire Abulaiti

ENKAWA

ENKAWA

ENKAWA

ENKAWA

The Multiclass Classification and the Application for SIMOT (in Japanese)Vol. 2, No. 2 Fall 2006
The Semi-supervised Classification and the Application for SIMOT (in Japanese)Vol. 3, No. 1 Spring 2007
Customer Satisfaction and Life Satisfaction: Cross National Comparative Study ofCultural InfluencesVol. 3, No. 1 Spring 2007
The Cultural Influence of Customer Satisfaction - Cross-national Comparison Vol. 3, No. 2 Fall 2007
A Comparison of Customer Satisfaction Between in Japan and in the US Based on
Customer Attributes* (in Japanese)Vol. 2, No. 1 Spring 2006
Influences of Institutional Environment Toward the Development of Supply Chain
Management
Vol. 2, No. 2 Fall 2006
Institutional Perspective on Logistics and Supply Chain Management in Thailand
Vol. 3, No. 1 Spring 2007
Impact of Information Technology and SCM Organizational Strategy on Corporate
Financial Performance
Vol. 3, No. 2 Fall 2007
Impact of Industry Type on Supply Chain Operational Performance in a Develping
CountryVol. 4, No. 1 Spring 2008
<poster> How Economic Processes and Institutional Characteristics Co-Evolvewith Customer Satisfacton and Loyalty
5th Annual SIMOT Symposium
How Economic Expansion Drives Customer Satisfaction: a Study from Germany
Vol. 3, No. 1 Spring 2007
Co-Evolution between Customer Satisfaction and Economic Development: An
International Comparison
Vol. 3, No. 2 Fall 2007
The Relationship between Economic Growth and Customer Satisfaction
Vol. 4, No. 1 Spring 2008
How to Better Interpret the Results of Longitudinal Customer Satisfaction Surveys
Vol. 4, No. 2 Fall 2008
Cultural Influences on the SIMOT Strategy Optimizing Customer Loyalty
Vol. 5, No. 1 Spring 2009
<poster> NPD of Japanese Manufacturing Firms: Institutional Views of R&D
Intensity and Technology Trajectories
5th Annual SIMOT Symposium
New Product Development Operational Performance and Its Influential Factors of
Manufacturing Firms in Japan
Vol. 3, No. 2 Fall 2007
Moderating Effect of Technology Trajectories on New Product Development
Efficiency and Firm’s Financial Performance
Vol. 4, No. 1 Spring 2008
Utilizing Computerized Tools and IT in New Product Development to Constitute
Firm’s Financial Performance and the Institutional View of R&D Intensity
Vol. 4, No. 2 Fall 2008
NPD of Japanese Manufacturing Firms: Institutional Views of R&D Intensity andTechnology Trajectories
Vol. 5, No. 1 Spring 2009
<poster> Cross-Industry Comparison of Drivers of Customer Satisfaction and
Repurchase Intention
5th Annual SIMOT Symposium
Cross-National Comparison of Customer Satisfaction and Repurchase Intention
Vol. 5, No. 1 Spring 2009

iii

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Rémy
Magnier-Watanabe

Yue WuGen Abiko

Chan-orn
Bongsebandhuphubhakdi

Toru Takahashi

Yosuke Shibata

SENOO

SENOO

TANAKA

SAIKI

SAIKI

SAIKI

Jian Wang

TSAO

Han-Gook Kim

IIJIMA<poster> Beyond Deliberate Corporate Control – The Roles of Isomorphic
Pressures, National Culture and Organaization in the Institutionalization of
Knowledge Management
5th Annual SIMOT Symposium
Cultural Dimensions and Regional Differences in Knowledge Management among
Three Industrialized Countries
Vol. 1, No.1 Fall 2005
Organizational Characteristics as Prescriptive Factors of Knowledge Management
Initiatives
Vol. 2, No. 1 Spring 2006
The Effect of Consistent Knowledge Management Behaviors on Competitive
AdvantageVol. 3, No. 1 Spring 2007
The Effect of Institutional Pressures on Knowledge Management and theResulting Innovation: The Case of the Smartcard in France
Vol. 3, No. 2 Fall 2007
Organizational Characteristics, Relative to National Culture, Exert a Stronger
Prescriptive Influence on Knowledge Management
Vol. 4, No. 1 Spring 2008
<poster> Institutional Congruence of Knowledge Creation Process
5th Annual SIMOT Symposium
An Ontological Model of Knowledge SpiralVol. 4, No. 2 Fall 2008
The Endless Knowledge Creation: Strategies and Institutions
Vol. 5, No. 1 Spring 2009
An Analysis on the Patent Ratio from the Viewpoint of the Quantitative Nature of
the Patent Description* (in Japanese)Vol. 2, No. 1 Spring 2006
A proposal on the method to numerically Displya the Scope of Patent Claims.* (inJapanese)
Vol. 3, No. 1 Spring 2007
A Study on Intellectual Property Management, Techonology Development andWorker’s Skill Development in Thailand- Automotive Parts Industry Vol. 2, No. 1 Spring 2006
Development of Human Resources-Technology and Intellectual Property
Management in the Auto Parts Industry in Thailand (in Japanese)Vol. 3, No. 1 Spring 2007
A Research on New Combination of Knowledge from the Perspective of Patented
Invention – A Method to Analyze the Novelty of Combination of Technological
Elements* (in Japanese)Vol. 3, No. 1 Spring 2007
<poster> The Dynamics of Knowledge Spillover for Functionality Development inJapanese Acoustic Equipment Industry
5th Annual SIMOT Symposium
Patent Portfolios for Strategic Technology Management
Vol. 4, No. 2 Fall 2008
The Dynamics of Knowledge Spillover for Functionality Development in Japanese
Acoustic Equipment Industry
Vol. 5, No. 1 Spring 2009
Research on Innovative Manaufacturing Systems under Turbulent Environment
Vol. 2, No. 1 Spring 2006
A Study on Unified Modeling Methodology for Information Systems
Development
Vol. 2, No. 1 Spring 2006
A Study on Failure Factors of IS Integration from Organizational Perspective
Vol. 3, No. 1 Spring 2007

iv

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….251

Bing Li

IIJIMA

Zheng Zhao

HIGA

Rui GuHIGA

Kang Chen

Javier P.
GuevaraSolvesRamon

UMEMURO

Eguez

Pujol

UMEMUROUMEMUROXi Zheng

HACHIYA

Pablo Ramirez

HACHIYAMin Teng

Manabu Kobayashi

HACHIYAKIMOTO

Business Process Management: A Short Review
Vol. 3, No. 2 Fall 2007
The Technology Management Requirements for the Telework-based Offshoring:
The Pre-evaluation Model to the Telework Readiness in Chinese Organizations
Vol. 3, No. 1 Spring 2007
A Study on the Behavior of Media Selection in Distributed Working
Vol. 3, No. 1 Spring 2007
Social, Cultural, and Personal Factors Influencing the Usage ofComputer-Mediated Communication Technology by Chinese Elderly People
Vol. 1, No.1 Fall 2005
Comparing with Personal , Cultural and Iinstitutional Factors Influencing on
Compter Media Comminication (CMC) Usage between Janpan and China
Vol. 2, No. 1 Spring 2006
Comparison of Institutional Factors Influencing Computer-MediatedCommunication Technology Using in Tokyo and Shanghai Older People
Vol. 2, No. 2 Fall 2006
<poster> Unobtrusive Estimation of Psychological States Based on Human
Movement Observation
5th Annual SIMOT Symposium
Unobtrusive Estimation of Psychological States Based on Human Movement
Observation
Vol. 4, No. 2 Fall 2008
Just Feel it!: A System for the Recognition of Emotion and Other PsycologicalStates by Unobtrusive Means
Vol. 5, No. 1 Spring 2009
<poster> Productive Love: A New Approach for Designing Affective Technology
5th Annual SIMOT Symposium
Personal factors influence on ICT engagement
Vol. 3, No. 2 Fall 2007
Towards Technologies That Promote Love. Preliminary Literature Review
Vol. 4, No. 1 Spring 2008
Implications From Erich Fromm for Designing Affective Technology to Promote
Productive Love
Vol. 4, No. 2 Fall 2008
Productive Love Related Devices and System Evaluation
Vol. 5, No. 1 Spring 2009
Dilution Effect and Earnings Management: Evidence from Japanese IPOs
Vol. 1, No.1 Fall 2005
A Comprehensive Study of Firm-Specific Organizational Capital : Evidence from
Japan
Vol. 3, No. 1 Spring 2007
<poster> Stock Repurchase as a Leverage Adjustment Device
5th Annual SIMOT Symposium
Research Report for the Fall Semester 2008
Vol. 5, No. 1 Spring 2009
<poster> On the Development of the High Pressure Steam Engine in the 19th
Century
5th Annual SIMOT Symposium
Comments on reports in SIMOT program (in Japanese)<reports>“On the improvement of steam pressure by using steel boilers”“On The Popularization of Thermodynamics among British Engineers in the 19th
Century”“From Bernoulli's Theorem to a Theory of the Steam Engine”“On the Development of Various Types of Steam Engines Based on Their Uses inthe Early Part of the 19th Century”
On The Popularization of Thermodynamics among British Engineers in the 19th
Century (in Japanese)

v

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….439
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Vol. 2, No. 1 Spring 2006
Takeshi Kurihara

Md.
RashidMamunur

Miyabi Hayama

Masanori Ohashi

YAMAZAKIYAMAZAKIWARAGAIWARAGAI

Historical Study on Reconstruction of the Organizations for Military Research andDevelopment in the United States after the Second World War (in Japanese)
5th Annual SIMOT Symposium
Scientific Mobilization and Scientists in the Development for the Atomic Bomb
Project during the Second World War (in Japanese)Vol. 1, No.1 Fall 2005
International Comparative Study on the Scientific Mobilizations during theSecond World War: Symbiotic Relationship between Military Agancy andUniversity (in Japanese)Vol. 2, No. 1 Spring 2006
Historical Study on the Scientific Mobilization: Reformation of the Organizations
for Nuclear Development after the Second World War (in Japanese)Vol. 2, No. 2 Fall 2006
Reconstruction of the Organizations for Nuclear Development in the United States
after the Second World War: Confrontation between Civilian and Military (inJapanese)
Vol. 3, No. 1 Spring 2007
Research and Development for Radiorogical Warfare Weapons in the UnitedStates after the end of the Second World War (in Japanese)Vol. 3, No. 2 Fall 2007
Reconstruction of the Organizations for Research and Development in the UnitedStates after the Second World War: Vannevar Bush and the Research andDevelopment Board in DOD (in Japanese)Vol. 4, No. 1 Spring 2008
Reconstruction of the Organizations for Research and Development after theSecond World War: Symbiotic and Confrontation Relationship between Military
Agency and Scientists in the Early Cold War Institution in the United States (inJapanese)
Vol. 5, No. 1 Spring 2009
<poster> The History and Prospects of Bangladesh to India Natural Gas Pipeline
Project
5th Annual SIMOT Symposium
Energy Policy and Market Reforms in Japan for RA ReportVol. 1, No.1 Fall 2005
Is Natural Gas a Blessing for Bangladesh?
Vol. 2, No. 1 Spring 2006
Bangladesh’s Natural Gas Export PotentialVol. 2, No. 2 Fall 2006
Enhancing Oil and Gas Exploration in Bangladesh
Vol. 3, No. 1 Spring 2007
Exploration and Supply of Natural Gas in India
Vol. 3, No. 2 Fall 2007
Political Tangles of a Natural Gas Pipeline Project from Bangladesh to India
Vol. 4, No. 1 Spring 2008
Bangladesh to India Natural Gas Pipeline Project: Its Story and Prospects
Vol. 4, No. 2 Fall 2008
Bangladeshi Exploration of Natural Gas and Reserve PotentialVol. 5, No. 1 Spring 2009
The "Management of ba" -From the view of SIMOT (in Japanese)Vol. 1, No.1 Fall 2005
The Concept of Institution from the point of view of the Methodology of Science-The Case of the Currency of the Equal Temperament (in Japanese)Vol. 2, No. 1 spring 2006
<poster> An Obsevation about SIMOT and Tense Logic
5th Annual SIMOT Symposium
Co-Evolution of Logics/Tense Logics and Science/Technology

vi

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….449
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….457
….461

….465

….469
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….351
….473
….477
….355

Satoshi Tanaka

WARAGAI

Shinya Kajiki

KAJI

Masanori Wada

KAJI

Vol. 5, No. 1 Spring 2009 ….356<poster> On the impact of Computer Science to the Development of the Origin ofModern Electrical Computer
5th Annual SIMOT Symposium ….360
On the impact of Computer Science to the Development of the Origin of Modern
Electrical Computer
Vol. 5, No. 1 Spring 2009 ….361
The problem of the research and development led by governmental ministries
and agencies: A case of a high-speed ship “Techno-Super-Liner (TSL)” (inJapanese)
Vol.1, No.1 Fall 2005 ….481
An analysis of the research and development led by governmental ministries andagencies: The Cases of STOL and TSL (in Japanese)Vol. 2, No. 1 Spring 2006 ….485
An analysis of Japan’s National Projects in Transportation Technology: A Case of
Shinkansen (in Japanese)Vol. 2, No. 2 Fall 2006 ….489
A historical analysis of Japan’s National Projects in Transportation Technology:
The Cases of STOL and TSL (in Japanese)Vol. 3, No. 1 Spring 2007 ….493
Comments on poster and reports (in Japanese)< research subject in SIMOT program >The Role of the Japanese Cultural Background in the Formation of Engineering….497
Education: in the Case of the Imperial College of Engineering* titles translated by the editor.

vii

Reports in English
Noritomo Ouchi

WATANABE

Chaojung Chen

WATANABE

Kwok L Shum

Shanyu Lei

Xuening Yao

Weilin Zhao

Koji Moriyama

Jae-Ho ShinWATANABE

WATANABE

WATANABE

WATANABE

WATANABE

WATANABE

An Elucidation of Canon’s High Profitability Mechanism
Vol. 3, No. 1 Spring 2007
The Effect of Technology on Diffusion Mechanism of Music Market- An
Empirical Analysis of CD Singles Market of Japan
Vol. 1,No1 Fall 2005
The Co-evolution Process of Technological Innovation - A Perspective from theRelationship between Mobile Phone Vendors and Telecommunication Service
Operators in Japan
Vol. 2, No. 1 Spring 2006
Similarity and Disparity between Mobile Phone and Automotive Industry ofJapan: Resilient Business Strategy toward a Ubiquitous SocietyVol. 2, No. 2 Fall 2006
An Empirical Analysis of Institutional Co-evolution in the Productizing of Solar
Photovoltaic – A Comparison between Japan and the USA
Vol. 1, No.1 Fall 2005
Technological Trajectory and Its Implications to Digital Convergence- the Case of Smart Solar Photovoltaic (PV)Vol. 2, No.1 Spring 2006
Government’s Role in Managing Disruptive Innovation – Lessons Learned fromthe Case of Electric Vehicle in Japan
Vol. 2, No. 2 Fall 2006
An Empirical Analysis of Dynamic Co-evolution between GDP, Education and
PCs Diffusion Focusing on China’s Unique Institutional Systems
Vol. 2, No. 1 Spring 2006
The Role of Market Learning as a Coordinator of Techno-CountervailingPower-An Empirical Analysis of Canon Printers Based on Optimal Theory
Vol. 2, No. 2 Fall 2006
Fusing Indigenous Technology Development and Market Learning for Higher
Functionality Development
Vol. 3, No. 1 Spring 2007
The Role of Informatization in Inducing Coevolution between Educational
Development, Urbanization and Economic GrowthVol. 2, No. 1 Spring 2006
Sustainable Economic Development with Inter-regional Heterogeneity in China
Vol. 3, No. 1 Spring 2007
Co-evolutionary Dynamism between Innovation and Institutional Systems in the
BRICs
Vol. 3, No. 2 Fall 2007
Co-evolutionary Dynamism between Japan and China in Software Outsourcing
Vol. 3, No. 1 Spring 2007
Risk Management in Outsourcing Service Industry - Suggestions from a
Portfolio Analysis of India’s Case
Vol. 3, No. 2 Fall 2007
An Exploration of Competitive Advantages in an Industry Cluster within Local
Institutional Systems: The Case of Dalian Software Park in China
Vol. 4, No. 1 Spring 2008
An Empirical Analysis of the Development Trajectory of Chinese Software
Industry: Focusing on Outsourcing and Industry Clusters
Vol. 4, No. 2 Fall 2008
R&D and Profitability: R&D as a Turbulence Role to Profitability
Vol. 4, No. 1 Spring 2008
Decisive Factors for Firms’ Sustainable Functionality Development
Vol. 5, No. 1 Spring 2009
Comparative Analysis of Diffusion Trajectory of Plasma TV between Japan,
Korea and Taiwan’s Companies
Vol. 2, No. 2 Fall 2006094

1

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….082
….086

Nazrul Islam

Seunghye Hong

Tien-Fang Kuo

Mizuho Ogikubo

Korrakot

MIYAZAKIMIYAZAKIYAJIMA

ENKAWA

ENKAWA

Yaibuathet

BjoernChristian

ENKAWAFrank

Tanyanuparb
Anantana

ENKAWA

Patent Analysis of Plasma TV between Japanese and Korean Companies098
Vol. 3, No. 1 Spring 2007
Transition Dynamism in Web 2.0: Emerging Dynamism of New Functionality
Vol. 3, No. 2 Fall 2007
Earlier Emergence of Functionality Development in a Diffusion TrajectoryVol. 4, No. 1 Spring 2008
Nanotechnology Innovation System: An Analysis of Technology Fusion
StrategyVol. 3, No. 2 Fall 2007
Comments on poster and reports in SIMOT program<poster>“The Diffusion of Mobile Broadband Services and the Role of Standards in the
Mobile Sector Ecosystem” 5th Annual SIMOT Symposium<reports>“Continuous Improvement and Innovation in Manufacturing Firms” Vol. 4,
No. 2 Fall 2008
“Mobile Sector Ecosystem - Actor Networks as the Key to Innovation and
Diffusion of Mobile Services” Vol. 5, No. 1 Spring 2009
Ranking and Selecting Terms for Text Categorization via SVM Discriminate
BoundaryVol. 1, No.1 Fall 2005
Customer Satisfaction and Life Satisfaction: Cross National Comparative Studyof Cultural InfluencesVol. 3, No. 1 Spring 2007
The Cultural Influence of Customer Satisfaction - Cross-national Comparison Vol. 3, No. 2 Fall 2007
Influences of Institutional Environment Toward the Development of Supply
Chain Management
Vol. 2, No. 2 Fall 2006
Institutional Perspective on Logistics and Supply Chain Management inThailandVol. 3, No. 1 Spring 2007
Impact of Information Technology and SCM Organizational Strategy on
Corporate Financial Performance
Vol. 3, No. 2 Fall 2007
Impact of Industry Type on Supply Chain Operational Performance in a
Develping Country
Vol. 4, No. 1 Spring 2008
<poster> How Economic Processes and Institutional Characteristics Co-Evolvewith Customer Satisfacton and Loyalty
5th Annual SIMOT Symposium
How Economic Expansion Drives Customer Satisfaction: a Study from
GermanyVol. 3, No. 1 Spring 2007
Co-Evolution between Customer Satisfaction and Economic Development: An
International Comparison
Vol. 3, No. 2 Fall 2007
The Relationship between Economic Growth and Customer Satisfaction
Vol. 4, No. 1 Spring 2008
How to Better Interpret the Results of Longitudinal Customer Satisfaction
SurveysVol. 4, No. 2 Fall 2008
Cultural Influences on the SIMOT Strategy Optimizing Customer Loyalty
Vol. 5, No. 1 Spring 2009
<poster> NPD of Japanese Manufacturing Firms: Institutional Views of R&D
Intensity and Technology Trajectories
5th Annual SIMOT Symposium

2

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Gulimire Abulaiti

Rémy Magnier-

ENKAWASENOO

Watanabe

Yue WuSENOO

Chan-orn
Bongsebandhuphubhakdi

SAIKI

Yosuke Shibata

SAIKI

Jian WangTSAO

New Product Development Operational Performance and Its Influential Factorsof Manufacturing Firms in Japan
Vol. 3, No. 2 Fall 2007
Moderating Effect of Technology Trajectories on New Product Development
Efficiency and Firm’s Financial Performance
Vol. 4, No. 1 Spring 2008
Utilizing Computerized Tools and IT in New Product Development toConstitute Firm’s Financial Performance and the Institutional View of R&D
Intensity
Vol. 4, No. 2 Fall 2008
NPD of Japanese Manufacturing Firms: Institutional Views of R&D Intensity
and Technology Trajectories
Vol. 5, No. 1 Spring 2009
<poster> Cross-Industry Comparison of Drivers of Customer Satisfaction and
Repurchase Intention
5th Annual SIMOT Symposium
Cross-National Comparison of Customer Satisfaction and Repurchase Intention
Vol. 5, No. 1 Spring 2009
<poster> Beyond Deliberate Corporate Control – The Roles of Isomorphic
Pressures, National Culture and Organaization in the Institutionalization of
Knowledge Management
5th Annual SIMOT Symposium
Cultural Dimensions and Regional Differences in Knowledge Management
among Three Industrialized Countries
Vol. 1, No.1 Fall 2005
Organizational Characteristics as Prescriptive Factors of Knowledge
Management Initiatives
Vol. 2, No. 1 Spring 2006
The Effect of Consistent Knowledge Management Behaviors on Competitive
AdvantageVol. 3, No. 1 Spring 2007
The Effect of Institutional Pressures on Knowledge Management and theResulting Innovation: The Case of the Smartcard in France
Vol. 3, No. 2 Fall 2007
Organizational Characteristics, Relative to National Culture, Exert a Stronger
Prescriptive Influence on Knowledge Management
Vol. 4, No. 1 Spring 2008
<poster> Institutional Congruence of Knowledge Creation Process
5th Annual SIMOT Symposium
An Ontological Model of Knowledge SpiralVol. 4, No. 2 Fall 2008
The Endless Knowledge Creation: Strategies and Institutions
Vol. 5, No. 1 Spring 2009
A Study on Intellectual Property Management, Techonology Development andWorker’s Skill Development in Thailand- Automotive Parts Industry Vol. 2, No. 1 Spring 2006
<poster> The Dynamics of Knowledge Spillover for Functionality Development
in Japanese Acoustic Equipment Industry
5th Annual SIMOT Symposium
Patent Portfolios for Strategic Technology Management
Vol. 4, No. 2 Fall 2008
The Dynamics of Knowledge Spillover for Functionality Development inJapanese Acoustic Equipment Industry
Vol. 5, No. 1 Spring 2009

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Research on Innovative Manaufacturing Systems under Turbulent Environment
Vol. 2, No. 1 Spring 2006 ….243

3

Han-Gook Kim

IIJIMA

Bing Li

IIJIMA

Zheng Zhao

HIGA

Rui GuHIGA

Kang Chen

JavierP.

UMEMURO

Eguez

UMEMURO

GuevaraSolves

Pujol

UMEMURORamon

Xi Zheng

HACHIYA

Pablo Ramirez

HACHIYAMin Teng

Md.
RashidHACHIYA

Mamunur

YAMAZAKI

A Study on Unified Modeling Methodology for Information Systems
Development
Vol. 2, No. 1 Spring 2006
A Study on Failure Factors of IS Integration from Organizational Perspective
Vol. 3, No. 1 Spring 2007
Business Process Management: A Short Review
Vol. 3, No. 2 Fall 2007
The Technology Management Requirements for the Telework-based
Offshoring: The Pre-evaluation Model to the Telework Readiness in Chinese
Organizations
Vol. 3, No. 1 Spring 2007
A Study on the Behavior of Media Selection in Distributed Working
Vol. 3, No. 1 Spring 2007
Social, Cultural, and Personal Factors Influencing the Usage ofComputer-Mediated Communication Technology by Chinese Elderly People
Vol. 1, No.1 Fall 2005
Comparing with Personal , Cultural and Iinstitutional Factors Influencing on
Compter Media Comminication (CMC) Usage between Janpan and China
Vol. 2, No. 1 Spring 2006
Comparison of Institutional Factors Influencing Computer-MediatedCommunication Technology Using in Tokyo and Shanghai Older People
Vol. 2, No. 2 Fall 2006
<poster> Unobtrusive Estimation of Psychological States Based on Human
Movement Observation
5th Annual SIMOT Symposium
Unobtrusive Estimation of Psychological States Based on Human Movement
Observation
Vol. 4, No. 2 Fall 2008
Just Feel it!: A System for the Recognition of Emotion and Other PsycologicalStates by Unobtrusive Means
Vol. 5, No. 1 Spring 2009
<poster> Productive Love: A New Approach for Designing Affective
Technology
5th Annual SIMOT Symposium
Personal factors influence on ICT engagement
Vol. 3, No. 2 Fall 2007
Towards Technologies That Promote Love. Preliminary Literature Review
Vol. 4, No. 1 Spring 2008
Implications From Erich Fromm for Designing Affective Technology toPromote Productive Love
Vol. 4, No. 2 Fall 2008
Productive Love Related Devices and System Evaluation
Vol. 5, No. 1 Spring 2009
Dilution Effect and Earnings Management: Evidence from Japanese IPOs
Vol. 1, No.1 Fall 2005
A Comprehensive Study of Firm-Specific Organizational Capital : Evidence
from Japan
Vol. 3, No. 1 Spring 2007
<poster> Stock Repurchase as a Leverage Adjustment Device
5th Annual SIMOT Symposium
Research Report for the Fall Semester 2008
Vol. 5, No. 1 Spring 2009
<poster> The History and Prospects of Bangladesh to India Natural Gas
Pipeline Project
5th Annual SIMOT Symposium
Energy Policy and Market Reforms in Japan for RA ReportVol. 1, No.1 Fall 2005

4

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Is Natural Gas a Blessing for Bangladesh?
Bangladesh’s Natural Gas Export Potential
Enhancing Oil and Gas Exploration in Bangladesh

Vol. 2, No. 1 Spring 2006 ….331
Vol. 2, No. 2 Fall 2006 ….333
Vol. 3, No. 1 Spring 2007 ….336

Exploration and Supply of Natural Gas in India

Masanori Ohashi

Satoshi Tanaka

WARAGAIWARAGAI

Vol. 3, No. 2 Fall 2007
Political Tangles of a Natural Gas Pipeline Project from Bangladesh to India
Vol. 4, No. 1 Spring 2008
Bangladesh to India Natural Gas Pipeline Project: Its Story and Prospects
Vol. 4, No. 2 Fall 2008
Bangladeshi Exploration of Natural Gas and Reserve PotentialVol. 5, No. 1 Spring 2009
<poster> An Obsevation about SIMOT and Tense Logic
5th Annual SIMOT Symposium
Co-Evolution of Logics/Tense Logics and Science/Technology
Vol. 5, No. 1 Spring 2009
<poster> On the impact of Computer Science to the Development of the Originof Modern Electrical Computer
5th Annual SIMOT Symposium
On the impact of Computer Science to the Development of the Origin ofModern Electrical Computer
Vol. 5, No. 1 Spring 2009

5

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An Elucidation of Canon’s High Profitability Mechanism
Noritomo Ouchi**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-49 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANouchi.n.aa@m.titech.ac.jp
Many Japanese electric machinery firms can not make a profit because of fast pricereduction. However, Canon has consistently kept high profitability. First, this study will
demonstrate dynamism between technological diversification, learning and functionlity
development. Second, this report will also demonstrate how Canon does the management
in its institutions. We took the cell production system as one of the Canon’s institutional
management.

dynamism between technological diversification,
learning and functionality development.
In addition, Mr Mitarai, who is chairman &CEO of Canon, suggests that it is important tomanage the firms taking into institutions
consideration. This report will also demonstrate
how Canon does the management in its institutions.
We take the cell production system for example of
the Canon’s institutional management.

1. Introduction
Although many Japanese electric machinery
firms can not make a profit under the severe pricecompetition, Canon has consistently kept highprofitability and its operation income to sales (OI/S)
has remained the highest among Japan’s leading
electric machinery firms.
Many researchers have pointed out that thesource of high profitability of Canon is its businessmodel with a high-profit structure of office supplies
in the business machines market. That is, once firms
sell copying machines and printers, they canconsistently earn profits from the maintenanceservice and consumption of office supplies.
However, the profitability of the business machinesegment of Canon is much higher than other rivals
in the business machine market (Ricoh, Fuji-Xerox,
Epson). This result suggests that it is insufficient to
explain the high profitability of Canon only withthe business model of office supplies.
The difference between Canon and rivals in thebusiness machine market is that it has a high market
share in both the copying machines and printersfields. In the copying machines’ market, Canon’s
share ranked top. As for printers, Canon’s shareranked 3rd. The top is HP. However, the laser beam
printer (LBP) of HP is OEM from that of Canon.
Therefore, Canon’s share is virtually top.
Although Xerox and Ricoh have high market
share in the copying machines’ market, they havelittle share in the market of printers. On the other
hand, Epson, which has a high market share in theprinters’ market, doesn’t produce copying machines.
It seems quite probable that the reason of highprofitability of Canon is having a high market sharein these two products. LBP was applyide to
Copying machien’s technology.
First, this report will demonstrate the reason ofhigh profitability of canon from the view of

2. Technological diversification
Canon has actively diversified its technologicalarea over the years. Watanabe et al. (2005) pointed
out that Canon’s technological diversification
strategy can be the source for the high level of its
profits. Suzuki and Kodama (2005) pointed out that
Canon rapidly expanded its business, in principle,
by building on existing core technologies, thereby
incrementally developing new technologies inrelated technology areas, which leads to new
business areas. That is, technological diversificationin closely related fields seems to be related toCanon’s high profitability.
3. Learning and functionality development
Under current severe price competition, themethods by which the firms raise their profitability
are accelerating cost reduction and slowing down
the speed of decreasing sales price.
Following Arrow (1962)’s pioneer postulate on“learning-by-doing”, many empirical analyses havedemonstrated that learning is important toaccelerate cost reduction.
To increase sales price (slow down the speed ofdecreasing sales price), creating new products
which have new value and functionality matchingthecustomerdemand(i.e.
functionality
development) is important. Several studies havebeen made on functionality development. Watanabe
et al. (2003) and pointed out spillover is significant

7

for functionality development. These studies
suggest that using spillover is essential to create
new function faster and more effective than therivals. In regard to spillover, by using the conceptof technological position proposed by Jaffe (1986),
many researchers have analyzed the effect of
spillover.
In addition, using spillover effectively increases
learning, because the new products induce thedemand and firms can get more opportunities forleaning.

The learning coefficient of the period aftercolor LBP (0.750) is higher than one of the period
before color LBP was introduced (0.251). This
result suggests that the learning effect of copying
machines increased by color LBP.
5. Sharing of Learning
In this section, we consider Canon's copying
machines and LBP to demonstrate how firms sharedlearning .2
Both copying machines and LBP have the same
printing process as follows:(1) Electrical Charging
The surface of the photosensitive drum isnegatively charged with about 700V.
(2) Exposure
Laser beams scan the surface of thephotosensitive drum to "draw" letters and images
by discharging static electricity.
(3) Developing
Negatively charged toner affixes to the areas ofthe photosensitive drum on which negative static
electricity has been discharged(4) Transferring
After paper is affixed to the photosensitive
drum, a positive charge is applied to attract toner(5) Fixing
Heat and pressure are applied to firmly fix the
toner to the paper

3. Dynamizm between technological diversification,
Learning and functionality development
Learning and spillover can be attributed totechnological diversification. In the case ofdiversifying technologies in a related area, firms
can increase the learning effect by the multi-use oftechnologies, and create new functionality
efficiently due to effective utilization of interspillover and intra-spillover. Each technology
develops
throughinteraction
with
other
technologies.
4. Learning curve of copying machinesFirst, we analyze the relationships between
copying machines and LBP. We measure thelearning effect of full color copying machines, andcompare learning effects of copying machines
before and after LBP being introduced.
It is best to analyze at the firm level. However,acquisition of data at the firm level is impossible
because firms have not released figures on thenumbers of production and cost. This study verifies
the characteristics of copying machines and printers
The learning curve is expressed as follows:
P = P0V − λ(1)ln P = A − λ ln V
( A = ln P0 )(2)
where P: production price, P0:initial price, V:
cumulative production.1
This study estimates the learning coefficient in
3 periods using dummy variables.
D1 = 1 (Jan. 97 - Jul. 98: The period before color
LBP introduced), 0 (others);
D2 = 1 (Aug. 98 - Jun. 02: The period after color
LBP introduced), 0 (others);
D3 = 1 (Jun. 02 - Dec. 04: The period of digitalizing
and networking, 0 (others)
The result of regression analysis is as follows:

Since they have the same process and same
technologies, such as drum, laser transmitter unit,
intermediate transfer belt and fixing roller, they are
obviously used for both copying machines and LBP.
Sharing these technologies make it possible that
Canon shares the learning effects from copying
machines and printers as illustrated in Figure 1.
Canon can reduce cost faster than a rival by meansof this mechanism.
Copying machinetechnology
Printing
Printing
process
process
technology
technology

Learning(2.01)(1.11)(-13.64)

adj. R2(-5.25)

0.903

DW

0.57

2

1

Learning

Chemical products (toner, drum and cartridge),
which are the source of profit in the businessmachines market, are an interesting example ofsharing of learning. Canon has the Chemical
Products Operations within the organization. This
operation division carries out R&D, procurement,−0.251D1 ln V − 0.750 D2 ln V − 0.558 D3 ln V (3)(-1.00)Sharing theeffectFigure 1. Sharing of learning between copying machinetechnology and LBP technology.

ln P = 3.049 + 6.386 D2 + 3.823D3(0.99)

LBP technology

In this section, the details of technology and history arebased on Canon(2006) and Nihon Keizai Shimbun, Inc.
(2004).

Data source is Machinery Statistics (MITI).

8

production, sales and quality assurance of chemical
products of both copying machines and printers.
Therefore, it can naturally share the learning fromboth copying machines and printers.

own company, so they don’t change a company.
Common destiny is made by lifetime
employment system. It is strong when theemployees belonging to the common destiny anddecide what they do by themselves with sense ofownership. Excellent people do not leave acompany even if the achievement of thecompany is bad or the salary is cut. That is acharacteristic of Japanese.
(Nihon Keizai Shimbun, Inc., 2004.)
These comments suggests that Canon manages
the firms taking into institutions consideration well.

6. Creating New Functionality due to Effective
Utilization of Inter-spillover and Intra-spillover
In this section, we take a System LSI
technology
as an example of functionality
development by effective utilization of interspillover and intra-spillover.
In 1993, NeXT Computer Inc. , dropped theirhardware business and re-named to NeXT Software,
Inc. Canon purchased their hardware businesssector and established FirePower Systems, Inc., awholly-owned subsidiary of Canon. FirePower
Systems developed a chipset packed MPU (Micro
Processing Unit) which was called “PowerPC”.
However, this business was not successful and
FirePower Systems were purchased by Motorola in1997. Although this business was a failure, Canonlearned circuit design technology from NeXT
Computer. By using this circuit technology, Canondeveloped System LSI. Canon installed System LSI
in copying machines and these machines had acharacteristic of “multi-function”. After Canon’s
System LSI was improved by learning, Canon
installed System LSI in LBP and other products. By
sharing of learning and improving System LSI,
Canon had responded flexibly to digitization andnetworking.
Canon’s System LSI technology is a good
example of creating new functionality due toeffective utilization of inter-spillover and intraspillover as illustrated in Figure 2.
External technology:
Circuit design
technology(Next Computer)Copying machinetechnology

LBP technology

SystemSystem LSI
LSI

SystemSystem LSI
LSI

Learning

8. Cell production system
We consider the cell production system forexample of a success of Canon’s institutional
management.
The introduction of the cell production system
in 1998 marked a major step forward for production
reforms at Canon. The system supports
responsiveness and flexibility in supply chain
management by allowing for "just-in-time
production", or manufacturing products only as
they are needed.
Before the introducing of cell production
system, theeconomy of advanced countries
became matured. Thus, flexible "limited productionof diversified product" was necessary. Howevere,
enterprises that succeed in time of constant growthmight think that inventory would be reduced
someday even if they do over-investment. In
addition, huge belt conveyer production system was
the symbol of success for the company which
succeeded by the system. Therefore, the change of
production system was difficult in the enterprise’sculture which was created through the past
successes.
Changing its culture and thinking, Canon had
developed the cell production system.
The factors which enabled Canon to change areas follows;(1) The intense leadership of Mr Mitarai, who waspresident at that time
With just bottom-up improvement whichemphasized decreasing wastefulness, thedynamic change of production system would not
be possible.
(2) External consultant
At the same time as introduction of cell
production system, training by the external
consultant's guidance was also started aiming to
re-form frontline workers’ consciousness.
In process in which a cell method spreads,
training of being a leader of the frontline (trainer)
was also started. At first, it began with thecooperation of external consultant, in process ofthe expanding cell production system, theLearning

Figure.2. Utilization of inter-spillover and intra-spillover.

7. Institutional management
Mr Mitarai, who is Chairman & CEO,comment about his management policy as follows:・ “There are international parts and local partsin the management. Development strategy,
merchandise strategy and financial strategy areinternational parts. In these fields, Canon use
international methods completely. Employment
and the strategy related to human must be local.”・ “Japanese people have consciousness, such as theCanon-Han (domain) and the Hitachi-Han(domain), and they do not change a company
until they die in battle. This is a Japanese culture.
They join a company with pride. They love their9employee of Canon became a teacher and taught
the employee.

It could be observed that after color LBP wereintroduced, the learning co-efficient of color
copying machines increased.
From the case study of copying machines andprinters, it was demonstrated that diversifying inclosely related fields increases learning effect andcreates new functionality. It is thought that firms
with high profitability like Canon manage thisdynamism well.
Second, we analyzed the Canon’s institutional
management. The reason of success of cell
production system is it matched institutions, andCanon changes institutions to mathe it more.
To generalize these suggestions, analyses ofother products and firms should be conducted.

At the beginning of introduction of cell
production system, the productivity had gone downin comparison with that of belt conveyor system. It
mounted dissatisfaction of the worker about cell
production system.
In those situations, the woman team of frontline
worker voluntarily organized meeting for
improvement of productivity. After three days ofstarting meeting, they achieved scheduled
production. Gaining inspiration from these
activities, other front workers began similar
activities. Frontline workers improved the
production process voluntarily. Cell production
system came to go well gradually. Dissatisfaction
and friction due to cell production system decreased.
The frontline workers contributed largely the
success of cell production system. The highqualities of frontline workers are related to
institutions which consist of lifetime employment,
and so on.
Mr. Mitarai said, “ The strong point oflifetime employment is that every employee spends
his/her whole life understanding the management
policy. Naturally, company spirit arises andemployees unite to fight against the crisis. Thisintangible assets are important. It is suitable for theJapanese climate. It is precious core competence tosurvive in a global market.”
The cell production system is a innovation
which matches institutions.
In addition, Canon had introduced several
systems which induce the development of cell
production system. Evaluation system was one ofthem.
The Canon Expert System, based on theGerman "meister" system, which certifies workers
as they progress through training, recognizes
outstanding workers for their well-developed skills
by conferring such special titles as Super-Grade
Expert on them. The system is well-suited formatching individual abilities to assembly
procedures.
Canon has changed institutions to match thecell production system. The cell production system
is a good example of success of co-evolution of
innovation and institutions.

References

9. Conclusions
This study attempted to elucidate the reason ofhigh profitability of Canon.
First, we analyzed dynamism between
technologicaldiversification,
learning,
andfunctionality development.

10

[1]

Arrow, K.J., 1962. The economic implicationsof learning by doing, Review of Economic
Studies 29, 155-173.

[2]

Canon Inc. 2006. Canon technology highlights,
Canon Inc, Tokyo.

[3]

Jaffe A.B., 1986. Technological opportunityand spillover of R&D: evidence from firm’s
patents, profits, and market value, American
Economic Review, 76, 984-1111.

[4]

Ministry of Economy, Trade and Industry(METI) Machinery statistics, Ministry of
Economy, Trade and Industry, Tokyo.

[5]

Nihon Keizai Shimbun, Inc., 2004. Canon
SHIKI, Nihon Keizai Shimbun, Inc., Tokyo(in Japanese).

[6]

Suzuki J., Kodama F., 2005. Study on Science- Technology - Industry Network - Analysis ofJapanese companies' return to core businessand absorption of new technologies, RIETI
Discussion Paper Series 05-J-010, ResearchInstitute of Economy, Trade and Industry,
Tokyo (in Japanese).

[7]

Watanabe, C., Asgari, B., Nagamatsu, A.,
2003. Virtuous cycle between R&D,
functionality development and assimilation
capacity for competitive strategy in Japan’s
high-technology industry, Technovation, 23(11), 879-900.

[8]

Watanabe, C., Hur, J.Y., Matsumoto, K.,
2005. Technological diversification and firm's
techno-economic structure: An assessment ofCanon’s sustainable growth trajectory,
Technological Forecasting and Social Change,
72 (1), 11-27.

The Effect of Technology on Diffusion Mechanism of Music Market- An Empirical Analysis of CD Singles Market of Japan
Chaojung Chen**

Department of Industrial Engineering and Managemen
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANchaojung@me.titech.ac.jp
This research takes the diffusion process of the CD singles in Japan to elucidate thepossible problem of the downloading music market. The sales of 2000 top hit CD singles
are analyzed for empirical analysis by Bass model, and the empirical result reveals thechange of diffusion processes in recent years. The result shows that, compared with themarket ten years ago, recently the peak of CD single sales (diffusion) curve tends to comeearlier and the sales drops faster, especially in the case of famous artists.
Due to the substitutability of the physical music
product and digital music content, the value of
global singles market is possibly overtaken by thegrowth of digital music market. Therefore, theexisting CD singles market is the market worth
further understanding for future strategy
development in the digital music market.

1. Introduction
Due to the growing penetration rate ofbroadband, diffusion of 3G mobile phones, portable
digital music players, and more and more active
cooperation of record companies with digital music
content providers/ distributors, the digital music
sales is being accelerated over the past year.
According to International Federation of the
Phonographic Industry (IFPI, 2005) [1], digitalmusic sales amounted to approximately $US 790
million, up from $US 220 million in the first half of2004, the equivalent of 6% of total record industry
sales. Not only has the possibility of digital music
downloading market attracted much attention ofboth consumers and businesses, but also its actual
growth has urged further understanding toward thecharacteristics of this market with high potential in
the near future.
However, the digital music downloading
market is not matured enough to offer much hints
for the business. In order to elucidate its
characteristics and possible development in the
future, it is required to select an existing market
with similar attributes. Currently there are two
common kinds of music downloading service by the
charging style, i.e. per-song downloading (pay-asyou-enjoy) or the flat rate service (pay-a-certain-fee
to download whatever you want). No matter whichcharging system the consumer chooses, he/she still
has to download by the unit of one song. Especiallyfor users of the per-song downloading service, thefee is basically proportional to the number of song
downloaded. Such song-unit charging characteristic
is considered to be similar to the CD single rather
than CD album since the consumers pay for eachspecific song when buying CD singles. Judging
from the change of CD single and CD album
market figures. (Fig. 1 and Fig. 2) It can beobserved that the CD single market has dropped
much more rapidly than the CD album market has.

140

Index (Year 1999 as 100)

120
100
80
60
40
20
0
USA

Germany

FranceUK

Japan

Fig. 1. The change of CD-album sales of the mainmarkets (1999-2003) by taking the sales in 1999
as 100Sources：Record Industry Association of Japan (2005)
140

Index (Year 1999 as 100)

120
100
80
60
40
20
0
USA

Germany

FranceUK

Japan

Fig. 2. The change of CD-single sales of the mainmarkets from (1999-2003) by taking the sales in1999 as 100
Sources：Record Industry Association of Japan (2005)11

By applying the initial condition F (t ) = 0 , thefunctions can be shown as (6) and (7).
1 − e −( p +q )t(6)
F (t ) =2. Framework of analysis
2.1 Diffusion models(1) Rogers’ diffusion theory
Rogers (2003)[4] defined innovation as objects,
behavior patterns and ideas that is perceived as new
by individuals or other units of adoption such asgroups and organizations. In other word, innovation
includes (a) innovative product (b) innovative
behavior pattern and (c) innovative information andknowledge. The value of music CD lies in its
content so it is classified as (c) innovative
information and knowledge. Innovation is also
defined as the process of dissemination through aspecific path among members in a social system astime goes by. Such a diffusion process consists fourbasic factors, i.e. innovation, dissemination path,time and social system. Rogers proposed thefollowing diffusion theory according to a lot of
results of researches. (Fig. 3)（34 ％）

後
期
多
数
採
用
者

（34 ％）f (t ) =q −( p + q )tep

( p + q) 2 e − ( p + q )t
⎧ q⎫p ⎨1 + e −( p + q ) t ⎬
⎩ p
⎭

2

(7)
The accumulated number of

adopter until time t is equal to mF (t ) .
Once the innovation coefficient p , theimitation coefficient q and the potential m are

specified, the diffusion curve will be specified. ThisX (t i ) = [ p + qY (t i )][ m − Y (t i )] enables theprediction of diffusion process at any time.
Yamada et al. (1995) [7] noticed the shape ofdiffusion curve and suggested use the ratio p / q
to define the five categories on the diffusion curve.
∗∗∗
Point T , T , T and TIN = T − 2(T − T1 ) are used as
division points. All diffusion curves are divided∗
into five classes and points where TIN , T1 , T ,and T2 turn into zero respectively are defined as
the division points. (Table 1)
1

Late minor adopters（13.5 ％）

前
期
多
数
採
用
者

Late major adopters

初
期
少
数
採
用
者

Early minor adopters（2. 5％）

Early minor adopters

Innovative adopter

Adopters

採
用
者
数

革
新
的
採
用
者

1+

採
用
遅
延
者

2

Table 1 Classification of diffusion curves（16 ％）

Class

TimingLower boundp/qUpper bound

Time
時間

Fig. 3. Diffusion model and adopter categorization
proposed by Rogers.

(2) Bass model
The number of adopter at time i is noted as
X (t i )and accumulated number of adopter until
time i is noted as Y (t i ) .
X (t i ) = P (t i ) + Q (t i )(1)
P (ti ) = p[m − Y (ti )](2)
Q (ti ) = p ′[ m − Y (ti )] = q′

(3)

q=

2.2 Data construction
Since albums contain different numbers ofsongs and the prices might be quite different, it is
too complicated to analyze the diffusion of CDalbums; therefore, this research only focuses on themechanism of CD singles. The target data for
analysis is top 100 CD singles from 1991 to 2002.
By collecting the weekly sales for these 1200 CD
singles, sales curves of them can be drawn and usedas the diffusion curves in this research.

Y (ti )
[ m − Y (ti )] = qY (ti )[ m − Y (ti )]
m

q′
m.

where
Rewriting (1) by using (2) and (3) results in (4)This model is called Bass’ discrete innovation
diffusion model with p as the innovation coefficientq imitation coefficient.
and

3. Analysis result and discussion
3.1 Classification
Table 2 lists the number of CD singles in eachclass of each year from 1991 to 2002 and the
proportion of each class is shown in Fig. 4. Class V
and Class Ⅳ can be characterized as “ initialstage concentrated sales patterns.” Among all the
top CDs, 855 belong to initial-stage concentrated
sales patterns while Class I consists only 75. The
two lower sections of the graph constitutes 71.25%
but Class I, which is most common in the case off (t )

is the possibility density function of
adoption by time and F (t ) the distribution

possibility function. The model in (4) can be shown
as a continuous innovation diffusion model as (5).
f (t ) =dF (t )
= [ p + qF (t )][1 − F (t )]
dt

(5)

12

traditional product diffusion curves, only occupies
6.25%.

Class IClassⅡ

Table 2 Classification of top CD singles (1991-2002)

100
90
80

ClassⅢ70

ClassⅣ

6050

Ⅰ Ⅱ Ⅲ Ⅳ Ⅴ

40

2002

5

3 13

3 76 100

2001

4

6

9

7 74 100

10

2000

8

3

8

5 76 10001991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002

1999

5

7

8

8 72 100

1998

6

6

7

6 75 100

1997

4 11 16 11 58 100

1996

6

9 14 10 61 100

1995

6

8 17

1994

4

9 25 10 52 100

ClassⅤ

20

Fig. 4. Trend of classification of top CD singles from(1991-2002)

3.2 Trend of classification
It is observed that sales curves of CDs have
moved gradually from the lower side of theseparating line toward the upper side since the 90s.
In other word, sales patterns have moved toward theinitial-stage concentrated curve and the averagevalue of Class Ⅳ and Ⅴ increase as time goes by.
Class I ,Ⅱ and Ⅲ are mainly comprised of
the following two types.
① The first type is the debut singles of new
singers are not famous yet or albums for themovies/ special events such as the theme of FIFA
World Cup 2002. The sales curve of such CDs lookas the most common diffusion curve.
② The other type is the Japanese musicalgenre Enka. Since Enka records are usually released
without large-scale promotion and the buyers do notconsider purchasing the CD immediately after the
release day is important, p is smaller than that ofother pop music CDs as a result.
However, there are still some singers whose
debut single attracted much attention rapidly so thatthe sales curve of their CDs belong to class Ⅳ andⅤ instead of lower classes of diffusion curves.
Judging from the diffusion curves of the same
singers at different time, the following features are
noticed.
①Ayumi Hamazaki: The sales curve of her
singles remained in Class Ⅲ and Ⅳ since her
first single until the seventh. However, the sales
curves belong to Class V since the eighth single
until the twenty-eighth.
② Utada Hikaru: Her first single in 1998
constructed a Class I sales curve and then all her
singles reveal Class V curves.
The empirical analysis of other singers also
shows that once the sales curve of a single CD
results in Class Ⅳ or V curve, the sales curve ofnext single will never belong to the lower classes
anymore. Therefore, by taking the line
in graph a the borderline, the empirical analysis ofJapanese music market confirms that the points
which represent the same singer’s sales curves can

7 62 100

1993 11 10 18 14 47 100
1992

6 21 21 10 42 100

1991 10 11 1030

4 65 100

Total 75 104 166 95 760 1200

Judging from the t -values of parameters
p , q and m at 5% or 1 % significance, it isproved that all the CDs which belong to Class I,
Ⅱ, Ⅲ and Ⅳ fit the diffusion model well.
However, in the case of CDs that are clearly
included in Class V, q values are notstatistically significant. Such result shows thatthose CDs might fir other kinds of diffusion
curves better and it also implies the limitationof Bass model. According to the original data
pf those CDs, they had been ranked in the topseller chart for only 10-15 weeks (about 3
months). Because CDs that are highly initialstage concentrated usually remain in the chart
shortly, it is inappropriate to neglect them even
if Shintaku (2003) [3] and Srinivasan（1986）[9] suggested that data of at least 10 periods isnecessary for statistical analysis. Therefore,
since q << p , we conducted non-linear
regression analysis again by supposing thatq = 0 and p＜1 as a condition to prevent p
from diverging. The new result of p falls into
the 95% interval of the previously estimatedp , and the estimations of CDs with pconverging to 1 are also statistically significant.
The estimations of p , q and m are listed
in the appendix.
13

only evolve from the lower section toward theupper part without any reverse movement.

necessary. The music downloading service bymobile phone is a new service that combined
mobile phone service and music downloading. In
the future, such new combination is definitely tonecessary to create new paradigm of music industry.

4. Conclusions
In conclusion, summarize the paper especiallyin light of Science of Institutional Management ofTechnology.

4.3 Future works
This research focused on the sales curves of CD
singles in Japan and its diffusion process in thesociety. In the future, after downloading service
become more and more popularized, the music
market may become a more international market
where a country is no longer an appropriate unit forthe diffusion curve analysis of music content. It is
important to include more details about how the
downloading service on the Internet diffuses among
different countries, not only the domestic market.
The complementarity of the Internet and CD is also
a subject worth more attention.

4.1 Conclusion
This research analyzes the diffusion curves ofCD singles by Bass model to categorize 1200 bestseller singles. The result shows approximately 70%
of CD singles followed the initial-stage
concentrated diffusion pattern. By focusing on
several specific singers who released many singles,
it is proved that once their product diffusion
trajectories enter the classes of initial-stage
concentrated diffusion curves, the diffusion curves
will never return back to the lower diffusion classes.
In the 90s, the exogenous parameterhasincreased continuously, and it indicates the degreeof initial-concentrated patter is higher and higher.
However, the sales figure during the first week after
release has decreased dramatically since the late 90s.
As a result, the total sales figure dropped obviously.
It is important for the music industry to realize
the traditional way of sell CD singles can no longlast as well as before. Not only the innovations suchas the Internet and MP3 have caused much effect,
but also the unique diffusion curve in music market
should be considered in order to devise a new kindof business model. Significant concerns placed on
exogenous mass media propaganda and efforts
made to increase the short-term sales figure may notwork well in the low growth economy anymore.

References[1] Press release of IFPI, http://www.ifpi.org/sitecontent/press/20051003.html[2] Press release of Record Industry Association ofJapan, http://www.riaj.or.jp[3] Shintaku, J., Tanaka, T. and Yanagawa N., 2003.
Geimu Sangyo no Keizai Bunseki, (Eds.), Toyo
Keizai Magazine. Tokyo. [in Japanese][4] Rogers, E. M. 2003. Diffusion of Innovations.
5.ed. New York: Free Press.
[5] Bass, Frank M., 1969. A New Product Growth
Model for Consumer Durables. Management
Science 15 (5) 215-227.
[6] Easingwood, C., Mahajan, V. and Muller, E.,
1983. A Nonuniform Influence Innovation
Diffuison Model of New Product Acceptance.
Marketing Science 2 (3) 273-295.
[7] Yamada, M., Furukawa, R. and Ishihara, M.,
1995. Classification Pattern of New ProductDiffusion. Marketing Science by Japan Instituteof Marketing Science 4, 16-36. [in Japanese][8] Tonegawa, K. 1998. Chaper 7: Diffusion of
New Products, Management Paradigm in the
Cyber Age. Tokyo: Doubun-kan Publishing. [inJapanese][9] Srinivasan, V. and Mason, C.H., 1986.
Nonlinear least squares estimation of new
product diffusion models, Marketing Science 5,169-178.
[10] Oricon Yearbooks, 1991-2003. Tokyo: OriconEntertainment. [in Japanese]

4.2 Policy implications
The information technology innovation has
promoted the substitution and competition processof different generations of products and service.
Similarly, since the music market has been stepping
into the digital stage, such substitution andcompetition process is also going on. However, due
to explosive amount of information, music
products/contents, just like other new innovations,can be popularized within a short period of time andmay also slip away from customers’ mind sooner
than being known by the consumer. However, thewhole music industry is still trying to use hugebudget o mass media propaganda to create millionsellers. Such strategies reveal their insufficientunderstanding about the society that has rapidlychanged by new information communication
technology. The mass production way may not be
the optimal path for the music industry anymore.
New functions should be built based on the full
utilization of core competences of music products.
Furthermore, the adaptation to, not escape from,new information communication technology is also

14

The Co-evolution Process of Technological Innovation- A Perspective from the Relationship between Mobile Phone Vendors andTelecommunication Service Operators in Japan
Chaojung Chen**

Department of Industrial Engineering and Managemen
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANchaojung@me.titech.ac.jp
In this research, the empirical analysis focuses on the mobile phone market in Japan,
whose achievement in various applications of mobile phone technology and high Internet
access rate through mobile phone. The analysis reveals that most domestic handset
vendors offer order-made models to maintain high-quality and to meet the specificdemands of each telecommunication service operators. As a result, global handset vendors
can hardly enter the co-evolution cycle by simply offering global models to the service
operators. Moreover, customers’ strong consciousness toward high quality and innovative
functions pulls out service operators and handset vendors’ commitment to quality andpushes the virtuous cycle of technological innovation to roll smoothly.

why the worldwide handset vendors are unable toperform in Japan as they accomplish in othercountries is explained. Finally, a co-evolution
mechanism between the customers and the supply
side, including handset vendors and service
operators, is elucidated in order to point out thebarriers for worldwide handset vendors inpenetrating such a well-defined market. This
research also aims at explaining how Japanese“inflexible” institution can drive the growth ofpenetration
rate
andenablethehighquality/advanced-features of the mobile phonemarket while impeding the Japanese service
operators and handset vendors to succeed in foreign
markets.

1. Introduction
While Japan’s rapid advancement of mobile
phone service is expected to be an important model
for similar advancement in other countries,
applying solely the experience of Japan to othermarkets does not promise the same level of successdue to various attributes of the markets. First, even
if it is noticed that Japan has achieved a relatively
high performance in the diffusion and innovation ofmobile phone, the attributes of the market that madethis possible are unclear. How to identify thequality and level of this market requires careful
examination. Next, what are the factors that
determine such an advanced market? Both thecustomer side and supply side should be taken into
consideration. Is R&D of the service operators andhandset vendors or the customers’ demanding
attitude toward new features the reason that enableshigh growth rate of new mobile services, such as
mobile Internet, and innovative handset features,such as the mobile camera? Last, the mechanismthat continues to drive the success of the mobile
phone market in Japan should be the key factor to
elucidate for the future of other mobile phonemarkets. Demonstration of the foregoing threehypothetical views is expected to lead a way inrevealing the above points in the veil.
Therefore, this research attempts to identify theuniqueness and quality of Japan’s mobile phonemarket. By classifying the handset models into
three classes, the extremely close and mutuallydependent relationship between the service
operators and handset vendors in Japan isdemonstrated. Based on the analyses, the reason

2. Analytical framework
2.1 Methodology
In order to elucidate the relation between
domestic handset vendors and service operators inJapan, it is necessary to clarify the pattern of how
handset vendors provide handset models to theservice operators. This analysis aims at classifying
the handset models into three types: global,
localized and customized model. Here “customized
model” means that the handset vendor provides thathandset model only to one service operator in thesame country. “Regional model” means that thehandset vendor provides very similar handset
models to different service operators in the same
country. “Global model” means that the handset
vendor provides that handset model to different
service operators in different countries.

15

handsets. On the other hand, Vodafone, the latest
comer among the top three service operators,
demonstrates the lowest ratio of customized andhigh-end handsets. This is considered as one of thedifferences of traditional Japanese service operator
and global-business oriented service operator.

2.2 Data
The target handset models are those listed in the
catalogs and websites of the handset vendors in
October 2005; the spec information and photos of
those handsets are collected from the catalogs andwebsites of NEC, Sharp, Panasonic, Fujitsu,
Mitsubishi, Sanyo, Toshiba, SonyEricsson in
September 2005). After the information of eachmodel is collected, all the models are listed byhandset vendor and then by service operator. By
comparing the spec and style of the same handset
vendor, it can be observed whether the same orsimilar model is provided to different service
operators. If the model is provided to only one
service operator, it is categorized as “customized”
model. If it is provided to multiple service operators
in Japan by only minor changes, it is considered as“regional” model. If it is also provided to otherservice operators in other countries, then it isclassified as “global” model.
3. Results and discussion
3.1 A “customized” model oriented market
The models analyzed are listed in Fig. 1 byhandset vendor and then by service operator. Somehandset vendors, such as Panasonic and Fujitsu,
only provide handsets to a specific service operator,
so the models are clearly classified in “customized”
models. Mitsubishi once provided handsets to two
service operators, but tend to concentrate on one
service operator after 3G models become the mainstream in the market. Other handset vendors,
including Sanyo, Toshiba, and SonyEricsson,
provide handsets to multiple service operators.
However, by comparing the spec and style of themodels, it is observed that these handset vendors
provide completely different models to different
service operators. Only N900iG and 802N made by
NEC as well as 802SH and SH506iC made by
Sharp provide similar models to different service
operators and are classified in “regional” models.
Other models made by Sharp and NEC except thesetwo pairs of models are, similar to Sanyo, Toshiba,
SonyEricsson and Mitsubishi, classified in“customized” models.
It demonstrates that 93% of the models in
September 2005 can be classified in “customized”
models. This analysis demonstrates the relationshipbetween handset vendors and service operators inJapan is proved to lie in the order-made pattern ofcooperation resulting in depending on “customized”
model. It is not an open environment for a handset
vendor to develop one universal model and simply
provide it to different service operators. It is also
observed that NTT Docomo, with its longest historyof mobile phone business in Japan, demonstrates
the highest ratio of customized and high-end

Fig. 1. Categorization of handset models by vendor andoperator (Sep. 2005).
Sources ： Website and catalogs of NEC, Sharp,
Panasonic, Fujitsu, Mitsubishi, Sanyo, Toshiba,
SonyEricsson.

3.2 Institutions molding Japan’s market
In Japan, the mobile handsets are sold with boththe name of the handset vendor and the service
operator. Therefore, from the service operators’
perspective, which model they should adopt is also
a decision that will affect their share in mobile
service market. For service operators, it isconsidered as an important strategy to obtain new
subscribers and maintain the existing users bylaunching more attractive handset models (NTT,1999). Moreover, the models that the service
operators adopt from the handset vendor to launchin the market also determine the structure ofcustomers’ subscription by digital segment.
Since the relationship between service operatorsand handset vendors is an important key factor todetermine the provision of handset models inJapan’s market, the ratio of high-end handset
models adopted by the service operators also affecttheir own 3G subscription rate. As illustrated in Fig.
2, the ratios of high-end handset models by service
operator are 50%, 40% and 21% for NTT Docomo,16

au KDDI and Vodafone respectively. Consequently,
by the end of September 2005, more than 70% of
NTT Docomo subscribers communicated through3G wireless technology and have the accessibility
to various advanced application service while only
55% of au KDDI and 40 % of Vodafone did so as
illustrated in Fig. 3 ( GfKMSJ, 2005). The level ofmodels adopted from handset vendors by theservice vendors definitely affects the level ofapplication services offered by the service operators.
NTT Docomo

(%)

au

persuade them to adopt the handset models.
Consequently, each model must meet the technicalneed of the service provided by the service operator
as well as the brand image of both the handset
vendor itself and the service operator. One manager
of Fujitsu confessed, “While we would like tocooperate with multiple service operators, too; it isreally difficult to afford the huge amount of R&D
invested separately for each service operator.” The
one-to-one close relationship between the handset
vendors and service operators can be considered asa consequence of supply-side co-evolution in orderto maintain high-quality and rapid innovative
process. In order to satisfy the demand of picky
customers, service operators use high standard inchoosing handset vendors and are the “real”
customers of handset vendors in Japan. Handset
vendors must develop and produce handset to meet
the technical specification and infrastructure of theservice operators, and they also have to design
fashionable products that can attract the end-users.
Customers, handset vendors and service operatorsform a strongly intertwined relationship wherehandset vendors and service operators supervise
each other and the customers dominate both handset
vendors and service operators as illustrated in Fig. 3.
Customized production and model development
combine the handset vendor and service operator
tightly leading their branding targets to converge
thereby satisfy Japan’s demanding customers’
qualified functionality requirement. Such a supply
structure, together with customers’ high level ofdemand structure, constitutes a sophisticatedinstitutional system leading Japan’s rapid increasein high functional mobile phones in a selfpropagating way.
However, this structure, on the other hand,resulted in the development of a barrier against
global handset vendors. By comparing the market
share of 3Q 2005 in the worldwide and Japan’s

Vodafone

80
60
40
20

Sep-05Aug-05Jul-05

Jun-05

May-05

Apr-050Fig. 2. Trend in the ratio of 3G mobile phone service
subscribers of each service operator in Japan(Apr. 2005 – Dec. 2005).
Sources：Database of subscribers by service operator( GfKMSJ, 2005).

Since all models are sold with both the namesof the service operator and the handset vendor, boththe service operator and handset vendor bear
responsibility for the handsets in Japan. In othercountries where the customers choose the handset
models with only the handset vendor’s name, thehandset vendors can focus simply on satisfying thedemand of the immediate customers.
Contrary to such a structure, the first step of thehandset vendor to keep a place in the market in
Japan is to satisfy the service operators andProduct
development

Production

Quality control

Japan
Vendors

Proposal based on
operators’ needs

Operators

Announcement
to the vendors

Products agreed
by vendors andoperators
Discussion
andadjustment

Marketing andsales

Far more testing
items than European
vendors
Double testing by
operators andfeedback to vendors

Other countries
Vendors

Operators

Vendors’ own
development

Based on theorder fromoperators

Vendors’ testing
system only

Sales prediction
and procurement

Feedback by
consumers

Invisible efforts
such as bugs
solving
Marketingdominated byoperators

Feedback to thevendors
Operators bear thecomplaints/ praiseof consumers

Marketing based Vendors bear theon the brand of responsibility
vendors

General testing on
the operator side

Fig. 3. The comparison of the mechanism under the mobile phone markets in Japan and other countries.

17

market, it is clear that top global handset vendors
do not perform well in Japan’s market as illustrated
in Fig. 4. Since most global handset vendors
provide global models in different countries, it isvery difficult for them to become so intimately
related to the service operators in Japan and enter
the one-to-one order-made tight relation of Japan’s
mobile phone handset supply side.

the quality of handset, and the service operators, notthe mobile phone end-users, are actually theimmediate customers of the handset vendors.
Handset vendors in Japan rely on the service
vendors very much. This close relationship of R&D,
manufacturing and sales cooperation drives the
progress of the mobile phone in Japan, but may not
be applicable in other markets where the service
operators and handset vendors have to face themarket separately. Japanese vendors and service
operators should learn to be more independent fromeach other and more flexible in order to adapt
themselves to the local supply side structure inother markets.

Others, 22.50%
Nokia, 32.00%

Sony Ericsson,
6.60%

References

LG Electronics,
7.40%

Casio
1.9%

NTT Mobile Communications Network, Inc.,
1999. NTT DoCoMo’s Vision towards 2010.
NTT Mobile Communications Network, Inc.,Tokyo.

[2]

GfK Marketing Services Japan Ltd.
(GfKMSJ), 2005. Panel Survey: ProFidenceof Mobile Market in Japan. GfKMSJ, Tokyo.

[3]

Website of NEC. Product information;
September 2005 <http://www.n-keitai.com/>.

[4]

Website of Sharp. Product information;
September 2005
<http://www.sharp.co.jp/products/index.html>.

[5]

Website of Panasonic. Product information;
September 2005 <http://panasonic.jp/mobile/>.

[6]

Website of Fujitsu. Product information;
September 2005 <http://www.fmworld.net/>.

[7]

Website of Mitsubishi. Product information;
September 2005
<http://www.mitsubishielectric.co.jp/products/
index.html>.

[8]

Website of Sanyo. Product information;
September 2005 <http://www.e-lifesanyo.com/>.

[9]

Website of Toshiba. Product information;
September 2005
<http://www.toshiba.co.jp/digital>.

Motorola,
18.60%

Samsung,12.90%

Sanyo
4.3%

[1]

Kyocera
1.3%

Nokia
0.5%
Sharp
19.3%

Mitsubishi
4.8%
Toshiba
6.3%
Fujitsu
9.8%

SonyEricsson
18.1%
Panasonic
15.9%
NEC
17.7%

Fig. 4. Market share of handset in the worldwide market
and Japan (3Q 2005).
Sources：Press release of International Digital
Corporation (IDC) and IDC Japan.

4. Conclusion
Due to Japan’s social institution, consumers’
strong consciousness toward high quality, andinnovative functions driving both service operatorsand handset vendors’ commitment to quality, aclosed but high-standard relationship between
handset vendors and service operators has beendeveloped which works closely with consumer
demand. This mutually dependent relationshippushes the virtuous cycle of technologicalinnovation so that it works smoothly and efficiently.
Japan has also become a market dominated byorder-made handset development between service
operators and handset vendors whose close tie-up
supports this demanding market. Both the service
operators and handset vendors are responsible for[10] Website of SonyEricsson. Productinformation; September 2005
<http://www.sonyericsson.co.jp/>[11] Website of International Data Corporation(IDC) Japan; September 2005
<http://www.idcjapan.co.jp/Press/index.html>.

18

Similarity and Disparity between Mobile Phone and Automotive Industry of Japan:
Resilient Business Strategy toward a Ubiquitous Society
Chaojung Chen**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANchaojung@me.titech.ac.jp
While Japan has experienced from the economic stagnation for over 10 years, its
outstanding achievement in mobile phone and automotive industry has attracted world
attention. Similarity is observed in the domestic saturated market which demands for highfunctionality. Moreover, both products are categorized as products requiring integrated
technology and manufacturing that result in the vertically closed intertwined relationshipof the supply side in both markets. On the one hand, these two markets also demonstrate
apparent disparity that Japanese automotive industry has demonstrated success in the
global market while handset vendors have suffered from frustration in global mobile
phone market. While automotive industry keeps emphasizing the optimization of the
supply side by improving the manufacturing technologies, mobile phone industry pays
more attention on customers’ demand and corresponds to them by creating new
functionalities aggressively to reach the optimization between the supply side and thedemand side. This research, based upon the comparison between these two leadingindustries of Japan, points out that automotive industry should construct a coevolutionary dynamism by taking the demand side into consideration in new functionality
creation while the handset vendors should extend to other markets first from the supply
side approach.
mass” (Rohlfs, 2001) of young users in 1999 where
entertainment content, a micro-payment system,and push-based Internet mail played key roles in thecreation of this critical mass of users (Jeffery, 2005).
On the other hand, many existing studies havepointed out the strength of automotive industry ofJapan in terms of not only efficient production
systems but also the rapidly growing market shareof Japanese automotive manufacturers all over theworld (Tsuchiya, 2006).
However, currently both the automotive
industry and the mobile phone industry have faceda certain bottlenecks that worth considering.
Although Japanese handset providers boast theirhigh-end handset models with new functionalities,
facing the saturated domestic market, they haveattempted to enter foreign markets but most of them
ended without successful results. In this case, theexperience of automotive industry becomes
important for adjusting the global strategies ofmobile phone handset providers. On the other hand,
the lessons from mobile phone industry are also
appreciated by the automotive industry. Whilemobile phone industry has reformed mobile phone
technology with the customers and demonstrates
high degree of self-propagating dynamism(Watanabe, 2005) by transforming handset fromvocal communication service device into a device

1. Introduction
Despite of the economic stagnation in the 1990s,
Japan has been identified as a successful industrial
manufacturing country, particularly in theautomotive and electronics sectors (Lamming,
2000). Although the massive recession in Japan cast
doubt on the efficacy of Japan’s industrial practices
that had been lauded for a long time as best practice,
the automotive industry and electronics sectors still
demonstrate a leading role in the global market.
Actually, the main industries of Japan have been
evolving with the external economic environment
and the Japanese economy can be divided into four
periods (Komiya, 1997; Nippon Kougyou Bank,
1997, Mitsubishi Research Institute, 2006). It isalso observed that automotive industry andinformation and communication electronics
industry are both the main industries in Japan of
this era. Among all information and communicationelectronics sectors, mobile phone is the one which
has demonstrated a significantly high growth inJapan’s market. Not only the diffusion rate ofmobile phone service subscription is high but also
the achievement of mobile Internet has positioned
Japan as a leading company of mobile phone
technology as Korea. The top telecommunication
service operator NTT DoCoMo created a “critical

19

for data communication service in Japan,
automotive industry is also facing the demand forbreakthrough functions that far outrun the attention
on energy efficiency and low-cost production.
Based on the foregoing observations, this paper
attempts to elucidate the similarity and disparitythat cause the automotive industry and mobile
phone industry to both succeed in the domestic
market but demonstrate completely different resultin the competition of global market then apply thelessons from one industry to the other.

enterprise instead of a foreign firm; therefore, sameco-evolutionary process cannot be reproduced inforeign mobile phone markets smoothly. First, theservice operator does not pay for the R&D inadvance as the Japanese operators do. Next, thefunctions that the service operators want to develop
are not as those in Japan. Furthermore, sincehandset vendors have got used to sell handset
models to the service operators instead of thecustomers, corresponding to the demand ofJapanese operators are important for the handset
vendors. Gradually they tend to consider the market
from only the Japanese market perspective and arepossessed by the illusion that, as long as they can
succeed in the highly demanding Japan’s market,
success in the global market is also promised. It is
unavoidable for the handset vendors to establish
their own brand images without depending on theservice operators in foreign markets. Due to thefundamental
differencesinstructuresasdemonstrated in Fig. 2., Japanese handset vendors
failed to create their own advantages in the foreignsystem.

2. Similarity and disparity of the co-evolutionary
mechanisms
2.1 Co-evolutionary mechanism of the supply
side
The relationship in the supply side largely
depends on importance of the cooperation during
the development or manufacturing processes.
Fujimoto et al. (2001) defined the matrix plotting
by classifying with two axes, i.e. productarchitecture and competition. In terms of productarchitecture, all are divided into “integrated” or“module” by the reliance of the product on the close
cooperation as shown in Fig. 1 on the axes ofclosed or open standard among firms as theindustry’s standard.

Table 1 Product complexity and development effort

Links
among
firms

Integrated

Closed(To be covered by theindividual firm)

Main frame
Handcraft machinery
Lego (Toys)

Passengers’ carMotorcycle
Small-sized electrical
product (eg. Mobile
phone)

Open(No specific restriction
but the industry’s
common standard)

Personal computer
Packaged software
BicycleRollerblades

Microfilm
Case

Desk Jet
Printer

Mid-Size
Car

3

35

35

200

10,0001 year

2 year

1 year

1.5 year

3.5 years

2 people3 people

10 people

65 people

500 people

1800 h8500 h14000 h14000 h

2.5 million h$150,000$750,000$1.5 million$50 million$1 billion

Number of
Unique Parts
Development
Time
Size of Team forDevelopment
Engineering
Hours
Development
Cost

Inter-manufacturer dependence in R&D
ModuleJobmaster
Screwdriver

Source: Ulrich and Eppinger (1995).

Fig. 1. Classification by product architecture andindustrial closed/open standard.
Sources：Fijimoto et al. (2006).

Product
development

Production

Quality control

Japan

Both automotive and small-sized electrical
productions belong to the integrated and closed
system. As shown in Table 1, automotive vehicles
are complicated and require high level ofdevelopment effort. This results in the verticallyclosed relationships through long-term cooperation
in R&D and manufacturing process. In the case ofmobile phone, since the functionality depends on
both the infrastructure/service provided by thetelecommunication operators and the specification,
including hardware and software, of the handsets,
early-stage cooperation between the operators andhandset vendors is utilized fully in mobile phoneindustry. However, in the mobile phone industry,
the infrastructure is usually controlled by a national

Vendors

Proposal based on
operators’ needs

Operators

Announcement
to the vendors

Products agreed
by vendors andoperators
Discussion
andadjustment

Marketing andsales

Far more testing
items than European
vendors
Double testing by
operators andfeedback to vendors

Feedback by
consumers

Invisible efforts
such as bugs
solving
Marketingdominated byoperators

Feedback to thevendors
Operators bear thecomplaints/ praiseof consumers

Other countries
Vendors

Operators

Vendors’ own
development

Based on theorder fromoperators

Sales prediction
and procurement

Vendors’ testing
system only

Marketing based Vendors bear theon the brand of responsibility
vendors

General testing on
the operator side

Fig. 2. The comparison of the mechanism under themobile phone markets in Japan and othercountries.

In the case of automotive industry, an
automotive manufacturer can take its suppliers to
set up the plants to foreign markets together with
automotive manufacturers in order to establish a20and energy efficient vehicles, but the attentions areusually limited in energy and environment issues.
The development of automobile is considered torely on the supply side more than on the demandside. Although the close intertwined relationships
between manufacturers and parts suppliers are alsostrong in automotive industry, its structure andrelation with the demand side, as demonstrated inFig. 5., is different from that of the mobile phoneindustry. The interactivity between the demand sideand the supply side is not as frequent as that in themobile phone market.

similar manufacturing system as soon as possible.
Moreover, studies have demonstrated that actually
not only the Japanese suppliers but also more andmore local suppliers have learned to keep long-termcooperation relation with the automotive
manufacturers. The relative power of players in theindustry is also different. In mobile phone industry
in Japan, service operators actually take more
power in the supply side than handset providers.
Other global handset vendors have created theiradvantages by their brand images among thecustomers. As a result, the co-evolutionary
dynamism between the handset vendors and service
operators can hardly be duplicated currently. In theautomotive industry, automotive manufacturers
grab more power than suppliers and automotive
manufacturers can lead the suppliers even in foreign
markets. This enables the automotive manufacturers
to move the main players and find out theappropriate local firms to establish the whole value
chain even in other countries.
Planning

DesignPrototyping

Massproduction

Japan’s mobile phone market

Supplier

Sales
company

Ordering prototype
Evaluating
and feedback toand approving
supplier
Design andadjustment

Prototyping
and adjustment

Evaluating
and approving

Internal R&D

Handset vendors
2. Strictrequirement

3. Cooperation
in R&D
6. Closer
relationship

Service
operators

Internal R&D

Handsetvendors

Service operators
1. Demanding 4. High quality
services/products
5. More request
demanding
Customers

Taking a delivery ofcomponents andassembling the final
products

Customersi) usually price-sensitiveii) basic functions

Fig. 4. Comparison of institutional systems in Japan’s
mobile phone market and in other markets.
Sources：Chen and Watanabe (2006).

Mass-producing
the components
Taking a delivery of
the final products
and making a saleFig. 3. The process of development and production in theautomotive industry.

Tier2

Tier2

Co-R&D
Tier1

2.2 The role of demand side in the co-

Tier1

Co-R&Devolutionary mechanism
As illustrated in Fig. 4., the dynamism occurs inJapan due to the close relationship between
telecommunications operators and handset vendors
as well as the demanding attitude of Japan’s
customers. According to a survey in the EU, over
60% of customers claimed that they only needmobile handset for calling and short massage
instead of for various functions (Nikkei Market
Access, 2006). Even if the structure of the supply
side becomes the same in both Japan and othermarkets someday in the future, the attitude ofcustomers will definitely affect the development ofmobile phone and lead the supply side to respond to
the average level of the demand side.
On the other hand, there are also somedisparities in the development of the automotive
industry. First, it has been considered as merelymeans of transportation and this concept does notchange much. Undoubtedly, both the supply sideand the demand side demand for more comfortable

･･
･

･･
･

Tier2

Tier1

Manufacturer

Distributor firm

Customers

Fig. 5. Relationships between the supply side anddemand side of the automotive industry.

The foregoing disparities between the mobile
phone industry and the automotive market areconsidered to the reasons that cause current
bottlenecks in mobile phone industry andautomotive industry in Japan as summarized in Fig.
6. Judging from the forgoing discussion, the next
important goals of the mobile phone industry andthe automotive industry are the different strategies
suitable for the foreign market and more attention to
the demand side, respectively.

21

Low-price,
mid-price, andhigh-end
handsets forcustomers tochooseClaimsClaims about
Claimsabout
about
network
handsethandset7. Better
services
Responsible
services andResponsible
Responsible
Responsible
for network
handsetproducts
forforforhandset
network
qualityqualityqualityservicesi) rich in curiosityii) smart in assimilation
learningiii) thoroughThorough in learningiv) demanding enhanced
functionality

Sales andmarketingJapan
Automobile Implementing the
manufacturer planning ofproduct and sales

Other markets

New functionality

Basic function

Japan
GlobalMobile phone industry ( → Ideal Market
How to succeed in othermarkets)
Automotive ( ↑ How to createco-evolutionary dynamism)

Fig. 6. Current situation and bottleneck of mobile phoneindustry and automotive industry.

4. Conclusion
This paper compared the automotive industry
and mobile phone industry that have marked
outstanding achievement in the domestic market but
demonstrated different performance in the global
market. Two industries were compared from theperspectives of the supply side structure and role ofdemand side. Similarities are specified as thedomestic saturated diffusion rate and the closed
intertwined relationships of the supply side. On the
one hand, the disparities were also pointed out inthe paper. While automotive industry keeps
emphasizing the optimization of the supply side by
improving the manufacturing technologies, mobile
phone industry pays more attention on customers’
demand and corresponds to them by creating new
functionalities
aggressively
to
reach
the
optimization between the supply side and thedemand side. Moreover, the self-propagating
character is fully utilized in the domestic mobile
phone market but failed in the global market due tothe illusion that strategies which succeeded in Japan
could also succeed in other markets.
In order to fulfill the optimization in both
Japan’s market and the global market, it issuggested that the automotive industry should
create new functionality by paying more attention
to customers’ real demands as how mobile phone
operators and vendors do in Japan’s market while
the mobile phone industry should extend to othermarkets from the supply side approach first.
Therefore, cooperation with existing players inother markets by providing Japan’s advanced
technologies and sharing experiences in developed
mobile phone industry is considered to be suitable
for Japanese manufactures that currently struggle in
the global market.
References[1] Lamming, R. Japanese Supply Chain
Relationships in Recession. Long Range
Plannin 2000; 33: 757-778.
[2] Komiya, R. Industry Policy of Japan. Tokyo:
Tokyo University Press; 1984.
[3] Nippon Kogyo Bank Investigation Department.
Industries in Japan. Tokyo: Toyo Keizai

22

Shinpo; 1997.
[4] Mitsubishi Research Institute. Industries inJapan. Tokyo: Toyo Keizai Shinppou; 2006.
[5] Rohlfs, J. Bandwagon Effects in Hightechnology Industries. Cambridge, MA: MIT
Press; 2001.
[6] Jeffery, L.F. The Future of the Mobile Phone
Internet: An Analysis of TechnologicalTrajectories and Lead Users in the JapaneseMarket. Technology in Society 2005; 27: 69–
83.
[7] Tsuchiya, Y. The Strength of Japanese
Automotive Manufacturers in Asia. Tokyo:
Diamond Press; 2006.
[8] OECD, 1997. Special Issue on Information
Infrastructures. Paris. STI Review.
[9] Nelson, R.R. and Sampat, B.N., 2001. Making
Sense of Institutions as a Factor Shaping
Economic Performance. Journal of Economic
Behavior & Organization 44 (1) 31-54.
[10] Watanabe, C. and Kondo, R., 2004.
Institutional Elasticity towards IT Waves forJapan’s Survival: The Significant Role of an
IT Testbet. Technovation 23 (4) 307-320.
[11] Bauer, M., 1995. Resistance to New
Technology. Cambridge. Cambridge
University Press.
[12] Nelson, R.R. and Sampat, B.N., 2001. Making
Sense of Institutions as a Factor Shaping
Economic Performance. Journal of Economic
Behavior & Organization 44 (1) 31-54.
[13] Amin, A. and Wilkinson, F., 1999. Learning,
Proximity and Industrial Performance: An
Introduction. Cambridge Journal of
Economics 23: 121-125.
[14] Bluestone, B. and Harrison, B., 2000.
Growing Prosperity. Berkeley. University ofCalifornia Press.
[15] Shah, A., 1995. Research and Development
Investment, Industrial Structure, Economic
Performance, and Tax Policies. Oxford.
Oxford University Press.

An Empirical Analysis of Institutional Co-evolution in the Productizing of Solar
Photovoltaic – A Comparison between Japan and the USA*

Kwok L Shum *Department of Industrial Engineering and Management
Tokyo Institute of Technology

In this paper, we studied and compared the actual historic solar photovoltaic
installation data in Japan and the USA and proposed two productizing1 models to accountfor the differences. Japan deploys PV as a manufactured technology focusing on the nicheof grid tied small-scale residential system; this seems to draw upon her strong
manufacturing culture and associated social technology and institutions for suppliers
dominated innovations. USA deploys PV as a broadly defined innovation using acustomization strategy emphasizing user-oriented innovation in both on grid and off grid
applications. Different institutions are necessary to support the user-oriented model.
Empirical analysis of the diffusion patterns of PV application in grid tied small scale
residential system in respective contexts suggests that Japan’s institutions fit its
productizing strategy but USA’s institutions may not be appropriate for hers. We thenmotivate a notion of institutional co-evolution for the case of the USA and illustrate how
SIMOT’s framework can help to address the critical issue of deployment of renewableenergy technologies.

BIPV area potential (roof + façade) of that of theUSA. This paper proposes that this dramaticdifference in the solar PV installation experience isdue to differences in barriers in respective national
contexts which are in turn driven by policy and PV
productization strategy. Existing studies on
renewable energy policy have mostly focused on
subsidiary or financial based instruments andincentives to compensate for market distortion
renewable energy facing. However, a more
fundamental issue is the economics of production of
the renewable energy. The economics are jointly
determined by the cost of the constituent
components making up a PV system such as solar
cell module [Watanabe et al. 2000] and other BOS(Balance of Systems)4 components and also how
the PV technology is productized.

1. Introduction
As energy resources and global environment issues
are emerging domestically and abroad, theimportance of carbon saving renewable energy suchas solar photovoltaic is ever increasing. Yet,
introduction of renewable energy such as solar PV
to existing fossil fuel energy regime faces different
types of barriers due to carbon lock-in [Unruh
2000]2 arise through a combination of systematicforcesthat
perpetuate
fossilfuel-based
infrastructure that includes physical, social andinformational elements. These barriers put
renewable energy at economic, regulatory or
institutional disadvantage relative to the incumbent
forms of energy supply. Three major categories ofbarriers [Beck and Martinot 2004]3 are: 1) costs andpricing such as high transaction cost for distributed
renewableenergyprojects;
2)
utilityinterconnection requirements hurdles and costs; 3)market performance such as lack of technical orcommercial skills and information and access tocredit. General as they are, these barriers are often
quite situation specific contingent upon local
regional or country situation. Indeed, a review ofthe historic solar PV installation data in Japan andthe USA shows a marked contrast. According to
IEA [2003] Japan’s cumulative PV installation isthree times that of the USA. In the specific categoryof grid tied small PV residential system, Japan’s
cumulative installation is almost eight times that of
USA despite that Japan has only one tenth of the

PV small system, no matter on or off the grid, whilebearing the nature of consumer electronics
appliance, is basically a small project that needs
extensive on-site integration and installation works.
Standardization in design, installation andinterconnection [if applicable] will greatly optimize
ex-post transaction and installation cost. During theperiod of 1992 – 2003, Japan has focused on
productizing PV as grid tied small scale PV
residential system accounting for over 90% of its
cumulative installation. On the other hand, USA has
productized PV as a broadly defined innovation or
general purpose technology, customizing thetechnology to end user oriented requirements as on
and off grid small systems5 for residential and23

commercial applications. Different institutions arenecessary for the success of each of these strategies.
Our aim in this paper for this conference is asfollow:

approach to productize PV technology in Japan fora specific standard application.

1) Explainthedifferencesof
these
productization
strategies
andthecharacteristics of the innovation process;2) Propose
anevolutionary-theoretic
technology diffusion framework byconsidering, as a unit of analysis, both thephysical technology and the institutions;3) Motivate a concept of institutional coevolution to study and manage technicalchange or management of technology.

Fig. 1. an integrated PV value chain within a firmboundary in the PV industry in Japan.
Source: Sekisui Ltd. Japan.

2.2 USAOn the other hand, as of FY 2003, PV
cumulative installation in USA reached 275.2 MWp
with approximately 95.6MWp installed as on grid
distributed application. In fact, USA PV installationin the small systems category (exclusive of on gridcentralized application) is well spilt among off griddomestic, non domestic and on grid distributed.
However, the PV market has been dominated by off
grid applications (~60% of total cumulative
application). These off grid installations include
remote residential power, industrial applications,telecommunications and infrastructure, such as
highway and pipeline lighting or buoys. For theseapplications, they are competitive already sincecostly grid extension is avoided. The drawback isthat these applications are mostly non-standardized
and systems integration is project by project
rendering any type of systemic learning7 impossible
as is usually the case for user-oriented innovations
in renewable.

2. Different PV Productization Strategies
2.1 Japan
As of FY 2003, PV cumulative installation in
Japan reached 860 MWp with approximately 623
MWp installed as grid connected residential PV
systems. As mentioned in the introduction, Japan
adopted a mass production strategy to productize
the PV technology focusing small scale grid tiedPV residential application, this draws upon her
excellence in manufacturing technology [Watanabe
and Kondo 2004] featuring TQC, JIT, Kaizen andother organizational innovations such as Keiretsu or
closed networks of interlocking suppliers. Withinthese close networks, implicit transaction rules
among related entities and specific communication
languages are developed to coordinate productdevelopment. In fact6, a special condition of theJapanese PV industry is the fact that a few large
companies internalize the whole or at least large
portions of the PV value chain inside their own
company offering solar cell, module, BOS
components financing and installation andmaintenance. A lot of the houses in Japan are
either pre-fabricated or that construction companies
use standardized building components, favorable
for the integration of solar module. Solar cellmanufacturers therefore have either bought orforged strategic alliance with housing or
construction companies leading to vertical
integrated entities. The integration of the PV system
at an early stage in the planning of pre-fabricatedand mass manufactured houses offers the chance fora significant price reduction of PV systems
compared to individually built houses or retro-fit
projects. The pre-installation and mass fabricationof the unit homes in Japan enables the
manufacturers to limit actual installation work of
the PV system on the building site leading toconsiderable savings for the installation. The
vertical integrated infrastructure in the PV industry[Figure 1] is very conducive to the mass production

2.2.1 PV value chain issue:
In addition, a long history of PV spending on
R&D to bring down the cost of PV cells andmodules has created an industry focused primarilyon component manufacturing. As a result, themajority of engineers employed in the PV industry
in the USA are engaged in technology development
rather than product development. A large
percentage of PV sales to final customers flows
through small systems integrators who assemble
custom systems for individual customers. This
market structure necessitates a large value-added
component to each system, adding more than 50%of the final per-kilowatt cost of PV in many end-use
applications. That is, many different firms
participate in the PV value chain, and each requires
an acceptable profit margin, thus raising the price ofthe final product substantially. More importantly,
thismarketstructureinsulates
primary
manufacturers from PV customers. It keeps themarkets small, because each small company lacks
the economies of scale of the large manufacturer.
The small companies serving end-use markets do
not have the resources to manufacture and further
innovate standardized PV products that serve wholemarket segments rather than just a few customers.824

As a result, one of the most conspicuous differences
between the Japanese and US PV industry can beseen not only in terms of the diversity of
applications but also in terms of the value chain
structure which brings these applications to themarkets. We can conceptualize these differences interms of the physical technology and social
technology dichotomy framework by Nelson andSampat [2002]9. This is now the theoretical aspectof our paper.

PV system category.
Sources: IEA [2004] and authors’ own calculation.

The individual entry in the table represents thepercentage of PV installation in the category of on
grid small system design in each country. Indeed,
we found that Japan’s percentage is increasing
monotonically approaching unity verifying ourhypothesis that the country is focusing on thiscategory. If we attempt to see these time series asa diffusion curve, what is diffusing is the“singleness” of the installation focus. The“saturation level” is the state at which all the PV
installation in the country will be in grid tied small
PV system. Now, our objective is to find a way totest if the social technology of integrated PV value
chain, coupled with other institutional factors, suchas utility interconnection standards or requirements,
national subsidiary policies, various information
dissemination programs etc. can sustain thisproductizing focus of PV in Japan.

2.3 What is social technology?
Social technology is a concept to elaborate thecarrying out of the physical technology recognizing
the multi-party interaction involved in the operationof most physical technologies which sometimes
goes on within a firm and sometimes between them.
Within a firm, the M form of organizing a multi[products] company can be interpreted as a social
technology. Among firms and in the context of joint
research and development, a consortium withmember firms can be seen a social technology.
Social technologies10 therefore define theproductive pathway for doing things and they
define low transaction cost ways of organizing thatinvolve coordinated human interaction. The
different PV value chain structure of the PV
industry suggested above between Japan and the
USA can be seen as different social technologies
that productize PV industry in the two national
contexts.

Japan’s data is found to fit the conventional logisticwith high significance with an adjusted R square of
0.989. The conventional logistic assumes a word of
mouth communication process resulting an
epidemic process. Recent evolutionary theory hassuggested that re-interpretation of the epidemic
approach is necessary and to broaden the interagents communication process to a wide class ofevolutionary
processes
andinstitutionalarrangements sustaining the dynamics of diffusion.
The fact that Japan’s data fits nicely to a single
logistics highly suggests that the PV value chain, all
the relevant policies and the productizing focus
reinforce one another. This characteristic will serve
as a benchmark when we analyze the data for theUSA. In fact, USA’s data did not fit the single
logistic and have an adjusted R square of 0.862.

3. A technology diffusion framework tounderstand the differences in PV productization
strategy:
Our objective now is to understand theimplications of different institutions or, broadly
defining, social technologies, coupled with different
PV productization strategies, upon the dynamics oftechnology diffusion. We investigated the set of
historic installation data of the grid tied distributed
small PV system category as a percentage of the
cumulative PV installation in each country. Table 1
shows the normalized numbers.
USA
Japan
1992
0.06
1993
0.09
1994
0.16
0.14
1995
0.249
0.145
1996
0.343
0.143
1997
0.472
0.155
1998
0.582
0.158
1999
0.714
0.179
2000
0.79
0.202
2001
0.846
0.242
2002
0.88
0.299
2003
0.904
0.3473In order to further characterize USA’s data, we
adopted Davies [1979]11 and Alderman andDavies’s [1990]12 process technology diffusion
model and hypothesized that normalized installation
patterns in the grid tied small PV system category
in the USA may follow either of the two different
patterns: that of a simple innovation or of acomplex innovation.
Following Alderman and Davies [1990], we Probit
transformed the USA data according to thefollowingtransformation:
Φ −1 (mt nt ) = a + b log t for simple innovationand Φ −1 (mt nt ) = a + bt for complex innovation
where Ф is the Probit operator. Our analysis
showed that the PV USA data is more close to

Table 1 Normalized installation pattern for on grid small

25

adjustmentorinstitutionalco-evolution?
Specifically, what are the content and objectives of
institutional co-evolution? The SIMOT [Watanabe2004]14 framework suggests the three dimensions ofinstitutions; namely: national strategy and socioeconomic system, corporate or entrepreneurial
strategy and historic factors. These three
dimensions subsume the more well-known
institutional aspects of technology suggested invarious settings such as (but not limited to):complex innovation, (adjusted R square forcomplex innovation is 0.849 vs. the adjusted R
square for simple innovation of 0.575). Since wehave interpreted the diffusion curve as the diffusionof percentage of PV installation that is in the
category of on grid small PV system, this suggeststhat US PV effort in this category features an initialslow take-off and needs continual social technology
adjustments or institutional co-evolution [Kodama
1995]13. The USA pattern therefore departs fromthat of Japan and may be due to US’s productizing
PV as an “information technology” [Watanabe andKondo 2004] like physical technology emphasizinguser-oriented
requirements
acrossdifferent
applications using a social technology offragmented value chains of intermediary andindependent
systems
integrators.
These
combinations are not particularly conducive to
productizing of a given single category of PV
application unless there are institutions thatfacilitate significant cross-learning or spillover
learning among designs [Shum 2003; Yoshikawa
and Watanabe 2005; Ohmura and Watanabe 2005].
These differences are now summarized in thefollowing:

1. Vertical and horizontal subcontracting
relationships
orotherinter-firms
relationships; aka social technology
2. Cooperation, exchange or movement ofskilled labors; aka employment institution
such as life time employment to motivate
spillover learning
3. Network of designers/developers [Clark
2004]
4. Sources of capital [Clark 2004]
5. Technology
standardizationasaninfrastructure for continual productinnovation
6. Consortium policy leading to generation of
new technologies in the pre-competitivestage
7. Intellectual Property policy etc.
All of these mentioned and others are highly
relevant to the generation, cumulative learning,productizing and appropriating economic rents of
new technological innovations. Institutional coevolution suggests that these and other are thestrategic levers or mechanisms that policy makers
should turn to in order to facilitate the launching of
new technological innovation cycle.

Multiple designs
without standards
SingledesignProductization

Social technology and Productizationmatrix

For the specific case of productizing of PV
discussed in this paper, we can use a theoretical
notion in institutional economics to further
conceptualize the differences as a consequence tothe differences in productization strategies.
Transaction cost is essentially the cost of using themarket; it entails the search cost, cost of contracting(ink cost) and other ex-post monitoring cost. Wallis
and North [1986]15 suggested that the larger thetransacting sector or the number of intermediary
sectors in an economy, the higher the transaction
cost. The case of fragmented PV value chain in
the USA seems then will have a higher transaction
cost than that of Japan. It highly suggests that
institutional co-evolution in the productization of
PV in the USA will involve the continual
economization of relevant transaction cost andemergence of institutions that facilitate spillover
learning. For the case of Japan, institutional coevolution will be more focused on new

USAPVDevelopment;
Does not fit logistic;
Fits Davies’
complex innovation

JapanPV
Development;
Fits a logistic
formulation

Integrated
chain

Disintegrated
andfragmented
PVchainSocial Technology

4. Policy implications and future works:
From a policy standpoint, one relevant questionis what is the meaning of social technology

26[13] Kodama [1995] The emerging patterns ofinnovation. Harvard Business School Press.
Kodama compared the installation andutilization patterns of computer in Japan’s
prefectural government during the 60s and 70s.
A particular advantage of Kodama’s data isthat he can interpret the delay in utilizing thepersonal computer in certain categories ofprefectural government jobs as due to thosejobs called for institutional adjustments,
compared to others which are rather
independent in nature.

functionality development such as productizing PV
into other applications and new business models ofenergy service provision. This will be our future
joint works with appropriate governmentorganizations in Japan.

Notes and References[1]

Hereafter, deployment and productization are
exchangeable.

[2]

Unruh, G. (2000). Understanding carbon lockin. Energy Policy 28 (2000) 817 – 830[3]Beck, F and E. Martinot (2004). Renewableenergy policies and barriers. Forthcoming inEncyclopedia of Energy, Cutler J. Cleveland,ed. Academic Press/Elsevier Science 2004.

[4]

These include inverter, two way net meters
and other installation accessories and theyjointly account for ~ 50% of the cost of a PV
generation system.

[5]

Besides small system, IEA also defined
another category of PV application known as
grid tied centralized power plant like theconventional fossil fuel based power plant.

[6]

The rest of this sub-section draws heavily
upon Jager-Waldau [2004] PV Status Report
2004 – Research, Solar Cell Production andMarket Implemenation of Photovoltaics by theEuropean Commission[7]

Ornetzeder M. and H. Rohracher (2006).
User-led innovations and participation
processes; lessons from sustainable energy
technologies. Energy Policy 34 (2006) 138 –
150.

[8]

Ingersoll, E. et al. Industry development
strategy for the PV sector. REPP paper. The
section on PV value chain issue of USA is
heavily drawn from this paper.

[9]

Nelson, R and Sampat, B (2001), ‘Making
sense of institutions as a factor shaping
economic performance’, Journal of Economic
Behaviour & Organization, Vol. 44, pp.31-54.

[14] Watanabe [2004] SIMOT Program proposal
submitted to MEXT.
[15] Wallis, J., and D. C. North [1986, page 121].
“Measuring the Transactions Sector in theAmerican Economy,” in Long Term Factors
in American Economic Growth, S. Engerman,
and R. Gallman eds., University of Chicago
Press.

[10] These also include forms of businessorganizations, management practices, market
mechanisms and structures, public policies,
legal and regulatory structures etc.
[11] The diffusion of process innovations.
Cambridge University Press, Cambridge.
[12] Alderman, Neil and S. Davies [1990]
Modeling themetalworking industries.
Regional Studies, vol. 24.6. p. 513 – 528.

27

Technological Tajectory and Its Implications to Digital Convergence– the Case of Smart Solar Photovoltaic (PV)Kwok L. Shum
Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANkshum@ml.me.titech.ac.jp*

Solar photovoltaic (PV) shares many characteristics with information technology; a mostconspicuous of which is that it needs local users or developers’ participation in its
commercialization and utilization. This suggests that local institutional conditions will influence
the development trajectory of PV. Previous research has shown that diffusion patterns of PV
appliance in Japan and the USA are different. This report hypothesizes a closed (Japan) and open
(USA) model of PV deployment to further elucidate such differences. We demonstrate that, PV
system cost learning behaviors, under each model, are also different. In the transition to ICT
enabled PV, we draw upon notions of technological paradigms and trajectories to reason thelikely transition trajectories in each national deployment context. A general econometricspecification of cost of PV system, incorporating induced technical innovation effects, is proposed
to test how such paradigmatic effects may influence PV product development in the ICT era.
Key Words: PV diffusion patterns; open and closed model; dynamic learning behavior; technological trajectories,
induced innovations.
vertical integrated or closed PV value chain in Japanfavors a hardware functionality development approach
to meet new technical requirements for such a transition.
Alternatively, a productive organization which is based
upon open industry standard will better coordinate
diverse inputs providers for new service and businessmodels synthesis down the value chain. We formalize
such observations in terms of the notion of technologicaltrajectory and summarize by proposing an open modeland closed model of technology development andmanagement.

1. Introduction:
A noted trend in the development of energy system is its
increasing decentralization. Decentralization can be seen
as a new techno-economic paradigm in energy provision.
However, the installation of modular distributed energy
system such as solar photovoltaic (PV) close to the users
is only the first step towards this transition to asustainable energy system. As increasingly more
distributed renewable energy systems are outfitted withinformation
communication
technologies(ICT)
functionalities and other sophisticated power electronics
technologies, this allows seamless integration of
distributed grid-tied distributed energy systems. As aresult of this, smart energy services co-provision,
coupled with innovative business model, is becoming areality.

2. Two PV industry structures and deployment
models in Japan and the USA:A review of the cumulative PV (Photovoltaic) installedbase (as of Dec. 2003) in Japan and the USA is shown infigure 1. Not only has Japan built an installed base threetimes that of the USA; in terms of PV applications,approximately 90% of the Japanese cumulative installedbase is in grid-connected distributed category while in
the USA, the distribution of applications is more
fragmented with the same category constituting
approximately only 30% of the installed base. See figure
1 for comparison.

We suggest that the ex-ante industry structure in the PV
industry will influence the transition to the smart energy
service era in different ways. A quintessential
production characteristic of smart energy service is it
calls for coordination of multiple inputs such as ICT
vendors, utility grid access, software developers,
systems integrators and data and content providers. An
ex-ante productive organization which optimizes thesystem integration aspect of PV, like that of highly28

Figure 1 Comparing actual solar photovoltaic installation in Japan and the USA. Japan’s overall cumulative installationis three times that of USA. (Japan is on left). Source: IEA (2004)
By the end of FY 2003, the cumulative PV power
installed in Japan has reached 860 MWp withapproximately 623 MWp installed as utility grid tied
residential PV system or PV appliance; PV appliance isrelatively standardized with minimal user-customization
features. It can therefore be regarded as manufactured
technology with suppliers controlling the [product]
features and minimal on site customization. Production
economy is primarily that of factory learning by doing.
This is reinforced by the fact that several major housing
manufacturers vertically integrate a large portion of thePV value chain to combine PV installation in their
newly built houses, creating a new and homogenous PV
appliance market. The combination of a focused
deployment using highly vertically integrated firms
prompts us to propose this as a closed model of PV
deployment. (Shum and Watanabe 20051); for the caseof the USA, there is no single dominant market for PV
as yet. It is a conglomeration of regional markets andspecial applications for which PV offers the most costeffective solution relative to centralized generated
electricity. Until recently, the PV market has been
dominated by off-grid applications, such as remoteresidential
power,
industrial
applications,telecommunications and infrastructure, such as highway
and pipeline lighting or buoys (Jager-Waldau 2004 2 ).
This deployment pattern leverages the general nature of
PV principle or sees PV as a broadly defined innovation
and adapts it to applications not necessarily with market
potential of massive magnitude. In addition, the US PV
industry consists of mostly small intermediary systems
integrators and other input suppliers, rendering it very
fragmented comparing to that of Japan. A combinationof diversity of applications and fragmented value chain
consisting of a multitude of independent market players
can be portrayed as an open model of deployment.

3. Exploring the differences of a closed and openmodel of PV deployment:
Previous research has shown that the diffusion patternsof PV appliance are different for each national context.
PV appliance in Japan diffuses like that of amanufactured technology, closely fitting a simple
logistics. PV appliance in the USA diffuses as acomplex diffusion pattern 3 (Davies 1979) and needs
continual institutional co-evolution. As a result, as wehave expected the speed of diffusion in the category ofsmall PV appliance in Japan is faster than that of the
USA (0.204 vs. 0.056)
Another way to characterize the differences of the open
and closed models is through the examination of the
dynamic learning behavior especially in the PV
appliance system integration cost. As we have proposed,in the close model, system integration cost learning isdone in the context of vertical integrated firms withminimal participation of third party independent systems
integrators. On the other hand, in the open model,
system integration cost learning is done in the context ofa much more distributed learning system made up of
independent third party independent installers andintegrators in the market. We are interested to find out
how learning effectiveness will differ in the context ofsuch learning system differences. Figure 2 summarizes
graphically our analysis.

3

It is beyond the scope of the current paper to discuss
the methodological foundation of our diffusion analysis.
Basically, Davies’ so called Probit model is anequilibrium diffusion model. On the other hand,institutional co-evolution, especially in the adopting or
diffusion environment, is a dis-equilibrium process. The
greatest contribution is therefore to model a disequilibrium phenomenon in the context of an
equilibrium set-up.

1

In Proceeding of Japan Society of Science Policy andResearch Management 2005
2
PV status report 2004 European Commission

29Comparing the dynamic learning behaviors in local PV system learningct = c0 (vcuml ,t )20

λ (t ) = α 0 + α 1t + α 2 t 215
λ (t ) = −.549 + 0.001t 2

10

02

1

20

00
20

98
19

19

96

λ (t ) = −.143 − 0.003t

94

92
19

Japan
(systemcost)
USA(system
cost)

5
0

0.59
0.54
0.49
0.44
0.39
0.34
0.29
0.24
0.19
0.14

λ (t )

19

PV system cost net of module per W

in the PV appliance category in Japan and the USA:

25

2

3

4

5

6

7

8

9 10 11

Figure 2 (L) – comparison of dynamic trend in system integration cost of PV appliance for each model of deployment
and (R) – the actual variation of learning effectiveness with respect to time (measured in years): upper curve is Japan.
Technological trajectory is an outlook, a set ofprocedures, a definition of the relevant problems, and of
the specific knowledge related to their solution, along
which the direction of advance is programmed. Note thattechnological trajectory or paradigm does not provide ageneral theory of technical change; rather it tries to
explain why certain technological developments emerge
instead of others. Once a path has been selected andestablished, it shows a momentum of its own. This
enforces the direction along which the problem solving
activity and logic moves. Nelson and Winter (1982)
called this a natural trajectory of technological progress.
Once ‘a lock-in’ in the paradigm has been effectuated,
the trajectory can be seen as a ‘cylinder’ in themultidimensional space defined by these technologicaland other economic or institutional variables enablingand constraining future technological developments. The
SIMOT program objective can be interpreted assuggesting a more refined structure of this technologicaltrajectory, at the socio-economic system level, as a three
dimensional intertwining process of historicalperspective, micro entrepreneurial or firm strategy andmacro government policy. Together, these threeconstitute a reinforced or sustained institutional systemgoverning the development of a new technology.

This comparison yields useful insights to the learning
dynamics of system integration in each national context.
Japan’s initial learning effectiveness is decidedly moresignificant than that of the USA (.549 vs. .143).
However, USA’s learning effectiveness will improveover time. This is to be reinforced by establishing ofinstitutions such as industry standards and professional
installation practice across the 50 states (Maycock 2006,
IEA 2003) 4 . In addition, an increasing focus on PV
appliance and more integration of the PV value chain
will also expedite learning and boast learning
effectiveness for the USA. It must be noted that
increasing industry standardization and installation
practices in USA’s PV industry will constitute a
profession based productive organization facilitating
decentralized innovation and adaptation. This is a byproduct of the open model of deployment. As we will
suggest next, this institutionalized profession based
productive organization will also enable an open
standard based development trajectory in the USA.
4. Transition to the Smart PV era:
Our major concern now is about how will the existing
open and closed model of deployment influence such atransition, in terms of how will the rate and direction of
innovationbeinfluencedineachnational
context .Viewing the transition as a technical change, it
is enabled and constrained by the logic of the existing
deployment model: mass deployment with a verticallyintegrated structure in the closed model and useroriented deployment drawing upon increasing industry
standardization and standardized system installation
practices, collectively constituting a profession- based
production structure in the open model. Formally, eachmodel of deployment entails a technological trajectoryalong which PV development will proceed.

4.1 Technological trajectory of a closed system:
For a closed model of PV deployment, the mostconspicuous characteristic is its massive deployment
focus of a standard type in order to leverage upon theeconomy of mass production. According to NEDO
(2004 5 ), the overall key objective of the Japanese PV
roadmap up to 2030 is to put more PV systems in thegrid or in clustered hybrid system. While the roadmap
makes no reference to the incorporation of ICT into a
PV system, it focuses on the technical pre-requisite tosuch a development. In fact, as more and more PV
appliances are connected to the electricity grid, they

4

Personal telephone conversation with Paul Maycock.
See especially the section on training of system
integrators in the IEA 2003 country report (USA).

530

PV roadmap to 2030

professional system integrators or developers who will
adopt the standard for decentralized innovations. The
economy of open deployment model, as explained in theanalysis above, is based upon inter-projects learning
among market based system integrators who haveundergone industry-standardized training and jointly
coordinated by industry standards. This learningorganization will enable a development trajectory that isbased upon open standards. Open standard allows third
party developers, system integrators or user-owned orinvested utilities to develop or coordinate new energy
services by recombining different DERs and otherauxiliary input suppliers through open standards orinterfaces over existing built grid structure or privately
owned wires or micro-grids. From a learning standpoint,
common open standards and standardized programming
practices such as using XML will allow for or facilitate
inter-projects learning or cross-learning. More important,such independent developers or smaller investor owned
utilities will have less severe organizational inertia
found in traditional gigantic utilities, preventing thelatter to develop new services via new and decentralized
productive organizations. In the demand side, customers
or energy using households achieved learning by using
via using different energy services. Learning by using isfound to be an important reason for the take off of
iMode mobile internet service in Japan (Watanabe et al.
20038)

would pose instabilities to the electricity distribution
systems. One of the noted developments of PV systemtechnology6 in Japan is therefore as follow:…In shifting to a new PV system that exerts lesser loadon the grid, it is essential to improve the stand-alone
capabilities of PV system technologies with electricity
storage functions, active grid control technology using
multi-functional inverters….
This new plethora of system technologies can be seen as
enabling building block technologies for the transition tosmart PV era. It is essential to point out that these are all
hardware and manufacturing oriented functionalities
which, once developed, can be applied to all PV
appliances. This functionality development therefore has
the characteristic of information and can therefore
confer a rate or multiplier effect giving rise to increasing
return. There is a virtuous cycle effect between thedevelopment of such functionalities and the number of
PV appliance installed. This anecdotal evidence
therefore suggests how a mass deployment-biased
technological trajectory will enable and constrain thefurther development of PV system technology.
4.2 Technological trajectory of an open system:
On the other hand, for the case of the USA, the efforts
toward the transition to Smart PV are most noticeable interms of following developments:
1.

2.

3.

4.3 An econometric model to check the effects oftechnological trajectory:

Developing information model for PV
systems: its object model, service model andprotocol to facilitate exchanging data between
PV system with other distributed energy
resources and the utility distribution network
These models and protocols will fit into an
open Utility Communication Architecture(UCA-DER7) (Electricity Innovation Institute2003)
These standards allow different kinds of DER
to interact with all levels of utility grid andwith other numerous complementary input
suppliers such as database and content
providers for energy transactions or services
leading to communications network-based
commerce and business models based upon
DERs; the 3G revolution in the Energy sector.

To make rigorous our anecdotal analysis above, we
attempt to outline a general econometric specification inorder to test for how prevailing technological trajectory
will influence product development in Smart PV era
under a closed and open deployment model. We
construct a general specification for the system
integration cost (net of module) in the Smart PV era as
follow:ln c smart = α + β 1 ln f + β 2 ln k + b ln v cuml ,t + ε

α = f α (t ) + α 3 ln( fs ) + α 4 ln(os )β 1 = f β1 (t ) + β 13 ln( fs ) + β14 ln(os)β 2 = f β 2 (t ) + β 23 ln ( fs ) + β 24 ln(os)where f is inverter functionalities related productcharacteristics which should be more prominent in theJapanese closed model of deployment; k iscommunication related functionalities which should be
more prominent in an American open model of
deployment. We have also included dynamic learning
effects in order to focus upon the contribution of thesetwo categories of characteristics to system integration
cost. β1 , β 2 are respective elasticity. α represents
autonomous technical change. To register the effects oftechnological trajectories, we measure the stocks ofOpen standards or, in general, standard is an institutional
form that can be interpreted as coordinating
development or production activities, much like vertical
integration or other social technologies. The other halfof a standard-based productive organization is the6

In fact, according to Kosuke Kurokawa (1996), since
the inception of the sunshine program in 1974, Japan has
also focused upon research and development in PV
system technology rather than R&D at the device level.
7
DER = Distributed Energy Resources such as a PV
appliance, a small turbine with remote control andmonitoring functionalities, CHP plant etc.

831

In Technovation

time enabling different development logics. The closed
model of mass deployment focusing upon one standard
application, with supplier controlling the productfeatures in Japan favors a hardware functionality
development/improvement logic which perpetuates themass deployment logic by leveraging upon a rate or
multiplier effect. The open model of user oriented
deployment leverages upon the general purpose natureof PV in the USA. However, institutional co-evolution
such as industry standards and certified training forsystem integrators facilitating inter-projects learning tocompensate for the forfeited mass production economy
are important prerequisites to such a deployment model.
To the extent that such institutions are available, thiswill facilitate or lock-in an open standard development
logic in the transition to the Smart PV era leading to theproliferation of new energy service business models
development, by third party decentralized systems
integrators.

product safety standards or standards governing the
hardware functions of a PV appliance fs and stock ofcommunication standards or addressable DER object
information models os. Intuitively, a closed model of
deployment should have its β1 more sensitive to fs;
while an open model of deployment should have its
β 2 more sensitive to os, all other things equal. In otherβ13 ( Japan) > β13 (USA);similarly,
β 24 (USA) > β 24 ( Japan); in the context of eachcountry,similarβ13 ( Japan) > β14 ( Japan);words,

predictions can be made with respect to the case of theUSA. One of the shortcomings is that we do not haveenough data in the Smart PV era yet that will allow us toactually test for the contribution of these and otherparameters. This remains an ongoing research work item.
5 Summary:This open vs. closed model perspective of technology
management and development seem to have some merits
in studying general purpose technology or broadly
defined innovation of which the actual productizing islocal driven. In other words, the actual local institutions
will dictate how such a general technology will be
developed according to the existing technologicaltrajectories or institutional structure of production.
Ongoing work will apply such a perspective to othersuch pervasive technologies from a theoretical andempirical
perspective,
data
permitting.

This paper draws upon International Energy Agency(IEA) installation statistics on solar photovoltaic in
Japan and the USA to propose two conspicuously
different deployment models. These deployment models
influence not only the diffusion patterns of PV appliance(small scale utility grid tied residential system); theyalso affect the learning behaviors in the localized system
integration activities for this category of application.
We formalize such differences also in terms of different
technological trajectories constraining and at the same
References[1]Shum, K. and C. Watanabe, “Comparing solar
photovoltaic (PV) deployment in Japan and the USA– its implications to the SIMOT,” Proceedings of the20th annual JSSPRM annual conference 2005[2]Jager-Waldau, A., PV status report 2004 Research,solar cell production and market implementation ofphotovoltaics. European Commission Joint ResearchCenter 2004
[3]Davies, S., The diffusion of process innovation.
Cambridge University Press 1979[4]Kurokawa, K., “An overview of system technology inJapan,” Renewable Energy, Volume 8, Issues 1-4,
May-August 1996, p. 480-484[5]Nelson, R and S. Winter, An Evolutionary Theory of
Economic Change (Belknap Press) 1982
[6]Watanabe、C. and R. Kondo, "Institutional Elasticity
towards IT Waves for Japan’s Survival, "Technovation 23, No. 4 (2003) 307-320.

32

Government’s Role in Managing Disruptive Innovation –Lessons Learned from the Case of Electric Vehicle in Japan
Kwok L. SHUM**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANkshum@ml.me.titech.ac.jp
The notion of disruptive innovation has increasingly captured attention of innovation
scholars and managers. It refers to incumbent firms failing in the face of new emerging
technologies due to the former’s lack of flexibility to respond to new market andoperational requirements. This paper builds upon this literature and suggests a strategicrole government can play in mitigating this dilemma firms are facing in adopting
disruptive technologies. The case of introduction of alternatives to conventional vehicles inJapan is used to illustrate our proposal. Policy implications are then explored.
users to understand their needs and develop product innovation,delivering a steady stream of continuous product and process
innovations and systematically exploring the full extent of theinnovation space defined by the the market. Controlling for thisresearch observation, their failure probably is not due totechnical capability. What has apparently caused them1 failed
is that their recipe for success, in following a new dominant
design, becomes one which shapes the signals firms perceive
about future opportunities and the ways in which they allocate
resources to them. Riding along on one particular bandwagon
makes the enterprise vulnerable in its ability to jump on thenext one when it starts to roll.

1. Introduction
Disruptive innovations refer to innovations that are either
radical or architectural, the introduction of which devastatedestablished firms. Empirical analysis has found that incumbents
failed not because of new technological requirements but of
new operational requirments necessitated by new markets.
The two most noted studies of disruptive technologies arethose of Henderson and Clark (1990) and Christensen (1997).
Henderson and Clark examined why seemingly minor
technological changes can have devastating impacts on
incumbent firms’ abilities to compete in the market. They haveshown that incumbents in the photolithographic equipment
industry were sequentially devasted by minor technicalchanges. They attribute these difficulties to the fact thatsystems-level or architectural innovation often requires newroutines to integrate and coordinate engineering tasks.
Productive system displays high interdependency, and that it
may not be possible to change one level without changing
others. The frequent failure of incumbents to introduce newtechnologies can thus be seen as a consequence of themismatch that exists between the set of organizational
processes needed to support the conventional products/services
and the requirements of the new (Teece et al. 1997, p. 520).

The key challenge which organizations find difficult todeal with in these cases is not technological advance but rathera change in the technology/need configuration for new andmainstream markets. Innovator dilemma refers to thedifficutlites incumbent players have in simultaneously
managing sustaining and disruptive innovations.
A major potential for the extrapolation of the disruptive
innovation theory hinges upon the assumption that firms facesuch dilemma alone or on their own. In essence, the disruption
challenge is due to a closed sysetm which is optimized
allowing for only incremental or minor innovation along agiven technological trajectory. The literature has yet to develop
to discuss the possibility of firms collaborating to address theinnovator dilemma.

Christensen (1997) studied a number of industries in depth
and particularly focused on the hard disk drive sector for it
represented an industry where a number of generations ofdominant designs could be found within a relatively shortperiod of time (~ 20 years from 1970 – 1990). His distinctive
observation is that with each generation almost all of thepreviously successful players in what was a multi-million
dollar market failed to make the transition effectively and were
often squeezed out of the market or into bankruptcy. Most ofsuch failed firms are not non-innovative firms. They were
textbook example of good practice, ploughing a highpercentage of sales back into R&D, working closely with lead1

The pattern of disruptive innovation can be seen in avariety of other industries – for example mini-mills
disrupting the market for integrated large-scale steel
producers or manufacturers of mechanical excavators
challenged by smaller, simpler hydraulic equipment.
Other examples are decentralized renewable energy
sources such as wind and solar photovoltaic challenging
centralized fossil fuel power plant etc.

33

technology. This will be the focus of this report. The rest of thepaper is organized as follow: section 2 reviews the earlier
support programs by MITI, section 3 discusses the interim
outcome of such programs. Section 4 includes the major
developments from the industry side, namely, one of the major
manufacturers which has commercialized a vehicle design. The
last section attempts to provide a strategic policy framework to
manage the introduction of disruptive innovation based on thesynthesis of the available knowledge, future policy
implications are then explored.

This paper uses the case of the development ofalternatives to conventional vehicles to explore such a strategy
involving collaboration of manufacturing firms andgovernment to manage the introduction of disruptive
innovation with widespread societal benefits.
Environmental considerations are bringing pressure on
manufacturers to produce vehicle designs that are radicallydifferent from the current, conventional powertrain consistingof an internal combustion engine combined with a mechanicaldrivetrain (ICEV). The alternatives that have been discussed by
car manufacturers and governments with increasing intensity
during the past 30 years are:
1)
2)
3)
4)

2. MITI programs2

battery-powered electric vehicles (BPEVs)
hybrid electric vehicles (HEVs)
fuel cell electric vehicles (FCEVs)
conventional alternatives based on internal
combustion engines such as compressed natural gas
vehicles (CNGVs), ethanol and methanol-fuelledvehicles.

The MITI established a basic market expansion plan for
BPEVs in 1976 (MITI 1990). This plan (and the following
revised versions) was a comprehensive commercialization plan
coordinating
government
agencies,
companies
andmunicipalities in their efforts to expand BPEV development.
Barriers were identified and the relevant actors were called
upon to make efforts to remove these barriers through technicaldevelopment, amending laws and taxes, creating new standards
and building a fuel infrastructure (Iguchi 1992).

These alternatives have the potential for substantiallyreducing tail-pipe emissions and greater energy efficiency than
improved conventional ICEVs.

The first market expansion plan was originally intended tocover 10 years, but after a few years it became apparent thatthe plan was no longer appropriate. The oil markets stabilized
and the progress in technical development was slower than first
anticipated so the plan was revised in 1983.

However, the traditional technical dominant design, theICEV, has been refined and improved over 100 years, andtogether with a global industry characterised by fierce
competition restricting the possibility of taking the risks
involved in developing an alternative design, this could well bedefined as a case of market lock-in or the kind of industry, thatis most susceptible to disruptive innovation.

At the end of the 1980s and after the Rio summit in 1992,
global environmental and energy issues became an important
topic for the MITI in Japan. These factors, together with the
newly adopted ZEV mandate in California, increased interestin BPEVs again as a long-term sustainable option. As aconsequence, a third and more aggressive market expansion
plan for BPEVs was issued by the MITI in 1991. The goal wasthen to have 200,000 BPEVs on the road by the year 2000.

In fact governments all over the industrialized world have
tried to support the development of less polluting and more
efficient vehicles. However, Japan is the first country in which
a vehicle with an alternative powertrain (the HEV) has become
available on the passenger car market. In 2002 there were atleast three different hybrid models on the passenger car market
in Japan. While their commercialization is still at its infancy,
why is Japan, the undisputed automobile nation, being able tocome up with these working and potential designs which willcertainly disrupt the incumbent automobile industry? There are
obviously many answers for such development. The first whichcomes to mind is that the industry may be proactive in
anticipating such disruption in order to leverage first moveradvantages and production learning. The second is simply thatJapanese manufacturers have more sophisticated technology sothat working designs can be developed. We cannot rule out
such speculations.

In 1997, the MITI altered the third expansion plan from 1991
to include not only BPEVs, but also HEVs, CNGVs, methanolfuelled vehicles and FCEVs under the definition of CleanEnergy Vehicles. A new expansion plan was drafted in thesame manner as previously with new targets for the number ofvehicles to be in use by 2010. This was the first time thediffusion of HEVs was included by the government. The
inclusion of HEVs can be seen in the light of the new CO2
reduction target for 2008–2012 under the Kyoto protocol.
Previous goals had the main ambition of replacing petrol withelectricity, hydrogen or natural gas in order to ensure energy
independence. The Kyoto Protocol can be regarded as an
exogenous element in the introduction of HEV.
In 2000, the Policy Study Group for Fuel Cell Vehicles drafted
yet another plan for fuel cell commercialization organized by
the MITI/METI. The methodology used is similar to that inprevious BPEV expansion plans, thus including manufacturers,
government and other possible actors. The plan presents acommon vision for future FCEVs and coordinates activities
such as R&D, infrastructure, demonstration and standards,

Our interests, however, are in the process of developmentof the HEV technology. For example, Japanese government
actually has programs to support diverse electric vehicle
technologies as mentioned. While all of such represent
disruptive designs, why does the HEV technology come out
and not the other? What determines the emergence of this2

Sections 2 &3 of this report draw heavily from Ahman(2006). We therefore make the acknowledgement here.

34

HEVs are now established as a commercial option to ICEVs inJapan. However, it is still too soon to tell whether hybrid
configurations, either with an IC-engine or fuel cells, will
become the dominant design or only continue as a fuelefficient option. Despite the success of the Prius and the Insight,
HEVs still only account for 1% of the newly registeredpassenger cars in Japan. For BPEVs, it is now only exploredfor potential future niche market rather than mainstream use.

among stakeholders. The study group expects the introduction
phase to be between 2005 and 2010, when 50,000 fuel cellvehicles will be introduced in public utilities and FC-relatedcompanies. The target for the year 2020 is 5,000,000 sold
FCEVs.
The above market expansion plans have in common that they
all present comprehensive plans for the development andcommercialization of the targeted technologies. The plansinclude all the relevant actors identified by the MITI, including
industry, universities, local governments and government
agencies. The aim of these plans is to induce a common vision
among the actors and coordinate industry and government
policy. The efforts and the process of the relevant actors arecoordinated and supervised by the MITI. Little formal pressure
exists according to the MITI and the plan rests on a vision inwhich all actors, including the Government, are expected toplay their part (Watanabe, 2004)

Thirty years of development since the first modern prototype
vehicles with electric drive-trains has advanced alternative
power-train technologies substantially. The batteries havedeveloped from lead/acid batteries (greatly improved versionsof lead/acid batteries are still used in some applications) tocurrently deployed NiMH batteries and in some cases Li-ion
batteries.
AC-induction motors replaced DC motors in the late 1980s andcurrently PM (Permanent Magnet) motors are deployed in all
Japanese BPEV and HEV models. The most crucial andenabling technology for HEVs has been the development ofadvanced, light, efficient and affordable power electronics
and control systems in combination with electric motors;
power electronics have been crucial for the utilization ofelectric drive-trains in vehicles. The main driver behind thedevelopment of power electronics development has, however,not been the automotive industry, but the needs from homeelectronics3 and the heavy industry. This is again a case orinter-industry spillover. Another important development is theintegration of mechanical and electronic transmission systems,
which enabled the further development of hybrid systems.

3. Interim outcome of the projects
From the BPEV field tests in 1996 it became relatively clear to
the automotive industry that the targets set up by the MITI in
the third expansion plan in 1990 would not be met (Patchell1999). The development in California was not encouraging, as
the ZEV mandate was being stalled and the market response to
BPEVs was weak. The perceived market outlook was thus
bleak and several battery development projects were halted, e.g.
Sony and 3M/HydroQuebec (Kalhammer et al. 1998).
Based on these reactions the marketing efforts for BPEVs
shifted from R&D on advanced batteries to educating users andfinding applications (e.g. rental, sharing or ITS systems) wherea state-of-the-art BPEV can function rather than trying to force
the technology to produce a vehicle with features comparable
to those of conventional vehicles. The MITI has beensponsoring the BPEV-ITS programs since 1997, but private
programs initiated by Toyota and Honda are also exploring thispath of development. Toyota has developed a special vehicle,
the Toyota e-com, which is available only through theseprojects.

As a result, the original or initial targeted technology (theBPEV) has not been established on the market. However, therecent market success of the HEV can partly be attributed to
the government support of the BPEV technology. The
enabling component, the electric drive-train, was developed
for automotive use within the BPEV programs offered by the
MITI. This technology was later utilized in the HEV. This is amajor observation (Ahman 2006) the current paper has drawn
upon.
The history of BPEVs in Japan therefore demonstrates that“picking winners” in government policy is not easy. Despite asustained and ambitious policy by the MITI, the developmentof alternative vehicles never unfolded according to plan. The
success factors for policy seem more related to technology
specific features than the particular policy style (Ahman 2006).
Evolutionary economics perspective of technical changes haslong suggested that technical change is highly nonlinear,
subject to path dependency and sensitive to initial conditions.
This seems to be a case that fits this conceptual framework
very well. While policy, subsidies and technology spillover
may partly constitute the emergence of hybrid, existing
literature lacks a perspective from the industry. The next
section attempts to provide some evidence.

3.1 Hybrid focus (1997)
The lack of confidence in the future BPEV-market and theAmerican PNGV program focusing on HEVs prompted the
MITI and the NEDO to start the ACE program in 1997,
unaware of Toyota's imminent release of the Prius. The ACE
program was changed at the last minute due to the release of
the Prius and is currently supporting research in and evaluating
the potential for, longer-term hybrid concepts, including
flywheels, ceramic engines for CNG vehicles, and bus concepts.
The real expansion came with the launch of the Prius and theinclusion of HEVs into the definition of CEVs, which qualified
them for economic support. During the first 2 years of the
Clean Energy Vehicles Introduction Program (1998–2000) 276
BPEVs and 12,242 HEVs were subsidized by the program. The
total number of HEVs sold was 22,400, thus only 55% of sales
was subsidized, whereas most of the BPEVs sold received a
subsidy. The CEV introduction program scheduled to continue
until 2001, but as more models became available on the market,
both BPEVs and HEVs, the program has been extended until
2003.

3

And no doubt, the consumer electronics industry inJapan is one of the strongest in the world, if not thestrongest. This again highlights how previous
technologies or knowledge will aid and shape thedevelopment of emerging techbnologies.

35

4. From the manufacturer side:
It was said that plenty of technical wizardy went intodeveloping the Prius, the popular gas-electric hybrid firstshipped for Japanese showrooms in 1997. But the production
tactics was also striking. Engineers at Toyota kept theassembly simple so the cars could be made in the same
production line as mainstream conventional models. This has
two strategic effects: 1) the learning and techniques acquired in
the mainstream models can be applied to the hybrid models; 2)minimal extra capital sunk into manufacturing. This isespecially important as the market4 for hybrid is still very
uncertain. Gas – electric hybrids have been around since theturn of 20th century. Porsche founder was among thevisionaries who tinkered with the technology. But few looked
for ways to mass-produce them. Toyota engineers settled for apartial solution by integrating an electric motor with aconventional power-train. As Mr. Takehisa Yaegashi has
concluded, ‘Hybrids began where EVs ended.’more exactly, the selection of a variant of electric vehicle
technology. Co-evolution therefore takes alternative form otherthan familiar formalism of coupled equations. This is a muchbroader and strategic view of the co-evolutionary dynamism.
The remaining question is then of course to study how theHEV technology in turn may shape the development or
optimize the performance of the institution into which HEV islaunched. Further study can also include cost learning
dynamism of different electric vehicle variants anddemonstrate that HEV has in fact traversed furthest down thelearning curve compared to other. Further analysis can also bedone to examine if the HEV learning characteristic has thesignature of a better match of institutions and technology
compared to other. Both analysis will hinge upon detailed
understanding of the cost structure of the different architecturaldesigns associated with different electric vehicle technology.
This will be an excellent joint collaboration opportunity
between an innovation management department and an
automotive engineering department.

5. Strategic policy framework and conclusion:

References

As we have suggested above, the development of the
BPEV has resulted in the HEV product in the market instead.
There are several reinforcing reasons for this unexpected
outcome. While regulation such as ZEV is one driver, othersuch as subsidy is also important for environmental innovation
the adoption of which is more expensive and the benefit is not
appropriable. This paper suggests a significant reason for HEV
is that it is the least disruptive among all the other electricvehicle technology due to that HEV assembly can leverage
upon incumbents’ existing operations and production
infrastructure. Government role in supporting the launching ofsuch new disruptive technology is to formulate consortium thatwill work on specific component technology such as battery
technology or control technologies upon a design the
manufacturing of which can leverage existing infrastructure.
To a certain degree, the HEV version is the least disruptive andis most compatible to the assembly of conventional vehicle.
Elsewhere, we have suggested a notion of the optimal
institutions for a disruptive or emerging technology is one
which will minimize transaction and production cost (Shum2006). In this case, since HEV can use existing manufacturing
infrastructure, involve no new re-fuelling infrastructure and canleverage upon existing distribution channel, the critical factor
becomes the production cost and learning potential of a new
power-train technology which in this case the HEV design
seems to stand out.
This case study also has interesting implication to the SIMOT
research program. This is a case in which technology andinstitutions co-evolution take place at the technology side; i.e.
how manufacturing institutions shapes the development or,

4

Takehisa Yaegashi – proud papa of the Prius (Dawson2005) from the web.

36

[1]

Ahman, Max. 2006. Government policy and thedevelopment of electric vehicles in Japan. Energy Policy
34 (2006) 433 – 443.

[2]

Christensen, C. 1997. The innovator dilemma. Harvard
Business School Press.

[3]

Dawson, C. 2005. Takehisa Yaegashi: Proud Papa of thePrius. BusinessWeek online.

[4]

Henderson, R. and K. Clark 1990. Architectural
innovation: the reconfiguration of existing producttechnologies and the failure of established firms.
Administrative Science Quarterly 35 9 – 30.

[5]Iguchi, M. 1992. Market expansion program of electricvehicles planned by MITI Japan. In proceeding of theurban electric vehicle OECD-conference Stockholm,
May 25 – 27.

[6]

Kalhammer, F. et al. 1998. Status and prospect of fuelcells as automobile engines. State of California air
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[7]

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expansion program in Japan. MITI. Electric vehicle
council Tokyo.

[8]

Patchell, J. 1999. Creating the Japanese electric vehicleindustry: the challenge of uncertainty and cooperation.
Environment and Planning A 31, 997 – 1016.

[9]

Shum, K. 2006. Closed and open PV deployment
models: characteristics and implication to the transition
to Smart PV. Tokyo Tech dissertation.

[10]

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technological, market and organizational change. 3rdedition. John Wiley & Sons Ltd., New Jersey.

[11]

Watanabe, C. et al. 2004. Effect and limit of thegovernment role in spurring technology spillover – acase of R&D consortia by the Japanese government.

An Empirical Analysis of Dynamic Co-evolution between GDP, Education and
PCs Diffusion Focusing on China’s Unique Institutional Systems
Shanyu Lei
Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-49 O-okayama, Meguro, Tokyo, 152-8552, Japan
leishanyu@ml.me.titech.ac.jp
Abstract
Number of PCs per 1000 people

30

Chinese government endeavors to create a “socialist market
economy with Chinese characters,” this economic system’s reformfrom planning-oriented economy to market-oriented economy
accelerated remarkable growth in economic development. In linewith rapid economic development, China’s education level andPCs diffusion developed significantly. Number of college students
per 1000 people and number of PCs per 1000 people increase 3.7
and 103.5 times from 1988 to 2002, respectively. Patterns of
Education and PCs diffusion trajectories demonstrate a parallel
path with GDP per Capita in China.
These characters in China prompt us to demonstrate dynamic
co-evolution between GDP, education and PCs diffusion focusing
on its unique institutional systems by diffusion theory.

20
15
10
5
0
1988

1990

1992

1994

1998

2000

2002

Number of colloge students per 1000 people

9
7
5
3
1
1980 1982 1984 1986 1988 1990 1992

1994

1996

1998

2000

2002

Fig. 3. Trends in Number of College Students per 1000
People in China (1980-2003).

2. Analytical Framework
In this research, the relationship between GDP, education andPCs diffusion are analyzed with the theory of diffusion. Therefore,
simple logistic model and Bi-logistic model are utilized as
illustrated in Fig. 4-5.

YYK
Y = −at+b
1+et
Fig. 4. Simple Logistic Model.

Y=

K1
K2
+
1 + e −a1t +b1 1 + e −a2t +b2

tFig. 5. Bi-logistic Model.

The analytical framework of this research is illustrated in Fig. 6.
E: number of college students
per 1000 people;
PC: number of PCs per 1000

9000
GDP per Capita (1995 fixed prices)

1996

Fig. 2. Trends in Number of PCs per 1000 People in
China (1988-2002).

1. Introduction
China’s rapid economic development draws the increasing
attention of the world, which is not only attributed to China’s
unique natural situation, but also attributed to her successfulreform of economic system. In China, economic system istransited from a planned economy to market economy from theend of 1978. This process is characterized as piecemeal, partial,
incremental, and often experimental (Justin et al., 1996), whichmatches China’s unique initial condition, such as large population,
great ratio of which live in urban areas, imbalance of local
economy. China’s reform in the micro-management institution canbe divided into four stages: Enterprises autonomy and the role offinical incentives with the traditional economic systems wasenlarged during the first stage (1979-83); shift to a formalizationof the finical obligations of the state enterprises to the government
and exposed enterprises to market influences during the second
stage (1984-86); The contract responsibility system, whichattempted to clarify the authority and responsibilities of enterprisemanagers, was formalized and widely adopted during the third
stage (1987-92); and during the fourth stage (1993- present), themodern corporate system was introduced to the state enterprises(Justin et al., 1996). Because of these reforms were performed in
China step by step, China’s economy, education and PCs diffusion
have developed significantly and their development patterns
demonstrate very similar as illustrated in Figs. 1-3.

25people
7000

5000

3000

1000
1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

Fig. 6. Analytical Framework

Fig. 1. Trends in China’s GDP Per Capita (1981-2002) -1995 fixed price.

37

As shown in Fig. 6, first, patterns of GDP, education and PCs
diffusion by time t are analyzed by means of simple andbi-logistic models (Steps 1-3), and then, the relationship between
them are analyzed by the foregoing two models (Steps 4-6).

From these results, it is identified that number of college
students per 1000 people grows in two trajectories, after 1995, thesecond trajectory grows very rapidly.
By means of the same method, patterns of PCs diffusion inleading 9 countries are analyzed. The results are summarized inTable 3.
Table 3 Estimation Results of the Development Trajectories of
PCs in the World

3. Empirical Analysis
Estimation results of the development trajectories of China’s
GDP over the period 1981-2002 by simple and bi-logistic models
are summarized in Table 1.
Table 1 Estimation Results for the Development Trajectoriesof China’s GDP per Capita (1981-2002)

K1

K1
1 + e − a1t + b1

K1

a1

b1

46420

0.074

-3.20

(1.02)(8.62)(-3.26)Bi-

4458.7

0.093

-0.52

8047.0

0.177

-3.81

logistic(4.35)(2.00)(-1.65)(2.12)(2.56)(-3.21)

K2

a2

b2

AIC

0.994

10.44

logistic

Simplelogistic

10.23

SimpleGDP per capita (RMB) 1995 fixed price13.347-133.48472.28

0.339

-7.98

(4.77)(3.11)(-3.11)(2.90)(28.35)(-21.03)

33.50

0.287

-5.59

(3.62)(26.96)(-27.70)

2.32

1.319

-18.30

8.69

0.321

-4.38

(2.15)(4.39)(-4.66)(3.04)(15.09)(-16.45)

0.390

-3.54
(-29.04)

5.05

0.808

-6.21

25.44

0.184

-3.77

Period0.987-0.600

1988-

0.999

-1.6220.999-2.7650.999-5.0120.999-2.7650.998-3.3990.999-3.2251.000-3.502

0.987

6.484

0.999

3.693

0.999

4.554

1.000

3.295

0.999

4.344

1.000

2.382

0.999

3.815

1.000

3.644

1.000

3.885

1.000

2.721

Estimated(7.84)(6.98)(-7.24)(2.36)(11.06)(-8.52)

19882002

79.76

0.193

-3.59

(2.34)(10.16)(-10.27)

Bi-

29.16

0.266

-2.84

275.061.600-27.43logistic(28.13)(46.41)(-102.4(10.46)(8.72)(-9.68)

19882002

5)

USA

S1

4000
3000

Simple

2000

S2

1000

Bilogistic

0
1981

1983

1985

1987

1989

1991

K1
1 + e − a1t + b1
K1

1993

1995

1997

1999

2001

E=
a1

b1

K2

SimpleBilogistic

adj. R2

b2

1228.9

0.118

-7.97

(0.85)(8.07)(-6.43)

SimpleBilogistic

SimpleBilogistic

Bi-

2.73

0.123

-0.50

8.47

0.737

-16.76logistic(4.89)(2.67)(-2.01)(7.41)(7.87)(-8.66)

0.996

-3.75

9
8
7

Estimated

Actual5

S2

4

231.83

0.473

-2.73

577.51

0.387

-7.42

(15.19)(13.57)(-21.21)(16.30)(11.24)(-11.75)

680.31

0.243

-4.05

(6.78)(12.49)116.280.912-11.891003.0

0.159

-3.87

(5.26)(9.48)(-10.45)(4.13)(17.41)(-15.46)

2002

S1

1

771.86

0.204

4.15

(26.09)(-68.61)232.240.710-14.35295.00

0.303

-3.90

(8.32)(8.78)(-8.81)(12.86)(24.32)(-65.33)

1984

1986

1988

1990

1992

1994

1996

1998

2000

19802002

766.82

0.179

-2.82

(4.67)(11.62)(16.70)103.471.017-11.82314.80

0.204

-1.79

(2.496)(4.11)(-4.27)(3.38)(7.34)(5.38)

19882002

816.34

0.159

-2.90

(6.93)(16.90)(-26.30)Bi-

189.42

0.329

-1.78

333.04

0.407

-6.68

logistic(5.65)(9.69)(-12.94)(3.83)(4.26)(-4.85)

19852002

China

India

Indonesia

Philippines

K1 (K1 + K2 )0.54%

21.07%

16.56%

9.59%

USA

Japan

CanadaFranceUK

K1 (K1 + K2 )28.64%

10.39%

44.05%

24.74%

36.28%

01982

19812002(15.40)

3
2

1981-

From Table 3, we note that all of results of Bi-logistic model
demonstrate statistically significant, which indicates that PCs
diffusion in these countries grows in double trajectories. However,comparing the ratio of the first carrying capacity and total
carrying capacities illustrated in Table 4 and Fig. 9, it is noted thatthe ratio of China is the lowest, which indicates the second
trajectory plays very important role in PCs diffusion.
Table 4 Ratio of the First and Total Carrying Capacities

106(-13.59)

UK

AIC

-3.77

-3.35

(10.22)

FranceSimple

0.999

0.137

(3.16)

CanadaK1
K2+
1 + e − a1t + b1 1 + e − a2t + b2
a2

1581.7

Japan

Education

1980

1988-

Phillipines

5000

SimpleAIC

2002(19.90)

SimpleActual

2

2002

12.68

8000

E=

per 1000 people

2.58(34.26)logistic

Fig. 7. Trends in China’s GDP per Capita with Bi-logistic
Growth Model with Time (1981-2002).
From this figure, we note that China’s GDP per capita develops
in double trajectories, the first trajectory develops in almost acertain level, on the contrary, the second trajectory develops fromthe low level, and overcame the first one after 1999.
Similarly, education pattern are examined by utilizing number ofcollege students per 1000 people over the period 1980-2003.
Estimation results are summarized in Table 2 and Fig. 8.
Table 2 Estimation Results for the Development Trajectoriesof China’s Education Level (1980-2003)

Number of college students

0.375(11.32)

Bi-

9000

6000

adj. R

Indonesia

By means of AIC, the regression results of bi-logistic model are
identified statistically more significant. Based on this result,trends in China’s GDP per Capita are illustrated in Fig. 7.

7000

b2

77.82

Bi-

0.997

a2

India

GDP
SimpleK2(2.71)
Bi-

adj. R2

b1

China
Simple

K1
K2
GDP =
+
1 + e − a1t + b1 1 + e − a2t + b2

GDP =

a1

2002

Fig. 8. Trends in China’s Education Level with Bi-logistic
Growth Model with Time (1980-2003).

38

50%

results of bi-logistic model are more significant. Based on theseresults, relationship between them is illustrated in Fig. 11.

44.05%
36.26%
28.64%

30%

Table 6 Estimation Results of the Development Trajectories ofChina’s Number of PCs per 1000 People by Education
Level (1988-2002)

24.74%
21.07%
20%

16.56%

10%

9.59%

10.39%

Philipp in es

Jap an

0.54%

PC =

0%
Ch in aIdo nesia

Ind iaFran ce

USA

UK

Canad aFig. 9. Ratio of the First and Total Carrying Capacities.

K1
1 + e − a1 E + b1
K1

a1

K1
K2
+
1 + e − a1E + b1 1 + e − a2 E + b2

PC =
b1

K2

a2

adj. R2

b2

AIC

PCs
SimpleTable 5 Estimation Results of the Development Trajectories ofChina’s Education Level by GDP per Capita(1981-2003)
E=

K

1+ e

1
− a1GDP + b1

K1

E=
K2

K1

1+ e
a2

+
− a1GDP + b1

a1

b1

699.540.0003-7.11(1.26)(11.32)(-8.65)Bi-

2.43

0.0008

-1.67

5.23

0.0024-17.00logistic(16.34)(4.99)(-5.52)(14.36)(9.08)(-9.49)K2
1 + e − a2GDP + b2

b2

adj. R2

AIC

0.999

-3.80

0.995

-4.17

Education
Simple6

Estimated

3

S1

2

S2

1

1983

1985

1987

1989

1991

1993

1995

1997

1999

11.17

8.118

-21.23

33.33

0.771

-5.45

logistic(20.08)(8.86)(-9.08)(3.96)(9.81)(-17.76)

1.000-0.6290.995-1.23630
25
20

Estimated

15

Actual

10

S2

S1

5
0
1990

1992

1994

1996

1998

2000

2002

Table 7 Estimation Results of the Development Trajectories ofChina’s GDP per Capita by Number of PCs per 1000
People (1988-2002)

01981(-4.92)

Fig. 11 shows strong relationship between PCs diffusion andeducation level in China, patterns of PCs grow in two trajectories,
which are very similar to education level, which suggests
education level strongly influenced PCs diffusion.
From an industrial society to an information society, IT plays
very important role in accelerating nation’s development. PCs are
key tools of IT, therefore the relationship between GDP per capita
and PCs diffusion is analyzed by the same method, and theestimation results are summarized in Table 7 and Fig. 12.

7

Actual-4.96(3.10)

Fig. 11. Trends in China’s Number of PCs per 1000 People
with Bi-logistic Growth Model by Education Level(1988-2002).

8

4

1.348

(7.91)

1988

Similarly, estimation result of Bi-logistic model is statisticallymore significant. Based on this result, trends in education level inline with GDP per capita are illustrated in Fig. 10.

524.309Bi-

Number of PCs per 1000 people

Nation’s education level chiefly depends on its economic
development. Therefore, in this research simple and bi-logistic
models analyze their relationship. The analytical results are
summarized in Table 5.

Number of College students

K1/(K1+K2) (%)

40%

2001

Fig. 10. Trends in China’s Education Process with Bi-logistic
Growth Model by GDP per Capita (1981-2003).

GDP =

K1
1 + e − a1 PC + b1

K1

Fig. 10 indicates that number of college students grows in double
trajectories; the patterns of education level are very similar to thatof GDP per capita (Fig. 7). However, the second trajectory ofeducation level grows rapidly after 1995, because in China,
reform of universities performed since 1995, many universities
endeavor to build comprehensive universities instead of single
colleges of social science or natural science, now local
governments try to build university cities in order to meet large
demand of high education in China.
PC’s operation need a certain level of knowledge, therefore, therelationship between PCs diffusion and education level aresimilarly analyzed by simple and bi-logistic models. Analyticalresults are summarized in Table 6. By AIC, we also note that

a1

GDP =
b1

K2

K1
K2
+
1 + e − a1PC + b1 1 + e − a2 PC + b2

a2

b2

adj. R2

AIC

PCs
Simple7127.50.336-0.101(18.74)(1.95)(-0.72)

Bi-

1983.9

4.042

-3.72

6862.40.080-0.282logistic(11.52)(4.81)(-4.27)(25.97)(11.10)(-3.71)1.000

12.222

1.000

8.807

Based on Table 7 and Fig. 12, we note that with great influenceof PCs diffusion, GDP per capita grows in double trajectories,
which are similar to PCs diffusion in China. Therefore, shiftingfrom an industrial society to an information society, PCs diffusion
influences nation’s IT level, which chiefly influences nation’s
growth. Therefore, China’s GDP grows significantly with rapid
PCs diffusion.

39GDP per Capita (RMB)

(i)

9000

Actual8000
7000

Estimated

6000

S2

5000
4000

Co-evolutionary dynamism between GDP, education and PCs
diffusion exists in China, that is, GDP effects education level,
and education accelerated PCs diffusion, which induced
GDP’s increase. This virtuous cycle can be attributed toChina’s reform of economic system.

3000
2000

(ii) China’s traditional economic system was itself a crystal ofinstitutional innovation induced by the government.
Self-propagating of institutional innovation accelerates
remarkable nation’s development including economy,
educational level and PCs diffusion.

S1

1000
0
1988

1990

1992

1994

1996

1998

2000

2002

Fig. 12. Trends in GDP per Capita Process with Bi-logistic
Growth Model by Number of PCs per 1000 People in
China (1988-2002).
From analytical results of Steps 1-6, it is identified that GDP per
capita, number of college students per 1000 people and number of
PCs per 1000 people in China grow in double trajectories,
furthermore, a virtuous cycle between them exist. Why suchspecial development trajectories and virtuous cycle exist in
China? Is it an occasional phenomenon or not? From thedevelopment history of China’s social and economical system, it
should be noted that since 1979, China began to change economic
system from planning-oriented economy to market-oriented
economy, after 1992, market economy are widely performed,
since this economic reform, China has great change in every field.
Therefore, from the view of institutional theory, relationshipbetween institutional reform and nation’s development could besummarized in Fig. 13.

(iii) Simultaneously, China’s unique institutional system decided
development patterns of GDP, education and PCs diffusion in
two double trajectories.
(iv) From China’s case, it can be concluded that reform ofsocio-economic system is the nutrition of nation’s institution,
only when this reform is adaptable and match with nation’s
actual situation, nation’s development in every field willgrow dramatically, otherwise, the socio-economic reform
will become the hell of the nation. China’s economic reform
matches the actual situation and changed step by step, which
are different from Russia and other countries.
(v) Given the unique institutional systems driving China’s
successful development, elucidation of the role ofinstitutional innovation in national, entrepreneurial andhistorical perspectives should be endeavored.

Double development trajectories of PCs Diffusion

References
1.

C. Benjamin and W. Olivier “National Institutional Frameworks,
Institutional

Double development trajectories of education

Complementarities

andSectoral

Systemsof

Innovation,” Cambridge University Press, 2004.
2.

R.L. Flood, “Complexity: A Definition by Construction of aConceptual Framework,” Systems Research 4 (1987) 177-185.

Double development trajectories of GDP

3.

F.R. Janes, “Interactive Management: Framework, Practice andComplexity,” in Ellis et al. (edt.), Critical Issues in Systems Theory
and Practice (Plenum Press, New York and London, 1995) 51-60.

4.

Y.L. Justin, C. Fang and L. Zhou, “The Lessons of China’s
Transition to A Market Economy,” Cato Journal 16, No. 2 (1996)
1-26.

5.

P. S. Meyer, “Bi-logistic Growth,” Technological Forecasting andSocial Change 47, (1994) 89-102.

1949

1979

1992

2005

6.

Co-existence

P. S. Meyer and J. H. Ausubel, “Carrying Capacity: A Model with
Logistically Varying Limits,” Technological Forecasting and Social
Change 61, No. 3 (1999) 209-214.

Fig. 13. Dynamism between Reform of Economy System, GDP,
Education and PCs Development in China.

7.

E.S. Phelps, “Models of Technical Progress and the Golden Rule ofResearch,” Review of Economic Studies 33 (1966) 133-145.

8.

C. Watanabe and R. Kondo, “Institutional Elasticity towards IT

4. Conclusion

Waves for Japan’s Survival,” Technovation 23, No. 4 (2003)

This research attempted to analyze the dynamism between
GDP, education and PCs diffusion focusing on China’s uniqueinstitutional structure. On the basis of an empirical analysis bysimple and bi-logistic models, noteworthy finding obtained
include:307-320.
9.

C. Watanabe, “Institutional MOT: Co-evolutionary Dynamism of
Innovation and Institution,” Proceedings of IAMOT 2005 (Vienna,2005).

40

The Role of Market Learning as a Coordinator of Techno-Countervailing Power-An Empirical Analysis of Canon Printers Based on Optimal Theory
Shanyu lei
Department of Industrial Engineering & Management
Tokyo Institute of Technology
Main control parameter R&D intensity µ (t ) is decided as

Abstract•µ (t ) =This analysis attempts to identify the optimal R&D investment level of thefirms and corresponding optimal level of learning efforts. By means of
the optimal theory postulated by Pontryagin, mathematical equations

T (t ) ,0 ≤ µ (t ) ≤ µ 0 < 1 .The finial form of dynamics for
S (t )

technology intensity can be expressed as:

identifying firms optimal R&D intensity level and corresponding optimal•levels of learning coefficient and marginal productivity of technologyx(t ) = µ (t )(1 − α )were developed. Taking Canon's printers development trajectories, their

Logarithmic index of consumption in time t:learning efforts were examined.

(4)

D(t ) = ln(1 − µ (t ) S (t ) = ln(1 − µ (t )) + ln S (t )(5)

1. Introduction

Based on equation (1), technology stock T (t ) can be expressed

Under a new paradigm characterized by a shift from an industrial society

as: T (t ) = S (t )1/ αto an information society, it is important for high-tech firms to improve

1/ α

A

.

their competitive power simply depends on continual R&D investment
which guarantees them to increase technology stock.

Therefore, technology intensity x(t ) and sales of innovative goods

The purpose of this research is to demonstrate a dynamic model, which

S (t ) can be expressed as follows:

includes increase growth and decrease trends of R&D investment, and try

S (t )1/ α
1−α
1/ α
(
)
T (t )
1
x(t ) == A
= ( )1/ α S (t ) αS (t )S (t )
A

to solve optimal problem for trajectories of firms’ technology growth.
Learning efforts of Canon printers will be examined by empirical analysis.

2. Analytical Framework

1αS (t ) = A1−α x(t ) 1−α

2.1 Assumption
For constructing a dynamic model for optimal R&D investment, sales ofEquation (5) can be developed as:

innovative goods S (t ) can be expressed as Cobb-Douglas productionln(1 − µ (t ) S (t ) = ln(1 − µ (t )) + ln S (t ) = ln(1 − µ (t )) +function of technology stock T (t ) as follows:

S (t ) = AT (t )α1αln x(t ) +
ln A
1−α
1−α

(1)

where A: scale factor and α : constant elasticity of sales to technology,. 0< α <1.

2.2 Utility Function

Take logarithms of equation (1):(2)

expressed by a discount rate
(1991) as follows:

Differentiate equation (2) in time t,+∞

J = ∫0 e − rt D(t )dt•

S (t )T (t )=αS (t )T (t )+∞= ∫0 e −rt (ln(1 − u (t )) +Technology intensity is defined as x(t ) = T (t )S (t )

where:

Therefore, dynamic process for technology intensity can be expressed as

•

•

•

•

•

•

T (t ) ' T (t ) S (t ) − T (t ) S (t ) T (t ) T (t ) S (t ) T (t )
) =
=
−
=
(1 − α ) (3)S (t )S (t ) 2
S (t ) S (t ) S (t ) S (t )ln x(t ))dt +ln A(1 − α )r

e − rt : discount multiplier.

+∞J ( x(t ), u (t )) = ∫0 e −rt (ln(1 − u (t )) +Under system’s dynamics,•

where μ(t) =α1−α2.3 Optimal Control Problem

follows:x(t ) = (J for optimal problem of R&D intensity can ber according to Grossman and Helpman

Utility function

ln S (t ) = ln A + α ln T (t )•(６)

T (t ) .= R(t)/S(t): R&D intensity.
S (t )•

x(t ) = µ (t )(1 − α ) ,

41

α
1−α

ln x(t ))dt

Control constraints: 0 ≤ µ (t ) ≤ µ 0 < 1 and initial condition for the

2.6 Saddle Character of the steady Statetechnology intensity: x(0) = x .

Jacobin matrix for the Hamiltonian system at the steady state0x= F1 ( x, z)z•x(t ) = (1 − α ) −2.4 Maximum Principle of Pontryagin
The Hamiltonian function for the stationary problem has the following•z = ρz +function:H ( x(t ), µ ,ψ (t )) =αln x(t ) + ln(1 − µ ) + ψ (t ) µ (1 − α )1−αz1= F2 ( x,z)
(1 − α ) −1−αxLinearization at the steady state,(8)

is defined as shadow price for x(t),∂F1
r (1 − α )11= − x=x = − * = −
z z=z
z
α
∂x

According to maximize principle of Pontryagin, maximum of the

∂F1
x
x*
r (1 − α ) 2= 2 x= x = − * 2 =
∂z
z z=z
(z )
α

Ajoint variables ψ = ψ (t )**

ψ (t ) > 0 .

**Hamiltonian function in control parameter should be:

z
z*
r
∂F2
= − 2 (1 − α ) x = x = − * 2 (1 − α ) = −
x
∂x
(x )
α
z=z

∂H
1
( x(t ), µ (t ),ψ (t )) =(−1) + ψ (t )(1 − α ) = 0∂µ (t )
1 − µ (t )µ (t ) = 1 −

*

*

∂F2
(1 − α )(1 − α )r (1 − α )
=r+
=r+
=ρ+
x=x
x
x*
α
∂z
z=z

1
ψ (t )(1 − α )**The Jacobi matrix at the steady state:

For adjoint differential equation,⎞⎟α⎟ = ⎛⎜ a11
r( 1 − α ) ⎟ ⎜⎝ a 21
r+
⎟
α ⎠

⎛ r( 1 − α )
⎜−
α
A=⎜
⎜ r
⎜−
⎝ α

∂H
α
1
ψ = rψ (t ) −= rψ (t ) −∂x
1 − α x(t )•2.5 Hamiltonian Systemr( 1 − α ) 2

a12 ⎞⎟a 22 ⎟⎠

Trace of the Jacobin matrix as:
According to the Hamiltonian system in prime and adjoint variables, thet = T2 A = a11 + a22 = r

following equations can be obtained:

Deter mint of the Jacobin matrix as follows:•x(t ) = (1 −d = def ( A ) = a11 a 22 − a12 a 21

x1
1
= (1 − α ) −)(1 − α ) = (1 − α ) −zψ (t )(1 − α )ψ (t )=−r( 1 − α )Because costs of technology intensity are expressed as: z = ψ (t ) x(t ) .

α

(r +

r( 1 − α )

α

)+

r r

αα

(1 − α )2 = −r 2 (1 − α )αFor the dynamics of costs,•••z = ψ (t ) x(t ) + ψ (t ) x(t ) = rµ (t ) x(t ) −Characteristic equation for eigenvaluesα+ ψ (1 − α ) − 11−αλ2 − tλ + d = 0 ,1zz= rz + (1 − α ) − 1 = rz + (1 − α ) −1−αxx
According to algebraic equation for steady state,z
1
rz + (1 − α ) −
=0
x
1−α

(9)

1
=0
xz

(10)

(1 − α ) −λ1,2 =

α and *z =r

4r 2 (1 − α )α2r 2 (1 − α )αr ± r2 +==0

4r 2 (1 − α )αr ± r 1+=2

4(1 − α )α2Therefore,

Based on equation (9) and (10), solution for steady states state should be:x* =r ± r2 +λ2 − rλ −αr (1 − α )λ1 =r + r 1+2

4(1 − α )α

> r ,and λ2 =r − r 1+4(1 − α )

2

α

<0

.
Equation for an eigenvector corresponding to the negative eigenvalue asfollows:

Optimal control at the steady states should be µ * = 0 .

42

⎛ λ2 − a11 − a12 ⎞ ⎛ y1 ⎞⎜⎜⎟⋅⎜ ⎟ = 0
λ2 − a22 ⎟⎠ ⎜⎝ y2 ⎟⎠⎝ − a22
r (1 − 1 +y 2 λ 2 − a11
=
=
y1
a12

4(1 − α )

α

)+

r

α

r

2 −α −α 1+2(1 − α ) 24(1 − α )α −α 1+z−z==αx − x**

4(1 − α )

α

(x −

α
r

)
>

x

< 2 − 2αα(1 − α ) 2α4(1 − α )α2(1 − α )(1 − α )4(1 − α )α(2 − α − α 1 +

+

r

2

2 −α −α 1+=α< 0 , which also coincides condition 2 ofcovertness of the solution.

Direction of an eigenvalue from the steady state,z = z * + a ( x − x* )3. Optimal R&D Investment and Learning

Sub optional control

3.1 Effect of Obsolescence of Technologyµ = 1−x( z * + a( x − x* ))(1 − α )•Change rate of technology stock T (t ) can be expressed as follows:•

T (t ) = − ρT (t ) + R(t )For condition 1 of covertness of the solution,x( z + a ( x − x * ))(1 − α )2 −α > α 1+

4 − 4α + α 2

4 − 4α >4(1 − α )

α

> 0

•

R(t ) = T (t )+ ρT (t )4(1 − α )•R(t ) T (t )T (t )=+ρS (t ) S (t )S (t )αα 2 +α 2>

ρ : Coefficient of obsolescence and R(t ) : real R&D investment.

Therefore, real R&D investment can be expressed as:> 0 , 2 −α −α 1+

Because α

where> 0 , z * + a ( x − x* ) > 0*4(1 − α )

•

where

α

R(t )
T (t ): real R&D intensity,: intensity of technology
S (t )S (t )

4α − 4α 2− (α − 1) 2 < 0

(11)

0 <

α

change and1

T (t ): technology intensity.
S (t )•z * − ax * > 0x=0αr (1 − α )−a1−(1 − α )1+

R(t ) T (t )T (t )1x)=+ρ= ρx + (1 − **( z + α ( x − x )) (1 − α )S (t ) S (t )S (t )αr> 02 −α −α 1+4(1 − α )α3.2 Optimal R&D Intensity4(1 − α )2(1 − α ) 2

αBecause at the steady state,>0
Therefore, optimal R&D intensity> 1 , which coincides the condition of the covertness.

x( z + a( x − x* ))(1 − α )αr (1 − α )

and

x* =

α
r

R(t )
ρα
= ρx * =S (t )r

In case when production function is depicted as follows,

For condition 2 of covertness of the solution,

*

z* =

S = Ae kt T α
optimal R&D intensity can be< 1

3.3 Optimal Learning

43

(1’)

µ = ( ρ + k )α / r .
*,Learning process can be depicted by prices of innovative goods

While the actual learning coefficient over the period 1985-1999 was

PV decrease by technology stock T as follows:slightly higher as 1.08 as estimated as follows:

PV = AT −φln PV = 6.608−1.083lnT − 0.149D DW 1.29

Differentiate by time t,

This suggests that Canon made intensive efforts in learning thereby,∆PV PV = −φ ∆T T

effective utilization of potential resources in innovation.

−φ = (∆PV PV ) R T

Table 2 summarizes Canon printers R&D trajectory over the period= (∆PV PV ) (( R S ) /( S / T )) = (∆PV PV ) ( x µ )When in optimal steady state,
Therefore,

adj. R2 0.990(−3.40)(53.42)(−35.71)

x* =1985-1999 after the full–fledged commercialization of LBP

bycomparing the optimal level.

α

,

r

µ * = ( ρ + k )α / r .

−φ = (∆PV PV ) ( x µ ) = (∆PV PV ) ( ρ + k )Indigenous R&D(12)

Utilization ofGrosspotential resources

technologic

in innovation

al growth(marketTFP/TF

learning)

Pb

φ

R&D

R/S

3.4 Optimal Marginal Productivity of Technology (MPT)

MPTa(1995 = 1.0)

contribution tosales( R / S ⋅ MPT )⊿Under the competitive circumstances

Optimal

5.63

1.23

6.92

0.91

7.83

Under the optimal R&D investment condition,

Actual

6.05

1.12

6.78

1.08

7.86

a

R / S = ( ρ + κ )α / r , α = MPT ⋅ T S = P ⋅ T S

Given the lead-time between R to T contributing S, average level in

1980-1999 is compared.

R S = ( ρ + κ ) ⋅ P ⋅ (T S ) / rb

P = ( R T ) ⋅ r /( ρ + κ ) = ( ρ + g ) ⋅ r /( ρ + κ ) ,

Since
∆TFP
TFP

Pt = P ⋅ PV

S = Aeκt T α ,= κ +α

∆T
T

=κ +

R
R
∂S T ∆T≈ κ + MPT ⋅ ≈ φ + MPT ⋅S
S∂T S T

5. Conclusions

where P: relative prices of technology; Pt: prices of technology and Pv: prices of innovative goods.

In light of the increasing significance of the effective utilization of theGiven that ( ρ + g ) /( ρ + κ ) = 1 / B , then r = BP , sincepotential resources in innovation for firms’ competition in a global

1 + mr = P /( ρ + r ) , 1 + mBP = P ( ρ + BP )megacompetition, this analysis attempted to identify the firms’ optimallevels of R&D investment and corresponding learning efforts.

From this equation, P can be identified as follows:P=

By means of the optimal theory postulated by Pontryagin, mathematicalequations− (mρB + B − 1) + (mρB + B − 1) − 4mB ρ
2mB 2
2

2

identifying

firms

optimalR&D

intensity

level

and

corresponding optimal levels of learning coefficient and marginal
productivity of technology were developed.
Taking Canon's printers development trajectories, their R&D intensity,

4. Impacts on Learning Coefficient – A Case of Canon Printers

marginal productivity and learning efforts were examined. Based on the

Table 1 summarizes the analytical results of Canon printers over the period

analytical results, it identified that while marginal productivity of

1975-1999 based on the following equation:technology is little bit lower than optimal level resulting in the lower
technology contribution to their sales than the optimal level despite higher
R&D intensity. However, learning efforts are maintained higher thanln(S T α ) = a + κ 1 Dt + κ 2 (1 − D)t + cD2

optimal level leading to complement the shortage of technology

Table 1 Analytical Results of Canon printers (1975-1999)

αcontribution thereby maintaining optimal TFP growth rate. These efforts

a

κ1

κ2

c

DW

AIC

adj. R 2

could be considered significant source of Canon’s high performance in

0.6

0.005
(0.02)

0.147(3.10)

0.285(17.38)1.132(5.41)

1.25

40.69

0.961

These results suggest the significance of the integrated approach in both

0.7

-0.042(-0.14)0.501(1.68)

0.129(2.74)
0.096(1.98)

0.266(16.43)0.220(13.16)

1.126(5.43)
1.197(5.60)

1.27

40.21

0.978

1.23

41.75

0.938

0.8

maintaining its conspicuous productivity over the last two decades.
indigenous R&D investment and market learning efforts for firms’ optimal
R&D strategy for their competitiveness.

Referenceswhere dummy variables D: 1975-84 = 1, D2: 1983-90 = 1, others = 0.

By comparison of AIC, under optimal state of Canon printers,κ

α = 0.7 ,[1]

is 0.129 over 1975-1984 and 0.266 over 1985-1999 after theAne, B.K., Tarasyev,A.M. Watanabe, C., 2006.

Impact of Technology Assimilation on

Investment Policy: Dynamic Optimization and Econometric Identification. Journal of

introduction of LBP in the market.

Optimization Theory and Applications, No.3．

Based on the result in Table 1, by means of equation (12) average learning[2]

coefficient with optimal R&D investment condition over the period

Arrow, K.J., 1985. Production and Capital. Collected Papers, Vol. 5. The Belknap Press ofHarvard University Press, Cambridge, Massachusetts, London.

1985-1999 can be computed as 0.91.

44

Fusing Indigenous Technology Development and Market Learning forHigher Functionality Development
ShanyuLei**

Department of Industrial Engineering and Managemen
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANleishanyu@gmail.com
Co-evolution between indigenous technology development in Canon’s printers and subsequent
market learning primarily from PCs producers through “coopetition” that attempts to learn theadvanced knowledge from the competitors by inspiring them in a cooperative way leverages afusion of indigenous printers technology and effects of market learning. Consequently, this coevolution leads to developing higher functionality development, which in turn induces further
strengthening indigenous technology.
where a : velocity of diffusion; V : carrying

1. Introduction
Canon constructed a sophisticated coevolutionary dynamism between its printersdevelopment and market learning primarily from
PCs producers through “coopetition” strategy.
Advanced printers induced further utilization of
PCs in broader fields which also induced further
advancement of printers technological development
and dissemination.
By means of this dynamism, notable fusion of thestrength of the printers technology and effects ofmarket learning emerged in Canon’s printersdevelopment which enhanced their functionality
development.
This paper, taking Canon’s printers development
over the period of 1975-1999, attempted anempirical analysis of the effects of the foregoing
fusion of Canon’s indigenous strength in printers
technology and its subsequent effects of the market
learning.
2. Framework of Analysis - Diffusion Trajectoryof Innovative Products

capacity, and FD =While emergence of innovation creates new
functionality, it obsolesces immediately. Given thelengthy years of efforts for emerging an innovation(e.g. 100 years from its origin), life time of newly
created functionality is an ephemeral existence.

Firms endeavor to maintain high level offunctionality development depending on
successive innovations leading to creating new
functionality as demonstrated in Fig. 1.
FD

⎛

b

⎞

⎞ − ai ⎜⎜⎝ 1− bKii ⎟⎟⎠ t⎛ b1⎟e
FDi = 1 + bi ⎜⎜1 + Ki ⋅bi 1 − a Ki ai ⎟⎠
⎝

FD1

FD2

FD3

FD4

Fig. 1. New Functionality Development Trajectory in a
Successive Innovation.

2.1 Functionality Development
Production of innovative goods V can bedepicted as follows:
V = F ( X ,T ) = F ( X ( T )) ≈ F ( T )(1)

2.2 Requirement to Sustainable Functionality
Development

where V: production of innovative goods; X:
labor (L) and capital (K); and T: technology stock.
Its diffusion trajectory by technology stock (T)can be developed in line with the following
epidemic function that leads to a single logistic
growth function:∂VV
1= aV ( 1 − ) = aV ( 1 −
)
∂T
FD
V

V
: functionality development.
VW

b ' = bη 2 η 2 = 1 −W = W ( κ2 )aKa

W = κ2

(2)

45

κ2

0

κ2

Figs. 2 and 3 demonstrate the actual and estimate
technology driven diffusion of LLBP as well as
LBP and BJ, respectively.

ln P / P0

κ2

Fig. 2. Requirement of External Learning to Sustainable
Functionality Development.
aκ 2 : elasticity of gross technology stock thatincorporated the effects of external learning; W :function of the effect of κ 2 ; γ , κ 1 , φ and A ,B : elasticities and scale factors of the following
functions, respectively:

1600
Cumulative sales of LLBP(\100 mils. at 1995 fixed priceln P0 / A ln T0 ⎞⎛W (κ 2 ) = ⎜ κ 1 −+κ 2 ⎟eln B
ln B ⎠
⎝

1400
1200

1994

1000
800
600

Actual

1990

1991

400
200

Estimate

1975

T# =

0

P = AT κ1 PC γ

0

10

20

30

ln q p= 37.29
p+q

40

50

60

φ

3. Empirical Evidences
3.1 Fusing Effects of Indigenous Technology
Development and Market Learning
Table 1 summarizes the comparative estimation
results of technology driven diffusion of Canon
printers by simple logistic model and Bass model.
The results by Bass model are demonstrated
statistically more significant by comparing the
Akaike Information Criteria (AIC).
Table 1 Estimation Results of Technology Driven
Diffusion of Canon PrintersV =120000

LLBP

LBP and BJ(1987-2005)

3.434(-13.14)96482.00-0.0343.471(94.94)(-30.12)(35.70)

LBP and BJ(1987-2005)(19.33)97205.00(166.57)

20000

LBP/BJ

1984
0
0

50

1997

T# =
100

lnq p
= 97.73
p+q
150

200

250

q − ( p + q ) ⋅Tep
1 − e − ( p + q ) ⋅T

1+
FD =

p

300

q

q/ p

LLBP

5.432*10-3

5.822*10-2

10.72

LBP/BJ

1.472*10-3

2.904*10-2

19.73

Fig. 4. Trends in Functionality Development of LLBP
and LBP/BJ.

0.999

Fig. 4 show that the q / p ration in LBP/BJ ishigher that that of LLBP which demonstrates thatfunctionality development in LBP/BJ is muchhigher than LLBP.

3.2

where V : cumulative sales, V : carrying
capacity, T : technology stock, p : innovation
parameter and q : imitator parameter.
pqadj. AIC
V
R2
1581.00

1996

1

V ( 1 − e −( p + q )⋅T )V =q
1 + e −( p + q )⋅Tp

LLBP (19751994)

40000

0.994

(20.64)(21.61)

Actual60000

Fig. 4 demonstrates the trends in functionality
development of LLBP and LBP/BJ respectively.
FD-0.0961

2005

Estimate

80000

T (technology stock)V
1 + e − aT −b1369.10

100000Fig. 3. Technology Driven Diffusion of LBP/BJ (1984-2005).

where V : cumulative sales, V : carrying
capacity, T : technology stock, a : diffusion
velocity and b : coefficients.
adj. R2Vab(1975-1994)

80

Fig. 2. Technology Driven Diffusion of LLBP (1975-1994).
Cumulative sales of LBP and BJ(\ 100 mils. at 1995 fixed prices)

T = B ⋅ PC
where P : relative technology prices of Canon
printers ( P0 means price at initial state); T : printers
technology stock and PC : cumulative PC shipment.

70

Technology stock

5.432*10-3(15.13)5.822*10(9.94)

0.999

6.85

1.472*10-3(2.273)2.904*10(37.96)

0.999

13.85

External Learning for Sustainable
Functionality Development

In order to examine Canon’s sustainable
functionality development with respect to its coretechnology, an empirical analysis focusing on its
printers technology development trajectory over theperiod 1985-2005 is conducted.
The result of the analysis is summarized in Table 2.

46

TTable2external learning from PC producers (Watanabe,2005). However, looking at the Fig. 5 carefully, we
note that the margin for satisfaction requirement has
been
decreasing year by year.
10

Correlation between Technology Stock,
Cumulative PC Shipment and Relative Prices
Canon Printers Technology (1985-2005)

ln P = ln A + α ln( T n PC ) + cD

W(κ2 )

n

ln A

α

c

adj.R 2

DW

AIC

0.1

3.44
(173.21)0.43(53.32)-0.30(-7.06)

0.996

1.79

-48.32

3.34(165.75)0.40(67.66)-0.25(-8.14)

0.997

3.16
(118.98)

0.40(48.36)-0.31(-6.33)

0.994

1986

ln P / P0

ln P / A lnT0 ⎞ κ2⎛
W( κ2 ) = ⎜κ1 − 0
κ2 ⎟e
+
ln B
ln B ⋅ ⎠⎝8

W = κ2

6

0.2

0.3

1.60

1.57

-51.31-42.49

D:200005=1,
others =0.
D:1986,20002005=1,
others=0.
D: 20002004=1,
others =0.

Table 2 suggests that coefficients of the two
factors learning effects in Canon’s printers
technology
overthe
period1985-2005
corresponding to equation (5-13) are:Table 3 Inducement Effect of PC in Printers Technology(1985-2005)(17.20)adj . R 2

0 . 997(-3.22)DW

1 . 00

2

3

4

5

6

> 0

∂ ln TPT

PV ,PTη increase

corresponding to equation (5-12) are1:

Profitsincreaseln B = 8.99 , φ = 0.30 .
Fig. 5 suggests that Canon printers has satisfied
requirementforsustainable
functionality
development which can largely be attributed to its
coopetition strategy thereby utilized the effects of
1

7

can maximize profits by increase in technology
prices and decrease in prices of innovative
products. Fig. 6 illustrates this firm’s strategic
focus in emerging stage.

respectively.
PC’s inducement in Canon’s printers technology

1

Therefore, in emerging stage, firms focus
should increase learning coefficients∂ ln PV(λ = −)as well as technology∂ ln T
elasticity to its prices (η = ∂ ln PT ), thereby they

where Di ( i = 1 ~ 4 ) : dummy variables: ( D1 :1986-1990 = 1, D2 : 1991-1997 = 1, D3 : 19982000 = 1, D4 : 2001-2005 = 1; other years = 0).
T : 10 thousand yen at 1995 fixed prices; andPC : unit.
In addition, P0 and T0 are 7.86 and 14.63,
Table 3 suggests that elasticity and coefficient of0∆PV∆MPT ∆PT
=
−
MPT
PT
PV

lnT = 8.99 + 0.26D1 ln PC + 0.40D2 ln PC + 0.40D3 ln PC + 0.30D4 ln PC− 1.92( D2 + D3 )(14.13)0

Fig. 5. Correlation between κ 2 and W (κ 2 ) in Canon’s Printersκ2
Development Trajectory (1986-2005).

3.3 Implication to Firms Profit

Second, inducement effect of PC in printers
technology is analyzed. The result of the analysis issummarized in Table 3.

(12.77)

2005

2

Based on the above analytical observations, we
can conclude that Canon printers take every effort
to maintain high functionality development level byfusing indigenous R&D investment and market
learning effects.
Firms can sustain their marginal productivity oftechnology (MPT) by increasing their production
prices ( PV ) to the level of technology prices ( PT )asln A = 3.34 , κ 1 = 0.08 and γ = 0.40

(27.63) (10.20)

Canon’s level
γ = 0.44

λ increase

PVT

In order to examine the state in the latest period,
average value over the period 2001-2005 wereanalyzed.

Fig. 6. Firms’ Strategic Focus in Emerging Stage.

47

Fig. 7 illustrates scheme of firm’s profitable
innovation strategy.

References:[1] Ambuj D. Sagar, Bob van der Zwaan,
2006. Technological Innovation in the
Energy Sector: R&D, Deployment, andLearning-by-doing. Energy Policy 34,
2601-2608.

FD

PV PT

η <0
η >0
λ >0

[2] Argote, L., Epple, D., 1990. Learning
Curves in Manufacturing. Science.

PV[3] Arrow, K.J., 1985. Production and Capital.
Collected Papers, Vol. 5. The Belknap
Press of Harvard University Press,
Cambridge, Massachusetts, London.

T
Fig. 7. Scheme of Firms’ Profitable Innovation Strategy.

Canon’s
accomplishmentinsustainable
functionality development by fusing its indigenous
strength based on its technological diversification
strategy and effective utilization of the effects ofexternal learning can be attributed to this strategy.

[4] Brandenburger, A.M., Nalebuff, B.J., 1997.
Co-opetition. Helen Rees Literary Agency,
New York.

4. Conclusions[5] Cohen, W.M. and Levinthal, D.A., 1989.
Innovation and Learning: The Two Facesof R&D. The Economic Journal 99, 569596.

On the basis of the intensive empirical analysis of
growth trajectory of Canon printers focusing on
indigenous technology development and market
learning, the following noteworthy findings wereobtained:(i) Emergence of innovation creates new
functionality and it obsolesces immediately
because imitation and diffusion of technology
in the market.
(ii) Canon printers endeavored to maintain highfunctionality
developmentbyfusingindigenous R&D investment and continual
market learning, which in turn induces further
strengthening indigenous technology.
(iii) This can largely be attributed to its coopetition
strategy primarily with its printers customers,
PC producers.
(iv) Firms’ innovation for option for profit
maximization depends on increase in marginal
productivity of technology through decreasein production prices and increase intechnology price.
(v) Confronting the megacompetition in a
globalizing economy, firms should endeavor
to invent new innovative products with highprice and high functionality.
Future works should focus on the comparative
analysis demonstrating the adaptability of firm
strategy in other industries and countries, fromwhich new suggestions regarding the governing
factors of functionality development as a functionof the institutional system.

[6] Dutton, J.M., Thomas, A., 1984. Treating
Progress Functions as a Managerial
Opportunity. Academy of Management
Revies 9, 235-247.
[7] Klaassen, G., Miketa, A., Larsen, K.,
Sundqvist, T., 2005. The Impact of R&D
on Innovation for Wind Energy inDenmark, Germany and the United
Kingdom. Ecological Economics 54, 227240.
[8] Miketa, A., Schrattenholzer, L., 2004.
Experiments with a Methodology to Model
the Role of R&D Expenditures in Energy
Technology Learning Processes. Energy
Policy 32 (15), 1679-1692.

[9] Nagamtsu,

A., 2001. Functionality
Development as a Source of Innovation in
High-Technology
Industry,
Ph.D.
Dissertation submitted to the Tokyo
Institute of Technology.

[10] Price, D., 1965. Little Science, Big
Science, Columbia University Press, New
York.

48

The Role of Informatization in Inducing Coevolution between Educational
Development, Urbanization and Economic Growth
Xuening Yao**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
430 W9 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANyxuening@ml.me.titech.ac.jp
China’s economic growth has been remarkable since the economic reform started in
1978, which incorporates a transitional process of institutional system. This research
focuses on the result of empirical analysis which demonstrates that informatization plays asignificant role in inducing a virtuous institution, thereby constructing a co-evolutionary
dynamism between the development of education, urbanization and economic growth.
institutional structuredevelopment.
Planning
economy(Strictly prohibited)Move from rural tourban area
Marketeconomy(Permitted and encouraged)

Im pedim ent of the fam ily registry (it isprohibited to m ove from rural to urban area)

1. Introduction
While China has been demonstrating aconspicuous economic growth, it incorporates
institutional fragility. The major source of thisfragility can be attributed to its transitional state ofits long lasting institutional system including
shifting to market economy, rapid industrialization
and urbanization, as well as dramatic reforms of its
educational system.
Chinese government has made every effort in
shifting this fragile institutional system to resilient
one by introducing comprehensive informatization
strategy. Thus, China’s informatization trajectory
can be interpreted to be subject to its institutionalfragility indigenous to its unique triangle structure
between education, urbanization and economic
growth.
Figure 1 demonstrates the dynamism between
urbanization, economic growth, high education anddependency on informatization in China. During theperiod of the planning economy, since move fromrural to urban area was strictly prohibited, rural
people were restrained in rural area with poor
education and low income. While this impedimenthas removed and move from rural to urban area has
been principally encouraged as market economy
emerged. People move to big cities aiming at
getting good education, job opportunities andearning high income. This process of urbanization
contributes to economic growth, again contributes
to improvement of education and a virtuous cycleof institutional structure between economic growth,education and urbanization is formed. It could beassumed that co-evolutionary relationship between
this unique institutional structure and activatedinter-firm technology spillover plays a significant
role in accelerating enhancing functionality of
informatization and resilience of institution in
China. Under such circumstances, dependency on
informatization
constructs
China’suniquewithrespect

No high
education

Restraintin ruralHigh
educationWork inurban area

to

ICT

Low
incomeGainingurban registryHigh
incomePurchasing
PCs

Fig. 1. Dynamism between Urbanization, Economic
growth, High Education and Dependency on
Informatization in China.

2. Cyclical Dynamism between GDP per Capita,
Education and Urbanization
2.1 Structure of Cyclical Dynamism
Figure 2 demonstrates the cyclical dynamism
structure between GDP per capita, education andurbanization. α, ß, γ represent the elasticity between
triangle institutional factors respectively, MIVEU(Mutual Interdependency between GDP per capita,
Education and Urbanization: αβγ) represents
productivity of the cyclical structure and entropy (ε)
represents resilience of the cyclical structure. The
computing methods of elasticities, MIVEU andentropy are given in following content.
(1) Cyclical structure –Elasticity (α, β, γ)γGDP per
capita (V)αUrbanization

EducationβFig. 2. Cyclical Dynamism Structure between GDP per capita,
Education and Urbanization.

49

(2) Productivity of the cyclical structurelnE = lnA + αlnV-1
lnU = lnB + ßlnE-1
lnV = lnC + γlnU-1

lnV = lnC + γlnU-1
3
2.5
2∂ ln E∂ ln U∂ ln V
, β =
, γ =
α =
∂ ln V −1∂ ln E −1∂ ln U −1

1.5

γ(t) = -0.049t + 0.026t2 – 0.004t3 + 0.0003t4 – 8.8E-06t5 + 1.12E07t6(-2.29) (3.99)(-4.31)(4.48)(-4.57)(4.59)
adj. R2 0.995

0
1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

-0.5

Fig. 5. Trend in Elasticity of U to V in China (1979-2003).
Sources: Statistics Yearbook of China (1979-2004).

1∑ P ln P
jt

j =1

Based on elasticities further computeproductivity and entropy as demonstrated in figure
6 and 7. Figures indicate: (i) Productivity continues
to increase. (ii) However, entropy stagnates andindicates a trend in slight decrease from 2000 which
demonstrates a slight fragile trend of institutional
structure in China. (iii) These demonstrate thetrade-off between productivity and resilience.

jt

Here, j represents V, E and U, t represents timeseries,αβγ, ∑ Pjt = 1
Pjt =
, 
, 
α + β +γ

i

i

i =0

0.5

(3) Resilience of the cyclical structure – Entropy
Entropy (ε) =

n

∑c t

1

∂ ln E ∂ ln U ∂ ln V⋅⋅
MIVEU = αßγ =∂ ln V−1 ∂ ln E−1 ∂ ln U −13γ=

α + β +γα + β +γ

2.2 Empirical Analysis
Using national level time series data over theperiod 1978-2003, assuming α, ß, γ as function oftime t, given 1978 = 0, we make regression analysis
to identify elasticities (α, ß, γ) as demonstrated infigure 3-5. The trends of elasticities indicate that α,ß and γ are all positive except a very short time at
the beginning of trend of ß. That indicates there is avirtuous cycle between GDP per capita, education
and urbanization. Economic growth contributes thedevelopment of education which further contributes
to urbanization, and urbanization promotes
economic growth which again accelerates thedevelopment of education. This co-evolution
mechanism between GDP per capita, education andurbanization have become the chief characteristic of
institution in China.
lnE = lnA + αlnV-1

n

α=

∑a t

1.2
1
0.8

α β γ 0.6
0.4
0.2
0
1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

Fig. 6. Trend in Mutual Interdependency between GDP per
capita, Education and Urbanization (1979-2003).
Sources: Statistics Yearbook of China (1979-2004).
3
2.5
2

ε

1.5
1

i

i

0.5

i =0

0
1979

1.7

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

-0.5

1.65

2

3

2

α(t) = 1.642 - 0.002t + 6.11E-05t(10.67) (-8.25)(10.06)

1.6
1.55

adj. R 0.995

Fig. 7. Trend in Entropy between GDP per capita, Educationand Urbanization (1985-2003).
Sources: Statistics Yearbook of China (1979-2004).

1.5
1.45
1.4

3. Informatization Trajectory - Measurement ofInformatization Index over the period of 19842003

1.35
1.3
1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

Fig. 3. Trend in Elasticity of V to E in China (1979-2003).
Sources: Statistics Yearbook of China (1979-2004).

3.1 Explanation of Information Index
Informatization index is a weighted averageindex (demonstrated as function (1)) of six factors:(i) Exploiting and using of information resources;(ii) Building of information net; (iii) Application of
information technology; (iv) Information products
andservice;(v)
Humanresourcesofinformatization;(vi)
Developmentof
informatization environment. Weights are identified
by Delphi Method. Figure 8 demonstrates thenational informatization index of China (19952000), it was measured by China Informatization
Evaluation Center in 2002 year.

n

β = ∑ bi t ilnU = lnB + ßlnE-1

i=0

0.9
0.8
0.7
0.6
0.5

β (t) = -0.111 + 0.008t1 + 0.004t2 – 0.0005t3 + 2.66E-05t4 – 4.5E-07t5(-3.31)adj. R2 0.999(1.87)(3.86)(-6.02)(7.32)(-8.16)

0.4
0.3
0.2
0.1
0
-0.1 1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

-0.2

Fig. 4. Trend in Elasticity of E to U in China (1979-2003).
Sources: Statistics Yearbook of China (1979-2004).

50

6I = ∑ wi X i = 15% X1 + 16% X2 + 18% X3 + 15% X4
i =1+ 20% X5 + 16% X6

3.3 Increase Time Trend EffectUsing equation (4) and increase time trend
effect, function (5) can be obtained.
ln It = A + 0.210ln Vt + 0.189ln Et + 0.443ln Ut + λt
(5)
(t: 1984 = 1)
Using following equations to identify A and λ,ln I (1995) = ln I1995
Primary national level index
ln I (2000) = ln I2000
Based on above computing, we can get A = 0.205, λ = 0.133, so the final time trend
informatization function is function (6), and Figure
10 demonstrates this estimated time trend fits withthe primary trend very well.
ln It = -0.205 + 0.210ln Vt + 0.189ln Et + 0.443ln Ut+
0.133t(6)(1)

50
Informatization index

40
30
20
10
0
1995

1996

1997

1998

1999

2000

Fig. 8. National Informatization Index of China (1995-2000).
Sources: NIEC, http://niec.org.cn/index.htm.

3.2 Regional Identify and Cross Regional
Regression Analysis of 31 Regions
Using regional informatization index of 31
regions by regression analysis we try to get crossdata function I = I (V, E, U). Regional characteristic
is identified firstly as figure 9 that indicates Beijing
and Shanxi are conspicuous by using average dataof 1998-2000. Then regression analysis is made asfunction (2) by taking coefficient dummy variable(Beijin, Shanxi = 1, others = 0). Based on function(2), taking weight of regional GDP per capita tocompute synchronic elasticity of V to I as function
6(3), thecross data function can be obtained as
wifinalXi∑function
(4).
i =1

80

Informatization Index

70

I
20
0

10000

15000

20000

25000

30000

V

ln I = 1.499 + 0.251Dln V + 0.207(1-D)ln V + 0.189ln E + 0.443ln U(2.08)(1.83)(1.35)

D: dummy variables, Beijing, Shanxi = 1, otherregions = 0
Synchronic elasticity∑ D ln V∑ D ln V31= 0.251 * r = 131+ 0.207 *ln V r
∑
∑
(3)
r =1
r =1
31

r

1992

1994

1996

lnV = lnA + η1 lnV
lnU = lnB + η2 lnE-1
lnV = lnC + η3 lnU-1

(2)

r

1990

1998

2000

2002

(2.51)

adj. R2 0.851

31

1988

4.1 Dynamism Structure
Figure 11 demonstrates the dynamism
structure between informatization and VEU, η1, η2,
η3 are elasticity of informatization to V, E, U
respectively, the computing method of elasticity is
as following equations:Fig. 9. Regional Identify by Average Data of 1998-2000.
Sources: Statistics Yearbook of China (1979-2004), NIEC,
http://niec.org.cn/index.htm.

(1.45)

1986

4. Analysis of the Influence of Informatization to
VEU
In this part, we will analyze the influence of
informatization to VEU in national level by using
estimated time trend informatization index. We also
use productivity and entropy to indicate the fragile
or resilient characteristic of institutional structure.

40

5000

20

Fig. 10. Time Trend of National informatization Index (19842003).
Sources: Statistics Yearbook of China (1979-2004), NIEC,
http://niec.org.cn/index.htm.

60

0

30

1984

Beijing

Shanxi

40

0

120

80

Estimated Index
Primary Index

50

10

140

100

60

η1 =

∂ ln V∂ ln I

∂V
∂I

⋅

η2 =

∂ ln E∂E=∂ ln I∂I⋅∂ ln U∂U=η3 =∂ ln I∂I

I⋅
U= 0.210ln V rr =1

D: dummy variables, Beijing, Shanxi = 1, otherregions = 0
ln I = 1.499 + 0.210ln V + 0.189ln E + 0.443ln U
(4)

=

I
V

GDP per
capita (V)Urbanizat
ion (U)η1
Informatiza
tion (I)η2
Education (E)I
E

Figure 11. Dynamism Structure
betweenInformatization and
VEU.

4.2 Elasticity of Informatization to GDP per

51

Capita, Education and Urbanization
Using model of logistic growth with a dynamic
carrying capacity (demonstrated as following) tocompute elasticity η1, η2, η3, Figures 12-14
demonstrate the results.
Kk
N (I ) =b ⋅ ak
1 + a exp(−bI ) +exp(−bk I )b − bk∂N ( I )N (I )= aN ( I ) ∗ (1 −)∂I
K (I )

consequence of the divergence trend in the third
period, productivity change to slight decrease in theend of the third period.
0.08
0.07
0.06

(6)

0.05
0.04
0.03
0.02

∂K ( I )K (I ))= a k K ( I ) ∗ (1 −
∂I
Kk

0.01
0
1984

0.6

η1

1986

1988

1990

1992

1994

1996

1998

2000

2002

Fig. 15. Trend in Productivity of Informatization to VEU (19842003).
Sources: Statistics Yearbook of China (1979-2004), NIEC,
http://niec.org.cn/index.htm.

0.5
0.4
0.3
0.2

1.1

0.1

1.05
0
1984

1986

1988

1990

1992

1994

1996

1998

2000

1

2002

0.95

Fig. 12. Trend in Elasticity of I to V (1984-2003).
Sources: Statistics Yearbook of China (1979-2004), NIEC,
http://niec.org.cn/index.htm.

0.9
0.85
0.8
0.75
0.7
ε
0.65
0.6

1.2

1984

η2 0.80.6
0.4
0.2
0
1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

0 .2

0 .1 50 .1

0 .0 5

0
1986

1988

1990

1992

1994

1996

1998

2000

1990

1992

1994

1996

1998

2000

2002

analysis,

following(i) China has been demonstrating aconspicuous economic growth. (ii) This can be
attributed to its unique institutional structure
characterized by a co-evolution relationshipbetween economic growth, development ofeducation and urbanization. (iii) Advancementof informatization accelerates the economic
growth. (iv) The contributing effect of
informatization to VEU balances thedevelopment of triangle factors, slows down
the fragile trend of institution to keep it not so
convergence, though V.E.U developmentchanged to slight fragile structure from 2000.

0 .2 51984

1988

5. Conclusions
Based on foregoingconclusion can be obtained:

Fig. 13. Trend in Elasticity of I to E (1984-2003).
Sources: Statistics Yearbook of China (1979-2004), NIEC,
http://niec.org.cn/index.htm.
η3

1986

Fig. 16. Trend in Entropy of Informatization to VEU (19842003).
Sources: Statistics Yearbook of China (1979-2004), NIEC,
http://niec.org.cn/index.htm.

1

2002

Fig. 14. Trend in Elasticity of I to U (1984-2003).
Sources: Statistics Yearbook of China (1979-2004), NIEC,
http://niec.org.cn/index.htm.

From η1, η2, η3 following implication can beobtained: (i) Informatization elasticity to V
continued to increase consistently by 1993. (ii) On
the basis of the learning exercise in the later half ofthe 1990s, the effect of Inf. incorporated in V. from2000. (iii) Influence of Inf. to urbanization
dramatically increased from the middle to the later
half of the 1990s. (iv) Advancement of Inf.
stimulated education. (v) Due to decrease inmotivation to move to urban area in the 2000s,
influence of Inf. to education decreased.

References[1] R. Kondo, C. Watanabe, 2003. The Virtuous
Cycle between Institutional Elasticity, IT
Advancement and Sustainable Growth: Can
Japan Survive in an Information Society?
Technology in Society 25 (3) 319-335.
[2] C. Watanabe, M. Kishioka, C. A. Carvajal, 2004.
IT Substitution for Energy Leads to a Resilient
Structure for a Survival Strategy of Japan’s
Electric Power Industry, Energy Policy 33 (8)1069-1084.
[3] C. Watanabe, R. Kondo, N. Ouchi, H. Wei, C.
Griffy-Brown, 2004. Institutional Elasticity as a
Significant Driver of IT Functionality
Development, Technological Forecasting andSocial Change 71 (6) 723-750.

4. 3 Productivity and Entropy
Further compute productivity and entropy
demonstrated as figure 15 and 16, and following
implication can be obtained: (i) Productivity
generally continued to increase. (ii) Due todifferences of the magnitude of impacts ofInformatization on V.E.U depending on three
periods, entropy changed from diversity toconvergence and again slight diversity. (iii) As a52

Sustainable Economic Development with Inter-regional
Heterogeneity in China
Xuening Yao**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
W9-430, 2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
yao.x.aa@m.titech.ac.jp

Per capita annual ne t in come (yuaChina has been demonstrating a conspicuous economic growth, which can be
attributed to its unique transitional institution structure comparing with other countries.
Taking China’s economic development in each respective 31 regions over the last two
decades, this research focuses on the result of empirical analysis which indicates that
China’s nationwide economic development has shifted from an inter-regional homogeneity
to an inter-regional heterogeneity to welcome the global shift from industry society to
information society since 1990s.

1. Introduction
China has been demonstrating an economic
miracle as one of the rapidest economic growthcountries in the world since its economic reformfrom 1978. Figure 1 indicates the economic growthtrend of China by using index of GDP per capita.
The average economic increase rate was more than
9% in the last two decades in China.

Rural households
Urban households

600.0

500.0

400.0

300.0

200.0

100.0

0.0
1978

1980

1985

1989

1990 1991

1992

1993

1994

1995 1996

1997

1998

1999 2000

2001

2002

2003

2004

Fig. 2. Increase trend of per capita annual
income (1978-2004).
Sources: Statistics Yearbook of China (1979-2005).

800
700
600
500
400

80.0

300

70.0

Rural households

200

60.0

Urban households

En gle c o e f f ic ie n t ( %G DP pe r c apita (1 9 7 8 = 1

700.0

100

19
7
19 8
7
19 9
8
19 0
8
19 1
8
19 2
8
19 3
8
19 4
8
19 5
8
19 6
8
19 7
8
19 8
89
19
9
19 0
9
19 1
9
19 2
93
19
9
19 4
9
19 5
9
19 6
9
19 7
9
19 8
9
20 9
0
20 0
0
20 1
0
20 2
0
20 3
04

0

Fig. 1. Increase trend of GDP per capita in
China. (1978-2004).
Sources: Statistics Yearbook of China (19792005).

50.0
40.0
30.0
20.0
10.0
0.0
1978 1980

1985 1989

1990 1991

1992 1993

1994 1995 1996

1997 1998

1999 2000

2001 2002

2003 2004

Fig. 3. Decrease trend of Engle coefficient (19782004).
Sources: Statistics Yearbook of China (1979-2005).

Companioning with the conspicuous economic
growth, per capita annual income increased morethan 5 times both in urban households and in rural
households since 1978 (shown as Figure 2).
Meanwhile the Engle coefficient of rural
households decreased from 67.7% in 1978 to 47.2%
in 2004, and that of urban households decreased
from 57.5% in 1978 to 37.7% in 2004 (shown as
Figure 3). This demonstrates that the living level ofChinese people has been improved greatly.

Beginning from the economic reform, many
aspects of Chinese institution has been changed andstill in changing such as culture and value
dimension, social and political condition, economic
policy, education and enterprises, which has comeinto been the institutional factor and reason tofurther stimulate economic growth. So there is a coevolutional mechanism between institutionalinnovation and economic growth in China. The
main aspects of transitional characteristic of53

institution in China are illustrated in Figure 4.

Cultureand value
dimension

Agriculture country
Social and Very poor
political
Centralist government
condition
politics
Unstable
Heavy andmilitary industry priory
Planning economy
Average income

After 1978
Open to all the world
Learn from developed countries
Strong economy faithWork for self-fulfillment
Heterogeneity
Weak moral sense

Nicer basis of industry Large population
Large market
Stable politics
Low cost of humanMore democratic
resources

Economic
policyHeavy and military industry priory
Planning economy
Average income

Satisfying people’ demand priory
Market economy
Gradient effect
Income according to work

Education

Essence higher education
Specialized college
Ignore education-Great Cultural Revolution
Connect state only

Universal higher education
Comprehensive university
Rely on science and education to rejuvenate
nationConnect more with enterprises

State economy and collective economy
Centralist management
Obey government (plan production and sale)- No competition- Carelessness of interest- Carelessness of market and demand- Carelessness of technology innovation
Lifetime employment system

Multi-economy
Modern enterprise institution- Decide by enterprise itself- High competition- Careness of interest- Careness of market and demand- Careness of technology innovation
Employer and employee choice

Enterprises

60000
50000
GDP per capita (yuan, 2004)

Before 1978
Close to west countries
Learn from Socialist countries and dependon itself
Communist faithWork for state
Homogeneity
Strong moral sense

demonstrates that China’s nationwide economic
development had gone in a homogeneity way
towards minimizing the gap between backward andleading regions after economic reform in 1980s, andthis trend changed to heterogeneity way towards
widening the gap between backward and leading
regions when industry society has shifted
information society globally since 1990s.
The dramatic imbalance of economic
development between 31 regions is indicated by
Figure 6, it can be seen that the leading regions are
far developed more than the backward regions.
Taking an extreme example, the GDP per capita ofthe top region, Shanghai, is more than 13 times ofthat of the most backward region – Guizhou in 2004.

40000
30000
20000
10000
0
Shanhai
Beijing
TianjinZhejiang
Jiangsu
GuandoFujianShandoLiaoning
Heilongji
Hebei
NeimonXinjiang
Jilin
Hubei
Chongqi
Henan
HainanShanxi1
Hunan
Qinghai
Jiangxi
SichuanNingxia
XizangAnhui
Shanxi2
Guangxi
YunnanGansu
Guizhou

Fig. 4. Transitional Characteristic of Institution in China.

2. Increasing Productivity by Inter-regional

Fig. 6 GDP per capita by regions in China (2004).
Sources: Statistics Yearbook of China (2005).

Heterogeneity

On the other hand, with the great nationwide
increase of anural income and people’s living level,
the regional disparity of income and living levelalso increased in the last two decades in China. The
Gini index of China increased from 23.4% in 1978
to 44.7% in 2004, which makes China changed
from one of the most balance income countries to
one of the most imbalance income countries. The
Gini index of 40 countries is demonstrated in
Figure 7, which indicates that China ranked
number 6 in the 40 countries, following Brazil,
Malaysia, Mexico, Philippines and Russia, this also
indicates a heterogeneity trend of economic
development in China from a view of income
besides GDP per capita.

As same as the dramatic economic growth of
the whole nation, there has been a rapid economic
development in each respective 31 regions of thewhole country. But the economic increasing
situations are very heterogeneous with deferent
regions. Generally, the economy of east area
increased quickly, on the other hand, the west area
has been following behind, and the middle area isbetween them.
GDP per capita (yuan)

60000
2004
1999
1994
1989
1984
1978

50000
40000
30000
20000

70.0

10000

60.0

0

Leading regions

Backward regions

40.0
30.0
20.0
10.0
0.0

5.

Increasing Productivity by Inter-regional
Heterogeneity.
Sources: Statistics Yearbook of China (1979-2005).

B
Ma razlilays
M ia
Ph exic
ilip o
pin
Ru es
ssia
Ch
ni a
Tu
Th rkeyaila
Sin ndgap
Po ore
rtu
Pogal
lan
d
US
Au A
stri
a
Ita
Gre lyInd eceones
Ice iala
Ne Taiwnd
wZ an
eala
nd
U
Sp K
ain
Ind
Ire ialan
Ko dre
Lu Jap axe an
mboAu urgstra
Ca lian
Ge adarman
F y
Hu ranc
Sw ngar e
itz y
erla
No nd
rw
Fin aylan
Slo dva
Ne Cze k
the chrla
Be ndsgl
De iumnm
Sw arked
enFig.

Gini index

Shanghai
Beijing
TianjinZhejiang
JiangsuGuangdonFujianShandong
Liaoning
Heilongjia
Hebei
Neimongg
Xinjiang
Jilin
Hubei
HainanChongqing
Henan
Shanxi1
Hunan
Qinghai
Jiangxi
SichuanNingxia
XizangAnhui
Shanxi2
Guangxi
YunnanGansu
Guizhou

50.0

Fig. 7. Gini Index of 40 Countries in 2004.
Sources: World Development Report 2005.

Figure 5 indicates the increasing productivity
by inter-regional heterogeneity since 1978. It

54

continued to 1990 with continuous production
increase which was a typical structure during thecourse of an industrial society. Such a trend shiftedto heterogeneity from the beginning of the 1990
which contributed to a more dramatic productivity
increase. This shift corresponds to the requirement
in a global information society.

3. Shift from Inter-regional Homogeneity to
Heterogeneity in an information society
3.1 Measurement of Heterogeneity by Entropy
Using entropy to measure homogeneity andheterogeneity, the significance of entropy is as
Table 1. The computing method of entropy is asfollowing.

3.32

n

1
ε = ∑ P j ln
Pj
j=1
j

3.26

, and ∑ Pj = 1 , 0<ε<lnn.

n∑X

Entropy

Xj

where P =

3.3
3.28

3.18
3.16

Table 1 Homogeneity and Heterogeneity by Entropy

Pj

1(maximum)

1/n(minimum)ε0(minimum)Lnn(maximum)

Monopoly
Convergence
Heterogeneity

Competitive
Divergence
Homogeneity

3.14
0

Fig.

3.289

Entropy

3.247

3.276

3.262

3.259
3.237

3.227

3.2
3.182
3.15

3.155

homogeneity

heterogeneity

3.1

1980

1984

1985

1989

1990

1992

1994

1995

1999

400

500

600

700

800

9.

4. Institutional Analysis by Structure of VEU
Observing the whole Chinese transitional
institution, the main economic and social
development in China is characterized byconspicuous economic growth, rapid urbanizationand development of education.
Given that a shift from an industrial society to
an information society emerged in the beginning of
1990s, the shift from an inter-regional homogeneity
to an inter-regional heterogeneity in China
responded the requirement of information society
very well, which contributed the sustainableeconomic growth in China. This can be attributed to

3.05
1978

300

3.3 Homogeneity and Heterogeneity in a
Paradigm Change
Foregoing analysis demonstrated that there is aparadigm
changefromhomogeneitytoheterogeneity. It indicates that China had been in aninter-regional homogeneity in 1980s characterized
by divergence and competition which contributed to
productivity increase responding to industrial
society.
Chinashiftedtointer-regional
heterogeneity in 1990s characterized by monopoly
and convergence which contributed to functionality
increase responding to information society.
Comparing with lower economic growth in 1980s,
China demonstrated sustainable rapid economic
growth since 1990s with respect of inter-regional
heterogeneity trend. Surely, shift from an interregional homogeneity to an inter-regional
heterogeneity is essential in an information society.
On the other hand, the discrepancy and social
stability has become a crucial problem needed
careful resolve in the near future.

3.297

3.251

200

Correlation between Entropy andproductivity. (1978-2004).
Sources: Statistics Yearbook of China (19792005).

3.35
3.3

100

Productivity

3.2 Entropy Trend in China from 1978 to 2004
Based on computing method of entropy, using
regional data of GDP per capita from 1978 to 2004,
the entropy trend in China is shown in figure 8. It
demonstrates that entropy in China increased from
3.155 in 1978 to the highest 3.297 in 1990 and thendecreased to 3.227 in 2004 since 1990s. So it is
clear
that
China’snationwide
economicdevelopment has shifted from an inter-regional
homogeneity to an inter-regional heterogeneity towelcome the global shift from industry society to
information society since the beginning of 1990s.

3.25

3.22
3.2

j

j =1

Social andeconomicsignificance

3.24

2004

Fig. 8. Trend of Entropy in China (1978-2004).
Sources: Statistics Yearbook of China (1979-2005).

Following the observation in Figure 1 withrespect to correlation between inter-regional
homogeneity/ heterogeneity, and by measuring
entropy nationwide productivity trend, Figure 9
demonstrates the correlation between them over theperiod 1978-2004. Figure 9 clearly demonstrates
this correlation indicating that homogeneity trend55

its unique institutional structure characterized by
V.E.U structure. The empirical analysis of the
dynamism structure between GDP per capita,
education and urbanization will be demonstrated asfollowing.
4.1 Structure of Cyclical Dynamism
Figure 10 demonstrates the cyclical dynamism
structure between GDP per capita, education andurbanization. α, ß, γ represent the elasticity between
triangle institutional factors respectively.

Sources: Statistics Yearbook of China (1979-2004).

(3) Elasticity of urbanization to GDP per capita
32.5

γ(t)= -0.049t + 0.026t2 –2+ 0.0003t4 –0.004t3

8.8E-06t5 + 1.12E-07t6

1.5
1
0.5
0
1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

-0.5

GDP per
capita (V)Fig. 13. Trend in Elasticity of U to V in China (1979-2003).

Sources: Statistics Yearbook of China (1979-2004).

γ

4.3 Implications of Empirical Analysis(ⅰ) Elasticities of α, ß, γ are all positive andsignificant. ( ⅱ ) Except elasticity of α had adecrease trend before the end of 1990s, the trendsof ß and γ continuously increased, which
demonstrates a growing stronger contributing effectbetween VEU structure. (iii) These demonstrate a
co-evolutionary dynamism between GDP per capita,
education and urbanization.

αUrbanization (U)Education (E)βFig. 10. Cyclical Dynamism Structure between GDP
per capita, Education and Urbanization.

Elasticities of α, ß, γ are subjected to following
models:lnE = lnA + αlnV-1
lnU = lnB + ßlnE-1
lnV = lnC + γlnU-1
α =5. Conclusions
Based on foregoing analysis, we can conclude
that: (i) China has been demonstrating aconspicuous economic growth; (ii) China’s
nationwide economic development has shifted froman inter-regional homogeneity to an inter-regional
heterogeneity responding to information society
since 1990s; (iii) The unique institutional structure
characterized by VEU structure formed a virtuous
cycle; and (ⅳ) The virtuous relationship between
this unique institutional structure plays a significant
role in accelerating heterogeneity trend andenhancing functionality of information society, on
the other hand, the heterogeneity economic
development contributes to enhancing institutional
virtuous cycle.

∂ ln E∂ ln U∂ ln V, β =, γ =∂ ln V −1∂ ln E −1∂ ln U −1

4.2 Empirical Analysis
Using national level time series data 19782003, assuming α, ß, γ as function of time t, given
1978 = 0, The elasticities can be obtained bymaking regression analysis as follows.
(1) Elasticity of GDP per capita to education
1.7
1.65
1.6

α(t) = 1.642 - 0.002t2 + 6.11E-05t3

1.55
1.5

References[1] R. Kondo and C. Watanabe, 2003. The Virtuous
Cycle between Institutional Elasticity, IT
Advancement and Sustainable Growth: Can
Japan Survive in an Information Society?
Technology in Society 25 (3) 319-335.
[2] C. Watanabe, B. Asgari and A. Nagamatsu,
2003. Virtuous Cycle between R&D
Functionality Development and Assimilation
Capacity for Competitive Strategy in Japan’s
High-Technology Industry. Technovation 23(11) 847-904.
[3] China Statistics Press, 1979-2005. Annual
Statistics Book of China.

1.45
1.4
1.35
1.3

1979
1983
1987
1989
1997
1999
2001
2003
Fig.
12.1981
Trend
in1985Elasticity
of 1991
V to 1993
E in1995
China(1979-2003).
Fig. 11. Trend in Elasticity of V to E in China (1979-2003).

Sources: Statistics Yearbook of China (1979-2004).

(2) Elasticity of education to urbanization
0.9
0.8
0.7
0.6
0.5
0.4

β (t) = -0.111 + 0.008t1 + 0.004t2 –0.0005t3 + 2.66E-05t4 –4.5E-07t5

0.3
0.2
0.1
0
-0.1 1979

1981

1983

1985

1987

1989

1991

1993

1995

1997

1999

2001

2003

[4] World Development Report 2005.

-0.2

Fig. 12. Trend in Elasticity of E to U in China (1979-2003).

56

Co-evolutionary Dynamism between Innovation and Institutional
Systems in the BRICs
Xuening Yao*
Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-430 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
yao.x.aai@m.titech.ac.jp
Contrary to the relative stagnation of economic growth in industrialized countries with matureeconomies, the so-called BRIC countries have shown conspicuous economic growth in the early
2000s.
However, as the development trajectories for industrialized countries suggest, sustainable
development in BRICs requires innovation for effective utilization of potential resources. This paper
focus on the impirical analysis of co-evolutionary dynamism between innovation and institutional
systems in 40 countries, and the BRICs are centered. The comparison between BRICs aredemostrated and sustainability of BRICs economic growth is subject to such co-evolution.
1. Introduction
It is well known that the BRICs, consisting ofBrazil, Russia, India and China are the four largest
developing countries with the most prospective
economic growth in the next generation in the world.
The BRICs generated 27% of the world GDP (PPP) in2005 by sharing 28.9% of land space and 43.2% of
population. The huge potential of BRICs economic
growth can be attributed to their advantages of affluent
natural resources and land, together with a large andcheap labor market as well as high density of foreign
direct investment.
However, as the development trajectories forindustrializedcountries
suggest,sustainable
development in BRICs requires innovation for
effective utilization of potential resources. Given theco-evolutionary dynamism between innovation andinstitutional systems is decisive to innovation driven
economy, sustainability of BRICs economic growth issubject to such co-evolution.

X = X ( PCx1 , PCx 2 , PCx3 , L , PCx n )Y = Y ( PCy1 , PCy 2 , PCy 3 , L , PCy n ) (2)Z = Z ( PCz1 , PCz 2 , PCz 3 , L, PCz n )where PCxi, PCyi, and PCzi (i = 1~n) are
principle components of three dimensions,
respectively.
Figure 1 demonstrates the constitution of themain Principle Components (PCs) of each respective
three dimensions with major proxies demonstrating thesignificant loading of variables.
1. National strategy and socio-economic system (NSE)
1) PC11 Quality of traditional development base1) PC31 Productivity seeking nationality(Life expectancy at birth(Productivity in services(Productivity in industries(Justice(Protectionism(Population over 65 years(Gini index(Market environment ICT(Urban population

2) PC32 Elasticity of heterogeneous nations(Efficiency of legal framework(Overall infrastructure quality(Quality of the educational system(Risk of political instability(GDP PPP per capita(Total expenditure on R&D

2) PC12 Manufacturing oriented socio-economic system(Need for economic and social reforms(Skilled labor3) PC13 Commodity trade dependency( Trade to GDP ratio( National culture3) PC33 Brain resources supply potential( Well distributed population

2. Analytical Framework
2.1 Constitution of institutional systems
Institutional systems (IS) are constituted of thefollowing three dimensions (Watanabe, 2004):

3. Historical perspectives (HPV)

2. Entrepreneurial organization and culture (EOC)
1) PC21 High qualified managerial system(Extent of staff training(Ethical behavior of firms(Reliance on professional management(Degree of customer orientation(Capacity for innovation(Extent of marketing(Efficacy of corporate boards(Nature of competitive advantage(Small and medium-size enterprises2) PC22 Liquidity of work force(Ease of hiring foreign labor(Hiring and firing practices

Fig. 1. Structure of Institutional Systems in 40 Countries (2004).

(i)
(ii)
(iii)

National strategy and socio-economic system,
Entrepreneurial organization and culture, andHistorical perspectives.
Therefore, institutional systems (IS) can be depictedby the following equation:
IS = F (X, Y, Z)(1)
where X, Y, Z: three dimensions of institutional
systems; and X = X (X1, X2, …, Xn), Y = Y (Y1, Y2, …,Yn), Z = Z (Z1, Z2, …, Zn) with major components Xi, Yi,
and Zi (i = 1~n).
Using Principle Component Analysis (PCA) for
the three dimensions respectively, institutional systems
can be depicted by means of the governing Principle
Components (PCs) as follows:

2.2

Measurement of co-evolutionary dynamism
between innovation and institutional systems
In light of the significance of the co-evolutionary
dynamism between innovation and institutional
systems, principal components regression analysis isconducted to identify the correlation between
innovation and PCs of the institutional systems in 40
countries (BRICs, OECD, 6 Asian newly
industrializing and developing countries) by taking
MT, ICT and software (SW) for innovation as follows.
Characteristics of co-evolutionary dynamism in BRICs
are highlighted by comparison with Japan and USA.

57

MT = F ( PCαβ , ICT , SW )(3)
ICT = F ( PCαβ , MT , SW )(4)
SW = F ( PCαβ MT , ICT )(5)
where PCαβ : governing principal components ofinstitutional systems; α: three dimensions ofinstitutional systems, α = x, y, z; and β: number ofprincipal components in three dimensions, β = 1~n.

(1.05)(4.61)SW)PC21-0.082ICTPC22+(-0.157-0.125ICT-3.778SW)PC32(-2.46)(-4.41) (-2.35)(-1.29)

4.96

-0.16

0.11

-0.46

0.02

-0.62

China

2.91

4.96

-0.24

0.04

-1.36

-0.01

-0.48

Japan

6.44

4.96

0.26

0.11

0.51

0.13

0.47

USA

6.11

4.96

0.24

-0.03

1.22

-0.06

-0.22

Nature of competitive advantage

MT = 4.960+(0.480-3.587SW)PC11+(0.200ICT+2.630SW)PC12+(0.620+2.138(4.71)

3.85

Table 1 demonstrates clear contrast between
BRICs and Japan/USA with respect to negative or
positive impacts of PC21 and PC11 on their MT
developments. While these institutional factors
induced MT in Japan and USA, they impeded MT
advancement in the BRICs.
In light of the significant contrasting negative
impacts of PC21 and PC11 on MT in the BRICs,
Figures 2 and 3 analyze the constitutions of PC21 andPC11 in the four BRIC countries by comparing scoresof 12 and 9 variables constituting these components,
respectively.
Figure 2 suggests that India and Brazil
developed better than China and Russia in PC21, andthe factors of efficacy of corporate boards, degree ofcustomer orientation, large corporations reliance on
professional management and extent of staff training
are the weakest factors in China, this urges it strong
enhancement. On the other hand, factors of capacity
for innovation, extent of marketing, nature ofcompetitive advantage, ethical behavior of firms, small
and medium-size enterprises, extent of staff training
and reliance on professional management are
extremely weak in Russia requiring it urgent
development.

3. Empirical Analysis of Co-evolution between
Innovation and Institutional systems
Aiming at examining the co-evolutionary
dynamism between institutional systems andinnovation, on the basis of equations (3)-(5), principal
components regressions between the principal
components of institutional systems and MT, ICT aswell as software between 40 countries in 2004 areconducted. MT, ICT and software are represented by
Production Process Sophistication (WEF, 2005),
Network Readiness Index (WEF, 2005), and Potentialof Software Development (SCI, 2005, IMD, 2005),
respectively. The Potential of Software Development
is computed by utilizing the ratio of the number ofpublications concerning software and GDP PPP per
capita.
3.1 Manufacturing technology (MT)Aiming at identifying the significant impacts ofinstitutional factors on MT, on the basis of equation(3), cross-country multi-regression analysis isconducted. Using Backward Eliminating Method(BEM) with 5% significant level criteria1, the principal
components that have significant influences on MT are
identified as follows:(148.31) (3.66) (-3.26)

India

Efficacy of corporate boards

0.6

Extent of marketing

0.4(2.82)

BrazilChina
India
Russia0.2

Ethical behavior of firms
2adj. R 0.967(6)
The regression result is statistically significant,and indicates that ICT, software and institutional
factors contribute to the development of MT. In
addition, quality of traditional development base
(PC11), manufacturing oriented socio-economic
system (PC12), high qualified managerial system(PC21), liquidity of work force (PC22) and elasticity ofheterogeneous nations (PC32) are significant governing
institutional factors to the development of MT in the
40 countries examined. Contributions of these factors
to MT in BRICs are summarized in Table 1. Japanand USA have been included for comparison.

PPS

Const.

PC11

PC12

PC21

PC22

PC32

4.23

4.96

-0.59

0.00

-0.50

0.01

0.35

Russia

3.17

4.96

-0.65

-0.04

-1.17

0.00

0.07

Capacity for innovation-0.4

Degree of customer orientation-0.6

Ease of hiring foreign labor

Small and medium-size
enterprises

Hiring and firing practices

Reliance on professional management

Extent of staff training
Large corporations

Fig. 2. Contribution of High Qualified Managerial System (PC21) in BRICs (2004).

Similarly, Figure 3 suggests that China developed
better than other three BRICs countries in quality of
traditional development base (PC11). However, thefactors of skilled labor, GDP per capita and quality ofthe educational system require further development.
India is required to improve its balance between
factors by enhancing total expenditure on R&D, trade
to GDP ratio, GDP per capita, as well as overall
infrastructure quality. Factors of risk of politicalinstability and need for economic and social reforms
are extremely weak in Russia, requiring it urgent
improvement. Brazil should pay attention on
reinforcing quality of the educational system andoverall infrastructure quality.

Table 1 Contribution of Institutional Factors to MT in 6 Countries (2004)
Brazil0-0.2

1
Due to significant differences in the growth rate of SW
depending on countries examined, certain interactions between
software and particular institutional factors permit 10-15%
significant level.

58

Efficiency of legal framework
0.8

Need for economic
and social reforms

0.6

Total expenditure on R&D

0.4

High positive scores of PC32 (elasticity ofheterogeneous nations) in India and China suggest thata large population, cheap labor, rapid economic
growth, high income imparity and development ofurbanization contribute to the advancement of ICT inthese two countries characterized by the world highest
diffusion velocity in PC, Internet and mobile phone.
Contrary to India and China, scores of PC32 in USA,
Japan as well as Brazil and Russia are negative or
negligibly small. In light of such a clear contrast in
PC32 between India/China and Brazil/Russia, Figure 4
analyzes the constitution of PC32 in the four BRIC
countries by comparing scores of 12 variables
constituting this component.

BrazilChina
India
Russia0.2
0-0.2

Trade to GDP ratio

Risk of political instability

-0.4
-0.6

Quality of the educational system

GDP PPP per capita

Overall infrastructure
quality

Skilled labor

Fig. 3. Contribution of Quality of Traditional Development Base (PC11) in BRICs (2004).

3.2 Information and communication technology (ICT)
Aiming at identifying the significant impacts ofinstitutional factors on ICT, on the basis of equation(4), cross-country multi-regression analysis isconducted. Using Backward Eliminating Method(BEM) with 5% significant level criteria (see footnote
1 in 3.1), the principal components that havesignificant influences on ICT are identified as follows:

Urban population
Productivity in services(19.44)(-3.87)(3.43)(-1.51)(1.78)

0(2.39) (-1.75)

Gini index

Market environment ICT-1National culture

Population over 65 years

Protectionism

Life expectancy
at birthadj. R2 0.947(7)
The regression result is statistically significant,and indicates that MT, software and institutional
factors contribute to the development of ICT. Qualityof traditional development base (PC11), manufacturing
oriented socio-economic system (PC12), commodity
trade dependency (PC13), liquidity of workforce (PC22)and elasticity of heterogeneous nations (PC32) aresignificant governing institutional factors to ICT.
Table 2 summarizes contributions of these factors to
ICT in BRICs, Japan and USA.

NRI

Const.

PC11

PC12

PC13

PC22

PC32

-0.33

0.73

-0.80

0.00

0.07

-0.05

-0.28

Russia

-0.27

0.73

-0.82

-0.17

0.10

0.01

-0.12
0.43

Justice
Real GDP growth
per capita

Fig.4. Contribution of Elasticity of Heterogeneous Nations (PC32) in BRICs (2004).

Figure 4 demonstrates that the factors of market
environment ICT, population over 65 years, justice,protectionism and national culture are all extremely
weak in Russia requiring it urgent improvement.
Factors requiring enhancement in Brazil are related toeconomic growth, construction of market environment
as well as population and urbanization.
3.3 Software (SW)
Similar to MT and ICT, aiming at identifying thesignificant impacts of institutional factors on software,cross-country multi-regression analysis is conductedbased on equation (5). Using Backward Eliminating
Method (BEM) with 5% significant level criteria, theprincipal components that have significant influenceson software are identified as follows:

Table 2 Contribution of Institutional Factors to ICT in 6 Countries (2004)
BrazilBrazilChina
India
Russia-0.5(-3.60)-2.000SW)PC13+0.010MTPC22+(0.400-0.060MT)PC32(-1.10)Total population

0.5

Productivity in industries

ICT = 0.730+0.559PC11+(-0.650+0.110MT-2.960SW)PC13+(-0.120(29.4)

1

India

0.61

0.73

-0.27

-0.37

0.12

-0.03

China

0.18

0.73

-0.67

-0.08

-0.01

0.02

0.20

Japan

1.20

0.73

0.33

0.01

0.22

-0.08

-0.01

(62.16) (-39.79)

USA

1.66

0.73

0.53

0.01

0.35

0.03

0.01

(0.007MT-0.011ICT)PC32+0.011Djp

SW = 0.040+(-0.009MT+0.016ICT)PC12+(0.008MT-0.011ICT)PC22+(31.54)

Table 2 demonstrates a clear contrast between the
BRICs and Japan/USA with respect to positive or
negative impacts of PC11 on their developments of ICT(see Figure 6). Furthermore, contrary to the strong
inducement of PC13 in Japan and USA, thisinducement is weak in the BRICs and even impedes in
China. Similar to MT, while PC11 consisting of
efficiency of legal framework, overall infrastructure
quality, quality of the educational system, risk ofpolitical instability, GDP per capita and total
expenditure on R&D, it reacted to impediment in
BRICs.

(-6.50)(10.76)(36.15)(-10.10)

adj. R2 0.994(8)(2.84)The regression result is statistically significant,and indicates that MT, ICT and institutional factors
contribute to the development of software. In addition,
manufacturing oriented socio-economic system (PC12),
liquidity of workforce (PC22) and elasticity ofheterogeneous nations (PC32) are significant governing
institutional factors to the development of software.
Contributions of these factors to software in the BRICs,
Japan and USA are summarized in Table 3.
Table 3 demonstrates that while USA is positivein all factors, it is the opposite for Japan. Among six
countries compared, China indicates the highest value

59

institutional systems, which in turn induces further
innovation leading to a co-evolution between them.
This co-evolution is a driving force of innovation
driven economy on which BRICs sustainable
development depends.

of potential of software development demonstrating its
rapid development of software, which can be
attributed to the highest impacts of PC32 and PC22 on
its software development. India demonstrates thehighest contribution of PC12 and significant positive
impact of PC32, which contribute to its conspicuous
software development. All the four BRIC countries
demonstrate positive impacts of PC12, while Russia
and Brazil demonstrate negative impacts in PC 32 andPC22 as well as PC32, respectively.

5. Conclusion
In light of the conspicuous economic growthdemonstrated by the BRIC countries in the early 2000s
and their significant contribution to the world
economy, this paper analyzed the co-evolutionary
dynamism and conditions of the BRICs’ sustainable
development.
Withtheunderstandingthat
advancement of technology induced by aco-evolutionary dynamism between innovation andinstitutional systems is indispensable for the BRICs’
sustainable development through effective utilizationof their potential resources, empirical analyses of thedevelopment trajectories in 40 countries centered by
the BRIC countries were conducted and demonstrated
the following noteworthy findings:(i) The major factor impeding BRICs’ substantial
technology innovation can be attributed to their
low MT level.
(ii) While BRICs have constructed a strong interacting
relationship between innovation including MT,
ICT and software and their institutional systems,
and therefore, advancement of MT depends on
the way of interaction between ICT, software andinstitutional systems. Certain institutional factors
impede this interaction to lead to a virtuous cycle
constructing a co-evolution between innovationand institutional systems.
(iii) Strong impediment factors in their institutional
systems common to the BRICs include theweakness of advanced management system suchas enterprise management, education and trainingof employees, reliability of professional
management and degree of efforts for consumer
satisfaction.
(iv) Contrary to the low level of MT, the level of
BRICs ICT and software demonstrates
noteworthy growth. While the current levels of
BRICs ICT and software have remained lower
than that of Japan and USA, the conspicuous
growth rates of ICT market environment, labor
source and human resource supply in China andIndia suggest their potential in rapid
development.
(v) Given the strong interaction between MT and
ICT/SW as well as institutional systems, further
advancement of ICT/SW in BRICs can leverage
the co-evolution between innovation andinstitutional systems leading to substantial
advancement of technology essential for theeffective utilization of potential resources fortheir sustainable development.

Table 3 Contribution of Institutional Factors to Software in 6 Countries (2004)
SW

Const.

PC12

PC22

PC32

Brazil

1.82

5.37

0.06

-3.56

-0.06

Russia

0.99

0.96

0.16

0.05

-0.17

India

4.51

3.10

0.83

-0.25

0.83

China

7.77

3.51

0.54

1.32

2.40

Japan

1.11

4.72

-0.52

-1.53

-1.56

USA

6.36

3.53

0.48

1.23

1.12

The forgoing analysis demonstrates that (i) The
advantage of ICT talent's training and talent supply
market of software contribute to the development of
the software industry in China and India; and (ii)Characteristic of “high-quality work force,” “cheappay” and “English sphere" in software industry
contribute to India for its competitive edge in theworld.
4. Co-evolutionary dynamism between Innovation
and Institutional Systems
Based on the foregoing analysis of correlation
between institutional systems and MT, ICT as well assoftware, it can be identified that institutional factors,
MT, ICT and software are interconnected andsignificantly contribute to each other. This
demonstrates that a strong interacting dynamism
between innovation represented by MT, ICT as well assoftware and institutional systems functioned well inthese 40 countries as illustrated in Figure 5.
Institutional systems

IC

MT

InnovationSW

1. PC11, PC12, PC13
2. PC21, PC22
3. PC32

Fig. 5. Co-evolutionary Dynamism between Innovation andInstitutional Systems.

Figure 10 demonstrates that institutional systems
play an important role in cultivating emerging
innovation similar to soil, if the foregoing interaction
reacts positively, leading to a virtuous cycle. In thiscase, emerged innovation contributes to a change in60

Reference[1]
IMF. World economic Outlook Database. IMF;
April 2006.
[2]
IMD. World Competitiveness Yearbook 2005.
Lausanne, Switzerland: IMD; 2005.
[3]
Kondo R, Watanabe C. The Virtuous Cycle
betweenInstitutional
Elasticity,
IT
Advancement and Sustainable Growth: Can
Japan Survive in a Information Society?
Technology in Society 2003; 25(3): 319-335.
[4]
Watanabe C, Kondo R. Institutional elasticity
towards IT waves for Japan's survival: The
significant role of an IT Testbet. Technovation
2004; 23(4): 307-320.
[5]World Economic Forum (WEF), The Global
Competitiveness Report 2005-2006.
[6]
International Telecommunication Union (ITU).
World Telecommunication Indicators 2004.
Switzerland: ITU; 2005.
[7]
Wilson D, Puruthaman R. Dreaming with
BRICs: The Path to 2050. Goldman sachs:
Global Economics Paper, N0. 99, 2003.
[8]
O'Neill J, Wilson D, Purushothaman R,
Stupnytska A. How solid are the BRICs?
Goldman Sachs: Global Economics Paper, No.
134, 2005.

61

Co-evolutionary Dynamism between Japan and China in Software Outsourcing
Weilin Zhao**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-49 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANZhao.w.aa@m.titech.ac.jp
Outsourcing from Japan to China has increased dramatically in recent years,
resulting in increased mutual benefit. Japan’s dependency on outsourcing of softwaredevelopment to China will lead to the most efficient information and communication
technology (ICT) development in Japan, which in turn will induce China’s ICTdevelopment. Software outsourcing leads to a co-evolutionary dynamism between bothcountries and such a co-evolution can be enabled by a co-evolutionary dynamism between
advancement of economy, ICT and software in both countries. This paper attempts anempirical analysis of Japan’s outsourcing of its software development to China by utilizing
the concept of substitution dynamism between Japan’s own software development and thedevelopment by software-leading countries, China, USA and India.

1. Introduction

1.2 Hypothesis
The foregoing observations suggest thefollowing hypothetical views with respect to the coevolutionary dynamism of software development
between Japan and China triggered by outsourcing:(i)Pursuing the most qualified software
resources available in the world market is
indispensable for nation’s competitiveness.
Japan’s dependency on outsourcing of softwaredevelopment to China can lead to the most efficient
ICT development in Japan, which in turn induces
China’s ICT development.
(ii) Software outsourcing can lead to a coevolutionary dynamism between bothcountries.
Such a co-evolution can be enabled by a coevolutionary dynamism between advancement of
economy, ICT and software in both countries. The
hypothetical view can be postulated as Figure 1-1.

1.1 Background
With progress in ICT, outsourcing (supply byan external entity of a service previously provided
in-house) has become feasible. In fact, theinternational outsourcing has been growing rapidly.
Software development outsourcing from USA to
India is a typical example. Similar to USA, Japan ismaking use of outsourcing to overseas to promote
its ICT development. In recent years, outsourcing to
China has been becoming focused. Table 1-1
demonstrates scale of outsourcing from Japan tooverseas over the period 2002 to 2004 which
demonstrates that the share of outsourcing to China
greatly increased from 48% in 2002 to 63% in 2004.
Table 1-1 Scale of Outsourcing from Japan to Overseas (02-04): ¥ millions
Country/Year

China
US
India
Australia
UK
Philippines
Korea
FranceCanadaVietnam
Others
Total

2002

9,833
3,260
1,908
0
20
1,864
1,952
0
496
30
888
20,251

2003

26,280
4,988
6,312
2,626
1,827
2,494
1,817
834
616
30
1,082
48,9602004

33,241
5,147
4,255
3,133
2,126
2,117
1,415
548
262
216
237
52,697%of
total
in 2004
63.08
9.78
8.07
5.95
4.03
4.02
2.69
1.04
0.50
0.41
0.43
100

Japan

China

Economic Development

ICT Development.
SoftwareDevelopment

SW
ExportOutsourcingin
Outsourcing
Softwarein develop.

SW
ImportICT Development

Economic Development

Source:An investigation from surveys by Japan Information
Technology Services Industry Association (JTSA), Japan
Electronics and Information Technology Industries Association(JEITA) and Japan Personal Computer Software Association(JPSA).

Fig. 1-1. Co-evolutionary Dynamism between Japan and
China through Outsourcing.

62

SoftwareUsedin country X is the source of such substitution.
When σ xj < 0, relatively higher software prices incountry X induces substitution of its softwaredevelopment for Japan’s software development
which implies that higher functionality in country X
is the source of such substitution.

2. Analytical Framework
2.1 Substitution of Software Development
Outsourcing from country Y to X can beanalyzed based on a concept of substitution
dynamism from country Y to X. Elasticity of
substitution of software in country X for that of inJapan is depicted as follows:σ xj =

2.2 Measurement of Software Prices
Since diffusion of software in the nation isgoverned by nation’s economic capacity, thistrajectory can be traced by the logistic growth
function with GDP as follows (see Figure 2-1):

(

)(
)
(2-1)
d[(∂Vj ∂SWj ) (∂Vx ∂SWx )] [(∂Vj ∂SWj ) (∂Vx ∂SWx )]d SWx SWj SWx SWj

dSW
SW= aSW (1 −)dVSWwhere SWx and SWj: potential of software development incountry X and Japan; andVj and Vx: GDP in Japan and country X; therefore,∂V x: marginal productivity of software in country X.
∂SW xwhere V: GDP; a: velocity of software diffusion; and SW :carrying capacity of software.
SW

SW

When software developers endeavor to
maximize their profits under the competitive
circumstance, marginal productivity of software incountry X corresponds to the relative prices ofsoftware as follows:
∂V x
P
= sx
∂SW x Pvx

V =F (SW)() (SWx SW j )=Psj
d (Psj Psx ) (Psj Psx )d ln∂V dSWdV∂V=⋅=
dSW ∂SW dSW ∂SW

(2-3)
(2-7)

Psx

Provided that software developers endeavor to
maximize their profits under the competitive
circumstance, marginal productivity of softwaredevelopment in equation (2-7) can be depicted asfollows:

Integrating the equation (2-11), the following
equation can be obtained:
ln

Psj
SW x
= a + σ xj ln
Psx
SW j

(2-6)

Differentiating V by SW leads to the following
equation:

Therefore, σ xj can be developed as follows:d SWx SW j

SW

Given that software (SW) leads the trajectory of
economic development in the nation, GDP (V) canbe depicted by the following function:

where Psx and Pvx: prices of software and GDP in
country X.

σ xj =

V

Fig. 2-1. Mutual Inspiration between Diffusion Trajectories
of Software and Economic Capacity.

2)

SWx
SW j

V

V

(2-

d ln

(2-5)

(2-

4)

P
∂V
= s
∂SW Pv

where a: coefficient.

(2-8)

where Ps and Pv: prices of software and GDP.

When σ xj > 0, relatively lower software prices incountry X induces substitution of its softwaredevelopment for Japan’s software development
which implies that cheaper software production cost

Given the existence of the reverse function
with respect to software development and GDP of
the nation, equation (2-8) can be developed as63

follows:∂SW Pv dSWSW=== aSW (1 −
)
∂V
Ps
dV
SW

Fig. 3-1. Software Outsourcing Driven Co-evolutionary
Dynamism between Japan and China.
a
ICT is based on IT index (1990 = 100).

(2-9)

3.2 Substitution of Software Development –Outsourcing Dynamism
In light of the significance of this outsourcing
triggering such a co-evolutionary dynamism, thedynamism spurring this outsourcing was analyzed.
Given the global nature of the potential of softwaredevelopment (nation’s resources potential insoftware innovation) and provided that thispotential can be internationally substitutabledepending on its prices and functionality, substitution

Therefore, relative price of software can becomputed by the following equation:
Ps
=
Pv

1
aSW (1 −SW
SW(2-10))

3. Empirical Analysis

3.1 Co-evolutionary Dynamism Triggered
by Software Outsourcing
Japan’soutsourcing
inits
softwaredevelopment to China has increased in recent years.
Consequently, co-evolutionary dynamism between
Japan and China in their GDP-ICT-SW (software)development has activated as demonstrated in
Figure 3-1.
CH: GDP – ICTa (90-04)
2004

1100
900
2000

500
1995

1990

100
1000

3000

5000

84
77
70
63
56
49
42
35
28
21
14
7

7000

9000

11000

CH: SW – SW export (99-04)

300

SW exports

500

700

2002

10

Figure 3-2 illustrates trends in the ratio ofsoftware development between Japan and three
1500software-leading countries (China, USA and India)
over the period 1992-2004. The figure demonstrates
that China’s development of software increased
dramatically than that of Japan. India’s softwaredevelopment also increased slightly higher thanJapan, while the reverse trend continued in USA’s
software development before it changed to slightly
higher than Japan from 2002.

900

1100

1300

ICT (1990=100)

2004

12

15

software in Japan and country X.

1991

100

S W ( S C C /( V /P ) )

2004

2003

11

5
0 1999
30
70

2002

SW x
SW j 16

10
110

150

190

230

270

SWrevenue

SW revenue

5

14

Ratio of SW imports from China
Ratio of SW imports from China

12

1

2

a

3

4

JP: ICT –GDP (90-04)
2004

ICT (1990 = 100)

160
150
140
130
120
1991

100
3

0
1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004

500

2000

490

460

5

7

SW(SCC/(V/P))

9

11

450
100

1990
110

120

130

140

150

160

Ind ia/Jap an
USA /Jap an

Fig.3-2. Trends in the Ratio of Software Development
between Japan and Three Software-Leading
Countries.

1995

470

1995

110

10

2

2004

510

480

Sw i/SWj

4520

GDP (￥ tril.)

2000

Ch in a/Japan

Sw u/SWj

6

530

180

SWc/SWj

8a

JP: SW – ICT (91-04)
170

software development in country X for that of in Japan; Vj and Vx:
GDP in Japan and country X; and Psj and Psx: fixed prices of

JP: SW import –SW (02-04)

13

20

and Japan; a: coefficient; σ xj : elasticity of substitution of2002

GDP per capita (Yuan/person)

25

(3-1)

where SWx and SWj: software development in country X
2004

S W ( S C C /(V /P ) )IC T (1 9 9 0 = 1 0 0 )

1300

300

∂V j
∂SW j
Psj
SW x
ln
= a + σ xj ln= a + σ xj ln
∂V x
SW j
Psx
∂SW x

CH: ICTa – SW (91-04)

1500

700

of software development in country X (SWx) for that ofin Japan (SWj) can be depicted by the following
equation:

170

180

ICT (1990 = 100)64

Based on these estimated logistic growth
function results , Figure 3-3 illustrates trends in theratio of relative prices of software between Japanand three software-leading countries over the period
1992-2004.

Table 3-1 Elasticity of Substitution of Software Development in
China, USA and India for Japan (1992-2004)

P sj

China

P sx

2.5

Psj/Psc
2

Japan/China

Psj/Psu
Psj/Psi

USA

Japan/India

1.5

India

1

a

b

σ1

σ2

1.316
(77.20)2.295(36.78)1.011(9.94)

2.847(6.50)-0.583(-2.36)0.956(1.93)

2.847(6.50)
0.852(4.58)
0.684(2.97)-2.100(-3.90)-0.194(-0.62)-0.776(-0.88)

adj.
R2
0.991

DW
1.96

0.697

1.10

0.790

2.10

0.5

4. Conclusion

Japan/USA
0
1992

1993

1994

1995

1996

1997

1998

1999

2000

2001

2002

2003

Software industry development in China has
been focused in recent years. It can be concluded
that the advancement of software is subject to theinstitutional structure of China. Furthermore, with
an empirical analysis of Japan’s outsourcing of its
software development to China by utilizing theconcept of substitution dynamism between Japan’s
own software development and the development bysoftware-leading countries, China, USA and India,
co-evolutionary dynamism between Japan and
China in software outsourcing was elucidated Sucha co-evolution can also be enabled by a coevolutionary dynamism between advancement of
economy, ICT and software in both countries.

2004

Fig. 3-3. Trends in the Ratio of Relative Prices of Software between
Japan and Three Software-Leading Countries.

Looking at the figure we note that Japan and
China ratio continued to increase in the 1990s to thebeginning of the 2000s before it changed todecreasing trend from 2002. This trend suggeststhat while China’s software demonstrated theadvantages of cheaper prices, it changed todemonstrate the advantages of higher functionality
from 2002 corresponding to “The Action Program
for Vitalization of Software Industry: 2002-2005”
initiated by the Chinese government in 2002. Basedon the analyses on Figures 3-2 and 3-3, Figure 3-4
demonstrates the trends in the substitution ofsoftware development in China, USA and India forJapan over the period 1992-2004.

References

Fig. 3-4. Trends in Substitution of Software Development
in China for Japan (1992-2004).

Since structural change was observed in 4
countries examined between the period before andafter 2002, regression analysis between the ratios ofsoftware development and relative prices was
conducted taking dummy variables reflecting such astructural change as (3-2), result of the analysis issummarized in Table 3-1.
ln

Psj
Psj
SW x
= a + bD + σ xj 1 (1 − D ) ln
+ σ xj 2 D ln
SW j
Psx
Psx

(3-2)

where D: dummy variable (2002-2004 = 1, other years = 0).

65

[1]

Apte, U., 1990. Global Outsourcing ofInformation Systems and Processing Services,
The Information Society 7, 287-303.

[2]

China
SoftwareIndustry
http://www.csia.org.cn[3]Japan Electronics and IT Industries Association
http://www.jeita.or.jp/japanese/[4]

Japan IT Services
http://www.jisa.or.jp/[5]

Ministry of Information Industry of the PRC,
Yearbook of Chinese Electronic Industry 2004,
http://www.mii.gov.cn/[6]Oza, N., Hall, T., Rainer, A. and Grey, S.,
2002,
Critical
FactorsinSoftwareOutsourcing – A Pilot Study, Communicationsof the ACM 45 (2002).

[7]

Oza, N.V., Hall, T., Rainer, A. and Grey, S.,
2006, Trust in software outsourcing
relationship: An empirical investigation ofIndia software companies,” Information and
Software Technology 48, 345-354.

[8]

US DOC, Digital Economy 2000, Washington,
D.C.

Industry

Association

Association

Risk Management in Outsourcing Service Industry- Suggestions from a Portfolio Analysis of India’s Case
Weilin Zhao**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANzhao.w.aa@m.titech.ac.jp
India, famous for its software outsourcing service, has achieved high growth rates insoftware exports for many years. The figure of Indian software export destination
constitution shows that the US has been the dominant destination for more than a decade.
The US is overall India’s largest partner in this sense. In other words, Indian software
export is heavily dependent on the US market. Risks exist in outsourcing market not only
for outsourcers but also for outsourcing service vendors. Risk awareness, avoidance andmanagement are very crucial for outsourcing service industry’s sustainable and healthy
growth. The paper attempts to give some suggestions for risk management in outsourcing
service industry by the portfolio analysis of India’s case. Utilizing the simplest portfolio
analysis model, the optimal point between markets can be figured out. Since therelationship between risks and revenues can also be illustrated, decision makings can beeasily done by different options according to different principals from the viewpoint ofrisk.
1. Introduction
1.1 Backgrounda long time. When they discuss outsourcing to India is

India, famous for its software outsourcing service, haschange simultaneously. Risk is inherent to almost any

achieved high growth rates in software exports forbusiness decision, in particular when it involves

many years. It seems not so interesting to summarize

different geographical and political boundaries.

that India’s outsourcing services are mainly US-

Outsourcing decisions and contractual arrangementsoriented developments, since it has been a commonof the type required by an IT outsourcing deal, aresense. Table 1 shows that the US has been thefactually an example of a risky business endeavor.

dominant destination for India for more than a decade.

While outsourcing can lead to lower costs, economies

on earth good or bad, profits from the US market willof scale, access to specialized resources, it can have

Table 1 India’s software export destination constitution : %unwanted outcomes such as geographical risks,

Japan

Other
Countries

Total

20.0

5.0

10.0

100

26.0

7.6

9.4

100

23.0

3.5

8.5

100

62.0

24.0

4.0

10.0

100

01/02

63.0

26.0

4.0

7.0

100

02/03

68.0

18.0

2.0

12.0

100

03/04

67.7

21.3

2.8

8.2

100

04/05

64.0

23.0

4.0

9.0

100

stances; the part for the vendors has been neglected.

05/06

62.1

27.8

3.0

7.1

100

While we should be aware that risks exist in

Year

USA

97/98

65.0

98/99

57.0

99/00

65.0

00/01

Europeescalating costs, diminishing service levels and loss ofexpertise. As in other risky business, risk assessment
and risk management are important contributors to thesuccess of an outsourcing venture. It seemed thatmany researches were done from the outsourcers’

Sources : Internet Searchoutsourcing market not only for outsourcers but also

The US is overall India’s largest partner in this sense.

for outsourcing service vendors, since outsourcing

In other words, Indian software export is heavily

service industry has been a crucial economic

dependent on the US market. In fact, In the US,

contributor in some developing countries like India.

outsourcing to India has been a controversial issue for66

1.2 Objectives

2.2 The simplest portfolio model
In case two markets, {x1 , x 2 }This paper attempted to analyze the risks from theAt first, risk is measured as standard deviation ofvendors’ stance. Considering India’s case, with two
main export markets for India’s selections, the risks,

portfolio as follows:

the expected return and the optimal export ratio are∑= Var = x σ + x σ + 2x x ρ σ σ
2
1

2
1

2
2

2
2

1 2

12

1

(1)

2

σ 12 , σ 22 - variance of investment into the two markets
σ 1 , σ 2 - standard deviation of σ 12 , σ 22ρ12 - correlation coefficient between investments into
two markets as − 1 ≤ ρ12 ≤ 1

calculated. Implications and suggestions from theanalysis are also given.
2. Analytical Framework
2.1 Portfolio theory
Portfolio Theory (PT) was firstly introduced byHarry Markowitz in his paper “Portfolio Selection” inSecondly, expected return is measured as follows:r - expected return of portfolio {x1 , x 2 }1952. After 38 years, he shared a Nobel Prize with

r1 , r2 - expected return of the two markets

two other scholars for this theory, since it has been an

Then, r = r1 x1 + r2 x 2important theory in finance. PT proposes how rational
investors will use diversification to optimize theirSince the analyzed objects are two markets here,
x1 + x 2 = 1 = 100% , and x 2 = 1 − x1 , 0 ≤ x ≤ 1

portfolios. PT models an asset’s return as a random

The function of expected return of portfolio (2) andvariable and models a portfolio as a weighted

standard deviation of portfolio (1) can be induced

combination of assets; the return of a portfolio is thus

further as follows:

the weighted combination of the asset’s returns.

r = r1 x + r2 (1 − x) = (r1 − r2 ) x + r2

Moreover, a portfolio return is a random variable, and∑ = x σ + (1 − x) σ + 2x (1 − x)ρ σ σ (4)2consequently has an expected value and a variance.

2
1

2

(2)

2
2

(3)
12

1

2

Risk, in this model, is the standard deviation of the

A parametric curve of expected return versus standard
deviation was depicted as Fig. 2.

portfolio’s return. Every possible asset combinationr

can be plotted in X_risk-Y_return space and thePareto m axim um points
r2

collection of all such possible portfolios defines aρ 12 = − 1

region. The line along the upper edge of this region isρ 12 = 1

called efficient frontier as illustrated in Fig. 1.
Mathematicallytheefficient

frontier

is

the

r1

intersection of the set of portfolios with minimum
variance and the set of portfolios with maximum

σ1

return.

σ2∑Fig. 2. Parametric curve of expected return and risk.

From Fig. 2, we can see that it is important to figureout the 5 parameters as r1 , r2 , σ 1 , σ 2 and ρ12 forfurther analysis.
Thirdly, portfolio with minimal risk is also
formulated with minimum conditions.
Fig. 1 Basic concept of portfolio theory.

67

d∑
dx

=

σ 12 x − σ 22 (1 − x) + σ 1σ 2 ρ12 (1 − 2 x)σ x + σ (1 − x) + 2σ 1σ 2 x(1 − x)
2
1

2

2
2

2

x(σ + σ − 2σ 1σ 2 ρ12 ) = σ − σ 1σ 2 ρ12
2
1

2
2
2
2

2
2

3. Empirical Analysis=0

3.1 Results
The five important parameters were firstly figuredout and the parametric curve was depicted (See Fig.
3.).

Then,

σ − σ 1σ 2 ρ12σ (σ − σ 1 ρ12 )= 2 2 222σ + σ 2 − 2σ 1σ 2 ρ12 σ 1 + σ 2 − 2σ 1σ 2 ρ12 r 5.0
σ 1 (σ 1− σ 2 ρ12 ) 4.0
σ 2 −σ σ ρ
1 − x = 1 − 2 2 2 1 2 12
= 2
σ 1 + σ 2 − 2σ 1σ 2 ρ12 σ 1 + σ 22 − 2σ 1σ 2 ρ123.0x=Parametric curve

2
1

If,

σ 2 − σ 1 ρ12 > 0
σ 1 − σ 2 ρ12 > 0

2.0

σ σ
ρ12 < min( 1 , 2 )σ 2 σ11.0
0.0

In this case,

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5 ∑

r σ (σ − σ ρ ) + r2σ 1 (σ 1 − σ 2 ρ12 ) Fig. 3. Parametric curve of risks and expected returns.
r = r1 x + r2 (1 − x) = 1 2 2 2 1 122
σ 1 + σ 2 − 2σ 1σ 2ρ12σ 1 = 3.14, σ 2 = 2.95, ρ12 = −0.77
At last, maximization of x was conducted from theHere,viewpoint of utility. In the analysis of this paper,.

r1 = 4.638, r2 = 1.729

utility is considered to be a simple one related to two

With the calculation based on minimum risk andeasy-to-get data as software export revenues and the

maximum expected return, the optimal portfolio of x

above mentioned risks.

as 0.527 with risk as 1.053 and return as 3.239 are
also clear now. It can be concluded that 52.7% is the

The function is as follows:
Utility = revenues – risk

optimal export ratio to the US.

(5)

The region under the pot line should be
neglected with the higher risks but lower
returns. Other important points can also befound out in the parametric curve. For example,
the highest risk point is 3.140 with the highest
return 4.638; the smallest risk point is 1.033
with the return 3.101; the middle risk point is
2.123 with the return 4.075. Then, different
decisions can be made according to different
considerations.

It can be expressed as the following formula,

Utility = r1 x + r2 (1 − x ) −(σ 12 x 2 + σ 22 (1 − x ) 2 + 2σ 1σ 2 ρ12 x (1 − x ))Considering minimum conditions:∂U= r1 − r2 − 2(σ12 +σ22 − 2σ1σ2ρ12)x + 2σ22 − 2σ1σ2ρ12 = 0∂xr − r + 2σ 22 − 2σ 1σ 2 ρ12
then, x = 1 22.
2(σ 2 + σ 12 − 2σ 1σ 2 ρ12 )2.3 Data construction{x1 , x 2 }were referred to the US and the European
markets for India’s outsourcing service. The analysis

r5.0

is to find out the optimal portfolio constitution

4.0

between the two markets. India’s software export

3.0

ratios to the US and the European markets from 1997

Parametric curve

2.0

to 2006 were utilized. In terms of expected return,1.0

mean values of real data as export revenues were used

0.0

here. Market ratio of x is produced by random number

0.0

between 0 and 1.

0.5

1.0

1.5

2.0

2.5

3.0

Fig. 4 Parametric curve with optional points.

68

3.5 ∑

reconsider this kind of relationship with the US. In

3.2 Discussions
This is a two-market objective analysis with theone hand, it is certainly important to go on keeping

simplest portfolio model. The purpose is certainly

the partnership with the US, because of its main

not to do the analysis itself, but to imply andcustomer’s position for India. In the other hand, tosuggest that risk should not be neglected by vendors

tap new markets and improve the market sharesand risk management is a good contributor to thepositively is also very crucial. In fact, India is now

success of outsourcing. Since the relationshipexploring and trying to occupy Asian markets, likebetween risks and revenues can also be illustrated,Japanese market. It might be a rival for China indecision makings can be easily done by different

this sense; however, it can make more success inoptions according to different principals from thecooperation with China. Though it is true that India

viewpoint of risk.

owns a great number of good-English speakers,
India should do the best to educate other language

4. Conclusion and Future Works

speakers and adapt to other markets by someinstitutional changes.

Risk and risk management have been studied inmany domains; especially such as capital market,

The analysis objectives in this paper are two

finance, insurance and management. Recently, itmarkets as the US and Europe, and one vendor as

has been a hot topic in IT fields, like project

India. It can be applied to more outsourcing markets

management,

andin the future research to find out the optimal point,

outsourcing service. In many cases, customers’

and then confirm the optimal export ratio

profits and risk loss are focused. For vendors, risks’constitution. At the same time, to apply the analysis

impacts are certainly huge. This paper tried to give

into China’s case seems very interesting.

softwaredevelopment

some analyses of risk from vendors’ stances. Before
conducting the analysis, it is essential that theReferences

conceptualization of risk and of risk management[1]

U. Gupta, A. Gupta, Outsourcing the IS
Function: Is It Necessary for yourOrganization?,
Information
Systems
Management, 1992, 44-50.

[2]

H.R. Rao, K. Nam, A. Chaudhury,
Information
Systems
Outsourcing,Communications of the ACM, 1996, 27–28.

[3]

Capital Market and Corporate Finance, Chuou
Economic, 1999.

[4]

National Association of Software and Service
Company (Nasscom).

[5]

Internet Search, Software Export Destination.

[6]

B. A.Aubert, Managing IT Outsourcing Risk:
Lessons Learned, CARANO, 2001.

adopted in the paper be consistent.
Risk awareness, avoidance and management arevery crucial for outsourcing service industry’s
sustainable and healthy growth. The paper attempts
to give some suggestions for risk management inoutsourcing service industry by the portfolio
analysis of India’s case. Utilizing thesimplest portfolio analysis model, the optimal point
between markets was figured out. For India, thebest export ratio to the US is about 52.7%. However,
we can see from Table 1 that except the 98-99 fiscal
year, export ratios to the US were all over 60%.
India’s software industry has been more dependent
on the US market for years, which incorporates
unavoidable risks. In other words, India should69

An Exploration of Competitive Advantages in an Industry Cluster within Local
Institutional Systems: The Case of Dalian Software Park in China
Weilin Zhao **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANzhao.w.aa@m.titech.ac.jp
This paper attempts to explore the competitive advantage of Chinese software parks
for promoting industrial development. These industry clusters provide competitive
advantage because they are rooted in local institutional systems. Taking the case of Dalian
Software Park in China, this analysis is conducted qualitatively based on Porter’s“diamond” model, SWOT framework and interview results. Industry clusters, which
encompass a series of interconnected firms in designated geographic concentrations, showcompetitive advantages for industrial development with substantial resources rooted inlocal institutional systems including government, industry and academia aspects. In orderto successfully navigate the economic paradigm shift from mass manufacturing
production to innovative new product development in China, it is essential that thecompetitive advantages of industry clusters are strengthened and sustained in order toenhance industrial development, generate innovation and increase regional economic
growth.
industry.
Consequently,
thedevelopment
environment of the Chinese software industry has
been dramatically improved and the awarenessabout the competitive advantages of these industry
clusters has greatly increased. Thus, more researchon the recognition and improvement of competitive
advantage in an industry cluster are indispensable.

1. Introduction
1.1 BackgroundIn recent years, ICT has been central to thediscussions
about economic
growthandperformance because it is pervasive and widely
diffused. China, with its high economic growth, hasalso experienced tremendous change in its ICTdevelopment and has achieved considerable
development in various sectors of ICT, particularlyin the development of the software industry. The
development history of the Chinese software
industry is not so long. In its short history, a distinct
industrial structure with two basic strategies
including development in domestic market andexport has been leading this effort. By stimulating
the domestic market demand and encouraging
software exports, software development resources
are expected to be improved in terms of quality andin turn, induce the further expansion of thedomestic market in this area and strengthen
competitive advantages of the industry. Efforts havecontinued from the national level to promote software
related industry clusters to realize the goals andachieve success in both domestic and international
markets. Since the early 1990s, China hascontinually established many software parks
including 11 national software industrial bases and6 national software export bases, which formed theoverall planning and layout of the Chinese software

1.2 Objective
This paper attempts to identify the institutionalsources for the competitive advantage of Chinese
software parks by taking the case of Dalian
Software Park (DLSP). Dalian’s local institutional
systems, particularly their driving forces forsoftware exports, are the focus. Section 2 introducessome related research work. Section 3 depicts theanalyticalframework
includinganalyticalmethodology and data collection.
Section 4
provides the results of the analyses, and then theimplications are discussed.
2. Literature Review
Competitive advantage is now a popular term inmany fields with the broader concept including
national, industrial and firm levels. In the book
“The Competitive Advantage of Nations” written
by Porter, he stressed the important role “played bya nation’s economic environment, institutions andpolicies” for successful competitive industry
development. This paper analyzed the competitive70

advantage of industry clusters embedded in local
institutional systems within the macro context ofnational institutional systems based on the“diamond” model presented by Porter.
Recent researches by Doeringer and Terkla
examine the literature regarding industry clusters
and identifies them as “geographical concentrationsof industries that gain performance advantages
through co-location”. As a specialization andconcentration of firms and industries in a region,
they usually have common markets, share common
suppliers, trade or education institutes, andintangible things like know-how and informationexchange.
Since the establishement of software parks in
the 1990s, the Chinese government launched 11
National Level Software Industry Bases in different
cities including Beijing, Shanghai, Dalian, Jinan,
Xian, Nanjing, Changsha, Chengdu, Hangzhou,
Guangzhou and Zhuhai in 2001 and 6 softwareparks, located in Beijing, Shanghai, Dalian,
Shenzhen, Tianjin and Xian, were authorized as
Software Export Bases in 2003. Cities with
software parks have emerged as leading softwarecities in China. When comparing the main softwareparks that have two identities as both a national
level software industry base and a software exportbase in China, the software park in Daliandemonstrates particular excellence in exports,
which can be attributed to a geographical advantage
in Dalian as well as a more appropriate
development strategy and industry policies
supported by the local government.
At the same time, in DLSP, indigenous
strength from Chinese firms and the learning effectsof the global best practice from foreign firms arewell fused. Table 1 gives the number and ratio of
local and foreign firms in DLSP. Compared withthe 33% foreign firms in Shanghai’s software parkand 30% in Beijing’s software park, DLSP
demonstrates the highest rate of the foreign firms,
which play significant roles in inducing theclustering and learning effects. Thus, under theclustering effects, firms from various countries withdifferent culture backgrounds and institutional
systems stimulate and encourage a co-evolutionary
development leading to the win-win development.
DLSP’s achievement can largely be attributed
to the clustering effects inducing its good businessenvironment, preferential supportive policies andhuge talent pool of human resources. All of thesefactors are significantly rooted in its local
institutional systems.

Table 1 Number of Chinese and foreign firms in DLSP
(2005-2007)
Number offirms/Year
Chinese firms
Foreign firms(including global 500
corporations)

Total

2005

2006

2007

159

211

227

(60%)

(58%)

(58%)

108

153

165

(40%)

(42%)

(42%)

(22)

(27)

(33)

267

364

392

Source: Author’s summary based on introduction of
Dalian Software Park.

3. Analytical Framework
3.1 Methodology
This paper analyzes the institutional sources forthe competitive advantage of DLSP as an industry
cluster. By means of the “diamond” model and
SWOT (strength, weakness, opportunity and threat)
analyses, the local institutional systems areanalysed. The overall analytical methodology inthis paper is based on a case study of DLSP. In
addition to the general analyses described above,
interview results are also added to provide morepractical management implications based on
managers industrial experiences at DLSP.
The “diamond” model has been used as aframework for evaluating the competitiveness ofregional industries and elucidating local industry
clusters. It includes four important drivers as
demand condition, factor condition, related andsupporting industries, firm strategy, structure andrivalry. SWOT refers to strengths (S), weaknesses(W), opportunities (O) and threats (T). A SWOT
analysis is useful in analyzing firms’ strategic
management and identifying the level of firms ineach respective dimension. In general, the SWOT
analyses provides a much clearer map of thestrengths, weaknesses, opportunities and threats of
DLSP, making it aware of its strategic position andindicating how to strengthen its competitiveness. In
order to support the general analyses from theindustry’s
viewpoints,
interview
surveymethodology was utilized that helped to evaluate
more qualitative aspects and gain insights into thecurrent issues in the development. The interviewsof the selected firms were conducted in Dalian in
January of 2007.

71

order to improve Intellectual Property (IP)protection awareness, the first IP service center in
China was set up in DLSP under the Dalian
government’s help. Similarly, corresponding to thelaws about private data protection in Japan, DLSP
also took early action to provide guarantee forJapanese customers. In a word, continued efforts
from the government lead to the achievement of
DLSP.

3.2 Data collection
The majority of the statistical data used for thispaper are from websites such as that for the China
Software Industry Association, and publisheddocuments such as the Annual Report of Dalian
Software and Information Service Industry andChina Statistics Yearbook on High Technology
Industry. In the interview survey, the selected firms
are representatives of all firm types in DLSP
including 4 branches of foreign firms, 2 China’s
top-ranked firms in software exports and one SME(Small Medium Enterprise). All the interviewees
have manager-level positions responsible for bothproject management and practical business
management.

4.1.2 Industry
The establishment of DLSP is for promoting
software industry development. Industry is thecore part of this endeavor and includes all parts of
the “diamond” model. In demand, rapid
development of ICT and informatization
construction provide huge domestic ICT markets
and the need for human resources has apull-through effect on the development of related IT
training industry, which results in more innovations
in traditional IT education at the universities. At theend of 2007, there were nearly 50 percent foreign
firms in DLSP including significant participation by
well-known multi-national corporations with Asian
operations. This can be ascribed to the uniquebusiness environment, rich development resources
and high potential for growth of DLSP. The
competition and cooperation among the firms is
considered to be another “virtuous self-propagating
cycle” bringing out more innovative ideas which inturn continues to stimulate industry dynamics.

4. Results
4.1 Diamond model analysis
In order to highlight the competitive
advantages of DLSP, the analysis was conductedfocusing on the three dimensional aspects ofgovernment, industry and academia in combination
with determinants of the “diamond” model. Since
all the determinants of the “diamond” model can bereasonably
summarized
into
these
three-dimensional
aspects,
this
kind
of
consideration for the analysis is appropriate. Withdetailed descriptions of supportive policies andstrategic actions in the three dimensional aspects, it
is noteworthy that the competitive advantages of
DLSP are rooted in the cooperation between
government, industry and academia. This
cooperation is driven by the local institutional
systems, which incorporate different importantfactor determinants of the “diamond” model
respectively. The local institutional systems seem tobe a “fertile soil” that promotes the growth of DLSP
as a mature industry cluster and determines its
competitive advantages.

4.1.3 Academia
Thesoftwareindustry,asaknowledge-intensive industry, cannot develop wellwithout enough qualified human resources. The
basic role of academia is to guarantee theavailability of human resources as an importantfactor condition of the “diamond” model. Since theestablishment of DLSP, software related education
has been strengthened. In addition to the quantity,
the current educational system focuses significant
attention on the quality of graduates. Many private
training institutes and centers are pursuing a new
demand-oriented training model with more focus onpractice to supplement the traditional education. By
collaborating with firms, basic research in theuniversities has a more practical focus in software
research and development.
This not only
enhances the demand and reputation for theacademic institutions but also promote the firms’
capacity in the development of innovative products.

4.1.1 Government
Unlike Silicon Valley, DLSP was initiallyestablished and organized by the local governmentand developed with government support. Though
Porter’s view was that government is only afacilitator, the government has been playing adecisive role in the establishment and developmentof DLSP with well-organized infrastructure
construction, top-down development guidance andsupportive policies. Factor conditions in the“diamond” model including physical, capital
resources and infrastructure can chiefly be
attributed to the support from the government. In

72the institutional resources of competitive
advantages for DLSP and provided insight into
industrial development. With the increasingawareness of competitive advantage in an industry
cluster for industrial development and regional
economics, this research highlights the role of local
institutions in this competitiveness. Considering thedeterminants of the “diamond” model, institutionalsources are categorized into government, industry
and academia vectors. After that, a SWOT analyses
pointed out areas for further improvement anddevelopment by identifying the strengths,
weaknesses, opportunities and threats faced by
DLSP. Interview data reflected the observations
from the industry supporting the general analyses.
The success of DLSP as an industry cluster is basedon institutional resources including all the efforts
from government, industry and academia. In otherwords, DLSP is a very good model of a localized
cluster in which development is deeply rooted in its
local institutional systems. It turns out to be a
co-evolutionary development between DLSP and
the local institutional systems. Similarly, DLSP
displays its competitive advantages by encouraging
networks among firms, integrating into theinternational value chain of activities andimproving its reputation internationally. The
clustering effects of DLSP in utilizing an array of
resources from different firms, stimulate moreinnovation, and facilitate industrial and regional
economic development.

4.2 SWOT analysis
Following the “diamond” analysis summary of
the Dalian’s local institutional sources, the SWOT
analysis, supplements and extends the concept ofcompetitiveness to the general opportunities andthreats, providing further insight into DLSP.
SWOT also provides a mechanism for identifying
areas in which the existing institutional systems canbe improved. Strengths are the ways DLSP canobtain opportunities and face the existing threats. In
most cases, weaknesses are considered to be theopposite of the strengths, but are areas that existing
strengths cannot easily overcome. Strengths need
to be further improved; weaknesses should beovercome; opportunities need to be taken; andthreats should be changed to enhancecompetitiveness.
Though Dalian has a favorable geographicallocation, the increasing living cost is threatening thecost of human resources. Dalian’s attractivenessshould be strengthened both in hard aspects and soft
aspects like improved legal environment. In orderto guarantee the talent pool, traditional IT
educational institutions are challenged to focus
more on quality rather than quantity only. Whensome firms are playing the leadership role in thesoftware industry’s development, the performance
gap exists and sometimes widens in the park. The
problem is that many firms tend to pursue a popular
technology without previous experience in this area.
Thus, the formation of technology concentration
creates bottlenecks for developing competitive
advantage. Developing unique requisite technology(rather than everyone pursuing a similar
technological area) will diminish these bottlenecks
and reduce the performance gap making firms morecompetitive.

References[1] China Software Industry Association.
http://www.csia.org.cn

4.3 Interview results
In addition to the general analyses of
institutional systems with the “diamond” model and
SWOT, it is crucial to make the firms’ strategic
thinking clear and know what their real needs are.
Considering the local institutional systems as aco-evolutionary process between government,
industry and academia, the interview survey was
focused on these three dimensions and results are
summarized with respect to several important issues
which will be summarized in another paper.

[2]

Michael EP. The Competitive Advantage of
Nations – with a new introduction. New York:The Free Press; 1990.

[3]

Doeringer PB, Terkla DG. Business strategy
and cross-industry clusters. Economic
Development Quarterly 1995; 9:225-37.

[4]

Watanabe C. Science of Institutional
Management of Technology.
http://www.me.titech.ac.jp/coe/.
Dalian Software Park. Available fromhttp://www.dlsp.com.cn/chinese/index.asp.

5. Conclusions
By taking the case of DLSP using qualitative
data collection and analyses, this paper identified73

An Empirical Analysis of the Development Trajectory of Chinese Software
Industry: Focusing on Outsourcing and Industry Clusters
Weilin Zhao **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANzhao.w.aa@m.titech.ac.jp
Since the middle of the 1990s, with the background of high economic growth and the
diffusion of CT development, software industry also has been making rapid conspicuous
development in China.
Focusing on the development trajectory of Chinese
software industry, outsourcing and industry clusters have been playing a crucial role forthe industrial development and more innovations. First of all, the software outsourcing
dynamism between Japan and China as the co-evolutionary dynamism is demonstrated bysubstitution dynamism; by means of Bass model, it is also demonstrated that highfunctionality development can be sustained by substitution of imitator as China forinnovator as Japan through outsourcing. Next, qualitative analyses on the exploration ofcompetitive advantages in an industry cluster within local institutional systems are
conducted with the case of Dalian Software Park (DLSP) to testify the competitive
advantages of industry clusters for industrial development with substantial resources
rooted in local institutional systems.
1. Introduction
1.1 BackgroundIn recent years, ICT has been central to thediscussions
about economic
growthandperformance because it is pervasive and widely
diffused. China, with its high economic growth, hasalso experienced tremendous change in its ICTdevelopment and has achieved considerable
development in various sectors of ICT, particularlyin the development of the software industry. The
development history of the Chinese software
industry is not so long. In its short history, a distinct
industrial structure with two basic strategies
including development in domestic market andexport has been leading this effort. By stimulating
the domestic market demand and encouraging
software exports, software development resources
are expected to be improved in terms of quality andin turn, induce the further expansion of thedomestic market in this area and strengthen
competitive advantages of the industry. Rapid
development particularly with export-oriented
development strategy in Chinese software industry
induced dramatic increase in software outsourcing
from Japan to China, which in turn stimulated further
development of Chinese software industry leading toconstructing a co-evolutionary dynamism.
In the meantime, efforts have continued from thenational level to promote software related industry
clusters to realize the goals and achieve success inboth domestic and international markets. Since theearly 1990s, China has continually establishedmany software parks including 11 national software

industrial bases and 6 national software exportbases, which formed the overall planning andlayout of the Chinese software industry.
Consequently, the development environment of theChinese software industry has been dramatically
improved and the awareness about the competitive
advantages of these industry clusters has greatly
increased.
1.2 Objective
This paper attempts to firstly elucidate theco-evolutionary dynamism between Japan and
China through outsourcing as substitution ofsoftware development by means of Bass model.
Then, the institutional sources for the competitive
advantage of Chinese software parks would be
identified by taking the case of Dalian Software
Park (DLSP).
2. Co-evolutionary dynamism
2.1 Substitution dynamism
In diffusion trajectory, substitution dynamism
can be depicted as follows:∂V j
Psj∂ SW jSW xln= a + σ xj ln= a + σ xj ln
V
∂
SW j
Psx
x
∂ SW xwhere σ xj : elasticity of substitution from j to x.
When σ xj > 0, relatively lower software prices
in country X induces substitution of its softwaredevelopment for Japan’s software development
which implies that cheaper software production costin country X is the source of such substitution.

74

When σ xj < 0, relatively higher software prices incountry X induces substitution of its softwaredevelopment for Japan’s software development
which implies that higher functionality in country X
is the source of such substitution.
Based on the above equation, relative prices ofsoftware and software diffusion were figured out as
Figure 1 shows the trend in substitution of softwaredevelopment between China and Japan.

Diffusion trajectory of Japan’s outsourcing to
China (1990-2006) by means of Bass model isanalyzed as tabulated in Table 2.
Table 2 Diffusion Parameters in Printers, Software andWeb
Printer

Ln (SWc / SWln(SWj) c/SWj)

q

q/p

B(x)

5.43×10-3

5.82×10-2

10.7

0.03

LBP/BJ

1.47×10-3

2.90×10-2

19.3

-0.35

7.30×10-4

3.6×10-2

49.3

-5

-1

Software (J outsourcing to C)

2.8

-0.59

2004

2.6

China

[1] p

LLBP

2003
2.4

Web

2002

2.2

2001

2

3

Web 1.0

1.38×10

1.08×107.8×10-0.87

Web 2.0

0.25×10-5

0.55×10-1

22.0×103

-0.89

2000

1.8

1998
1999

1.6

1997
1996

1.4

1992 1995
1.2
1994
1993
-1

-0.8

-0.6

-0.4

-0.2

1
0

0.2

0.4

0.6

0.8

1

ln(Psj/Psc)ln(P sj/P sc)

Fig. 1. Trend in substitution of software development
between China and Japan (1992-2004).

Since structural change was observed between
the period before and after 2002, regression
analysis between the ratios of softwaredevelopment and relative prices was conductedtaking dummy variables reflecting such a structuralchange as follows:ln

Psj

Fig. 2. Conditions for sustainable FD.

Psj

SW x
= a + bD + σ xj 1 (1 − D) ln+ σ xj 2 D ln
SW j
Psx
Psx

where D: dummy variable (2002-2004 = 1, other years = 0).
Table

1

Elasticity of Substitution of Software
Development for Japan (1992-2004)
a

ｂ

σxj1

σxj2

adj. R2

DW

China

1.316
(77.20)2.847(6.50)

0.880(20.28)-2.100(-3.90)

0.991

1.96

USA

2.295
(36.78)-0.583(-2.36)0.852(4.58)-0.194(-0.62)

0.697

1.10

India

1.011
(9.94)

0.956(1.93)

0.684(2.97)-0.776(-0.88)

0.790

2.10

The result of Table 1 suggests that, since 2002,
Japan’s substitution depended greatly on China by
its higher functionality, not by cheap labor.
Consequently, absolute value of elasticity of
substitution dramatically increased leading to astrong inducement of the outsourcing of Japan’s
software development to China expecting its higher
functionality.

3. Analytical framework for analysis of DLSP
3.1 Introduction
Competitive advantage is now a popular termin many fields with the broader concept including
national, industrial and firm levels. In the book
“The
Competitive Advantage of Nations” written byPorter, he stressed the important role “played by anation’s economic environment, institutions andpolicies” for successful competitive industry
development. This part analyzed the competitive
advantage of industry clusters embedded in local
institutional systems within the macro context ofnational institutional systems based on the“diamond” model presented by Porter.
When comparing the main software parks thathave two identities as both a national level software
industry base and a software export base in China,
the software park in Dalian demonstrates particular
excellence in exports, which can be attributed to a

2.2 Functionality development
The functionality development (FD) is
generally defined as the ability to dramatically
improve performance of production process, goods
and services by means of innovation. In Bass model,
it can be depicted as
Y =As showed in Figure 2, q substitution for pmeans China substitution for Japan throughoutsourcing, which is similar to the relationship ofimitator and innovator as the relationship offollower and leader. With the change of imitator
substituting for innovator, open innovation andsustainable functionality development are focused
as important strategies. In software development,
China substituting for Japan through outsourcing is
the same as imitator substituting for innovator
leading to sustainable functionality development,
which is undoubtedly crucial for Chinese software
industry.

N (1 − e − ( p + a ) t )q −( p + q )t1+epwhere p: innovator; and q: imitator parameter.

75

geographical advantage in Dalian as well as a more
appropriate development strategy and industry
policies supported by the local government.
Similarly, compared with the 33% foreign firms inShanghai’s software park and 30% in Beijing’s
software park, DLSP demonstrates the highest rateof the foreign firms, which play significant roles in
inducing the clustering and learning effects. Thus,
under the clustering effects, firms from various
countries with different culture backgrounds andinstitutional systems stimulate and encourage aco-evolutionary development leading to thewin-win development. As a typical industry cluster,
the research on DLSP is very significant.

cooperation is driven by the local institutional
systems, which incorporate different importantfactor determinants of the “diamond” model
respectively. The local institutional systems seem tobe a “fertile soil” that promotes the growth of DLSP
as a mature industry cluster and determines its
competitive advantages.
3.4.1 Government
Unlike Silicon Valley, DLSP was initiallyestablished and organized by the local governmentand developed with government support. Though
Porter’s view was that government is only afacilitator, the government has been playing adecisive role in the establishment and developmentof DLSP with well-organized infrastructure
construction, top-down development guidance andsupportive policies. Factor conditions in the“diamond” model including physical, capital
resources and infrastructure can chiefly be
attributed to the support from the government. In
order to improve Intellectual Property (IP)protection awareness, the first IP service center in
China was set up in DLSP under the Dalian
government’s help. Similarly, corresponding to thelaws about private data protection in Japan, DLSP
also took early action to provide guarantee forJapanese customers. In a word, continued efforts
from the government lead to the achievement of
DLSP.

3.2 Methodology
By means of the “diamond” model and SWOT
(strength, weakness, opportunity and threat)
analyses, the local institutional systems leading to
the development of DLSP are analysed. The“diamond” model has been used as a framework forevaluating the competitiveness of regional
industries and elucidating local industry clusters. It
includes four important drivers as demandcondition, factor condition, related and supporting
industries, firm strategy, structure and rivalry.
SWOT refers to strengths (S), weaknesses (W),
opportunities (O) and threats (T). A SWOT analysis
is useful in analyzing firms’ strategic management
and identifying the level of firms in each respective
dimension. In general, the SWOT analyses provides
a much clearer map of the strengths, weaknesses,
opportunities and threats of DLSP, making it awareof its strategic position and indicating how tostrengthen its competitiveness.

3.4.2 Industry
The establishment of DLSP is for promoting
software industry development. Industry is thecore part of this endeavor and includes all parts of
the “diamond” model. In demand, rapid
development of ICT and informatization
construction provide huge domestic ICT markets
and the need for human resources has apull-through effect on the development of related IT
training industry, which results in more innovations
in traditional IT education at the universities. At theend of 2007, there were nearly 50 percent foreign
firms in DLSP including significant participation by
well-known multi-national corporations with Asian
operations. This can be ascribed to the uniquebusiness environment, rich development resources
and high potential for growth of DLSP. The
competition and cooperation among the firms is
considered to be another “virtuous self-propagating
cycle” bringing out more innovative ideas which inturn continues to stimulate industry dynamics.

3.3 Data collection
The majority of the statistical data used for the
analysis are from websites such as that for the
China Software Industry Association, and publisheddocuments such as the Annual Report of Dalian
Software and Information Service Industry andChina Statistics Yearbook on High Technology
Industry.
3.4 Diamond model analysis
In order to highlight the competitive
advantages of DLSP, the analysis was conductedfocusing on the three dimensional aspects ofgovernment, industry and academia in combination
with determinants of the “diamond” model. Since
all the determinants of the “diamond” model can bereasonably
summarized
into
these
three-dimensional
aspects,
this
kind
of
consideration for the analysis is appropriate. Withdetailed descriptions of supportive policies andstrategic actions in the three dimensional aspects, it
is noteworthy that the competitive advantages of
DLSP are rooted in the cooperation between
government, industry and academia. This

3.4.3 Academia
Thesoftwareindustry,asaknowledge-intensive industry, cannot develop wellwithout enough qualified human resources. The
basic role of academia is to guarantee theavailability of human resources as an importantfactor condition of the “diamond” model. Since the76establishment of DLSP, software related education
has been strengthened. In addition to the quantity,
the current educational system focuses significant
attention on the quality of graduates. Many private
training institutes and centers are pursuing a new
demand-oriented training model with more focus onpractice to supplement the traditional education. By
collaborating with firms, basic research in theuniversities has a more practical focus in software
research and development.
This not only
enhances the demand and reputation for theacademic institutions but also promote the firms’
capacity in the development of innovative products.

networks (with Japan) through outsourcing,domestic networks in industry clusters foroutsourcing leading to functionality development ofChinese software industry cannot be neglected. Bytaking the case of DLSP using qualitative datacollection and analyses, this paper identified theinstitutional resources of competitive advantages
for DLSP and provided insight into industrial
development. With the increasing awareness ofcompetitive advantage in an industry cluster forindustrial development and regional economics, thisresearch highlights the role of local institutions inthis competitiveness. Considering the determinantsof the “diamond” model, institutional sources are
categorized into government, industry andacademia vectors. After that, a SWOT analyses
pointed out areas for further improvement anddevelopment by identifying the strengths,
weaknesses, opportunities and threats faced by
DLSP. The success of DLSP as an industry cluster
is based on institutional resources including all theefforts from government, industry and academia. In
other words, DLSP is a very good model of a
localized cluster in which development is deeply
rooted in its local institutional systems. It turns out
to be a co-evolutionary development between
DLSP and the local institutional systems. Similarly,
DLSP displays its competitive advantages byencouraging networks among firms, integrating into
the international value chain of activities andimproving its reputation internationally. The
clustering effects of DLSP in utilizing an array of
resources from different firms, stimulate moreinnovation, and facilitate industrial and regional
economic development.

3.5 SWOT analysis
Following the “diamond” analysis summary of
the Dalian’s local institutional sources, the SWOT
analysis, supplements and extends the concept ofcompetitiveness to the general opportunities andthreats, providing further insight into DLSP.
SWOT also provides a mechanism for identifying
areas in which the existing institutional systems canbe improved. Strengths are the ways DLSP canobtain opportunities and face the existing threats. In
most cases, weaknesses are considered to be theopposite of the strengths, but are areas that existing
strengths cannot easily overcome. Strengths need
to be further improved; weaknesses should beovercome; opportunities need to be taken; andthreats should be changed to enhancecompetitiveness.
Though Dalian has a favorable geographicallocation, the increasing living cost is threatening thecost of human resources. Dalian’s attractivenessshould be strengthened both in hard aspects and soft
aspects like improved legal environment. In orderto guarantee the talent pool, traditional IT
educational institutions are challenged to focus
more on quality rather than quantity only. Whensome firms are playing the leadership role in thesoftware industry’s development, the performance
gap exists and sometimes widens in the park. The
problem is that many firms tend to pursue a popular
technology without previous experience in this area.
Thus, the formation of technology concentration
creates bottlenecks for developing competitive
advantage. Developing unique requisite technology(rather than everyone pursuing a similar
technological area) will diminish these bottlenecks
and reduce the performance gap making firms morecompetitive.

References
[1]
[2]

[3]

[4]
[5]
[6]
[7]

4. Conclusions
The paper firstly analyzed the co-evolutionary
dynamism and functionality development between
Japan and China through software outsourcing in amacro level and made the export-oriented strategy
and its role clear in the development of Chinese
software industry. Except the international

[8]
[9]

77

China
SoftwareIndustry
Association.
http://www.csia.org.cn
Michael EP. The Competitive Advantage of Nations– with a new introduction. New York: The Free
Press; 1990.
Doeringer PB, Terkla DG. Business strategy andcross-industry clusters. Economic Development
Quarterly 1995; 9:225-37.
Watanabe C. Science of Institutional Managementof Technology. http://www.me.titech.ac.jp/coe/.
DalianSoftwarePark.
Availablefrom
http://www.dlsp.com.cn/chinese/index.asp.
Japan
IT
Services
Industry
Association
http://www.jisa.or.jp/
Hung SC. Social construction of industrial
advantage. Technovation 2000; 20: 197-203.
Rogers EM. Diffusion of Innovation. The Free Pressof Glencoe, New York, 1962.
Mahajan V, Muller E, and Srivastara RK.
Determination of Adopter Categories by Using
Innovation Diffusion Models. Journal of Marketing
Research, 1990; 27: 37-50.

R&D and Profitability: R&D as A Turbulence Role to Profitability
Koji Moriyama**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
moriyama.k.aa@m.titech.ac.jp
Everywhere in the world, the gap between haves and have-not are big issue in foreign
affairs. At the same time, the gap between profitable firms and unprofitable firms areobserved and it is prominent in high technology industry. This observation suggests that
there is significant relationship between profitability difference and R&D efforts. This
paper created a simple model and conducted an empirical analysis. The result suggested
that the width of the gap in R&D has a positive impact on the width of gap in profitability.

1. Introduction
Innovation gathered the consciousness because of
the fierce competition amongst firms caused by the
globalization of the world economy and unity of themarket. Innovation is required for a company tosurvive in the market. R&D expenditure is regarded
as one of the significant sources of innovation. This
relationship between R&D and firms output, profit
have been discussed. Profitability is a index how
firms act efficiently. Firms are required to beefficient because of the limitation of resources like
employee, money, and time. In addition, firms areentity to which money was input and make a output
and it goes many fields such as internal financing,
dividends, payment to debt and so on. Even thoughprofit in financial statement is not the only one
absolutely valuable index, it can show thecomprehensive power firms have. So firms shouldseek high profitability. People will evaluate the firmby profitability.
Thinking of the relationship between R&D andprofitability, they can be linked in three different
ways (Branch, 1974).
First, successful R&D leads to new product andearn a profit. Second, some portion of profit isdistributed to R&D expenditure. Third, future
expectation for future profit opportunities can exert
R&D expenditure.
The different view from classical view of therelationship between R&D and profitability wassuggested in observing the distribution of
profitability. Observation of distribution of
profitability suggests that the higher the R&D
expenditure becomes, the higher the variance ofprofitability in a certain industry rise. That is, it issuggested that the effort for R&D across industry
seems to bring the width of profitability differencein the industry. The width of difference ofprofitability seemed to be caused by R&D effort.
The difference of profitability in industries has also

discussed in academic field (Demzets, 1973;
Mancke,1974;)
2. Literature Review
Determinants of firms R&D expenditure has been
researched for a long time by many researchers.
Some emphasize the demand factor (Grilliches,
1957; Scherer, 1982) and others emphasize
technology opportunity (Scherer, 1965; Rosenberg,1974) and appropriability (Levin et al. 1987). In
addition Cohen and Klepper (1992) suggested thatthe determinants of R&D are unobservable andprobabilistic factors are underlying.
Firm size and R&D effort has also discussed(Levin et al., 1987, Cohen and Klepper, 1996). Not
only the link between firm size and R&D effort but
also firm size and innovative performance is alsostudied. Damanpour (1992) insist that large firms
can access large realm of innovation or risky
projects which small firms cannot approach, while
Rotemberg and Saloner (1994) emphasize theadvantage of small firms because firms loseeffectiveness of its governance as firms becomelarge.
Many researches tackle on elucidation of therelationship between R&D and the productivity(Mansfield, 1980; Grilliches,1979; Grilliches, 1998).
Firms cannot decide when they can exploit the fruitof R&D and how much the demand is. In spite ofsuch a nature of R&D, some research proved thecontribution of R&D to Profitability by using R&D
as a stock and so on (Grabowski and Mueller. 1978;
Connolly, 1984; Grabowski and Veron, 1990).
Those support the legitimacy of R&D as a source
for the future growth.
Profitability is not only the result of R&D but also
one of the determinants of R&D. it is natural thatmanagers decide the expenditure in accordance withthe result of firms’ performance and the economic
environment including. They may increase the78

R&D expenditure for the future growth or therivals’ movement. Or they decrease R&D
expenditure because of the pessimistic future or
seeking for short term return. Some examined
whether profitability can be one of the determinantsof R&D. (Hundley et al., 1996; Grabowski, 1968).
The Relationship between innovation and firm
growth, profitability, size, and R&D intensity byusing interesting data (Audretsch, 1995; Geroski etal., 1993 ).
The difference of profitability in industries has
also discussed in academic field. As for the researchon the difference in profitability, Itami (2006)
surveyed the comparative analysis between USA
companies and Japanese companies and tried toreaveal the gap of profitability from many aspects
like intra-industry gap and its difference and international gap, He compare top comoanies in thosecountries and intraindustry gap in each country.
Shortly speaking USA has larger gap than Japan.
Demsetz (1973) argued that the profits of leading
firms in concentrated industries are due to theirgreater efficiency, and not to market power byconcentration. In addition, he warned the anti-trust
law because it deprive firms of efficiency.
McGahan and Porter (2002) argued that industry
and corporate-parent effects are important andrelated to one another. That is firm specific factors
are crucial. Business specific effects, which arise
from competitive positioning and other factors,
have a large influence on performance.

model of identifying the determinants is proposed.
The width of difference in profitability within
industry seems to be different across firms byobservation. The width of difference in someindustry is measured by the variance of profitability.
Although there might be much other measurement,variance is used because variance is well-known
and basic measure of statistical dispersion.
At first, the variance of inverse number of priceelasticity can be written as follows:
⎛ 1 ⎞
var⎜
⎟ = var(∏ ) + var(Ω ) + cov(∏, Ω )⎝ε ⎠pq

By the fact that current R&D rarely contribute atonce and variance of profitability and R&D
intensity is not so large so covariance between
profitability and R&D intensity can be assumed tobe 0. In addition inverse number of price elasticity
can be written as a function of R&D and ε andε are dominated by management skill andindependent of R&D effort. So (14) can be written
as follows:rqrc⎛ Ω −ε ⎞var(∏ ) = var⎜
⎟ − var(Ω )⎝ ε −ε ⎠⎛ 1 ⎞=⎜⎟ var(Ω ) − var(Ω )⎝ ε −ε ⎠
rq

rq

rq

rc

⎡⎛ 1 ⎞⎤= ⎢⎜⎟ − 1⎥ var(Ω )
ε
ε
−
⎠
⎣⎝
⎦
2

3. Model Development
Based on the Lee (2003), R&D intensity is decided
as follows:
R ε
1 ⎞
⎛
(1)
Ω=
=
+ ε ⎜1 −
⎟
pq ε
⎝ ε ⎠

rc

(5)
This illustrates that difference in profitability isdetermined by the difference in R&D effort in someindustry and those have positive relationshipbecause (1 ε − ε ) − 1 > 0 is positive.
This suggests that difference in profitability isdetermined by R&D effort. That is, R&D effort
seems crucial to profitability. If R&D effort iscrucial to profitability, on the basis of the fact thatR&D is determined by technological opportunity(Klevorick et.al,1995; Levin et.al, 1985; Angelmar,1985), it is implied that profitability also relates tothe technological opportunity. So one of the answers
to the difference in industry profitability is thedifferenceintechnologicalopportunity.
Technological opportunity is determined by thenature of technology. For example, electronics
require the knowledge of science, while textile orapparel industry does not. Therefore nature oftechnology is crucial to industry difference inprofitability across industries.

Rq q

Rc c

pq

rq

In this research, the link between R&D
expenditure and profitability will be consideredafter R&D expenditure was decided. Generally
profitability was measured by profit divided bysales. Therefore, profitability of firm i at theequilibrium is expressed as
cq
r
∏ ∏
=
= 1−
−
S
pq
pq pq
1
=
−Ω

ε

pq

(2)
If it is assumed that profitability is positive, theformula below has to be satisfied.

1 − (ε − ε ) − ε ε > 0
rq

rc

rc

pq

rc

2

rq

pq

(4)

(3)

rc

2

4. Empirical Analysis
Based on the simple model above empiricalanalysis was conducted. The financial data andProceeding to the difference in profitability, the79

R&D expenditure of firms can be obtained from the
NIKKEI NEEDS Database. Based on the data, thevariance and average of 3-digit industry level was
attained. In some 3-digit industry, there is only 1.
Therefore variance cannot be attained for thoseindustries. Owing to the limitation of space to show
all 3digit level industry, 2-digit level industry or insome case 3digit level industry was displayed. The
industries which belong to manufacturing industry
or information technology were selected because
R&D directly contributes to the firm profitability or
survival of the firms in those industries. In addition,
firms which have survived until the fiscal year 2005
in each industry were selected.
For empirical analysis, the model below will be
estimated. Size factor was introduced as control
variable.

big impact.
Table 1 Result of regression analysis (Industries are
divided into High tech and low tech industry with a criteriaof R&D intensity)

Var (Π ) = a + b var(Ω ) + c var(S ) + dS + e var(Ω ) × S

High Tech (R&D
intensity is 2%
and more than
2%)

Low Tech(R&D
intensity is lessthan 2%)

Coefficient

Coefficient

Constant-0.0438(-2.012)0.003982(2.181)

Var (R&D
intensity)

3.0517(3.341)14.9942(3.622)

Var (S)

2.03E-09(1.312)

6.7E-10(1.299)ln S

1.04E-06(0.153)

2.26E-06(0.805)

Var (R&D
intensity)
×ln S-0.0276(-3.074)-0.0472(-1.653)

2-digitindustry
dummy

includedincludedNumber ofobservation

50

60

Number ofgroups22

22

adj. R2

0.703

0.258

(6)

where S stands for stands for the industry. To
elucidate whether the behavior of high tech industry
and low tech industry are different or not, theestimate was conducted after divided into high techand low tech industries. The result is shown in table
1
Firstly, The variance of R&D is significantly
related to the variance of profitability.
The sales are not significant. It shows that width ofdifference in size doesn’t have significant effect on
the difference in profitability.
Interaction term of R&D and Sales is significant
and negative. This means that as size becomesbigger, the average of profitability is smaller.
The differences between high tech industries andlow tech industries are observed. The remarkabledifference is coefficient of variance of R&D
intensity. Te coefficient of high tech industries ismuch lower than that of low tech industries. This isconsistent with suggestion in determinants of R&D
intensity. Because R&D intensity has positive
correlation with ε − ε , ε − ε in high techindustries is higher than that of low tech industries.
So the coefficient predicted in mode (1 ε − ε ) − 1
is lower in high tech industries than in low techindustries.
It means that in low tech industries, the difference
in R&D effort has more effect on the difference inprofitability. But does this mean R&D is more
important in low tech industries than in high techindustries? Perhaps, it suggests that R&D is the key
to differentiate itself with others in low tech. The
R&D’s effect is bigger in low tech firms than inhigh tech firms. Nevertheless, it does not indicatethat R&D is important in low tech industry. In low
tech firms R&D is not regarded as crucial, so thedifference in making an effort to R&D may have
rq

rc

rq

a

5. Conclusion
Constructing a simple model, the determinants ofdifference in profitability was analyzed. It isobserved that the difference in effort to R&D is
crucial to the difference in profitability.
This can leads to the idea that profitability also
relates to the technological opportunity which isone of the determinants of R&D activity, and thentechnological opportunity is determined by thenature of technology. Therefore nature oftechnology is crucial to industry difference inprofitability across industries.
Although the difference in size does not havedirect influence on the difference in profitability, itaffect thorough the difference in effort to R&D
intensity. As average size becomes bigger, that is,market becomes more concentrated, difference in

rc

rq

rc

Numbers in parenthesis are t-value.

280

[12] Griliches, Z., Hybrid Corn: An Exploration in
the Economics of Technological Change.
Econometrica, 1957. 25(4): p. 501-522.
[13] Grilliches, Z., Issues in Assessing theContribution of Research and Development to
Productivity Growth. The Bell Journal of
Economics, 1979. 10(1): p. 92-116.
[14] Griliches, Z. R&D and Productivity: theEconometric Evidence, Chicago: University of
Chicago Press, 1998.
[15] Hundley, G., C.K. Jacobson, and S.H. Park,
Effects of Profitability and Liquidity on R&D
Intensity: Japanese and U.S. Companies
Compared. The Academy of Management
Journal, 1996. 39(6): p. 1659-1674.
[16] Itami, H. Corporate profitability in Japan andthe U.S. Tokyo: Yuuhikaku, 2006.
[17] Klevorick, A. K., R. C. Levin, R. R. Nelson,
and S. G. Winter, On the Sources andSignificance of Inter industry Differences inTechnological Opportunity. Research Policy,
1995. 24(2): p. 185-205.
[18] Lee, C.-Y., A Simple Theory and Evidence on
the Determinants of R&D. Economics ofInnovation and New Technology in Society,2003. 12(5): p. 385-395.
[19] Levin, R.C., et al., Appropriating the Returns
from Industrial Research and Development.
Brookings Papers on Economic Activity,
1987(3): p. 783-831.
[20] Levin, R. C., W. M. Cohen, and D. C. Mowery,
R&D, Appropriability, and Market Structure:
New Evidence on Some Schumpeterian
Hypotheses. American Economic Review ,1985.
75(2): p. 20-24.
[21] McGahan, A., M., and M., E., Porter, What Do
We Know about Variance in Accounting
Profitability?. Management Science, 2002.
48(7): p. 834-851.
[22] Mansfield, E., Basic Research and Productivity
Increase in Manufacturing. American
Economic Review, 1980. 70(5): p. 863-873.
[23] Rosenberg, N., Science, Invention andEconomic Growth. The Economic Journal,
1974. 84(333): p. 90-108.
[24] Rotemberg, J.J. and G. Saloner, Benefits ofNarrow Business Strategies. American
Economic Review, 1994. 84(5): p. 1330-1349.
[25] Scherer, F.M., Demand-Pull and TechnologicalInvention: Schmookler Revisted. The Journalof Industrial Economics, 1982. 30(3): p. 225237.
[26] Scherer, F.M., Inter-Industry Technology
Flows and Productivity Growth. The Review of
Economics and Statistics, 1982. 64(4): p. 627634.

R&D effort has smaller effect on difference inprofitability.
High tech industries and low tech industries has
difference in the effect of difference in R&D effort
to the difference in profitability. It may besurprising that in low tech industries, the effect of
R&D is bigger. This may suggest that R&D isimportant even in low tech industries.
The capability of utilizing R&D as a source ofprofitability, management skill is important. The
difference in profitability seems to stem mainly
from the skill of firms. But averaging the skill byusing many datasets, this research may reached thetip of the iceberg.
6. References[1] Angelmar, R., Market Structure and Research
Intensity in High Technological Opportunity
Industries. Journal of Industrial Economic,
1985. 34(1): p. 69-79.
[2] Branch, B., Research and Development
Activity and Profitability: A Distributed Lag
Analysis. The Journal of Political Economy,
1974. 82(5): p. 999-1011.
[3] Cohen, W.M. and S. Klepper, The Anatomy ofIndustry R&D Intensity Distributions.
American Economic Review, 1992. 82(4): p.
773-799.
[4] Cohen, W.M. and S. Klepper, Firm Size andthe Nature of Innovation within Industries: The
Case of Process and Product R&D. The Review
of Economics and Statistics, 1996. 78(2): p.
232-243.
[5] Connolly, R.A. and M. Hirschey, R & D,
Market Structure and Profits: A Value-BasedApproach. The Review of Economics andStatistics, 1984. 66(4): p. 682-686.
[6] Demsetz, H., Industry Structure, Market
Rivalry, and Public Policy. Journal of Law andEconomics, 1973. 16(1), pp. 1-9.
[7] Damanpour, F., Organizational Size andInnovation. Organization Studies, 1992. 13(3):p. 375-402.
[8] Geroski, P., S. Machin, and J.V. Reenen, The
Profitability of Innovating Firms. The RAND
Journal of Economics, 1993. 24(2): p. 198-211.
[9] Grabowski, H.G. and D.C. Mueller, Industrial
Research and Development, Intangible Capital
Stocks, and Firm Profit Rates. The Bell Journalof Economics, 1978. 9(2): p. 328-343.
[10] Grabowski, H.G., The Determinants ofIndustrial Research and Development: A Studyof the Chemical, Drug, and Petroleum
Industries. The Journal of Political Economy,
1968. 76(2): p. 292-306.
[11] Grabowski, H. and J. Vernon, A New Look at
the Returns and Risks to Pharmaceutical R&D.
Management Science, 1990. 36(7): p. 804-821.

81

Decisive Factors for Firms’ Sustainable Functionality Development
Koji Moriyama**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
moriyama.k.aa@m.titech.ac.jp
Japan’s required strategy is that FD (Functionality development) induces higher MPT. The
learning efforts for self-propagating assimilation capacity essential to sustainable
functionality development (FD) is required for profitability in innovation environment
nowadays. This research developed models and proposed the condition for sustainable FD. Thissuggests to firms the strategy for high profitability that learning from others is critical.

1. Introduction

Diffusion has gathered interest of many
researchers. Diffusion can be observed in many
fields. The pioneer work is research by Rogers(1962). Rogers also identified four main elements inthe diffusion of innovations: innovation features,
communication channels, time, and social system.
This diffusion process is actually quite similar tothe contagion process of an epidemic disease.
Grilliches (1957) implemented S-shaped growth.
Grilliches estimate the diffusion of hybrid corn.
This process is well modeled by the simple logistic
growth function, an epidemic function which was
first introduced by Verhulst in 1845 (Meyer, 1994).
Since the logistic growth function has proved useful
in modeling a wide range of innovation processes, anumber of studies applied this function in analyzing
the diffusion process of innovations as well (e.g.
Griliches, 1957; Metcalfe, 1970). As well as thelogistic growth function, “Gompertz curve” and“Weibull curve” has been used to analyze diffusion
process (e.g., Dixon, 1980).
Watanabe and Asgari (2004) analyzed the
dynamic interaction between learning effort andfunctionality development, and demonstrated thatfunctionality development increases as learning
increases leading to a virtuous cycle.

Because of low birthrate and an aging population,
the Japan’s required strategy is that FD(Functionality development) induces higher MPT:
MPT =

1 ⎞
∂S
⎛
= aS ⎜1 −⎟∂T⎝ FD ⎠(1)

While FD can be measured by the raito of thecarrying capacity (K(t)) of the diffusion trajectory(upper limit of thetrajectory) and the level ofdiffusion (S(t)), carrying apacity can be enhanced
by learning ( λ )leading to enhanced FD (= K (t) /S(t), Watanabe and Asgari (2004))1.
This research focuses on the condition for firms toattain sustainable development which is required
for firms to survive ahd accoplish high profitability
in the open innovation environment.

2. Literature Review
1

1. Dynamic learning coefficientλ (t ) = α + β 1t + β 2 t 2

⎞ ⎛
⎛
bk
a k bk ⎞⎟ t − a h bh t 2= ⎜⎜ b ++ a h ⎟⎟ − ⎜⎜ ba +1 − ak / a
1 − a k / a ⎟⎠⎠ ⎝⎝2. Dynamic carrying capacity incorporating learning
coefficients.

K (t ) =3. Model Development
3.1 Necessary Condition for
Functionality Development

Kk

1 + bk e − ak t + [a(a + 2a h t )]bh e ah t

2

Sustainable

In order to investigate the condition of utilizationof external R&D resources for functionary
development (FD), gross technology stockformulation dynamics model was developed.
Given that technology stock T increases
proportional to t, by utilizing diffusion function, T

3. Logistic growth within a dynamic carrying capacity
Kk
S (t ) =2bke − ak t + bh e aht
1 + be − at +1 − ak / a⎛dS (t )S (t ) ⎞⎟⎟= aS (t )⎜⎜1 −dt⎝ K (t ) ⎠82

and FD can be depicted as follows2:Y=N,
1 + be − aT

z=

(2)

n

n

∑ [1 + b (1 − a T )] ≡∑ FD (T )
j

j

j =1

j

(3)

j =1

where Y : production of innovative goods ; N :carrying capacity; a and b: coefficients representing
diffusion velocity and initial stage of diffusion,respectively; and a j =(5)

As demonstrated in Fig. 1, FD function can be
developed to multi-logistic growth model as afunction of gross technology stock which consists ofindigenous technology stock and assimilated spillover
technology.

FD = N / Y = 1+be -aT ≈ 1+b (1-aT)
=

T
1
⋅ id
∆Ts Ts T s
1+∆Tid Tid

3

Level of gross technology stock (T)increases in a cascading way depending on
assimilation capacity (z)T =T + z TTab⋅ Pj , [b − (n − 1)]⋅ Pj ,
bj

i

3 s

N

Y (T3 )

T = Ti + z 2Ts
N/2

T3
T2

n

N
3+ 3

T1

T = Tid + z3Ts T > T > T
Y (T )) zT
T =TTid= T+Yz(T+2Tof diffusions Levelwhen FD emergest+zT
T =tT3 Tt2id=tT
+
z
T
1 s
Assimilation
capacity induces
1
T = T + earlierz T FD development.
3

T = Ti + z1Ts

∑ Pj = 1 and FD j (T ) = a + b j (1 − a j T ) .

Ti

j =1

2

1

2

id

1

1

s

id

2

s

id

3

s

Fig. 1. Acceleration of FD emergence depending on
assimilation capacity.

Gross technology stock T can be depicted asfollows:
T = Tid + zTs

Timing of FD emergence is accelerated
as T increases induced by assimilation
capacityY

As illustrated in Fig. 2 since level of T increases ina cascading way depending on assimilation capacityz, and timing of FD emergence is accelerated as T
increases, level of FD can be classified as
decreasing FD, constant FD and sustainable FDdepending on assimilation capacity. Selfpropagating assimilation capacity increase leads tosustainable FD.

(4)where Tid : indigenous technology stock; Ts :technology spillover pool, and z: assimilation
capacity. z can be depicted as follows:

Indigenous technology stock2

The gross technology stock is measured by Grilliches(1980) :Tt = Rt − , + (1 − ρ )Tt −1

Assimila ted spillover technology

T = Tid + zTs

Gross technology stockz ≠ 0 (Multi-logistic growth)z = 0 (Simple logistic growth)

Self-propagating
Z increasedz/dTid > 0

dz/dTid = 0
Decreasing FD

where Tt : technology stock at time t; Rt : R&D
investment at time t; m: lead-time between R&D andcommercialization; and ρ : rate of obsolescence oftechnology.
Tt can be expressed by the following equation at theinitial period:
T0 = R1−m (ρ + g )where g : growth rate of R&D investment at the initialperiod.
Thus,
Tt = Rt +(1−m ) (ρ + g ) , Tt −1 = Rt −m (ρ + g )Sustainable FD

Constant FD

Y

Y

Y
Y

N
3+ 3

N1
3+ 3

t

ln(2 − 3 )baln( 2 − 3 )b1
a1ln(2 − 3)b2
a2

Y1

N2
3+ 3

t

N1
3+ 3

3+ 3

FD 1

t

Y1

ln( 2 − 3 )b1
a1

tln(2 − 3 )b2
a2

FD

FD

3+ 3
FD

t

Y2

FD

FD

FD

Y

Y

Y2

N2
3+ 3

t1

3+ 3

FD 2

t2

FD 2 = 1 + b 2 exp( − a 2 T ( z 2 ))FD 1 = 1 + b 1 exp( − a 1T ( z 1 ))t

t1

t2 t2 /

t

Fig. 2-16. Comparison of growth trajectory between
simple and multi-logistic growth.

Given the average growth rate of Tid and Ts
g id , g s , and their ration w,

Tid = Tid 0 e g id t , Ts = Ts 0 e g s t and

and

g id
=w
gs

(6)

where Ti 0 and Ts 0 : initial level of Tid and Ts ,respectively, and t: time trend.
z in equation (5) can be developed as follows:1− ρt −m 1 + g.
Rt −m = R0 (1 + g )ρ+g
ρ+gGiven that g << 1 and ρ and g are stable, as:Tt = Rt −m +Tt ≈ R0 (1 − mg + gt )(1 + g ) (ρ + g ) = α + β t

1+ g
1+ g
and β = R0 g
.
ρ+g
ρ+g
Therefore, proportional relationship between grosstechnology stock T and t can be observed as depicted byabove.

where α = R0 (1 − mg )3

Timing of FD emergence corresponds to the timing thatmaximizes the secondary derivative of the diffusion
trajectory, and its level is 3 + 3 (Rogers, Mahajan, Moore)

83

z=

g t
T
w Tid 0 g s (w−1)t1
w Tid 0 e id
⋅ id =⋅=⋅e
gs t
g s T s 1 + w Ts 0 e
1 + w Ts 01+
gi

Gross technology stock in firm i can bedepicted as follows:

(7)
dz
dz dt
= ⋅
dTid dt dTid

Ti = (Tid )i + z i (Ts )i , (Ts )i =n

∑ (T )
id

j

(4’)

j =1
j≠i

(8)

As illustrated in Fig. 4, sustainable
functionality development (FD) condition canbe depicted as follows:

From equation (7)Tdz
w Tid 0w(w − 1)g s (w − 1)e g s (w−1)t ==⋅⋅ g s ⋅ id 0 e g s (w−1)t dFD
dz
>0 ⇔
>0
dt 1 + w Ts 0
Ts 0
1+ w
dt
dTid

(15)

(9)

As demonstrated by the preceding analysis,
this condition can be developed as follows:dz> 0 whendtw(w − 1)⋅ gs > 0
1+ w

Since

∆T
∆T
dz
> 0 ⇔ id > s
dTid
Tid
Ts

(10)

dTid
dt
> 0 when g id > 0= Ti 0 g i e g id t ,dTiddtThis implies that within the dynamic game ofinter-firm technology spillover, those firms that
can increase their indigenous technology fasterthan their competitors only be able to maintainsustainable FD. Since FD is ability to improve
perforrmance of production processes, goods
and services of innovation, those firms that can
provide such goods and services better (e.g.,earlier,higherquality)than
their
competiterscan only secure customers thereby
mainteinaco-evolutionary
dynamismproduction, innovation and FD advancement
leading to sustainable FD. Equtaion (16)provides a reasonable rationale to thiscompetitive game in the market.

From equations (9) and (10),dz> 0 when
dTid

(11)

w(w − 1)⋅ g s > 0 and g id > 0
1+ w

(12)

Necessary condition for sustainable FD can be
identified as inequalities (9) and given that g id > 0
and g s > 0 , it can be identified as follows:w(w − 1)
>0
1+ w

(16)

(13)

4. Empirical Result

Since

Fig. 3 illustrates the spillover dynamism.
Technology spillover emerges in accordance withthis dynamism,.

g
w = i > 0 and w − 1 > 0 , g id > g s
gsThis impliesnTs = ∑ Tid j∆Tid ∆Ts
>
>0
Tid
Ts

i =1
i≠ j

Technology spillover pool

(14)

( Tid ) i
Indigenous
technology stock

Fig. 3. Technology spillover dynamism.

3.2

Therefore,

Co-evolutionary Domestcation for
Sustainable Functionality Development
84

when

∆Tid ∆Ts
>
>0
Tid
Ts

,

dz
> 0 which means self-propagating z increase
dTid

0.4
0.38
0.36
0.34
0.32
0.3
0.28
0.26
0.24
0.22
0.2

leads to sustainable functionality development (FD).
In order to examine the sustainability oftechnology development in group IV firms, thegrowth rate of indigenous technology stock (and technology spillover pool (

∆Tid
),
Tid

∆Ts
) over theTs

5. Conclusion
Canon which accomplish high profitability has
conspicuous position in terms of sustainable
functionary development and DAST. This suggeststhat the learning efforts for self-propagating∆Tid). This demonstrates that Canon
Tid

assimilation capacity essential to sustainable
functionality development (FD) is required for

conduct significant more cumulative learning thanthe other rival firms. The increased learning
coefficient enhances functionality development
leading to an increase in MPT (Marginal
productivity of technology) and subsequent TFP(Total factor productivity) growth. Firms which

profitability in innovation environment nowadays.
This research ]suggests to firms the strategy forhigh profitability that learning from others is critical.
6. References∆Tid ∆Ts>> 0 are able tosatisfy the condition
Tid
Ts

[1]

utilize the mechanism. On this mechanism further
analysis will be conducted in following section.

[2]

0.1
0.09
0.08

∆Tid Tid

[3]

0.07
0.06
0.05

zTs
Tid + zTs

Fig. 5. Comparison of the DAST (Dependency on
assimilated spillover technology) (1996-2005).

period 1996-2005were computed as compared inFig. 2-18.
Looking at Fig. 4, we note that Canon maintains
the highest growth rate of indigenous technology
stock (DAST＝

∆Ts Ts

0.04
0.03

[4]

Fig. 4. Comparison of the satisfaction of sustainable
functionary development condition leading toleading technology-based firms (1996-2005).
a
Seiko Epson was excluded because it was listed inTokyo exchange in 2003 and available data was notenough.

[5]

Fig. 5 illustrates the DAST (Dependency on
assimilated spillover technology) of major firms inleading technology-based firms. This index iscomputed as assimilated spillover technology
divided by gross technology stock. This index
indicates how well external resources are used in
the firm. It is observed that Canon utilize external
resources conspicuously well.

[6]
[7]
[8]

85

Dixon, R., 1980. Hybrid Corn Revisited,
Econometrica 48 (6), 1451-1461.
Griliches, Z. 1957. Hybrid Corn: An
Explorationinthe
EconomicsofTechnological Change. Econometrica 25 (4),501-522.
Mahajan, V., Muller, E., and Srivastara, R.K.
1990. Determination of Adopter Categories
by Using Innovation Diffusion Models.
Journal of Marketing Research 27, 37-50.
Metcalfe, J.S., 1970. The Diffusion of
Innovation in the Lancashire Textile Industry.
Manchester School of Economics and Social
Studies 2, 145-162.
Meyer, P.S. and Ausbel, J.H., 1999. Carrying
Capacity: A Model with Logistically Varying
Limits. Technological Forecasting andSocial Change 61 (3), 209-214.
Moore, G.E. 1965. Cramming MoreComponents onto Integrated Circuits,
Electronics 38 (8), 1-4.
Rogers, E. M., 1962. Diffusion of Innovations.
The Free Press of Glencoe, New York.
Watanabe, C., Asgari, B. 2004. Impacts offunctionality development on dynamism
between learning and diffusion of technology.
Technovation 24 (8), 651-664.

Comparative Analysis of Diffusion Trajectory of Plasma TV between
Japan, Korea and Taiwan’s Companies
SHIN Jae-Ho**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-49 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANjhshin@ml.me.titech.ac.jp
The Plasma TV industry recently achieved conspicuous development within Japan,
Korea and Taiwan. As of 2005, Japan and Korea occupied an enormous 90% market
share of plasma TVs. On the basis of comparative analysis about plasma TVs, thisresearch attempts to identify factors contributing to the co-evolution within theinstitutions. Through an empirical analysis, the unique institutional structures will bedemonstrated. By measuring the dynamic learning coefficient, which represents themarket learning effects, diffusion trajectory can be interpreted, and through comparing
dynamic carrying capacity of diffusion process, structural sources can be interpreted.

characteristics of plasma TV from 2002 to 2005.
We can also observe the unique plasma TV industry
among Japan, Korea and Taiwan by measuring the
cumulative shipment.

1. Introduction
The objective of this research is to elucidate
dynamic interaction between diffusion process andlearning effect of plasma TVs between Japan,
Korea and Taiwan’s companies.
The plasma TV industry recently achieved
conspicuous development within Japan, Korea andTaiwan. As of 2005, Japan and Korea occupied anenormous 90% market share of plasma TVs. It was
initially Japan that developed and launched theplasma TVs into the global market but in the fourth
quarter of 2004, the total shipment of plasma TVs
was reversed for the first time. On the basis ofcomparative analysis about plasma TVs, thisresearch is focuses on identifying factors
contributing to the co-evolution within theinstitutions. Through an empirical analysis, theunique institutional structures will be demonstrated.
Comparing with LCD (Liquid Crystal Display)industry, PDP (Plasma Display Panel) industry has
no distinct competitor because of the short period ofcommercialization and its restrictive demand. It was
early simplified through the withdrawal of PDP
business from Fujitsu, the undertaking of NEC’s
PDP business sector by Pioneer and market
expansion through aggressive investment from
Korea’s companies. Therefore, the market
competition’s structure was reorganized among
Matsushita, Samsung SDI and LG electronics since
the end of 2004, and more intensive competition is
expected to be.
In the case of Matsushita, its capability
concentrates on the PDP business and makes fulluse of the production of majority PDP panels into
its own PDP TV. Figure 1 demonstrates the

Taiwan

100%

80%

Korea

60%

40%

Japan

20%

0%

02.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

Fig. 1. Total Ration of Cumulative Shipment of
Plasma TV in Japan, Korea and Taiwan(2002-2005; 16 quarters).

2. Diffusion Trajectory
2.1 Analytical Framework
In this research, the diffusion trajectory can beanalyzed with dynamic carrying capacity as
illustrated in equation (1).
f (t ) =KKb ⋅ aK
1 + a ⋅ exp (− bt ) +exp (− b K t )b − bK(1)

When aK = 0, equation (4) is a general functionof the epidemic behavior encompassing a simple
logistic growth function, and the ratio of aK and a(aK /a) indicates the degree of non-SLF (simple
logistic growth function) structure (degree offunctionality). For data construction, depreciation
rate ρ can be treated as a reverse of the life time andcumulative shipment also can be measured by thefollowing equation:86

Shipment (1,000 sets)

6000

S t = C t + (1 − ρ )S t − 1

(2)

S0 =

C1
(g + ρ )

(3)

ρ=

1
LT

(4)

)
(1 000

2000

1000

1000

0

Shipment (1,000 sets)

Carrying capacity

2500
2000

Actual1500

Estimate

1000
500

Through this result, cumulative shipment
exhibited a dramatic increase among the threecompanies and changed slow down. However, it
still maintains sustainable increase over the period
examined. Table 1 compares the factors
characterizing carrying capacity structure of plasma
TV in three countries.
Table 1 Comparison of Factors Characterizing
Carrying Capacity Structure of Plasma TV
in Each Companies

02.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

Fig. 2. Cumulative Shipment of Plasma TV in Japan,
Korea and Taiwan’s Companies (2002-2005; 16
quarters).

Country

Based on the above Fig. 2, Samsung SDI
exceeded the cumulative shipment of Matsushita in
the fourth quarter of 2004 for the first time. This
result was caused by the institutional uniqueness of
Samsung SDI and these are as follows: (i) verystrong supply oriented; (ii) professional display
oriented company; (iii) technology innovation by
world’s first glass cutting development and world’s
largest size plasma TV development in 2004.
Results of the analysis on the trends in the
diffusion process of plasma TV over the period
2002-2005 by using dynamic carrying capacity
depicted by equation 1 are illustrated in Figure 3.

Japan

Velocity ofDegree ofYear toDiffusion

Functionality

Reach

b

aK/a

bK/b

ln aK / bK

Matsushita

0.251

0.207

0.851

11.7

FHP

0.313

0.595

0.516

23.6

Pioneer

0.179

0.089

0.603

25.8

NEC

0.487

0.229

0.233

33.9

0.387

0.739

0.840

9.9

LG

0.344

0.329

0.911

6.4

Formosa

0.187

0.009

0.663

26.8

CPT

0.507

0.256

0.354

22.9

Company

Samsung

SDI

Korea

TaiwanThe functionality development concept can bematerializedbycorrelating
technology
elasticity to sales as well as logistic growth within adynamic carrying capacity which depicts the
diffusion of technology and its dynamic carrying
capacity that represents the state of the functionality
development (Watanabe et al., 2002). Table 1
interprets the institutional structure affecting thedifferences of these carrying capacity structures in

8000
7000
6000

Carrying capacity
Estimate

4000

3000

Fig. 3. Carrying Capacity of Plasma TV in Matsushita,Samsung SDI and LG (2002-2005; 16 quarters).

NEC
Formosa
CPT

500

3500

02.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

LG
Pioneer

1500

Shipment (1,000 sets)

Actual2000

0Samsung SDI
Matsushita
FHP

2500

Shi

Estimate

Carrying capacity

3000

02.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

3000

3000

4000

0

St: cumulative shipment at time t; Ct: annual
shipment at time t; g: increase rate of shipment in
the initial period; ρ: depreciation rate and LT: life
time.
Generally, life span is defined as the period
until the brightness of the screen is diminished by
50%. With this application, the life time of plasma
TV is over 60,000 hours. By means of the above
equation and understanding, we can analyze thecomparative study of each company amongst thethree countries. Trends in cumulative shipment ofplasma TV over the period 2002-2005 (16 quarters)
classified by each company and based on the above
approach are illustrated in Figure 2.

5000

5000

Actual2000
1000
002.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

87

Japan, Korea and Taiwan. Furthermore, Figure 4
demonstrates the highest degree of the functionality(bK/b) and the lowest degree of the year to reach (t#)
among the top three companies such as Matsushita,Samsung SDI and LG electronics. These top threecompanies also have common technology
innovation, such as: (i) glass cutting technology; (ii)the effort of reduction of glass thickness from
2.8mm to 1.8mm; (iii) technology innovation
through world’s largest size plasma TV
development year by year, respectively.
In addition, they show their mutual inspiration
through the patent litigation and technology
innovation.

Degree of functionalitybK
bTable 2 Comparison of Learning Coefficient of Plasma TV in
Japan, Korea and Taiwan’s companies(

P: price; S: sales; t: time trend.

Company

lnA

a0

a1

a2

a3

a4

a5

Matsushita

1.89

0.418

-0.1220.035-4.0*10-3

2.5*10-4-4.9*10-6(3.81)(2.79)(-3.79)(3.83)(-3.61)(3.23)(-2.82)2.12

2.7*10-3-3.3*10-4

1.1*10-5(2.61)(4.36)(-3.69)(3.19)

FHP

1

MAT

SAM

0.8

LG
PIO

0.6

FOR

bK
ln aK
= 1.048 − 0.022
bbK(3.95) (-8.21)

Pioneer

3.02

0.048

-5.9*10-3

1.9*10-4(24.8)(3.81)(-3.77)(3.26)

DW

adj R2

2.71

0.974

2.26

0.700

1.69

0.887

1.51

0.840

2.80

0.808

2.39

0.700

2.18

0.947

2.72

0.947

adj R2 0.708

FHP

NEC

0.4

CPT

0.2

)

ln P = ln A − a 0 + a1t + a 2 t 2 + a 3 t 3 + a 4 t 4 + a 5 t 5 ln S

2.45

0.265

-0.0630.015-1.3*10-3

3.4*10-5(7.82)(2.61)(-3.17)(3.53)(-3.58)(3.39)

1.02

0.813

-0.1330.016-1.0*10-3

2.5*10-5(1.75)(3.18)(-2.95)(2.53)(-2.27)(2.14)

2.09

0.199

-0.002-2.5*10-4-6.5*10-5

3.9*10-6(0.26)(2.49)(-2.35)(-2.42)(-2.48)(2.50)

1.98

0.871

-0.2790.077-0.011

6.3*10-4-1.4*10-5(4.73)(2.32)(-2.93)(2.58)(-2.54)(2.49)(-2.43)

2.44

0.567

-0.2350.063-8.0*10-3

4.6*10-4-9.6*10-6(15.6)(2.59)(-3.25)(3.51)(-3.51)(3.36)(-3.18)NEC
Samsung
SDI

0
0

10

20

30

40

50

ln

aK
bK

LG

Fig. 4. Degree of Functionality of Plasma TV in
Each Companies (2002-2005; 16 quarters).
Formosa

3. Learning Effect
3.1 Analytical Framework
By measuring the dynamic learning coefficient,which represents market-learning effects, diffusion
trajectory can be interpreted. Learning effects canbe captured by the following equation.
P = AY− λCPTLearning is remarkable for complex products or
special usage method and market learning can be
defined as a series of learning process of production,
distribution and utilization.

(5)

Taking the logarithm of equation (5):Dynamic learning coefficient

0.4nln P = ln A − ∑ ai t i ln Y

(6)

i=0

Since learning coefficient λ is a function of
successive
coefficientsduringproduction,
distribution and utilization phases in theirdissemination process, these coefficients can bedepicted as a function of time trend t as:nλ (t ) ≈ ∑ ai t i(7)

λ (t ) = 0.418 − 0.122t + 0.035t 2 − 4.0 × 10 −3 t 3 + 2.5 × 10 −4 t 4 − 4.9 × 10 −6 t 5

0.3

0.2

0.1

Matsushita
002.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

0.8

Dynamic learning coefficient

i =0

Stimulated by these understandings andprompted by a concept of learning effect, theanalysis of the dynamic learning coefficient
between Japan, Korea and Taiwan’s companies aredemonstrated in Table 2.

88

0.7

λ (t ) = 0.813 − 0.133t + 0.016t 2 − 1.0 × 10 −3 t 3 + 2.5 × 10 −5 t 4

0.6
0.5
0.4
0.3
0.2
0.1

Samsung SDI

0

02.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

Dynamic learning coefficient (λ)

0.3

4. Conclusion
Samsung’s noteworthy cumulative shipment
lead to improvement of learning capacity and thenincrease in functionality development due tolearning effects. On the basis of above, we canobserve the flow of virtuous cycle.
Through
uniqueinstitutional
structure,
Samsung accelerates learning effort and that
became motivation for Matsushita throughinspiration. In the case of mutual inspiration,
among leading companies, we can consider theincrease in shipment, technology improvement(world’s largest plasma TV) and patent litigationeach other as an example of it.

λ (t ) = 0.20 − 0.002t − 2.49 × 10 −4 t 2 − 6.5 × 10 −5 t 3 + 3.9 × 10 −6 t 4

0.25
0.2
0.15
0.1

LG

0.05
0

02.1Q 02.2Q 02.3Q 02.4Q 03.1Q 03.2Q 03.3Q 03.4Q 04.1Q 04.2Q 04.3Q 04.4Q 05.1Q 05.2Q 05.3Q 05.4Q

Fig. 5. Trend in Dynamic Learning Coefficient of
Plasma TV among Top Three Companies.

By measuring dynamic learning coefficient,which represents market learning effects, diffusion
trajectory can be interpreted. Figure 5 demonstrates
the decreasing trend of dynamic learning coefficientamong the top three companies.
On the basis of own empirical analysis,correlation between sales of plasma TV and prices
in Samsung SDI are illustrated in Figure 6.

(i) Samsung SDI can be attributed to rapid
diffusion and market learning effects comparedwith other companies, which originated from theincreasing level of cumulative shipment andaccelerating learning effect.
(ii) Samsung SDI’s co-evolutionary virtuous
cycle through co-evolution between activation inplasma TV development and dynamic carrying
capacity accelerated enhancing functionality
development with learning effect.

Dynamic learning coefficient

1.4

1.2

λ (t ) = 0.813 − 0.133t + 0.016t 2 − 1.0 × 10 −3 t 3 + 2.5 × 10 −5 t 4

1(iii) Samsung SDI’s conspicuous figures can be
attributed to unique dynamic interaction between
diffusion and learning.

0.8

0.6

2005. 2Q

0.4
0.2

ActualEstimate0

References

02.1Q
02.2Q
02.3Q02.4Q
03.1Q03.2Q
03.3Q
03.4Q04.1Q
04.2Q
04.3Q04.4Q
05.1Q05.2Q
05.3Q
05.4Q06.1Q
06.2Q
06.3Q06.4Q
07.1Q07.2Q
07.3Q
07.4Q

Fig. 6. Trend in Dynamic Learning Coefficient of
Plasma TV in Samsung SDI (2002-2007; 24
quarters) - Actual (2002-2005; 16 quarters) and extended[1]

C. Watanabe, B. Asgari, 2004. Impacts ofFunctionality Development on Dynamism
between Learning and Diffusion ofTechnology, Technovation 24 (8) 651-664.

[2]

C. Watanabe, J. Y. Hur and S. Lei, 2006.
Converging Trend of Innovation Efforts inHigh Technology Firms under Paradigm ShiftA Case of Japan’s Electrical Machinery,
Omega 34 (2) 178-188.

[3]

Y. H. Hahn, P. I. Yu, 1999. Towards a New
Technology Policy: The Integration ofGeneration and Diffusion, Technovation 19(3) 177-186.

[4]

J. D. Choi, 2006. A Menace to Status of
Korea’s Display Industry. LG Economic
Research
InstituteWeeklyEconomy,http://www.lgeri.com[5]

Y. Nakane, 2004. LCD Industry Outlook,
Deutsche Bank .

estimate (2006–2007; 8 quarters) by the above learning effectequation.

The PDP industry is a very noteworthy thatboth supply and production are almost
accomplished between Japan, Korea and Taiwan.
Not only plasma TV but also LCD or other displaysin the world market prominently dominated bythose countries. For instance, as Khan (1998)
pointed out, Korea’s success in the area ofelectronics over the past 20 years, mainly camefrom its learning process through target-oriented
policy towards export.
In the case of Samsung SDI, learning effectsupports this result and it induces the broad
opportunity of diffusion process and also
accelerates the dramatic increase in cumulative
shipment of plasma TV.

89

Patent Analysis of Plasma TV
between Japanese and Korean Companies
SHIN, Jae-Ho**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANshin.j.aa@m.titech.ac.jp
The Plasma TV industry recently achieved conspicuous development within Japan,
Korea. On the basis of comparative analysis about plasma TVs, this research attempts to
identify factors contributing to the co-evolution within the institutions. Through an patent
analysis, outstanding performance amongst the leading companies will be demonstrated.
By measuring the patent activity index (PAI), which represents the patent activity of eachcompany among others, technological innovation can be interpreted.
This research, of course, has a point ofcomplement and improvement. However, theobjective of this research attempts to look at thetrend of each company's technological development
and strategy through the appicated patent counts.
Based on this methodology using the search period,
search formual and target companies, we can also
observe the outstanding performance amongst the
top tree companies, such as Matsushita, Samsung
SDI and LG, as illustrated in Figure 1.

1. Introduction
The PDP industry is very unique one becausethat of production, technology and major companies
are almost conspicuosly concentrated between
Japan and Korea. Not only plasma TV but also
LCD (Liquid Crystal Dispaly)or other displays in
the world market prominently dominated by thosecountries. In order to obtain more profoundanalyses and results, I analyzed and developed theresearch by using patent analysis based on the datafrom both JPO (Japanese Patent Office) and
KIPRIS (Korea Industrial Property Rights
Information Service). Through the patent analysis
from 1995 to 2005, we can see that plasma industry
is mainly led by Japan and Korea. Moreover, we
can also observe the same result as the cumulative
shipment amongst the top three companies throughthe patent analysis and this result provides a good
example of the mutual inspiration by competitivetechnology development. The information implicitin patent counts, in the number of patents issued at
different times, in different countries and todifferent types of inventors also contains important
information supportive to techno-economic analysis(Griliches, 1984).

Table 1 The Outline of Patent Analysis
Item

Application
country
Database
SearchperiodSearchformulaRemarkJapan and Korea
KIPRIS and JPO

On line service

1993.01-2005.12
PDP*[name ofcompany]

Elimination of noise
IPC (International
Patent Classification)

Japan: Matsushita,

2. Analytical Framework
Target2.1 Analysis of Patent Document
Table 1 shows the outline of patent analysis in
this research. As see this table, we can observe theassumption and limitation using by short period,
limited application country and classification ofcompany. Although patent analysis provides apractical method for examining a great number ofpatents in a practical way, this method contains
substantial constraints as it depends on aclassification by proximity which is subjective tothe examiners (Watanabe, 2001).

company
Number ofobserved
patentFujitsu, NEC, Pioneer
and Dainippon printing
Korea: Samsung
SDI, LG, Orion,
Daewoo and Hynix
semiconductor

Japan: 7,543
Korea: 3,515

Sources: JPO and KIPRIS (1993-2005).

90

Total: 11,058

Dainippon
11%

we can carture the patent activity amongst the top
three companies and also can observe an interesting
result that the top three companies through thepatent analysis seem to be very different trend
recently. This result provides an example of themutual inspiration by competitive technology
development and different business strategy within
the framework of the institutional characteristics(entrepreneurial level). Accordingly, we seems toneed to analyze the patent activity of each company.

Fujitsu
23%

NEC
15%

JP
Pioneer
10%
Matsushita
41%

Daewoo
7%

Orion
5%

Hynix
2%
Samsung SDI
40%

KR

0.500
0.450

Fujitsu

Patent Activity Index

0.400

LG
46%

Fig. 1. The Patent Number of Top 5 Companies
between Japan and Korea (1993-2005).

PAI =

250
200
150
100
50
0
1996

1997

1998

1999

2000

2001

2002

2003

2004

1996

1997

1998

1999

2000

2001

2002

2003

2004

2005

Number of patents of company
Total number of patents(1)

By measuring the PAI, which represents thepatent activity of each company among others,
technological strategy and development can beinterpreted. In the case of Matsushita, the patentapplications for Plasma TV had increased graduallyand recently the trend decreased slowly. However,Matsushita shows the most distinguishd activity
than other Japanese firms.
In this research, we sellect the IPC (International
Patent Classification) analysis in order to clarify thetechnological strategy and trajectories amongst
targeted companies. IPC offers a more detailed
description or a categorization that is different fromwhat the IPC code offers (Ueno and Amano, 1998).
As postulated Suzuki and Kodama (2004), top
ranking IPC codes were classified into technology
fields representing the respective firm's major
business domains and patent application indicatesan accumulation of knowledge and advancement oftechnological trajectory. The IPC code placed at the
primary position, namely `primary IPC`, has special
meaning. The primary IPC represents the coretechnology which the invention pertains to. Any
additional IPC code which may exist represents the

Matsushita

1995

1995

The Patent Activity Index (PAI) can be expressed
as follows:

300

1994

1994

Fig. 3. The Patent Activity Index among JapaneseCompanies (1993-2005).

LG

1993

NEC

0.150

1993

450

350

0.200

0.000

500

400

Matsushita

0.250

0.050

Samsung SDI

550

0.300

0.100

Patent data provide important information
supportive to techno-economic analysis derivablefrom patent documents which encompass thegeographic distribution of particular inventions,citation networks and patterns, as well as detailed
text of a series of patents in particular field
representing the raw material for a techno-economic
history of particular areas. R&D activities generateinnovations. Innovators generally protect theirintellectual assets as an innovator, usually by patent.
In light of this general behavior, patent statistics
have fascinated economists concerned about
innovation. Consequently, patent statistics havebeen used as a proxy of innovation. Moreover, we
can also observe the same result as the cumulative
shipment amongst the top three companies throughthe patent analysis and this result provides a good
example of the by competitive technology
development.
600

0.350

2005

Fig. 2. The Trend of Patent Number among Top 3
Companies (1993-2005).

Figure 2 shows the trend in application of patent
during between 1993 and 2005. Based on this result,91specific application field or a closely related
technology field pertinent to the invention. Table 2
shows the primary IPC code in display.

postulated that, among patent applications applies
to foreign countries, applications to the USA
provide strong representability of innovation since
the number of patent applications to the USA is
proportional to the extent of innovation. Figure 5
illustrates the performance of patent activity
application from 1995 to 2005.

Table 2 The Primary IPC code in Display
IPC code
Remark
G09G A equipment circuit for control of display
H01J Electron tube or electric discharge of a lamp
H04N Image processing or communication
H05K Interference of electromagnetic waves
G09F Manipulator

US

LG
38%

Verspagen(1996)
arguedinter-sectoral
knowledge spillovers assuming that the primary
IPC provides a good proxy of the knowledgeproducing sector, and that the additional IPC codes
provide a good proxy of the spillover-receiving
sectors. Therefore, based on this understanding andapplication, the result of IPC analysis amongst the
top three companies illustrated in Figure 4.

Fujitsu limited
15%
Pioneer
9%

Matsushita
22%

Samsung SDI
16%

Fig. 5. The Number of Patent Applications in US
among Top 5 Companies (1995-2005).

And then , we analyzed application patent in US
above and beyond that of in EU, too. Figure 6
visualizes the patent activity in EU from 1995 to
2005.

G09G
900
750
600
Etc

H01J

450

LG
16%

300
150

Samsung SDI
11%

0

G09F

(a) Matsushita

G09G
900

H04N

Matsushita
44%

600
H01J

Etc

450

300

300

150

150

0

0

G09F

FHP
13%

750

600
450

EU

G09G
900

C 09K

750

Etc

Fujitsu limited
16%

H04N

G09F

H01J

Fig. 6. The Number of Patent Applications in EU
among Top 5 Companies (1995-2005).
H04N

H05K

H05K

(b) Samsung SDI(c) LG

3. Discussion
We can also observe the similiarity of patentacitivity amongst the top three companies not onlyin Japan and Korea but in US and EU. Based on
this results, we need to remark the Matsushita's
business strategy in PDP (Plasma Display Panel)
recently. As mentioned in Figure 3, only this firmshows the active performance compared to otherplayers, lately. Because the PDP industry was earlysimplified through the withdrawal of PDP businessof Fujitsu, the undertaking of NEC’s PDP businesssector by Pioneer and then market expansion of
aggressive investment of Korean companies.
Therefore, a market competition’s structure wasreorganized among Matsushita, Samsung SDI and
LG electronics since the end of 2004, and then is
expected to be more intensive competition. In
addition to these, the results through patent analysis
are conformable with the rank of world's mostinnovative company provided by business week in2006. Through an article, we can see noteworthy

Fig. 4. The Radar Analysis of IPC Code among
Top 3 Companies (1993-2005).

On the basis of Figure 3, the three companies
competitively concentrate on the specified field oftechnology, such as G09G and H01J, and theyshow analogous points not only the cumulative
shipment but also the patent strategy. These results
and trends amongst the companies can be linked
with the litigation of patent they maintain with eachother.
Up to this moment, analysis demonstrated
through data from between JPO and KIPRIS duringfrom 1993 to 2005. In line with this analysis, weneed to enhance and assess the results within theframework of the data from USPTO (US Patent andTrademark Office). They, Soete and Wayatt (1983),

92accomplishment amongst the top three companies.
Table 3 shows the world’ most innovative
companies in 2006.

References[1]Griliches, Z., 1984. R&D, Patents andProductivity. The University of Chicago Press,
Chicago, IL/London.

Table 3 The Top 100 Most Innovative Companies
Ranking
Rank
Company1
Apple2
Google3
3M
25
Samsung
71
Matsushita
85
LG*Source: BusinessWeek, 2006.

[2] Watanabe, C.,Tsuji., Y.S., and Griffy-Brown, C.,
2001. Patent statistics: deciphering a ‘real’
versus a ‘pseudo’ proxy of innovation.
Technovation 21 (12), 783-790.
[3]Ueno, S., Amano, H., 1998. Improvement of the
IPC. Discussion paper for advanced seminar on
the international patent classification, Newport,
United Kingdom, 7-11 December 1998.
IPC/SEM/98/10.

Therefore, we can conclude the distinguishedaccomplishment amongst the top three companies
through patent counts analysis and investigation of
the most innovative companies in the world.

[4]Suzuki, J., and Kodama, F., 2004. Technologicaldiversity of persistent innovators in Japan :Two case studies of large Japanese firms.
Research Policy 33 (3), 531-549.

4. Conclusions
1. The three companies competitively concentrateon the specified field of technology, not only the
cumulative shipment but also the patent. These
results and trends amongst the companies can belinked with the litigation of patent they maintainwith each other.
2. Based on the overall application of patent and the
distribution of different nation’s ratio, we can seethat the plasma TV’s technology has passed its
maturity and is approaching the time of utilizationin earnest.
3. Moreover, we can also observe the same result as
the cumulative shipment amongst the top threecompanies (Matsushita, Samsung SDI and LG)
through the patent analysis and this result provides
a good example of the mutual inspiration bycompetitive technology development.
4. Through the patent analysis from 1993 to 2005,
we can see that plasma TV industry is mainly led
by Japan and Korea.
5. Within the framework of the unique institutional
characteristics, Samsung SDI and LG acceleratelearning effort and that became motivation for
Matsushita through inspiration. As postulated
Porter (1980), firms can learn from physicalinspection of competitor’s proprietary products andother characteristics of competitor’s operation andother characteristics of competitor’s operation. This
assertation has something in common with mutual
inspiration in this research. In case of mutual
inspiration among these leading companies, we canconsider the increase in shipment, technology
improvement (world’s largest plasma TV) andpatent analysis each other as an example of it.

[5] Verspagen, B., 1996. Measuring intersectral
technology spillovers: estimates from theEuropean and US Patent Office Databeses.
Economic Systems Research 9 (1), 47-65.
[6] Soete, L., and Wayatt, S., 1983. The use offoreign patenting as an international
comparable science and technology output
indicator. Scientometrics 5 (1), 31-54.
[7] Porter, M., 1980. Competitive Strategy:
Techniques for analyzing industries andcompetitors. Free Press, New York.
[8]

Kodama, M., 2007. Innovation throughboundary management - a case study in reforms
at Matsushita electric. Technovation, 27(1-2),
15-29.

[9] McGregor, J., M. Arndt, R. Berner, I. Rowley,
G. Edmonson, S. Hamm, M. Ilhwan and A.
Reinhardt., 2006. The world's most innovative
companies. BusinessWeek, April 24.

93Transition Dynamism in Web 2.0:
Emerging Dynamism of New Functionality
SHIN, Jae-Ho**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANshin.j.aa@m.titech.ac.jp
While it is broadly pointed out that the emergence of Web 2.0 has been
substantially changing the traditional Internet-based communication structure
and providing significant impacts on the business behavior, its transition
dynamism remains a black box. Aiming at identifying the shift in the leadingrole between innovators and imitators and subsequent change in functionality
corresponding to the shift from Web 1.0 to Web 2.0, a Bi-Bass model
demonstrating the diffusion trajectory initiated by both innovators andimitators in line with the transition from Web 1.0 to Web 2.0 was constructed.
development and dissemination and subsequentchange in functionality. In light of the significant
impacts such a shift may provide on the businessbehavior, this paper attempts to demonstrate theforegoing hypothetical views. An empirical analysis
focusing on the diffusion trajectory of Japan’s Internet
dependency taking number of co.jp domains over thelast 14 years is conducted. By means of the empiricalanalysis utilizing the Bi-Bass model, this paper
attempts to demonstrate that the emergence of Web
2.0 has induced a shift from innovator initiative toimitator initiative and enhanced functionality
development and also identifies substantial transition
timing from Web 1.0 to Web 2.0.

1. Introduction
The transition of the Internet-based communication
structure has provided significant impacts on thebusiness behavior in the world. While the bursting of
the net bubble early in the 2000s revealed thefragileness of an information society, successive
emergency of Web 2.0 that emerged from a conference
brainstorming between O'Reilly and MediaLive
International (O'Reilly，2005) has explored the newwave toward a ubiquitous society. Figure 1
demonstrates the trend in the Japanese corporates’
Internet-based communication over the period May
1993-June 2006 by means of cumulative number ofco.jp domains.

2. Analytical Framework

Cumulative number of domains

3.5E+05

Window 95
Integration between
Internet and PC

3.0E+05
2.5E+05

Bursting of the net bubble Postulate of
Improvement of Web system Web 2.0

2.1 Diffusion Model
Since the prime objective of this paper is to analyze
the transition from Web 1.0 to Web 2.0, and also theshifting trend from innovator initiative to that ofimitator as illustrated in Figure 2, proposed diffusion
model should satisfy both functions of equations (1)[Bass model] and (2) [Bi-logistic growth model]
leading to the Bi-Bass model as depicted by equation(3).

2.0E+05
1.5E+05
1.0E+05
5.0E+04

Web 1.0

Web 1.5

Web 2.0

1995

2000

2004

0.0E+00

1993

2006

Fig. 1. Trend in Cumulative Number of co.jp Domains(May 1993 – June 2006).

Source: Japan Registry Services Co., Ltd (2006).

Y (t ) =Looking at this Figure we note that while thistrajectory first traced a sigmoid curve with its
inflection point around 2000, it moved slightly to
upward from 2003-2004. This suggests a transition
from Web 1.0 to Web 1.5 corresponding to thebursting of the net bubble and emergence of the Web
2.0 in 2003-2004 (Wikipedia).The characteristics of
Web 2.0 (“user participation” and “open orientation”)
inevitably lead to shift in the leading role between
innovators and imitators in the process of theY(t) =

N (1 − e − ( p + q ) t ) )q
1 + e −( p + q ) t
p

N1
N2
+
−b1t
1+a1e
1+a2e−b2t

(1)

(2)

where p: innovator parameter; and q: imitator parameter.
where Y(t): diffusion level of innovative goods; b:
coefficient of diffusion velocity; N: carrying capacity;and t: time trend.

94

Logistic

Single model

Bi-modelSimple logistic growth model

Bi-logistic growth model

While the transition timing from Web 1.0 to Web
2.0 can be identified by the inflection point of the
Bi-Bass model, this can be identified by means of the
1st and the 2nd differentiation of the Bi-Bass model asfollows [equation (5) and (6), respectively]:

Bi-Bass model

Bass

Bass model

Shift from p (innovator) to q (imitator)dY (t )=
dt

Co-existence of Web 1.0 + Web 2.0

N1 ( p1 + q1 )e −( p1 +q1 )t (1 +(1 +and their transition

N1 (1 − e − ( p1 + q1 )t ) N 2 (1 − e − ( p 2 + q 2 ) t )+qq
1 + 1 e − ( p1 + q1 ) t
1 + 2 e − ( p2 + q2 )t
p1
p2

(3)

+
(1 +

0

N
Y=
1 + ae − btN
FD = = 1 + ae −btY(5)

q2 −( p2 +q2 )t 2
e
)
p2

(6)

Y (t )

Time

t

Time

t

dY (t )
dt

d 2Y (t )dt 2Prolongation-100 years

q2
)
p2

Figure 4 illustrates trajectories of equations (1), andthe equations (5) and (6) which demonstrate theproperties of the diffusion trajectory examined.

2.2 Functionality Development
Provided that the state of innovations and theirdiffusion are traced by the trajectory of functionality
development, this functionality leads to create
successive innovations through the efforts formaintaining its level. While emergence of innovation
creates new functionality, it obsolesces immediately.
Given the lengthy years of efforts for emerging an
innovation, lifetime of newly created functionality is
an ephemeral existence. While newly emerged Web
2.0 could promote firm’s technology development andits performance, it broadly popularized long-tailphenomena that accelerate obsolescence of technology.
Therefore, information technology’s (IT) new
functionality development corresponds to the effort toprolong this ephemeral existence as demonstrated in
Figure 3.
FD

N 2 ( p2 + q2 )e −( p2 +q2 )t (1 +qqqqN1(1+ 1 )(p1 +q1)2e−(p1+q1)t[1− 1 e−(p1+q1)t ] N2(1+ 2 )(p2 +q2)2e−(p2+q2)t[1− 2 e−(p2+q2)t ]
p2
p2
p1
p1
d2Y(t)=−−
q2 −(p2+q2)t 3
q1 −(p1+q1)t 3
dt2
(1+ e
)
(1+ e
)
p2
p1

Fig. 2. Concept of the Bi-Bass Model.
Y (t ) =q1 −( p1 +q1 )t 2
e
)
p1

q1
)
p1

Time t10 yearsFig. 4. Properties of the Diffusion Trajectory.
Source: Mahajan et al. (1990).

where FD: functionality development.

2
The trend in d Y (t ) demonstrates a tendency toFig. 3. Emergence of Innovation and New Functionality.

dt 2

In case when the diffusion trajectory is traced by theBass model in equation (1), its FD can be depicted byequations (4).

inflect with time, the maximum/minimum diffusionq
1 + e −( p + q )t
N
N
p
FD =
=
=
− ( p + q )tY
N 1− e1 − e −( p + q )t
q −( p + q )t
1+ ep

trajectory.

(

level, and also increasing/decreasing trend in diffusion(4))(2) Substitution of the Bi-Bass Model
In addition to the above analysis, dynamism
inducing a transition from Web 1.0 to Web 2.0 can beanalyzed based on a concept of substitution. On thebasis of existing works, the mechanism of substitution
can be analyzed by utilizing equation (6). This
analysis leads not only to transition dynamism from

2.3 Diffusion Dynamism of the Bi-Bass Model(1) Inflection of Diffusion Trajectory95

Web 1.0 to Web 2.0 but also to emerging dynamism of
post-Web 2.0.

(2) Bi-Bass Model
Table 2 Estimation of the co.jp Domains by the
Bi-Bass Model (May 1993- June 2006)

3. Empirical Analysis
3. 1 Diffusion Trajectory
Aiming at identifying the diffusion trajectory of theJapanese
corporates’
Internet
dependency
incorporating a transition from Web 1.0 to Web 2.0, acomparative empirical analysis of the monthly
diffusion trend in number of co.jp domains over theperiod May 1993–June 2006 is conducted.

Parameter

Estimate

t-valueadj.R2AIC

N1

2.42×105145.87

0.999

17.08

N2

2.49×105

75.66

p1

1.38×10-5

8.35

q1

1.08×10-1

58.33

p2

0.25×10-5

2.60

q2

0.55×10-1

22.74(1) Bi-Logistic Growth Model
Table 1 Estimation of the co.jp Domains by the
Bi-Logistic Growth Model (May 1993 – June2006)

Sub trajectory

Parameter

Estimate

t-valueadj.R2

AIC

0.999

17.08

5

N1

2.40×10129.49N2

2.45×105

32.83

a1

3

8.36×106.10

b1

0.11×10-2

54.49

a2

7.14×103

2.87

b2

4.79×10-2

23.05

p1/ q1 = 0.78×104

p2/ q2 = 2.20×104

Inflection point

Y1

t1# =

ln q1 / p1
p1 + q1

82.9 (Mar. 2000)

Y2

t2# =

ln q2 / p2
p2 + q2

182.9 (Jul. 2008)

6.0E+05

5.0E+05

4.91E+05

Y1+Y2

4.0E+05

2020/5

2019/5

2018/52017/5

2016/5

2015/5

2014/5

2013/5

2012/5

2011/5

2010/5

2009/5

2008/5

2008/7
2007/5

2006/5

2005/5

2004/5

2003/5

2002/5

2001/5t 2#

Y2

2000/3
2000/5ln a2b2

1997/5t 2# =t1#

Y1

1.0E+05

1999/582.8 (Mar. 2000)

0.0E+00

Y2

2.42E+05

1996/5ln a1b1

1995/5Y1

2.49E+05

2.0E+05

1994/5t1# =3.0E+05

1998/5

Inflection point

1993/5Sub trajectory

185.0 (Sep. 2008)

Fig. 6. Trend in the co.jp Domains by the Bi-Bass
Model (May 1993- Dec. 2020)a.
a

4.50E+05

4.85E+05

Y1+Y2

4.00E+05
3.50E+05

3. 2 Result of the Empirical Analysis
Results of the comparative empirical analysis
indicate that both bi-diffusion models (Bi-logistic
growth model and Bi-Bass model) demonstratestatistically significant. These bi-diffusion models
demonstrate that the trajectory of this Web can be
decomposed into two trajectories, Y1 and Y2.

3.00E+05

2.45E+05

2.50E+05

2.40E+05

2.00E+05

Y1

t1#

1.50E+05
1.00E+05

Y2

t 2#

2000/3

2008/95.00E+04

2010/5

2009/5

2008/5

2007/5

2006/5

2005/5

2004/5

2003/5

2002/5

2001/5

2000/5

1999/5

1998/5

1997/5

1996/5

1995/5

1994/5

1993/50.00E+00

Fig. 5. Estimation of the co.jp Domains by the
Bi-Logistic Growth Model (May 1993- Dec. 2010)aa

May 1993 - Jun. 2006: actual, and Jul. 2006 - Dec. 2020: extended

estimates by the model using May 1993 - Jun. 2006 data.

5.00E+05

3. 3 Functionality Development
Web 2.0 demonstrates higher functionality
development than that of Web 1.0 as demonstrated
in Figure 7. It is identified that the emergence of Web
2.0 has induced shift from innovator to imitator andenhanced functionality development and this result
support our hypothesis.

May 1993 - Jun. 2006: actual, and Jul. 2006 - Dec. 2010: extended estimates.

Table 2 and Figure 5 demonstrate the estimation of
the co.jp domains utilizing the Bi-Logistic growthmodel. In order to elucidate the transition dynamism
from Web 1.0 to Web 2.0, the following empiricalanalyses are conducted.
96

of its transition dynamism. First, substitution effectinduced by the dynamism of “Switch (disadopt)” and“Acceptance of the innovation” is linked by transition
dynamism
leadingtohigherfunctionality
development and shift from innovator to imitator in
Web 2.0. Second, functionality development can beconsidered the motivation of substitution and theninduces the transition dynamism through elasticity of
substitution. These phenomena also can be observedin the transition of the co-existence and co-diffusionof Web 1.0 and Web 2.0 shifting from innovator toimitator initiative. Third, the analysis utilizing the
Bi-Bass model demonstrated that the transition fromthe preceding trajectory (Web 1.0) to the succeeding
trajectory (Web 2.0) identified by the inflection pointof diffusion trajectory was Oct. 2003. Fourth, theseanalyses provide the following important suggestions
suggestive to corporates’ behavior corresponding to
the transition:(ⅰ) Emerging dynamism of transition leads to thesubstitution effect.
(ⅱ) Emergence of Web 2.0 can be conceptualized byco-diffusion and co-existence.
(ⅲ) This rationale can be observed through analysis
of higher coefficient of innovator and imitator
leading to functionality development.
(ⅳ) The transition dynamism can largely be attributed
to its solution of diffusion trajectory with the
Bi-Bass model.
(ⅴ) Confronting the transition dynamism, thephenomena and characteristics of Web depend on
how to transmit and provide the information tousers easily and promptly.
References[1] T. O'Reilly，What Is Web 2.0 -Design Patterns andBusiness Models for the Next Generation ofSoftware, 2005.
[2] Japan Registry Services Co., Ltd, Trend in domainsof co.jp, 2006．
[3] F. M. Bass, A New Product Growth Model for
Consumer Durables, Management Science 15 (5)(1969) 215-227.
[4] P. S. Meyer, Bi-Logistic Growth, Technological
Forecasting and Social Change 47 (1) (1994) 89102.
[5] C. Watanabe, R. Kondo, N. Ouchi, H. Wei, and C.
Griffy-Brown, Institutional Elasticity as a
Significant Driver of IT Functionality Development,
Technological Forecasting and Social Change 71(7) (2004) 723- 750.
[6] A. J. Norton, and F. M. Bass, A Diffusion Theory
Model of Adoption and Substitution for Successive
Generations of High-Technology Products,
Management Science 33 (9) (1987) 1069-1086.
[7] V. Mahajan, E. Muller, and R.K. Srivastara,
Determination of Adopter Categories by Using
Innovation Diffusion Models, Journal of Marketing
Research 27 (1990) 37-50.

2000/3
200

150

100

50

2003/10

7. Trend in Functionality Development
Trajectories (May 1993- Dec. 2020)ain

2 0 2 0 /5

2 0 1 9 /5

2 0 1 8 /5

2 0 1 7 /5

2 0 1 6 /5

2 0 1 5 /5

2 0 1 4 /5

2 0 1 3 /5

2 0 1 2 /5

2 0 1 1 /5

2 0 1 0 /5

2 0 0 9 /5

2 0 0 7 /5

2 0 0 6 /5

2 0 0 5 /5

2 0 0 4 /5

2 0 0 3 /5

2 0 0 2 /5

2 0 0 1 /5

2 0 0 0 /5

1 9 9 9 /5

1 9 9 8 /5

1 9 9 7 /5

1 9 9 6 /5

1 9 9 5 /5

1 9 9 4 /5

2 0 0 8 /5

2008/7

0

Fig.
a

FD 2

FD 1

1 9 9 3 /5

Functionality Development (FD)

250

Two

May 1993 - Jun. 2006: actual, and Jul. 2006 - Dec. 2020: extended estimates.

3.4 Transition Timing from Web 1.0 to Web 2.0
400

d 2Y (t )dt2

1999/3 (t1)

300

200

d 2Y (t )d 2Y1 (t ) d 2Y2 (t )= dt 2 +dt 2
dt 2

2006/7 (t1)

100

20
19
/5

20
20
/5

20
19
/5

20
20
/5

20
19
/5

20
20
/5

20
17
/5

20
18
/5

20
16
/5

20
16
/5
20
16
/5

20
17
/5

20
15
/5

20
15
/5
20
15
/5

20
18
/5

20
14
/5

20
14
/5
20
14
/5

20
18
/5

20
13
/5

20
12
/5

20
13
/5
20
13
/5

20
17
/5

20
12
/5
20
12
/5

20
11
/5

20
11
/5
20
11
/5

20
10
/5

20
10
/5
20
10
/5

20
09
/5

20
08
/5

20
07
/5

20
06
/5

20
05
/5

20
04
/5

20
03
/5

20
02
/5

20
01
/5

20
00
/5

19
99
/5

19
98
/5

19
97
/5

19
96
/5

19
95
/5

19
94
/5

19
93
/5

0

-100

-200

-300

300

d2Y1(t)dt2

200

2000/3 (t#)

2003/10 (t#)

100

20
09
/5

20
08
/5

20
07
/5

20
06
/5

20
05
/5

20
03
/5

20
04
/5

20
02
/5

20
01
/5

20
00
/5

19
99
/5

19
98
/5

19
97
/5

19
95
/5

19
96
/5

19
93
/5

19
94
/5

0

-1 0 0-2 0 0-3 0 02001/3 (t2)2008/7 (t#)

802

d Y2(t)
dt2

60

40

20

20
09
/5

20
08
/5

20
07
/5

20
06
/5

20
05
/5

20
04
/5

20
03
/5

20
02
/5

20
01
/5

20
00
/5

19
99
/5

19
98
/5

19
97
/5

19
96
/5

19
95
/5

19
94
/5

19
93
/5

0

-2 0

-4 0

-6 0

-8 0

2010/7 (t2)2Fig. 8. Trend in d Y (t ) (May 1993 – Dec. 2020).

dt 2

The Figure demonstrates the peaks of the change in
2000/3 and 2008/7 corresponding to the peaks in
dY1 (t ) as well as dY2 (t ) and also corresponds to thedt
dt

inflection points in the preceding analysis asdemonstrated in Figure 8. Furthermore, as postulatedby Mahajan and Muller (1996), the intersection of the
diffusion of successive innovation indicates the timingof the substantial substitution from old innovation to
new innovation. Therefore, the timing of the transition
from Web 1.0 to Web 2.0 can be considered the timingof the substantial substitution from Web 1.0 to Web
2.0.

4. Conclusion
In light of the noteworthy observation that the
emergence of Web 2.0 has been substantially changing
the traditional Internet-based communication structure,
this paper attempted to elucidate inside the black box
97

Earlier Emergence of Functionality Development
in a Diffusion Trajectory
SHIN, Jae-Ho**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-49 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANshin.j.aa@m.titech.ac.jp
Given the declining nature of functionality development after its emergence,firm strategy must address the issue of how to sustain this function. Thus,
sustainable functionality development has become crucial to a firm’s
competitiveness, which inevitably necessitates an earlier emergence offunctionality development. An earlier emergence of functionality development
depends on imitator substitution for an innovator. This substitution corresponds
to the dynamism induced by open innovation. Consequently, functionality
development through follower substitution for a leader should be considereddecisive to a firm’s competitiveness in an open innovation environment. On thebasis of empirical analyses of dynamism substituting between printers, software
outsourcing, and the Web, this paper attempts to demonstrate the foregoing
hypothetical view.
1. Introductionrole of innovator and imitator in leading innovation
diffusion.

Sustainable functionality development is decisive tofirm’s profitability in their new innovation in acompetitive market. While functionality instills
attractive values in innovative goods leading to adramatic increase in profit through increasing demandand higher prices, it obsolesces immediately in acompetitive market. Therefore, how to maintainsustainable functionality development is decisive tofirm survival strategy within the context ofmega-competition in a globalizing economy.
Epidemic function has been popularly used for the
analysis of the diffusion trajectory of innovation(Meyer and Ausbel, 1999). This epidemic function
identifies the contagion process similar to epidemic
behavior (Modis, 1992) and exhibits sigmoid growth.
Since Verhulst (1845) introduced the logistic model
depicting sigmoid growth, a number of studies havedemonstrated this model in analyzing diffusion
trajectory. Diffusion trajectory of high-technology
products has also been demonstrated to correspond to
this trajectory.

In light of the significant impacts of open
innovation (Chesbrough, 2003, von Hippel, 2005, andChesbrough et al., 2006), this paper attempts todemonstrate the significance of the imitator
substitution for innovator for the emergence offunctionality development in a diffusion trajectory. An
empirical analysis focusing on the diffusion trajectoryof printers, software, and the Web in Japan isconducted by utilizing the Bass model.
First, an attempt to demonstrate a numericalanalysis
depictingtheearlierfunctionality
development emergence in a diffusion trajectory is
conducted. Second, by incorporating governing
factors and their magnitude to increase trend ininnovative
goods,
sustainable
functionality
development is analyzed. Third, utilizing the result of
the boundary function satisfying the earlier
functionality development emergence, the dynamismof open innovation is elucidated. Fourth, based onthese analyses, sustainable functionality development
leading to open innovation in firm’s competitivenessis identified.

Utilizing the logistic growth function, Watanabe etal. (2005) postulated that the ratio of carrying capacity
to the level of diffusion represents the extent offunctionality development.
The emergence ofinnovation leads to new functionality development
and the efforts for maintaining the level offunctionality development leads to create successive
innovations.
While there have been variety of diffusion models
depicting the diffusion trajectory of innovation, Bassmodel (Bass, 1969) enables the identification of the

2. Analytical Framework
2.1 Functionality Development Concept
Diffusion of innovative goods is induced by theirability to dramatically improve the performance of
production processes, goods and services by means ofinnovation. This ability can be defined as functionality
development (Watanabe et al., 2003).
Based on this postulate, Watanabe et al. (2004)98

demonstrated that the state of functionality
development (FD) can be traced by the diffusion
trajectory depicted by the following epidemic
function:dY
Y= aY (1 − )dtNemergence and its governing factors can be considered
critical to firm strategy.
(1)

(1)

Incorporating the contribution of innovator andimitator to the diffusion trajectory, equation (1) can be
developed to the following Bass model:(2)

where p: innovator; and q: imitator parameter.
While Y continues to diffuse as far as it incorporates
functionality development, since equations (1) and (2)suggest dY = 0 when Y reaches N, Y terminates todt

diffuse when it reaches the level of carrying capacity
N.
This termination can be attributed to the
obsolescence of functionality development. Therefore,
the degree of functionality development can be
identified by potential capacity before reachingobsolescent stage which can be measured by the ratioof carrying capacity to the level of diffusion as
follows:
Degree of FD = N(3)YSince equation (2) can be developed to the following
diffusion trajectory depicted by equation (4), the FD
can be depicted by equation (5):Y (t ) =(4)

N (1 − e − ( p + q ) t ) )q
1 + e −( p + q )tpq
1 + e −( p + q )t
N
N
p
=
=
FD(t ) =Y (t ) N 1 − e −( p + q )t
1 − e −( p + q )tq
1 + e −( p + q )tp(Functionality

Development

Based on the Bass model, Norton and Bass (1987)
demonstrated
thesubstitution
effectofhigh-technology products by taking the secondary
derivative of Y(t) which incorporates thesehigh-technology products. They considered the
maximum/minimum level of the secondary derivative
as the point of the substitution of high-technology
products since this level corresponds to the inflection
point of the diffusion. Inspired by Bass (1969) and
Rogers (1983), Mahajan et al. (1990) analyzed thecategories of adopters of the innovative goods(“adopter categories”) by taking the tertiary derivativeof Y(t) which enables the determination of the sizes of“adopter categories” by time as illustrated in Figure 1.
They analyzed inflection points of the diffusion as
indicated in the right hand side of the Figure andcorresponding “adopter categories.” Moore (1991)
pointed out that there exists a deep trench repelling
new ventures start-up called CHASM that lies
between minor and major markets corresponding to
the early adopters and the early majority of the
diffusion trajectory as illustrated in Figure 1. These
rationales demonstrated by Rogers (1983), Mahajan etal. (1990), Moore (1991), and Watanabe et al. (2003)
suggest that functionality development emergence canbe identified as the ability to overcome the barrier ofthe market by means of new innovation.
Consequently, it can be concluded that the
emergence of FD occurs at certain point
corresponding to cross the CHASM and also that thetiming of FD emergence can be identified as theearlier inflection point of the first derivative of t1.
Furthermore, Figure 1 demonstrates that earlier
emergence of FD enhances the higher level of FD.
This earlier emergence of FD leads to a firm’s
competitiveness corresponding to not only
technology-oriented
but
also
market-oriented
adoption.
Rogers (1962) postulated that the breeding stage of
new innovations can be divided into the five stages as
innovator (2.5% of the life time), early minority(13.5%), early majority (34%), late majority (34%)
and laggard (16%).
The point of the CHASM corresponds to the point
when new functionality development emerges as thelife time confronting with the CHASM equivalents to16%, while the similar life time when FD emerges
equivalents to [21% - 1/(1+b)] suggesting that in casewhen the initial level of the diffusion [1/(1+b)] = 0.05,
Mahajan’s point corresponds exactly to the point of
the CHASM.

where Y: production of innovative goods; N:
carrying capacity; and a: velocity of diffusion.

dYY= ( pN + qY )(1 − )dtNTiming ofEmergence(5))

2.2 Emergence of Functionality Development
Since functionality development decreases as time
passes while its level is crucial for firm’s
competitiveness, timing for functionality development99

high-technology in the Bass model is conducted. As
illustrated in Figure 1, timing of FD emergence can be
identified as t1 that satisfies the following condition:FD

t1 = −

Emergence of FD

FD1
FD#
FD2

Y2
Y#
Y1

(1)

)

Requirement for Earlier
Development Emergence

(

t

d 2Y
dt 2

Functionality

Since q/p demonstrates prolongation ability of FD,
the following analysis examines whether q/p increase
contributes to decrease in t1. This can be examined asfollows:
dt1
dt
ν
dν
x
= 1 =
ln[
]+
dq / p dx dx
x
2+ 3

t

dY
dt

(

⎡
(2 + 3 )p⎤xln ⎢ 2 + 3 ⎥ = −ν ln[] = ν ln[
]
q
x
(
2
3)
+
⎦
⎣

where t1: timing of functionality development
emergence.

t

Y

1

( p + q)

ν=

ν
1
1
,
=
,
p(1 + x)x p(1 + x) x

)

dν
=
dx

dp
+ p]
.
dx
[ p (1 + x )]2− [(1 + x)

Therefore, the above equation can be developed asfollows:
t

d 3Y
dt 3

t1

t#

dt1
=
dq / p⎡(2 + 3 ) ⎤dp+ p] ln[]x ⎥⎢ [(1 + x )
1
dx
x
⎢1 +
⎥
=
px (1 + x ) ⎢p(1 + x )
⎥
⎢⎣
⎥⎦

t

t2

dp
+ p]
1
x
dx
ln[
]+
+ x)
[ p(1 + x )]2(1px(2 + 3 )− [(1 + x )Timing of FD emergence

From the above analysis, since q/p increase induces
earlier FD emergence leading to sustainable FD,

Innovators

Early
adopterEarlymajorityLatemajority

dt1< 0 can be concluded as necessary conditions
dq / pLaggards

for earlier functionality development emergence.
(2) Boundary Satisfying Earlier Functionality
Development Emergence

CHASM: critical point

Aiming at identifying the boundary condition
satisfying earlier FD emergence in the Bass model, thefollowing analysis is attempted.

Figure 1. Level and Timing of Inflection in a Diffusion
Trajectory.

dt1
<0 ⇔
dq / p3. Empirical Analysis[(1 + x)(2 + 3 )dp]x+ p ] ln[dxx
< −1
p (1 + x)

3. 1 Sustainable Functionality Development(2 + 3 )dp (2 + 3 )ln[]x ln[
]x
x
x
⇔ dx
+
< −1
(1 + x)p

Aiming at demonstrating sustainable functionality
development by means of earlier emergence of FD, anempirical analysis taking the diffusion trajectory of
100

dt1
dp 1
<0 ⇔
>−
dq / pdx p

1
1−(1 + x )(2 + 3 )
ln[
]x
x
1
dp x
x
⇔ ε ≡
>−
−
dx p
(2 + 3 ) (1 + x )
ln[
]
x

(iii)
(iv)

Therefore, boundary function satisfying earlier FD
emergence can be depicted as follows:

References2

ε
dp x 1.5
( ⋅ )
dx p

B(x)

B(x) = −[1] P.S. Meyer, J.H. Ausbel: Carrying Capacity: A
Model with Logistically Varying Limits,
Technological Forecasting and Social Change 61 (3)(1999) 209-214.
[2] T. Modis: Prediction, Simon & Schnster, New York,
1992.
[3] C. Watanabe, J.Y. Hur, K. Matsumoto:Technological
Diversification
andFirm’sTechno-economic Structure: An Assessment ofCanon’s
Sustainable
GrowthTrajectory,
Technological Forecasting and Social Change 72 (1)(2005) 11-27.
[4] C. Watanabe, B. Asgari, A. Nagamatsu.: Virtuous
Cycle between R&D, Functionality Development andAssimilation Capacity for Competitive Strategy inJapan’s High-Technology Industry, Technovation 23(11) (2003) 879-900.
[5] F.M. Bass: A New Product Growth Model for
Consumer Durables, Management Science 15 (5)(1969) 215-227C.
[6] H.W. Chesbrough: Open Innovation: The New
Imperative for Creating and Profiting fromTechnology, Harvard Business Press, 2003.
[7] E.A. von Hippel: Democratizing Innovation, MIT
Press, Cambridge, 2005.
[8] H.W. Chesbrough, W. Vanhaverbeke, J. West: Open
Innovation: Researching a New Paradigm, Oxford
University Press, 2006.
[9] C. Watanabe, R. Kondo, N. Ouchi, H. Wei, C.
Griffy-Brown: Institutional Elasticity as a Significant
Driver of IT Functionality Development,
Technological Forecasting and Social Change 71 (7)(2004)723-750.
[10] A.J. Norton, F.M. Bass: A Diffusion Theory Modelof Adoption and Substitution for Successive
GenerationsofHigh-Technology
Products,
Management Science 33 (9) (1987) 1069-1086.
[11] E.M. Rogers: Diffusion of Innovation. 3rd ed. The
Free Press, New York, 1983.
[12] V. Mahajan, E. Muller, R.K. Srivastara:
Determination of Adopter Categories by Using
Innovation Diffusion Models, Journal of Marketing
Research 27 (1990) 37-50.
[13] G.A. Moore: Crossing the Chasm: Marketing and
Selling Technology Products to Mainstream
Customers, New York, Harper Business Essentials,
Harper Collins, 1991.

1x−(2 + 3) (1+ x)
ln[
]
x

1

0.5

0

for a leader that also enhances the level offunctionality development,This substitution corresponds to the
dynamism induced by open innovation, andConsequently, functionality development
through imitator substitution for innovator
should be considered decisive to a firm’s
competitiveness in an open innovation
environment.

LLBP
2+ 3

5

-0.5

10

x# = 11.1
50

LBP/BJSW

x (q/p)
100

500

1000

5000

10000

Web 1.0

15000

20000

25000

Web 2.0-1

Figure 2. Conditions for Sustainable Functionality
Development.

Figure 2 demonstrates that while latest
high-technology products as LBP/BJ, software
outsourcing, Web 1.0, and Web 2.0 satisfy conditions
for sustainable functionality development, LLBP
which was developed in 1976 does not satisfy these
conditions resulting in being substituted by LBP and
BJ. Figure 8 also demonstrates that the ratio of q/p(imitator/innovator) increases as innovation proceeds.
Therefore, imitator substitution for innovator all
supports the hypothetical view and demonstrates thesignificance of an open innovation.
4. Conclusion
In light of the significance of the sustainable
functionality development for firms’ profitability intheir new innovation in a competitive market, thispaper analyzed necessary conditions enabling firms
prolong their functionality development. On the basisof the mathematical analysis utilizing the diffusion
function, it was identified that the earlier emergence offunctionality development is inevitable for firms’
sustainable functionality development. An empiricalanalysis taking the series of high-technology products
from printers, software, and the Web was conducted.
Noteworthy findings obtained include:(i)
Given the declining nature of functionality
development,sustainabilityof
thisfunction has become crucial to a firm’s
competitiveness, which necessitates an earlier
emergence of functionality development,(ii)
An earlier emergence of functionality
development depends on follower substitution101

Nanotechnology Innovation System: An Analysis of Technology Fusion Strategy
Nazrul Islam* , Kumiko Miyazaki
Department of Innnovation, Graduate School of Innovation Management, Tokyo Institute of Technology
2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN*islam.n.aa@m.titech.ac.jp
In the early stage of nanotechnology development and diffusion, many expected
benefits have not yet been fully accomplished. However, researchers of scientificdisciplines aggressively got involved in the relevant research as a parallel way to boost
nanotech competitiveness through academic research, and corporations direct their R&D
activities towards the exploration of nanotech opportunities. Through a combination ofquantitative (bibliometrics) and qualitative method (primary data analysis), the paper
attempts to establish the trend of science disciplines’ fusion into nanotechnology. This
study is identified the concerned factors driving nanotechnology fusion, that would be agood evidence of fusing previously separate disciplinary activities into nanotechnology.
affected technological domains, are to be expected. This
paper compares the trends of scientific disciplines’
fusion into nanotechnology over time in the global
perspective and attempts to establish the patterns ofscience disciplines’ knowledge fusion into nanotech.
Attempts are then made to identify the main factors
driven for nanotech fusion.

1. Research Concern
Nanotechnology, an emerging technology with theability to control, manipulate and fabricate
nanostructures, has become a very active and vital areaof research which is rapidly developing and spreading toalmost every field of science and engineering disciplines.
Nanotechnology enables the design and manufacture ofcomponents, systems which are far more efficient thanthe existing ones, leading from discovery to the design of
new materials for particular applications. Many of thepotential benefits of nanotech arise from the fact thatengineered nanoscale materials exhibit chemical,
physical, and biological properties and behavior different
from those of the same materials in bulk or macroscopic
form [10]. The emergence of nanotech was enabled by
the development of specialist instruments which in turnfacilitated the observation and manipulation ofnanostructures at the nanometer scale (“nano” means
one-billionth of a meter) as well as the discoveries of
new nanomaterials [4] such as carbon nanotubes andfullerenes 1 , which offered a foundation for creating
nanoproducts with enhanced performance parameters ofelectronic, cosmetic, textile and other industries. It has
been estimated that nanotechnology is currently at alevel of development similar to early commercial
applications of information technology in the late 1960s
or to the emergence of biotechnology in the 1980s [11],and further impressive discoveries transforming theIt interprets the development of nanotechnology
using the framework of systems of innovation [2] [9],which is applicable on several levels – such as national,
regional, sectoral, or related to a specific technology,
which has an impact on various industries (as in the caseof nanotechnology). Systems of innovation related tonanotechnology can be thought of as a complex systemof different science and engineering disciplines on nanoscale, a set of actors engaged in the development,
diffusion and utilization of the technology, a linkage ofdifferent actors (who particularly focuses on a nanotech
domain,e.g.,
nanomaterials,
nanoelectronics,
nanobiotech, nanomanufacturing & tools) having
research collaborations and exchange mechanisms [5]. A
systems approach is needed to visualize the dynamics ofnanotech innovation. Techno-economic network (TEN)
provides a useful method of structuring and interpreting
the roles and linkages within a technological system [1][6] [8]. Nanotechnology is currently positioned just prior
to or at the beginning of commercialization. The present
research focuses on the Science pole (where academic
publications related to nanotech are regarded as viable
scientific output indicators) as well as on the Technology
pole where primary data on R&D systems (retrieved
through interviews with nanotech scientists andresearchers from universities and public research
institutes in Europe) stand a significant input to analyze.

1[Fullerenes called carbon 60, a new class of carbon material, arespherical molecules about 1 nm in diameter, comprising 60 carbon
atoms arranged as 20 hexagons and 12 pentagons: the configuration ofa football.
Carbon nanotubes (CNTs) are extended tubes of rolled grapheme
sheets, single-walled and multi-walled types. CNTs have assumed an
important role in the context of nanomaterials, because of their novel
chemical, physical and electrical properties. They are mechanicallyvery strong as stiff as diamond, flexible about their axis and canconduct electricity extremely well. All of these remarkable properties
give CNTs a range of potential applications: for example, in reinforced
composites, sensors, nanoelectronics and display devices etc]

This study is related to some other concerned
research on fusion, a pioneering work by Kodama on thetechnological opportunities of technology fusion [7]. The
most highlighted aspect of technology fusion is its
association with emerging technology and high102Technology Institute publications, over the period of
1995, 2000 and 2005) and qualitative method (primarydata analysis: conducting interviews with nanotech
academic scientists and researchers from university andpublic research institutes in Europe such as UK,
Germany, France, Switzerland and Italy). Based on theseanalyses, we attempts to establish the trend of science
disciplines’ knowledge fusion into nanotech.

technological opportunities. He argued that tightintegration of different technologies creates new values.
Unlike Rosenberg’s concept of technologicalconvergence that emphasizes generic technology,
technology
fusionemphasizes‘integration’characteristics [3]. In the case of nanotechnology, itneither forces technological convergence nor
technological integration, rather it bridges divergent
disciplines or brings different expert people to work
together at nano-scale, seamlessly applicable to manytechnologies or industries and thus explores thetechnology. Therefore, it is meaningful to investigate thetrend of nanotech fusion with multi-disciplines and how
it has changed over time and then identify the factors
behind it.

3. Nanotechnology Fusion Strategy

2. Research Methodology
The main objective of the present research is toinvestigate the trend of nanotechnology fusion withmulti-disciplines and how it has changed over time.
Nanotechnology is a prioritized field and the increased
funding is available. The general disciplines that were
not getting much funding, now have re-labeled what they
do as nanotech rather than general disciplines such as
chemistry, physics, material science, biology. It can beargued that to analyze the effect of re-labeling by theterm ‘nano’ from the traditional discipline based on
previously separate scientific streams of activity (e.g.,
Are nanotech researchers or scientists doing anything
different from what they did 10 years ago or did they justre-classify or re-label themselves?) would be meaningful.
Over time though scientists become more sophisticated,
they develop their own techniques, concepts, theories,
paradigms and may be a few decades later we certainly
realize that we have a new discipline such as
nanoscience2 (e.g., if we look at the history of science
subjects like biochemistry showing its distinctive activity
by merging chemistry and biology).
The question arises here how we measure the fusionof scientific disciplines into nanotech. In terms of fusing
disciplines together, a number of approaches wereconsidered: 1) Searching for a set of nanoscience papers
in each disciplinary journals at present, 5 years ago aswell as 10 years ago and their reference citations(finding what they cite and what proportions ofreferences were coming out or linking with each otherdisciplines; 2) Look for factors that drives multidisciplines’ fusion into nanotech, that would be a goodevidence of fusing previously separate disciplinary
activities into nanotech.
The analysis is based through a combination ofquantitative method (bibliometric exploration: relevantscientific outputs worldwide – nanotech-related
academic publications from SCI database, using
specialist keywords, derived from Nano Science andNanotechnology is highly prioritized area on the
global scientific agenda. Many countries worldwide
regard it as an interesting as well as an important area of
future exploitation, setting up national initiatives in orderto prepare for the technological challenge. In order toanalyze the performance of nanotechnology systems ofinnovation, we used bibliometric indicator as a measureof the output of the research system. Volumes ofscientific publications are a commonly acceptedindicator of scientific performance in specifictechnological domains – they help illustrate the existing
status and forecast future developments of a technology.
We analyzed the references of each disciplines’ nanotech
papers into disciplines by journals classified by ISI andinvestigated what proportions of references were comingor cited from the journals of different disciplines andhow it has changed over time [e.g., in three periods suchas the present (2005), 5 years before (2000) and 10 years
before (1995)]. This analysis was done for two
nanotechnology domains such as nanomaterials andnanoelectronics3. We have selected a set of nanotech
papers from each discipline and analyzed the references
linkage by multi-disciplines to establish the trend of
fusing disciplines. As demonstrated in Figure 1, fornanomaterials domain, it indicates that each discipline
citing references were strongly linked with the respective
discipline 10 years ago (1995), whereas this trend haschanged at present (2005), rather sharing nanotech
knowledge with different disciplines (i.e., focusing
multi-disciplines’ linkages). In the case of chemistryjournals, the share of cited references from chemistry
related areas was 64.47% in 1995, but dropped to40.65% in 2005. In the case of physics, material scienceand biology, it dropped from 74.39% to 53.71%, 39.02%
to 29.15% and 54.12% to 36.02% respectively. On theother hand, the share of cited references from otherdisciplines has grown over last 10 years period. With theevolution of nanotechnology, the basic research trend by
disciplines has been changing over time from more
separate disciplinary base to a more multi-disciplinary
type (i.e., moved from a system or culture of specific

3 [Earlier we have characterized 4 nanotechnology domains such as
nanomaterials, nanoelectronics, nanomanufacturing & tools,
nanobiotechnology by using Engineering Index (EI) defined by
Elsevier Compendex. For every domain, detailed lists of relevant EI
codes were identified – specific domains corresponded in general todistinctive EI classes (bionanotechnology: EI code 4.x, nanoelectronics:
EI codes 6.x and 7.x, nanomaterials: EI codes 5.x and 8.x,
nanomanufacturing/tools: EI code 9.x)]2[Interview with Professor Ben Martin, Former Director of SPRU,
University of Sussex]

103fields or topics into something that is mixing in the nanoscale). This may be the cause of new nanomaterials
discovery (such as carbon nanotubes, fullerenes etc) as
well as the development of techniques (such as nanotools STM, AFM etc) to control and manipulatematerials on the nano-scale.

but now the trend has changed with having much scopeof utilizing techniques to explore unfocused areas.
Researchers are more interested or have to interact withresearchers from other disciplines to share their expertiseor knowledge to uptake more efficient outcome throughnanotechnology. In addition, this only happens as amulti-disciplinary approach, trying to break down of theboundaries of all scientific disciplines. However, theconcept of nanotech does not allow a specificdisciplinary knowledge, rather blurring of multidisciplinary disciplines.

80

Perce n t a g e ci t es

70

Chem

60
fore ca st ing

50

Phy
Mat Sci

40

Biol

30

Multidis20

Nano Sci

Having analyzed in some detail the extent andtrend to which nanotechnology research is fused withmulti-disciplines over the period from 1995 to the end of
2005; we are now in a position to draw some
implications relevant to nanotech fusion with disciplines.
Based on the interviews, an analysis is made toinvestigate the concerned factors relevant to multidisciplinary fusion into nanotech. The interview
responses tended to conform to certain patterns and it istherefore relatively easy to identify them into a numberof separate categories and the related factors.

10
0

1995

2000
2005
Tim e Periods

2010

Figure 1. Trend of nanotech fusion in the materials
domainFor electronic domain, the same trend appears but
shows relatively more fusion with diversified disciplinesat present, as illustrated in Figure 2. In the case ofchemistry journals, the share of cited references fromchemistry related areas was 67.85% in 1995, but theshare dropped to 37.26% in 2005. In the case of physics,
material science and biology, it dropped from 77.69% to43.16%, 53.26% to 33.69% and 61.65% to 34.11%
respectively. On the other hand, the share of citedreferences from other disciplines has grown over the last
10 years period and balanced the gap. Nanotech
evolution derives basically from taking advantages ofscientific opportunity that could allow researchers toundertake or share multi-disciplinary research by
90
80
Chem

Pe rce n t a g e ci t e s

70

Phy

60

f ore ca st ing

50

Mat Sci

40

Biol

30

Mult idis

20

Nano Sci

10
0

1995

2000
2005
Tim e periods

2010

Most of the European scientists believe that
nanotechnology enables people to move from a systemof specific areas into something that is a bridge of multifields in nano-scale. In this sense, one expert from one
field may crosscut with another expert and develop somecross-linkages, help move very separate disciplinary
system into a more homogeneous system. The trend of
nanotech fusion emphasizes in converging all scientificdisciplines since it is an interface of all disciplinary
fields due to having nano-scale. Some experts believethat the starting point for such fusion is scientificopportunity that could begin to address a new system(e.g., biological system for physicists, engineers etc)4.
Therefore, it would be a very real scientific opportunity
to begin fusing disciplines by coming together andtaking elements from each of the discipline. Anotherextremely important factor appears to have been the relabeling research topic, because it is quite fashionable
now a day to pull funding for research by traditional
disciplines in this competitive age. The most basic point
would be new nanomaterials discovery with novel
properties and function as well as new applications, andthe development of techniques to observe, manipulate
and fabricate the nanostructures. The interview analysis
is summarized in Table 1, which lists the relevant factors
related to the categories cited by 20 percent or more of
the interviewees.

4. Conclusion

Figure 2. Trend of nanotech fusion in the electronics
domainNanotechnology has been recognized as an expansion
area of the research fields nowadays in almost allscientific and technical disciplines worldwide atuniversities, public research institutes as well as inutilizing nano-tools on ‘nano’ theme. In the earlier
period, researchers linked with their respective
disciplines’ research due to lack of much instruments,

4[interview with Professor John Ryan, Director of IRC
Bionanotechnology, University of Oxford]

104

Table 5.5: Factors explaining nanotechnology fusion in the case ofEurope (percentage of interviewees believing this factor to have been
important)i) Converging all scientific disciplines into nanotech
since it is an interface of all areas due to nano-scale
90ii) Bringing people (scientists, engineers,
Trend of
Nanotech Fusion researchers) of different background to work65
togetherwith Multiiii) Addressing a homogeneous system for all
disciplines
scientific and engineering disciplines to grasp or 35
achieve scientific opportunityi) Re-labelling the research topic
90ii) Introduction of new nanomaterials (such as
CNTs, fullerene) with novel properties and new
Factors of70
Fusing Scientific applicationsiii) Development of techniques or instruments to
Disciplines
control the function and manipulate materials in the55
nanometer scale

universities and public research institutes in
UK, Germany, France, Switzerland and Italy.
COE of SIMOT at Tokyo Institute ofTechnology was partially supported thisstudy — which provided financial support
for the fieldworks in Europe in 2006.

References[1] Bell, G., Callon, M., 1994. “TechnoEconomic Networks and Science andTechnology Policy,” STI Review,
OECD, 14, 59-118.
[2] Carlsson, B., Jacobsson, S., Holmen,
M., Rickne, A., 2002. “Innovation
systems: analytical and methodologicalissues,” Research Policy, 31, 233-245.

[3] Hwang, J., 2005. “How DoesTechnology Fusion Generate Technological
Opportunities?” STEPI International Symposium
on Science and Technology Policy, Korea.

companies. It has been of importance to investigate how
different disciplines’ are facing nanotech and fusing into
it, and what would be the trend of fusion over time andwhat were the factors concerned with this evolutionary
technology development.

[4] Islam, N., Miyazaki, K., 2006. “Nanotechnology
Innovation System - Strategic Perspective,”
International Journal of Knowledge and Systems
Sciences, 3(1), 34-42.

The research identified the concerned factors relevant
to nanotechnology fusion with multi-disciplines byinvestigating both bibliometrics and primary data
analysis (interviews). The research analyses pointed tothe existence of strong links between researchorientations of specific disciplines, suggesting thepotential for nanoscientific research worldwide. The
findings showed that the basic research trend by
disciplines has been changing over time from more
separate disciplinary base to more multi-disciplinary typein both cases for nanomaterials and nanoelectronics
domains. In the earlier phase, researchers linked with
their respective disciplines’ research, but now they areinterested to share their expertise or knowledge to uptake
more efficient outcome through nanotechnologies, trying
to break down the boundaries of all scientific disciplines.

[5] Miyazaki, K., Islam, N., 2007. “Nanotechnology
Systems of Innovation - An Analysis of Industry
and Academia Research Activities”, Technovation,
27, 661-675.
[6] Klincewicz, K., Miyazaki, K., 2005. “Software
Systems of Innovation in Asia: Empirical Analysis
of Industry and Academia Research Activities,”
STEPI International Symposium on Science andTechnology Policy, Korea.
[7] Kodama, F., 1991. “Analyzing Japanese HighTechnologies: The Techno-Paradigm Shift,”
London: Pinter Publishers.
[8] Kumaresan, N., Miyazaki, K., 1999. “An Integrated
Network Approach to Systems of Innovation-theCase of Robotics in Japan,” Research Policy, 28,
563-585.

The authors finally identified the most relevant
factors related to nanotech fusion with multi-disciplines,
such as i) scientific opportunity; ii) nano-scale researchexperiences; iii) strong interest of government andindustry and collaboration with them; iv) re-labeling the
research theme; v) new nanomaterials discovery withnovel properties and lot of applications; vi) developing
techniques to be able to control, manipulate and fabricate
nanostructures; and vii) multi-disciplinary research type.
The policy makers can benefit from the findings ofnanotechnological research fusion with traditional
disciplines. The institutional authorities such asuniversity, public research institute and industry
authority can also benefit by their increasing
competitiveness in nanotechnology activities.

[9] Malerba, F., 2002. “Sectoral systems of innovationand production,” Research Policy, 31, 247-264.
[10] NSTC [National Science and Technology Council]),
2006. “The National Nanotechnology Initiative:
Research and Development Leading to a
Revolution in Technology and Industry” Report.
[11] Roco, M., 2005. “International Perspective on
Government Nanotechnology Funding in 2005,”
Journal of Nanoparticle Research, 7(6), 707-712.

Acknowledgement
The authors gratefully acknowledge by giving
thanks to nanotech scientists and researchers from105

Short comments on my research in SIMOT program
Seunghye Hong**

Department of Innovation
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
hong.s.aa @m.titech.ac.jp
Comments on reports
As a first-year Ph.D. student, I felt much encouraged to do my research on the mobile
telecommunication industry during the SIMOT program. I wrote RA report titled "Continuous
Improvement and Innovation in Manufacturing Firms" and “Mobile Sector Ecosystem-Actor
Networks as the Key to Innovation and Diffusion of Mobile Services”, however, they are notappearing here. These reports are only the initial results, and I will study harder to continue thisresearch.

Comments on Poster paper
I wrote a poster paper for the 5th Annual International Symposium, which was titled " The Diffusionof Mobile Broadband Services and the Role of Standards in the Mobile Sector Ecosystem”, however,
it is not appearing here. The poster paper is only the initial results. The research models used in theposter paper will be developed and tested to better identify the current mobile telecommunicationindustry in the future research.

106

Ranking and Selecting Terms for Text Categorization via SVM Discriminate
Boundary
Tien-Fang Kuo and Yasutoshi Yajima **Department of Industrial Engineering and Managemen
Tokyo Institute of Technology
2-12-1 W9-526 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
kuo@me.titech.ac.jp
The problem of natural language document categorization consists in classifying
documents into predetermined categories based on their contents. Each distinct term, orword, in the documents is a feature for representing a document. In general, the numberof terms may be extremely large and the dozens of redundant terms may be included,
which may deteriorate the performance of classification.
In this paper, an SVM based feature ranking and selecting method for text
categorization is proposed. The contribution of each term for classification is calculated
based on the nonlinear discriminate boundary generated by support vector machine(SVM). The results of experiments on the Reuters-21578 dataset show that the proposed
method achieves higher classification performance than existing feature selection based on
LSI andχ2 statistics values.

1. Introduction
Document classification is one of the mostimportant research areas in information retrieval.
Many supervised learning algorithms have been
proposed for this purpose. Among them are
Rocchio [11], naive Bayes [9], and k-nearest
neighbor [16]. In these algorithms, a document isrepresented using a vector where each componentof the vector corresponds to the frequency of a term,
or a word, appeared in the document. Usually, ahuge number of dimensions are required torepresent documents written in natural languages.
In most practical situations, the highdimensionality of the vector is a crucial problem indocument classification. In order to remove
extraneous information or noise from the data, andto improve computational efficiency, there is a needto reduce the dimension of the original space.
Latent Semantic Indexing (LSI) [3] is a commonlyused tool for the dimensionality reduction. In LSI,
one has to calculate the singular value
decomposition (SVD) of a document-by-term
matrix which consists of the document vectors in its
columns. Empirical researches have shown that LSI
could be an effective method in the field of
information revival and document classification.
Also, several modifications have been proposed to
improve the classification accuracies [2], [4], [13].
It should be noted that, however, a considerable
amount of computations and memory are required
to calculate the decomposition, which mightprohibits the use of LSI when the number of
documents or terms are quite huge. Also, the basic

107

idea underlying LSI is that there exists a latent
structure in the collection of the documents, andSVD enables us to extract a number of featuresreflecting the whole structure of the collection.
These features might be irrelevant to theclassification.
In this paper, we are going to propose a method
for feature selection and ranking based on anonlinear classifier generated by Support Vector
Machines(SVM) [13], which have been widely
accepted as a promising tool for documentclassification [6]. Although SVM is required to
optimize a quadratic programming problem togenerate
discriminate
functions,severalsophisticated algorithms [5], [9], [10] enables us tosolve huge problems in a practical amount ofcomputational time. Recently, Zhang and Liu [17]have introduced a method for characterizing
important features based on the nonlinear SVM
classifier, and the associated decision boundaryfeature matrix (DBFM) [7]. Motivated by these
papers, we will introduce a computationallyefficient method for calculating the contribution ofeach term in classifying the documents, even when
the documents are represented by a huge number ofterms. In section 2, we will introduce SVM and
DBFM. Section 3 is devoted to describe the detailof the proposed method of feature ranking andselection. Finally, we will show the performance ofour method on the Reuters-21578 dataset.

Several properties of the RBF function are
exploited in this paper. It have been known that theparameter σ in (3) controls the flexibility of theassociated transformation φ(･). One can generate
discriminate functions which classify any labels
correctly to use sufficiently small value of σ. In
such a case, the matrix K becomes close to theidentity matrix. In general, the following
proposition holds:
Proposition 1: Suppose that a kernel function
K( ･ , ･ ) generates a positive definite, i.e.,
nonsingular matrix K. Then, there exists a vector w∈F such that

2. Preliminaries
2.1 Support Vector Classification
Let us consider the problem of generating
discriminate functions for a set of M given training
vectors denoted by D={(x1,y1),…, (xM,yM)}, wherexi ∈ RN is the i-th training vector with N
dimensional attributes, and yi ∈ {-1,+1} is theassociated binary label. In the standard SVM,
nonlinear transformation φ which maps the vector
xi into a high dimensional feature space F isemployed to find a hyperplane <w,φ(x)>+b=0 todiscriminate the training vectors, where < ･ , ･ >denotes the inner product in the feature space F.
SVM generates a vector w in F and a real number b,referred to as a bias term, by solving the following
optimization problem:
Min. 1/2<w,w>+C Σ iM=1 ξis.t. yi(<w,φ(x)>+b)≧1-ξi
ξi≧0, i=1,2,…,M.

<w,φ(xk)>=yk, k=1,2,…,M.

Proof: Let us assume that the vector w∈F isgiven as a linear combination of φ(xk)’s, that is, w= Σ iM=1 βiφ(xk). Let β=(β1β2…βM)T. Then, theequation (4) can be written as

(1)

Kβ=y.

Here, let K denote a symmetric M×M matrix
whose i-j element Kij is the inner product between
the transformed images of the vectors xi and xj, i.e.,
Kij =<φ(xi),φ(xj)>. Also, let e∈RM be a vector of
all ones, a vector of labels y=(y1y2…y M)T, and Y be
an M × M diagonal matrix consisting y as the
diagonal elements. Then, introducing a vector ofdual variable α=(α1α2…αM)T, the problem (1)is equivalently optimized by solving the following
so called dual formulation:
Min. 1/2αTYKYα-eTαs.t. yTα=00≦α≦eC.

Since K is nonsingular, this equation always hasa solution β= K-1y, which completes the proof. ■Therefore, we can assume that the set oftraining vectors D can be classified by an unbiased
linear function g(x)=<w,φ(x)>, which is obtainedby solving simpler primal and dual problems given
as follows:
Min. 1/2<w,w>+C Σ iM=1 ξi(5)s.t. yi<w,φ(x)>≧1-ξi
ξi≧0, i=1,2,…,M.

(2)

Min. 1/2αTYKYα-eTαs.t. 0≦α≦eC.

It has been known that one can calculate theinner product directly from the vectors xi, xj by akernel function K(xi, xj). Throughout this paper, we
will focus on the following radial basis function(RBF) as the kernel function:
K(xi, xj)=exp(-||xi-xj||2/2σ2),

(4)

(6)

2.2 Decision Boundary Feature Matrix
Now, suppose that we have generated an
unbiased discriminate function by solving the dual
formulation (6). In the rest of the paper, forsimplicity, let us denote an optimal solution of the
problem (6) as α=(α1…αM)T without adding theasterisk, “*”. Then, the discriminate boundary isgiven as follows:(3)

where σ is a parameter controlling thenonlinearity of the transformation φ(･). The RBF
kernel is one of the most popular kernel functions
and successfully applied to many classification
problems.
Now, let α *=( α 1* α 2*… α M*)T denote an
optimal solution of (2), then the associateddiscriminate function is given by

B={x∈RN | Σ iM=1 αiyiK(xi, xj)=0}.

(7)

Associated with the boundary, Lee andLandgrebe [7] have introduced the idea of
discriminantly redundant and discriminantly
informative directions which are defined below:
Definition 1: Let v∈RN be a vector with theunit length, and U be the projection matrix defined
as U=I-vvT, where I is an identity matrix of order N.
Then, associated with the discriminate boundary B,
v is called a discriminantly redundent direction if

g(x)= Σ iM=1 αi*yiK(xi, x)+b*,
where b* is calculated by b*=yk- Σ iM=1 αi*yiK(xi,x), for an arbitrary index k such that 0<αk*<C.

108

nonlinear. Therefore, we need to select points
which are located closely to the boundary, which
requires to calculate the distances for every pair ofvectors lying on the different side of the boundary.
Moreover, we have to use an iterative proceduresuch as a binary search to solve the equation (10).
In the next section, exploiting the special structureof the RBF kernel function (3), we will propose an
efficient method for generating the points on thediscriminate boundary, as well as their gradientvectors, only by the elementary matrix and vector
calculations.

g(xi)g(Uxi)>0 holds for any vector xi. Similarly, v iscalled a discriminantly informative direction if there
exists a vector xi such that g(xi)g(Uxi)<0.
We note that we can arbitrary change the vector
xi along the direction v without changing theclassification result if v is a discriminantly
redundant direction, i.e.,g(xi)g(xi+λv)>0, ∀λ∈R
Furthermore, Lee and Landgrebe haveintroduced the following decision boundary featurematrix (DBFM) ΣDBFM to extract those directions.
ΣDBFM=1/p∫B{∇g(x)∇Tg(x)/||∇g(x)||2}p(x)d(x),3. SVM Based Feature Ranking
3.1 Calculating Gradient Vectors on the(8)

Boundary
Let us first consider calculating the vectors
which are lying on the discriminate boundary. The
key idea of our method is to generate such vectors
in the feature space F rather than in the original
input space RN. For each training vector xk(k=1,2,…, M), letφ(xk)∈F denote the mapped
image of xk. Also, recall that the discriminate
function is expressed as the linear function <w,φ(x)>=0, where w∈F.
Now, for each mapped data point φk∈F, let
us definewhere p(x) is a probability density function of
the data and P=∫Bp(x)d(x).
Now, let λi and v∈RN denote the eigenvalues
and eigenvectors of Σ DBFM, respectively. Also,
assume that there exist r nonzero eigenvalues which
are sorted so that
λ1≧λ2≧…≧λr≧λr+1=…=λN=0.
Then, any vector v which belongs to thesubspace spanned by the eigenvectors vr+1, vr+2,…,
vN is orthogonal to all the gradient vectors ∇g(x’k)
on the boundary B, which implies that v is adiscriminantly redundant direction. On the other
hand, the directions belonging to the eigenvectors
with nonzero eigenvalues are essential with respect
to the classification. The following theorem given
by Lee and Landgrebe [7] summaries this.
Theorem 2: The eigenvectors of the DBFM ofa pattern recognition problem corresponding to
non-zero eigenvalues are the necessary feature
vectors to achieve the same classification accuracy
as in the original space for the pattern recognition
problem.
Let us now consider calculating the DBFM,
practically. First, suppose that we have a sufficientnumber of vectors x’1,…, x’l lying on the boundary.
Then, the DBFM can be approximated as follows:

φ’k=φk-θkw,

where θk=<w,φk>/<w,w>. It is obvious to see
thatφ’k is on the boundary and is the closest point
to φk. Therefore, if we can find the pre-image of
φ’k, i.e., the point x’k∈RN such thatφ(x’k)=φ’k,
we can obtain gradient vectors at x’k corresponding
to the given training vectors xk.
As we assumed in the previous section, we
generated an unbiased nonlinear discriminate
functiong(x)= Σ iM=1 αiyiK(xi, x),(12)where the αi’s are obtained by optimizing the
problem (6) and K(･,･) is assumed to be a RBF
function (3). Then, a straightforward calculationshows that the gradient vector at x’k ∈ RN is
expressed aslΣ’DBFM=1/l Σ i =1 {∇g(x’i)∇Tg(x’i)/||∇g(x’i)||2}. (9)However, in the training data, quite few vectors
are on the boundary.
Recently, Zhang and Liu [16] numericallygenerates a point on the boundary by choosing two
training vectors xi, xj such that g(xi) g(xj)<0, and bysolving the following equation with respect to θg(θxi+(1-θ)xj)=0.

(11)

M

∇g(x’k)= Σ i =1 αiyiK(xi, x’k)(xi-x’k).

(13)

Moreover, since the vector x’k∈RN lies on theboundary, i.e.,Σ iM=1 αiyiK(xi, x’k)=0,(10)

the equation (13) can be simplified as follows:

It should be noted that the solution of theequation (10) is not always unique when g isM

∇g(x’k)= Σ i =1 αiyiK(xi, x’k)xi.

109

(14)

the training vector xi corresponding to the nonzero
optimal solution α i is referred to as a support
vector. Moreover, as noted in [7], Σ’DBFM should
be constructed using the gradient vectors lying on apart of the discriminate boundary intersecting withthe region where most of the training data vectors
are located. We approximately accomplish this bygenerating boundary points from the the training
vectors xi lying inside the margin, i.e., the training
vectors satisfying -1<g(xi)<1. Note that thosetraining vectors are shown to be support vectors(see, for instance [12]).
Now, for simplicity, assume that the first L
training vectors x1, x2,…, xL correspond to the
support vectors, and that αL+1=αL+2=…=αM=0.
Also, let us define the associated L dimensional
sub-vectors g*, α*∈RL, sub-matrices Yα*, K*∈
RL×L, and X*=[x1x2…xL]∈RM×L, associated withthe support vectors. Then, it is obvious to see thatthe equation (17) can be equivalently calculated asfollows:

The following lemma enables us to calculate
the gradient ∇ g(x’k) without knowing the preimage x’k.
Lemma 3: Assume that SVM generates thediscriminate function given in (12). Let xi, xk∈RN
be arbitrary data vectors, andφi, φk ∈F be thecorresponding images of xi and xk, respectively.
Also, let x’k be the pre-image of the boundary
pointsφ’k defined by (11). Then, the following
equation holds:
K(xi, x’k)=K(xi, xk)-θk Σ iM=1 αiyiK(xi, xj).

(15)

where
M

xj’).

M

M

θ k= Σ j =1 α jyjK(xj, x)/ Σ j =1 Σ j '=1 α j α j’yjyj’K(xj,Proof: Since the kernel function gives the innerproduct in the feature space, we haveK(xi, x’k)=<φi,φ’k>=<φi,φk>-θk <φi,w>=<φi,φk>-[<w,φk>/<w,w>]<φi,w>.

[∇g(x’1)…∇g(x’L)]=X*Yα*(K*-g*g*T/α*TK*α*). (18)(16)

Note that the vector w∈F is given as w = Σ Mj=1
αjyjφj . Then, we substitute w into to yield theequation (15), which completes the proof.
■
In summary, gradient vectors ∇ g(x’k)(k=1,2,…, M) can be calculated in the following
way. Let X=[x1…xM] denote an N × M matrix
consisting of the training vectors, g=[g(x1)…g(xM)]T,
α=(α1…αM)T, and Yα is a M×M matrix with its
i-th diagonal element be αiyi. Then, we have thefollowing expression to calculate a set of gradientvectors on the boundary.
[∇g(x’1)…∇g(x’M)]=XYα(K-ggT/αTKα). (17)It should be emphasized that, although thematrices inside the parentheses in (18) are fully
dense, the size of those, L, are small enough so thatthey can fit in memory. Let∇g*(x’1)=∇g(x’1)/||∇g(x’1)||, (i=1,2,…,L)
and∇G=[∇g*(x’1)∇g*(x’2)…∇g(x’L)],

we can obtain the DBFM as follows:Σ’DBFM =1/L(∇G∇GT).

(19)

Finally, let us consider to calculate thecontribution of each term for classification. As
described in Section 2.2, the eigenvector v∈RN
corresponding to the nonzero eigenvalues of
Σ’DBFM are essential directions for the classification.
The magnitude of eigenvalue can be considered toreflect the importance of the direction for thediscrimination. Then, let us introduce the following
function F(v) to measure the importance of thedirection v.
Definition 2: Let v∈RN be an arbitrary vector
with the unit length. The contribution of thedirection v for discrimination is defined as

Here, it should be noted that, in many textclassification tasks, the number of training vectors(M) as well as that of terms (N) are quite huge. In
order to calculate this expression practically,
several properties of SVM should be exploited,which will be described in the next section.
3.2 Ranking and Selecting Terms
In this section, we will discuss a practicalprocedure for constructing Σ’DBFM given in (9), as
well as that for selecting important terms for thediscrimination based on the DBFM.
In has been commonly observed that an optimal
solution of the problem (2) contains a small numberof nonzero variables, which makes it possible tooptimize the problem (2) with a huge number ofvariables in a practical amount of time. Note that

F(v)=vTΣ’DBFM v.
Obviously, the maximum of the F(v) is attainedby an eigenvector corresponding to the maximum

110eigenvalue of Σ ’DBFM. Therefore, for each term
i=1,2,…,N, let ei∈RN denote the i-th unit vector,
the amount of contribution of the i-th term will begiven as F(ei)=eiTΣ’DBFM ei which is equivalent to
the i-th diagonal element of the Σ’DBFM.

For each category, we consider a binaryclassification problem which distinguishes one
specific category from other categories. We first
generate a nonlinear discriminate boundary bysolving the unbiased formulation (6). As describedin Section 3.2, we only use the vectors locatedinside the margin to generate gradient vectors, andobtain Σ’DBFM given in (19). We extract a numberof terms based on the magnitude of the diagonal
elements of Σ’DBFM. Then, we generated training
and test vectors only with the selected terms. We retrain the vectors by solving the standard SVMs
given in (2) with the RBF kernel with the same
parameter settings.
We use a method of latent semantic indexing(LSI) as well as χ 2 statistics to compare theperformance. In LSI, we apply SVD to the
document-by-term matrix corresponding to thetraining articles, and extract a number of features
based on the singular values. Then, we project theoriginal training and test vectors onto the spacespanned by the extracted features and apply thestandard SVMs with the RBF kernel. It should be
mention that the features extracted in LSI do notdepend upon the categories and that the resulting
projected training and test vectors are no longer
sparse.
In this experiments, the number of selectedfeatures ranges from 10 to 100. Figure 1 and 2 show
the performance curves of the test set precisionrecall breakeven points (BEP) generated by the
propose method (indicated by DBFM), LSI andχ2
statistics [15] values for the categories “earn” and“ship”, respectively. Also, Table 2 summarizes theresults of the maximum BEP and the associated thenumber of selected features up to 100, as well as the
BEP when we use all 9370 features (denoted by“ALL”). The highest BEP, as well as the smallest
number of features among the three methods aremarked by bold font.

4. Numerical Experiments
In this section, we will report the performanceof our feature ranking method based on thediscriminate boundary generated by SVMs with the
RBF kernel (3). The experiments are conducted on
the Reuter-21578 dataset which is a commonly usedbenchmark collection for text classification. The
standard “ModApte” split is used to extract 7063
training and 2742 test articles. Also, as in manyother papers, we have considered the top ten mostfrequently occurring categories. Table 1 shows thenames of such categories and the number of articles
contained in training, test, and the whole set,
respectively. After stemming and stop word
removal by the rainbow program, a part of the Bow
toolkit [8], frequency of each term is counted. We
extract 9370 distinct terms excluding the one
appears less than in 3 articles, and TF-IDF term
weighting is used to represent each article as avector. We use SVMlight [5] to optimize theproblem (6) with a fixed value of C=1000 and the
RBF parameter 1/2 σ 2=0.01 throughout theexperiments. It also can be expected that the
proformance may be improved by tuning the valueof C and σ.
Table 1. Top 10 categories and the numberof articles in Reuters-21578

Name
Train
Test
Total
earn
2709
1044
3753
acq
1488
643
2131
money-fx
460
141
601
grain
394
134
528
crude
349
161
510
trade
337
112
449
interest
289
100
389
ship
191
85
276
wheat
198
66
264
corn
159
48
207
Preprocessed version of Reuter-21578 available
from: http://www.cs.technion.ac.il/ronb/thesis.html

Table 2. P/R-breakeven points (%) for ten
categories
categoryearn
acqmoney-fx
grain
crude
trade
interest
ship
wheat
corn

Most of the classification performance isevaluated by accuracy. For the data set with only
small proportion of positive patterns, using
accuracy in measurement of performance may get a
trivial classifier that classifies all patterns tonegative class achieves with high accuracy. Thus,
precision-recall breakeven points is used in text
categorization to measure the appropriateclassification performance.

DBFM
98.37(70)
94.71(100)76.60(60)
92.54(40)
86.34(100)76.79(100)77.00(40)64.71(80)90.91(40)
89.58(70)χ298.08(90)93.16(100)75.18(60)
91.79(90)84.47(60)72.32(40)76.00(100)72.94(50)90.91(50)
89.58(30)LSI
98.08(90)93.78(100)74.47(80)82.09(70)86.34(100)73.21(80)72.00(90)89.41(10)89.39(60)77.08(10)

ALL
98.76
95.80
78.01
88.06
90.06
83.93
76.00
82.35
83.33
83.33

The number of selected features are given inparethesis.

111

provides a mean to enhance the effectiveness in text
categorization tasks and other classification
applications for SIMOT.
References

Fig. 1. BEP(%) for the category earn.

Fig. 2. BEP(%) for the category ship.

We see from Table 2 that the proposed feature
selection method achieves the highest BEP for nine
categories. Also, the performance curve given in
Figure 1 shows typical behavior of our method
which outperforms other two methods over a wide
range of the number of selected terms, except thecategory “ship” (see Figure 2). Moreover, except a
few categories (“ship” and “trade”), the proposed
procedure generates almost the same, or better
results than the case without feature selections.
5. Conclusion
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by calculating the contribution of each term forclassification. In the proposed procedure, several
properties of SVMs with RBF kernel functions are
exploited to calculate the vectors lying on the
nonlinear discriminate boundary. We show thatthese vectors, as well as their gradient vectors, canbe calculated efficiently only by the elementary
matrix and vector calculation. The results ofnumerical experiments on the Reuter-21578 dataset
show that the proposed method achieves higher
classification performance than that based on LSI
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Customer Satisfaction and Life Satisfaction:
Cross National Comparative Study of Cultural Influences
Mizuho Ogikubo**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-57 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANogikubo.m.aa@m.titech.ac.jp
The purpose of this study is to investigate influential factors of customer satisfaction
and life satisfaction and discuss possible common structures between them. Comparing
aggregate-level data of customer satisfaction and life satisfaction from ten countries, theimpacts of national culture was analyzed. The results indicated positive correlation
between customer satisfaction and life satisfaction, and customer/life satisfaction is higher
in countries where uncertainty avoidance is weak and individualism is high.

1. Introduction
Globalization and diverging consumer needs
have made it increasingly important to understandinstitutional contexts of consumer behavior. While
there were little cross national study on customer
satisfaction, life satisfaction has been widely
studied for a long term by analysis within a country,
across countries, and over time. Comparing
customer satisfaction and life satisfaction, thispaper examines cultural and economic influences.
In the reminder of this paper, parts of the results
will be presented and implications for SIMOT
framework will be discussed.
2. Theoretical Backgrounds and Hypothesis
According to the prevailing theory, customer
satisfaction is determined by the relative
discrepancy between consumers’ prior expectations
and their evaluation after consumption (called
perceived quality). In other words, satisfaction
occurs when perceived quality exceeds expectations,while dissatisfaction occurs if perceived quality isworse than expected.
In recent years, a significant development incustomer satisfaction research has been theemergence of National Customer Satisfaction
Indexes that not only measure customer satisfaction
at the individual company level, but also provide
aggregated results at the industry, sector, andnational economy levels (e.g. Fornell et al., 1994).
Adopting the similar measurement methodology,
such indexes have been operating in USA, Sweden,
Germany, Denmark, Finland, Hong Kong, Iceland,
Norway, South Korea and several other countries.
The standardized methodology of National
Customer Satisfaction Index has enabled broadbased comparison among industries or countries
though it is still in an initial stage. Johnson et al.

113(2002) reported that customer satisfaction is higher
in USA than in Sweden and Germany, while
Sweden and Germany are almost in equal scale.
They usually attributed cross-national differences toeconomic competitiveness, but this kind ofargument does not consider much of cultural orother institutional contexts.
Life satisfaction is defined as “the degree towhich someone evaluates positively the overall
quality of his or her present life as a whole”. Since
it is an elusive concept and its definition differs byindividuals, the self-evaluation of one’s life is left
to the individual. In this regard, it is said that aneffective measure of life satisfaction is asking thisquestion: “How satisfied are you with your life as awhole?” (Diener and Suh 2000)
There have been a number of researches on
institutional factors of life satisfaction. For example,
it was reported that political, economic, andpersonal freedom are strongly correlated with life
satisfaction (Veenhoven 2000). Wealthy countries
are happier on average than poor ones. However, indeveloped countries, life satisfaction increased
surprisingly little over the last several decades inspite of the expansion of their wealth. In the case ofJapan, where income per capita increased by almost
six times since 1958, average happiness remained
constant over the same period (Frey et al., 2002). It
was also reported that unemployment has a strong
negative effect on life satisfaction.
Comparing the hypothesized models, customer
satisfaction is determined by the degree to which
the actual performance fulfills or falls short of thelevel of consumers’ expectations, whereas life
satisfaction is determined by the degree to which
their aspiration levels are achieved. On both models,satisfaction occurs by the achievement of
individuals’ evaluation standards.

3. Analysis of Cross National Difference
To examine the relationship between cultural
factors and customer/life satisfaction, National
Customer Satisfaction Indexes are available from
Sweden, South Korea, Germany, US, Hong Kong,
Denmark, Finland, Iceland, and Norway for theyears of 2003-2005. Although Japan does not havesuch an index, the own survey data of 2004
measuring customer satisfaction with durable goods
were used as a proxy measure. As a comprehensive
and widely authorized measure of national culture,
Hofstede’s (2004) four dimensions are employed:
uncertainty avoidance, individualism/collectivism,
power distance, and masculinity/femininity.
Table 1 provides Hofstede’s cultural dimension
scores and customer/life satisfaction scores
averaged over 2003-2005 for the ten countries.
Customer satisfaction is highest for U.S. andfollowed by Finland, Denmark, Iceland, Hong
Kong, Sweden, Norway, Germany, Japan, andSouth Korea. This ranking seems to correspondwith economic competitiveness as there is apositive correlation between GDP per capita andcustomer satisfaction (r = 0.545, p < 0.003, n = 28)
and life satisfaction (r = 0.595, p < 0.004, n = 21).
Customer satisfaction and life satisfaction ineach country averaged over 2003-2005 is presented
in Fig. 1. It should be noted that life satisfaction ispositively correlated with customer satisfaction (r =0.816, p < 0.001，n = 20). South Korea and Japan
where uncertainty avoidance is quite strong andindividualism is low show lower levels both ofcustomer satisfaction and life satisfaction. On theother hand, Finland and Denmark, which areincluded in high-individualism society, show higher
levels of customer satisfaction and life satisfaction.

Customer Satisfaction (2003-2005 Average)

80

Hofstede's Cultural Dimension Score

CS

LS

16

71.7

81.5

26

73.0

78.4

35

66

63.9

63.7

25.0

68.0

57.0

68.8

71.4*2

N/A

N/A

N/A

N/A

69.5

77.6*3

South Korea

85.0

18.0

60.0

39.0

52.5

66.5*4

Norway

50

69

31

8

66.1

76.0*5

UAI

IDV

PDI

MAS

Denmark

23

74

18

Finland

59

63

33

Germany

65

67

Hong Kong

29.0

IcelandSweden

29

71

31

5

66.5

75.4

USA

46

91

40

62

73.7

76.0

Japan

92

46

54

95

61.5

56.2*6

USA

70

SW E
65

FIN

DEN

ICE

HOK

NOR

GER
JPN

60

55
KOR
50
55.0

60.0

65.0

70.0

75.0

80.0

85.0

Life Satis faction (2003-2005 Average)

Fig. 1. Correlation between Customer Satisfaction andLife Satisfaction

Correlation coefficients between the culturaldimension scores and customer/life satisfaction arepresented in Table 2. Both customer satisfaction
and life satisfaction seem to be positively correlatedwith individualism and negatively correlated withuncertainty avoidance and power distance. The
same tendency can be observed with life
satisfaction.
Table 2 Correlation between Cultural Dimension
Scores and Customer/Life Satisfaction
Customer Satisfaction

Life Satisfactionrp-valuer

p-value

1. UAI-0.712 **0.000

1. UAI-0.675 **0.000

2. IDV
3. PDI
4. MAS

0.657 **
-0.480 **-0.194

0.000
0.008
0.176

2. IDV
3. PDI
4. MAS

0.374 *
0.079
-0.556 **0.006-0.1200.585*p < 0.05, **p < 0.01.

In order to further examine the magnitudes ofimpacts of national culture and economy, multiple
regression analysis was conducted using customer
satisfaction as the dependent variable and the four
cultural dimension scores and GDP per capita as
explanatory variables. Since the cultural dimension
scores are correlated with each other, the backward
selection method was adopted to help guard against
multi-collinearity. As can be seen from Table 3,
standardized regression coefficients (β) suggest thatthe magnitude of the impacts of uncertainty
avoidance,
individualism/collectivism,andmasculinity/femininity is larger than that of GDP
per capita. This result implies that these cultural
factors explain the difference between countries
more than economic factors. Accounting for 65.4 %of the variance, the selected Model 3 which shows
the largest explanatory power indicates negative
regression coefficient for uncertainty avoidance andpositive coefficient for individualism. These results
indicate that customer satisfaction is higher incountries where uncertainty avoidance is weaker
and individualism is higher.

Table 1 Cultural Dimension Scores andCustomer/Life Satisfaction
Country75*1: 2004 data only, *2: 2002 data only,*3: 2002 data only, *4: 2005
data only, *5: 2002 data only, *6: averaged for 2003-2004

114

Table 3 Results of Multiple Regression Analysis of Customer Satisfaction
Model
Independent
Variable
1. UAI

1

2

3

4

β

t-valep-valueβt-valuep-valueβt-valuep-valueβt-valuep-value-0.571-3.7540.001-0.581-4.0760.001-0.586-4.1700.000-0.487-3.578

0.002

0.409

2.162

0.043

0.499

3.849

0.001

0.486

3.575

0.002

0.242

1.815

0.084

2. IDV

0.469

1.528

0.143

3. PDI

0.078

0.249

0.806

4. MAS

0.243

1.188

0.249

0.277

1.905

0.071

5. GDP/capita

0.133

0.647

0.526

0.132

0.655

0.520

R

0.840

0.839

0.835

0.806

2

0.705

0.704

0.698

0.650

Adjusted R2

0.627

0.645

0.654

0.618

R

Table 4 Results of Multiple Regression Analysis of Life Satisfaction
Model
Independent
Variable
1. UAI

1

2

3

4

β

t-valep-valueβt-valuep-valueβt-valuep-valueβt-valuep-value-0.479-3.8670.001-0.496-4.2860.000-0.495-4.2860.000-0.650-5.583

0.000

0.249

1.705

0.103

0.350

3.428

0.002

0.362

3.111

0.005

-0.310-2.8280.010

2. IDV

0.334

1.429

0.168

3. PDI

0.114

0.470

0.643

4. MAS-0.326-2.0040.059-0.273-2.3540.028

5. GDP/capita

0.150

0.972

0.343

0.146

0.963

0.347

R

0.903

0.902

0.898

0.735

2

0.816

0.814

0.806

0.712

Adjusted R2

0.770

0.779

0.779

0.474

R

85

In the same manner as the analysis of customer
satisfaction, multiple regression analysis was
carried out with life satisfaction (Table 4). Thismodel accounts for 77.9 % of the variance and theresults suggest a negative regression coefficient for
uncertainty avoidance and masculinity and apositive coefficient for individualism. On bothcustomer satisfaction and life satisfaction, thenegative impact of uncertainty avoidance and thepositive impact of individualism can be commonly
observed. Comparing their explanatory powers, theresults of life satisfaction shows higher adjusted R2(0.779) than customer satisfaction (0.618). These
results suggest that the impacts of cultural factors
are stronger on life satisfaction than cus-tomer
satisfaction.
To further assure reliability of the analysis,
more varied countries’ data will be required.
While customer satisfaction data are limited ataggregated level, life satisfaction data covers far
more countries. Beginning with analysis of all
countries’ data (n = 110), obviously life satisfaction
seems to be higher in developed countries thandeveloping countries. This is consistent with theliteratures which investigated effects of income
level (e.g. Frey et al. 2002). But the cultural factors
appear to have no significant correlations with life
satisfaction probably due to great effect of
economic disparity among nations.

Denmark

Ireland
Austria

Switzerland

80

FinlandNetherlands
New Zealand
U.S.
Australia
NorwayMexicoLife Satisfaction

CanadaSweden75

United Kingdom

Belgium

Germany
Italy

France
Spain

70

65

Japan
S. Korea

60
0

50

100

Uncertainty Avoidance (UAI) Score

Fig. 2. Life Satisfaction and Uncertainty Avoidance

To control economic levels, the analysis was
focused on OECD countries and multiple regression
was carried out in a similar way with the previous
analyses of cultural factors. The results suggest
uncertainty avoidance shows significance and it
accounts for 43.0% of the variance. Unlike theprevious analysis of the ten countries, individualism
and masculinity do not show statistical significance.
This may be due to the fact that many of theanalyzed countries are classified into rather strongindividualism group.
Fig. 2 presents life
satisfaction and uncertainty avoidance score of theOECD countries. This result of larger number ofcountries also suggests that life satisfaction ishigher in countries where uncertainty avoidance isweaker.

115

influenced by uncertainty avoidance and positively
influenced by individualism. But these cultural
impacts are stronger on life satisfaction thancustomer satisfaction.
As managerial implications of this study, asimple comparison of customer satisfaction acrosscountries may not be enough in terms ofeffectiveness measurement of marketing. Therefore
special efforts will be necessary in marketing a
product/service in countries where uncertainty
avoidance is strong because consumer expectations
and demand levels are higher than other countries.
As an implication for SIMOT framework, in
addition to the quantitative measures such as GDP,
productivity, or profit, qualitative measures such as
customer satisfaction, life satisfaction, or job
satisfaction should be more taken into consideration
since these satisfaction indicators does not always
correspond with traditional economic or businessperformance measures. Further investigation isunderway to better understand the insistitutional
mechanism of customer, life, and other domains ofsatisfaction.

4. Discussion
As an interpretation of the negative influence of
uncertainty avoidance on customer satisfaction,
Hofstede (2004) mentions precision and punctuality
are emphasized in a strong-uncertainty-avoidancesociety. This leads to high demand levels and strict
evaluation by consumers, and such strict consumers
search a lot of information and expect high level ofproduct functions and quality.
Due to thedifficulty to meet their higher expectations,customer satisfaction will be lower in a stronguncertainty-avoidance country. As well, in a highindividualism culture, it is considered that
innovations,entrepreneurship,
freedom arepromoted in a working situation, economy, or
politics (Hofstede, 2004). These situations may leadto superior abilities and motivations of a company
or economy to provide better experience toconsumers. Consequently perceived quality will be
relatively higher and customer satisfaction is
expected to be higher in a high-individualism
country than a low-individualism country.
Regarding life satisfaction, it was reported thatpeople in a strong-uncertainty-avoidance culture
show lower life satisfaction than people in a weakuncertainty-avoidance culture. This may be because
they tend to feel high stress and anxiety (Hofstede2004). Besides, high-individualism people may feel
higher life satisfaction than low-individualism
people. This is because they put an emphasis on
personal lives rather than their in-groups, and also
showing happiness feelings is encouraged. The past
researches suggested that collectivist countries
show low levels of life satisfaction (e.g. Inglehart etal., 2000).
While these cultural effects was commonly
observed in customer satisfaction and life
satisfaction, the degrees of impacts were found tobe higher in life satisfaction. From the perspectiveof their characteristic features, customer satisfaction
has a tangible object for evaluation and a
product/service itself possesses objective evaluation
elements which are somewhat common to every
customer. In contrast, life satisfaction is a result of
judgment for overall circumstances of one’s life andnot a specific domain of life. As it is considered thatpeople in dissimilar societies consider different
criteria when judging their life situation, life
satisfaction encompasses more subjective judgment
and reflects features of the cultures and values.

References

5. Conclusions
This paper examined the impact of national
culture on customer/life satisfaction by analysis
across countries. It also discussed their similarities
and differences in terms of their determinants. The
results of the analysis indicated that both customer
satisfaction and life satisfaction are negatively

116

[1]

Diener, E. and Suh, M., 2000. Measuring
subjective well-being to compare the qualityof life of cultures, In Diener, E. and Suh, M.
(ed.), Culture and Subjective Well-being(Massachusetts, USA: The MIT Press),
chapter 1, 3-12.

[2]Fornell, C., Johnson, M.D., Anderson, E.W.,
Cha, J. and Bryant, B.E., 1996, The American
Customer Satisfaction Index: Nature, Purpose,and Findings. Journal of Marketing, 60 (10),
7-18.

[3]

Frey, B. S. and Stutzer, A., 2002. Happinessand Economics: How the Economy andInstitutions Affect Human Well-Being,
Woodstock, UK: Princeton University Press.

[4]

Hofstede, G. and Hofstede, G. J., 2004.
Cultures and Organizations: Software of the
Mind; Revised and Expanded 2nd Edition,
New York, USA: McGraw-Hill.

[5]

Johnson, M. D., Herrmann, A., andGustafsson, A., 2002. Comparing Customer
Satisfaction across Industries and Countries,
Journal of Economic Psychology, 23 (6), 749769.

[6]

Veenhoven, R., 2000. Freedom and happiness:
A comparative study in forty-four nations in
the early 1990s, In Diener, E. and Suh, M.
(ed.), Culture and Subjective Well-being(Massachusetts, USA: The MIT Press),
chapter 10, 257-288.

The Cultural Influence of Customer Satisfaction - Cross-national Comparison
Mizuho Ogikubo**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANogikubo.m.aa@m.titech.ac.jp
This study investigates the effect of national culture on customer satisfaction andcompares its mechanism with life satisfaction, financial satisfaction, and job satisfaction.
The analytical results indicated strong interrelation among these four satisfaction
measures and regardless of the measurement of culture, the negative effect of “uncertainty
avoidance” was found in common between them.
basic data were collected over 30 years ago andobsolete, because the four dimensions are notenough, and because the results of the survey to thesubsidiaries of a multinational company may notprovide information about entire national cultures.
In consideration of these arguments, theexamination of the cultural impacts will be
replicated using a different measure of national
culture. Here, the GLOBE (Global Leadership andOrganizational behaviour Effectiveness) project has
recently been drawing attention, citing results of awide-scale study by than 150 researchers andcollecting information on more than 18,000 middle
managers in 62 countries/regions [3]. They
identified nine dimensions of cultural variation –Assertiveness, Institutional Collectivism, In-Group
Collectivism,
FutureOrientation,
Gender
Egalitarianism, Humane Orientation, Performance
Orientation, Power Distance, and Uncertainty
Avoidance. Among the nine dimensions,
Institutional
Collectivism
andUncertainty
Avoidance will have close relationships withcustomer satisfaction and it is expected that theresults lead to similar findings with the literature
which dealt with Hofstede’s dimensions.
Hypothesis 1 Customer satisfaction will be
negatively correlated with collectivism andUncertainty Avoidance of GLOBE’s scale as wellas Hofstede’s scale.

1. Introduction
Customer satisfaction has been identified as a
key issue in marketing theory and practice. The
latest study [1] has attempted to compare customer
satisfaction among countries and demonstrated therole of national culture as a predictor ofinternational difference. However, as the numberof the countries covered in the analysis waslimited in the extant literature, more variedcountries’ data are needed to assure higher
reliability and stability of its results. In contrast to
customer satisfaction indices, other satisfaction
measures such as life satisfaction, financial
satisfaction, and job satisfaction cover a lot morecountries, and it is expected that they have similar
constructs and influential factors. Using these foursatisfaction measures, the impacts of cultural
factors will be explored in this paper. With respect
to the measurement of national culture, Hofstede’s
cultural dimensions [2] were used by the literature,
but there are some arguments on their usage. In
order to confirm the generality of the literature andusefulnessof
Hofstede’s
dimensions,complementary analyses will be carried out by
using an alternative cultural indicator called“GLOBE” [3] and compare the results for
Hofstede’s dimensions.
2. Theoretical Backgrounds and Hypothesis
A recent development in customer satisfaction
research has been the emergence of the National
Customer Satisfaction Indices (CSIs) – theaggregate measures on how satisfied domestic
consumers are with different types of products andservices nationwide (e.g. [4]). Using these CSIs andHofstede’s cultural dimensions [2], Ogikubo et al.
[1] reported the systematic differences in customer
satisfaction levels between countries, and theyfound that customer satisfaction is higher incountries where Uncertainty Avoidance is weaker
and Individualism is higher. However, there is
criticism on Hofstede’s dimensions because the

The availability of customer satisfaction data israther limited at this time, but if widening the scope
further to other domains of satisfaction, namely life
satisfaction, financial satisfaction, and job
satisfaction cover a lot more countries/regions. Lifesatisfaction is measured by asking individuals“How satisfied are you with your life as a whole?”,financial satisfaction is measured by asking “Howsatisfied are you with the financial situation of yourhousehold?”, and job satisfaction is measured bythis question: “How satisfied are you with yourwork?”

117

Table 1 Correlations between Customer Satisfaction and the Cultural Dimension Scores
Hofstede

GLOBE
GenderAssertivenes Institutional In-Group
FutureHumane Performance Power Uncertainty
EgalitarianissCollectivism Collectivism Orientation
Orientation Orientation Distance Avoidance
m

PDI

UAI

IDV

MAS

-0.480-0.7120.657-0.194-0.066-0.325-0.614

0.497

0.794

0.522

-0.149-0.7040.491

p-value 0.008

0.000

0.000

0.176

0.770

0.139

0.002

0.019

0.000

0.013

0.508

0.000

0.020

25

25

25

22

22

22

22

22

22

22

22

22

r
N

25

Table 2 Multiple Regression Results of Customer Satisfaction with Hofstede's Dimensions
Model
UAI
IDV
PDI
MAS
GDP/capita
Adjusted R2

1

2

3

4

β

t

p

β

t

p

β

t

p

β

t

p

-0.571
0.469
0.078
0.243
0.133

-3.754
1.528
0.249
1.188
0.647
0.627

0.001
0.143
0.806
0.249
0.526

-0.581
0.409-4.076
2.162

0.001
0.043

-0.5860.499-4.170
3.849

0.000
0.001

-0.4870.486-3.578
3.575

0.002
0.002

0.277
0.132

1.905
0.655
0.645

0.071
0.520

0.242

1.815

0.084

0.654

Comparing the research results between thesesatisfaction measures, one can find similarities intheir constructs. For example, it was reported that aperson who is satisfied with one aspect of life tends
to be also satisfied with other domains and inparticular, satisfaction with life, job, house, health,leisure, and environment were found to be stronglyinterrelated due to common explanatory variables[5]. In this study, it is expected that customer
satisfaction is also correlated with these satisfaction
measures having similar cultural and economic
factors.
Hypothesis 2 There will be strong
intercorrelations between customer satisfaction, life,
financial, and job satisfaction, and they havecommon cultural and economic factors.

0.618

Institutional Collectivism means, conversely,
positive correlation with Individualism.
Since simple correlation cannot isolate effects
of other variables, multiple regression analysis was
carried out using backward selection. From theresults for Hofstede’s scale shown in Table 2, thenegative impact of Uncertainty Avoidance and thepositive effect of Individualism are observed.
Likewise, the results for GLOBE’s scale presented
in Table 3 indicate negative effect of Institutional
Collectivism and Uncertainty Avoidance, and theseresults seem to be corresponding to Hypothesis 1.
Table 3 Multiple Regression Results with GLOBE's
Dimensions
Model

3. Data and Analysis
The CSIs are available from Denmark, Finland,
Germany, Hong Kong, Iceland, Norway, South
Korea, Sweden, and USA for the years of 20032005. The data used for the analysis are given by
100-point scale scores. Although Japan does nothave such an index, our own survey data on
Japanese consumers’ satisfaction with durable
goods can be used as a proxy measure of CSI [1].
Life satisfaction data were collected via World
Database of Happiness [6] and financial satisfaction
and job satisfaction data were retrieved from 42 and22 countries/regions respectively by the World
Values Survey [7].
Correlations between customer satisfaction andthe cultural dimension scores are presented inTable 1. Both from the results for the Hofstede and
GLOBE scale, customer satisfaction is positively
correlated with Individualism and negatively
correlated with Uncertainty Avoidance and power
distance. Here, the negative coefficient sign with

Independent
Variable
AssertivenessInstitutional
Collectivism
In-Group
Collectivism
HumaneOrientation
Performance
Orientation
Power Distance
Uncertainty
Avoidance
GDP/capita
Adjusted R2

1

2

β

t

p

β

t

p

0.713

3.275

0.006

0.729

3.917

0.002

-0.965-5.7060.000-0.946-8.247

0.000

0.765

3.522

0.004

0.789

5.580

0.000

0.786

4.131

0.001

0.765

6.027

0.000

-1.679-7.4130.000-1.694-8.5640.000-0.940-4.8180.000-0.956-6.0110.000-0.244-2.4150.031-0.245-2.5320.024-0.027-0.155

0.879

0.967

0.970

With respect to the other cultural dimensionsof GLOBE, the results suggest the positive effectsof Assertiveness, In-group Collectivism, andHumane Orientation, and negative effects of
Performance Orientation and Power Distance.
House et al. [4] mentioned that hospitality is118thought to be important and people feel high degree

Individualism and negatively correlated with Power

Table 5 Correlations between GLOBE's Cultural Dimension Scores and Each Satisfaction Index

CS
LS
FS
JS

r
p
r
p
r
p
r
p

Assertiveness-0.0660.770-0.027
0.899
0.054
0.783
-0.1180.652

Institutional
Collectivism-0.3250.139-0.1430.506-0.079
0.690
0.020
0.939

In-Group
Collectivism-0.614
0.002
0.149
0.488
0.010
0.960
0.046
0.859

FutureOrientation
0.497
0.019
-0.421
0.041-0.4330.021-0.2610.312

Gender
Egalitarianism
0.794
0.000
0.409
0.047
0.472
0.011
0.000
0.999

of satisfaction in high-Humane-Orientation society,which is consistent with these results.

HumaneOrientation
0.522
0.013
0.027
0.900
0.177
0.366
-0.0600.820

Performance
Orientation-0.149
0.508
0.248
0.243
0.217
0.267
-0.0900.732

PowerDistance-0.704
0.000
0.162
0.449
-0.1280.517-0.0380.885

Uncertainty
Avoidance
0.491
0.020
-0.5720.003-0.6940.000-0.4190.095

distance and Uncertainty Avoidance. Job
satisfaction is negatively correlated with
Uncertainty Avoidance. Likewise, Table 5 shows
the correlations with GLOBE’s cultural dimension
scores. There are positive correlations between
financial satisfaction and Gender Egalitarianismand negative correlations with Future Orientationand Uncertainty Avoidance. Job satisfaction isnegatively correlated with Uncertainty Avoidance.
From these results, Uncertainty Avoidance is foundto have significant negative correlations with all
satisfaction measures except customer satisfactionin GLOBE’s model. These results appear to beconsistent with Hypothesis 2 which predicts that
there are intercorrelations between the foursatisfaction measures, and they have common
cultural and economic factors.

Figure 1. Satisfaction Indices of the Ten Countries/Regions.

Table 4 Correlations between Hofstede's Cultural
Dimension Scores and Each Satisfaction Index

Figure 1. Satisfaction Indices of the Ten Countries/Regions.

Figure 1 illustrates customer, life, financial,
and job satisfaction of the ten countries/regions. Job
satisfaction is lowest in Japan as well as life
satisfaction and South Korea shows lowest financial
satisfaction and job satisfaction. These evidencesindicate economic wealth is not entirely inaccordance with satisfaction but it serves very
different meanings across cultures.
Customersatisfaction
coversnine
countries/regions in common with life satisfaction
and financial satisfaction, and five countries withjob satisfaction. Life satisfaction shares 41
countries in common with financial satisfaction and22 with job satisfaction. And there are 19 countries
commonly covered between financial satisfaction
and job satisfaction. To test Hypothesis 2,
correlations among the four satisfaction indiceswere analysed and the results are shown in Table 4.
It is clearly observed that there are positive
intercorrelations among the four satisfaction indicesand all coefficients show 1% significance. Table 5
presents the correlations between four satisfaction
measure and Hofstede’s cultural dimension scores.
Financial satisfaction is positively correlated with

CS
LS
FS
JS

r
p
r
p
r
p
r
p

PDI
-0.4800.008-0.5560.006-0.5050.010-0.1120.691

UAI-0.7120.000-0.6750.000-0.4260.034-0.492
0.063

IDV
0.657
0.000
0.374
0.079
0.539
0.005
0.153
0.586

MAS
-0.1940.176-0.1200.585-0.1460.485-0.080
0.777

4. Conclusions and Discussions
This paper has focused on the investigation of thecultural impacts on customer satisfaction, andexplored its relationship with other satisfaction
measure, namely, life satisfaction, financial
satisfaction, and job satisfaction. First of all,utilising GLOBE’s cultural dimensions, ouranalytical results confirmed the past researchfindings which stated that customer satisfaction ishigher in countries where Uncertainty Avoidance isweaker and Individualism is stronger. These
cultural influences were observed regardless of themeasurement of national culture, which in turn
reassured the usefulness of Hofstede’s dimensions.
Second, we found that life satisfaction, financial

119

Rotterdam: Erasmus University, Available:
http://www.worlddatabaseofhappiness.eur.nl

satisfaction, and job satisfaction are also negatively
influenced by Uncertainty Avoidance, and there
found to be strong intercorrelations among thesethree satisfaction indices.
Our study possesses some theoretical andpractical implications. In the first place, we need totake cultural and socio-economic factors into
account when analysing customer satisfaction data.
In particular, our results suggest that special efforts
will be necessary to satisfy consumers in countries
where Uncertainty Avoidance is strong because of
the high demand levels or expectations. Second,
research attention in customer satisfaction study
field should be devoted more to the culturalcharacteristics. Our findings will contribute totheoretical understanding of customer satisfaction
from the perspective of cultural contexts. Surveybased analysis at individual-level in parallel withcountry-level analysis will better confirm ourfindings. Besides, further examinations of otherinfluential factors are underway to advance theunderstanding of the mechanism of customer
satisfaction and its linkage with other satisfaction
indices.

[7]

References[1]

Ogikubo, M., and Enkawa, T., 2007. Cross
National Analysis of Customer Satisfaction,
Economic Institutions and Cultural Factors,
Journal of Japan Industrial Management
Association, 58 (3), 167-172.

[2]

Hofstede, G. and Hofstede, G. J., 2004.
Cultures and Organizations: Software of the
Mind; Revised and Expanded 2nd Edition,
New York, USA: McGraw-Hill.

[3]

House, R. J., P. J. Hanges, M. Javidan, P. W.
Dorfman, and V. Gupta, 2004. Culture,
Leadership, and Organizations: The GLOBE
Study of 62 Societies, Thousand Oaks, Sage
Publications.

[4]

Fornell, C., Johnson, M.D., Anderson, E.W.,
Cha, J. and Bryant, B.E., 1996, The American
Customer Satisfaction Index: Nature, Purpose,and Findings. Journal of Marketing, 60 (10),
7-18.

[5]

Van Praag, B.M.S., P. Frijters, and A. Ferreri-Carbonell. 2000. A structural model of wellbeing: With an application to German data.
Amsterdam: Tinbergen Institute Discussion
Paper, No. 53/3, Tinbergen Institute.
Available:
http://www.tinbergen.nl/discussionpapers/000
53.pdf[6]

Veenhoven, Ruut. 2006. World Database ofHappiness: Distributional Findings in Nations.

120

World Values Survey. 2007. Available:
http://www.worldvaluessurvey.org/

Influences of Institutional Environment
Toward the Development of Supply Chain Management
KorrakotYaibuathet**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-57 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANyaibuathet.k.aa@m.titech.ac.jp
The development of supply chain operational performance in global context is often
limited by some of the institutional constrains. In order to enhance the ability of supply
chain operational performance, it is essential for the focal company to understand theinstitutional environment of the supply chain members. The proper institutionalarrangement should be, furthermore, positioned to induce cooperation and motivate all
chain members to participate activities which produce reciprocal benefits. The research on
supply chain performance has been carried out in Japan and Thailand. The findings
indicated that the institutional environment may play important roles in the current
performance level and could be one of the main obstacles in improving the supply chain
operational performance. The different strategies of institutional arrangement may beintroduced to each country individually according to the distinctive social believes,business behaviors or cultural backgrounds.

which is referred to as “Institutional system” in thisarticle. Supply chain innovation includes theselection of appropriate information technology,
logistics procedures and marketing procedures
which suit for different supply chain operations ineach unit. However some investment and changed
activity sets are required for successful innovationin the supply chain such that firms are reluctant toparticipate in an innovation unless they could gain
adequate benefits. Meanwhile, the institutionalarrangements are necessary to support the supply
chain innovation. Institutional environment of
supply chain should be well comprehended before
proper institution arrangements such as newcontracting, ownership realignment are allocated.
The conceptual framework of SCM development inglobal market channel which was partly modified
from [1] is exhibited in Figure 1.
Referring to the conceptual framework,
Institutional Environment (IE) is one of the mostsignificant factors for an achievement of SCM
development. It was recognized as an integration ofvarious building blocks of a national setting andcontext. Forces within an IE may pressure local
firms to maintain traditional channel systems thatare suboptimal for the perspective of supply chain
development [2]. In particular, institutional theorists[3], [4] acknowledge that IE is composed of
predominantly three components Regulative,
Normative, and Cultural-cognitive.

1. Introduction
In view of the fact that business management in
21st century has encountered the inter-networkcompetition, individual business has no longer
competed as solely independent entity, but rather,as a supply chain. Henceforth, innovation in supply
chain is, additionally, required for efficient supply
chain integration. However, numerous factors are
considered having an effect on supply chain
innovation. In particular, the regulatory, normative,
and culture cognitive elements of Institutional
Environment around the world could either improveor impede the ability of supply chain partners which
directly results in the operational performance ofthe entire supply chain ([1], [2]).
The surveys on supply chain operational
performance were conducted in Japan and Thailand
in order to verify if manufacturing sector from twocountries perform at a different performance level.
The result implies that the discrepancy ininstitutional environment may influence the level ofsupply chain operational performance in somespecific areas.
2. The Development of SCM in Global market
ChannelThe development of SCM could be achieved
from the co-evolution between proper supply chain
innovation and suitable institutional arrangement

121

Thailand. Twenty items in four area of assessment
namely, (1) corporate strategy and interorganization alignment, (2) planning and execution
capability, (3) Logistics performance, and (4) IT
methods and implementation were thoroughly
evaluated among each participants in both countries.
The strengths and weaknesses from each country
are consecutively revealed. Discussions are latermade to elucidate how institutional environment
affects supply chain operational performance bothin Japan and Thailand.

Institution
Institutional Environment

Institution
Incumbent Institutional
Arrangement• Regulatory• Normative• Cultural-Cognitive• Contracting

New
NewInstitution
Institution
Arrangement
Arrangementsupporting
supporting
SupplySupplyChain
ChainInnovation
Innovation• Ownership• Social Elements(CO-EVOLUTION)(CO-EVOLUTION)

Supply Chain Innovation• Information Technology• Logistics procedures• Marketing Procedures

Innovation

Development
Developmentof
ofSCM
SCM
Required changed
characteristics for Innovation• Investment• Activity Sets

Innovation

3. Research Methodology
3.1 Data Collection Process
SCM Logistics scorecard (LSC) has beenutilized as a data collection in this stage. Thisscorecard has been developed since 2001 by
Enkawa Lab, Tokyo Institute of Technology incollaboration with Japan Institute of Logistics
system (JILTS). LSC encompasses 20 assessment
items based on four fundamental areas, which are(1) Corporate strategy and Inter-Organization
Alignment, (2) Planning and Execution Capability,(3) Logistics Performance and, (4) IT methods and
Implementation. Each assessment item wasallocated into five-level from one to five. The detail
description of each level was depicted on the LSCwith the 5th level indicated as the best practice ofeach item. The score of one integer and a half (forexample 2.5) were also acceptable for managers
who placed their companies between two levels.
Data collection has been carried out in Japan
since 2003 and extended to Thailand in early 2005.
Most of the data was obtained by interviewing thehigh-leveled managers individually in eachcompany. The feedback report was conveyed backto each company so as to be incentive after dataacquisition. At the time of report, the numbers ofparticipating companies are 205 from Japan and
153 from Thailand’s industrial sector. The categoryof participated companies was represented in Table
1.

Figure 1 Conceptual framework of SCM
development in global market channel
Regulative element refers to the demands ofgovernments and regulatory bodies to comply withlaws and other requirements such as government
constrains which inhibit the development of modern
logistics in China in the sense of underdeveloped
infrastructure [5]. Normative element mentions
about the society’s values and norms that direct
behavior
throughsocialobligations
andexpectations [3]. The normative is always exposedin terms of countries’ social believes or businessbehavior, for example, the strong loyalty among
existing partners in Japan. Although new business
partners may be considered more advantageous forthe focal firm, they could not easily replace or enteras a new member of the chain. The last dimensionof IE is Cultural-cognitive, which refers to acommon framework of individual society that has
been formerly created. It was later brought about“Prefabricated organizing models and script ofactions” for society [3]. Sometimes, the cultural
cognitive may negatively impact the willingness
and ability of the firm for institutional arrangement.
It is conclusive from the previous section that
the Institutional Environment plays important roles
on the development of supply chain management.
Therefore, this paper will discuss on how IE could
affect a performance of supply chain operations.
Supply chain operational performance of
manufacturing sector from two countries was
successively investigated. In comparison purpose,
Japan symbolizes developed country while
Thailand represents developing country where
institutional environments of both countries are
divulged difference. As a result, the following
hypothesis is derived.

Table 1 The category of participating companies
Number of Company
CategoryJapan
Thailand
Food
Electronics
Automotive
ChemistryFiber
Pharmaceutical
Others
Total

Hypothesis: The difference of Supply chain
operational performance level between Japan and
Thailand is influenced by different institutional
environment.
This hypothesis is verified by comparing
supply chain operational performance of Japan and

122

39
56
29
23
19
27
12
205

35
31
37
30
12
2
6
153

3.2 Data Analysis
As a result from the data collection process, thedata attribute and the distribution of the total score
between Japan and Thai are exhibited in table 2.

Japanese, which signified that Thai data showed
higher degree of variation.
The average score of four assessment areas
were calculated and presented in table 3. It wasobserved here again that the score from twocountries are not significantly different. However,the biggest discrepancy was found on the IT
method and implementation which was dominatedby Japanese. On the other hand, Thai industry held
a noticeable higher than Japanese in the area ofplanning and execution capability.
The analysis was made consistently to thosetwenty items of assessment and the comparison
result is exhibited in terms of radar chart in Fig.1.
The strengths and weaknesses are revealed as aresult of comparative study. The highest
competence of Japanese industry was apparent ondelivery performance and the usage of IT evolution
such as introducing the electronic data interchange,or employing bar code system to synchronize thematerial and information flow in the supply chain.
These Japanese strengths are discovered to be main
weaknesses for Thai industry. On the contrary,
Thais revealed their perceptible strengths on system
for measuring and improvement of customer
satisfaction, the adaptability of SCM planning andprocess standardization level above the Japanese
average.

Table 2 Data attribute of total score between Japanese,
Thai manufacturing
Japan
ThailandNumber of Data
Mean
Standard Deviation
Variance
MedianMode
Range
Maximum
Minimum

205
58.67
10.74
115.31
58
51
58.5
87.5
29

153
57.65
13.14
172.66
57
62
61
94
33

The reliability analysis of LSC was conductedduring the data collection process. The results areshown in term of Cronbach`s coefficient alpha for
20 assessment items at 0.911 and 0.940 from Japanand Thailand respectively. These results also
indicated the high reliability of LSC. From the data
attribute, the average total score between Japaneseand Thai companies were not markedly different.
However, the standard deviation, variance andrange of Thai were observed larger than the

Table 3 The average score of four areas between Japanese and Thai manufacturing
Japan (205)1.Corporat strategy and InterOrganization alignment
2. Planning and Execution capability
3. Logistics Performance
4. IT Methods and Implementation

Thailand (153)t-valuep-value

AverageSD

Average

SD

3.054

0.63

3.068

0.72

-0.183

0.855

2.945
2.759
2.974

0.57
0.68
0.67

3.026
2.764
2.885

0.73
0.77
0.83

-1.149-0.067
1.256

0.250
0.947
0.210

Due to the fact that Japan has been recognized
as a developed country as well as a world leader
in manufacturing sector, the score achieved fromthis country should be significantly higher thanfrom the developing country. Astonishingly, we
have found that the result from Japan and
Thailand were not markedly different. This
conceivable result could be explained by the factthat around 50 percent of Thai participants were
Multinational Companies (MNCs). Knowledge,
manufacturing
standard,
technology
andmanagement system were transferred from mothercompanies in Japan, Germany, US, etc., to set up
the manufacturing based in Thailand. Besides,

those industries have confronted a highcompetition with other South East Asian countries
and China where lower wage has been paid. Thais,
therefore, could not struggle on labor cost
reduction but they have to survive the competition
by increasing the product quality, applying
specific techniques to generate productivities,
reducing inventory cost as well as leveling up thecustomer responsiveness. Otherwise, the mothercompanies may relocate their manufacturing baseto other countries which may possibly influence
country economic as a whole. Thus, the scoreachieved from those MNCs were considerablyhigh when compared with local Thai companies.

1231-(1)Corporate strategy regarding logistics and its
importance
1-(2) Definition of supplier contract terms & degree of
5
information
sharingcontract terms & degree
1-(3) Definitionof customer

4-(5) Decision-making systems and support to supply
chain partners
4-(4) Open s tandards and unique identification codes
4-(3) Effective usage of computers in operations anddecis ion-making (ERP, supply chain planningsoftware, etc.)
4-(2) Usage of Bar Coding / Automatic Identification
and Data Capture (AIDC)
4-(1) Electronic Data Interchange (EDI) coverage

4of information s haring
1-(4) System for measurement and improvement ofcustomer satisfaction

32

1-(5) Sys tem for employee training and evaluation1

2-(1) Strategies for optimizing logis tics s ystem
resources based on design for logistics

0

3-(5) Supply chain inventory visibility & opportunitycosts

2-(2) Unders tanding of market trends & accuracy ofdemand forecasting

3-(4) Delivery performance and quality

2-(3) Accuracy and adaptability of SCM planning

3-(3) Customer lead time (from order placement toreceipt) and load efficiency
3-(2) Inventory turnover & cas h-to-cash cycle time

2-(4) Control and tracking of inventory(product/parts/W IP): accuracy and vis ibility
2-(5) Process s tandardization and visibility
3-(1) Just-In-Time

Japan (Manufacturing)
Thail (Manufacturing)

Fig. 1 Radar Chart of 20 items from LSC result between Japan and Thai manufacturing
may affect performance of both sectors. In thecase of MNCs, they were found located in highscore group. The driving force may derive fromhigh competitive among the same company inother parts of the world. Moreover, proper
technology and management know-how weretransferred from Mother Company and installed at
the company institution which could reduce
Cultural problems within the firm. This could
allow the institution arrangement to be madeeffortlessly such as new investment and changesof activity sets. As a result, industries in thisgroup perform better than Locals.
In terms of Thai Local companies which werepositioned in the lower score group, they mostly
originated from home business then extended to alarger scale. Owners have operated their businessusing primitive management style and wereunenthusiastic to strive for the better approach toachieve higher productivity. This could beconsidered as one of the Normative problems for
Thai local company. Furthermore, the low level ofchanged characteristics have been found in thisgroup such as uneasy to approve for the newinvestment and intricate to change existing
business behavior. Owning to the high investment,
the modern IT implementation was seemed to be
excluded from their existing operation. From theelucidated reasons, corporate strategy regarding to
SCM and IT utilization area have not been
improved much in this group.

4. Discussion
4.1 Japanese Manufacturing InsightSince the weaknesses of Japanese were foundon system for improving customer satisfaction andability in process standardization, these could be
explained by Japanese business behavior. The firstobservation indicated that Japanese workers could
perform high quality job without standardization
since they themselves are of high self-discipline[5]. Thus, process standardization is notconsidered necessary for them. As a function ofcustomer satisfaction improving system, although
the system is not fully existed, customer could
give feedback to company by employee base thenproblem is immediately solved. Since thecustomer awareness is embedded in individual
employees as of they started working with thefirm, no system is required to maintain Japanese
high-class service level. Both business behaviors
on self discipline and service mind of Japanese areclassified into Normative element of Institutional
Environment. It could be implied from thisobservation that IE may considerably influence
Japanese supply chain operational performance inthe noticed area.
4.2 Thai Manufacturing Insight
From the conclusive finding of Thai industry,
two groups are classified, which are Thai
Multinational and Thai Local Company. It wasnoticed that some of the Institutional Environment124

5. Conclusion
Owning to the investigation of supply chain
operational performance between two countries, it
could be indicated that the institutional
environments play important roles in current
performance level and could be one of the main
hindrance for improving purpose. The weaknesses
in supply chain operation of Japan and Thailand
could be explained by the context of institutional
environments, which are Normative and Culturalelements to some extent. Apart from employing
proper supply chain innovation such as IT anddecision support system, supply chain managers
should realistically assess the constraints ofInstitutional Environment of partners thenadopting suitable institutional arrangement forthem so as to develop the SCM and Logistics
operations as a whole.
References[1]

Carney, M., Gedajlovic, E., 2002. The coevolution of institutional environments andorganizational strategies: The rise of familybusiness groups in the ASEAN region,
Organization studies 23(1), 1-29.

[2]

Bello, D.C., Lohtia, R., Sangtani, V., 2004.
An institutional analysis of supply chain
innovations in global market channels,
Industrial Marketing Management 33, 57-64.

[3]

Scott, R.W., 2001. Institutions andOrganization, second ed. Thounsand Oaks,
CA: Sage.

[4]

Grewal, R., Dharwadkar, R., 2002. The roleof institutional environment in marketing
channel, Journal of Marketing 66, 82-97.

[5]

Jiang, Bin, 2002. How international firms
are coping with supply chain issue in China,
Supply Chain Management: An International
Journal 7(4), 184-188.

[6]

Lim, H., 1982. A Japanese agenda for
management development, Training andDevelopment Journal 36 (3), 62-67.

125

Institutional Perspective on Logistics and Supply Chain Management in Thailand
KorrakotYaibuathet**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-71 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANyaibuathet.k.aa.@m.titech.ac.jp
Thailand has long term suffered from high logistics cost comparing with other developed
countries. This problem could be considered as a significant barrier to build up the topnotch supply chain for the nation.
In order to achieve the target of reducing logistics cost and building up the world class
supply chain for Thailand, corporations are required from several parties such as
government, entrepreneur, including logistics service providers and users. Current related
institutional environments are investigated to find out the suitable strategy for enhancing
logistics and supply chain innovation in this country. Towards the end, it has been realizedthat institutional arrangement and encouraged innovation should be in place to develop
readiness for building excellent supply chain to be a survival in the world of competition.
therefore, allocated as a hub of Asian highway
network (Economic and Social Commission for
Asia and The Pacific, 2003). Efficient operation ofdeep sea ports and new international airport accountfor attractiveness of Thailand as anothercompetitive advantage for being logistics center forthe region.
The remainder of this paper is organized in afollowing order. Starting the next section withThailand logistics institution environment, reveals
main problems in improving national logistics.
After that, five Thailand logistics strategies are
introduced to business sector as solutions for
improving logistics system in Thailand. Section 4
defines Thailand and readiness to build up worldclass supply chain. Conclusion is finally given in
the last part of this paper.

1. Introduction
Manufacturing sector in Thailand has longstanding encountered extremely high logistics costespecially when compared with other developed
country such as Japan, UK, and US. When consider
the portion of logistics cost, more than 50% of
overall logistics cost is consumed in transportationaffair while around 30% is spent on warehousemanagement (NESDB, 2006). Due to thedeclaration of National agency on Logistics costissue, more attention has been paid to assist
entrepreneurs to reduce their logistics related cost.
The country also set target of reducing thistremendous cost from 19.17 % to be 13% per GDP
by year 2010. It is intuitive that reducing logistics
cost could provide substantial benefits to investors
in all targeted sectors, for example, manufacturing
and logistics service provider.
It has been declared by Thai government latelythat the country has sufficient potential to become
Logistics center for South-East Asia (SEA).
Thailand achieves great advantage from its
geographical setting which is located in the centerof international transport routes, linking the origins
with destinations. This strategic location leads tofaster delivery time and saving transportation cost.
In addition, the country has good trade relation withother countries in South East Asia. Government
policy encourages overseas capitalist to invest andestablish multi-national company in Thailand withfurther attractive factors which are able to induce
foreign to work in Thailand. Infrastructure
readiness is one of the notable potentials of thiscountry. With regard to road and railway mode,
strategic advantage has been found when comparedto other Asian country. This country has been,

2. Thailand Logistics Institutional Environment
National Economic and Social Development
board of Thailand reveals that Thailand still
confronts a lot of difficulties to increase logistics
efficiency. Focused business sectors, agri-business,
manufacturing and service industry, are now facing
mainly five problems which are considered as
vicious institutional environment for Thai business.
They are:• Low efficiency in business logistics
management in manufacturing sector•
Congesting problems in gathering,transferring and distribution around the main
merchandise area including lacking of proper
integrated logistics network• Low competency of local logistics service
providers (LSPs) as well as unable to produce highvalue-added service

126•Import and export processes are toocomplicate resulting in tremendous delay• Lacking of logistics personnel in bothmanufacturing and LSPs sectors
These problems should be taken into
consideration to enhance logistics innovation in
Thailand. Corporations from associated parties suchas government, providers of transportation services
and user of those services should be honestly
achieved.

and national level. This can be done by renovatingstate railway authority of Thailand.
Agenda3: Logistics Service Internationalization
Upgrading of Thai’s logistics service providers
so that they will be internationally competitive andbe able to be in higher value-added logistics service
market is expected as a result of this agenda. Major
challenge is to promote strategic alliance between
Thai logistics providers and foreign small or
medium provider for exchanging information andsharing cost such as trucks and warehouse. On topof those, local LSPs are turned into more integrated
services. The succeeding effort is to advancelogistics service to accommodate specific need of
local industry. To bring this agenda into realistic,
government need to update investment promotion
criteria and other related rules and regulations toaccommodate private investment and businessexpansion.
Agenda 4: Trade Facilitation Enhancement
This agenda focuses on reducing import andexport handling costs. Implemented strategies are todevelop comprehensive E-logistics system such as
one stop service, facilitate import and export
process through information linkage. Moreachievement concentrates on improving customer
clearance and its taxation system related to importand export transshipment, which could reduce cost
and time. E-transaction is further promoted with theaim to reduce documentation and informationdelivery cost.
Agenda 5: Capacity Building
The goal of this strategy are to produce
sufficient knowledgeable logistics personnel to bothmanufacturers and the logistics-service industry as
well as to establish data system and a mechanism
needed for planning and monitoring theperformance of Thailand’s logistics development.
Institution environment of Thai firms should bechanged to support capacity building by creatingawareness of the importance of logistics and urging
company to send staff for training and allow tax
deduction for training expense. Moreover,
improvement of training process is underway. Highskill logistics professionals are developed tocompete in the international business arena.
Corporation between research institutes to promote
R&D activities are required to resolve problems forindustry or business. Next attempt is forwarded togenerate country wide database system for logistics
management both at the macro and business levels
to help formulate and drive strategy. The key
information need to be collected at the national
level, are information on commodity flows,
operating costs and added values in the logistics
industry.
A study of transport needs of SMEs (Buapht,
2004) revealed that logistics development in small

3. Enhancing Logistics Innovation in Thailand
From the determined problems, Thaigovernment has developed five logistics
development strategies to resolve them (NESDB,
2006). Elucidations of each strategy are defined asfollowed.
Agenda 1: Business Logistics Improvement
The goal of this strategy is to encouragebusiness in strategic industries to have an efficientand traceable logistics system throughout the
supply chain. Firstly, the institution environment
should be rearranged by promoting of better
understand among business owner in implementing
logistics management and logistics best practice intheir operation. After that, IT and logistics softwareare introduced to be implemented in own businessand outsource service as logistics innovation.
Government, besides, has plans to support
associations and manufacturers in managing
logistics efficiently, encouraging traceability andtracking ability in the supply chain.
Agenda 2: New Trade Lanes and Logistics
Network Optimization
The target of this approach is to set up an
integrated logistics management system toaccommodate Thailand’s status as Indochina
logistics hub in gathering, transferring, anddistributing
merchandise
regionallyandinternationally. To achieve the ultimate goals, thefirst line of attack is to develop new trade lanes to
Middle East, Africa and Europe via Thailand’s
Andaman sea to accommodate the expanding tradeactivities of its neighboring countries by developing
deep sea ports in the west coast as well as an
economic corridor linking ports with the country’s
and the region’s major transporting bloodlines. The
second effort is to link the country with overseas
markets through the development of, among otherthings, motorway, logistics and distribution center.
This effort is considered to reduce transportation
time and cost on the main route. Meanwhile, active
participation of both local and international
competent private operator either in terms of project
financing or management will be strongly
advocated. On top, support on efficientmanagement of transport for energy saving isrequired to lower transportation cost at the business127

and medium sized enterprise should take place
based on the principle of balanced development inevery sector and at every component. Constructionof infrastructure should not be focused alone as it
would not be worth the money invested if no rules
are adjusted and no management methods are
updated. For example, the success of the Single
Window Entry system not only depends on
information technology, but also on changes torelated rules and regulations to facilitate trading
activities.

adopter, skillfulness in self product or technology
innovation seems deficiency. And this is considered
as lacking pieces that will drive the country towardbuilding top-notch supply chains.
Fromthereportof
NESDB
byTempittayapaisith (2006), Knowledge Assessment
Methodology (KAM) is employed to measure
Thailand against other countries, which is shown in
Figure 1. KAM is based on four pillars ofknowledge economy developed by World Bank
Institute. The four pillars include (1) an economic
and institutional regime, (2) an educated and skilled
population, (3) a national innovation systems, and(4) a dynamic information infrastructure. KAM is
designed to help countries assessing their strengths
and weaknesses in making transition to knowledge
economy (The World Bank Institute, 2006.). This
assessment benchmarks the various capability
dimensions of Japan, Korea, and China and reveals
that Thai’s investment on ICT, which is a key partof building efficient supply chain, is less than halfof China and a lot less than Japan and Korea.

4. Thailand and Readiness to Build World-Class
Supply Chain
Foreign investors, currently, are confident inThai manufactures that they can produce
outstanding quality of merchandise. A lot ofopportunities so as to attract investment in Thailand
are given out by related organizations. The country
has gained benefits from job creation and generates
income for communities. Additionally, Thailand
has received technology transfers in the past 30
years. As this country is a long-term technology

Fig. 1 KAM radar chart for Thailand, Japan, Korea, and China
Moreover, in the area of professional workers,
and technicians as a percentage of the labor force,the proportion of Thailand is tremendously low
comparing to Japan and Korea. It was indicatedthat Thai professionals lack an interest in joining
proficient associations that could strengthen theircareer paths. Accordingly, it could result inlacking of continue knowledge update. As it isrealized that human resource is deliberated as oneof the significant factors for supply chain
development, the increasing of professional
workers is inevitably required. With regard tototal expenditure for R&D as percentage of GDP,
Thailand invests a lot less than those from China,
Korea and Japan. It was further uncovered that thecountry invests less than 12 times of Japan. This128

signifies that Japan’s rate of development inknowledge and innovation is 12 times faster thanThailand. Meanwhile, China is 5 times and Korea
is 10 times more rapidly. However, thegovernment has tried to increase this number from
0.26% of GDP to be 0.40% as intended target assoon as possible. Encouragement should be placed
to create enough incentive in order to continue
investment in innovation. Increasing in R&D
activities is claimed as a crucial part for advancing
supply chain competency for business andnational level.
As a result of as-if assessment for Thailand,
attention should be focused on increasing ICT
expenditure, professional technicians and R&D
expenditure so as to build top-notch supply chain
for the country.

counterparts to further improve the product byenhancing R&D skill and increasing productinnovation level. Last but not least, anenvironment conductive to innovation should becreated in the country for sustainableenhancement of logistics and supply chain as awhole.
References

5. Conclusion
To enhance logistics innovation as well asbuilding up competitive supply chain in Thailand,
institutionalarrangement
andencourage
innovations should be in place. The
accomplishment is determined by bothgovernment and private sector. First of all,government should expand the mission of Boardof Investment (BOI) to include active surveillanceof companies with innovations that should bepromoted (Pantumsinchai, 2006). The country,
moreover, need strong capable leaders and a highconcentration of skilled engineers that have rightgoals to improve supply chain efficiency
including increasing logistics innovation. It isfurther required from the government to provide
real support to private sector, such as, provide tax
privileges for company investing in research anddevelopment. The firms should actively seek
foreign investors to co-invest with Thai

129

[1]

Buapht, Napaporn., 2004. Transportation
service demand of small and medium
enterprise, A thesis submitted in partial
fulfillment of the requirements for the degreeof Master of Engineering in Civil
Engineering, Chulalongkorn University.

[2]

Economic and Social Commission for Asiaand the Pacific., 2003. Asia Highway
Handbook.

[3]

National Economy and Social Development
Board (NESDB)., 2006. Thailand Logistics
Development Strategy.

[4]Panthumasinchai, P., 2006. Building Worldclass logistics and supply chain: Volume 1The beginning for Thailand. TLAPS
Yearbook & Directory 2006.

[5]

Termpitayapaisit, A., 2006. Thailand and its
knowledge Economy. Workshop on “Lesson
from Japanese Experience for Developmentof Knowledge Economy in Thailand” May
2006, Bangkok.

[6]

The World Bank Institute., 2006. KAM
Spidergram
analysis,cross-national
comparison.

Impact of Information Technology and SCM Organizational Strategy on Corporate
Financial Performance
Yaibuathet Korrakot
Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-57 O-Okayama, Meguro-ku ,Tokyo, 152-8552 JAPANYaibuathet.k.aa@m.titech.ac.jp
It has been discussed widely about the relationship between information technology(IT) and productivity at national, industry, and company levels. Previous literatures
suggested that in order to implement IT into an enterprise efficiently, it is required not
only to introduce IT into existing process, but also to adopt intangible approaches such asorganizational reformation. In this research work, organizational strategy is identified as avital ingredient. Our findings highlight the adoption of organizational strategy tosupplement IT usage in an enterprise and their remarkable impact on the financial
performance. IT implementation and SCM organizational data collected fromparticipated companies in Japan using SCM Logistics Scorecard are utilized for
hypothesis verification. It is conclusive that as long as introduction of IT is accompanied
by proper SCM organizational strategy, favorable improvement in the management
performance can be ascertained.
the correlation result can be improved using
externally reported, audited, publicly available
information. Similar agreement from Melnyk et al.
(2004) stated that using audited, externally reported
financial performance measures adds an importantdegree of verifiability. Exploring correlation
between IT utilization ability and firm’s financial
performance using external financial data is arelatively new approach in the field. There are only
a few articles reporting on it. To the authors’knowledge, no literature can be found regarding an
extension of the complement of IT utilization
ability and SCM organization strategy on thecorrelation with publicly known financial index.
The aim of this research is to rectify thelimitation of previous studies by adopting theJapanese publicly opened financial data from
Nikkei NEEDS instead of data from respondent
survey in the investigation. This research study
introduces, for the first time here, SCM
organization strategy to further compliment IT
utilization upon firm’s financial performance.
Empirical equation on ROA as a function of IT
utilization and SCM organization strategy aredeveloped here for manufacturing sector in Japan
which has not been elaborated in previous studies.

1. Introduction
In a new era of business management, strategic
priorities such as SCM have emerged to beimportant for competition rather than a cost
reduction focus. In this environment, information
technology (IT) is vital for successful competition
as it can facilitate the attainment of these strategic
targets (Theodorou and Florou, 2008) and provides
opportunity for improvement (Ross, 2002).
Implementation of IT in supply chain enables a firm
to develop and accumulate knowledge about its
customers, suppliers, and market demands, which inturn influences the firm performance (Tippins andSohi, 2003). However, IT-focused capabilities alone
cannot be a distinctive factor directly related tofirm’s management performance. To fully utilize it,this tool should be accompanied with practicalorganization management. The organization
strategy may serve as a catalyst in transforming ITrelated resource into higher added value for the firm
(Wu et al., 2006).
This research highlights the business value of
IT by showing the importance of complement
between IT utilization ability and SCM organization
strategy on firm’s management performance.
Previous literatures in this area derived therelationship between IT investments in SCM withthe firm performance from financial data limited
solely to survey respondents (Byrd and Davidson,
2003 and Vickery et al., 2003). However, Ross
(2002) and Dehning et al. (2007) argued that
adoption of internal financial data from respondents
alone may not sufficiently produce highly reliable
result. Both studies pointed out that reliability of

2. Background and Research Hypothesis
IT usage is increasingly becoming a source ofsustainable competitiveness and opportunity for
improvement of the firm. However, IT-focused
capabilities alone cannot be considered as a
distinctive factor directly relating firm’s financial
performance. Strassman (1988) stated that130

“Computers will not make a (poorly) managed
business better. The expenses for computerization… are likely to accelerate the decline ofincompetent management.” This statement was insimilar conclusion with the finding from Ross
(2002) that IT investment has a positive impact onmarket performance as a result of better
coordination in the value chain, but that larger
investment does not seem to lead to higher
performance. IT could not be fully utilized unlesspractical organization management has been
established. Efficiency and profitability may havemore to do with precise resource allocation andeconomic cycles, rather than purely with IT
investment. Several studies suggested that internalorganization strategy could influence the directionand extent of financial benefits for those who
implement IT as an SCM tool (Mata et al., 1995;
Powell and Dent-Micallef, 1997; Brynjolfsson et al.,
2002; Boudreau and Robey, 2005; Melville et al.,
2004; Wu et al., 2006). Based upon above
discussions, we hypothesize:
H1: The interaction between IT utilization and
SCM organization strategy results in positive
impact on firm’s financial performance
Hypothesis one is validated by examining
interaction effect of IT implementation and SCM
organization strategy on external firm’s financial
indicator instead of merely IT utilization. The
overall financial indicators that become renownedfor holistic measures of firm performance are ROA
and operating cash flow (Tan et al., 1999; Byrd andDavidson, 2003; Vickery et al., 2003). One of the
major benefits of SCM implementation is inventory.
Lower inventory turnover period may be achieved
where SCM is well operated. Hence, three financial
indices which signify management performance ofa company are taken up, namely, ROA, operating
cash flow per sale and inventory turnover.
3. Influence of IT utilization and SCM
organization strategy on Financial performanceThis section aims to validate Hypothesis 1 that
IT and SCM organization interaction lead tofavorable financial performance using data fromJapanese companies. Data collection is processed
via LSC before conducting factor analysis on
overall 222 data. Correlation analysis between three
extracted factors and selected financial indexes arethen investigated. The multiple regression analysis
is finally utilized to observe interaction effect of
SCM organization strategy and IT utilization ability.
3.1 Data Collection and Processing

131

SCM Logistics scorecard (LSC) has beenutilized as a data collection tool. LSC has beendeveloped since 2001 by Tokyo Institute ofTechnology in collaboration with Japan Institute of
Logistics system. The element of LSC and its
superiority over other scorecards were previously
discussed in Yaibuathet et al. (2007).
Data of more than 350 companies was
accumulated from Japan between 2001 and 2006. In
addition, three financial indices considered topresent the result of management were used, namely,
total capital operating profit margin (ROA) andOperating cash flow per sales and Inventory
turnover period. Those financial ratios data wereobtained from Japanese Nikkei NEEDS from 2002
to the present. From more than 350 Japanesecompanies, only 222 data sets from manufacturing
were employed in this research in which 103
corporate financial data was available.
3.2 Factor Analysis - Japan
A factor analysis was carried out in this stage to
identify the factor structures which may reflectcompany approach to SCM, using data from 222
Japanese manufacturings. The initial solution wasdetermined using principal axis factoring with theconstraint of an eigen-value of more than one.
Varimax rotation was further applied in this analysis
to avoid multicollinearity among extracted factors
since the factor scores from this analysis will be
employed as inputs for correlation and regression
analyses later in section 3.3. As a result, the rotatedfactor matrix of factor analysis is given in Table 1.
The large factor loading of more than 0.4 washighlighted, indicating the strong relationshipbetween each item and factor. The cumulative
contribution rate from 222 Japanese companies was
43.03 % and the KMO test which measures of thesampling adequacy for 20 assessment items was
0.926. This result also indicated the reliability offactor analysis. As a result, the three factors wereextracted and the names of them are interpreted asfollowed:
Factor 1 : SCM organization strategy
Factor 2 : Responsiveness
Factor 3 : IT utilization ability
The factor score extracted from this analysis
will be utilized in the next stage of research to
explore the correlation between each factor and therelated financial indexes.

Table 1 Rotated factor matrix of 222 Japanese manufacturing (after Varimax rotation)
Factor (Japan, n=222)

Assessment Item
1-(1)Corporate strategy regarding logistics and its importance
1-(2) Definition of supplier contract terms & degree of information sharing
1-(3) Definition of customer contract terms & degree of information sharing
1-(4) System for measurement and improvement of customer satisfaction
1-(5) System for employee training and evaluation
2-(1) Strategies for optimizing logistics system resources based on design for logistics
2-(2) Understanding of market trends & accuracy of demand forecasting
2-(3) Accuracy and adaptability of SCM planning
2-(4) Control and tracking of inventory (product/parts/WIP): accuracy and visibility
2-(5) Process standardization and visibility
3-(1) Just-In-Time
3-(2) Inventory turnover & cash-to-cash cycle time
3-(3) Customer lead time (from order placement to receipt) and load efficiency
3-(4) Delivery performance and quality
3-(5) Supply chain inventory visibility & opportunity costs
4-(1) Electronic Data Interchange (EDI) coverage
4-(2) Usage of Bar Coding / Automatic Identification and Data Capture (AIDC)
4-(3) Effective usage of computers in operations and decision-making
4-(4) Open standards and unique identification codes
4-(5) Decision-making systems and support to supply chain partners

3.3 Correlation between IT utilization ability,
SCM organization ability and firm’s financial
index
Pearson correlation analysis was initially
carried out to explore the relationship between
three extracted factors and selected financial indexs,
ROA and Operating cash flow per Sales The survey
data collected from individual firms were mapped
exactly to the financial ratio data from Japanese
Nikkei NEEDS before conducting correlation andregression analyses. The finacial data was all
adjusted using industry average to present actual
deviation from its industry standard. As a result, thecorrelation outcomes are presented in Table 2 .
According to the research scope which focuses on
the impact of IT and SCM organization strategy,“Responsiveness” factor will not be included infurther analysis of Japanese study.

Supply Chain Organization
Strategy

IT Utilization Ability

Correlation

ROA

2

3

0.65220.55620.62370.59810.5066
0.48970.46590.37740.44590.29580.2586
0.32660.13770.23380.42020.13910.17630.36870.1657
0.33800.23380.14040.12640.35130.19570.31570.32410.58180.37100.55380.57090.52340.64580.55210.31650.34010.29300.25770.16250.15620.21910.27790.15390.07360.14370.17780.27830.15830.25570.30820.29660.21010.14520.25680.31990.48050.44270.42640.77300.5034

Communalities
0.528
0.406
0.428
0.486
0.316
0.371
0.400
0.506
0.403
0.489
0.481
0.425
0.457
0.425
0.379
0.366
0.313
0.384
0.651
0.392

Operating CF/Sales). The list of independent
factors and results are shown in Tables 3 and 4.
Table 3 Coefficient model of 2 factors and theirinteraction on ROA
Unstandardized
Coefficients

N=103

Standardized
Coefficientst

p-value

0.890

0.376

-1.0480.297

B

Std.Error

Beta(Constant)

3.616

4.065

SCM Organization Strategy-1.3001.241-0.346

IT Utilization Ability-2.4511.366-0.700-1.7940.076

SCM × IT

0.836

0.418

1.003

2.001

0.048

R = 0.349, R2 = 0.121 , Adjusted R2 = 0.095, Std. Error of the Estimate = 2.857

Table 4 Coefficient model of 2 factors and theirinteraction on Operating CF/Sales
Unstandardized
Coefficients

N=103

Table 2 Correlation coefficient between three
extracted factors and financial indicators
Factor1

Standardized
Coefficientst

p-value

1.684

0.095

-1.4280.157

B

Std.Error

Beta(Constant)

9.510

5.647

SCM Organization Strategy-2.4611.723-0.472IT Utilization Ability-4.7051.898-0.969-2.4790.015

SCM × IT

1.322

0.581

1.142

2.276

0.025

R = 0.346, R2 = 0.120 , Adjusted R2 = 0.093, Std. Error of the Estimate = 3.969

Operating CF per Sales

+2yrs

+1yr

+0yr

+1yr

+0yr

PearsonCorrelation

0.343**

0.281*

0.284**

0.313**

0.250*

p - value

0.003

0.011

0.003

0.005

0.011

PearsonCorrelation

0.009

0.097

0.056

0.078

-0.107p - value

0.942

0.390

0.576

0.491

0.281

N

74

80

103

80

103

The outcomes multiple regression analysis
indicate that the standard regression coefficients for
IT utilization ability on both financial indices arenegative and highly significant especially on
CF/sales. It is identified that when the ability on IT
utilization increases, ROA and CF/sales tend to
decrease. On a contrary, when considering IT
utilization in cooperation with SCM organization
strategy factor, positive correlations on bothfinancial indices are detected at a significant level.
It is implied that organization strategy is a vitalelement to enhance IT usage in a company and later
bring about growth on financial performance. Threevariables account for 9.5% and 9.3% for ROA andCF/sales, respectively, which are considered to be

The multiple regression analysis was carried out toobserve interaction effect of SCM organization
strategy and IT Utilization ability on adjusted
financial indices. To show their interaction effect,
product of the two factors was required and it was
treated as another independent variable. Thus, three
independent variables are considered to findcorrelation on each dependent variable (ROA and132

relatively small. Low level of Adjusted R2 implies
that apart from SCM organization strategy and IT
utilization ability, there exist other factors beyond
the scope of this study that may influence firm’s
financial performance, such as, supply chain
flexibility, responsiveness etc. Higher Adjusted R2
is expected when a greater number of factors areincluded.
Non-linear effect is observed as results ofcorrelation of SCM organization strategy and IT
utilization on ROA and CF/sales. They are shownas 3-dimensional function chart as well as
mathematical expressions. Factor score of SCM
organization strategy is represented by x whereas ysymbolizes IT utilization ability of a specific firm.
Meanwhile, z is referred to ROA in Figure 1.
Similar shape of function chart is observed when
consider operating cash flow per sale as dependent
variable.

financial performance. In this research, adoption of
SCM organization strategy to enhance IT
utilization is shown to make vital contribution
toward better financial performance. Hypothesis
one is validated from correlation analysis. Thisfinding explains why IT investments failed to
improve financial performance for some firms but
noticeable improvements are achieved by others.
Considering the SCM organization strategy as animportant aspect to upgrade IT performance impact,
this research signifies the effect of IT on firm’s
financial performance that may depend on how
well each individual company can organize theirmembers in the supply chain. Strategic planning of
IT utilization among supply chain members should
be carefully arranged such as locating appropriate
level of IT implementation to each supply chainnode.
In this work, empirical models based on ROA
as a function of IT utilization and SCM
organization strategy is developed from statisticalanalysis of audited and publicly reported financial
data. The model indicates that low implementationof IT together with low SCM organization strategy
would yield better financial performance thanextension of IT usage alone in supply chain.
Managers and practitioners need to identify theappropriate context related to IT resource
deployment and to reconfigure the organizational
strategy in a way that can realize the full potentialof IT in the context of SCM.

z = 3.616 - 1.300 x - 2.415y + 0.836xy
ROA
15

10

5

0

2
2

3

1
4

SCM Orgamiza
tion Strategy

5

6

0

4

5

Ut
il

1

3

IT

-15

6

iz a
tio
nA
bil
i

-10

ty

-5

References

Fig.1. 3-Dimensional function chart of ROA

These findings verified Hypothesis 1. SCM
organization strategy is deliberated as a necessary
aspect to increase contribution of IT utilization
toward financial performance. The implementationof both SCM organization strategy and IT results inbetter financial performance as observed from the
proposed analysis. It should be noted that low
implementation of IT together with low SCM
organization strategy yield better financial
performance than merely extension of IT usage insupply chain. Implication can be drawn thatmanagers and practitioners need to identify theappropriate context related to IT resource
deployment and reconfigure the organizational
strategy in a way that can realize the full potentialof IT in supply chain management, as can be seenclearly in Japan.
4. Conclusions
This research stresses upon business value of
IT by indicating the importance of its integration
with SCM organization strategy on the firm
performance. Majority of previous studies focused
only on the contribution of IT in SCM to firm’s

133

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Boudreau, M.C., Robey, D., 2005. Enacting
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Brynjolfsson, E., Hitt, L., Yang, S., 2002.
Intangible
Assets:Computers
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Economic Activity 1, 137–182.

[3]

Byrd, T.A., Davidson, N.W., 2003.
Examining possible antecedents of IT impact
on the supply chain and its effect on firm
performance, Information and Management
41 (December (2)), 243–255.

[4]

Dehning, B., Richardson, V.J., Zmud, R.W.,
2007. The financial performance effects of
IT-based supply chain management systems
in manufacturing firms, Journal of Operations
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[5]Mata, F.J., Fuerst, W.L., Barney, J.B., 1995.
Information technology and sustainedcompetitive advantage: a resource-based
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[6]Melnyk, S.A., Stewart, D.M., Swink, M.,
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Melville, N., Kraemer, K., Gurbaxani, V.,
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[8]

Powell, T.C., Dent-Micallef, A., 1997.
Information technology as competitive
advantage: the role of human, business andtechnology resources, Strategic Management
Journal 18 (5), 375–405.

[9]Ross, A., 2002. A multi-dimensional
empirical
explorationoftechnology
investment,
coordination
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performance, International Journal of PhysicalDistribution and Logistics Management 32 (7),591-609.

[16] Yaibuathet, K., Enkawa, T., Suzuki, S. 2007.
Supply chain operational performance and its
influential factors: cross national analysis,
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[10] Strassman,
P.A.,
1988.
Management
productivity as an IT measure, in Berger, P.,
Kobielus, J., and Sutherland, D. (Eds),
Measuring Business Value Information
Technologies, ICIT Press, Washington, DC,
17-55.
[11] Tan, K.C., Kannan, V.R., Handfield, R.B.,
Ghosh, S., 1999. Supply chain management:
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[12] Theodorou,P.,
Florou,G.,
2006.
Manufacturing strategies and financial
performance- The effect of advanced
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Omega 36(1), 107-121.
[13] Tippins, M.J., Sohi, R.S., 2003. ITcompetency and firm performance: Is
organizational learning a missing link?,
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[14] Vickery, S.K., Jayaram,J., Droge, C.,
Calantone, R., 2003. The effects of an
integrative supply chain strategy on customer
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[15] Wu, F., Yeniyurt, S., Kim, Daekwan,
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134

Impact of Industry Type on Supply Chain Operational Performance in a Develping
Country
Korrakot YAIBUATHET
Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-57 O-Okayama, Meguro-ku ,Tokyo, 152-8552 JAPANyaibuathet.k.aa@m.titech.ac.jp
This research investigates the supply chain operational performance of Thailand’s
manufacturing sector through the use of a supply chain management logistics scorecard(LSC). The LSC was developed as a self-evaluation tool for companies and focuses on four
key areas. Over 150 companies from five industries in Thailand participated in the study
by providing their LSC self-evaluation data. This data was analyzed to identify
determinants of supply chain operational performance in terms of industry type. The
results indicate that different industries have focused on different areas of supply chain
operational performance. The findings of this research may be useful as guidelines forinvestigating and enhancing supply chain operational performance in other newly
industrialized or developing countries

company’s ownership status and industry type on
its supply chain operational performance and its
supply chain management approach will be
examined.
For this research, the manufacturing sector of
Thailand was selected as a case study. Five
different industry types are examined:food,electronics, automotive, chemical, and textile
industries.
Past research has indicated thatdifferent industry types may focus on different
supply chain capabilities (Chan, 2003), which canbring about different levels of SCM performance ineach industry (Li et al., 2006).
Consequently, theeffect of industry type on supply chain operational
performance is a focal area of analysis in thisresearch. By examining supply chain operational
performance in Thai industry, it is hoped that thisresearch will contribute to the SCM literature inunderstanding the effects of industry type on supply
chain operational performance This researchfindings may provide useful implications andguidelines for improving supply chain operational
performance in newly industrialized and developing
countries.

1. Introduction
With the rise of inter-network competition,individual businesses may no longer compete solely
as independent entities but must do so as supply
chains.
Companies associated in the same
network require efficient supply chain integration inorder to optimize their collective performance. To
this end, supply chain management (SCM) has
become recognized as a key business competency.
Moreover, numerous companies have started toappreciate that SCM plays a major role in building
a sustainable competitive edge for their products inhighly competitive markets (Jones, 1998). Past
research (e.g. Kuwaitti and Kay, 2000) has notedthat measurement of supply chain performanceprovides an important foundation for improving theefficiency of the entire supply chain. Performancemeasures can be used not only for driving
continuous improvement of the business, but also
for setting directions for future organizational
strategies. Thus, appropriate and accurate
performance measurement has been consideredbeneficial in the improvement of SCM.
In the global context, the industries of many
newly industrialized or developing countries arelooking to efficient supply chain management as ameans to enhance their competitiveness. This isincreasingly important as their historical advantagesof lower labor and raw material costs fade awaywithprogressive
economicdevelopment.
Accordingly, the aim of this research is toempirically measure supply chain operational
performance in a newly industrializing country andto identify contextual factors which influence
performance.
In particular, the effects of a

2. Background and Research Hypothesis
The SCM literature was reviewed for relevant
research, particularly regarding the relationshipbetween industry type and supply chain operational
performance.
Chan (2003) compared supply chain
performance in three different industries. In theelectronics industry, achievement of quality, ontime delivery and cost were found to have thehighest priority, whereas the logistics services

135industry concentrated on service accuracy andflexibility. In contrast, cost and visibility were
found to be the main concerns in the textile industry.
Similar findings were reported by Li et al. (2006),
who observed that SCM performance and practices
may be influenced by industrial type, as well asother factors such as firm position in the supply
chain and the complexity of the supply chain. Fromthese previous findings, Hypothesis 1 is developed
as follows.
Hypothesis 1: Different industries focus on
different aspects of supply chain operational
performance.
To examine this hypothesis, five industry
sectors in Thailand (food, electronics, automotive,
chemical and textile) are investigated regarding
four assessment areas of supply chain operational
performance. Assessment scores are analyzed for
differences between industries as well as forinteraction effects between assessment area andindustry type. This analysis indicates that different
industries focus on different aspects of supply chain
operational performance.
3. Data Collection and Processing
The data collection process in Thailand waslaunched in 2005 in cooperation with Tokyo
Institute of Technology, Chiang Mai University,
Japan External Trade Organization, Thailand(JETRO), the Thai National Shippers’ Council(TNSC) and the Federation of Thai Industry (FTI).
To date, more than 180 companies from various
industries have participated in this research projectby evaluating their SCM/logistics performance withthe scorecard. Most of the scorecard data was
obtained by an interview process with high-level
managers in the companies so that questions andclarifications could be made regarding theassessment items and levels. As an incentive toparticipate, an individual feedback report wasconveyed back to each company after a database
containing the responses of all companies wascreated.
This confidential feedback reportcontained the results of the company compared withothers in the same industry including its rank
among competitors whose names remained
anonymous. Thus, the feedback incentive helped
to assure the reliability level of the obtained data.
Unlike other scorecards, the LSC has accumulated a
database which has created a virtuous cycle of datacollection and reliability of feedback reports.

only data from these companies was used in thisresearch. The data is classified into five mainindustry types. The category of participatingcompanies is shown in Table 1. As a result of thedata collection process, the histogram of the LSC
total score (100) for 153 companies is displayed in
Figure 1 so as to present the overview of the Thaimanufacturing sector. It can be seen clearly from
Figure 1 that the distribution of the LSC total scorecollected from participants is evenly distributed.
Reliability analysis of the LSC was conductedduring the data collection process. Result is shownin terms of Cronbach’s coefficient alpha of 0.931
for 20 assessment items from the Thaimanufacturing sector. This result indicates that highreliability of the LSC was ensured.
Table 1 Description of participating companies
Industry type
Food
Electronics
Automotive
Chemistry
TextileOthersNo. of Participant
35
32
37
29
12
8

Total

153

Figure 1 Distribution of LSC total scores for Thaimanufacturing sector (five industries combined)

4. Data Analysis
4.1 Data structure and characteristics
At the time of writing, data from more than 180
companies has been collected. Only 153 of thesecompanies are in the manufacturing industry and so136

4.2 Comparative analysis on different industry
type

3.5

3.3

The purpose of this section is to test
Hypothesis 1 by verifying that different industries
focus on different area of supply chain operational
performances. The examination of five industry
clusters, namely: food, electronic, automotive,
chemical, and textile industry in Thailand are
required at this stage. Total LSC score including
four area scores of surveyed industries arecompared and presented in Table 2 and Figure 2.

Area Average Score

3.1
Food
Electronic

2.9

Automotive
ChemicalTextile

2.7

2.5

2.3
1

2

3

4

Area

Figure 2 Averagearea score of five industry clusters

Table 2 Comparison of average total scores and the four LSC assessment areas between five industry sectors in
Thailand
Food

Electronic

Automobile

ChemicalTextile

35

32

37

29

12

Sample Size (n)
Ave

SD

Ave

SD

Ave

SD

Ave

SD

Ave

SD

Total score (100)

57.97

12.66

63.03

14.47

59.78

14.28

53.80

10.19

53.21

10.18

Area 1: Corporate strategy and InterOrganization Alignment

3.069

0.709

3.278

0.751

3.263

0.663

2.947

0.618

2.625

0.643

Area 2: Planning and Execution
Capability

3.135

0.673

3.254

0.734

3.049

0.723

2.881

0.658

2.775

0.690

Area 3: Logistics Performance

2.857

0.670

2.865

0.802

2.902

0.854

2.626

0.620

2.525

0.528

Area 4: IT Methods and
Implementation

2.533

0.802

3.046

0.854

2.743

0.968

2.422

0.510

2.717

0.542

Table 3 Summary of one-way ANOVA result for total score and the four LSC assessment areas by industry type
Total 100

Area 1

Area 2

Area 3

Area 4F-value

2.586

2.889

1.699

1.125

3.194

d.f. (Between groups : Within groups)

4 : 140

4 : 140

4 : 140

4 : 140

4 : 140p-value

0.040

0.025

0.154

0.347

0.015

One-way ANOVAs were primarily conducted
on total score together with each average area score.
The outcomes are given in Table 3. Electronic
industry is found to occupy the highest total scorewith the highest variance while the lowest scorebelongs to textile industry with the minimum
number of data and degree of variation. Findings
from one-way ANOVAs demonstrate that the Fvalues of total score, area 1, and area 4 show
statistical significance with p-value of less than
0.05. It can be concluded that the industries are
statistically different from one another. At thisstage, the analysis seems to imply that supply chain
operational performance in terms of LSC score has
actually been influenced by industry type and eachindustry sector may focus on different areas ofsupply chain operational performance.
It is interesting to shed some light on theinteraction effect between assessment area andindustry type. The outcomes are expected tosupport findings from one-way ANOVAs and tofurther confirm Hypothesis 1. Average scores ofarea 1 to area 4 from entire samples were tested
beforehand, to assess correlations between four
assessment areas using Mauchly’s spherical test.
This test examines the form of the common
covariance matrix. A spherical matrix has equalvariance and covariance equal to zero. In practice,
the univariate approach is appropriate only when
the assumption of sphericality is valid. If the137spherical assumption is invalid, then in mostsituations, the multivariate approach is moresuitable.
In this study, the Chi-square approximation for
Mauchly’s spherical test is 20.735 with fivedegrees of freedom and an associated probability ofless than 0.01. Since this is less than the alpha levelof 0.05, the tested data do not meet the sphericality
criterion. The result of Mauchly’s spherical test
indicates that the four areas interact with one
another. Thus, the multivariate approach using
repeated measures ANOVA is employed to find theinteraction effect between assessment area andindustry type.
The repeated measures ANOVA was executedby setting area scores from the four assessment
areas as the within-subject factor and setting thefive industry types as the between-subjects factor.
The result of this analysis is shown in Table 4.
Repeated measures ANOVA reports four different

multivariate test statistics (Pillai’s, Hotellings’,
Wilk’s, and Roy’s). However, results given in thissection only show the F statistic for Wilks’ Lambda
because the normal distribution is detected among
samples (Stevens, 1996). Since the F ratio for thistest is large [F (3: 138) = 19.770, p = 0.000], themain effect of assessment area is observed. Thissuggests that the area score is influenced byassessment areas. With regard to within-subjects by
between-subjects interaction effect, the F-value
shows highly statistical significance with p-valueless than 0.01 [F (12 : 365) = 2.677, p = 0.002].
This means the interaction effect between
assessment area and industry type is significant
among samples. It can be concluded that changes inarea score across assessment areas depend upon
industry type or the area score is influenced by the
combination effect between assessment area andindustry type. This finding confirms Hypothesis 1.

Table 4 Multivariate test result of Within-Subjects effects (assessment area × industry type)
EffectValue

F

Hypothesis df

Error df

p-value

Area(Wilks’ Lambda)

0.699

19.7703.000

138.000

0.000

Area × Industry(Wilks’ Lambda)

0.800

2.677

12.000365.405

0.002

of supply chain operational performances and the
supply chain operational performance is therefore
influenced by industry type. A similar conclusion
was confirmed by the findings of Chan (2003)
and Li et al. (2006) but our research scope waslimited to the context of a developing country. Theinteraction effect between performance area andindustry type was not considered in earlier works.
Moreover, three additional industries were
inspected on top of three business types which werepreviously investigated by Chan (2003). The resultsin this paper could possibly help researchers andpractitioners better understand what performanceareas should be initially focused on forimprovement purposes in a different industry typeespecially in a developing country.

5. Conclusions
With respect to the findings from this section,
the main effect on assessment area and interaction
effect between assessment area and industrial typeare observed to be significant. Three considerations
are then derived from the analysis result:(1) The first consideration focuses on the scoreachieved from area 1 where the high score group isamong electronic and automobile industries (Figure2). These sectors are positioned in a highly
competitive group, involving a high complexity ofsupply chain. Thus, the close relationship withcustomers and suppliers including sharing ofsuitable information with those business partners
would be considered as a main concern.
(2) Regarding area 4, electronic, automotive
and textile sectors have performed competently.
This group is engaged in high design and processcomplexity in which accuracy is unavoidably
required. Hence, the implementation of practical IT
could assist in accurate data exchange processes
between partners as well as monitoring flow ofmaterial in the supply chain.
(3) Since food and textile sectors may bechallenged with high demand uncertainty, they
have focused their effort on area 2 which is related
to forecasting and ability in adjusting SCM
planning. The analysis results obtained from thissection clearly support Hypothesis 1. It is evident
that different industry types focus on different areas

References
[1]

[2]

[3]
[4]

138

Chan, F.T.S. (2003) Performance Measurement in a
Supply Chain, International Journal of Advanced
Manufacturing Technology, 21, 534-548
Li, S., Ragu-Nathan, B., Ragu-Nathan, T.S., Rao, S.S.
(2006) The impact of supply chain management
practices on competitive advantage and organizational
performance, OMEGA: The International Journal ofManagement Science, 34, 107-124.
Jones, C. (1998) Moving beyond ERP: making themissing link, Logistics Focus, 6(7), 2-7.
Kuwaiti, M.E., Kay, J.M (2000) The role ofperformance measurement in business process reengineering, International Journal of Operations andProduction Management, 20(12), 1411-1426.

How Economic Processes and Institutional Characteristics
Co-Evolve with Customer Satisfaction and Loyalty
Björn Frank
Department of Industrial Engineering and Management, Tokyo Institute of Technology
frank.b.aa@m.titech.ac.jp
1. Introduction

Customer-oriented
performance+

Customersatisfaction

Customersatisfaction

0.326

Perceived
value

0.085

Quality
expectations

0.168

Fig. 1 Economic Growth and Customer Satisfaction.

Firm/brand
image

0.123

3. Removing Economic Influences from Customer
Satisfaction to Improve Quality Management

Switchingcosts

Economic
growth+Perceived
value

+

+
Economic
expectations+

Quality
expectations–

Customersatisfaction

Customer satisfaction survey goal

Customer loyalty is a core driver of business performance. Within the
SIMOT framework, my research explored the moderating impacts ofmarket characteristics, gender, culture, and Chinese-Japanese differences on
the determinants of customer loyalty in Japan. I found that customer
satisfaction is the most important driver of customer loyalty in Japanese
product industries, whereas brand image is the most important loyalty
driver in service industries. Women care far more than men about brandimage and less about customer satisfaction, price, and new productfunctionalities. Switching costs have stronger effects on men than women.
Chinese care more about price and less about brand image than Japanese.
Uncertainty avoidance positively relates to customer loyalty. Time-related
switching costs and brand image have a stronger influence on the loyalty
attitudes of collectivist than individualistic consumers.

+

Details:

Firm

+

+
–

Remove economic
influences from customer
satisfaction scores

4. The Influences of Gender and Culture on the
Determinants of Customer Loyalty

Since supply-side innovation and demand-side needs are interdependent,
I analyzed whether customer satisfaction and economic development areelements of a co-evolutionary relationship. My analyses of eight countries
revealed that economic growth exerts a positive influence on customer
satisfaction, whereas economic expectations exert a negative influence.
Conversely, customer satisfaction does not have a positive impact on
economic growth.

Economic
growthEconomic
growthEconomic
expectations

Fig. 2. Correcting Customer Satisfaction Scores.

2. Co-Evolution between Economic Processes andCustomer Satisfaction across Countries

Co-evolution? No!

EconomyThe analysis of institutional influences on co-evolutionary dynamisms
between economic growth and innovation is at the heart of the SIMOT
framework. I conducted this type of analysis from the perspective of
marketing and quality management. My research analyzed the co-evolution
between quantitative and customer-perceived qualitative economic
indicators and explored how national and industrial institutions affect these
relationships. After basic research established a fundamental theory of these
dynamisms, applied research explored consequences of this theory for
management and policy makers. In this process, I developed techniques torefine quality management and international marketing strategies.

Customersatisfaction

The above research project found that customer satisfaction is positively
influenced by economic growth and negatively by the national stock index.
These results are important to managers using customer satisfaction surveys
to benchmark changes in their firm’s customer-oriented performance overtime. They run the danger of misinterpreting economic-induced variations
in customer satisfaction as caused by changing customer-oriented
performance. My study on durable goods and hospitals shows that thisdanger is justified because economic processes explain 49 to 95%, thus the
majority, of variations in firm-level customer satisfaction scores. To help
firms interpret variations in customer satisfaction, I proposed two methods
to correct time series of customer satisfaction by removing economic
influences. I verified the corrected scores by their impact on future businessperformance. In a number of institutional settings, I confirmed that mycorrection methods can help managers better understand their firm’s
customer-oriented performance and predict future business performance.

Chinese(vs. Japanese)

–

+

–

0.120

–

Customerloyalty

–

+ –
–
–

+

+

FemaleUncertainty
Individualism(vs. male)avoidance

Fig. 3 Determinants of Customer Loyalty.

5. Conclusion
The most important results of my SIMOT research were that customer
satisfaction is positively influenced by economic growth and negatively byeconomic expectations. Conversely, customer satisfaction does not affecteconomic growth. Removing economic influences from time series ofcustomer satisfaction may enhance the strategic meaningfulness ofcustomer satisfaction scores and thus improve quality management. New
knowledge about differences in consumer behavior between men andwomen, Japanese and Chinese, individualistic and collectivist consumers
enable firms to design cross-cultural customer retention strategies.

139How Economic Expansion Drives Customer Satisfaction: a Study from Germany
Bjoern Frank*, Takao Enkawa**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANfrank.b.aa@m.titech.ac.jp
Changes in customer satisfaction (CS) are usually linked to a firm’s performance insatisfying its clients or to developments within its direct competitive environment.
Managers should better extend their view towards accounting for the overall economic
development. This study reveals that the economic development (EE) is driving CS via the
expansion of the average consumer’s budget and via an increasing perceived value (PPR)
of offerings. The effect is positively moderated by the degree of competition on price, by
the degree of technology used for creating products or services, and by the speed ofinnovation.
1. Introduction and purpose
Up to now, research on management oftechnology (MOT) has focused upon how to
improve internal processes within companies(process innovations) and how to create new
products for the market (product innovation).
Another research approach would be to analyze
how consumers perceive the results of that
innovation. Marketing research has mostly analyzed
how improved products, the result of productinnovation, have impacted upon consumers, but
process innovations have been neglected. By
focusing on the socioeconomic system, an
institutional dimension within the SIMOT
framework (Science of Institutional MOT), wewould like to analyze how economic expansion(EE) affects customer satisfaction (CS). The reason
we put emphasis on EE is that in the long term,
innovation is the only driver of EE in a closed
economy (Blanchard, 2006): Process innovations
free up financial resources without altering the total
economic output. These freed financial resources
can then be invested into consuming new products
or services, and the total economic activity grows
accordingly. Therefore, the economy cannot growfaster than the rate of process innovations.
Based on a comprehensive data set from
Germany and on knowledge from contradictory
pioneer work in this field (Fornell & Stephan, 2002;
Fornell, 2003; VanAmburg, 2004; Ikeshoji &Enkawa, 2004; Ikeshoji et al., 2005; Fornell & Rust,
2005), this study aims at illustrating themechanisms by which EE drives CS and at showing
how they are moderated across industries. By
examining the moderating influence of quality vs.
price competition, technology, and the speed ofinnovation, we hope to provide companies with140

more detailed information necessary to conduct
realistic forecasts in their specific field of business.
2. Development of hypotheses
2.1 The impact of aggregate perceived value
Since marketing became aware of the great
importance of convincing consumers, myriad
studies have analyzed the antecedents to CS. They
have first identified consumer-perceived quality as
the main driver of CS (Cardozo, 1965; Olson &Dover, 1979; Oliver, 1980; Churchill & Surprenant,1982; Bearden & Teel, 1983; Oliver & DeSarbo,
1988; Tse & Wilton, 1988; Anderson et al., 1994;
Ikeshoji et al., 2003) and then shifted to the conceptof perceived value, also called the perceived
performance-price ratio (PPR) (Sawyer & Dickson,
1984; Zeithaml, 1988; Fornell, 1992; Anderson &Sullivan, 1993; Anderson et al., 1994; Fornell et al.,
1996; McDougall & Levesque, 2000; Spiteri &Dion, 2004), i.e. perceived quality in relation to theprice of a good or service. CS can be raised either
by providing higher consumer-perceived quality at
the same price or by providing the same quality at alower price.
Literature has been focusing on what leads tothe satisfaction of an individual customer. Since EE,
the focal independent variable of this study, is anaggregate concept, it is necessary to understandwhat drives the satisfaction of the average
consumer within an economic zone. The obvious
idea is that the individual effect persists at theaggregate level: The average perceived value drives
the average CS. This conclusion can only be true if
there is no stronger aggregate counter-effect, e.g.
stemming from interactions between consumers.
Fig. 1 displays hypotheses H1 and H2.
H1:
The average PPR has a positive impact
upon average CS.

Fig. 1. Hypotheses H1 and H2

hypothesis H1 is true, then EE should positively
affect the average CS. Fig. 2 illustrates the temporaldevelopment of the average CS, the average PPR,
and the average consumer’s budget modeled by thereal disposable income of private households per
capita (RDI/C).
H2:
EE has a positive impact upon the
average CS via an increased average PPR.

2.2 The impact of economic expansion (EE)
Recent studies based on American data reveal a
positive relationship between aggregate CS andaggregate consumer spending (Fornell & Stephan,
2002; Fornell & Rust, 2005) or GDP growth(Fornell, 2003; VanAmburg, 2004), two highly
correlated variables. Their authors argue thatsatisfied customers spend more, which drives thewhole economy. One should be very careful when
making such interpretations. It has been shown thata customer who is satisfied with one company will
resort to the services of that company more often(Bolton, 1998; Fornell, 1992), but at the same time
he should consume fewer offerings fromcompetitors. Also, the consumer should reshuffle
his expenses between industries. For example, aconsumer who is highly satisfied with his car mighttake the train less often. Consumers reorganize theirexpenses in a way that they get the same utility at alower cost. Higher CS should therefore not cause
EE.

2.3 Moderators upon the EE-CS chain
Depending on the market structure, on thenature of goods and services, and on personal tastes,
consumers may either have a stronger price or
quality orientation. According to hypotheses H1and H2, EE drives aggregate CS via the aggregate
PPR. EE implicates a higher average consumer
budget, which makes prices seem more affordable(higher average PPR) and thus enhances theaverage CS. Since this mechanism acts on the pricecomponent of the PPR, the effect should be stronger
in industries where consumers have a relatively
stronger price orientation and lower in industries
where consumers have a relatively stronger quality
orientation. All hypotheses regarding moderators on
the EE-CS chain are displayed in Fig. 3.
H3:
The positive impact of EE on average
CS is more pronounced in industries with arelatively stronger price orientation and lesspronounced in industries with a relatively stronger
quality orientation of consumers.

H1

EE+ Consumer +budget

PPR

+

CS

H2

RDI/C [1000 EUR; Price-Level of 2000]
PPR [0-100]
CS [0-100]
66

RDI/C

16.5

62

16.0

58

15.5

54

15.0
14.5

H3
CS / PPR

17.0

Degreeof priceorientation

EE+

Amount oftechnology
H4+

Speed ofinnovation

+
+

H5
CS

Fig. 3. Hypotheses H3 to H5 – Moderating Effects

50

Technological progress is the main driver of EE(Blanchard, 2006). On the supply side of theeconomy, high-tech firms profit more from
economic up-turns than low-tech firms because they
can reinvest their profits, which grow in times of
economic growth, into improving their products
even more due to their higher industrial researchorientation (Arthur, 1996). On the demand side, EE
leads to rising consumer budgets, which incurs theprimary consumer orientation to slowly shift fromprice towards quality (Kohli & Jaworski, 1990;
Banker et al., 1996). Consumers spend more (Petre,1986) and are more willing to try new andinnovative things with their excess money, which
increases CS by more consumption experienceswith previously unknown offerings (Fornell, 1992).

1992 1994 1996 1998 2000 2002 2004 2006

Fig. 2. EE, Average CS, and Average PPR in Germany(1992 – 2006)

We rather assume that EE drives the average
CS. Since the size of the economy is measured as
the sum of all incomes (GDP), an expansion of theeconomy is equivalent with a higher average
income and thus a higher average consumer budget.
With a rising consumer budget, prices seem lower(more affordable) relative to the budget, whichmeans that the average perceived performance-priceratio (PPR) increases. At the individual level, the
PPR is the main driver of CS (Sawyer & Dickson,
1984; Zeithaml, 1988; Fornell, 1992). If this effectis also persistent at the aggregate level, i.e. if

141

H4:
The positive impact of EE upon CS
should be stronger for high-tech industries andweaker for low-tech industries.
Similar to the state of technology, the speed ofinnovation should have a moderating impact on the
EE-CS chain. From a consumer’s point of view,high speed of innovation can be associated with ahigh level of risk because consumers need to adapt
to new situations without knowing how much theoutcome will please them in the end. Low speed ofinnovation represents a high level of security
because everything remains more or less unchanged,
in a configuration to which consumers are wellaccustomed (Kohli & Jaworski, 1990; Bennett &Cooper, 1981; Houston, 1986; Kaldor, 1971). In
times of EE and rising consumer budgets,
consumers have a more positive attitude and enjoyrisks and dynamic processes (e.g. fashion, stock
market) whereas secure, static things do not rise ininterest (e.g. churches) or even become boring(Tauber, 1974; Arthur, 1996). One can well
imagine the opposite for an economic down-turn.
H5:
The positive impact of EE upon CS
should be stronger for industries with a high speedof innovation and weaker for industries with a low
speed of innovation.
3. Data and methodology
This study uses national economic data from
Germany (Destatis, 2007) and consumer (CS, PPR)
data the German Customer Monitor (CGM; Meyer& Dornach, 1992-1994; Servicebarometer, 19952006) throughout the whole period of availability,
i.e. from 1992 until 2006. Established in 1992, theGCM became one of the world’s biggest CS
barometer in terms of the sample number (Bruhn &Murmann, 1998; Grigoroudis & Siskos, 2004).
30,000 customers are interviewed once a year withrespect to CS, PPR, and other aspects of consumer
attitudes in 30-40 industries per year, totalling 79
industries because of a fluctuating industrial
composition. National CS and PPR values represent
arithmetic averages of the underlying industry-level
data. Fig. 2 gives an overview of the economic, CS,
and PPR development during the survey period. For
the moderator analysis, the industries are divided
into subgroups representing their level in therespective category.

consumption of private households (RC), as both anabsolute and a per capita (/C) measure. It can beseen that the measure displaying the highest andmost significant correlation is the disposable
income per capita (RDI/C), i.e. the consumer
budget, which is in line with the hypothesizedargumentation. The correlation becomes stronger
the more industries are included in the national CS
average, probably because the CS measure becomes
more representative for the macroeconomic
situation. A separately conducted Granger test of
causality (Granger, 1969) shows that while EE
influences CS, CS does not significantly influence
EE.
Table 1 The Impact of EE on PPR and CS (1992-2006) –Real Economic
PPR
CS
Indicators
Cor. p-Val
Cor. p-Val
RGDP
0.626 0.008
0.847 0.000
RGDP/C
0.642 0.007
0.849 0.000
RDI
0.634 0.007
0.878 0.000
RDI/C
0.661 0.005
0.888 0.000
RC
0.577 0.015
0.825 0.000
RC/C
0.595 0.012
0.828 0.000
PPR
0.808 0.000
Sample Number 14 (1993-2006) 15 (1992-2006)
Correlations and SignificanceAn interesting observation from Table 1 is that
the RDI/C more significantly affects CS than PPR,
which challenges our hypothesis H2 claiming that
PPR mediates the relationship between the average
consumer’s budget and the average CS. To further
investigate this issue, Fig. 5 compares threestructural models (SEM) created in AMOS. It
displays standardized path coefficients and, inparentheses, the level of significance. While pathcoefficients in the hypothesized model 1 are highly
significant, the model does not have an acceptable
overall fit. As the source of this low fit might be thefact that, against hypothesis H2, the impact of the
RDI/C on CS is not mediated by PPR, model 2 tests
a situation where both PPR and CS are
independently influenced by RDI/C. However, itturns out that the hypothesized model 1 is better
than model 2, which gives support to the idea of
mediation. Model 3 tests the possibility that theeffect is only partially mediated by PPR. It turns outthat model 3 has a very good fit and is superior toboth models 1 and 2 and that the hypothesizedindirect effect is stronger than the additional direct
effect.
A possible reason for a direct effect is that the
PPR rather captures process than productinnovations: On the one hand, process innovations
create the financial scope for economic growth, i.e.

4. Results
As can be seen in the lower part of Table 1, CS
and PPR are highly correlated, which confirms
hypothesis H1.
Table 1 shows that EE has a positive andsignificant impact on both PPR and CS. EE ismodeled by real GDP (RGDP), the real disposable
income of private households (RDI), and the real142the expansion of consumers’ budgets (affects priceperception). On the other hand, process innovations
make products cheaper. However, new, initiallyhigh-priced products (product innovations) will notnecessarily improve the PPR, but they may
fascinate the consumer, thus raising CS directly.

significant and even enhance the fit of all models in
Fig. 4.
All three hypotheses H3 to H5 are confirmed
and mainly rely on the indirect impact of theaverage consumer’s budget on CS via PPR, which
was already hypothesized in hypothesis H2. The
results are also valid and significant for the overall
effect but weakened by the additional direct effectfrom RDI/C to CS. Additional analyses show thatfor all subgroups in Table 4, the RDI/C is thedominant economic measure explaining CS and
PPR.

N=14 (1993-2006, Yearly All-Industry Averages,
Only Industries with Both CS and PPR Data)
Model 1:
RGDP/C

0.984(0.000)

RDI/C

0.661
(0.001)PPR

0.925(0.000)CS

df: 3; Chi-Sq.: 12.047 (0.007); GFI: 0.770;
NFI: 0.866; RMSEA: 0.482
Model 2:
0.984
RGDP/C(0.000)0.661 (0.001)
RDI/C
0.827 (0.000)

5. Conclusion
With a SIMOT approach focusing on the socioeconomic dimension of institution, we showed how
economic expansion (EE) drives customer
satisfaction (CS) and thus gained knowledge about
how innovation affects consumers in the long term.
The size of the economy is a measure of how its
participants on the supply side perform in satisfying
the needs of the demand side. Technologicalprogress in a large sense, i.e. not only referring tobetter machines but also to improved concepts andnew ideas, is the main driver of long-term economic
growth (Blanchard, 2006). Products and services
are becoming better and better, and increasing
production efficiency makes salaries rise.
In other words, the price-level, relative to thetotal, rising consumer budget, for existing goods
and services of constant quality is decreasing
continuously. Literature has shown that such an
improvement of the perceived value of goods andservices (PPR) increases the satisfaction ofindividual consumers (Sawyer & Dickson, 1984;
Zeithaml, 1988; Fornell, 1992; Anderson &Sullivan, 1993; Anderson et al., 1994). We firstprove that this effect is also valid at the macroeconomic level: The PPR as perceived by theaverage consumer in the economy strongly
influences the average CS (hypothesis H1). Since
EE is equivalent with an improvement of theaggregate PPR, we then also demonstrate that EE
drives the average CS mainly via changes of theaverage consumer budget (hypothesis H2). In
addition to the mediation via PPR, there seem to be
additional, weaker intermediate steps in the relation
EE and CS, which we can only hypotheticallyexplain.
The analyses relating to hypotheses H3 to H5
explore the effect of moderating variables upon therelationship between EE and aggregate CS.
Technology being the central driver of EE, theamount of technology (H4) and the speed ofinnovation (H5) within industries wield a positiveeffect on the relationship between EE and aggregate
CS. Since the relationship mainly works via the
expansion of the average consumer budget, we

PPRCS

df: 3; Chi-Sq.: 22.248 (0.000); GFI: 0.704;
NFI: 0.752; RMSEA: 0.703
Model 3:
RGDP/C

0.984(0.000)RDI/C

RDI/Capita Æ CS:
Direct: 0.382
Indirect: 0.444
Total:
0.827

0.661(0.001)

PPR

0.672(0.000)CS

0.382 (0.000)
df: 2; Chi-Sq.: 1.047 (0.585); GFI: 0.962;
NFI: 0.988; RMSEA: 0.000

Fig. 4. Comparison of Hypothesized Structural Modelwith Alternatives
Table 1 Moderating Impacts on the EE-CS Chain –Industry-Level SEM Paths from Model 3 (seeFig. 4)
Criterion for Industry
Classification
Category N
Consumer Orientation: quality
32
Quality vs. Price
equal
101
price
217
Amount of Technology low
176
high
174
Speed of Innovation
low
204
high
146

RDIC → CS
Direct Indirect
0.164 0.004
0.076 0.152
0.070 0.181
0.159 0.003-0.007 0.250
0.037 0.139
0.166 0.190

After the previous section provided strong
empirical evidence for the impact of EE on CS andthus confirmed hypothesis H2, Table 2 uses model
3 from Fig. 4 to verify the moderating effects ofvariables as hypothesized in H3 to H5: consumers’
relative quality vs. price orientation, the degree oftechnology, and the speed of innovation. The direct
and indirect SEM path coefficients between RDI/C
and CS are relatively low compared to Fig. 4
because the consumer-data is now industry-specific,
whereas the economic data is still an aggregate
variable, which introduces a lot of variation acrossindustries. However, when using industry-level datafrom all industries, the correlations are still143

show that the effect is more pronounced if
consumers have a stronger focus on prices than on
quality (H3).
This study has important implications formarketing managers: The results of internal CS
barometers may not only be influenced by a firm’s
own performance, but also by the industrial or even
economic development. Scores on such surveys
may improve as a consequence of rising spending
power, even if the firm does a poor job in satisfying
customers. Forecasting the impact of spending
power on CS is crucial for designing goodmarketing strategies and for drawing the rightconclusions from customer surveys.
Since satisfaction is a central social objective,
public policy makers should understand how EE
can improve CS. This study provides public policy
makers with empirical results allowing them toquantify in how far a combination of transfer
payments, market regulations, and incentives forhigh-tech and innovative industries can influence
CS. Important messages from our study are that arising consumer budget drives CS and that thisrelationship becomes stronger with fiercer pricecompetition, thus advocating anti-trust regulations
as well as deregulation and privatization of public
monopolies. The relationship also becomes stronger
for high-tech industries and for those with shortinnovation cycles, suggesting a positive impact ofpublic incentives for those economic areas.
Future research should attempt to explain
missing elements in the relationship from the
expanding consumer budget to CS. Anotherpossible direction of research might be to extend
the analysis from a highly-developed country like
Germany to emerging markets with much stronger
yearly variations in economic development,
spending power, and product quality, although it
might take a couple of years to collect sufficientlongitudinal data.

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References
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Arthur, W.B., 1996. Increasing Returns andthe New World of Business. Harvard Business
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Abbreviations
CS
customer satisfaction
EE
economic expansion
PPR
perceived performance-price ratio
RDI/C
real disposable income of privatehouseholds per capita
[1]

[3]

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144

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145

Co-Evolution between Customer Satisfaction and Economic Development: An
International Comparison
Björn Frank, Takao Enkawa**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-429 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANfrank.b.aa@m.titech.ac.jp
Since consumer appreciation represents both an objective and a source of corporate
endeavors, we analyze whether customer satisfaction and economic development areelements of a co-evolutionary relationship. Our analyses of eight countries reveal that
economic expansion exerts a positive influence on customer satisfaction, whereas economic
expectations exert a negative influence. Conversely, we also analyze whether priceadjusted customer satisfaction growth has a significant, positive impact on spending
growth, but we can only confirm the effect for Sweden.

1. Introduction
Managers and marketing researchers regard
customer satisfaction (CS) as a central goal for
corporate marketing strategies because it induces
repurchase behavior (Fornell, 1992) and word-ofmouth communication (Oh, 1999); reduces
marketing costs (Reichheld & Sasser, 1990); andenhances sales (Gómez et al., 2004) andprofitability (Anderson et al., 1994).
Satisfaction is not only a corporate objective,
but also a societal goal. Initial studies haveanalyzed whether and how the economic
development contributes to variations in CS(Dermanov & Eklöf, 2001; Ikeshoji & Enkawa,
2004; Frank & Enkawa, 2007). The first objectiveof our study is to deepen these initial theories and toassess their general validity by comparing themacross countries: Denmark, Germany, Hong Kong,Japan, South Korea, Sweden, and the United States.
Conversely, some authors (Fornell, 2003;
Fornell & Rust, 2005) argued that growing
aggregate CS is the most reliable short-term
predictor of spending and GDP growth. Therefore,
the second goal of our article is to reexamine theseanalyses and compare them across countries to test
their general validity.
Economic development is a mirror oftechnological progress (Blanchard, 2006) and thusof efforts in the management of technologies(MOT). Hence, our research design corresponds toan investivation of how MOT output and CS coevolve at the aggregate level on the long-term. We
will explain international differences on the basis ofinstitutional characteristics and hence provide an
original contribution to the science of institutional
MOT (SIMOT).

2. Development of hypotheses
2.1 CS theory
Literature agrees that CS results from a
cognitive comparison between pre-purchase
expectations (negative impact) and the postpurchase perceived value (quality divided by price)of goods and services (positive impact). If theperceived value exceeds prior expectations, theconsumer will be satisfied, and vice versa(Churchill & Surprenant, 1982; Oliver & DeSarbo,
1988).
2.2 The impact of economic expansion on CS
As the economy expands and the standard ofliving improves, consumers should become moresatisfied. While this mechanism may seem obvious,
previous studies (Dermanov & Eklöf, 2001; Fornell,
2003; Fornell & Rust, 2005; Ikeshoji & Enkawa,
2004; Frank & Enkawa, 2007) did not yield
concurrent results, most likely because theirrespective argumentation only captured part ofreality.
On the supply side of the economy, firms invest
R&D in order to improve their products andenhance CS (Churchill & Surprenant, 1982; Oliver& DeSarbo, 1988). This supply-side effect of R&Ddriven economic growth on CS should involve asignificant, industry-specific time-lag from
corporate investments to final consumption.
On the demand side, economic expansion
brings about higher real incomes, which makes
prices seem lower relative to the greater
consumption budget, and thus positively affects CS(Churchill & Surprenant, 1982; Oliver & DeSarbo,
1988; Frank & Enkawa, 2007). Since this effectrelates to current income, the time-lag between
growing income and consumption should be
relatively short. The long-term supply-side and the146short-term demand-side effects converge into ourhypothesis:
H1: Economic expansion positively affects CS.

countries in which so-called national CS barometers
have measured CS for an acceptably long time in ahigh number of industries: Denmark, Germany,
Hong Kong, Japan, South Korea, Sweden, and theUnited States. We will choose the variables in
direct correspondence with our hypotheses.
In order to test the hypotheses H1 and H2, wewill first conduct a principal component (PC)analysis (Dunteman, 1989) of the economic
expansion and economic expectations measures andthen regress these principal components on CS foreach country. In our investigation of hypothesis H3,
we will stick to the model that Fornell & Rust(2005) used to illustrate the impact of one-quarterlagged price-adjusted CS (CS) growth on consumer
spending (consumption/capita) growth.

2.3 The impact of economic expectations on CS
Economic
expectation
andconfidence
indicators (e.g. consumer confidence, industrial
confidence, retail confidence, and the stock index)
are measures of the expectations that market players
have regarding current and future economic
development which is an aggregation of corporate
activities. Since these expectations relate toproducts and services, they should have a negative
impact on CS (Churchill & Surprenant, 1982;
Oliver & DeSarbo, 1988).
H2: Economic expectation and confidence
measures negatively affect CS.
2.4 The impact of CS on spending
While our argumentation in the previous two
sub-sections focused on the impact of economic
development on CS, the authors publishing theAmerican CS Index (ACSI) disagree and argue thatCS growth has a positive, short-term impact onspending growth (Fornell & Stephan, 2002; Fornell& Rust, 2005) and on GDP growth (Fornell, 2003;
VanAmburg, 2004), two highly correlated variables.
They argue that more satisfied consumers spend
more, which drives the whole economy. Theirfinding may be quite important because it offers a
new way to forecast consumer spending, but wequestion their argumentation. Consumers satisfied
with the goods and services of a certain company
should buy more from that company, but at thesame time less from competitors. It is by no means
clear that satisfied consumers will increase their
total consumption expenditures. On the contrary,
consumers can be thought to enhance theirsatisfaction by choosing the company offering thesame utility at the lowest price, which should
reduce total expenditures.
Based on these doubts, we would like toreexamine their results and compare them acrosscountries to verify their general validity. In theirmost recent article, Fornell & Rust (2005) argue
that there is a strong impact of one-quarter-lagged
price-adjusted CS, i.e. CS divided by the consumer
price index (CPI), on the per-capita spending
growth. We will thus base our investigations on
their methodology and hypothesize as follows:
H3: The one-quarter-lagged growth of priceadjusted CS positively affects per-capita spending
growth.
3. Data and methodology
Since all our analyses relate to longitudinal
analyses of the relationship between CS andeconomic developments, our study will use
aggregate economic and CS data from those147

4. Results
4.1 The impact of economic development on CS
To measure the impact of economic
development on CS, we extracted uncorrelated
principal components (PC) from our dataset for
both economic expansion (Econ) and economic
expectations (Expt) in each country. Then we
regressed these PC on CS. The results in Table 1
reveal that economic expansion has a positive andeconomic expectations have a negative impact on
CS, which confirms our hypotheses H1 and H2.
Table 1 Regression analysis explaining CS

F
Country
Regressor t-val (p-val) Adj. R²
DenmarkEcon
8.448 (0.001) 38.39(N=7: 99-05) Expt
-2.326 (0.081) 0.926
GermanyEcon
4.204 (0.000) 17.01(N=15: 92-06) Expt1-5.226 (0.000) 0.774
Expt2-2.460 (0.032)
Hong KongEcon
3.724 (0.010) 10.27(N=9: 98-06) Expt
-2.582 (0.042) 0.699
Japan
Econ
2.394 (0.062) 5.33
(N=8: 83-04) Expt
-2.210 (0.078) 0.553
South Korea
Econ
8.343 (0.000) 37.96(N=15: 92-06) Expt
-2.513 (0.027) 0.841
SwedenEcon
8.582 (0.000) 49.17(N=12: 94-06) Expt
-4.570 (0.001) 0.898
USA
Econ
1.986 (0.078) 5.45
(N=12: 95-06) Expt
-2.120 (0.063) 0.447
Even though the results confirm our hypotheses,
there are small differences between countries,
which can be explained by institutional parameters.
Germany is the only country where retail
expectations (Expt2) constitute a separate PC with asignificant impact on CS. Among the countries

analyzed, Germany has the most competitive retailmarket where firms show the fastest reaction tochanging consumer demands. Hence, retailconfidence validly reflects changing consumer
expectations, whereas in other countries with lower
competitive intensity in the retail market, retailconfidence seems to be a less salient indicator of
consumer expectations.
In Japan the negative economic expectations
effect is expressed by investor expectations rather
than by consumer confidence, which is most likely
because the surveyed industries all concern durable
goods and thus large industrial groups in the stockindex rather than service companies which arecloser to the customer.
In Hong Kong, the impact of economic
expectations on CS involves a time-lag of two years
which is longer than in the other countries. Since
Hong Kong’s economy strongly depends on
arbitrary, hard-to-predict political decisions by the
Beijing regime, citizens of Hong Kong seem toneed more time to develop trust in the sustainabilityof current economic development.
Conversely, the impact of economic
expectations on CS in South Korea is shorter thanin the other countries. It seems that in South Korea
general expectations are very fast to be translated to
the level of goods and services. Perhaps therelatively low per-capita income and the long
history of strong growth cause general expectations
to be strongly linked to consumption. The results
might therefore be an indicator of the situation indemocracies with strongly developing economies.
For the United States, the analyses only show
acceptable results when using stronger time-lags(up to five years) for the economic expansion
variable. A reason for the lower significance may
be a weak income-based short-term impact of
economic expansion on CS, coupled with astronger-lagged R&D-based long-term impact (seeargumentation of hypothesis H1): Over the survey
period, the workers’ salaries did not profit from theeconomic expansion as elsewhere and the current,
non-lagged impact of economic expansion on CS
should thus be weaker than in other countries (seeargumentation for hypothesis H1). On the other
hand, the R&D-based long-term impact of
economic expansion on CS involves a relatively
long time-lag because the US is home to manystrong high-tech firms with long R&D cycles.
In summary, the positive impact of economic
expansion and the negative impact of economic
expectation measures on CS are supported acrossall investigated countries. There are minor
differences among countries which can be
explained on the basis of the country-specificpolitical, cultural, and macroeconomic framework.

4.2 The Impact of CS on spending
Based on Fornell & Rust (2005), hypothesis H3
assumes an impact of the one-quarter-lagged
growth of price-adjusted CS, i.e. CS divided by the
consumer price index (CS/CPI), on per-capita
consumer spending growth.
Table 2 The impact of CS-price ratio growth on
spending growth

Correlations: Delta ln [CS/CPI (t-1 quarter)]↔ Delta ln [Real Consumption per Capita(t)]Using Data with Yearly Periodicity
Country
N Period Correlationp
Denmark
6 99-05
0.056
0.458
Germany
14 92-06
0.042
0.444
Hong Kong
8 98-06
0.109
0.398
South Korea 14 92-06-0.321
0.131
Sweden16 89-06
0.618
0.005
USA
12 94-06
0.284
0.186
The international comparison in Table 2 reveals
that the effect is only significant in Sweden. In the
United States, the result is only significant whenusing quarterly (as done by Fornell & Rust, 2005)
instead of yearly data, which is methodologicallyinappropriate because data in every industry are
updated only once per year.
When not using growth variables in themultiplicative regression model of Fornell & Rust(2005), but instead regular variables in an additive
regression model, the one-quarter-lagged impact ofprice-adjusted CS on consumer spending turns
significantly negative (!) in all countries. That is
because inflation accompanies consumption growthon the long-term, which systematically decreases
the price-adjusted CS (CS/CPI) while realconsumption increases. Therefore, Fornell & Rust’s(2005) findings can only have partial validity
within the rigid framework of their short-term
model.
In summary, we cannot detect any generalimpact of one-quarter-lagged price-adjusted CS
growth on spending growth. Using Swedish data inthe model of Fornell & Rust (2005) yields
significant results, which should receive further
scrutiny from future research.
5. Conclusions
Since CS is both the source and the target ofcorporate R&D/MOT activities, we investigated theco-evolutionary dynamisms between economic
development and CS. For our analyses, we used
economic and consumer data from all countries
with a long-enough history of customer satisfaction148

measurement: Denmark, Germany, Hong Kong,Japan, South Korea, Sweden, and the United States
We found that the economic development
indeed significantly impacts CS via two
mechanisms: a positive impact of economic
expansion and a negative impact of economic
expectations. Our results can be viewed as a
generalization of disconfirmation theory fromindividual consumers to macroeconomic processes.
The international differences can be interpreted asfollows:
A) Retail expectations are a valid, separate indicatorfor economic expectations if the retail market ishighly competitive (Germany).
B) The time-lag of the negative impact of economic
expectations on CS is larger in a situation ofpolitical uncertainty (Hong Kong) and shorter inthe case of strongly developing countries (South
Korea).
C) The time-lag of the positive impact of economic
expansion on CS is larger if the average
consumer cannot profit from economic growthand if a national economy has a considerable
share of high-tech, long-term R&D firms (US).
Conversely, our analysis analyzed the impact of
CS on economic development but did not yield any
generally supportive result. Among all countries,
only Sweden showed a significant positive effectand only if analyzed in the rigid model proposed byFornell & Rust (2005).
In summary, our results indicate that no generalco-evolution exists between economic development(created by MOT-based R&D efforts) and CS. Only
Sweden shows such co-evolution. In the othercountries, economic development significantly
influences CS, but not vice versa. Future researchought to investigate the reasons for co-evolution in
Sweden and whether the Swedish economic model
includes components transferable to other countries.

[5]

Dunteman, G.H., 1989. Principal Components
Analysis. Sage Publications, Newbury Park.

[6]

Fornell, C., 1992. A national customer
satisfaction
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Swedishexperience. Journal of Marketing, 56 (1) 6-21.

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nation’s economy. Quality Progress, 36 (2)25-31.

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Fornell, C., Rust, R.T., 2005. The Effect ofBuyer Satisfaction on Consumer Spending
Growth. Research paper, Sep 9. University ofMichigan.

[9]Fornell, C., Stephan, J., 2002. Consumer
Spending Growth Predicted by Buyer
Satisfaction. Research report, The National
Quality Research Center, Ann Arbor.

[10] Frank, B., Enkawa, T., 2007. How economic
growth affects customer satisfaction: a study
from Germany. Proceedings of the 13th APMC
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D.R., 2004. Customer satisfaction and retailsales performance: an empirical investigation.
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[13] Oh, H., 1999. Service quality, customer
satisfaction, and customer value: a holistic
perspective. Hospitality Management, 18 (1)67-82.
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References[15] Reichheld, F.F., Sasser Jr., W.E., 1990. Zerodefections: quality comes to services. Harvard
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[1]

Anderson, E.W., Fornell, C., Lehmann, D.R.,
1994. Customer satisfaction, market share,and profitability: findings from Sweden.
Journal of Marketing, 58 (4) 53-66.

[2]

Blanchard, O., 2006. Macroeconomics, forthed. Pearson Prentice-Hall, Upple Saddle River.

[3]

Churchill, G.A., Surprenant, C., 1982. An
investigation into the determinants ofcustomer satisfaction. Journal of Marketing
Research, 19 (4) 491-504.

[4]

Dermanov, V., Eklöf, J. (2001) Using
aggregate customer satisfaction index:
challenges and problems of comparison withspecial reference to Russia. Total Quality
Management, 12 (7) 1054-1063.

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in a changing economy: results from theAmerican Customer Satisfaction Index.
Annual Quality Congress Proceedings, 58,
233-236.

The Relationship between Economic Growth and Customer Satisfaction
Björn Frank **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-429 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANfrank.b.aa@m.titech.ac.jp
Based on data from Germany, South Korea, Sweden, and the US, this article analyzes
the relationship between economic growth and customer satisfaction. Researchers haverepeatedly stated that aggregate customer satisfaction would positively affect aggregate
consumption and thus economic growth. Using Granger tests and structural equation
modeling, we find that these claims are wrong. Conversely, economic growth does affectcustomer satisfaction. This effect is mediated by aggregate income and the perceived valueof goods and products. It is stronger in high-tech industries, industries with rapid
innovation cycles, and industries with fierce price competition. Of SIMOTic relevance, wefind that there is no co-evolution between economic growth and customer satisfaction but
a purely unidirectional relationship. SIMOT should consider enlarging its target variables
to include utility measures such as customer satisfaction because society primarily pursues
well-being, not just economic growth.
concern for the science of institutional MOT(SIMOT), we are interested in whether international
and industrial differences in institutions moderate
this relationship.

1. Introduction
Managers strive for high levels of customer
satisfaction (CS) because CS leads to repurchasebehavior (Fornell et al., 1996), positive word-ofmouth referrals (Fornell et al., 1996), lower
marketing costs (Reichheld & Sasser, 1990), higher
sales (Reichheld & Sasser, 1990), and higher
profitability (Ikeshoji & Enkawa, 2004).
Economic policy aims at improving the benefitsof market participants, but the underlying dynamics
have not yet been well understood. Some
researchers argue that economic growth contributes
to aggregate CS (Ikeshoji & Enkawa, 2004).
Conversely, other researchers argue that aggregate
CS contributes to economic growth (Fornell, 2003;
Fornell & Rust, 2005). It might even possible that
economic growth and CS build two elements of aco-evolving system.
Our objectives are to solve the contradiction
between these two existing theories and to explore
the mechanisms within the relationship between
economic growth and CS. For these ends, our study
uses data from the world’s most comprehensive
national consumer barometers in Germany, South
Korea, Sweden, and the United States.
Our analysis of the co-evolutionary processes
between economic growth and CS has important
implications for the management of technology(MOT). Currently, MOT research mainly focuseson economic growth as the target variable andignores consumer utility, even though society
primarily pursues subjective well-being. Potential
co-evolutionary processes between economic
growth and CS might justify a need for MOT
research to account for consumer utility. Of special

2. Development of hypotheses
Based on US data, marketing researchers
identified a positive association between economic
growth and CS (Fornell, 2003; Fornell & Rust,
2005; Fornell & Stephan, 2002; VanAmburg, 2004;
26 press releases from 2002 to 2007 in NQRC,
2008). They understood this relationship as an
influence of aggregate CS on economic growth.
Specifically, they argued that satisfied customers
spend more, which drives the whole economy.
We cannot agree with this argumentation.
Satisfied customers repurchase from their preferredcompany, but simultaneously reduce purchasesfrom competitors (Fornell et al., 1996; Reichheld &Sasser, 1990). Also, consumers reshuffle theirexpenses between industries to attain a certain
utility at minimum costs (Sinha & Batra, 1999). It is
not clear that repurchases will lead to higher overallsales in the whole industry or economy. Due to thelack of theoretical evidence for such an effect, we
will hypothesize as follows:
H1: Aggregate CS does not affect economic
growth.
On the contrary, we rather assume that
economic growth affects the average customer
satisfaction. Marketing research found that theperceived value (PV; quality in relation to price) ofgoods and services is the main driver of CS (Fornell
et al., 1996). Economic growth is equivalent withgrowing aggregate income (Blanchard, 2006). With150

growing consumption budgets, consumers perceive
constant prices as more affordable, i.e. as lower
relative to the budget. This is mathematicallyequivalent with a rise in PV and leads to higher CS(Fornell et al., 1996).
Besides these marketing-related considerations,
economics and social science also support a
positive impact of income on utility and happiness(Argyle, 1999). This mechanism is mediated by theability of income to improve life throughconsumption and is thus based on largely the same
psychological patterns as the formation of customer
satisfaction.
H2: Economic growth enhances CS. This effectis mediated by aggregate income and PV.

yearly data in Germany, South Korea, and Sweden,
and for both yearly and quarterly data in the UnitedStates.
Table 1 Granger Test of Causality: Economic Growth
Drives CS

CS →

→ CS

GDP/Capita

Country

F

(p)

F

(p)

Germany

7.67(0.017)0.07(0.790)15.60(0.002)0.18(0.675)27.99(0.000)0.48(0.502)10.33(0.011)0.09(0.769)10.33(0.002)0.13(0.721)

South
Korea
Sweden3. Data and methodology
To verify our hypotheses, we need data on
economic growth, aggregate income, aggregate CS,
and aggregate PV. Inflation-adjusted economic data
were obtained from the European Union (2008).
We obtained CS data from the world’s fouroldest and most comprehensive consumer
barometers: the Swedish Customer Satisfaction
Barometer (SCSB: 1989-2007 except in 1998;
Svenskt Kvalitetsindex, 2008), the German
Customer
Monitor(GCM:
1992-2007;
Servicebarometer, 2008), the Korean Customer
Satisfaction Index (KCSI: 1992-2007; KMAC,
2008), and the American Customer Satisfaction
Index (ACSI: 1994-2007; NQRC, 2008). The
number of consumer opinions included in these
consumer barometers ranges between 20,000 and
40,000. In all four countries, customer satisfaction
is measured with a yearly periodicity. The ACSI ispublished in the form of quarterly scores, but thedata are updated only once per year, one quarter ofthe industries each quarter (Fornell et al., 1996).
Thus, we included the data as both yearly andquarterly scores.
To test the overall relationship between
economic growth and CS (hypotheses H1, H2), we
will conduct Granger tests (Granger, 1969). Since
only the GCM publishes PV data, we can test theinternal dynamics of H2 only for Germany. We will
use structural equation modeling (SEM; Garson,2006) to illustrate the detailed relationship between
economic expansion, disposable income, perceived
value, and customer satisfaction.

GDP/Capita

USA(yearly)USA(quarterly)

Table 1 shows that economic growth affects
aggregate CS (left side of Table 1), whereas
aggregate CS does not affect economic growth(right side). These results confirm hypotheses H1and H2. Obviously, the interpretation by US
researchers (Fornell, 2003; Fornell & Rust, 2005;
Fornell & Stephan, 2002; VanAmburg, 2004; 26
press releases from 2002 to 2007 in NQRC, 2008)
that aggregate CS would lead to economic growthis wrong. There is a positive relationship between
both variables, but it leads from economic growth
to CS.
After our hypotheses were confirmed, wewould like to verify our argumentation on themechanism within the impact of economic growthon CS. Hypothesis H2 states that economic growthwould drive CS via aggregate income and PV. We
modeled this relationship with a structural equation
model (SEM) depicted in Fig. 1. The model usedmaximum likelihood estimation (Garson, 2006). Fig.
1 shows the standardized path coefficients, thecorresponding
levelsofsignificance(inparentheses), and fit measures selected according to
Garson (2006): the relative chi-square (χ²/df: to be
below 5), the minimum sample discrepancy (levelof significance in parentheses: not to be significant),
the normed fit index (NFI: to be over 0.9), thegoodness of fit index (GFI: to be over 0.9), and theroot mean square error of approximation (RMSEA:
to be below 0.08).
Model 1 corresponds to our argumentation(hypothesis H2). In this model, economic growth(GDP/Capita) is assumed to affect CS via aggregate

4. Results
Table 1 contains the results of a Granger test
which tests the causal direction of the relationshipbetween economic growth and CS. Unlike
correlations, the Granger test also accounts fortime-lags and is based on an autoregression model(Granger, 1969). Table 1 includes the results for151disposable income (DI/Capita) and PV. While allpath coefficients of model 1 are highly significant,the model does not have an optimal fit. Althoughthe χ²/df, minimum sample discrepancy, and NFI
indicators are in the acceptable range, the GFI and
RMSEA criteria are not met (Garson, 2006).

For the additional direct effect (not mediated byPV) of income on CS, which we did not
hypothesize, we do not see any immediate
theoretical basis. We can imagine that this effect is,
in fact, mediated by firm/brand image, for which
sufficient longitudinal data do not yet exist.
Recently, firm image has been shown to be an
important deteminant of CS (Johnson et al., 2001).
Perhaps, consumers care more about firm image
relative to PV as their income grows and they canafford luxury goods.

N=15 (1993-2007, yearly all-industry averages)
Model 1:
0.994

0.673

GDP/ (0.000) DI/ (0.000)
CapitaCapitaPV

0.933(0.000)CS

Table 2 Moderators of the Relationship between
Disposable Income and CS

df: 3; χ²/df (p): 2.445 (0.062); GFI: 0.825;
NFI: 0.931; RMSEA: 0.321

Model 2:0.994
GDP/ (0.000)

CapitaSubgroup analysis: Industry-

0.673(0.000)PVlevel data (1993-2007)

DI/
CapitaCriterion for
0.794(0.000)industryCS

Model 3:GDP/
Capita0.994(0.000)DI/
Capita0.673(0.000)PV

0.729(0.000)

Direct Indirect

Consumer

Quality33

0.176-0.055orientation:

Equal

102

0.080

0.175

Price

222

0.064

0.177

Degree of

Low

180

0.156

0.026

technology

High

177

-0.0050.251

Speed of

Low

207

0.025

0.120

innovation

High

150

0.188

0.199

357

0.078

0.139

Quality vs.

CS

price

0.303
(0.003)
df: 2; χ²/df (p): 0.220 (0.803); GFI: 0.985;
NFI: 0.996; RMSEA: 0.000
Abbreviations:
GDP: Real gross domestic product; DI: Real gross national
disposable income; PV: Perceived value (quality in relation to theprice) of goods and services; CS: Customer satisfaction

Total

Fig. 1. Comparison of Hypothesized Structural
Model with Alternatives

DI/Capita → CS

Subgroup
category Nclassification
df: 3; χ²/df (p): 7.345 (0.000); GFI: 0.704;
NFI: 0.793; RMSEA: 0.673

SEM paths

To learn more about the differentation between
the direct (potentially mediated by firm image) andindirect effects (mediated by PV as stated in
hypothesis H2) of aggregate income on CS, we
compared the validity of model 3 across threeindustrial dimensions shown in Table 2. Since ouranalysis uses industry-specific PV and CS data andnational aggregate income, the path coefficients are
smaller than in Fig. 1 but highly significant.
Our hypothesized indirect effect of income via
PV on CS is strong in industries where consumers
focus on prices rather than quality, in high-techindustries, and in industries with fast innovation
cycles. The additional direct effect of income on CS(see model 3 in Fig. 1) is strong in industries where
consumers focus on quality rather than price, in
low-tech industries, and also in industries with fastinnovation cycles. It seems reasonable to assume
that this direct effect is indeed mediated by firm
image because image shields firms from price

Model 1 might have a low fit because
correlation analysis suggests that aggregate income
might impact CS independently of PV. We tested
this assumption by model 2. However, model 1 hasa much better fit than model 2, which lends support
to our idea of mediation. Consequently, model 3
tests the possibility that the impact of income on CS
is only partially mediated by PV. It turns out thatmodel 3 has an excellent fit and is superior to bothmodels 1 and 2.
In model 3 the indirect (mediated) effect ofincome via PV on CS (DI/Capita Æ PV: 0.673; andPV Æ CS: 0.729; which leads to DI/Capita Æ PV
Æ CS: 0.673 * 0.729 = 0.491) is larger than the
direct effect of income on CS (DI/Capita Æ CS:
0.303). Hence, the impact of economic growth on
CS is mainly, but not completely mediated by PV.

152

Nature, purpose, and findings. Journal ofMarketing, 60 (4) 7-18.

competition and plays a predominant role in lowtech markets without clearly visible differences intechnical features (Johnson et al., 2001).
5. Conclusions
US researchers published that aggregate CS
would impact economic growth, a result that would
revolutionize economic forecasting. This study
showed that their claims are wrong because therelationship is inverse to their assumptions. In fact,economic growth affects aggregate CS. An in-depth
analysis revealed that this effect is mediated byaggregate income and partially mediated by PV.
Future research might assess whether firm
image plays a role in the effect of economic growthon CS. Currently, not enough aggregate data are
available to test this assumption.
Quality managers should rethink their
methodology of conducting customer-based
performance evaluations. It seems that longitudinalcomparisons of CS capture variations in not only
firm performance but also economic trends.
Managers should not interpret economic-induced
CS changes as performance-induced CS changes.
Our results indicate that no general coevolution but only a unidirectional relationshipexists between economic growth (created by MOTbased R&D efforts) and CS. Since CS is not asignificant driver of economic growth, SIMOT does
not need to include CS as a separate regressor when
explaining the economic impact of MOT operations.
However, SIMOT researchers might consider
enlarging their set of target variables. Economic
growth is not a goal in itself but only a means ofachieving the ultimate goal of consumer utility. It
might thus be interesting to know whether MOT
operations also impact CS directly, not only via
economic growth.

[6]

Fornell, C., Rust, R.T., 2005. The Effect ofBuyer Satisfaction on Consumer Spending
Growth. Research paper, Sep 9. University ofMichigan.

[7]

Fornell, C., Stephan, J., 2002. Consumer
Spending Growth Predicted by Buyer
Satisfaction. Research report, The National
Quality Research Center, Ann Arbor.

[8]

Garson, D.G., 2006. Structural equation
modeling. http://www2.chass.ncsu.edu/garson/
pa765/structur.htm.

[9]Granger, C.W.J., 1969. Investigating causal
relations by econometric models and crossspectral methods. Econometrica, 37 (3) 424438.

[10] Ikeshoji, M., Enkawa, T., 2004. A study on
the relation between customer satisfaction
index and business conditions. Journal of theJapanese Society for Quality Control, 34 (4)90-99 (in Japanese).
[11] Johnson, M.D., Gustafsson, A., Wallin
Andreassen, T., Lervik, L., Cha, J., 2001. The
evolution and future of national customer
satisfaction index models. Journal of
Economic Psychology, 22 (2) 217-245.
[12] KMAC, 2007. Korean Customer Satisfaction
Index. Seoul. http://www.kmac.co.kr/.
[13] NQRC, 2008. The American customer
satisfaction index. Ann Arbor, MI.
http://www.theacsi.org/.
[14] Reichheld, F.F., Sasser Jr., W.E., 1990. Zerodefections: quality comes to services. Harvard
Business Review, 68 (5) 105-111.
[15] Servicebarometer, 2008.
Customer Monitor. Munich.

References[1]

Argyle, M., 1999. Causes and correlates ofhappiness, in: Kahnemann, D., Diener, E.,
Schwarz, N. (Eds.), Well-Being: The
Foundations of Hedonic Psychology. Russell
Sage Foundation, New York, pp. 353-373[2]

Blanchard, O., 2006. Macroeconomics, forthed. Pearson Prentice-Hall, Upple Saddle River.

[3]

European Union, 2008. Eurostat. Brussels.
http://epp.eurostat.ec.europa.eu/.

[4]Fornell, C., 2003. Boost stock performance,
nation’s economy. Quality Progress, 36 (2)25-31.

[5]

Fornell, C., Johnson, M.D., Anderson, E.W.,
Cha, J., Everitt Bryant, B., 1996. The
American Customer Satisfaction Index:

The

German[16] Sinha, I., Batra, R., 1999. The effect ofconsumer price consciousness on private labelpurchase. International Journal of Research inMarketing, 16 (3) 237-251.
[17] Svenskt Kvalitetsindex, 2008. Customer
satisfaction index. Stockholm. http://www.
kvalitetsindex.se/.
[18] VanAmburg, D., 2004. Customer satisfaction
in a changing economy: results from theAmerican Customer Satisfaction Index.
Annual Quality Congress Proceedings, 58,
233-236.

153

How to Better Interpret the Results of Longitudinal Customer Satisfaction Surveys
Björn Frank*, Takao Enkawa*

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-429 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANfrank.b.aa@m.titech.ac.jp
Past SIMOT research demonstrated that economic processes influence customer
satisfaction (CS). CS is positively influenced by economic growth and negatively by thenational stock index. These results are important to managers using CS surveys tobenchmark changes in their firm’s customer-oriented performance over time. Managers
may misinterpret economic-induced variations in CS as caused by changing customeroriented performance. Our study on the durable goods and hospital industries shows that
this danger is justified because economic processes explain 49 to 95%, thus the majority,of CS variations. To help firms interpret variations in CS, we propose two methods tocorrect CS scores by removing economic influences. We verify the corrected scores by
their impact on future business performance. In a number of institutional settings, we
confirm that our correction methods can help managers better understand their firm’s
customer-oriented performance and predict future business performance.
1. Introduction
Customer satisfaction (CS) is a leading
indicator of business performance. CS leads torepurchase behavior (Fornell, 1992) and positive
word-of-mouth referrals (Oh, 1999). Hence, CS
positively affects sales volume (Gómez et al., 2004),
profitability (Ittner and Larcker, 1998), and market
shares (Ikeshoji et al., 2003).
In a SIMOT-based effort to improve products,
services, and MOT processes, firms thus conduct
yearly customer surveys and compare CS over time
(Oriola, 2007; Shelton, 2000; White, 1999). Rising
CS is viewed as an improvement of customeroriented performance, falling CS as a deteriorationof performance (Oriola, 2007; Shelton, 2000; White,1999). Our research suggests that this interpretation
may not be valid.
In an analysis of Japan from 1977 to 2001,
Ikeshoji et al. (2003) discovered a negative impactof the stock index on CS. Using data from Germany,
Sweden, South Korea, and the United States, Frankand Enkawa (2008) discovered a positive impact of
economic growth on CS. In short, these studies
demonstrated that CS with goods and services is not
only influenced by the performance of the providerof these goods and services but also by external
economic developments.
The existence of such external influences on CS
may be a source of weaknesses in contemporary
MOT techniques. Variations in CS may be causedby external economic influences and have nothing
to do with customer-oriented performance.
Misinterpreting economic-induced variations in CS
as caused by corporate customer-oriented

154

performance can lead to wrong management
decisions and sub-optimal MOT strategies.
In order to improve managerial decision
making in MOT, our study deals with ways tocorrect time series of CS by removing external
economic influences. We will use time series of CS
data from the durable goods and hospital industries
in Japan.
2. Data
Our analyses require data on economic
processes and firm-level CS. As economic variables,
we used the real gross domestic product (GDP:European Union, 2008) and the Nikkei stock index(Nikkei: Yahoo, 2008). We thus followed themethodology of earlier SIMOT research (Ikeshoji etal., 2003; Frank and Enkawa, 2008).
Regarding firm-level CS, we obtained two
datasets from Japan. The first dataset contains aninverted proxy measure of CS measured on a Likert
scale: the amount of quality improvement necessary
to achieve perfect CS. We inverted the measure to ascale from 0 (very large quality improvement
necessary to achieve perfect satisfaction = very
dissatisfied) to 4 (perfectly satisfied). We will
simply refer to this measure as CS. The survey was
conducted from 1979 to 2007 in intervals of three
years. It covers three durable goods industries:
refrigerators, TV’s, and washing machines.
A second dataset was obtained from a Saitamabased hospital. The survey was conducted from1987 to 2006. It measures CS for out-patients, inpatients, and all patients. CS is measured on a
Likert scale (1: very satisfied; 5: very dissatisfied),which we inverted to increase readability (1: highly
dissatisfied; 5: highly satisfied).

durable goods study, we analyzed the cases of thefour leading firms in each market. The correlations
were negative and significant for 11 out of 12 firms.
In the second step, we regressed firm-level CS
on the current and lagged (up to two years) Nikkei
and GDP variables. To select an appropriate
regression model, we used backward regression.
Tables 1 and 2 show an extract of the results ofthese regression analyses. For all firms, backward
selection identified a model with significant
regressors. In all models, CS is positively
influenced by the GDP and negatively by the
Nikkei stock index. This result shows that thecountry-level findings of Ikeshoji et al. (2003) andFrank and Enkawa (2008) are also valid at the firmlevel. The Adj. R² in Tables 1 and 2 tell us that
economic influences represent 49% – 89% of thevariations in firm-level CS in the refrigerator
market, 70–95% in the TV market, 64–93% in thewashing machine market, and 77–84% in thehospital case. Therefore, the majority of thevariations in firm-level CS are caused by aggregate
economic processes and not by firms’ individual
customer-oriented performance.

Table 1 Contribution Ratio in Regression: Economic
Influences on Customer Satisfaction with
Durable Goods

RefrigeratorTV

Washing machine

Firm

Adj. R2

R_A

0.886

R_B

0.591

R_C

0.681

R_D

0.489

Industry

0.922

T_A

0.817

T_B

0.953

T_C

0.753

T_D

0.699

Industry

0.762

W_A

0.809

W_B

0.943

W_C

0.640

W_D

0.748

Industry

0.953

4. Correcting Customer Satisfaction Scores
When firms conduct CS surveys over several
years, they seek to know how their offers performed
from the customers’ point of view (Oriola, 2007;
Shelton, 2000; White, 1999). However, the resultsof the previous section made clear that the majorityof the variations in firm-level CS are caused byaggregate economic processes and not by firms’
individual customer-oriented performance. A rise in
CS thus rather reflects a change in economic
processes than in customer-oriented performance.
Hence, the risk of misinterpreting the results of CS
surveys is extremely high.
Therefore, we would like to propose two
methods to correct CS scores such that they reflect
corporate customer-oriented performance rather
than economic processes. From the original CS
scores, these methods subtract the portion of CS
that is explained by economic processes.
Correction method 1 removes the influences of
economic growth and the stock index, as calculated
in Tables 1 and 2:

Table 2 Contribution Ratio in Regression: Economic
Influences on Customer Satisfaction with
Hospital Services

Adj. R2
Out-patients

0.774

In-patients

0.837

All patients

0.786

3. Economic influences on customer satisfaction
Previous SIMOT research by Ikeshoji et al.
(2003) and Frank and Enkawa (2008) found that thenational stock index negatively affects CS, whereas
economic growth positively affects CS.
Our goal is to verify in how far these economic
influences apply to firm-level CS data. Therefore,
we first calculated the correlations between the
Nikkei stock index and CS: In the hospital case, thecorrelations were -0.719 (p < 0.001) for out-patientsand 0.767 (p < 0.001) for in-patients. For ourCSt(1) = CSt − Cˆ St(1) ;Cˆ St(1) = b0 + b1Stockt + b2 Stockt −1 + b3 Stockt −2+ b4GDPt + b5GDPt −1 + b6GDPt −2
b j ： Unstandardized regression coefficient
Correction method 2 has a much simpler andeasier-to-implement structure. It only removes theinfluence of the stock index.

155

CS t( 2 ) = CS t − Cˆ S t( 2 ) ;Cˆ S ( 2 ) = b′ + b′Stockt

01

For the three durable goods industries, we
obtained Japanese market share data (Yano, 19792007) as a measure of business performance. Hence,
Table 3 compares the impacts of the original andcorrected CS scores on future market share growth.
On the one hand, our results show that the original
CS scores do not significantly correlate with future
market share growth. On the other hand, corrected
CS scores show significant positive correlations
with future market share growth. Correction method
1, which removes the influences of economic
growth and the stock index on CS, turns out to yield
better results than method 2 which only removes
the influence of the stock index.

tb′j ： Unstandardized regression coefficient
5. Verification of Corrected CS Scores
In addition to the logical derivation of our
proposed CS correction methods, we would like toempirically verify whether using these correction
methods is advantageous for managers.
Table 3 Correlations between CS and Future Market
Share Growth: Durable Goods

Timelag(years)RefrigeratorTV

Washing
machine* p < 0.05;

Original
CS

Table 4 Correlations between Customer Satisfaction and
Future Business Performance: Hospital

Corrected Corrected
CS:

CS:

Time-

Method 1 Method 2

lag

Original
CS

Corrected Corrected
CS:

CS:

1

0.168

0.324*

0.292*(years)

2

0.125

0.202

0.178

0

0.895**

0.736**

0.912**

30.164

0.301*

0.293*

4

0.192

0.293*

0.275

Number1

0.818**

0.237

0.548*

5

0.024

0.037

0.035

of new2

0.793**-0.003

0.337

out-

1

-0.038-0.052-0.053

3

0.898**

0.170

0.526*

patients

2

0.152

0.274*

0.214

4

0.852**

0.146

0.254

3

0.248

0.444**

0.346*

50.809**-0.136

0.153

4

0.131

0.234

0.182

0

0.053

0.457

-0.145

5

0.094

0.175

0.136

1

0.142

-0.039-0.1091

0.157

0.416**

0.367*

Costs /

2

-0.064-0.079-0.07420.183

0.331*

0.312*

revenues

3-0.052-0.193

0.068

3

0.160

0.286*

0.265

4-0.310-0.316-0.142

4

0.040

0.079

0.073

5
-0.432** p < 0.01

-0.103-0.564*5
0.007** p < 0.01

-0.027-0.024* p < 0.05;

Marketing research found that CS has a positive
impact on future business performance, i.e. on sales(Gómez et al., 2004), market share growth (Ikeshoji
et al., 2003), and profitability (Ittner and Larcker,
1998). To verify our correction methods, we willthus compare the impacts of the original andcorrected CS scores on future business performance.
Since our correction methods remove external
influences on CS, the corrected CS scores should
betterreflect
corporate
customer-oriented
performance and thus show stronger correlations
with future business performance.

156

Method 1 Method 2

Next, Table 4 contains the results of the same
analysis for the hospital study. As performancemeasures, we used data on the yearly no. of new
out-patients and the hospital’s cost/revenue ratio.
The correlations between original CS scores and theno. of new out-patients are very strong. However,they express the economic influence on both CS
and the no. of new out-patients, rather than therelationship between the firm’s customer-oriented
performance and future business performance.
Corrected CS scores reflecting only customeroriented hospital performance still significantly
correlate with the no. of future patients and are thus
highly valuable to managers.

The lower half of Table 4 demonstrates that theoriginal CS scores are not correlated with thecost/revenue ratio, an inverse measure of
profitability. Corrected CS scores only show asignificant correlation for method 2.

References

6. Conclusions
Recent SIMOT research demonstrated that
economic processes strongly affect CS. CS is
positively influenced by economic growth (Frankand Enkawa, 2008), and negatively by the national
stock index (Ikeshoji et al., 2003). These effects
may complicate the work of MOT managers who
use CS surveys as a tool to benchmark theirperformance (Oriola, 2007). They usually interpretrising CS as improving customer-oriented
performance and falling CS as worsening customeroriented performance (Oriola, 2007; Shelton, 2000;
White, 1999). Since CS is not only influenced bycustomer-oriented performance at the firm-level but
also by economic processes at the country-level,
MOT managers may easily misinterpret economicinduced variations in CS as caused by their own
corporate actions. Our research on durable goods
and hospital services demonstrated that this danger
is imminent because economic processes explain 49
to 95% of the variations in firm-level CS.
Thus, it may be helpful for firms to remove
economic influences from CS scores to let thesescores reflect customer-oriented performance rather
than economic processes. We proposed two
methods to correct CS scores. Method 1 removes
the influences of both economic growth and thestock index. Method 2 only removes the influenceof the stock index. To verify whether these
correction methods help managers, we compared
the impacts of original and corrected CS scores on
future business performance for numerous firms in
the institutionally different durable goods andhospital industries.
Our analysis revealed that correcting CS scoresis beneficial to MOT managers because it separates
the impact of the firm’s customer-oriented
performance on CS from economic impacts. We
recommend method 1 if managers seek to interpret
how changes in CS impact future market shares. On
the other hand, we recommend method 2 if MOT
managers seek to interpret how variations in CS
impact business performance measures tightly
linked to average consumer income.
A limitation of our work is that we only
analyzed firms from the durable goods and hospitalindustries. SIMOT research in additional industries
would certainly be beneficial.

[1]

European Union, 2008. Eurostat. Brussels.
http://epp.eurostat.ec.europa.eu/.

[2]Fornell, C., 1992. A national customer
satisfaction
barometer:the
Swedishexperience. Journal of Marketing, 56 (1) 6-21.

[3]Frank, B., Enkawa, T., 2008. How economic
growth affects customer satisfaction. Asia
Pacific Management Review, 13 (2) 531-544.

[4]Gómez, M.I., McLaughlin, E.W., Wittink,
D.R., 2004. Customer satisfaction and retailsales performance: an empirical investigation.
Journal of Retailing, 80 (4) 265-278.

[5]

Ikeshoji, M., Enkawa, T., Suzuki, S., 2003.
Longitudinal change pattern of customer
satisfaction and its correlation with market
share based on quality improvement
expectation data. Journal of the JapaneseSociety for Quality Control, 33 (3) 93-103.

[6]

Ittner, C.D., Larcker, D.F., 1998. Are
nonfinancial measures leading indicators offinancial performance? An analysis ofcustomer satisfaction. Journal of Accounting
Research, 36 (3) 1-35.

[7]

Oh, H., 1999. Service quality, customer
satisfaction, and customer value: a holistic
perspective.
International
Journalof
Hospitality Management, 18 (1) 67-82.

[8]

Oriola, S., 2007. Gauging customer
satisfaction.
http://www.entrepreneur.com/
marketing/onlinemarketing/article183316.html.

[9]Shelton, P.J., 2000. Measuring and Improving
Patient Satisfaction. Jones & Bartlett
Publishers, London.

[10] White, B., 1999. Measuring patientsatisfaction: how to do it and why to bother.
Family Practice Management, 6 (1) 40-44.
[11] Yahoo,
2008.
Yahoo
http://finance.yahoo.com/.

Finance.

[12] Yano Economic Research Institute, 1979-2007.
Japanese Market Share Dictionary. Tokyo.

157

Cultural Influences on the SIMOT Strategy Optimizing Customer Loyalty
Björn Frank*, Takao Enkawa**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
W9-57, 2-12-1 O-okayama, Meguro-ku, Tokyo, 152-8552 JAPANfrank.b.aa@m.titech.ac.jp
Customer loyalty is one of the most important drivers of profitability and should thus
be a key target variable for managerial SIMOT activities. In these times of globalization,
SIMOT should be essential in enabling firms to adapt their MOT processes acrossdifferent cultures. Based on a consumer survey in Japan, this study analyzed theinfluences of Hofstede’s cultural dimensions and gender on customer loyalty and its
formation process. The study found that the most important drivers of customer loyalty
are customer satisfaction, expectations regarding the quality of currently offered products
and services, the perceived value (quality related to price) of goods and services, brandimage, switching costs, individualism, and uncertainty avoidance. Women care far morethan men about brand image and less about customer satisfaction, perceived value, quality
expectations, and switching costs. Collectivist consumers care more than individualistic
consumers about brand image and less about perceived value.
1. Introduction
The Science of Institutional Management ofTechnology (SIMOT) deals with the crossfunctional organization of technology so that theresulting products and services yield maximum
profits. One of the most important profit drivers iscustomer loyalty which is mostly defined byresearchers as the intention to repurchase goods andservices from the incumbent supplier rather thanswitch to a competitor (Reichheld and Sasser, 1990).
Customer loyalty is positively associated withactual repurchase behavior, positive word-of-mouthreferrals, sales, profits, and stock value (Anderson
et al., 2004; Fornell, 1992; Reichheld and Sasser,1990). It also reduces marketing costs and thebusiness risk (Anderson and Sullivan, 1993;
Reichheld and Sasser, 1990). To maximize thenumber of loyal customers, it is essential to know
the factors driving customer loyalty.
Over the past few decades, firms became facedwith the challenges posed by the processes ofglobalization and growing economic participationof previously disadvantaged groups such as women.
These processes introduced great cultural diversity
into the customer base and thus potentially into thesuccess factors driving customer loyalty and profits.
Hence, there is a need for SIMOT to understand theinfluence of culture on the drivers of customer
loyalty.
Therefore, this study explores the factors
driving customer loyalty and gives special attention
to the main and moderating effects of gender andthe cultural dimensions of individualism anduncertainty avoidance. We conducted a consumer
survey in Japan. The survey included questions on

158

thirteen different industries: five products (cars,
game consoles, mobile phones, personal computers,
shampoo) and eight services (airlines, banks,
convenience stores, gas stations, hairdressers,
hospitals, mobile carriers, supermarkets). The data
was collected between March and June 2008.
2. Research Hypotheses
According to the marketing literature, the main
drivers of repurchase are customer satisfaction [CS],the perceived value (quality related to price) ofgoods and services [PV], expectations regarding thequality of currently offered goods and services[QExp], brand/firm image [Image], and switchingcosts [SC] (Burnham et al., 2003; Fornell, 1992;
Johnson et al., 2001).
There are only few studies examining theinfluences of culture on customer loyalty. Yet, in
our times of globalization, SIMOT-related
knowledge about these influences has become more
important than ever. There are many scales tomodel culture. A prominent scale was introduced by
Hofstede (1980). He characterized cultures using
four dimensions: individualism, uncertainty
avoidance, power distance, and masculinity. Our
study focuses on the influences of individualism
and uncertainty avoidance.
Uncertainty avoidance means that individuals
have a tendency to favor behavior which avoids risk
(Hofstede, 1980). Switching providers is an action
associated with uncertainty (Burnham et al., 2003).
Consumers switching from the incumbent toanother provider usually do not have complete
information on the goods and services offered by
the other provider. Switching providers thus causes

increased uncertainty compared with repurchasingfrom the incumbent provider. Hence, consumers
with a strong desire to avoid the uncertainty
associated with switching providers should prefer tostay with the incumbent supplier. In other words,
uncertainty avoidance should positively affectcustomer loyalty (Jin et al., 2008).
H1:
Uncertainty avoidance [UAI] has apositive impact on customer loyalty.
Men and women do not always behave alike,which may have its origin in biological properties
and gender roles present in the social environment.
On the average, more women than men consider
themselves as interdependent, whereas more men
than women consider themselves as independent(Cross and Madson, 1997).
To a large degree, firm/brand image represents
the opinion of the social environement (Roth, 1995).
As the characteristic of interdependence entails botha desire to please the social group and greater
openness to opinions in the group (Cross andMadson, 1997; Meyers-Levy, 1988), women should
value image more than men in repurchase decisions.
Accordingly, they should value their individual
opinion and experiences and thus customer
satisfaction (Johnson et al., 2001) less than men(Cross and Madson, 1997; Meyers-Levy, 1988). As
the ability to please the social environment
constitutes an additional value of a good or service,
women should be willing to pay a price premiumfor this additional value.
H2:
Firm/Brand image is a more importantdriver of customer loyalty for women than for men.
H3:
Customer satisfaction is a lessimportant driver of customer loyalty for womenthan for men.
H4:
The perceived value of goods andservices is a less important driver of customer
loyalty for women than for men.
Collectivism is the opposite of individualism(Hofstede, 1980). Consumers who value
collectivism or group culture should attach
relatively more importance to opinions within theirgroup (image) and accordingly less importance totheir personal opinions and experiences (customer
satisfaction). This general behavior should bereflected accordingly in consumption decisions. For
collectivist consumers, consumption may also serve
as a means to satisfy social expectations and obtainsocial recognition by their group (Roth, 1995).
While customer satisfaction is associated withpersonal opinions and experiences (Johnson et al.,2001), image is also associated with opinions
prevalent within the social environment (Roth,
1995). Hence, firm/brand image should be astronger and customer satisfaction a weaker
determinant of customer loyalty for collectivist
compared with individualistic consumers (Roth,

159

1995). Collectivist consumers should also be
willing to pay price premiums to satisfy social
expectations and obtain goods and services with astrong brand image (Erdem et al., 2006). In otherwords, the perceived value of goods and services(quality-price ratio) should be a less important
determinant of customer loyalty for collectivist
compared with individualistic consumers.
H5:
Individualism [IDV] has a negative
moderating effect on the relationship between
firm/brand image and customer loyalty.
H6:
Individualism
hasapositive
moderating effect on the relationship between
customer satisfaction and customer loyalty.
H7:
Individualism
hasapositive
moderating effect on the relationship between theperceived value of goods and services and customer
loyalty.
3. Data
To test our research hypotheses, we conducteda consumer survey in Japan between March andJune 2008. The questionnaire consists of questions
regarding three areas: socio-demography, cultural
traits, and supplier-related attitudes specific to fiveproduct industries (cars, game consoles, mobile
phones, personal computers, shampoo) and eightprivate-sector service industries (airlines, banks,
convenience stores, gas stations, hairdressers,
hospitals, mobile carriers, supermarkets). These
supplier-related attitudes include customer loyalty
and the primary determinants of customer loyalty.
In terms of culture, the questionnaire contains 3
question items on individualism [IDV 1…3] and 5
questions on uncertainty avoidance [UAI 1 …5].
333 consumers participated in the survey. The
sample is evenly distributed among men andwomen. It covers the student and working
population in Japan, but it does not adequately
account for senior citizens and overstates therelevance of students. 42.6% of the respondents arefrom the Tokyo metropolitan region. The sample
numbers amount to approximately 300 for mostindustry-specific question items.
4. Results
Our survey contained data on three question
items regarding individualism [IDV 1…3] and fiveitems regarding uncertainty avoidance [UAI 1…5].
Before testing our hypotheses, we intended to
calculate higher-level cultural scores and verify
whether the lower-level items properly load on thehigher-level constructs. Therefore, we conducted aprincipal component analysis with Varimax rotation(Kaiser, 1958). Unfortunately, the lower-levelindicators did not load on the principal components
as anticipated. Hence, we suppressed those items

showing irregularities and re-ran the analysis. The
result is shown in Table 1.

firm image, switching costs, individualism, anduncertainty avoidance. These results confirm
hypothesis 1.

Table 1 Principal Component Analysis: Cultural
TraitsVariables
Individualism

Uncertainty
avoidance

1
2
3
1
2
3
4
5

Interpretation
IDV: Individualism;
Varimax-rotatedb

Loadingsb
UAI
IDVa
suppressed-0.1080.704-0.0370.750
suppressed
0.658-0.1040.661-0.137
0.737
0.213
0.398
-0.191
1.585
1.170

Category
Variablet(p)
Demography Femalea-4.287(0.000)Age
0.629(0.529)b
CultureIDV
2.391(0.017)UAI
2.060(0.039)SupplierCS
9.014(0.000)relatedPV
2.440(0.015)
attitudesc
QExp
4.917
(0.000)Image
3.387(0.001)SC
5.448(0.000)Moderator:
Female * CS
-9.385(0.000)GenderFemale * PV
-2.786(0.005)(FemaleFemale * QExp
-6.388(0.000)vs. male)
Female * Image
116.9(0.000)Female * SC
-5.187(0.000)Moderator:
IDV * CS
1.716
(0.086)
Individualism IDV * PV
-1.102(0.271)(IDV)
IDV * QExp
0.612
(0.540)IDV * Image-1.952(0.050)IDV * SC
-1.713(0.087)
Moderator:
UAI * CS
-0.833(0.405)
Uncertainty UAI * PV
1.308
(0.191)
avoidance
UAI * QExp
-0.686(0.493)(UAI)
UAI * Image-1.153(0.249)
UAI * SC
1.305
(0.192)
Adj. R²
0.725
Sample number
3240aFemale: Female 1, male 0 (dummy variable)b
IDV: Individualism; UAI: Uncertainty avoidancec
CS: Customer satisfaction; PV: Perceived value
QExp: Quality expectations; SC: Switching costsaEigenvalue% ofvariance
Cumulated %aTable 2 Moderated Regression Analysis:
Determinants of Customer Loyalty

26.41019.49726.41045.908
Uncertainty
Individualism
avoidance
UAI: Uncertainty avoidance

The analysis extracted two prinipal components
with eigenvalues larger than one. They stand for
45.9% of the variance in the dataset. The firstprincipal component has high loadings for
uncertainty avoidance and very low loadings forindividualism. We thus interpreted this component
as representing uncertainty avoidance and named it
UAI. The second principal component has highloadings for individualism and low loadings
uncertainty avoidance. Hence, we interpreted it as
standing for individualism and named it IDV. These
component scores will be used as regressors in thefollowing regression analyses.
To test our research hypotheses, we conducteda moderated regression analysis using the pooled
dataset from all surveyed industries. The dependent
variable of the analysis was customer loyalty. To
cope with heteroskedasticity caused by pooling thedata, we calculated White-corrected t and p values(White, 1980). Table 2 contains the results of thisanalysis. Besides testing the main effects ofdemographics, culture, supplier-related attitudes,
our analysis also tested the moderating effects ofgender and culture on these main effects. The
moderating effects were tested using interaction
terms.
The analysis identifies the following significant
drivers of customer loyalty: customer satisfaction,
image, the perceived value of goods and services(quality compared to the price), expectations
towards currently offered products and services,

There were strong motivational differences
between men and women. Our analysis indicatesthat women care far more than men about firm
image in repurchasing decisions. In return, theycare less about the other factors driving customer
loyalty: customer satisfaction, the perceived valueof goods and services, expectations regarding thequality of currently offered goods and services, andswitching costs. This analysis not only confirms our
hypotheses 2 to 4 about the moderating effects ofgender on the influences of image, customer
satisfaction, and perceived value on customer
loyalty. It also shows that switching costs are lesseffective in keeping female than male customers.

160

Moreover, expectations regarding the quality ofcurrently offered products and services (e.g., newproduct features) are less important for women thanmen in forming repurchase intentions.
Our analysis also supports hypothesis 5
suggesting that individualistic consumers care lessabout firm image than collectivist consumers informing loyalty attitudes. Hypothesis 6 assumes a
positive moderating effect on the relationshipbetween customer satisfaction and repurchaseintentions. This hypothesis could only be partiallyconfirmed. It is rejected according to the two-sided
p-value of 0.086, but accepted according to the onesided p-value of 0.043. Our analysis did not support
hypothesis 7 which concerns a positive moderating
effect of individualism on the relationship between
perceived value and customer loyalty.

References

6. Conclusion
Customer loyalty is one of the most importantdrivers of business performance (Reichheld and
Sasser, 1990). In this SIMOT research project, weanalyzed the success drivers involved in producing
loyal customers across cultures. With thisknowledge, firms should be able to optimize theircross-functional MOT activities to achieve highcustomer loyalty.
Our research found that customer loyalty is
positively influenced by customer satisfaction,
perceived value, quality expectations, firm image,switchingcosts,
individualism,
uncertainty
avoidance, and male vs. female gender. Women
care fare more than men about firm/brand image
and less about the other factors. They are also lessinfluenced by switching costs. Compared withindividualistic consumers, collectivist consumers
care more about firm/brand image and less about
perceived value (i.e. quality compared with price).
The results underscored the importance offocusing MOT activities on developing products
and services satisfying customers. While customer
satisfaction is a long-term success factor, theimportance of quality expectations and thus ofinnovative processes leading to new functionalities
is also substantial. These success factors vary acrossinstitutional parameters. Firms should use different
MOT processes for men and women as well as forindividualistic and collectivist consumers. Products
targeted at individualistic consumers and men
should be developed focusing on new
functionalities and price. Offerings targeted atcollectivist consumers and women may be more
simple but should be offered with intensive
marketing campaigns inducing a strong brandimage.

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161

NPD of Japanese Manufacturing Firms: Institutional Views of R&D Intensity
and Technology Trajectories
Tanyanuparb Anantana**Department of Industrial Engineering and Management
Tokyo Institute of Technology
anantana.t.aa@m.titech.ac.jp
1. Introduction

their typical features of in-house technology development as well as theirinternal learning and experience. Meanwhile, firms in science-based group,
which technologies are mostly generated from internal R&D, shouldespecially emphasize on developing their human resources andorganizations.
Average factor score plot of three factors

Firms have to heavily rely on New Product Development (NPD), tosurvive in the intensive competition and dynamic business environment.
According to the empirical research on 396 Japanese manufacturing firms
by using New Product Development Scorecard (NPDSC), three NPD
influential factors of “Development strategy and organization”,“Utilization capability of tools and IT” and, “Development production
technology”, are explored. In accordance with this, firms with different
institutional level of R&D intensity may have different ways of
implementations of these factors to contribute firm’s financial performance.
In addition to the factor level, analysis through the NPDSC can provide theguidance of critical NPD operations contributing to NPD performance.
Among several NPD performances, NPD efficiency is mainly constitutedby the technology of firms. Therefore, firms might require different critical
NPD operations to improve development efficiency in each institutional
trajectory of technology.

NPD Influential factors
Factor 1

A v e ra g e fa c to r s c o re3.60

“Development strategy
and organization”
Factor 2“Utilization capability oftools and IT”
Factor 3“Development
production technology”

Fig. 1. Framework of NPD through the institutional
R&D intensity and Technology Trajectories views

3.50
3.40

High R&D intensity group
Low R&D intensity group

3.30
3.20
3.10
3.00
Development strategy and Utilization capability of tools Development production
organization
and IT
technology

Multiple Regression Analysis (High R&D intensity)
UnstandardizedStandardized
Coefficients
Coefficients t-value
B
Std. Error
Beta(Constant)
1.446
2.208
0.655
Strategy x Technology
0.461
0.191
0.250
2.412
2
2
R=0.250, R =0.063, Adj.R =0.052, Std.Error of the estimation=6.607
High R&D intensity group, N=89
Revenue Growth(Average of 5 years)

p -value
0.514
0.018

Multiple Regression Analysis (Low R&D intensity)
UnstandardizedStandardized
Coefficients
Coefficients t-value
B
Std. Error
Beta(Constant)
0.266
1.466
0.181
Strategy x Tools and IT x Technology 0.152
0.040
0.381
3.753
2
2
R=0.381, R =0.145, Adj.R =0.135, Std.Error of the estimation=5.884
Low R&D intensity group, N=85
Revenue Growth(Average of 5 years)

p -value
0.857
0.000

Fig. 2. NPD Influential Factors and Institutional level of R&D
Intensity

2. Relationships between NPD Influential Factors andInstitutional Level of R&D Intensity
In general, firms need to implement tools and IT incorporated with
development strategy and organization factor or development production
technology factor in order to constitute firms’ financial performance (herein,
revenue growth average 5 years). When considering the effect of
institutional level of R&D intensity, the ways of implementations of thesethree factors are different. Firms with high R&D intensity need to integrate
the implementation of development strategy and organization factor anddevelopment production technology factor to constitute firm’s financial
performance. In this case, using tools and IT might be considered as thefacilitating factor which could not directly contribute to financial
performance but still necessary to support those factors integration. On theother hands, for low R&D intensity group, firms require the combination of
all three factors in order to bring about competitive advantage and later
directly enhance financial performance.

3. Critical NPD Operations for Each Institutional
Technology Trajectory
Regarding Pavitt’s industries classifications of four groups oftechnology trajectories, firms in each institutional trajectory might focus on
different critical operations in order to improve NPD efficiency. Sincetechnologies for supplier-dominated group are provided by suppliers, firms
in this group should specifically emphasize on the exchange of technicalstandardized data with their suppliers as well as the design rationale system.
Meanwhile, because technology for specialized suppliers group are
generated from customer requirements, thus firms in this group should put
the importance on grasping needs of customers and markets and try to makethe relationship with them to. On the other hand, for scale-intensive group,
firms should focus on product data management that will be able to respondSupplier-DominatedScale-Intensive

Critical operation: Use of open standard data

Critical operation: Product Data Management

Development Efficiency
Bt-valuep -value(Supplier-Dominated, N=81)(Constant)
0.160
0.892
0.375
1-(1) Strategy and resource
0.172
2.555
0.013
1-(2) Patent and partnership-0.328-3.9040.000
2-(3) Project management
0.302
3.649
0.000
2-(4) DR
-0.289-3.4450.001
2-(7) Design rationale
0.262
2.774
0.007
3-(5) Design for Envi.
0.352
4.655
0.000
4-(1) QFD
0.466
5.843
0.000
4-(2) DFM
-0.393-3.9460.000
4-(6) Use of open standard
0.156
2.454
0.017
R=0.861, R2=0.742, Adj.R2=0.701, Std.Error of Estimate=0.407

Development Efficiency
Bt-valuep -value(Scale-Intensive, N=85)(Constant)-0.587-2.6420.010
1-(1) Strategy and resource
0.322
4.205
0.000
4-(1) QFD
0.193
2.214
0.030
4-(2) DFM
0.278
2.611
0.011
4-(5) PDM
0.250
2.741
0.008
R=0.816, R2=0.666, Adj.R2=0.648, Std.Error of Estimate=0.584

Science-BasedSpecialized Suppliers

Critical operation: HRD and organization development

Critical operation: Needs of customer and market

Development Efficiency
t-valuep -value
B(Science-Based, N=162)(Constant)-0.504-2.3090.022
1-(1) Strategy and resource
0.129
2.464
0.015
1-(4) Needs of cus. and mkt.
0.179
2.443
0.016
1-(6) HRD and developt. org.
0.190
2.019
0.045
2-(3) Project management
0.194
2.667
0.008
2-(4) DR
-0.150-1.9230.056
3-(6) NP ramp-up smooth.
0.174
2.349
0.020
4-(2) DFM
0.290
3.596
0.000
R=0.748, R2=0.559, Adj.R2=0.539, Std.Error of Estimate=0.550

Development Efficiency
Bt-valuep -value(Specialized Suppliers, N=297)(Constant)-0.426-2.7380.007
1-(4) Needs of cus. and mkt.
0.165
3.119
0.002
2-(1) Quality of planning
0.179
2.885
0.004
2-(3) Project management
0.153
2.985
0.003
3-(6) NP ramp-up smooth.
0.144
2.750
0.006
4-(2) DFM
0.154
2.448
0.015
4-(4) CAD
0.106
2.400
0.017
R=0.693, R2=0.480, Adj.R2=0.469, Std.Error of Estimate=0.559

Fig. 3. Critical NPD Operation for Development Efficiency inEach Institutional Trajectory

4. Conclusion
The institutional level of R&D intensity and institutional technology
trajectories respectively affect the ways of implementations for the NPD
influential factors as well as the critical operations. These might bebeneficial as the guidance for firms to let them know how and what to bedone in order to enhance firms’ financial performance and development
efficiency in accordance with these institutional perspectives.

162

New Product Development Operational Performance and Its Influential Factors of
Manufacturing Firms in Japan
Tanyanuparb Anantana **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-57 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANanantana.t.aa@m.titech.ac.jp
This paper attempts to reveal the influential factors for an efficient New Product Development(NPD) operational performance. New Product Development Scorecard (NPDSC) has been utilized as
the self-diagnosis tool for the number of 386 participated firms in Japan. According to NPDSC results,
the factor analysis was conducted to identify influential factors for successful NPD. The analysis
results explore that there are several influential factors which could lead to an efficient and successful
NPD depending on performance perspectives. Additionally, the levels of NPD operational
performance are different according to the typical features of industry classifications.
1. Introduction
Since Japan is the one of the world’s largest
market with high competitiveness, New ProductDevelopment (NPD) has therefore become thecenterpiece of today’s competitive strategies. In
order to improve the NPD performance, theperformance measurement might be realized as away to support the performance improvement byreflecting the existing status. The concept ofscorecard is one of the effective performancemeasurement tools regarding to innovation and
NPD measurements, for example; Innovation
scorecard (Chiesa et al, 1996), Product scorecard
and product innovation scorecard (Sahu, 2004).
Regarding to these scorecards, New ProductDevelopment Scorecard (NPDSC) was established
not only to evaluate the new product itself, but also
to promote the improvement and mechanism
creation to proceed with more successful NPD
effectively and speedily (Irikura and Enkawa, 2005).
Therefore, in this research, this NPDSC was
utilized to explore the influential factors for an
efficient NPD operational performance. The
diversity of NPD operational performance levels bydifferent industries was also examined
2. New Product Development(NPDSC) and hypothesis

Scorecard

2.1 NPDSC and Data Collection Process
NPDSC was initiated by Japan Organization for
Quality Innovation (JOQI) which was three years
government – industry – university activities andestablished in 2001. NPDSC was intended for selfdiagnosis of NPD management to understand thestrength - weakness and also provides “how andwhat to be done” and “up to what level” in terms of

163

NPD improvement. It encompasses 25 assessment
items based on four core assessment areas; (1)Organization Systems of Development, (2)Planning and Execution Ability, (3) New ProductDevelopment Performance, and (4) Exploitation ofmanagement tools and information technology.
Each assessment item is allocated into five-levelwith given detail descriptions. The 5th level
represents for the best practice for each item. (asshown in APPENDIX 1). The score of one integer
and a half (for instance 2.5) is also acceptable incase company or division’s level is considered inexisting between two levels. Additionally, Irikura
and Enkawa (2005) confirmed the effectiveness ofusing NPDSC as performance measured andbenchmarking tool to real managerial performance
Regarding to the data collecting process,
NPDSC has been used to collect data fromparticipated firms in Japan manufacturing sector
since 2003 by using the interviewing method within-charge person of NPD and/or high-leveled
manager of each company (Irikura and Enkawa,
2005). Slight revisions has been accomplished to
NPDSC itself and version 3 was currently utilized
so as well to this research. From the end of May
2007 until the end of June 2007, by the cooperationof Japan Standard Association (JSA) and Tokyo
Institute of Technology, the data collecting was
conducted again by mailing system for 6,000
members of JSA.
Finally, total of 441 samples (from 386
companies including multiple assessors) wereobtained. In these samples, they also covered wide
range of firm sizes. Since selecting multiple
industry categories was allowable, the total numberof samples became 639 when classified according
to industry categories and others. The details ofnumber of samples for each industry categories
were shown in Table 2.

representative performance measurement indiceswere considered from the three different
perspectives. These are: (1) enhancing positive
quality perspective, (2) efficiency perspective and(3) preventing negative quality perspective.
Corresponding to these perspectives, assessment
items of 3-(1) Quality of New Product (NP), 3-(3)Development efficiency, and 2-(5) Quality
Assurance (QA) and reliability could represent foreach performance perspective, consecutively.

2.2 Research Hypotheses
Regarding to the study of Meybodi (2005),
several of NPD performance measures could beselected to represent NPD performances. The
efficient and successful NPD might be represented
by various NPD performance perspectives. With
respect to some studies on NPD issues, (Delvin,1999), (Abdul Ali, 2000), (Fujimoto and Yasumoto,2000), (Kumar and Phrommathed, 2005), and (Sunand Wing, 2005), it has been revealed that there areseveral factors which could lead to an efficient NPD
performance and successfulness. Additionally, thedifferent in firm sizes, industries, and countries
were also explored that effect on the NPD
performance and its success. From these studies, thehypotheses in this research are derived:
Hypothesis1: There are several influential
factors which could constitute to the efficient andsuccessful NPD, depending on the NPD
performance perspectives.
Hypothesis2: The levels of NPD operational
performance are different by industry classifications
according to their typical features.

Table 1 Rotated Factor Matrix of all industries
Assessment Item
1-(1) Strategy and resource
1-(2) Patent and partnership
1-(3) Matching technology and market
1-(4) Needs of customer and market
1-(5) Alliance with suppliers
1-(6) HRD and development organization
2-(1) Quality of planning
2-(2) Production technology ability
2-(3) Project management
2-(4) Design Review (DR)
2-(5) QA and reliability
2-(6) Concurrent Engineering
2-(7) Design rationale
3-(1) Quality of NP
3-(2) Development lead time
3-(3) Development efficiency
3-(4) Target costing
3-(5) Designs for Environment
3-(6) NP ramp-up smoothness
4-(1) QFD
4-(2) DFM
4-(3) FMEA
4-(4) CAD
4-(5) PDM
4-(6) Use of open standard

3. Factor Analysis
First, factor analysis was conducted by utilizing
the data obtained from NPDSC in order to identify
the influential factors which constitute to an
efficient NPD operational performance. Conducting
factor analysis for all industries (441 samples),Principle Axis Factoring (PAF) with the constraintof eigen-value more than one was performed. In
this study, Varimax rotation was selected in order toremain the independent relations among theextracted factors. As a result, the three factors wereextracted with the cumulative contribution of
54.32%. In the factor matrix showed in Table 1,
items with higher factor loading more than 0.4 foreach factor are highlighted and at the same time, thehighest loading compared to other factors for each
item is highlighted in dark. Accordingly, all of theassessment items which mainly refer to strategy andorganization were strongly related to factor 1. So it
was entitled as “Development strategy andorganization”. Meanwhile, factor 2 had strong
relation to items mainly which refer to production
technology capability and efficiency. Therefore, thegiven name for factor 2 was “Development
production technology”. Considering factor 3,
related items concerned to execution ability of tools
and IT. Hence, the factor 3 was named as“Utilization capability of tools and IT”.
In order to derive the approaches of influential
factors for the efficient and successful NPD,

1
0.695
0.624
0.702
0.689
0.572
0.490
0.617
0.386
0.538
0.404
0.420
0.484
0.292
0.508
0.326
0.415
0.421
0.351
0.289
0.207
0.285
0.257
0.244
0.215
0.259

Factor
2
0.264
0.182
0.263
0.289
0.318
0.407
0.402
0.477
0.380
0.388
0.421
0.456
0.461
0.423
0.583
0.447
0.453
0.414
0.696
0.542
0.531
0.410
0.221
0.209
0.143

3
0.308
0.387
0.275
0.203
0.321
0.291
0.232
0.127
0.419
0.473
0.426
0.405
0.458
0.172
0.130
0.396
0.396
0.362
0.286
0.398
0.451
0.502
0.678
0.702
0.678

From Table 1, considering the cause-effectmodel within each factor, the highest loading of
item 3-(1) showed in factor 1 compared to the otherfactors and it also showed relatively higher factor
loading in factor 2. These relationships implied thatfactor 1 could lead to an efficient and successful
NPD in term of enhancing the quality of NP.
Meanwhile, factor 2 could also constitute to thisperformance, although its influence is rather weaker
than that of factor 1. In the same way of
considerations, factor 2 could be the main approachfor the development efficiency. Besides, factor 1
also constituted to this performance. For thepreventing negative quality perspective whichreferred to QA and reliability, since this item
showed the highest factor loading in factor 3 buthigh loading were still observed in factor 1 and 2.
In this point, factor 3 mainly leads to QA andreliability. Accordingly, factor 1 and 2 also support
to this performance perspective. From these results,
it might be identified that these influential factors as
managerial approaches could lead to the efficientand successful NPD in terms of these three
performance perspectives. Therefore, hypothesis 1

164might be supported.

score 3) and assembly (high level of factor score 3)
group industry. Consequently, the investigation of
influential factors’ diversities by these industry
group classifications would be performed.
Next step, the classifications of industry
categories based on three typical features ofindustry (technology intensive, complexity of
product, and production system characteristics)
would be classified. With respect to the definitionsof these typical features (OECD, 2001), (Novak andEppinger, 2001), and (Kukowski and Boulton,
1995), the results of industry classifications in thisstudy were shown in Table 2. It should be noted
that, most firms of cloth & apparel industry in thisdatabase were the suppliers for automobile industry
which might be regarded in the same classifications.

4. Diversity of NPD Operational Performance
Levels by Different Industries
In this section, differences level of NPD
operational performance in terms of influential
factor scores caused by industry categories would
be investigated. First, the scatter plots of theaverage factor scores of each industry type and subgroup were drawn as shown in Figure 1 and 2.
1.0
10-1 A & M

0.8

Factor 2: Devlopment production technology

0.6

0.4
13-2 Ma. P (Ot hers)-0.6

7-2 Ma. (BB)

5-3 Chem (BB)13-1 Ma. P (Auto)

3 C& A

0.2
12-1 Elec. P (Auto)
11-1 P Ma. (BC) 8-1 E Ma. (BC)2-1 Food
7-1 Ma. (BC)10-2 S & O
12-2 Elec. P (Others)
5-2 Chem (BC)0.0
8-2 E Ma. (BB)
6 Iron
-0.2
0.1
0.3
0.5

-0.4
1 Con.

9 IC

4-1 W & F

0.7

0.9

Table 2 The details of industry group classifications
by three different features-0.2
11-2 P Ma. (BB)

4-2 P & P

-0.4
4-3 Print.

-0.6

-0.8

Industry Category

5-1 P harIndustry Group Classification Number ofsamples

1 Construction
2-1 Processed Food

-1.0

2-2 Beverage & Liquor

Factor 1: Development strategy and organization

3 Cloth & Apparel
4-1 Wood & FurnitureFig. 1. Average factor score plot between factor 1& 2

4-2 Paper & Pulp
4-3 Printing
5-1 Pharmaceutical
5-2 Chemistry for General Use
5-3 Chemistry for Business Use and material
6 Iron-Steel & Nonferrous metal
7-1 Machinery & Appliances for General Use
7-2 Machinery & Appliances for Business Use

1.0

8-1 Electrical Machinery & Appliances for General Use
8-2 Electrical Machinery & Appliances for Business Use

0.8

Factor 3: U tilization capability of tools and IT

9 Information Communication
10-1 Automobile & Motorcycle

0.6
8-1 E Ma. (BC)7-2 Ma. (BB)11-1 P Ma. (BC)11-2 P Ma. (BB) 0.4
9 IC
13-2 Ma. P (Others)
0.2
7-1 Ma. (BC)10-2 Ship & Other transportation
11-1 Precision Machinery & Appliances for General Use

12-1 Elec. P (Auto)

8-2 E Ma. (BB)11-2 Precision Machinery & Appliances for Business Use

10-1 A & M

13-1 Ma. P (Auto)

12-1 Electronic Part & Devices for Auto Industry

12-2 Elec. P (Others)

12-2 Electronic Part & Devices for Others

10-2 S & O
-0.7

-0.5

-0.3

1 Con.
4-2 P & P
4-1 W & F

0.0
-0.1
6 Iron
-0.2

0.1

0.3

4-3 Print.

-0.4

0.7

13-2 Machinery Part for Others

0.9

Technology intensiveHighMedium-Low

Complexity of product
High

Low

Con.

*

*

Food

*

*

B&L

*

*

C&A

*
*

*

P&P

*

*

Print.

****

Chem (BC)*Chem (BB)

*

Iron

*

Ma. (BC)*

Ma. (BB)*

E Ma. (BC)

*
*
*
*
*

*

E Ma. (BB)

*

*

*

IC

*

A&M

*

*

S&O

*

*

P Ma. (BC)**P Ma. (BB)

*

*

W&F

Phar

Production systemcharacteristic
Process
Assembly***

Elec. P (Auto)**Elec. P (Others)**

Ma. P (Auto)**

Ma. P (Others)**

Remarks: Software industry (14 samples) and Others (27 samples) were excluded for these industry group classifications

5-1 Phar

5-3 Chem (BB)
5-2 Chem (BC)13-1 Machinery Part for Auto Industry
3 C0.5
&A

58
4
0
7
12
7
4
8
19
76
47
26
55
36
68
15
15
10
10
39
21
26
23
12

Abbreviation

2-1 Food

Then, three-way ANOVA were conducted inorder to verify the significant different of factor
score among these industry group classifications bysetting each factor as dependent variable andindustry classifications together with theirinteractions as fixed factors. The summary ofsignificant results which were found was shown in
Table 3.

-0.6

-0.8

-1.0

Factor 1: Development strategy and organization

Fig. 2. Average factor score plot between factor 1& 3

It could be observed the typical diversity offactor score in the dimensions of factor 1 and factor
2 in some industries. Accordingly, the diversity of
the factor 3 might be classified into two groups ofhigh and low level in this factor score.
Considering typical features for the industries
regarding to Fig. 1 and 2, the diversity of factor
score 1 and 2 might be considered by the typicalfeature of technology intensive (ex; hightechnology group industry for high level of factor
score 1), and complexity of product (ex; highcomplexity of product group industry for high levelof factor score 2), respectively. Meanwhile, thediversity of factor 3 might be explained by thetypical features of their production systemcharacteristics such as process (low level of factor

Table 3 Summary of significant results from threeway ANOVA<Dependent Variable: Factor score1>
SourceTechnology intensive
Technology intensive x Production system
Error
Total

Sum of Square
7.902
3.737
414.037435.124

df
1
1
590
598

Mean Square
7.902
3.737
0.702

F
11.2605.325

p -value
0.001
0.021

<Dependent Variable: Factor score2>
SourceComplexity of product
Technology intensive x Complexity of product
Technology intensive x Complexity of product x Production system
Error
Total

S.S
8.460
5.421
2.837
387.878408.115

df
1
1
1
590
598

Mean Square
8.460
5.421
2.837
0.657

F
12.8698.246
4.315

p -value
0.000
0.004
0.038

<Dependent Variable: Factor score3>
SourceProduction system characteristic
Error
Total

SS
11.504369.400
430.224

df
1
590
598

Mean Square
11.5040.626

F18.374

p -value
0.000

From Table 3, the diversity of NPD operational165performance levels in terms of factor score 1 could
be explained by technology intensive classification
and also the interactions of technology intensive
and production system characteristics classifications.
It might be implied that the high technology firms
who already possessed high level of development
strategy and organization should maintain that highlevel in order to prevent losing theircompetitiveness especially in the quality of NP
performance. Meanwhile, the significant differentof factor score 2 could be found in the complexityof product classification and the interactions
between technology intensive and complexity of
product and also three of interactions. It might be
implied that the firms who engaged with highcomplexity of product should maintain high level ofdevelopment production technology which would
particularly constitute to their development
efficiency performances. Accordingly, the factor
scores 3 are markedly different only by theclassification of production system characteristics.
In this sense, it might be implied that process group
and assembly group industry have different attitudein emphasizing on utilization capability of tools andIT owing to their different features. Besides,
assembly group industry seems to be moreconcerned to this factor in supporting the NPD
improvement rather than process group industry.
Consequently, hypothesis 2 might be supported.
5. Conclusions
The findings and implications are concluded asfollowings; first, the influential factors for an
efficient NPD operational performance were
explored. They are: (1) Development strategy andorganization,(2)
Development
production
technology, and (3) Utilization capability of tools
and IT. Second, it was confirmed that these
influential factors could constitute to NPD
successfulness depending on the NPD performance
perspectives. These perspectives are (1) enhancing
positive quality perspective which refers to qualityof NP, (2) efficiency perspective which refers todevelopment efficiency performance and (3)preventing negative quality perspective whichrefers to QA and reliability performance. Third, thediversity of the NPD operational performances interms of influential factor level could be explainedby the typical features of industrial classifications
which are technology intensive, complexity of
product, and production system characteristics.
Accordingly, this result might also imply that thedifferent institutional system among industries
could affect to the NPD operational performance.
However, these classifications should be moreverified and required supporting by, for instance,

166

some surveys for further studies. Consequently, theexplorations in this study would be beneficial forthe firms’ manager in different industries who
would like to improve the NPD performance byknowing what kind of implementation should be
performed.
References[1] Abdul Ali. (2000). The Impact ofInnovativeness and Development Time on
New Product Performance for Small Firms.
Marketing Letters. Vol.11 (2), pp. 151-163[2] Chiesa, V and Coughlan, P and Voss, A Chris.
(1996). Development of a technical innovation
audit. Journal of Product Innovation
Management. Vol.13 (2), pp. 105-136[3] Devlin K. (1999). Info Sense – Turning
information into knowledge. WH Freeman
and Company, New York[4] Fujimoto, T. and Yasumoto, M. (2000). Seikosuru seihin kaihatsu (Successful New ProductDevelopment),
Yuhikaku,
Tokyo(inJapanese)[5] Irikura, N and Enkawa, T. (2005). Proposal on
New Product Development Scorecard and its
Application. Journal of the Japanese Society
for Quality Control. Vol.35 (4), pp. 73-84 (inJapanese)[6] Kukowski, A John and Boulton, R William.
(1995). Electronics manufacturing andAssembly in Japan. Panel report, Japan
Technology Evaluation Center. pp. 97-114[7] Kumar, S and Phrommathed, P. (2005). New
Product Development: An Empirical Study of
the Effects of Innovation Strategy,
Organization
Learning,andMarketConditions. Springer Science and BusinessMedia, Inc.
[8] Meybodi, M.Z. (2005). The impact of just-intime practices on new product development: amanagerial perspective. International Journalof Product Development, Vol.2 (3)[9] Novak, S and Eppinger, D Steven. (2001).
Sourcing By Design: Product Complexity andthe Supply Chain. Management Science. Vol.
47 (1), pp. 189-204[10] OECD. (2001). STI Scoreboard 2001, Paris.
[11] Sahu, P. (2004). Strategy-focused productinnovation with product scorecard and productinnovation
scorecard.
International
Engineering Management Proceedings, pp. 813[12] Sun, H and Wing, C Wong. (2005). Critical
Success
FactorsforNew
Product
Development in Hong Kong Toy Industry.
Technovation. Vol. 25 (3), pp. 293-303

Moderating Effect of Technology Trajectories on New Product Development
Efficiency and Firm’s Financial Performance
Tanyanuparb Anantana **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-57 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANanantana.t.aa@m.titech.ac.jp
This research intends to investigate the moderating effect of different sources oftechnology on New Product Development (NPD) operations for development efficiency
and firm’s financial performance. As the results, it is confirmed that technology
trajectories affect the relationships between the NPD operations and development
efficiency, level of development efficiency performance, and the relationships between
NPD efficiency and financial performance. Additionally, it is also found that NPD
efficiency positively relates to firm’s financial performance.
company could be compared against competitors inthe same industry as well as across the industries.
Owing to the data collecting process, NPDSC
has been used to collect data by interviewing
method from participated firms in Japan
manufacturing sector since 2003 (Irikura and
Enkawa, 2005), then by maling method in 2007
(Anantana et al., 2007). Finally, total of 625
samples (from 396 companies including multiple
assessors and industries categories selections) wereobtained and shown in Table 1.

1. Introduction
Development technology is considered as oneof the key factors to contribute success in New
Product Development (NPD) efficiency (Kumar
and Phrommathed, 2005; Anantana et al., 2007).
This pushes firms in various industries try todevelop their technology for achieving. However,required technology and source of technology ineach industry is different. In this sense, it isimportant for firms to know that, based on theirtechnologies, which operations should be regradedas critical to constitute NPD efficiency, thenaffecting financial performance. Hence, thisresearch aims to investigate the moderating effectof different sources of technolgy on the NPD
operations for development efficiency and firm’s
financial performance. The results from such kindsof these analyses would be expected to provide
useful managerial implications for firms in different
groups of technology trajectories.

2.2 Industries Classification by Sources ofTechnologies (Technology Trajectories)
According to the industries classifications bytechnology trajectories from Tidd et al. (2005), fourgroups of industries were classified. The differenceof each group concern to the source of technology
and development. These groups are; (1) SupplierDominated, (2) Scale-Intensive, (3) Science-Based,and (4) Specialized Suppliers, as shown in Table 1.

2. Research Background and Hypothesis
2.1 New Product Development Scorecard(NPDSC) and Data Collecting Process
NPDSC was initiated by Japan Organization for
Quality Innovation (JOQI) in 2001. NPDSC is
designed for being self-NPD performanceassessment tool covering all Japan manufacturingindustry. It encompasses 25 assessment items basedon four core assessment areas; (1) Organizational
Systems of Development, (2) Planning andExecution Ability, (3) New Product Development
Performance, and (4) Exploitation of management
tools and information technology. Each of the 25
assessment items is rated according to five definedlevels (with detailed description), with the 5th levelsupposing to be the best practice. Additionally, theresult of assessment from NPDSC for individual

Table

1

Industries
Trajectories

Classification by Technology

Industry
1 Construction
2-1 Processed Food
2-2 Beverage & Liquor
3 Cloth & Apparel
4-1 Wood & Furniture
4-2 Paper & Plup
4-3 Printing
5-1 Pharmaceutical
5-2 Chemistry for General Use
5-3 Chemistry for Business Use and material
6 Iron-Steel & Nonferrous metal
7-1 Machinery & Appliances for General Use
7-2 Machinery & Appliances for Business Use
8-1 Electrical Machinery & Appliances for General Use
8-2 Electrical Machinery & Appliances for Business Use
9 Information Communication
10-1 Automobile & Motorcycle
10-2 Ship & Other transportation
11-1 Precision Machinery & Appliances for General Use
11-2 Precision Machinery & Appliances for Business Use
12-1 Electronic Part & Devices for Auto Industry
12-2 Electronic Part & Devices for Others
13-1 Machinery Part for Auto Industry
13-2 Machinery Part for Others
14 Software
Total

167

Number of SupplierScalesamples dominated intensive
58
4
0
7
12
7
4
8
19
79
47
26
57
36
68
15
16
11
10
40
22
26
27
12
14
625

81

85

SciencebasedSpecialized
suppliers

162

297

the critical NPD operations which could constituteto the development efficiency.

2.3 Research Hypothesis
Development efficiency of new product isimportantly contribute to NPD success (Lewis,2001). It is indicated that NPD efficiency is mainly
constituted by the development technology (Kumar
and Phrommathed, 2005; Anantana et al., 2007).
However, firms in different industries havedifferent aspects of technologies, such as, historicalpattern of technology development, and strategic
technology implications (Tidd et al., 2005). In
accordance with this, firms who have different
sources of technology may require different criticaloperations to improve development efficiency. Thismight consequently influence on the result offinancial performance, as well. According to thetechnology trajectories classification from Tidd
(Tidd et al., 2005), the set of first hypothesis isestablished.
Hypothesis 1: The technology trajectories could
moderate (a) the relationships between the NPD
operations and development efficiency, (b) level ofdevelopment efficiency performance, and (c) the
relationships between development efficiency andfinancial performance
In addition, improving NPD efficiency
performance might contribute to better financial
performance. Therefore, the second hypothesis isderived.
Hypothesis 2: Development efficiency positively
relates to financial performance

Table 2 NPD operations for development efficiency for
all samples
Development Efficiency(All samples, N=625)

Bt-valuep -value(Constant)-0.405-3.7810.000
1-(1) Strategy and resource
0.113
3.551
0.000
1-(4) Needs of cus. and mkt.
0.106
2.786
0.006
2-(1) Quality of planning
0.120
2.744
0.006
2-(3) Project management
0.167
4.448
0.000
2-(4) DR
-0.085-2.1240.034
2-(5) QA and reliability-0.084-2.1660.031
2-(7) Design rationale
0.100
2.479
0.013
3-(5) Design for Envi.
0.078
2.432
0.015
3-(6) NP ramp-up smooth.
0.122
2.969
0.003
4-(1) QFD
0.078
2.382
0.018
4-(2) DFM
0.139
3.130
0.002
4-(4) CAD
0.087
2.877
0.004
2
2
R=0.738, R =0.544, Adj.R =0.535, Std.Error of Estimate=0.557

3.2 Moderating Effect of Technology
Trajectories on the NPD Operations forDevelopment Efficiency
The separate regression analyses for each groupaccording to the classification of technology
trajectories were conducted. Same methodology as
all samples is used. The results of regression
analyses will be compared with the reference modelin Table 2, as mentioned earlier. The separate
regression analyses results are respectively
displayed in Table 3.
As the results, focusing on the positive effect,
for Supplier-dominated group, the typical NPD
operations which is different from the reference
model is use of open standard. This finding
corresponds to the characteristics of industries inthis group (such as food, cloth & apparel industry)
which sources of technology mainly rely on
suppliers. Therefore, use of open standard between
firms and their suppliers might be able to improve
development efficiency.
For Scale-intensive group, the typical NPD
operation which is different from the reference
model is Product Data Management (PDM). It
might be explained by the characteristics of theincrementally technology development of industry(such as automobile industry) in this group.
Therefore, PDM which could react to enableeffective use of data responding to the technologicalchange might be able to contribute to development
efficiency.
For Science-based group, the typical NPD
operations which are different from the reference
model are HRD and development organization andTarget costing. Both NPD operations support thecharacteristics of indsutries in this group (such as
pharmaceutical, chemical, and electronic industry)
which technologies mainly come from the internal
R&D and knowledge, skills and techniques of

3. Results of Analyses
3.1 NPD Operations for Development
Efficiency
According to NPDSC, each assessment item
could be considered as either NPD operation or
performance. In order to find the NPD operations
for development efficiency, regression analysis was
conducted by setting item 3-(3) development
efficiency as the dependent variable and taking up
rests of 24 assessment items as the independent
variables. Then, backward variable selection
method was used. The remained items in the model
represents for NPD operations which directly
impact to development efficiency. The model ofthese NPD operations would be used as thereference model for investigate the moderating
effect of technology trajectories. The result ofregression analysis is shown in Table 2. Since thisresearch focuses on the contribution of NPD
operations to development efficiency, only the
positive effect result would particularly be
explained.
From Table 2, considering the distinctive
significance by p-value, the NPD operations ofstrategy and resource and project management are

168

type of businesss to business) which the main
source of technology are generated by the specificrequirements from customer.
According to the findings in Table 3, it could beobserved that the critical NPD operations fordevelopment efficiency in each group are different.
In this sense, these differences might come from thedifferent source of technology in each group. It
might also conclude that the technology trajectories
could moderate the relationships between the NPD
operations and development efficiency. Therefore,
hypothesis 1(a) might be supported.

firm’s staffs. Therefore, improving these operations
could contribute to better development efficiency
performance for this group.
Table 3 NPD operations for development efficiency foreach group
Development Efficiency(Supplier-Dominated, N=81)

B

t-valuep -value(Constant)
0.093
0.520
0.605
1-(1) Strategy and resource
0.191
2.863
0.006
1-(2) Patent and partnership-0.317-3.9310.000
2-(3) Project management
0.363
4.160
0.000
2-(4) DR
-0.249-3.0040.004
2-(6) Concurrent Eng.
-0.173-1.9580.054
2-(7) Design rationale
0.281
2.650
0.010
3-(5) Design for Envi.
0.338
4.573
0.000
4-(1) QFD
0.472
5.913
0.000
4-(2) DFM
-0.381-3.9770.000
4-(6) Use of open standard
0.193
2.983
0.004
R=0.876, R2=0.767, Adj.R2=0.733,Std.Error of Estimate=0.390
Development Efficiency(Scale-Intensive, N=85)

B

t-value

3.3
Moderating
effectofTechnology
Trajectories on the Level of Development
Efficiency Performance
In this section, one-way ANOVA was
performed in order to find the significant differenceof development efficiency among each group. The
results of differences are shown in Table 4 and Fig.
1, respectively.

p -value(Constant)-0.587-2.6420.010
1-(1) Strategy and resource
0.322
4.205
0.000
4-(1) QFD
0.193
2.214
0.030
4-(2) DFM
0.278
2.611
0.011
4-(5) PDM
0.250
2.741
0.008
R=0.816, R2=0.666, Adj.R2=0.648, Std.Error of Estimate=0.584
Development Efficiency
Bt-valuep -value(Science-Based, N=162)(Constant)-0.630-2.6800.008
1-(1) Strategy and resource
0.161
3.042
0.003
1-(2) Patent and partnership-0.145-2.0330.044
1-(4) Needs of cus. and mkt.
0.232
3.169
0.002
1-(6) HRD and developt. org.

0.202

2.181

Table 4 ANOVA result of different development
efficiency performance between four groups
DV: Development Efficiency, Factor: Technology Trajectories classificationB

t-value

SD

SI

SB

SS

F

Development Efficiency

1.716

1.918

2.105

1.987

4.300**

Differences between group: SB>SD, SS>SD
Level of significant **=0.01
SD: Supplier-dominated, SI: Scale-incentive, SB: Science-based, SS: Specialized-supplier

De velopment Efficie ncy performance

0.031

2-(3) Project management
0.141
1.937
0.055
2-(4) DR
-0.163-2.0890.038
3-(4) Target costing
0.163
2.149
0.033
3-(6) NP ramp-up smooth.
0.161
2.203
0.029
4-(2) DFM
0.213
2.594
0.010
4-(4) CAD
0.168
2.520
0.013
4-(5) PDM
0.137
1.960
0.052
4-(6) Use of open standard-0.241-3.5000.001
R=0.785, R2=0.617, Adj.R2=0.585, Std.Error of Estimate=0.522

Development Efficiency(Specialized Suppliers, N=297)

Variable

2.2
2.1

score

2
1.9
1.8
1.7
1.6
1.5

p -value

Supplier-dominatedScale- intensive

Science-basedSpecialized suppliers

Technology traje ctorie s(Constant)-0.396-2.5290.012
1-(4) Needs of cus. and mkt.
0.210
3.861
0.000
2-(1) Quality of planning
0.180
2.898
0.004
2-(3) Project management
0.162
3.118
0.002
2-(5) QA and reliability-0.152-2.7430.006
3-(5) Design for Envi.
0.090
2.015
0.045
3-(6) NP ramp-up smooth.
0.140
2.638
0.009
4-(2) DFM
0.165
2.521
0.012
4-(4) CAD
0.112
2.520
0.012
2
2
R=0.707, R =0.500, Adj.R =0.485, Std.Error of Estimate=0.552

Fig.1. Level of development efficiency performance foreach group

From Table 4 and Fig. 1, level of development
efficiency in each group could be observed thatdifferent. Group of Science-based possesses thehighestlevel
ofdevelopment
efficiency
performance. Besides, the development efficiency
level for the group of Science-based andSpecialized supplier are significantly higher thanSupplier-dominated group. This might imply thatfirms that internally develop technology on theirown could bring about higher level of development
efficiency, compared to relying on external source.
From this point, hypothesis 1(b) might be supported.

For Specialized suppliers group, although there
is no typical different NPD operation in this group,
the obvious critical operation could be observed in
the model. The operation of needs of customer andmarket is strongly positive impact to development
efficiency. This result also corresponds to thefeature of this group (such as software, and industry

169

3.4 The Relationship between Development
Efficiency and Financial Performance and theModerating Effect of Technology Trajectories
In this section, the regression analyses by using
dummy variable were carried out. Three groups ofSupplier-dominated,Science-based, and Specialized
suppliers were coded as the dummy variables of SD,
SB, and SS, consecutively. Group of Scaleintensive was omitted as reference case since it
showed the median results in terms of development
efficiency performance level and number ofsamples. In the regression model, the financial
index of ROA (from Japanese Nikkei NEED in thesame year of NPDSC data) was set as a dependent
variable. Meanwhile, the development efficiency
performance, dummy variables of three groups, andinteraction between dummy variables anddevelopment efficiency were taken up as theindependent variables. The results of regression
analyses are shown in the Table 5.
Table 5 Regression analysis result by using dummy
variable
ROA as Dependent Variable, Standard regression coefficients displayed
3
Model
1
2
Developtment efficiency (Dev.Eff.)
Supplier-Dominated (SD)
Science-Based (SB)Specialized Suppliers (SS)Dev.Eff x SD
Dev.Eff x SB
Dev.Eff x SS

0.162*

0.162*-0.0650.179*
0.273*
0.242*

0.068-0.516+-0.097

relationships between the NPD operations anddevelopment efficiency, level of development
efficiency performance, and the relationships
between NPD efficiency and financial performance.
Additionally, it is found that new productdevelopment efficiency positively impacts tofinancial performance (herein, represented by ROA).
Additionally, this research reveals some learning in
the view point of institutional system for industries
or firms level. Firms in the industries that havedifferent institutional of technology sources should
focus on different critical operations in order toimprove development efficiency. In accordancewith this, they might have to set their competitive
strategies for NPD by considering such theconstrains of their technology fundamentals. Finally,
the managerial implications might be generated
from the results of different crucial NPD operations
for contributing development efficiency in eachgroup of technology trajectory. These might beused as the guideline for firm in different groups tounderstand which NPD operations should be
improved in order to constitute development
efficiency, resulting in better firm’s financial
performance.
References[1] Anantana, T., Enkawa, T., Suzuki, S. 2007.
New Product Development Operational
Performance and Its Influential Factors of
Manufacturing Firms in Japan , Proceeding of
the 12th Annual International Conference on
Industrial Engineering-theory, Applications
and Practice.
[2] Irikura, N. and Enkawa, T. 2005. Proposal on
new product development scorecard and its
application, Journal of the Japanese Society
for Quality Control 35 (4), pp. 73-84, (inJapanese)[3] Kumar, S. and Phrommathed, P. 2005. New
Product Development: An Empirical Study of
the Effects of Innovation Strategy,
Organization
Learning,andMarketConditions, Springer Science and BusinessMedia, Inc, NY.
[4] Lewis, A. M. 2001. Success, failure andorganizational competence: a case study of the
new product development process, Journal ofEngineering Technology Management 18,
pp.185-206.
[5] Tidd, J., Bessant, J., Pavitt, K. 2005.
Integrating
technological,
marketandorganizational change, Managing Innovation,
3rd edition, pp. 169-174.

0.075
0.849*
0.358

R2
0.026
0.068
0.112
R2
0.042
0.044
Adj.R2
0.021
0.048
0.077
F
0.028*
0.046*
0.038*
Level of significant +=0.1, *=0.05
SD,SB,SS are dummy variables for Technology Trajectories category(omit Scale-Intensive (SI) as the reference)

From Table 5, model 1 is baseline model which
could explore the main effect of development
efficiency on the financial performance. The resultshows that development efficiency positively
impacts on ROA which might consider to support
hypothesis 2. Then, the dummy variables of eachgroup and their interactions with development
efficiency were entered into the model 2 and 3,
respectively. The results of model 2 and 3 showedthat the R2 increased significantly and theinteraction terms of development efficiency and
Science-based group were significant. In this sense,technology trajectories could moderate relationshipbetween development efficiency and financial
performance that might support hypothesis 1(c).
4. Conclusions
The explorations in this study confirm themoderating effect of technology trajectories on the170

Utilizing Computerized Tools and IT in New Product Development to Constitute
Firm’s Financial Performance and the Institutional View of R&D Intensity
Tanyanuparb Anantana **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-57 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANanantana.t.aa@m.titech.ac.jp
This study focuses on how to utilize computerized tools and Information Technology(IT) in New Product Development (NPD) that can contribute to firm’s financial
performance. Impact of R&D intensity on relationship between tools and IT utilizationand financial performance is also examined. As a result, in order to make a positive effecton financial performance, tools and IT should have to be incorporated with the enabling
factors of “Development strategy and organization” and “Development production
technology”. In addition, it is found that level of utilization capability of tools and IT issignificantly higher in high R&D intensity group comparing to the low one which affects
on the implementation methods of tools and IT for NPD as well as the contribution on
financial performance, as well.
years government–industry–university activities
and established in 2001. NPDSC encompasses 25
assessment items based on four core assessment
areas: (1) Organizational Systems of Development,(2) Planning and Execution Ability, (3) New
Product Development Performance, and (4)Exploitation of management tools and information
technology. Each of the 25 assessment items is
rated according to five defined levels (with detailed
description), with the 5th level supposing to be thebest practice.
Scope of samples in this research covered awide range of industries in Japanese manufacturingsector. According to the data collecting process,
NPDSC has been used to collect data byinterviewing method from participated firms inJapan manufacturing sector since 2003 (Irikura and
Enkawa, 2005), then by maling method in 2007
(Anantana et al., 2007). Finally, total of 649
samples (from 396 companies including multiple
assessors and industries categories selections) wereobtained. In accordance with these samples, as theexternal publicy source of financial data (Japanese
Nikkei NEEDS) was used in this research, 193
financial data was available, as shown in Table 1.

1. Introduction
Owing to the benefit of computerized tools andIT for NPD, companies have heavily invested andimplemented in such kinds of these techniques(Clark and Fujimoto, 1991; Gonzalez, 2002).
Nevertheless, it is not always for every firm that
could earn full advantage and investment pay-off
from the implementation of these techniques.
Several pitfalls have been pointed out, for example,
high investment, inappropriately implementationand management (Dodgson, 2001; Thomke, 2006;).
Therefore, it is necessary for firms to find out thatwhat they should do, in order to earn the businessvalue from investing and using tools and IT in theirdevelopment processes.
When firms make the R&D investment, it
usually affects on the investment of tools and IT for
NPD. In this sense, level of R&D investment might
influence the capability of tools and IT
implementation that might result in the different
ways of utilization. In this research, theinvestigation would be performed through theR&D
intensity (R&D expense per sales) that could better
represent not only the R&D investment but also theeffort in the real business (Cohen and Klepper,
1992).

2.2 Industries Classification by R&D Intensity
The term of R&D intensity used in this researchis represented by R&D expense per sales (%). The
industry classification by different level of R&D
intensity was performed. Regarding NPDSC
database, first, each firm was checked for theavailable of R&D expense per sales data fromJapanese Nikkei NEEDS of the same year of firm’s
NPDSC data. Then, for those available data,

2. Research Background and Hypothesis
2.1 New Product Development Scorecard(NPDSC) and Data Collecting Process
In this research, New Product Development
Scorecard (NPDSC) was used as a data collecting
tool for samples of manufacturing firms in Japan.
This NPDSC was initiated by Japan Organizationfor Quality Innovation (JOQI) which was three171average of R&D expense per sales for each industry
was figured out. The average for all industries was
also calculated. Then, comparing industry average
to overall average, two groups of high and low
R&D intensity were classified, as shown in Table 2.

such the factors as strategy, organization, andmanagement practice (Brynjolfsson and Hitt, 2000;
Thomke, 2006; Chen, 2007), technology (Ozer,
2000; Dodgson, 2001) .In accordance with thesefactors, this research defines them as the “enabling
factors” which should complementarily be appliedwith tools and IT implementation. Therefore, thefirst hypothesis is established:
Hypothesis1: Utilizing computerized tools and IT
in NPD should be incorporated with the enabling
factors in order to bring about positive impact onfirm’s financial performance.

Table 1 Samples in each industry
Industry category

Number of samples

Construction
Processed Food
Beverage & Liquor
Cloth & Apparel
Wood & Furniture
Paper & Plup
Printing
Pharmaceutical
Chemistry for General Use
Chemistry for Business Use and material
Iron-Steel & Nonferrous metal
Machinery & Appliances for General Use
Machinery & Appliances for Business Use
Electrical Machinery & Appliances for General Use
Electrical Machinery & Appliances for Business Use
Information Communication
Automobile & Motorcycle
Ship & Other transportation
Precision Machinery & Appliances for General Use
Precision Machinery & Appliances for Business Use
Electronic Part & Devices for Auto Industry
Electronic Part & Devices for Others
Machinery Part for Auto Industry
Machinery Part for Others
Software
Others
Total

58
4
0
7
12
7
4
8
19
79
47
26
57
36
68
15
16
11
10
40
22
26
27
12
14
24
649

Financial Data from
Nikkei NEEDS
14
1
0
3
2
1
0
5
5
22
14
6
16
6
23
6
10
5
4
11
7
6
9
4
4
9
193

In the globalization era, computerized tools andIT are importance for R&D process. With respect tothe study of Lee and Hwang (2003), augment of
R&D intensity could upgrade tools and IT potentialthat will constitute firm’s competitiveness.
Additionally, it is stated that high level of R&D
intensity is significantly associated with high levelof using computerization in development process(Ettlie, 1998). Addressing this relationship, thesecond hypothesis is proposed:
Hypothesis2: Firms in high R&D intensity grouppossess higher capability of computerized tools andIT utilization for NPD, comparing to low R&D
intensity ones.

Table 2 Industry classification by R&D intensity
Industry

Average of R&D expense per
sales

Number of Samples(available data)

2.81

181

5.95
2.90
3.15
3.07
4.08
3.10
4.86
3.53
4.66
3.46
3.88
3.87

5
6
6
23
6
10
4
11
7
8
4
90

All industries avarage of R&D expense per sales

Generally, level of R&D intensity could
represent for the business competitive environment(Takayama et al., 2002). Owing to such kind of thiscompetitive environment, NPD need to be fastenough to capture changing customer demands andtechnology advances (Chen et al., 2005; Langerak
and Hultink, 2005). Due to benefit of computerized
tools and IT for speeding up NPD as discussed
earlier, firms in high R&D intensity group have tointensively focus on using these techniques in their
NPD process. Through this point of view, only
using tools and IT might not enough to bring thecompetitive advantage that directly contribute tofirm’s financial performance. On the other hand, for
low R&D intensity group, the firms who can
implement tools and IT to speed up NPD might beable to enhance their competitiveness that makes
them differentiated from their competitors. In thissense, firms could earn benefit from implementing
tools and IT that directly bring about growth on
financial performance. According to these
considerations, hypothesis 3a and 3b is proposed:
Hypothesis3a: For high R&D intensity group, as afundamental requirement for NPD, using tools andIT is not enough to bring the competitive advantagethat directly contribute to firm’s financial
performance.
Hypothesis3b: For low R&D intensity group, using
tools and IT in NPD can bring the competitive
advantage that directly contributes to firm’s
financial performance.

Above avarage of R&D expense per sales group (High R&D intensity group)
Pharmaceutical
Machinery & Appliances for General Use
Electrical Machinery & Appliances for General Use
Electrical Machinery & Appliances for Business Use
Information Communication
Automobile & Motorcycle
Precision Machinery & Appliances for General Use
Precision Machinery & Appliances for Business Use
Electronic Part & Devices for Auto Industry
Machinery Part for Auto Industry
Software
Average / Total
Below avarage of R&D expense per sales group (Low R&D intensity group)
Construction
Processed Food
Cloth & Apparel
Wood & Furniture
Paper & Plup
Chemistry for General Use
Chemistry for Business Use and material
Iron-Steel & Nonferrous metal
Machinery & Appliances for Business Use
Ship & Other transportation
Electronic Part & Devices for Others
Machinery Part for Others

0.80
14
2.47
1
2.18
3
0.49
2
0.36
1
2.79
5
2.68
21
1.02
13
2.52
16
1.59
5
2.54
6
2.61
4
Average / Total
1.84
91
Remark: Beverage&Liquor and Printing industries are excluded in this classification owing to limitation of available data

2.3 Research Hypothesis
Although several studies confirmed thebusiness value of implementing tools and IT on
firm performance, the findings are still inconsistentand controversial (Loveman, 1994; Sweeny, 1996;
Li and Ye, 1998). Thus, recent scholars try to focus
on the method of utilizing computerized tools and
IT by linking with strategic management frameworkor organizational factors. It is argued that
implementing tools and IT alone might not
sufficient to generate the impact on firm’s financial
performance (Grover et al., 1998; Lee, 2001).
Supporting to this point, several researches stated
that, in order to achieve in business value, tools andIT should be implemented at the same time with172

to investigate the significant impact of each factor
on financial index As focusing on the integrating
implementation of tools and IT with the enabling
factors, the three extracted factors and products of
their interactions were treated as independent
variables for analyzing. And the financial index ofrevenue growth (average 5 years) was treated as
dependent variable. Result of regression analysis isshown in Table 4.

3. Analyses and Results
3.1 Factor Analysis
First of all, a factor analysis for all samples was
conducted to extract the influential factors for NPD
as preparatory analysis. Principle Axis Factoring(PAF) with the constraint of eigen-value more than
one was performed. Varimax rotation was selected
in order to remain the independent relations among
the extracted factors.

Table 4 Regression analysis for all samples

Table 3 Rotated Factor Matrix for all 453 samples (afterVarimax rotation)
NPDSC Items
1-(1) Clarification of development strategy and resource arrangement
1-(2) Patent strategy and partnership
1-(3) Matching of own technologies & markets and benchmarking
1-(4) Grasping needs of customers and markets and relationship with them
1-(5) Cooperation with suppliers
1-(6) Human resource development and development organization
2-(1) Quality of Planning
2-(2) Production engineering ability
2-(3) Project management of development and its control
2-(4) Practice of DR (Design Review) and its quality
2-(5) Systematization of quality assurance and establishment reliability
2-(6) Concurrent engineering and source stream management
2-(7) Practice of design rationale and feedback to next development
3-(1) Quality of new products and their innovative attractiveness3-(2) Lead time and deliver date of development
3-(3) Development efficiency (utilization of front loading method)
3-(4) Practice of target costing and its quality
3-(5) Quality of DFE (Design for Environment)
3-(6) Period of early-stage production control
4-(1) Utilization of QFD (Quality Function Deployment)
4-(2) Utilization of DFM (Design for Manufacturing) and MP (Maintenance Prevention)
4-(3) Utilization of reliability analysis (e.g. FMEA) and Taguchi methods
4-(4) Utilization of CAD (two and three dimensional) and CAE
4-(5) Arrangement of technical database and PDM (Production Data Management)
4-(6) Digitization of technical data exchange and its standardization
Eigen-value
Contribution rate (%)
Cumulative Contribution rate (%)

1
0.690
0.626
0.707
0.690
0.574
0.485
0.624
0.395
0.542
0.405
0.412
0.474
0.296
0.515
0.333
0.416
0.434
0.353
0.297
0.212
0.295
0.255
0.250
0.214
0.252
5.212
20.85
20.85

Factor
2
0.310
0.393
0.282
0.207
0.332
0.306
0.237
0.130
0.425
0.485
0.452
0.426
0.480
0.166
0.138
0.389
0.399
0.371
0.292
0.413
0.460
0.522
0.674
0.711
0.691
4.351
17.40
38.25

UnstandardizedStandardized
t-value
Coefficients
Coefficients
B
Std. Error
Beta(Constant)
2.521
2.021
1.247
Utilization capability of tools and IT-2.0470.995-0.258-2.058Strategy x Tools and IT
0.536
0.177
0.296
3.031
Tools and IT x Technology
0.398
0.158
0.272
2.525
2
2
R=0.323, R =0.104, Adj.R =0.089, Std.Error of the estimation=6.231
All samples, N = 177
Revenue Growth(Average of 5 years)

3
0.273
0.182
0.260
0.285
0.316
0.401
0.403
0.479
0.380
0.378
0.416
0.449
0.460
0.421
0.580
0.445
0.446
0.415
0.691
0.542
0.527
0.417
0.215
0.200
0.142
4.194
16.78
55.03

As a result, the three factors were extractedwith the cumulative contribution of 54.03%. As
shown in the factor matrix (Table 3), items withhigher factor loading more than 0.4 for each factor
are highlighted. According to Table 4, all of theassessment items of area 1 and some of area 2 and 3,
which refer to strategy and organization, werestrongly related to factor 1. So it was entitled as“Development strategy and organization”.
Meanwhile, related items of factor 2 were only inarea 2 and 4 concerning to execution ability ofmanagement tools and IT. Thus, factor 3 wasnamed as “Utilization capability of tools and IT”.
Considering factor 3, it had strong relation to items
mainly in area 2 and 3 which refer to production
technology capability and efficiency. Therefore,“Development production technology” was thegiven name for factor 3. Consequently, these threefactors in terms of their factor scores would be usedin the following section in order to investigate therelationships between each factor and financial
index.
3.2 Utilizing computerized tools and IT in NPD
that contribute to firm’s financial performance
In this section, to verify the first hypothesis,
multiple regression analysis was conducted, byusing backward variable selection method, in order173

p -value
0.214
0.041
0.003
0.012

According to Table 4, three variables ofutilization capability of tools and IT and its
interaction with development strategy, and with
development production technology still remain in
the model with significantly correlated to revenue
growth (average 5 years). However, it could beobserved that the standard regression coefficient for
utilization capability of tools and IT is significantly
negative. In contrast with above finding, interactionof utilization capability of tools and IT with
development strategy and organization factor aswell as interaction with development production
technology factor show positive effect with highly
significant. In this sense, it might imply thatemphasizing on utilization of tools and IT alone
could not contribute to positive impact, but rather
bring negative effect on firm’s financial
performance. On contrary, when tools and IT is
incorporated with development strategy andorganization factor or development production
technology factor, positive impact on this financial
index could be achieved. From this point, the first
hypothesis is supported.
3.3 Different level utilization capability ofcomputerized tools and IT by R&D intensity
In this section, hypothesis 2 that focuses on
relationship between level of utilization capabilityof tools and IT and R&D intensity was investigated.
According to the industry classification by R&D
intensity as mentioned in section 2.2, one-way
ANOVA was conducted in order to explore
significant differences of utilization capability oftools and IT among high and low R&D intensity.
For analysis, the three factors were treated as
dependent variable while R&D intensity
classification was set as factor in one-way ANOVA
model. As a result, factor score average plot for thethree factors is illustrated in Figure 1. And theoutcome of ANOVA is shown in Table 5.

From Table 6, in the group of high R&D
intensity, it is found that only the interaction termof development strategy and organization anddevelopment production technology exists withsignificantly positive impact on revenue growth(average 5 years) while the utilization capability oftools and IT as well as its interaction do not appear
in the model. From this finding, although using
tools and IT in this case can not directly constitutefinancial performance, they might be considered as
the facilitating factor to support the integrating
implementation of development strategy andorganization factor and development production
technology factor for contributing to financial
performance.
However, this result does not mean that using
tools and IT is not necessary for high R&D
intensity group. Considering ANOVA result inprevious section, it is showed the significantly
higher level of utilization capability of tools and IT
for high R&D intensity group. This finding might
confirm that using tools and IT in NPD is thefundamental requirement for this group. In addition,
as supported by Takayama et al. (2002), firms insuch kind of this group have to maintain their highlevel of R&D intensity for sustaining their corecompetency. This implies that firms in this groupstill need to keep in existence of high capability ofusing tools and IT in NPD in order to compete intheircompetitiveenvironment.
Therefore,
hypothesis 3a is supported.
On the other hand, result from Table 7 indicatesthat for low R&D intensity group, only theinteraction term of three factors is found in themodel with a positive significant effect on thefinancial index. This finding implies that for low
R&D intensity group which enroll with not so highcompetitive environment, firms still can use tools
and IT by integrating at the same time withenabling factors of development strategy andorganization
anddevelopment
production
technology to bring competitive advantage and later
directlyenhancefinancialperformance.
Consequently, hypothesis 3b is supported.

Average factor score plot of three factors

Average factor score

3.60
3.50
3.40

High R&D intensity group

3.30

Low R&D intensity group

3.20
3.10
3.00
Development strategy andorganization

Utilization capability of tools
and IT

Development production
technology

Fig. 1 Average factor score plot for two groups ofdifferent R&D intensity
Table 5 One-way ANOVA result for two groups ofdifferent R&D intensity
Average of factor score
VariableHigh R&D
intensity group

Low R&D
intensity group

F

Development strategy and organization
Utilization capability of tools and IT
Development production technology

3.423
3.550
3.222

3.308
3.129
3.124

0.932
12.843**0.649

Level of significant **=0.01

From Figure 1, factors score averages of all
three factors for high R&D intensity group werehigher than low R&D intensity group. Especially inthe utilization capability of tools and IT whichshows the obvious difference. In accordance withthis figure, ANOVA result from Table 5 indicatesthat significant difference of factor score averageamong two groups is only found in utilization
capability of tools and IT. It implies that firm inhigh R&D intensity group possesses higher level oftools and IT utilization capability when comparing
to the low one. According to this result, hypothesis
2 is supported.
3.4 Impact of R&D intensity on the relationshipbetween computerized tools and IT utilization
for NPD and financial performance
In this section, hypothesis 3a and 3b would be
examined. In order to explore the impact of R&D
intensity on the utilization method of tools and IT
for NPD that affects on financial performance,
multiple regression analyses, by backward variables
selection method, for two groups of high and low
R&D intensity were separately performed, as
shown in Table 6 and Table 7, respectively.
Table 6 Regression analysis result for High R&D
intensity group
UnstandardizedStandardized
Coefficientst-value
Coefficients
B
Std. Error
Beta(Constant)
1.446
2.208
0.655
Strategy x Technology
0.461
0.191
0.250
2.412
2
2
R=0.250, R =0.063, Adj.R =0.052, Std.Error of the estimation=6.607
High R&D intensity group, N=89
Revenue Growth(Average of 5 years)

Table 7

4. Conclusions
This research highlighted on how to utilize
tools and IT in NPD that could constitute corporate
financialperformance.
Thefindings
aresummarized as followings.
First, the results suggested that emphasizing
and implementation of tools and IT alone could notbring the positive effect on firm’s financial
performance. Tools and IT should have to be
utilized incorporated with such enabling factors as

p -value
0.514
0.018

Regression analysis result for Low R&D
intensity group

UnstandardizedStandardized
t-value
Coefficients
Coefficients
B
Std. Error
Beta(Constant)
0.266
1.466
0.181
Strategy x Tools and IT x Technology 0.152
0.040
0.381
3.753
2
2
R=0.381, R =0.145, Adj.R =0.135, Std.Error of the estimation=5.884
Low R&D intensity group, N=85
Revenue Growth(Average of 5 years)

p -value
0.857
0.000

174

development strategy and organization anddevelopment production technology. Learning of
this practice may extend to other important issues
for a firm to make a consideration when applying
tools and IT for NPD.
Second, according to the effect of R&D
intensity on tools and IT utilization for NPD, it
indicates that firm with high R&D intensity will
possess higher level of utilization capability of tools
and IT, comparing to the low intensity. This finding
reveals such a characteristic of tools and IT
utilization capability in accordance with different
institutional features of R&D intensity. Firms in
different level of R&D intensity should realize thistypical when they want to make any decisions
which have to care about tools and IT utilization
capability. In addition, this finding reflects aperspective of mutual causation between R&D and
IT which extends from suggestions in recent studies(Lee and Hwang, 2003; Raminez and Kraemer,2007).
Third, it is found that the institutional aspect ofdifferent level of R&D intensity affects on the waysof utilizing tools and IT as well as the impact onfinancial performance. The finding in this researchsuggests that for the firms in high R&D intensity
group, firm should achieve high level of tools andIT utilization capability as the fundamental
requirement. Then, in order to bring about growthon firm’s financial performance, they shouldemphasize on the integrating of the factors ofdevelopment strategy and organization anddevelopment production technology. Thus, tools
and IT might be regarded as a facilitating factor forabove implementation. Meanwhile, for the firms in
low R&D intensity group, integrating tools and IT
with both enabling factors will enhance thecompetitiveness that consequently contributes tofinancial performance. From this point, it might bestated that utilizing tools and IT in NPD can either
direct or subsidiary constitute firm performance,
depending on the level of R&D intensity. With
respect to Raminez and Kraemer (2007), due toincreasing of innovation importance for competingin today’s business, R&D intensity of firms also
tends to increase, consecutively. Therefore, theresult in this part would be advantageous to firms
for having a practical guidance of how to
implement tools and IT which will correspond totheir levels of R&D intensity.

Industrial Engineering-theory, Applications
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[2] Brynjolfsson, E. and Hitt, L. M. 2000. Beyond
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[3] Chen, C.J. 2007. Information Technology,
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176

NPD of Japanese Manufacturing Firms:
Institutional Views of R&D Intensity and Technology Trajectories
Tanyanuparb Anantana**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANanantana.t.aa@me.titech.ac.jp
This research focuses on the implementation of New Product Development (NPD)
influential factors and critical operations through the institutional perspectives of R&D
intensity and technology trajectories. Using New Product Development Scorecard(NPDSC) as the data collecting tool for 396 manufacturing firms in Japan, three NPD
influential factors of “Development strategy and organization”, “Utilization capability oftools and IT” and, “Development production technology”, are explored. These three factors
are investigated for the way of implementation in different institutional level of R&D
intensity. In addition to the factor level, analysis through the NPDSC can provide theguidance of critical NPD operations contributing to NPD performance. The results suggestthat firms in different institutional R&D intensity as well as technology trajectories
require different implementation of factors and operations according to their institutional
contexts.

Institutional Views

1. Introduction
Firms have to heavily rely on New ProductDevelopment (NPD), to survive in the intensivecompetition and dynamic business environment.
This makes firms have to emphasize and invest on
R&D to develop new product [1]. In general,
different level of R&D intensity may affect firm’s
NPD performance and related practices. As several
studies have pointed out the key success factors for
NPD in several contexts of countries and industries[2], this research specifically investigates the waysof implementation of influential factors among
different institutional level of R&D intensity ofJapanese manufacturing firms contributing to firm’s
financial performance.
In addition to the factor level, owing to theutilizing New Product Development Scorecard(NPDSC) for data collecting and analyzing tool for
396 manufacturing firms, the guidance of critical
NPD operations contributing to NPD performancecan be explored. In accordance with the NPD
performance, NPD efficiency is indicated thatmainly constituted by the technology of firms [3].
Therefore, this research scopes on the critical NPD
operations to improve development efficiency
which correspond to each institutional trajectory oftechnology. The framework of this research isclearly illustrated in Fig. 1.

Japan Organization for Quality
Innovation (JOQI) in 2001

Field survey for 14 industries in Japan

NPD influential
factors

New ProductDevelopment
Scorecard(NPDSC)
Utilized by Titech andcooperation with JSA

R&D intensity

Technology Trajectories
Critical NPD
operations

396 Manufacturing firms in Japan

Fig. 1. Research Framework of NPD of Japanese
Manufacturing Firms through Institutional
R&D Intensity and Technology Trajectories
Perspectives

2. NPDSC and Data Collecting Process
NPDSC was initiated by Japan Organization for
Quality Innovation (JOQI) in 2001. NPDSC is
designed for being self-NPD performanceassessment tool covering all manufacturingindustries in Japan. The scorecard encompasses 25
assessment items based on four core assessment
areas: (1) Organizational Systems of Development,(2) Planning and Execution Ability, (3) New
Product Development Performance, and (4)Exploitation of management tools and information
technology (see Fig. 2.) Each of assessment item israted according to five defined levels (with detailed
description), with the 5th level supposing to be thebest practice. Additionally, the result of assessment
from NPDSC for individual company could becompared against competitors in the same industry
as well as across the industries.

177

classified in this study, as shown in Table 1. These
are: (1) Supplier-dominated; Technological change
comes almost from suppliers of machinery andother production inputs, (2) Scale-intensive;
Technology is incrementally accumulated from thebasis of earlier experience, and internal
improvements, (3) Science-based; Technology
accumulation mainly generates from R&D activities
of firms, and is heavily dependent on knowledge,
skills and techniques emerging from academic
research, (4) Specialized suppliers; Technologicalaccumulation takes place through the design,building of specialized inputs that will be provided
to next customer.

<3>
New Product Development
Performance（６ assessment items）<1>
Organization
al Systems ofDevelopment（６ assessment
items）

Effective
Development<4>
Exploitation ofmanagement tools and IT<2>Planning andExecution
Ability（7 assessment
items）（６ assessment items）

Fig. 2. Area of Assessment of NPDSCHigh R&D Intensity
Pharmaceutical
Preccision Machinery (BC)Electronic Part (Auto)
Information Communication
Software
Precision Machinery (BB)
Machinery Part (Auto)
Electrical Machinery (BC)
Automobile
Electrical Machinery (BB)
Machinery (BC)Owing to the data collecting process, NPDSC
has been used to collect data by interviewing
method from participated firms in Japan
manufacturing sector since 2003[4], then by maling
method in 2007 [3]. Finally, total of 396
participated firms in Japanese manufacturing wereobtained.

Average R&D Intensity = 2.81%

3. Institutional Perspectives
3.1 Institutional Level of R&D Intensity
This research focuses on R&D intensity as theindicator to reflect the difference of competitiveenvironment that might affect the way of
implementing NPD influential factors as well as
their contributions to firm’s financial performance.
In accordance with this, the term of R&D intensity
used in this research is represented by R&D
expense per sales (%). The industry classification
by different level of R&D intensity was performed.
According to the NPDSC database, first, each firm
was checked for the R&D expense per sales datafrom Japanese Nikkei NEEDS of the same year offirm’s NPDSC data. Then, for those available data,
average of R&D expense per sales for each industry
was figured out. The average of all industries was
also calculated. Then, comparing industry average
to overall average, two groups of high and low
R&D intensity were classified, as shown in Fig. 3.
3.2 Institutional Technology Trajectories
Pavitt [5] has classified firms into the four
categories of technological trajectories byconsidering several indicators, as followings: theindustrial sector, the source of technology, the typeof user of technology, the means of appropriation,
the relative balance between product and process
innovation, as well as the intensity and direction oftechnological diversification. According to thedefinition of industry classification from Pavitt, by
focusing on the aspect of source and direction oftechnology, four groups of industries were

5.954
4.858
4.663
4.077
3.875
3.532
3.455
3.147
3.097
3.069
2.898

Low R&D Intensity
Chemistry (BC)Chemistry (BB)
Machinery Part (Others)
Electronic Part (Others)
Machinery (BB)
Food
Cloth&ApparelShip
Iron&Steel
Construction
Wood &Furniture
Paper

2.788
2.679
2.613
2.540
2.517
2.470
2.180
1.588
1.019
0.798
0.485
0.360

Fig. 3. Institutional Level of R&D Intensity
Table 1 Institutional Technology Trajectories
Industry
1 Construction
2-1 Processed Food
2-2 Beverage & Liquor
3 Cloth & Apparel
4-1 Wood & Furniture
4-2 Paper & Plup
4-3 Printing
5-1 Pharmaceutical
5-2 Chemistry for General Use
5-3 Chemistry for Business Use and material
6 Iron-Steel & Nonferrous metal
7-1 Machinery & Appliances for General Use
7-2 Machinery & Appliances for Business Use
8-1 Electrical Machinery & Appliances for General Use
8-2 Electrical Machinery & Appliances for Business Use
9 Information Communication
10-1 Automobile & Motorcycle
10-2 Ship & Other transportation
11-1 Precision Machinery & Appliances for General Use
11-2 Precision Machinery & Appliances for Business Use
12-1 Electronic Part & Devices for Auto Industry
12-2 Electronic Part & Devices for Others
13-1 Machinery Part for Auto Industry
13-2 Machinery Part for Others
14 Software
Total

4.

Number of SupplierScalesamples dominated intensive
58
4
0
7
12
7
4
8
19
79
47
26
57
36
68
15
16
11
10
40
22
26
27
12
14
625

81

85

SciencebasedSpecialized
suppliers

162

297

Relationships between NPD Influential
Factors and Institutional Level of R&D
Intensity
According to the previous study [3], by using
factor analysis, three NPD influential factors of178

“Development strategy and organization”,“Utilization capability of tools and IT” and,“Development production technology” were
explored. In this research, levels of these factors
were compared between high and low R&D
intensity (see Fig. 4). The regression analysis byusing backward variable selection method for all
samples was conducted to find the relationships
between these factors and firms financial
performance (herein, revenue growth average 5
years). The result indicated that firms need to
implement tools and IT incorporated with
development strategy and organization factor ordevelopment production technology factor in order
to constitute firms’ financial performance, as shownin Table 2.

NPD Influential factors
Factor 1“Development strategy
and organization”
Factor 2“Utilization capabilityof tools and IT”
Factor 3“Development
production technology”
Average factor score plot of three factors

Average factor score

3.60

Table 2 Relationships between NPD Influential
Factors and Financial for All Samples
UnstandardisedStandardisedt-value
Coefficients
Coefficients
B
Std. Error
Beta(Constant)
2.521
2.021
1.247
Utilisation capability of tools and IT-2.0470.995-0.258-2.058Strategy x Tools and IT
0.536
0.177
0.296
3.031
Tools and IT x Technology
0.398
0.158
0.272
2.525
2
2
R=0.323, R =0.104, Adj.R =0.089, Std.Error of the estimation=6.231
All samples, N = 177
Revenue Growth(Average of 5 years)

3.50
3.40

High R&D intensity group
Low R&D intensity group

3.30
3.20
3.10
3.00
Development strategy and Utilization capability of toolsorganization
and IT

Development production
technology

Fig. 4. NPD Influential Factors and Their Different
Level among High and Low R&D Intensity Groups

p -value
0.214
0.041
0.003
0.012

Table 3 Relationships between NPD Influential
Factors and Financial Performance in each
Institutional R&D Intensity
Multiple Regression Analysis (High R&D intensity)

In this research, when considering the effect of
institutional level of R&D intensity, the regression
analyses (by using similar method to all samples)
were separately conducted for high R&D intensity
and Low R&D intensity group. As a result in Table
3, in the group of high R&D intensity, it is foundthat only the interaction term of development
strategy and organization and development
production technology exists with significantly
positive impact on financial performance, while theutilization capability of tools and IT and its
interaction do not appear in the model. Thisconfirms the effect of institutional R&D intensity
on the ways of implementation of each influential
factor. It also imply that firms with high R&D
intensity need to integrate the implementation ofdevelopment strategy and organization factor anddevelopment production technology factor toconstitute firm’s financial performance. In thissense, together with the consideration of level ofutilization capability of tools and IT factor which
was higher in high R&D intensity group, it might
imply that using tools and IT in this high group
might be considered as the facilitating factor which
could not directly contribute to financial
performance but still necessary to support thosefactors integration. On the other hands, for low
R&D intensity group, firms require the combinationof all three factors in order to bring about
competitive advantage and later directly enhancefinancial performance.

UnstandardizedStandardized
Coefficientst-value
Coefficients
B
Std. Error
Beta(Constant)
1.446
2.208
0.655
Strategy x Technology
0.461
0.191
0.250
2.412
2
2
R=0.250, R =0.063, Adj.R =0.052, Std.Error of the estimation=6.607
High R&D intensity group, N=89
Revenue Growth(Average of 5 years)

p -value
0.514
0.018

Multiple Regression Analysis (Low R&D intensity)

UnstandardizedStandardized
t-value
Coefficients
Coefficients
B
Std. Error
Beta(Constant)
0.266
1.466
0.181
Strategy x Tools and IT x Technology 0.152
0.040
0.381
3.753
2
2
R=0.381, R =0.145, Adj.R =0.135, Std.Error of the estimation=5.884
Low R&D intensity group, N=85
Revenue Growth(Average of 5 years)

5.

p -value
0.857
0.000

Critical NPD Operations for Each
Institutional Technology Trajectory

According to the institutional perspective oftechnology trajectories in section 3.2, regression
analysis was conducted for all samples by setting
item 3-(3) development efficiency as the dependent
variable and taking up rests of 24 assessment items
as the independent variables. Then, backward
variable selection method was used. The remained
items in the model represents for NPD operations
which directly impact on development efficiency.
The result of regression analysis was shown in
Table 5.
Then, the separate regression analyses for each
institutional technology trajectory were conducted.
Same methodology as all samples was used. The
results of regression analyses would be compared to
the reference model in Table 5, in order to indentify
the typical NPD operations that might be vital foreach group, as shown in Table 6.

179technologies for supplier-dominated group areprovided by suppliers, firms in this group should
specifically emphasize their suppliers as well as thedesign rationale system. Meanwhile, because
technology for specialized suppliers group are
generated from customer requirements, thus firms
in this group should put the importance on graspingneeds of customers and markets and try to make therelationship with them to. On the other hand, forscale-intensive group, firms should focus on
product data management that will be able torespond their typical features of in-house
technology development as well as their internallearning and experience. Meanwhile, firms inscience-based group, which technologies are mostly
generated from internal R&D, should especiallyemphasize on developing their human resources andorganizations.

Table 5 Reference Model og NPD Operations forDevelopment Efficiency for All Samples
Development Efficiency
Bt-valuep -value(All samples, N=625)(Constant)-0.454-4.3380.000
1-(1) Strategy and resource
0.108
3.399
0.001
1-(4) Needs of cus. and mkt.
0.085
2.279
0.023
2-(1) Quality of planning
0.102
2.333
0.020
2-(3) Project management
0.148
4.085
0.000
3-(5) Design for Envi.
0.071
2.242
0.025
3-(6) NP ramp-up smooth.
0.144
3.579
0.000
4-(1) QFD
0.065
2.004
0.046
4-(2) DFM
0.141
3.197
0.001
4-(4) CAD
0.075
2.491
0.013
R=0.732, R2=0.535, Adj.R2=0.528, Std.Error of Estimate=0.560

Table 6 Critical NPD Operations for Development
Efficiency in each Technology TrajectoryGroup

6. Conclusions
This research corresponds to the dimensional of
Entrepreneurial organization and culture, fromthree dimensional approaches of institutional
system, which focuses on the micro level ofindustries and enterprises. The results in thisresearch confirm that institutional level of R&D
intensity and institutional technology trajectories
respectively affect the ways of implementations for
the NPD influential factors as well as the criticaloperations. These might be beneficial as theguidance for firms to let them know how and what
to be done in order to enhance firms’ financial
performance and development efficiency inaccordance with these institutional perspectives.
.

Development Efficiency
Bt-valuep -value(Supplier-Dominated, N=81)(Constant)
0.160
0.892
0.375
1-(1) Strategy and resource
0.172
2.555
0.013
1-(2) Patent and partnership-0.328-3.9040.000
2-(3) Project management
0.302
3.649
0.000
2-(4) DR
-0.289-3.4450.001
2-(7) Design rationale
0.262
2.774
0.007
3-(5) Design for Envi.
0.352
4.655
0.000
4-(1) QFD
0.466
5.843
0.000
4-(2) DFM
-0.393-3.9460.000
4-(6) Use of open standard
0.156
2.454
0.017
R=0.861, R2=0.742, Adj.R2=0.701, Std.Error of Estimate=0.407
Development Efficiency
t-valuep -value
B(Scale-Intensive, N=85)(Constant)-0.587-2.6420.010
1-(1) Strategy and resource
0.322
4.205
0.000
4-(1) QFD
0.193
2.214
0.030
4-(2) DFM
0.278
2.611
0.011
4-(5) PDM
0.250
2.741
0.008
R=0.816, R2=0.666, Adj.R2=0.648, Std.Error of Estimate=0.584

References[1] Ettlie, J. E., 1998. R&D and Global
Manufacturing Performance, Management
Sciences, 44 (1) 1-11.
[2] Sun, H. and Wing, C. W., 2005. Critical
Success
FactorsforNew
Product
Development in Hong Kong Toy Industry,
Technovation, 25, 293-303.
[3] Anantana, T, Enkawa, T, and Suzuki, S, 2009.
Empirical Research on The Influential Factors
for Successful New Product Development andtheir Differences among Industries, Journal ofJapan Industrial Management Association, 59(6) 494-504.
[4] Irikura, N. and Enkawa, T., 2005. Proposal on
new product development scorecard and its
application. Journal of the Japanese Society
for Quality Control, 35 (4) 73-84 (in Japanese).
[5] Pavitt, K., 1984. Sectoral patterns of technicalchange: Towards a taxonomy and a theory.
Research Policy, 13 (6) 343-373.

Development Efficiency
Bt-valuep -value(Science-Based, N=162)(Constant)-0.504-2.3090.022
1-(1) Strategy and resource
0.129
2.464
0.015
1-(4) Needs of cus. and mkt.
0.179
2.443
0.016
1-(6) HRD and developt. org.
0.190
2.019
0.045
2-(3) Project management
0.194
2.667
0.008
2-(4) DR
-0.150-1.9230.056
3-(6) NP ramp-up smooth.
0.174
2.349
0.020
4-(2) DFM
0.290
3.596
0.000
R=0.748, R2=0.559, Adj.R2=0.539, Std.Error of Estimate=0.550

Development Efficiency
Bt-valuep -value(Specialized Suppliers, N=297)(Constant)-0.426-2.7380.007
1-(4) Needs of cus. and mkt.
0.165
3.119
0.002
2-(1) Quality of planning
0.179
2.885
0.004
2-(3) Project management
0.153
2.985
0.003
3-(6) NP ramp-up smooth.
0.144
2.750
0.006
4-(2) DFM
0.154
2.448
0.015
4-(4) CAD
0.106
2.400
0.017
R=0.693, R2=0.480, Adj.R2=0.469, Std.Error of Estimate=0.559

Considering Table 6, firms in each institutional
trajectory focus on different critical operations inorder to improve NPD efficiency. Since

180

Cross-Industry Comparison of Drivers of Customer
satisfaction and Repurchase Intention
Gulimire ABULAITI
Department of Industrial Engineering and Management, Tokyo Institute of Technology
Gulmire.a.aa@m.titech.ac.jp
1. Introduction

the goods and services is corporate image rather than satisfaction. This
indicates the approach to predict loyalty based only on customer satisfaction

Customer satisfaction which has became a popular term of the 1990s,

is not sufficient. Building a good corporate image should be given due

generating much interest among academic researchers. Studies have shownconsideration. Impact of other drivers such as satisfaction, perceived quality,

beneficial effects of satisfaction on consumer behavior, which result inperceived value, switching cost differs from product to product (Figure2)

increased loyalty, positive word-of-mouth advertisement, reduced pricesensitivity, reduced switching to competitors, and increased profits andgrowth. For these reasons customer satisfaction and loyalty have been
widely studied as well as their influential factors. National customer
satisfaction index/barometer has been developed in some countries toenhancing the performance of firms, industries, economic sectors andnational economics. However, in the studies industrial differences of driversof customer satisfaction and loyalty have been paid little attention.
The purpose of the research is to investigate cross-industry variation incustomer satisfaction and repurchase intention which also refers to as
loyalty, as well as determinates of them to explore Japanese consumer
behavior.

2. Survey Methodology
In order to explore the drivers of customer satisfaction and repurchaseintention, a corresponded survey was designed with three main parts. The
first part contains demographic questions along with economic and quality
expectations. The second part contains questions about culture and life
satisfaction. The last part includes a series of questions toward goods andservices (Table1).

Figure1. Drivers of Customer satisfaction

Table1. Details about Industries and Questions

3. Drivers of Customer Satisfaction

Figure2. Drivers of Repurchase Intention

The main driver of customer satisfaction in Japan is perceived quality
which has positive strong effect in all industries. Other important drivers areperceived value and corporate image. However, the impact of them varies
from industry to industry. As to the purchase experience, for the productswith high rate of change such as shampoo, hair salon, fast food showed
positive effect while products with low rate of change like automobile andmobile phone service provider showed negative impact. Time sincepurchasing which data is only available for PC, mobile phone, mobile
phone service provider and automobile can be considered as products withlow rate of change, showed negative impact on customer satisfaction(Figure1).

5. Conclusion
Through the analysis of the data, we found that in various Japanese
consumer markets determinants of customer satisfaction and repurchaseintention are different. To invest in the items which having strong effect on
customer satisfaction and repurchase intention would be helpful formarketing managers in decision making. Customer satisfaction andrepurchase intention model not only varies from industry to industry but
from country to country. Same survey were conducted in China and resulted
differently from Japanese consumers. We are also conducting the survey inUSA, France, Thailand and Bolivia at the moment to investigate thecross-cultural difference of drivers of customer satisfaction and repurchaseintention.

4. Drivers of Repurchase Intention
In Japan, the most influential driver of repurchase intention for most of181

Cross-National Comparison of Customer Satisfaction and Repurchase Intention
Gulimire Abulaiti**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
W9-57 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
Gulmire.a.aa@m.titech.ac.jp

This study investigate the drivers of customer satisfaction and repurchase intention
using data from Japan and China. It is found that peceived quality is the main driver ofcustomer satisfction while corporate image is the main driver of repurchase intention bothin Japan and China. However, the influence of these main drivers differ in these twocountries. Besides, other drivers of customer satisfaction and repurchase intention are also
vary both in Japan and China.

1. Introduction
Customer satisfaction which has became apopular term of the 1990s, generating much interest
among academic researchers. Studies have shown
beneficial effects of satisfaction on consumer
behavior, which result in increased loyalty, positive
word-of-mouth advertisement, enhanced firm’s
reputation, and increased profits and growth. For
these reasons customer satisfaction and loyalty havebeen widely studied as well as their influential
factors.
National
Customer
Satisfaction
index/barometer has been developed in somecountries to enhancing the performance of firms,
industries, economic sectors and national
economics. Although these National Customer
Satisfaction Indices are fundamentally similar, they
have some obvious distinctions in model’s structure,
variables selection, corresponding survey questions
related to each variables, and scoring system. Thismeans cross –national comparison can not be doneusing these customer satisfaction indices.
The purpose of the research is to investigate
cross-country and cross-industry variation incustomer satisfaction and repurchase intention
which also refers to as loyalty, as well as
determinates of them to explore consumer behavior
in different countries.
2. Survey Methodology
In order to explore the drivers of customer
satisfaction
andrepurchaseintentionacorresponded survey was designed with three mainparts. The first part contains demographic questions
along with economic and quality expectations. The
second part contains questions about culture andlife satisfaction. The last part includes a series ofquestions toward four goods, six private services
and five public services. Question items in this part
mainly contains purchase experience, time sincepurchasing, main purpose of usage, overallsatisfaction, pre-purchase expectations, perceived
quality, perceived value (product quality relative tothe price), recommendation intention, repurchaseintention, corporate image, relational switching costand non-relational (time, money, risk) switching
cost.
Table 1. Details of Products and Services
Products
Private Services
Public Services
・Automobile
・Bank・Drivers’ license
・Mobile Phone ・Fast Food
Renewa・Municipal・PC・Hair Salon
Administration
・Shampoo・Hospital
・ Mobile Phone ・Power Supply
ServiceCompany
Provider・Post Office・Super Market
・Tax Authorities

We have been conducting survey in Japan since
October, 2008. Survey in china has been done in
September, 2008. Table 2 display the sample
distribution of Japanese and Chinese data.
Table 2. Demographic Sample Distribution
Japanese
ChineseMale
FemaleMale
Female
10-19
6
24
34
18
20-29
143
71
73
43
30-39
46
71
73
43
40-49
37
44
54
33
50-59
36
44
37
18
60+
14
10
8
13
Total
562
634

3. Results
3.1 Comparion of Customer Satisfaction
The Comparison of satisfaction of Japanese182

and Chinese consumers is carried out in products,
services and public services. As displayed in Figure
1, customer satisfaction is high in products, lower
in services and lowest in public services both inJapan and China. This result is consists with
empirical study conducted by Johnson et al. (2002)
Considering the difference between products andservices, Johnson et al. (2002) argued thatdifference is due to the distinction between productand service production and delivery. Products areproduced at a time and in a place of the supplier’s
choosing and not in the presence of customers. In
contrast, services are co-produced in the customer’s
presence, at a time and in a place of the customer’schoosing, with the customer’s input. It puts both
employees and customers into the production
process. Unlike products, if something goes wrong
in the service production process, it is often too late
to institute quality controls before the service
reaches the customers (Hoffman & Bateson, 1997).
Another major distinguishing feature of service istheir intangibility. Services can not be touched or
felt in the same way as physical products (Hoffman& Bateson, 1997). Johnson & Nilsson (2003)
examined 188 firms from 30 industries found thatsatisfaction is lower for service than for products
because significantly lower service reliability
outweighs the advantages afforded by service
customization. Among public and government
agencies competition is restricted, and it eliminates
the entrepreneurial incentives to provide goods andservices that better need customer needs (Johnson etal., 2002).

by shampoo, hair salon, mobile phone, mobile
phone service provider, PC, super market, fast food,
hospital, bank, power supply company, post office,municipal administration, drivers’ license renewal
and tax authorities. In China, customer satisfactionof automobile industry also ranked the highest,
following by PC, shampoo, mobile phone, bank,fast food, mobile phone service provider, supermarket, hair salon, drivers’ license renewal,
electricity, municipal administration, post office,tax authorities and hospital.

Figure2.Comparison of Customer Satisfaction (each industry)

3.2 Drivers of Customer Satisfaction
In order to explore the drivers of customer
satisfaction in Japan and China, we conducted
multiple regression analysis at aggregate level.
Satisfaction is the dependent variable where prepurchase quality expectations (QExp), perceived
quality (PQ), perceived value (PV), corporate image(image) are independent variables. Figure 3
illisutrated the result of multiple regression analysis.
Vertival axis is standarded coefficient β, and weonly displayed the resutls of statistically significant
variables. The score of the variables which has
insignificant impact on dependent variable wasdeleted. In Japan, perceived quality is the main
most influencial driver of customer satisfaction.
Perceived value and corporate image also effectcustomer satisfaction. However, the influence aremuch more weaker than perceived quality. We cansay that Japanese consumers are more quality
driven. In china, perceived quality is also the main
driver of customer satisfaction. However, theinfluence is not as strong as in Japan. Besides,
image, perceived value, quality expectations arealso important driver of customer satisfaction.
According to the discoveries of uncetainty
avoidance related marketing literature (Tsoukatos
and Rand, 2007), the higher the uncertainty
avoidance, the more attentions are paid on thequality in terms of reliability, responsiveness,assurance and so on. With extremely highFigure1.Comparison of Customer Satisfaction (Japan-China)

In order to know the satisfaction level of eachproduct and service we examined the satisfactionlevel of each product and service with comparisonof Japanese and Chinese data (Figure2). As can beseen from the figure satisfaction level crossindustry varies among Japanese and Chinese
consumers. In Japan, customer satisfaction of
automobile industry ranked the highest, following

183In order to explore drivers of repurchaseintention, multiple regression analysis was
conducted at aggregate level using Japanese andChinese data. Repurchase intention is the dependent
variable while customer satisfaction (CS), perceived
quality (PQ), perceived value (PV), corporate image(image), time, effort, money, risk related switchingcosts (SC1) and relationship related switching costs(SC2) are independent variables. Figure 5 displays
the result of multiple regression analysis. Vertival
axis is standarded coefficient β, and we only
displayed the resutls of statistically significant
variables. The score of the variables which has
insignificant impact on dependent variable wasdeleted. In Japan, corporate image is the main
driver of repurchse intention. Other importantdrivers are satisfaction, perceived qulity andperceived value. Both of the two switching costhave no significant influence on repurchaseintention. In china, image is also the main driver of
repurchase intention. Other drivers are perceived
value and time, effort, money, risk related switchingcost. Perceived quality and relationship related
swtiching costs have no significant influence on
repurchase intention. Suprisingly, customer
satisfaction has negative influence on repurchaseintention which is apparently against previous
researches (Homgurg et al., 2005; Anderson andSrinivasan, 2003). One of the possible reason forthis is heteroskedasticity, which means the randomvariables have different variance and it is aviolation of some preliminary assumption like thatthe error term has a constant variance (Greene,2003). It often occurs in the case with crosssectional or time series measurements. Since thismultiple regression analysis is based on aggregate
level consists of data form ten different industries,
appearance of heteroskedasticity may explain theunexpected result.

uncertaintly avoidance of Japanese (Hofested,2004) they make excessive demands on quality andfear failing purchasing experience caused by poor
quality. Consequently Japanese will feel satisfied aslong as a product or service with considerablyhigh qualtiy, no matter how expensive it is. So forJapanese market it is important to have high quality
products or services.

Figure3.Drivers of Customer Satisfaction

3.3 Comparison of Repurchase Intention
Comapriosn of repurchase intention of eachproduct and service conducted for both Japan and
China. In Japan, repurchase intetion of hair salon
ranked the highest following by shampoo, supermarket, hospital, mobile phone servie provider,
automobile, fast food, bank, mobile phone and PC.
In china, mobile phone service provider ranked thehigest following by bank, shampoo, super market,
automobile, fast food, mobile phone, hair salone,
PC and hospital (Figure 4). From the result we caninterpret in Japan and china the repurchase intention
towards same product is different. futhurmore, we
also can say that high satisfaction is insufficient for
repurchase intetion. Although, industries such as
automobile, PC, mobile phone ranked highest in
satisfaction, repurchase intention are not ranked
very high.

Figure5. Drivers of Customer Satisfaction
Figure4. Compariosn of Repurchase Intention

4. Conclusions
This study focused on antecedents of customer
satisfaction and determinents of repurchaseintention based on the questionnaire survey

3.2 Drivers of Repurchase Intention

184

conducted in Japan and China. Through the analysisof the data, we found that in Japanese and Chinese
consumer markets infuluence of drivers of customer
satisfaction and repurchase intention are different.
Although the main driver of customer satisfaction isperceived quality and main driver of repurchaseintention is corporate image both in Japan and
China, the degree of impact differ in two countries.
Besides, impact of other drivers on customer
satisfaction and repurchase intention are also
different in both countries.
To invest in the items which having strong
effect on customer satisfaction and repurchaseintention would be helpful for marketing managers
in decision making. Customer satisfaction andrepurchase intention model not only varies fromcountry to country but from industy to industry.We
are also conducting the survey in USA, France,
Thailand and Bolivia at the moment to investigate
the cross-cultural difference of drivers of customer
satisfaction and repurchase intention in more details.
References[1] Aderson, R.E. and Srinvan, S.S., 2003. Esatisfaction and E loyalty: A Contigency
Framework, Psycholology and Marketing,20( 2) 123-138.
[2]

Greene, W.H., 2003. Econometric Analysis
5th Edition, Prentice Hall, Upper Saddle
River.

[3]

Hofstede,
G.,
2004.
Culturesand
Organizations: Software of the Mind;
Revised and Expanded 2nd Edition. New
York, NY. USA: McGraw-Hill.

[4]

Homburg, N.K. and Hoyer, W.D., 2005. Do
satisfied Customers Really Pay More? A
Study of the Relationship between Customer
Satisfaction and Willingness to Pay, Journalof Marketing, 69(2) 84-96.

[5]

Huffman,k.D., & Bateson,J.E.G., 1997.
Essentials of services marketing. Fort Worth,
TX: Dryden Press.

[6]

Johnson, M. D., Nilsson, L., 2003. The
importance of reliability and customizationfrom goods to services. Quality Management
Journal, 10(1) 8–19

[7]

Johnson, Michael M.D., Andreas Herrmann,
A. and Anders Gustafsson 2002. Comparing
Customer Satisfaction across Industries andCountries, Journal of Economic
Psychology, 23 (6) 749-769.

185

[8]

Tsoukatos, E. and Rand, G.k., 2007. Cultural
Influence on Service Quality and Customer
Satisfaction: Evidence from Greek Insurance,
Managing Service Quality, 17(4) 467-485

Beyond Deliberate Corporate Control - The Roles of
Isomorphic Pressures, National Culture and Organization in
the Institutionalization of Knowledge Management
Rémy Magnier-Watanabe
Department of Industrial Engineering and Management, Tokyo Institute of Technology
magnierwatanabe.r.aa@m.titech.ac.jp
1. Introduction

to a newfound virtuous cycle of growth. Knowledge management, as
enabler of change using its knowledge creation capability, is subject todifferent forces that shape its processes and eventually the resulting
innovation. A qualitative analysis based on data gathered from the casestudy of the first major rollout of smartcard technology in France shows
how institutional isomorphic pressures affect the KM processes applied in
the creation and maintenance of the resulting innovation. The government
impetus, legal authorities and cultural expectations in the French society
produced coercive isomorphic pressures onto the credit card industry, while
existing credit card solutions, systems and standards played the role ofmimetic isomorphic pressures, and professional networks and network
effects functioned as normative isomorphic pressures. Also, a systems
perspective of institutional pressures was found to provide a better
understanding of interdependence mechanisms.

Knowledge management (KM) has been recognized not only as a sourceof sustainable competitive advantage, but also as a primary driver forcompetitiveness. However, the use of knowledge in organizations is largely
a discretionary behavior that can be encouraged but not demanded by thefirm, and turning employees into knowledge workers may not solely dependon corporate decree. Therefore, the purpose of this research is to identify,
through qualitative and quantitative analyses, the prescriptive factors
influencing KM beyond the deliberate systems introduced by the firm, inparticular intrinsic forces such as company-specific business configurationand national culture, and extrinsic environmental pressures (Fig. 1), andevaluate its effects on sources of competitive advantage

Isomorphic
pressures

4. Organizational Characteristics and National
Culture as Prescriptive Factors of KM(3)
National
Culture(2)

KM
Indiv. | Group(1)

Using both a qualitative approach with semi-structured interviews
and quantitative data gathered from a questionnaire survey with several
international offices of a major Japanese pharmaceutical company,
organizational characteristics – specifically structure, membership,
relationship, and strategy – and national culture – power distance,
individualism-collectivism, masculinity-femininity, and uncertainty
avoidance – were found to affect KM – namely knowledge acquisition,
storage, diffusion, and application – respectively (Fig. 2). These results
suggest that practitioners can increase the yield of KM when integrated
upstream into the elementary business processes and adapted to the cultureof each local office.

Organization(4)
Sources ofComp. Adv.

Fig. 1 Research Framework on the Institutionalizing
Factors of Knowledge Management

2. The Effect of Congruent KM Behaviors on
Sources of Competitive Advantage
Since processes designed at enhancing the productivity of knowledge do
not equally contribute to the organization’s capabilities, the first part of thisresearch first focuses on how different perceptions and behaviors related to
KM affect competitive advantage. Using data collected from the populationof a firm’s personnel in Japan, results show that the perceived importance of
KM activities appears as an important source of competitive advantage
related to technical knowledge, and that more time spent on KM activities
contributes to a competitive advantage related to affective knowledge.
Further analysis involves a taxonomy of employees based on theirperceived importance of and the time they spend on KM. There is evidence
suggesting that KM strategies should be tailored to fit the discriminate
beliefs and actions of each group of workers, identified based on their levelof congruence between their espoused theories and theories-in-use related
to the management of knowledge.

National Culture

KM Value-Chain

Power distance
High
Low

Acquisition
FocusedOpportunistic

 Structure
VerticalHorizontal

Organization

Individualism
IndividualCollective

Storage
PrivatePublic Membership
IndividualCollective

Masculinity
Masculine
Feminine

Diffusion
Prescribed
Adaptive Relationship
Systematic
Ad-hocUncertainty avoidance
High
Low

Application
Exploitative
Explorative Strategy
Reactive
Innovative

Fig. 2. Organization and National Culture as
Prescriptive Factors of KM

5. Conclusion

3. The Effect of Institutional Pressures on KM
and the Resulting Innovation: A Case Study

These analyses have uncovered some of the institutionalizing forces –responsible for the creation and perpetuation of enduring social features –affecting KM that exist inside and outside the firm’s boundaries. Thesefindings are expected to improve the design and efficiency of KM
especially in heavily-regulated industries and international operations.

As governments attempt to stimulate the economy, solving the issue of
disconnect between institutional systems legitimized in routine on the one
hand and innovation striving on change on the other hand, promises to lead

186

Cultural Dimensions and Regional Defferences in Knowledge Management
among Three Industrialized Countries
Remy Magnier-Watanabe**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-527 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
remy@ml.me.titech.ac.jp
This research seeks to validate a new Knowledge Management (KM) framework,
identify whether national culture has a unifying influence over KM, and whether locallyadopted and implemented KM initiatives are perceived as more successful than thosemodeled after the country of headquarters. Uncovering the correlation between culturalenvironment and corporate entrepreneurship development through the use of KM tools
will help organizations better understand the implications of R&D decisions andimplement strategies capitalizing on the cultural diversity in its local teams.
The goal of this research endeavor is toempirically test the typology of companies based on
their KM strategy and structure and determine
whether there is a pattern of local similarities orinternational differences. For this purpose, I will
focus on KM initiatives applied to corporate
entrepreneurship efforts and seek to uncover the ties,
if any, between successful and lagging KM types
and cultural identities among American, Japaneseand French companies.

1. Introduction
1.1 Background
Economic growth usually triggers aninternational expansion in order to capture thepotential of a wider market. In this predicament,
organizations set up offices abroad and encourage
innovation at the local level with the purpose ofdeveloping products or services matching andserving regional needs.
Many frameworks or strategies to implement
KM have been tentatively developed in previous
research (Holsapple and Joshi, 2000; RubensteinMontano et al., 2001; von Krogh et al., 2001;
Armistead and Meakins, 2002). However, few havefocused on a possible correlation between theimplementation of KM initiatives and the culture of
its local practitioners (Desouza and Evaristo, 2003;
Kankanhalli et al., 2004).
This paper will help corporate entrepreneurshipstakeholders understand and re-think their KM
processes aimed at improving their innovation
efforts, in order to optimize it at each local level.

2. Research planThis research project spans 3 full years of
doctoral research. Each year roughly corresponds toa step in the progress of this investigation.
2.1 First year
The first semester has been so far dedicated to“on-the-job training” completing projects under thesupervision of my advisor. A new framework wasdeveloped following a thorough review of theexisting literature on KM systems and models(Polanyi, 1966; Nonaka and Takeuchi, 1995;
Demarest, 1997: Kelloway and Barling, 2000). The
validation of such framework will help create atypology of companies based on theirorganizational characteristics and associated KM
initiatives. Semi-structured interviews with one
global company with offices in Japan, France, andthe United States will be conducted by the end of
the school year.

1.2 Hypotheses
I first redefine KM as aiming at rationalizing,
regulating, transmitting, channeling, and exploiting
any present or absent (but desirable) knowledge
within the organization’s boundaries with the
purpose of accomplishing corporate objectives in
the most efficient manner (H1). After validating thisdefinition, I will seek to test the following: incompanies turned toward innovation, the national
culture of local stakeholders has a unifying
influence over their perspective on KM initiatives(H2); locally-adopted and implemented KM
initiatives within a corporate entrepreneurship (newbusiness initiative within established companies)
milieu are perceived as more successful than thosemodeled after the country of headquarters (H3).

2.2 Second year
In the second year, this research project
involves the utilization of previous research
conducted by Geert Hofstede (1980) in the 1970’s
on cultural dimensions. For this reason, the second
year will have the task of validating Hofstede’s
findings with fresh and new data on culturaldimensions in work-related values. The next stage

187

will be to investigate possible correlations between
Hofstede’s
culturaldimensions
andtheorganizational characteristics and typology from theprevious stage, mainly using questionnaires withseveral global companies with offices in Japan,
France, and the United States.
2.3 Third year
The final year will primarily focus on thewriting of the doctoral thesis as well as theconsolidation of the results of the two previous
years, and possibly gathering additional data if
needed.
3. Existing work
3.1 Past research
Since entering the doctor course at TITech in
April 2005, I was able to assist Professor Senoo in
the writing of a paper on workplace reformation as
well as present it at an international conference.
Consequently, the paper named “How to
Design Active BA: Interactions with Physical and
Virtual Environments” was presented at the PacificAsian Conference on Information Systems (PACIS)
in Bangkok, Thailand at the beginning of July thisyear. Following is the abstract of that paper.
In “the age of knowledge”, knowledge has
become the main asset in solving issues andcreating value in organizations. In this regard,“workplace reformation” actively participates inpromoting knowledge creation. One of the key
factors supporting knowledge creation is “thecreation of BA”. In the workplace reformation
process, when BA fosters the creation of knowledge,
it is called “active BA”. In this paper, we propose aframework to design active BA. The workplacereformation is first segmented into virtual andphysical environments; then, we consider theeffects of each environment on active BA, as wellas the interactions between each environment;
finally, we analyze the synergistic and offset effects
from both environments on active BA. Based on
this framework, we introduce 2 case studies of
workplace reformation. In the case of Company X,
we describe the effective implementation of such
workplace reformation. In the case of Company Y,
we examine the results of a questionnaire survey
carried out at three different stages of theimplementation. Our results demonstrate thevalidity of our framework: (1) the effective
implementation of workplace reformation in bothCompany X’s Sales Department and Company Y’s
IT Department enabled the creation of active BA,
and was consistent with our framework; (2) the
influence of the physical and virtual environments
onto the creation and activation of BA weredifferent, thus justifying our assumption of thedivision of such environmental factors.

188

3.2 On-going projects
The previous paper is now published in theproceedings of the PACIS conference. The
comments and feedbacks from researchers andacademics during the presentation have enabled amajor revision of the paper with additional findings
for an attempted publication in an international
journal in 2006.
This revised paper is called “Workplace
Reformation, Active BA and Knowledge Creationfrom a Conceptual to a Practical Framework”.
Further analysis of the data collected during theinvestigations yielded new results leading to new
findings in the fields of knowledge management
and workplace reformations and to the developmentof a new practical framework.
Our data unexpectedly showed that the type of
workplace reformation, whether partial (virtualonly) or complete (virtual and physical), has an
influence on the resulting factors of BA, and thus
on the knowledge-creation process itself. In thisregard, the virtual-only workplace reformation
contributed to an increase in “Information Sharing”,
while the dual virtual and physical workplacereformation participated in more “Direct
Communication”.
4. Current research
The title of the current research project is“Organizational Characteristics as Prescriptive
Factors of Knowledge Management Initiatives” andcorresponds to the first year of the research plan.
4.1. Abstract
Organizational characteristics and their infinite
combinations make each organization unique andconsequently its need for Knowledge Management
System (KMS) distinctive. Based on previous
research (Simon, 1946, 1957; Nonaka and Takeuchi,
1995), it is argued that the range of organizational
characteristics gives rise to two contrasting
managerial models, “bureaucracy” and “taskforce”,
and that organizations usually adopt a position in
between.
This research proposes to identify theorganizational characteristics influencing thedecision to adopt and the nature of KM initiatives(H1). By surveying companies with offices in Japan,
the United States and France, this project also aims
at uncovering similarities and differences among
these countries on KM (H2 and H3).
4.2. Hypotheses and objectives
First, KM was redefined (H1, see 1.2)
according to the efficiency priority of theknowledge worker (Drucker, 2001).

Table1 Managerial goals andorganizational characteristics

Managerial
Goal
Rationalization
Regulation
Transmission
Channeling
Exploitation

round of short interviews by a group session(Table 3). These twelve semi-structured interviews
would consequently provide valuable informationon the matter being investigated, possibly yielding
complementary perspectives among countries anddifferent departments.

corresponding

Organizational
Characteristic
Knowledge type
Knowledge ownership
Communication
Structure
Purpose / Strategy

Table 3 Interview methodology
Sales
MarketingIT
All

Then, from these 5 managerial goals, 5organizational characteristics are inferred in orderto build the appropriate KMS addressing the KM
needs and characteristics of the organization. These
5 organizational characteristics are respectively:
knowledge
type;knowledge
ownership;communication; structure; and purpose or strategy(Table 1).

FranceF1F2
F3
F1+F2+F3

USA
U1
U2
U3
U1+U2+U3

4.4. Underlying research
The second stage of the research will focus on
testing Geert Hofstede’s (1980) leading research on
cultural dimensions in work-related values withfresh data.

Table 2 Range of organizational characteristics
Organizational
Characteristic
Knowledge type
Know. ownership
Communication
Structure
Purpose /Strategy

Japan
J1
J2
J3
J1+J2+J3

Table 4 Hofstede’s cultural dimensions
Range
Explicit
Individual
FormalVerticalDecisionmaking
Bureaucracy

Power
Distance

Tacit
Collective
InformalHorizontal

Individualism

Innovation

Masculinity

Taskforce
Uncertainty
Avoidance

The range of these organizational features gives
rise to 2 different managerial models (Simon, 1946,
1957; Nonaka and Takeuchi, 1995); the first one
called “bureaucracy”, builds on explicit knowledge,
individual
knowledge
ownership,
formalcommunication, vertical structure, and a decisionmaking strategy; the second one called “taskforce”,
draws on tacit knowledge, horizontal structure,collective
knowledge
ownership,
informalcommunication and an innovation strategy.
Businesses are rarely of one type or the other; theyrather emerge as a mix of characteristics ranging
between these 2 extremes (Table 2).
The purpose of this survey is to research the
key organizational characteristics influencing thedecision to adopt and nature of KM initiatives or
KMS.

Degree of equality or inequality insociety, tolerance for power disparity(from small to large)
Individual or collective achievement
and interpersonal relationships
Degree of traditional masculine workrole model with male achievement,
control, and power
Tolerance for uncertainty, ambiguity,
risk (from weak to strong)

Hofstede(1980)
conductedalarge
questionnaire survey between 1967 and 1973
among 40 local offices of IBM about culturaldimensions and his analysis yielded the following 4
main categories (later work produced an additional
dimension applicable only to Asian countries):
Power Distance (PDI), Individualism (IDV),
Masculinity (MAS), and Uncertainty Avoidance(UAI) (Table 4).
Once Hofstede’s model is established, aquestionnaire survey will be used to rate a sample
of international offices of global companies
according to the newly-developed KM framework(by knowledge type, knowledge ownership,communication, structure, and purpose/strategy)(H1). These 2 sets of data will provide the basis fora correlation analysis between Hofstede’s culturaldimensions and KM features (H2) (Table 5) andanalyze their perception regarding local KM
initiatives (H3). Figure 1 shows the scores ofFrance, Japan and the USA for the 4 culturaldimensions.

4.3. Methodology
We propose to survey the regional offices of a
global corporation in Japan, the United States andFrance to ensure consistency and representation
among “developed countries”. We will include ineach office one interviewee from sales, one frommarketing and one from IT and will conclude this189

Fig. 1. Scores for France, Japan and the USA in
Hofstede’s model

References

100
90
80
70
60
50
40
30
20
10
0
PDI

UAI
France

IDV
Japan

USA

Table 5 Potential correlations between Hofstede’s
cultural dimensions and new KM framework’sorganizational characteristics

Individualism
Masculinity
Uncertainty AvoidanceArmistead, C., Meakins, M., 2002. A Frameworkfor Practicing Knowledge Management. Long
Range Planning 35, 49-71.

[2]

Demarest, M., 1997. Understanding Knowledge
Management. Long Range Planning 30 (3), 374384.

[3]

De Souza, K., Evaristo, R., 2003. Global
Knowledge Management Strategies. European
Management Journal 21 (1), 62-67.

[4]

Drucker, P. F., 2001. The Essential Drucker: TheBest of Sixty Years of Peter Drucker’s Essential
Writings on Management, Harper Business.

[5]

Hofstede, G., 1980. Culture’s Consequences. Sage
Publications.

[6]

Hofstede, G., Hofstede, G. J., 2005. Cultures andOrganizations: Software of the Mind. McGrawHill.

[7]

Holsapple, C. W., Joshi, K. D., 2000. An
Investigation of Factors that Influence theManagement of Knowledge in Organizations.
Journal of Strategic Information Systems 9, 235261.

[8]

Kankanhalli A., Tan B.C.Y., Wei K., Holmes M.C.,
2004. Cross-cultural Differences and Information
Systems Developer Values. Decision Support
Systems 38, 183-195.

[9]

Kelloway, E. K., Barling, J., 2000. Knowledge
Work as Organizational Behavior. International
Journal of Management Reviews 2 (3), 287-304.

MAS

Source：Hofstede, G., 1980. Culture’s Consequences:
International Differences in Work-Related
Values. Sage Publications, Inc.

Hofstede’s
Dimensions
Power Distance[1]

KM Framework
Structure
Knowledge
Ownership
Communication;
Knowledge type
Purpose (strategy)

5. Conclusion
This research fits with the broader objectives of
the Science of Institutional Management ofTechnology (SIMOT) where national culture
belongs to the “informal (but no less real)constraints” recognized by Douglas North (1994) in
his definition of institutions.
The main hypothesis being examined in thisresearch states that national cultures are sources ofregional differences in organizational characteristics
and consequently, in KM initiatives. As previous
research showed, management and leadership
cannot be isolated from other parts of society andthey are subsequently a direct result of national
culture, defined as a stable collective phenomenon
embedding social rules governing the behavior of agroup of individuals (Hofstede and Hofstede, 2005).
In this regard, institutions and culture have thesame features (Hofstede and Hofstede, 2005;
Tolbert and Zucker, 1996) of (1) social purpose, (2)permanence, (3) transcendence over a group ofindividuals and (4) creation and enforcement of its
own rules. Therefore, this research is equivalent toinvestigating the institutionalization of knowledge
management from a national culture perspective.

190[10] Nonaka I, Takeuchi H., 1995. The KnowledgeCreating Company: How Japanese Companies
Create the Dynamics of Innovation. Oxford
University Press.
[11] Polanyi, M., 1966. Tacit Dimension. Peter Smith.
[12] Rubenstein-Montano, B., Liebowitz, J. Buchwalter,J., McCaw, D., Newman, B., Rebeck, K., The
Knowledge Management Mehodology Team, 2001.
A Systems Thinking Framework for Knowledge
Management. Decision Support Systems 31, 5-16.
[13] Simon H. A., 1946, 1947, 1957,
Administrative Behavior. Free Press.

1976.

[14] Tolbert P. S., Zucker L. G., 1996. The
Institutionalization of Institutional Theory.
Handbook of Organizational Theory, pp175-190,
Sage.
[15] Von Krogh, G., Nonaka, I., Aben, M., 2001.
Making the Most of your Company’s Knowledge:
a Strategic Framework. Long Range Planning 34,
421-439.

Organizational Characteristics as Prescriptive Factors ofKnowledge Management Initiatives
Remy Magnier-Watanabe**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-527 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
remy@ml.me.titech.ac.jp
The use of knowledge in organizations is largely a discretionary behavior that can be
encouraged but not demanded. As such, the firm can only attempt to provide the rightconditions for employees to endorse the role of knowledge workers. This research
proposes a new framework showing the prescriptive role of organizational characteristics
onto Knowledge Management (KM) initiatives. Based on this framework, the case study ofan international pharmaceutical company is presented as qualitative support to the
hypothesis that the organization’s structure, membership, relationship, and strategy affectknowledge acquisition, sharing, diffusion, and application respectively.
Table 1: Organizational characteristics as prescriptive
factors of Knowledge Management initiatives

1. Introduction
The use of knowledge in organizations islargely a discretionary behavior that can be
encouraged but not demanded by organizations andtheir management (Kelloway and Barling, 2000).
As such, the firm can only attempt to provide theright conditions and enhance the employees’ ability,
motivation and opportunity in order for them toendorse the role of knowledge worker.
Many frameworks or strategies to implement
Knowledge Management (KM) have beententatively developed in previous research(Holsapple and Joshi, 2000; Rubenstein-Montano etal., 2001; von Krogh et al., 2001; Armistead andMeakins, 2002), however, few have focused on a
possible link between the firm’s organizational
characteristics and KM. The framework introduced
here acknowledges the strong role of managementin the firm’s handling of knowledge and attempts tooperationalize the findings of a case study andmake them readily usable by practitioners.

Org. Characteristics
Vertical
Structure
Horizontal
Individual
MembershipCollective
Systematic
Relationship
Ad-hocReactive
StrategyInnovative

KM Value-Chain
FocusedAcquisition
Opportunistic
Selective
Sharing
Inclusive
Prescribed
Diffusion
Adaptive
Exploitative
Application
Explorative

For example, the acquisition (and/or creation)of knowledge in the organization will greatly
depend on its structure, knowledge sharing on its
membership attribute, knowledge diffusion on its
relationship pattern, and knowledge implementation
on its strategy.
Each organizational characteristic can bedepicted as adopting mostly one form or another,based on the qualitative and quantitative
distribution of its constituents. For instance,
structure can be either vertical or horizontal;
membership, individual or collective; relationship,
systematic or ad-hoc; and strategy, reactive or
innovative. Each of these 8 attributes oforganizational characteristics promotes a specificfeature of the KM value-chain: vertical (horizontal)
structure
supports
focused(opportunistic)
knowledge acquisition; individual (collective)
membershipsupports
selective(inclusive)
knowledge
sharing;systematic(ad-hoc)
relationshipsupports
prescribed(adaptive)knowledge diffusion; reactive (innovative) strategy
supports exploitative (explorative) knowledge
application.
This definition of KM is consistent with theknowledge value-chain approach common to many
KM descriptions (Shin et al., 2001) and the2. Theoretical Framework and Hypotheses
Knowledge Management is the process foracquiring, sharing, diffusing and implementing both
tacit and explicit knowledge inside and outside theorganization’s boundaries with the purpose ofachieving corporate objectives in the most efficientmanner. As KM is most effective when tightly
integrated within the organization’s processes,organizational characteristics greatly determine therelevant types of KM initiatives and shape thefirm’s KM policy. As a result, strategic alignment isensured by the congruence of each step of the KM
value-chain with the organizational characteristicsof the organization (See Table 1).

191efficiency priority of KM within the organization(Alavi and Leidner, 1999; Drucker, 2001). The KM
value-chain mirrors the knowledge-creating view ofthe firm, which defines knowledge as a process ofjustifying belief toward the truth (Nonaka and
Takeuchi, 1995).

that one subscribes to the values, policies orobjectives of the group, since, at least contractually,
one is free to withdraw if an impossible conflictarises. Membership is a subjective social factor thatcan be expressed objectively when examining thesystem of incentives and rewards, the disseminationof best practices and corporate vision across thewhole firm, and the duration of initial training.
Membership can be either collective or
individual, depending on whether the employee
identifies with one (or several) team(s) or doesn’t
recognize his or her interests in those of the group.
A person identifies him or herself with a groupwhen, in making decisions, he or she evaluates theseveral alternatives of choice in terms of theirconsequences for the specified group. Collective
membership ensures that the decisions that an
employee makes as a member of an organization
are consistent with its personal decisions (Simon,
1976).
When membership is individual, knowledge isconsidered as a tool for personal achievement andan output of the organization for the benefit of theemployee. When membership is collective,knowledge is seen as benefiting both theorganization and the employee and is perceived asboth an input and an output of the organization to
the employee and reciprocally. In the same
perspective, knowledge is considered to be“owned” by the individual in the case of individual
membership, and by the organization in the case ofcollective membership. When knowledge isindividually owned, it is seen as a source of
personal competitive advantage and as a resource
worth trading, leading to selective knowledge
sharing within the organization. When knowledge iscollectively owned on the other hand, it isconsidered as a source of both organizational andpersonal competitive advantage and as a resource
worth disclosing as every worker is trusted to do,
prompting to inclusive knowledge sharing within
the company. This organizational characteristic is
deeply rooted in the culture of the organization andis consequently not easily changed.

2.1. Structure and Knowledge Acquisition
Most organizations can be classified as either
vertically or horizontally structured. Some aspectsof vertically-structured organizations include
specialized tasks, a strict hierarchy with many rules,
vertical communication and reporting systems, few
teams or task forces, and centralized decisionmaking. On the other side of the spectrum,
horizontal structure involves shared tasks andempowerment, a more relaxed hierarchy with fewer
rules, horizontal face-to-face communication, moreteams or task forces, and decentralized decisionmaking (Ranson et al., 1980). These specificfeatures lead to different benefits: control,
efficiency, stability, and reliability in the former;
coordination, change, learning, innovation, andflexibility in the latter. The nature of the verticalstructure emphasizes depth, while that of thehorizontal one stresses breadth. There areadvantages to both types of organization eventhough the vertical one may have a higher cost
(Simon, 1976).
Knowledge acquisition is the process of gaining
new knowledge, from either inside or outside theorganization. Even though acquisition supposes thatknowledge already exists and is brought in fromanother location, the fact that this already-existingknowledge becomes part of the organization gives it
the status of new knowledge inside the firm. To
some extent, knowledge creation is the acquisitionof knowledge from within the organization, whileknowledge addition is the acquisition of knowledge
from outside the organization. As the difference
between knowledge creation and acquisition is not
the focus of this paper, both will be usedinterchangeably. Knowledge acquisition is a social
process that occurs between individuals (Nonaka
and Takeuchi, 1995) where the role of theorganization is to provide the proper contexts orsituations for knowledge acquisition to occur
according to the corporate objective.
As a consequence of structure, the knowledge
gained or acquired in each type of organization ismuch different as it is restricted in breadth in thevertical organization, whereas it is limited in depth
in the horizontal one.

2.3. Relationship and Knowledge Diffusion
The organization needs to identify these
relationships
makingup
thecompleteorganizational communication network in order tocapture the knowledge being transmitted.
Relationships within the firm can be of two types,
systematic or ad-hoc. One visible determinant ofrelationships is the use of taskforces tailored totackle specific issues. These customized teams
bring people from different backgrounds and areas
together, enabling a potentially richer andopportunistic cross-pollinization.
On the one hand, formal organizations provide
a set of written rules leaving very little discretion so

2.2. Membership and Knowledge Sharing
The concept of membership whereby theworker is a member of the firm, deals with theextent to which the employee feels part of thatorganization. To belong to an organization implies192

as to the choice of communication partners
throughout the company. On the other hand,
informal organizations leave a large degree of
autonomy to its workers to decide which
communication channel and recipient fit best therequirements of each situation.
In addition, work conditions influence theoccurrence of spontaneous relationships, not always
necessarily motivated by an underlying businessagenda. For example, the break room is much morethan a simple coffee machine spot since it brings
people from different departments and ranks
together, provided that such interactions are madepossible. These enabling factors of communications
can either be physical, embodied in the workplacelayout, or even virtual, using direct contacts by wayof telecommunication networks (phone, Internet).
The nature of these relationships influences the
diffusion of knowledge, where systematic
relationships trigger a prescribed diffusion ofknowledge, while ad-hoc relationships produce anadaptive diffusion of knowledge. The former uses
predetermined routes based on the establishedhierarchy, while the latter arises from changes incommunication paths due to personal relations
between coworkers based on the needs of the
moment.
Diffusion deals with efficient knowledge flows,which may or may not be a priori embedded within
theorganization’s
patternofsystematic
relationships as defined in the corporate
communication routes and nodes. Even ifconnections may naturally develop based on
individual affinity and initiative, the organization
itself can proactively create relationships between
those apt at becoming productive senders or
receivers. The purpose of knowledge diffusion is toconsolidate and make any knowledge available toand useable by all relevant members of theorganization. This is especially true when theorganization uses adaptive work configurations(transversal or ad-hoc teams) to match therequirements of punctual but crucial projects. Since
these teams do not necessarily match thearrangement of predefined systematic relationships,
the knowledge having been created may end up
getting lost upon completion of the project (Lost
Knowledge book), loosing any chance of further
return (on investment) or diffusion.
As previous research showed (Wenger et al.,2002), firms who encourage social interactions,
whether formal or informal, increase opportunities
for adaptive knowledge diffusion along ad-hoc
networks. Also, it is important to note that the
diffusion of knowledge depends more on the
purpose and motivation of the preceding
relationship than on the nature of knowledge,
whether tacit or explicit, as relationships aid toknowledge conversions optimizing for the relevant
type of knowledge.
2.4. Strategy and Knowledge Application
Strategy is the carefully devised plan of action
to efficiently achieve a corporate goal, consideringthat efficiency is the attainment of maximum value
with limited means. Organizational decisions follow
a strategy, itself carrying expectations drawn fromknowledge. The role of knowledge is to increase thefirm’s rationality, which involves knowing all theconsequences following from each alternative
strategy and comparing all the potential outcomes(Simon, 1976). This quest to overcome bounded
rationality makes knowledge central, not only indiscovering all the consequences of all possible
alternatives, but also in identifying the alternatives– or strategies - firsthand.
Strategies can broadly be categorized in 2 types,
either offensive or defensive, based on the positionof the firm among its competitors and leading to theidentification of leaders and followers. On the one
hand, the purpose of an offensive strategy for an
early mover is to create a sustainable competitive
advantage (Porter, 1990) that is made possible only
if the organization is ahead of its competition, or inother words, if it addresses a common problem
differently through innovation. On the other hand,
the goal of a defensive strategy for a late mover is
to maintain its position while reacting to its
competitor’s moves, usually imitating the industry
leader and hoping to benefit from its success. Inturn, these two opposite strategies can be qualified
of innovative versus reactive, as knowledge is usedin contrasting ways. Compared to reactive strategies,
innovative strategies tend to be self-avowed and aresupported by greater autonomy, job rotation andtaskforces in order to overcome a higher
competitive intensity.
A reactive strategy exploits existing knowledge,
whether it is the organization’s own or anothercompany’s. Exploitation refers in this case to the
productive use of existing knowledge to efficiently
execute the organization’s strategy conforming topractices already tried and true. An innovative
strategy uses an explorative approach to knowledge
application in order to compete in a new or
improved way, yielding new knowledge apt at
producing a new competitive advantage ormaintaining an existing one. The merits of
exploitative knowledge application are the lower
cost of imitation and the reduced level of
uncertainty of using a tested approach. The benefits
of explorative knowledge application are those ofearly movers in terms of economies of scale, brandrecognition, minimum competition and cumulative
learning.
As previous research showed, knowledge, as ahigh-value form of information ready to be applied193

to decisions and actions (Davenport et al., 1998)
has become the primary tool of the organization in
determining its strategy. Consequently, the first 3
organizational
characteristics,
structure,membership, and relationship, support andconstrain at the same time the strategy of thebusiness. For that matter, the selected strategy
should help management adapt the characteristics ofthe organization in the pursuit of its goals. The KM
value-chain reflects this dependency where theacquisition, sharing, and diffusion of knowledge
affect its potential application, which should be thestarting point of a KM initiative.

department, and retained people from top
management, middle management, and front linewith a direct hierarchical link between them.
As a result, a total of 9 semi-structured
interviews were conducted with Eisai employees
holding positions of Sales Director, District
Manager, an Medical Representatives, in English(with an interpreter in Japan), on location, between
November 2005 and March 2006, each lasting
about 90 minutes and being later manuallytranscribed by the interviewer.
3.2. Organizational Profile
The first step in applying the framework to thecase study is to determine the organizational profile
of Eisai. In order to position the firm according toeach organizational characteristic, a Boolean
approach suitable to qualitative comparison was
adopted (Ragin, 1987). This method uses binary
data representing the two conditions of Boolean
algebra where 1 indicates presence (True) and 0
indicates absence (False), and matches theoutcomes to truth tables used as references.
From the previous discussion about theconstruction of the theoretical framework, four
variables were identified for each organizational
characteristic (See Table 2).

3. Case-Study
3.1. Sample selection and data collection
As a qualitative comparative method is well
suited for addressing questions about outcomes
resulting from multiple and conjectural causes, acase-oriented approach was selected (Ragin, 1987).
Eisai is a global pharmaceutical corporationthat can be qualified in its industry as a medium
size company with yearly sales of about 5 billion
USD (FY2005) covering both prescription andover-the-counter drugs. Eisai is active primarily inthe fields of neurology with Aricept, a treatment for
mild-to-moderate
Alzheimer's
disease,andgastroenterology with Pariet/Aciphex, a proton
pump inhibitor for the healing of erosive gastroesophageal reflux disease and duodenal ulcers.
Eisai’s global corporate mission is to be a “humanhealthcare company” or “hhc”, where employees
give their first thoughts to patients and theirfamilies and contribute to increasing their benefits.
As the investigation of organizational
characteristics may be potentially affected byregional cultures, the study is focusing on
culturally-diverse locations where Eisai has
research centers in addition to traditional sales
activities. As a result, this survey is covering Eisai
offices in the United States, the United Kingdom
and Japan.
When comparing qualitative data, it isnecessary to prevent bias by tightly matching thequalitative samples. In this research project,consistency was thoroughly built into the selectionof the sample by identifying national culture,
department activity, product or service, andhierarchical position as key elements for reliable
qualitative assessment. Only local nationals fromthe Japanese headquarters of Eisai as well as its
American and British regional offices were
included, as perceptions of organizational
characteristics may be different across cultures; thesurvey focused in all 3 locations on the sameprescription
drugmarket(Aricept
andPariet/Aciphex), the same sales and marketing

Table 2: Binary variables for determining organizational
characteristics
Structure
STC1
STC2
STC3
STC4

Shared tasks
Horizontal communication, relaxed hierarchy
Decentralized decision-making
Many teams or task forces

Relationship
REL1
REL2
REL3
REL4

Informal communication
Physical communication enablers
Virtual communication enablers
Many teams or task forces

Membership
MEM1
MEM2
MEM3
MEM4

Collective incentives and rewards
Sharing of corporate vision
Sharing of best practices
Training duration

Strategy
STY1
STY2
STY3
STY4

Self-avowed original strategy
Autonomy
Job rotation
Many teams or task forces

Truth tables establish an outcome following
different conditions; here only the truth table related
to “structure” is shown (See Table 3). For example,
when looking at the structure’s alternative #12, theexistence of shared tasks and horizontal
communication and the absence of decentralized
decision-making and various teams or task forces
produce a more vertical-type of structure, as
opposed to an horizontal one. These truth tables

194were constructed by the researcher and checkedagainst the qualitative assessment of a seasoned
associate professor in the department of Industrial
Engineering and Management. The assessment of
each
organizational
characteristic’s
binarycondition (presence or absence) was determinedbased on the detailed transcripts of the 9 interviews.

StructureMembership
Relationship
Strategy

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16

STC1
0
0
0
0
0
0
0
0
1
1
1
1
1
1
1
1

JP
VerticalCollective
Ad-hocInnovative

3.3. Knowledge Management Profile
3.3.1. Knowledge Acquisition
Across the 3 offices, front-line medical
representatives (MRs) perform relentlessly the same
type of activities, making daily visits to targets
while providing relevant information about the drug
they market. Despite a few differences mostly
stemming from local regulations– US and UK MRs
also meet with patients and distribution partners’
counterparts, while Japanese MRs probe drugs
wholesalers and pharmacists – they always interact
with the same parties and are only familiar with one
aspect of the doctor-drug-patient relationship. Also,
the activity of sales is rather focused and intensive
and requires MRs to keep visiting their customers
to maximize brand exposure, continuously pushingback the attacks of competitors, and providing thelatest clinical trial information.
As a result, the knowledge acquisition of all 3
offices can be labeled as focused rather thanopportunistic.
3.3.2. Knowledge Sharing
Recruitment and training practices greatly
influence the sharing of knowledge. On the one
hand, the US and UK offices tend to mostly recruit
seasoned medical representatives with years ofexperience working with competitors, subsequently
minimizing the time and cost of training thatusually lasts less than 3 weeks. On the other hand,
the Japanese headquarters seek highly-motivated
new graduates with no previous experience andspend 6 months training them, with the first 5
months in the office at headquarters with rotations
in different departments. The Japanese approach isconsistent with the (now declining) lifetime
employment model where employer trades
extensive skills training for loyalty. However,American, English and Japanese MRs are mostly
rewarded financially according to their personal
performance.
As the US and UK offices are not equippedwith a centralized knowledge sharing tool, field tips
and best practices are not shared across the sales
department but generally communicated from the
MR to the district manager who forwards them tothe sales director if deemed valuable enough.
Sometimes, the MR may also call his or her

Outcome
STC4
0
1
0
0
1
0
1
1
0
1
0
0
1
0
1
1

UK
VerticalIndividual
Ad-hocInnovative

The next step is then to examine the KM profile
of each office according to the 4 steps of the KM
value-chain presented in the framework. To do so, athorough qualitative analysis of the interview
transcripts yielded the following findings.

Table 3: Truth tables for the “structure” organizational
characteristics; STC outcome: 0= verticalstructure; 1= horizontal structure
Conditions
STC2
STC3
0
0
0
0
0
1
1
0
0
1
1
1
1
0
1
1
0
0
0
0
0
1
1
0
0
1
1
1
1
0
1
1

US
VerticalIndividual
Systematic
Reactive

0
0
1
0
1
1
0
1
0
0
1
0
1
1
1
1

From the 3 opinions provided by the topmanagement, middle-management, and front-line
employees working in a direct chain of command,the organizational profile of their office wasdetermined by taking the “majority” of their views,
considering that each employee’s opinion had anequal weight. For example, since in the UK office,both top and middle management employees’interviews supported an individual style ofmembership, whereas only the front-line
employee’s indicated a collective one, the office isconsidered as a whole to have an individual style ofmembership.
The results of the Boolean approach show that
despite belonging to the same organization, the 3regional offices display different organizational
characteristics (See Table 4). This diversity allowed
a complete exploration of the possibleorganizational characteristics combinations, withthe exception of the first characteristic where all 3
offices display a vertical structure. Then, the US
and UK entities show an individual membershipcompared to a collective one in the Japaneseheadquarters. Last, the US bureau exhibits
systematic relationships and a reactive strategy,
while the UK and Japanese workplaces
demonstrated ad-hoc relationships and an
innovative strategy.
Table 4: Organizational profile of each office

195

teammates with a tip, but it rarely gets sent to otherregional sales teams.
Conversely, Japanese MRs must fill out an online database of tips, best practices andsuccess/failure stories at least twice a month; thattool is dutifully read by the whole salesorganization, from the regional director, to otherMRs, contributing to knowledge being seen as bothan input and an output. Employees rate each tip
with “thank you points” when considered valuable,
and medical representatives take pride in achieving
high “thank you ratings” from other co-workers.
Subsequently, the knowledge sharing of the US
and UK offices can be identified as selective, whilethat of the Japanese headquarters as inclusive.
3.3.3. Knowledge Diffusion
In the 3 offices, MRs use a centralized system,
however different, to input the details of their day’s
visits, including the doctors’ references, the topics
discussed and the objectives for the next visit. Then,as MRs and district managers in the US and the UK
work from home, they spend most of their time on
the road and rarely come into the office andtherefore have few opportunities for interactingwith other departments employees.
On the contrary, Japanese MRs have their own
desk in the office and are seated in front of theirdistrict manager, without partitions, in the sameroom as the regional director. They come to theoffice at least once in the day and favor face-to-faceencounters to email exchanges, having theopportunity to meet coworkers from otherdepartments as well. Also, as a centralized salesrelated knowledge sharing tool exists with amonitored usage, knowledge is ensured diffusion to
those who need it most.
Even though English MRs don’t go to the officeevery day, Eisais’s “hhc” mission encourages themto take initiatives; when recently launching a new
epilepsy drug in their market, a group of MRsarranged (and were allowed) to sit during patients’consultations at a local clinic. This project allowed
them to build new relationships and top
management is now considering making thatexperience mandatory for other sales teams.
Accordingly, the knowledge sharing of the US
branch can be classified as prescribed, while that of
the UK and Japan as adaptive.
Yet, it should be noted that because the numberof representatives under the interviewed topmanagement sales executive differed greatly for the
US office, (5 times that of the Tokyo office and 25
times that of the UK subsidiary), the pattern ofknowledge diffusion may be compartmented to
avoid information overload and irrelevant
knowledge-sharing. Hence, diffusion of knowledge
is mostly achieved using group voice mail withineach team.

196

3.3.4. Knowledge Application
The “hhc” corporate mission is wellcommunicated and known by all interviewees
across the three countries. However, only in the UK
and Japan does that corporate vision also translate
into concrete actions recognized by the topmanagement and clearly taken into account as partof their job evaluation. In the UK and Japan, as atask considered in their job evaluation, medical
representatives must contribute by participating to“hhc awards” improving the life of patients, in linewith the company’s corporate vision.
For example in Japan, a team of representatives
found out after meeting with a group of pharmacists
that one of their drugs was rather difficult to drink
and was able to benefit from tips shared by patientswith those pharmacists; these tips were later sharedthrough the corporate knowledge-sharing databaseand are now being used during most doctor visitsconcerning that drug. In the UK, a team has createdan album where Alzheimer’s patients can record
their memories as it is sometimes difficult for caregivers or visitors to find discussion topics; also, if
patients are moving to a different institution,
albums can assist in showing the receiving medical
staff the personality or the type of person they were
before and in making them appear as living humanbeings.
On the contrary, most pharmaceuticalcompanies in the US rely on doctor-specificprescription drug data that is purchased and updated
monthly and enables MRs to follow to keep a close
eye on the “writing levels” of their targets. US MRs
have less incentive to take initiatives in order tolearn more about their market as doctor-specificprescription drug data is sometimes considered as
the ultimate business indicator and tool.
Therefore, the knowledge application of the US
office can be seen as exploitative, while that of the
UK and Japan as explorative.
3. Findings
The case study of the sales department of Eisai
across the US, UK and Japan yielded significant
results supporting the proposed framework.
In every case, vertical structure induced focusedknowledge acquisition, individual and collective
membership selective and inclusive knowledge
sharing respectively, systematic and ad-hoc
relationships prescribed and adaptive knowledge
diffusion respectively, and reactive and innovative
strategy exploitative and explorative knowledge
application respectively.
However, because this case study focused onsales organizations which are typically verticallystructured, there was no sufficient qualitative data
to reliably validate the relation between horizontal
structure and opportunistic knowledge acquisition.

One can only assume here that since horizontal
structure emphasizes breadth rather than depth inthe organization, workers have more autonomy andcan therefore gather knowledge from uncharted
sources.

Knowledge in Organizations, Journal of Strategic
Information Systems 9, 235-261 (2000).

4. ConclusionThisframework
linking
organizational
characteristics to KM initiatives has received a firstjustification using a case-study approach and aqualitative comparative method. As such, thefindings of this research can already be useful topractitioners so as to optimize the organizationalfeatures of sub-teams and obtain the desired KM
practices.
However, in order to conclusively validate thecausal link between the firm’s features and KM, aquantitative analysis using larger data sets drawn
from questionnaires is needed. Subsequently, future
research will focus on investigating a more generalapplication of the framework using a variableoriented approach.
Also, as differences emerged in the regional
branches of a same company, another avenue forresearch may consider whether national culture hasa unifying influence over organizational
characteristics and KM attributes. As institutions
and culture have the same features (Hofstede andHofstede, 2005; Tolbert and Zucker, 1996) of social
purpose, permanence, transcendence over a groupof individuals and creation and enforcement of its
own rules, this research is equivalent toinvestigating the institutionalization of knowledge
management from a national culture perspective.

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197

The Effect of Consistent Knowledge Management Behaviors
on Competitive Advantage
Rémy Magnier-Watanabe**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-527 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANmagnierwatanabe.r.aa@m.titech.ac.jp
While Knowledge Management (KM) has been shown to be a strategic source ofcompetitive advantage (CA), processes designed at enhancing the productivity ofknowledge do not however equally contribute to the organization’s capabilities.
Consequently, this research, using data collected from the entire population of a firm’s
personnel, focuses on the relationship between each mode of the KM process onto multiple
CAs, and investigates how different perceptions and behaviors on KM affect those CAs.
Preliminary results show that the perceived importance of KM appears as an importantsource of ‘technical competitive advantage’, and that more time spent on KM activities
contributes to an ‘affective competitive advantage’. Further analysis involves a taxonomyof employees based on their perceived importance of and the time they spend on KM.

processes between tacit and explicit knowledge Socialization, Externalization, Combination, andInternalization, or SECI - help synthesize subjective
values into objective and socially shared knowledge(Figure 1).

1. Introduction
In the field of Business Administration, theparadigm where organizations are regarded as
centers of information processing has begun to shift
to the paradigm where organizations are regarded assources of knowledge creation [1] and wherelearning has become a key construct defined interms of outcomes and processes [2]. The premiseof the "knowledge creation theory" based on thisparadigm is the supposition that all knowledge canbe classified in either "tacit knowledge" [3] or“explicit knowledge”. On the one hand, tacitknowledge is cognitive knowledge and is hard to
express with language or numbers: for example,
beliefs, points of view, technical skills and knowhow are all part of tacit knowledge. On the other
hand, explicit knowledge is objective and rational
knowledge and can be expressed with language or
number: texts, equations, specifications andmanuals are a few examples.
This paper describes in section two thetheoretical foundation and hypothesis of thisresearch. Then, section three presents themethodology of the questionnaire survey followedby the data analysis in section four. Section fiveincludes a discussion of the study’s findings andsection six concludes the paper.

Figure 1: The SECI model

The knowledge-creation process starts withsocialization where the tacit knowledge ofcustomers and competitors is acquired through fieldbuilding. That knowledge is then externalized
through dialogue into explicit knowledge to beshared within the firm. Next, the explicit knowledge
is in a form appropriate to be diffused throughout
the organization and combined with other existingknowledge. Subsequently, the firm’s workers
internalize these complex sets of explicit knowledge,
and then determine the most favorable application
to be put in action. The multiple ontological levels individual, group, and organization - of thecompany enable the creation of an organizational
knowledge-creation spiral.

2. Background and Hypothesis
2.1 Knowledge-Creation Theory
In the knowledge-creating view of the firm,knowledge is defined as a process of justifying
belief toward the truth [4]. The conversion

198

Thus, when an organization is considered asource of knowledge creation, the promotion of theknowledge-creation process expressed by the SECI
model becomes an important part of theorganization’s management.
The objective of this paper is first to examine
how each mode of the KM process affects thefirm’s CAs, and then to identify the relationshipbetween identified sub-groups of workers and CAs.
Finally we will discuss the implications for practiceof such taxonomy.
2.2 Hypothesis
As knowledge management is intended to help
improve the organization’s efficiency, it can also
contribute to the creation of competitive advantages.
In this regard, we explore how the employees’
opinions about their perceived importance of andthe time spent on SECI affect how they rate thecontribution of several business practices, making
no prior assumption on the existence or strength of
the relationships between SECI modes and CAs(Figure 2). This approach is preferred to a bivariate
correlation analysis between each step of SECI andeach CA as there is no a priori hypothesis on thecovariance among the 4 modes of SECI.
Figure 2: Structural model exploring
the relationship between KM and CA
Perceived
importance /Time Allocation

Competitive
advantage

Socialization

Experiential
knowledge

Externalization

Conceptknowledge

Combination

Systemknowledge

Internalization

Culturalknowledge

Knowledge Management from several Japanese
National Universities.
We are using here the data of JPC’s entire
workforce in Japan, or 1,330 people and arefocusing on the relationship between knowledge
management (SECI) and competitive advantage(experience, concept, system, and culture). The
questionnaire uses a 5-point Lickert scale. The
knowledge management section uses tested
questions from established research and includes 6questions for each of the 4 modes of the SECI
process; each question asks for both perceived
importance and time allocation, thus making up a
total of 48 variables. 11 questions in the survey
addressed how employees perceived thecontribution of certain behaviors, processes, or
instruments at work. Those questions were designed
to encompass 4 types of knowledge properties,
including experience, concept, system and culture.
Experience knowledge items addressed individual
skills and know-how, respect and trust, enthusiasm
and competitive spirit, and frequent knowledge andexperience sharing; concept knowledge items dealt
with concerns for quality, the company reputation,and intellectual property; system knowledge items
tackled policies and procedures, and internal
databases; and cultural knowledge items
concentrated on corporate culture including mission,
vision, and values.
4. Analysis
4.1 Introductory statistics
The data shows that some type of balance has
been achieved among the 4 modes of SECI since
the mean of both perceived importance and time
allocation scores, around 3 on the 5-point Lickert
scale, appear uniform across all 24 questions(Figure 3).
This indicates that the respondents equallyvalue the 4 modes of SECI. However, as SECI’s
perceived importance ranked consistently higher
than its time allocation, we can infer that eventhough respondents know SECI is important, they
don’t spend as much time as they think is necessary.
The standard deviation across all 24 questions (notshown) ranges from 0.8 to 1.2 and, similarly to themean, both variables closely follow each other.
Let’s now look at correlation scores between
the perceived importance of SECI and competitive
advantage. They turned out to be significant(p<0.01 or p<0.05) and to display similar patterns
across each of the 4 modes of SECI – S, E, C, and I(Figure 4).
One question on the experience knowledge
property (Q313) - dealing with knowledge andexperience sharing among employees advantage displayed a much higher correlation with SECI than

3. Methodology
The analysis is using questionnaire data from aJapanese pharmaceutical corporation that can bequalified in its industry as a medium size company
covering both prescription and over-the-counter
drugs. As the organization prefers to remain
anonymous, we will refer to it as JPC (JapanesePharmaceutical Corporation).
JPC recognized the value of KM early on andconducts frequent surveys of its entire global
workforce covering topics such as knowledge
management behaviors and competitive advantage.
The survey has been developed over many years
with the collaboration of several professors of199

the others, with coefficients ranging from R=0.293(p<0.01) with externalization to R=0.332 (p<0.01)
with internalization.

knowledge property among the 4 competitive
advantages investigated here.
While the correlation scores of SECI’s time
allocation with competitive advantages appear
consistent across all 4 SECI dimensions, they tend
to be lower than those with SECI’s importance withno value above R=0.253 (p<0.01). Nevertheless,correlations with questions on the experienceknowledge property (Q306 and Q307) ranked
consistently higher overall (R=0.253 and R=0.240
with S, p<0.01). As a result, more time spent on
SECI activities (socialization in particular) benefits
the experience knowledge property.
These correlation scores show that SECI’s
importance and time allocation primarily affect thecompetitive advantage related to experienceknowledge.

S
I
I

3.5

S
S

3

I

S

2.5
2

I

S

1.5
1

I

S

0.5
I

E

0

C

E
C

E
C

4.2 Factor analysis and regression model
A factor analysis of the dependant constructs
was carried out to ensure that all 11 questions
measuring each competitive advantage displayed
higher loadings on the intended construct rather
than on the other ones. The factor analysis revealed
that in fact, the questions on competitive
advantages could be grouped into 3 factors different
from the intended constructs (Table 1).

E
C

E
C

E
C

Mean "Time Allocation"
Mean "Perceived Importance"

Figure 3: Mean of SECI’s perceived importanceand time allocation questions

Table 1: Rotated Component Matrix of theprincipal-component analysis of the CA questions
Component
1
2
3
Q305
.750
Q306
.738
Q307
.788
Q308
.484
Q309
.508
Q310
.702
Q311
.702
Q312
.638
Q313
.753
Q314
.580
Q315
.503

The next highest correlation was also withanother experience knowledge property question(Q305), with a score of R=0.256 (p<0.01).
Q305
0.350
Q315

Q306

0.300
0.250
0.200

Q314

Q307

0.150
0.100
0.050
0.000

Q313

Q308

Q312

The loadings show that, unlike previously
designed, there were 6 questions in factor 1, 3 infactor 2 and 2 in factor 3. Factor 1, with higher
loadings on questions Q310, Q311, and Q312
corresponds to embedded knowledge available inwritten documents, databases, and intellectual
property. Factor 2, with higher loadings onquestions Q306 and Q307 is consistent withaffective knowledge found in love, care and trust,and the employees’ enthusiasm and competitive
spirit. Factor 3, with higher loadings on questions
Q305 and Q313, clearly contributes to technicalknowledge related to technical skill and shared

Q309

Q311

Q310

SOCIAL_IMPORT

EXTERN_IMPORTCOMBIN_IMPORTINTERN_IMPORT

Figure 4: Correlation radar graph of SECI’s
perceived importance with each question on CA

As a result, we can safely say that those who
found SECI important also ranked the experienceknowledge property as important. In other words,
SECI appears as the best predictor of experience200

know-how. The results of the factor analysis bringus to revise our structural model and change the 4
CAs into the 3 factors defined above.
We first performed a multiple regression
analysis with SECI’s perceived importance as
independent variables and the 3 CA constructs
extracted from the principal-component analysis(Figure 5).
Perceived
importance of:Competitive
advantage

Socialization

Embeddedknowledge
R² = 0.007

Externalization

Combination

B=0.123

B=0.092
B=0.178

Internalization

B=0.121strongest effect on affective knowledge andexternalization the weakest.
Time Allocationof:Competitive
advantage

Socialization

Embeddedknowledge
R² = 0.035

B=0.151
Externalization

Combination

B=0.084
B=0.093
B=0.136

Affectiveknowledge
R² = 0.015

Internalization

Affectiveknowledge
R² = 0.122
Technical
knowledge
R² = 0.001* p < 0.01

Technical
knowledge
R² = 0.170

Figure 6: Graphical summary of results for the time
allocation of SECI and CA

Consequently, more time spent on SECI, in
particular socialization, appears as the mostimportant source of affective knowledge CA.

* p < 0.01
Figure 5: Graphical summary of results for theperceived importance of SECI and CA

4.3 Taxonomy of workers toward KM
As aggregate statistics only give the big picture,
we decided to divide the population into ataxonomy based on the respondents’ perceived
importance and time allocation of SECI. We
grouped the answers on SECI’s perceived
importance together and calculated the mean of the
24 scores for each case; we simultaneously did thesame for the answers on SECI’s time allocation.
Clusters were made according to the mean of each
respondent’s aggregate score for SECI and labeled
as follow.
When the mean of the respondent’s aggregate
score on SECI’S perceived importance and on time
allocation are both equal to or greater than 4, he/she
is called a KM advocate. When the mean of the
respondent’s aggregate score on SECI’S perceived
importance and on time allocation are both equal toor lower than 2, he/she is called a KM skeptic.
When the mean of the respondent’s aggregate score
on SECI’S perceived importance is equal or greaterthan 4 and that on time allocation is equal or lower
than 2, he/she is called KM busy. And when themean of the respondent’s aggregate score on
SECI’S perceived importance is equal or lower than
2 and that on time allocation is equal or greater than4, he/she is called KM hopeful (Figure 7).
As the groups in the taxonomy are mutually
exclusive, we performed a correlation analysis
between those and the 3 competitive advantages

The explanatory power of the structural model
was evaluated based on the amount of variance inthe dependant constructs (embedded knowledge,
affective knowledge, and technical knowledge) for
which the model could account (R²). The structuralmodel could explain 17% of the variance fortechnical knowledge, but only 1.5% for affective
knowledge and less than 1% for embedded
knowledge. The value of the beta coefficient (B)indicates which of the independent variables have agreater effect on the dependent variable in themultiple regression analysis. In our model, all thestandardized coefficients are highly significant(p<0.01) and combination shows the strongest
effect on technical knowledge and externalization
the weakest.
As a result, the perceived importance of SECI,
especially combination, appears as the mostimportant source of technical knowledge CA.
Next, we carried out a multiple regression
analysis with SECI’s time allocation as independent
variables and the 3 CA constructs (Figure 6). The
structural model could explain 12% of the variancefor affective knowledge, but only 3.5% forembedded knowledge and virtually none fortechnical knowledge. In our model, all thestandardized coefficients are again highly
significant (p<0.01) and socialization shows the201constructs extracted from the principal-component
analysis.
Mean “SECI’s Time Allocation”

technical knowledge, that there is a medium
positive correlation (R=0.302, p<0.01) between KM
busy people and the contribution of embedded
knowledge, and that there is also an even stronger
positive correlation (R=0.473, p<0.01) between KM
hopefuls and the contribution of affective
knowledge. Also, it is interesting to note thatamong the population of 1,330 respondents, theadvocates make up the highest share (516),
followed by the skeptics (314), the busy (98) andthe hopefuls (60). These 4 categories of people
cover about 75% of the entire population of JPC’s
Japanese operations.
Further analysis will be performed on the data,
including taxonomies derived from stricter andlooser mean criteria as well as absolute mean scores.

5

Hopeful

Advocate

Skeptic

Busy

4

3

2

1
1

2

3

4

5

5. DISCUSSION
The discussion will explore the underlying
reasons behind the results of the structural model inorder to explain the relationship between theperceived importance and the time allocation of
KM onto the contribution of the 3 CAs – embedded
knowledge, affective knowledge, and technicalknowledge - derived from the principal-component
analysis.
Then, we will focus on the results involving thetaxonomy of workers on their KM behaviors.

Mean “SECI’s Perceived Importance”
Figure 7: Taxonomy of workers’ perceived importanceand time allocation of SECIAs the data covers the entire population of
JPC’s workers in Japan, we can reasonably assume
that the independent and dependant variables follow
a normal distribution, and therefore we can use thePearson correlation coefficient as the best estimateof the correlation of SECI and CA.
Table 2: Correlation between the taxonomy of workers
and the 3 factors of CA
Factor 1
Factor 2
Factor 3
Embedded
Affective
Technical
Knowledge Knowledge Knowledge
Skeptic
Pearson.021.178(**)-.232(**)
Corr.
Signif.
.300
.000
.000
N
314
314
314
Busy
Pearson.302(**)-.178(**)
.011
Corr.
Signif
.000
.000
.755
N
98
98
98
HopefulPearson.027.473(**)
-.056
Corr.
Signif
.555
.000
.219
N
60
60
60
Advocate
Pearson.130(**).230(**)-.334(**)
Corr.
Signif
.000
.000
.000
N
516
516
516
**Correlation is significant at the 0.01 level (2-tailed)

5. CONCLUSION
The preliminary findings suggest that theperceived importance of KM appears as animportant source of ‘technical competitive
advantage’, and that more time spent on KM
activities contributes to an ‘affective competitive
advantage’. The taxonomy of employees based on
their perceived importance of and the time they
spend on KM shows that KM advocates do notbelieve technical skills and know-how to beimportant factors of success, that KM busy consider
documents and databases as source of competitive
advantage, and that KM hopefuls think that love,care, trust and enthousiasm contribute greatly to theorganization.
In the perspective of SIMOT, these findings
may help develop tailored KM stategies targeting
each group of worker according to their faith in KM
activities in order to improve their productivity. As
the management of technology greatly depends on
the beliefs and actions of knowledge workers, thefirm will greatly benefit from a finer understandingof the effect of perceptions of KM onto competitive
advantages. Further analysis will attempt to uncovercorrelation patterns in order to formulate KM
strategies adapted to specific workers andidentifiable competitive advantages.

The results in Table 2 indicate that there is amedium negative correlation (R=-0.334, p<0.01)
between KM advocates and the contribution of202

REFERENCES[1]

Nonaka, I., Umemoto K., and Senoo D.,
1996.From Information Processing toKnowledge Creation, Technology in Society(18:2), pp. 203-218.

[2]

Argyris, C., Schön, D. A., 1992. Theory inPractice: Increasing Professional Effectiveness,
Jossey Bass Higher and Adult Education
Series, San Francisco, CA.

[3]

Polanyi, M., 1966. Tacit Dimension, Peter
Smith, Gloucester, MA.

[4]

Nonaka, I, Takeuchi, H., 1995. The
Knowledge-Creating
Company:
How
Japanese Companies Create the Dynamics ofInnovation, Oxford University Press, New
York, NY.

203

The Effect of Institutional Pressures on Knowledge Management and the Resulting
Innovation: The Case of the Smartcard in France
Remy Magnier-Watanabe**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-527 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANmagnierwatanabe.r.aa@m.titech.ac.jp
A qualitative analysis based on data gathered from the case study of the first majorrollout of smartcard technology in France shows how institutional isomorphic pressures
affect not only the management of technology but also the knowledge management
processes applied in the resulting innovation. The government impetus, legal authorities
and cultural expectations in the French society produced coercive isomorphic pressures,
while existing credit card solutions, systems and standards played the role of mimetic
isomorphic pressures, and professional networks and network effects functioned as
normative isomorphic pressures. In addition, a systems perspective of institutional
isomorphic pressures provides a better understanding of interdependence mechanisms.
1. Introduction
As Burgelman and Grove (2007) have clearly
explained, “nonlinear strategic dynamics comeabout as industry participants – sometimes
incumbents, but probably more frequently new
entrants – change the rules of the game”. These
rules span normative rules based on laws, customs,
and administrative principles; technological rules
based on available technical solutions; economic
rules reflecting existing bargaining power
relationships among the industry players (often
captured in contracts); and cognitive rules that are
widely shared judgments about key success factors.
The authors contend that whether implicit or
explicit, the rules of the game usually remainunchallenged for extended periods of time (Grove,2003), thereby engendering a strong tendency
toward strategic inertia among the industry
incumbents (Burgelman and Grove, 2007).
Institutions are the sources of such rules that are
imposed to the organization and its competitors.
They have the power, as it will be illustrated with acase study, to induce innovations and make use of
their strong institutional impetus.

2.2 Institution and Institutionalization
Institutions are products of the humansocialization process. When frequently repeatedactions become cast into a pattern leading to an
economy of effort and greater efficiency (alsocalled learning curve), this habitualized activity
frees up valuable resources for reflection andinnovation. A more operational description
recognizes institutions as having the 4 defining
featuresofsocialpurpose,permanence,transcendence over a group of individual andcreation and enforcement of its own rules (Tolbert
and Zucker, 1996).
However, as classic research showed (Zucker,
1977; DiMaggio and Powell, 1983), institutions areespecially prone to inertia, reducing their capacity
to change, while undergoing isomorphic(institutional and competitive) pressures forcing
them to adopt the same structure fitting theenvironment’s constraints.
Institutionalization is a core process in thecreation and perpetuation of enduring social groups(Berger and Luckmann, 1966).
Zucker (1977) defines institutionalization as avariable,withdifferent
degreesofinstitutionalization altering the cultural persistence
which can be expected. She argues that culturalpersistence is determined by first the transmission
from one generation to the next, second themaintenance of the culture which must occur
sequentially and third the resistance to attempts tochange with the degree of resistance directly relatedtothedegreeofinstitutionalization.
Institutionalization is not only a property variable,
but also the process by which individual actors
transmit what is socially defined as real and, at the

2. Literature Review
2.1 Knowledge Management
Knowledge Management is the process foracquiring, sharing, diffusing and implementing both
tacit and explicit knowledge inside and outside theorganization’s boundaries with the purpose ofachieving corporate objectives in the most efficientmanner. This definition is consistent with theknowledge creation view of the fim of Nonaka and
Takeuchi (1995).

204same time, at any point in the process the meaningof an act can be defined as more or less a taken-forgranted part of this social reality.
According to Tolbert and Zucker (1996), theprocess of institutionalization goes through 3
sequential stages: habitualization, objectificationand sedimentation. The habitualization stage is thedevelopmentof
patterned
problem-solving
behaviors and the association of such behaviors
with particular stimuli; this stage brings the
structurein
pre-institutionalization.
The
objectification stage is the development of general,
shared social meanings attached to these behaviors;
this step is necessary to ensure the diffusion ofthese structures uses evidence-gathering andchampions, and brings the structure in semiinstitutionalization. The sedimentation stage, as the
spread and perpetuation over time of the structure,is the last stage of the institutionalization process.
Full institutionalization requires low resistancefrom opposing groups, a strong advocacy base andthe achievement of the desired goals. Tolbert andZucker (1996) point out that a major shift in theenvironment
canalwaystriggerthedeinstitutionalization process as well.

that encourages imitation. Organizations tend tomodel themselves after similar organizations intheir field that they perceive to be more legitimate
or successful.
Normative isomorphism is a consequence ofprofessionalization.
Two
aspects
ofprofessionalization are important aspects of
isomorphism: formal education and legitimation ina cognitive base produced by university specialists
on the one hand, and growth and elaboration of
professional networks that span organizations andacross which new models diffuse rapidly on theother hand. The filtration of personnel is an
important mechanism for encouraging normative
isomorphism.
3. Research Hypotheses
Because the organization is subject to constantinstitutional pressures, whether coercive, mimetic,or normative, KM must also comply with these
isomorphic pressures (Fig.1). But while thesepressures exist simultaneously, they may also becontradictory and the firm must adopt the KM
arrangement most suitable to satisfy all forces. It is
important to note that coercive isomorphic
pressures – drawn from political influence,
legitimacy and culture – are strongest since theyexert a prescriptive power over the very existenceof the organization.

2.3 Isomorphic Pressures
DiMaggio and Powell (1983) argued that today,
structural change seems no longer driven bycompetition or the need for efficiency, but rather byprocesses, making organizations more similar
without necessarily making them more efficient.
The authors point out that once structured into afield, organizations become more similar among
them in a process of homogenization called
isomorphism. Isomorphism is a constraining
process that forces one unit in a population toresemble other units that face the same set ofenvironmental conditions.
There are two types of isomorphism,
competitive and institutional, and we focus here on
the latter kind which counts three mechanisms of
institutional isomorphic change: (1) coercive
isomorphism that stems from political influence andthe problem of legitimacy; (2) mimetic
isomorphism resulting from standard responses to
uncertainty; and (3) normative isomorphism,
associated with professionalization.
Coercive isomorphism is the result of bothformal and informal pressures exerted onorganizations by other organizations upon which
they are dependant and by cultural expectations inthe society within which organizations function.
Mimetic
isomorphism
occurswhenorganizational technologies are poorly understood,
when goals are ambiguous, or when theenvironment creates symbolic uncertainty; thenorganizations may model themselves on otherorganizations. Uncertainty is also a powerful force

Institutionalpressures
Coercive
isomorphism
Mimetic
isomorphism
Normative
isomorphism

Knowledge
Management
Acquisition
StorageDiffusion
Application

Fig. 1. The influence of institutional pressures on
Knowledge Management

4. Case Study: The “GCB
Using an interpretive case study methodology(Walsham, 1995), data were gathered from public
information and an interview conducted in 2005 in
Paris with Mrs. Martine Briat, Chief Legal Officerof the “Groupement des Cartes Bancaires” (GCB),
responsible for organizing and managing the “Carte
Bancaire” (CB) payment card system.
A payment card is a card enabling both
payments and withdrawals and is in France
alternatively called a bank card. Such card equippedwith a functional chip used for payments with a PIN

205

(Personal Identification
smartcard.

Number)islabeledthe 7,000 ATMs which were then in service,whatever the card issuer bank, and to pay forpurchases at the 300,000 CB affiliated merchants.
Thus, the CB system made the three systems, at thetime – Carte Bleue, Crédit Agricole and Crédit
Mutuel – interoperable.

4.1 The Genesis of the GCB
The issuance of payment cards is in France
carried out by financial institutions brought together
and organized as an “Economic Interest Group”(EIG) named “Groupement Cartes Bancaires”(GCB) and created in November 1984 following anagreement among the three major payment card
networks dated July 31, 1984. The foundation ofthis group composed of all the French payment card
issuers represented the outcome of a trend amongbanks to pull together and share costs and efforts inmanaging that new payment instrument.
In 1967, French consumers discover the firstpayment cards when 6 banks (Banque Nationale deParis, Crédit Commercial de France, Crédit du Nord,
Crédit Industriel et Commercial, Crédit Lyonnais,
and Société Générale) launch the “Carte Bleue” tocompete with American cards like American
Express and Diners Club. The Carte Bleue
differentiates itself using immediate debit requiringno additional payment order as opposed to payment
on credit for its competitors. In 1971, the first
automated teller machines (ATMs) enabling cash
withdrawals are made available to the public using
the magnetic strip technology, and 2 more banks(Crédit Agricole with the “Carte Verte”, Crédit
Mutuel) launch their own card network. The
following year in 1972, the 6 issuing banks of the“Carte Bleue” found the “EIG Carte Bleue”, whichcounts 71 members. In 1976, the “EIG Carte Bleue”
becomes a member of Visa, and the “Carte Verte”
network of EuroCard /MasterCard, enablingcardholders to use their card abroad. In 1980, thefirst electronic point of sale (POS) terminals are
installed on merchants’ counters. In 1983, 3 morebanks join the EIG “Carte Bleue” (Banques
Populaires, Caisse d'Epargne, Chèques Postaux;
there are now 3 competing bank card networks: the“Carte Verte” (Crédit Agricole) with 7.7 million
cards, that of the Crédit Mutuel with 1.3 million
cards, and the “Carte Bleue” with 5 million cards.
The founding of the “Groupement des Cartes
Bancaires” on July 31, 1984, combines the threepreviously competing networks consisting of theoriginal 11 banks, leading to the issuance of asingle payment card labeled “Carte Bancaire” or“CB”1.
The 1984 Memorandum of Understanding
laying the foundations for CB inter-banking enables
all CB cardholders to withdraw cash from any of1

Source: Antitrust Council’s judgment #88-D-37 of October
11, 1988.

206

4.2 Description of the GCB
By signing the 1984 agreement, the three card
networks commit to building among them a totalinter-bank card system for the functions of cash
withdrawal and payment, enabling any customer
holding a card issued by one of its member banks
and financial institutions to use all the ATMs aswell as pay at any merchant affiliated with the CB
network. The compatibility of all withdrawal andpayment systems is achieved at the end of 1985.
The broad mission of the GCB is to promote,develop and ensure the security of the CB system,
and represent almost 150 members from French andforeign banking and financial institutions, mostly
operating in France.
4.3 The Mission of the GCB
The role of the GCB consists of 4 main
activities. First, it is responsible for establishing therules applicable to CB members by overseeing theCB system and managing the common resources of
its members, who are represented on the Board of
Directors by the 11 founding banks. Second, it is incharge of defining the system’s general architecture,
the standards and inter-banking procedures requiredfor its operation, and of ensuring compliance, acting
as the guarantor of the rules defining each of thesystem functions – card issuance, cash withdrawal
management, and payment acceptance – as well as
the technical specifications and tools for dataexchange.
Third,itmanagestransaction
authorizations, inter-banking services and fees,
providing its member banks with common tools fordata exchange such as the e-rsb (CB authorization
switching network) which switches the payment
and cash withdrawal authorisations between themember institutions, and the SICB (CB Information
System). Last, the GCB is accountable forcertifying the compliance of equipments to CB
standards, working closely with manufacturers ofelectronic payment systems.
In France today, domestic cards can only be
used within the CB system and international cards
bearing the CB logo and that of an international
partner network, MasterCard or Visa, can also be
used anywhere in the world.
The GCB does not have the status of a credit
institution and does not issue payment instruments
nor manages customer accounts. All operational
aspects related to CB cards are the reserve of themember banks and credit institutions. The GCB is aseparate organization from the EIG Carte Bleue
which handles the relations with Visa and from theEuropay France organization that handles relations
with MasterCard.
4.4 Recent GCB Figures
The GCB is responsible for the first major rollout of smartcard technology in the banking industry
using a chip embedded in the card for all its cards,
allowing cardholder to take advantage of off-line
PIN verification and therefore significantly reduce
the level of fraud. In 2006, the network counted
over 53.6 million CB smartcards (+4.8% vs. 2005)
held by 87% of the French aged 18 and over, almost
48,000 ATMs and 1 million points of acceptance.
In 2006, 6.67 billion transactions were realized fora total of 349.5 billion euros, with payments, as
opposed to withdrawals, representing more than
70% of the total in value (Figure 4-5 and Table 4-1).
The 5.34 billion CB card payments in 2006
represent more payments by CB cards thanpayments by checks in Europe.
The number of payments by CB smartcard
continues to increase, to the detriment of payments
by check or cash, and they now represent 25% ofconsumer expenditures in 2004 in France and36.5% of card payments in the Euro zone. As
stressed by Mrs. Briat, “97% of CB cardholders are
satisfied and 69% are very satisfied2”.
5. Analysis and Framework Testing
Isomorphic pressures apply to the genesis andon-going activities of the GCB on the one hand, andto the knowledge management processes applied in
the creation and maintenance of the CB smartcard.

consequences of their actions; and politicaldecisions are applied across the board to entire
classes of organizations, thus making suchdecisions less adaptive and less flexible.” In thecase of the GCB, coercive institutional pressures
include the impetus and support of the government,
the judgment of the Antitrust Council in its favor,
and cultural expectations specific to the Frenchsociety.
About mimetic isomorphism, DiMaggio andPowell (1983) explain how modeling is a response
to uncertainty: “Models may be diffused
unintentionally, indirectly through employeetransfer or turnover, or explicitly by organizations
such as consulting firms or industry tradeassociations, and innovation can be accounted forby organizational modeling.” In the case of the
GCB, mimetic institutional pressures include theformat of the CB smartcard, and the compliancewith the EMV standard.
Concerning normative isomorphism, DiMaggio
and Powell (1983) interpret professionalization as“the collective struggle of members of an
occupation to define the conditions and methods oftheir work, to control the production of producers
and to establish a cognitive base and legitimation
for their occupational autonomy.” In the case of the
GCB, normative institutional pressures mainly
consist of the movements of personnel from thebanks to the GCB and back and a network effectcreated by the rise in the number of points ofacceptance.
5.2 Isomorphic Pressures and KM
Isomorphic pressures have shaped theknowledge management processes used in themaking of the GCB and its CB system (Table 1). In
other words, KM has played the role of interface
between organizations – here the banks – and the
management of technology – namely the GCB – at
the source of innovation embodied by the
successful diffusion of the smart card.

5.1 Isomorphic Pressures at the GCB
The case study of the launch of the smartcard inFrance shows that among the three types of
institutional isomorphisms, coercive isomorphic
pressures exerted the strongest influence on thework of the GCB and the resulting roll-out of thesmartcard.

The government impetus, legal authorities andcultural expectations in the French society produced
coercive isomorphic pressures onto the credit card
industry, while existing credit card solutions,systems and standards played the role of mimetic
isomorphic pressures, and professional networks
and network effects functioned as normative
isomorphic pressures.

On the topic of coercive isomorphism,
DiMaggio and Powell (1983) report how Pfeffer
and Salancik (1978) observed that “Politicallyconstructed environments have two characteristicfeatures: political decision makers often do notexperience directly the consequently directly the2

Phone survey by Taylor Nelson-Sofres conducted in
November 2006, sample of 1,105 individuals ages 15 and older(of whom 931 cardholders ages 18 and older) representative of
the French population, results analyzed only using individuals
ages 18 and older.

207

Table 1. The influence of institutional isomorphic
pressures on Knowledge Management in therollout of the CB smartcard

5.3 Isomorphic Pressures and Causal Loops
The case study of the Groupement des Cartes
Bancaires illustrates how institutional isomorphic
pressures greatly constrain the development of an
application based on some existing technology.
Let’s now look at these institutional isomorphic
pressures from a systems perspective and examine
the interdependence cycle with organizations inmarkets under their influence.

Knowledge Acquisition
Coercive Isomorphic Pressure
Government impetus The banks pool their data together through the GCB.
Normative Isomorphic Pressure
Professional networks
 The merger of the three existing card networks
includes their work and management methods.
Knowledge Storage/Diffusion
Coercive Isomorphic Pressure
Government impetus The GCB has the mission to store and protect the datathat has been provided by the banks.
 Each member-bank and partner is owed relevant andtimely information by the GCB.
Antitrust Council
 The judgment recognizes the principle of interchange
as necessary for the GCB to operate.
Cultural expectations
 The off-line authorization system limits the transfer of
information consistent with the French culture of data
privacy.
 Historically higher telecom costs support the CB’s
off-line authorization chip technology and the RCB’s
authorization switching network architecture.
Mimetic Isomorphic Pressure
EMV standard The migration to the EMV standard complies with restof the financial industry.
Normative Isomorphic Pressure
Professional networks
 Personnel transferred from the member-banks to the
GCB act as intermediaries.
Knowledge Application
Coercive Isomorphic Pressure
Government impetus The French government wants a new application for
French patents on the electronic chip.
 All CB card applications have to remain open tomember-banks for technical integration.
Mimetic Isomorphic Pressure
Card format
 The smartcard format fits the current standards of thecredit card industry and suppliers’ production
processes.
 The CB card starts with a conventional magnetic strip
widely in use in the US and switches gradually to theelectronic chip.
e-rsb
 The RCB switching network was replaced in 2005 by
the e-rsb (Banking Service Network) which now uses
Internet protocols in accordance with the latest trend
in IT.
Normative Isomorphic Pressure
Network effect The rising number of points of acceptance prompts
non-card-holders to join the existing network andbenefit from its ubiquitous offering.

5.3.1 Description of Causal loops
Continuous causal circuits, as proposed by
Weick (1979), are used here to examine the actionof institutional isomorphic pressures with anemphasis on interdependent variables, causal loops,
and the presence or absence of control. Thesecausal circuits have been successfully used inprevious research to investigate from a systems
perspective the challenges that organizations facewhen harnessing knowledge (Garud andKumaraswamy, 2005). Loops that are deviationcounteracting generate stable systems which
includeintegrated
controls that dissolve
randomness; loops that are deviation-amplifying
produce unstable systems – whether constructive ordestructive – devoid of built-in controls.
According to Weick, the tactic of using arrows
and plus and minus signs is simply a means toportray situations of complex interdependence insuch a way that one can then ask better questions
about these situations. The cycling back of loops
means that what was originally a cause is now
suddenly an effect. This is a prominent feature ofany structure of causal circuits.
5.3.2 Isomorphic Pressures in a Causal Loop
This causal circuit (Fig. 2) depicts the cycle ofinstitutional isomorphism in a specific field or
domain of influence, and it is found to be a
deviation-counteracting loop. When isomorphic
pressures – coercive, mimetic, or normative –increase, the resulting variety among theorganizations under the scope of institutional
authority decreases. In turn, this limited variety
generates greater inertia as existing players and newentrants are all the more encouraged to conform to
the prevalent model as the number of complying
organizations is important. Then, inertia prevents
the players in the field to adapt to the ever-changing
environment and eventually causes a loss ofdifferential performance compared to other fields.
Subsequently after some time, poor fit andperformance will prompt the players in the field todistance themselves from those isomorphic
pressures and break away from the detrimental
norm.
Once the effect of isomorphic pressures has
weakened due the resulting sub-par fit and208

current institutions have no incentive for pushingchange. However, when environmental fit andperformance are declining, the actors of the field
shy away from the current isomorphic pressures,and this deterioration promotes institutional actors
to make changes in the existing isomorphic
pressures and propose a new set of constraints
through institutional impetus.

performance then variety increases and inertia
decreases. Better environmental fit and greater
performance consequently strengthen the remaining
isomorphic forces that can be credited with theturnaround. It is important to note that therelationships between the variables are not always
instantaneous and may take time in the build-up andresulting consequence; for example, declining
variety will result in inertia only after some time,once the level of diversity has reached a critical low
point over a period of time.

5.3.4 Institutional Impetus and New Isomorphic
Pressures
Even though the action of institutional impetus
onto isomorphic pressures appears contradictory tothat of environmental fit and performance – with an
ensuing opposite sign – in reality, the nature of theresulting isomorphic pressures is different.
Environmental fit and performance influence
the effect of existing isomorphic pressures, while
institutional impetus triggers new isomorphic
pressures designed to suit the new constraints of theenvironment. Therefore, as in the absence ofinstitutional impetus, when environmental fit andperformance decrease, the effect of existing
isomorphic pressures decline as a result of players
in the fields taking their distance from the not-sosuccessful norm (Fig. 4).

Environmental fit& performance

Inertia-+

Variety

Isomorphic
pressures-

Fig. 2. The isomorphic cycle without institutional
impetus: a deviation-counteracting loop-

5.3.3 Institutional Impetus and Isomorphic
Pressures
In the causal circuit described previously,change results from the actors of the field who reactaccording to their performance or lack thereof.
However, change can also be initiated by deliberateinstitutional action – called institutional impetus –distinct from the players in the field. Thisinstitutional impetus participates in keeping
isomorphic pressures relevant and strong (Fig. 3).

-+
Isomorphic
pressures

Variety

Existing
isomorphic
pressuresInstitutional
impetus++

Environmental fit& performance-+

Variety-

Inertia

Environmental fit& performance

InertiaNew
isomorphic
pressures

Fig. 4. Institutional impetus and the isomorphic cycle: adeviation-counteracting loop, breakdown version

Institutional
impetus

In addition, institutional impetus reduces theinfluence of existing isomorphic pressures byintroducing and promoting new isomorphic
pressures, which in turn increase organizationalvariety.

+-

6. Conclusion
When institutions are viewed as “the humanly
devised constraints that structure humaninteraction” (North, 1994), then institutions can beseen as shaping much of the knowledge of oursocieties, both as inputs and outputs. And because,
as previously defined, technology is knowledge-

Fig. 3. Institutional impetus and the isomorphic cycle: adeviation-counteracting loop

When environmental fit and performance in thefield increase, the underlying isomorphic pressurespersist and grow as previously explained, and in
addition, any institutional impetus remains low as

209

Sociological Review (48:April), 1983, pp.
147-160.

based, innovation turns out to be an outcome ofinstitutions.
This qualitative analysis based on data gatheredfrom the case study of the first major roll out ofsmartcard technology in the French banking
industry showed how institutional isomorphic
pressures affected not only the genesis and ongoing activities of the management of technology,
but also the knowledge management processes
applied in the creation and maintenance of resulting
innovation.
The government impetus, legal authorities andcultural expectations in the French society produced
coercive isomorphic pressures onto the credit card
industry, while existing credit card solutions,systems and standards played the role of mimetic
isomorphic pressures, and professional networks
and network effects functioned as normative
isomorphic pressures.
Whenthetechnology
hasbecomeinstitutionalized (Tolbert and Zucker, 1996) withthe four defining features of social purpose throughsafer and faster payment system, permanence
legitimized by court ruling and EMV and thedevelopment of a national industry, transcendence
over a group of individuals where all French banks
are CB members, and creation and enforcement of
its own rules since the CB system is backed by thepolice and financial institutions, long-term successtranslates in a high degree of adoption of the
product and the creation of a competitive domestic
industry leader in that technology. However,whatever support an institution provides at one
point can be taken away by the same institution or
by a higher one at another point in time.
Last, a systems perspective of institutional
isomorphic pressures can help organizations
identify the forces they are subject to, and optimize“their institutional positioning” in the market inorder to maximize the success of their technology.

Berger, P. L., and Luckmann, T., The Social
Construction of Reality: a Treatise in theSociology of Knowledge, Anchor Books, New
York, NY, 1966.

[2]

Burgelman, R. A. and Grove, A. S., “Let
Chaos Reign, then Rein in Chaos –Repeatedly: Managing Strategic Dynamic for
Corporate Longevity”, Strategic Management
Journal, in press, 2007.

[3]

DiMaggio, P. J., and Powell, W. W., “The
Iron
Cage
Revisited:
Institutional
Isomorphism and Collective Rationality in
OrganizationalFields”,
AmericanGarud, R. and Kumaraswamy, A., “Vicious
and Virtuous Circles in the Management ofKnowledge:
The
Case
of
InfosysTechnologies”, MIS Quarterly (29:1), 2005,
pp. 9-33.

[5]Grove A. S., Churning Things Up, Fortune,
August 11, 2003, pp 114-118.

[6]

Nonaka, I, Takeuchi, H., The KnowledgeCreating Company: How Japanese Companies
Create the Dynamics of Innovation, Oxford
University Press, New York, NY, 1995).

[7]

North, D. C., “Economic Performance throughTime”, American Economic Review (84:3),
1994, pp. 359-368.

[8]

Pfeffer, J., and Salancik, G. R., The External
Control of Organizations: A Resource
Dependence Perspective, Harper and Row,
New York, NY, 1978.

[9]Tolbert P. S., Zucker L. G., “TheInstitutionalization of Institutional Theory”, in
Handbook of Organizational Theory, pp. 175190, Sage Publications, Beverly Hills, CA,
1996.

[10] Walsham, G., “Interpretive Case Studies inInformation Systems Research: Nature andMethod”, European Journal of Information
Systems (4), 1995, pp 74–81.
[11] Weick, K. E., The Social Psychology ofOrganizing (2nd edition), McGraw-Hill, New
York, NY, 1979.
[12] Zucker L. G., “The Role of Institutionalizationin
CulturalPersistence”,
AmericanSociological Review (42:October), 1977, pp.
726-743.

References
[1]

[4]

210

Organizational Characteristics, Relative to National Culture, Exert a Stronger
Prescriptive Influence on Knowledge Management
Remy Magnier-Watanabe**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-527 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANmagnierwatanabe.r.aa@m.titech.ac.jp
The purpose of this research is to quantitatively validate the previous finding thatorganizational characteristics indeed constrain the nature of knowledge management(KM) within the firm, and to assess whether the national culture of knowledge workers
equally affect the management of knowledge. Based on data gathered from aquestionnaire survey of a Japanese pharmaceutical company’s 15 foreign subsidiaries, therelationships between organization and KM on the one hand, and between national
culture and KM on the other hand were tested using structural equation modeling.
The findings show that organizational characteristics – structure, membership,
relationship, and strategy – and national culture – power distance, individualismcollectivism, masculinity-femininity, and uncertainty avoidance – affect KM – knowledge
acquisition, storage, diffusion, and application – respectively. Among the predictors of KM
beyond the realm of deliberate measures within the firm, organization was found to be astronger prescriptive factor compared to national culture. Hence, corporations should first
focus on adjusting knowledge management to its organization and then to the national
culture of local offices.
et al., 2001) and the efficiency priority of KM
within the organization (Alavi and Leidner, 1999;
Drucker, 2001). The knowledge management valuechain mirrors the knowledge-creating view of thefirm, which defines knowledge as a process ofjustifying belief toward the truth (Nonaka and
Takeuchi, 1995).

1. Introduction
While it is intuitive and logical to consider that thefirm’s strategy should dictate the specificknowledge management policies and practices
necessary to achieve its corporate objective, in fact
previous research has shown that the very
organization of the firm (Magnier-Watanabe andSenoo, 2008) and national culture (Möller andSvahn, 2004; Martinsons and Davison, 2007)
constrain and influence the nature of KM.
Therefore, firms should accept that some taken-forgranted aspects of their organization and theirworkers’ cultural inclinations may need to be taken
into account in order to realize the full potential
benefits of knowledge management.

2.2 Organizational Characteristics
Magnier-Watanabe and Senoo (2008) haveshown how the organization of the firm can beevaluated according to its structure (vertical or
horizontal), membership (individual or collective),
relationship (systematic or ad-hoc), and strategy(reactive or innovative). This segmentation into
structure and strategy on the one hand, andmembership and relationship on the other hand, isalso consistent with the prevailing leadershiptheories taking roots in the seminal Ohio State
University Studies (Katz and Kahn, 1953) and the
University of Michigan Studies (Halpin and Winer,
1957) of leadership behaviors. These studies foundthat leaders were mostly of two kinds, with a focus
on structure or consideration in the former, and on
being production or employee-centered in the latter.
These results were later confirmed by thecontingency model of Fiedler (1981) showing aneither human-relations orientation or task
orientation among leaders.

2. Background and Hypothesis
2.1 Knowledge Management
Knowledge management can be defined as theprocess for acquiring, storing, diffusing andimplementing both tacit and explicit knowledge
inside and outside the organization’s boundaries
with the purpose of achieving corporate objectives
in the most efficient manner (Magnier-Watanabe
and Senoo, 2008).
This definition of knowledge management is
consistent with the knowledge value-chain
approach common to many KM descriptions (Shin211

Organization
Management
CultureThese four characteristics are also consistent
with the cultural influences of Simon (1976) which
are carried out through authority, organizational
loyalties, advice and information, the criterion ofefficiency, and training.

StructureStrategy

RelationshipMembership

Means

Fig.

Business
1. The segmentation
characteristics

Table 1 Organizational characteristics as prescriptive
factors of Knowledge Management
Org. Characteristics
Vertical
Structure
Horizontal
Individual
MembershipCollective
Systematic
Relationship
Ad-hocReactive
StrategyInnovative

KM Value-Chain
FocusedAcquisition
Opportunistic
Selective
Sharing
Inclusive
Prescribed
Diffusion
Adaptive
Exploitative
Application
Explorative

2.3 National Culture
Hofstede (1980) defines culture as a “collective
phenomenon”, because it is at least partly sharedwith people who have lived within the same social
environment where it was learned. It is thecollective programming of the mind that
distinguishes the members of one group or categoryof people from another.
Culture is expressed through symbols, heroes,
rituals and concepts, which are ordered from themost superficial to the deepest manifestations ofculture. The first three are visible and can therefore
be grouped under the term practices, which can beused to interpret their hidden cultural meaning.
Also, as people belong to many groups at the sametime, they carry several layers of cultures withinthemselves, i.e. national, regional, ethnic, gender,
corporate level, etc. Culture propagates itself
through the basic elements of society, also known
as institutions, such as the family, the school, thecommunity and the workplace (Hofstede andHofstede, 2005).The early years spent with one’s
family and in school shape the underlying values
making up national culture, while the time spentworking in an organization mainly yields corporate
practices that are more superficial.
Hofstede (1980), who also investigatedcorporate culture, claims that national culture
differences reside more in values and less inpractices and that organizational culture differences
reside more in practices and less in values.
Hofstede’s research, with a questionnaire survey ofmore than 100,000 IBM employees worldwide(Hofstede, 1980), uncovered five dimensions ofculture: power distance, uncertainty avoidance,
individualism-collectivism, masculinity-femininity,
and time horizon.
Power distance (PDI) is the tolerance for power
disparity in society (from low to high).
Individualism-collectivism (IDV) is how much agiven individual put his/her interests ahead of thoseof the group to which he or she belongs.
Masculinity-femininity (MAS) relates to theemphasis on clear distinctions between emotionalEndsof organizational

The selected organizational characteristics canbe seen as belonging to both organizational
management and culture. This segmentation (Fig.1)
can be read horizontally where, on the management
side, structure appears as the business means to thebusiness end of strategy, and on the culture side,
relationship emerges as the business means to thebusiness end of membership. This segmentation canalso be read vertically where on the means side,
relationship and structure are the two parts of theculture and management organization couple, andon the ends side, membership and strategy are thetwo parts of the culture and management
organization couple.
As knowledge management is most effective
when tightly integrated within the organization’s
processes, organizational characteristics greatly
determine the relevant types of KM initiatives andshape the firm’s KM policy. As a result, strategicalignment is ensured by the congruence of each stepof the knowledge management value-chain with theorganizational characteristics of the organization(Magnier-Watanabe and Senoo, 2008) (Table 1).
For instance, the acquisition (and/or creation) of
knowledge in the organization will greatly dependon its structure, knowledge storage on its
membership attribute, knowledge diffusion on its
relationship pattern, and knowledge application on
its strategy.

212gender roles, where for example, in more feminine
countries women are expected to stay at home tocare for their offspring. Uncertainty avoidance(UAI) represents the tolerance for uncertainty,
ambiguity, risk and the need for formal rules (fromlow to high). Finally, time horizon relates towhether a person is short-term oriented or longerterm oriented. Western societies are typicallyshorter term oriented than Eastern societies. For the
purpose of the present research, only the first four
dimensions of culture will be used.
Other studies have confirmed the validity ofthese dimensions (Ronen and Shankar, 1985;
Shackleton and Ali, 1990) and employed them toaccount for empirical observations (Earley, 1993;
Straub, 1994; Tan et al., 1998). This study uses themodel of Hofstede (1980) because it has beenshown to be stable and useful by numerous studies
across many disciplines (Garfield and Watson,1998) [see review by Sondergaard, 1990].
The scores measure differences between country
cultures and not cultures in an absolute sense.
According to Hofstede and Hofstede (2005), thecultures may have evolved, but as long as they
evolved together under the influence of the same
global forces, the scores remain valid.
High power-distance societies, where power
disparity and specialization are favored, may foster
a focused knowledge acquisition; individualistic
societies, where the interests of the individual lie
ahead of those of the group, may promote private
knowledge storage; masculine societies, where
decisive and aggressive management is preferredover intuition and consensus, may encourageprescribed knowledge diffusion; and highuncertainty-avoidance societies, where tolerance forrisk and uncertainty is low, may support
exploitative knowledge application (Table 2).

one hand, and between national culture andknowledge management on the other hand.
H1a. Vertical structure (relative to horizontal
structure) is positively related to focusedknowledge acquisition (relative to opportunisticknowledge acquisition).
H1b. Individual membership (relative tocollective membership) is positively related to
private knowledge storage (relative to publicknowledge storage).
H1c. Systematic relationship (relative to ad-hoc
relationship) is positively related to prescribedknowledge diffusion (relative to adaptive
knowledge diffusion).
H1d. Reactive strategy (relative to innovative
strategy) is positively related to exploitativeknowledge application (relative to explorativeknowledge application).
The case study analysis of Eisai in the UnitedStates, the United Kingdom and Japan by MagnierWatanabe and Senoo (2008) showed that indeed
vertical structure supported focused knowledge
acquisition; individual and collective membershippromoted private and public knowledge storage
respectively; systematic and ad-hoc relationships
encouraged prescribed and adaptive knowledge
diffusion respectively; and reactive and innovative
strategy fostered exploitative and explorativeknowledge application respectively.
H2a. High power distance (relative to low
power distance) is positively related to focusedknowledge acquisition (relative to opportunisticknowledge acquisition).
H2b. Individualism (relative to collectivism) is
positively related to private knowledge storage(relative to public knowledge storage).
H1c. Masculinity (relative to femininity) is
positively related to prescribed knowledge diffusion(relative to adaptive knowledge diffusion).
H1d. High uncertainty avoidance (relative to
low uncertainty avoidance) is positively related to
exploitative knowledge application (relative to
explorative knowledge application).

Table 2 National Culture as prescriptive factors ofKnowledge Management
National Culture
High
PDI
Low
Individual
IDV
Collective
Masculine
MAS
Feminine
High
UAI
Low

KM Value-Chain
FocusedAcquisition
Opportunistic
Selective
Sharing
Inclusive
Prescribed
Diffusion
Adaptive
Exploitative
Application
Explorative

Kankanhalli et al. (2004) describe how Hofstede(1980) argues that uncertainty avoidance (UAI) andpower distance (PDI) are especially relevant for
research pertaining to organizational behavior andpractices. This is because uncertainty avoidance andpower distance jointly determine key aspects ofcorporate behavior such as distribution of decisionauthority, establishment of rules and methods, andmanagement of risks and ambiguity. The authors

2.4 Hypotheses and Research Model
The following hypotheses are derived from theprevious discussion on the relationship between
organization and knowledge management on the213report of several studies conducted at theorganizational level that have made use of these two
cultural dimensions to account for empirical results(Garfield and Watson, 1998; Png et al., 2001; Shore
and Venkatachalam, 1995). Hofstede (1980) alsosuggests that individualism–collectivism (IDV) andmasculinity–femininity (MAS) may be more
relevant for research on individual behavior andpractices. Kankanhalli et al. (2004) also refer toseveral empirical studies that have successfully
used individualism-collectivism (Chen et al., 1998;
Jung and Avolio, 1999; Tan et al., 1998) andmasculinity-femininity (Gefen and Straub, 1997;
Helgstrand and Stuhlmacher, 1999) to predict
human behavior at the individual level.

The present KM performance is proof that theoutput of knowledge management can be
successfully improved through a company-wide
voluntary policy of integration into the elementarybusiness processes.
Therefore, since the Japanese workforce hasreceived extensive training on knowledge
management and has consequently been displaying
a heightened awareness in the four steps of theknowledge management value-chain, it was
excluded from the present analysis. Only foreign
Eisai employees working abroad (in descendingorder of headcount) in the United States (USA),
Indonesia (IDN), China (CHN), Great Britain(GBR), Taiwan (TWN), Germany (GER), Thailand(THA), the Philippines (PHL), France (FRA),
Korea (KOR), Spain (ESP), Malaysia (MYS),
Hong-Kong (HKG), and Singapore (SGP), whohave not benefited from the same intensive andregular KM-specific education, were included in thesample, making up 1,724 people
The questionnaire data includes responses fromseveral different countries, providing the necessary
data to assess the effect of national culture on
knowledge management using Hofstede’s culturaldimension scores.

3. Analysis
3.1 Methodology, Sample Selection and Data
Collection
The analysis is using questionnaire data from asingle Japanese pharmaceutical corporation, Eisai,
which can be qualified in its industry as a medium
size company with yearly sales of about USD 5
billion (FY2005) covering both prescription andover-the-counter drugs. Eisai is active primarily inthe fields of neurology with Aricept, a treatment for
mild-to-moderate
Alzheimer's
disease,andgastroenterology with Pariet/Aciphex, a proton
pump inhibitor for the healing of erosive gastroesophageal reflux disease and duodenal ulcers.
Eisai’s global corporate mission is to be a “humanhealthcare company” or “hhc”, where employees
give their first thoughts to patients and theirfamilies and contribute to increasing their benefits.
The present quantitative analysis is drawing onquestionnaire data collected in 2005 from a 200item survey instrument using a 5-point Likert scalethat was developed over several years with thecollaboration of professors of knowledge
management from a number of Japanese National
Universities. Eisai recognized the value of KM
early on and conducts frequent surveys of its entire
global workforce covering topics such as
knowledge management and organization.
The data of Eisai’s entire workforce worldwide
is used – more than 7,000 people at the time of thesurvey – minus that of the Japanese workforce – orabout 5,000 staff. Indeed, Eisai has been involved
in knowledge management initiatives for years andhas dedicated a team to monitor and implement
relevant projects aimed at boosting the yield of KM
activities. Previous similar surveys conductedinternally at Eisai have demonstrated a steady
improvementinknowledge
management
perceptions and behaviors among Japanese workers.

3.2 Selection and Operationalization ofConstructs
Since the variables from the 2005 survey do not
perfectly match those investigated in this present
research, the entire list of questions was examined
and only relevant items were selected for both
dependent and independent constructs.
KM as Dependent Variables
This research hypothesizes that knowledge
management is subject to influences embedded bothin the pattern of organizational constraints of thefirm and in the learned behaviors of its contributors(Garud and Kumaraswamy, 2005). As such,knowledge management can be divided between
individual KM – or as KM in-use – and group KM– or espoused KM – as the actual values androutines of the individual may differ from thoseadvocated by the group when it comes to the
management of knowledge (Argyris and Schön,
1992; Kelloway and Barling, 2000). For example,
while some individuals may feel more comfortableusing existing knowledge to yield greater efficiency,
the group may alternatively encourage a more
explorative approach leading to the creation of new
knowledge.
Therefore, different questions were selected
when possible to measure knowledge managementin the relationships between cultural dimensions

214and KM on the one hand and between
organizational characteristics and KM on the otherhand. In the former, individual KM questions wereselected for storage and diffusion and group KM
questions for acquisition and application, while in
the latter, KM questions pertaining to the group ororganization were picked for all four knowledge
activities.
For knowledge acquisition, a higher scorereflected opportunistic knowledge acquisition,
whereas a lower score reflected focused knowledge
acquisition. For individual knowledge storage, ahigher score represented private knowledge storage,
whereas a lower score represented publicknowledge storage. For group knowledge storage, ahigher score indicated public knowledge storage,
whereas a lower score indicated private knowledge
storage. For both individual and group knowledge
diffusion, a higher score signaled ad-hoc knowledge
diffusion, whereas a lower score signaled
prescribed knowledge diffusion. And forknowledge application, a higher score corresponded
to explorative knowledge application, whereas alower score corresponded to exploitative knowledge
application.

3.3 Structural Model
As the size of the sample is large, we canassume that the population is normally distributed
and thus perform a multiple regression analysis
between the selected independent and dependent
variables (Elliott and Woodward, 2007).

Independent Variables
Organization was measured using appropriatequestions on structure, membership, relationship,and strategy. Concerning the structure variable,
only an individual question was found to be
relevant for the construct, while the other threeorganizational characteristics could be assessedusing general statements about the firm. For
structure, a higher score reflected horizontal
structure, whereas a lower score reflected verticalstructure. For membership, a higher score
represented collective membership, whereas a lower
score represented individual membership. For
relationship, a higher score indicated ad-hoc
relationship, whereas a lower score indicatedsystematic relationship. And for strategy, a higherscore signaled innovative strategy, whereas a lower
score signaled reactive strategy.
For power distance, a higher score reflected highpower distance, whereas a lower score reflected low
power distance. For individualism-collectivism, ahigher score represented individualism, whereas alower score represented collectivism. For
masculinity-femininity, a higher score indicatedmasculinity, whereas a lower score indicatedfemininity. And for uncertainty avoidance, a higherscore signaled high uncertainty avoidance, whereas
a lower score signaled low uncertainty avoidance.

B=0.181**

Relationship between organization and KM
A multiple regression analysis was first
performed
with
the
four
organizational
characteristics as independent variables and the four
steps of knowledge management as dependent
variables.
Organizational
Characteristics

Knowledge
Management

Structure

Acquisition
R² = 0.214**

Membership
Relationship
Strategy

B=0.358**
B=0.120**B=0.171**
B=0.241**

Storage
R² = 0.100**
Diffusion
R² = 0.287**
Application
R² = 0.053****p<0.001
Fig. 2. Regression model for the influence oforganization on knowledge management

The explanatory power of the structural model(Fig.2) was evaluated based on the amount ofvariance in the dependent constructs (knowledge
acquisition, storage, diffusion, and application) for
which the model could account (R²). The structuralmodel could explain 21% of the variance forknowledge acquisition, 10% for knowledge storage,
and 29% for knowledge diffusion (p<0.001). These
exceeded 10% which was proposed by Falk andMiller (1992) as indication of substantive
explanatory power. However, the model could only
account for 5% of the variance for knowledge
application(p<0.001).
Eachhypothesis
corresponded to a path in the structural model. Thus,
support for each hypothesis could be determined byexamining the sign (positive or negative) andstatistical significance for its corresponding path.
The absolute value of the beta coefficient (B)indicates which of the independent variables have agreater effect on the dependent variable in themultiple regression analysis.
In the model, all the standardized coefficientsare significant (p<0.001) and structure shows thestrongest (positive) effect on knowledge acquisition,215

membership and relationship the strongest(positive) effects on knowledge storage,
relationship the strongest (positive) effect onknowledge diffusion, and strategy the strongest(positive) effect on knowledge application.
These results are consistent with the findings
from the previous case study-based qualitative
analysis. The only difference is that in addition tomembership, relationship was found to also be a
predictor of knowledge storage. Also, even though
the model could only account for 5% of thevariance for knowledge application, it is still highly
significant (p<0.001).
As a result, the structural model supports H1a,
H1b, H1c, and H1d where organization exerts asignificant influence on knowledge management.
And since the respondents in the survey comefrom different countries, the effect of national
culture must be controlled in the relationshipbetween organization and knowledge management.
Controlling for the effect of national culture, partial
correlations (p<0.001) between the independent
variables – organization – and the dependent
variables – knowledge management – confirm theprevious results.

statistical significance for its corresponding path.
The absolute value of the beta coefficient (B)indicates which of the independent variables have agreater effect on the dependent variable in themultiple regression analysis. In the model, all thestandardized coefficients are either mildly
significant (p<0.1), or highly significant (p<0.001)
and power distance shows the strongest (positive)
effect on knowledge acquisition, individualismcollectivism the strongest (positive) effect onknowledge storage, masculinity-femininity thestrongest (positive) effect on knowledge diffusion,and uncertainty avoidance the strongest (positive)
effect on knowledge application.
CulturalDimensions

Knowledge
Management

Powerdistance

Acquisition
R² = 0.051**

Individualism
collectivism
Masculinity
femininity

Relationship between national culture and KM
Another multiple regression analysis was thenperformed with the four dimensions of national
culture (Hofstede, 1980) as independent variables
and the four steps of knowledge management as
dependent variables.
In order to verify H2a, H2c, and H2d, thequestions on knowledge acquisition, diffusion, andapplication were reverse-coded. Consequently,
betas with positive signs in the structural model
would show support for the four hypotheses on therelationship between national culture andknowledge management.
The explanatory power of the structural model(Fig.3) was evaluated based on the amount ofvariance in the dependent constructs (knowledge
acquisition, storage, diffusion, and application) for
which the model could account (R²). The structuralmodel could explain 12% of the variance forknowledge storage (p<0.001). This exceeded 10%
which was proposed by Falk and Miller (1992) as
indication of substantive explanatory power.
However, the model could only account for 5% of
the variance for knowledge acquisition (p<0.001),
0.5% for knowledge diffusion (p<0.1), and 7% forknowledge application (p<0.001). Each hypothesis
corresponded to a path in the structural model. Thus,
support for each hypothesis could be determined byexamining the sign (positive or negative) and216

Uncertainty
avoidance

B=0.180**
B=0.505**

Storage
R² = 0.124**

Diffusion
R²= 0.005***
B=0.080***

B=0.302****p<0.001; ***p<0.1

Application
R² = 0.066**

Fig. 3. Regression model for the influence of culturaldimensions on knowledge management

As a result, the four hypotheses H2a, H2b, H2c,and H2d are supported, where national culture
exerts a significant influence on knowledge
management.
Strength-assessment of the relationship between
organizational and KM and between cultural
predictors and KM
Since the hypotheses on the influence oforganization and national culture on knowledge
management were supported, an additional multiple
regression analysis is required to assess which
predictor has the strongest effect on the dependent
variables based on the strength of the betacoefficient (not shown).
The absolute value of the beta coefficient (B)indicates which of the independent variables have agreater effect on the dependent variable in themultiple regression analysis. In the model, all thestandardized coefficients are either significant(p<0.01) or highly significant (p<0.001), with the
exception of the beta coefficient for the relationshipbetween masculinity and knowledge diffusionwhich is found to not be significant. Nevertheless,in every instance, organization, relative to national
culture, shows the strongest (positive) effect onknowledge management.
4. Discussion
4.1 Organization and KM
The relationship between organization and KM
suggests that there is a natural fit between theorganization of the firm and the management ofknowledge. As a result, when internationalorganizations expand abroad and adopt a different
organization to fit the needs of the local market, thefirm may have to also adapt its KM systems andpolicies since a misfit between organization and
KM may hinder the productivity of knowledge.
However, it is important to note that while
structure and relationship exert a strong influenceon knowledge acquisition and knowledge diffusion
respectively, membership displays only a mild
influence on knowledge storage, and strategy
exhibits a weak influence on knowledge application.
4.2 National Culture and KM
Even though the data supporting the framework
was gathered from individuals with different
national cultures, it does not in any way represent atypology of national models. The influence ofnational culture on KM is considered relative;
therefore it carries meaning in the comparison
among several countries of such influence.
The quantitative analysis showed that national
culture has a significant influence on knowledge
management. However, it is important to note that
although significant, the explanatory power ofnational culture on knowledge management issubstantial only in the relationship between
individualism-collectivism and knowledge storage.
And the linear relationship that is established forpredicting knowledge management based on
cultural dimensions only applies to the range ofcultural dimension scores used in developing theregression line. However, as the scores of PDI, IDV,
MAS, and UAI range between 35 and 104, 14 and91, 34 and 66, and 8 and 86 respectively, the data
provides a broad enough spectrum to draw general
conclusions about other countries not included in
the current sample.
The relationship between national culture andKM implies that the management of knowledge
may not only depend on the organization of the firm
and its deliberate and explicit procedures andguidelines, but may also be constrained by themental models of its practitioners drawn fromnational culture. This provides further support for217

the tailoring of KM not only according to theorganization of each office, but also based on the
country in which it operates. Still, even thoughnational culture was shown to be a significant
predictor of knowledge management, the strengthof the relationship is weaker than that withorganization.
5. Conclusion
Knowledge management can no longer be solely
attributed to specific KM policies, but should take
into account internal factors such as the influence ofthe organizational arrangement of the firm andexternal factors such as the effect of national culture.
As Weick (1979:88) previously noted, there ishost of influencing factors lying beyond theboundary of the firm: “The word organization is anoun, and it is also a myth. (…) Just as the skin is amisleading boundary for marking off where aperson ends and the environment starts, so are thewalls of an organization. Events insideorganizations and organisms are locked into causal
circuits that extend beyond these artificial
boundaries.”Thisframework
linking
organizational
characteristics and national culture to knowledge
management had received a first justification using
a case-study approach with a qualitative
comparative method (Magnier-Watanabe, 2008)
and has now been validated with a quantitative
approach. Among the predictors of knowledge
management beyond the realm of deliberatemeasures within the firm, the data showsorganization to be a stronger prescriptive factor
compared to national culture. Hence, corporations
should first focus on adjusting knowledge
management to its organization and then to thenational culture of local offices.
This qualitative data hold true only for thesurveyed Japanese pharmaceutical company; as aconsequence, further research is needed to confirm
the validity of the framework in other industries.
But in the meantime, these results have beenreliably confirmed and represent a solid starting
point. The findings of this research can already be
useful to practitioners so as to realize thatknowledge management should be integrated into
the elementary business processes rather than beleft to the discretion of knowledge workers. The
optimization of the organizational features of local
sub-teams can greatly improve the desired output
and serve corporate strategy. However, changes tothe concerned organizational characteristics may
not be realized at once since they deal both with thefirm’s management or production and its culture or
human actors.

[13] Helgstrand, K.K., and Stuhlmacher, A.F.,“National Culture: An Influence on Leader
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219

Institutional Congruence of Knowledge Creation
ProcessYue WuDepartment of Industrial Engineering and Management
Tokyo Institute of Technology
wu.y.ac@m.titech.ac.jp

Abstract—
Knowledge creation
Current theories of knowledge creation theories defineknowledge creation process as conversion between tacitknowledge and explicit knowledge. Based on such perception, thisresearch has two phases. Firstly it visualized the knowledge
creation key process, and constructs a model forknowledge-creation process throughout and out the firm. And
based on such model, this research examines the institutional
congruence of knowledge creation activities in each model. It has
potential to: 1. Help managers to diagnose the project and findspecific enablers/barriers in a certain organization. 2. Help
researchers find mechanisms and adopt operational approaches
to enhance each step in a creating project.
Index Terms—organizational knowledge creation, ontologicalmodel, isomorphic pressures, Ba,

1

OVERVIEW OF THE RESEARCH

1.1 Methodology of Japanese Mode of Technology Innovation
During the recent half century, knowledge creation theory
has tried to contribute in three main fields: discovery ofenablers and barriers, improvement of organizational
infrastructure, and examination of knowledge creation
mechanisms. However, lacking of solid evidence and visible
key process, there are always gaps in the theory construction
and practical instruction. Therefore, this research has twocontents: Visibility of knowledge creation key process byconstructing practical model; and examination institutional
congruence based on such model.
As the epistemological research of knowledge creation
has been well developed, this research focus on the

ontological aspects: the dynamic of stakeholders andknowledge creation entities. “Boom-up” and “Slip-down”
are the two mechanisms in such ontological shifting.
Institutions are the influential factors in knowledge creation
projects.
1.2 Surveys and Data Collection
In The model construction project, second data from cases inexisting knowledge creation literatures are adopted to create themodel (Panasonic bakery and 3M’s post-it note). In addition,interview with Sanyo’s knowledge activist in their invention ofdetergent free washing machine is implemented to do
evaluation and comparison.
In the second project, product development cases in ZTE
China (an international communication provider) are examined.
3 cases are selected (according to the ontological taxonomy ofknowledge creation) to evaluate the institutional influential
factors.
2

FINDINGS IN EACH PROJECT

2.1 Ontological Model of Knowledge Spiral
A four-layer model of presented as Knowledge creation
activities sometimes start from individual inspiration,
boom-ups through group, organization and social network
towards rent appropriation and have different task to completein each ontological layer. This model discovered the underlying
isomorphism of knowledge creation in all ontological layers,
and regards SECI as the epistemological base for model
demonstration. (Figure 1).
S

E

I

C
Organization
S
I

S

E
I

C

E
C

Group

SocialNetwork

PTK
I

E
C

Boom-up

Slip-down

Individual
Fig. 1. 12 Ontological Model of Knowledge Creation

2.2 Institutional Congruence of Knowledge Creation
In this research, we presented a hypothesis that theisomorphic pressure and differentiation strategy, as two
aspects of institutions, have influence on the knowledge
creation key processes both inter-layer and intra-layer

220

An Ontological Model of Knowledge Spiral
Yue Wu*Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
wu.y.ac@m.titech.ac.jp
The knowledge-creating capability has been recognized to be significant. However, alack of holistic models prevents organizations from systematically analyzing. This researchaims at providing a systemic and holistic model enabling the identification of the uniqueenablers and barriers of the knowledge-creation process for any given organization. This
paper draws a picture of the knowledge-creation throughout and out the firm: ontologicalshifts from the individual to the group, the organization, and internal and external social
networks. The upward shift – called boom-up – and downward shift – called slip-down –are the two important knowledge engines that induce the continuous knowledge-creating
spiral and add value to the firm. The application and usefulness of this model areillustrated using Sanyo’s detergent-free washing machine development project.
Key Words: Knowledge-creating capability, Knowledge spiral, Ontological model

1. Introduction
Many literatures show advancement towards
increasing productivity of knowledge creation since
1959, when Drucker(1993) argued that knowledge
turned to be the basic economic resource in“knowledge society”. However, according to
Kakabadse’s (2003) taxonomy, knowledge creation
and application research fall into the category
named “community of practice (CoP) model”.
According to this perspective, knowledge is createdbased on “learn[ing] from stories” (Kakabadse et al.,2003). Such justification considers knowledge
creation research as “story telling” and empirical,
and thus supports a discrete case-study
methodology which blinded us from making
causality observations.
research on knowledge creation has primarilyadvanced in three fields: the definition of enablers(Nonaka and Tacheuchi, 1995; Krogh et al., 2000);
the discovery of barriers (Szulanski, 2003); and theconstructionoftangibleandintangible
organizational infrastructure (Delong, 2004). The
multitude of “enablers” presented by scholars is agood example. Nonaka and Tacheuchi (2005) for
instance presented five different factors forknowledge creation – as “unified enabler” – andproved their existence using actual cases. However,no evidence has shown either the sufficiency ornecessity of these enablers.
The research objective of this paper is todevelop a methodology for discovering specificenablers and barriers for each specific organization
to create knowledge, and complete the ontological

221

view of SECI which has potential to induce
institutional forces into the knowledge creating
model. In order to solve the issue of causal
ambiguity, this paper abandons ambitious unified“enablers” or “barriers” and instead proposes amodel to visualize the knowledge creation key
processes, while providing rules to diagnoseorganizational contexts. This model has also thepotential to monitors the on-going knowledge
creating process.
2. Ontological Shifts during the Knowledge
Creating Process
2.1 Knowledge creation ontology: the role oforganizational activities
Although existing research insists that it is theindividual rather than the organization that createsknowledge, the importance of the organizational
context is compelling (Grant, 1996; Nonaka, 1994).
The role of the organization in creating related
activities can be roughly classified into two
categories: 1. enhancement in knowledge
production, such as BA construction for knowledge
workers (Nonaka and Konno, 1999), crystallization(Nonaka and Takeuchi, 1995); and 2. optimizationofknowledge
application,
includingthecoordination of the specialists’ efforts (Grant, 1996),
and the deployment and utilization of intangible
assets (Teece, 2000). In short, the organization acts
as an activator – while the individual as an actor.
These justifications work well when revealingorganizational mechanisms during the creatingprocess; however, they place the individual at thecenter of a conscious knowledge-creation processsimilar to a black box.
The
individual
conscious
black-box
phenomenon is caused by the absolute distinction
between the role of the organization and that of theindividual in the creation of knowledge. De factoorganizations are capable to accomplish all fourmodes of the knowledge-creation process –socialization, externalization, combination andinternalization – insofar as we adopt Barnard(1938)’s definition of organization seen as“purposeful cooperation”. The issue of whether theindividual or the organization is at the root ofknowledge creation is pointless since it can belikened to a chicken-or-egg discussion. Based on
the idea that organizational creating activities occur
in parallel to individual ones, the SECI modes canbe considered as the epistemological basis for themodel.

appropriation. In this model, it is thecounterclockwise ontological shifting (in Figure 1)
from individual to group, organization, social
network and then back to individual. Boom-up
shifting can occur from any of the four
epistemologicalmodes
ofsocialization,
externalization, combination and internalization, as
shown in Figure 2.

Transmitter

Contribution

C

Activity

S-Boom-up

CommonInvolve more stake holders
understanding of in discussion to achieve
the circumstance contribution

E-Boom-up

Explicit
knowledgeknowledge
carrier

Report, delivery, or display
or the contribution to receiver
layer

Smoothutilization
adaptation

Spread the contribution toand the receiver layer byintensive application

Table 2 Boom up from the ４ modes
S
I
Group

PTK
I
IndividualE

C-Boom-up Justification and Force the receiver layer
feasibility
accept the contribution byresearchorganizational consensus or
power.

S
E
Organization
I
C

C

C

Ontological shifting can not take place unlessmembers in receiver layer are involved in any
creation modes in transmitter layer. Creation ubiety
is changed to the receiver layer when boom up in
any modes (SECI) carries contribution of former
activities to the receiver layer. Boom-up from thefour modes submits these activities andcontributions by different means. (Table 2)

I-Boom-up

E

S/PT
K
I

E

Figure 2 Boom-up

2.2 Four ontological layers as creating nursery
In this paper, we use Nonaka and Takeuchi’s(1995) first three ontological levels of individual,group, and organization, and “social network” inplace of the inter-organization layer. Social
networks are formed by the two essential elementsof “actors” and “relationships” (Wasserman and
Faust, 1994). There are two reasons to use “social
network” instead of “inter-organization”. First,
according to its definition, the structure of a social
network is comparable to that of the otherontological levels (group and organization) andconsists of both subjects and their interdependency.
Second, a social network involves related
individuals besides organizations, and covers abroader domain in knowledge creation activities
outside the organization. Consequently, we consider
the four ontological levels to be individual, group,
organization and social network (Figure 1).

S
I
SocialS/PT
K
I

ReceiverE
CE
C
Boom-up

2.4 The Slip-down spiralDefinition: Slip-down is the process whereby
the knowledge creating subject exploits hidden
value from its available knowledge resource. It isthe clockwise ontological shifting (in Figure 1)
from organization to group, individual and social
network. Unlike boom-up, slip-down is always adiscrete process happening between successfulboom-up processes. Similar to boom-up, slip-down
can occur from any of the four modes of SECI.
However, when a slip-down takes place, it
generally means that the final SECI mode before

Slip-down

Figure 1 Four ontological layers
2.3 The boom-up spiralDefinition: Boom-up is the process whereby theknowledge creation subject spreads its contribution
to the decision center nearest to organizational rent-

222the slip-down occurred can not successfully deliver
the expected knowledge conversion (Figure 3).
S/PTK

Transmitter Layer
I

down

E
C

Slip-down often takes place when theknowledge creating layer has difficulty in continue
the SECI activities within it bases on current
process. When organization stopped its running
SECI circle and distributes knowledge creation
work to a specific group or individual, no matterconsciously or unconsciously, it is a slip-down
process that exploit its hidden value. When
individual met difficult and ask his/her social
network for help, it is also a typical slip-down
process that the potential knowledge resource isrecalled.
BetweenSNandorganization,organization always works as knowledge resource
for the whole society and create knowledge for theoutside needs. It can not work if the specific modeslipped can not find its ground – if such mode is not
successful also in the receiver layer. (Table 3)

Time
Sept. 1, 1998
Aug.
1999

S-Slipdown

E-Slipdown

Knowledge
can
not The receiver layer as on
externalized to be clear oftheavailable
concept or product in the knowledge resource islayer
recalled to accomplish it

C-Slipdown

TheknowledgeThose who believes its
contribution is justified tofeasibility
workedbe unfeasible according
forward to a more
to objective or capability
persuadable outcome
within the layer

I-Slipdown

Those who are able toTheknowledge
comprehend or utilize
contribution can not be
continue the creation
comprehended or utilized
project

21,

Aug. 1, 2000
Aug. 1, 2001

Activity

Marketed productUltrasonicWashing
Machine(ASW-EP80A/EP70A)
Leaning Washing Machine (ASWEP800/EP700)
Half-detergent Washing Machine(ASW-EC801/EC701)
Detergent-free Washing Machine(ASW-ZR800/ZR700)

Table 3 Sanyo’s Development towards Detergent Free

Amongst the four phases, the first one faced
most difficulties therefore it will be illustrated inthis report.
Case description: In 1995, Kawazoe took the
responsibility of sales director in laundry BU of
Sanyo. At that time, all producers in laundry market
targeted on similar style of performance innovationin their products: such as stainless washing tanks,bigger capacity, reutilization of bath water and soon. Sanyo has high reputation in the laundry market,
and was called “Washing-Machine Sanyo”.
Therefore, Kawazoe is very unsatisfied with thesituation of homogenous competition. Since hisskin is sensitive to lotions, Kawazoe got an idea:
Why not develop a lotion-free washing machine?
He got inspiration from the ultrasonic glasses
cleaner. Since he is not a researcher but a salesman,
Kawazoe expressed his ideas to R&D engineers.
“Impossible.” That was what they replied. Nevereasily giving up, Kawazoe visited Hiroda, teamleader of drying machine development, who shows
partially interest in Kawazoe’s ideas. Hiroda start
his research and experiments, with continuous
advices from Kawazoe. After many failures, hesuccessfully developed the ultrasonic washingmachine which requires less lotion. At first, the topline was hesitating about the safety of ultrasonic.
Kawasoe persuaded them by remind them theultrasonic diagnosing machine used for pregnant
women. In 1st Sep. 1998, first series of ultrasonic

Activity

Impossible
forthe Gather part of thesenecessary
tacit- holders or directly use
knowledge holders sit tacit knowledge from an
and discuss with together isolated individual

Knowledge

washing machine
Sanyo’s innovation towards the detergent-freewashing machine can be divided into four phases:
decreasing the amount of required detergent in theultrasonic washing machine, creating a leaning-tankwashing machine, cutting the amount of required
detergent in half in the leaning-tank washingmachine, and creating the final detergent-free washmachine (Table 4).

Figure 3 Slip-Down

Failures

Effective

3.1 Case description: towards the detergent-free

C

I

for

Visualization

E

S/PTK
Receiver Layer

3. Keep the Spiral Moving: Boom-up and Slip-

Table 4 Slip-down from 4 modes

223

washing machine called ASW-EP80A/EP70A
entered market.
Now do the demonstration.
Firstly, define the start point of this loop.
Kawazoe works as the most important activist andtherefore his activities is taken as the start point.
Secondly, determine ontological layers oforganizational creation. The organization is Sanyo
firm which is able to put products into market
directly. In this case, there are two group layers
which are active in knowledge creation: R&D as
formal group and Twosome of Kawazoe and Hiroda
as informal group. Kawazoe is in the individual
layer. Social network, in this phase, refers to themarket and competition circumstance. Finally, draw
the arrows of creation flow. The knowledge
creation project could be described by the following
figure. (Figure 4)
13th

I

S
12th

S
14th

R&D

C
Organizatio

S

E

10th

3rd

Social
1st
I

PTK
2nd

7th 8th
4th

E
C

The model presented in this paper is only a starting
point. Although enablers are essential inorganizational knowledge creation, it is notnecessary for every firm to activate all enablers andrealize boom-ups in all SECI modes. A given firm’sknowledge creation capability may be unbalanced
among all four SECI modes and therefore
knowledge-creation routes specific to that firm may
be necessary. The routing design consisting ofstrategies for boom-ups and slip-downs is thus
crucial for organizational knowledge-creating
research. In addition, this ontological model has thepotential to uncover not only mechanisms within
the organization, but also affect individual
contribution and institutions present in theenvironment. It considers outside social networks as
an indispensable field to continue the organizational
knowledge creation spiral, and regards individuals
as the nerves stimulating organizational creation
activities. Based on this holistic view oforganizational knowledge creation, we plan ondeveloping a methodology to enhance theinteraction between layers and create connecting
points.

C

E
C

Ontological shifting is essential to organizational
knowledge creation project. It denotes the transferof ownership of knowledge itself and of theknowledge creation project and realizes rentyielding potential of knowledge resource. We
described the two types of ontological shifting,boom-up and slip-down, which indicate theexistence of enablers and barriers respectively.
Sanyo’s case was used to demonstrate theusefulness of the model. Compared to Nonaka’s
five enablers and Szulanki’s nine barriers, thebarriers and enablers derived from the direct
observation of ontological shifting is more practicaland can be applied to the entire knowledge-creation
project.

11th

E

I
I

layer. This model uncovers the underlying
isomorphism of knowledge creation in all
ontological layers, and uses SECI as its
epistemological basis.

9th

S 6th
E
I
C
Kawazoe & Hiroda

5th

KawazoeFigure 4 Ultrosonic washing machine
Each successful boom-up is enabled by aspecific organizational or social characteristic, as
shown below.
1. Strong intention of knowledge activist
2. Communication channels with people fromdifferent
functionsand with top
management
3. Autonomy in the establishment of an
informal workgroup
4. Hierarchical power used to overcome
reluctance
5. Overlapping
consideration
andunderstanding of R&D and marketability
simultaneously
6. Innovation meetings as organizationalroutines

References[1]

Barabas, C. (1990), Technical Writing in a
Corporate Culture. Ablex, Norwood, N.J..

[2]

Barnard , C.I. (1938).The Functions of the
Executive, Harvard University Press.

[3]

Delong,.D.W. (2004). Lost
Oxford University Press.

[4]

Drucker, P.F. (1993). Post-Capitalist Society.
Butterworth/Heinemann, Oxford.

Conclusion and Future research
The ontological model is demonstrates how
knowledge creation activities occur throughout andout of the organization. Knowledge creation
sometimes starts from individual inspiration, booms
up to the group, the organization and a social
network
towards
rent
appropriationandaccomplishes different tasks in each ontological224

Knowledge,

[5]Grant, R.M. (1996). Toward a knowledgebased theory of the firm. Strategic
Management Journal, 17, 109–122.

[6]

Kakabadse, N.K., A. Kakabadse and A.
Kouzmin (2003) . Reviewing the knowledge
management literature: towards a taxonomy.
Journal of Knowledge Management, 7 (4), 7591.

[7]

Nonaka, I. and H. Takeuchi (1995). The
Knowledge-Creating
Company.
OxfordUniversity Press.

[8]

Nonaka. I.(1994). A Dynamic Theory ofOrganizational
Knowledge
Creation.
Organization Science, 5(1), 14-37[9]

Nonaka, I. and N. Konno (1999). The Conceptof ‘Ba’: Building a foundation for knowledge
creation, The Knowledge Management
Yearbook
1999-2000,
ButterworthHeinemann.

[10] Krogh., G.V., K. Ichijo and I. Nonaka (2000).
Enabling Knowledge Creation: How to
Unlock the Mystery of Tacit Knowledge andRelease the Power of Innovation. Oxford
University Press.
[11] Simon, H.A. (1997). Administrative Behavior– a Study of Decision-Making Processes in
Administrative Organizations (4th edition),
The Free press.
[12] Szulanski, G. (2003). Sticky knowledge:
barriers to knowing in the firm. Sage.
[13] Teece, D.J. (2000). Managing intellectual
capital: organizational, strategic, and policy
dimensions. Oxford University Press, NewYork.
[14] Wasserman, S. and K. Faust (1994). Social
Network Analysis: Methods and Applications,Cambridge University Press, 1994.
[15] Wiener, Y. (1988) .Forms of Value Systems:
A Focus on Organizational Effectiveness andCultural Change and Maintenance. The
Academy of Management Review, 13(4), 534545.
[16] Wilensky,
H.L.(1967).
Organizational
intelligence: knowledge and policy ingovernment and industry. Basic books.

225

The Endless Knowledge Creation: Strategies and Institutions
Yue Wu**Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
wu.y.ac@m.titech.ac.jp
The knowledge creation study up to now is bounded in a macro view: take a creation
project as a whole object in research. Thus it was difficult to find out the mechanism that
how the institutions effect on knowledge creation and what kind of institutions have effecton which specific aspect. In this report, the organizational knowledge creation activities ismodelized as a closed loop with subdivided activities. Knowledge creation could rise in anyof the four layer of Individual, Group, Organization and social network, trigger thecollective creation activities in the next layer, and finally influence on the original layer by
the interaction with internal and external creation entities. Based on such understanding,
the knowledge creation activities is categorised into two groups of key activities: intralayer creation and inter-layer creation. The institutions, as isormorphic pressure anddifferentiation strategy have positive influence on each of them.
Key Words: Knowledge spiral, Ontological model, Boom-up, Isomorphic Pressure,
Differentiation Strategy
1. Introduction
During the recent half century, knowledge
creation theory has tried to contribute in three main
fields: discovery of enablers and barriers (Nonaka
and Tacheuchi, 1995; Krogh et al., 2000; Szulanski,2003), improvement of organizational infrastructure(Delong, 2004), and examination of knowledge
creation mechanisms (Nonaka and Tacheuchi, 1995).
However, lacking of solid evidence and visible key
process in knowledge creation, there are always gaps
in the theory construction and practical instruction.
Therefore, this research has two contents: Visibility ofknowledge creation key process by constructing
practical model; and examination institutional
congruence based on such model.
Knowledge creation has two dimensions:
epistemological and ontological. The epistemologicalresearch of knowledge creation has been welldeveloped: Current theories of knowledge creation
theories define knowledge creation process as
conversion between tacit knowledge and explicit
knowledge. Such conversion including socialization,
externalization, combination and internalization(SECI).( Nonaka and Tacheuchi, 1995). Suchperception is the premise of this study. However,Nonaka regards knowledge creation as a one-way
spiral ontologically, as the figure shows below.

l dFigure 1 Knowledge Creation Ontology (Nonaka, 1995)
This figure illustrates the knowledge creation
activities as one-way SECI from individual to interorganization. However, such a model indicate two
assumptions: 1. the knowledge creation reachs a
end after it become a “inter-organization” activity. 2.
The knowledge spiral goes naturally fromindividual to inter-organization ontologically, when
it successfully continue the SECI spiral
epistemologically. These assumptions are not as226solid as we thought. In real cases, it always happensthat a individual creation activities lasted many
years and had great contribution but never turned
into organizational creation activity. Therefore, thisresearch focus on the ontological aspects: the dynamicof stakeholders and knowledge creation entities.
This research has two phases. Firstly it visualized
the knowledge creation key process, and constructs amodel for knowledge-creation process throughout andout the firm. And based on such model, this research
examines the institutional congruence of knowledge
creation activities in each model. It has potential to: 1.
Help managers to diagnose the project and findspecific enablers/barriers in a certain organization. 2.
Help researchers find mechanisms and adopt
operational approaches to enhance each step in acreating project.

In this example, the layer shifting follows 3
steps.
(1)
Knowledge creation activities (SECI)
took place in the transmitter layer.
(2)
In a certain circumstance, thetransmitter layer express their result
through one path of SECI to thereceiver layer.
(3)
Such activity enables the knowledge
creation activities continue in thereceiver layer.
2.2 Inter-layer knowledge creation
There are two kinds of inter-layer knowledge
creation: Boom-up and Slip-down. Considering the
epistemological description of knowledge creation,
there are S-boom-up, E-boom-up, C-boom-up, and Iboom-up, as well as S, E, C or I slip-down. Figure 2 isa typical E-Boom-up.
Definition: Boom-up is the process whereby theknowledge creation subject spreads its contribution
to the decision center nearest to organizational rentappropriation, from Individual to group,
organization, social network and then individual.
Definition: Slip-down is the process whereby theknowledge creating subject exploits hidden value
from its available knowledge resource. From
Individual to social network, organization, groupand then individual.

2. Key Activities in Knowledge Creation: Boomup, Slip-down and intra-SECI
2.1 Creation Entity and Layer Shifting
In this paper, we use Nonaka and Takeuchi’s(1995) first three ontological levels of individual,group, and organization, and “social network” inplace of the inter-organization layer. Social
networks are formed by the two essential elementsof “actors” and “relationships” (Wasserman and
Faust, 1994). There are two reasons to use “social
network” instead of “inter-organization”. First,
according to its definition, the structure of a social
network is comparable to that of the otherontological levels (group and organization) andconsists of both subjects and their interdependency.
Second, a social network involves related
individuals besides organizations, and covers abroader domain in knowledge creation activities
outside the organization. Consequently, we consider
the four ontological levels to be individual, group,
organization and social network.
Layer shifting emerged when a knowledge
creation activity extend its influence to the otherlayers. Figure 2 is a common example to show such
dynamics.

ReceiverTransmitter

S/PT
(3)
K
I
S/PT
K (1)
I

2.3 Intra-layer Knowledge Creation
On the other hand, intra-layer knowledge
creation, which is regarded as the traditional SECI
are also important. In figure 2, intra-layer
knowledge creation took place in the (1) and (3)steps. All modes of SECI takes place in each layer
except individual layer - within individual layer,
personal tacit knowledge (PTK) itself forms thecreating resource and derivate new perception.
Therefore, “personal tacit knowledge” locates on
individual layer instead of “socialization”, and is
the headstream of all knowledge flows in creating
activities.
2.4 Keep a Eye on Key Activities: theOntological Model

E
C

S
E
Organization
I
C

(2)
E
C

S
I
Social

S
I
Group

E
C
PTK
I
Individual

Figure 2 Layer Shifting
Figure 1 Four ontological layers

EC

Figure 3 Ontological Model

227

E
C
Intra-Layer
InterlayerIn this model, key activities are the intra-layer
SECI, as well as SECI-boom-up and slip-down.

3.2 Case description
These hypotheses are created by theobservation of voice-coder creation in ZTE
Corporation. ZTE is the largest listed
communication company in China, and have morethan 50 thousands of employees. In the end of lastcentury, ZTE start the CDMA related development
and research. Voice-coder is a necessary part in theCDMA communication system. However, at thattime all voice-coder is produced by Qualcomm.
Further, all technical standards for the voice-coder
are created by Qualcomm. Communicationcompanies have to by it from Qualcomm, the only
provider. The knowledge creation project of voicecoder started from Mr. Zhang, a common engineer
at that time. The processes could be described asfollowing.

3. Institutional Congruence on Knowledge
Creation
3.1 Concept Definition and Hypothesis
Based on the perception that key activities inknowledge creation are the inter-layer and intralayer SECI, the institutional congruence ofknowledge creation could be analyzed. This
research examines the institutions as isomorphic
pressures and differentiation strategies. Institutional
isomorphism is caused by the efforts to achieve
rationality with uncertainty and constraint lead tohomogeneity of structure (DiMaggio & Powell,.
1983). Differentiation strategy means creatingproducts that are being packaged as unique (Porter,1980). Isomorphic pressure and differentiation
strategy are pair of opposite concepts, however,they interact each other and can cause each other ina certain of circumstance (Senoo and Nomura,2009).
Differentiation strategy and isomorphic
pressure is a pair of opposite concept. However,they can interact and cause each other. This
research present a hypothesis based on case study
which integrate them together and analyze theirinfluence on knowledge creation during dynamics,
as Figure 5 shows.

(1)

Pressure

Isomorphic
PressureBA(2)

on Strategy

a)on Strategy

(3)

(4)
Enab

BA

KC
Inter-layerf)Boom-ups &Slip-Downs

Intra-layer
Enab

b)

Knowledge
Creationc)a) Mr. Zhang found himself had the knowledge
and technical experience to develop the speechcoder instead of buy it from monopoly (Qualcomm).
He want to break the current mode.
b)Such differentiation strategy enhanced his
intention to do experiments; his group, which also
helds the interests of be different, give him
necessary atonomy. Directed by the differentiation
strategy, more speciality and academic fields haveto be involved and led to variety, redundancy andcreative chaos.
c)Mr. Zhang made the experiments and worked
for it for several years (Intra-layer SECI). As the
project going forward, it required more resourceand people. Mr.Zhang collect his result and prepare
to submit it to the company.
d)On the other hand, although Mr.Zhang wang
to create a different product, he have to obey themarketprinciples,
evaluation
criterias,organizational processes and existing standards
which formed the isomorphic pressure.
e) These same perception give Mr.Zhang’sgroup member a shared understanding on his work,and enhanced BA.
f)Thecompany
accepted
Mr.Zhang’s
contribution and set up a new team under his
direction. The personal creation turned to be agroup creation.

Inter-layer
Boom-ups &Slip-Downs

Differentiatie)Differentiati

KC

Institutions
Isomorphicd)Institutions

Intra-layer
Knowledge
Creation

Figure 3 Ontological Model
H1. Isomorphic Pressures have positive effectin constructing BA.
H2. Well constructed Ba has positive effect inthe ontological shifts: boom-ups and slip-downs.
H3. Differentiation strategy have positive effectinenhancing
Knowledge
Creation
Enablers.(Intention,
Variety,
Autonomy,
Redundancy, Fluctuation and Creative Chaos)H4. Enablers have positive effect in intra-layer
knowledge creation.

228[10] Szulanski, G., 2003, Sticky knowledge:
barriers to knowing in the firm, strategy series,
Sage, P18

3. Conclusion and Further Research
A four-layer model of Knowledge creation
activities sometimes start from individual
inspiration, boom-ups through group, organizationand social network towards rent appropriation.
Knowledge creation has different tasks to completein each ontological layer. This model discovered
the underlying isomorphism of knowledge creationin all ontological layers, and regards SECI as the
epistemological base for model demonstration.
In this research, we presented a hypothesis thatthe isomorphic pressure and differentiation strategy,
as two aspects of institutions, have influence on theknowledge creation key processes both inter-layer
and intra-layer
In this report, only case-study is adopted toprove the later hypothesese. In furture study, morequalitive and quatitive research should be
implemented, including questionair analysis, hard
data and interviews.
References[1]

Delong,.D.W., Lost Knowledge,
University Press,. 2004

Oxford[2]

DiMaggio, P. and Powell, W. (1983) The ironcage revisited: institutional isomorphism andcollective rationality in organizational fields.
American Sociological Review 48:2 , pp. 147160.

[3]

Krogh., G.V.; Ichijo., K.; Nonaka., I.;
Enabling Knowledge Creation: How to
Unlock the Mystery of Tacit Knowledge andRelease the Power of Innovation, Oxford
University Press, 2000

[4]

Nonaka. I, A Dynamic Theory ofOrganizational
Knowledge
Creation,
Organization Science, Vol. 5, No. 1, (Feb.,
1994), pp. 14-37[5]

Nonaka. I, Konno., N (1999), The Concept of‘Ba’: Building a foundation for knowledge
creation, The Knowledge Management
Yearbook
1999-2000,
ButterworthHeinemann[6]

Porter, M.E. (1980) "Competitive Strategy",
The Free Press, New York, 1980.

[7]

Senoo, D.; Nomura, T., Promotion ofOrganizational Knowledge Creating by
Reforming Ba; SIMOT Symposium 2009

[8]
[9]

Simon., H.A., Administrative Behavior – aStudy of Decision-Making Processes in
Administrative Organizations (4th edition),
The Free press 1997229

A Study on Intellectual Property Management,
Techonology Development and Worker’s Skill Development in Thailand- Automotive Parts Industry Chan-orn Bongsebandhu-phubhakdi**

Graduate School of Innovation Management
Tokyo Institute of Technology
3-3-6 Shibaura, Minato-ku, Tokyo, 108-0023 JAPANb-p05@mot.titech.ac.jp
This study investigates Intellectual Property management and the relation between
technology development and worker’s skill development in Thailand, specifically in thefield of automotive parts industries. The interviews to six firms, Japanese and Thai owner
firms, were conducted. The investigation by interviews shows that although the firms havedeveloped their technology and worker’s skill relatively, they still have problems of lack of
IP management.
Table: 2 Number of Granted Patent
Granted Patent
Year
Total
Thai
Foreigner
2001
1,516
418
1,098
2002
2,466
635
1,831
2003
2,326
797
1,529
2004
2,044
867
1,177
2005
1,322
505
817
Source: Thailand’s Patent Office

1. Introduction
1.1 Intellectual Property System in Thailand
Thailand has the law relating to patents,
trademark, copyrights, and design since 1979 and
the Central Intellectual Property and International
Trade Court (CIPIT) was set up in 1997 after Thai
Government approved on Agreement on TradeRelated Aspects of Intellectual Property Rights,
including Trade in Counterfeit Goods (TRIPs) in
1993 to be special court deal with Intellectual
Property(IP) and International Trade cases.

1.2Intellectual
Property
Situation in Thailand

The number of patent applications in Thailand
has gradually increased from 7,994 applications in2001 to 10,885 applications in 2005. (Table 1)
However, there are a lot of backlog to be examined.
There are only 1,322 granted patents in 2005
because of a lack of experts for examination. (Table
2)

Although Thai government has taken theanti-imitation campaign into action, number of
infringement cases in Intellectual Property rights,
especially, Copyrights (CD,DVD) and Trademark
does not reduce as well.

Table 1: Number of Patent Application Classified by
Selected Countries
Unit: Number
Country ofApplicant
Thai
US
Japan
EU
Total

Infringement

2001

2002

2003

2004

2005

2,504

3,030

3,426

3,428

4,258

1,567

1,266

1,359

1,429

1,625

1,711

1,533

1,631

1,762

2,150

1,241

1,116

1,401

1,419

1,789

7,994

7,726

8,574

8,942

10,885

Source: Thailand’s Patent Office230

According to the comments of a patentlawyer in Thailand, as technical level of Thailand’s
industries has risen gradually, number of design
imitation goods has also increased. Because someof Thai manufacturers do not have the idea offostering their original brand and do not properly
have knowledge of Intellectual Property rights,
according to the comments of a manager ofThailand Automotive Institute.
CIPIT Statistics shows Intellectual Property
infringement cases that brought to CIPIT in 2005
are 5,756 cases (Total amount in dispute of civil
cases is about 3.59 billion Yen.) Trademark cases
are the most among all infringement cases.
Moreover, number of Intellectual Property
infringement cases has gradually increased in thepast 5 year. (Table 3)Table 3: Number of Intellectual Property
Judicial Case in Thailand (2000-2005)

is growing relatively and its production amount hasreached 1 million units milestone in 2005.[2]Year

2.2 Automotive Parts Industry

Criminal
Civil
Total
case
Case
2000
2,141
102
2,243
2001
3,252
138
3,390
2002
3,582
157
3,739
2003
4,001
173
4,174
2004
5,354
212
5,566
2005
5,565
191
5,756
Source: Thailand’s Central Intellectual Property andInternational Trade Court

According to the increasingly growth ofautomotive industry, the automotive parts industries--the supporting industries-- which commenced
altogether with automotive industries in 1960’s,
have to adapt themselves to contribute substantiallyto manufacturing parts for all automotive
production.
It is said that Thailand’s Automotive Parts
Manufacturing sector has a lack of appropriate
skilled workers, because the growth of automotive
parts industries have been rapidly.

2. Automotive Industry in Thailand
2.1 The growth of Automotive Industry

Therefore, Thai Government has cooperated
with Automotive Non-government organization (ex.
Thailand Automotive Institute--TAI, Thailand Auto
Parts Manufacture Association--TAPMA) to makeprojects to resolve some of these problems, such as
Skilled Certificate System for Automotive Industry
which started in 2006 and Automotive Human
Resource Development Program--AHRDP whichstarted in 2007, etc., according to the comments ofmanager of Thailand Automotive Institute.

According to the phenomenal growth ofautomotive industries in Asia since 2000, Thailand
automotive and parts industries need to challenge
their competition against other Asian countries. To
broaden the productivity in automotive sector,
Thailand’s government has carried out the ‘Detroitof Asia’ policy in 2004. The policy promotes thedevelopment for both quantity and quality ofAutomotive technology in Thailand so that the
Automotive industries become the center of
automotive production, information and technology
in the Asia and aims to have the automotive
industries in Thailand produce automotives 1
million units in 2006 and 1.8 million units in 2010.
[1] (Table 3)

Thailand’s automotive parts industries havedeveloped their technical levels by degrees by Thaigovernment incentive policy and their necessity todevelop technology for new model of products or
cost reduction.

Table 3. Thailand’s Quantitative Targets for2006 and 20102003

2006 target

2010 target
1,800,000
742,000 units
1,000,000
units
Automobion(No.16 in theunits(No.9 iniles
world)
the world)
Export400,000
800,000
235,000 units
units
units
MotorcycProduct2,424,678
2,500,000
3,000,000
units
units
units
les
ion
Export500,000
600,000
604,775 units
units
units
ExportOEM:
OEM:
OEM: bt27.5
bt27.5
bt27.5billionbillionbillionParts
REM: bt86.8
REM:
REM:
billionbt86.8bt86.8billionbillionbt114.3
bt114.3
bt114.3
Totalbillionbillionbillion(bt:Thai currency baht)
Sources: Thailand Automotive Industry Directory
2005-2006
Product-

Consequently, Thailand’s automotive industry

231

Under Thai government incentive policy, thecompanies who invest in Automotive R&D field
will receive a tax exemption incentive fromThailand Board of Investment (BOI). As a result,the major automotive industry and parts industries,
such as Toyota and Honda set up their R&D Centeras well as Denso.
In this study, the investigation by interviews
was made about (1) Intellectual Property
Management and Intellectual Property Infringement,(2) Technology Development and Worker’s Skill
Development of Thailand’s Automotive Parts
Manufacturers.
3. Literature Review
In the context of IP management study ofThailand, there is the study of N. Cheeptham et al.
(2001) about IP management in university level.
They indicated that Thailand has the problems ofintellectual property in universities which include apoor negotiating position in formulating licensing.
Improvements at the universities proposed toaddress these issues embrace setting up intellectual
property departments within each university andsubstantially increasing the level of intellectual
property awareness in both under- and postgraduate
courses. [3]corresponding IP rights.
- Interest in Intellectual Property
Rights
The two Japanese Owner sampling firms arefound to be interested in registration of their
Trademark. All of them are not interested inapplications for patent rights.

T. Laosirihongthong et al. (2003) investigated
the usage of New Manufacturing Technology(NMT) and showed how important to manage theusage and applicability of these systems in Thai
Automotive industry. [4]N. E. Waldeck et al.(2005) reported on theimportance of workforce development in the
successful
implementationofadvancedmanufacturing technologies (AMT) and the impactsof environment and human resource (HR) manager
perceptions on the provision of workforce
development activities.[5]The sampling firms do not have specificperson who is directly responsible for managementof IP and so they do not consult with any Patent
Law Office even most of Trademark-holder firms
have faced the trademark infringement or design
infringement.
However, all of Japanese Owner firms areinterested in participation in the IP Seminar to get
the knowledge about IP and IP management.

4. Research Methodology & Results
4.1 The Interviews
The main purpose of this research is to examine
the intellectual property management and therelations of technology development and worker’s
skill development of Thailand’s automotive parts
manufacturers.
The interviews were conducted in March-April
2006, to 3 Japanese ownership firms and 3 Thaiownership firms in the area of Bangkok andsuburban.(Table 4)
Table4 Basic Information about Automotive
Parts Manufacturers Interviewed
Auto A
Auto B
Auto C

Establishment
1997
1969
1987

Auto D
Auto E
Auto F

1974
1970
1940

Ownership
JapaneseJapaneseJapanese
Thai
Thai
Thai

Main products
Plastic Parts
Rubber Tire
Aluminum
Alloy
Wheel
Press Parts
Clutch Discs
Non-tire Rubber

The Questionnaire was regarding IP
management (IP applications and rights, R&D
department and so on), Technology (Quality system,
CAM,CAD technology and so on) and Worker’s
skill (employment requirements, in-house or outsidetraining and so on).
4.2 Results
4.2.1 Japanese Owner Firm
- Intellectual Property Infringement
Due to rather low amount of infringement
and a lack of IP management system in the firms,
the infringement of products in Automotive Parts
Industry does not impact to the sampling firms.
Even though they found some imitation goods,
Trademark infringement in After Service Market orsome design imitations, they decided to take nomeasures to resolve these problems because volumeof imitation is low and they do not hold- R&D and Technology Development
One sampling firm does not have R&D
section, because it is a Make-to-order firm and noton After-service market. For the other 2 firms,
being on After-service and import market, it isnecessary to develop their technology and qualityof their products to be competent for manufacturing
requirements of products. Their R&D sections aremainly responsible for product design or
improvement of technology use in the plants rather
than inventions.
Three Japanese owner firms have changed
their machines into Automatic Manufacturingsystem in the past 5 years. Robotic technology isnecessary for them in order to replace workforce inthe jobs under high temperature and with heaviness.
- Skilled Worker Development
1 of 3 firms employs their workers/operators
as permanent workers. The other 2 firms employ
both permanent workers and subcontract workers.
Subcontract employment system is regularly usedin the industrial estate that has the competition in
job employment. Minimum educational backgroundof their employees varies, junior high school level,high school level or professional school level.
All of Japanese Owner firms sent theiroperators/technician to outside the company
training program, such as Thailand Automotive
Institute (TAI), Thai-German and also have foreign
training system. Most of them found that
operators/technicians have got a related knowledge
and have broadened their views about working
method.
4.2.2 Thai Owner firm
- Intellectual Property Infringement
Automotive parts product infringement do
not directly affect to the Thai owner sampling firms.
Although there are some Trademark infringement inThailand’s After Service market and China’s
market, the volume is not so much as they will232

bring the cases to the court.

Automotive Parts Industries have gradually
increased in volume of productivity andtechnology; a lack of IP Management system is still
be problems that ought to resolve immediately to
avoid and protect IP rights infringement in intensity.
The future works of this research are analysis ofdata from interview and questionnaire andinvestigation into how to enhance appropriate IP
management Model to automotive parts firms.

- Interest in Intellectual Property
RightsAs the same as Japanese Owner firms, Thai
Owner firms are interested in registration of their
Trademarks, except one which are OEM’s made-toorder firms, and all of them are not interested inapplications for patent rights.
2 of 3 firms are interested in participation in
IP Seminars to get the knowledge about IP and IP
management.

References- R&D and Technology Management
One of 3 sampling firms does not have R&D
section due to being Make-to-order firm. The firm
is not on After-service market. The other two are on
After-service and import market and so it isnecessary for them to develop their producttechnologies.
The development of technology andtechnology usage in Thai owner firms is up to their
executive view of doing business. All of them arefamily business.
Thai owner firms developed their technology,
considering as their priorities.

[1]

Cosmic Enterprises’ Editorial and Research
Team, 2006. Detroit of Asia in the 21stCentury, Thailand Automotive Industry
Directory 2005-2006 125-131.

[2]

The Japan Research Institute Limited, 2006.
Asia Monthly, http://www.jri.co.jp/english/
asia/2006/03/country.pdf[3]

Cheeptham, Naowarat and Chantawannakul,
Panuwan,2001.
Intellectual
Property
management
andawarenessinthebiotechnology era: a Thai perspective. World
Patent Information 23(2001) 373-378.

- Skilled Worker Development
All of Thai Owner firms employ theirworkers/operators as permanent workers. Minimum
education for their employees is Junior High Schoollevel or High School level with English Proficiency.
Standard workforce training system of Thai
Owner firms is Orientation (1/2-1 day) and OJT
system. 2 of 3 firms have follow-up training system
which deals with Quality Control, and Technicalskills.
2
of
3
firms
have
sent
their
operators/technician to outside of the company fortraining program. Most of them satisfied with
development of operator’s skill after the training
program. One firm prefers in-house training thanoutside training, because it can watch employees
through the in-house training course.

[4]

Laosirihongthong, T., Paul, H. and Speece,
M.W., 2003. Evaluation of new manufacturing
technology implementation: an empirical
study in Thai automotive industry.
Technovation 23(2003) 321-331.

[5]

Waldeck, Nancy E. and Leffakis, ZacharyM., 2005. HR perceptions and the provision of
workforce training in an AMT environment:
An empirical study. Omega In Press.

[6]International Intellectual Property Protection
Forum, http://www.iippf.jp/01/pdf/0403senshi
njirei/2-2-08.pdf[7]Japan Patent Office, 2005. The Fact-finding
Report on Circulation of the Chinese Imitation
Goods to Third Countries (Japanese),
http://www.jpo.go.jp/torikumi/mohouhin/moh
ouhin2/kanren/pdf/china_mohou/02.pdf

5. Conclusion
The investigation by interviews shows that,regardingThailand’s
Automotive
Parts
Manufacturers,
1) IP management and IP Infringement are notconsidered as a serious matter to protect,evaluate, and be practical.
2) Technology has been developed relatively andthe development depends on Technology
transfer from Head Office and their own
development.
3) Automotive Parts Firms are attentive to develop
worker’s skill in satisfaction level.
The research found that even Thailand’s

233

The dynamics of Knowledge Spillover for functionality
development in Japanese Acoustic Equipment Industry
Yosuke Shibata
Graduate School of Innovation Management, Tokyo Institute of Technology

shibata.y.ah@m.titech.ac.jp
1. Introduction

4. Analyzing model of Knowledge Spillover

A plethora of papers has been published discussing the usefulness ofKnowledge Spillover as one of the foremost factors in encouraging thedevelopment of technological innovation. Many previous papers havemainly discussed the Knowledge Spillover at the level of countries,
industries, or companies. From the viewpoint of an institution, we discuss
the Knowledge Spillover by taking the difference of characteristics inindustries and also in technologies into consideration. The purpose of thisstudy is to propose a new scope of Knowledge Spillover between
technologies in a product.

2. Technological development in a speaker industry

The number of patent applications is used as an indicator of innovation.
It is demonstrated that the number of patent applications began to increase
rapidly in the late 1990s. Obviously, innovations in speaker technologies
occurred at that period.
Electro-acoustic equipments are classified by IPC as [H04R]. As BasicTechnology, we chose two types of transducers (H04R9, H04R17). As
Complementary Technology, there are three main devices; namely the
Component (H04R1; mechanics), Circuit (H04R3; electronics), andDiaphragm (H04R7; materials).We use patent data to analyze the relation
between innovation and Technological Knowledge of Basic Technology andeach Complementary Technology.

We focus on a speaker as a main product. By a historical analysis of apatent application, the functionalities of a speaker are found to be developedin two stages. In the first stage, Basic Technology is developed in order tohave products working by focusing on structural technologies. After the
structural technologies have already been developed to a certain level, at thenext stage, the functionality of a product is developed. In this process,Knowledge Spillover occurs in the transition from Basic Technology tofunctional technologies indicated as Complementary Technology.
The IPC (International Patent Classification) is used to group thetechnologies used to produce a product into “Basic Technology” and“Complementary Technology”. We define “Basic Technology” as atechnology which uses the fundamental physical laws as the coretechnology of a product and “Complementary Technology” as a technology
which supports Basic Technology to produce an efficient product.

Fig. 3. Analyzing Model and Result

4. Conclusion
It is also shown that the Knowledge Spillover could account for thedevelopment and there is Knowledge Spillover from Basic Technology toComplementary Technology. On the basis of intensive empiricalobservation on patent statistics, it can be said that Material technologies
have an important role in leading the flow of Knowledge Spillover, and thus
improving the functionality of speakers in the acoustic industry. Thisconclusion is also acceptable on the physical aspect.

Fig. 1 Technological development process of a speaker

Fig. 2 Technological Composition of a speaker

Fig. 4. Fundamental physical force flow234Patent Portfolios for Strategic Technology Management
Yosuke Shibata
Innovation Management
Tokyo Institute of Technology
3-3-6 Shibaura, Minato-ku, Tokyo, 108-0023, JAPANshibata.y.ah@m.titech.ac.jp
Patent and R&D expenditure might be sole useful parameter to evaluateinnovation on the aspect of technology. Many papers analyze relation between innovationand knowledge spillover based on these statistics. However, in using these data, we mightface difficulties of how to control technological and industrial characteristics. In thisresearch, to deal with this difficulty, international patent categorization (IPC) is focusedon as to divide technology to the Basic Technology and Complementary Technology. This
paper aims to propose evaluation method of the knowledge spillover effect between Basics
and Complements. To analyze this, elecroacoustic industries is picked up as a model .
Keyword: Innovation; Patent; IPC; Knowledge Spillover
First one is technological affinity between
companies. Between companies which treat similar
technological segment, it is comparatively easy toabsorb the knowledge flow from other companies,
because it is assumed that these Companies have
similar technological background and experience.
These companies can grow the productivity of
R&D by referring research result of others. (Jaffe,
1986)
Second one is geographical distance between
companies. Geographical distance relate to theavailability of communicating with aroundcompanies. Companies which are located on close
region can contact easily, so that they haveadvantage to change information promptly. These
companies can have good opportunities ofabsorbing Knowledge flow directly from others.
(Jaffe, Trajtenberg and Henderson, 1993)
Third one is cultural difference. It is relatively
easy for Companies to make a cooperation withother companies which can share similar culture
such as management principles, business structure,
language and so on. Mutual understanding for otherculture could be the key of knowledge spillover.
In this paper, trying to control information oftechnology more precisely which construct a
product, we focus on more micro model. And, main
purpose of this research is visualizing andconceptualizing how Knowledge Spillover between
technologies influence the innovation.
By visualizing the spillover effect between
technological segment, it might be possible topropose more effective IP management which canmaximize the interaction between institution andinnovation.

1. Introduction
1.1 Back ground
Innovation is the important activity forindustries, and new technological discovery cancontribute to develope a society.
There are many papaers which discuss thefactor of innovation, and Knowledge Spillover isknown as the effective factor of this. As the
Griliches mentioned (1979), the level ofproductivity achieved by one firm or industry
depends not only on its own research efforts but
also on the level of the pool of general knowledge
accessible to it.
Besides this, evaluation method of innovation
also be focused on. To evaluate the trend anddegree of innovation, Patent data was taken up as a
useful paramer. How to use these Patent data is
discussed as the main topic in mamy papers.. （Acsand Audretsch, 1989）
1.2 The Scope of Knowledge Spillover
As the scope of knowledge spillover, how does
the spillover effect from foreign countries affectdomestic productivity has discussed. (Branstetter,
2001; Eaton and Kortum, 1999; Keller ,2002).
And, the importance of knowledge spillover
between industries is also discussed. (Scherer,
1984: griliches and Lichetenberg, 1984: Jaffe,1986). Additionally, the importance of controllingthe industrial characteristics is argued recently.
(Henderson and Cockburn, 1996: Terero, 2001)
1.3 Three element of Knowledge Spillover
A number of these papers heve discussion
focused on one of three important elements which
heavily influence the knowledge spillover effect.

235

model of speakers. In 2000s, diffusion of cellphoneor small music player prompted this direction.
Second one is to improve the quality of sound of
speakers. Third one is about volume of speakers.
However, it is constitutionally difficult to satisfy
both demands coincidentaly, downsizing andimprovement of quality and volume. Because of thestructural problem, the large diaphragm is better tocreate large volume, and Frequency characteristics
also dependent on the width of diaphragms.
Innovation history of speakers is summarized to thestory of maximizing the balance of downsizing
with quality and volume.
Based on IPC, acoustic equipments is classified
four complementary technologies (components,
circuits, diaphragms,and others) and one basic
technologies (transducers).
For instance, Dynamo-electric Transducer ismost diffused type, and it is based on the Fleming’s
left hand rule as fundamental physical discipline.
This rule decribe how to change electric signals to
structural vibration. Passing a current through coilgenerate electromagnetic force in response tomagnetic field lines, and this electro magnetic force
is used for generating structural vibrations, so thatthree composition (Diaphragm, Coil, and Magnet)
are essential which are arranged as Fig 2 (crosssection diagram of electrodynamic speakers).

2. Hypothesis
As Griliches (1979) mensioned, the level ofproductivity achieved by one firm or industry
depends not only on its own research efforts but
also on the level of the pool of general knowledge
accessible to it. However, the degree of knowledge
spillover varies with factors such as the existence ofrelated industries or the maturity of technologies, sothat industrial characteristics and technologicalcharacteristics should be reflected when knowledge
spillover is measured. (Geroski, 1995)
However, because of the difficulty to divide a
product to technological segment and consider the
spillover effect such a micro level, there is not somuch papers discussing spillover effect in thisapproach.
To deal with this difficulty, one of the mostuseful baseline to categorize the technologies isInternational Patent Classification (IPC). IPC is theclassification method of technology for patents, and
it is admitted as a global standard.
In this research, it is assumed that Technologythat make up a product is classified to BasicTechnology and Complementary Technology which
could be defined by IPC. Basic Technology means
devices to realize the physical laws as a core of
products, and Complementary technology means
devices to support that Basic Technology canconstruct a product. It could be said that Products
are composed of both Basic Technology andComplementary Technology.
Main purpose of this research is to prove theknowledge spillover between technologies, and it
could be guessed that knowledge flows from Basics
to Complements. It means that central research area
shifts from Basics to Complements, and this trend isexpressed as the increase and decrease of patents.
Therefore, hypothesis is set up like follows.

Fig. 1. Patent Share of Japan about Acoustic
Equipment (1995-2004)[Hypothesis]
The trend of patents’ application is shift fromones describing Basic technology to ones
describing
both
Basic
Technology
andComplementary Technology

Sources: Japan Patent Office
Table 1. Top 10 Japanese Companiese which have
Patents of Acoustic Equipment (2005)

3. Explanation about ModelIn this research, electroacoustic industry is
picked up as a model. Main product in this industry
is products which embody speakers in it such as
Television, Note PC, Audio, cell phone etc. Fig. 1
shows the world patent share of Japanese
cpmpanies which is related to speakers, andJapanese companies can occupy over 50% share ofPatent (1995-2004). Table 1 shows Top Japanesecompanies which apply for acoustic equipments.
Generally speaking, there are three demands forspeakers from markets. First one is downsizing the

1
2
3
4
5
6
7
7
9
10

Panasonic
PioneerSONY
YAMAHATOSHIBAKENWOODSANYORIONMITSUBISHI
Victor

Sources: Japan Patent Office

236

158
138
131
104
54
41
39
39
36
28

Fig. 3. IPC Classification of Acoustic Equipment

4.2 Analyzing Model
The analyzing model is described as follows byusing Taylor expansion Theory. This model (1) can
express the relation between innovation andTechnology Knnnowledge.
(1)
P=A+αTbaisc+∑kλkTcomp(k)where, A means firm specific difficulty. Pmeans innovation of electroacoustic industry, andsummation of Patents relating to “Acoustic
equipment” is used as a proxy variable. Tbaisc means
Technology Knowledge of Basics, and summationof patents including “IPC of Basics in Fig 3” isused as a proxy variable. Tcomp(k) means Technology
Knowledge of Complements, and summation ofpatents including “IPC of each Complements in Fig
3” is used as a proxy variable.
Complements which belongs to Others is not somuch, so that this classification is ignored in thispaper. Only other three Complements are
considered in this model, so that (1) is rewritten like(2).
(2)
P=A+αTbaisc+λ1Tcomp1+λ2Tcomp2+λ3Tcomp3
To make the attribution of technology more
obvious, change the expression of variables:
Complements 1 (Tcomp1) means Components (Tmec;
mechanics), Complements 2 (Tcomp2) means Circuits(Tele; electronics), and Complements 3 (Tcomp3)
means Diaphragms (Tmat; materials). Finally, (2) isrewritten as (3).
(3)
P=A+αTbaisc+λ1Tmec+λ2Tele+λ3Tmat

Fig. 2. cross-section diagram of electrodynamic speakers

4. Classification of Technology based on IPC
4.1 Composition of Acoustic Equipment
Electroacoustic Equipment is defined as H04R
in IPC sub-class.
About Basic Technology, 5 types of transducers
are picked up as important ones, and these aredefined as H04R9/00, H04R13/00, H04R17/00,
H04R19/00, and H04R23/00 by IPC main-group.
About Complementary Technologies, devices
can be categorized to Component, Circuits,
Diaphragm, and Others. Components are defined as
H04R1/00. Circuits are defined as H04R3/00.
Diaphragms are defined as H04R7/00. Others aredefined as IPC main- group other than those above.
In this research, to control the information oftechnologies more presisely, technologies are
divided into IPC sub-group level. This sub-groupclassification is acceptable rather than main-groupclassification to consider the spillover effectbetween technologies constituting a product.
Finally, the technological composition of Acoustic
Equipment which is defined as IPC sub-group isorganized like Fig 3.

After gathering the Patent data, I will try to
make it obvious in the future by using this modelthat what classification of Technology Knowledge
can contribute the increase of innovation.

237

5. Analyzing method & Conclusion
Time trend of each Technology knowledge ofJapanese companies is like Fig 4. In electroacoustic
industries, it is obvious that there are two peaks in1982 and 2006. however composition of these two
waves is different.
In the peak around 1982, the increase ofTechnology knowledge of Basics comtributes tocreate innovation. On the other hand, in the peakaround 2006, the quantity of technology knowledgeof Basics is not changed so much, so that it could
be considered that what contributes to leadinnovation is the increase of Technology
knowledge of Complements. This facts suggest thepossibility of Knowledge Spillover from BasicTechnology to Complementary Technology.
Comparing thses two peaks has importantmeaning to analyze spillover effect from BasicTechnology to Complementary technology. One of
the keys to treat this phenomenon is focusing on thetechnological affinity, and this affinity could be
definied as the rate of combination of IPC sub-grop.
For instance, the number of patents which include
IPC of both Basics and Mechanics is increasing
gradually, in comparison, the numer of patents
which include IPC of Basics and Materials isdecreasing. This means that Mechanics can possessa significant position to absorb spillover effect from
Basics, and interaction
between these two
Technologies contributes the development ofindustries. Complementary Technology which
belongs to similar segment with Basic Tecnology
could receive most benefit and contribute to leadinnovation in 2000s.

References

Fig. 4. Time flow of each technology knowledge

238

[1]

Griliches, Z [1979], “Issues in Assessing theContribution of R&D to Productivity Growth”[2]

Henderson, R and Cockburn, I [1996], “Scale,
Scope, and Spillovers: The Determinants of
Research Productivity in Drug Discovery”,
Rand Journal of economics, vol27, pp32

[3]

Geroski, P [1995], “Markets for Technology:
Knowledge, Innovation and Appropriability”,
Handbook of Innovation and Technological
Change, Blackwell, pp90

[4]

Verspagen,B[1997],“Measuring
Intersectoral Technology Spillover: Estimatesfrom the European US Patent Office
Databases”, Economic Systems Research,
vol9, pp47

[5]

Jaffe, A [1986], “Technological Opportunity
and Spillovers of R&D: Evidence from Firm’s
Patents, Profits and Market value”, American
Economic Review, vol76, pp984[6]

Hausman, J. Hall, B and Griliches, J [1984],“Econometric Models for Count Data with an
Application to the Patents-R&D Relationship”,
Econometrica, vol52, pp909[7]

Cameron, C and Trivedi, K [1998],
Regression analysis of count data, Cambridge
University Press

The Dynamics of Knowledge Spillover for Functionality Development
in Japanese Acoustic Equipment Industry
Yosuke Shibata
Graduate School of Innovation Management
Tokyo Institute of Technology
3-3-6 Shibaura, Minato-ku, Tokyo, 108-0023, JAPANshibata.y.ah@m.titech.ac.jp
The purpose of this study is to demonstrate how Knowledge Spillover affects
functionality development by an analysis of trends in the number of patent applications as
proxy of technologies. We group acoustic equipment technologies, a speaker as a product,in Japan using International Patent Classification (IPC). The result shows that, in theprocess of functionality development of a speaker, it can be said that Material technologies
have an important role in leading the flow of Knowledge Spillover.
1. Introduction
It is important for companies to continuously
produce valuable new technologies and by
assimilation of new skills, inventions and ideas
show their innovation capability. The Research andDevelopment (R&D) efforts of companies, whichlead to innovations, are essential for a company’s
growth and also for the growth of society itself.
A plethora of papers has been publisheddiscussing the usefulness of Knowledge Spillover
as one of the foremost factors in encouraging thedevelopment of technological innovation. As
Griliches (1979)[1] has mentioned, the level ofproductivity achieved by one firm or industry
depends not only on its own R&D efforts but also
on the general knowledge accessible by it, which
includes Knowledge spilled over from othercompanies and industries.
In previous studies, patent data has beenrecognized as a useful indicator in quantitatively
evaluating technological innovation (Griliches,1990)[2]. A relation between Innovation andKnowledge Spillover is discussed by using patent
data in many papers.
In this study, we use patent data to analyze therelation between innovation and Knowledge
Spillover among the technologies used in the
manufacture of a product, and examine how
Knowledge
Spilloveraffectsfunctionary
development. We make use of the International
Patent Classification (IPC) to group thetechnologies used in the creation of a product into
Basic Technology and Complementary Technology.
The purpose of this study is to propose a new scopeof Knowledge Spillover between these technologies.
When Knowledge Spillover is discussed,
industrial
characteristics
andtechnologicalcharacteristics should be taken into consideration.
Recent papers have focused on this point anddiscussed the existence of the Knowledge Spillover239

effect between different technologies. Ohmura and
Watanabe (2006) analyzed the Technology
Spillover effect in fine ceramics. Nakagawa and
Watanabe (2007) also analyzed the Technology
Spillover effect in the nonferrous metal industry,
and they have introduced two dimensional models(inter-technology spillover and intra-technology
spillover) to analyze Technology Spillover more
specifically (2008)[3].
2. Acoustic Industry in Japan
We focus on the electro-acoustic industry as theplace to analyze Knowledge Spillover effect among
technologically different components. We select aspeaker as the product, a main product in theindustry.
Today, many products, especially Information
Technology (IT) and digital equipments contain asmall-sized speaker, for example, Headphone,
Earphone, Cellular phone, Portable music player,
Notebook PC, PDA (personal digital assistant), and
Flat-screen television. The dissemination of theseIT and digital equipments has accelerated the
expansion of the market in speakers since the late
1990s.
The Basic Technology used in a speakerconsists primarily of the dynamo-electrical system,
which is based on Fleming’s rules. The dynamoelectrical system has been used in a speaker forover 30 years. It can thus be said that the BasicTechnology of a speaker has remained the same.
The Dynamo-electric Transducer is the mostpopular as a Transducer model, and its mechanism
is based on Fleming’s left hand rule as thefundamental physical discipline. The process ofchanging electrical signals to structural vibration
follows this rule. Passing a current through a coilgenerates electromagnetic force(Coil) in response to
the magnetic field lines (Magnet), and thiselectromagnetic force is used for generating
structural vibrations (Diaphragm).
Japanese companies occupy a large share of themarket in speakers in the world. Japanesecompanies also contribute nearly 70% to thenumber of patent applications relating to speakers
in the world.
Figure 1 shows the trend in the number ofpatent applications relating to a speaker which werefiled to the Japan Patent Office (JPO). It
demonstrates that the number of patent applications
began to increase rapidly in the late 1990s.
Obviously, innovations in speaker technologies
occurred at that period.

to satisfy the demands of miniaturization of
speakers.
In a mature market, essential structural
technologies for the product have already beendeveloped to a certain level. Therefore,technological improvements relating to thefunctionality of the product to satisfy a newcustomer’s needs is required in the next stage.
Based on such an historical analysis as above,
we consider that the functionalities of a speaker
have been developed in two stages of Knowledge
Spillover. In the first stage, Basic Technology isdeveloped in order to have products working byfocusing on structural technologies. After the
structural technologies have already been developed
to a certain level, at the next stage, the functionalityof a product is developed, and in this process
Knowledge Spillover occurs in the transition from
Basic Technology to functional technologies
indicated as Complementary Technology.
Collaboration
among
the
functional
technologies comprising the Complementary
Technology is required to satisfy the new demandsof the customer.
In the second stage, theKnowledge should thus be able to freely passbetween Complementary Technologies. Therefore,
the hypothesis is set up like as follows.

Fig.1 The trend in the number of patentapplications relating to a speaker
3. Hypothesis
In the late 1990s, demands in the market havechanged from the relatively large-sized speakers of
the 1980s to small-sized speakers. Development of
IT and dissemination of digital equipments, forexample, cellular phones and portable music
players, are considered as reasons for the demands
concerning the decrease in size of speakers.
The requirements for miniaturizing speakers
and improvement of the acoustic characteristics of
speakers are contradictory. The key components tosatisfy the two requirements simultaneously are
diaphragms, as they exist in the widest part of alldevices and also control the acoustic characteristics
of a speaker. The ability of diaphragms depends on
its materials.
Therefore, speaker companies no longer could
rely on papers to make diaphragms as they had in
the 1980s, but had to develop materials withsuitable characteristics which could be used as
diaphragms in smaller-sized speakers.
In the 1980s, R&D was concerned with thefield of structural technologies such as the
manufacture of a transducer or mechanical partsrather than with the material of diaphragms, which
was made from a paper having light weight andhigh rigidity, considered the best material at thattime. Then, in the late 1990s, R&D concentrated in
the field of functional technologies, that is, indeveloping other materials for diaphragms in order[Hypothesis]
1, There is Spillover of Technological Knowledge
in the development of functional technologies
2, There are two kinds of Technological Knowledge
Spillover in the development of functional
technologies; a) Spillover from BasicTechnology to Complementary Technology andb) Spillover from one Complementary
Technology
toanotherComplementary
Technology.
4. Analyzing Model
Griliches (1984) has suggested by empiricalanalysis a quite strong relationship between R&D
and the number of patents and concluded that patentstatistics could be a useful economic indicator inilluminating the process of innovation. We use thenumber of patent applications as an indicator ofinnovation, and the number of patent applications
given the specific IPC or FI(File Index) as BasicTechnology or Complementary Technology as anindicator of Technological Knowledge of BasicTechnology or Complementary Technology,
respectively.
In this study, we use FI to group technologies.
FI developed by the JPO is a more specific patentclassification than IPC. FI is given to patentapplications by the JPO as well as IPC.

240

We use as proxy variables of Innovation andTechnological Knowledge the following.
[The process of innovation]
The trend in number of patent applications relating
to a speaker[Technological Knowledge]
The number of patent applications grouped as either
Basic Technology or Complementary Technology
by using IPC or FI.

segments; Basics, Mechanics, Electronics, andMaterials. The three Complementary Technologies
correspond to components, circuits, and diaphragms,
respectively. Then, “n” can be considered equal to3, ”m” is equal to 11 according to the combinationsof Complementary Technology. Comp1 is termed“Mechanics: mech”. Comp2 is termed “Electronics:ele”. Comp3 is called “Materials: mat”. The
equations are then rewritten as (1-2).

Patent applications are filed for inventions and
IPC are given by the JPO according to theinventions in the patent applications. Inventions aredefined as technological ideas in patent applications.
The number of patent applications published withspecified IPC correspond to the volume oftechnological ideas published in patent applicationsof the technology fields of the given IPC. Patentapplications filed and published depend on
inventions disclosed in patent applications astechnological ideas in both the groups of BasicTechnology and Complementary Technology.
Basic Technology and individual Complementary
Technology are defined independently by IPC or FI.

P=A+αTbasic+β1Tmech+β2Tele+β3Tmat+γ1K(basic-mech)+γ2K(basic-ele)+γ3K(basic-mat)+γ4K(mech-ele)+γ5K(mech-mat)+γ6K(ele-mat)+γ7K(basic-mech-ele)+γ8K(basic-mech-mat)+γ9K(basic-ele-mat)+γ10K(mech-ele-mat)+γ11 K(basic-mech-ele-mat)

The number of patent applications relating to a
speaker (P) in the innovation process of a speaker
and Technological Knowledge of Basic Technology
and Complementary Technology are described as inequation (1-1):.
P=A+αTbasic+∑nβnTcomp(n)+∑mγmKspill(m)
1)

(1-

(1-2)

5. Definition about IPC Composition of Speaker
Electro acoustic Equipment such as a
microphone, a recorder, and a speaker are classified
by IPC as [H04R]. We select technologies related toa speaker from those technologies using FI.
1, As Basic Technology, we chose two types oftransducers. These are defined by IPC as
Transducers of moving-coil type (H04R9) andPiezo-electric transducers (H04R17) in the maingroup level of IPC.
2, As Complementary Technologies, there are threemain devices which support the work of atransducer in a speaker; namely, the Component(H04R1;
Mechanics),
Circuit(H04R3;
Electronics), Diaphragm (H04R7; Materials).
6. Entropy about Technology knowledge
We analyzed the diversification rate in thenumber of patent applications of these four
Technology Knowledge, by calculation of Entropy.
The value of Entropy is computed by thefollowing equation:

where, “A’” indicates a constant value. Tbasic
indicates Technological Knowledge of BasicTechnology, and it is measured by the number ofpatent applications given “IPC of Basic Technology
without IPCs of Complementary Technology”.
Tcomp(n) indicates Technological Knowledge ofComplementary Technology, and it is measured by
the number of patent applications given “individual
IPC of Complementary Technology without IPCsof other Complementary Technology”. Kspill(m)indicates Technological Knowledge Spillover
between technologies, and it is measured by the
number of patent applications given “both IPCs of
Basic Technology and Complementary Technology
or two or more IPC(s) of Complementary
Technology”. “n” indicates the number ofComplementary Technology. ”m” indicates thenumber of combinations of Complementary
Technology. α, β and γ are coefficient values,
respectively.
We group the technologies of a speaker by IPC
or FI into one Basic Technology (transducers) andThree
Complementary
Technologies(Comp1,
Comp2, Comp3), that is, four technological

E=-ΣiSilog2Si
where E; Entropy, Si; Share of Technology
Knowledge (i=1~n). Entropy can have a value
from 0 to 2.
As the variable of Entropy, following four
elements is substituted in this formula. S1~S4
indicates the share of the number of patentapplications
relatingto“Basics”:
S1,“Electronics”:
S3,
and“Mechanics”:S2,“Materials”: S4, respectively.
Figure 2 demonstrates the trend of Entropy
values and shows that there are two waves. During
the first wave (1980~1989), it is considered that anincrease of the number of patent applications in
Mechanics and Electronics contributes to theincrease of Entropy. During the second wave241

(1996~2006), an increase of the number of patentapplications in Materials contributes to the increaseof Entropy.
Therefore, comparison between the trends ofthe number of patent applications of these two
periods was made to analyze how technologicalcompositions changed

stage. On the other hand, the contribution of BasicTechnology decreased.
The Knowledge Spillover between Basics andMechanics, Mechanics and Electronics, andMechanics and Materials is revealed to bestatistically significant in this period.
8. Discussion
On the basis of intensive empirical observation
on patent statistics, it could be concluded thatTechnology Knowledge Spillover leads to thefunctional development of a speaker in theelectrical acoustic industry. It is shown that there
were two stages in the functional development of
speaker technologies. The Knowledge Spillover
could account for the development and there is
Knowledge Spillover from Basic Technology toComplementary
Technology.;
especially,
Knowledge Spillover from Basic Technology toMaterials,
andbetweenComplementary
Technologies; especially, Knowledge Spillover
between Mechanics and Materials.
It could be considered that, in the process of thefunctional development of a speaker, theKnowledge is spilled over from Basic Technology
to Material technologies, and then the Knowledgeof Material technologies is spilled over to
Mechanical technologies. As previously mentioned,
the demands of miniaturization and improving thesound characteristics of a speaker are structurally
contradictory. The key to satisfy both of thedemands is the invention of a new material. In the
acoustic industry, it can be said that Material
technologies have an important role in leading theflow of Knowledge Spillover, and thus improving
the functionality of speakers. It also can be said thatby this flow of Knowledge, the development of thefunctionality of materials was accelerated.
In future works, an analysis of this technology
spillover effect from the aspect of physics should be
helpful.

Fig.2 Entropy of four Technology Knowledge
7. Result
A result by the multiple regression analysis of
the equations (1-2) in the two periods is as follows.
To ensure degrees of freedom, we divide the data in
one year into the data in four terms of the year. As
to the equation (1-2), the quantities of K(basic-mech-ele),K(basic-ele-mat), K(mech-ele-mat), K(basic-mech-ele-mat) measured
by the number of patent applications are less than
1% of the value of Tbasic , and so we can eliminate
these proxies.
The result of the analysis follows after
eliminating the proxies with low t-values.
[1st wave; 1980 to 1989]
P=48.51+1.47Tbasic+1.45Tmec+1.18Tele+1.28Tmat(3.90) (5.32) (4.25) (3.70) (5.00)+0.73K(basic-mat)(2.07)
DW; 1.72
adj R2; 0.85
[2nd wave; 1996 to 2006]
P=33.27+1.04Tbasic+1.57Tmec+1.02Tele+3.05Tmat(2.64) (2.81) (6.25) (3.86)(4.77)+0.70K(basic-mech)+0.66K(mech-ele) +2.11K(mech-mat)(2.83)(2.47)(2.56)
adj R2; 0.96 DW; 2.48

References

In the first wave, Basic Technology isdemonstrated to have mainly contributed to theincrease of “P”. Only Spillover of Technology
Knowledge between Basic Technology andMaterials is revealed to be statistically significant.
In the second wave, Technological Knowledgeof Materials is demonstrated to have contributed themost to the increase of “P”. The contribution ofTechnological
Knowledge
ofMaterials
significantly increased comparing that in the first

242

[1]

Z. Griliches, Issues in Assessing theContribution of R&D to Productivity Growth,
Bell Journal of Economics, 10, 92 (1979)[2]

Z. Griliches, Patent Statistics as Economic
Indicators: A survey, Journal of Economic
Literature, 28, 1661 (1990)[3]

M. Nakagawa and C. Watanabe, A Driver for
Materials Technology Innovation: Changes inTechnology Spillover Structure in Japan’s
Nonferrous Metal Industry, New Directions ofTechnology Management, 1 , 25 (2008)

Research on Innovative Manaufacturing Systems under Turbulent Environment
Jian Wang**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANwang@ie.me.titech.ac.jp
Innovations in manufacturing systems under turbulent environment were studied.
Based on literature review, innovative manufacturing systems with the capaiblity ofdealing with change and uncertainty were collected and anlsyzed through keywords. Ten
types of innovations in manufacturing under turbulent environment were identified. This
results provide a basis for further studies on the dynamic relationships among innovations,business strategy, and competitive environment.

1. Introduction
With competitive environment becoming turbulent,managing change has become a central theme inmanufacturing management. Lots of innovations in
manufacturing focus on dealing with change anduncertainty. Generally, these innovations locate inthree levels, i.e., strategic level, systematic level,and practical level. In this paper, we focused on theinnovations in the systematic level, and made awide survey on the innovative manufacturingsystem under the turbulent environment. Using text
mining software, we analysis the characteristics ofthese innovative manufacturing systems, andidentified several types of innovations in
manufacturing systems. Then, we can propose one
framework for explaining the dynamical
relationships among environment, strategy andsystem under the turbulent environment.
The remainder of this report is organized asfollows. Section 2 made a literature review on therelationships between manufacturing systems,
strategy, and environment and explained theresearch methodology in this paper. In section 3 wecollected and introduced innovative manufacturingsystems in the turbulent environment. Section 4
made a quantitative analysis on the innovative
manufacturing systems. At last, in sect 5, weconclude the report.
2. Literature Review and Research Methodology
Nowadays, competitive environment has beencharacterizedasturbulentenvironment.
Accordingly, there are many innovative approaches
for dealing with the changing and uncertain in the
turbulent environment. For example, Wiendahl and
Scholtissek concluded that: (1) the most important
trends for reactions in industry to increasing
complexity are decentralization of company
functions, exploitation of creativity, experience andcompetence of the employees, and concentration on
the core skills of the company; (2) reactions in thescientific field are aiming to develop new designs
for production structures and dynamic processes(Wiendahl and Scholtissek, 1994). Monostori et al.
(1998) concluded manufacturing systems resistanceagainst changes and disturbances in three ways.
Usually, these innovative approaches can be known
as manufacturing or production systems andmanufacturing
practices.
Respectively,
manufacturing practices can be regarded as aconception located in a micro level or practicallevel, manufacturing system can be regarded as aconception located in a midcro level or systematiclevel. In different studies, studying focus hasvarying levels of specificity as well as different
contents. In this paper, our intention is on
systematic level.
In order to analysis the relationships among
these innovative manufacturing systems, there aremany studies. A traditional way to analyze therelationships among these innovations in
manufacturing is configuration. Traditional
configurations of manufacturing systems are often
based on three basic characteristics: operational
characteristics,
operational
objectives,andoperational flow (McCarthy, 1995). Melcher et al.
(2002) gave out a comprehensive classification of
production system with four dimensions. Bolden etal. (1997) reviewed 254 terms of manufacturing
practices, and clustered them into 87 clusters.
Though these classifications discovered somecharacteristics of manufacturing systems, it may bedifficult to set up their relationships with
manufacturing strategy based on the dimensions forconfiguration. In this paper, we focus on therelationships among innovative manufacturingsystems and setting up their relationships withstrategy based on their approach or methodologies

243in dealing with the changes and uncertainty.
For the above purpose, we need to know what
innovations are there in the turbulent environment.
Therefore, we make a wide literature review on theinnovative manufacturing systems in the turbulent
environment. Then, we analyze the relationships
among the innovative manufacturing systems. Since
traditional
dimensions
for analyzing therelationships are not satisfying, we need anothernew approach. In this paper, we generate thedimensions from keywords of each manufacturingsystem. There are two ways employed in this paper.
In qualitative way, we analysis each manufacturingsystem by ourselves, and generate the dimensions.
In quantitative way, we get help from software,such as Text Mining. With the keywords of eachmanufacturing systems, we can analysis therelationships among the systems based on thefrequency of keywords appeared in systems.

In order to find as many as possible innovative
manufacturing systems, we also searched in thefollowing database with five keywords, such as
manufacturing system, production system, bestpractice,
manufacturing
paradigm,
andmanufacturing strategy.
V ScienceDirect: http://www.sciencedirect.com/
V InderScience:
http://www3.interscience.wiley.com/
V Springerlink: http://www.springerlink.com/
V Taylor&
Francis:http://journalsonline.tandf.co.uk/
V Emerald: http://rudolfo.emeraldinsight.com/
V IEEE Explore: http://ieeexplore.ieee.org
After we found innovative manufacturingsystems, we need to search for the researches
related to each system. Beside to the above
publications and database, we also made a researchin two famous databases on publications as follows.
These two databases were searched with the namesof manufacturing systems.
V EIdatabase: http://www.engineeringvillage2.org
V SCI database: http://isiknowledge.com/
At last, we found 83 innovative manufacturingsystems in the turbulent environment as listed inTable 1. Following section will analysis therelationships among these systems.

3 Innovative Manufacturing Systems
A wide literature review covers important
publications in three areas related to the innovations
in manufacturing, such as Operations Management,
Industrial
Engineering,andManufacturing
Engineering. The time period covers from 1990 to2005.
When selecting publications, we refer to theimpact factors provided by ISI in 2003. Therefore,
we can get following 30 journals as follows.
V Top ten journals in Operations research andmanagement science provided by ISI ranked by
impacted factor (Year 2003, from 57 journals)
V Top ten journals in Industrial Engineering
provided by ISI ranked by impacted factor(Year 2003, from 33 journals)
V Top ten journals in Manufacturing Engineering
provided by ISI ranked by impact factors (Year2003: from 37 journals)
In addition, there are some researches on
manufacturing strategy and operations management
recommended by some researchers. Totally, we had
three important sources as follows.
V 23 important journals on Manufacturing Strategy(Dangayach and Deshmukh, 2001)
V 24 top journals on Operations Management(Vastag, 2002).
V 28 top journals on Operations Management andOperations Research (Olson, 2000)
In addition, we also include 15 popular
journals manufacturing engineering recommended
by the professors in our university. Totally, we get
70 journals for our further research.

Table 1 Innovative manufacturing systems andrelated researches
Innovative Manufacturing Systems
Adaptive production
Agent
based
manufacturing/multimanufacturing
Agile manufacturing
Anthropocentric Production
Autonomous decentralized manufacturing

agent

Bionic manufacturing/Biological manufacturing
Cellular manufacturing
Computer integrated manufacturing
Contract manufacturing
Distributed manufacturing
Distributed virtual manufacturing
E-manufacturing
Flexible computer integrated manufacturing
Flexible integrated manufacturing
Flexible manufacturing
Flow manufacturing
Fractal manufacturing/company
Green manufacturing
High commitment work system
Highly informative manufacturing
Holistic model-driven manufacturing
Holonic manufacturing244Virtual cellular manufacturing
Virtual factory
Virtual flexible manufacturing
Virtual manufacturing
Virtual production
Web-based manufacturing
World class manufacturing

Human centered manufacturing
Human oriented manufacturing
Human-resource-based production
Information-based manufacturing
Instant customization
Intelligent manufacturingIntelligent production
Interactive manufacturing
International cooperative global complementary
production
International manufacturing. network
Internet-based manufacturing
Inter-world manufacturing
Inverse manufacturing
Knowledgeable manufacturing
Layered manufacturing
Lean production/manufacturing
Learning manufacturing
Life cycle production/manufacturing
Mass customization
Manufacturing re-insourcing
Manufacturing synchronisation
Millennium manufacturing
Mobile manufacturing
Modular production/manufacturing
Multi-channel manufacturing
Multi-site production system
Networked joint manufacturing
Networked manufacturing
Network integrated manufacturing
Next generation manufacturing systems
Original Equipment Manufacturer
Outsourced manufacturing
Part oriented production system
Post-mass production
Quick response production/manufacturing
Random flexible manufacturing
Random manufacturing
Reconfigurable manufacturing
Remanufacturing
Recoverable manufacturing
Responsibility-based manufacturing
Self-adaptive production
Self-organizing manufacturing
S-model manufacturing
Shared manufacturing
Short cycle time manufacturing
Strategically flexible production
Sustainable production
Synchronous production
Symbiotic production
Tele-manufacturingThought model-based Manufacturing
Time-based manufacturing
Ultimate manufacturing

4 Relationships Analysis
In this report, we regarded that if different
keywords appear in the same systems always, there
may be close relationships among these keywords.
From the literature review, we already collected
related papers for each system. In this section, we
adopted Text Mining software to analysis thefrequency of keywords appearing in different
systems.
Among the 83 systems, some of them havebeen few studied in the selected journals. Therefore,
we may not consider them when calculate theappearance frequency of keywords. Totally, we
deleted 19 manufacturing system because of only
one or two papers can be found related to them.
There are 21 manufacturing system, which have
only one or two related papers and also have close
relationships with other manufacturing systems inoriginal sources, were combined them together.
Therefore, we get 53 manufacturing system forfurther analysis.
Text Mining for Clementine 3.1 was adopted
in this analysis. We made a text extract for eachsystem based on the found papers. For each system,
we generate keywords less than 500 according to
the appearance frequency. From 500 keywords, weselected the keywords related to manufacturingsystems. Generic terms, such as system or
technology, were not considered. Total, we got 1278
keyword for the whole 53 manufacturing systems.
Among there 1278 keywords, many keywords referto same keywords. Therefore, we combine them as
one keyword based on linguistic contents. After that,
we got 74 keywords for the 53 manufacturingsystems. We found that some manufacturingsystems have data on very few keywords, and somekeywords appear in very few manufacturingsystems. Therefore, we deleted 10 manufacturingsystems, which have keywords less than 4. We alsodeleted 11 keywords which appeared in
manufacturing systems less than three, such as
adaptability, bionic, centralization, contract, culture,
decentralize, globalization, inverse, layer, recoverage and world class. In addition, we combine
six keywords with others because of their similar
content, such as Collaboration & Cooperation,

245

Artificial intelligent & Intelligent, Just in time &Lean production, Network & Internet & Web,
Response & Quick response. At last, we got 55
keywords and 43 innovative manufacturing systems.
Among the 55 keywords, we can find that
there are 14 keywords related to the performance of
manufacturing systems or the characteristics ofcompetitive environment, such as Agility, Change,
Complex, Cost, Delivery, Dynamics, Flexibility
Innovation Productivity Quality Real time
Response Time Uncertainty. There are four
keyword related to the ecology, such as
Remanufacturing, Reverse, Life cycle, andSustainable. One keyword “mass production” is areference conception to the turbulent environment.
The other 35 keywords are related to the structure
and process characteristics of manufacturing system,
which are also the focus of our research.
We can find there are significant relationships
between the appearance frequencies between somekeywords. The significant relationships cannot
mean there are significant relationships between
these two characteristics, but discover their close
relationships. Therefore, we further made a factor
analysis on the frequency data of these keywords.
Through a factor analysis, we got 15 common
factors. Some keywords in the factor analysis are
related to some certain organizations, such as cell,holon, fractal, and agent. These specialorganizations are proposed by some special
manufacturing systems and have different
characteristics. What we consider is thecharacteristics of these organizations, but not only
organizations. In the next analysis, we may notconsider these organizations. On the other hand,hierarchichal and heterarchial are two types ofstructure of manufacturing systems. Therefore, 15common factors in the factor analysis can besummarized as ten types as follows. These ten
factors can stand for the innovations in
manufacturing system under the turbulent
environment.
V Type 1: Share in supply chain throughapproaches such as outsourcing
V Type 2: Enhance automation with computer
aided and robot
V Type 3: Improve modularity and selforganization
V Type 4: Improve standardization level and use
mobile and network
V Type 5: Organize people with team and enhancetrain
V Type 6: Improve intelligent and emphasize theusage of knowledge

246

V Type 7: Improve autonomy and emphasizing
learning
V Type 8: Emphasize concurrent engineering andvirtualization
V Type 9: Combine distribution and integration
V Type 10. Enhance cooperation and collaboration
Based on the detailed keywords related to the ten
types and the results of the qualitative analysis, we
can discuss the relationships between these ten
types of innovation and the capability of dealing
with change and uncertainty.
5. Conclusion
In this study, we identify the innovation in
manufacturing systems under turbulent environment
in ten types and analyze the relationships between
the innovation in manufacturing and environment.
In the future work, we would like to analysis the
dynamic relationships between innovation, strategy
and environment and develop a tool for explaining
the dynamic relationships among them.
Reference[1] Bolden, R., Patrick Waterson, Peter Warr, Chris Clegg and Toby
Wall (1997) ‘A new taxonomy of modern manufacturing
practices’, International Journal of Operations and Production
management, Vol.17, No.11, pp.1112-1130.
[2] Dangayach, G. S. and Deshmukh, S. G. (2001) Manufacturing
strategy Literature review and some issues, International Journalof Operations & Production Management, Vol. 21 No. 7, 2001, pp.
884-932.
[3] Vastag, Gyula and Montabon, Frank (2002), Journal characteristics,
rankings and social acculturation in operations management,
Omega Vol. 30, pp.109 – 126.
[4] Monostori, L., Kádár, B., and Hornyák, J. (1998) ‘Approaches toManaging Changes and Uncertainties in Manufacturing’, Annals of
CIRP, Vol.47/1, pp.365-369.Montreuil et al., 2000
[5] McCarthy, Ian (1995) ‘Manufacturing classification: Lessons fromorganizational systematics and biological taxonomy’, Integrated
Manufacturing Systems, Vol.6, No.6, pp.37-48.
[6] Melcher, Arlyn J., Moutaz Khouja, David E.Booth (2002) ‘Toward
a production classification system’, Business Process Management
Journal, Vol.8, No.1, pp.53-79.
[7] Olson, Josephine E. (2000) Associate Dean and Professor of
Business Administration, The Joseph M. Katz Graduate School ofBusiness, University of Pittsburgh, Pittsburgh PA 15260 USA,
August[8] Wiendahl, H.P. and Scholtissek, P. (1994) ‘Management andcontrol of Complexity in Manufacturing’, Annals of CIRP,
Vol.43/2, pp.533-540.

A Study on Unified Modeling Methodology for Information Systems Development
HanGook Kim**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-66 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANKorea712@me.titech.ac.jp
The issue of customer-centric enterprise focusing on realizing customer needs has
recently received considerable attention in the corporate world. However, little research
has yet been reported on developing Information Systems (IS) supporting the customercentric enterprises. This research proposes an integrated approach of IS development that
supports organizations aiming to become customer-centric enterprises using various
customer profiles. The proposed approach unify goal modeling, business process modeling,
and information systems modeling. The approach is expected to be seamlessly linked withthe object-oriented systems development methodology. Finally, we apply this approach to
the real case of a securities company in Japan.

characteristics: (1) they have customers (internal orexternal), (2) they cross organizational boundaries,
in that they occur across or between organizational
subunits. One technique for identifying businessprocesses in an organization is the value chain
method proposed by Porter and Millar (1985).

1. Introduction
Recently, the issue of customer-centric
enterprise has received considerable attention in thebusiness environments. The increasing complexityof technology and products requires acorresponding increase in awareness of customer
needs and in the way humans interact with systems(Karl and Matthew, 2001).
Concerning the definition of customer-centric,
we strongly believe that in order to become
customer-centric, organizations need to rebuild
business processes to eventually realize customer
needs. Customer-centric organizations focus onunderstanding and transforming their customer’s
activities with internal business processes.
However, although an increasing amount ofresearch has appeared on customer-centricorganizations, little of it shows how customers
interact with internal business processes, how tomodel their activities, and how to develop
information systems to support these businessactivities.
Therefore, in this research, we propose an
integrated approach of IS development that
supports organizations aiming to become customercentric enterprises by using object-oriented
modeling and customer profile analysis.

2.2 Figures and Tables
Fig.1 explains how goal-oriented businessprocess modeling fulfills business needs. These
steps consist of (a) business needs, (b) businessgoals modeling, (c) business process modeling, and(d) IS development. First, we need to definebusiness goals associated with specific businessneeds, and list all business processes needed tofulfill each goal. Then, we consider the
implementation of IS to support these businessprocesses.

Business needs
Business goals

Business process model

2. The style
2.1 Business Process
Davenport and Short (1990) define business process
as a set of logically related tasks performed toachieve a defined business outcome. It implies astrong emphasis on how work is done within an
organization (Davenport, 1993). In theirperspectives, processes have two important

IS development
Fig.1. 4 Proposed Steps to Realize Business Needs

247

2.3 The Zachman Framework and Personas
In this research, we have focused on (1)architectural frameworks that visualize the entire
scope of projects, and on (2) methods that createcustomer profiles, in an integrated approach. Manyarchitectural frameworks have been used tocomprehensively describe the architecture ofenterprises’ IS, for example, the Zachman
Framework, RM-ODP (Reference Model of OpenDistributed Processing) (Putman, 2001), TOGAF(The Open Group Architecture Framework) (TheOpen Group, 2003), and so on. Among these tools,
the Zachman Framework differs from otherarchitectural framework tools in its independent,
holistic view of the enterprise, because it is neutral
with respect to methodology, process andtechnology, including the breadth of scope tohandle all areas of the enterprise (O’Rourke et al.,2003). This is why we adopt it in this research.
Meanwhile, we utilize personas to create customer
profiles, for personas provide us with insight into
how the organization needs to work for customers
and how it is best designed. Market segmentation isan invaluable tool for identifying the types ofcustomers to profile. However, it rarely provides
the richness required to write personas.

Fig.2. Overall View

Fig. 3 depicts the overall view of the detailed
methodology proposed in this paper. Our
methodology involves seven main steps.
(1) Identify the customer profiles: We use
personas to guide our creation of the customer
profiles. Each persona should have a name, animage, an occupation, behavioral patterns andspecific needs related to the project. Giving thepersona a name is one of the most important parts ofsuccessfully defining one (Cooper, 1999). Cooper
insists that a persona will never be a concrete
individual in anyone’s mind without a name. A
customer profile that we proposed in the paper
describes the typical customer image, attributes andgoals which affect the relation with the business.
Identifying the focal customer (primarypersona) is a vital step in these processes. A primarypersona has needs so unique that it calls for a very
distinct form. In contrast, a secondary persona has
needs that can be fulfilled by the primary user needs
with only relatively minor modification.
(2) Describe a static conceptual data model: It
is valuable to describe a static conceptual data
model, for it is needed something to recognize theentire image and clarify circumstances and scope.
In this paper, the “Static conceptual data model” isdefined as a model that describes representations ofinterested objects and represents the staticinterrelationships between these objects in a realworld domain.
The modeling notation used in this step refers
to the Entity-Relationship (E-R) modeling (Chen,

3. Integrated Approach for IS Development
Conventional business process modelingtechniques have been focusing on perceiving anddescribing business processes, from the viewpointof business function of the organization (Hou et al.,2003). However, business processes must be
viewed from the perspective of the customer in acustomer-centric enterprise. Although mostbusiness processes cross functional lines, theprocess is a single and continuous activity from thecustomer’s perspective. Therefore, procedures need
to be developed with the customer’s perspective inmind.
In this research, selecting a key customer
group is a key decision. In order to identify who the
key customer is and what her/his needs are, we
exploit persona, for it is an interaction design
technique with considerable potential for software
product development. Customer needs are broken
down into business goals by asking how theseneeds should be achieved. Business goals are
divided into units, which are called Business
Process Unit (BPU). The customer profile describes
the typical customer image and attributes which
affect the relation with the business. On the basis ofsuch customer profile, the customer action scenario
is designed. The customer action scenario consistsof stories rich in context that focus more on what
the customer will do than on how he will do it.

248

1976) which makes use of three main constructs:
data entities, relationships, and their associatedattributes. The E-R model notation has
subsequently been extended to include additional
constructs by Chen and others (Teorey et al., 1986;
Storey, 1991). For simplicity purposes, we haveadopted a common notation for this paper, the socalled crow’s foot notation.
(3) Define BPU related to the business goals:
Based on identified profiles, we define the businessgoals in order to fulfill the defined customer needs.
Selecting two or three primary goals is the mostappropriate. Selected goals are divided into
Business Process Unit (BPU). A BPU that relates
directly to the customer’s needs is selected. If BPU
that is the smallest unit in our methodology appears,
stop subdividing goals.
(4) Create the customer action scenario: On thebasis of such customer profile and business goals,
design the customer action scenario within the BPU.
Scenarios can play a wide variety of roles
throughout the development process. In thisresearch, a scenario describes a particular situation
between business organizations and customers
showing the main course of action but also
including variations or possible alternative cases.
The customer action scenario is an action patterncomposed of two types, the present one (As-Is) andthe improved one (To-Be).
These scenarios are described by the notationof activity diagram in UML. Activity diagrams
allow analysts to model a process as a collection ofactivities and transitions between those activities. In
order to describe the As-Is scenario, it is necessary
to start by identifying and designing the customers’core processes by considering which behavioral
patterns they have. Then redesign it into theimproved one referring to the customer needs andrequirements.
(5) Design the Customer-Business (C-B) activity
diagram: We consider how the enterprise deals with
To-Be customer action using the Swim lanes in theactivity diagram. The C-B activity diagram shows
activities of the business organizations based on the
behaviors of the customers inside the BPU.
The swim lanes represent the actions andactivities carried out, so the number of swim lanes
matches the number of relevant businessorganizations (Eriksson and Penker, 2000). We use
vertical swim lanes to emphasize the top-down flowof processes from business organizations, an overall
pattern that matches the organization diagram
locating business organizations and customers in asimilar manner.
(6) Create the business process diagram: The

249

completed business process diagram of one business
function is obtained from all scenarios using theAssembly line diagram, a Unified Modeling
Language (UML) extension developed by Eriksson
and Penker (2000).
In this business process diagram, we put aprocess diagram at the top of the assembly line
diagram. An assembly line package is a UML
package that is drawn as a long horizontal rectangle.
Each package can represent an entire information
system, a subsystem in an information system, or a
specific type or group of resources. The purpose ofthis diagram is to indicate how the processes in theupper part of the diagram refer to objects in theassembly line. A reference from a process to an
assembly line package is indicated with a dashedline between the process and an object within theassembly line package.
(7) Identify use-cases: The business process
diagram shows how the process interacts with theinformation system. The references to the assemblyline packages consist of information flow to andfrom the information system and show the interface
between the business process and the information
system. This interface is described through usecases in object oriented modeling. And a set ofreferences in an assembly line diagram typically
becomes a use-case that the information system has
to provide. It maps the business process to use-casesthat describe the functional requirements of an
information system. And, it also identifies theproper actors of the use-cases.
Our main concern is about the upper process in
the implementation of information system. So, we
limit the scope of this paper that covers from thecreation of customer profiles to identification of use
cases, which is the first step of information systemmodeling using UML.
4. Conclusions
In this paper, we showed how to modelbusiness processes for realizing customer needs
based on various customer profiles. In chapter 3, we
proposed an integrated approach unifying goal,
business process and information systems modeling.
Finally, we illustrated how to apply this approach
using a real case.
The proposed methodology has three featuresdifferent from those of the existing methodologies.
First, it includes a step “Identify the customer
profiles” for identifying customers and their needs.
This step provides the starting point to help theanalyst capture the primary customer’s needs.
Second, the Zachman framework is used as an[11] The Open Group., 2003. Welcome to TOGAF
8: “Enterprise Edition”.
http://www.opengroup.org/architecure/togaf/

architectural framework for visualizing the entire
scope of projects. It will support the description
process of conceptual static data model. Third, it
seamlessly integrates customer needs, businessprocess, and information system.
Moreover, in light of the Science ofInstitutional Management of Technology (SIMOT),
this research also aims to give an illustration on
how to link them in a seamless approach andinvestigate which methods are appropriate so as tointegrate them.

[12] Teorey, T. J., Yang, and J. P. Fry., 1986. A
Logical Design Methodology for Relational
Databases Using the Extended EntityRelationship Model, Computing Surveys,
18(2), 1997-221.

References[1]

Chen, P. P-S., 1976. The Entity-Relationship
Model – Toward a Unified View of Data,
ACM Transaction on Database Systems, l,March, 9-36.

[2]

Cooper, A., 1999. The Inmates Are Running
the Asylum: Why High Tech Products Drive
Us Crazy and How To Restore The Sanity,
Macmillan.

[3]

Davenport, T.H., 1993. Process innovation:
reengineering work through information
technology, Harvard Business School Press,
Boston, MA.

[4]

Davenport, T.H. and Short, J.E., 1990. The
new industrial engineering: information
technology and business process redesign,
Sloan Management Review, Summer, 11-27.

[5]Eriksson, H.E. and Penker., M., 2000.
Business modeling with UML: Businesspatterns at work, Wiley Computer Publishing.

[6]

Hou, S., Iijima, J., Toda, Y., Kobayashi, T.,
Byun, D. and Kim, H., 2003. Customerorinted
Business
Process
Modeling,
Proceeding of National Conferences of Japan
Society for Management Information., 416419.

[7]

Karl, L.S., and Matthew, E.W., 2001.
Designing systems that support learning anduse:acustomer-centeredapproach,
Information & Management, 39, 177-190.

[8]

O’Rourke, C., Fishman, N. and Selkow, W.,
2003. Enterprise Architecture Using the
Zachman Framework, Thomson.

[9]Porter, M.E. and Millar, V.E., 1985. How
Information
Gives
You
Competitive
Advantage, Harvard Business Review, 63(4),149-160.

[10] Putman, J., 2001. Architecting with RM-ODP,
Prentice Hall.

250

A Study on Failure Factors of IS Integration from Organizational Perspective
Han-Gook Kim**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-66 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANKimhangook2007@yahoo.co.jp
In this research, we propose a model with multiple components in order to explain afailure of IS integration more clearly. Moreover, we propose a framework that uses
components of the IS integration model as horizontal axis, and phases of IS integration asvertical axis. This framework serves to analyze both failure factors and the relationships
according to the IS integration model. Also, the result of the analysis may indicate what
factors are important in development of IS for reducing IT risk.

1. Introduction
Coping with complex IT projects continues tobe a central problem for information systems(Keider, 1984). While information technology has
become an integral part of organizations, the failure
rate of IT projects remains high (Cole, 1995). A
project is usually deemed successful if it (a) meetsrequirementsoffunctionality,
reliability,
maintainability, portability, efficiency, integration,and operability; (b) is delivered on time; and (c)stays within budget (Powell, 1996). Citing a 1995
Standish survey, May reported that only one-sixthof all projects were completed on time and withinbudget; one-third of all projects were cancelled; andover half were considered “challenged”.
The structure of this chapter is as follows. In
Chapter 2, we propose a new model of systems
integration and examine the processes by which
obstacles to a successful system occur. In Chapter 3,
we identify the main risk factors in IS integration
failure from some failed cases. Finally, in Chapter 4,
we analyze three actual cases using the proposed
analytical framework, and consider how they
avoided the risk factors for the successful project.
2. Framework for Analyzing IS Integration Risk
2.1 IS Integration Model with Customers
Boehm and Ross (1989) point out that different
stakeholders in a software development project haveunique objectives that often conflict with one
another. For instance, users require a robust, userfriendly system with functions that can support theirtasks. At the same time, development teammembers hope to encounter interesting technicalchallenges. These differing expectations create
fundamental conflicts when simultaneously
approached, resulting in an unclear or
misunderstood scope of the project. In the light ofthese difficulties, we propose a new model (Fig. 1)
for analyzing obstacles in system integration, using
Sauer’s model (Sauer, 1993) as the base. The
relationships between the components directly
involved in IS integration are more clearly
expressed by adding the Integration Promotion
Committee (IPC), and by separating users fromsupporters.

Fig. 1. IS Integration Model

2.2 Phases of IS Integration
When IS integration accompanies merging
operations such as M&A, it is necessary to consider
the integration analysis and design phases, though
they are not seen in ordinary information systemconstruction phases. Therefore, in this research we
divide the plan phase into two steps — an analysis
phase and a design phase based on Yamamoto’s
work (2002).
Uniting the IS integration model with thePhases of IS integration completes the framework(Fig. 2) to analyze such obstacles.

251

Fig. 3. Failure Factors in IS Itegration

Fig. 3 takes the organizational view point. The
organizational view point captures the nature andcontents of organizational roles by whichorganizational activities and tasks are carried out.
We focused on behavior expectations, authority,and task performance of organization’s component
in this research. Components in IS integration
projects have their own roles and agenda to achievein each phase of the project. We try to point out
where and which problems exist in each component
by using Fig. 3.
Fig. 3 can be used for analyzing failure andsuccess factors of IS integration projects. In failed
projects, we can explain why the project failed andwhere the failure factors appeared. Also, bycomparing these failure factors, we can identify
what critical success factors worked in projects
considered successes.
After conducting case studies based on Fig. 3,
we identify the three main risk factors – leadership,communication, and enterprise-wide perspective for analysis of IS integration as shown in Fig. 4,
because theses factors were clearly common inthese cases.

Fig. 2. A New Analsys Framework for IS
Integration

3. Three Main Risk Factors of IS Integration
In order to construct checklist (Fig. 3) for
failure in IS integration, we conducted three steps.
In the First step, we prepared 3×3 matrix based on
Fig.2 that used a horizontal axis to represent
components (Users, Supporters, and Project
organization) of IS integration model, and a verticalaxis to represent phases of IS integration (Analysis,
Design, and Implementation). In next step, so as tocollect critical failure factors in IS integration andgain the union of them, we interviewed several
project members.

.

Fig. 4. Three Main Risk Factors of IS Itegration

4. Case Study
4.1 Sompo Japan Project
In April 2001, three new non-life insurancecompanies (Sompo Japan, Millea and Mitsui
Sumitomo Insurance Co.) were founded as a resultof mergers. With the accelerated movement ofmergers, consolidation, and affiliation, the non-life
insurance industry had reached a peak in its
reorganization.
Since the end of World War II, the Japanese
non-life insurance industry had been enjoying
steady growth with stable profitability, until thesituation dramatically changed in the wake of theliberalization. Beginning with the revision of the
Insurance Business Law (IBL) in April 1996, the252following seven and a half years can be described as
the hardest and most turbulent years in the historyof the industry. The industry has since been forced
to undergo a rapid and substantial change due toliberalization and deregulation within theframework of the Japanese Big Bang—a national
project for structural reform of the entire financial
market.
The Sompo Japan project was considered asuccess, as it fulfilled the desired objectives. Sompo
Japan was established on July 1, 2002, through amerger between Yasuda Fire & Marine InsuranceCo., Ltd. and Nissan Fire & Marine Insurance Co.,
Ltd. There were additional mergers with Dai-ichi
Property and Casualty Insurance Co., Ltd. in April
2002, and with Taisei Fire & Marine in December
2002, respectively.

Lipitor,prostate
treatment
Harnal,andimmunosuppressant Prograf.
Astellas Pharma also integrated the systems of
Yamanouchi Pharmaceutical Co., Ltd. and Fujisawa
Pharmaceutical Co., Ltd. when the two companies
merged in April 2005 and that the new integrated
system has now achieved stable operation.
The new system used SAP R/3, an ERP(enterprise resource planning) package developedby SAP, the solutions provider used by
Yamanouchi and Fujisawa to integrate the existing
business processes of the two companies in all areas,
including accounting, production, sales &distribution, purchasing, and personnel. A
consulting firm provided support in the supervisionand management of implementation of the project
for the integration of the two companies' basic
systems.

4.2 JFE Steel Project
In recent years, the steel mill industry has beencharacterized by consolidation, globalization, andcompetitive pressures. JFE Steel was established in
April 2003 after the merger of two steel mills, theformer NKK and Kawasaki Steel. JFE SteelCorporation is one of the worldwide leading steel
corporations(capital:
239.6
billionyen,
consolidated net sales: 2,103.9 billion yen, numberof employees: 44,192 respectively as of March 31,
2004).
JFE made all kind of efforts in order to develop
a system that could handle diverse types of business
operations, including order processing and others.
The existing order processing system was expanded
to create a system that supports the three businessprocesses of negotiation, product specifications andordering. As a result, the existing system wastransformed into a sales system that prioritizes
point-of-contact information with the customer.
For mill operation, the new system responded
flexibly to changes in demand from the customer
and to changes in mill production at JFE Steel sothat the company can fully use the expanded scaleof assets which resulted from the merger. In
addition, integration of product specifications on aenterprise-wide database has made mill operation
more flexible so that JFE can shift production
between plants.

4.4 Implication of Cases
We analyzed cases described above based onthese aspects as below.
1) Communication
In the Sompo Japan case, they were eager toestablish a clear communication system to avoid thefailure factor ‘Ineffective communications’ in Phase
1 of Figure 3.4. Good communication among thecomponents is essential to accomplish the overall
goals of the IS integration project. Especially,
communication between users and project
organizations directly relates to the success of the
project.
In the JFE case, the project team utilized theconcept data model as a communication tool. The
team modeled As-Is business processes based on
the concept data model, and drew To-Be processes
from them. In the development of J-Smile, the team
identified 90,000 data in the business processes andsystems.
In the Astellas case, the executives could
decide the basic policy for IS integration in an earlyphase. They aimed to attain the best practice among
the existing systems. The project team separated thewhole IS into four sub-systems, for example, R&D,
sales, and Enterprise Resource Planning (ERP),
infrastructure and so on. The project team chose thesuperior system within each old sub-system. The
team’s communication for IS integration projectproceeded smoothly.
2) Leadership
In the Sompo Japan case, by recognizing theimportance of the system integration from the initial
phase, supporters quickly decided on theorganization and integration option for the system
integration, so that the IPC was able to prevent
confusion in the implementation phase. They also
did not forget to check how the integration process
was proceeding by carrying out periodic briefing
session in the implementation phase.

4.3 Astellas Pharma Project
Astellas Pharma Inc. was born after
Yamanouchi Pharmaceutical acquired fellow
Japanese druggernaut Fujisawa Pharmaceutical
Company in 2005. With the combined revenues of
the two companies, Astellas is one of the largest
pharmaceutical companies in Japan (as of 2005),
behind Takeda and the newly formed Daiichi
Sankyo. Main products include cholesterol drug253

In the JFE case, JFE executives recognized thatsystems integration that occurs after a merger isfrequently biased toward the business processes ofthe strongest unit in the merger, so they set goals toachieve the integrated reform and redesign ofexisting business processes, as well as to definebusiness control indexes and base data. The
executives were committed to developing thesystems which promoted integration of the twocompanies as well as the innovation of completely
new business processes.
In the Astellas case (CIO Magazine, 2006),
Toichi Takenaka, CEO of the Astellas, instructed
the IPC on how to integrate the information systemsof two former companies from the first phase of IS
integration. He settled on a One-sided (select one
company’s system) option from the enterprise-wide
perspective, which helped the project team carry out
the integration operation smoothly. Isao Kishi,
project manager & head of the IS division, had aclear and strong policy necessary to keep the ISarchitecture aligned with the business structure to
support the long-term business strategy andcontinually enhance business performance.
3) Enterprise-wide perspective
In the Sompo Japan case, the integration planwith Tai-Sei F&G was announced when the basic
system implementation started. It can also be said
that the Yasuda fire project was interrupted at its
beginning. But, on this occasion the threecompanies, including Yasuda fire, decided
simultaneously to proceed with integration anddevelopment.
New system developments were, for example,(a) an accident response system, (b) a contract
management system, (c) a next generation system,and (d) a network infrastructure restructuring
project. These systems were developed without
interruption in spite of the sudden system
integration. Eventually, they led the IS integration
project to a success by integrating IS centered onthese systems.
In the JFE case, the project manager could
adopt an enterprise-wide perspective for successfulproject development. There are also some featuresthat facilitate success, for example, the subdivisionof implementation at the corporate level,bureaucratic decision on system adoption, andstrategy-lead change.
In the Astellas case, the executive could
provide employees with a clear vision of theintegrated future company, so that complex
progress could be completed in a short period. They
had been willing to understand customer needs andfocus on achieving customer satisfaction.

5. Conclusions
In this research, we proceeded in three steps inorder to construct a check-list for failure in IS
integration. In the first step, we prepared a 3×3
matrix using, as unit of analysis, components (Users,
Supporters, and Project organization) of IS
integration model on the horizontal axis, andphases of IS integration (Analysis, Design, andImplementation) on the vertical axis. In the next
step, we interviewed several project members so as
to collect critical failure factors in IS integrationand make an exhaustive list of those factors.
Moreover, in light of the Science ofInstitutional Management of Technology (SIMOT),
this research also aims to give an illustration on
how to analysis IT risks in integration of
information systems and how to reduce them induring business mergers.
References[1] Boehm, B., Ross, R., 1989. Theory-W software
project management principles and examples,IEEE Transactions on Software Engineering, 36,
902-916.
[2] CIO Magazine Editorial Desk, 2006. Focusingon IT not Business Leads Integration Project toSuccess, CIO Magazine, January, 2006. (InJapanese)[3] Cole, A., 1995. Runaway projects—Cause andeffects, Software World, 26, 3-5.
[4] Keider, S. P., 1984. Why Information Systems
Development Projects Fail, Journal of
Information Systems Management, 1, 33-38.
[5] Powell, P.L., and Klein, J.H., 1996. Risk
managementfor
information
systems
development.
JournalofInformation
Technology, 11, 309-319.
[6] Sauer, C., 1993. Why Information Systems Fail:
A case study approach, Alfred Waller, HenleyOn-Thames.
[7] Yamamoto, S., 2002. M&A to IS integration,business communication, 39, 62-71. (inJapanese)

254

Business Process Management: A Short Review
Bing Li**
Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANli.b.ab@m.titech.ac.jp
Business process management (BPM) is receiving great attention in industrial andacademia societies. BPM paradigm advances in the process centric thinking and is enabled
by some ICT technologies. In contrast with the tranditional Workflow Management
Systems (WfMS), the emerging business process management systems (BPMS) expand
their lifecycle and integrate more process analysis functions. This paper attempts to makea short review about the ongoing changes or new features of business process managementfrom the technical perspectives.
1. Introduction
As part of modern enterprise information
systems (EIS), business process management
systems (BPMS) are receiving great attention fromthe enterprise’s executives and IT engineers.
Evolvingfromthetraditional
workflowmanagement systems (WFMS) and embracing somenew computing concepts, the emerging BPMSs aremaking strengths on system integration.
Process orientation is the key concept thatdrives the development of BPMS. The EISs shift
from the traditional data orientation to process
orientation (Van Der Aalst et al. 2003). Process
orientation improves the abstraction level andseparates the concerns of businesses from theimplementation systems. This way the EISs canenhance their flexibility and adaptability to theexternal and internal changes.
Besides the technical perspective, Business
Process Management (BPM) also involves the
managerial perspective that requires organizationalchanges to adapt to the new paradigm. The recent
development of BPM is driven by business needs
and enabled by advancement and penetration of
information and communication technology (ICT).
In this paper, BPM research is generally
reviewed in Section 2. Then Section 3 scopes theresearch of BPM, especially focuses on BPMS – thetechnical perspective of BPM, and explains some
active research fields. Finally conclusion and future
work are given in Section 4.
2. Business Process Management (BPM)
2.1 Definition
Business Process Management (BPM) issummarily defined as “both a set of tools andtechniques for improving processes and a method
for integrating the whole organisation” (Lee andDale, 1998). This summarized definition reflected
the diverse perspectives of BPM. The enterprises’

executives and IT engineers will view BPM
differently and thus emphasize different aspects of
BPM. The former will be more strategic andmanagerial while the latter will be more tactic andfocusing on the system implementation.
Zur Muehlen (2007) reviewed the BPM fromtwo perspectives. Organization theorists andManagement Science (OTMS) research focus on
the structuring of organizations around processes
and the effects of information technology onorganizations while Computer Science andInformation System Engineering (CSISE) focus on
the components of BPMS and the formalisms of theunderlying languages. These two perspectives
generalize the viewpoints from the executives andIT engineers.
Emphasizing the managerial perspective(OTMS), Hill et al. (2006) defined BPM as “amanagement discipline that requires organizations
to shift to process-centric thinking, and to reduce
their reliance on traditional territorial and functional
structures. Focusing on the supporting softwaresystems (BPMS), Van Der Aalst et al. (2003)
defined BPM as “supporting business processes
using methods, techniques, and software to design,
enact, control, and analyze operational processes
involving humans, organizations, applications,documents and other sources of information”.
2.2 Business Process Management Systems
Business Process Management Systems(BPMS) concentrate on the software systems that
support the process management in the enterprises,
reflecting the CSISE perspective and typically
representing what IT engineers concern about BPM.
BPMS is defined as “a generic software system thatis driven by explicit process designs to enact andmanage operational business processes” (Van Der
Aalst et al. 2003). BPMS usually consists of several
key components that perform the functions ofbusiness process design, enactment, monitoring and255

control, and analysis.
2.2.1 WFMS and BPMS
The emerging BPMS has a great relatedness
with the traditional Workflow Management System(WFMS) and recently they are actually evolving
and merging along some sharing concepts. WFMS
focuses on a special kind of business process,workflow process or workflow.
In The Workflow Handbook 2001 (Allen,
2000), the Workflow Management Coalition(WfMC) defined workflow as “the automation of abusiness process, in whole or part, during whichdocuments, information or tasks are passed fromone participant to another for action, according to aset of procedural rules”. WFMS was defined as “asystem that defines, creates and manages theexecution of workflows through the use of software,
running on one or more workflow engines, which isable to interpret the process definition, interact withworkflow participants and, where required, invoke
the use of IT tools and applications”.
By comparing the above mentioned definitions
about BPMS and WFMS, it can be seen that the
BPMSs expand the functions and scopes of the
traditional WFMS. Business processes cover not
only administrative processes, but also otheroperational processes running in or across theenterprises.
The lifecycle of the BPMS has been expanded
to include more analysis. Van Der Aalst et al.
(2003) compared BPM with workflow management
by using the lifecycle. The traditional WFMS
focused on the lower level and more restricted on
the enactment of workflow processes. There waslittle support to the diagnosis phase. The emerging
BPMSs are integrating more analysis functions
such as business process control and monitoring,
diagnosis, mining, etc.
Moreover, the emerging BPMS makes strengths
on adaptability to external and internal changes.
These strengths will improve the flexibility ofenterprise systems and enabled by some newly
computing concepts such as service oriented
architecture.
2.2.2 Enabling Technologies
Although there are diverse perspectives of BPM,
the BPM researchers have the common
understanding that successes in BPM can not be
separated from its supporting tools, i.e., enabling
technologies. For example, Hill et al. (2006)
considered BPM as an IT-enabled management
discipline while Zur Muehlen (2007) and Lee andDale (1998) recognized the multi-disciplinaryfeature, covering organizational theory, computerscience, information systems, and management

science. In summary, enabling technologies,
especially ICT, are critical factors for the success of
BPM. Advancement in IT technologies enables theimplementation of process centric paradigm.
Service Oriented Architecture (SOA) can beconsidered as a distinguishing enabler to the BPMS
(Hill et al. 2006; Havey, 2005; Van Der Aalst et al.
2003). In SOA paradigm, a business process can bewell encapsulated as a service that is ready to serve
local or remote invokers; a business process canconsist of primitive or complex activities, which
can be an encapsulated service in and across anenterprise. SOA makes it flexible for an enterprise
to manage its processes. Implementation of theconcepts in SOA involves a suite of technologies
such as XML and Web services.
XML is gradually becoming the universal
standard for businesses to store their data. XML
provides the uniform format and can beconveniently added application-specific schemas.
The transmission across the network is platformindependent. The stored data are available topotential analysis. These strengths of XML make it
employed as the data storage format in the current
BPMS. Many standards in BPM industry are
expressed in XML syntax, two outstanding of
which are XML Process Definition Language(XPDL) and Business Process Execution Language(BPEL).
There are many other IT technologies that alsoenable the development of BPMS. One good
example is the Internet and broadband connection.
These technologies connect the business systems
across the world with gradually decreasing prices.
The emerging BPMS can manage local or remotebusiness processes with transparence, i.e., thesystem need not concern about the location. The
collaboration and outsourcing can be implemented
conveniently. Customer needs can be potentiallyrecognized or predicted, which puts the customercentric thinking into practice in the real world
business processes.
3. Scope of BPM Research
The previous researches have shown the diverse
perspectives of BPM according to the specificaspect that a certain research concerns. These
perspectives can be simply generalized into two
categories, that is, to view BPM separately fromorganization theorists and management science(OTMS), and Computer Science and Information
System Engineering (CSISE) (Zur Muehlen, 2007).
Lee and Dale (1998) summarized BPM similarly
with the technical and managerial perspectives.
This categorization can be referred to scope theexisting BPM research.

256

3.1 OTMS Perspective
BPM research in managerial perspective
focuses on the structuring of organizations aroundprocesses and the effects of information technology
on organizations (Zur Muehlen, 2007). Evolvingfrom the former practice in business process
reengineering (BPR) and total quality management(TQM), the existing BPM is a comprehensive
approach to implement the process centric thinking.
Hill et al. (2006) stated that “BPM is neither atechnology nor an updated version of BPR. It is an
IT-enabled management discipline. BPM represents
a fundamental change in how businesses manage
and run their operational processes.”
BPM requires the fundamental changes in anenterprise-wide scale. These changes are not only
involving the information systems that support andimplement the business process management, butalso cover the fields of human resources and culture,
which have been obviously demonstrated by thepast experience and practice in BPR (Wells, 2000).
The BPM practice should involve enterprise-widechanges so as to fully implement and obtain thebenefits of BPM. Thus it will be systematic work
for an enterprise to succeed in the strategic andtactic shift to BPM. BPM covers many existing
research fields in the management discipline, suchas human resource, change management, andperformance measurement, etc.
3.2 CSISE Perspective
This perspective is more concentrating on thetechnical implementation of BPM paradigm inenterprise information systems. Research in thisperspective is usually done by researchers with thebackground of computer science and information
system engineering (CSISE). Their researches focus
on the components of BPMS and the formalisms of
the underlying languages.
The emerging BPMSs are integrating more andmore functional components by comparing with thetraditional workflow management systems. The
expanded lifecycle of BPM requires the inclusion ofcorresponding supporting components to businessprocess analysis. According to these constituent
components in BPMSs, we can review the BPM
research in this perspective.
3.2.1 Business Process ModelingBusiness process modeling is an active research
field in BPM. Some researchers also use BPM as
the abbreviation of business process modeling. In
the lifecycle of BPM, business process modeling is
mainly the work in the phase of process design. To
some extent, process modeling forms thefoundation of the other BPM research related to
BPMS. Well-defined business process models willbring forward many benefits to the whole BPMS.
Business process modeling methodologies
originated from systems analysis to provide agraphical description of business activities (Barber
et al., 2003). The value of process modeling is well
documented, noted for illustrating the big picture,
and as a vehicle for development andcommunication (Williams, 1994). Business processmodeling has advanced beyond the pure aim forgraphical representation and enables more process
analysis, such as process verification, diagnosis,
business activity monitoring and dynamic planning.
The artifacts of business process modeling arebusiness process models that define thefunctionality and structure of a process (subprocesses, activities and operations), the sequenceof activities and their relationships, the cost andresource usage characteristics, etc. Business processmodels, as a specialized category of enterprisemodels, focus on the description of businessprocess features and characteristics (Kalpic andBernus, 2006).
The previous and existing research in businessprocess modeling results in numerous approaches
and methods to model business processes. These
approaches can be categorized into formal andinformal approaches according to their degree of
employing mathematics (Li and Iijima, 2007).
The formal approaches employ a specificformal language that is usually defined based on acertain mathematical logic. Application of formal
methods in process modeling will bring about muchstrength to business process design and the whole
BPMS (Van Der Aalst and Van Hee, 2002;
Schumann, 2001). For example, the process model
specified in a formal language will be more precise
and remove ambiguity (Koubarakisa andPlexousakis, 2002). Benefiting from the underlying
formalism, these approaches can verify processmodels mathematically and reach higher degree ofrobustness. The potential reasoning capability suchas automatic process composition can also be
implemented since these methods are usually basedon a logic language that inherently enables thelogical inference.
The informal approaches usually lack theobvious support from mathematical theories. They
design business processes with a graphical or textbased language and make some simple simulation
to test the defined model. These approaches are
driven by the industry and have gained some
support and application in the business systems.
They are easily accessible to general business users
when there is a graphical interface. But only some
simple syntax errors can be detected, which
depends on the performance of simulation engines.

257

Detection of design errors is postponed to thetesting or even the execution phase of businessprocesses. This will obviously increase the cost andrisk for the development of BPMS.
3.2.2 Business Process Simulation (BPS)Business process simulation (BPS) has a close
relationship with business process modeling since
the implementation of simulation is necessarily
based on a defined business model. But BPS has its
own emphasis on simulating the dynamic features
or nonfunctional aspects such as cost and efficiency
while business process modeling concentrates moreon the static features or functional aspects ofbusiness processes. BPS allows management tostudy the dynamics of the business and consider theeffects of changes without risk (Barber et al., 2003).
Basically, BPS can detect some errors that haveexisted in the design phase. Ideally speaking, thiserror detection should be done during processmodeling phase. Since the existing BPM tools
usually lack sufficient verification function forprocess modeling, the designed process models arethus tested in the simulation phase. Some deadlocks
or unreachable activities can also be found by using
process simulation.
BPS can be used to allocate resources tobusiness processes. Many existing commercial or
noncommercial BPM tools usually include afunction to simulate a process according to thedesignated resources such as the number of
employees for a specific task in a process. Undercertain circumstances, for example, a certain
number of incoming orders in each hour, thissimulation could be used to test if the allocation of
employees is appropriate and efficient.
BPS can also be used to evaluate the IT
investment by simulating a business process before
and after the introduction of the new IT system that
implements the process (Giaglis et al., 2005;
Serrano and Den Hengst, 2005). By comparing thesimulation results, business analysts and decision
makers can arrive at more informed choices for
system design and evaluation.
4. Conclusions
Generally, BPM will involve many research
fields from either perspective of OTMS or CSISE.
With the maturing of BPM, this discipline will be
multidisciplinary, across the social and naturalscientific fields. The BPM practice will necessarily
involve organizational and technical changes so as
to succeed in a dynamic world. From theinstitutional perspective, management of businessprocesses and involved technologies is still an open
question for researchers and practitioners.

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Weske, M. (2003). Business Process Management:
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258

The Technology Management Requirements for the Telework-based Offshoring:
The Pre-evaluation Model to the Telework Readiness in Chinese Organizations
Zheng Zhao
Department of Industrial Engineering and Managemen
Tokyo Institute of Technology
2-12-1 W9 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANzhao.z.aa@me.titech.ac.jp
According to the two surveys that carried out during the 2005 to 2006, a pre-evaluation
model to the telework implementation readiness of the Chinese organization based on thefour factors including culture, management, communication and technology was proposedin this paper. The model consists of two parts including the questionnaire and theevaluation rules which can identify the telework preparation stage of Chineseorganizations by the score obtained from questionnaire.
By the result that field tested in a Chinese organizations, it is clear, the pre-evaluation
model had resulted in a series of significant and unambiguous results, and a valuable
experience, which can be used for the pre-evaluation before the designing and launching
telework on a larger scale in the organization.
increased from USD 0.25 billions of the year to
USD 2 billions of the year 2003.
In 2004, data were collected by survey to findwhether the telework fit Chinese organizations.
Then another survey was also carried out focus on
the management Requirement of Chineseorganizations to the telework implementation. The
survey looked at Chinese organization
computerization in terms of strategy, process, andother management activities. According to thesurveies have done in China, a pre-evaluate model
was proposed. First and foremost the aim of themodel was to identify the borderline between thereadiness and the telework. Furthermore a majortask for the model was to identify the readiness ofdifferent issues that was perceived to effect the
telework adoption including the culture,
management, technology, and communication
issues. This chapter will start with a introduction to
the questionnaire and detail discussion of theindividual issues and subsequently followed by adiscussion of the evaluate system to thequestionnaire result.
The pre-evaluation model is field tested in twocases which belong to the high-technology in orderto evaluate their telework preparation level.

1. Introduction
China is attempting to establish and promotecompanies that can compete globally, especially inadvanced technologies. What are the prospects ofcontinued reform and progress in the future? There arethree sets of forces that determine institutional changes
in China. These are the role of the government,
incentives generated in the market sectors and inertia
inherent in economic institutions. In the last twenty
years the government has guided the changes in
economic institutions. In the future the government
will remain active, especially in the technology areas.
China Software Industry has developed
rapidly in recent years with an average annual
growth of 30% on sales and 7 times growth onsoftware export for the past five years. Software
industry has already become a strategic industry
for national economy and social development.
China is emerging as one of major markets ofsoftware outsourcing services. According to thelatest survey report released by Gartner, Chinese
software outsourcing earnings is expected to catchup that of India in 2006 with the export of softwaredevelopment service to 27 billion dollars(ExpressIndia.com, 2002). If this trend continues,
China will become a major competitor in the global
outsourcing market (Thiagarajan, 2002). Besides
this, China is also a software consuming market
with a population more than 1.3 billion and morethan 15,000 middle-size and small-size domestic
firms, which are adapting to the world market
particularly since China became a member ofWTO. According to statistics, the sales revenue ofChina software industry had increased from RMB
59.3 billions of the year 2000 to RMB 160 billionsof the year 2003, and software export had

2. Related work and literature review
2.1 Literature review
The review of literature on telework adoption
reveals that the success of telework is significantly
affected by the usage of ICT (Information andCommunication Technology). ICT provides theopportunity to create new relationships andcontacts (Gaspar and Glaeser 1996). Telework is
a distributed and virtual work arrangement that259

allows employees to perform their work away fromthe central office using ICT (Lindstrom et al. 1997).
Adequate ICT provision, in the form of enhanced
electronic linkage plays a vital role in telework
success (Lucas and Baroudi 1994). Telework
demands that teleworkers and co-workers rely on
ICTs for communication, for coordination, and forcollaboration during the process of business. The
effectiveness of these virtual processes isinevitably affected by the quality of technology
support and communications management (Shin etal. 2000).
Spinks (Spinks 2001) conducted aninternational comparison of Japanese and North
American organizational telework programs toascertain what the crucial elements were for aneffective organizational telework program.
According to her findings, the four key factors
selection, training, support, and evaluation wereidentified. Almost all these factors are mainly forthe adoption procedure; however, a support canalso be considered as one of the key factors fortelework adoption prediction. According to Spinks,
the support can be divided into five major
elements: technology support, office environment
support, communication and feedback support,
career and compensation support, and top
management support. About the technology
support, the need for well-thought out support fromsuitable technology is a well-documented
requirement (Kinsman 1987; Olmsted and Smith
1989). The Office environment support is not only
important for home-based telework, but also fortelework centre setting (Huws et al. 1990).
Communication and feedback support are channelsof communication between teleworkers,
supervisors and co-workers (Kinsman 1987). The
need for top management support is constantly
stressed in the body of literature (Olmsted andSmith 1989). Communications and its coordination
quality, during the adoption of telework within an
organization, becomes a major concern (Shin et al.
2000). Communication is fundamental to any formof organizing, but it is preeminent in virtualorganizations. Without communication, theboundary-spanning among virtual entities would
not be possible. Electronic communication enables
parties to link across distance, time, culture,
departments, and organizations, thereby creating"anyone/anytime/anyplace" alternatives to the
traditional same-time, same-place,functionally-centered, in-house forms oforganizational experience (O’Hara-Devereaux andJohansen, 1994). Electronic communicationloosens constraints of proximity and structure on
communication, making it possible for spatially or260

organizationally distant parties to exchange
messages with one another (Feldman 1987).
Further, electronic communication provides anopportunity to signal interest in forming
connections that otherwise would be difficult or
impossible to maintain (Fulk et al. 1996). In thisway, communication is not only the trigger for
virtual relationships but also can be the outgrowthof them (DeSanctis, Staudenmayer and Wong inpress). New exchanges between parties, or new
relationships, can occur as a result of establishedconnections among distributed entities (Monge etal. 1998). Indeed, one of the hopes for virtualorganizations is that new connections among
entities will result from lateral boundary spanningand blending of expertise (Davidow and Malone
1992). According to this view, the real power ofthe virtual form is realized when relationships
among electronically connected people or firms
produce new and/or qualitatively different
communication that yields product or process
innovation (Ring and Van de Ven 1994).
Generally, examination of successful modern
organizations confirms that sharing long-term
common goals and values, developing anorganizational culture based on learning, andfocusing on knowledge acquisition anddevelopment are indissolubly connected to success.
It is not only a matter of adding basic technologicalskills in societies often still largely illiterate, but ofdeveloping a variety of new enriched skills capableof meeting the requests of more sophisticatedforms of global teleworking.
In successful organizations, investment in
ICTs goes with investment in training. For
countries, high levels of education and theavailability of communications infrastructure are
significantly correlated to economic growth. But
the fact that people are educated and have greater
access to information and communication are notsufficient to generate growth. Management styleand organizational structures must be in place withorganizational culture based on factors such as
flexibility, freedom, stability and trust, which
reward people for their motivation, commitment,
participation and learning. In short, organizational
environment is the catalyst to transform
information into knowledge, and then competitive
advantage.
According to the survey (Zheng, Z and Kazuo,
N.J., 2005) the ICT usage level of the Chineseorganizations is remarkably high: 83% respondents
use email and the rate of internet user is more than
90%, moreover, 85% respondents have their own
website. In this paper, we focused on the
management culture and management style issues

full-time telework for office workers may bedifficult to deploy without well-defined strategic
goals, which receive full endorsement by top
management. Advanced virtual process demands
that upper management be determined, and have acomplete understanding of telework’s implications(Kunihiko,H. and Bongsik,S, 2003).

to find whether Chinese organizations have
prepared as the partners of the developed
countries’ companies for the telework-based
offshoring.
Previous researches identified factors seem toimpede successful telework adoption. The fear oflost managerial control is reported to be asignificant issue preventing diffusion of telework(DeSanctis,G., 1984; Savage,J.A., 1988). Managers
are also concerned that telework may require themto change their management style because direct
monitor and control are unavailable. Researchers
suggested that a more results-oriented management
style is needed (Duxbury,L.E., Higgins,C.A., andTrving,R.H., 1987; Metzger,R.O., and Von
Glinow,M.A., 1988) and a shift in managementfrom being a passer of information to a leader orcoach is necessary (Savage,J.A., 1988;
Duxbury,L.E., Higgins,C.A., and Trving,R.H.,
1987). The cost of the ICTs equipments to work ina remote site is also seen as a possible obstacle,
requiring additional investment from managers(Hendricks,C.F., and McMains,G.L., 1989).
Technologies do not spread in an isolated
laboratory but in the living reality of enterprises
and societies. This means that their theoretical
impact is filtered through different environments
and reshaped by a variety of people into concrete
applications (Vittorio, D.M., 2005). Large-scale
Traditional culture
Misunderstanding of telework
Paper –based documents
Face-to-face meeting
Un-upgrade websites

Direct supervision
Low-level cross-department
co-operation
Low-level flextime work

Low-level remote access

Weakness

2.2 Related work
In summary, telework adoption usuallyrequires high technological environment support,
integrated communication channel, open culture
background, and efficient management style. All ofthese are critically dependent on the smoothfunctioning of the ICT usage. The survey describedand analyzed in this paper was carried out by
email-based questionnaire between June andNovember 2004. Its aim was to identify ICT usage
level of Chinese organizations and telework
diffusion level amongst the sample. Four issues
were also emphasized:
1.
Technology
2.
Management
3.
Communication,
4.
Culture.
According to the aforementioned four main
factors, the strength and the weakness factors oftelework adoption in China can be depicted in
Figure 1.

CultureCultural exchange via off-shoring.

Communication

High-level ICT usage (E-mail,website, mobile phone, telephone,internet)

Management

Existence of off-site work andoff-shoring

Technology

High-level ICT support (E-mail,website, mobile phone)

Telework Adoption in China
Figure 1 Strength and weakness of telework adoption in China

261

Strengthrelated to the company telework implementation.
By filling-out the questionnaire thoroughly, theresults will be obtained including an overview ofthe strong and weak points in company and what
deserves further attention. There are always fivealternative answers offered for individual groups ofissues. After evaluating them, the respondents wereasked to tick off the answer characterizing thesituation in their company most precisely.
Among the issues, Culture and management allow
us to determine the success of a random
organization, while technology and communication
are related to the level of cost and difficulty on
adopting telework.

Another survey was carried out during May
and August 2005 in China by e-mail questionnaire
which addressed issues of concern to the top
management level of the organization, considered
to focus on the high-tech fields including software,
hardware, and communication firms, thus it did not
addressed the ICT usage of respondents issue indetail.
According the survey data, Although, thetechnological environment for Chineseorganizations is ready for telework and thetelework-based offshoring, there are still many
issues such as management, culture andcommunication issues need to be solved especiallyin management issue before full adoption of
telework-based offshoring is considered by
Chinese organizations.

3.1.1 Culture
Current management very often strongly
emphasizes culture. Social anthropologists define
culture as: “Culture comprises inherited artefacts,
goods, technical processes, ideas, habits andvalues” (Bronislaw Malinowski) or: “Thehumankind is in reality bound together by culture –shared ideas and standards.” (Ruth Benedict).

3. Pre-evaluation
modeloftelework
implementation
According to the literature review and thesurvey which have been done in Chineseorganizations, it appeared that the telework canwork in some high-technology organizations suchas software companies especially in the developedarea of China. In fact, among these companies,
offshoring already exist and play a key role in thebusiness activities. On the other hand, more
Chinese organizations believed that telework-based
offshoring will provide opportunities to improvethe management skills and promote to be truly
global organizations. However, there are still many
problems in technology, management andcommunication issue such as only small number of
employees can use remote access, un-updated
website, and high frequency level of face-to-facemeeting, and so on.
In order to investigate the ability of
implementing a telework program, a pre-evaluation
model was established. This model consists of two
main parts: questionnaire mapping the company
preparedness to telework adoption and manual for
its evaluation. It is intended for the companies
which offshoring now or wish to do offshoring orother telework and its purpose is the initialassessment of the implementation potential. The
result of this assessment serves to the companies offurther training program which should help to
introduce or improve the telework adoption.

High
High

Consensus

Intensity

Low

StrongCultureNo Goals

Conflicts

Detached
Control

Low

Figure 2 Factors influencing the impact of standards onthe company culture

The standards can differ in two important
aspects: intensity and consensus. Strong culture ischaracterized by a high degree of the standards
impact and high degree of consensus. If there is ahigh degree of consensus but low degree of thestandards impact, the mission is often not achieved.
If the degree of the standards impact is high but thedegree of consensus is low, conflicts often occur
more easily. Low degree of both the factors reflects
the detached company management, shown infigure 2.

3.1

Questionnaire
In the questionnaire totally consist of 37
questions, and 4 main categories were focused.
This questionnaire includes four groups of issues262Successful strategic changes can be performed
only if the internal company system of values – its
shared culture – reflects the new reality. Well-built
company culture can multiply the motivation
elements in promoting the company’s strategy. The
company culture conceptions can be compared as
Table 1:

Culture is important for the telework adoption
for two different reasons:z It can help or hinder the strategy
implementationz It can deepen the motivation and feelingof joint responsibility inside the group oramong the organization members.

Table 1 Comparison of the organization culture conceptions

Old conception of culture
•
•
•
•
•

habits of the pastsharing of traditions
sharing of myths
sharing of rituals
sharing of heroes

New conception of culture
•
•
•
•
•

Company culture and its stimulating impulses,
voluntary human creativity and belief in thecompany’s ideology are the stimulating factors of
the internal powers.
Sharing of the company vision by its
employees is the founding stone of the company
culture, and also important for the implementationof the telework. Three questions were created andcovered three issues:- Organization values- Employee values- Character of leaders
The question which focuses on theorganization values issue epitomizes whether awell through-over strategy of companies that beable to succeed in future was established. In ahigh-score organization, they perceive thecompany culture not only as a mean of thecompany promotion but also as an instrument forincreasing of its output. At the same time thelong-term notion of this process is accepted.
In some low-level organizations, they just try
to build its company culture as a part of its
development plan. It means that building of thecompany structure does not belong to priority
strategic programs. The company’s central focus isin the presence. Moreover, in some organizations
the current problems take up the managers’ timeand operational approach prevails in the
management. In such an environment the teleworkor other innovation activities are not purposefully
developed.
The “Agree” or “Strong agree” answer to thequestion “My organization encourages an open
relationship between managers and workers.”suggests that the employees are informed about thecompany’s intentions. Thereby the company

genetic code of future actions
sharing of visiondevelopment and conflicts of ideas
innovation behaviour
teams of champions
opens up space for an initiative of its employees
and can effectively use it afterwards. However
flatness of such campaign can lead to its formalismand eventual stimuli do not represent sufficiently
effective motivation. The open relationshipbetween managers and employees allows theproper use of the employees’ potential. The“bottom-up” initiative is important here. The
possibility of active participation on the company
future formation creates preconditions for the useof motivation factors and continuous building of
the company culture.
The “Disagree” or “Strong disagree” answer
to Question “My organization is open to new
ideas.” is defined in last Question. Companies that
do not deal with monitoring of their employees’satisfaction are not interested in their systematic
motivating. An employee receives precise tasks
and he is evaluated according to their fulfilments.
That means the company is not interested insupporting its employees’ initiative, rather it justtries to make maximum use of them.
3.1.2 Management
The ability to understand and use the relation
between the management and telework gains evermore importance in the today’s global competitiveenvironment. Monitoring and analyses of the
management provide a company with instructions
for the adoption of practical steps for thetechnology improvement. The management
procedures are defined as significant activities
leading to business activities by application ofresearch and development results, building thebridges between the traditions and the future. The
management analysis is characterized by the
discussion whether tacit knowledge owned by an263

motivating and rewarding of employees. The aimof the motivation is to activate the process ofknowledge sharing and the development ofinterdisciplinary qualifications. That is closely
connected to the human resources management
concerning the career growth, increasing of expert
knowledge inside the company but only withpartial focus on skills deepening the company’s
innovation potential by means of knowledge
sharing and development of multidisciplinary
experience. Such as:• Organizations offing various training
program for employees. This is deemed to
be a precondition for a career growth aswell as looking for and exchange ofknowledge of various origin.
• Employees in the company are publicly
awarded for their contributions and merits
influencing the project course.

individual can be effectively transformed into an
explicit knowledge that can be shared in time andspace, for example in computer databases andnetworks. Such discussion is then focused on thewhole management system role in the process of
forming and achieving of the company’scompetitive advantage.
On the other hand, innovation activities
served for the creation of specific procedure that
distinctively differentiated between manners, inwhich individual companies engaged knowledge indevelopment of innovations. That predestines thedependence on the evolution path that isdetermined by the accumulated knowledge andexperience within the given company culture,
management style and setting of execution
processes.
By introduction and improvement of thetelework the company can realistically modify anddevelop its boundaries of innovation and open new
business opportunities. That is achieved byincreasing the company’s ability to produce
modifications while using the existing practices
and abilities as a platform for the research of newopportunities. Discovering the relations between
the management and the telework adoption alsooffers to companies an opportunity to sharpen theirtraditional innovation skills and open up new ways
to business success.
The management practices are regularrepeatable activities applying the acquired
knowledge in some manner. They can be bothformal and informal, in a traditional or electronic
form, initiated by people or the system. They
include wide range of factors such as:- Human resources
Successors;
Employee satisfaction;
Educational Programs / Training;
Hierarchical Style;
Intra labor market.
- Job evaluation
Employee performance;
Group performance;
Output evaluation.
- Management process
Resistance to the NEW (low,medium and top levels)
Feedback- Management decision
Management issue is related to theco-ordination of the internal and externalpossibilities of knowledge, information,
intra-company relations and market requirements.
The management issue also focused on the
telework adoption must treat the issue of

3.1.3 Technology
The current rapid development of informationand communication technologies offers
opportunity to transform the information
management activities, such as access to databases
and publishing of news influencing the work of theother company’s structures. Communication
technologies within the knowledge management
approaches trigger the creation or modification of
the knowledge management approaches. The
significant current growth in the multidisciplinarily of information technology scienceand the electronically supported formation ofvirtual project teams for science and development
have caused that the information management
specialists are turning their attention to applications,quick diffusion and sophistication ofcommunication technologies into activities related
to the change management.
Examples of the information technologies
management activities:• Allowing controlled external access forthe customers and external company
science and research co-workers in order to
identify and accelerate the key
development activities in the monitored
fields.
• Forming of “virtual teams” producing
innovative solutions.
• Definition of address space for theprovision of “navigation by means of
information” that is important for the
management particularly in the early
project stages.
• Introduction of web-research, so called“white pages” on the intranet.

264

of executing their concrete work
activities.
Telework will be implement in the long-term
strategic plan, company communication is theconcept often used by the modern strategic
management to describe the company’s way tohigher output.
It is known that the innovation activities
cannot be related just to the technical projects.
Every planned change such as telework adoption in
the business plan structure leading to the output
increase can represent an innovation. J.A.
Schumpeter pointed that out already in the 1920s
and he also defined two conditions for a successful
innovation:• Successful innovation is an accomplishedchange• Businessman, who can identify anopportunity for higher profit from theinnovation activity,
represents the decisive
power for the innovation performance
In communication issue, the following factors
was focused.
- Work style
Autonomous, Team-based,
Project-based;- Information sharing
Face to face, paper based, network
access (asynchronous/synchronous);- Communication direction
Vertical, horizontal and etc.
- Media / Channel• Extension of the applicability within thecompany with an interface allowing toshare of information both in theorganizational structures and towards thecustomers.
Several issues were considered to identify
the current technology level for the telework
implementation. Such as:- Infrastructure availability
Software, Hardware and Network;
E-mail, mobiles and remote accessto database;PCs and e-mail accounts / user
- Literacy level
Effective usage of infrastructure;
Training programs (IT related);
The high level technology stage will help totake the company on a higher-output-track and it
also makes the company to b more comprehensible
to its partners.
3.1.4 Communication
Business systems could be more effective andefficient if exploiting fully the possibilities of the
new ICT, relying on modern software applications
and hardware platforms. Information technology
communication applications support distributed
users using communication infrastructures andinformation technology, usually across theboundaries of organizations, are developed not
only to facilitate the communication between
distant business processes but also to create others
information transfer channels backgroundsupporting these processes.
The fact that some of the current businesssystems were designed before the modern
technology came in, without the particular thoughtin mind that they should possess an IT background,created the necessity of re- engineering some ofthese systems, re-designing their businessprocesses in order to make them easily supportableby new ICTs applications. As long as telework
appeared as a result of the ICT spread, it doesn’t
possess any of these problems. Something more,telework is inherently open to any kinds ofapplication support, because of the mere fact that itexists via modern software applications.
So, there is no doubt those ICTs applications could
support telework in many different ways, some ofwhich are outlined below.
z
ICTs applications could
facilitate the mere telework process,creating an environment, suitable for atelework implementation process.
z
Some ICTs applications could
support the teleworkers in the process

3.2
3.2.1

Evaluation of the questionnaire
Function proposal
This model includes four groups of issues
which mentioned before: culture, management,
technology and communication. All these issues
are related to the company telework
implementation. By filling-out the questionnaire
it is possible obtain an overview of the strong andweak points of a company and how the company
managed to create environment for effective
implementation of telework, and how it is capableof implementing telework into its activities.
There are always five alternative answers
representing different point offered for individualquestions of issues. After evaluating them, theanswer characterizing the situation in the company
most precisely is ticked off.
As for functional forms, the estimate function
was postulated as follow:
Score =Σ xi ai
xi: Individual score of the questions of different
factors (culture, management, technology, andcommunication);265ai: Value of the questions
i: Number of questions (totally 37 questions).

3.2.3
Identify the telework
preparation stage of organizations
According to the scores that were gotten bymanagers during the questionnaire, the companies
were classified into four classes.
• “D” class (Need improved): Companies
whose final score was less than 60 are
ranked into this class. Companies in thisclass did not build up their culture because
they see their task in defending of theircurrent position and securing of thecompany’s survival for the immediate
future. The company management mostly
corresponds
tothecharismaticmanagement position – owners who havelinear links set for the performance of theirtasks. At the same time, however, it claims
all the responsibility for the company
running and there is no space for the joint
decision-making of the employees. In brief,
their environment is not prepared for the
implementation of telework and if thecompanies want to deal with the telework
they need to perform radical changes intheir activities and organizations of therelevant area. Only after carrying out of therecommended changes and improving the
problems, the companies can further ondeal with the telework implementation on
systemic basis.
• “C” class (Normal): This class includes
companies whose final score was between
60 and 74. Linear links dominate in thesecompanies. The management uses thelower management for managing; somepowers are delegated to them.
The
consensus inside the company is secured
by a system of performance bonuses andsanctions.
The
communication
corresponds to the needs and possibilitiesof the linear management structure. The
company culture concept is familiar in thecompany however it is not systematicallyestablished but it is often substituted byeffect conditioning the company image. So,
their environment is not yet set for possible
work with telework and dealing withtelework but they are correctly oriented onfinishing of necessary changes in theirstructures and organizational structures.
Use of methodological coaching inhandling these basic reorganization
activities can be again recommended tothem and after that they can join theprocesses of systemic development of their

3.2.2

Value arrangement
According the survey research, the technology
level such as ICT usage of the internet and e-mailby the Chinese organizations is quite high. Suchhigh level of the ICT usage can be considered as apositive sign of potential adoption of telework, andit will be helpful to make the communication more
efficient and effective after the integration of ICT
with management process. Moreover, thepre-evaluation model was designed mainly for thehigh-technology organizations even in which there
was offshoring existed. Therefore, there are only
10% weight was given to technology issue and foreach question the value to the point was 0.33. For
example, we have the question as following:
Question: Considering aspects on technologicalknowledge, the employees are able to deal withconstant changes.
Strongly Agree--5
Agree--4
Moderate--3
Disagree--2
Strongly Disagree--1
If the answer is “strongly agree”, the scorewill be 5 (point) multiply 0.33 (value) equal 1.65
point.
On the other hand, there are still many
problems in management, technology andcommunication issues such as only small number of
employees can use remote access, un-updated
website, high frequency level of face-to-facemeeting, direct supervision, flexible work, andChinese traditional culture, and so on. Therefore, itappeared that we should pay more attention on theseissues, so 30% weight was given to culture issue andthe value to each point was 2; the highest weight
40% was arranged to management issue and thevalue was 0.66 per point; communication issue was
the 20% weight and 0.27 values for each point,
shown in Table 2.
Table 2 Value arrangement

Category%

Qs

V

Culture

30

3

2.00

Management

40

13

0.62

Technology

10

6

0.33

Communication

20

15

0.27

Total

100

37

% : weight ; Qs :question number ; V : value toeach point.

266

of the Chinese organization is fit the model, but thissituation was quickly rectified when the telework
introduction training was undertaken and theorganizations found the telework was actually they
expected. The pre-evaluation model generally
identified the organization current status in theculture, management, technology, andcommunication issues which was considered as the
key factors to the telework implementation.
Moreover, by pre-evaluated the organizations also
an overview of the strength and weakness points inthe company and what deserves pay more attention
in the telework implementation process.
On the other hand, there are still somethingneed to improve in the pre-evaluate model, such asindividual issue evaluate model to illustrate theactual weakness point more deeply so the consulting
company or organization itself can make the straightsolution to the points. The organizations also wanta model to monitor the change process in detailparticularly those related to changes in work
processes, training, management, organizational andcultural change.
Overall, it is clear, the pre-evaluation model
has resulted in a series of significant andunambiguous results, and a valuable experience,
which can be used for the pre-evaluation before thedesigning and launching telework on a larger scalein the organization.

innovation
potentials
withoutanydifficulties.
• “B” class (Good): Companies in thisclass meet the preconditions for effective
work with their innovation potential for the
telework implementation. The final score
should between 75 and 89. Companies
have built company culture anticipated intheir strategies.
It means that inaccordance with the basic standard they arecapable of using changes and innovations
for securing of their future prosperity andin fact they are ready to go through theprocess of certification. It is useful forthese companies to get the final success inthe telework implementation program.
• “A” class (Best): Companies with highscore (more than 90) belong here. These
companies meet the strict requirements ofthe telework adoption standard. It is mostprobable they have an overview of theirinnovation potential and they are looking
for ways of its further development. These
companies have establishes a solid
fundament for the further development of
the company culture. Organization
structure in the company is flat; delegationof responsibilities is related to thedelegation of powers. There is a career
growth system prepared for all theemployees and based on it a motivation
system is drawn.
Conflicts at theworkplace are analyzed from the point ofview of their benefit for the company andthey are also viewed as a source of ideas
for possible future output increase.
Implemented and from the side of
employees mastered and used information
system is necessary for the functioning of
the flat organizational structure. All thesefacts will great helpful to the teleworkadoption and organizations will strongly
recommend starting telework adoption
immediately in order to find new business
opportunities.

Reference[1] Davidow, W. H., Malone, M. S., 1992. The
Virtual Corporation. New York: Edward
Burlingame Books/Harper Business.
[2] DeSanctis, G., Staudenmayer, N., Wong, S-S.
(in press). Interdependence in virtualorganizations. In C. Cooper and D.Rousseau(Eds), Trends in Organizational Behavior. NY:
John Wiley.
[3] Duxbury,L.E., Higgins,C.A., Trving,R.H.,
1987. “Attitudes of Managers and Employees
to Telecommuting,” Infor 1987,
25(3):273-285[4] ExpressIndia.com, 2002. “China Catching Up
on Software Exports: Gartner,” September 23,
2002,
href=”http://www.expressindia.com/fullstory.p
hp?newsid=15036”[5] Feldman, M. S., 1987. Electronic mail andweak ties in organizations. Office: Technology
and People, 3, 83-101.
[6] Fulk, J., Flanagin, A., Kalman, M., Monge,
P.R., Ryan, T., 1996. Connective andcommunal public goods in interactive
communication systems. Communication
Theory, 6, 60-87.

4. Conclusions
From January to September in 2006, one
organization practiced the pro-evaluation model toevaluate their readiness level to the telework
implementation. Although some shortcomings were
found in the pre-evaluation model, the overall
judgment is that the model has been undertaken
professionally and effectively. There were somedelays at the start in pre-evaluation implementing thatsome organizations doubted whether the environment

267

The 6th International Telework Workshop
September 2001, Amsterdam[22] Thiagarajan, Krishnan, 2002. “Offshore
Outsourcing: Getting More Mainstream,”Businessline, Islamabad, October 20, 2002.
[23] Vittorio, D.M., 2005. “The High Road of
Teleworking,” href=”http://www.ilo.org/public/english/protection/s
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Fit China,” San Diego International Systems[7] Gaspar, J., Glaeser, E., 1996. “Information
Technology and The future of Cities,”
working paper 5562, National bureau of
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[8] Hendricks,C.F., McMains,G.L., 1989. “Fitting
the Homeworker into Corporate Culture, ”
Personal Administrator 1989, 34:38-43[9] Huws, U., Korte, W.B., Robinson, S., 1990.
Telework: Towards The Elusive Office,Information Systems Series, John Wiley &Sons, Chichester[10] Kinsman, F., 1987. The Telecommuters, John
Wiley & Sons, Chichester[11] Kunihiko,H., Bongsik S., 2003. “The
Telework Experience in Japan,”Communication of the ACM 2003,
46(9):233-242[12] Lindstrom, J., Moberg, A., Rapp, B., 1997.
“On The Classification of Telework,”
European Journal of Information System, 6(4),243-255[13] Lucas, H.C., Baroudi, J., 1994. “The Role ofInformation Technology In Organizational
Design,” Journal of management information
system, 10(4), 9-23
[14] Metzger,R.O., Von Glinow,M.A., 1988.
“Off-site Workers: At Home and Abroad,”
California Management Review 1988,
30(3):101-111[15] Monge, P.R., Fulk, J., Kalman, M., Flanagin,
A., Parnassa, C., Rumsey, S., 1998. Productionof collective action in alliance-based
interorganizational communication andinformation systems. Organization Science, 9,411-433.
[16] O’Hara-Devereaux, M., Johansen, R., 1994.
Globalwork. San Francisco: Jossey-Bass.
[17] Olmsted, B., Smith, S., 1989. Creating a
Flexible Workplace: How To Select andManage Alternative Work Options, Amacom,
American management Association, NewYork.
[18] Ring, P. S., Van de Ven, A., 1994.
Developmental processes of cooperativeinterorganizational relationships. Academy ofManagement Review, 19, 90-118.
[19] Savage,J.A., 1988. “California Smog Fuels
Telecommuting Plans,” Computerworld 1988,
22(18):65-66[20] Shin, B., Sheng, O., Higa, K., 2000.
“Telework-existing Research and Future
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Telework Implementation Model Changed?,”Conference, 2005

268

A Study on the Behavior of Media Selection in Distributed Working
Rui Gu**Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-110 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
Gurui@craft.titech.ac.jp
The behavior of media selection in IT companies in China and Japan was analyzed
using a framework of media fitness. The analysis included rational, social, andenvironmental aspects, therefore, more comprehensive than previous research. Combined
media usage was analyzed and strong positive correlation between choice based onrational thinking and that based on social influence was found. Furthermore,
complementary media were found to be used to satisfy the rational needs and to releaseenvironmental limitations, but not to raise the social satisfaction. Findings in this researchmight lead to the change of previous theories about media selection.

1. Why combined media are popularly used,and how the combinations help to prompt
communication.
2. The relation of medium in combined media
selection.

1. Introduction
The development of information technology
brought about the distributed work. People
cooperating remotely must face the problem ofchoosing right media to support communication. In
organizations, the problem of media selection iseven more complicated and important for mostremote workers. To answer the question “what kindof communication medium is good for mycommunication”, scholars proposed various
theories. Among them, the media richness theory(Daft and Lengel, 1986) [1] and the social influence
perspectives (Fulk, Schmitz, and Steinfeld, 1990)[2]are the two most well-known theories.

2. Introduction to the framework of MFT
In order to conduct this research, an evaluation
framework was constructed according to the media
fitness theory (MFT) (Higa and Gu, 2007) [3]. The
basic idea of the MFT is that people choose certain
media to communication because that media fits thevarious requirements, including rational, social andenvironmental aspects, of the communication task.
In the MFT, factors related to media fitness are
divided into three groups. Group I describes theneeds of communication task, Group II focuses on
the user and user group, and Group III is about
resource limitation that may influence the final
decision of media choice. According to MFT, thesethree aspects influence the media users integrally inthe process of media selection.
MFT is not a simple combination of MRT and
SIP. We demonstrate the relationship of MFT with
MRT and SIP in Table 1.

In the media richness theory (MRT), Daft et al.
tried to prompt a concept of media richness andused this concept to provide explanations for media
selection. In their view, media selection is madebased on the physical properties of various media.
According to the MRT, rich media to communicate
rich information is more effective than lean media,
and vice versa; and people will choose media basedon the richness level of a communication task. The
basic idea of social influence perspectives (SIP) isthat media selections are based on the preference ofpeople towards media and are influenced by thesocial environment.
During the studies after the proposal of MRTand SIP, both parties gradually accepted some ideas
from each other. And the debate between MRT and
SIP seemed to be subsided. But just as Webster andTrevino (1995) [5] pointed out, the problem ofmedia selection is still far from being solved. In thispaper, we try to provide answers to the following
questions relate to the behavior of media selection:

Table 1 Table 1 The coverage and relationship of MFT,MRT and SIP
MFT Group

MFT Property Name

MRT

SIP

I-1

Response time

〇

×

I-2

Security

×

×

I-3

Sharing△×

I-4

Retrieving

×

×

No.

269

I-5

Multiparty

×

×

I-6

Expressive power

△

×

II-1

Skill of using media

×

△

II-2

Preference of media

×

〇

II-3

Group lifespan×△III-1-1

Available time××

III-1-2

Available location

×

×

III-2

Bandwidth

×

×

III-3

Cost

×

×

3. Research methodology
Although there are a lot of papers related tomedia selection, little research has been done about
the comparison among media in a wide range. In
this research, we chose 6 typical media that arecommonly known by all and used by distributed
communicators. They are fax, email, telephone,instant messenger (IM), video conferencing system(VCS) and face-to-face (FTF). We use the term“sample media” to refer to these six media in thispaper. Sample media do not represent any specificmedia, they are the abstract media derived from
common features of certain kind of media.
Although it is possible to be computer-based andpaperless, the fax we defined here is a medium thatcan be used to transfer paper-based black-and-white
printed or written message though telephone line.
And the email here is text based and optionally with
attachments, running on the desktop computer.
Telephone is a medium to transfer real-time humanvoice with mobile communication ability. IM is amedium to transfer synchronous or asynchronous
text message and near-real-time low quality voice
and video. VCS is the special equipment fortransferring real-time and high quality voice andvideo.
We used an investigation template to test theframework we proposed. Templates consist of threeparts. The first part is the explanation of the aim theprocess and what to do. The second part is the
template table for respondents to fill in. The thirdpart is descriptions of all the properties listed in thetemplate table.
Four types of tasks were used in the research.
They are notification/transmission, coordination,
creation or decision, negotiation/persuasion, ranged
from simple to complex as proposed by Nakamura,et al. (1996) [4]. Respondents were asked toenumerate one typical communication task for each
type, write a text based task description and giveout the media that were practically using. Then
respondents were asked to fill in the template tablewith the references to the property description.
The investigations were firstly done in three IT
related companies in Japan. Then all illustrations
are translated into Chinese and applied to more IT
related companies both in Japan and China. Finally,
we got responses from totally 16 companies (6 from
China and 10 from Japan). Data collected was
calculated by the MFT framework.

△: Partially covered by MRT/SIP 〇: Fully covered by MRT/SIP ×: Not

coveredIn MRT, media richness is defined as thenatural property of a communication medium, andpeople make decision based on their rational
comparison of the richness of media and task. In
MFT, we try to project these properties of themedium onto the requirements of the task, thus
establishedtherelationshipbetweenthecommunication task and the attribute ofcommunication medium.
There are totally 12 major properties identified
by MFT (some have sub-properties) arranged in thethree groups mentioned above.
Response time is after how long an interval thecommunicator must get the response from thecounterparty. Sharing represents how much theinformation need to be personalized. Retrievingmeans how easy the information may be retrieved
or indexed for later use. Expressive power includes
text, picture, voice and video. Preference of media
is defined as whether the superior/majority of thegroup members like or adapt to use certain media.
Available time and location are when and where themedia are available for use. Bandwidth means how
much bandwidth can be provided forcommunication media. Cost means how much cost
can be provided for running communication media
by the organization. For more details of thedefinition of these properties, please refer toanother paper about the MFT framework (Higa andGu, 2007) [3].
Although MFT fully covered neither MRT nor
SIP, their basic points were succeeded. Since MFT
is not a simple composite of MRT and SIP, so wewill use the term “rational thinking” or “rational
selection” and “social consideration” or “social
choice” to represent the media richness part andsocial influence part respectively in this paper.

4. Data analysis
The primary medium is the main medium usedin real cases. If there was a secondary medium beenused for the same task, it was counted as thecomplementary medium. The primary medium isthe only medium been selected in single-media

270

cases, and is the most important or indispensable
medium in combined media selections.
Media selections according to the calculation ofrational thinking, social consideration and MFT
were compared with the real-case choices in eachtask.

Primary

Primary

type

rationalsocialChinamentary

mentary

rationalsocialType 14501Type 22

5

2

1Type 3

4

5

0

3

5

Type 1

10

9

0

4

Type 259

13Type 38704Type 49

8

0

3

Table 3 Result of Spearman’s correlation test
Spearman’s test

Primary

Primary

CompleComplerationalsocialmentary

mentary

rationalsocialPrimary rational

1.0000Primary social

0.8768**1.0000Complementary-0.7135*-0.4078

1.00000.11320.18020.05730.11321.0000

rational
Complementarysocial**: significant level of 1% *: significant level of 5%

From Table 4 we may find that the rational
selection and complementary choices are
significantly positively correlated, which means
rational selection and social choices are mutualpromoting rather than conflicting.
The negative correlation between primary andcomplementary rational selection indicates thatonce a media selection is done by rational thinking,it is likely: (A) there will be no need forcomplementary media, or (B) the complementary
media tends to be the competing candidate to theprimary medium.
4.3 The analysis about the increase of scores
when complementary media are involved inTable 2 Summary of counts of media choice matches
Task

3

A Spearman’s correlation test was done to test
the relation of the primary and complementary
choices under the direction of rational and social
thinking.

primary and complementary selection
We count the number of matches that rational
selection and social choice match with the real
choice and group them according to task type andcountry. The summary of the choices is listed inTable 2.

Country4

Note: Task 1-4 refer to four types of communication tasks.

4.2 The analysis about the relation between

Comple-1Japan

4.1 Overview
There were 16 cases in this research, and every
case contained 4 tasks, i.e. there were totally 64
tasks examined. MFT indicated the exact same
media choices as real choices in 63 tasks. The only
task which MFT failed match with, was undergoingwork-style changing. The follow up investigation
verified MFT was still effective in that task. So it issafe to say MFT matched with media choices in all
64 tasks.
According to the calculation results of all the 64
tasks, rational selections matched with the primary
selections in 43 tasks (67.2%) and social choices
matched with primary selections in 52 tasks(81.3%). This result positively matched with theresults of previous researches that social choiceseems to be more effective in media selection
predictions. Rational selection and social choice
pointed at the same choice in 35 tasks (64.1%). This
fact indicated that the choices resulted from these
two thinking have big overlaps.
In all the 64 tasks, only 21 (32.8%) tasks used
only one medium. Both MRT and SIP did notprovide explanation for combined media choice, so
MFT is notably more widely applicable. If we only
focus on the primary media selections, we will alsofind that there are 4 tasks in which real choices
match with neither rational selections nor social
choices. This furthermore indicates that MFT is
more comprehensive than MRT and SIP.

Comple-Type 4Complementary media are used to complement
the defects of the primary media. The introductionof complementary medium may raise the total scoreof combined media in three property groups, thus
makes the combined media better than single media
choice. We traced down the calculation procedureof MFT and count the times that complementary
media provided an increase, and then recorded thesum in Figure 1.
Among all 43 tasks that used combined media,
there were 23 cases in which only the score of271

Group I was increased. And in 6 tasks only thescore of Group III was increased. But in no task
only the score of Group II was increased. In 2 tasks
both the scores of Group I and II were increased, in
7 tasks both the scores of Group I and III wereincreased, and in 1 task both the score of Group II
and III was increased. And in 4 tasks, the score of
all three groups were increased.
We may found that, the reason for using
complementary media mainly concentrated insatisfying the needs of rational functions. And thesecond reason is to release from the environment
constrain. It is remarkable that no task usecomplementary media only for satisfying the social
needs.

We did F-test to the primary counts and thecomplementary counts, and got a p-value of 0.0331,
which indicates the distributions of the two groups
are significantly different. We may easily foundthat email and face-to-fact are the main primary
choice in most companies (76.6% of all tasks). But
the complementary media selection tends to bedispersed.
4. Conclusion
Based on the situation of real usage, we clearly
differentiated the primary from complementary
media. From the analyses in section 4.2, we foundthat rational selection and social choice are notconflicting in the real media choices. This factprovided us a clue to think about rational and social
choice, which one is more active, namely, it is thesocial thinking follows up the change of rational
selection, or vice versa. The analyses in section 4.3
provide a possible answer to the question: to raisethe degree of social acceptance is not the reason
why complementary media are used. So, it is logicalto derive that rational selection is the motor of
media selection. The analyses in section 4.4
indicate that email and face-to-face are the twomost important communication media nowadays.
There still potential problems in this study. The
companies we investigated in are IT relatedcompanies, so there is a possibility that thediscussion will not be applicable universally. And
the sample number is small, which might influence
the accuracy of the analyses.

Group I
23
2

7
4

0

6

Group II

1

Group III

Fig. 1. Counts of increase of scores caused bycomplementary media

4.4 The analysis about the behaviour of choosing

References

media in primary and complementary media
selection
We summarized the counts of all sample media
and user defined media in Table 5. Email was usedas primary medium in 25 tasks, which was thehighest count, and followed closely by face-to-facefor 24 tasks. Email also got the highest count inbeing used as complementary medium, followed byuser defined media.

[1]

Daft, R.L. and Lengel, R.H., 1986,
Organizational information requirements,
media richness and structural design.
Management Science, 32(5), 554-571.

[2]

Fulk, J.Schmitz, J. A. and Steinfeld, C. W.,
1990, A social influence model of technology
use, Newbury Park, CA: Sage, 117-140.

[3]

Higa, K. and Gu, R., 2007, Communication
media selection for remote work: Towards atheory of media fitness. Journal of E-Working,1(1), 45-68.

[4]

Nakamura, K.Ide, T. and Kiyokane, Y., 1996,
Roles of multimedia technology in telework.
Journal of Organizational Computing andElectronic Commerce, 6(4), 385-399 .

[5]

Webster, J. and Trevino, L.K., 1995, Rationaland Social Theories as Complementary
Explanations of Communication Media
Choices: Two Policy-Capturing Studies. The
Academy of Management Journal, 38(6),1544-1572.

Table 4 Counts of the media been used
Media

Used as primary

Used as complementary

Fax

0

0

Tel

2

9

Email

25

11

IM

3

2

VCS

1

5

FTF

24

6

User

9

10

272

Social, Cultural, and Personal Factors Influencing the Usage ofComputer-Mediated Communication Technology by Chinese Elderly People
Kang Chen**

Tokyo Institute of Technology
2-12-1 Ookayama, Meguro-ku,Tokyo, 152-8550, JAPANchenkang@ml.me.titech.ac.jp
Since the last century, information and communication technology (ICT) has been
introduced into both developed and developing countries. In those countries, however,older populations have problems in adopting those emerging technologies and taking fulladvantages of them. The factors influencing older people’s usage of modern technologies
include various factors from personal to social and cultural. Thus the acceptance oftechnologies might depend on each country’s institution. The goal of this study is to
identify social, cultural and personal factors influencing older people ’ s using
computer-mediated communication (CMC) and compare between countries
1.

Introduction
Not only the developed countries such as Japan,
but also the developing countries such as China
have to face the rapidly aging populations. The ratioof the population aged over 65 was 6.96% in 2000.
In Shanghai, the ratio was 11.3% in 2000
(NBSC,2003).
On the other hand, more people, including
elderly, can benefit from various new technologies
as now they are increasingly utilized (Czaja, 1997).
It is very important to promote the utilization of
new technologies by elderly, because informationand communication technologies (ICT) may
support them in the daily life. The older adults havethe motivator and possibilities learn and use ICT(Morrell et al, 2000; Blit-Cohen & Litwin, 2005).
Psychological and human factors studies havebeen conducted on the issues of elderly people's useof computers and the Internet (Jay & Wills,1992;
Ellis & Allaire, 1999). One of the promisingpredictors of older users’ computer usage iscomputer attitudes (Umemuro & Shirokane, 2003).
However, the influence of social, cultural, andpersonal factors on usage had rarely been studied(Xie, 2003). As one in the society, our personality isdeveloped over time and influenced by social andcultural factors(Cross & Markus, 1999).
Personality should influence on people’s
participation in the virtual world as it does in thereal world. The perception on the virtual society
should influence people’s participation in it. The
social and cultural factors in real world should
influence the participants’ action in the viralworld. The social and cultural system is one part ofthe institution.
The purpose of this study was to investigate therelationship between these factors and usage of thecomputers and network among elderly and compare
countries to find out the difference between their

institutions influences.
2. Methods
2.1 Participants and Procedure
945 elderly adults, aged between 50 and 88 (M= 62.2, SD = 7.2), was selected from the four
districts in Shanghai, China and completed survey
study. Shanghai was selected because the society isfacing aging problem and the citizens have thebasic economic and educational background to own
the computer and ability to use ICT. Among
participants, 517 were female and 428 were male.
There were 663 personal computer (PC) users, 516
WWW users, 505 e-mail users, 334 Bullitin Board
System (BBS) users and 332 chatting room (CR)users.
The investigation was conducted during August
2004. Participants gathered in groups at local
centers. They first had the purpose and outline of
the research explained, then asked to complete thesurvey questionnaire, which consisted of five parts.
The first part was about participants’ demographic
data and health condition. The second part was
about the computer background and attitude. Part 3
was about the participants’ perception of CMC. The
fourth part was probing participants’ personality.
The last part was probing participants’ expectationof the influence of social/cultural factors on
people’s BBS usage.
2.2 Measurement
Participants’ computer attitude was investigatedusing the Attitude Toward Computer Questionnaire(ATCQ) (Jay & Wills, 1992), a 35-item
multidimensional scale for assessing sevendimensions of attitude toward computers: Comfort,
Efficacy,
GenderEquality,
Control,
Dehumanization, Interest, and Utility. Participants
responded to each item by a five point Likert scale
between 1 (strongly agree) to 5 (strongly disagree).
273

The responses were further converted so that lager
numbers represented more positive attitudes. The
response scores were then summed to obtain scoresfor each of seven subscales.
A questionnaire was developed to assessparticipants’ perception of BBS perception. The
questionnaire consisted of 40-item scale forassessing 8 dimensions of CMC perception: Anxiety,
Addiction, Openness, Participation, Manner, Utility,
Liking and Self-confidence. Participants responded
to each item by a five point Likert scale between 1(strongly agree) to 5 (strongly disagree). The
responses were further converted so that the lager
numbers represent more positive perceptions, andsummed to obtain the score for each of eight
dimension subscales.
Participants’ personality was assessed using the
Big Five Personality Dimensions (John et al., 1991),
a 44-item scale for 5 dimensions of personality:
Extraversion, Agreeableness, Conscientiousness,
Neuroticism and Openness. Participants responded
to each item by a five point Likert scale between 1(strongly agree) to 5 (strongly disagree). The
responses were summarized to obtain scores foreach of five personality scales.
3. RESULTS
3.1 Personality
Scores of five personality scales were compared
between groups of users (U) and non-users (NU) of
PC, WWW, e-mail, BBS and CR. Table 1
summarizes the results of the comparisons. The
Openness scales were significantly different
between U and NU groups of all fivetechnologies/media. This result implies that
openness to new experiences is strongly related tothe usage of these Internet technologies.
Conscientiousness was significantly different
only between PC users and non-users. The use of
PC seems to require the user’s characteristics towork in a right way.
n the other hand, the Extraversion scale wassignificantly different between U and NU groups ofe-mail, BBS, and CR. This result implies that theusers of these media have common characteristics
to like social interactions with other people.
3.2 Computer Attitude
ATCQ subscale scores of all participants werecompared between users and non-users groups for
PC, WWW, e-mail, BBS and CR. Table 2
summarizes the results of the comparisons. Comfort,
Efficacy, Interest, and Utility subscales weresignificantly different between U and NU groups of
all five technologies/media. This result is in linewith the previous studies that positive attitudes are
related to the use of computers. Also, Control
subscale was significantly different between U and
NU groups of four technologies other than CR.
274

3.3 CMC perception
Scores of participants’ perception of CMC werecompared between U and NU groups of PC, WWW,
e-mail, BBS and CR. Table 3 summarizes theresults of the comparisons. There is a generaltendency that users of all five technologies/media
had more positive perception of CMC than
non-users. Interestingly, users perceived that BBS isless addictive than non-users did. On the other hand,users also perceived that CMC is the place where
manner of people are bad more than the non-users.
3.4 Social/Cultural Factors
Table 4 summarizes the ratio of participants who
responded that any of eleven social/cultural factors
were either helpful or obstructing the people’s use
of BBS. For both users and non-users, the largest
number of people responded that education level
was important factor, which might help or obstructpeople’s participation in BBS. Other social factors
with which larger number of participants responded
as helpful were: social support, law and economy.
People’s willingness to challenge new things was
also considered as helpful by many participants.
In addition to education mentioned above, othersocial factors with which large number ofparticipants responded as obstructing were:
economy, law, and infrastructure. People’s
willingness to challenge new things was also
considered as obstructing by many participants. In
addition, BBS non-users also consider thatgovernment, social support, and netiquette are
obstructing people’s participation to BBS
community.
4. Discussion and Conclusion
The purpose of this study was to investigate thesocial, cultural, and personal factors that might
influence elderly people’s use of CMC. The result
showed that some of personality scales, computer
attitudes, and CMC perception were related to the
usage
of
CMC
and
other
Internettechnologies/media. Also social/cultural factors
which people considered either helpful or
obstructing were identified.
Among personality scales, openness to newexperiences was found to be related to the usage of
all technologies/media investigated: PC, WWW,
e-mail, BBS, and chatting room. On the other hand,
extraversion was only related to the usage of e-mail,BBS and chatting room, and not to PC and WWW
usage. The reason for this result is considered thatthe three media, e-mail, BBS and chatting room areInternet technologies on one hand, but also
communities where people socialize and interact
with other users. Thus, to make use of these media
or not should be strongly related to people’s
tendency for socialization. On the other hand, theuse of PC and WWW do not necessarily requireinteraction with other people. Thus the users of PC
and WWW didn’t show clear extraversion
characteristics.
Some of computer attitude subscales, such as
Comfort, Efficacy, Interest, and Utility, were foundto be related with usage of PC, WWW, E-Mail,BBS and chatting room. This result is in line withthe previous studies that positive computer attitude
is a reliable predictor of computer usage.
People’s perception of CMC was related to all
five technologies/media investigated. Among eightfactors, non-users appeared to believe that CMC is
addictive more than users did. This perception
might baffle non-users and make them reluctant toparticipate in CMC community. In order to promote
the people’s CMC usage, it might be necessary to
make opportunities to communicate between users
and non-users, and improve this under-appreciation.
In addition to the social factors such as
education, law, and economy, non-users of BBS
appeared to consider that lack of social support, andproblems of netiquette are obstructing people fromparticipation. In order to promote older people’s use
of BBS, communities need efforts to improve
themselves and support new participants. The
problem of addiction above might also be overcome
by such efforts of communities.
The results of this study might depend on thesocial/cultural characteristics of China or the
Shanghai region. In order to generalize theimplications from this study, comparative studies
with Japan would be done. Also, newer
technologies and new form of communities, such as
weblog and ubiquitous network access, areemerging. The participation of elderly people, andfactors that may influence their participation should
also be investigated in the future study.

constitution of personality. In: Pervin LA,
John OP editors. Handbook of Personality.
New York 1999: 378-396[3] Czaja, S. J. (1997). Using technologies to
aid the performance of home task. In Fisk,
A.D., Rogers, W.A. (Ed.). Handbook ofhuman factors and the older adults(pp.311-334). San Diego: Academic Press.
[4] Ellis RD, Allaire JC.(1999). Modelingcomputer interest in older adults: the roleof education, computer knowledge, andcomputeranxiety.
Humanfactors;41(3):345-355[5] Jay, G. M. and Wills, S. L. (1992).
Influence of direct computer experience onolder adults’ attitude toward computers.
Journal of Gerontology: Psychological
Sciences, 53B(5), 329-340.
[6] John, O. P., Donahue, E. M., and Kentle, R.
L.
(1991).
The
“Big
Five”
inventory—version 4a and 54. Berkeley:
University of California, Institute of
Personality and Social Research.
[7] Morrell, R. W., Park, D. C., Mayhorn, C. B.
and Kelly, C. (2000). Effects of ages andinstructions on teaching older adults to use
ELDERCOMM, an Electronic Bulletin
Board System. Educational Gerontology,
26, 221-235.
[8] National Bureau of Statistics of China(2003). 2000 population census of China.
2003 China Statistical Year Book, chapter
4: population: Basic statiscal on national
population census in 1953, 1964, 1982,
1990 and 2000.
[9] Umemuro, H., and Shirokane, Y. (2003).
Elderly
Japanesecomputerusers:
Assessing changes in usage, attitude, andskill transfer over a one-year period.
Universal Access in the Information
Society, 2(4), 305-314.
[10] Xie B.(2003), Older Adults, computers,
and the internet: Future Direction;
Geronthechnology; 2(4):289-305.

REFERENCES[1] Blit-Cohen E, Litwin H.2005 Computerutilization in laterlife: Characteristics andrelationship to personal well-being.
Gerontechnology, 3(3): 138-148[2] Cross SF, Markus HR, 1999. The cultural

Table 1 Means and standard deviations (in parentheses) of the Big Five Personality Inventory scale scores.
(N=945). Asterisks indicate significance levels of t-tests between U and NU groups. *p < .05. ** p <.01
Subscale
Extraversion
AgreeablenessConscientiousness
Neuroticism
Openness

PC
U
26.1
(3.2)
31.1
(2.3)
31.9*
(3.0)
21.3
(3.4)
33.6**
(3.9)

NU
25.8
(3.2)
30.8
(2.4)
31.4
(2.9)
21.7
(3.5)
32.0
(4.0)

WWW
U
NU
26.1
26.0
(3.2)
(3.2)
31.1
30.9
(2.2)
(2.6)
31.9
31.6
(2.9)
(3.2)
21.1*
21.7
(3.3)
(3.4)
33.5*
32.7
(3.8)
(4.2)

275

E-MailU
NU
26.3**
25.6
(3.2)
(3.2)
31.1**
30.8
(2.2)
(2.6)
31.9
31.5
(2.9)
(3.1)
21.3
21.5
(3.4)
(3.5)
33.7**
32.4
(3.9)
(4.0)

BBS
U
NU
26.7*
25.6
(3.2)
(3.2)
31.2
30.9
(2.3)
(2.4)
32.0
31.6
(3.0)
(3.0)
21.2
21.5
(3.3)*(3.5)
34.0**
32.6
(3.9)
(4.0)

CR
U
NU
26.6**
25.6
(3.2)
(3.2)
31.1
30.9
(2.3)
(2.4)
31.9
31.6
(3.0)
(2.9)
21.4
21.4
(3.4)
(3.5)
33.6**
32.8
(3.9)
(4.0)

Table 2 Means and standard deviations (in parentheses) of Attitude toward Computer Questionnaire subscalescores. Asterisks indicate significance levels of t-tests between U and NU groups. *p <.05. ** p <.01
Subscale
Comfort
Efficacy
Gender Equality
Control
Dehumanization
Interest
Utility

PC
U
NU
18.0*
15.3
(2.9)
(3.2)
19.1**
16.8
(2.5)
(3.3)
15.8*
16.3
(2.7)
(2.6)
19.4**
18.7
(2.4)
(2.9)
13.9
13.6
(2.7)
(2.8)
19.7**
18.1
(2.3)
(3.0)
16.0**
15.0
(2.8)
(2.6)

WWW
U
NU
18.2**
16.1(2.99)(3.4)
19.2**
17.6
(2.4)
(3.3)
15.9
16.0
(2.8)
(2.7)
19.5**
18.9
(2.4)
(2.7)
13.8
13.9
(2.7)
(2.8)
19.7**
18.7
(2.2)
(2.9)
16.1**
15.3
(2.8)
(2.8)

E-MailU
NU
18.3**
16.0
(2.8)
(3.4)
19.4**
17.4(2.4)(3.14)
15.9
16.0
(2.8)
(2.6)
19.5**
18.9
(2.4)
(2.7)
13.8
13.8
(2.8)
(2.7)
19.8**
18.5
(2.2)
(2.9)
16.1**
15.2
(2.8)
(2.8)

BBS
U
NU
18.6**
16.6
(2.6)
(3.3)
19.5**
17.9
(2.5)
(3.0)
15.8
16.0
(2.9)
(2.7)
19.5*
19.1
(2.6)
(2.6)
14.1*
13.7
(2.8)
(2.7)
19.8**
18.9
(2.2)
(2.8)
16.1*
15.5
(3.0)
(2.7)

CR
U
NU
18.4**
16.6
(2.8)
(3.4)
19.6*
17.9
(2.6)
(2.9)
15.9
15.9
(2.9)
(2.7)
19.2
19.3
(2.5)
(2.6)
13.9
13.8
(2.7)
(2.8)
19.8**
18.9
(2.4)
(2.7)
16.1**
15.5
(3.0)
(2.7)

Table 3 Means and standard deviations (in parentheses) of BBS perception subscale scores. Asterisks
SubscaleAnxiety
LikingUtility
Addiction
MannerContribution
Participation
Self-confidenceU
16.6**(2.5)
17.9**(2.7)
16.0**(2.6)
14.7**(2.7)
14.2**(2.7)
16.0**(2.6)
17.9**(2.6)
16.5**
(2.3)

PC

NU
16.1
(2.1)
16.3
(2.7)
15.1
(2.0)
14.3
(2.1)
14.7
(2.1)
15.1
(2.0)
16.6
(2.6)
14.8
(2.1)

WWW
U
NU
16.6
16.3
(2.6)
(2.3)
17.9**
17.0
(2.7)
(2.9)
16.0*
15.6
(2.6)
(2.3)
14.7*
14.4
(2.6)
(2.4)
14.3
14.4
(2.7)
(2.4)
16.0*
15.5
(2.6)
(2.4)
17.9**
17.2
(2.7)
(2.5)
16.6**
15.4
(2.4)
(2.2)

E-Mail
U
NU
16.7*
16.2
(2.6)
(2.2)
18.0**
16.7
(2.7)
(2.9)
16.2**
15.3
(2.6)
(2.2)
14.8**
14.3
(2.7)
(2.4)
14.0**
14.7
(2.7)
(2.4)
16.7**
15.9
(2.5)
(2.5)
18.0**
17.0
(2.6)
(2.6)
16.8**
15.1
(2.3)
(2.2)

BBS
U
NU
16.9**
16.2
(2.7)
(2.2)
18.5**
16.8
(2.6)
(2.8)
16.5**
15.2
(2.6)
(2.3)
14.7
14.5
(2.8)
(2.3)
13.8**
14.7
(2.8)
(2.4)
17.1**
15.8
(2.6)
(2.4)
18.4**
17.0
(2.6)
(2.6)
17.1**
15.2
(2.6)
(2.4)

CR
U
NU
16.3
16.6
(2.4)
(2.5)
18.6**
16.8
(2.5)
(2.8)
16.4**
15.3
(2.7)
(2.3)
15.4**
14.0
(2.8)
(2.3)
14.4
14.3
(2.8)
(2.5)
17.1**
16.0
(2.7)
(2.3)
18.3**
17.1
(2.6)
(2.6)
16.9
15.5
(2.3)** (2.3)

indicate significance levels of t-tests between U and NU groups. *p < .05. ** p <.01
Table 4. The ratio of participants who responded as the social/cultural factors would have positive or
negative influence on people’s use of BBS.
Help (positive)
Obstruct (negative)
factorsBBS Users (%) BBS Non-users (%) BBS Users (%) BBS Non-users (%)
Law
27.3
28.8
21.8
29.1
Government
19.0
22.5
15.2
18.8
Education
39.9
33.6
44.8
37.9
Economy
25.3
21.7
30.5
27.3
Infrastructure
21.8
17.5
21.0
14.8
Family Support
20.4
12.5
12.1
13.0
Social Support
28.7
22.7
17.5
18.4
People’s willingness
27.0
21.9
22.1
17.4
Stress
9.5
10.1
14.9
12.8
Open-mindedness
18.7
15.3
6.3
5.6
Netiquette
17.2
17.3
16.7
18.6

276

Comparing with Personal , Cultural and Iinstitutional Factors Influencing on
Compter Media Comminication (CMC) Usage between Japan and China
Chen Kang**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANchenkang@ml.me.titech.ac.jp
we built a model of the three level roles influencing the existing and novel technologies
usage. The three levels consist of macroscopic, mesoscopic and microscopic ones. My
hypothesis is that macroscopic level played a main role in the very early steps oftechnological innovation. Mesoscopic level played an improve/making role. And microscopic
played a using and testing role. A survey was conducted on how social and cultural factors
influencing old adults using CMC technologies/media. A tentative finding is that the main
factors influencing/obstructing using these technologies are economic, education, willingness
and netiquette in both Tokyo and Shanghai. But some other factors are quietly different
between two cities.

1. Introduction
With the internet and computer technology
development, more and more people ,including theelderly, benefit from using it1). At the same time ,not only the industry countries, but also thedeveloping countries such as China have to face therapidly aging society problemes2).
Even it is believed that information andcommunication technologies can support the elderlyin the daily life, there are still less older adults using
it compareing with the younger adults3,4).
How to encounrage and help more elderly touse IT technologyies has been stuied by someresearchers in psychological and human factors area.
One of the promising predictors of older users’
computer usages is computer attitudes5,6,7). Somepersonal factors such as Big Five can predict theusageofintentandcommunication
technologies/meida, especialy the computer media
comminication (CMC) technologies8). Olsons’considerder that there should be four basic concepts
duringstudyingthetele-comunication
technologies usage9). The most diffificult part is thatthe cultural facorts influencing people readiness fortechnologies usage. However, the influence ofsocial and cultual factors on usage had raely beenstudied.
We considered the usage and popularization of
new technologies should be in three leveles. The
three levels consist of macroscopic (countries andgolbalization enterprizements), mesoscopic (Smalland medium enterprizements) and microscopic ones
(person). The upper two levels mainly provide thetechnologies readiness preparision. The micoscopic
level prepare the motivation readiness and thecommon ground. All these are influenced by the277

ecomomic, education, law, social support and othersocial and cultual factors.
The purpose of this study was to invest thedifferences
and similar socialand cultural
factors between usages of CMC techchonlogies inthe developed countries and developing countries .
CMC technologies (such as e-mail, Bulletin Board
System (BBS), Chatting Room (CR) ) was selected
as the target technologies, since their usage not onlyreflect people participatory behavior in the cyber
spaces, but also consists of active interaction among
participants, and thus various factors in personality,
society and person-community relationship are
expected to influence their participation.
2. Methods
2.1 participants
There are 882 (M = 62.2, SD = 7.2) shanghai
elderly adults and 286 Tokyo elderly adults (M =67.9, SD = 5.4) who aged over 50. Here, we selectthese two cities, because their society both facing
aging problem and the citizens have the basic
economic and education background to own thecomputer and ability to use the CMC.
2.2 Procedure
In Shanghia, the investigation was conductedduring August 2004. Participants gathered ingroups at local centers. They first had the purposeand outline of the research explained. They werethen asked to complete the survey questionnaire,
which consisted of five parts. The first part was
about participants’ demographic data and healthcondition. The second part was about the computer
background and attitude. Part 3 was about theparticipants’ perception of CMC. The fourth partwas probing participants’ personality. The last partwas probing participants’ expectation of theinfluence of social/cultural factors on people’s BBS
usage.
In Tokyo, the survey was done with the samequestionnaire by mail in July ,2005.

role as a helpful factor and social surpport as a main
obstucting factors.

2.3 Measurement
Participants’ computer attitude was investigatedusing the Attitude Toward Computer Questionnaire(ATCQ)6), a 35-item multidimensional scale forassessing seven dimensions of attitude toward
computers: Comfort, Efficacy, Gender Equality,
Control, Dehumanization, Interest, and Utility.
Participants responded to each item by a five point
Likert scale between 1 (strongly agree) to 5
(strongly disagree). The responses were further
converted so that lager numbers represented morepositive attitudes. The response scores were thensummed to obtain scores for each of sevensubscales.
A questionnaire was developed to assessparticipants’ perception of CMC perception. The
questionnaire consisted of 40-item scale forassessing 8 dimensions of BBS perception: Anxiety,
Addiction, Contribution, Participation, Manner,
Utility, Liking and Self-confidence. Participants
responded to each item by a five point Likert scale
between 1 (strongly agree) to 5 (strongly disagree).
The responses were further converted so that thelager numbers represent more positive perceptions,and summed to obtain the score for each of eight
dimension subscales.
Participants’ personality was assessed using the
Big Five Personality Dimensions10), a 44-item scalefor 5 dimensions of personality: Extraversion,
Agreeableness, Conscientiousness, Neuroticism andOpenness. Participants responded to each item by afive point Likert scale between 1 (strongly agree) to
5 (strongly disagree). The responses weresummarized to obtain scores for each of fivepersonality scales.
3. Results

3.1 Social/Cultural Factors

Table 1 and 2 summarizes the ratio ofparticipants who responded that any of elevensocial/cultural factors were either helpful or
obstructing in Tokyo and Shanghai.
In Tokyo, paticipants consider personal attitude
and personality, such as personal willingness andopen-mindedness , as main factors helpful or
obstructing their usage of CMC. And in social
facotrs, education economic and infrastructure is
the main factors.
In Shanghai, there are similar results were
found. But people there respond the government

Table 1 The ratio of participants in Tokyo who
repsonded as social/ cultual facorts would havepositive or negative infulence on people use of
CMC
Obstruct(negative)%Help(positive)
%

Law

17.4

24.0

Government

12.5

20.9

Education

43.2

50.2

Economy

31.4

33.1

Infrastructure

32.1

42.5

Family Support

16.0

21.3

Social Support

24.4

36.6

People’s

66.9

68.3

Stress

13.9

11.8

Open-

48.4

51.9

30.7

40.1

Factors

willingness

mindedness
Netiquette

Table 2. The ratio of participants in Shanghai who
repsonded as social/ cultual facorts would havepositive or negative infulence on people use of
CMC
Factors

Obstruct(negative)%Help(positive)%

Law
Government
Education
EconomyInfrastructure
Family Support
Social Support
People’s
willingness
StressOpenmindedness
Netiquette

27.3
19.0
39.9
25.3
21.8
20.4
28.7
27.0

21.8
15.2
44.8
30.5
21.0
12.1
17.5
22.1

9.5
18.7

14.9
6.3

17.2

16.7

3.2 Personality, Computer Atitude and CMC
perception
Table 3, 4 and 5 summerized the comparision
scores of five personality scales, ATCQ and CMC
perceptionsacels
betweenTokyonessandShanhainess.

278

In personality, there are significantly difference
between them in every sacel except the extraversion.
Only in the openness scale, Tokyoness showed
more positive than shanghainess.this was in linewith the economic background of tow cities. As
this scale is relationship with interst in travle, manydifferent hobbies, knowledge of foreign cuisine andso on11).

Extraversion
Agreeable
Conscientiousness
Neuroticism
OpennessTokyo(n=269)25.56(4.37)
29.98(3.78)**
30.13(4.34)**
23.59(4.26)**
34.31(5.08)**

LikingUtility

Shanghai(n=882)26.03(3.23)
30.99(2.38)
31.77(3.06)
21.39(3.39)
33.21(4.02)

Contribution
Participation
MannerAddiction
Self-Confidence

Table 4. Means and standard deviations (inparentheses) of the ATCQ scale scores. Asterisks
indicate significance levels of t-tests between user(U) and non-user (NU) groups.
Shanghai(n=282)(n=859)

Comfort16.10 (3.58)**

17.30 (3.27)

Efficacy

16.65 (3.48)**

18.52 (2.91)

Gender Quality

15.04 (2.02)**15.94 (2.76)

Control

16.54 (2.98)**

19.26 (2.56)

Dehumanization

15.50 (3.55)**

13.83 (2.75)

Interest

18.08 (3.16)**

19.24 (2.60)

Utility*p <.05. ** p <.01

18.46 (3.85)**

15.75 (2.84)

Shanghai(n=792)16.48(2.45)
17.50(2.83)
15.77(2.52)
16.38(2.54)
17.59(2.65)
14.36(2.59)
15.40(2.56)
16.07(2.38)

4. Disscusion
Both people in Tokyo and people in Shanghai
considered that economic and educationis very
important factors counrage them to use the newtachnology which will enhance and improve theirlater life quality. This surprising result was notcoincide with recently researches but coincide withstudies 10 years ago. As in most studies, theparticipants were younger adults. The older adults
are less incomes compared with the younger adults
and have to pay more for their medicine fees.
The education consider as the main factor may becaused by CMC technologies were developed inlast 30 years, to young adults, it is just used with
their growing up. While for elderly, they consider
learning these technologies need knowledge in
specialist level.
The difference opnions in the government role
during the elderly usge of CMC betweeen people
in Tokyo and Shanghai can be understand the tow
countries institional differences. China in last 60
years is a socialist state. People get used to realy on
the government since they were born. While inJapan, people depend on themselves.
As people’s personality, perception andattitude is shift by the society and cultal factors.
Some scale such as openness in BFI, ulitity in
ATCQ is related with eonomic factors direcltly. For
those who lacks the common ground andtechnologies readiness of some new technologies,

In computer attitude, there are significanlydiference between two groups in every sacel. In
utility and dehumanization scales, the Tokyonessshowed more positive attitude than Shanhainess.
While, in other sacles, Shanhainess showed more
postive attitude than Tokyoness. This was in linewith the results of BFI.

Tokyo

Tokyo
(n=277)
11.71(2.72)**
14.99(3.15)**
15.07(2.42)**
14.97(2.70)**
14.48(2.59)**
12.62(3.13)**
15.86(2.32)**
13.49(3.12)***p <.05. ** p <.01

*p <.05. ** p <.01.

ATCQ

CMC
Anxiety

Table 3. Means and standard deviations (inparentheses) of the Big Five Personality
Dimensions scale scores. Asterisks indicate
significance levels of t-tests between user (U) andnon-user (NU) groups.
BFI

CMC than Shanghainess. Intersting . tokyonessshowed less addictive than non-users did.
Table 5. Means and standard deviations (inparentheses) of the CMC Perception scale scores.
Asterisks indicate significance levels of t-tests
between user (U) and non-user (NU) groups

In CMC perception , there is a general tendancy
that Tokyoness had more negative perception of279

such as CMC, it is difficult for them to be ready touse those technogolgies9).

direct computer experience on older adults’attitude toward computers. Journal ofGerontology: Psychological Sciences, 53B(5),329-340.
[7] Morrell, R. W., Park, D. C., Mayhorn, C. B. and
Kelly, C. (2000). Effects
of ages andinstructions on teaching older adults to use
ELDERCOMM, an Electronic Bulletin Board
System. Educational Gerontology, 26, 221-235.
[8] Chignell M, Park H, Ruppenthal L, Leung M.
CPI: A communication preferences inventory foruse in design and marketing of information
technologies. Toronto, Ontario: University ofToronto, Interactive Media Lab. Tech. Rep. No.
IML-2002-01[9] Olson GM, Olson JS. Distance matters. HumanComputer Interaction, 2000, 15, 139-178[10] John, O. P., Donahue, E. M., and Kentle, R. L.
(1991). The “Big Five” inventory—version 4aand 54. Berkeley: University of California,
Institute of Personality and Social Research[11] John OP, Srivastava S. The Big Five Trait
Taxonomy: history, measurement and theoreticalperspective. In: Pervin LA, John OP editors.
Handbook of Personality. New York 1999:102138

5. Conclusion
It is believed that elderly late late life quality will
be improved with the information technologies
uages1,3,4). The aging society problem can be solved
with IT developing. CMC technologies utilizations
also help to sovle the distance matters9). This
studies find out that social and cultural factors
helpful and obistructing people in different
countries using the CMC technologies such as
economic ,education, social support. The personal
willingness and openmind is influenced by scoial
factors and is very important persoanl factor predict
people usgage of CMC. In order to promote thepeople in delveloping countryies’s CMC and othernew technology usage, it might be necessary to
make opportunities to improve their instersting in
the usage and prove more society surpport. An topromote people in developing countries, it might tohave the government invest more in theinfrastructure and pefect the welfare policy to bulid
a soundness commonground for the technologies
populariztion.
Today, technologies are developing in a amazaing
speed for us to catch up. Technologies is made forpeole live a well life and should be enhance our life
quality. The study on the uage and popularizationof new technologies will help us well-uderstand the
key factors inside. Such as in this study, the elderly
usage of CMC, it is found that social, cultural andpersonal facors have reationship among themselves.
References[1] Czaja, S. J. (1997). Using technologies to aid
the performance of home task. In Fisk, A.D.,
Rogers, W.A. (Ed.). Handbook of human factors
and the older adults (pp.311-334). San Diego:
Academic Press.
[2] National Bureau of Statistics of China (2003).
2000 population census of China. 2003 China
Statistical Year Book, chapter 4: population:
Basic statiscal on national population census in
1953, 1964, 1982, 1990 and 2000.
[3] McConatha D. Aging online: Toward a theoryof e-quality. In: Morrel R.W. editor. Olderadults, health information, and the World Wide
Web. New Jersey 2002: 21-42[4] Melenhorst AS, Bouwhuis DG. When do older
adults consider the internet? An exploratory
study of benefit perception. Gerontology 2004,
3(2): 89-101[5] Umemuro, H., and Shirokane, Y. (2003).
Elderly Japanese computer users: Assessingchanges in usage, attitude, and skill transfer overa one-year period. Universal Access in the
Information Society, 2(4), 305-314.
[6] Jay, G. M. and Wills, S. L. (1992). Influence of280Comparison of Institutional Factors Influencing Computer-MediatedCommunication Technology Using in Tokyo and Shanghai Older People
CHEN Kang**Tokyo Institute of Technology
2-12-1 Ookayama, Meguro-ku, Tokyo, 152-8550, JAPANchenkang@ml.me@me.titech.ac.jp
While the study about the relationship between institutional factors and usage of thecomputers and network among elderly have been done. This research is to investigate tocompare the area difference. A survey study with 273 Tokyo participants and 563 Shanghai
ones was conducted, where both societies are facing ageing problem and the citizens havethe basic economic and educational background to own the computer and ability to use PC
and Computer-Mediated Communication.
1 Introduction

2 Methods
2.1 Participants
273 older adults in Tokyo (M=68.0, SD=4.3)
and 563 older adults in Shanghai (M=65.9,
SD=5.2) joined in this survey. Both genderratios (female to male) are nearly one in twocities.

The personal computer and internet
technologies (IT) is increasing becoming apart of life for more and more people. It not
only is using by teenagers or young adults,
but also used by the older adults. Even there
are some researches have reported how theolder adults use these technologies and what
be the main effected factors influence them,such as the attitudes1, axiety2, andpsychological factors3 and so on. Thesefindings mainly have been done in industry
countries, there are little studies have been
done in the developing countries or compared
the cross cultural differences among thecountries.

2.2 Procedure
The investigation was conducted in Tokyo
during winter 2005 and conducted in
Shanghai during summer 2004. The
participants first had the purpose and outlineof the research explained. They were thenasked to complete the survey questionnaire,
which were in five parts (the demographic
data and health condition part, the computer
background and attitude part, the CMC
perception part, the personality part and theinstitutional part).

China, a developing country, now has toface the aging society problems as thedeveloped countries, such as Japan. It isestimated that the aging population ration inchina will be over 12% in 20104, while theration of Tokyo will be 19.5%5. These areas
have to face a series of the very serious
problems such as the human resources
shortage, the welfare burden and so on. Even
it is known that high technologies such as IT
can support us, the confused part is if we canapply them with same qualities and efficacy
in different area.
The purpose of this research is to investigate
the differences between Tokyo and Shanghaiin the institutional factors which aresupposed to influences older adults to adopt
using the PC and Computer-MediatedCommunication technologies (CMC).

2.3 Measurements
Participants’ computer
attitudewasinvestigated by the Attitude Toward
Computer Questionnaire (ATCQ) 6), a
35-item multidimensional scale for assessing
seven dimensions of attitude toward
computers: Comfort, Efficacy, Gender
Equality, Control, Dehumanization, Interest,
and Utility. Participants responded to each
item by a five point Likert scale between 1(strongly agree) to 5 (strongly disagree). The
responses were further converted so thelarger numbers represented more positive
attitudes. The respond scores were thensummed to obtain scores for each sevensubscales.
Participants’ CMC perception was assessedusing a questionnaire, a 40-item scale forassessing 8 dimensions of perception toward
281

BBS: Anxious, Liking, Utility, Contribution,
Participation, Manner, Addiction and
Self-Confidence. Participants responded toeach item by a five point Likert scale
between 1 (strongly agree) to 5 (strongly
disagree). The lager numbers represent morepositive attitudes by converted responses.
And the numbers were summed to obtainscores for each subscale.
Participants’ personality was assessed using
the Big Five Personality Dimensions 7), a
44-item scale for 5 dimensions of
personality: Extraversion, Agreeableness,
Conscientiousness,
Neuroticism
andOpenness. Participants responded to each
item by a five point Likert scale between 1(strongly agree) to 5 (strongly disagree). The
lager numbers represent more positive
attitudes by converted responses. And thenumbers were summed to obtain scores foreach subscale.

Table 2. Means and standard deviations (inparentheses) of Attitude Toward Computer
Questionnaire subscale scores.
SubscaleTokyo
ShanghaiD
Comfort
16.10
17.30
**
Efficacy
16.65
18.52
**
Gender Equality
15.04
15.94
**
Control
16.54
19.26
**
Dehumanization
15.50
13.83
**
Interest
18.08
19.24
**
Utility
18.48
15.75
**
*p <.05. ** p <.01

3.3 CMC Perception
CMC questionnaire scores compared by
Tokyo participants and Shanghai ones. Tokyo
ones only showed higher self control ability
than the Shanghai ones(t =2.42, p<.01,
BBS (t (df=298.6) =7.31, p<.01) in addiction
scale.
3.4 Social/Cultural Factors
According to the ratio of participants who
responded that any of eleven social/cultural
factors were either helpful or obstructing thepeople’s use of CMC, both cities participants,
the largest number of people responded that
education (nearly half of the participants inboth cities) and economy level (nearly 40%
participants in each) was important factor,
which might help or obstruct people’s
participation in CMC. Other factors withwhich larger number of participants
responded as helpful for Tokyo participants
were: openness (66%) and People’s
willingness to challenge new things (53%)
was also considered, but for Shanghai ones
were infrastructure (33%).

3. Results
3.1 Personality
Scores of five personality scales werecompared between the Tokyo participants
and the Shanghai participants. Table 1
summarizes the results of the comparisons.
Except the extraversion scale, the participantsin two cities showed quite different in otherscales. Tokyo participants showed morepositive in openness scale, but more negativein other three ones.
Table 1. Means and standard deviations (inparentheses) of the Big Five Personality
Dimensions scale scores.
BFI
Tokyo
ShanghaiD
Extraversion
25.56
26.03
Agreeableness
29.98
30.99
**
Conscientiousness
30.13
31.77
**
Neuroticism
23.59
21.39
**
Openness
34.31
33.21
**
*p <.05. ** p <.01.

4 Discussion and Conclusion:. The purpose of this study was toinvestigate the social, cultural, andpsychological factors that might influenceelderly people’s use of CMC in different area.
The result showed that some of personality
scales, computer attitudes, CMC perception
were related to the usage of CMC and other
Internet technologies/media in different area.
Also social/cultural factors which people
considered either helpful or obstructing wereidentified.
Among personality scales, all were foundto significantly difference between two cities’
people except the extraversion as we have

3.2 ATCQ
ATCQ subscale scores of all participants
were compared between Tokyo citizens andShanghai citizens. Table 2 summarizes theresults of the comparisons. Tokyo
participants only got specifically higherscores in Dehumanization and Utility scales
than Shanghai ones.

282

hypothesized The reason for this result is
considered that both cities’ family structure
have changed to the simple structure (lessthan 3 persons) and the citizens have busy
and a speedy life which limit theircommunication time.
Two of computer attitude subscales,
Dehumanization and Utility, were found thatTokyo people showed more positive attitude
than Shanghai ones. This result is thanks to
Toyo has been adopted the high technologies
in the citizens’ life these years. For example,
c-mail (the e-mail send by mobile) has beenused by nearly everyone, younger and elderly,
here and there. Tokyo people have been
enjoyed in the convenience that hightechnology brought to their life and not soworry about the negative effect as Shanghai
ones. .
In addition to the social factors, bothcities’ elderly consider education andeconomy are help for people participating. In
order to promote older people’s use of CMC,
the economy level and education backgroundshould be the important factors in very area.
Finally, the results of this study might dependon the social/cultural characteristics of the
Shanghai region. In order to generalize theimplications from this study, comparative
studies with gender, age differences should
be done. Also, newer technologies and newform of communities, such as weblog andubiquitous network access, are emerging. The
participation of elderly people, and factors

283

that may influence their participation should
also be investigated in the future study.
Reference[1] Czaja, S.J. (1997). Using technologies to
aid the performace of home task. In Fisk A.D.,
Rogers W.A. (Ed.). Handbook of humanfactors and the older adults. San Diego
Academic Press;1997. p.311-34.
[2] Umemuro H. Computer attitudes,
cognitive abilities, and technology usage
among
older
Japanese
adults.
Gerontechnology 2004. 3(2): 64-76.
[3] Chen Y, Persson A. Internet use among
young and alder adults: Relation topsychologicalwellbeing.
Educational
Gerontology, 2002, 28, 731-744.
[4] National bureau of statistics of china,
2000 population census of china,2003 china
statistical year book, chapter 4: population;
basic statiscal on national population census,
in 1953, 1964, 1982, 1990 and 2000.
[5] Cabinet Office. The aging society reportof 2005.
[6] Jay, G.M. & Wills, S.L. (1992). Influenceof direct computer experience on older
adults’ attitude toward computers. Journal ofGerontology:
Psychological
Sciences,
53B(5):329-40.
[7] John, O.P., Donahue, E.M., & Kentle, R.L.
(1991). The “Big Five” inventory—version
4a and 54. Berkeley: University of California,
Institute of Personality and Social Research.

Unobtrusive Estimation of Psychological States Based on Human Movement Observation
Javier P. Eguez Guevara** Department of Industrial Engineering and Management, Tokyo Institute of Technology
eguezguevara.j.aa@m.titech.ac.jp

1. Introduction

Overall results revealed that fear state received no marks from any of

Emotions are integral to human life and as such, the recognition

the subjects. Anger, sadness, and surprise states marks do not reach theand classification of emotions becomes an important venue to

5% of the emotion distribution along the three subjects. It was found a

understand emotions dynamics and complexity. Within Institutional

greatly unbalanced mark distribution along the studied emotions.

Societies, effective emotion recognition may enable effective, realworld, interaction strategies, which could lead to new group interaction
and performance evaluation possibilities. The purpose of this study was
to investigate the possibility of estimating users’ emotion and otherpsychological states based only on body movements. No video or audio
monitoring mechanisms were used protecting users’ privacy. Besides,
in order to minimize intrusiveness to users, no devices were attached tousers. Methods to estimate users’ emotion and other psychologicalstates based on information retrieved from movement and infrared
sensors were proposed and validated.

2. Procedure
Two sources were reviewed in order to set up the basis for the

Fig. 2 Emotion Paper Responses

hypotheses to be tested in this study. The first source was the results ofa pilot study which aimed to derive predictions to estimate human

Results of hypotheses accuracy for subject A revealed thatemotions based on observable gross movements. This previous study

velocity and motion load were good psychological states descriptors forrevealed speed, physical activity, walking directness and arm usage tosubject A. Results of hypotheses hit rates for subject B showed thatbe emotion movement predictors. The second source was the Emotion

velocity and motion load were again effective emotion estimating

Diagram which is a summary of the literature review concerning humandescriptors for subject B. Subject C differed from subject A and B, inemotion recognition by gross movements.

that his emotion mark distribution is the most unbalanced one with 0%marks distribution for anger, fear, sad and surprise states; no more than
10% of the total emotion marks for disgust (4%), happy (8%), andthinking (5%) states. Neutral state with more than 80% of subjective
response invalided every hypothesis which did not relate neutral state.

Fig. 3 Emotion Recognition Accuracy

4. Conclusion
Results in the validation experiment showed that psychologicalstates could be estimated by predictors such as walking speed, motion

Fig. 1 Emotion Diagram.

load and walking directness, after being analyzed for individual subject

Three subjects performed daily routines in the presence of thisusers. Within the institutional point of view, in order to acknowledge

experiment’s motion-sensor-based recognition system called “Just Feelthe entrepreneurial organization and its structure, it is also necessary to

It!”. It recorded the subjects’ body movements converting body motion

understand the condition of its human capital. Comprehensive human

into six basic emotion labels proposed by the sources aforementioned.

state appreciation assures a better fit for the evolutionary fusion of

The subjects wrote their emotions once every thirty minutes during
three weeks, choosing from a list of psychological states: anger, disgust,fear, happy, sad, surprise, neutral, tired, energetic and thinking. After

operating techniques within a home setting, the workplace, a workgroup, a working process, or the mind itself. Therefore, studying humanbehavior within institutions gives evidence of the dynamic evolution

collecting the subjects’ written responses, these were compared with

between innovation and institution itself. This study showed how

the emotion recognition system output.

technological innovation may serve to supply the identification of gaps

3. Results

within organizations to achieve better performance levels and working

Paper responses described the emotion responses for each subject.

atmosphere.

284

Unobtrusive Estimation of Psychological States Based on Human Movement
Observation
Javier P. Eguez Guevara**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-67 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANeguezguevara.j.aa@m.titech.ac.jp
The purpose of this study was to investigate the possibility of estimating six types ofusers’ emotions and three other psychological states based on external emotional signals
such as human body movements. In order to protect user’s privacy, no video or voicerecordings were used. Also, no devices were attached to the users. Instead, sensors were
utilized to estimate psychological states in real-life settings.
1. Introduction
Emotions are integral to human life and as such,the recognition and classification of emotions
becomes an important venue to understandemotions dynamics and complexity. Additionally,
emotions play a critical role in contemporary
technical societies which are equipped withnumerous systems that serve human beings invarious ways (Scott, Clifford, 2003). Many of thesesystems - such as cooking assistance devices,presence tellers, or real-time emotion-assessing
personal computers -are filling offices, lounges,
cars and other environments. In doing so, assistancesystems
demonstratevariousinteraction
possibilities. These systems and environments thatprovide services to its occupants has been called
smart environments. These environments must beable to detect settings’ emotional state (with regards
to the peoples present) or context (with regards tothe environment itself) (Dey, et al., 1999). Social
interfaces have been identified as requiring theability to recognize and respond to users’ emotions(Picard, 1997). This process of recognizing andresponding to emotion might enable effective, realworld, interpersonal interaction strategies. Within
Institutional
Societies,
effective
emotionrecognition may enable effective, real world,interaction strategies, which could lead to newgroup interaction and performance evaluation
possibilities (Business Microscope n.d.).
The purpose of this study was to investigate thepossibility of estimating users’ emotion and otherpsychological states based only on body
movements. No video or audio monitoringmechanisms were used protecting users’ privacy.
Besides, in order to minimize intrusiveness to users,
no devices were attached to users. Methods toestimate users’ emotion and other psychologicalstates based on information retrieved frommovement and infrared sensors were proposed andvalidated.

2. Related Work: Emotion Recognition
Previous studies on emotion recognition haveused techniques that include the analysis of brain
responses using electroencephalogram recordings
EEG (Frijda, 1986), physiological responses by
galvanic skin response, heart rate and temperature(Lisetti, Nasof, 2004), and body movements bymarkers attached to the body landscape (De Silva,
et al., 2006; Atkinson, et al., 2004). However it has
been discussed that generally the use of devices inlaboratory settings can be cause stress anddistraction in subjects; it has also been said thateven the most modern EEG devices are still clumsy,
obstructive and impractical for their use (Scott,
Clifford, 2003), limiting the normal activities of thesubjects being tested. Emotion inducing studies
have relied on music (Wagner, et al., 2005),
pictures (Hillman, et al, 2004), movies (Lisetti,Nasoz, 2004), or autobiographical memories (Scott,
Clifford, 2003). It has been argued that thementioned inducing mechanisms are the main
reason for poor results in emotion related studies
because they induce weak emotions that lack incontext, and may comprise ethical issues (Peter,
Herbon, 2006). Most of these studies use behavior
monitoring mechanisms utilizing visual and audio
cues (Sebe, et al, 2006), text, audio and video (DeSilva, et al, 2006), as well as speech, image,physiological signal and gesture (Park, Sim, 2006).
The use of these monitoring systems generally
conduces to input-specific issues named display
rules, deception, and systematic ambiguity. Display
rules refer to the fact that when subjects are being
video or audio tracked they tend to hide whenembarrassing situations arise. Also it has been
observed that subjects overact to fit in groups(Note: this is an example of the display rules).
Finally, the systematic ambiguity states that whenstudying behavior movements, similar movement
features correspond to different emotions. Thispotential mismatching of behavior movements to285

emotions may be conducing to undesired results(Fragopanagos, Taylor, 2005).
3. Earlier Work
Two sources were reviewed in order to set up
the basis for the hypotheses to be tested in thisstudy. The first source was the results of a pilot
study reviewed in the following subsection. The
second source considered was the Emotion Diagram
formulated in light of the related literature. The
Emotion Diagram is described in subsection 3.2
The Emotion Diagram.
3.1 Pilot Study
This pilot study aimed to derive hypotheses toestimate human emotions based on observable grossmovements. The everyday motions in real-life
settings of an individual subject and a group of
subjects were observed by means of video
recording, excluding all audio inputs. The subjects
were asked to report their emotions once every 30
minutes based on a list of six basic emotional states
namely, anger, disgust, fear, happy, sad andsurprise states, as well as neutral state. The grossmovements of participants recorded in video werecompared with their subjective emotion reports tofind possible relationships. With these results,
candidates for the association rules between
motions and emotions were discussed in an
exploratory way. It was observed that the groupsubjects portrayed display rule issues. While
everyone had to share the same space, anger,
disgust or sad state displays were scarcely shown.
Therefore it was found that fear, surprise and anger
states in the group subjects were the least marked.
However, these emotions were also scarcely
displayed by the single subject. Individual
differences between subjects were also noticed, asdifferent subjects expressed their psychologicalstate in different ways by portraying energetic,
tiredness or “thinking” states. Furthermore, velocity,
directness, trunk orientation, arms movements,
motion load, and individual characteristic gestures
were found to describe positive and negative
valence emotions (e.g. happy as opposed to disgust).
3.2 The Emotion Diagram
The Emotion Diagram was a summary of theliterature review concerning human emotion
recognition by gross movements. The diagram was
set up in a similar fashion as Peter and Herbon’s(Peter, Herbon, 2006) diagram to describe mixed
emotions. The diagram illustrated the six primaryemotions (anger, fear, disgust, sad, surprise andhappiness). It described the characteristic
movement feature for each emotion over a onedimensional space (valence) (Montepare, et al,1999).
3.3 Informed Hypotheses from Earlier Work

The hypotheses proposed for this study
according to their corresponding human286

movement descriptor are divided in thefollowing 4 groups, velocity, motion load,
walking directness and arm movements. The
velocity hypotheses are two. H1: High walking
speed denotes disgust, happy or angry states;and H2: Low walking speed denotes neutral orsad states. High and low walking speed
parameters may differ between experimental
settings and subjects. There are also threemotion load hypotheses, which are H3: Highphysical activities denote happy or angry
states; H3’: High physical activity denotes
energetic state, and H4: Low physical activity
denotes neutral or sad states. Motion load
levels will be characterized by each subject
according to their own physical activity in agiven period. The third group, walking
directness, has three hypotheses, H5: Indirect
movements denote disgust or neutral states;
H5’: Indirect movements denote reflection, andH6: Direct movements denote neutral or anger
states. Indirect movements refer to walking
trajectories with many intermediate stops. On
the other hand, direct movements are describedby walking trajectories without intermediatestops. The final group is arm movement, withthree 3 hypotheses, namely, H7: Active upper
limb stretching conveys happiness; H7’: Active
upper limb stretching conveys tiredness, and
H8: Passive upper limb usage expresses neutralor sad states. Arm movements descriptor refers
to the frequency in which a subject lifts his or
her upper limbs above his or her head level.
This descriptor was also considered as acharacteristic intrinsic to the subject.
4. ProcedureThree single male Japanese aged 43 (subject A),
25 (subject B), and 24 (subject C) years old, and insound health conditions, were selected as theparticipants for the validation experiment. Each ofthem pursue daily academic work in three different
rooms. Room for subject A was middle sized, withfree walking possibilities, while rooms for subjects
B and C were smaller and much more scattered innature. In addition, rooms for subjects B and C
were not suitable for arm movements’ hypotheses
testing. Due to this reason, subject A participated totest hypotheses H1 through H8, whereas subjects B
and C only participated on the testing of
hypothesisH1 through H6.One computer withdigital web camera, which served as the apparatusof the study, was set up in each of the subjects’room. The web camera used was the Logitech
QuickCam for Notebooks Pro and its corresponding
QuickCam Software version 10.0. Additionally, a
set of 6 motion sensors and 2 IR sensors were used.
These sensors were adapted to a board, thePhidgetsInterface 8/8/8 (Phidgets n.d.), and anemotion recognition system called Just Feel It!
designed for this purpose.
In a first stage subjects were video recorded togather the information about the places they moved
along their rooms and to calculate threshold times
concerning the emotion recognition system. The
period in which the validation experiment was
realized was of 12 days for subject A for 87
analyzed hours, 27 days for subject B for 81
analyzed hours, and 15 days for subject C for 78
analyzed hours. The Emotion Recognition System
Just Feel It! was loaded at the place where thesensors and the System was mounted, and was not
stopped unless the subject needed. Meanwhile the
Recognition System was running, it was asked tothe subjects to act freely in their room in order to let
the Recognition System capture the subjects’ body
movements. Additionally, it was asked to thesubjects to write over the provided paper responsematerial their emotion once every thirty minutes
marking from a list of psychological states anger,
disgust, fear, happy, sad, surprise, neutral, tired,energetic and thinking. After collecting the
subject‘s emotion marked material, the emotion
recognition system output was compared with themarks to find out the hit rate HR which will bedefined in the next subsection.
4.1 Estimation Heuristic
Hit rate is defined as the quotient resulting fromthe division of the number of hits over the total
number of responses for each hypothesis, for the
total analysis time in one day, or for the total
analysis time for all the validation experiment. Hit
rate HR is defined as:

5. Results
5.1 Self-Report: Paper Responses
As previously mentioned, the paper responses
described the emotion for each subject A, B, and C.
Overall results revealed that fear state received nomarks from any of the subjects. Anger, sadness, andsurprise states marks do not reach the 5% of theemotion distribution along the three subjects.
Energetic and happy states were the most answeredby the subject A. Neutral and tired states were themost marked by subject B, while subject C has aprominent mark for neutral state. It was found agreatly unbalanced mark distribution.
5.2 Estimation Results
Results of hypotheses hit rates for subject A
revealed thatH1, H2, H3’, and H5 had more than an
80% of accurateness (80%, 85%, 86%, 86%
respectively) explaining that velocity and motion
load were good psychological states descriptors for
subject A. H5’ and H7’ have low hit rates (26% and36%respectively) showing that emotion estimation
by walking directness and arm movements were noteffective in estimating emotion for subject A.
Results of hypotheses hit rates for subject B
showed that H2and H4 were the most effective
hypotheses with hit rates of91% and 82%
respectively, showing that velocity and motion load
were again effective emotion estimating descriptors
for subject B. However H1, H3’ and H5’ showed
low hit rates (38%, 5%, and 11% respectively).
This could be explained by the fact that subject’s B
room did not presented many possibilities to freely
walk around. Thus, walking directness descriptor
sensors could have been triggered along withmotion load sensor’s misleading the results of thesehypotheses.
Subject C differed from subject A and B, in that
his emotion mark distribution is the most
unbalanced one with 0%marks distribution foranger, fear, sad and surprise states; no more than
10% of the total emotion marks for disgust(4%),
happy (8%), and thinking (5%) states. Neutral statewith more than 80% of subjective response
invalided every hypothesis which did not relate
neutral state.
5.3 Contribution of the Present Study
Emotion recognition systems were proposed toanalyze human emotion in many ways as reviewed
in the previous sections. Nowadays, users benefit
from technology in many ways. The contribution oftechnology is evident especially in enabling users to
do various things any where and in the ways theywant things to be done. However, the ways inwhich smart systems may serve users without
intrusive tendencies have not yet been studied. The
present study focused on how systems may
recognize human behavior without monitoring
techniques. The shift from explicit means of humannumber of hits (i, j)
HR(i, j)=total responses (i, j)

where HR (i, j) represented the hit rate for
hypothesis i in day j, i was the hypotheses (i=1,2, 3, 3’,..., 8), j was the day (j=1,2,3,..., n), hit
was considered to be a response from thesystem which had at least one mark of the same
emotion category from the subject within therange of 30 minutes before and 30 minutes
after the time the response was reported, andtotal responses (i, j) being the total number of
responses from the system for hypothesis i in
day j. A hit was considered to be a response
within a given range since the autonomic
nervous system, after an emotion-eliciting
stimuli has come and gone, takes a time toreturn to its deactivated state (Brave, Nass,
2003). This time has not been clearly definedby the literature. Thus, this range has been set
to 30 minutes after and 30 minutes before a
mark.
287

input to more implicit forms of input enables morenatural interactions with the physical environments,
which provide sufficient input and information
without burdening users. Hence, this study proposes
methodologies to estimate human emotion based
only on external signal like body movements withneither the use of physically demanding devices
attached to the body, nor psychologicallydemanding video or voice recording.

[4]

[5]

[6]

6. Conclusion
This study investigated the possibility of
estimating user’s emotions based on human body
movements. The importance of this study lies inthat emotions are a fundamental component forhuman’s life in today’s technical societies.
Identifying emotions play an important role in thiscontext because it allows interpreting the users’
affect to calculate the degree to which a user’s goals
are being met. The present study’s core contribution
was to estimate human emotion without monitoring
techniques. The results in the validation experimentshowed that psychological states could be estimatedby predictors such as walking speed, motion load
and walking directness, after being analyzed forindividual subject users.
Within the institutional point of view, in orderto acknowledge the entrepreneurial organizationand its structure, it is also necessary to understandthe condition of its human capital. Comprehensive
human state appreciation assures a better fit for theevolutionary fusion of operating techniques withina home setting, the workplace, a work group, aworking process, or the mind itself. Therefore,
studying human behavior within institutions gives
evidence of the dynamic evolution between
innovation and institution itself. This study showed
how technological innovation may serve to supply
the identification of gaps within organizations toachieve better performance levels and working
atmosphere.

[7]

[8]
[9]

[10]

[11]

[12]

[13]

References[1]
Atkinson, A. P., et al, 2004. Emotion
perception from dynamic and static body
expressions in point-light and full light
displays. Perception, 33, pp. 717-746.
[2]
Business Microscope (n.d). Research &Development, Hitachi Technology 20082009, Retrieved October 20, 2008, pp. 81.
Available online from:http://www.hitachi.com/ICSFiles/afieldfile/2
008/07/24/r2008_technology_rd.pdf[3]
Brave, S., Nass, C., 2003. Emotion inhuman-computer interaction. In Julie A.
Jacko and Andrew Sears (Eds): The Human
ComputerInteraction
Handbook:
Fundamentals, Evolving Technologies andEmerging Applications. New Jersey:

[14]

[15]
[16]

[17]

288

Lawrence Erlbaum Associates, pp. 81-96.
De Silva, P., et al, 2006. Towards
recognizing
emotionwithaffective
dimensions through body gestures. Face andGesture Recognition, pp. 269-274.
Dey, A., et al., 1999. A context-based
infrastructure for smart environments.
Managing
Interactions
in
Smart
Environments, pp. 114-128.
Elizabeth, C., Melissa, G., 2007. Motion
capture and emotion: Affect detection inwhole body movement. Proceedings of
ACCI, pp. 95-101.
Fragopanagos, N., Taylor, J. G., 2005.
Emotion recognition in human-computerinteraction. Neural Networks, 18(4), pp. 389405.
Frijda, N. H., 1986. The Emotions.
Cambridge: Cambridge University Press.
Hillman, C. H., et al,. 2004. Emotion andmotivated behavior: Postural adjustments toaffective picture viewing. BiologicalPsychology, 66, pp. 51-62.
Lisetti, C. L., Nasoz, F., 2004. Using
Noninvasive
wearablecomputers
torecognize
humanemotionsfromphysiological signals. EURASIP Journal on
Applied Signal Processing, 11, pp. 16721678.
Montepare, J., et al., 1999. The use of body
movements and gestures as cues to emotions
in younger and older adults. Journal of
Nonverbal Behavior, 23, pp. 133-152.
Park, C., Sim, K., 2006. The Interactive
Feature Selection Method Development foran ANN Based Emotion Recognition System.
Knowledge-Based Intelligent Informationand Engineering Systems, 4253, pp. 241-247.
Peter, C., Herbon, A., 2006. Emotion
representation and physiology assignments
in digital systems. Interacting with
Computers, 18, pp. 139-170.
Phidgets Inc. (n.d.). Developer andManufacturer of Phidgets. Retrieved
November 1, 2007. Available online fromhttp://phidgets.com/
Picard, R. W., 1997. Affective Computing.
Cambridge: The MIT Press.
Sebe, N., et al., 2006. Emotion Recognition
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Recognition, 1, pp. 1136-1139.
Wagner, J., et al., 2005. From physiologicalsignals to emotions: Implementing andcomparing selected methods for feature
extraction
andclassification.
IEEE
International Conference Multimedia Expo,
pp. 940-943.

Just Feel it!: a System for the Recognition of Emotion and Other
Psycological States by Unobtrusive Means
Javier P. Eguez Guevara **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANeguezguevara.j.aa@m.titech.ac.jp
This study provides the description of the system of emotional and psychologicalstates Just Feel it!. Such system is designed to minimize impediments in subjects as it does
not use devices or equipments attached to the users. As an alternative, motion andinfrared sensors are proposed to estimate emotional states and other human condition.
The sensory technology used, the system’s interface and its operation mode are described.
1. Introduction
Emotions play a critical role in contemporary
technical societies which are equipped withnumerous systems that serve human beings invarious ways (Brave, Nass, 2003). The process ofrecognizing and responding to emotion might
improve exisiting real-world interaction strategies.
Also within the institutional view, group interaction
and performance evaluation possibilities (Business
Microscope n.d.) and individual differences arebeing assesed for the better understanding of humanbehavior. This study provides the description of an
unobtrusive recognition system of emotional andpsychological statescues (Sebe, et al, 2006), text, audio and video (DeSilva, et al, 2006), as well as speech, image,physiological signal and gesture (Park, Sim, 2006).
The use of these monitoring systems generally
conduces to input-specific issues where subjects
hide from cameras when embarrassing situations
arise. Systematic ambiguity is another inputspecific issue where similar body movement
features correspond to different emotions. Thispotential mismatching of behavior movements toemotions may be conducing to undesired results(Fragopanagos, Taylor, 2005) in the emotion
recognition process.

2. The emotion recognition
Studies on emotion recognition have used brain
responses techniques using electroencephalogram
recordings EEG (Frijda, 1986), physiologicalresponses by galvanic skin response, heart rate andtemperature (Lisetti, Nasof, 2004), and body
movements by markers attached to the bodylandscape (De Silva, et al., 2006). However it has
been discussed that generally the use of devices inlaboratory settings can be cause stress anddistraction in subjects; it has also been said thateven the most modern EEG devices are still clumsy,
obstructive and impractical for their use (Scott,
Clifford, 2003), limiting the normal activities of thesubjects being tested. Emotion inducing studies
have relied on music (Wagner, et al., 2005),
pictures (Hillman, et al, 2004), movies (Lisetti,
Nasof, 2004), or autobiographical memories (Scott,
Clifford, 2003). It has been argued that thementioned inducing mechanisms are the main
reason for poor results in emotion related studies
because they induce weak emotions that lack incontext, and may comprise ethical issues (Peter,
Herbon, 2006). Most of these studies use behavior
monitoring mechanisms utilizing visual and audio

3. System of Unobtrusive Estimation
This study proposes a system of emotional andpsychological states called “Just Feel it!”. The
designed system is proposed for a single room
environment in a real-life context.
3.1 General Design
The system was designed to be installed in asmall-to-midsized room where a single user carriedout daily activities. The system consisted of a set of
sensors to detect the positions and movements of
the user, a computer and an interface board tocontrol the sensors, and a set of computer program
to process the signals from the sensors to estimate
the emotion of the user.
The system was designed to report an estimationof the user emotion at a semi-real time basis. That is,
the system continues to monitor the signals from thesensors, while it does not need to report theestimation responding to the information in a very
short time period. The time margin to report theestimation is about a half to a few hours.
3.2 Sensory Technology
In order to detect the positions and motions of
the user in the room, sensors provided by Phidgets

289

(Phidgets, n.d.) were used. The main reason to haveselected Phidgets sensors was that Phidgets offers awide range of sensors and accessories as well assoftware support for development of the system.
Phidgets handles a robust Application Programming
Interface(API)
supporting
Microsoft.Net
framework which was selected as the development
platform for this system.
The sensors chosen for this system were infrared(IR) reflective sensors and motion sensors. The IRreflective sensor measures reflections of infrared
light and can detect the presence of a highlyreflective object within the range of 10cm, while forless reflective objects this distance could be about
5cm. The motion sensor is an infrared motion
detector sensor which tracks changes in infrared
radiation as it perceives the movement of a person
or an object whose temperature differs from that of
the environment.
In order to interface between those sensors and acomputer system, Phidgets provides several
interfaces. In this study, PhidgetInterfaceKit 8/8/8
board was employed, which includes eight analog
inputs for sensors. Since both the motion sensor andthe IR reflective sensor are analog sensors (i.e.
inputs held by sensors to measure continued
quantities), these were connected to any of the eightanalog inputs.

• A start button called ‘Begin’ by which thesystem starts to store data in thecorresponding database Table Sensor,• The date and time inputs to set thecalculation period,• The parameters for the sample interval,
which is the length in minutes for the period
to be analyzed,• The parameters for the update interval, which
define how often the system will search for
new events triggered by the sensors,• A set of buttons to compute each of the
movement descriptors’ calculations; and,• A ‘Results’ button containing the commandthat fills an Output table of recognized
movements and emotion
3.5 The Operation Mode
After connecting the sensors to the interface
board and plugging this board to one USB port in acomputer running “Just Feel it!”, the system will
run by loading the executable file. After selecting
the required sensors sensitivity level by moving thesensitivity slider, clicking the button “Begin”
instantializes the data collection and storage in its
corresponding database on the table Sensor. Making
an additional click, the storage terminates. If thesystem’s database has already stored data, theResults button may be pressed for immediate results.
The sample time and the update time must be
defined at this point, which are predetermined at 30
minutes and 1 minute for data updating. Next, aclick in the commands for the movement
descriptors retrieves the data required for therecognition method calculation and stores it. Afterat least one of the movement descriptor tables has
been loaded, clicking the Result button retrieves
partial or full emotion recognition results, which
will be displayed as the Recognition Output.

Figure 1: Interface of Just Feel It!

4. Discussion
Along the process of design and elaboration ofthis system, several measuring possibilities wereconsidered. Other sensors where tested besides thetype of sensors used for the construction of thissystem. A main concern of this study was to make avast review and evaluation of the existing andpossible mechanisms to recognize arms movements.
This study considered distance sensors that could be
set in the ceiling and would activate when the arms
were stretched. It was rather complex to make thesensor discriminate only the arms movements andtherefore this option was aborted. In addition, thisstudy considered including touch sensors in objects
around the desk such as the mouse, or force sensors

3.3 Development platform
Visual Basic .Net of Microsoft was selected as
the development platform. As Phidgets is providing
API libraries for this language, this system could
take advantage of the API to reduce the time needed
to manage sensory control.
3.4 The User Interface
As shown in Figure 1, the system’s interface
screen includes:• The controllers for the sensors’ sensitivity,• A set of eight textboxes for the eight analog
sensors output values,290under the keyboard, but these approaches would
inform only about the presence or absence of thesubject in such place. The motion sensor approachin the back of the chair had preliminary good resultsin the testing-stage and therefore was adopted as
one way to measure arms movements.
Another measuring opportunity considered was
the use of background sound information. For
example the sound emitted by the subject’s steps
may be used to predict the way the subject walks, or
it may be also considered as a presence teller in a
multiple user setting without needing to recognize
their voice. This approach needs further testingplanned for future research.

[4]

[5]

[6]
[7]

5. Conclusion
Despite the limitations described, the system
proved capability to recognize human movements
in order to predict human emotion (Eguez, 2009).
Nonetheless, the amount and nature of nonobtrusive sensors for recognizing movement wereinsufficient. Other emotion recognition system
programs have failed to show valid results for thecomplexity of measurement in real-life settingseven with external stimuli. Non-elicited emotions
with unobtrusive measuring mechanisms remain to
be a challenge for further recognition systems.
Technological innovation serves to supply thebetter understanding of institutional dynamism: its
performance, working atmosphere, knowledge
creation, creativity. Within insitutional onthologicallevels, comprehensive emotional and psychologicalstate awareness may assure a good fit for theevolutionary fusion of operating techniques within
the workplace, a work group, a working process, orthe mind itself. Thus, studying human behavior
within institutions is one of the key elements tounderstand the dynamic evolution between
innovation and institutions itself.

[8]

[9]

[10]

[11]

[12]

[13]

References[1]
Brave, S., Nass, C., 2003. Emotion inhuman-computer interaction. In Julie A.
Jacko and Andrew Sears (Eds): The Human
ComputerInteraction
Handbook:
Fundamentals, Evolving Technologies andEmerging Applications. New Jersey:
Lawrence Erlbaum Associates, pp. 81-96.
[2]
Business Microscope (n.d). Research &Development, Hitachi Technology 20082009, Retrieved October 20, 2008, pp. 81.
Available online from:http://www.hitachi.com/ICSFiles/afieldfile/2
008/07/24/r2008_technology_rd.pdf[3]
De Silva, P., et al, 2006. Towards

291

recognizing
emotionwithaffective
dimensions through body gestures. Face andGesture Recognition, pp. 269-274.
Eguez Guevara, J. P. et al, 2009.

Unobtrusive estimation of psychologicalstates based on human movement
observation. IADIS International eSociety Conference, Barcelona, Spain.

Fragopanagos, N., Taylor, J. G., 2005.
Emotion recognition in human-computerinteraction. Neural Networks, 18(4), pp. 389405.
Frijda, N. H., 1986. The Emotions.
Cambridge: Cambridge University Press.
Hillman, C. H., et al,. 2004. Emotion andmotivated behavior: Postural adjustments toaffective picture viewing. BiologicalPsychology, 66, pp. 51-62.
Lisetti, C. L., Nasoz, F., 2004. Using
Noninvasive
wearablecomputers
torecognize
humanemotionsfromphysiological signals. EURASIP Journal on
Applied Signal Processing, 11, pp. 16721678.
Park, C., Sim, K., 2006. The Interactive
Feature Selection Method Development foran ANN Based Emotion Recognition System.
Knowledge-Based Intelligent Informationand Engineering Systems, 4253, pp. 241-247.
Peter, C., Herbon, A., 2006. Emotion
representation and physiology assignments
in digital systems. Interacting with
Computers, 18, pp. 139-170.
Phidgets Inc. (n.d.). Developer andManufacturer of Phidgets. Retrieved
November 1, 2007. Available online fromhttp://phidgets.com/
Sebe, N., et al., 2006. Emotion Recognition
Based on Joint Visual and Audio Cues.
International
ConferenceonPattern
Recognition, 1, pp. 1136-1139.
Wagner, J., et al., 2005. From physiologicalsignals to emotions: Implementing andcomparing selected methods for feature
extraction
andclassification.
IEEE
International Conference Multimedia Expo,
pp. 940-943.

Productive Love:A New Approach for Designing Affective Technology
Ramon Solves Pujol
Tokyo Institute of Technology
solves.r.aa@m.titech.ac.jp
1.Introduction
Thinking about the future, it seems obvious that technology will go
further than nowadays applications. Expertise on design of new
applications of technology could be a key of a new innovative science forthe management of the technology.
A technology designed in a way that connects people and promotes lovemight be successful. In the field of HCI (Human Computer Interface) there
have widely been realized studies about transmission of personal
information, intimacy, connectedness, awareness, and social presence.
However, the understanding of love has not been approached specifically.
Moreover, the studies done in relationship to love are mainly based on
people experiences and opinions. A philosophical approach may represent afurther understanding of the experience of love. The objective of thisresearch is providing an understanding of the nature of love in a mannerthat may be usable for designing love-promoting technology.

The elements from literature summarized in table 1 were analyzed andclassified, resulting in a list of 10 elements of Productive Love, which are
represented in figure 1.

1. Love approach from theoretical review

Fig. 1. Elements of Productive Love

It seems that most people share the tendency to regard love as innate,passive, and basically the same as falling in love. However, Enrich Fromm
differentiated two kinds of love. Immature love and mature love, which is
attributable to the person who has developed productive character ororientation, and we define as Productive Love [1]. The idea of Productive
Love has been approached by several philosophers under different
designations such as agape love by Bernard Murstein [2]. As a validation of
Productive Love-related theories that regard it as a higher form of love,
agape love was positively correlated with relationship satisfaction [3]. Webase the present survey on our extensive review of the works of othertheorists and researchers, which are summarized in table 1.

2. Practical Design Example
A hypothetical system is described. Its objective is to improve the love
between persons that are distant from each other.
The system automatically takes pictures of each of the users and sends
to another selected user. This frees the users from a task that could
represent duty, a burden, and thus, could be abandoned.
The pictures are taken in random intervals, this way the photographedperson appears natural. Realistic information is a good basis to appreciate
the other.
The span of time where the pictures are taken is selected manually by
the user, from very short, in punctual situations such as while having lunch,
to longer, such as while being in a room, etc.
A set of three pictures is send everyday. The receiver is able to findthem very easily in an digital picture frame or a “love device”.
The system includes a touch panel display. The pictures are directly
commented writing on them, and re-send to the original person. Thisencourages the person to take an action related to the other which may
initiate other forms of communication.

3. Conclusion
Loving relationships are part of entrepreneurial and other institutionalorganizations, therefore their improvement could contribute to the dynamic
evolution between innovation and institutions. By providing enjoyment of
doing activities related to the other person, a love-promoting technology
may substitute general forms of entertainment. Spending time considering
the other person is a condition that may lead to improve love. As further
work, the differences of love among cultures, and thus the differences oftechnological needs are factors to be considered by the institutional
management of technology.

4. References

Table 1. Factors related to Productive Love fromtheoretical review.

292[1] Fromm, E. The Art of Loving, 1995 edn. Thorsons, London, 1956.
[2] Le, T.N. A measure of immature love, Individual Differences Research,
3, b, (2005).
[3] Lin, L., and Huddleston-Casas, C.A. Agape love in couple
relationships. Marriage and Family Review, 37 (4), (2005).
29-48. J.

Personal Factors Influence on ICT Engagement
Ramon Solves Pujol*

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-28 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANsolves.r.aa@me.titech.ac.jp
The present research investigates the relationships between new ICT engagement andthe individual psychological factors. A questionnaire-based investigation was conducted.
The collected data was analyzed using Structural Equation Modeling to examine
hypothetical causality model. The results not only corroborated the previous studies’
partial results but also revealed new implications to be used for designing highly
pleasurable ICT, which could contribute to build a successful national strategy.

1. Introduction
Information and communication technologies(ICT) are becoming more important everyday.
Accepting new technologies and utilizing them arehighly emotional events or governed by emotional
factors. In the latter years some studies haveconcerned about engagement modes (EM), which
contribute to a better interaction with technology.
EM have been used for describing generalproperties of the people’s activities in relation to theexternal world (Heidegger, 1927/1962, cited in
Montgomery, et al. 2004). Among them, numerous
researchers have focused on flow concept, which
was initially introduced by Csikszentmihalyi, 1990,
defining it as the state of being fully immersed in an
activity. Similarly, personal factors such as theautonomy, controlled and amotivated orientations(Deci & Ryan, 1985), have been related to EM withtechnology, for instance, by Montgomery et al.,2004 and Sharafi, et al., 2006. Nevertheless there
are other EM and personal factors, which may also
have influence on the technology engagement.
Besides, recent literature shows the importance of
the aesthetics as an emotional factor. Norman, 2003,
introduced a factor for enhancing usability called
the pleasant aesthetic design.
Although some relationships among among thementioned factors have been investigated locally by
individual studies, a big picture of the relationships
or causalities among ICT, Personality traits
engagement, and aesthetics has not been explored.
The purpose of this research was to investigate therelationships between new ICT engagement ,individual psychological factors and aesthetics.
2. Engagement modes
Montgomery et al., 2004 and Sharafi et al.,2006, explained EM with IT as involvement of a
subject (e.g., a person using the computer) who is293

engaged in an activity with an object (e.g., aspecific computer program) in a certain manner (themode). The authors developed a general model
involving three positive EM: enjoying/acceptance,
ambition/curiosity and frustration/anxiety and two
negativeEM:efficiency/productivity
andavoidance/hesitation. The authors found flow tofollow from a positive engagement. Besides, built
on the concept of flow, cognitive absorption (CA) isdefined as a state of deep involvement or a holistic
experience an individual has with an IT and isrelated to intrinsic motivation (Agarwal &Karahanna, 2000).
Additional constructs that seem worth to
explore are: Arousal as the increase of readiness to
respond to internal and external stimuli. Playfulness,
defined as the disposition to find or make causes foramusement. Mental focus, is the degree to which
someone is able to concentrate and become
absorbed in an activity. Elliot and Harackiewicz,
1996 found that focus on the positive brings
enthusiasm and optimism; which should facilitate
interest and absorption in the achievement task. The
way that individuals perceive and respond toachievement situations is explained by Dweck andLegget, 1998, through achievement goals; which
are divided into performance-mastery pattern whichis the attempt to meet personal standards ofaccomplishment, performance-approach which is
the orientation toward earning a favorable judgmentfrom the others, and performance-avoiding patternwhich prompts efforts to escape potential failure
consequences. Lee et al., 2003, found correlation
between enjoyment and performance-approach goal
through mental focus. While correlation between
Enjoyment and performance-avoiding goal, wasalso through mental focus, but negative.

3. Personality traits
Sharafi al., 2006, explained Locus of control(LOC): Locus object or external is the case where
the user perceives he as needed to learn skill tocontrol the object. Locus subject or internal
explains the case when the subject perceives
himself as controlling the object. Locus of causality
examines The source of the motivation: Intrinsic
motivation drives to do things just for the fun while
extrinsic motivation drives to do them in order toattain some separable outcome (Deci & Ryan,
1985). Intrinsic motivation is correlated withinterest, enjoyment and inherent satisfaction, while
extrinsic motivation has an external perceived locus
of casualty. Similarly, the general causality
orientations explain how events and objects
influence people. Sharafi et al., 2006 review
explains autonomy orientation as the orientation
toward intrinsic motivation, challenges andfeedback, intrinsic motivation was related withinternal LOC, ability, effort, achievement positive
EM and high levels of flow. Controlled orientationis the orientation towards being controlled byrewards and deadlines; amotivated orientation was
positively correlated with efficiency/productivity
and flow, but also with avoidance/hesitation.
Finally, the amotivated orientation represents
people who have no sense of being able to affectoutcomes or cope with demands or changes andwas correlated with the negative EM and had
negative relationship with flow experience.
Csikszentmihalyi, 1990, explains “autotelic” asdoing an activity because the doing itself is the
reward. Autotelic individuals experience flow more
frequently and more intensely than others do, havemore positive experiences and more well definedgoals. Amabile et al., 1994, found creativity output
positively associated with intrinsic motivation, andnegatively associated with extrinsic motivation.
Besides, the conceptualization of creativity might
benefit from adding a third dimension, aesthetics
that refers to a beauty or refinement in an outcome
product. (Holt, 1997, cited in Burroughs & Mick,
2004). Aesthetic experience (AE) is defined as thestudy and philosophy of the quality and nature of
sensory responses related to beauty. Stamapolou,
2004, realized a literature review exploring theinfluential factors, including arousal and absorption.
Openness to absorption trait, as explained by
Tellegen, 1974, is the openness to a wide array ofabsorbing and self-involving sensory andimaginative experiences. Arousable persons are
more emotional they experience strong emotion
more easily and for more time. Finally trait
pleasure-displeasure is explained by Mehrabian,
1996, as the person's characteristic prevalence of
positive affective states over negative ones.

4. Method
The participants were 139 undergraduate andgraduate students with technology and sciencebackgrounds of an university located in a city areaof Japan, aged between 18 and 26 years old (mean= 20.35 yr, standard deviation = 1.845. 128 weremales and 11 were females (7.9% females).
Voluntary participants received individually
one questionnaire battery and answered it in theirown pace, receiving a gift card of 500 Yen whenreturning the questionnaire. The questionnaire
battery consisted of three parts: demographic
background, personality traits and new ICT
engagement. For the second and third parts, all theutilized questionnaires were borrowed fromstatistically validated questionnaires, except for theassessment of creative product and arousal, whichwere based on existing scales. Finally, threequestionnaires were constructed from scratch inorder to assess which new ICT devices wererecalled by the participants while answering thequestionnaire, its length and frequency of use.
5. Results
Correlations among 26 scales were assessed.
Since indices for the length and frequency of new
ICT usage were highly correlated to each otherfactor analysis with principal axis factoring with
Promax rotation method and Kaiser normalization
was applied. The rotation converged in three
iterations and identified a three-factor structure
which factors were named: “PC personal use” “PCuse in work” “Cellular phone use”.
.09

.34

Autonomy

AestheticExp.62.20
Op_Absoprpt

Intrinsic-.31 .19

-.30

-.19

.35

.30

.40
PC_personal

.16

.32

.43.53.14.11

ment_foc.72 .22.21

ArousalPlayfulness

PC_work

.05

.37
.13

CreatPers.46

perf_master

.33

.31

.32
.74

+engagement.35

arousability-.22
Cogn_Abs.13.36

Controlled

.45

.49

.32

.10

.32

.45

.17

.41
.09

LOC_O

.22

.73

Flow

.15

-.22

.24

-.33

.18

.22
Pleasure-disp

.23

.29

.16

perf_app.21 .24

.29

.40

.26

Creat_Prod

Extrinsic.15

Cell_Phone_use

.22

-.36
.10

-.36

.16

Amotivatedperf_avoid

.34

.15

-.38

.19

.55

- engagement.52

Fig. 1. Personality traits and new ICT engagement final
model.

The causality relationships among personality
traits and new ICT engagement factors were
exploratory investigated using covariance structure
analysis (CAS, also known as structured equation
modeling, or SEM) method. At first, initial path
diagrams were constructed based on the reflections
on the correlation analysis. The model was refined294

until all the remaining paths had statisticalsignificance higher than 5% (p<0.05). During therefinement process, one element, the autotelic scalevariable demonstrated not to be stable and wasremoved, the reason may be that this variable wasbased on the assessment of two unique question
items, being possible not to be enough toproportionate a valid measurement. The final modeland the estimated weights are shown in Figure 1.
The notes for the model were: χ2 = 1990.571 (df =1100, p <0.001), and the model fit indices were:
GFI = 0.655, AGFI = 0.616, and AIC = 2240.571.

Performance avoidance achievement goal
positively predicted negative engagement andnegatively predicted playfulness.
6.3 Personality – new ICT usage relationship
Positive engagement factors were predicted byintrinsic
andextrinsic
motivation-related
personality traits. The first one was intrinsic
motivation-performance mastery, the second one
wasfromextrinsic
motivation-controlledorientation and both, performance mastery andperformance approach. Being controlled orientationand performance mastery relationship not in linewith the previous studies, as well as for the case ofcontrolled – creative personality, and the further
explained, extrinsic motivation- creative product,
could be explained, as it is in the section 6.1 by thenature of the Japanese sample. Moreover, pleasuredispleasure trait predicted flow and positive EM,
connecting intrinsically motivated personalities
with positive engagement dominating factors,
highlighting intrinsically motivated personalities
dominance in the positive engagement factors
versus intrinsically motivated personalities. The
result suggests that autonomy-oriented individuals
with prevalence of positive affective states engage
in a positive mode easily. Openness to absorption
negatively predicted creative product. Recalling thatCA positively predicted creativity product, thepresent, at first contradictory can be explained by
the nature of openness to absorption which focuseson the proximity between absorption and hypnotic
susceptibility (Tellegen & Atkinson, 1974) versus
CA as a state of deep involvement or a holistic
experience an individual has with IT.
It is through performance avoidance thatamotivated individuals may engage in a negativemode. Besides, extrinsic motivation had positive
prediction to performance avoidance and negative
engagement, highlighting that while intrinsicallymotivated individuals showed to statisticallysignificant experience only positive engagement,
extrinsically motivated ones can experience both,
positive and negative engagement.

6 Discussion
In the following sections the contributions of
the present study are discussed while the results inaccord with previous studies are just mentioned.
6.1 Dominating factors in personality
Intrinsic motivation predicted autonomy
orientation, openness to absorption and negatively
predicted amotivated orientation; In addition,
intrinsic motivation had negative variance withexternal LOC. Autonomy predicted openness toabsorption, AE and pleasure-displeasure.
Extrinsic motivation predicted controlledorientation and arousability appearing to beprobably caused by external events. Stamapolou,
2004, included openness to absorption andarousability; as components of the AE, thecontribution of the present research is throughopenness to absorption that arousability trait
predicts AE. Extrinsic motivation negatively
predicted creative personality. In the other hand, thecontrolled orientation scale, closely associated withextrinsic motivation, positively predicted creative
personality. It may be due to the Japanese sample,
which by being more group oriented is able to havecreative personality in a controlled orientation.
6.2 Dominating factors in new ICT engagement
Performance
mastery
andperformance
approach predicted CA which as well, predicted
positive EM, mental focus, flow, playfulness andcreative product. Besides, positive engagement andflow were predicted as well directly by performance
mastery goal, pointing up its dominance in thepositive engagement factors versus performance
approach goal. In the other side, performance
approach predicted just CA. Mental focus appeared
to be an optional mediating process between CA
and flow, attributable to while the rest of thepositive engagement dominating factors contained
elements of enjoyment on their loading items or
sub-factors, mental focus involves only its own
dimension. Positive engagement predicted arousal
as well as arousal predicted playfulness and creative
product.

6.4 Nature of new ICT usage
Creative product was predicted by cognitive
absorption, arousal and playfulness. This group of
engagements was labeled “qualitative engagement”.
To this group, paths started from intrinsic
motivation and extrinsic motivation, result not inaccordance with the general belief that extrinsic
motivation does not cause or even undermines
creativity. This result can be explained as in section
6.1 by the nature of the Japanese sample. In
addition ICT could work as an extrinsic motivationfor extrinsically motivated individuals, which could
be aimed to produce a creative product.

295

Positive engagement leaded to personal use ofcomputer, being logic that a pc will rather not be
used in the personal life if the computer is not
enjoyed. Playfulness leaded to use it at work,suggesting that the ones who go further than feeling
positively engaged with technology, but tend toplay with it, are more eager to have jobs where they
can use it. Finally, amotivated orientation had
negative correlation with cellular phone use.
Suggesting that amotivation on interpersonal life
could be reflected on the cellular phone poor use.
This second group of engagements was labeled“quantitative engagement”.

inventory: Assessing intrinsic and extrinsic
motivational
orientations.
Journalof
Personality and Social Psychology, 66, 950967.

6.5 The Role of the aesthetic experience
Yet AE had no direct effect to ICT usage, AE
was not linked by any means with Amotivation andany of the negative EM, however openness toabsorption central role on predicting A.E. and its
negative prediction of creative product suggests thataesthetic oriented individuals could find difficulties
to engage with ICT in a qualitative way.
7.Conclusions
The present research not only corroborated theprevious studies’ partial results but also revealed
new implications between personality types and
ICT engagement modes, those are: (1) Positive andnegative engagements were differentiated as well as
its leading causality paths from intrinsic andextrinsic motivation personality traits. (2) The
dominating factors for new ICT use were detected:
cognitive absorption, arousal and flow. And (3)Quantitative and qualitative nature of positive
engagement with new ICT were identified.
Understanding the nature of ICT engagement as
an interdisciplinary study of science and technology
can play an important role in designing specific ICT,
obtaining in a highly pleasurable ICT could be a
key to build a successful national strategy. At first,
three implications derived for ICT design: First,
design should be differently directed to those users
who tend to engage with technologies in a positive
way, it is, intrinsically and extrinsically motivated.
And to those who engage in a negative way, it is,amotivated individuals. Secondly, an ICT thatprovides CA, arousal and flow might be the mostsuccessful to provide ICT engagement. Finally, thethird implication should be that ICT could also beoriented on its construct to satisfy quantitative andqualitative engagement.
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Csikszentmihalyi, M., 1990. Flow: The
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Montgomery, H., Sharafi, P., & Hedman, L. R.
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[10] Norman, D. A., 2003. Emotional Design: Why
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Amabile, T. M., Hill, K. G., Hennessey, B. A.,& Tighe, E. M., 1994. The work preference296

Towards Technologies that Promote Love. Preliminary Literature Review
Solves Pujol Ramon **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-28 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANsolves.r.aa@me.titech.ac.jp
The objective of the present study is to investigate the possibility of using technology
for improving a people’s love. The study reviews and reflects on what has been empiricallyand theoretically suggested about love. Specifically, explores mature love in depth, anddraws special attention four basic elements for mature/productive love proposed by
Fromm, 1956, those are: care, responsibility, respect and knowledge, which stand up as
possible key-elements for designing a technology that aims to promote love.

exclusiveness and absorption, (5) felt affiliative anddependent needs, and (6) the relative unimportanceof universalistic norms in the relationship. Other
speculations about the nature of love were the onesby Weinstein, 2007, who suggested that love seems
to underline terms as: empathy, compassion,
acceptance, joining, reflecting, positive feedback,holding and containing environments, meeting
mutual needs, and corrective emotional experience.
Similarly, Averill, 1985, cited in Dion and Dion
1996, proposed four features of romantic love:
idealization of the romantic partner, suddenness of
onset, physiological arousal, and commitment to thewell-being of the loved person.
With reference to to differences in intimate
relationships, Walster, Walster and Berscheid, 1978,
cited in Hatfield, Utne and Traupmann 1979,
suggeted seven aspects: (1) Intensity of liking(loving), (2) depth and breadth of informationexchange, (3) length of relationship, (4) value ofresources exchanged, (5) variety of resources
exchanged, (6) substitutability of resources, and (7)the unit of analysis: from you and me to we

1. Introduction
The actual paradigm of electronic devices andapplications are extensively oriented to help work,
to make people’s lives easier, and, to provide fun.
However, there are practically no antecedents on
devices that aim to improve love relationships froma realistic point of view. The motivator of thepresent study is to investigate the possibility ofusing technology for improving an elemental
human aspect such as it is the capacity to love.
Fromm, 1956, proposed that love is not apassion like most of the people believe, but that it isan action; therefore it could be learned as an art is.
Fromm differentiated it from falling in love andcalled it Productive love. Moreover Fromm
proposed four basic elements for Productive love:care, responsibility, respect and knowledge, whichappeal to us as a possibility for using them as a keybasis for a technology to promote love. Although
Fromm’s theories are highly encouraging for being
used, we believe that to limit ourselves to thetheories of Fromm would not be the best way toapproach love in an objective way. Therefore, thisstudy aims to review and reflect on what has been
empirically and theoretically suggested about love.
2. Theoretical studies
Concerning with the conceptual alocation oflove, Newcomb, 1960, cited in Rubin 1970, placed
love alongside with varieties of personal attraction
such as: Liking, admiration, and respect.
As for the undersatanding of love nature, Rubin,
1970, complides theories of De Rogemont, 1940,;
Freud, 1955; Fromm, 1956; Goode, 1959; andSlater, 1963. Indicating that the nature of love wasrelated to: (1) Physical attraction, (2) idealization(2) predisposition to help, (3) the desire to shareemotions and experiences, (4) feelings of297

3. Empirical studies
In order to construct the fist empiricalmeasurement tool of love, Rubin, 1970, exploredtheoretical and empirical literature on interpersonal
attraction or liking, which was obtained from
Linzey and Byrne, 1968, and included: (1) thedesire to affiliate with the target in various settings,(2) evaluation of the target on several dimensions,(3) the salience of norms of responsibility andequality, (4) feelings of respect and trust and (5) theperception that the target is similar to oneself.
Rubin’s measurement resulted to identify threemajor components of romantic love: (1) Affiliativeand dependent need. (2) Predisposition to help And(3) Exclusiveness and absorption.
Another well standarized assessment about love
is Lee’s, 1973, love attitudes scale, which according
to Hendrick, Hendrick and Dicke, 1998, has beenused and tested across may years and many studies.
Lee scale assesses six love styles: Eros, ludus(passionate love), storge (friendship), pragma(practical love), mania (Possessive, dependentlove) , and (6) Agape (altruistic love). Shorter
versions of Lee love attitudes scale have beendeveloped by Hendrick, Hendrick, Hendrick &Dicke, 1998, yielding in 18-item and 24-item scales(3-tem and 4-item subscales) witch Hendrick et al.
reported by the authors to have even stronger
psychometric properties than the original scale.
In another attempt to obtain a tool to assess love,
Sternberg, 1997, constructed a triangular love scale,
which measured the intensity levels of threecomponents: (1) Intimacy, which included
closeness, connectedness, and bondedness. (2)Passion, which included romance, physicalattraction, and sexual consummation. And (3)Commitment, which included the decision toremain with another and the shared achievements
and plans made with that other.
4. Believes about love
Love was defined by Cronbach & Meehl, 1955,
cited in Rubin 1970, as: “Attitude held by a person
toward a particular other person, involving
predispositions to think, feel, and behave in certain
ways toward that other person”. Similarly, Fromm,
1956, based his theory about Productive love on thepremise that love is a voluntary action, not apleasant sensation that to experience is matter ofchance. Burston, 2007, explains that this believe,that love always includes an element of volition, isrepresented as well by Kierkegaard, Scheler, andBuber. In the other side, the common understandingthat Erotic love is an involuntary passion, wherelove is "blind" and therefore, the adversary ofreason is represented by Plato, Schopenhauer,
Nietzsche, Freud, and, Lacan.
Similarly it exists also a dichotomy on the
beliefs that love is innate or learned. Singer, 1987,
cited in Le 2005, explains that, for instance, Plato,and Dalai Lama support innate love, while
Psychoanalysts support a learned affectionate
system. In that sense, numerous philosophers,
theorists and spiritual gurus have tried to teach thenature of love with a no more success than reaching
to a few curious persons. We believe that in the eraof ubiquitous technology, where almost all thepeople feel more excited for using the latest
technology than reading the latest books, it exists
the possibility to make use of the technology topromote love. A key element for this purpose seems

Fromm, 1956, distinction between immature love or
symbiotic union and productive love (or maturelove), in the following sections we will discuss
what has been described by Fromm and othertheorists in relation immature love and mature love.
4.1 Immature love
Fromm, 1956, explained that consequently
immature love is focused on acquiring andpossessing the other person, or other’s love. Fromm
criticized as well manifestations of love incontemporary society, which engage the principleof fair exchange. Similarly, Maslow, 1968,1970, in
Le, 2005, suggested Deficiency love (D-love),which reflects lower love in service of needs.
Similarly, Loy, 2002, cited in Le 2005, explainsthat love become a means to ground oneself andfulfill one’s sense of lack, which is rooted on theego need to ground itself through objectification ofself and others. Unless one is able to transcend theself-object duality, any love or attempt of love will
never be completely satisfying or adequate.
Moreover, Singer, 1987, cited in Le 2005, explainsthat Falling in love, being in love and staying inlove are features of egoism where one is not able tosee the other she is. Those features include twocomponents: Appraisal, which stands for assessing
the other’s utility and Bestowal, which refers tocreate own value in the other person.
Le, 2005, explained immature love to be rooted
in self-other distinctions, and that could be selfish
and instrumental. Le developed a measurement oflove in its immature form, which resulted to havesatisfactory validity but fairly low reliability.
4.2 Productive/ Mature love
Fromm, 1956, explains Productive/Mature loveas the union under the condition of preserving one’s
integrity and individuality, and the active striving
for the growth and happiness of the loved person. A
close concept to Fromm’s productive/mature love is
Maslow’s, 1968,1970, cited in Le, 2005, Being
Love (B-love), explained as the appreciation on theothers and the experience of love per se. Maslow’s
B-love is explained in Gelbond, 1979, as the love
for the being, presence or qualities, gifts acts andaspirations of another person. One gives oneself
without necessarily expect any return. Similarly,
Gelbond, 1979, explains that May, 1969, regarded
love as “a delight in the presence of the otherperson and affirmation of his value anddevelopment as much as one’s own”.
Fromm, 1956, describes giving as the foremostof the basic elements of all forms of love, In thesame line, Kierkegaard, 1995, in Shinebourne 2006,
argued that the person who loves "does not seek hisown, because he gives in precisely such a way that
it looks as if the gift were the recipient's property".
Similarly, Murstein, 1990, in Le 2005, describes

298benevolent love / altruistic love / agape love as theintention to help and to give to another person
without shades of self-interest, and including:spontaneity and motivation by selflessness,
impartiality and creativity. Similarly, Sorokin, 1954,
regarded love as the relationship between two
persons in which the aspirations and aims of one areshared and helped in their realization by the other.
Sorokin as well,understood love as having
qualitative forms as empathy, sympathy, kindness,
devotion, admiration, benevolence, reverence,
respect, adoration and friendship.Moreover, Fromm
1956, pointed out that there is no need to care about
the fairness of a relationship, citing Marx, 18441953,: “…you can exchange love only for love…”.
This idea is similar to the one expressed by Levinas,
2001, in Shinebourne 2006, who argued that "therelation is always nonreciprocal; love exists withoutworrying about being loved".
Besides, Fromm, explains as well that mature
love depends on the character development of theperson, as the overcoming of one’s Narcissism isthe condition for mature love. Similarly, Maslow,
1968,1970, in Le 2005, stated that self-actualized
persons are freer on dependency and able to engage
in B-love. As for describing mature love, Gelbond,
1979, explains that Maslow described B-love as thetendency toward more and more complete
spontaneity, the dropping of defenses and roles, andgrowing intimacy, honesty, and self-expression.
Maslow stressed as well the following aspects:
Eagerness for the growth of the other, essential
affirmation and respect for the other’s individuality,
the absence of jealousy, enjoyment (fun,exuberance, gaiety, and the absence of anxiety).
Maslow pointed as well that B-love is a richer,higher and more valuable subjective experience
than D-love, which all B-lovers have also
experienced.
5. The four basic elements for productive love.
Fromm, 1965, proposed four basic elements for
Productive love: care, responsibility, respect andknowledge, In order to understand them better, thissection explores Fromm’s description as well asother studies about those concepts in relation withlove.
5.1 Care
To Fromm, 1956, love is the active concern forlife and the growth of that which we love, theessence of love is to ‘labour’ for something. In thatterms, Ungerson, 2005, explains that Graham, 1983,
and Ungerson, 1983, made a basic distinction for
the use of the word 'care', differentiating between:'Caring about'; defined within feelings terms and'Caring for'; task oriented activity and hence mostclosely defined as 'work'.

5.2 Responsibility
Fromm, 1956, explains responsibility as being
implied by care and concern. Fromm pointed that
Responsibility is usually meant to denote duty,
something imposed from the outside, however,
Fomm, explains it to be a voluntary act, to be able
and ready to ‘respond’ to the needs, expressed or
unexpressed of another human being. Which in thelove between adults it refers mainly to the psychic
needs of the other person.
The importance of responsibility in relationshipwith love was supported by Buber, 1958: 29, citedin Shinebourne, 2006, who conceived love as
responsibility for the other. Similarly, Levinas,
2001cited in Shinebourne, supported that "This
responsibility for the other is the grounding momentof love".
5. 3 Respect
Fromm, 1956, explains that respect is not fear
and awe, differently, in accordance with the root of
the world (respicere, to look at) it is the ability to
see a person unique individuality and concern thatthe other person should grow and unfold as he is.
To Fromm Respect implies absence of exploitation,is possible only if we have achieved independence
and on the basis of freedom.
Besides, Hendrick and Hendrick, 2006,
explained that respect is understood as an emotion
in folklore, but not on people's understanding, forinstance Frei and Shaver, 2002, pointed that respectseems that is an attitude that is directed to a partner
who is: trustworthy, considerate and accepting.
Similarly, respect is defined by Jackson, Esses, andBurris, 2001, in Hendrick et al., as a "Type of
attitude characterized by feelings of esteem foranother that manifest in both highly valuing to theperson's feelings, thoughts, and behaviors and awillingness to be influenced by that person".
Hendrick and Hendrick, 2006, suggest thatstructurally respect can be seen (1) as an attitude(consistent with Jackson et al. 2001, Frei et al. 2002,
and Kvecses 1990) consisting on: affect, cognition,and behavioral tendencies. And (2) as content canbe devided in two primary components: Equality/
mutuality and Caring/ supportiveness. Hendrick etal, found as well, respect to correlate positively
with: eros, storge, agape, satisfaction, commitment,
and self-disclosure (except for older couples,.
Respect as well correlated negatively with: ludus,
permissiveness, and instrumentality.
5.4 Knowledge
Fromm, 1956, explains that among the layers ofknowledge, the one which is an aspect for love is
one which does not stay at the periphery, but
penetrates to the core, it is, to know the otherobjectively, which is possible only when we areable to trancend the concern of ourselves.

299

In a study of Organization of the beliefs of apartner, Showers and Limke, 2006, differentiatedthat beliefs of a partner that are activated in aparticular situation can be organized in from: (1)“compartmentalized knowledge” which is more
efficient and thus easier to maintain, may be used
for a partner with many possitive attributes, andmay be more optimistic, lead to like their partner
better and be more satisfied with the relationship.
To (2) “integrated knowledge”, which being more
effortful, may be used in stressful situations.
6. Conclusions
The princiopal apportation of the present study
is the suggestion that technology could be used to
improve love. This proposition seems to be possible
when considering inmature love versus productive/
mature love, which stands out to be a love approachthat allows for improvement.
In an attept to provide a realiable basis fordesigning for improving human relationships, thepresent study provided wide review of te theories,
emprirical studies and tendencies of thought about
love. Depending on the understanding of thedesigner, the target device, application or inended
activity. a design for love should undertake somethe previous conditions in order to be realistic on its
conception. Particularly, Fromm’s, 1956, four basic
elements of productic love, care, responsibility,
respect and knowledge seem to offer a compact andround theory for the understanding of productive
love. Case oriented analisis and interpretation ofthem may provide insighs of how to be used.
A technology wich improve love in presonal
relationships supports institutional managemnet oftechnology in two aspects. First, offers a theposssibility of an innovative field for technology:
Love is an universal aspect of live, which if it could
be successfully improved, offers an opportunity for
new technlological products or systems. Secodly,
the improvement of human relationships itself isequal to the improvement of the institutions that
contains those individuals, offereing a possibility to
improve nowadays societies in any scale.

Burston, D., 2007. Reply to Pnina
Shinebourne's Essay Review in Existential
Analysis, 17 (on the Art of Loving by Erich
Fromm. Existential Analysis. 18(1) 198-201.

[2]

Dion, K.K., Dion, K. L., 1996. Cultural
perspectives on romantic love. Personal
Relationships, 3, 5-17.

Fromm, E., 1957. The Art of Loving 1995 edn.
London: Thorsons.

[4]Gelbond, B., 1979. Self-actualization andunselfish love. Journal of Religious
Humanism, 13, 74-78.

[5]Hatfield, E., Utne, M.K., Traupmann, J., 1979.
Equity theory and intimate relationships, in
R.L., Burgess, T.L. Huston (Eds.), Social
Exchange in Developing Relationships,
Academic Press, New York, NY.

[6]

Hendrick, C., Hendrick, S., S., Dicke, A.,
1998. The love attitudes scale: short form,
Journal of social and Personal Relationships,
15(2) 147-159.

[7]

Hendrick, S.S., Hendrick, C., 2006. Measuringrespect in close relationships. Journal ofSocial and Personal Relationships, 23, 881-89.

[8]

Le T.N., 2005. A measure of Immature love,
Individual Differences Research, 3(2).

[9]Lee, J.A., 1973. The colors of Love: An
exploration of the ways of loving. Don Mills,
Ontario, Canada: New Press.

[10] Lee, J.A., 1988. Love styles. in R.L. Stemberg,
M.L. Barnes, (Eds.), The psychology of love
(38-67,. New Haven, CT: Yale University.
[11] Rubin, Z., 1970. Measurement of Romantic
Love, Journal of Personality and Social
Psychology, 16(2) 265-273.
[12] Shinebourne, P., 2006. Erich Fromm’s The
Art of Loving: 50 Years On. Existential
Analysis: Journal of the Society for Existential
Analysis, 17 (2) 397-408.
[13] Showers, C. J., Limke, A., 2006. Organizationof partner knowledge: Implications for liking,loving, longevity, and change. In K. D. Vohs
& E. J. Finkel, (Eds.), Self and relationships:
Connecting intrapersonal and interpersonal
processes, 177-192. New York: Guilford Press.
[14] Sorokin, P., 1954. The ways and power oflove: Types, factors, and techniques of moraltransformation. Boston: Beacon Press.
[15] Sternberg, R.B., 1997. Construct validation ofa triangular love scale. European journal of
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[16] Ungerson, C., 2005. Care, Work and Feeling.
The Sociological Review, 53(2) 188-203.
[17] Weinstein, R.S., 2007. What Heals in
Psychoanalysis? Psychoanalytic Inquiry, 27(3)302-309(8).

300Implications From Erich Fromm for Designing Affective Technology to Promote
Productive Love
Solves Pujol Ramon **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-28 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANsolves.r.aa@me.titech.ac.jp
Based on an extensive review of literature and an exploratory brainstorming, we offer
an original proposal of guidelines for designing technology that aims to improve loving
relationships. Furthermore, we explore principles of engagement with technology, such astechnology as a mirror, fun, pleasure and flow, which may be important when designinglove-promoting technology. Finally we propose a practical design example of a Productive
Love promoting application that embraces several of the proposed guidelines.

1. Introduction
Nowadays electronic devices and applications
are extensively oriented for making people’s lives
easier, to help on work activities and to provide
entertainment. However, there are practically noantecedents on devices or applications that aim to
improve loving relationships. We investigate thepossibility of using technology for improving apeople’s elemental human aspect such the capacity
to love. In the era of ubiquitous technology, almost
all the people feel more excited for using the latest
technology than reading the latest books. Therefore,
it seems possible to make use of technology as a
medium for human-human interaction and improvelove. The objective of this study is to provide anunderstanding of the nature of love in a manner that
may be usable for designing the most appropriate
love-promoting technology.
Erich Fromm, 1956, in his book “The art ofloving” proposed four basic elements common in
all forms of for love: care, responsibility, respectand knowledge, which appeal us to use them as a
key-basis for designing technology to improve love.
In addition to Erich Fromm’s approach, we base thepresent survey and proposed guidelines on an
extensive review of the works of other theorists andresearchers. Still, the theories and researches taken
into account have as a common focal point theunderstanding of love not as an involuntary passion
but as a voluntary action, which can be improved.
The reason that brought us to choose this approachis that the understanding of love as an action brings
up the possibility to make use of the existent or
future technologies to help to improve love.

2. Love approach from theoretical review
It seems that most of the people and sometheorists as well share the tendency to regard love
as innate, passive, and basically the same as fallingin love. For instance, Burston explains that Plato,
Schopenhauer, Nietzsche, Freud, and, Lacan
represents the common understanding that Erotic
love is an involuntary passion, where love is "blind"
and therefore, the adversary of reason. On the other
hand, Burston, 2007, points as well that
Kierkegaard, Scheler, Buber, and Fromm represents
the belief that genuine love always includes anelement of volition. Specifically, Fromm, 1956,
differentiated two kinds of love. Immature love or
symbiotic union, which corresponds to the person
whose character has not developed further than thereceptive orientation, which we call Receptive Love.
And mature love, attributable to the person who has
developed productive character or orientation,
which is the representative of the active love, andwe call Productive Love.
In this study five key aspects are taken into
account in order to understan Productive Love, firstwhat has been described to be in relationship to it.
Secondly we contrast with what has been describedin relation to Receptive Love, its antagonist. Third,
we explored elements of theories and empiricalstudies about love in general terms that seem to bein accordance with Productive Love. Finally, inorder to explore what Fromm’s four basic elementsof love mean for nowadays people we include a
comparison between Fromm’s, 1956, understandingof care, respect, responsibility and knowledge and301

rules of “good” or “bad”. There should neither be
obligation to do stereotyped acts such as using
emoticons, which may not represent the user. On
the other hand, love-promoting technology should
facilitate every person to feel easy to express freely,for example accepting an open-ended rage ofactions instead of offering a pre-defined and limitedone.

the results of a brainstorming regarding to them
carried out with five participants.
2.1 Discrepancies Between Fromm’s (1956)
Theory and an Exploratory BrainstormingFirst, Fromm, 1956, defined care as active
concern for life and the growth of that which welove. However, participants mainly concerned aboutcare between equals, and not much about care aswork for the other. Second, Fromm explained
responsibility as a voluntary act, to be able andready to respond. Conversely, participants
understood it mostly as a duty. Third, Fromm
explained respect to be the ability to be aware of theother’s person unique individuality. In spite of this,participants concerned about too much respect, as
negative. Finally, Fromm explained that theknowledge that is a factor for love is the one thatpenetrates to the core. However, participants did notadvert about objectiveness as key for knowledge.

4.2 Respect, not Objectification or Exploitation
Love-promoting technology should respect
everyone’s desired degree of privacy, for instance
not encouraging the use of devices such as cameras
if they attempt against one’s privacy or lead control
over a person. Moreover, love-promoting
technology should not help for acquire a person, or
obtain something from the other, as it could be toobtain personal favors or getting chores done.
4.3 Self-growth, not Dependency on Others
Love-promoting technology should not lead tocreate dependency, for instance, a device thatfacilitates a person to awake the other person in themorning would be better if facilitates as well thereceiver learn to do it by himself. A love-promoting
device that intends to improve self-growth could
facilitate to show the person’s improvements, which
may help to improve self-awareness.

4. Final Elements of Productive Love
In order to obtain a summary representative of
Productive Love, the above-introduced elementsfrom literature were analyzed and classified
grounded on theory. In addition, insights from thebrainstorming were taken into account, resulting in
the following list of elements of Productive Love.
• Preservation of personal individuality andfreedom, not feeling of duty.
• Respect, not objectification or exploitation.
• Self-growth, not dependency on others.
• Care, responsibility and active concern, notinvoluntary love.
• Giving, not exchange and fairness.
• Selflessness, not egoism.
• Enjoy the other, as he is, not evaluation of theother.
• Enjoyment of the love experience, notmaterialism.
• Realism, not delusion.
• Knowledge, not lack of understanding.

4.4 Care and Responsibility not InvoluntaryLove
A love-promoting technology which intends toimprove active concern for the other person andresponsiveness for the other’s actions could inform
about the person illusions, dislikes or moods which
could motivate to be responsive to the other needs,
for example thinking how to do something for theother person when seeing that he or she needs it.

4. Guidelines for designing technology that
promotes productive love
This section introduces an initial proposal oftheory and some examples of how the final
elements of Productive Love could be taken into
account when designing love-promoting technology.
4.1 Preservation of Personal Individuality andFreedom, not Feeling of Duty
When using a love-promoting technology, there
should be freedom of actions; there should not be

302

4.5 Giving, not Exchange and Fairness
The actions done on love-promoting technology
should facilitate to understand the other’s paceinstead of focus on a return, which may be derived
for instance, from an operating logic that requires
correspondence of actions. The user should not findpleasure only on receiving an action from the other,but doing an action for the other, for instance, this
could be motivated by providing information of theother person’s feelings when receives an action.
4.6 Selflessness, not Egoism
In a love promoting technology the source ofpleasure should not remain in the human-device
interaction but grow to be in the human-humaninteraction, which may lead to learn to enjoy doing
actions for the other. In order to accomplish that,the actions carried out in the love-promoting
technology should be far from fiction, as the ones

of technology that requires human-technology
interaction. This section discusses factors that seemcritical to effectively engage with the lovepromoting technology.
Bolter and Gromala, 2003, defended thattechnology can be a mirror where every applicationmust be an experience. Besides, concerning with
the quality of the experience, the importance ofenjoyment related to human computer interactions
has been discussed by Blythe and Hassenzahl, 2003,
who explained fun to be trivial, repetitive,
spontaneous, frivol and spectacle-like. Whilepleasure was explained to be relevant, progressive,
not necessarily spontaneous, somehow serious,
aesthetics or art-like, to require commitment to thebasic principles and rules of the activity and whichsources are limited to three: opportunities for
personal growth, memory attachment, andanticipation. Accordingly, in order to make theexperience pleasurable, the love-promoting
technology could strive for the feelings that can beexperienced when remembering a loved person, or
when anticipating the other person acts. Moreover,the mirroring of own acts could stress theconsciousness of the active engagement, which maylead to personal growth. For example, a gamewhere one is able to discover and do things for apartner could be a way to motivate the user toinitiate some of the above described keys ofpleasure in relation to the other.
Nevertheless, besides being pleasurable, lovepromoting technology might need to provide an
extra attractiveness in order to compete withnowadays most popular daily leisure activities suchas watching TV, browsing the Internet, or playing
videogames. Among nowadays popular leisureactivities, videogames and web activities have been
extensively linked to flow, concept that was
initially introduced by Csikszentmihalyi, 1990, who
explained it as an optimal experience that follows
the optimal combination of challenge and skill
levels of the person and the situation. In that sense,a game-oriented or web-oriented application could
be at first appropriate for the love-promoting
technology, for example if icons that appear on ascreen suggest some kind of easy interaction it
might lead to reactive operation and thus, beattractive and fun.

carried out by fictional characters in fictional
contexts in most of the videogames, but closer toreal actions and real persons as accurately as
possible,
4.7 Enjoy the Other, as he is, not Evaluation of
the Other
Love-promoting technology should not makedifferences of rank, status, personal scoring,comparisons or competition, for instance highamount of actions should not be evaluated as better.
Likewise, actions such as “buying a present” or“asking how are you” should not be established ashaving different value, both of them should beshown as valuable in order to let the receiverunderstand its context and enjoy them.
4.8 Enjoyment of the Love Experience, notMaterialism
Love-promoting technology should notpremium the user actions by obtaining any return
such as points or evaluation, which may drive tofocus on the regard. However, initially, somethingsimilar to a game might provide initial interest,
which could help to appreciate the love experience.
4.9 Realism, not Delusion
Love-promoting technology should avoid
showing an unreal or partial image of the partner,
which may lead to create a wrong image of him or
her. Love-promoting technology should avoid for
instance, to improve idealization of the partner byshowing too many sings of affection such as
exaggerate emoticons, for example. What is more,in order to help for an objective understanding of
the partner; love-promoting technology should
transmit realistic information about both, good andbad things.
4.10 Knowledge, not Lack of Understanding
Knowledge about the partner should bepromoted by the love-promoting technology. Toknow about the other person could be helped byfacilitating the user to provide personal informationsuch as answering questions, being motivated totalk or write about oneself, or to share personal
images or objects. However knowledge could becollected as well automatically, using for instance,
sensory technology that may collect images, sound,movement, presence, etc. It is possible as well to
use the collected data to estimate the person’s
activity, emotions or feelings.

6. Practical Design Example
In this section we describe a hypotheticalsystem that targets to improve the love between
persons that are distant from each other, they could
be lovers, familiars, friends, etc. This intends toprovide a practical example of a love-promoting

5. Engagement with the technology
Love-promoting technology besides being avehicle for human-human interaction is still a piece303

technology design that embraces several of the
proposed guidelines for love-promoting technology
and factors of engagement with technology.
The system automatically takes pictures of eachof the users and sends to another selected user. The
automatism frees the users from a task that could
represent duty, a burden, and thus, could beabandoned. Essentially, it intends to provide better
engagement with the system, and consequently withthe other person.
The pictures are taken in random intervals, thisway the photographed person appears completely
natural, doing whatever he is doing and away fromposing and choosing the best smiling picture to be
send. This ensures that the information objectively
represents the person. Realistic information is agood basis to appreciate the other, as he is, to see
what he does, how he looks, or even to infer how hefeels.
However, in order to respect intimacy, the user
is able to regulate the extent and allocation of time
for the taken pictures. The span of time where thepictures are taken is selected manually by the user,
it varies from very short, in punctual situations suchas while having lunch, or while using the PC, tomore longer spans of time, such as while being in aroom, kitchen, etc. This regulation reflects degrees
of openness between the users, providing
information about them and the relationship. The
degree of clarity of the pictures can be regulated aswell; as a result, those who feel very open choose acompletely clear picture, while when the user needs
to keep some distance he or she selects a blurryeffect. The option of blurry the image includes
artistic effects, which are playful and motivates
engagement. However, in order to avoid shifting the
focus of attention from the person into the art effect,
which would distract the main objective ofimproving love for the person, the artistic effects
are limited.
The number of pictures sent is handy, a set ofthree plus a short video every day. The receiver isable to find them very accessibly in an applicationof his computer, gaming console, digital picture
frame or a “love device”. The user feels desire oftaking a look into his lover pictures, and then to hismother pictures for instance.
In order to promote active concern for the otherperson, as well as engagement with the system, thesystem includes a touch panel display. Using thetouch panel display, the pictures are directly
commented writing on them, and re-send to theoriginal person. This encourages the person to takean action related to the person who appears in the
picture, which helps to move the concern from the304

self to the other person. What is more, receiving
commented pictures of oneself, which one has evennot seen yet, serves as a mirror that supports
personal awareness. This also keeps the userinterested and engaged with the technology, andtherefore with the loved person.
7. Conclusion
A love-promoting technology might not be able
to create love itself, however, based on providing
enjoyment of doing activities related to the otherperson may be able to create the conditions to findways to improve love. Eventually, those activities
might substitute general forms of entertainment,
which are done without relation with the loved
persons, for instance, watching TV, or playing
videogames. Spending time considering the otherperson seems a way to help to know the other,respect him, feel responsible for him, and care forhim, which are the basic elements of Fromm’s,
1956, productive love.
This idea offers a new ground design of new
applications of technology wich could be a key
field to establish a new innovative science for the
management of the technology. Besides, love, aspart of human relationships relationships is present
at entrepreneurial and other institutionalorganizations, therefore an appoach to comprehend
it could contribute to the dynamic evolution
between innovation and institutions.
References[1]

Blythe, M., & Hassenzahl M., 2003. The
semantics of fun: Differentiating enjoyable
experiences. In M. A. Blythe, A. F. Monk, K.
Overbeeke & P. C. Wright (Eds.), Funology:
From Usability to Enjoyment, Kluwer,
Dordrecht, the Netherlands, pp. 91-100.

[2]

Bolter, J.D., Gromala D., 2003.Windows andMirrors: Interaction Design, Digital Art andthe Myth of Transparency, M.I.T. Press,
Cambridge.

[3]

Burston, D., 2007. Reply to Pnina
Shinebourne's Essay Review in Existential
Analysis, 17 (on the Art of Loving by Erich
Fromm. Existential Analysis. 18, 1, pp.198201.

[4]

Csikszentmihalyi, M., 1990. Flow: The
Psychology of Optimal Experience, Harper
Row, New York.

[5]

Fromm, E., 1956, The Art of Loving, 1995.
edn. Thorsons, London.

Productive Love Related Devices and System Evaluation
Solves Pujol Ramon **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-28 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANsolves.r.aa@me.titech.ac.jp
Love is highly present in peoples talks and all cultural spheres, its importance suggests
the need to understand what role technology plays in relation to it and the roles it could
play in the future. We review studies related to love in HCI and we identify a lack ofconsideration of philosophy as a background for love understanding. Based on own
elaborated guidelines for Productive Love we present a Productive Love promoting system,
which evaluation indicated it to be useful to improve Productive Love.

2. Love approach from theoretical review
Erich Fromm (1956) differentiated two kinds oflove. Immature love or symbiotic union, whichcorresponds to the person whose character, has notdeveloped further than the receptive orientation,
and we define as Receptive Love. Mature love,
attributable to the person who has developed
productive character or orientation, is therepresentative of active love, and we define as
Productive Love [5]. The idea of Productive Lovehas been approached by several philosophers under
different designations such as being love byAbraham Maslow or benevolent love, altruistic love
and agape love by Bernard Murstein [14]. As avalidation of Productive Love-related theories thatregard it as a higher form of love, agape love waspositively correlated with relationship satisfaction[15].
We base the proposed system on an extensive
review of the works of several theorists andresearchers. In this survey we considered western
philosophy and psychological studies, yet some of
the included authors took into account eastern
approaches on their studies. Still, the theories andresearches taken into account understand of love
not as an involuntary passion but as a voluntaryaction, which can be improved. The reason thatbrought us to choose this approach is that theunderstanding of love as an action brings up the
possibility to make use of the existent or futuretechnologies to help to improve love, while theunderstanding of love as a involuntary passion
offers few room for doing anything for it.

1. Introduction
Participation on SIMOT lectures, forums andsymposiums provide me a accurate vision of what
are the key aspects of the institutional managementof the technology. Among them uniqueness andinovation outsatnded as decisive for technology
design, the reseach presented here aims to provide
an original approach for designing the futuretechnology.
In relationship to love and in the field of HCI
there have widely been realized studies abouttransmission of personal information, intimacy,
connectedness, awareness, and social presence.
However, the understanding of love has not been
approached specifically. Besides, what has been
done is mainly based on people experiences andopinions. On the other hand, a philosophicalapproach may represent a further understanding of
the experience of love, consequently, in this paper,
our goal is to explore how technology cancontribute to improve love relationships throughbasing our principles on philosophy.
Our contribution is the description of theexisting and potential design space for HCI in
relation to the field of love. In order to do that, we
will introduce an approach on conceiving loving
relationships and explore its applicability in HCI.
We want to highlight the possibility of a new line ofresearch that has for the most part been unobserved
within HCI to date. That is the possibility of using
philosophy and technology to improve loving
relationships.

305

Finally, the Syncromate allowed exchanging amessage while it was being composed, [6]. Those
devices provided more realistic information about
the other person actions, however in our opinion,
those devices are restricted concerning thetransmission of information about the person’s
inner situation, which would be highly valuable inpromoting Productive Love
Some proposals transmitted even more personal
information. The Hand Holding transmitted
heartbeat and warmth and the Love egg acted as avoice mail [12]. The Scanboard enabled two houses
to share a writing surface. [9]. The I-fuzz allowed toleave messages around to be found serendipitously[6]. Finally, in the ToTell list, pictures or messages
acted as a post card, that functioned as a reminder
of interesting moments and experiences to talkabout [17]. Those devices provided more objective
and intimate information about the partner, however
they required a voluntary action of the user. We
believe that there is the possibility to provide
intimate information automatically, without
voluntary action, which may not fail to becontinuously provided and may serve to initiate
concern about the other and instigate Productive
Love growth. This belief as well as previous
remarks will be materialized in the practical design
example of the last section.

3. Previous Related Works
In this section we explain previous researches
whose approach could be related to Productive
Love and its elements. First, we describe systems
that provide some aspects related to Productive
Love. Second, we describe the methods that havebeen used for designing some of the describedsystems.
3.1 Systems
Intimate awareness systems were exploredthrough metaphoric representations. For instance,
the Feather let a plume float on a transparent tube,
and the Scent let an fragrance vaporize in the room
when a distant partner touched a frame of a pictureof the couple. The Shaker transmitted a vibration
maintaining timing and amplitude of movements[19]. The LumiTouch picture frame lighted when
the remote user touched a picture [2]. The Lover’s
cups transmitted the movement of the cup into
illumination [3]. The Sensing beds transmitted theremote user position by heat [7]. The Secret touchallowed sharing tactile impulses from the pockets,
the Hug over a distance composed by jackets
allowed to exchange a virtual hug [6]. Pulling theCurtain IPL the user was shown as a flower. In
touch transmitted touch into glow, warmth orvibration [9]. Finally, he Digital family portrait
examined abstract visualizations of information
about well being of an elderly relative [15]. These
devices provided awareness through several kindsof actions and representations. However, themetaphoric representations provided by thesedevices may be excessively ambiguous on its
interpretation under the point of view of Productive
Love; therefore, they may fail to provide objective
knowledge about the partner, which is needed as abasis for growing Productive Love.
Some proposals transmitted the information in amore objective way. Social presence was achievedby displaying a remote friend watching the same
television program [11]. The Coffee aroma
generator was used as a clear and naturalrepresentation of a distant action [18]. The
Gustbowl was a bowl placed at the home entrance,
which sent pictures when things like keys were
dropped into it [10]. The Whereabouts clock
demonstrated to serve as reassurance through an
animated representation of family location where
members of the household are represented by icons
linked to the location of their cell phones [1]. The
synchronized CommuteBoard was a whiteboardthat visually showed general noise level at the
remote location and the Romlink connected two
remote locations with high quality audio [9].

3.2 Methods
In order to approach the above-mentioned
designs related to love, several research methods
have been used. First, designs were based oninterviewing couples in long distance stable
relationships [12]. Participatory designs were used
to find out what people miss [10]. Cultural probes
were used as well [9, 20]. Furthermore, Vetere
listedseveralresearchmethods:
onlinequestionnaires, data logs, longitudinal focus groups,
interviews, and written reflections [20].
The pointed methods rely on people’s opinions
and habits about their relationships. However, we
believe that generally, people usually may notunderstand love in such a deep way as philosophers
do. People’s ways are not perfect and could be
improved through the Productive Love principles.
Besides, we believe that the principles of
productive love are not commonly known andshared, therefore, the above mentioned methods
seem to not be applicable for assessment about
them.
3. System: Pictures’ call.
This section provides a practical example of asystem that embraces several of the proposed306

guidelines for love-promoting technology andfactors of engagement with technology.
3.1 Description
The system automatically takes pictures of eachof the users and sends to the other. The automatism
frees the users from a task that could represent duty,
a burden, and thus, could be abandoned. Essentially,
the automatism intends to provide better
engagement with the system, and consequently withthe other person.
The pictures are taken through a tablet PC that
displays a mirror image when functioning. Five
pictures a day are taken in random intervals, thisway the photographed person appears completely
natural, doing whatever he is doing and away fromposing and choosing the best smiling picture to be
send. This ensures that the information realisticallyand objectively represents the person.
In order to respect intimacy, the system
incorporates a reset button and the pictures are sent
after a security delay of thirty minutes. This way, if
necessary, the user is able to reset the system
anytime before the pictures are sent, protecting his
individuality and freedom.
The pictures are received in a second tablet PC,
where the pictures are automatically displayed as aslideshow. Receiving updated pictures of thecompanion is useful for improving the knowledge
about the other, and may motivate care andresponsibility. Moreover, in order to promote active
concern for the other person, as well as engagementwith the system, the pictures are directly
commented by writing on them using the touch
panel display, and re-sent to the original person.
This encourages the person to take an action related
to the person who appears in the picture, which canbe considered as a gift and a selfless act. What ismore, receiving commented pictures of oneself,
which one has even not seen yet, serves as a mirrorthat supports personal awareness. This also keeps
the user interested and engaged with the technology
and therefore with the loved person, which helps toenjoy the love experience, and the other.
3.2 Evaluation
The system installed in two households, one ofwhich were parents on their fifties, and the otherwas their son on his twenties. The participants used
the system for one week and answered sixquestionnaires about Productive Love and thesystem use.
Before using the system, the participants
answered a questionnaire about how much theyvalued the items of Productive Love. This
questionnaire was returned after using the system

307

and they answered a second questionnaire on how
the system helped them to achieve Productive Love.
Besides, the participants answered a Productive
Love questionnaire about their relationship with theother household member. This questionnaire wasadministrated before and after using the system inorder to detect if the participants experienced
changes on their Productive Love relationships.
A fourth questionnaire assessed the costs andbenefits of communication. A fifth questionnaire
assessed three of the Nielsen's [16] five criteria ofusability: learnability efficiency and satisfaction.
Finally, a sixth questionnaire asked theirimpressions about the system.
The participants evaluated positively the
Productive Love items, indicating that were suitable
for them. The most valued factor was respect andthe less valued was realism. The participants feltthat the system helped them to achieve Productive
Love as well, particularly, the participant that rated
the system as more helpful was the mother who
spent more hours with the system. The factors thatthe device was ranked on being more helpful werecare and responsibility, selfless, enjoy the other andknowledge, while the factor that was less ranked
was self-growth. In the other side, the overall
difference before and after using the system, about
Productive Love between the distant familiars, still
positive, was minimal, which seems attributable tohaving used the system for only one week, which
may be not long enough to lead the action done for
Productive Love be reflected on the users
relationship.
The costs and benefits of communicationquestionnaire showed that the system was not wellevaluated in terms of privacy. The reasons were
where the mother’s concern about spending longtime in front of a camera, and the son’s concern
about the fact that a large part o his room was takenby the camera. Placing the camera in a lessintrusive place might solve those problems. In theother side, the system was well evaluated in termsof not causing expectations or obligations. This
makes the system valuable for relationships where
one of the parties has higher desire of updated
information than the other, for example,
grandparents who may want to see more about the
young generations, which are sometimes to busy tokeep informing them.
The learnability and efficiency of the system
where evaluated low, the reason seems to be thatthe system had technical problems, and stopped
several times. For instance, the system errors madethe son worry about if his parents had received hiscomments or not. In the other side, the system waswell evaluated in terms of satisfaction the witch
indicates that in spite of its errors the participants
were able to enjoy it. The father appreciatedsending comments, but he would like as well, tosend own-taken pictures through the system and use
it for videoconference. The mother enjoyed seeing
things in a natural setting that she even did not see
when living together with her son. The son highly
valued sending and receiving hand righting in realtime, and being able to handwriting itself, which let
him transmit his feelings.

[7]

Goodman, E. Misilim, M., 2003, The Sensing
Beds. In Proc. UbiComp Workshop 2003

[8]

Hatfield, E., Utne, M.K., Traupmann, J., 1979.
Equity theory and intimate relationships, in
R.L., Burgess, and T. L. Huston, (Eds.). Social
Exchange in Developing Relationships,
Academic Press, New York,[9]

Hindus, D., Mainwaring, S.D., Leduc, N.,
Hagström, A.E., and Bayley, O., 2001.
Casablanca: Designing social communication
devices for the home, In Proc. CHI 2001,
ACM Press, 325-332.

4. Conclusions
Expertise on creating the future technologicalapplications can be a key factor of the science ofmanagement of the technology. In order to do that
we have proposed an innovative approach:
Productive Love-promoting technology. This study
is pioneer in the improvement of Love, which as
being part of all huma relationships, should
contribute to the dynamic evolution between
innovation and institutions.Our system evaluation
indicated that the participants felt that I the device
positively helped them to achieve Productive Love.
However, further evaluations should be done during
longer period in order to materialize those
improvements in the users lives. Besides, future
development of the system should address theexperienced technical problems.

[10] van der Hoog, W., Keller, A.I., Stappers, P.J.,
2004. Gustbowl: Technology supporting
affective communication through routine
ritual interactions. Ext. Abstracts CHI 2004,
ACM Press, 24-29.
[11] Huijnen, A. IJsselsteijn, W., Markopoulos, P.,de Ruyter, B., 2004. Social presence andgroup attraction: exploring the effects ofawareness systems in the home, Cognition,
Technology and Work, 6, 1, 41-44.
[12] Kaye, J.’J.’ and Goulding, L., 2004. Intimate
objects. Proc. DIS 2004, ACM Press.
[13] Le, T.N., 2005. A measure of immature love,
Individual Differences Research, 3, b.
[14] Lin, L., and Huddleston-Casas, C.A., 2005.
Agape love in couple relationships. Marriage
and Family Review, 37 (4), 29, 48. J.

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Brown, B., Taylor, A., Izadi, S., Sellen, A.
2007. Kay, J. Locating Family Values: A
field trial of the whereabouts clock. In Proc.
UbiComp 2007. Insbruck, Austria. Springer,354-371.

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Chang, A., Resner, B., Koerner, B., Wang, X.,
and Ishii, H., 2001. LumiTouch: An emotional
communication device. Ext. Abstracts CHI
2001, ACM Press, 313-314.

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Supporting peace of mind for extended family
members. In Proc. SIGCHI 2001, ACM Press,333-340.
[16] Nielsen, J., 1993. Usability Engineering,Morgan Kaufmann, San Francisco.
[17] Romero, N., Markopoulos, P., Baren, J.,
Ruyter, B., Ijsselsteijn, W., Farshchian, B,
2007. Connecting the family with awarenesssystems, Personal and Ubiquitous Computing,11, 4, 299-312.

Chung, H. Lee, C.H., Selker, T., 2006. Lover's
Cups:
Drinking
interfaces
asnewcommunication channels. Ext. Abstracts CHI
2006, ACM Press.

[18] Siio, I., Rowan, J., Mima, N. and Mynatt, E.,
2003. Digital Decor: Augmented everyday
things. Graphics Interface, 11, 13,155-166.

Dion, K.K., Dion, K.L., 1996. Cultural
perspectives on romantic love. Personal
Relationships, 3, 5-17.

[19] Strong, R. and Gaver, B., 1996.Feather, Scentand Shaker: Supporting simple intimacy. Proc.
CSCW 1996, ACM Press[5]

Fromm, E., 1956, The Art of Loving, 1995.
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Gibbs, M. F., Vetere, M. Bunyan, and Howard,S., 2005. Syncromate: A phatic technology formediating intimacy. In Proc. Designing User
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SIGCHI 2005, ACM Press, 471-480.

Dilution Effect and Earnings Management:
EVIDENCE FROM JAPANESE IPOS
Xi Zheng**

Department of Industrial Engineering and Managemen
Tokyo Institute of Technology
2-12-1 W9-427 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
Zhengxi666@hotmail.com
This reasearch attempts to reveal the relationship between the dilution effect at thetime of the initial public offering (IPO), and the pre-IPO earnings management thatcarries weight in the decision of offer price. An important finding is that the motivation to
reduce wealth transfer from pre-IPO shareholders to new investors, taking effect throughIPO underpricing, has a significant impact on pre-IPO earnings management. In
particular, the IPO issuers are inclined to utilize positive abnormal accruals in order toreduce the wealth loss suffered by stable shareholders during the IPO process.
2. Hypotheses
2.1 Wealth transfer
When IPO firms go public, they usually issue
new shares to raise funds and sell a part of the
pre-IPO shares in order to realize insiders’ profit.
Since these shares are typically sold at a discounted
price, this sale of shares means a wealth transferfrom the pre-IPO shareholders to the newshareholders during the IPO. Habib and Ljungqvist(2001) argue that the IPO issuers’ attitude on theunderpricing of shares depends on the magnitude ofboth original shares and new shares that they offer
during the IPO. As long as there is underpricing, themore the number of shares offered during the IPO,
the greater the wealth is transferred from thepre-IPO shareholders to the new investors. In
consideration of the impact of the pre-IPO
accounting performance on the offer price, theissuers might utilize positive abnormal accruals to
reduce the level of underpricing in order to mitigate
the wealth transfer. Thus, I develop the hypothesis
as follows:
H1: There is a positive relationship between thelevel of shares offered at the time of the IPO andthe abnormal accruals before it.
2.2 Control transfer
Apart from the wealth transfer, the pre-IPO
shareholders might suffer another type of transfer— the transfer of corporate control over the firm.
The issue of new shares and the offer for sale at thetime of the IPO will dilute the ownership of the
pre-IPO shareholders. In other words, raising
capital and realizing insiders’ profit are achieved at
the expense of a partial transfer of corporate control
over the firm. One of the means to minimize thecontrol transfer is to manipulate the distribution ofshares so as to create a favorable ownership
structure. Stoughton and Zechner (1995) and
Brennan and Franks (1997) suggest that the ownersof IPO firms could underprice IPO shares in order

1. Introduction
Some researchers argue that IPOs create strong
motivations of earnings management in order toinfluence the offer price, manipulate the allocationof IPO shares, reduce the possibility of litigation,etc. Nagata and Hachiya (2004) investigate theearnings management of Japanese IPO firms andargue that earnings management is used to ensure
the “display of growth,” which is an importantcriterion for IPO firms, in order to fulfill the listing
requirements and attract potential investors. In thisstudy, I attempt to explore other motives that induce
Japanese firms to manage earnings at the time of
the IPO. I particularly investigate the relationshipbetween pre-IPO earnings management and the
dilution effect suffered by the pre-IPO shareholders
at the time of the IPO. The theoretical basis of thisinvestigation is the information asymmetry between
an IPO firm’s insiders and outside potential
investors. The information asymmetry around the
IPO might induce the firm’s insiders to control the
IPO process for their own interest. Earnings
management is one of the possible means by which
the offer price can be influenced in a manner that isbeneficial to the insiders.
This study contributes to the existing literatureof earnings management in several different ways.
First, unlike the existing studies that mostly focus
on the relationship between earnings management
and post-IPO underperformance of the IPO firm, I
explore the source of earnings management by
utilizing the pre-IPO information of the IPO firm.
Second, I highlight the impact of the twocontrastive factors – wealth transfer and control
transfer – on the earnings management behavior.
Third, I link the earnings management to thefeatures of Japanese corporate governance. My
analysis suggests that the ownership structure of the
IPO firm will influence the decision of earnings
management.

309

to manipulate the distribution process. Since
underpricing the offer can assist in ensuring
over-subscription, the issuers will be then able toafford allocating the shares among the investors
according to their target ownership structure. In
consideration of the impact of pre-IPO accounting
performance on the offer price, the issuers mightutilize negative abnormal accruals to increase thelevel of underpricing in order to mitigate the control
transfer. I thus establish the second hypothesis,
which is the converse of the first.
H2: There is a negative relationship between
the level of share offered at the time of the IPO andthe abnormal accruals before it.
2.3 Shareholder characteristics
Although the wealth and control transfers thatthe pre-IPO shareholders suffer at the time of the
IPO induces them to manage the earnings, the levelof earnings management also depends on the firm’s
ownership structure since the pre-IPO shareholders
might not be treated equally by the managers. With
regard to the shareholders’ characteristics, theissuer might pay more attention to the shareholders
that are more committed to their business. For
Japanese IPO firms, constructing a close
partnership with a particular group of associates
through cross shareholding is considered as animportant capital policy to be implemented prior to
the IPO. Firms that have business and financial
relationships with IPO firms typically holdimportant positions in the pre-IPO ownership
structure of the IPO firms. Based upon the businessor financial relationship with the IPO firm, someshareholders, such as the main banks and business
partners, are inclined to retain their shares over a
relatively long term. These groups of shareholders
are generally considered as the IPO firms’ stableshareholders. For these stable shareholders, holding
the IPO firm’s stock is a type of policy investment,such as the reinforcement of a long-run relationship,rather than a means to profit from the expected
stock return of the IPO firm. Including thesebusiness and financial partners in its group ofshareholders might not only foster the IPO firm’s
stable and sustainable development but also make it
immune to hostile takeover; more importantly, it
will secure the existing management’s control overthe firm. Therefore, a high proportion of stableshareholders would exert a considerable pressure on
the IPO issuers to control the loss from the dilution
effect and minimize it through earnings
management. On the other hand, the free float
shareholders, typically some individual investors,
have relatively short-term relationship with the IPO
firm and are less committed to the IPO firm’s
business. The free float shareholders, particularly
those who do not maintain any business relations
with the IPO firm, are relatively speculative and310

more likely to sell shares in pursuit of the capitalgain in the stock market. Therefore, the managers
should pay more attention to the stableshareholders’ interest rather than to that of the free
float shareholders. In terms of wealth and control
transfers, therefore, it is rational that the IPO issuers
disregard the impact of the dilution effect when thefree float shareholders dominate the pre-IPO
shareholders.
Based on the above discussion, I establish thethird and fourth hypotheses as follows.
H3: There is a positive relationship between the
pre-IPO level of the ownership by stableshareholders
andtheabnormalaccruals
immediately before the IPO.
H4: There is a negative relationship between
the pre-IPO level of the ownership by free float
shareholders
andtheabnormalaccruals
immediately before the IPO.
It also is necessary to have a more detailed
discussion on the influence of the stableshareholders on pre-IPO earnings management. To
some extent, the IPO firm’s relationship with thebusiness partners might take precedence over thatwith its main banks. The former relationship isforged on the basis of the contract to trade materials.
The IPO firm’s business partners, whether suppliers
or customers, are generally irreplaceable. In
addition, the investments in relationship-specificassets strengthen the relationships between the IPO
firm and its business partners. The magnitude ofthese investments in relationship-specific assets
makes it difficult for IPO firms to change partners.
Meanwhile, the cross shareholding between the IPO
firm and its business partners could also mitigate
the risk of hold-up problem accompanying theseinvestments in relationship-specific assets. As
opposed to business relationships, financial
relationships are forged by contracts based on
money. Although the financial support from themain banks is very important to IPO firms, it is not
irreplaceable; therefore, the IPO firm might value
the relationship with its business partners more
highly than that with the main banks. This attitude
may accordingly influence the decision of pre-IPO
earnings management. In other words, the pre-IPO
earnings management would differ according to the
proportion of the ownership by business partners tothat by main banks. Therefore, I will further test the
impacts of business partners and main banks when
examiningtheimpactofshareholders’characteristics on earnings management.
3. Data and methodology
3.1 Variable definitions
Abnormal accruals: In this study, I use abnormal
accruals (AAC) as a measure of earnings
management. Abnormal accruals are defined as thedifference between the total and expectedaccruals (EAC), where non-abnormal accruals are
estimated using an extension of the cross-sectional
modified Jones model. In this model developed by
Dechow et al. (1995), expected accruals arecomputed as follows:

The analyses on the relationship between
wealth transfer and earnings management and thatbetween control transfer and earnings management
offer contrasting predictions regarding theassociation between the dilution effect proxies(OFS and TSS) and abnormal accruals. In order todetermine the type of dilution effect—wealthtransfer or control transfer—that induces Japanesefirms to manage earnings before the IPO, I use a
two-dimensional analysis to test the first two
hypotheses. Nagata and Hachiya (2004) investigate
the abnormal accruals of the JASDAQ IPO firms
and argue that earnings pressure, which is definedas the gap between the IPO firm’s pre-managed andtarget earnings, has a substantial impact on theabnormal accruals. To control the influence of
earnings pressure, I first divide the sample firms
into two groups by the median value of EP－1. In
both the high EP－1 and low EP－1 group, the sample
firms are further divided into three subgroups by
the value of OFS. I then calculate the mean andmedian values of AAC－1 for each group to identify
how the abnormal accruals vary according to thewealth and control transfers. The same process isalso applied to investigate the manner in which
AAC－1 varies with TSS.
In order to more rigorously investigate whether
earnings management is influenced by the motive to
reduce wealth or control transfers, I construct thefollowing regression model:

EACit−1 =α1(1/ Assetit−1) +α2[(∆REVit −∆ARit ) / Assetit−1]+α3(PPE
it / Assetit−1) +εi

where EAC is the expected accruals, ∆REVit is thechange in revenues from period t–1 to period t;∆ARit is the change in accounts receivables fromperiod t–1 to period t; PPEit is the gross property,
plant, and equipment at the end of period t; andAssetit–1 is the total assets at the end of period t–1.
The model parameters a1, a2, a3 are estimated using
OLS regression, usually using the contemporaneous
data of comparable firms. However, it appears
inappropriate to use the data of post-IPO,
publicly-traded firms as comparables since firms in
the pre-IPO periods possess features that are quite
different from those of the publicly-traded ones interms of size, business model, growth rate, and soon. Therefore, I randomly select some of the sample
IPO firms in order to estimate parameters andmeasure abnormal accruals for the remaining IPO
firms. Hence, the abnormal accruals in this study
reflect the relative level of earnings management
among IPO firms.
Wealth and control transfers: I choose twovariables as proxies for both the wealth and control
transfers that the pre-IPO shareholders suffer fromas a result of the dilution effect. The first variable
OFS denotes the ratio of the offer for sale at thetime of the IPO to the total shares immediately
before the IPO. The second variable TSS denotes
the ratio of the total shares sold at the time of theIPO (offer for sale + new shares) to the total shares
immediately before it. I choose two variables inorder to capture the difference between the loss
suffered by the insiders who sell their shares at thetime of the IPO and that suffered by all the pre-IPO
shareholders.
Stable shareholders: Due to the dearth of data, I
use the sum of the main elements—directors,
financial institutions, and corporations—as a proxy
for the stable shareholder.
Free float shareholders: The proxy of the free
float shareholders is the pre-IPO individual
shareholders.
Ownership by business partners and that bymain banks: When testing the impact ofshareholders’characteristics
onearnings
management, I further test the impacts of business
partners and main banks. The ownership bycorporations and that by financial institutions areused as the proxies for the ownership by business
partners and that by main banks, respectively.

AAC−1 = m0 + m1TRANSFER+ m2 EP−1 + m3 AGE + m4 BB + ε(1)where AAC－1 is the abnormal accruals in the year
before the IPO; TRANSFER denotes the ratio of theoffer for sale at the time of the IPO to the total
shares immediately before the IPO (OFS), or theratio of the total shares sold at the time of the IPO
to the total shares immediately before the IPO(TSS); EP－1 is the earnings pressure in the year
before the IPO; AGE is the firm’s operational
period from start-up to the IPO, counted by month;and BB is a dummy variable that equals one if a
firm conducts its IPO with the book-building
method, and zero other wise.
To test the relationship between AAC － 1 andTRANSFER, I include three control variables in the
regression model. The earnings pressure proxy EP
is used as the first control variable. The second
control variable AGE is used as a proxy for thestability of the firm’s pre-IPO performance because
a highly volatile performance may create a strong
motive to manage earnings. Due to the dearth of
information on the firms’ pre-IPO performance, I
use their pre-IPO operational history as a proxy. It
is reasonable to consider that a firm with a longer
operational history has a relatively steady
performance. Further, I include a dummy variable

3.2 Methods311

BB to detect the impact of the change in the IPO
issuance method on the earnings management
decision.
If the IPO issuers want to reduce the wealthlosses suffered by the pre-IPO shareholders at thetime of the IPO, they are expected to manage theearnings upward. Therefore, as predicted in
hypothesis 1, the coefficients of TRANSFER, i.e.,
the proxies of the dilution effect, should be positive.
On the contrary, when the IPO issuers are moreconcerned about the control transfer, they would
manage earnings conservatively in order to set theoffer price at a relatively low level so as tomanipulate the allocation of shares. Accordingly,
hypothesis 2 predicts negative coefficients for
TRANSFER.
Hypotheses 3 and 4 predict that the firm’s
pre-IPO ownership structure has an impact on theearnings management decision since the issuer
would prioritize the stable shareholders’ interest
over that of the free float shareholders. These
predictions are preliminarily tested using the sametwo-dimensional analysis introduced before. In
other words, I examine how AAC －1 varies with
STABLE － 1 and FFLOAT － 1 after controlling theinfluence of earnings pressure. This is followed bya regression analysis as follows:

earnings management varies with the ownership bybusiness partners and that by main banks:
AAC −1 = y 0 + y1TRANSFER + y 2 ASSOCIATE −1+ y 3 EP−1 + y 4 AGE + y 5 BB + ε(3)where AAC－1 is the abnormal accruals in the year
before the IPO; TRANSFER denotes the ratio of theoffer for sale at the time of the IPO to the total
shares immediately before the IPO (OFS), or theratio of the total shares sold at the time of the IPO
to the total shares immediately before the IPO(TSS); ASSOCIATE － 1 denotes the ownership bycorporations in the year before the IPO (PARTNER－1), or the ownership by financial institutions in theyear before the IPO (BANK－1); EP－1 is the earnings
pressure in the year before the IPO, AGE is thefirm’s operational period from start-up to the IPO,
counted by month; and BB is a dummy variable that
equals one if a firm conducts its IPO by the
book-building method, and zero otherwise.

AAC −1 = s 0 + s1TRANSFER + s 2 SHAREHOLDER−1+ s3 EP−1 + s 4 AGE + s 5 BB + ε(2)where TRANSFER denotes the ratio of the offer forsale at the time of the IPO to the total shares
immediately before the IPO (OFS), or the ratio of
the total shares sold at the time of the IPO to thetotal shares immediately before the IPO (TSS);SHAREHOLDER－1 denotes the ownership by stableshareholders in the year before the IPO (STABLE－1),or the ownership by free float shareholders in theyear before the IPO (FFLOAT－1); AAC－1 is theabnormal accruals in the year before the IPO; EP－1
is the earnings pressure in the year before the IPO;
AGE is the firm’s operational period from start-up
to the IPO counted by month; and BB is a dummy
variable that equals one if a firm conducts its IPO
with the book-building method, and zero otherwise.
Similarly, the control variables used in theprevious regression model are included. According
to hypotheses 3 and 4, STABLE－1 and FFLOAT－1
should have positive and negative coefficients,
respectively.
Furthermore, IPO firms might discriminate
between their business partners and the main banks
on the basis of their business and financial
relationships
with
these
different
stableshareholders. I employ the following regression
analysis to test the manner in which the pre-IPO

312

3.3 Sample selection
This study analyzes a sample of firms that madetheir IPOs on the JASDAQ market, therepresentative OTC market in Japan. Compared to
the IPOs on the Stock Exchange, JASDAQ IPOs
possess features that are more distinguishing. In
particular, the relatively serious information
asymmetry around the IPO firms makes JASDAQ
IPOs a good subject for IPO study.
I construct the sample based upon threedatabases. The first database — Annual Securities
Statistics of the JASDAQ market supported by the
JSDA — provides listing information of IPO firms,
such as the offer price and the number of newshares. Information on the JASDAQ market index
is obtained from the Nikkei OTC Market Index
Data, supported by Nikkei Media Marketing. The
financial Information of IPO firms is obtained from
Nikkei Financial Data, supported by Nikkei Media
Marketing.
The sample is selected through the following
procedures.
(1) First, I excluded the firms lacking
necessary financial information. I was then left with
831 firms of the 920 firms that made their initialpublic offerings on the JASDAQ market from April
1989 to March 2000.
(2) In order to obtain suitable parameter
estimates for the modified Jones model, I exclude
extreme observations, the total accruals of whichwere three times below or above the standard
deviation. This procedure reduced the sample to775 firms.
(3) In order to estimate the abnormal accruals
by the method described above, 194(775*25%)
samples were selected randomly. Consequently, thesample was further reduced to 581 firms.

shares. Moreover, the ownership by stable shareholderof sample firms reaches 76.12% at the time of the IPO.
The main banks and the corporate shareholders who
are the associates of the IPO firms are allocated 8.96%
and 33.11% of the ownership, respectively. Thesefindings correspond to the previous discussion that thepre-IPO shareholder stabilization is considered as animportant capital policy for the IPO firms. At thesame time, the average ownership by free float
shareholders of sample firms was 22.37% for the year
before the IPO.

(4)
I further excluded firms regarding
which the necessary information on theownership structure during the IPO wasunavailable. Thus, 428 firms were finallyemployed in my test.
4. Results
4.1 Descriptive statistics
Panel A of Table 1 presents the descriptive statistics
for AAC－1. The 0.17% mean and 0.22% median of
AAC － 1 identify that the average level of pre-IPO
earnings management are captured by the above
method. Panel B of Table 1 summarizes thecharacteristics of the variables related to the dilution
effect at the time of the IPO. The mean volume of theTable 2 is the correlation matrix for the main variables
used in this chapter. The significant negative
correlation between EP － 1 and AAC － 1 is consistent
with the findings of Nagata and Hachiya (2004).

Table 1
Descriptive statistics
Panel A: Earnings management variable
Variable

AAC－1

Mean

0.0017

Median0.0022

1st
Quartile

3rd
Quartile

Standard
deviation

Maximum－0.03540.03780.0701

0.2424－0.2747

No. of observations

Minimum
Total

AAC－1 < 0

AAC－1 >0

428

207

221

Panel B: Dilution effect variables
Variable

MeanMedian

1st
Quartile

3rd
Quartile

Standard
deviation

Maximum

Minimum

No. of observations

OFS

0.06510.0701

0.04250.08550.03700.22790.0000428

TSS

0.16740.16110.14610.18160.03530.34780.0441428

STABLE－1

76.12%

79.02%

67.46%

87.50%

15.63%

100.00%

5.62%

428

FFLOAT－1

22.37%

19.64%

11.39%

31.13%

14.84%

75.13%

0.00%

428

PARTNER－1

33.11%

29.05%

14.06%

45.55%

24.42%

100.00%

0.00%

428

BANK－1

8.96%

8.16%

4.91%

11.30%

6.08%

50.67%

0.00%

428

Table 2
Correlation matrix for main variables (No. of observations = 428)
AAC－1

OFS

TSS

EP－1

AGE

STABLE－ 1

FFLOAT－1

AAC－1

1.00000.03980.0177－0.8820***－0.02890.0105－0.0395

0.0024－0.0293OFS

0.05031.00000.4699***0.0334－0.03770.0157－0.0083

0.0072－0.1079**

BANK－1PARTNER－1

TSS

0.00980.5323***1.00000.0064－0.1311***0.0743－0.0257－0.0102－0.1425***EP－1－0.8931 ***0.05250.04651.00000.0241－0.00900.0304－0.01030.0707AGE－0.0300－0.0675－0.1187**

0.06341.0000－0.3638***

0.4153***0.1422***－0.0194

STABLE－1

0.0356

0.0261

0.0961**－0.0134－0.3172***

1.0000－0.9361***－0.1061**

0.3865***FFLOAT－1－0.0604－0.0159－0.0266

0.08210.3876***－0.8890***

1.00000.1203***－0.3566***

BANK－1－0.0070－0.0774－0.0918*0.01710.1546***－0.06290.0890*1.0000－0.1131***PARTNER－1－0.0174－0.1266***－0.1176***0.0504－0.05110.4359***－0.4106***－0.1633***

1.0000Notes: 1) *, **, and *** indicate the significance at the 10%, 5% and 1% levels, respectively.
2) The values of Pearson correlation are given in the lower left triangle of the matrix; the values of Spearman correlation are given in the upper right triangle ofthe matrix.

However, neither OFS nor TSS shows significant
correlation to AAC － 1. In addition, although thecorrelation between STABLE－1 and AAC－1 and thatbetween FLOAT－1 and AAC－1 are insignificant, theiroffer for sale in the sample firms is 6.51% of the
pre-IPO total shares. The total shares sold at the timeof the IPO, including the offer for sale and the newshares, are equivalent to 16.74% of the pre-IPO total313

abnormal accruals in hypotheses 1 and 2. I predictthat managers utilize positive abnormal accruals to
reduce the level of underpricing when the pre-IPO
shareholders suffer the wealth transfer from thedilution effect at the time of the IPO. Alternatively,
it is also likely that in order to reduce the dilution in

relationship matches my prediction.

4.2 The impact of dilution effect on earnings
management
I make contrasting predictions regarding therelationship between the dilution effect andTable3Two-dimensional analyses for the effects of wealth and control transfers on pre-IPO earnings management
Panel A: relation between offer for sale (OFS) and abnormal accruals (AAC－1)
EP> Median

AAC－1

OFS

MedianLow－0.0483－0.0336

71

Median－0.0457－0.029471

High－0.0384－0.0357

72

F (One-way ANOVA test )0.6656Chi-Square (Kruskal-Wallis test )< Median

No. of observations

Mean

1.1594Low

0.04850.0392

71

Median0.04280.026771

High

0.05150.037372

F (One-way ANOVA test )0.4957Chi-Square (Kruskal-Wallis test )1.0113

Panel B: relation between total share sold at the time of IPO (TSS) and abnormal accruals (AAC－1)
EP> Median

AAC－1

TSS

MedianLow－0.0411－0.0328

71

Median－0.0478－0.028571

High－0.0436－0.0377

72

F (One-way ANOVA test )0.2883Chi-Square (Kruskal-Wallis test )< Median

No. of observations

Mean

0.5105Low

0.03850.0326

71

Median0.04640.032471

High

0.05790.052572

F (One-way ANOVA test )2.4414*Chi-Square (Kruskal–Wallis test )3.7739Notes: 1) *, **, and *** indicate the significance at the 10%, 5% and 1% levels, respectively.

Table 4
Regressions of pre-IPO earnings management on wealth and control transfers (model 1)
Independent variable
Intercept
OFS

Dependent variable
AAC－1

AAC－1

AAC－1

－0.0188－0.0189－0.0147(－3.9747)***(－2.2362)**(－1.7461)*

0.15030.1641(3.7065)***(3.4981)***

TSS
EP－1
AGE

0.0581－0.0291(1.3326)(－0.5854)－0.7969－0.7958－0.7969(－43.2457)***(－42.5976)***(－43.2108)*0.00000.00000.0000(1.9621)**(1.8738)*(1.9015)*0.01660.01830.0170(4.4365)***(4.7912)***(4.4693)***Adjusted-R2

0.81490.80970.8147

F-value

471.1169***455.3161***376.3764***

No. of observations

428

428

428

BB

Notes: 1) t-Statistics are presented within parentheses.
2) *, **, and *** indicate the significance at the 10%, 5% and 1% levels, respectively.

314

their ownership at the time of the IPO, themanagers utilize negative abnormal accruals before
the IPO to retain control over their firm after going
public. Table 3 presents the results of thetwo-dimensional analysis. The mean and medianshareholders suffer the wealth transfer from thedilution effect. As compared with the wealthtransfer, the managers of IPO firms do not consider
control transfer at the stage of IPO pricing. A
possible explanation for this result is that the impact

Table 5Two-dimensional analyses for the effects of shareholder characteristics on pre-IPO earnings management
Panel A: relation between stable shareholder’s ownership (STABLE－1 ) and abnormal accruals (AAC－1)
EP> Median

AAC－1

STABLE－1
MeanMedianL－0.0379－0.0232

71

M－0.0536－0.0392

71

H－0.0410－0.033672

F (One-way ANOVA test )1.7703Chi-Square (Kruskal-Wallis test )5.3527*< Median

No. of observations

L

0.0356

0.026371

M

0.05030.043071

H

0.05680.046172

F (One-way ANOVA test )3.0492**Chi-Square (Kruskal–Wallis test )6.9410**Panel B: relation between free float shareholder’s ownership (FFLOAT－1) and abnormal accruals (AAC－1)
EP> Median

FFLOAT－1

AAC－1
Mean

Median－0.0415－0.0336M－0.0541－0.0392

71

H－0.0370－0.0227

72

L

F (One-way ANOVA test )2.0223Chi-Square (Kruskal-Wallis test )5.9843**< Median

No. of observations
71

L

0.05640.044071

M

0.0501

0.048271

H

0.0366

0.026572

F (One-way ANOVA test )(2.6222)**

Chi-Square (Kruskal-Wallis test )(6.5697)**

Notes: 1) *, **, and *** indicate the significance at the 10%, 5% and 1% levels, respectively.

value of AAC－1 appears to be positively correlatedwith the OFS (TSS) level in all the sub-groups
considered for comparison, although the most ofthese differences are insignificant.
To control the influence of other factors while
examining the impact of the dilution effect on theabnormal accruals, I employ the regression model 1.
The regression results are listed in Table 4. This
regression model exhibits considerable explanatory
power with the adjusted R-squared of 81.49%,
80.97%, and 81.47%, respectively. The positivecoefficients of the OFS variable are consistent with
H1 and confirm that the IPO firms have a strong
motive to use positive abnormal accruals to increase
the reported earnings when the pre-IPO

315

of control transfer could be resolved at the stage ofshare allocation. For example, the managers could
use IPO underpricing to control the share allocationin order to retain control over their firms.
Furthermore, the statistically significant andinsignificant coefficients of OFS and TSS,
respectively, could be explained by the
managers’ sole concern for the insiders’ loss rather
than that of all the pre-IPO shareholders.
In Section 2, I argue that the managers are likely
to utilize positive abnormal accruals to reduce thestable shareholders’ loss resulting from the dilution
effect. In order to test the relationship between
shareholders’characteristics
andearnings
management, I first conduct the two-dimensional

analysis. Table 5 presents the results of the analysis.
AAC－1 seems to be positively correlated with the
STABLE－1 and negatively correlated with FFLOAT
Moreover, there are some statistically－ 1.

shareholders. That is, individual shareholders areunable to represent the free float shareholders
perfectly since the former might overlap with someof the stable shareholders.

Table 6Regressions of pre-IPO earnings management on the dilution effect (model 2 ~3)Panel A: Stable shareholders and free float shareholders
Independent variable
Intercept
OFS

Dependent variable
AAC－1

AAC－1

AAC－1

AAC－1

－0.0357－0.0345－0.0186－0.0187(－3.6161) ***(－2.9263)***(－3.8659) ***(－2.1998)**

0.14870.1503(3.6777) ***(3.7010) ***0.05130.0581(1.1760)(1.3315)TSSSTABLE－1

0.01920.0189(1.9480)**(1.8921)*FFLOAT－1
EP－1
AGE
BB

－0.0020－0.0023(－0.1884)(－0.2126)－0.7976－0.7965－0.7967－0.7956(－43.4175) ***(－42.7550)***(－43.1311)***(－42.4842)***0.00000.00000.00000.0000(2.4897) ***(2.3792)**(1.8795) *(1.8082)*

0.01720.01900.01670.0184(4.5846) ***(4.9574)***(4.4342) ***(4.7897) ***Adjusted-R2

0.81620.81090.81450.8093F-value

380.1424***367.1906***

376.0413***363.4397***

No. of observations

428

428

428

428
(continued)

significant differences in the mean and mean of
AAC － 1 among the subgroups of STABLE － 1 andFFLOAT－1.

According to Panel B of Table 6, the significant
and insignificant coefficients of PARTNER－1 andBANK－1, respectively, show that at the time of the
IPO, the firms are more concerned with the loss of
their business partners rather than to that of theirmain banks.

In order to test the relationship between
shareholder
characteristics
andearnings
management, I run regression models 2 and 3. The
results are listed in Table 6. Panel A shows that thecoefficients of STABLE－1 are significantly positive,
which is consistent with hypothesis 3. The findings
confirm that the proportion of the ownership bystable shareholders before the IPO is one of theimportant elements that induce managers to utilize
positive abnormal accruals. On the other hand, thenegative coefficients of FFLOAT－1 are consistent
with hypothesis 4. However, they are insignificant.
This might be due to the proxy of the free float

5. Conclusions
Previous researches document the fact that IPOs
create various incentives for the managers of IPO
firms to manage earnings. I find that the dilution of
wealth and control of the pre-IPO shareholders is an
important factor in explaining pre-IPO earnings
management. The findings indicate that positive
abnormal accruals serve as an effective means
against the wealth transfer suffered by the pre-IPO
shareholders from the sale of original and new316

shares at a discounted price during the IPO.
Moreover, this study provides insights into therelationship between pre-IPO earnings management
and the managers’ attitude toward different
categories of shareholders. The finding thatprovide useful information to the market participants,
such as issuers, investors and the market regulators.
This is very important to the improvement of not
only the Japanese stock market but also the Japanesefinancial system.

Table 6 － Continued
Panel B: Business partners and main banks
Independent variable
Intercept
OFS

Dependent variable
AAC－1

AAC－1

AAC－1

AAC－1

－0.0254－0.0257－0.0198－0.0198(－4.7125)***(－2.8666)***(－3.9024)***(－2.2629)**0.16160.1518(3.9856)***(3.7319)***TSSPARTNER－1

0.06790.0594(1.5550)(1.3570)0.01510.0134(2.5043)***(2.1888)**

BANK－1EP－1

0.01350.0100(0.5540)(0.4031)－0.8004－0.7989－0.7970－0.7959(－43.5784)***(－42.8312)***(－43.2138)***(－42.5572)***0.00000.00000.00000.0000(2.1493)**(2.0435)**(1.8567)*(1.7945)*0.01750.01910.01660.0183(4.6804)***(4.9936)***(4.4360)***(4.7872)***Adjusted-R2

0.81720.81140.81460.8094F-value

382.8449***368.4753***

376.3374***363.5641***

No. of observations

428

428

428

428

AGE
BB

Notes: 1) t-Statistics are presented within parentheses.
2) *, **, and *** indicate the significance at the 10%, 5% and 1% levels, respectively.

abnormal accruals are positively correlated to theownership by stable shareholders suggests that IPO
firms value their relationship with the stableshareholders who have a long-term commitment
toward them; they would therefore resort to pre-IPO
earnings management in order to control the loss
resulting from the dilution effect that the stableshareholders suffer. When exploring the componentsof stable shareholders further, I find that the IPO
firms value their relationship with their business
partners more than that with their main banks. I
interpreted this as a result of more indulgent attitude
adopted by the business partners toward theperformance of IPO firms.
In light of Science of Institutional Management ofTechnology, this study examines how the uniquefeatures of Japanese corporate governance affect thedecisions during the IPO process. The findings

317

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Initial public offerings, accounting choices,and earnings management. Contemporary
Accounting Research 10 (l), 61–81.
[2] Brennan,
M.J.,
Franks,J.R.,
1997.
Underpricing and control in initial public
offerings of equity securities in the UK.
Journal of Financial Economics 4, 391– 413.
[3] Dechow, P.M., Sloan R.G., Sweeney A.P.,
1995. Detecting earnings management. The
Accounting Review 70 (20), 193–225.
[4] DuCharme, L.L., Malatesta, P.H., Sefcik, S.E.,
2004. Earnings management, stock issues, andshareholder lawsuits. Journal of Financial
Economics 71, 27–49.

[5]Friedlan, J.M., 1994. Accounting choices ofissuesofinitialpublicofferings.
Contemporary Accounting Research 11(1),
1–32.
[6] Habib, M.A., Ljungqvist, A.P., 2001.
Underpricing and entrepreneurial wealthlosses in IPOs: Theory and evidence. The
Review of Financial Studies 14 (2), 433–458.
[7] Hachiya, T., Zheng, X., 2004. The effect of
information asymmetry, ownership change,
and regulation change: An empirical study ofinitial returns of the IPOs in JASDAQ market.
Japan Journal of Finance 23 (1), 56–76.
[8] Hachiya, T., Zheng X., 2005. Directors’
motivation to keep control of their firms in the
IPO process. Japan Journal of Finance 23 (2),2–16.
[9] Jackson, S.B., 2004, Earnings management byinitial public offering firms: A reexamination.
Journal of Forensic Accounting 5, 67–90.
[10] Kim, M., Ritter, J.R., 1999. Valuing IPOs.
Journal of Financial Economics 53 (3),409–437.
[11] Nagata, K., 2004. Purpose of initial public
offerings
andearnings
management.
Accounting 166 (6), 86–99. (in Japanese).
[12] Nagata, K., Hachiya, T., 2004. Earnings
management during initial public offerings.
Accounting Progress 5, 91–106. (in Japanese).
[13] Stoughton, N., Zecher, J., 1995. IPO
mechanism, monitoring, and ownership
structure. Working paper, University ofCalifornia, Irvine.
[14] Takami, S., Hachiya, T., 2002. The
characteristic financial ratios on the valuationof IPO firms. Japan Journal of Finance 22 (1),50–64.
[15] Teoh, S.H., Wong, T.J., Rao, G.R., 1998. Are
accruals during initial public offerings
opportunistic? Review of Accounting studies
3, 175–208.
[16] Teoh, S.H., Welch, I., Wong, T.J., 1998.
Earnings management and the long-run
market performance of initial public offerings.
Journal of Finance 53, 1935–1974.

318

A Comprehensive Study of Firm-specific Organizational Capital:
Evidence from Japan
Pablo Gonzalo Ramirez**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
pablo@ml.me.titech.ac.jp
The purpose of this research was to investigate whether organizational capital isaccumulated by Japanese firms, and also to gain a better understanding of its impact.
Results suggested that regardless of the firm’s type, the size of organizational capital issignificant when compared to traditional assets. Results supported the hypothesis oforganizational capital as a source of differences in firms’ corporate performance. Thosefirms with higher stocks were more productive, valuable and profitable.
to provide, there are no operational measures offirms’ organizational capital.
Since data
constrains do not allow me to rely in any particularorganizational practice as proxy for organizational
capital, in this work I assume that organizational
capital plays a critical role in linking a bundle oforganizational resources into a systematic process,which facilitates value creation.

1. Introduction
The notion that intangible assets supersede
tangible assets as the primary source of competitive
advantage is now commonly accepted in the
management literature.
While much of theprevious work has been devoted to somecomponents of intangibles like R&D, brand andhuman and social capital, less attention has been
devoted to other intangibles like organizational
capital. It is the purpose of this study to shed lighton issues related to the size and influence of thefirm-specific organizational capital (FSOC) on
output for Japanese firms. This work considers
two specific research streams. Firstly I focused on
the measurement of FSOC growth at firm level.
Secondly I examined the interactive effect of FSOC
and other intangibles (R&D, brand, and human andsocial capital) on firm’s value/sales.

2.2 Measurement
Assuming that it is possible to estimate FSOC
as a residual without relying on any organizational
practice (see, Lev and Radhakrishnan, 2003 andSadowski and Ludewig, 2003), I assessed it at thefirm-level before shedding light on its contribution.
The assessment of FSOC was carried out by theestimation of the systematic component of theresidual output by using two alternative
econometric techniques, REM (random effectmodel) and FEM (fixed effect model). Following
the above mentioned works, I considered two typesof organizational capital, one referred as common
organizational capital (λc) available to all firms, likelevel of employee education (off-job- training),
legal and institution regulations, technologies andbusiness practices available within a domestic
context. The second type refers to FSOC (λs) was
built up and enhanced by each firm.
Assuming that firms with competitive
advantages will tend to have higher nominal sales
or higher market value as the result of better
products or management then it is possible to use
alternatively both sales and market value as proxies
for firm’s output an estimate organizational capitalas unaccounted residual input.
In order to approximate the effects oforganizational capital, the relationship between
outputs and inputs was approached using the
traditional standard production function. Following
previous literature we used the augmented Cobb

2. Organizational Capital
2.1 Definition
The concept of organizational capital has notbeen yet unified and differences range from two
different points of view.
One considers
organizational capital closely connected withhuman capital, in the sense that firms are structures
where agents (employees) have incentive to acquire
and reveal information in an efficient manner.
Hence the manner in which information (asset) is
stored and used is called organization capital.
The second school of understanding considers
organizational capital as embodied and linked to theorganization itself rather than individuals. Lev andRadhakrishnan (2003) suggested that organizational
capital can be intuitively conceptualized as an extra,
often unmeasured factor of production responsible
for abnormal firm performance, and even though
examples of high organizational practices are easy319

Douglas function. After accounting for traditional
inputs like labor, capital and technology I added
several other control variables to account for theeffect of additional inputs like SGA (selling,
general and administrative), brand and human andsocial capital. Besides, ratios to control intraindustry differences in the intensity of mentioned
intangibles were included.
The systematic component of the residual
output, the proxy for differences due toorganizational capital was estimated by using the
econometrictechniques
mentioned
above.
Accordingly it was assumed that fixed effectdummy or the error component term coefficient
included the idiosyncratic effect (firm-specificeffect) which is constant over the time and is not
attributable to the effect of other input
To transform the coefficient estimates into amonetary measure of organizational capital, I
estimated the difference in value or sales inducedby the inclusion and exclusion of firm-specificorganizational capital (see Ramirez and Hachiya,
2006a, 2006b for details).

included in the sample only if there were at least
two firms belonging to each industry.
4. Results
4.1 FSOC measurement
In terms of percentages, the mean FSOC togross assets represents 16 % (20%) for R&D firms
using alternatively REM (FEM) estimates
respectively. For non- R&D firms the mean FSOC
to gross assets represents 32% (42%) using REM(FEM) respectively. Regardless of the firm type,these results show that in monetary terms the valueof FSOC stock is significant when compared withtraditional assets. This was consistent with the idea
of FSOC as a source to explain firms differences on
productivity or market value.
The results also indicate that 50% of the firms(R&D and non-R&D as well) have negative FSOC
stocks, suggesting that organizational capital could
be damaging (instead of helping firms increase theirvalue, lessen it).
Besides, highly skewed distribution isconsistent with the presumption of exclusiveness or
uniqueness attributable to FSOC and responsible
for the explanation of cross-sectional differences in
the market values of firms.

3. Sample
The sample consisted of firms listed in theTokyo Stock Exchange. Financial and performancedata were extracted from Nikkei Corporate
Financial Database, and stock prices from Toyo
Keizai Stock Price Data Bank. The firms weredivided into ones having available data on researchand development expenditures (RE) (high-techfirms) and those that have not (low-tech firms).
The sample included observations from 472 R&D
and 234 non-R&D firms through the years 19882001.
Those firms with missing data for any of thefollowing variables: sales (SA), the net value of
property plant and equipment (PE), number of
employees (EM), advertising expenditures (AD),payroll costs (PAY) and selling general &administrative (SGA) which includes salescommissions, marketing expenditures, patent fee
payments, rent expenses, depreciation andamortization, packing and storage costs, and others
SGA were excluded. The R&D firms’ portfolio
included firms for which no data was missing on
research and development expenditures (19882001). Besides, research and development capital(RC) (key variable of this study), was estimated bycapitalizing and amortizing (5 years, 20% annual
amortization rate) the annual research anddevelopment expenditures (for similar approach see
Lev and Radhakrishnan, 2003).
The sample of R&D firms includes 22
industries whereas the non-R&D includes 23 (4digits industrial classification).
Firms wereTable 1 Assessment of FSOC
R&D Portfolio

non-R&D Portfolio

Gross Assets

FSOC

Gross Assets

Obs.

2,639

2,633

1,078

FSOC
1,124

Mean

334,888

54,574

348,015

111,626

Std. D.

987,803368,179

839,106

399,274

Minimun

3,845-1,701,207

1,893-179,831

Quartile 25

39,248-15,306

34,053-19,004

Median79,682-536

69,134-3,467

Quartile 75

227,978

21,727

190,286

26,600Maximum

14,297,627

8,820,235

7,644,861

3,275,584

Note: The numbers in Table 1 are in million of yens. The
estimated value for FSOC presented here wasbased on coefficients obtained through REM
technique. To estimate FSOC I computed thedifference in market value induced by the
inclusion and the exclusion of FSOC.

4.2 FSOC and corporate performance
According to Lev and Radhakrishnan (2003),
the contribution of organizational capital isreflected in the firm performance (sales andearnings growth). Accordingly, it was conjectured
that firms building up higher stocks of FSOC would
enhance their corporate performance. Therefore, it
was hypothesized that different level of FSOC
stocks leads to substantial differences in corporate
performance.
Parametric (t-test) and nonparametric test (Mann-Whitney U test) were used to320examine differences on firms performance. Meansfor sales, EBITDA, and market value all scaled by
employee, and Tobin’s q were calculated for subsamples of firms sorted by distribution pattern(quartiles). The results suggest that regardless ofthe firm’s type (high /low technology) different
levels of FSOC stocks lead to different levels of
productivity, profitability and value. Difference
between higher (quartile 4) and lower (quartile 1)
FSOC stocks were significant at the 1% level.
These findings support the hypothesis thatdifferent levels of FSOC stocks explain differencesin firms’ corporate performance. It is remarkablethat there were no significant variations whencompared the results obtained through neither
different assessments procedures (REM/FEM) nor
the proxy for output (market value or sales) usedfrom which FSOC is estimated.

levels of mentioned assets relative to industry
competitors).
Similarly, the combinations of
FSOC- AD, and FSOC-RC were examined. We
could expect that the average sales/market value foreach group relative to the baseline case (high/high)differ (in the magnitude and also be negative in sign,
which should indicate that firms increasing both
assets have higher levels of either sales or market
value than competitors).
Table 3 Interactive effects (assessment of FSOC throughREM technique)
R&D Portfolio
M. Value
Sales

non-R&D Portfolio
M. Value
Sales

High-Low-0.14***-0.19***-0.23***-0.39***

Low-High-0.83***-0.57***-1.25***-0.91***

Low-Low-0.86***-0.65***-1.31***-1.11***

Table 2 Assessment of FSOC (assessment of FSOC

Adj R293.00%

95.30%

88.50%

92.30%

through REM technique)F statistic

2325***

3574***

617***

1192***

R&D Portfolio

Differences H-L

Low FSOC

High FSOC

t-testz-testSale/emp

52.36

126.516.00***

16.86***EBITDA/emp

4.46

9.52

13.91***

15.17***

MV/emp44.44

133.6020.25***

24.02***

Tobin's q

1.19

1.64

10.00***

9.82***

non-R&D Portfolio
Sale/emp

FSOC-PyE
High-HighFSOC-RI
High-High

Differences H-L

Low FSOC

High FSOC

t-testz-test74.43

320.668.00***

7.74***EBITDA/emp

3.04

36.85

7.03***

15.83***

MV/emp37.64

429.92

13.11***

18.59***

Tobin's q

1.15

1.39

5.37***

4.26***

High-Low

0.13***

0.16***

Low-High-0.68***-0.36***

Low-Low-0.70***-0.40***

Adj R293.00%

95.60%

F statistic

2322***

3774***

FSOC-AI
High-High

Note: t-test and z-test correspond to differences between
fourth-first and second-first quartile of FSOC
stocks. Mean values are in million yens, except
for Tobin's q, which is a ratio. *** indicate
significance at the 1% level.

R&D Portfolio
M. ValueSales

R&D Portfolio
M. Value
Sales

non-R&D Portfolio
M. Value
Sales

High-Low

0.19***

0.33***

0.19***

0.46***

Low-High-0.67***-0.34***-1.08***-0.54***

Low-Low-0.61***-0.19***-0.99***-0.44***

Adj R293.00%

95.60%

88.30%

92.40%

F statistic

2328***

3815***

607***

1211***

Notes: Results are based on FSOC stocks calculated as
the difference in market value by estimatesobtained through random effect model (REM).
Coefficient estimates are based on linear
regression with dependent variables market
value and sales. Positive (negative) stock andindex ratio bigger (smaller) than 1 are cut points
for high (low) FSOC and high (low) PyE, RI
and AI respectively. *** Significant at the 1%
level.

4.3 Interactive effects
Once FSOC growth was estimated, I attempted
to determine the interactive effect of changes in
FSOC stocks, in combination with changes in otherinvestments, like payroll per employee (PyE,
human capital), R&D (technology) and advertising(brand). It was hypothesized that increase in
FSOC stocks combined with increase in otherintangibles assets boost (reduce) sales growth.
Interactions among various combinations of
inputs were tested using regression analysis. A
group of interaction terms were added to thestarting model. For instance, to examine how
FSOC-PyE affect sales/market value, the fixed
effect estimator (Dit) was replaced by a set ofdummies variables. These set of dummies split
observations in four groups of firms (higher-lower

As shown in the upper part of the Table 3,
regardless the type of firms (R&D or non-R&D
performers) those which combine higher levels of
FSOC and human and social capital (baseline case)with similar levels of other investments are on
average, more valuable and have higher level ofsales than its competitors suggesting not only theimportance of FSOC but also human and social
capital.

321

Table 3 also indicates that the interaction
between RI and FSOC, keeping constant all otherinvestments, suggesting that higher levels of RI
investments are preferred over lower levels only
when the firm has negative stocks of FSOC. Whenthe firm has positive stocks of FSOC, lower levels
of RI are preferred. Together, the results suggestthat when R&D intensity exceeds a threshold,additional investments could be inefficient (forsimilar results, see Watanabe and Asgari, 2003).
Finally, the interactive effect between FSOC-AI
shows that firms with higher stocks of FSOC have apositive impact on output (value or sales) regardlessof the level of advertising intensity investments.
Investments on brand (advertising) above industry
average could not compensate the negative impactof lower levels of FSOC on output.
The associated effect between AI and FSOC
(higher/lower) is also remarkable. Lower levels of
AI investments were always preferred over thehigher. Similarly to previous results (interaction
between FSOC-R&D), it seems that an optimallevel of advertising expenditures exists, and once
reached, marginal increases in advertising have anegative impact on market value and sales.

of organizational capital and human and social
capital are more valuable and productive. This
result implies that managers have to consider build
up and enhance higher levels of organizational
capital first, and then reconsider all otherinvestments.
As predicted by the literature,enhancement of organizational capital is linked to
the reduction of opportunistic behavior. This
leads firms to reduce the social uncertainty(between the organization itself and its relationships,
which include employees, suppliers, customers andshareholders)andincreasethesystemtrustworthiness. Further, I conjecture that thosefirms that build up higher levels of organizational
capital, may benefit from higher levels of humancapital (more prepared people might be willing tobelong to the organization), social capital (system
reliability and less social uncertainty should reduce
employee turnover, hence increase social capital)
and brand (system reliability increase brandrecognition and positioning among customers,
suppliers, potential employees and investors).
References

5 Conclusions
This work contributes to the existing body ofknowledge in various aspects. Extending the works
of Lev and Radhakrishnahan (2003) and Sadowsky
and Ludewig (2003), this study build up amethodology by which organizational capital isestimated using two alternative econometrictechniques. The quantified value is derived fromtwo different measures of outputs, controlled for thesame inputs. As expected, the value of FSOC
among Japanese firms is significant when comparedeither to traditional inputs or outputs. Since most of
the FSOC stocks were clustered in the middle ofscales, and only few cases could be classified as
outliers, this is consistent with the presumption of
FSOC as a source of abnormal performances, due tothe lack of codification and uniqueness(difficultness of replication), which is in line withthe theory (Resource Based View).
On the other hand, the fact that 50% of thesample owns negative FSOC stocks should not beinterpreted as inability to create value; that is, firms
are not efficient in the use of their resources (whichis consistent with our assumption of whatorganizational capital is).
Third, evidence relative to the interactive effectof intangible investments suggests that the morereliable input is organizational capital, regardlessthe performance measure evaluated.
This study also has important implications for
management and competitive strategies. First,
results suggest that firms that build up higher levels

322

[1]

Lev, B., Radhakrishnan, S., 2003. The
Measurement of Firm-Specific Organization
Capital. NBER Working Paper No. 9581.
Cambridge, MA: National Bureau of
Economic Research (NBER).

[2]

Ramirez, P.G., Hachiya, T., 2006a. Measuring
Firm-Specific Organizational Capital and its
impact on Value and Productivity: Evidence
from Japan. Review of Pacific Basin Financial
Markets and Policies 9, 4, 549-575.

[3]

Ramirez, P.G., Hachiya, T., 2006b. How do
firm-specific organizational capital and otherintangible assets affects sales, value andproductivity? Evidence from Japanese firmlevel data. International Journal of Innovation
and Technology Management 3, 3, 1-18.

[4]

Sadowski,D.,
Ludewig,O.,
2003.
Organisational Capital: The Power of andEconomic Methaphor: Organisational Capitalin German Establishments. Discussion Paper
Series No. 2003/02. Institute of Labour Law
and Industrial Relations in the European
Community (IAAEG).

[5]

Watanabe, C., Asgari, B., 2003. Dynamic
interactions between assimilation capacity,
technology spillovers, sales and R&D
intensity -the case of electrical machineryindustry in Japan. Technovation 23, 15–34.

Stock Repurchase as a Leverage Adjustment Device
Min TENG
Department of Industrial Engineering and Management
Tokyo Institute of Technology
teng.m.aa@m.titech.ac.jp
1. Introduction
1(small)Previous studies have successfully discussed the financial behavior ofstock repurchase and document the potential motivations of it, likesignaling of undervaluation, takeover defense, dividend substitution, stock
options and capital structure adjustment. Less attention has been given to
motivation of leverage adjustment. Managers may weigh emergent
motivations against capital structure adjustment when they make decisionof repurchasing shares. The theory of capital structure adjustment may be(1)ln value(2)ln number

14.33714.413(3)ln value(4)ln number

14.333
14.541(5)ln value(6)ln number

13.74914.246(7)ln value(8)ln number

14.33614.333

not always consistent. It is expect to examine the motivation of capital
structure adjustment predicted by trade-off theory and to find out theevidences that firms are likely to neglect capital structure when they haveemergent motivations.

Deviation
2
3(middle)
4
Pannel A: Total sample
14.30414.262
14.20814.16714.16914.441Pannel B: DT=1
14.23714.33114.25514.11014.29314.515Pannel C: DC=1
13.69213.73813.69714.07414.12814.289Pannel D: DCash=1
14.40114.47014.02814.15614.20014.2425(large)difference
1-5
t-statistic

14.10314.5630.233 (2.092)**-0.150 (-1.359)

14.20314.7670.130 (0.847)-0.226 (-1.585)

13.72614.5590.023 (0.165)-0.313 (-2.226)**

14.10214.7980.234 (1.455)-0.465 (-2.998)***

4. Multivariate Regression Tests

2. Motivations of Stock Repurchases

Stock repurchase may be used as a device of leverage adjustment if theirdebt ratio is lower than target leverage. This relation between stock

Corporate management always has better information about their firms

repurchase and capital structure is directly tested by a basic model in whichthan outside investors and attempt to tell their private information to

stock repurchase is depended on a set of potential motivations. After that,outsiders and expect positive reaction from markets. Undervalued firms

emergent motivations of stock repurchase, undervaluation and takeover

may subject to the risk of being acquired and might undertake stock

threat, are taken into account, and other models are used to test hypotheses

repurchases to increase the acquisition price and lower the threat ofthat undervalued firms and firms with the threat of becoming takeover

becoming takeover targets. Firms retiring a large number of shares by stocktargets do not pay attention to capital structure and neglect the impact ofrepurchases increase their debt to equity ratio and achieve their target. Since

repurchase on leverage.

income tax rate is higher than capital gain tax rate, management may preferrepurchase over dividends. Stock options encourage managers to substitutestock repurchases for dividends because repurchases decrease the shares
outstanding.

Fig.2. the emergent motivation of signaling of undervaluation

Fig.1. the effect of stock repurchase on capital structure
Fig.3. the emergent motivation of takeover defense

3. Univariate Analysis

5. Conclusion

It is investigated whether firms use stock repurchases to adjust capital
structure and mitigate deviation between actual leverage and target leverage

This paper focuses on the notion of capital structure adjustment and also

predicted by trade-off theory by univariate tests. Five portfolios are formed

controls other motivations of stock repurchases. By testing the trade-off

based on deviation and compute the mean of stock repurchase in eachtheory of capital structure, this paper confirms that firms with leverage ratio

portfolio. t-statistic for the difference between small portfolio and largethat is below their targets have a tendency to undertake stock repurchases

portfolio is reported, which shows that hypotheses are partly supported.

and to mitigate deviation. This paper investigates real purpose of 2163 stock

Since the results are mixed, multivariate regressions are employed to makerepurchase announcement and finds that the theory of capital structure

them clear and test the relation between stock repurchase and deviation in

adjustment is not always consistent, and comparing to emergent motivations

next section.

of stock repurchases, capital structure adjustment is a secondary motivation.
Firms neglect the impact of stock repurchase on capital structure if they are

Table 1. the relation between repurchase and deviation

undervalued or have the threat of becoming takeover targets.

323

Research Report for the Fall Semester 2008
Min TENG*(HACHIYA Laboratory)*

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANBackground of my research
Stock repurchases experienced waves in Japan in recent 10 years. I investigatedopen-market stock repurchase announcement in Japan from fiscal year 1997 to 2006
and found that both the number and the value of stock repurchase were at muchhigher level in 2nd half period. Firms were able to hold more treasury stocks during 2nd
half period.
There are some reasons for increase in treasury stocks. One is a revise of Japan’scommercial code in October 2001. A system of treasury stocks with related new
institutions was introduced, which allows companies to acquire treasury stock,
regardless of the purpose of the acquisition, and to hold such shares without being
subject to any requirement for immediate redemption or disposition. It is necessary
for Japan, like the United States, to make active use of this system to activate themarket. Another important reason is increase in hostile takeover. The potential of
global competition is firing up the Japanese mergers and acquisitions market, as theJapanese government relaxes its restrictions. The increase in hostile takeover hascome on the back of foreign funds' rising investment in Japanese firms, as well as new
merger system allowing foreign companies to acquire Japanese firms more easily. It issaid that the existence of the threat of hostile takeovers serves the purpose of
motivating Japanese executives to increase business efficiency and corporate value, sothat Japanese companies can compete in the global market. It lead firms pay more
attention to corporate governance then before.
The current Japanese Corporate law allows companies to choose to either adopt theUnited States style of board structure or continue a traditional system. It is good togive companies freedom to choose a corporate governance structure. Japan has
adopted many features of the U.S. style of corporate governance in the last decade,which aims to maximize profits for shareholders. For instance, appointments ofoutside directors, granting stock options and repurchasing stocks now are quite
popular. But 10 years ago none of these was common to the Japanese economy.
Summary of my research
Why do firms repurchase their shares outstanding? I reviewed previous empiricalstudies and find that previous studies have successfully discussed this financial
behavior and document the potential motivations of stock repurchase, like signaling ofundervaluation, dividend substitution, takeover defense, stock options and capital
structure adjustment. Most of earlier empirical studies provide evidence in support oftheories that stock repurchase is effective tool of signaling of undervaluation,
dividend substitution and other motivations.
324

By focusing on capital structure adjustment of open-market stock repurchases, I
investigate the relative priority of motivations, especially signaling of undervaluationand takeover defense. According to the traditional theory of capital structure, thevalue of a firm consists of the unlevered value, present value of tax shield and present
value of financial distress cost. Firms have a tendency to move towards their optimal
debt ratio by balancing the tax and other benefits of debt against the costs of financial
distress as trade-off theory of capital structure predicts. Previous empirical studies ofleverage adjustment document that, in the long term, overleveraged firms are likely todecrease debt, and underleveraged firms tend to increase debt to equity ratio, in orderto achieve approximately optimal leverage. However, those previous studies do not
pay attention to corporate emergencies. Firms may take into account the effect ofstock repurchase on their leverage in advance but still pursue other effects, when they
confront emergencies, such as undervaluation and threat of becoming takeover targets.
I examine the relative priority of emergent motivations of stock repurchaseannouncements.
First, I directly test whether undervalued firms and firms confronting risk of being
acquired pay little attention to capital structure when they undertake stock repurchaseby frequency, and find that firms benchmark themselves to industry counterparts andneglect capital structure when they are undervalued or have high cash level.
Univariate analyses are used to further examine the relation between stock
repurchase and capital structure, in which I form five portfolios based on deviationand compare subsamples with low market-to-book ratio and high cash level to total
sample respectively. I find that stock repurchase undertaken by firms with low
market-to-book ratio or high cash level mitigates the effect of capital structure
adjustment.
I employ multivariate regression models to test the relation between stock
repurchase and deviation by control other effects. I develop the basic model andregress other eight models to examine if firms pay little attention to capital structure
when they are undervalued or subject to the threat of being acquired. By testingdeveloped models, I find that, in spite of deviation increase, undervalued firms
repurchase shares outstanding to correct the misevaluation, which mitigate the effectof stock repurchase on capital structure adjustment. Undervalued firms with high cash
level may have stronger threat of becoming takeover targets and undertake stock
repurchase. I also find those firms undertake stock repurchase to avoid being acquired
rather than to adjust capital structure and they pay little attention to increase inleverage.
To summarize, the evidence I develop supports the hypothesis that capital structure
adjustment is a secondary motivation comparing to emergent motivations of stock
repurchase. Firms repurchase shares outstanding to signal undervaluation or avoid
becoming takeover targets and pay little attention to the effect of stock repurchase on
capital structure, if they are undervalued or confront the threat of being acquired.
The limitation of my research is that I investigate stock repurchase announcements,
while firms do not always have to implement the announcements.

325

The History and Prospects of Bangladesh to India Natural Gas
Pipeline Project
Md. Mamunur Rashid (PhD Candidate)
Department of Industrial Engineering and Management

Tokyo Institute of Technology

mamun@m.titech.ac.jp

1. Introduction

When exports start, Bangladesh also could expect‘revenues and tax receipts of at least USD 3.7 billion over a
period of 20 years’. This works out to approximately USD
175 to USD 319 million per year.

This study explores problems in the case of
Bangladesh’s natural gas marketing, focusing on the
difficulties that the Union Oil of California (later
renamed as Unocal, and now as Chevron)encountered when it tried to build a pipeline in
Bangladesh to transport natural gas to India. Thiscase of Bangladesh’s natural gas exploration andconsumption may offer new insights into theutilization of natural resources in developing
countries.

Unocal’s experience of gas exploration and export Thailand,
Myanmar, Nigeria, Netherlands in particular bear lessons for
Bangladesh. It is also encouraging for the Bangladeshi gas
export. For example, in Nigeria, for example, has increased
its per capita income from USD 300 to USD 2,000 throughexporting oil and gas.

4. Natural Gas Pipeline Proposal

2. Unocal’s Operations in Bangladeshi Gas
Exploration and the Idea of Bangladesh India
Gas Pipeline

Unocal’s proposed plan included the construction of athirty inch diameter, 1,363 kilometer (847 mile) longpipeline with an initial capacity of 500 million cubic feet gas
per day of gas, from northeastern Bangladesh (from the
Unocal-developed gas field Bibiyana) to West Bengal andto New Delhi with an extension. It is expected that WorldBank Group, Asian Development Bank (ADB), the Oversea
Private Investment Corporation (OPIC), the US EXIM Bankand the Japan Bank for International Co-operation (JBIC)
would participate in the project as lenders and loan
guarantors.
The dilemma faced by the Bangladeshi government intaking a decision on gas export is a case of rather a strange
politicization in domestic politics. Both the parties when in
power tackle the issue tactically to consolidate their powerfrom local and international pressure. In their ruling termeach party supports gas export. But when it is out of power,
then it is no wonder the opposition parties becomes major
critic and oppose of gas export in Bangladesh. They havecaused numerous problems, such as protests and street riots.
As a result, Bangladesh has failed so far to create a common
ground for solving issues relating to natural gas export.

Unocal began its operations in Bangladesh in 1974 with ajoint-venture to develop an offshore gas field. In 1977,
Unocal discovered a gas reservoir at Kutubdia, the first
offshore gas field in Bangladesh. In 1998, Unocal
discovered the world-class Bibiyana field. Shortly
afterwards, Unocal announced discoveries of significant gas
reserves at the Jalalabad gas field located in block 13, and of
the Moulavi Bazar Field situated in block 14. Thus, largely
thanks to Unocal’s explorations and technologies,
Bangladesh came to be ranked among the world’s tophydrocarbon provinces with significant development
potential.
The export of gas by pipeline from Bangladesh to India is
an old issue. But the Bangladeshi government did not makea special effort to promote it because of political reasons. In
the 1990s, a strong lobby of foreign oil companies investingin petroleum sector in Bangladesh emerged in support of apipeline to India to transport gas. Unocal’s formal proposal
came in late 2001 officially that the proposed pipeline
would be 1,363 kilometer (847 mile) long pipeline from its
field at Bibiyana in Bangladesh to Delhi, through West
Bengal, Bihar and Uttar Paradesh, and linking up the HBJ
pipeline saying it could earn Bangladesh extra USD 500
million a year.

5. Conclusion
The case of Bangladesh-India pipeline project provides a
specific example of political difficulties that might appear innatural resource rich developing countries. If political parties
set aside their differences they may be able to find acommon ground. When the Bangladesh government choosesa sound export policy, it will also be easy to set up a neutral
agency to study the future of the pipeline program. Thissolution may be a way-out from the difficulties that are
peculiar to natural resource rich developing countries

3. The Economic Prospects of a
Bangladesh-India Pipeline and thePoliticization of the Pipeline Project and Gas
Export326

Energy Policy and Market Reforms in Japan for RA Report
Md. Mamunur Rashid**

Department of Industrial Engineering and Management
Tokyo Institute of Technology

This study aims to address potential impacts of growing reliance on natural gas as anenergy source, how they stimulate the trend towards reform of gas markets, and then anumber of issues that have arisen for the Japan’s policy makers to tackle. It also describes
the current structure of the gas marketing model and its history, and policies in eachmajor area that have been proposed to make the market more competitive.

1. Introduction
Japan has been promoting the use of natural gas,
which is abundant throughout the world and low inenvironmental impact. Japan itself has very limited
gas production. It relied on import for almost all of
its gas needs. Gas is imported through LNG. About
three-fifths of gas comes from Asian countries,
mainly APEC members, for example, Indonesia,
US, and non-APEC members Quarter, Oman etc.

Fig.1. Evolution of Japan’s LNG sources under long–term Contracts

327Japan’s LNG and pipeline network is owned andcontrolled by three kinds of firms: Regional Gas
Utilities, Electric Utilities and Domestic Gas
Development companies.
The Ministry of Economy, (figure2) Trade andIndustry (METI) regulates gas tariffs and pipeline
access through its office of national gas regulation.

Fig. 2. Main Players in Japan Gas Market
Source: IEEJ (2002).

is expected to play a vital role in achieving
energy security and climate change mitigationin Japan. The government’s long-term energy
supply and demand outlook projects a 30%
increase in nuclear power generation by
2010.Special measures for ensuring gas supply
security reflect such fundamental policies.

2. The history
2.1 Regulatory reform
Japan has initiated the reforms through two
amendments of the gas industry law, which has
regulated the gas industry since 1954. The first
regulatory reform was implemented in 1995. In theJapanese gas market, production is entirely
unbundled from transportation to distribution.
JAPEEX and TEIKOKU own gas pipelines but theirdomestic productions supply only a few percent off
the overall gas demand. The bulk of production isprovided by competing supplies abroad. With
respect to the bulk of gas transport system in Japan,
provision for third party access has been absent.
The urban heat energy subcommittee of METI’s
advisory committee for national resources
considered several proposals in 2002.

2.3 Gas market model and competition
In Japan electricity utilities have a strong
influence on the LNG market.
WHEN? Japan imported 54.5 million tons of LNG.
About 70% imported LNG was consumed byelectricity utilities for power generation and gas
utilities consumed the remaining 30%.Due to thelack of a nationwide gas distribution network, about
half of gas users in Japan purchase bottle LPG from
LPG dealers. Due to growing awareness of theenvironmental issues, gas utilities have shifted their
input material from LPG and coal-type gas to LNG.
In Japan LNG demand will increase steadily infuture. Energy prices in Japan are still highest
among the IEA member countries.
To remedy this, the government has launched newmarket reforms, with the process most advanced in
the oil sector, which has been fully liberalized.
Japan’s gas market would seem to fit most closely
the wholesale competition model. Instate of one
principal wholesale buyer of gas each region, there
are two: the franchised gas utility and thefranchised electric utility.

2.2 Security of gas supply in JapanThe government of Japan considers thatthe policy on security of gas supply as part ofits comprehensive energy security policy. Dueto the lack of its domestic energy resources,
and remote geological location, Japan strives toreduce its dependency on oil. Diversification ofenergy supply sources, and developing
domestic energy production including nuclear
power and renewable energies. Nuclear energy
328

Fig.3. Regional Market for Gas and Electricity inJapan
Source: MEITI Gas Market Division (2003).Governmentof Japan (2003).

Kanto, Kansai, Chubu and Kyushu. There is nogovernment policy for expansion of natural gas
networks to such areas as it has been judged
uneconomical. There are no links between thepipeline networks of the four major regional gas
utilities. Although Japan is the seventh biggest gas
consumer in the world, it has no integrated gas
transmission system.

At the same time, Japan’s market fit the retail orchoice competition model, at least with respect tolarge costumers, costumers. Both major industrial
firms and electric utilities have access to competing
suppliers on gas pipelines. There is a high degree ofvertical integration between gas and electric
markets in Japan.
The move will apply to both the retail andwholesale gas markets. However, the urban heat
energy sub committee laid out a timetable for
expanding choice of gas suppliers in the retailmarket. It recommended that retail choice beintroduced for industrial and commercial firms.

4. Conclusions
In the light of SIMOT perspectives, this casedemonstrates that a model is not a static thing but a
dynamic process. The model here responded tochanging preferences in energy market andinstitutional innovations in natural gas sector.
Furthermore, the business policies and institutionaland regulatory frameworks of individual economies
play a significant part in shaping a gas marketingmodel.

2.4 Gas transportation infrastructure
The gas distribution network in Japan is welldeveloped in densely inhabited districts such as329

References[1]

IEA(International
EnergyAgency),Developing China’s Natural as Market: The
Energy Policy Changes (France: OECD/IEA,
2002), 310-312.

[2]

APERC (Asia Pacific Energy ResearchCenter), “Natural Gas Market Reform in the
APEC Region.” Institute of Energy Economics,(2003).

[3]

Historical data for 1980 and 1990 werecomplied by the international Energy Agency(IEA). Projection for 2000, 20101st 2020 weremade by APERC(Data from APERC 2002).

[4]

Institute of Energy Economics , Japan(2002).

[5]

Government of Japan and Government of theUnited States (2002).

[6]

MEITI (The Ministry of Economy, Trade andIndustry) as Market Division 2003.

[7]

APEC Energy Working Group (2002), page
119.

[8]

IEA (International Energy Agency (1997)
pages 11.19-21, IEA (2002a) pages iii.30-32.

[9]Miyamoto (2002), pages 132-3,153,172 METI
(2003).

[10] MEITI Gas Market Division (2003) and METI
(2003)

330

Is Natural Gas a Blessing for Bangladesh?
Md. Mamunur Rashid**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-527 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANmamun@me.titech.ac.jp
It looks at the dilemma of natural gas facing Bangladesh. First, it defines the problem anddebates whether Bangladesh should export its gas and use revenues in poverty relief and otherdevelopment program. Second, it offers a brief history of Bangladeshi gas exploration and export
potential. Three, it assesses, the pros and cons of the debate. Finally, concludes that there is an urgent
for radical reforms in the Bangladeshi gas industry and institutions from exploration to marketing.
reserves. Its deep water natural gas potential, which
remains to be assessed, holds great hopes for evenlarger gas reserves in the future. Many are now
convinced that natural gas is a crucial window ofopportunity for the country in the near future. They
believe that natural gas will become the motor of
Bangladesh industrial development, modernization
program. For example, they hope that gas revenues
will help to reform and energize economy andindustry, and reduce poverty.
owever, this promise is partly overshadowed by
the fact that there is no agreement on the size of gas
reserves. This matter is, in fact, closely associatedwith the issue of gas export debate. Because antiexport groups cite low figures while the pro-export
individuals and groups cite higher figures, each inan effort to support their respective arguments.

1. Introduction
Bangladesh is now believed to possess vast
reserves of natural gas. With its current gas
production far exceeding its domestic demand, thishas generated a hot public debate: Should
Bangladesh sell some of its surplus gas reserves tovitalize its weak economy and reduce poverty? Orshould Bangladesh conserve its gas reserves athome for long-term sustainable development? Thus,
selling or not selling its natural gas is a major
dilemma for Bangladesh. Even if the country finallyallows gas export, it will have to overcome theanticipated problems such as the Resource
Curse.This report hopes to articulate this dilemma.
2. History of Exploration in Bangladesh andexport Potential

2.3 Is Bangladesh Floating on Gas?

2.1 Natural Gas Exploration in Bangladesh
Geological exploration in what came to be
Bangladesh in the Indian Subcontinent commenced
in the middle of 19th century by British geologists;then continued under Pakistani rule by the Shell oil
company. When Bangladesh finally became
independent in 1971, it set up a state oil and gas
company, Petrobangla. Under Production Sharing
Contracts, Petrobangla engaged such international
companies as Nippon Oil and Unocal Oil.
From1985 to 1989 Petrobangla in collaboration
with the World Bank divided all the potential
natural gas areas into 23 sections. Although
Petrobangla was able to make some initial successes,
it soon became less and less productive. In the mid
1990s, the Bangladeshi government took steps toliberalize its gas sector and exploration policies.
Then major international Oil Companies (IOCs)
came to Bangladesh, and began to explore gas
fields. In fact, more than 90% of Bangladeshi
current gas production comes from the fields
discovered by foreign companies.
2.2 The Promise of Natural Gas
With its 22 gas fields already dicovered,
Bangladesh has a very high potential for further gas

331

According to Petrobangla and US Geological
Survey, Bangladesh’s total estimate of gas reserves
ranges from minimum of 37.3 Tcf to maximum of
94.6 Tcf. Foreign oil companies, especially US andEuropean energy companies –who have invested
heavily in the country give even higher numbers.
They have spelt out reserve figures like 80 Tcf, 100
Tcf, and 150 Tcf. The Shell Oil estimates that
Bangladeshi natural gas potential is as big as that ofIndonesia.In spite of this partly politicallymotivated confusion, it is almost certain that
Bangladesh has a great potential to become one of
the world’s natural gas-rich countries in the near
future.
2.4 Domestic Gas Surplus and Pressure to
Export
The large new gas reserves in Bangladesh
created a problem in the face of limited local
demand. Foreign energy firms which discovered
and operated gas fields became nervous.Theycould
not recover their investments, because currently gas
export is not allowed or too limited. Together withinternational organizations, governments, think tankinstitutions, oil lobbies, foreign companies (Unocal
and Shell), and senior politicians (including theformer US president Bill Clinton, and the current
vice president Dick Cheney) have put pressure on
the Bangladeshi government to allow substantial
gas exports especially by pipelines. Influential
economists, diplomats of foreign missions, businessleaders, bureaucrats, and major donor agencies havemade a similar call. Behind this pressure, on one
hand, there is a desire to make a profit, on the other,genuine desire to help the country.

demands. But this is the cost of development.
Although, gas export may not.

3.5. Dutch Disease is Curable
The Dutch Disease is still a major danger,
especially for developing countries with newly
discovered natural resources, such as Bangladeshwith its natural gas.

4. Conclusions

3. Should Bangladesh Sell Natural Gas?

The issue of natural gas in Bangladesh
illustrates a complex relationship between
institutions,governments,local and international
companies and civil institutions. It shows that there
is a dynamic relationship between the local andinternational institutions. In this case, there areinteraction among institutional players, and willaffect innovations in terms of gas exploration,
pipeline development. This is similar to therelationship between innovations and institutions in
SIMOT. Natural gas export and the revenues it may
generate to transform industry co-evolve. In futureadequate institutional capacity should be built in
Bangladesh Petroleum Exploration and Production
Company for conducting more exploration anddevelopment of natural gas. Appropriate attention
should be given to the development transporting
natural gas through pipelines. Some issues andpotential barriers still exist that need to be solved.
Finally, all possible factors such as institutional,
technological, and legal should take into account toensure efficient use of export.

In Bangladesh the export issue has divided thecountry into two camps, often politically oriented:
one that favors it, and the other that opposes it.
3.1 Supporters arguments:
There are several arguments. Here I will
mention only a few.
1).It will stimulate inflow of foreign direct
investment. Most of gas rich countries like Nigeria
and Bolivia have attracted FDI.

3.2. Opponents and critics augments:
Again, there are many arguments. Here I
mention only some.
1). It is better for Bangladesh to develop, control
and manage its own natural resources.

3.3. A Momentous Issue for Bangladesh:Should it Sell Gas?
The fact that gas export question has beenhighly politicized is, perhaps, the single mostserious obstacle. Local political parties and interest
groups have simply exploited the gas export issue
for their political ambitions. Bolivia, which has vast
natural gas reserves and has grappled with thequestion for decades, has recently decided in areferendum to allow gas exports. It is uncertain if
Bangladesh will follow suit, but it certainly does
not have the luxury of waiting for decades.

References[1]

Petrobangla, “Exploration Opportunity in
Bangladesh,” Petrobangla, Ministry of Energy
andMineral Resources,(Dhaka), February
2000.

[2]

M.A. Maroof Khan, “Oil and Gas prospects
in Bangladesh,” in Khalilur Rahman
Chowdhury et al. (edited), Bangladesh
Mineral Exploration and Development
Corporation (Dhaka: Bangladesh GeologicalSociety, 1975), 6-10.

[3]Mark Jacard, Mujibur Rahman Khan, andJohn Richards, Natural Gas Option for
Bangladesh. (Dhaka: Centre for Policy
Research, IBUAT-International University ofBusiness, Agriculture and Technology, winter(2000), 1-60.

[4]Joseph E. Stiglitz, (a) Globalization and its
Discontents (New York: W.W. Norton &Company 2002).Joseph Stiglitz, (b) “We Can
Now Cure Dutch Disease” the Guardian, (UK)
August 18, 2004.

3.4. Is gas Export simply an Option for
Bangladesh
In spite of its assumed drawbacks, gas export
for Bangladesh is not simply an option, but anecessity, especially, when the country’s mostpressing problem, poverty is taken into account. Itis perhaps the only way out of the Vicious Circle ofpoverty and underdevelopment. On the contrary to
the claims by its critics, gas export will notnecessarily make the country more dependent. In
fact, it may give Bangladesh a stronger voice inshaping and controlling its own economy. There is
no doubt that foreign investors could easily exploit
their financial control of raw materials for politicaland economic advantages. Bangladesh needing theirtechnological and financial assistance, Bangladesh
will have to give in to at least some of their332

Bangladesh’s Natural Gas Export Potential
Md. Mamunur Rashid
Department of Industrial Engineering and Management
Tokyo Institute of Technology
The natural gas potential of a country is a rough estimation of its undiscovered gas reserve, in
addition to its discovered gas reserve. A most pressing problem facing Bangladesh today is the lack of
a complete assessment of its full gas reserve potential. The issue of gas resource potential in
Bangladesh illustrates a complex relationship among governments, local and international companies,
and financial institutions. The interaction among these institutional players has effected innovations in
gas industry, gas estimation, gas export and the pipeline development for gas export.

big gap between the demand for gas and its supply
and production. Gas production has been exceeding
the local demand. This partly hindered the more
exploration efforts. At present, total Bangladesh gas
resource base is over 60 trillion cubic feet. This
resource base covers an area of 207,000 square km
and with only 65 exploratory wells drilled to date.
At the same time, the country ranks as one of theworld’smostsignificant,under-evaluatedhydrocarbon regions, while its exploration successrate is about 35%, nearly triple of the world
standard. Furthermore, Bangladesh’s deepwater gas
potential is still not included in the current known
resource base.

I. Introduction
With the discovery of 24 gas fields and 1
oilfield, Bangladesh promises a very high potential
for further natural gas reserves. The western partand offshore areas are relatively unexplored. Only
limited seismic and drilling have been done there.
An overview of the result of the various recent
studies carried in deep-water of Bay of Bengal
Bangladesh to the occurrence of natural gas andtheir potential supports this expectation. Geologicalsurveys show that the Bay of Bengal is rich in oil
and gas. As a result, several foreign oil giants
including Japan have expressed their interest in
explorations in the region. Bangladesh’s unexplored
deep waters hold great hopes for further gas
reserves. Besides natural gas exploration andreserve extraction and intensification efforts are notlimited to offshore or to onshore areas, but they aim
to improve the efficiency of reservoir, technologies
and recovery techniques. This in turn led to theintensification and expansion of

2.2 Present Bangladeshi reserve may meetdomestic demand for several decades
Bangladesh is well known in internationalenergy markets for its potential for large natural gas
reserves. The current recoverable reserve of gas isthus sufficient to meet Bangladeshi domestic
demand for 35–40 years at the current consumption
rate. Even with rapid growth in demand of about 8–
10 percent per annum, the proven reserves areadequate for the next 15–20 years. Furthermore,according to some estimates, Bangladesh has
substantially larger gas reserves, enough to makethe country a major gas producer as well as supplierto the potentially vast external markets.
A recent assessment of Bangladesh’s natural
gas resources in the large, lightly explored GangesBrahmaputra delta by a team of scientists andengineers from Petrobangla and the US Geological
Survey resulted in an estimate (mean) of about the32.1 TCF of technically recoverable previously
undiscovered natural gas. This estimate assumes
active exploration for natural gas for the next 30
years, and does not include the potential for gas insmall fields, in the large deep-water portion of the

exploration efforts and reservoir technique forfinding new potential of natural gas.
Besides natural gas exploration and reserve
extraction and intensification efforts are not limited
to offshore or to onshore areas, but they aim to
improve the efficiency of reservoir, technologies
and recovery techniques.
2. Bangladesh’s Gas Reserve, debate, and survey
report2.1 Current total gas reserve
Bangladesh has been producing natural gas
for more than three decades. However, all its major
fields are underdeveloped and their potential has
not been properly assessed. Presently, there exists a

333

Bengal fan, or for field growth of discovered andpotential undiscovered natural gas fields (USGeological Survey– Petrobangla, 2001).
2.3 Gas reserves are not static
Reserve estimation is very important for theproper planning of the energy sector. However, thereserve estimation is a dynamic process. The
reserve of a gas field needs to be reassessed by upto date techniques and technologies, and production,and development activities. Technically, reserves
include both proven reserves and non provenreserves. Several different reserve classification
systems are in use by different organizations, as
preferred for operational reasons. In June 2002, theNational Committee for Gas Demand and Reserve
concluded in its report that the initial gas reserves in
22 gas fields of the country is between 16.64 and20.42 trillion cubic feet (TCF). Two more gas fields
were discovered in 2004 and 2005. Their reserves
are yet to be estimated (Imam, 2005). According toPetrobangla and US Geological Survey,
Bangladesh’s total estimate of gas reserves ranges
from minimum of 37.3 TCF to maximum of 94.6
TCF (Unocal Corporation, 2000).
2.4 Debate and discussion of pipeline gas export
Up until recently, debate and discussion ofpipeline gas export issues in Bangladesh has been
confined to mainly proven gas reserves. The
question of reserves is a controversial issue for thecountry, largely due to the uncertainty involved in
the gas reserve calculations. Reserves can not bemeasured exactly but only estimated.
2.5 Petrobangla and the U.S geological survey
ReportA report prepared jointly by Petrobangla andthe U.S geological survey in 2001, shows
Bangladeshi gas reserves as high as 65 TCF or as
low as 8.4 TCF. However, foreign oil companies,
especially US and European energy companies who
have invested heavily in the country give evenhigher estimation. The Shell Oil estimates that
Bangladeshi natural gas potential is as big as that ofIndonesia. Recently, China values Bangladesh for
its immense natural gas reserves of 60 TCF, whichrivals that of Indonesia. The highest figure would
exceed the combined reserves of India and Pakistan,which are about 55 TCF and would permit the
supply of consideration amounts of natural gas toEastern India.

Bangladesh’s gas fields have been discovered anddeveloped mainly with a little demand, with limited
infrastructure and low prices, and without applying
advanced technologies. The new technologies such
as 3–D seismic surveys, compression, and effective
management are likely to increase these sums
greatly. (The 3–D seismic survey provides a moreaccurate reserve assessment than 2–D seismic
surveys). For example, an initial 3–D seismic
survey by Unocal at the Bibiyana field resulted in a
10% increase there, and it is likely to rise by 50%.
According to Unocal by using this technology theproven reserve may be double in Bangladesh.
3.2. Science and Technology Infrastructure for
Expanding Natural Gas Reserves
Oil and gas sector is a capital, technology,
and expertise intensive sector. Bangladesh is
suffering from especially the lack of experienced
staff trained in geology, geophysics, and drilling.
This shortage is reflected in petroleum exploration.
Bangladesh initially received help from the Soviet
Union in geological and drilling activities startingin 1972. Under the technical aid agreement withGermany (West), the Prakla-Seismic, a German
Geophysical Contractor, began digital seismic
exploration surveys in co-operation withPetrobangla in some areas of Bangladesh in 1977.
A reconnaissance aeromagnetic survey was
carried out over whole of Bangladesh by a US
company,
STANVAC.
Later
exploration
department of Petrobangla started gravity survey indifferent parts of the country. The US Departmentof Energy has taken initiative for technologicalassistance and capacity building in the energy
sector in Bangladesh.
3.3 Gas Production and Domestic Market
Constrains
At present Bangladesh gas production isconcentrated in the hands of a small number ofsuppliers. The foreign oil companies produce aquarter of total production. Cairn Energy produces
16% of the total while Unocal accounts for theremaining 9%. The rest is produced by the two
Petrobangla firms, Bangladesh Gas Fields Company
Limited and Sylhet Gas Fields Limited (55% and
20% respectively). Total production has on averageincreased by 7.1% per year during the last decadeand daily production is nearly 900 million cubicfeet. According to a demand forecast for the
Bangladesh gas market by Wood Mackenzie: theBangladesh gas market will be oversupplied for the
next five years.

3. 3–D seismic surveys
3.1 New technologies such as 3–D seismic
surveys
Typically, 60–90% of the gas initially inplace is recoverable from the fields. Most of the

4. Conclusions
Bangladesh has a high potential for
additional natural gas reserve. Bangladesh belongs

334

Environmental Sociology at the University of
Wisconsin, Eau Claire. He specializes inresource-

to one of the largest delta basins of the world;
therefore its natural gas prospect may becomparable to other delta basin of the world such as
Niger Delta basin. Since the exploration for oil andgas in Bangladesh began British colonial period late
19th century, only 64 exploration wells have been
drilled in the country within an area of 207,000 sq.
km. This means that Bangladesh is one of theleast explored countries in the world. Manycompanies and institutions have attempted to assess
its natural gas potential, but they have come up withdifferent figures. In particular, there are vastdifferences between estimation of natural gas
potential by local and foreign companies. The factthat reliable natural gas estimation has so far beenlacking in Bangladesh is a major problem for its
export policy. The case of Bangladesh natural gas
reserve estimation and export shows a complex
interplay of several institutions, including domestic
and international legislations. It shows that there isa dynamic relationship between local andinternational institutions.

[7]

References[1]

Chowdhury, K. R. et al. (edited) (1980),‘Petroleum and Mineral Resources ofBangladesh’, Dhaka: Geological Survey ofBangladesh, pp. 30-34.

[2]

US Geological Survey-Petrobangla (2001),‘US.
Geological
SurveyPetrobangla
Cooperativeof
undiscovered natural gas
resources of Bangladesh’, Petroleum System
and Related Geologic Studies in Region 8,
South Asia (edited, C.J. Wandrey), ‘US
Geological Survey Bulletin 2208-A’, US
Department of Interior, US Geological Survey.

[3]

M.A. Maroof Khan, “Oil and Gas prospects
in Bangladesh,” in Khalilur Rahman
Chowdhury et al. (edited), Bangladesh
Mineral Exploration and Development
Corporation (Dhaka: Bangladesh GeologicalSociety, 1975), 6-10.

[4]Murshid A.K.S. and Arne Wiig (2001), ‘A
Review of Development Trends in the Energy
Sector of Bangladesh: CMI Report Chr’,
Michelson Institute Development Studies,
Norway.
Exploration and Development
Corporation’, Dhaka: Bangladesh GeologicalSociety, pp. 6-10.

[5]]Imam, B. (2005), ‘Energy Resources ofBangladesh’, Dhaka: University Grand’s
Commission of Bangladesh, pp: 38- 85.

[6]

Niazi, T. (2005), ‘China, India and the Futureof South Asia’, Tarique Niazi teaches.

335

Unocal Corporation (2000), ‘Bangladesh
Natural Gas pipeline Project’, Pipeline
Development Plan, Dhaka.

Enhancing Oil and Gas Exploration in Bangladesh
Md. Mamunur Rashid**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-51 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANmamun@me.titech.ac.jp
Natural Gas Exploration and development is a dynamic issue. A successful gas
exploration venture continues re-evaluation of law, policies, contracts, join collaboration
work. Bangladesh has made several policy changes including legislative and contractual
frameworks. It has also offered competitive incentives to encourage foreign participation.
For example, the promulgation of petroleum act 1974 and later policy changes led to aconsiderable increased exploration activities. Exploration activities co-evolved with several
national and international legislations and technology and innovations. This paper gives
an overview of Bangladesh’s exploration history reveals development strategies anddiscusses the current situation.

1. Introduction
After becoming an independent state in 1971,
Bangladesh nationalized its gas reserves, andestablished a state oil and gas company,
Petrobangla. Although Petrobangla was able to
make some initial successes, it soon became lessand less productive. Petroleum Act, 1974 opened
the opportunity for foreign oil companies to explore,
develop and produce oil and gas under Production
Sharing Contracts (PSCs). But the early exploration
was not successful. The economic value of natural
gas a commercial commodity was first realized in
the 1980, following the effect of the Arab oil
embargo of 1973-1974, which proved the strategic
value of oil. This had a huge impact on natural gas
as an alternative energy source. In addition,
environmental concerns and the quest for cleaner
energy made gas a popular choice. Oil and gas
sector is a capital, technology, and expertise
intensive sector.
From 1980 to 1990,
Petrobangla’s exploration in the offshore area
yielded very little. It suffered from especially thelack of experienced staff trained in geology,
geophysics, and drilling and financial capabilities.
In the mid 1990s, the government opened gas sector
to private ownership, and encouraged foreigncompanies to invest in oil and gas exploration.
Innovative measures were introduced in this period
to reduce the risk for the private investors. One
measure was Petrobangla’s partnership in these
exploration ventures. As a result, success in oil
and gas discoveries has come in cycles. During
this period all of the known major fields in
Bangladesh were identified. From 1995 to 2005
mostly foreign energy companies discovered a large
number of gas fields, and Bangladeshi gas reserve
expanded exponentially. In fact, more than 90% of

336

Bangladeshi current gas production comes fromfields discovered by foreign companies. Presently
there are more than 40 foreign energy firms
operating in the country.
2. The exploration history and Development
2.1 Petroleum Act 1974
Petroleum Act 1974 was promulgated in 1974
and came in force in August 1974 to provide legal
framework for oil and gas exploration, development,
exploitation, production, processing, refining andmarketingofpetroleumproducts.
Afterpromulgation of this act Bangladesh government
found favorable conditions to enter into petroleum
agreements with any person or company for oil andgas exploration and development. In the mid 1980s
more and more industries were converted to gas in
Bangladesh. As a result, the demand rose
dramatically. To increase the exploration andproductivity, Bangladesh introduced a new
petroleum policy in 1993, and a model of PSCs. It
helped open the door to foreign participation innatural gas exploration (Tamim, 2003).
2.2 IOCs and Local involvement
The foreign Company’s played a crucial role ingas exploration in Bangladesh. Most of the worldleading oil and gas companies are now represented
in Bangladesh. These companies include: Unocal
Shell, Cairn Energy, Rexwood, Texaco, Chevron,
Enron, Halliburton, UMC, British Petroleum, Mobil,
Tullow Oil, Maersk Oil and Total. They discovered
13 gas fields having a total gas initially in place(GIIP) of 22.2 trillion cubic feet (TCF). Theirfinds have added approximately 14 TCF in total
recoverable gas reserves. Petrobangla had
discovered 11 fields with have a total of GIIP of 2.1

TCF. This is a notable achievement as Petrobangla
has discovered a total recoverable gas reserve of
1.47 TCF. Currently, there are several big IOCs
operating in Bangladesh such as Unocal Oil, Cairn
Energy, Tullow, Texaco, Chevron, and Niko Oil.
There are also a few Australian companies that are(or have been) active in the Bangladesh oil and gas
industry.
In the preliminary stage, Petrobangla, with theassistance of the Soviet Union, conducted generally
low risk exploration, and initially made somesuccessful discoveries. But by 1987, this state
corporation began to run into problems and becomeless productive, if not defunct.
Excessive
bureaucracy in decision making too createddeficiencies that cost Petobangla time and money.
Furthermore, Petrobangla appeared unwilling to
introduce new technologies made available byforeign entities to increase its productivity. Other
national oil companies such as Petronas (Malaysia),
CNPC (China), and Petrobras (Brazil) havebenefited from imported technologies gained
through active participation in IOCs andinternational service companies (Coleman, 2004).
To date, Petrobangla has not taken advantage ofoutside resources, and its natural gas exploration
has stagnated as a result. Today, Petrobangla’s
financial status is precarious as it is not earning
sufficient capital to pay for the development of its
gas fields (CSIS, 2000).

Source: Murshid A.K.S. and Arne Wiig (2001), ‘A
Review of Development Trends in the Energy Sector of
Bangladesh: CMI Report Chr’, Michelson Institute
Development Studies, Norway.

The main investment costs in the natural gas sector
are related to the construction of the production
facilities and pipeline transport. In Bangladesh thegas sector is controlled by Petrobangla. Throughits nine subsidiaries, Petrobangla is involved in all
stages from exploration to the distribution of gas.
The functions in the supply chain are therefore
vertically integrated or bundle between companies
in the same group. In addition to Petrobangla, there
are two foreign companies (Cairn and Unocal)
produced natural gas in Bangladesh. There are also
some local and foreign energy-servicing firms
which have located themselves in Bangladesh inorder to service the gas production industry.
3.2 FDI and Human Resource Development
The IOCs in energy sector have since 1993
invested at least $600 million in natural gas
exploration and production sector, resulting in newgas reserves. According to an estimate (World Bank
1999), the inflows of FDI into gas and power
sectors of Bangladesh amounted to
US$635
million and US$381 million respectively during theperiod 1994/95 through 1998/99.
The total
inflows of FDI into the country were estimated 181
million US$ for the same period. In other words,
the combined share of gas and power sectors intotal FDI was about 60% for the mentioned period.
According to the United Nations Conference on
Trade Development (UNCTAD) World Investment
Report 2002 total foreign direct investment to
Bangladesh from 1997 to 2001 was US$865 million.
During the same 5-year period, FDI to India
totaled over $14 billion, while Pakistan and Sri
Lanka attracted FDI totaling US$2.4 billion and
US$1.2 billion respectively. The current stock offoreign investment in Bangladesh is totaling $2.2
billion.

3. Current situation
3.1 Actors: Petrobangla and IOCs
The supply chain in the gas sector can bedivided into six phases from exploration of gas toits distribution to the final consumer. Whiletransmission and distribution are downstream
activities, the other four activities are so-called
upstream activities. The following table 1 shows thedifferent actors involved in each stage.
Functions
Exploration(logging,seismic
surveyanddwelling)
Engineeringofaproduction facility(platform)

Actors Involved
Foreignoilcompanies
andPeobangla
Foreignoilcompanies
andPeobangla
Construction of production Foreignoilfacilities
companies
andPeobangla
Production
Petobangla
andForeignoilcompanies
Transmission
Petobangla
Distribution
Petobangla

3.3 ADB Support
The assistance of the Asian Development Bank
(ADB) since 1975 has been instrumental inenhancing gas production and upgrading its
transmission and distribution capacity. More
importantly, ADB helped the Bangladeshi
government to undertake reforms in energy sector
restructuring, tariff rationalization and privatization.
ADB is now shifting the focus of its assistance togas transportation, distribution, and utilization(Murshid and ArneWiig, 2001). This includes
supporting policy and institutional reforms forfacilitating private sector participation in these areas.

337

The major policy issues being addressed by ADB
are (i) enactment of the Gas Act for regulation ofdownstream operation, (ii) operational autonomy tothe sector entities, (iii) introduction of a rationaltariff structure, (iv) private sector participation in
downstream operation, and (v) limited gas export
through pipeline to ensure a market for theinternational oil companies and to generate theforeign exchange necessary for the development of
the sector. ADB is now helping with a project topromote Bangladesh’s economic growth and,protect the environment, through a technicalassistance grant of about half a million
US$ annually (ADB, 2001).

multidimensional, and co-evolutionary structure.
The concept of co-evolution developed by
Prof. Chihiro Watanabe and SIMOT programprovides a very useful tool for analyzing thisstructure. It is also akin to what Franco Malerba, abusiness management scholar, recently identified in
his sectoral system of innovation. A sectoral
innovation or technological change in general isaffected by three main factors: knowledge andtechnologies, actors and networks, and institutions(Malerba, 2004). Noting that general or horizontal
policies may differ dramatically across sectors,
Malerba suggests that different policy measures
may be needed for different sectors. This idea ofsectoral innovation system thus offers a new way tolook at gas exploration, reserve estimation, and gas
export, and to the whole energy sector in
Bangladesh.

3.4 Gas Production and Domestic Market
Constrains
At present Bangladesh gas production isconcentrated in the hands a small number ofsuppliers; three national and two foreign oil
companies. The foreign oil companies produce aquarter of total production. Cairn Energy produces
16% of the total while Unocal accounts for theremaining 9%. The rest is produced by the two
Petrobangla firms, Bangladesh Gas Fields Company
Limited and Sylhet Gas Fields Limited (55% and
20% respectively). Total production has on averageincreased by 7.1% per year during the last decadeand daily production is nearly 900 million cubicfeet in 2000. The current production potential isaround 1,362 million cubic feet per day, and is
expected to rise to about 1,900 million cubic feetgas per day (MMCFD) by 2015 (Imam, 2005). It
is thus likely that Bangladesh will continue to
produce an excess supply even under most
optimistic domestic demand projections. This
makes exporting some of the gas an attractive
option (Murshid and Arne Wiig, 2001).

References[1]

Imam, B. (2005), ‘Energy Resources of Bangladesh’,Dhaka: University Grand’s
Commission of
Bangladesh, pp: 38- 85.
[2]Petrobangla, (2000), ‘Exploration Opportunity in
Bangladesh’, Petrobangla, Ministry of Energy andMineral Resources, (Dhaka), February, 1-44.
[3]
Tamim. M.‘Policies and Priorities in Bangladesh Gas
Sector Planning,’ Energy for Sustainable Development,
Volume 7, No.2(June 2003): 57-65.
[4]Coleman, R. T. (2004), ‘Natural Gas Utilization in
Bangladesh: Trends in the Fertilizer and Power
Industries’, American International School/Dhaka –Senior Project.
[5]
CSIS (Centre for Strategic and International Studies,(2000), ‘Energy in Bangladesh: Step by Step’.
[6]
World Bank (2000/2001), ‘World Development Report:
Attacking Poverty’, Selected World Development.
[7]
United Nations (2000), ‘An Investment Guide to
Bangladesh:
Opportunities
andConditions:International Chamber of Commerce the Word Business
Organization.
[8]
ADB (2001), ‘Economic Update Bangladesh’,
Bangladesh Resident Mission Asian Development Bank
Website: www. adbbrm@adb.org[9]Murshid A.K.S. and Arne Wiig (2001), ‘A Review ofDevelopment Trends in the Energy Sector of
Bangladesh: CMI Report Chr’, Michelson Institute
Development Studies, Norway.
[10] Malerba, F. (2004), ‘Sectoral Systems of Innovation:
Concepts, Issues and Analyses of Six Major Sectors in
Europe,’ Cambridge University Press.
[11] US Geological Survey-Petrobangla (2001), ‘US.
Geological
Survey-Petrobangla
Cooperativeof
undiscovered natural gas resources of Bangladesh’,
Petroleum System and Related Geologic Studies inRegion 8, South Asia (edited, C.J. Wandrey), ‘US
Geological Survey Bulletin 2208-A’, US Department ofInterior, US Geological Survey.

4. Conclusions
The issue of natural gas exploration and its
export potential in Bangladesh shows that there is acomplex relationship among natural gas explorationand distribution technologies, institutions governments, financial, legal, donor and civil
institutions, lobbies-, and local and foreigncompanies. Petroleum act 1974, urged thegovernment’s to enter into agreements with foreigncompanies. Foreign companies began to find afavorable environment in Bangladesh they
discovered several gas fields.
Drilling and operating a gas field, ex, involves
several countries, national and foreign companies,
technologies, management skills, and the support ofdomestic and foreign institutions. This shows thatnatural gas sector in Bangladesh has a dynamic,

338

Exploration and Supply of Natural Gas in India
Md. Mamunur Rashid
Department of Industrial Engineering and Management Tokyo Institute of Technology
mamun@me.titech.ac.jp
Indigenous energy supply base in India is too small to meet the country’s energy
needs. The Indian government has developed a four–pronged strategy in order to copewith energy demand. The first strategy encourages the exploration of natural gas by local
and foreign participation. Second is importing natural gas from various places in the formof LNG or through pipelines. The third is maintaining special petroleum reserves in order
to cope with a sudden energy crisis. Fourth aims at the production and development of
non-conventional hydrocarbon like Hydrates and Coal Bed Methane (CBM) in near
future. These four strategies co-evolved together. Their relationship is a similar to
institutional based framework that is promoted in SIMOT program.
India

1. Introduction
has come in cycles. There have been brilliant

In the 1970s all of the known major fields in
India were identified, in many cases theirdiscoveries such as the Bombay High and otherdevelopment occurred much later. There have been

western offshore fields. By and large, exploration

few important finds in the last decade. However

has been in the hands of National Oil Companies

33% of the total 3.14 million sq.km sedimentary(NOCs)-

area of the country has been explored upto

Ltd,(ONGC) and Oil India Limited (OIL), being

moderate level. The three main oil and gas

commercial organizations, their strategy has been

producing basins in India, the western offshore

to concentrate in areas near producing fields. Thereregion, the Cambay basin in Gujarat, and a Upperare 26 sedimentary basins in India including six

Assam region, are in the mature phase ofbasins that have been moderately well explored.

exploration. The more recently discovered fields of(The major basins are found along the east and west

Gauvery and Krishna Godavari off the east coast of

coasts, through the Assam fold belt, onshore

India are relatively small but Krishna Godavari is

Gujarat, Rajasthan, the Ganges Valley, Bengal, andbelieved to hold a promise for further development.

the Vindhyan and Deccan Synclines in central west

India has rightly taken interest in pipeline natural

India. Other smaller basins are found scattered

gas import some of these countries such as, theacross the sub-continent. The rest of the basins

Middle East, Russian Far East to Asian countries.

have not been explored at all well. The sedimentary

Gas hydrates are one of the promising alternate

basins in India add up to 3.14 million square km in

viable resources in addition to coal bed methane.

area. Of this, 67.3% is unexplored. The exploratory

Oil

and

NaturalGas

Corporation

drilling activity is very low if compared to that ofUSA.

2. Exploration Activities in India

2.2 The accelerated program for exploration

2.1 Exploration activity is very limited

ONGC and OIL have been known as good

The success in oil and gas exploration in339

finders. However, as they faced the challenge of
exploring more difficult areas and the deep waters,

Round

Year

the technology gap became critical. According toBlock

Bids Received

Offeredexperts, this gap between the best globally available

1

1979

32

4

technology and that used by ONGC is serious and

2

1982

50

Nil

could grow larger. The Eight Five-year Plan Period

3

1986

27

13

(1992-97) started on a poor note. The accretion in

4

1991

72

24

5

1993

45

15

6

1994

125

70

7

1995

34

22

the first three years was far short of target and thegovernment decided to launch the accelerated
program for exploration(APEX), which had anumber of components including: I) A national

Source: India Gas Report (2001).

seismic grid, II) Exploration in frontier areas and2.4 Consumption and demand for natural
gas

deep waters.
Attempts to involve the private sector inforTill the late 1980s the demand lagged behind

speculative surveys were not successful. However,the supply mainly because of lack of infrastructure.

joint venture speculative surveys with participation

In the 1990s the demand has exceeded supply. Theof the Directorate General of Hydrocarbons (DGH)

power and fertilizer sectors have been allocatedhave been more successful.

most of the gas. These two sectors together

seismic

surveysthroughbidingroundsconsume about 80% of the gas today. Natural gas is

2.3 Private sector and biding roundalso supplied to the residential and the commercial

Exploration bidding rounds started in 1997, farsectors in Mumbai, Delhi and few towns of Gujarat,

ahead of the economic reforms of the 1990s, but theAssam and Tripura. This gas is used for cooking

early rounds were not successful. The first four

only, as space heating is not required. The use ofrounds took twelve years to come (1979-91). The

CNG in lieu of petrol has been popular in Mumbai

next five rounds came in two years (1994-95) andand is now picking up in Delhi. The requirement of

succeeded in generating some interest in thegas over time horizon up to 2025 would depend

international oil industry. To increase this interest,

upon a number of factors and complex inter-government decided to award some small andrelationship.

medium sized fields for development to private andjoined sectors respectively.

Innovative measures

3. Import options

were introduced in this period to reduce the risk for

There are two options for importing natural

private investors by ONGC/OIL as partners in thesegas into the country-piped gas and LNG. Gas

exploration ventures. The number of blocks

transported by a pipeline is usually cheaper thanadvertised before the launch of the new Explorationthat as LNG over longer distances up to 3,000 to

Licensing Policy (NELP) and the bids received in

4,000 km for an onshore pipeline, and 1,000 to

the various were as shown in table:

2,000 km for an offshore pipeline. But withimprovements in technology, the relative costs ofpipelines and LNG may change significantly.

340

3.6 Bangladesh to India
Reserves of gas in Bangladesh at around 20 tcf

3.1 Piped gas for India
The world’s seventh largest energy consumer

the potential reserves are 3 to 4 times more. This

mainly for power generation, India’s need forperceived as an attractive source for piped gas into

natural gas is likely to increase. On the account ofIndia with significant mutual benefits for both

the growing demand for gas and the limitations ofcountries. However, gas can be exported fromindigenous resources, a number of gas import

Bangladesh only after the internal requirements inprojects have been pursued. These include:

the country have been met. In October 2001 Unocal
submitted a proposal for the construction of a

3.2 Oman to India via a deep water pipeline

pipeline from Bangladesh to India.

It was envisaged that two deep-sea pipelines

3.7 LNG Option

would bring 56.6 MMCMD of gas from Oman to
Gujarat. The Oman Oil Company (OOC), which

In view of the problems faced by the pipeline

was to lay the offshore pipeline, had indicated thatprojects, LNG import options have been pursued to

an investment of US$ 5 billion would be required.

meet the immediate needs for imported gas. Four

The OOC is no longer interested in the project, as

large oil and gas sector companies (ONGC, GAIL,

the feasibility of the deep-sea pipeline could not be

IOC, and BPCL) have formed Petronet LNG toproved.

import LNG into India.

3.3 Iran to India via Pakistan
Pakistan has favored a pipeline route passing

3.8 Strategic alliances in the hydrocarbon
sectoroverland through its territory allowing it to tap

Meeting the first growing demand for oil andsome gas also. India agreed to examine this option

gas in India would call for a number of alliances atalong with the sub- sea route. However, no progress

the company level as well as at the level ofhas been made either way.

governments. The objectives behind such alliances
would be the acquisition of latest technologies,

3.4 Turkmenistan to India via Afghanistan
and Pakistan

which may not be available commercially for years
to come and also to mobilize the necessary financesThis project was at one time being pushed byfor

Unocal were pursuing an alignment throughdeveloping

the

oil

and

gas

industry.

Unconventional gas sources like Hydrates andAfghanistan and Pakistan. There are obvious(Coal Bed Methane (CBM), will need to be tapped

political and security problems associated with thefor the next century. The technologies in these areas

project and an early breakthrough is not expected.

would be available to India only to extend that

Unocal has since withdrawn from the project.

India participates in their development and this has

3.5 Myanmar to India via Bangladesh

to be done in partnerships with leading countries

Exploration for more gas continues and in caseand companies.

more gas becomes available, it may be feasible to

3.9 Exploration for gas Hydrates and Coaltransport it to Indian through an offshore pipeline in

Bed Methane (CBM)

combination with gas from Bangladesh. A pre-At present gas from hydrates is being produced

feasibility study of these options is under way.

only in Russia but both USA and Japan have taken

341

My next plan is to study this issue more closely.

up projects for development of gas production fromhydrates. A number of hydrates deposits have been
located off the eastern and the western coasts ofReferences

India. However, the technology of tapping the[1]

TERI (Tata Energy Research Institute), “India
Gas Report: Task Force on Energy
Infrastructure Development Project,” BIMST –EC Energy Sector, February 2001.

[2]

IEA (International Energy Agency), “Natural
Gas Transportation,” Organization andRegulation, OECD Paris 1994.

[3]

Kapil Thukral , R.K. Pachauri,“Energy
Policy Issues,” Processing of a Workshop
Jaipur, July 1984.

[4]

Dr. Duncan Seddon, Gas Usage and Value:
The Technology and Economics of Natural
Gas Use in the Process Industries ( PennWell,
2006).

[5]

Jane Whaley, Exploration: “India- an
Unprecedented Opportunity,” GEO ExPro
March 2006.

methane in these deposits is yet to be proved.
Hydrates can block deep sea pipelines. Research on
hydrates

may

also

offer

new

methodsoftransporting gas in a cheaper and easier way than as
LNG. The Indian National hydrates program maybenefit from collaborating with Japan and USA.
Coal bed methane is a clean burning fuel the samechemical compound as natural gas, but formed
under different circumstances. India is endowedwith rich deposits of coal and lignite. The
commercial production of such methane, better
known as CBM is a proven technology and has
added to the natural gas production of somecountries. In 1997, Indian government wishes toinvolve both the public and the private sectors indeveloping these resources.

4. Conclusion
India is trying to reduce its dependence on oil
imports by expanding domestic exploration andproduction.

In

February

1997,

the

Indiangovernment endorsed a new Exploration Licensing
Policy to provide, a framework for newcomers in
oil and gas exploration. The liberalization andreforms implemented in early January 2000 opened
theonshoreandoffshore

exploration

andproduction blocks to private and foreign firms via
Production Sharing Contracts. However considering
the size of its gas reserves, the domestic gas supply
in India is not likely to keep pace with domestic
demand. It will have to import most of its
increasing requirements either via pipelines or LNG
tankers. India is also planning to explore coal bed
methane and hydrates production in the near future.

342

Political Tangles of a Natural Gas Pipeline Project from Bangladesh to India
Md. Mamunur Rashid**Department of Industrial Engineering and Managemen Tokyo Institute of Technology
mamun@me.titech.ac.jp
In the 1990s mostly with the help of international oil companies Bangladesh expended thenumber of its natural gas wells, raising its prospect for a gas rich country. Soon, its natural gas
production exceeded its limited domestic demand. In 2001 Unocal, one of the companies active in
exploration proposed building a pipeline from Bangladesh to India to export gas. Although, the idea
received great attention, it has not been built, mostly due to political issues attached to the project. The
case illustrates how political and institutional factors may hinder a great economic and industrial
project; therefore it also illustrates the lack of a co-evolutionary symbiosis among the factors
impacting this project.
2. A Brief History of IOCs Role in Bangladesh
1.

2.1 IOC involvement in Exploration Sector

Introduction

International Oil Companies have played a

In the mid 1990s, the Bangladeshi government
opened gas sector to private ownership encouraged

veryInternational Oil Companies (IOCs) to invest in gas

exploration history, which began 100 years ago.

exploration. As a result, success in oil and gas

Total 64 exploration wells drilled IOCs drilled 44

discoveries has come in cycles.

However, thiswells with 12 discoveries, the remaining 10 fields

created a problem. The gas production soon came

were discovered by the public sector including

to surpass the limited local demand. To increase

OGDC, Petrobangla , and Bapex. More than 18

their profits, IOCs together with the Bangladeshi

tcf or about 92% of these recoverable are located ingovernment, sought way it to market it elsewhere.

12 gas fields discovered by IOCs. Currently, there

Among the options is building of a pipeline to sell

are big IOCs operating, ex. Unocal, Shell, Cairn

Bangladeshi gas to India. A pipeline was proposed

Energy, BP, Chevron, Halliburton, Mobil, Tullow

by Unocal, but the issue has generated a fierce

Oil & Total. There are also a few Australian &debate: Should Bangladesh export natural gas orJapanese, companies that are active in the

keep its reserves for future domestic use? The gas

Bangladesh Petroleum industry.

export has become heavily politicized.

2.2The Prospect on Natural Gas in Bangladesh

If thegovernment decides to sell gas, the opposition will

significant

role

in

Bangladesh’sgas

and Indian Export Target

call for mass protests, and if they decide not to sell,

Bangladesh’s current proven recoverable gas

then the opposition will gain the credit. There isreserves of 14 tcf. Foreign investors believe that thelittle ideological difference between the two major

potential reserves are significantly higher, althoughpolitical parties: the real issue is who is in power

their estimates differ. Petrobangla and the U.S

and who is out.

geological survey shows gas reserves as high as
94.6 tcf or as low as 8.4 tcf. The Shell and Cairn
low-case scenario of potential reserves is 35 years,343

indicating a surplus large enough to allow gas

capable of building a vast pipeline, the initiatives

exports to India. Wood Mackenzie, study confirms

for this pipeline have come from private companies.

that Bangladesh gas market is oversupplied for

In November, 2001 Unocal submitted a proposal

some years to come, it appears that exports arefor the construction of a pipeline from Bangladesh

feasible Supply to meet any additional demand in

to India. Later, Shell Oil joined the scheme.

the Bangladesh market after 2008 could come from

3.2 Unocal’s Pipeline Project

existing fields, new discoveries etc. In its growing

Unocal and its subsidiaries have been active indemand for gas India is primarily dependent on

gas exploration and production in Bangladesh fornatural gas import from abroad. It has imported

several years in the blocks 12, 13, and 14 innatural gas mostly in the form of LNG. But for thenortheastern Bangladesh. In 1998, it discovered thelast two decades, India has shown its increasing

Bibiyana gas field, the biggest gas field in South

interest in importing gas from international gas

Asia.

market by a pipeline.

Macnaughton

The indigenous gas fields in India are located inconsulting firm, confirmed that the Bibiyana field

Western India, which is relatively far from theheld an estimate 6.6 Tcf of gas. Unocal and its

markets in New Delhi and West Bengal. Thus

subsidiaries offered to build a pipeline, known asconsidering that an abundant supply exists in

the Bangladesh natural gas pipeline project.

Bangladesh, building a pipeline from Bangladesh

Unocal plans to construct a 1,363-kilometer (847

would be both closer and more convenient thanmile) pipeline, with the initial capacity of 500

LNG imports or domestic sources. The markets that

MMCFD from the Bibiyana field in northeast

can utilize gas imports from Bangladesh are near

Bangladesh to Delhi market area in India. Unocal

New Delhi and West Bengal. India is trying to

identified three major markets that could be served

reduce its dependence on oil imports by expandingby the pipeline: the HBJ Market, the Northerndomestic exploration and production.

India isMarket and the Route Market It concluded that anplanning to explore coal bed methane and hydrates

export pipeline to markets in India would yield the

production in the near future.

highest value for Bibiyana gas.

The

following
an

year,

DeGolyerinternationallyandrecognized3.3 Socio-economic Benefits of the Projected

3. Natural Gas Markets for Bangladesh
Current situation

Pipeline
To begin with, Bangladesh will capture an

3.1 Bangladesh –India Pipeline

opportunity to become a regional energy hub, with

The export of gas by pipeline from Bangladesh toa promise of a leadership position in South Asia’s

India is not a new issue.

growing energy industry. Other potential benefits of

It came to be talked of as early as the 1980s. But

the pipeline include:

the Bangladeshi government did not make a special(1) Expansion of pipeline infrastructure (2)effort to promote it. The pipeline project is now

Promotion of gas exploration activities.(3) Project-gaining a considerable momentum. India andrelated temporary and permanent employment and

Bangladesh discussed the matter officially at anadvanced training opportunities.(4) It will enhanceenergy conference sponsored by ADB in 2001. As

community development programs, for example,

Bangladesh is not technically and financially344

(Yadana) from Burma to neighboring Thailand.
In 1996, a class action lawsuit was filed in a
US federal court against Unocal by the Brumes
farmers. They alleged that numerous humanrights violations such as being forced by the
Burmese military to work on the pipeline andeducation, health care services etc.
Furthermore, Unocal has proposed to undertake acomprehensive risk assessment of the pipeline’s
environmental and social impact.
Export can help Bangladesh in other areas ofIndia’sstrengthlike

software,exploration

The increase revenues could reduce the trade deficit

relatedinfrastructure
projects.
The
environmental degradation resulting from sucha project could be devastating to thebiodiversity and natural wealth of the region.
Some of Unocal’s past records concern
Bangladesh
directly.
A
Bangladeshi
parliamentary committee found Unocal“negligent” in its management of the
Magurchara gas field

to at least $2.1 billion year, with the potential to

3.6 The Issue of Exports to India has caused

have a trade deficit of only $700 million year. As

National Debates.

for India, From an economic point of view, it

Supporters’ arguments

technologies etc.
3.4 Win –Win Solution
As for Bangladesh, in 1998, Bangladesh
exported $5.1 billion worth of merchandises, with a$2.4 billion trade deficit.

Exporting natural gas

from Bangladesh to India through a pipeline will
increase export revenues by maximum of $300
million and a maximum of 1.7 billion year initially.

would clearly prefer to have access to less-

Advocates of the pipeline argue strongly that

expensive pipeline natural gas. LNG costs aa Bangladesh-India pipeline will help to improve

minimum of $2.50 MMbtu to bring it to port,$0.70

relations not only between Bangladesh and India,

MMbtu to regasify it, and another $0.2.5-

but also between Bangladesh and Pakistan and Iran.

0.35MMbtu to bring it to New Delhi; the total

If the natural gas pipeline from Bangladesh to India

would be $3.45-3.55MMbtu at the city gate of New

is built and possibly it will be extended to Myanmar

Delhi. The LNG price is substantially greater thanand Thailand, there would be a natural gas

the above natural gas price from Bangladesh totransmission system linking much of Asia. Denying

New Delhi of $2.80-3.00MMbtu, a potential

it may have the opposite impact. The pipeline willsavings of up to $400 million an year. Finally, italso please IOCs and international donors, which

is much less expensive for India tio by gas frommay finance new exploration aggressively.

Bangladesh than to import LNG, it is much more

Opponents & critics’ arguments

expensive Bangladesh to retain its gas than to

Opponents suggest that there is a great
possibility pipeline will carry the politicalstigma of long term tension between
Bangladesh and India. Pipeline may create asituation for Indian military intervention. As aresult small neighboring country Bangladesh’s
national security and territorial integrity may
be threatened. Left-wing political parties led byexport it to India.
3.5 Why Unocal’s Pipeline is a Sensitive Issue?

In spite of its economic promisingprospects, Unocal’s projected pipeline has
raised several objections. A key objection
concerns the company’s human rights records.
Unocal has recently built a gas pipeline345

the main opposition grouping have argued that
Bangladesh needs its reserves for its own
economic development. Lastly, they believethat the pipeline will make Bangladesh all themore dependent on India for selling its naturalgas.

Bangladesh. Local parties and interest groups in

3.7 A Momentous Issue for Bangladesh

gas export plan will be mutually beneficial in terms

particular are exploiting gas export issues for theirpolitical advantages. Both the government andopposition are in agreement that natural gas
resources offer perhaps the only hope for a brighter
future. It has been observed that Unocal proposedof both economic and political gains.

Supporters and critics of gas export and gas

To implement this project, there is need forpipelines have put forward a line of credible

local and international cooperation confidence

arguments. But they are very selective in theirchoice of international experience and of relevantbuilding, investment, and technology transfer

examples. Furthermore, they are, at least at the local

and energy market integration. This case illustrates

level, often politically motivated, and are linked to

how such political and institutional factors may

certain interests groups. On the other hand, thisobstruct accruing a crucial economic-industrial

public debate has helped to illuminate the pains andproject. It thus also shows the lack of a co-gains of export.

The fact that issue has been

evolutionary process or symbiosis among all thehighly politicized is, perhaps, the single mostfacts impacting this project, when a reasonable co-serious obstacle.

evolutionary symbiosis established among these

Local political parties andinterest groups have simply exploited the gas export

factors the project should proceed.

issue for their political ambitions. Bolivia, which

References

has vast natural gas reserves and has grappled with[1]

Unocal Corporation (2002), ‘Bangladesh
Natural Gas Pipeline Project: Fact Sheets’,
Sugar Land, TX: Unocal.

[2]

Fereidum. F.(2000), ‘Bangladesh Natural Gas
Exports to India,’ Oil & Gas Journal, 19 June,
pp.20-24.

[3]

Shamsuddin,A.H.MTodd A.Brown and Mike
Rickard(2002), Bangladesh Gas Reserve,
Resource Potential May Be Underestimated:
Bangladesh Gas Endowment-2 Oil & Gas
Journal, 29, April, pp.40-43.

[4]

Steven Poruban( 3003), ‘ Unocal’s Stone:‘Window of Opportunity’ Closing on
Bangladesh-to India gas Pipeline Project,’ Oil& Gas Journal, 27 January, pp18-20.

[5]Robert C. Millici. Peter D. Warwick Emil
Attanasi( 2002), ‘ To Sell or Not Sell:
Assessments of Bangladesh Hydrocarbons,’
US Geological Survey Reston Va. Oil and
Gas Journal 18 November, pp24-28.

[6]

Tamim. M. (2003), ‘Policies and Priorities in
Bangladesh Gas Sector Planning,’ Energy for
Sustainable Development, 7(2), pp. 57-65.

the question for decades, has recently decided in areferendum to allow gas exports. It is uncertain if
Bangladesh will follow suit, but it certainly does
not have the luxury of waiting for decades.
4. Conclusions
Unocal, a large investor in Bangladeshi gas has
proposed to build the pipeline, partly to sell the gas
from its discovered field. The pipeline will be amajor boon for the company and Bangladesh gas
industry.

But the project has sparked a fierce

public debate. A section of Bangladeshi population
opposes the export to India in particular. On theother hand, many firmly believe that the gas export
to India will bring the two countries closer, and will
reduce the historical animosity between them. It isobserved that the politicization of the gas export
debate is one the most fundamental problems in346

Bangladesh to India Natural Gas Pipeline Project: Its Story and Prospects
Md. Mamunur Rashid**Department of Industrial Engineering and Management Tokyo Institute of Technology
mamun@me.titech.ac.jp
Natural resource rich developing countries often face political, economic, technological, andmarketing difficulties to utilize their own natural resources. One of the main challenges comes frompolitical instability and conflict which led to corruption. The economic problem has come to be called
the ‘Dutch disease’. Most of other developed countries did the same. This study explores suchdifficulties that Unocal encountered when it tried to build a pipeline from Bangladesh to India. In
November, 2001, Unocal submitted a formal proposal for building a pipeline. It has not been built, due
to political issues attached to the project. This case of gas pipeline project also describes how politicaland institutional factors may hamper a crucial economic project.
the

1. Introduction

prospectsofbuildingapipeline

from

It has been widely recognized that natural

Bangladesh to India. A major reason behindresource rich developing countries often face

Unocal’s offer was the huge reserves of its

political, economic, technological and marketing

Bibiyana field. Unocal spent millions of dollars on

difficulties to utilize their own natural resources.

that discovery, so it is natural Unocal wanted toThis study explores such difficulties that the US-find a viable market for it. So in November 2001,

based gas and oil company Union Oil of California

Unocal submitted a formal proposal for building a(Unocal) encountered when it tried to build apipeline. The project has generated a public debate

pipeline in Bangladesh to transport natural gas toand speculation on Bangladesh’s natural gas

India. This case of Bangladesh’s natural gas

reserves as well as on the question of exporting gas.

exploration and consumption may offer new

Although there has been a great interest in theinsights into the use of natural resources inproject,

developing countries. It also looks at the political

government approval was, however, not and has notfactors that often constrain or prevent the

been forthcoming, and such a pipeline has not been

implementation of such a big project as thebuilt so far. However, the debate on a Bangladesh

Unocal’s Bangladesh to India Pipeline.

to India pipeline has not subsided. This paper

nationallyandinternationally,

the

in

attempts to look at the story of the project. Firstly, it

andoutlines a brief history of Unocal’s operations in

production since 1974. There it has discovered

Bangladeshi oil and gas exploration. Secondly, it

several gas fields including Bibiyana, the largest

explores the idea of a pipeline to India for exportinggas field in northern Bangladesh. Local demand innatural gas from Bangladesh. Thirdly, it examines

Bangladesh for Bibiyana’s sizeable reserves was

the details of Unocal’s natural gas pipeline proposal.

limited at least. From the outset, Unocal had been

Fourthly, it discusses the economic prospects of aaware of the fact that India was the most viable

Bangladesh-India

export market for Bangladeshi gas. In the light ofinternational context and comparisons. Fifthly, it

this, in November 6, 2000, Unocal and its

defines the political issues associated with thissubsidiaries in Bangladesh submitted to thepipeline project and the subject of gas export

Bangladeshi government a preliminary report on

problems. Finally, it concludes with an assessment

UnocalBangladesh’s

has

been

natural

gas

a

major

force

exploration347

pipelineandplacesits

of what benefits Bangladesh can draw from such aBibiyana gas field in 1998. As there was little

pipeline.

prospect for domestic gas market growth, the best

2. A brief history of Unocal’s operations in

option was to export gas. Since then the company
has been pursuing the issue. In 2000, Unocal has

Bangladeshi oil and gas exploration.
2.1 Unocal’s role in Bangladesh gas Exploration

reportedly raveled its plan to lay an under water

Among International Oil Companies(IOCs) operating in Bangladesh, especially
Unocal, has played a significant role in the
country’s gas exploration history. Union Oil of
California (later renamed as Unocal, and now
as Chevron) began its operations in Bangladesh
in 1974 with a joint-venture to develop an
offshore gas field. In 1977, Unocal discoveredgas reservoir at Kutubdia, the first offshore gas
field in Bangladesh. In 1998, Unocal
discovered the world-class Bibiyana field
located in block 12 which has 5.5 trillion cubicfeet of proven plus probable including
additional possible reserves. Shortly afterwards,
Unocal announced discoveries of significant
gas reserves at the Jalalabad gas field located inblock 13, and of the Moulavi Bazar fieldsituated in block 14. It introduced of newtechnologies
inthe
exploration
anddevelopment. ‘Monobore’ well design.

natural gas pipeline from Bangladesh to Andra

2.2 Explores the idea of a pipeline to India for

a portion of the country’s large gas reserves. India

exporting natural gas from Bangladesh.

would be the initial buyer and, logically, India

The export of gas by pipeline fromwould be willing to pay for less expensive piped

Bangladesh to India is not a new issue. The schemegas over the more costly liquefied natural gas

for such a pipeline came to be talked of as early as(LNG). For example, pipeline imports fromthe 1980s. But the Bangladeshi government did not

Bangladesh to New Delhi are a potential saving of

make a special effort to promote it because of$ 400 million a year for India. Currently foreign

political reasons. Cairn Energy and Halliburton

companies(US) have long planned to pipe gas export fromgovernment does not allow gas export. The

their discovered field Sangu in 1996. There weregovernment is afraid of various confusing data

several informal talks and proposals. But they wereabout actual reserve and not having enough supply

inappropriate and the government did not take themfor itself. Foreign investors, however, believe that

seriously. Unocal began negotiations with India forthe potential reserves are significantly higher

export of Bangladeshi gas after it discovered thealthough their estimates differ. According to a348

Pradesh in India and another surface pipeline to
Delhi trough Calcutta (Mokarram 2000). But in2001 Unocal postponed of its proposal for laying agas pipeline from Bibiyana gas field in Bangladesh
to New Delhi in India. The idea of building apipeline gained a considerable momentum in 2001.
Because a group of local politicians, professional
institutions, bureaucrats, lobbyists, and local andforeign energy experts were promoting pipeline gas
exports as a profitable option. But, there was also
opposition from various local politicians, andprofessional institutions, and energy experts havealso been on their stand on the issue of export ofnatural gas by saying that the country still had too
little gas for even its own domestic development.
Since the beginning of the 1990s, several gas fields’
discovered by IOCs in Bangladesh. IOCs arewilling to spend more money to explore in
Bangladesh, however, claimed that they can export

hesitatetoinvestbecausetheDemand forecast for the Bangladesh gas market in

new inter-regional gas pipeline is here for few

Wood Mackenzie study confirmed that gas market

decades and shadowed by regional political cloud.

was oversupplied for the next five years.
3. The economic prospects of a Bangladesh-India
pipeline and place its international context
and comparisons

The question here is not whether to construct gas

3.1 Economic prospects

within the region. Proposal to carry natural gas

pipeline but whether to cooperate with each other at
all either for imports from abroad or for exports

The proposed pipeline project will provide

from Middle East (Iran, Oman and Qatar) and also

Bangladesh with several socio-economic benefits,

central Asia (Turkmenistan) to India and Pakistan

To begin with,have been pursued at the government level as well(i) Bangladesh will capture an opportunity to

as by several IOCs. With the exception of Oman

become a regional energy hub, with a promise of apipeline, all the pipeline projects depend on

leadership position in South Asia’s growing energy

cooperation between India and Pakistan. However,industry. (ii) the billions of dollars in revenues fromrecent proposal from Unocal to establish a joint

gas exports which could be used to help reduce

pipeline from Bangladesh to India is the only hopepoverty in the country.(iii) It will open up new

for foreign companies and others interested in thisbusiness for Bangladesh and this means more jobs,

field for such a pipeline. It is thought that if a

training opportunities, promotion of gas exploration

Bangladesh-India pipeline is built, it will affect theactivities.

community

new prospect of South Asian politics, a new

development programs, ex, education and healthprecedent of co-operation between neighbors will

care services. As projected by HCU-NPD study forbe established. Most of natural gas rich countries

export volumes of 500 million cubic feet gas per

such as Nigeria, Bolivia and Netherlands have beenday, the Bangladeshi government revenues range

developing pipeline exports markets from whichfrom USD 2.9 billion at the floor export price of

they have benefited immensely. Bangladesh could

USD 1.37 per million British thermal unit to USD

follow suit. In Nigeria, for example, has increased

5.8 billion at the ceiling price of 2.96 per million

its per capita income from USD 300 to USD 2,000

British thermal unit. At an export price of USD 2.50

through exporting oil and gas. After thirty five

per million British thermal unit the expected total

years of export gas to European common market

revenue would be USD 4.8 billion. If the quantum

their reserves are the same as it was in 1965. Thisof exports is increased from 500 to 1000 million

means that new discoveries have been made in

cubic feet gas per day, the revenues for Bangladesh

response to export demand. Bangladesh may

will go up to USD 9 billion approximately. The

emulate the above countries policy, in the case ofexport decision is also likely to improve the overall

export the gas reserve estimation does not matterclimate for Foreign Direct Investment (FDI) flows

too much. The country Bangladesh has a large

to Bangladesh.

excess of gas reserves, which local market cannot

3.2 International Context and Comparisonsconsume.

(iiii)

It

will

enhance

Unocal’s

experienceof

Unocal’s

While new pipelines are being built Europe,

experience of gas exploration and export Thailand,

Latin America and other parts of Asia, Indian-

Myanmar, in particular bear lessons for Bangladesh.

Subcontinent is rather behind. The proposal to build

It is also encouraging for the Bangladeshi gas
export.

349

3.3 The Politicization of the Pipeline Projectrequires a new way of thinking based on creating aand Gas Export
The dilemma faced by the Bangladeshi

common ground by ‘setting aside’ personal andpolitical differences for the future of the country. A

government in taking a decision on gas export is a

SIMOT

case of rather a strange politicization in domestic

experience may also help to solve this problem.

politics. In their ruling term each party supports gas

This case of natural gas pipeline project describes

export. But when it is out of power, then it is no

how political and institutional factors may hamper awonder the opposition party becomes major critic

crucial economic project. It thus shows the lack of aof gas export in Bangladesh. As a result, the rulingco-evolutionary process among the entire factor

party has not been able to implement a major policy

impacting this project. When a reasonable co-such as gas export.

evolutionary

3.4 Overcoming the Difficulties Encountering of

established among its components, the projectframework

process

especiallymaturesits

andmanagerial

becomesshould proceed.

Unocal’s Pipeline Project and the Divisive
Politics of Natural Gas Export

References

Most IOCs and Unocal are convinced that

[1]

Auty,
R.M
and
RaymondF.
Mikesell(1998),Sustainable Development in
Mineral Economics Oxford: Clarendon Press.

[2]

Fereidum. F. (2000), ‘Bangladesh Natural Gas
Exports to India,’ Oil & Gas Journal, 19 June,
pp.20-24.

[3]

Haq Emanul, H. (2002), ‘International
Transportation of Natural Gas by Pipeline:
Prospects of Bangladesh,” the Independent(Dhaka) 1March.

[4]

Jeff, M. (2005), ‘Unocal is a Rich Prize for
Chevron,’Alexander’s
Gas
&
Oil
Connections, Vol. 10, Issue 16, August 31.

[5]

Muni, S.D., and Girijesh, P. (2005), India’s
Energy Security: Prospects for Cooperation
with Extended Neighborhood. New Delhi:
Rupa .Co.

[6]

Shishir K, Deb. (1993), ‘Political Economy of
Gas Export: CDRB Publication’, Asian Affairs,
35(3), pp.58-68, July- September.

[7]

Steven, P. (3003), ‘Unocal’s Stone: ‘Windowof Opportunity’ Closing on Bangladesh-to
India gas Pipeline Project,’ Oil & Gas Journal,
27 January, pp18-20.

[8]Unocal Corporation (2002), ‘Bangladesh
Natural Gas Pipeline Project: Fact Sheets’,
Sugar Land, TX: Unocal.

commercial risks can be effectively addressed when
the time comes, but they are not so sure about its
political difficulties. Political matters make theproject implementation much more uncertain andcomplex. Natural gas through a pipeline had clearly
divided, the country into two segments, feeding afierce of political rivalry. Bitter party rivalries aremajor challenges to a sound natural gas export
policy. There is need for a new thinking. There isno magic solution for this issue in Bangladesh. Thisrequires creating a common ground by ‘setting
aside’ personal and political differences and theirstrongfeelings

andconsidersthecountry’s

improvement
4. Conclusions
In 2001 Unocal proposed to build a pipelinefrom Bangladesh to India, but the project did not
realize. The government, fearing opposition, did not
officially back the project. Like many developing
countries Bangladesh faces political unrest, andother difficulties that need to be handled. There isno magic solution for this issue in Bangladesh. It

350

Bangladeshi Exploration of Natural Gas and Reserve Potential
Md.Mamunur Rashid**Department of Industrial Engineering and Management
Tokyo Institute of Technology
Bangladesh is one of the least explored nations in the world in natural resources. Many
foreign firms and institutions have attempted to assess its natural gas reserve potential,
but they have come up with different figures. The fact that a reliable gas estimation has so
far been lacking in Bangladesh is a major problem for a comprehensive assessment of thecountry’s natural gas potential and thereby its export policy. This also stems from aknowledge and technology gap in natural gas reserve estimation. One way to do reduce
this gap is to bring in technologically and managerially efficient companies, for example,
from Japan and Europe, and SIMOT experience to make more accurate assessments.
Secondly it offers an overview of Bangladeshi

1. Introduction

science and technology infrastructure, and geology

Bangladesh is agrarian society with a poor

education, associated with natural gas. Thirdly, it

economic performance. Hence, it has been largely

studies foreign and local company’s involvement in

dependent on foreign aid. The ongoing debates on

oil and gas sector. Fourthly, it evaluates theits prospects of rich natural gas reserves have raised

Bangladeshi gas marketing capabilities, including

Bangladeshi hopes for a positive change: thethe prospects of the Bangladesh-India pipeline.

possibility that it may become a natural gas rich

Lastly it attempts to situate the Bangladeshi natural

nation. In spite of these high hopes and promises,

gas exploration and export.

however, a genuine and reliable assessment of

2. Natural Gas Exploration in Bangladesh

natural gas reserves in Bangladesh is lacking. There
are several differing estimates given by different

2.1 British, Pakistan and Bangladesh Period

local and international companies and institutions

The exploration of gas in Bangladesh can be

operating in the country. Nevertheless, in spite ofseparated into three phases as the British, Pakistani,

their differing numbers and estimates, all theand Bangladeshi periods. In Phase I, from 1908 to

relevant institutions and companies support the idea

1933, six exploration wells were drilled by thethat Bangladesh possesses vast natural gas reserves.

Burma Oil Company (BOC), and the IndianOver the last two decades, with the help of

Petroleum Prospecting Company (IPPC). Three ofinternational gas and oil companies, Bangladesh has

them were abandoned as no gas was discovered.

increased it proven reserves greatly. Therefore,

During Phase II (1947-1971), the search for natural

furtherbettergas continued in Bangladesh, now under thetechnologies, and administrative reforms in natural

Pakistani rule.In 1948, the government promulgatedgas exploration should increase Bangladeshi natural

a Petroleum Act to encourage oil and natural gas

gas potential even further. At the present, theexplorations. The act had the immediate effect ofcountry’s natural gas production exceeds its

dramatically increasing the search for fossil fuels indomestic demand, allowing its export.

the region. This increase in exploration activity

This paper first looks at the Bangladeshi

especially after 1951 was partly due to the

exploration of natural gas and reserve potential.

government’s offering petroleum concessions toinvestments,

applicationsofforeign and domestic companies. International Oil

351

Companies (IOCs), as well as Domestic Oil

institutions, and financial and other resources

Companies (DOCs), took up concessions underallocated for research and development the country.

Production Sharing Contracts (PSCs). During thisScience and technology education is greatly

period twenty-one exploratory wells were drilled,

neglected in Bangladesh. It is estimated that today

and eight gas fields were discovered. The

Bangladesh has about 50,000 scientists andfoundation of independent Bangladesh marked thetechnology experts with postgraduate qualifications

beginning of Phase III (1972 up to the present).

and over 100,000 lower level scientific andPetrobangla, a state company to oversee natural gas

technological personnel.

and oil, was established in 1974. From 1974 to

2.4 Geology Education in Bangladesh

engagedIn Bangladesh, four national universities, andinternational companies and foreign experts in

one institute, Bangladesh Petroleum institute (BPI),

developing the country’s oil and gas revenues. Six

offer

contracts were signed with IOCs. From 1974 to

Bangladesh due to limitations and financial support,

1976 a total of nine exploration wells were drilled.

only a few students conduct research at Ph.D level.

This resulted in the discovery of only one offshore

Recently, Department of Petroleum and Mineralgas field. However, exploration activities gained

Resources Engineering, Bangladesh University ofconsiderable momentum in the 1990s when moreEngineering and Technology (BUET) is taking acontracts were signed with foreign companies.

leadership role in improving the situation and

From 1990 to present, Petrobangla and IOCs,

training manpower for Bangladesh’s oil and gas

drilled a total of sixteen exploration wells, and six

sectors.

gas fields were discovered

2.5 Gas reserves are not static

1978

under

a

PSC,

Petrobangla

professional

training

ingeology.

In

The reserve estimation is a dynamic process.

2.2 Bangladesh’s Natural Gas Reserve

The reserve of a gas field needs to be reassessed

Potential
The problem facing Bangladesh today is thewith the exploration, production, and development

lake of an assessment of its gas reserve potential.

activities. Technically, reserves include both proven

Most exploration has been conducted in eastern part

reserves and non proven reserves.

of the country. The western part and offshore aredifferent reserve classification systems are in use by

unexplored.

different organizations, as preferred for operational

Only limited seismic and drilling

Severalhave done there. Geological surveys show that thereasons.

Bay of Bengal is rich in oil and gas. The world’s

2.6 IOCs and Local Involvement in the Oil

mostsignificant

under-evaluatedhydrocarbon

and Gas Sectors
The IOCs played a crucial role in gas

regions, its exploration success rate is about 35%,
nearly triple of the world standard.

exploration in Bangladesh. They discovered 13 gas

2.3 Science and Technology Infrastructure

fields having a total gas initially in place (GIIP) offor Expanding Natural Gas Reserves

22.2 trillion cubic feet (TCF). Their finds have

Bangladesh has a relatively weak scientific andadded approximately 14 TCF in total recoverable

technological infrastructure. This can be seen in thegas reserves. Petrobangla had discovered 11 fields

educational and training facilities available, number

with have a total of GIIP of 2.1 TCF. This is aof qualified science and technology manpower,

notable achievement as Petrobangla has discovered352

a total recoverable gas reserve of 1.47 TCF.

3.3 Politics of Export
Whether Bangladesh should sell its extra gas

3. Bangladesh Gas Marketing Capabilities

reserves for hard currency or to utilize it internally

3.1 Gas Marketing Technology
The production and marketing of natural gas

has been a sensitive issue. Political considerations

in Bangladesh started in 1960 with a pipeline gas

are already playing a major role in the export debate.

supply from the Chattak gas field to a Chattak

A popular perception is that gas reserves are limited

cement factory. In 1961, a second gas field, Sylhet,

and exhaustible, and should be preserved forbegan to produce and supply gas to the Fenchuganj

domestic consumption. The estimates of gas

fertiliser factory. In 1961 the total gas produced wasreserves are not without doubt as already discussed.

3.5 billion cubic feet. Production and marketing ofDifferent methods and technologies may change thegas in the country has grown steadily ever since. In

estimates. For example, the IOCs and Petrobangla

2001, production of natural gas in Bangladesh ishave come up with different estimates. IOCs

carriedestimated Bangladesh’s potential gas resource as 65

out

by

three Petrobangla subsidiarycompanies: Bangladesh Gas Fields Company Ltd,TCF, while Petrobangla suggested just 16 TCF.

Titas Gas Transmission and Distribution Company

3.4 Official Development Assistance (ODA)

Ltd, and

Program for Bangladesh: Economic Growth of

Bangladesh Petroleum Exploration

Developing Countries?

Company; and two international oil companies:
gas

Bangladesh remains one of the world's

companies,

poorest and most densely populated, nations.

responsible for bringing gas to the power plants,

External factors ex. foreign aid, remittances andfertilizer

have always played important roles to Bangladesh’s

Shell

and

Unocal.

transmission

andfactories,

There

are

severaldistribution
anddifferent

industrial,commercial and domestic end users through an

economy.

extensive network of pipelines.

Two types of foreign aid
Bangladesh receives two types of foreign aid:

3.2 Bangladesh India Pipeline Prospect
The geographic proximity makes the export

loan and grant. Grant is provided to the country forof gas to that country not just convenient, but alsofinancing the development need of the country.

economically an attractive option.The Northeastern

Bangladesh is a major recipient of Japanese ODA

states, would be better served bygas from(about 60% on a monetary basis). Debate on these

Bangladesh rather than from Iran and other distantissues has been ongoing for many years, andfields. Pipeline gas from Bangladesh to New Delhi

continues today.

will save US$400 m per year for Indian LNG

Supporters argue:

imports. It will increase the financial gains for

To begin with, Jeffrey Sachs, Joseph Stiglitz,

Bangladesh itself. Unocal has proposed to build a

Nicholas Stern, Papanek, Singh, finds a positive

pipeline, partly to sell the gas from its field. Two

relation between aid and growth. They have argued

countries and the IOCs all involved will gainthat although aid has sometimes failed, but it has

considerable

help

supported poverty reduction and growth in someBangladesh in other areas of India’s strength likecountries, ex. Botswana, Indonesia,, more recently,

software, exploration technologies etc.

Tanzania and Mozambique.

benefits.

Exportcan

Critics say:353

Critics such as Milton Friedman,

additional

Williamgas

reserve.

Many

foreign

firms

Easterly, and P.T. Bauer have charging that aid

attempted to assess its gas reserve potential, have

has enlarged government bureaucracies perpetuatedcome up with different figures. Reliable gas

bad governments and enriched the elite in poor

estimation has so far been lacking in Bangladesh: iscountries has a limited capacity to improve poverty.

a major problem for an assessment of natural gas

They cite widespread poverty in Africa (ex. thepotential and hereby for its export policy. The

Congo, Haiti, Papua New Guinea, and Somalia) and

Bangladesh government should: (i) Bangladesh

South Asia countries like Bangladesh despite threeshould export gas to vitalize its economy anddecades of aid.

reduce poverty and dependency of ODA ii) must

3.5 Foreign Aid Curse analogous ‘Natural

focus on private investment.With appropriate

resource curse, ‘Dutch disease’reforms and policies, it can avoid the ODA resource
curse as same as the natural resource curse' ‘Dutch

Aid can spur inflation and cause a realappreciation of the exchange rate, which reducesdisease' and other problems.

the profitability of production of all tradable goods,

References

creating “Dutch disease” effects. A number of[1]Abdul Quader, A.K.M. (2003), ‘Natural Gas andthe Fertilizer Industry’, Energy for Sustainable
Development,7(2), pp. 40-48.

studies have shown that aid inflows indirectly
eroded the export competitiveness of developing
countriesbycausingrealexchange[2]Ahmad, Q.K., and A.U. Ahmad (2002),‘Bangladesh: Citizen Perspective on Sustainable
Development. Dhaka Bangladesh Unnayan
Parishadrateappreciation. Van Wijnbergen , Younger , Whiteand Wignaraja , and Elbadawi , these authors find[3]Banglapedia (2003), ‘Geology Education’.
Dhaka: Asiatic Society of Bangladesh.

there is a “foreign aid curse” in aid-receiving
countries analogous to the “natural resource curse”[4] Imam, B. (2005), Energy Resources ofBangladesh. Dhaka: University Grands
Commission of Bangladesh, pp. 38- 85.

‘Dutch disease’ that plagues many resource-richcountries.

[5]Mark, T. (2003), ‘Bangladesh: ANESA; Asia;
South Asia; ADB’, Country Commercial Guide
FY 2004: Invest Climate,

3.6 ODA inflation in Bangladesh
ODA still poses a major threat, for Bangladesh[6]Shamsuddin, A.H.M. (2001), ‘Bangladesh Gas
Reserve and Resources: Fact and Reality’,
Independent, (Dhaka), 14 December.

especially for developing countries with newly
discovered natural riches, as with its poor economy.
In Bangladesh, the ODA inflation rate was 4.5 % in[7]Unocal Corporation (2002), ‘Bangladesh Natural
Gas Pipeline Project: Fact Sheets’, Sugar Land,
TX: Unocal.

2005 now it is over 7% ODA.
3.7. ODA inflation Avoidable or Curable[8] Vu Minh Due (2006, ‘Foreign Aid andEconomic Growth in the Developing CountriesA Cross-Country Empirical Analysis.

i) by depositing a chunk of the volume of
ODA or export earnings overseas/friendly countries
and bringing home gradually. iii) strong politicalwill.
4. Conclusion
Bangladesh is one of the least explorednations in the world; it has a high prospect of354

An Observation about SIMOT and Tense Logic
Masanori OHASHITokyo Institute of Technology Department of Industrial Engineering and Management
Graduate School of Decision of Technology
ohashi.m.ab@m.titech.ac.jp
1. Introduction(iii) Scientific Problem and Mathematical Problem
Mechanical watches need for precision of pendulum
Precision of pendulum needs for analysis of pendulum
Analysis of pendulum with physics and mathematics

Tense Logic is an improvement of Mathematical Logic. Mathematical
Logic is a study of Logics, which has been studied since ancient times, withmathematical way. Mathematical Logic was born in the beginning of 20th
Century. And it is a modern style of study while Logics has been studied forvery long time. The contexts such that mathematical way was introduced
into Logics, can be explained with the histories from 17th Century. Social
conditions required technological innovations. Then these requests
demanded scientific and mathematical improvements. Next, scientificimprovements created logical problems, and logical solution was required.
Finally, Mathematical Logic was born. Recent studies of Mathematical
Logics are contributing to improvements of science, especially computerscience. This paper introduces one of the processes of Co-Evolution, andattempts to insist that Logics, which is seemed it has no relations to Social
problems, is developing together with other fields.
This paper is a survey of many other works of histories, but it covers
across many fields. There are few works such that explain clearly about arelation between the establishment of Mathematical Logic and Society.
Because many works write about each history of developments in their own
fields respectively. This paper avoids following the detail processes, andgives an importance to following the total process of Co-Evolution.

Pictures of analysis of pendulum(iv) Differential Calculus and logical problem
Investigations of physics and their calculus contributed for
discovering deferential and integral calculus

Possibility of logical confusion on infinity of mathematics

2. My Own Intention for Studying Logics
Intellectual works must be shared with all the people even thoughhundreds years later. It is very important for intellectual works to write
down in explicit sentences. The completeness of the correspondence
between sentences and their meanings also becomes very important. The
study of Logics is concerning with this correspondence focusing on theirlogical constructions respectively.

(v)

Establishment of Mathematical Logic

Mathematical Logic for analysis of logic of mathematics

4. Tense Logic and author’s present study

3. The history of establishment of Mathematical Logic

The Mathematical Logical systems are called `Classical Logic’.
Classical Logic is suitable for analyzing the logic of mathematics, but it has
limitations for analyzing other logical problems, especially philosophicallogical problems. For this reason, many attempts for improving Classical
Logic, with philosophical insights, have been studied. Tense Logic is one ofthese attempts. In the 1960s, Arthur N. Prior succeeded in constructingsome systems which formalized the use of tenses of ancient arguments, butthere still remain some philosophical problems. On the other hands, Prior’s
results contributed to development of computer science, and now, thiscontribution of study is lasting. The author of this paper tried to solve theremained philosophical problems, and found some results. This author isstudying to improve these results, and thinking about applying his results toother fields.

thThis chapter introduces the history from 17 Century’s development of
capitalism and globalization of Markets, to birth of Mathematical Logic.
From this history, it is intended to explain about dynamic Co-Evolution;
Society-Technology-Science-Mathematics-Mathematical Logics.

(i) Social Background
Development of Capitalism and Globalization of Markets
Need for long distance sea transportation

5. Conclusion
Although the study of Logics seemed to have no relation to Scientific/
Technological problems, and Social problems, it has many relations withthose problems and Co-Evolution with other fields. The study of Logics
does not contribute to Social problems directly, but it is necessary as a partof Co-Evolution and also necessary to solve those social problems. I
conclude that Logics is included in Institution.

Fig.1(ii) Demand for Technological Innovation
Compass
Watch
Telescope

Fig.2

Fig.3

Fig.1 北極海航路, Fig.2 方位磁針, Fig.3 時計の歴史, Fig.4 望遠鏡
フリー百科事典『ウィキペディア（Wikipedia）』

Fig.4

355

Co-Evolution of Logics/Tense Logics and Science/Technology
Masanori OHASHI **Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANohashi.m.ab@m.titech.ac.jp
This paper attempts to explain Co-Evolution of Tense Logic and Science/Technology
by glancing the history of the birth of Mathematical Logic and Tense Logic. Tense Logic
attempts to improve Mathematical Logic for analyzing philosphical arguments on time.
Therefore, it is hard to see the relations between Tense Logic and Scinece/Technology.
This paper collected some works on the histories of Science/Technology and Logics, andmade it clear they have Co-Evolution.

1. Introduction
Tense Logic is one of the attempts to improve
Mathematical Logic. Mathematical Logic is a studyof Logics, which has been studied since ancient
times, with mathematical method. Mathematical
Logic was born in the beginning of 20th Century.
And it is a modern style of study while Logics has
been studied for very long time. The contexts thatmathematical method was introduced into Logics,
can be explained with the histories from thedevelopment of capitalism and globalization ofMarkets in 17th Century. Social conditions required
technological innovations. Then these requests
demanded for scientific and mathematicalimprovements. Next, scientific improvements
created logical problems, and logical solution was
required. Finally, Mathematical Logic was born.
Although Mathematical Logic –Classical Logic- is
suitable to analyze logic of mathmematics, it is notsuitable to analyze other philosophical problems.
Tense Logic attempts to improve mathematicalways for analyzing arguments on time, therefore itis hard to see the relations between Tense Logic andScience/Technology. This paper introduces one ofthe processes of Co-Evolution, and attempts toinsist that Logics is developing together with otherfields, though it is seemed there are no relations
between Logics and Social problems,This paper is a survey of many other works ofhistories, but it covers across many fields. There are
few works that explain clearly about the relations
between the birth of Mathematical Logic andSociety. Because many works write about eachhistory of developments in their own fields
respectively. This paper avoids following the detailprocesses, and gives an importance to following thetotal process of Co-Evolution.

2. My own intention of studying Logics
My own intention of studying Logics is todefine the correctness of Logics.
Here, by Logics I understand the rules/lawswith which we derive/get new valid informationfrom former information.
How to define the correctness is concerningwith the correspondence between meanings andsyntax. Syntax corresponds to explicit sentences. In
Mathematical Logic, explicit sentences are treatedas sequences of symbols.
These explanations about study of Logics arevery abstract, therefore they seem to be purephilosophical matters and it seems that there arefew connections to Science/Technology. But the
study of Logics has very strong connections to
Science/Technology. In order to be understoodthese connections it is better way to explain one ofthese connections as following chapters.
3. The history of Mathematical Logic
3.1 17th Century
Social conditions and technological problems
17th century saw the development of capitalism
and globalization of Markets. This created a hugedemand for a long distance sea transportation.
In turn this created the demands for new
knowledge and technologies, such as the calculationof longitude. These demanded the improvements ofwatches, telescopes, chronometers and compasses.

Fig.1 Compass

356

Fig.2 Watch

Fig.3 TelescopeSources; Fig.1 方位磁針, Fig.2 時計の歴史, Fig.3
望遠鏡, フリー百科事典『ウィキペディア（Wikipedia）』
In order to improve mechanical watches, theprecision of pendulum is required.
Fig.7 Analysis of the trajectory of pendulum (2)Sources; マイケル・S・マホーニィ, 2007, p.267, p.271
One of the important physicists is Christiaan
Huygens.

Fig.4 Marine clock
Sources;マイケル・S・マホーニィ, 2007, p. 286
Fig.8 Christiaan Huygens, Netherlands, 16291695
Sources; クリスティアーン・ホイヘンス,
フリー百科事典『ウィキペディア（Wikipedia）』
Their investigations contributed to theestablishment of differential and integral calculus
later. Newton, I. and Leibniz, G. W. had establisheddifferential and integral calculus independently at
the same time. (About the last of 17th Century)
Fig.5 Picture of pendulum clock
Sources; マイケル・S・マホーニィ, 2007, p.256
3.2 Technological and Scientific problems
Precision of pendulum needs the analysis of the
trajectory of pendulum. This analysis needs to beformalized and solved in physics and mathematics.
Today, we use differential and integral calculus tosolve these problems. But at that time, differential
and integral calculus were not known. Physicists
worked without using differential and integral
calculus. They concluded that the trajectory ofpendulum should be cycloid. (Their calculus wasvery complex.)

Fig.9
Fig.10
Fig.9 Issac Newton, U.K., 1642-1727
Fig.10 Gottfried Wilhelm Leibniz, Germany,
1646-1716
Sources; Fig.9 アイザック・ニュートン, Fig.10 ゴットフリ
ート・ライプニッツ, フリー百科事典『ウィキペディア（Wikipedia）』
3.3 18th -19th Century Scientific/mathematicalproblems and Logical problems on infinity
Leibniz paid his attention to the possibility thatdifferential and integral calculus might have somelogical inconsistencies. He tried to solve thisproblem, but he could not reach a conclusion.
Later, Cantor was studying other mathematicalproblems focusing on the number of singular points.

Fig.6 Analysis of the trajectory of pendulum (1)Sources; マイケル・S・マホーニィ, 2007, p.254

357

He realized the difference of infinities of Natural
numbers and Real numbers. He then tried toanalyze the infinity. He had reached to theestablishment of Set Theory.

mathematics. That syntax is a formalization ofmany arguments on many fields; philosophy,
dialectic, rhetoric and logics, etc. And its semantics
uses the idea of Boolean algebra. The Logicalsystem, which was established at this time, is called
Classical Logic.
3.5 Classical Logic has problems
Classical Logic is suitable for analyzing the
logic of mathematics, but it includes many strange
theorems. For examples,
This theorem means, for any sentences, A andB, either if A then B, or if B then A.
For example, if A stands for `I am Japanese’
while B stands for `Obama is President of the U.S.',
then this sentence becomes as follows.

Fig.11 Ferdinand Ludwig Philipp Cantor, Russia(Germany), 1845-1918
Sources; ゲオルク・カントール, フリー百科事典『ウィキペディア（Wikipedia）』
Set Theory is very useful to reconstructing
Mathematics from foundation. And it also made it
clear the possibility that the differential and integral
calculus may have critical inconsistency.

``Either, if I am Japanese then Obama is Presidentof the U.S., or, if Obama is President of the U.S.
then I am Japanese.’’This sentence is very strange. Because weintuitionally judge the sentence `if A then B’ isvalid when there are some logical deductions
between `A’ and `B’. There are many other strange
theorems in Classical Logic. Those problems had an
impact on improving Classical Logic. In thiscontext, Modal Logic and Many Valued Logic havebeen established and they are also being
investigated today.

3.4 19th -20th Century the Establishment ofMathematical Logic (Classical Logic)
It is needed to ensure that differential andintegral calculus have no inconsistency, and alsoneeded for Logic to solve the mathematical infinity
problems. Many famous mathematicians andlogicians thought about them. From their works,
Mathematical Logic was born. Two importantstudies were by Frege and Russell.

4. Tense Logic
Tense Logic is a kind of Modal Logic. Tense
Logic investigations began as an attempt to analyze
the arguments on time.
Especially, McTaggart’s essay had a great
impact to the establishment of Tense Logic.
McTaggart insisted `Time is unreal' and `I have
proved it' in 1908. McTaggart (John McTaggart
Ellis McTaggart) is a British idealist who had great
influence (1866-1925).
Because his proof was not evident,
philosophical demands had arisen for analyzingarguments on time with Mathematical Logicalmethod. Many logicians had investigated Logics fortime, i.e. Tense Logic.
In the 1960s, Prior, A. N. succeeded inconstructing Modal Logical system named Minimal
Tense Logic Kt. He had formalized tenses based
mainly on Diodorus' arguments. (Prior, A. N. is alogician who was born in New Zealand, alive since
1914 to 1969. Diodorus is an ancient Greek
philosopher.)But Kt also has a problem. It includes
deterministic logical rules and theorems.

Fig.12
Fig.13
Fig.12 Friedrich Ludwig Gottlob Frege,
Germany, 1848-1925
Fig.13 Bertrand Arthur William Russell, U.K.,
1872-1970
Sources; Fig.12 ゴットロープ・フレーゲ, Fig.13 バート
ランド・ラッセル, フリー百科事典『ウィキペディア（Wikipedia）』
Principia Mathematica (1910-1913) is theirvery famous and big work. In this book, Russell had
reconstructed mathematics using Mathematical
Logic. Mathematical Logic is a system of syntax
and semantics built for the purposes to reconstruct358

For examples, Kt has a following formula as anaxiom, named A4.

In addition to considering with these themes, I
am thinking about the applications of my researches
to other fields.

Axiom A4

5. Conclusion
Although it is hard to see the relations between
the study of Logics and Scientific/Technological,
Social problems, there are many relations with eachothers. They have Co-Evolution with each others.
The study of Logics does not stand alone. And it
does not only contribute to Social problems, butalso it is necessary as a part of Co-Evolution. I
conclude that Logics has some elements which arestrongly related to Institution.

This axiom means if A at now, it has always
been true that it will be the case that A.
Here, for example, if A stands for ``The Wall of
Berlin is broken.’, then this theorem corresponds tofollowing.
``If the Wall of Berlin is broken now, then it has
always been true that the Wall of Berlin will be
broken.’’This above sentence accepts the deterministic
insist that before something happens, the happeningof that something has already been decided to behappened later.
Our ordinary intuition cannot accept such insist.
Therefore, Kt might not be sufficient forformalizing our use of tenses.
Prior couldn't solve this problem before his
death. It needed more work and time to produce asolution. On the other hands, Kt can be applied tocomputer science and AI fields. Today
deterministic problem is left and unsolved. Indeed,
there are no systems which correspond to the nondeterministic theorems and logical rules.
I have gotten some parts of a solution to thisproblem in master thesis last year (2008). First, I
studied Prior’s work, and observed that the natureof the problem is the behavior of the free variables.
This fact corresponds to the confusion of the variety
of present tenses. Next, I researched the essay `On
Determinism’ written by Jan Łukasiewicz in 1961. I
found some very important deductions in his essay.
I formalized these deductions into symbols using
Mathematical Logical methods, and I observed
those formulae. As a conclusion, I clarified that inorder to avoid that the systems have deterministic
sentences like an axiom A4, it is necessary to
introduce at least one more new tense operator in
addition to two tense operators which are futuretense operator and past tense operator, into Tense
Logical systems. In fact, Kt has only two tense
operators lacking this extra operator. I am thinking
this operator corresponds to one of the present
tenses.
Today I am studying to improve my results. As
main themes of my study, I am interested in two
problems; one is about constructing nondeterministic Tense Logical systems using this new
operator, and the other is about the mechanism how
the systems have the deterministic characters. I taketwo approaches to study; the philosophical insights
and the meta-logical considering.

References

359

[1]

Prior, A.N., 1967. Past, Present and Future,
Oxford University Press[2]

安倍齋, 1989,『微積分の歩んだ道』,森北出版[3]

廣瀬健・横田一正 , 1985,『ゲーデルの世界完全性定理と不完全性定理-』,海鳴社[4]

マイケル・S・マホーニィ, 2007,『歴史における数学』（佐々木力訳）,勁草書房[5]マートン, R. K. , 1961,『社会理論と社会構造』（森東吾他訳）,みすず書房

On the impact of Computer Science to the Development of the Origin of Modern
Electrical Computer
Satoshi Tanaka∗

1

Background and Aims of this research

The importance of computation is now widely accepted, and many researchers are making efforts to develop quantum computer.
Theory of quantum computation expects that quantum computers cansolve several problems faster than classical computers. For example, every RSA-encrypted sentence can be solved effectively by using quantum
computers. Quantum computation is expected to bring us a lot of profits.
So, we can say that Computer Science is stimulating the actual development of quantum computers.
In 1930s, the theory of classical computability appeared successively.
Especially, the notion of Turing Computability is said to be the first rigorous definition of algorithm and computation. And after a decade, modern electrical computers were invented. Then, did Computer Science also
stimulate the development of the usual electrical computer as well as thecurrent Computer Science did?
This research focuses on the impact of Computer Science, especiallythe influence of Alan Turing, on the actual development of modern electrical computers. This research hopes to clarify the relation between theactual computer development and the development of Computer Science,compared with the current development of quantum computers, and shedsome light on the relation between the foundational research and the applied research as a case study.

2 Brief History of Computer Science
The development of computability theory in the field of logic was
rapid. In the 1920s, German mathematician David Hilbert began to workon a program which aimed to formalize all mathematics in a finite complete axiomatic theory. This movement is now called Hilbert Program.
Hilbert guessed that every problem in mathematics can be solved bysome definite procedure, that is, can be solved by computers.
In 1931, Godel presented his famous Incompleteness Theorems which
are now reformulated as:
1. Every consistent and effectively computable extension of Peano
Arithmetic is not complete.
2. In every consistent and effectively computable extension of Peano
Arithmetic, we cannot prove its own consistency.
But, the notion of computability had not yet been defined. So, there
was a great demand for a rigorous definition of computability.
The theoretical origins of Computer Science date back to the early
1930s. Electrical computers had not yet been developed. The term ‘computer’ was used to describe the ideal calculating man. In the 1930s, several logicians defined the notion of ‘computability’ independently. The
formalization of these definitions were very different, but later the definitions were proved to be equivalent to each other.
1934
1935
1936
1936
1938

Herbrand and GödelChurchPost
TuringKleeneGeneral Recursivenessλ -Definability
Post Machine Computability
Turing Machine Computabilityµ -Recursiveness

Year
1941

MachineZuse(Z3)

1942

ABC

1944

Colossus

1944

HarvardMark I

1946

ENIAC

1948

SSEM
(The Baby)

1949

EDSAC

4

∗ Department of Industrial Engineering and Management, Tokyo Institute of Technol-ogy

The first practical electromecanicalprogrammablecomputertThe first practical electronic
digital computer
The first stored-program electronic computer (test machine)
The first practical storedprogram electronic computer

John V. Atanasoff,
Clifford BerryTommy Flowers,
Allen Coombs
Howard H. Aiken,
IBM engineers
John Mauchly,
J. Presper Eckert
Frederic C. Williams,
Tom Kilburn
Maurice Wilkes

Turing and ACE project

Alan Turing is said to be the father of Computer Science. He presented
the virtual machine model which is now called Turing Machine. His mostsignificant work for developments of actual computers is to design the
ACE project at the National Physical Laboratory (NPL). He wanted todesign the ACE computer as the Universal Turing Machine (UTM). The
notion of UTM was invented in his 1936 paper and UTM is the machine
which can simulate all other Turing machines.
ACE project was the most direct attempt to realize his results of Computer Science in the electrical computer invention in the 1940s, but the
project did not go well because the Mathematical Division of the NPL
did not have the ability to invent the ACE computers, and NPL does nothave enough power after WWII. Then Turing left the NPL before thecompletion of any ACE computer.
The architecture of ACE computers did not become the main streamof computer architecture. The architecture and its coding are more complicated and less practical than other competitors. Therefore, Practicality
had more priority than the theoretical ideas.

5

Turing and von Neumann

There were few people who understood the notions Computer Scienceand participated in the development of modern electrical computer inthe 1940s. Von Neumann is sometimes said to be the father of modern digital computers. He wrote the famous report about EDVAC andStored-Program computers in 1945. Von Neumann was well aware of
the fundamental importance of Turing’s theory. He sad that the fundamental conception is owing to Turing.
It is difficult to say that Turing’s computability theory had a big impact
on Stored-Program computers. There are structural differences between
Turing machine and stored-program computer. Turing machine consists
in a infinite tape and a moving head, but stored-program computers consist in five parts and there are no vestiges of the notion of Turing machines. And there are no citation about Turing’s 1936 paper in his famous
Draft about EDVAC.
Moving Head

Alonzo Church was the first man who offered a rigorous definitionof computability and Turing was the first person who described the theoretical basis for computers. These definitions are now accepted as the
Church-Turing Thesis which says that every effectively computable function or set (calculable by an algorithm) is calculable by one of the above
definitions.

It is difficult to determine which machine was the first electrical computer, since the definition of the modern electrical computer is somewhat
vague and controversial.
Table 2 shows some of examples of computer in the 1940s. There weremany motives for developing these computers. For example, ENIAC
and EDVAC were invented to solve the ordinary differential equations inexternal ballistics and make many artillery firing tables at the Ballistics
Research Laboratory of the U.S. Army.
These electrical computers were developed to meet a practical demand.
So, these motives do not have a direct relationship to what motivatedComputer Science. Many engineers and designers did not know the resultof the Theory of Computability.

Main Engineers
Konrad Zuse

Table.2 Development of modern electrical/electro-mechanical computers in the 1940s

Table.1 Definitions of Computability in the 1930s

3 Brief History of the Developments of Modern
Electrical/Electro-mechanical Computers

FeatureThe first electro-mechanicalprogrammable computer
The first electronic digitalcomputer0

1

1

Infinite Long Tape00

Figure.1 Turing Machine

Von Neumann is sometimes described as the unique inventor of StoredProgram computers, but this is not correct. John Mauchly and Presper
Eckert who were the main engineers of the EDVAC project are often
said to create the most parts of Stored-Program architecture. If this iscorrect, Turing’s theory did not have influence on the Stored-Programarchitecture at all.

6

Conclusion

Computer Science and the development of modern electrical computers stem from different motivations and contexts. Computability theory
including Turing Machine did not have much influence to modern storedprogram computers. Computer Science at that time mainly dealt with thenotion of computability, but in the development of digital computers, thecomputability would be less important than the practical subject like themethod of effective calculation. Practicality had priority as in the originof modern digital computers.

On the impact of Computer Science to the Development of the Origin of Modern
Electrical Computer
Satoshi Tanaka**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
W9-406, 2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANTanaka.s.ai@m.titech.ac.jp
This research focuses on the impact of Computer Science, especially the influence of
Alan Turing, on the actual development of modern electrical computers in the 1940s. First,
to survey the brief history of Computer Science and the developments of modern
Electrical/Electro-mechanical Computers in the 1940s, we see that these two fields
developed independently and by their own motive. Then, we evaluate the influence of Alan
Turing’s work and conclude that Turing’s theory did not have much influence on thedevelopments in the practical point of view. The further research topics are described at
the end.

movement is now called Hilbert Program. Hilbert
guessed that every problem in mathematics can besolved by some definite procedure, that is, can besolved by computers.
In 1931, Gödel presented his famous
Incompleteness Theorems which are now
reformulated as:1) Every consistent and effectively computable
extension of Peano Arithmetic is not complete.
2) In every consistent and effectively
computable extension of Peano Arithmetic, we
cannot prove its own consistency(Gödel[6]).
But, the notion of computability had not yet
been defined. So, there was a great demand for arigorous definition of computability.
The theoretical origins of Computer Science
date back to the early 1930s. Electrical computers
had not yet been developed. The term `computer'
was used to describe the ideal calculating man. In
the 1930s, several logicians defined the notion of`computability' independently (Table 1). The
formalization of these definitions was very different,
but later the definitions were proved to beequivalent to each other.

1. Background and Aims of this research
The importance of computation is now widely
accepted, and many researchers are making efforts
to develop quantum computer.Theory of quantum
computation expects that quantum computers cansolve several problems faster than classicalcomputers. For example, every RSA-encrypted
sentence can be solved effectively by using
quantum computers. Quantum computation is
expected to bring us a lot of profits. So, we can saythat Computer Science is stimulating the actual
development of quantum computers.
In 1930s, the theory of classical computability
appeared successively. Especially, the notion ofTuring Computability is said to be the first rigorous
definition of algorithm and computation. And after
a decade, modern electrical computers were
invented. Then, did Computer Science also
stimulate the development of the usual electricalcomputer as well as the current Computer Science
did?
This research focuses on the impact ofComputer Science, especially the influence of Alan
Turing, on the actual development of modern
electrical computers. This research hopes to clarify
the relation between the actual computerdevelopment and the development of Computer
Science, compared with the current development of
quantum computers, and shed some light on therelation between the foundational research and theapplied research as a case study.

Table.1.
1934

2. Brief History of Computer Science
The development of computability theory in thefield of logic was rapid. In the 1920s, German
mathematician David Hilbert began to work on a
program which aimed to formalize all mathematics
in a finite complete axiomatic theory. This

361

Definitions of Computability in the
1930s

1935
1936

Herbrand,
Gödel
ChurchPost

1936

Turing

1938

KleeneGeneral Recursiveness( Gödel [7])λ-Definability(Church[3])Post Machine
Computability(Post[12])Turing Machine
Computability(Turing[17])μ-Recursiveness(Kleene[9])Alonzo Church was the first man who offered arigorous definition of computability(Church[3]) andTuring was the first person who described thetheoretical basis for computers(Turing[17]). These
definitions are now accepted as the Church-Turing
Thesis which says that every effectively
computable function or set (calculable by analgorithm) is calculable by one of the above
definitions.

There were many motives for developing thesecomputers. For example, ENIAC and EDVAC were
invented to solve the ordinary differential equations
in external ballistics and make many artillery firing
tables at the Ballistics Research Laboratory of the
U.S. Army(Goldstein[8]).
These electrical computers were developed tomeet a practical demand. This is partly because of
the enormous cost involved in developing them.
But, these motives do not have a direct relationshipto what motivated Computer Science. Many
engineers and designers did not know the result of
the Theory of Computability in the 1930s.
Therefore, these motives do not have a direct
relationship to what motivated Computer Science.
Many engineers and designers did not know theresult of the Theory of Computability.
So, it is difficult to say that Computer Sciencestimulated the actual development of computers,
but it would reasonable to say that these two fields
developed independently and by their own motives.
Of course, there were few people who understoodthe notions of Computer Science and participated in
the development of modern electrical computers in
the 1940s. The most influential among them are
Alan Turing and John von Neumann. They
impacted greatly the development of modern digitalcomputers.

3. Brief History of the Developments of Modern
Electrical/Electro-mechanical Computers
It is difficult to determine which machine was
the first electrical computer, since the definition of
the modern electrical computer is somewhat vague
and controversial.
Tble.2. Development of modern
electrical/electro-mechanical computers in the
1940s
MachineFeatureThe first electroZuse
mechanicalZ3(1941) programmablecomputerABC(1942)

Main Engineers
Konrad Zuse

The first electronic John V.Atanasoff's
digital computer
Clifford Berry

Colossus(1944)Tommy Flowers
Allen Coombs

HarvardMark I(ASCC)(1944)

The first practicalelectro-mecanical
Howard H. Aiken
programmable
IBM engineerscomputerThe
firstpractical
John Mauchly
electronic
digitalJ. Presper Eckert
computer
The first stored-program
SSEM
Frederic C.Williams
electronic computer (test(1948)Tom Kilburn
machine)The
firstpractical
EDSAC
stored-program
Maurice Wilkes(1949)
electronic computer
ENIAC(1946)

Table 2 shows some of examples of computerin the 1940s. The most famous computer of thisgeneration would be ENIAC (Electronic Numerical
Integrator and Computer) which was developed in
the United States to calculate the trajectory ofcannonballs. EDSAC is also famous which isoften said to be the first stored-program electronic
computer, but this is not correct. SSEM which wasinvented in Victoria University of Manchester was
the first stored-program electronic computer.

362

4. Turing and ACE project.
Alan Turing is said to be the father of Computer
Science. He presented the virtual machine model
which is now called Turing Machine. After Turing
presented his notion of computation, he worked todecrypt the German encryption Enigma and FISH
from 1938. Then he invented the Turing bombe
which was used for decrypting the Enigma cipher.
But, calculation with Turing bombe is categorized
as analog computing, so this is not related tomodern digital computers.
His most significant work for developments ofactual computers is to design the ACE project at the
National Physical Laboratory (NPL). He wanted todesign the ACE computer as the Universal Turing
Machine (UTM). The notion of UTM was invented
in his 1936 paper and UTM is the machine which
can simulate all other Turing machines.
ACE project was the most direct attempt torealize his results of Computer Science in theelectricalcomputerinventioninthe1940s(Copeland[5]), but the project did not go wellbecause the Mathematical Division of the NPL did
not have the ability to invent the ACE computers,
and NPL does not have enough power after WWII.
Then Turing left the NPL before the completion of
any ACE computer.
The architecture of ACE computers did not
become the main stream of computer architecture.
The architecture and its coding are morecomplicated and less practical than other computers.
Someone evaluated the project as……We can now read his work sympatheticallybecause much of his dream has been realised,
but at the time it must have seemed quite far
fetched and impractical in parts. On top of thisTuring was an intruder, a mathematician in anengineers' domain, proposing a different
approach to computing than that arising fromthe successful development of electronic
machines in the United States. (Carpenter andDoran[2])Therefore, Practicality had more priority than
the theoretical ideas at that time.
5. Turing and von Neumann
There were few people who understood thenotions Computer Science and participated in thedevelopment of modern electrical computer in the
1940s. Von Neumann is sometimes said to be thefather of modern digital computers. He wrote thefamous report about EDVAC and Stored-Program
computers in 1945.
Von Neumann met Turing in 1935, but von
Neumann did not seem to regard Turing’s work asimportant at that time. Then, von Neumann became
well aware of the fundamental importance ofTuring's theory around 1940(高橋[16]). He had ahigh opinion of Turing’s theory. He told toPhysicist Frankel that ``the fundamental conception(of computer) is owing to Turing’’(Randell[13]). So,some people want to say that Turing’s theory highlyreflects on the modern digital computers, but thissimplifies the situation too much.
Figure. 1. Structure of Turing Machine

Figure. 2. Structure of Stored-Program Machine

Von Neumann is often described as the uniqueinventor of Stored-Program computers, but this is
still a controversial point. Someone says John
Mauchly and Presper Eckert created the StoredProgram architecture. They are the main engineersof the EDVAC project and many historians thinkthat they made the most parts of the Stored-Programarchitecture
beforethe
EDVAC
project
began(Aspray and Campbell-Kelly[1]). If this iscorrect, we can say that Turing’s theory did nothave much influence on the developments.
Even if it was not true, it is difficult to say that
Turing’s computability theory had a big impact on
Stored-Program computers. There are structuraldifferences between Turing machine and storedprogram computer. Turing machine consists in a
infinite tape and a moving head, but stored-program
computers consist in five parts and there are no
vestiges of the notion of Turing machines. And
there are no citations about Turing's 1936 paper in
his famous Draft about EDVAC.
6. Conclusion
Computer Science at that time mainly dealt
with the notion of computability, but in thedevelopmentof
digitalcomputers,
thecomputability would be less important than thepractical subject like the method of effective
calculation. Practicality had priority as in the originof modern digital computers.
Computer Science and the development ofmodern electrical computers stem from different
motivations and contexts. Computability theory
including Turing Machine did not have muchinfluence to modern stored-program computers.
Computer Science at that time mainly dealt with thenotion of computability, but in the development ofdigital computers, the computability would be lessimportant than the practical subject like the methodof effective calculation. Practicality had priority asin the origin of modern digital computers.
In the 1960s, Computational Complexity
Theory grew rapidly which mainly focuses on thealgorithm’s execution time. Computational
Complexity Theory stimulates the Quantum
Computation in the 1980s, since its merit was first
demonstrated in the area of complexity. So, these
two fields seem to have become closer gradually.
Therefore, to go deeply into the relationshipbetween the fundamental research field and theapplied research field, historical study would be
required furthermore.
References
[1]

363

Aspray, W., Campbell-Kelly, M., Computer:
A History of the Information Machine, Basic
Books, New York, 1996.

[2]Carpenter, B.E., Doran, R.W., `The other
Turing machine’, The Computer Journal, Vol.
20(1977), pp. 269-279.

[15] Soare, R.I., `Computability and Recursion',
The Bulletin of Symbolic Logic, Vol. 2, No. 3(Sep., 1996), pp. 284-321.

[3]

Church, A., `An Unsolvable Problem of
Elementary Number Theory‘, American
Journal of Mathematics, Vol. 58, No. 2. (Apr.,
1936), pp. 345-363.

[16] 高橋 正子, `論理学の歴史とコンピュータ’, 数
理解析研究所講究録, Vol. 1286(2002), pp.
85-100.

[4]

Copeland, B.J., The Essential Turing: Seminal
Writings in Computing, Logic, Philosophy,
Artificial Intelligence, And Artificial Life; Plus
The Secrets Of Enigma, Oxford University
Press, Oxford, 2004.

[5]

Copeland, B.J., Alan Turing's AutomaticComputing Engine, Oxford University Press,
Oxford, 2004.

[6]

Gödel, K., `Über formal unentscheidbare
Satze der Principia Mathematica undverwandter Systeme I‘, Monatshefte fürMathematik, Vol. 38. (1931), pp. 173-98,
English translation is in Martin[11], pp. 4-38.

[7]

Gödel, K., `On Undecidable Propositions ofFormal Mathematical Systems’ (Princeton
Lectures) , 1934. in Martin[11], pp. 39-74.

[8]Goldstine, H.H., The Computer: from Pascal
to Von Neumann, Princeton University Press,
Princeton, New Jersey, 1972.

[9]

Kleene, S.C., `On Notation for Ordinal
Numbers’, The Journal of Symbolic Logic,
Vol. 1, No. 3. (Sep., 1936), pp. 103-105.

[17] Turing, A., `On Computable Numbers, with
an Application to the Entscheidungsproblem’,Proceedings of the London MathematicalSociety, Ser. 2, Vol. 42(1936-7), pp. 230-265.
[18] Turing, A., `Proposal for development in the
Mathematics Division of an AutomaticComputing Engine (ACE)’, Report to the
Executive Committee of the National Physics
Laboratory, 1945.
[19] Von Neumann, J., `First Draft of a Report on
the EDVAC’, Moore School of ElectricalEngineering, University of Pennsylvania,
unpublished, 1945.

[10] Martin, D., `Mathematical Logic and theOrigin of Modern Computers’, in The
Universal Turing Machine: A Half-Century
Survey, Herken, R.(ed.), pp. 135-158. Oxford
University Press, Oxford, 1995.
[11] Martin, D(ed.),. The Undecidable: Basic
Papers on Undecidable Propositions,
Unsolvable problems and Computable
Functions, Raven Press, New York, 1965.
[12] Post, E.L., `Finite Combinatory ProcessesFormulation 1’, The Journal of Symbolic
Logic, Vol. 1, No. 3. (Sep., 1936), pp. 103105.
[13] Randell, B., `On Alan Turing and the Origins
of Digital Computers’, in MachineIntelligence 7, Meltzer, B. and Michie, D.
(eds.), pp. 3-20. Edinburgh University Press,
1972.
[14] Sieg, W., `Step by Recursive Step: Church's
Analysis of Effective Calculability', The
Bulletin of Symbolic Logic, Vol. 3, No. 2 (Jun.,
1997), pp. 154-180.

364

日本語レポート
山田 晃央
渡辺
渡辺

森山

幸司

渡辺

インスティテューションの戦略提携への影響に関する考察 －半導体産業の場合－
Vol. 1 , No.1 Fall 2005 ….367
研究開発の適応力と多角化のダイナミズムに関する試論
Vol. 2, No. 1 Spring 2006 ….371<ポスター> 日本のハイテク企業の研究開発の収益構造の 3 極化 － 市場の自己増殖機能の共進的内生化による持続的新機能創成
5th Annual SIMOT Symposium ….375
日本のハイテクセクターにおける収益 2 極化構造の分析－研究開発のインプットとアウトプットの代替・補完関係

北原

郭

知就

天放

水野

矢島

池庄司雅臣

圓川

安彦

田中

元

ポンパンプ
ーパックデ
ィ・チャン
オーン
高橋 徹

佐伯

小林

木本

学

佐伯

Vol. 2, No. 2 Fall 2006
The Analysis of the Bipolarization of Profitability amongst Japanese Hi-technology Firms
Vol. 3, No. 1 Spring 2007
The Analysis of the Bipolarization of Profitability amongst Japanese Hi-technology Firms:
The Disparity of Effort for External Acquisition
Vol. 3, No. 2 Fall 2007
<ポスター> SIMOT and Optimization
5th Annual SIMOT Symposium
ミニマックス基準の下での判別規則の研究
Vol. 3, No. 1 Spring 2007
一般化チェビシェフ不等式とその最適化への応用
Vol. 3, No. 2 Fall 2007
基底ブロック下三角行列形を用いた重み付き最小 2 乗法と層別最小 2 乗法の解析
Vol. 4, No. 1 Spring 2008
線形計画問題に対する内点法アルゴリズムの理論的解析とその SIMOT へのインパ
クトVol. 4, No. 2 Fall 2008
ロバスト最適化と SIMOT
Vol. 5, No. 1 Spring 2009
SIMOT における特徴選択の応用
Vol. 2, No. 1 Spring 2006
多クラス判別分析と SIMOT における応用
Vol. 2, No. 2 Fall 2006
半教師あり学習と SIMOT における応用
Vol. 3, No. 1 Spring 2007
顧客属性に基づく顧客満足度の日米比較
Vol. 2, No. 1 Spring 2006
特許明細書の定量的性質に注目した特許率の分析
Vol. 2, No. 1 Spring 2006
特許請求の範囲の数値化表示方法の提案
Vol. 3, No. 1 Spring 2007
タイ国自動車部品企業の人材・技術発展と知的財産管理
Vol. 3, No. 1 Spring 2007

….376
….380
….384
….388
….389
….393
….397
….401
….405
….408
….412
….416
….420
….424
….426

….429
特許発明からみた知識の新結合の研究 －要素技術の組合せの斬新さの分析手法－
Vol. 3, No. 1 Spring 2007 ….433<ポスター> On the Development of the High Pressure Steam Engine in the 19th Century
5th Annual SIMOT Symposium ….438
本誌非掲載分のレポートについて＜SIMOT プログラムにおけるレポート＞「ボイラへの鋼の使用に蒸気圧力向上について」Vol. 1, No.1 Fall 2005
「１９世紀イギリスにおける技術者への熱力学の普及について」Vol. 2, No. 1
Spring 2006
「ベルヌーイの定理から蒸気機関の理論へ」Vol. 2, No. 2 Fall 2006
「１９世紀初期における各用途に起因する蒸気機関の発展の相違について」 Vol.
3, No. 1 Spring 2007
….439

365

19 世紀イギリスにおける技術者への熱力学の普及について
栗原岳史

葉山

雅

加治木紳哉

和田

正法

山崎

藁谷

梶

梶

Vol. 2, No. 1 Spring 2006
<ポスター> 第二次大戦後の米合衆国における軍事研究開発体制の再編成の歴史的研究
5th Annual SIMOT Symposium
第二次世界大戦期における科学動員と科学者－米国の原爆開発の場合－
Vol. 1, No.1 Fall 2005
第二次世界大戦期における科学動員の国際比較－軍と大学の共生関係－
Vol. 2, No. 1 Spring 2006
第二次世界大戦期の科学動員の歴史研究－戦後の米国における核開発体制の転換－
Vol. 2, No. 2 Fall 2006
第二次世界大戦終結後の米国における核開発体制の再編成－文民と軍と対立－
Vol. 3, No. 1 Spring 2007
第二次世界大戦終結後の米国における放射能戦の研究開発
Vol. 3, No. 2 Fall 2007
第二次世界大戦後の米国における研究開発体制の再編成－ヴァネヴァー・ブッシ
ュと国防省研究開発委員会－
Vol. 4, No. 1 Spring 2008
第二次大戦後の米国における研究開発体制の再構築―冷戦後米国のインスティテューションにおける軍と科学者の共生と対立―
Vol. 5, No. 1 Spring 2009
「場のマネジメント論」検討－インスティテューショナル技術経営学的観点からVol. 1, No.1 Fall 2005
科学方法論的観点からのインスティテューション概念検討－平均律の普及を事例として－Vol. 1, No. 1 Spring 2006
政府主導による研究開発の問題点－テクノスーパーライナーのプロジェクトを例にVol.1, No.1 Fall 2005
政府主導による輸送技術開発に関する考察－STOL 実験機「飛鳥」とテクノスーパ
ーライナーを例にVol. 2, No. 1 Spring 2006
国家プロジェクトによる輸送技術開発に関する考察－東海道新幹線を例にVol. 2, No. 2 Fall 2006
国家プロジェクトによる輸送技術開発の歴史的分析
Vol. 3, No. 1 Spring 2007
本誌非掲載分のレポートについて＜SIMOT プログラムにおける研究テーマ＞工学教育の形成における日本型文化の役割：工部大学校の場合について。

366

….440
….444
….445
….449
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….457
….461
….465
….469
….473
….477
….481
….485
….489
….493
….497

インスティテューションの戦略提携への影響に関する考察－半導体産業の場合－
山田 晃央 *
* 東京工業大学大学院社会理工学研究科経営工学専攻〒152-2552 東京都目黒区大岡山 2-12-1 W9-49 大岡山西 9 号館
ayamada@ml.me.titech.ac.jp

本考察は戦略的提携へ各企業の本国のインスティテューションがどのように影響を与えているか、を半導体産業を例にとり、検証するものである。対象企業は半導体大手 14 社とその本国 8 カ国である。結果としては、各企業の提携戦略に地域差の影
響があることが分かった。また、日本企業については、提携によって十分な収益が得られないのは、①チャレンジ精神の欠如、②官学の非効率性とベンチャー企業不足、③自社内重視の開発という 3 点が負の連鎖を起こしているからであろうと考えられる。
1. 序
本稿は、日米欧亜の各国間、また同国間の様々な戦略的提携のために各企業が採用する戦略が、各企業の意図や資源だけでなく、各企業の母国の外部環境、特にインスティテューションによって影響を受けることを数量的に分析することを目的としている。
日本、米国、ドイツ、韓国、台湾などといった全世界の企業が非常に激しい競争を繰り広げる一方で、非常に入り組んだ提携活動を行っている半導体産業を分析対象としている。
半導体産業全体は、元々シリコンサイクルと呼ばれる景気のサイクルが存在するために、産業自体が不安定である。そのために、特に複数の事業を抱える日本の総合電気企業は半導体事業をスピンオフしたり、複数の企業の合弁会社を設立して、リスクを軽減する行動をとっている。スピンオフの例としては、シ
ステム LSI （SoC）に主力製品を絞った NEC
エレクトロニクス（NEC からスピンオフ）が挙げられる。合弁企業の例としては、日立製作所と NEC の合弁メモリ会社エルピーダメモ
リ、日立製作所と三菱電機の合弁企業である
ルネサステクノロジなどが挙げられる。
共同開発「ロジックプロセス、フラッシュメモリなど」

フリースケール（元モトローラ）

合弁会社「300mmウェハ生産」

キヤノン

フィリップス
共同開発
「90nm
プロセス」

共同開発
「次世代リソグラフィ」

デュポン

共同開発
「次世代マスク技術」

共同開発「リードフリー半導体」

インフィニオン

共同開発「STBチッ
プセット」

共同開発
共同開発
「SoC、MRAMなど」「FeRAMなど」

共同開発「携帯電話用LSI」

ソニー
エリクソン

AMD

けて、全体としてはプラス成長を続けている。
しかし、①先端的な研究開発や工場などの設備への投資負担増加、②M&A やスピンオフ・
スピンアウトを活用した事業の選択と集中を遂行するために、また、研究開発から生産・販売まで一貫した事業を行うために、広範囲にわたる企業間提携やコンソーシアム設立が行われいている（Fig.1.）。
Table 1 と Table 2 は世界各国の主要な半導体企業の業績と売上高ランキングである。
Table 1 からは日本企業の売上高営業利益率と1 人あたりの営業利益はともに他国の企業に比べて低いことがわかる。10%を超える企業もある中、日本企業の売上高営業利益率は 10%を超えない。1 人当たりの利益についても、数字が分かる企業の中だけで見た場合、マイナスの値を示しているのは日本だけである。
Table 2 からは、Table 1 と同様に、日本企業の低迷ぶりが目立つ。売上高のランキングは日本企業のみが順位を下げている。また、売上高の成長率については、日本企業は 10%台の成長率しか残せていない。
日本の半導体企業は、一時期の大不振から脱したと言われる。たしかに売上高は成長している。しかし、
富士通
世界の競合企業に比べると、売上高、利益率、その成長率という点で依然として色あせて見える。
HP

合弁会社「スパンション」

共同開発
「DSP」

共同開発
「IA-64」

2. 既存研究
これまで多くの研究者が戦略的提TSMC携について、議論をしてきた。Porter
東芝
シャープ
and Fuller (1986)は、提携のメリット
ソニー
を 4 つあげている。①リスクの低減、
NEC
日立製作所
サムソン電子②規模の経済の追求、③技術ニーズ
マイクロン
三菱電機
テキサス
や市場への接近、④政府の圧力への・インスツルメンツ
対応の 4 つである 1)。
Fig. 1. 適応可能性の主要な支配要因.
Granstrand et al. (1992)は日本、スウェーデン、
出所: ED リサーチ（2005）より一部抜粋. 米国の企業が最も重要だと認識している技術獲得戦略は企業研究としているが、その次に
このように競争が激しく、景気の変動が激重要なのは「技術情報の収集」であると述べ
しいとはいえ、90 年代半ば以降の PC、インタている 2)。
ーネット、携帯電話の普及などの追い風を受
合弁生産「ファンドリ」

製造提携「ファンドリ」

標準化
「90nm
プロセス」

共同開発・合弁会社「SHシリーズ」

合弁会社
「ルネサス
テクノロジ」

STマイクロ

インテル

IBM

共同開発
「SoC」

共同開発
「フラッシュメモリ」

共同開発
資本提携
「100～50nmプロセス、「DRAM支援」
次世代プロセサ」

標準化「90nmプロセス」

合弁会社「エルピーダメモリ」

TIがDRAM
売却

仕様統一「QDSRAM」

共同開発「携帯電話機用半導体」

367

企業に代表される、特に IT やバイオテクノロ
ジーをベースにした新企業を生み出し続ける
米国の文化的・制度的特徴が賞賛された。
しかし、Numagami (1996)が述べるように、柔軟なシステムを持つからといって、最終的によい結果を残せるとは限らない。彼は日米のデジタル腕時計産業を挙げて、柔軟なシス
テムはその特徴のために近視眼的な技術選択をしてしまうために、逆に柔軟ではないシステムを持つ企業に比べて技術選択を誤ってしまうことを実証している 5)。ここで柔軟なシステムを持つのは米国、柔軟ではないシステムを持つのは日本の企業である。
このように企業に関する戦略を考察する場
合には、各企業が影響を受ける各国のインス
ティテューションを分析対象として包含するが、現在の経済の好調さに惑われないことが必要である。
戦略的提携に関しては、企業間の戦略や関係にのみ注目するのではなく、その企業が属する国家などのネットワークを考慮することを意味するだろう。Gulati (1998, 1999)は、戦略的提携の既存研究は、提携や企業行動に影響を与える社会的な要因やつながりの説明が十分ではなかったと批判している 6,7)。
ここで本稿の分析対象である半導体産業、
特に日本企業について概観しておこう。機械
振興協会経済研究所（2003）では日本の半導体企業の問題点の指摘と政策提言を行っている 8)。
1 つ目の課題は「国内企業間での差別化の不足」である。多くの企業（特に大手 4 社）が、①世代揃え、②自律主義、③一貫のすべてを目指しているので、製品・アプリケーションの絞込みとともに、ビジネスモデルの多様化が必要であると述べている。
2 つ目の課題は「人材活用の整備不足」である。儲かる分野に集中していない、組織や方法が洗練されていないなどの理由により、国内の設計エンジニアの人数不足と低い生産性を招いているので、利益貢献とそのための人
材活用の体制作りが必要であると述べている。
最後の課題は「人材流動化とファブレス企業の不足」である。世界に比べて、人材の流動化と国内のファブレス企業の数があまりにも少なすぎるので、一定期間に限定した政府による人材流動の間接支援が望まれると指摘している。
以上より、世界の半導体企業はいずれも、合弁会社設立や共同研究開発といった戦略的提携を増加させているにもかかわらず、その成果や最終的な売上や利益が異なることがわかる。
インスティテューションという観点からは日本企業のこれらの課題と欧米企業との違いが一企業にのみ当てはまるのではなく、大手の日本企業すべてが該当することが重要である。つまり、各企業の行動や戦略に影響を与Table 1 半導体（もしくは電子デバイス部門）における各社業
績（2002 年度）.
企業名

本国 売上高（億円）

売上高
1人当たり
営業利益率（%） 営業利益

東芝

日本

8,286

7.9

NEC

日本

7,251

4.2

日立製作所＋三菱電機

日本

10,502

-

242
122
-139

富士通

日本

6,874

-4.6

インテル

米国

28,102

16.4

-113

IBM

米国

5,053

-22.0

？

サムスン電子585

韓国

12,368

27.0

1,113

STマイクロエレクトロニクス 仏伊

6,634

9.6

150

TSMC

台湾

4,911

19.5

606

ARM

英国

238

27.3

867

出所: ガートナー（2003）、機会振興協会経済研究所（2003）の資料を基に筆者作成.
Table 2 世界半導体企業ランキング（2004 年度）.
ラン
キング

企業名

ランキングの前年比

売上高（百万ドル）

03-04年の売上高成長率（%）

1

インテル→

30,7307.9

2

サムスン電子

→

7,251

4.2

3

テキサス・インスツルメンツ↑

10,5024

ルネサステクノロジ

↓

6,874

-4.6

5

インフィニオンテクノロジーズ↑

28,102

16.4

6

STマイクロエレクトロニクス

→

5,053

-22.0

7

東芝

↓

12,36827.0

8NECエレクトロニクス

→

6,634

9.6

9

フィリップス

↑

4,911

19.5

10

フリースケール

↓

238

27.3

出所: ガートナー（2005）.

Leonard-Barton (1995)は、企業がコアケイパ
ビリティを形成する一つの方法として外部からの専門知識の導入を挙げ、非独占的ライセ
ンス、共同研究よりもコミットメントが大きいジョイントベンチャーと M&A を重要だとしている 3)。
Yasuda and Iijima (2005)は、提携の対称性と業務の上流・下流の関係から、戦略的提携の分析ツール（提携マトリクス）を提供し、実際に半導体産業について分析している 4)。
これまでに述べた戦略的提携についての既存研究はひとつの問題点がある。それは企業間の間の関係に焦点を当てすぎているという点である。たしかに、戦略的提携に、大きなところでは企業間の文化の違い、小さなとこ
ろでは使っている用語の違いなどが影響を与える。しかし、この文化の違いは国際的に見た場合には、宗教や慣習の違い（例えば、クリスマスを重視する欧米、正月を重視する日
本、旧正月を重視する中国や台湾など）によって受ける面も多い。もちろん、言語の違いやハンデも大きく作用する。従って、企業間の違いは内部の組織文化の企業間における違いだけでなく、内部の組織文化の違いに影響を与える国家・地域の文化や慣習の違いも考慮する必要がある。
このような国家間・地域間の文化の違いを述べると、現在好調な国の文化をより良いものだと強調する傾向が強い。例えば、長期（終身）雇用や年功序列賃金制といった人事制度、自動車に代表される系列などを 80 年代の日本の経済成長を生み出した文化的・制度的特徴とみなしてきた。しかし、90 年代になると逆に人材の流動性が激しく、ベンチャー368

えているインスティテューションの課題があると考えられる。
3. 分析フレームワークと分析手法
従って、戦略的提携とそれによる収益は各企業（の母国）のインスティテューションの違いによって、影響を受けるだろうという仮説が立てられる。本稿ではこの仮説を検証することを目的とする。
提携とインスティテューションの関係を Fig.
2.の分析フレームワークをベースに、統計的な分析方法を使って分析を行う。このフレームワークでは、これまでの企業間の提携に国家
戦略・社会制度、企業レベルでの組織・風土、時代背景（SIMOT の 3 軸）の観点から構成されるインスティテューションが外部環境として存在し、企業間の提携と共進化的な関係にあることを示している。

ューションの指標を選択し、その指標を使って主成分分析を行うことにより、対象企業の本国のインスティテューションの特徴を抽出する2。
【インスティテューションを代表する指標】
1. 国家戦略・社会制度

共進化

提携先の
主体的行動

共進化

共進化

イノベーション
企業レベルでの組織・風土-

1000 人当たりの研究開発費-

研究開発の法的環境-

公的研究機関の質-有名ジャーナルでの引用数-

特許と著作権の保護-

高等教育の達成度-

新しい技術への対応度-

経済リテラシー-

ビジネスの効率性-

1000 人当たりの民間企業の研究開発費

3. 時代背景

提携
共進化

政府による教育への支出
政府の効率性

2. 企業レベルでの組織・風土

国家戦略
・社会制度

イノベータの
主体的行動

-

時代背景

-

柔軟性と適応力-

国民の文化（オープンカルチャー）-

科学技術への関心度

-

起業家精神

-

経済・社会の変革への積極性

4. 分析結果
具体的には、下記アプローチで分析を行う。 4.1 数量化理論の分析結果
はじめに数量化理論 1 類と 2 類の分析結果
Yasuda and Iijima (2005)の下記の 4 つの提携マ
1
は、自由度調整済み重相関係数が80.5、相関トリクスの各ゾーン と収益、地域の関係を数比が0.92となり、いずれも十分な説明力を有量化理論 1 類と 2 類を使い、収益と各ゾーンしている。
のポジショニングに影響を与えている要因に数量化理論 1 類については、企業の収益について分析を行う。
影響を与えるのが、各企業の地域差よりも提• 1st Zone
: 水平的提携＋対称的提携
携マトリクスのゾーン戦略の方が大きい影響• 2nd Zone
: 垂直的提携＋対称的提携を与えていると考えられる。
• 3rd Zone
: 垂直的提携＋非対称的提携
数量化理論 2 類については、各企業の提携• 4th Zone
: 水平的提携＋非対称的提携
マトリクス戦略に影響を与えているのは、各数量化理論 1 類については、被説明変数を
企業の収益よりも各企業の地域差が大きいこ
各企業の営業利益率の平均値（1999 年からとがわかる。
2003 年）、説明変数を提携マトリクスの 4 つ
4.2 主成分分析の分析結果のゾーンと本国の地域（日本、北米、欧州、
国家戦略・社会制度の主成分分析の結果は、アジア）の 2 つにしている。
カイザー基準を基に第 2 主成分まで採用する数量化理論 2 類については、被説明変数をと変数のバラツキの 71.8%を説明でき、十分な
提携マトリクスの 4 つのゾーンにし、説明変説明力があると判断できる。
数を各企業の営業利益率の平均値（1999 年か
固有ベクトルの大きさから、第一主成分はら 2003 年）と本国の地域（日本、北米、欧州、 「公的機関の研究能力」、第二主成分は「効アジア）の 2 つにしている。
率性」と解釈できる。この解釈をベースにし次に SIMOT の 3 軸をベースに世界銀行、国た主成分得点の散布図は Fig. 3.で示される。
連開発計画、IMD、世界経済フォーラムなど
Fig.3.より、日本は官学の効率性・研究能力との各種報告書から、企業間の提携に影響を与もに高くはないことがわかる。
えると考えられる下記のようなインスティテ
企業レベルの組織風土の主成分分析の結果
は、カイザー基準を基に第 1 主成分だけで変1
数のバラツキの 67.4%を説明できる。決して大提携マトリクスのゾーンは比較優位度数に変更し、分析を行Fig. 2. 分析フレームワーク.

った。これにより分類が不明確であった3社は、インフィニオ
ン（1st Zone）、フリースケール（元モトローラ；3rd Zone）、
フィリップス（1st Zone）に再分類した。

3692

台湾はデータが不十分なため分析対象から除外した

きくはないが、十分な説明力があると判断できる。
固有ベクトルの大きさから、第一主成分は「技術への対応力・吸収力」と解釈できる。
この解釈をベースにした主成分得点は Table 3で示される。Table 3 より、日本は企業レベル
では特に新しい技術への対応力とそれのベースとなる吸収力が高いことが分かる。

一般レベルでは科学技術への関心もあまり高くない。
5. 結論と将来への課題
これまでの分析から、各企業の提携戦略を象徴する提携マトリクスのゾーンは、各企業の収益よりも本国の地域差の方から大きく影響を受けていることが分かった。また、提携
戦略とインスティテューションとの関係は下記のような負の連鎖が起こっていると考えられ、どこかでこの連鎖を断ち切るための方策を見つける必要があり、そのために半導体固有の情報を更に盛り込んだ分析が必要になるだろう。
1. 日本企業の新技術への対応力やそのベースとなる高等教育の水準は米国に次ぐ水準であるが、官学の効率性や研究能力が他国に比べて劣るため、自社内、もしくは民間企業間での研究開発推進が必須となっており、事業の選択と集中が十分に進まない要因にもなっている。
2. 日本の特徴として、起業や社会・経済の変革へのチャレンジ精神にかけ、新しい状況や環境への柔軟性や適応力が劣るた
めに、半導体産業のファンドリ設立のための重要な要因である大学発などのベンチャー企業設立やスピンアウトによる独立といった行動が制限されている。
3. 2.は事業の選択と集中が進まない要因にもなっており、提携戦略による効果を十分に生み出せない土壌になっていると考
えられる。

2.0

Italy
1.0

UnitedFranceNetherland States
Germany

Japan
0.0
-6.0

-4.0

-2.0
Korea

0.0

2.0

4.0

6.0

→ 公的研究機関
の研究能力

-1.0

-2.0

→ 効率性

-3.0

Singapore-4.0

Fig. 3. 主成分得点の散布図（国家戦略・社会制度）.
Table 3 主成分得点（企業レベルの組織風土）.
技術への対応力・
吸収力 ←

主成分得点

第一主成分

United States

2.304

Japan

2.122

Singapore

1.688

Netherland

0.106

Germany-0.917

Korea-0.943

France-0.944Italy-3.4162.0

1.5

技術への関心度 ←

2.5

参考文献

Singapore[1] Porter, M. E., Fuller, M. B. (1986). Coalition and global

1.0FranceJapan
Germany

0.5→ 柔軟性とチャレンジ精神

0.0
-3.0

-2.0

-1.0

Italy 0.0

1.0

2.0

3.0

-0.5

-1.0

Netherland
United States
Korea

-1.5

Fig. 4. 主成分得点の散布図（歴史的背景）.

歴史的背景の主成分分析の結果は、第 2 主成分までで変数のバラツキの 74.4%を説明でき、十分な説明力があると判断できる。
固有ベクトルの大きさから、第一主成分は「柔軟性とチャレンジ精神」、第二主成分は「科学技術への関心度」と解釈できる。この解釈をベースにした主成分得点の散布図は Fig.
4.で示される。Fig. 4.より、日本は柔軟性と適応力が低く、また変革や起業するようなチャンレンジ精神に乏しいと考えられる。また、

370

strategy. In Porter, M. E. (Ed.), Competition in global
industries (pp.315-343). Boston, MA: Harvard
Business School Press.
[2] Granstrand, O., Bohlin, E., Oskarsson, C., Sjorberg, N.
(1992). External technology acquisition in large multitechnology corporations. R&D Management, 22(2),111-133.
[3] Leonard-Barton, D. (1995). Wellspring of Knowledge.
Boston, MA: Harvard Business School Press.
[4] Yasuda, H., Iijima, J. (2005). Linkage between strategic
alliances and firm’s business strategy: the case of
semiconductor industry. Technovation, 25(5), 513-521.
[5] Numagami, T. (1996). Flexibility trap: a case analysis of
U.S. and Japanese technological choice in the digital
watch industry. Research Policy, 25(1), 133-162.
[6] Gulati, R. (1998). Alliances and networks. Strategic
Management Journal, 19(4), 293-317.
[7] Gulati, R. (1999). Network location and learning: The
influence of network resources and firm capabilities onalliance formation. Strategic Management Journal,
20(5), 397-420.
[8] 機械振興協会経済研究所 (2003) 『半導体の創造的破壊力の解放を目指して －プラットフォームと市場開拓を鍵として－』

研究開発の適応力と多角化のダイナミズムに関する試論
山田 晃央 *
* 東京工業大学大学院社会理工学研究科経営工学専攻〒152-2552 東京都目黒区大岡山 2-12-1 W9-49 大岡山西 9 号館
ayamada@ml.me.titech.ac.jp
本稿は企業の研究開発の多角化の動的な動きから研究開発の適応力を捉え、さらにその適応力と多角化との関係に対しての考察である。研究開発の適応力の概念提示
は、進化論の適応放散の概念を応用することによって行い、次に研究開発の多角化のパターンとの関係を論じている。具体的な計測と分析は日本特許を用いて、IPC（国際特許分類）のサブクラスの観点から行っている。 対象企業はソニーであり、対象
期間は 1992 年から 2001 年までである。
1. 序
本稿は、技術の多角化（技術の多重利用）と研究開発の多角化との循環サイクルと変化する外的環境に適切に適応する企業の能力（適応力）との共進ダイナミズムの関係を解明することを目的とする。具体的には特許のIPC（国際特許分類; International Patent Code）のサブクラスのデータを用いて、計量的に分析を行う。
研究開発に携わるマネジャやエンジニアにとって、研究開発の効率化と多角化を同時に実現することは非常に難しい。なぜならば、両者がトレードオフの関係にあるために、大きなジレンマをもたらすためである。
研究開発の効率性は、多く場合、投資した研究開発費に対して得られた利益の大きさで表現される（例; 村上, 1999）。近年、日本企業の研究開発の効率性が低下しているとの指摘が相次いでいる（例; 榊原, 2005, 内閣府,
2002）。
技術の多角化については、今日まで多くの研究者によって、製品や事業の多角化だけでなく、技術の多角化と組織構造や製品・事業の多角化との関係について論じられてきた(Argyres, 1996, Granstrand and Oskarsson, 1994,
Granstrand et al., 1997, Granstrand, 1999, Gemba
and Kodama, 2001, Fai, 2003, Watanabe et al.,2003, Lin et al., 2006) 。しかし、「技術の多角化」という同じ名称を用いているにもかから
わず、技術の多角化の明確な定義が多くの学者の間で共有されているとは必ずしも言えない。
既存研究の技術の多角化という概念には 2つの意味があると考えられる。1 つ目は 1 つの技術を多くの製品やサービスに応用することによって、範囲の経済と規模の経済の効果を享受し、既存製品の付加価値を向上させるだ
けでなく、新たな製品やサービスを市場に投入することである。本稿ではこれを「技術の多 角 化 （ 技 術 の 多 重 利 用 ） （ Technologicaldiversification（
Multi-utilizationoftechnology））」と定義する。2 つ目の意味は、
技術コンピタンスもしくは技術ケイパビリテ
ィをより広範囲の技術分野に拡大し、様々な技術を開発することによって、企業が多くの

371

分野の技術資産を所有することである。本稿
で は こ れ を 「 研 究 開 発 の 多 角 化 （ R&Ddiversification）」と定義する。
資金や人材といった企業の資源は限りがあるため、一企業が内部で研究開発の多角化を無限に行うことは現実的に限界がある。よって、技術の多角化と研究開発の多角化は、時間的な流れの中で、動的に変化し、循環する性質を持つ。
2. 研究のフレームワーク
技術の多角化と研究開発の多角化の循環サ
イクルの中で、研究開発の効率性を向上させるためには、実際の作業レベルでは、自社における研究開発テーマの選定が重要となる。
効率性の観点からは、事業化や収益向上に繋がる研究開発テーマを早く採用し、成果を残す必要がある。また、決して事業化や収益向上に繋がらない既存の研究開発テーマを早期に中止し、そのおかげでできた余剰能力を将来性がある研究開発テーマに振り分けなければならない。多角化の観点からは、事業戦略
や技術戦略を踏まえた上で、将来性のある技
術分野の研究開発テーマを採用する必要がある。
しかし、企業は、未来を完全に予測し、将来利益をもたらす研究開発テーマだけを選定することはできない。よって、自社の既存の技術資産、人材、コンピタンス（ケイパビリ
ティ）、市場動向、社会環境などを考慮しながら、研究開発のテーマ、そのテーマのベースとなる技術分野、その分野やテーマの増減を動的に決定していく能力が求められている。
この能力は一度保有したら、常に適切な研究
テーマや技術分野を選択できるのではなく、時代によって変遷する、企業内外のインスティテューショナルな要素に対応して、その時々において、適切な意思決定を行うために常に強化しなければならない。
本稿では、この機能を、研究開発の適応力、つまり、企業が技術機会に柔軟かつ的確に対応しつつ自律的に研究開発テーマを取捨淘汰できる環境適応能力と定義する（Yamada and
Watanabe, 2005）。この適応力を内生化したビ
ジネスモデルは、外生的な環境の変化に対して強靭性を発揮し、自身の研究開発の多角化によってもたらされる様々な技術資産の蓄積とその資産の有効な活用（技術の多角化（技術の多重利用））の共進的発展に貢献する。
研究開発の適応力の概念は、進化論の適応放散 1の考えを導入することによって、具体化され、実際に計測が可能になる。同一種としてある技術テーマを考えると、その技術テー
マは、市場のような環境や規制などのインス
ティテューショナルな要因に適応するために、
時間と共にその性質を変化させる。そのときに新たな技術分野が追加される。この性質や分野の変化は生物界では突然変異によってもたらされるが、研究開発においては研究者やエンジニアの自発的な研究開発活動や研究開
発テーマ選択によってもたらされる。
研究開発の多角化は、研究開発テーマの時
間的推移のモデルをベースにして、研究開発
テーマの技術分野の幅と研究開発テーマの取捨選択方法の 2 つの観点から、6 つに分類される（図 1）。研究開発テーマの技術分野の幅の視点では、開発テーマの技術分野の増加、減少、もしくは一定に維持の 3 種類から判別している（1.多角化型、2.均衡型、3.選択と収集型）。研究開発テーマの取捨選択方法の観点からは、現在行っている研究技術分野をできるかぎり維持するか、もしくは現在行っている研究技術分野をできるかぎり減少させるかの 2 種類から判別している（A.スタティック
型、B.ダイナミック型）。企業は無限に多角化することはできないので、これら 6 つのパ
ターンのどれかを採用し、またどれかのパターンに移動しながら研究開発活動を行っていると推測される。
①多角化型

②均衡型

時間

時間

時間

時間

研究テーマの分野の幅

研究テーマの分野の幅

研究テーマの分野の幅

ダ: イナミック型

B③選択と集中型研究テーマの分野の幅

研究テーマの分野の幅

研究テーマの分野の幅ス: タティック型

A

時間

時間

図 1. 研究開発の多角化の 6 パターン.

これら 6 つのパターンのうち、ダイナミッ
ク-多角化型、もしくはダイナミック-均衡型のモデルを採用している企業の方が研究開発の適応力が高いだろうと推測される。なぜなら限りがある資源を有効に活用するために将来性が低い技術分野や開発テーマを中止し、その分将来有望な技術分野や開発テーマに積極的に進出し、資源を集中させているからである。ダイナミック-選択型と集中型では、限ら1

れたテーマや分野に絞っているために、短期的にはその分野で競争優位性を築くかもしれないが、将来の種への取り組みが不十分に思われる。また、このモデルは既存顧客のニーズに過剰に適応してしまう危険性も有している。
3. 分析手法
本稿では特許データの IPC 分類（第 8 版）を活用することによって、企業の研究開発のパターンと適応力を、第 2 章で提示した研究
開発の多角化の 6 つのパターンに基づいて、分類し、分析する。具体的には、今回の分析
では、これまで革新的な日本の企業の象徴として有名であったエレクトロニクス企業、ソニーの 1992 年から 2001 年までの日本で出願した特許データを使用している2。
IPC は全世界共通の特許の分類指標であり、大きく A から H までの 8 つのセクションに分かれている。各セクション（最上位）は、クラス、サブクラス、メイングループ、サブグ
ループ（最下位）の 4 つの階層で構成されている。ひとつの特許には複数の IPC 分類を付与することができる。本稿では、中間である
サブクラスレベルでデータを分類し、集計する。
これら収集された特許の IPC データをベースに第 2 章で提示した研究開発の多角化の 6
つのパターンに当てはめる。具体的には、2 つの評価軸から分類を行う。1 つは 1 期前の付与されたサブクラスとの比較である。サブクラスが増加していれば研究開発の技術分野が増加した、つまり研究開発を多角化したと見なせるだろう。一方でサブクラスが減少すれば、研究開発の技術分野が減少した、つまり集中特化したと見なすことが可能であろう。2 つ目が基点の年（今回の場合 1992 年）のサブクラスが何年後かにどれぐらいカバーされているかを集計する。基点の年のサブクラスが減少
していけば、ダイナミックな変化が発生していると判断できる。
4. 分析結果
はじめに、表 1 は、各セクションのソニーの 1992 年から 2001 年までの出願特許のサブクラス数の推移を表している。第 3 章で述べたとおり、1 つの特許には複数のサブクラスを付与することが可能であり、合計のサブクラ
ス数と特許出願数は同じにはならない。
表 1 IPC セクション別サブクラス数
IPCセクションA 生活必需品

1992

93

94

95

96

97

98

99

2000

01

8

6

5

9

20

7

4

9

10

8

B 処理操作；運輸

417

338

376

431

473

272

373

373

292

309

C 化学；冶金

73

10

74

83

139

94

69

63

62

111

D 繊維；紙

0

1

1

3

1

1

0

E 固定構造物

1

0

10

8

14

3

0

0

0

0

F 機械工学；照明；加熱；武器；爆破

5

11

25

17

26

17

22

50

8

10

3

0

5

G 物理学

3235

2714

2908

3059

3158

3179

3503

3149

3271

3206

H 電気

3930

3623

3562

3907

4115

4035

4245

3645

3659

3762

合計サブクラス数

7669

6703

6961

7517

7946

7610

8216

7290

7302

7411

数値があるサブクラス数

103

94

108

110

105

101

105

101

98

106

出所: IPB（2004）をベースに筆者作成.

適応放散（Adaptive Radiation）とはもとの同一種の動物あるいは植物が、生活条件の違いに適応しつつ、様々な形態をとるこ
2とを意味する（Patterson, 1999）。

372

IPB社の特許四季報 2004を活用している（IPB, 2004）。

10 年の間の 8 つのサブクラスごとのソニーのサブクラス数は、ソニーがエレクトロニク
ス企業であることもあり、セクション G の物
理学とセクション H の電気で全体の 90%以上を占めることが分かる。セクション G が 10 年
間 の 平 均 で 3138 の 値 を 示 し 、 全 体 の 中 で42.1%を占めている。セクション H は平均で3848 の値を示し、全体で 51.6%を占めている。
ここ 10 年間の時間的推移を見てみると、93 年に 10 年間で最も低い 6703 の値を示しているが、その後の大半の時期は 7000 以上の値を示しており、出願された特許のサブクラス数は
平均して約 7500 になることがわかる。これは毎年の出願されている特許が平均して 7700 程度であることを考慮すると、おおよそ 1 つの特許に対して 1 つのサブクラスが付与されていると考えられるだろう。しかし、99 年以降
はまた数値が下がり、7500 以下の水準になっている。
出願された特許が 1 つ以上属するサブクラ
スも、1992 年から 2001 年までの 10 年間で、平均 103 のサブクラスとなり、ほぼ一定であることが分かる。サブクラス数と同様に、93
年に最も低い値 94 を示しているが、10 年間の間、概して 100 の値を示していることがわかる。
表 2 IPC サブクラス数の時系列変化
1992

93

94

95

96

97

98

99

2000

01

数値があるサブクラス数

103

94

108

110

105

101

105

101

98

106

サブクラス増加数

-

22

34

30

27

25

33

28

27

32

サブクラス減少数

-

31

20

28

32

30

29

32

30

24

サブクラス純増

-

-9

14

2

-5

-5

4

-4

-3

サブクラス純増割合

-

-8.74

14.89

1.85

-4.55

-3.81

3.96

-3.81

-2.97

8.16

1992年のサブクラスがカバーされている割合

-

69.90

75.73

75.73

66.99

69.90

72.82

71.84

67.96

71.84

8

出所: IPB（2004）をベースに筆者作成.

次に、出願された特許が 1 つ以上属するサブクラス（1992 年から 2001 年までのサブクラ
スは平均して 103 となる）について、第 3 章
で述べた評価方法に従って、表 2 から 10 年間のソニーの研究開発の多角化のパターンを分類する。1 期前の付与されたサブクラスについては、はじめに増加分については、10 年間の間、最も低い値でも 22、最も大きな値でも 34と大きな変化はなく、平均して 28.67 の値を示している。減少分も同様にあまり大きな変化
はなく、増加分とほぼ同じ 28.44 の値を示している。従って、純粋な増加分は平均して 0.22、その増加率は 0.56 となり、これも数値的に大きくない。時系列の観点からは、93 年のサブクラスが少なかった影響で、94 年に顕著な増加が見られるが、それ以降はほぼ 0 付近にいることがわかる。2001 年に大きな増加が見られるので、それ以降の動きは検証する必要があるだろう。以上の 1 期前のサブクラスとの比較からは、ソニーのサブクラスは、1992 年
から 2001 年までの 10 年間、多少の増減はあるものの、概して一定で推移してきたので、研究開発テーマの技術分野の幅については、均衡型に分類されると考えられる。

373

次に基準の年となる 1992 年のサブクラスが時間を経るごとにどれぐらいカバーされているかを評価する。10 年間の平均カバー率は71.4%となる、そして最小値が 96 年の 66.99%、
最大値が 94 年と 95 年の 75.73%となるが、約70%でほぼ一定であることが分かる。さらに、最も少ないのは 93 年のサブクラス（94）であるが、カバー率が最も小さいのは、サブクラスが 92 年よりも大きい 96 年であることも分かる。よって、数値だけから見ると、全体のサブクラスの推移はほぼ一定であっても、個別のサブクラスが特許に付与されているか、いないかということには時間的に変化していることがわかる。つまり、企業が関与する技
術分野は変化していることと推測される。本
分析のソニーの場合は、基準となる年のサブ
クラスのカバー率が約 70%で一定なので、スタティック型に分類されると考えられる。
これまでの分析は特許に付与されているすべてのサブクラスを対象としたが、多くの特許が属するサブクラスのみ取り上げた分析結果が表 3 になる。表 3 より総サブクラス数の1.0%を 超 え る サ ブ ク ラ ス は 平 均 し て 16.9、5.0%を超えるサブクラスは 3.5、10.0%を超えるサブクラスは 3.1 となることが分かる。ソニーのほとんどのサブクラスを占めるセクショ
ン G と H の合計は、そのセクションの全サブ
クラス数 117 に対して、5.0%以上を占めるサブクラスは約 3%、10%以上を占めるサブクラ
スは約 2.7%に過ぎない。これより、ゲーム、音楽、映画からテレビ、デジタルカメラまでの幅広いエレクトロニクス商品を扱うソニーという巨大企業でさえも、そのほとんどの特許は非常に限られたサブクラスに属することが分かり、比較的限られた技術分野の範囲の中で社内の研究開発活動が行われていることが推測される。
表 3 全サブクラスに占める割合ごとのサブクラス数
1992

93

94

95

96

97

98

99

00

01

10.0%以上

3

3

3

3

3

3

3

3

3

4

5.0%以上

3

3

3

3

3

4

4

4

4

4

1.0%以上

15

15

16

16

16

19

15

17

20

20

0.5%以上

29

29

32

32

30

29

32

33

32

31

0.1%以上

65

63

69

67

67

64

64

59

63

59

0.05%以上

74

72

83

80

82

76

73

76

71

75

0.01%以上

103

94

108

110

105

101

105

101

98

106

全サブクラス数

103

94

108

110

105

101

105

101

98

106

全サブクラスに占める各サブクラスの割合

出所: IPB（2004）をベースに筆者作成.

時系列の観点から見た場合、総数の 1.0%以
上、5.0%以上の項目については、97 年以降、
10.0%以上の項目については、2001 年以降増加に転じているので、より多くの特許が属する
サブクラスをその企業のコア技術分野だと見なすと、ソニーのコア技術は多角化を目指そうとしている可能性がある。
5. 結論と将来への課題
分析結果は、研究開発の効率性向上と技術の多角化というトレードオフに対しての対処
法を、進化論の考えを導入した研究開発の適応力の視点から分析することによって、いくつかの重要な理論的かつ実践的な示唆を示している。はじめに、これまで「技術の多角化」という言葉で多くの学者が研究してきた概念を、より詳細に理論的定義づけを行った。
具体的には、技術の多角化を技術の多重利用と定義し、また、本稿で提案された研究開発の多角化を、技術コンピタンス、もしくは技
術ケイパビリティをより広範囲な技術分野に拡大し、技術資産を獲得すること定義した。
これまでの技術の多角化に関する議論は、ある期間において、企業のパフォーマンスに良い影響があるか、もしくは悪い影響がある
かといった、単純な二元的な問いに終始することが多かった。この議論の問題点は、もし多角化が企業のパフォーマンスによい影響を与えるという結論が得られても、企業は無限に技術の多角化をすることはできないということを無視していることである。
リソースベースドビューの観点に基づいて分析している場合には、自社の限られた特殊な技術ケイパビリティが企業の競争優位を築く上で重要な要因だと述べているにもかかわらず、その技術ケイパビリティを無限に拡大できてしまっては明らかに矛盾する。
本稿では、特許に付与される IPC という客観的な指標を用いて、ソニーを例として分析することによって、研究開発の技術分野の幅の時間的な推移を追跡することができた。これによって、時間がたつと共に新しい技術分
野を追加していることが分かる。具体的には、サブクラスは 10 年間の間ほぼ一定であるにもかかわらず、基点の年となる 92 年のサブクラ
スが、各年において、70%しか特許出願されてないことから、サブクラスの観点からは、残りの 30%は、企業が必ず新しい技術分野に研究活動を拡大させていることが分かる。しかし、10 年間の間は約 70%で一定になっており、
新しい技術分野の追加に対して非常に積極的だとは言えない。特に近年のソニーが他社に比べて競争優位を有していると見なされていたテレビ事業やエンターテインメント事業において、液晶や PDP のような薄型テレビや、
iPod や iTuuns Music Store などのデジタルミュ
ージックプレイヤや音楽配信事業で他社の後塵を拝しているのは、90 年代により多くの技術分野に積極的に進出しなかったせいかもしれない。つまり、それまでに蓄積されていた研究開発の適応力を強化しなかったために、技術の多角化と研究開発の多角化に悪循環をもたらしてしまった可能性が考えられる。
多くの特許が属するサブクラスを企業のコアとなる技術分野と見なしたときには、ソニーの場合、その技術のサブクラスは 3 つ、もしくは 4 つ程度で非常に少ないことが分かった。これは、ソニーのような巨大な企業であっても非常に少ない技術分野がコアとなっていることを示しており、技術の多角化の重要性も示唆していると考えられる。また、コアとなる技術分野が限定されているからこそ、

374

新たな技術分野の研究開発を積極的に行うことによって、双方の共進的発展をもたらす必要があるが、ソニーはそれを怠っていたとも考えられる。
最後に、将来への課題としては、メイング
ループやサブグループのような IPC のより詳
細なレベルで特許分析を行った場合、今回の分析以上によりダイナミックかつよりはっきりとした動きを捉えられるのではないかと推測される。今回の分析では、スタティック均
衡型に分類されたおかげか、技術分野の幅がダイナミックな動きを見せているとは言えない。
また、分析対象期間と、日立製作所や東芝のようなコングロマリット企業、キヤノンや村田製作所のような特化型企業などを含めた対象企業、医薬品などの対象産業をより追加することによって、より広範囲な比較分析が可能になるだろう。
参考文献[1] Argyres, N. (1996). Capabilities, technological diversificationand divisionalization. Strategic Management Journal, 17(5),395-410.
[2] Fai, F.M. (2003). Corporate Technological Competence andthe Evolution of Technological Diversification. Edward Elgar
Publishing, Cheltenham, UK.
[3] Gemba, K., Kodama, F. (2001). Diversification dynamics of
the Japanese industry. Research Policy, 30(8), 1165-1184.
[4] Granstrand, O., Patel, P., Pavitt, K. (1997). Multi-technology
corporations: Why they have “distributed” rather than
“distinctive core” competencies. California Management
Review, 39(4), 8-25.
[5] Granstrand, O., Oskarsson, C. (1994). Technology
diversification in “MUL-TECH” corporations. IEEE
Transactions on Engineering Management, 41(4), 355-364.
[6] Granstrand, O. (1999). The Economics and Management ofIntellectual Property. Edward Elgar Publishing, Cheltenham,UK.
[7] IPB. (2004). 『特許四季報 創刊 2 号』 アイ・ピー・ビ
ー.
[8] Lin, B.-W. (2006). Patent portfolio diversity, technology
strategy and firm value. IEEE Transactions on Engineering
Management, 53( 1), 17-26.
[9] 村上路一 (1999) 「危機意識から生まれたイノベーショ
ン・マネージメント」 『Works』 37.
[10] 内閣府（2002） 『経済財政白書<平成 14 年度>－改革
なくして成長なし（2）』 財務省印刷局.
[11] Patterson, C. (1999). Evolution, Second edition. The Natural
History Museum, London.
[12] 榊原清則 （2005） 『イノベーションの収益化―技術
経営の課題と分析』 有斐閣.
[13] Yamada, A., Watanabe, C. (2005). Firms with adaptability
lead a way to innovative development. The proceedings of 14th International Conference of the International Association
for Management of Technology.
[14] Watanabe, C., Hur, J.Y., Matsumoto, K. (2003).
Technological diversification and firm’s techno-economic
structure: An assessment of Canon’s sustainable growthtrajectory. Technological Forecasting and Social Change,
72(1), 11-27.

日本のハイテク企業の研究開発の収益構造の3極化－市場の自己増殖機能の共進的内生化による持続的新機能創成
森山幸司

東京工業大学 社会理工学研究科 経営工学専攻
moriyama.k.aa@m.titech.ac.jp
1. 序 論3. 普及過程での新機能創成ダイナミズム

Aoki et al. (2007) によれば、図 1 に示すように日本企業はハイブリッ

次に持続可能な FD のダイナミズムを解明するための研究を日本のド会社、セミ・ハイブリッド企業と伝統的な日本企業が三極化してい携帯電話の発展軌道を例に取り実施。図 4 に示されるように IP 携帯電ることが示唆。

話の FD が持続可能な FD をもたらすタイミングより早く現れて、このShare (%)

Hybrid 1
Traditional
J firms

Traditional
J firmsNum berof firms

Employees

24

67

55

23

External
governance (%)

Internal
governance (score)Bondra tio

Ba nk
loa n

Tra nspa rency

9

11

18.2

1

19

8.2

早期創成は継続的な学習によるものであり、携帯電話の普及に貢献しEmployment andincentives (%)

CGI
boa rdLifetim eemploym ent

Merit ba sed
pa y

13.7

94

45

4.7

100

Canon
Sharp
Panasonic
ToyotaNissanHonda

たことを実証。
FD

5 (1 )
3+

24

携帯FD
（包絡線

∆FD
∆ FD

3

）

第二次
携帯FD

2

第一次携帯FD

Hybrid 2(IT andnew ventures)

21

10

100

100

3

17

11.0

10.6

29

mixi
OBIC
NRI

100

図 1. 日本企業の経営構造の変化 (723 社、2002 年 12 月).
a

∆ｔ

∆t

96/7
第一次携帯の本格立ち上げ(携帯電話ポケベルを凌駕）

97/10（携帯 e-mail の登場 )図 4. 日本の携帯電話の連続的イノベーションによる新機能創成軌道.

CGI: Corporate Governance Indicators.

Source: Aoki et al. (2007).

その持続可能な FD を達成するダイナミズムは図 5 に示されている

そのような注目に値する構造変化にもかかわらず、産業分類はまだ
労働生産性に基づいており、新しいパラダイムに適合した新産業分類

が、それは継続的学習により収益性を高めるリーディング技術基盤企業の研究開発活動ダイナミズムと一致。
市場の自己増殖的機能が奏功という発想が不可欠。

内生変数: 価格（ P）, 利用者
先決変数: Ⅰ期前の価格価、1期前の利用者
外政変数: FD、タイムトレンド

2. サービス化経済に向けた産業分類の再構築

収益の増大
価格上昇

ln Pt = − 262 . 968 + 215 .242 ln FD t − 14 .286 ln V t + 0 .743 ln Pt −1 − 0 . 220 t(-2.04)∂Var (OI S ) Var (OI S )(2.05)(2.07)(11.30)

研究開発の営業利益率 (OIS) 弾性値（ ε = ∂Var ( R S ) Var ( R S ) ）による学習効果 λ (V )ln V t = − 18 . 672 + 15 .199 ln FD t − 0 .004 ln Pt − 0 .015 t(-4.25)

利用者数の増大 V (FD )(-1186.87)と新しいベンチャー企業) 、リーディング技術基盤企業 (主としてハイFD (λ )

新機能創成 FDadj . R 2 = 0 . 999

テク電気機械・輸送機械企業) 、伝統的日本企業（素材型）、伝統的日携帯電話の革新
革新のための外部資源

本企業（組立型）に分類。
図 5. 携帯電話発展のダイナミズム.

∂Var (OI S ) Var (OI S )ε=により（IT基盤企業・リーディング技術基盤企業、伝統的企業群（組立、素材）の4グループに分類∂Var ( R S ) Var ( R S )無機化学工業製品製造業
有機化学工業製品製造業
油脂加工製品・石けん・合成洗剤・界面活性剤・塗料製造業
医薬品製造業
化粧品・歯磨・その他の化粧用調整品製造業
その他の化学工業
その他のプラスチック製品製造業
ゴムベルト・ゴムホース・工業用ゴム製品製造業
ガラス・同製品製造業
電線・ケーブル製造業
その他の金属製品製造業
金属加工機械製造業
繊維機械製造業
特殊産業用機械製造業
事務用・サービス用・民生用機械器具製造業
その他の機械・同部分品製造業
発電用・送電用・配電用・産業用電気機械器具製造業
電球・電気照明器具製造業
電子応用装置製造業
電気計測器製造業
その他の電気機械器具製造業
通信機械器具・同関連機械器具製造業
電子計算機・同附属装置製造業
電子部品・デバイス製造業
自動車・同附属品製造業
計量器・測定器・分析機器・試験機製造業
医療用機械器具・医療用品製造業
光学機械器具・レンズ製造業
がん具・運動用具製造業
他に分類されない製造業
ソフトウェア業
情報処理・提供サービス業
インターネット附随サービス業

規模の経済

内生化

(863.48) (1271.17)

価格低下

市場の自己増殖的機能の開拓(-12.55)

adj . R 2 = 0 . 998

製造業の新しい産業分類の開発を試み、IT 基盤企業 (主として IT 企業

172
173
175
176
177
179
199
203
221
244
259
264
265
266
268
269
271
273
274
275
279
281
282
291
301
311
313
315
323
329
391
392
401

t
99/4
第二次携帯の本格立ち上げ(Ezweb)99/2
第二次携帯の出現(i-mode)

401
391
266
392
311
199
279
264
265
259
269
203
275
313
273
323
291
329
172
274
177
176
179
175
173
268
244
221
271
281
315
282
301

インターネット附随サービス業
ソフトウェア業
特殊産業用機械製造業
情報処理・提供サービス業
計量器・測定器・分析機器・試験機製造業
その他のプラスチック製品製造業
その他の電気機械器具製造業
金属加工機械製造業
繊維機械製造業
その他の金属製品製造業
その他の機械・同部分品製造業
ゴムベルト・ゴムホース・工業用ゴム製品製造業
電気計測器製造業
医療用機械器具・医療用品製造業
電球・電気照明器具製造業
がん具・運動用具製造業
電子部品・デバイス製造業
他に分類されない製造業
無機化学工業製品製造業
電子応用装置製造業
化粧品・歯磨・その他の化粧用調整品製造業
医薬品製造業
その他の化学工業
油脂加工製品・石けん・合成洗剤・界面活性剤・塗料製造業
有機化学工業製品製造業
事務用・サービス用・民生用機械器具製造業
電線・ケーブル製造業
ガラス・同製品製造業
発電用・送電用・配電用・産業用電気機械器具製造業
通信機械器具・同関連機械器具製造業
光学機械器具・レンズ製造業
電子計算機・同附属装置製造業
自動車・同附属品製造業

I
IT基盤企業

4. 競争･協力戦略を通じた共進的内性化
先に示された一致に注目し、高い研究開発収益性を示したキヤノン
II
伝統的日本企業（組立型）

によって実行されている共進的内生化を解明する分析を実施。その結果、(i) 魅力的な革新的製品を市場に供給、 (ii) 市場での自己増殖的
FD 誘発の誘導、(iii) 市場でイノベーションを活性化、(iv) 協調・競争

III
伝統的日本企業（素材型）戦略により競合企業の革新を促進しながらその成果を内生化、そして(v) 社内技術スピルオーバーによって包括的な共進的内生化を図 6 に示されるように行っていることを特定。

IV
リーディング技術
基盤企業

携帯電話

キヤノン・PC

収益の増大

キヤノンの収益の増大

図 2. 従来の分類と新分類の対応（企業数 10 社以上のセクター）.
価格上昇

価格低下

価格上昇

市場の自己増殖的機能の開拓

リーディング技術基盤企業を対象に、オープンイノベーション環境

学習効果 λ (V )下において必要とされる持続的に技術を取り入れ利用する能力を示す
同化能力を自己増殖的に増大し持続的新機能創成を達成する条件を満FD (λ )

新機能創成 FD

∆Tid ∆Ts>> 0 が必要十分
Tid
Ts

Ts

Tid

0.1
0.09
0.08
0.07

∆T
Tid の増加率（ id ）Tid

利用者数の増大 V (FD )Ts の増加率（ ∆Ts ）Ts

FD (λ )

規模の経済

PCの普及 Y (FD )新機能創成 FD

携帯電話の革新

プリンタの革新

革新のための外部資源革新のための外部資源

図 6. 携帯電話発展のﾀﾞｲﾅﾐｽﾞﾑとｷﾔﾉﾝの共進的内性化のﾀﾞｲﾅﾐｽﾞﾑ.

0.06
0.05
0.04
0.03

5. 結 論企業が高収益性達成のためには学習により、自己増殖的に同化能力増大し、持続的新機能創成をするという好循環の構築が不可欠である

図 3. 持続的新機能創成のための条件 (1996-2005).

との結論を提示。

375

内生化

持続的新機能創成には

学習効果 λ (V )

規模の経済

内生化

たす企業を特定。その結果を図 3 に示す。

価格低下

市場の自己増殖的機能の活用

「日本のハイテクセクターにおける収益 2 極化構造の分析－研究開発のインプットとアウトプットの代替・補完関係」
森山

幸司*

*

東京工業大学大学院 社会理工学研究科 経営工学専攻〒152-8552 東京都目黒区大岡山 2-12-1 W9-49 渡辺研究室
moriyama.k.aa@me.titech.ac.jp

日本のハイテクセクターにおいて、収益の 2 極化構造が進展している。この状況は企業の競争力の源泉の技術経営規範として、以下のことが不可欠であると認識。これらの差異により 2 極化するに至ったことを検証
ⅰ

Ｒ＆Ｄのインプット（R/S）重視からアウトプット（OI/R：OIR）重視への転換

ⅱ

このためには自前のR&D主義から継続的な学習を”てこ”にした外部技術獲得へのシフト

ⅲ

外部技術獲得による新しいビジネスモデル、資金調達方法等の導入による技術経営構造変革

1 序

0.14

1.1収益力の2極化

0.12

製造業の付加価値の15%, 研究開発の30%を

バブル期

90年代

ITバブル崩壊後

0.1

占め、日本産業をリードする電気機械産業は、

0.08

他の先進国に比べて営業利益率は低位にとどま

0.06

り、バブル崩壊後から景気回復局面にある現在

0.04

0.02

に至る流れを見ても、引き続き低迷の一途をた0

どっている（図1）。しかし、その中でも、キャ

キヤノン

シャープ

三洋電機

富士通

NEC

三菱

ソニー

日立

東芝

松下電器

ノン、シャープ等に代表される中堅企業の中に

図2.

電気機械上位10社の売上高営業利益率の推は近年、バブル期並み、あるいはそれ以上の収移（1987-2003、各期間平均、連結ベース）.

益力を身につけ、それを持続し続けている企業
2 仮 説

も現れ始めている。
これに対して、日立、松下などの伝統的な大以上の背景分析から、鮮明に示されるポスト

手総合電気機械企業は、バブル期における高営

情報化社会のとば口に立ったハイテク企業群の業利益率とは好対照に、おしなべて低利益率を技術経営における注目すべき潮流は、今後、日かこっている。（図2）

本企業がポスト情報化社会に向けて国際的競争

0.2

力を発揮・持続していくための条件として次の3
キヤノン

0.15

方向が不可欠との仮説を示すものである。

0.1

シャープ
0.05

日立、松下など大手総合電機

1.

として、研究開発強度（R/S）等R&Dのイン

0

1987

1989

1991

1993

1995

1997

1999

2001

2003

2005

プット重視から研究開発投資営業利益率-0.05（OI/R）等 R&D のアウトプット指向への

-0.1

図1.

ポスト情報化社会に向けての技術経営規範

転換。

電気機械上位10社及び米国電気機械企業売上げ上位2社の売上高営業利益率の推移（1987-2005）.

2.

376

このためには自前の R&D 主義一辺倒から4.2

継続的な学習を“てこ”にした外部技術の企業の技術進歩Wは収益の研究開発への投資

効果的獲得へのシフト。
3.

技術経営規範これは、国際的な市場学習を通じて日本型

率X及び売上高に対する収益性Yに依存するので、同質企業群を2極化し、伝統的な同質企業群

次のように表せる。

を前提とした技術経営から異質企業間の共W = F (X, Y)(4-1)

2次項までテーラー展開すると進化を追求した技術経営への転換。

lnW = a + b lnX + c lnY
3 既存研究レビュー(4-2)+ d lnX lnYa, b, c, d: 係数

榊原・辻本（2003）は日本企業の技術戦略とそのイノベーション課題の変化及び研究開発マ

ここでlnW, lnX, lnYをそれぞれ

ネジメントの特徴を調査した。

∆TFP
（全要素生
TFP

外部技術獲得に関して、Veugelers (1997) はフ産性），R/OI（営業利益あたり研究開発費），

ランドルのR&D活動が活発な企業の外部R&D活

OI/S (売上高営業利益率) で表すと企業の技術進

動と内部R&D活動の間の相互作用について分析

Lanctot and Teegen (2000) は内部研究開発の状況

歩は、
∆ TFP
R
OI
R OI
=a+b
+c
+d
⋅
TFP
OI
S
OI S
R
OI
R
= a+b
+c
+d
OI
S
S
b
OI R
R
=a+
+c
⋅ +d
OI R
R S
S

と3つのパフォーマンスの関係について、回帰分で示すことができる。このダイナミズムは図3の析により計量的に分析した。市場学習効果につように示される。

した。また、Katz and Allen (1982) はNIH (NotInvented Here) シンドロームについて分析した。
Lambe and Spekman (1998) は提携と不連続技術
変化の関係についての分析を行った。Jones,

いては、Arrow (1962) の“Learning by Doing”の(4-3)

このダイナミズムに乗った企業が好循環サイ

啓発来多くの研究が重ねられ、Rosenburg (1976)、 クルに乗る一方、それに失敗した企業が悪循環
Cohen and Levinthal (1990) 等によって、技術のに陥り2極化が起こっているということが示唆さスピルオーバー効果との関係も分析されてきて

れる。

いる。

MVE

4 分 析

TFP growth

4.1

データ
R/OI

OI/S

ブルームバーグデータの売上高上位1000社に入る日本の電気機械企業80社のうち、2001年かR/Sら2004年の時価総額平均以上19社を分析の対象

TFP：全要素生産性；OI/S：売上高営業利益率；
R/S：売上高研究開発投資；R/OI：営業利益に対する研究開発投資．
① R/Sは営業利益率（OI/S）、営業利益のRへの再投資（R/OI）のダイナミズムを形成② 同ダイナミズムは、技術進歩率 （TFP成長率）と共進化しつつ展開③ 高収益企業のTFPは、とした。
ブルームバーグデータから得たデータは2001
年から2004年のデータであり、それ以外の分析
期間内のデータは各社のアニュアルレポート、
日経財務データを参照した。

377イ）OI/S、R/OIの精妙なバランスロ）R/SとOI/Rの代替・補完関係にセンシティブであることを示す。

図3.

∆TFP
1
= −0.031 + 0.844 D1 xα + 0.017 (1 − D1 ) + 1.545 (1 − D1 )x1+α − 0.039 D2 − 0.124 D3
TFPx(-1.09)(1.59)(3.36)(2.33)(-2.39)

技術経営ダイナミズムと全要素生産性の共進ダ(-1.85)2

adj. R = 0.678

イナミズム.

(5-2)

「R/S（売上高当り研究開発投資）のOI/R弾性

D1：キーエンス、ファナック、ローム、村田、京セラ(OI/Rが高水

値」α により共進化が検証。また、このαは、準)競争力に依存する。

D2：日立、松下、ソニー（ΔTFP/TFP が大）(4-4)

R S = A ⋅ (OI R )α

D3：キヤノン、リコー（ビジネスモデルの相違）

ln R S = ln A + α ln (OI R )この結果を基に図4に示すように各企業の技術

x = OI R , y = R S , w = ∆TFP TFP

経営軌道を描くことができる。
(4-5)

b
w = a + + cxy + dyxy = A ⋅ xα (各企業の OI/SのR/S 代替・補完
代替弾性
企業名
値
キーエンス
-0.62
ファナック
-0.47
ローム
-0.39
村 田
-0.33
京セラ
-0.32
キヤノン
-0.24
リコー
-0.22
セイコーエプソン
-0.09
シャープ
-0.09
三 洋
-0.08
TDK
-0.05
東京エレクトロン
-0.04
三 菱
0.03
NEC
0.06
ソニー
0.06
日 立
0.06
富士通
0.07
東 芝
0.08
松 下
0.23

表1

(4-6)

であることから
w=a+((4-7)b+ cx ⋅ Axα + d ⋅ Axαx

極小（大）値をとる時のxは以下の式を満たす。
1
dw
dα
dα
= − 2 + cA(α + 1)x α ⋅+ dAα x α −1 ⋅
=0
dx
dx
dx
x

(4-8)
以上の式展開から、技術経営軌道の2極化が観察
できる。
5 結 果
αは α = β 0 + β 1 ln x + β 2 (ln x) 2 + L とする。
回帰結果は式（5-1）
ln R S = −3.061 + (− 0.108 − 0.095 ln OI R ) ln OI R + 0.55 D1 + 0.484 D3(-73.78)(-2.44)(-4.32)(5.15)(4.69)

∆TFP
TFP

2

adj. R = 0.756

0.35

0.3

(5-1)

0.25

D1：キーエンス、ファナック、ローム、村田、キヤノン

0.2

グループB

(売上高営業利益率が10％以上と他を圧倒)
D2：東京エレクトロン、松下

グループA

0.15

松下

*東芝
キヤノン
* *リコー** 富士通日立* ソニー
セイコーエプソン
*
NEC
シャープ
0.05
*
*洋
**三
* **TDK京セラ 村 田三菱
東京エレクトロン**（R/S が大きい）

0.1

この式より各企業の ∂ (ln R S ) が求められる。

ローム

0

1

2

3

ファナック

*

0
4

キーエンス

*
5

6

7

8

≈

∂ (ln OI R )

9

*

15
10

OI/R

その結果は表1の通りである。

図4.

この結果を基に式を回帰。

378

各企業の技術経営軌道.

6 結 論参考文献

研究開発のインプット（R/S）に対するアウト[1]

榊原清則, 辻本将晴, 「研究開発の効率性はな ぜ 低 下 し た の か 」 , 『 ESRI Discussion
Paper Series No.47』(内閣府経済社会総合研究所, 東京, 2003 年).

[2]Veugelers, R., “Internal R&D Expenditures andExternal Technology Sourcing,” Research
Policy 26, 1997, 303-315.

[3]Katz, R., and Allen, T. J., “Investigating the Not
Invented Here (NIH) Syndrome: A lock at the
Performance, Tenure, and Communication
Patterns of 50 R&D Project Groups,” R&DManagement 12, 1, 1982, 7-19.3.

[4]

Lambe, J.C., and Spekman E.R., “Alliances,
External
Technology
Acquisition,
andDiscontinuous Technological Change,” Journalof Product Innovation Management, 14, 2, 1997,
102-116.

[5]

Jones K., G., Lanctot A., JR., and Teegen J.,H.,“Determinant and Performance Impacts ofExternal Acquisition,” Journal of Business
Venturing 16, 2000 255-283. Veugelers, R.,“Internal R&D Expenditures and ExternalTechnology Sourcing,” Research Policy 26,
1997, 303-315.

[6]

Arrow, K. J., “ The Economic Implication of
Learning by Doing,” Review of Economic
Studies 29, 1962, 155-173.

[7]

Rosenburg, N., “Factors Affecting the Diffusionof Technology,” Cambridge University Press,
Cambridge, 1976.

[8]

Cohen, W.M., and Levinthal, D.A., “Absorptive
Capacity: A New Perspective on Learning andInnovation,” Administrative Science Quarterly
35, 1, 1990, 128-152.

プット（OI/R）の弾性値の2極化が観察された。
インプットとアウトプットの関係が代替、すなわち弾性値が負の企業群とインプットとアウ
トプットの関係が補完、すなわち弾性値が正の企業群に分かれる。
このOI/RのR/S代替・補完のスキームとして考えられるのは図5に示す場合である。代替企業群
は変動費および固定費を削減することなくRを削減し、それによってOIを増加させている。補完企業群のうち、リストラによってR3 を増大させるほど、OI/RおよびOI/SのR/S補完が大きくなる。
また、代替企業群の場合、獲得外部資源Aが大きいほど、OI/RおよびOI/SのR/S代替が大きくなる。
一方、補完企業群は変動費および固定費を削減して研究開発投資（R）を増大させることによって減少した営業利益率（OI）を、さらに変動費および固定費を削減させることによって確保している。
技術経営軌道はOI/Rの水準によって決定されている。
OI/RとΔTFP/TFP の関係はある一定水準まで
はOI/R が高まるとΔTFP/TFP が減少するが、ある水準を越えるとΔTFP/TFP が触発される状況が観察される。代替企業と補完企業の2極化がこ
こでも観察される。
R/S 牽引 （内部での吸収）
V˝

V´

V

売上原価 V

F´－R2

F－R

F－R

R3

R2

R

R1 = R － A

OI3

OI2

OI

OI1 = OI + A

F˝－ R3
OI4
売上高 S

R3

>

R2

R3 >

OI 2

S

OI 3 + OI 4
OI 3 + OI 4

図5.

OI/R 牽引（外部からの吸収）

S

>

R

R2 <

OI

> OI 2 S <

OI

S

A

R1

>

R

< OI1 R =S<=

獲得外部資源

R− A
S

S

S

販売費及び
一般管理費 FAOI + AR−A
OI1 = OI + A
SS
1OI/R のR/S 代替・補完のスキーム.

379

The Analysis of the Bipolarization of Profitability
amongst Japanese Hi-technology Firms
Koji Moriyama**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-49 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
moriyama.k.aa@m.titech.ac.jp
Contrary to the homogeneous behavior, Japan’s leading high-technology firms now
demonstrate contrasting behavior. The bipolariztion of profitability is observed. Given thesignificance of such a bipolarization in innovation inducement and consequent global
competitiveness structure, this paper attempts to demonstrate the co-evolutionary

dynamism between
bipolarization.

profitability

and

1. 導入

productivity,

andmechanismof額）の推移を求めたものである。但し、ここ日本経済はロスト・ディケードと呼ばれたで定義したある年（T）のR&D生産性は（T－

長期にわたる景気の低迷状態から抜け出たよ

４年からT年）までの５年間の累積営業利益をうに見えるが、回復が十分でない企業と以前同じ過去の5年間の累積R&D投資で割ったもの

以上の利益率を達成する企業も存在する。

である。1990年代はほぼ一貫して生産性を下

図1は電気機械企業における売上高上位10げているが、昨今の好調な経済環境を反映し社の過去30年間の売上高営業利益率（OIS）をか生産性が向上する兆しを見せ始めているも5年ごとにグループ化した値を示したものであのの、1994年時点の水準までには至っていなる。

い。

収益力の差が近年明らかに拡がってきてい170%る。両企業群間には大きな収益力の格差が生160%

じてきており、OISの2極化が顕著に現れてき

150%

ている。
0.14

0.12

日立

松下

ソニー

東芝

NEC

富士通

ｷｬﾉﾝ

三菱電機

シャープ

R
& 140%
D
生
産 130%
性
120%

サンヨー

売
上
高
営
業
利
益
率

0.1

110%

ｷｬﾉﾝ
松下

0.08

100%
1994 1995

ソニー

1996

1997 1998

1999

2000 2001

2002

2003 2004

シャープ

0.06

図2. R&D生産性の推移.

0.04

出典: 経済財政白書2005および科学技術研究調査0.02

報告 (1980-2006) を基に作成.

01975-1979

1980-1989

1990-1999

2000-2005

年

図1. 電気機械企業売上高上位１０社の売上高-営業利益率（OIS）の推移.

図1、図2の両図を見ても分かるように、収益と生産性は相互関係にあり、生産性の向上
が収益に結びつき、その収益追及姿勢が生産

図2はR&Dの生産性 （＝営業利益/R&D投資

380

性向上にフィードバックし、収益が向上する

バブル崩壊から回復基調となってきた2002-という共進化サイクルをうまく回していると

2005年の４年間で平均時価総額以上を維持しころは、収益力をますます体化し収益をあげている39社を日経NEEDS・データベースによる一方、それをうまくできない企業は悪循環り選択した。

に陥っており、ますます収益を下げて、この表1

共進化ダイナミズムが見られるようになって企

対象企業一覧
業

名きた結果、2極化が観察される結果となってき

１

キヤノン

21

ダイキン工業ているのではないかという仮説が導かれる。

２

ソニー

22

オムロン

３

松下電器産業23

コニカミノルタホ

2. 分析手法
2.1 同時方程式モデル

ールディングス

４

日立製作所

24

船井電機

同時方程式モデルとは経済変数間の複雑な

５

シャープ

25

ヒロセ電機

相互依存関係を、複数個の方程式で表すモデ

６

ファナック

26

パイオニア

ルのことをいう。この手法は一般的に需要関

７

ローム

27

マブチモーター

数・供給関数のモデル化、家計の消費関数の

８

京セラ

28

横河電機（＊）

モデル化に用いられるが、ここでは、OIS（収

９

リコー

29

スタンレー電気

10

東芝

30

カシオ電算機

11

村田製作所

31

イビデン

12

富士通

32

アルプス電気13

ＮＥＣ（＊）

33

日本精工

14

東京エレクトロン

34

ウシオ電機

15

三菱電機

35

ブラザー工業

キーエンス

36

富士電機ホールデ

OIS t および TFPt はそれぞれ、t年の売上高

16

営業利益率、t年のTFP をあらわす。 OIS t お

17

ＴＤＫ

３７

沖電気工業

18

アドバンテスト38

日本ビクター

19

三洋電機

39

太陽誘電

20

日本電産

益力を表わす指標）とTFP （R&D生産性を表す指標）の相互作用を同時方程式モデルによって検証する。
モデル式は以下の (2-1)、(2-2) である。

OIS t = α 1TFPt + β 1 OIS t −1
TFPt = α 2 OIS t + β 2 TFPt −1

(2-1)
(2-2)

よび TFPt は内生変数であり、 OIS t −1 およびTFPt −1 は先決変数である。

ィングス

同時方程式モデルでは普通の最小二乗法を用いると、推定したパラメータにバイアスが3.2 TFPの算出発生するため、この同時方程式モデルを2段階

TFPの算出にはAw, B. Y. et al. (2001）の研究

最小二乗法により推定する。

で用いられた (3-1)式の推計方法によって算出した。TFPは単純に言えば、生産高から労働、

3. 分析

資本、中間投入の貢献を引いて余った残差で3.1 分析対象企業ある。すなわち、生産高への労働、資本、中表1は対象企業として選択した39社の一覧表

間投入以外の貢献を示すものである。TFPは技である。

術革新、労働の質の向上、資本の熟度、経営選択基準は電気機械産業を対象として、ITの改善、生産効率をも包摂しており、研究開381

発投資効果以外の効果も含まれてはいる（渡力が高く、逆にロスト・ディケードと呼ばれ辺ほか(2001)）。しかしながら、これらはすべ

る1990年代は最も低い平均値となっている。

てイノベーションと深いかかわりを持つもの

2000年代はITバブル崩壊による影響はあったであり、TFPはイノベーションを計測するのにものの全体としては回復傾向が見られる。
ばらつきを示す標準偏差に注目すると、各有効な指標であると考えられる。

(

)

(

ln TFPf ,t = ln Y f , t − ln Yt + ∑ s =1 ln Ys − ln Ys −1

(

t

)(

)

企業間で収益のばらつきが大きくなってきて)

1
S i , f , t + S i , t ln X i , f , t − ln X i , t
2tn 1− ∑ s =1 ∑ i =1 S i , s + S i , s −1 ln X i , s − ln X i , s −12
− ∑ i =1n()(

いることを示しており、これが収益の2極化傾向を示唆するものである。

)

(3-1)

Yf,t は t 年における産出. Xi,f,t はt年の企業

1980年
1990年
2000年

f の3つの生産要素 i の投入量、 Si,f,t はt年の企業 f の3つの生産要素 i のコストシェアで

最小値

最大値

平均

0.020
-0.008
0.008

0.393
0.392
0.479

0.099
0.079
0.091

表2

ある。数字上の線は平均を示す。

標準
偏差
0.076
0.081
0.098

分布の基本統計量

各企業の生産高の算出は売上高を企業物価
図3、図4、図5は各年代のOIS分布の形を示

指数で1995年価格に換算したものである。
労働、資本、中間投入の3つの生産要素の算

すヒストグラムである。縦軸は度数、横軸は出方法については労働の投入量は、従業員数

OISの水準を表示したものである。なお、数字に労働時間をかけたものとした。資本投入量のOISが0.21を超えるものについてもすべて0.2の算出は、土地以外の有形固定資産を形態別に含まれている。
7

総資本形成デフレータで1995年価格に換算したものを用いた。中間投入の算出については、

65

売上原価+販売費・一般管理費－(人件費 + 減

4価償却費) を企業物価指数で1995年価格に換算3したものを用いた。
2

コストシェアの算出については、労働費用、資本コスト、中間投入費用を足した総費用に

1
00

対する各要素のシェアとして求めた。ここで0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.2

図3. 売上高営業利益率 (OIS) の分布図

労働費用とは人件費、資本コストは資本投入＜1980年代＞.

量に資本のサービス価格(Jorgenson, D. W. and

12

Griliches Z. (1995)) をかけたもの、中間投入費
10用は中間投入そのものの値を用いた。
8

4. 分析結果

6

4.1 収益分布の分析

4

近年、収益の2極化が起きているのかを統計

2

的かつ視覚的に検証するために、収益の分布

0

-0

0

0.01 0.02 0.03 0.04 0.05 0.06 0.07 0.08 0.09 0.1 0.11 0.12 0.13 0.14 0.15 0.16 0.17 0.18 0.19 0.2を分析した結果を表2に示す。この表から分か
図4. 売上高営業利益率 (OIS) の分布図

ることは、1980年代は概して日本企業の収益

382

α2
ロスト・ディケード
（1994-1997）
IT バ ブ ル 期 (19982001)
IT バ ブ ル 崩 壊 後(2002-2005)

β2

1.163

1.149

(6.45)(22.17)-0.1581.041(-0.679)(38.83)

0.217

1.120

(3.57)(162.20)

TFPt = α2 OISt + β2 TFPt-1

adj. R 2
0.754

括弧内の数値はt値
5. 分析結果の考察

0.204

ITバブル崩壊後の産業界では、R&Dの効率

0.920

的展開による生産性の向上はますます重要となってきている。収益悪化、生産性低減に陥＜1990年代＞.

っている企業は収益悪化と生産性低減の悪循

12環に陥り、高収益企業は、高生産性を力とし10て両者の好循環によるそれらを上昇させるこ8とができる。こうした結果として2極化が顕在6化することとなっている。
4

References

2

0
0

0.01

0.02

0.03

0.04

0.05

0.06

0.07

0.08

0.09

0.1

0.11

0.12

0.13

0.14

0.15

0.16

0.17

0.18

0.19

0.2

[1]

Aw, B. Y., Chen, X. and Roberts, M. J. (2001).
Firm-level
Evidenceon
Productivity
Differentials and Turnover in Taiwanese
Manufacturing. Journal of Development
Economics, 66(1), 51-86.

[2]

Cabinet office, Government of Japan(19942006), Annual Report on National Accounts.
Tokyo: Cabinet Office, Government of Japan.
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Paper. Tokyo: Cabinet Office, Government ofJapan.

[3]

Cabinet Office, Government of Japan (2005).
Economy and Public Finance White Paper.
Tokyo: Cabinet Office, Government of Japan.

[4]

Fukao K., Inui, T., Kawai, H., Miyagawa, T.
(2003). Sectoral Productivity and Economic
Growth in Japan, 1970-1998: An Empirical
Analysis Based on the JIP Database. ESRI
Discussion Paper Series, 67.

[5]Jorgenson, D. W. and Griliches Z. (1995). The
Explanation of Productivity Change. In D. W.
Jorgenson (ed.), Productivity Volume 1:
Postwar U.S. Economic Growth, Cambridge,
Mass.: The MIT Press, 1995.

[6]

Klomp, L. and van Leeuwen, G. (2001).
Linking Innovation and Firm Performance: A
New Approach. International Journal of the
Economics of Business, 8(3), 343-364.

[7]

Ministry of Health, Labour and Welfare(1994-2006), Monthly Labour survey. Tokyo:
Ministry of Health, Labour and Welfare,
Government of Japan.

図5. 売上高営業利益率 (OIS) の分布図
＜2000年代＞.

1980年代には平均化していた収益であるが、徐々にばらつき始めていることが分かる。
4.2 同時方程式モデルの結果
表3、表4は同時方程式モデルの算出結果を示したものである。2003-2006年のITバブル崩
壊後の値のみ、 α 1 or α 2 のt値が有意となっロスト・ディケード
（1994-1997）
IT バ ブ ル 期 (19982001)
IT バ ブ ル 崩 壊 後(2002-2005)

α1β1adj. R-0.003

1.068

0.920

(-0.47)(34.18)-0.0030.862(-0.28)(11.73)

0.011

0.918

(2.78)(24.50)

2

0.560
0.865

ていることから、OIS とTFPに相互作用、共進化が起きていることが示している。
表3 同時方程式の推定結果(1)モデル式： OISt = α1 TFPt + β1 OISt-1
括弧内の数値はt値
表4 同時方程式の推定結果(2)383

The Analysis of the Bipolarization of Profitability amongst Japanese Hi-technology
Firms: The disparity of effort for external acquisition
Koji Moriyama**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-49 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
moriyama.k.aa@m.titech.ac.jp
The homogeneous behavior is what Japanese firms used to be. Japan’s leading hightechnology firms now demonstrate contrasting behavior. The bipolariztion of profitability
is observed after the Informaiton society. The bipolarlization seemes caused by thedisparity of learning effort for external aquisition. The external acquisition is the key oftodays R&D. This paper showed the disparity between high profitable firms and low
profitable firms.

電気機械企業の研究開発強度は1980年代に入

1．背景り、急激に増加した。バブル経済の崩壊後、
図1は産業レベルの電気機械企業の研究開発

多少減少するも、景気回復期にかけて、増加効率を示している。前5年の累積の営業利益をしている。研究開発のインプットの量はそれさらにその5年前の累積研究開発費で割ったもほど落ち込んではいないが、近年イノベーシのを研究開発効率と定義した（c.f. 「平成17年

ョンが少ないといことがところどころで言わ経済財政白書」）。1980年から2005年までのれている。

研究開発効率はほぼ年々下がっている。研究0.075

開発活動に問題があると考えられる。そして、

0.07
0.065

近年日本発のイノベーションがないといわれ

0.06て久しいが、イノベーションの源泉たる研究

0.055
0.05

開発がどのような状況になっているのか、分

0.045

析する。

0.04
0.035
0.03
19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04

4
3.5
3
2.5

図2.

2

研究開発強度（売上高に対する研究開発投資比率）の推移（1974-2005*）.

1.5
1

資料:

0.5

科学技術研究調査報告.
*

2002年から電気機械が3つに分割.

19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00
20
02
20
04

0

図3に電気機械産業の売上高営業利益率をし
図1.

電気機械企業の研究開発効率の推移.

めす。売上高営業利益率1970年代には、高度

資料: 科学技術研究調査報告.

成長が終わってからも一定の利益率は確保できていた。しかし、1980年代に入ると、利益

図2に電気機械産業の研究開発強度をしめす。

384

率が下がり始める。バブル経済の絶頂期に多

0.25
0.23
0.21
0.19
0.17
0.15
0.13
0.11
0.09
0.07
0.05

少の利益率の改善がみられるも、以前の水準には届いていない。1990年代のロスト・ディ
ケードの期間は下降トレンドであったが2000
年頃から一時的に回復するも、アメリカのIT
バブル崩壊により2001年は大幅に落ち込んでいる。近年の家電のデジタル化などにより、

19
74
19
76
19
78
19
80
19
82
19
84
19
86
19
88
19
90
19
92
19
94
19
96
19
98
20
00

需要が拡大しており近年電機機械産業全体では好景気を謳歌している。好景気に頼るのではなく、イノベーションにより、さらなる付

図4.

新規技術輸出比率の推移.

加価値のある産業となり永続性のある産業へ

資料:

科学技術研究調査報告.

と脱皮しなければならない。
2．研究開発投資既存研究レビュー
0.09
0.08
0.07
0.06
0.05
0.04
0.03
0.02
0.01
0
-0.01

イノベーションを生み出すには企業の大きさは大きいほうがよいのか、小さいほうがよいのかShumpereter（1942）は大企業のほうが、研究開発に資源をつぎ込めるし、規模が大き

19
71
19
74
19
77
19
80
19
83
19
86
19
89
19
92
19
95
19
98
20
01
20
04

くさまざまな部署との連携ができ効率的な研図3.

究開発ができると主張した。しかし、大きくなりすぎると慣性が大きくなり、研究開発の電気機械企業の売上高営業利益率の推移の方向性の転換、研究者の評価の難しさが表面

推移（1974-2005*）.
資料:化し、研究開発効率が低下するという指摘も科学技術研究調査報告.

な さ れ て い る （ （ Cohon and R. Levinthal*

2002年から電気機械が3つに分割.

（1989）、Rotemberg and Saloner（1994））。
そして、組織が自ら開発したもの以外は認め

日本企業が、イノベーションと考えられる技術をないというNIH（Not Invented Here） シンドロ

開発したならば、それが海外企業にも供与などさームに陥る（Katz and Allen（1986））。

れ、新規技術輸出が増加すると考えられる。したがCohen and Levinthal（1990）は、外部技術・って、この新規技術輸出比率をイノベーションの指資源獲得はイノベーションにとって重要であ標の一つとして新規技術輸出比率のグラフを図4ることを実証した。

に示す。利益率の高かったバブル期にかけてその外部技術・資源だけに目を向ければよいと比率は増加している。しかし、そしてその後、減少いうわけではなく、その獲得は内部研究開発傾向にある。すなわち、新規技術輸出は日本の電力がないとどれが必要な外部技術・資源獲得

気機械企業も他企業と同様に好収益を上げていかを認識できない（Rosenberg（1994））。すた背景には、景気拡大はもちろん研究開発活動のなわち、R&D投資により、技術に対する知識

イノベーション創出能力も高かったと考えられる。

をつけると他の技術を吸収する力（Absorptive
capacity ） を 高 め る こ と が で き る 。 Jaffe（1986）は企業の特許取得活動収益はその地

385

方の他企業、大学の研究開発投資と深い関係

2極化をイノベーション能力の差ととらえ、があることを示し、スピルオーバーの効果を

ダミー変数を用いたパネルデータ分析をおこ明らかにした。Huston and Sakkab（2006）ではなった。被説明変数に研究開発強度（売上高

P&Gの外部技術・資源獲得姿勢が紹介されてに対する研究開発投資比率: R/S）、説明変数いる。

にイノベーション指標と考えられる新規技術

Eident and Martin（2000）は即座に組織構造

輸出量（INN）を使う。この新規技術輸出量はを認識し技術や市場の変化に対応するダイナ

産業別の数値である。各社が同じイノベーシ

ミックケイパビリティを議論した。

ョンを行った時に、研究開発投資の貢献がど

外部技術・資源獲得は経路依存性すなわち、 うなるのかという考えでこの回帰分析モデル
ある技術開発をしているときにそれとまったを用いた。

く関係のない領域では、獲得が難しくなり、

技術輸出量と研究開発投資の相関分析の結自 ら の 経 路 周 辺 で し か 獲 得 で き な い （ Dosi

果を表1に示す。イノベーション指標は各社共（1988））。

通であり、所与であると考える。それと各社

Brown （1997） によれば、成功するイノベの意思決定の産物である研究開発投資との関ーターはイノベーション戦略マネジメントプ係をみる。高収益企業群では弾性値が負で、ロセスをきっちり立てている。すなわち、イ

低収益企業群では正となっている。イノベー

ノベーションはやみくもに起こるのではなくション度合いに対して、正であるとはイノベ計画して起こされる。すなわち、それをマネ

ーション数とともに研究開発活動投資を抑制、ージメントすることは可能である。すなわち、 負の場合はその逆である。高収益企業群ではイノベーションをどのようにして起こすかとイノベーションが起こった時、研究開発投資いう議論の重要性をサポートしている。

を減らしている。しかし、低収益企業群では、研究開発投資が増加している。これを解釈す
るならば、イノベーションが起こる時、図6の3 電気機械企業2極化要因パネルデータ分析

Aに示すような、外部資源獲得に動いていると
図5に電気機械企業売上高上位10社の売上高いうことと解釈できる。一方、低収益企業群

営業利益率の推移をしめす。売上高営業利益

は研究開発投資が重荷となり、低収益にあえ

率は1980年代、1990年代は全社同じ動きをしぐ結果となっている。

ていたが、近年2極化がみられる。
0.14

0.12

日立

松下

ソニー

東芝

NEC

富士通

ｷｬﾉﾝ

三菱電機

シャープ

表1

Variables

サンヨー

売
上
高
営
業
利
益
率

0.1

パネルデータ分析の結果（固定効果モデル）

ｷｬﾉﾝ
松下

0.08

ソニー
シャープ

0.06

Estimated
Coefficient

INN1
INN2

-0.2530.090

R-squared
F value

0.471
24.16

0.04

0.02

0
1975-1979

1980-1989

1990-1999

2000-2005

年

図5.

売上高営業利益率の推移（1975-2005）．

386

t-statistic
-3.41
2.43

1990. 35(1): p. 128-152.
[4] Dosi, G., Sources, Procedures, andF˝－ RMicroeconomic Effects of Innovation. Journal
OI
販売費及び
F´－R
F－R
F－R
一般管理費 Fof Economic Literature, 1988. 26（3）: p.
S
R = R －A
A+αR
RR
1120-1171.
A
獲得外部資源[5]
Eisenhardt,
K.M. and J.A. Martin, Dynamic
OI
OI = OI + A
OIOIcapabilities: what are they? Strategic
Management Journal, 2000. 21: p. 1105-1121.
R
R
R
R[6] Granger, C. W. J., Investigating Causal
Relations by Econometric Models and Cross図6. イノベーションと外部資源獲得及び利益率
Spectral Methods, Econometrica, 1969. 37: p.
の関係.
424-438.
[7] Huston, L., and N., Sakkab,, Connect andDevelop: Inside Procter & Gamble’s New
4 結論
Model for Innovation. Harvard Business
Review , 2006. 84(3); p. 58-66.
[8]Jaffe, A.B., Technological Opportunity and外部技術・資源獲得の状況の変数として、Spillovers of R & D: Evidence from Firms'
イノベーション時に、研究開発投資がどのよ
Patents, Profits, and Market Value. The
American Economic Review, 1986. 76（5）: p.
うになっている要かを考察した。もし、研究
984-1001.
開発投資が減るようだと、外部技術・資源獲[9] Katz, R., and T., J, Allen, Investigating the Not
得に動いているとみなし、増えているようだ
Invented Here （NIH） syndrome: A look at
theperformance, tenure, and communicationと自社開発という方向に動いていると考えら
patterns of 50 R&D project groups. R&D
れる。その結果として、2極化の原因としては、Management, 1982. 12（1）: p. 7-19.
外部資源獲得への積極性が示唆された。
[10] National Science Foundation, Science andEngineering Indicators 2006. 2006. Virginia:
イノベーションには、外部技術・資源獲得
National Science Foundation .
をすることが重要である。しかし、自前で開[11] Rosenberg, N., Exploiting the Black Box:
Technology, Economics, and History. 1994,
発しないと、必要な外部技術・資源が見えて
Cambridge: Cambridge University Press.
こないので、外部技術・資源獲得能力が高ま[12] Rotemberg, J.J. and G. Saloner, Benefits ofNarrow Business Strategies. The American
ることはない。この、オープンというべき態
Economic Review, 1994. 84(5): p. 1330-1349.
度および、真摯自らの道を進み研究開発する[13] Shumpeter, J. A., Capitalism, Socialism an
クローズとでもいうべき態度の両方が求めら
Democracy. 1942, New York: Harper &Brother Publishers.
れている。
[14] 総務省, ｢科学技術研究調査報告｣, （総務省, 東京, 各年版）.
参考文献[15] 内閣府,「平成 17 年 経済財政白書」,（内閣府,東京, 2005）.
[1] Brown, S.L. and K.M. Eisenhardt, The Art ofContinuous Change: Linking Complexity
Theory and Time-Paced Evolution in
Relentlessly Shifting Organizations.
Administrative Science Quarterly, 1997. 42（1）: p. 1-34.
[2] Cohen, W.M. and D.A. Levinthal, Innovationand Learning: The Two Faces of R & D. The
Economic Journal, 1989. 99(397): p. 569-596.
[3] Cohen, W.M. and D.A. Levinthal, Absorptive
Capacity: A New Perspective on Learning andInnovation. Administrative Science Quarter,
R/S 牽引 (内部での吸収)V˝

OIR 牽引(外部からの吸収)VV´

売上原価 V

3

4

3

2

3

2

3

2

2

1

1

1

387

SIMOT and Optimization
Tomonari Kitahara
Department of Industrial Engineering and Management
Tokyo Institute of Technology
kitahara.t.ab@m.titech.ac.jp

3.

1. Optimization –on my research-

From Optimization to SIMOT•

Real Problems : Full of decision making– Ex. Production planning, Logistics, Finance• For reasonable decision making
1. Modeling problems into mathematicalformula2. Solving the problem by mathematicalmethods & computers• Strong interests in mathematical methods

Sophisticated modeling techniques developed in
the long history of Optimization

Strong driver for conceptualizing the co-evolution
between innovation cycle and institutions

2. Goals of SIMOT

From SIMOT to Optimization

Elucidating, conceptualizing and

SIMOT’s goal : Very complex, hard

operationalizing the co-evolutionary
dynamism between innovation cycle andinstitutions, leading to accruing to global assets.
New methodologies are needed

New scope on Optimization

4.
My hope- co-evolution of SIMOT
and Optimization –•Close, positive relation between SIMOT
and Optimization•

Co-evolution of SIMOT and
Optimization388

ミニマックス基準の下での判別規則の研究
北原＊東京工業大学

知就＊

社会理工学研究科 経営工学専攻

東京都目黒区大岡山 2-12-1 W9-526
kitahara.t.ab@m.titech.ac.jp
概要
本研究では Lanckriet et al. (2002) によって提案された線形ミニマックス判別問題の 2 つの一般化を提案し，それらの間の関係を理論的に解析する．１つは 2 次ミニマッ
クス判別問題であり，もう 1 つは凸集合ミニマックス判別問題である．本研究の結果，本質的に線形ミニマックス判別問題の最適解から 2 次，凸集合ミニマックス判別問題の最適解が構成できるという非常に興味深い性質が示される．
マックス基準の下で線形判別関数を求め1．はじめにる問題を線形ミニマックス判別問題と呼平均ベクトルと分散共分散行列が与えられた 2 つの群を判別することを考える．

ぶ．
本研究では，ミニマックス線形判別問

このような状況は，保持する情報の少な

題の二つの一般化を提案し，それらの問さもあり，しばしば見られる．
判別関数を決定する際，なるべく判別

題の関係を解析する．１つは 2 次ミニマ

精度をよくしたい，というのは当然の要ックス判別問題であり，もう 1 つは凸集求である．しかし，判別の精度は各群の合ミニマックス判別問題である．これら

平均ベクトル，分散共分散行列だけでなの問題の詳細については後の節で述べる．

く，各群の分布形にも依存する．このよ

本研究によって得られた主な知見は次うな課題に対し，Lanckriet et al. (2002)の 2 点である．第 1 点は，本研究で提案

は，線形の判別関数で 2 群を判別する際，した問題は，線形ミニマックス判別問題

各群に対し与えられた情報を満たすすべの一般化であるのにもかかわらず，本質ての分布形を考えた時の最悪の(マック的には線形ミニマックス判別問題を解けス)場合の誤判別率を最小に（ミニ）する

ば，その最適解から各問題の最適解が構ような判別関数を選ぶことを提案した．

成できるということである．第 2 点は，

このようにすることで，実際の分布形が一般化によってより小さな最悪の場合のどのようなものであっても判別精度がそ

誤判別率を与える判別規則が得られる可れほど悪くはならないものと期待される． 能性があったが，実際は全て同じになる，ということである．

本稿ではこの基準をミニマックス基準と呼び，Lanckriet et al. が提案したミニ389

3．2 次ミニマックス判別問題

2．線形ミニマックス判別問題

平均ベクトル，分散共分散行列が既知

平均ベクトル，分散共分散行列が( µ i , Σ i ) (i = 1, 2) である 2 群があるとする． な 2 群を 2 次の判別関数
以下では，各分散共分散行列は正定値でq ( z ) = z T Az + 2b T z + c

あるとする．サンプル x が与えられたとを用いて判別することを考える．このとTき，線形判別関数 l ( z ) = a z + b を用いて

き， A は対称であるが，凸であることは判別する．すなわち， l ( x) < 0 ならば第 1仮定しない．このとき， q( z ) の最悪の場

群に， l ( x) > 0 ならば第 2 群に判別し，合の誤判別率 α q は，l ( x) = 0 ならばどちらに判別しても良いとする．判別関数が与えられたとき，第 1

α q = max{α q12 , α q 21 } (2)群のサンプルが第 2 群に誤って判別される確率は第 1 群の平均ベクトル，分散共ただし，分散行列だけではなく，第 1 群の分布形にも依存する．そこで，平均ベクトルが µ1 ，分散共分散行列が Σ1 であるような全ての

α q12 = sup x ~ ( µ ,Σ ) Pr{x T Ax + 2b T x + c ≥ 0}
1

1

α q 21 = sup x ~ ( µ ,Σ ) Pr{x T Ax + 2b T x + c ≤ 0}1分布を考えたときの誤判別率の上限を考
え，それを

1

である．2 次ミニマックス判別問題とは(2)で定義される最悪の場合の誤判別率

α l12 = sup x ~ ( µ ,Σ ) Pr{a T x + b ≥ 0}
1

1

α q を最小にするような 2 次判別関数を求と表す．同様に，第 2 群のサンプルを第 1群に誤って判別する確率の上限 α l 21 は，める問題である．このときの最適値を α Q*

α l 21 = sup x ~ ( µ ,Σ ) Pr{a T x + b ≤ 0}22と表す．ここで，線形関数は 2 次関数のと表される．そして，判別関数 l (z ) の最特別な場合であるから，悪の場合の誤判別率 α l を

α Q* ≤ α L*

α l = max{α l12 , α l 21 } (1)(3)と定義する．線形ミニマックス判別問題という自明な不等式が成り立つことに注は，最悪の場合の誤判別率を最小にする

意する．

線形判別関数を求める問題である．以下
では，この問題の最適値を α L* と表す．

4．凸集合ミニマックス判別問題

Lanckriet et al. (2002) は線形ミニマ

線形判別や 2 次判別で利用される判別

ックス判別問題が 2 次錐計画問題に帰着規則はある集合とその外部，および境界され，効率的に解くことができることをによって特徴付けられる．例えば，線形示した．

判別の場合，

S = {z ∈ ℜ n | a T x + b < 0}とすると，判別規則は S とその外部

390

ext ( S )最適解を l * ( z ) = (a * ) T z + b * とする．このext ( S ) = {z ∈ ℜ n | a T x + b > 0}
および境界 bd ( S )とき，半開区間

H * = {z ∈ ℜ n | (a * ) T z + b * < 0}bd ( S ) = {z ∈ ℜ n | a T x + b = 0}

は凸集合ミニマックス問題の最適解となる．したがって， α C * = α L* となる．

によって特徴付けられる．そこで，線形ミニマックス判別問題のもう一つの一般

この定理を証明するに当たり，次の命化として，一般の集合 S を考えることは題が非常に重要である．この命題は，そ興味深い．本研究では，その第一歩としれ自身非常に興味深い結果であるので，て S を開凸集合に限定する．

ここに記す．

開凸集合 S が与えられたとする．この

命題 2．(Marshall and Olkin (1960))

とき，サンプル x が S に属するならば第 1

平均ベクトルが µ ，分散共分散行列が Σ群に， ext ( S ) に属するならば 第 2 群にである確率変数があるとする．また，T を判別し， bd ( S ) ならばどちらに判別して凸集合とする．このとき，も良いとする．このとき， S の最悪の場

1,
1+ d 2d 2 = inf z∈T ( z − µ ) T Σ −1 ( z − µ ),sup x ~ ( µ ,Σ ) Pr {x ∈ T } =合の誤判別率 α S は，

α S = max{α S12 , α S 21 } (4)が成立する．

ただし，

命題 2 は平均ベクトル，分散共分散行

α S12 = sup x ~ ( µ ,Σ ) Pr{x ∈ bd ( S ) U ext ( S )}11

列が既知な確率変数が与えられた凸集合

T に属する確率の上限が， T と平均との

α S 21 = sup x ~( µ ,Σ ) Pr{x ∈ bd ( S ) U S }22ある種の距離によって与えられることを示している．

である．凸集合ミニマックス判別問題とは，この α S を最小にする開凸集合を求め

次の命題は，2 次ミニマックス判別問題

る問題である．この問題の最適値を α C * とにおいて判別関数の凸性を仮定してよい

する．なお，線形判別関数によって定まことを示している．
命題 3．任意の 2 次関数 q( z ) に対して，る判別領域は開凸集合であるから，

α C * ≤ α L* (5)ある凸 2 次関数 g ( z ) が存在して，なる関係が成立することに留意する．

αg ≤ αq5．各問題間の関係を満たす．ただし，α q , α g は(2)で定義さこの節では，本研究の結果明らかになった各問題間の関係を簡潔にまとめる．

れる．

なお，紙数の関係上証明は割愛するが，

定理 1 および命題 3 から 2 次ミニマッ

詳細は Kitahara et al. (2007) を参照さ

クス判別問題に関して次の定理を証明すれたい．

ることができる．

定理 1． 線形ミニマックス判別問題の定理 4．線形ミニマックス判別問題の最391

適解を l * ( z ) = (a * ) T z + b * とする．このと[2]

Lanckriet, G.R.G., El Ghaoui, L.,
Bhattacharyya C., and Jordan, M.I.,
2002. A Robust Minimax Approach toClassification, Journal of Machine
Learning Research 3, 555-582.

[3]

Marshall, A.W., and Olkin, I., 1960.
Multivariate Chebyshev inequalities,
Annuals of Mathematical Statistics,
31(4) 1001-1014.

き， l * ( z ) は 2 次ミニマックス判別問題の最適解である．よって，α Q* = α L* となる．
定理 1，定理 4 の興味深い点は，2 次，
凸集合ミニマックス判別問題を解くことは難しいように思われるが，実際には線形判別問題を解くことでそれらの最適解が得られる，という点にある．更に，線
形ミニマックス判別問題の一般化によってより小さな最悪の場合の誤判別率を持つ判別規則を得られる可能性があったが，実際にはそのようなことはなく，3 つの問
題で全て一致するというのも注目に値す
る．
6．結論
インスティテューショナル技術経営学(SIMOT)の「イノベーションとインスティ
テューションの間の相互作用を解明し，可視化，操作化できるようにする」という目的において，判別技術の発展は必要不可欠である．本研究では Lanckriet etal. (2002) によって提案された線形ミニ
マックス問題の 2 つの一般化を導入し，それらの問題間の関係を理論的に解析した．
今回得られた知見は数学的な結果であるが，この結果が SIMOT の学術的進展に少しでも貢献することがあれば，著者にとって望外の喜びである．
参考文献
[1]

Kitahara, T., Mizuno, S., Nakata, K.,
2007. Generalizations of the Linear
Minimax
Classification
Problem.
Technical report.

392

一般化チェビシェフ不等式とその最適化への応用
北原＊東京工業大学

知就＊

社会理工学研究科 経営工学専攻

東京都目黒区大岡山 2-12-1 W9-526
kitahara.t.ab@m.titech.ac.jp
概要
一般化チェビシェフ不等式 Vandenberghe et al. (2007)とは，平均ベクトルと分散共分散行列が既知な確率変数がある 2 次不等式によって記述される領域に入る確率の下限を与えるものである．本研究では一般化チェビシェフ不等式の最適化への 2 つの応用を提案する． 1 つ目の 2 次ミニマックス判別問題は平均，共分散がわかっている 2 つのクラスを判別するための 2 次関数を求める問題である．このとき，各クラスに様々な分布を考えたときの最悪の場合の判別率が最良なものを求める．2 つ目は，平均，共分散が与えられたとき，(1)確率変数の分布形によらずそこに入る確率がある要求水準以上である，(2)体積がなるべく小さい，という 2 つの条件を満たす楕円を決定する問題(確率制約付最小楕円決定問題)である.本研究によって，各問題に対して興味深い理論
的性質，数値実験の結果が示される．
1．はじめに

ここで,世の中の多くの事象は確率変数によっであり，我々が知りうるのは，その平均⎧1 / 2k 2 ( X = µ − kσ )⎪Pr ( X ) = ⎨1 − 1 / k 2(X = µ)⎪1 / 2k 2 ( X = µ + kσ )⎩や分散といったごく一部の情報である．

という確率変数を考えると,その平均はそれにも関わらず，その変数によって制µ ，分散は σ 2 であり,かつて記述される．しかし，その確率変数についての完全な情報を得ることは不可能

御される事象が起こる確率を見積もらな

Pr{| X − µ |< kσ } = 1 −くてはならないことは多々ある．

1
k2

1 次元の確率変数 X があり，その平均となる．このように,実際に下限を達成すを µ ，分散を σ とする．今, k を 1 よりる確率変数が存在するという意味で(1)大きいスカラーとする．このとき,次の関は厳密な不等式である．

2

最近は,1 次元のチェビシェフ不等式を係が成り立つことが知られている．

Pr{| X − µ |< kσ } ≥ 1 −

1
(1)
k2

多次元に拡張した一般化チェビシェフ不等式が Vandenberghe et al. (2007)など(1)はチェビシェフの不等式と呼ばれる．

393

で盛んに研究されている．一般化チェビ

シェフ不等式については 2 節で詳説する

ト最適化等との関連から,このような問が,その重要な点として,次の 2 点が挙げ題を考えることは重要である．この問題られる．

については,数値実験の結果から,最適な1. (1)に見られるように,1 次元のチェ

楕円の形状が分散共分散行列から決定さビシェフ不等式において確率を見積れるという興味深い現象が観察された．

もる領域が平均を含む区間であるの

本稿では S n は n 次元実対称行列の集合に対し,一般化チェビシェフ不等式

を表し，ℜ n は n 次元実ベクトルの集合をではより広い領域を許す．

表す.

2. (1)のように確率の下限を陽に与えることはできないが,関連する半正2．一般化チェビシェフ不等式

定値計画問題を解くことで確率の下限とそれを達成する分布を構成する

n 次元の確率変数 X があり,その平均ベクトル，分散共分散行列 ( µ , Σ) が既知でことができる．ここで半正定値計画あるとする．本稿では以下このことを問題とは,近年の内点法アルゴリズ

X ~ ( µ , Σ) と表記する．いま,有限個の 2ムの発展により効率的に解くことが次不等式制約によって定まる次の領域

できるようになった重要な数理計画

T

T = {x ∈ ℜ n | x T Ai x + 2bi x + ci < 0,問題である．

∀i = 1,..., m} (2)このような最近の研究の動向を踏まえ,
著者らは一般化チェビシェフ不等式の 2が与えられているとする．ここで , ( Ai , bi , ci ) ∈ S n × ℜ n × ℜ (i = 1,...m) でつの応用を研究した．一つは 2 次ミニマ
ックス判別問題である．これは,平均ベクあり,各 Ai は半正定値であるとは限らな

トルと分散共分散が既知な 2 つのクラス

い ． Vandenberghe et al. (2007) はが与えられたとき,様々な分布を考えた

X ~ ( µ , Σ) なる確率変数が T に入る確率

ときの最悪の場合の判別率が最良であるの下限,すなわち inf X ~ ( µ ,Σ ) Pr{ X ∈ T } が2 次判別関数を決定する問題である．この問題はパラメータ付半正定値計画問題と次の半正定値計画問題の最適値であるこ

して定式化されるが,著者らは最適な 2 次とを示した：

判別関数の中に線形のものが含まれるとm

min 1 - ∑ λiいう興味深い性質を明らかにした．

i =1

二つ目の応用は確率制約付最小楕円決

s.t

定問題である．これは確率変数の平均ベクトルと分散共分散行列が与えられたときに,そこに入る確率が前もって決められた要求水準を満たし,かつ体積が最小

⎡ Zi
⎢z T
⎣ i

zi ⎤
f O (i = 1,..., m),λi ⎥⎦m⎡Σ + µµ T µ ⎤⎡ Z i zi ⎤∑⎥,⎢ T λ⎥ p ⎢T1⎦
i =1 ⎣ z i
i⎦
⎣ µ
T

(3)

tr ( Ai Z i ) + 2bi z i + ci λi ≥ 0, i = 1,..., m.

である楕円を決める問題である．ロバス

394

ここで, Z i , z i , λi (i = 1,..., m) が変数であ究されていることを注記しておく.詳細

る．確率の下限を達成する分布は(3)の最は割愛するが,著者らは Kitahara et al.

適解から計算することができる．

(2007)で(2)の双対問題を利用して 2 次ミ

3．2 次ミニマックス判別問題

ニマックス判別問題が次のパラメータ付
半正定値計画問題に帰着できることを明

平均ベクトル，分散共分散行列が( µ i , Σ i ) (i = 1, 2) である 2 群があるとする． らかにした：
以下では，各分散共分散行列は正定値でmin αあるとする．サンプル x が与えられたとTTT

s.t tr((Σi + µi µi )Pi ) + 2µi qi + ri ≤τ iα (i =1,2)T

き，2 次判別関数 q ( z ) = z Az + 2b z + c⎡ Pi qi ⎤⎢q T r ⎥ f O (i =1,2),i⎦⎣ i
q1 −b ⎤⎡ P1 − A⎢(q −b)T r −τ − c⎥ f O,
1
1
⎦
⎣ 1

を 用 い て 判 別 す る ( こ こ で ，( A, b, c) ∈ S n × ℜ n × ℜ , A は 凸 で な く ても良い)．すなわち， q( x) < 0 ならば第 1群に， q( x) > 0 ならば第 2 群に判別し，(4)

q2 + b ⎤⎡ P2 + A⎢(q + b)T r −τ + c⎥ f O,
2
2
⎣ 2
⎦

q( x) = 0 ならばどちらに判別しても良いとする．判別関数が与えられたとき，第 1群のサンプルが第 2 群に誤って判別され

τ i > 0 (i =1,2),

る確率は第 1 群の平均ベクトル，分散共

2 次ミニマックス判別問題に関して,著

分散行列だけではなく，第 1 群の分布形

者らは次の興味深い性質が成立することにも依存する．そこで，平均ベクトルが µ1 ， を示した．
分散共分散行列が Σ1 であるような全ての定理 1．(Kitahara et al. (2007))線形分布を考えたときの誤判別率の上限を考

ミニマックス判別問題の最適解をえ，それをl * ( z ) = (a * ) T z + b * とする．このとき，
l * ( z ) は 2 次ミニマックス判別問題の最適α l12 = sup x ~ ( µ ,Σ ) Pr{q( x) ≥ 0}
1

1

解である．

と表す．同様に，第 2 群のサンプルを第 1群に誤って判別する確率の上限 α l 21 は，

定理 1 が述べるように実際に(4)を解く

α l 21 = sup x ~ ( µ ,Σ ) Pr{q ( x) ≤ 0}
2

2

ことなく 2 次ミニマックス判別問題の最と表される．そして，判別関数 q(z ) の最適解が得られるというのは興味深い.ま悪の場合の誤判別率 α l をた，2 次ミニマックス判別問題を考えるこ

α l = max{α l12 , α l 21 } (1)とにより線形関数より良い最悪の場合のと定義する．2 次ミニマックス判別問題は， 誤判別率を持つ判別関数を得られる可能
最悪の場合の誤判別率を最小にする 2 次性があったが，実際にはそのようなこと

判別関数を求める問題である．ここに，はないというのも注目に値する．

判別関数が線形である線形ミニマックス
判別問題は Lanckriet et al. (2002)で研395

5. おわりに

4．確率制約付最小楕円決定問題

X ~ ( µ , Σ) なる n 次元確率変数がある

インスティテューショナル技術経営学とする．また, α を 0 より大きく 1 より小(SIMOT)の「イノベーションとインスティ

さい実数とする．このとき,次の 2 条件をテューションの間の相互作用を解明し，満たす楕円を決定することを考える：

可視化，操作化できるようにする」という目的において，最適化技術の発展は必要不可欠である．本研究では最近盛んに

1. 確率変数がその楕円内に入る確率の下限は α 以上である．

研究されている一般化チェビシェフ不等式の最適化への応用を 2 つ提案した.一つ

2. 楕円の体積はなるべく小さい．

は 2 次ミニマックス判別問題であり，もこの問題はロバスト最適化と呼ばれる不う一つは確率制約付最小楕円決定問題で確実性下での意思決定問題と密接な関連ある.各問題に対して，興味深い理論的性がある．

質，数値実験の結果を示した.

ここでは,簡単のため楕円の中心は確今回得られた知見は数学的な結果であ

率変数の平均とする．そのような楕円はるが，この結果が SIMOT の学術的進展にある n 次元正定値対称行列 P を用いて少しでも貢献することがあれば，著者にnE = {x ∈ ℜ : || P

1/ 2

( x − µ ) || < 1}

とって望外の喜びである．

と表される．すると,確率制約付最小楕円
決定問題は次の問題に帰着される：

参考文献

max det ( P)

[1]

s.t

Kitahara, T., Mizuno, S., Nakata, K.,
2007. Generalizations of the Linear
Minimax
Classification
Problem,Technical report.

⎡ Q r⎤⎢r T s ⎥ f O,⎣⎦
[2] Lanckriet, G.R.G., El Ghaoui, L.,
r + Pµ⎡ Q−P⎤
Bhattacharyya C., and Jordan, M.I.,⎢(r + Pµ ) T s − τ − µ T Pµ + 1⎥ f O, (5)⎣⎦2002. A Robust Minimax Approach toClassification, Journal of Machine
Learning Research 3, 555-582.

τ - tr((Σ + µµ T )Q) − 2r T µ − s ≥ τα ,P f O, τ ≥ 0.

[3]

こ の 問 題 に お け る 変 数 は( P, Q, r , s,τ ) ∈ S n × S n × ℜ n × ℜ × ℜ で ある．この問題は Maxdet 問題と呼ばれ，効率的に解けることが知られている．
予備的な数値実験を行った結果，最適な楕円の形状は共分散の逆行列の定数倍によって定まる現象が観察された．この現象の一般性の検証は，今後の課題である．

396

Vandenberghe, L., Boyd, S. andComanor, K., 2007. Generalized
Chebyshev bounds via semidefinite
programming, SIAM Revies 49, 52-64.

基底ブロック下三角行列形を用いた
重み付き最小 2 乗法と層別最小 2 乗法の解析
北原＊東京工業大学

知就＊

社会理工学研究科 経営工学専攻

東京都目黒区大岡山 2-12-1 W9-526
kitahara.t.ab@m.titech.ac.jp(統計数理研究所

土谷隆教授との共同研究)概要
重み付き最小 2 乗法は、与えられたデータ間に最もよく当てはまる線形
連立方程式を推定する手法で、各方程式にはその優先度に対応した重みが付与されている。本稿では、各方程式の重みがグループ化でき、かつグループ間の重みの比が非常に大きい場合を解析する。解析では基底ブロック
下三角行列形を用いる。解析の結果、上記の重み付き最小 2 乗法の解が、
グループごとに重み付き最小 2 乗法を用いた層別最小 2 乗法の解で近似されることが示され、さらにその差の上界が得られる。
1．はじめに⎡1 y11
⎢1 y
21
A=⎢
⎢M M
⎢
⎣1 y m1

観測した数値データから因果関係を見出すということは非常に重要である。いま、z を目的変数、 y を n 次元説明変数とするとき、

z =αT y + β

y1n ⎤L y 2 n ⎥⎥O M ⎥⎥L y mn ⎦Lとし、目的変数のデータからなるベクトを線形モデルという。ここで、 α , β はそルをれぞれ n,1 次元のパラメータであり、データからこれらを推定するのが目的である。
線形モデルは単純であり、かつその適用範囲は非常に広い。
最小 2 乗法は、与えられたデータに最⎡ z1 ⎤⎢z ⎥b=⎢ 2⎥
⎢M ⎥
⎢ ⎥
⎣zm ⎦
とする。また変数のベクトルをもよく当てはまる上記パラメータを推定

x = [β α 1 α 2 L α n ]する手法である。データの数を m とし、と定める。すると、最小 2 乗法は説明変数のデータからなる行列を

min || Ax − b || 2 と定式化される。
観測されたデータにはその精度にばらつきがあるのが普通であり、それを推定397

に反映させるのが自然である。このよう(2005)にあるように、そのモデリング能力

な考えに基づく方法を重み付き最小 2 乗が最近注目されている。

法という。 D を m 次元正定値対角行列と本研究は、重み付き最小 2 乗法と層別最すると、重み付き最小 2 乗法は2

min || D( Ax − b) || と表される。

小 2 乗法の定量的な関係を理論的に解析する。これまで、Vavasis et al. (1996)によっ

以下では、重みがグループ化でき、グてギャップが無限大に発散するに連れて重ループ間の重みの比が非常に大きい状況

み付き最小 2 乗問題の解が層別最小 2 乗問を考える。すなわち、重み行列が題の解に収束するという定性的な性質は知

⎡ D1
⎢O
D=⎢
⎢M
⎢
⎢⎣ O

られていたが、定量的な研究はこれまでほO⎤M ⎥⎥M O M ⎥⎥
L L D p ⎥⎦

O L
D2 L

とんどなかった。本研究の貢献として、以下の 2 点が挙げられる。

1. 解析のための主要ツールとして、行と p グループに分けられ、そのギャップ列の基底ブロック下三角形を導入する。

min( D p −1 )min( D1 ) min( D2 ),, K,
} 2. 重み付き最小 2 乗問題の解と層別最g = mix{max( D2 ) max( D3 )max(D p )小 2 乗問題の解の差を陽に導く。

が非常に大きい状況である。このような場

χ A , χ A を行列の条件数（第 2 節で導合、以下のように、重み付き最小 2 乗問題

入）とすると、2 つの方法の解の差はを層ごとに解くことにより、近似解が得られる。いま、重み行列に従って、データ行

O( χ A χ A

列、目的変数ベクトルを層別する。

2 ( p +1)

g −2 || b ||)で抑えられる。

⎡ A1 ⎤⎡ b1 ⎤
⎢A ⎥
⎢b ⎥
2 ⎥
2
⎢
A=
, b=⎢ ⎥
⎢ M ⎥
⎢M⎥
⎢ ⎥
⎢ ⎥
⎢⎣ A p ⎥⎦⎢⎣b p ⎥⎦

2．行列の条件数

A を m 行 n 列の実行列で、列一次独立とする。このとき、次式で表される

上述した方法は、まず第 1 層の重み付き

χ A , χ A を A の条件数という。

最小 2 乗問題 min || D1 ( A1 x − b1 ) || 2 を解き、次に第 1 層の残差を変えないというχ A = max{|| B −1 ||: BはAT の基底行列}

条件のもとで第 2 層の重み付き最小 2 乗

χ A = max{|| B −1 AT ||: BはAT の基底行列}2

問 題 min || D2 ( A2 x − b2 ) || を 解 き .. ということを p 層まで繰り返すものである。

これらの条件数は線形計画問題や最小 2

このような方法は層別最小 2 乗法と呼ばれ乗問題と深い関係がある。本研究では、ている。層別最小 2 乗法は Tsuchiya et al.

行列の条件数が基底行列によって特徴付

398

けられることに注目し、与えられた重み

わち、 n× n 正則行列 G が存在して、付き最小 2 乗問題のデータ行列を基底ブ

T = AG −1 が基底ブロック下三角形にな

ロック下三角形に変換して解析を行う。

るようにできる。

3．基底ブロック下三角行列形

4．重み付き最小 2 乗法と層別最小 2 乗法

いまの解析
ここでは紙数の関係上、解析を詳細に⎡ A1 ⎤⎢A ⎥A i = ⎢ 2 ⎥ (i = 1,..., p ),⎢M ⎥⎢ ⎥⎣ Ai ⎦

述べるということはしないが、そのポイ
ントと得られた結果について簡潔に述べる。
解析の一番のポイントは与えられたデ

r i = rank ( A i ) (i = 1,... p ),ータ行列 A を基底ブロック下三角行列形

ri = ri − r i −1 (i = 2,..., p )に変換することである。2 節で述べたよう

r1 = r 1と定める。このとき、4 つの性質を満たす

A の条件数 χ A , χ A は基底行列によってm 行 n 列の実行列 T を、基底ブロック下

特徴付けられるため、解析の過程で現れ三角行列と言う。
1.

るさまざまな値を χ A , χ A を用いて容易T は p × p ブロック下三角行列。
⎡ T11
⎢ T
⎢ 21
T =⎢ M
⎢⎢T p −1, p⎢ T p1
⎣

O
T22

L
O

L
L

M

O

O

T p −1, 2

O T p −1, p −1

Tp2

L

T p p −1に評価できる。

O⎤
O ⎥⎥
M ⎥
⎥
O⎥
T pp ⎥⎦

解析によって得られた結果を、次の定理にまとめる。
定理 2 (Kitahara et al. (2008))**
をそれぞれ、重み付き最小 2 乗
xWLS, x LLS

2. 各 i (i = 1,..., p ) について、Tii は列一次法、層別最小 2 乗法の解とする。また、重み行列のギャップ g を独立である。
3.

T は適切な行変換の後に n × n 単位行
g = mix{列を含む。
4.

Tii は適切な行変換の後に ri × ri 単位行列を含む。

min( D p −1 )min( D1 ) min( D2 ),, K,}max( D2 ) max( D3 )max(D p )とする。このとき、**|| xWLS− x LLS||= O ( χ A χ A

定理 1 (Kitahara et al. (2008))
与えられたデータ行列 A は列変換のみでが成立する。

基底ブロック下三角行列にできる。すな

399

2 ( p +1)

g −2 || b ||)定理 2 が与える示唆として、次のようなを持っている。今後の研究として、SIMOTことが考えられる。

で現れる問題の層別最小 2 乗法によるモデル化を検討してみたい。

1. 層別最小 2 乗法の近似としての重み付き最小 2 乗法：層別最小 2 乗問題

参考文献

を解くのは若干煩わしい。そこで、[1]

Kitahara, T. and Tsuchiya, T., 2008. An
Analysis of Weighted Least Squares
Method and Layered Least Squares
Method with the Basis Block Lower
Triangular Matrix Form. Technicalreport. Available at optimization online
http://www.optimization-online.org/[2]

Tsuchiya, T. and Sasakawa, T. , 2005.
Robust optimization of magnetic
shielding with second-order cone
programming (in Japanese). The
Proceedings of The Institute of
Statistical Mathematics, 55, 297-315.

[3]

Vavasis, S. and Ye, Y., 1996. A
primal-dual accelerated interior point
method whose running time depends
only on A. Mathematical Programming,
74, 79-120.

定理に示した評価式を参考にして重みを調整した重み付き最小 2 乗問題を解く。
2. ギャップのみに依存した評価式：層別最小 2 乗問題を重み付き最小 2 乗問題で近似することを考えるとき、
ギャップさえ適正に保っていれば重みは数値的に安定なものを選ぶことができる。
5. まとめと SIMOT へのインパクト本研究では重み付き最小 2 乗問題と層別最小 2 乗問題の関係を定量的に解析した。解析のために、基底ブロック下三角行列形を導入し、重み付き最小 2 乗問題の解と層別最小 2 乗問題の解の差がO( χ A χ A

2 ( p +1)

g −2 || b ||)で抑えられることを示した。
インスティテューショナル技術経営学(SIMOT)の「イノベーションとインスティ
テューションの間の相互作用を解明し，可視化，操作化できるようにする」という目的において，モデリング技術の発展は必要不可欠である．本研究は、層別最小 2 乗法という新しいモデリング技術の発展に貢献できた。層別最小 2 乗法によるモデリングは現在のところほとんど行
われていないが、Tsuchiya et al.(2005)の研究に見られるように、大きな潜在力

400線形計画問題に対する内点法アルゴリズムの理論的解析とその SIMOT へのインパクト北原＊東京工業大学

知就＊

社会理工学研究科 経営工学専攻

東京都目黒区大岡山 2-12-1 W9-526
kitahara.t.ab@m.titech.ac.jp(統計数理研究所

土谷隆教授との共同研究)
概要

SIMOT で得られた知見を実務・業務レベルで適用するためには、多くの意思決定問題を解くことが必要になる。線形計画問題は、このような実務・業務問題の多くをモデル化することができる重要な数理計画問題である。本研究では、線形計画問題の有力な解法である
内点法を理論的に解析した。線形計画問題は(1)制約行列 (2)制約ベクトル (3)目的関数ベク
トルによって記述されるが、本研究の結果、アルゴリズムが終了するまでの理論的な回数が目的関数に依存しない量で抑えられることが示される。アルゴリズムの実行に本研究の知見を組み込むことにより、多くの現実問題がより効率的に解ける可能性がある。

1. はじめに計画問題を効率的に解くためのアルゴリ

1.1

ズムの研究は不可欠である。

SIMOT と線形計画問題

SIMOT は、(1)インスティテューション
1.2 線形計画問題に対する内点法とイノベーションの共進ダイナミズムを解明し、(2)可視化、操作化できることを

内点法は線形計画問題に対する有力な目指している。(2)のためには、(1)の研アルゴリズムのひとつである。図 1 に示究によって得られた知見を企業等の日々すように、内点法は中心パスと呼ばれるの実務・業務レベルで適用可能な仕組み

最適解に向かって伸びるパスの周辺に点づくりが必要である。線形計画問題は、列を生成する。

行列 A ∈ ℜ
ル c∈ℜ

n

m×n

m

、ベクトル b ∈ ℜ 、ベクトを デ ー タ 、 ベ ク ト ルmy ∈ ℜ , s ∈ ℜ n を変数として、
max

中心パス

bT y

(1)Predictor(2)Corrector

subject to AT y + s = c, s ≥ 0,
最適解と表される数理計画問題で、多くの現実問題をモデル化できる。そのため、線形

図 1：内点法の概要

401

中心パス
の近傍

1.5 本研究の結果・貢献

一般に数理計画問題に対するアルゴリ
ズムに対しては、実用的な性能と、理論

本研究の結果および貢献として、以下の的な性質が問題になる。理論的な性質と点が挙げられる。

しては、実際の問題に適用したときに最1. 実用的内点法(第 2 節で導入)に対し悪でどのくらいの反復回数を要するかがて、その最悪の場合の反復回数が問題にされることが多い。理論的な性質の効率化が図れる可能性がある。そのたC ' ( n 3.5 f ( A) + n 2 g ( A, c) (2)であることを証明した。 C ' は問題に無関係な定数で、 n は問題のサイズ、g ( A, c) は制約行列 A 、目的関数ベク

め、このような理論的性質についての研トル c のある関数である。この結果は究が必要である。

Vavasis と Ye には及ばないが、実用を明らかにし、その知見を実際のアルゴ
リズムに組み込むことで、アルゴリズム

的内点法の最悪の場合の反復回数が制約ベクトル b に依存しないという

1.3 既存研究
Vavasis と Ye は層別ステップ内点法を

点は今まで知られていなく、注目に提案し、その反復回数が多くとも

Cn

3.5

値する。

f ( A) (1)2. 本研究によって、中心パスの新しいであることを証明した。ここで、 C は問性質が明らかにされた。1 の結果は、題に無関係な定数で、 n は問題のサイズ、

この結果を利用することにより得ら

f ( A) は制約行列 A のある関数である。彼れた。この結果をアルゴリズムの実らの結果は最悪の場合の反復回数が制約行

行の盛り込むことで、アルゴリズム

列 A にしか依存しないことを示した画期の効率化が見込まれる。

的なものである。しかし、層別ステップ
内点法は実用には程遠い内点法であった。 2．実用的内点法
現在、実用的内点法として広く知られて い る の は 、 Mizuno-Todd-Ye

1.4 仮説と本研究の目的
内点法は、中心パスの付近に点列を生成

Predictor-Corrector(MTY-PC) 内 点 法 でする方法であるから、中心パスの性質をよある。以下ではこの方法について簡単にり精密に解析することで、実用的な内点法説明する。

に対しても Vavasis と Ye に迫る結果が得ら

MTY-PC アルゴリズムは、中心パスの近傍に点列を生成する。図 1 に示したようれると考えられる。
本研究では、この仮説を検証し、その過に、アルゴリズムでは内近傍と外近傍と程で得られた知見を実際のアルゴリズムにいう 2 つの近傍を考える。アルゴリズム

組み込むことを検討する。それによって、は内近傍に含まれる点からスタートする。

アルゴリズムの効率化が見込まれる。

まず Predictor ステップによって外近傍の境界まで移動する。その後、Corrector
ステップによって点を内近傍まで戻す。

402

以上のステップを繰り返しながら点列をMTY-PC 内点法の最悪の場合の反復回数が、生成することで、得られた点列が最適解

C ' ( n 3.5 f ( A) + n 2 g ( A, c) (2)に収束していくことが知られている。

で抑えられることを示すことができる。

3．幾何学的視点からの中心パスの解析

これは、MTY-PC 内点法の最悪の場合の反ここでは紙数の関係上、解析を詳細に

復回数が制約ベクトル b には依存しない

述べるということはしないが、そのポイことを示している。このような結果はこントを述べる。

れまでに知られておらず、本研究で初めて示されたものである。この結果はVavasis と Ye の既存の結果(1)には及ばないが、彼らの解析対象が層別ステップ
内点法という実用的でないものであった

中心パス(1)最適解から遠いことに留意すべきである。
5. まとめと今後の課題(2)最適解付近
最適解

線形計画問題は多くの現実問題をモデル化することができる重要な数理計画問

図 2：中心パスの幾何学的イメージ題である。線形計画問題がより効率的に中心パスの性質で重要なのは、その微解けるということで、SIMOT の「共進ダイ分的性質である。つまり、中心パス上の

ナミズムの操作化」という目的に貢献す一点に着目したとき、その点で各変数がることができると考えられる。

どのように変化しているかということで内点法は線形計画問題を解くための有ある。図 2 では 5 つの境界があるが、こ力なアルゴリズムである。内点法が最悪

こにおける変数とは中心パス上の点から

でどのくらいの反復回数を要するかを知各境界までの距離と思えばよい。幾何学

ることは、実用的側面からも必要である。

的には、(1)最適解から遠い場合には、すVavasis と Ye は層別ステップ内点法といべての変数が一様に減少していると考えう実用的でない内点法に対してられ、(2)最適解付近では値が減少していC n 3.5 f ( A) という良い結果が知られている変数のグループと、値がほとんど変化

た。本研究では MTY-PC 内点法という実用しない変数のグループがあるように思わ的な内点法を解析の対象とした。幾何学れる。本研究では、このようなイメージ的な観点から中心パスを解析し、MTY-PC

をもとに、中心パスを解析し、このよう内点法の最悪の場合の反復回数が、な直感が理論的に正しいことを証明した。

C ' ( n 3.5 f ( A) + n 2 g ( A, c) で 抑 え ら れ る

このような幾何学的観点からことを示した。実用的な内点法に対して
制約ベクトル b によらない反復回数を示

4.

制約ベクトルに依存しない反復回数したのは、本研究が初めてである。

3 節の中心パスの性質をもとにすると、

403

今後の研究として、本研究で得られた

中心パスの性質等の知見を実際のアルゴ
リズムに反映させていきたいと考えてい
る。
参考文献
[1]

Mizuno, S, Todd, M. J, and Ye, Y.,
1993. On adaptive-step primal-dual
interior-point algorithms for linear
programming.
Mathematics
ofOperations Research, 18, 964-981.

[2]Monteiro, R. D. C and Tsuchiya, T.,
2004.
A new iteration-complexity
bound for the MTY predictor-corrector
algorithm.
SIAM
Journalon
Optimization, 15 319-347.

[3]

Vavasis, S. and Ye, Y., 1996. A
primal-dual accelerated interior point
method whose running time depends
only on A. Mathematical Programming,
74, 79-120.

404

ロバスト最適化と SIMOT
北原*東京工業大学

知就*

社会理工学研究科 経営工学専攻

東京都目黒区大岡山 2-12-1 W9-526
kitahara.t.ab@m.titech.ac.jp
概要
本稿ではロバスト最適化について概説し、その SIMOT への示唆について論じる。ロバ
スト最適化は、不確実な環境下で意思決定を行うための方法論で、近年盛んに研究が行われている。ロバスト最適化では、意思決定問題におけるデータが一つに決まっているとするのではなく、ある集合内にあるとする。そして、データがその集合内を動くときの最悪の場合を最良にするような解を採用する。ロバスト最適化では最悪の場合の挙動を最良にするようにするため、解が保守的になりやすいという批判がある。このことは、インスティテューションとイノベーションの共進的ダイナミズムのモデリングについての一つの示唆を与えている。すなわち、共進的ダイナミズムのモデリングに際しても、一つの普遍的なモデルを与えてインスティテューションの違いはパラメータの調節によってカバーする、という発想ではうまくいかない可能性がある。そうではなく、インスティテューションの違いをモデルに組み込むことが重要である。
ロバスト最適化では、従来のようにデー

1．はじめに我々の日常生活は個人レベルから企業、 タが１つに(1 点に)決まっているとする
国家レベルまで意思決定の連続である。

のではなく、ある集合内にあるとする。

それらの意思決定問題の多くはある制約

そして、データがその集合内を動くときの元での目的関数の最小化という構造をの最悪の場合を最良にするような解を採しており、その効果的な解決のために最用する。近年の理論的進展、計算機技術

適化がしばしば用いられる。

の発達によりこのような解は容易に計算

意思決定問題の主な構成要素としては、 できるようになっている。
目的関数、制約、変数、データがある。

本稿では、ロバスト最適化について概従来は、問題のデータは既知とすること説し、その SIMOT への示唆について論じが多かった。しかしながら、情報化の進る。SIMOT ではインスティテューションと展等で意思決定の環境は不確実性を増しイノベーションの共進的ダイナミズムをており、この仮定は必ずしも成り立たな

解明し、それをどのようなインスティテ

くなっている。

ューションであっても適用可能なものにロバスト最適化は、このような不確実することを目指している。このように、な環境下での意思決定を行うための方法

さまざまなインスティテューションを考論で、近年盛んに研究が行われている。

えるという点は、ロバスト最適化の思想

405

多くの意思決定問題は次のようにモデに通じるものがある。
ロバスト最適化では最悪の場合の挙動

ル化できる。

を最良にするようにするため、解が保守

min f ( x)

的になりやすいという批判がある。このsubject to g i ( x) ≤ 0 (i = 1,2,..., m)(1)

ベーションの共進的ダイナミズムのモデ

f (x) は 目 的 関 数
g i ( x) (i = 1,2,..., m) は制約関数であり、 x

リングについての一つの示唆を与えていは変数ベクトルである。先ほどの例は利る。すなわち、共進的ダイナミズムのモ益の最大化問題であったが、利益関数にデリングに際しても、一つの普遍的なモ-1 をかけた関数を考えることで、最小化

デルを与えてインスティテューションの問題に帰着できる。

こ こ で 、

ことは、インスティテューションとイノ

違いはパラメータの調節によってカバーする、という発想ではうまくいかない可

3．ロバスト最適化とは能性がある。そうではなく、インスティ

先ほどの問題(1)では問題のデータはテューションの違いをモデルそのものに目的関数や制約関数に織り込まれている

組み込むことが重要である。

として、明示しなかった。そこで、問題のデータを表すパラメータ α を導入して、本稿の構成は、次の通りである。この後の第 2 節では意思決定問題のモデル化問題(1)を次のように書き直す。

について述べる。第 3 節ではロバスト最適化について詳説する。第 4 節ではロバ

min f ( x)(2)subject to g i ( x, α ) ≤ 0 (i = 1,2,..., m)

スト最適化が SIMOT に与える示唆につい詳細は割愛するが、一般性を失うことなて論じる。最後の第 5 節では結論を述べ

く制約関数のみがデータ α に依存するとる。

することができることが知られている。
ロバスト最適化はこのような不確実な2．意思決定問題のモデル化

環境下での意思決定法を扱う方法論であ

まず次のような意思決定問題の例を考る。ロバスト最適化のある理論では、デえる。ある工場経営者がおり、その工場

ータ α が一つに決まっているとするのでではいくつかの製品を生産している。経はなく、不確実集合 U 内のある値を取る、営者はその利益が最大になるように各製とする。そして、この実際のデータがこ品の生産量を決定したい。

の集合内のどのような値をとっても制約

この例で、意思決定問題の構成要素をが成立するような意思決定の中で最良な確認する。まず、目的関数は利益である。

ものを選択する。式で表すと制約は予算や各材料からどれだけ各製品

min f ( x)subject to maxα∈U g i ( x, α ) ≤ 0 (i = 1,2,..., m)

を作れるか、などである。変数は各製品の生産量である。最後にデータは各製品(3)を 1 単位生産したときの利益や、各材料となる。

の値段などである。

これまでに、さまざまな問題に対する406

ロバスト最適化の応用が研究されている。 スティテューションとイノベーションの古典的な資産運用モデルに H.マーコヴッ

共進的ダイナミズムの解明、およびそれツによる平均分散モデルがある。これはをどのようなインスティテューションで株式等の資産の平均ベクトル、分散共分も適用可能にする、という目的に対して散行列をデータとして、一定の収益率の重要な示唆を与えている。すなわち、共元でリスク(収益率の分散)を最小にする

進ダイナミズムのモデル化において、(イようなポートフォリオ(資産配分)を与え

ンスティテューションの違いを考慮しなる。最適ポートフォリオは平均ベクトルいで)一つのモデルを設定し、インスティ

や分散共分散行列に対して敏感である。

テューションの違いをパラメータの違い

すなわち、これらのデータが少しずれるで反映させるという方法はうまくいかなと最適ポートフォリオが大きく変化する

いのではないか。そうではなく、インスことが知られている。しかしながら、こティテューションの違いをモデルそのもれらのデータを過去情報から精密に推定のに反映させることが重要であると考えすることは困難である。この平均分散モられる。

デルに対してロバスト最適化を適用する
5．おわりにと、平均ベクトルや分散共分散行列に対する不確実性集合を適切に設定すること

本稿では最適化の世界で盛んに研究さにより、問題(3)(に相当する問題)は最適

れているロバスト最適化を解説し、その解を計算できる[2]。このようにして求まSIMOT への示唆について論じた。結論を端った解は不確実性に対して強い(ロバス的に述べると、インスティテューション

トな)解となっている。

を共進ダイナミズムモデルのパラメータに反映させるのではなく、モデルそのものに反映させることが肝要であるという

4. ロバスト最適化の SIMOT への示唆
これまでに紹介してきたロバスト最適ことである。今後、このようなことを念化の理論は、不確実性に対応するために、頭に、モデリングの方法論、技術を追求

可能なすべてのシナリオを考え、その中して行きたいと考えている。

の最悪の場合を最良化することを考える。
これによって、実際にどんなシナリオが参考文献

起こっても最悪の場合は回避できる。し[1] Bental, A. and Nemirovskii, A., 2001.
Lectureson
ModernConvex
Optimization: Analysis, Algorithms, andEngineering Applications. Mps-Siam
Series on Optimization.

かし、このように求まった解は非常に保守的であることが知られている。つまり、(ほとんど起こりえない)最悪の場合を回避することによって、大部分を占める普[2] Goldfarb, D. and Iyengar, G., 2003.
Robust Portfolio Selection Problems.
Mathematics of Operations Research. Vol.
28, No. 1, pp. 1-38.

通のシナリオでのパフォーマンスがあまり良くないのである。
このような現象は、SIMOT が目指すイン

407

SIMOT における特徴選択の応用
郭

天放*

*

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
kuo@me.titech.ac.jp
現在、データマイニング（data mining）は注目されている研究分野の一つである。
データマイニングとはデータベースについて分析を行い、効率的に隠された有用な知識を取り出し、現実の状況を判別、予測することである。
一般的なデータベースには、各データに対していくつかの属性値と一つの分類値が与えられた。特徴選択とは、元のデータベースから、最もこのデータベースを代表できる部分のデータと属性を抽出することである。特徴選択によって、その後の分析を効率的に進めることができるようになる。

1. はじめに
現在、データマイニング(data mining)は注
目されている研究分野の一つである。データ
マイニングとはデータベースについて分析を行い、効率的に隠された有用な知識を取り出し、現実の状況を判別、予測することである。
応用分野としては、マーケティング、画像認
識など、幅広い範囲に渡っている。
データマイニングの大きな問題の一つとしては分析するときの計算時間である。例えば、
マーケティング分析における一年間の販売データ数は数十万から数百万に至る可能性が有り、かつ、各データにはまた数十種類の属性を含むことになる。このような膨大なデータ
ベースにおいて直接分析を行うと、計算時間が非常にかかるという問題がある。また、収集された元のデータにおいて、無関係なもの
又はノイズが含まれる可能性が高い。これら
は分析時間の長時間化、かつ、分析精度の低下などの事態が生じる恐れがある。それゆえ、
データマイニングの研究分野において、デー
タベースの特徴選択は一つの重要な課題である。
本研究では以上の問題を解決するため、SVM(support vector machine)の判別境界線による特徴選択の手法とそのアルゴリズムを提案する。提案された手法によれば、データベースにおける全ての属性についてランク付けし、ランクが上位のいくつかの属性だけ取り出し、重要性が低い属性を削除する。また、特徴選
択の手法により一部の属性を削除するデータ
ベースについて、既存の分析方法をさらに効率的に行うことができる。

408

2. 特徴選択とSIMOTにおける応用
2.1 特徴選択
一般的なデータベースには、各データに対していくつかの属性値（例えば、サイズ、重量などの数値）と一つの分類値（例えば、良いと悪い）が与えられた。特徴選択とは、元のデータベースから、最もこのデータベース
を代表できる部分のデータと属性を抽出することである。特徴選択によって、その後の分析を効率的に進めることができるようになる。
現在の特徴選択の分野において、アルゴリ
ズムの研究が最も必要とされている。それらのアルゴリズムの目的は、いかに高速にデー
タベースの特徴を選択するかということにある。そして、その上で選択した特徴は、最もこのデータベースを代表できるものであることも要求される。また、それらのアルゴリズ
ムにおいて、重要な概念として、属性の重要さを測る指標の計算がある。
指標の計算とは、各属性の重要性を測り、このデータベースにおけるある程度以上重要なものを選択することである。指標の設計において、属性の重要性を測れるものを探し、抽出した部分のデータと元のデータベースとは類似する性質があることが要求される。そのうえ、指標の計算時間も一定の範囲内に抑えなければならない。それゆえ、指標の設計は得られたデータの代表性と計算の速度を兼ね備えるべきである。
また、SVM の判別境界線による特徴選択の手法は、カーネル関数を使う手法の一つである。カーネル関数を使う手法とは、有限次元のデータベースをより一層高い次元空間（無限次元空間）に射影して、このデータベースのなかに存在する特殊な性質を探す方法である。カーネル関数を使う手法が、数多くのデータマイニングの分析方法で有効である

ことは、すでに証明されている。しかし、カーネル関数を用いる計算において、計算式はいくつかのカーネル関数の制限に合わせる必要がある。また、計算時間もかかるので、適切なアルゴリズムが必要である。
2.2 SIMOTにおける応用
SIMOT において、データベースから入力
因子(input)と出力結果(output)の関係を見出す
ことをひとつの目的とする。一般的な状況において、入力因子から出力結果への変換過程
はブラックボックスのような状態である。このブラックボックスを解明するため、入力因子から出力結果への変換過程又は入力因子同士の相互作用を可視化させることがひとつの手法である。
変換過程又は相互作用の可視化には、主成
分分析、判別分析など数多くの既存分析手法が適用される。しかし、分析しようとするデータベースには上記のように無関係な属性とノイズが含まれている可能性が高い。そのま
ま使って分析を行うと、結果の精度が低下し、かつ、計算時間が長時間化するなどの問題が発生する恐れがある。さらに属性数が多いほど、それぞれの属性自身の重要性及び結果との関連性を明示し難い。
以上の課題を鑑みて、特徴選択によって、元のデータベースから不要な部分を取り除き、さらに上記のように、特徴選択は元のデータベースにおける各属性の指標値を計算するので、その結果からそれぞれの属性の重要性を明示することができる。また、特徴選択が前処理として、その後の更なる分析を効率的に行うことができる。

本研究では、RBF カーネルのいくつかの性質を見出した。そして、トレーニングデータ
D が線形関数 g(x)=<w,φ(x)>で判別されると仮定することによって、この線形関数 g(x)は以下の主問題と双対問題で解くことができる。
Min. 1/2<w,w>+C Σ iM=1 ξi(2)s.t. yi<w,φ(x)>≧1-ξi
ξi≧0, i=1,2,…,M.
Min. 1/2αTYKYα-eTα(3)s.t. yi(<w,φ(x)>+b)≧1-ξi
0≦α≦eC,
ここで、α=(α 1…α M)T は双対変数のベクトルとする。
双対問題を解いて、判別境界線は以下の式で表す。
(4)B={x∈RN | Σ iM=1 αiyiK(xi, xj)=0}.
また、Lee and Landgrebe [8] は以下の式のDBFM(decision boundary feature matrix)、ΣDBFMを提案して、境界線から必要な属性（方向）を抽出する。
ΣDBFM=1/p∫B{∇g(x)∇Tg(x)/||∇g(x)||2}p(x)d(x),(5)

ここで、 p(x) はデータの確率密度関数であり、P=∫ Bp(x)d(x)である。また、DBFM における非零固有値に対応する固有ベクトルに属する方向は、元のデータベースとは同じ精度の判別に対する必要な方向である。
DBFM の計算には、十分なデータ x’1,…, x’lが境界線にいると仮定すると、DBFM は以下の式で近似できる。
lΣ’DBFM=1/l Σ i =1 {∇g(x’i)∇Tg(x’i)/||∇g(x’i)||2}.

(6)

しかし、トレーニングデータにおいて、境界線にいるデータが非常に少ないため、一般的には DBFM はうまく計算できない状態になる。最近、この課題を解決するため、Zhang
3. SVM判別境界線による特徴選択
and Liu [7] は g(xi)g(xj)<0 の関係を満たす二つのトレーニングデータ
xi, xj を選んで、以下の3.1 SVMとDBFM
等式のθを解いて、境界線にいるデータを作与えられた M 個のトレーニングデータがる。
D={(x1,y1),…, (xM,yM)}とし、xi∈RN は N 個の(7)g(θxi+(1-θ)xj)=0.
属性値がある i 番目のトレーニングデータであしかし、この手法において、g が非線形のり 、 yi ∈ {-1,+1} は 対 応 し た ラ ベ ル で あ る 。
場合には、式(7)の解が唯一ではないことがあ
SVM において、xi が非線形変換φにより、特る。また、境界線の両側のそれぞれに属する
徴空間 F に射影してから、トレーニングデー
データを選択するには、組合せの数が非常にタを判別できる超平面<w,φ(x)>+b=0 を探す。
多くである。さらに、式(7)を解くには繰り返
ここで、<･,･>は特徴空間 F にける内積とする。
しの過程が必要である、という問題点がある。
ここで、K は M×M 対称行列とし、K の i-j
3.2 SVMの判別境界線による特徴選択
要素 Kij=<φ(xi),φ(xj)>、xi と xj の射影の内積で本研究では上記の課題を解決するため、効ある。また、この内積はカーネル関数 K(xi, xj).
率的な計算方法を提案した。提案した手法にで直接計算できることが既に知られている。
おいて、RBF カーネル関数と DBFM の計算式
本研究において、以下の式の RBF(radial basisの性質を組合せ、行列とベクトルの計算によfunction)カーネル関数を適用する。
り簡単に DBFM の対角線の値を計算する。
(1)
K(xi, xj)=exp(-||xi-xj||2/2σ2).
まず、境界線にいるデータ（ベクトル）を
ここで、σは変換φ(･)の非線形を制御する見出すのに、RN 空間ではなく、特徴空間 F にパラメーターである。
おけるベクトルを探す。各トレーニングデー
ま た 、 e ∈ RM は 1 の ベ ク ト ル と し 、 y=
(y1…yM)T 、Y は対角要素が y の M×M 対角行
タ xk について、φk∈F は xk の射影と設定する。
列とする。
また、それぞれのデータについて、(8)
φ’k=φk-θkw,

409

と定義する。ここで、θk=<w,φk>/<w,w>である。この式により、特徴空間において、φ’kは境界線にいるデータであって、φk とは最も近いポイントである。つまり、φ’k を計算でき
れば、与えられたデータ xk に対応する境界線にいるデータ x’k の勾配ベクトルが得られる。
前節で示した非線形判別関数(9)g(x)= Σ iM=1 αiyiK(xi, x).
について、データ x’k における勾配ベクトルは以下の式で計算できる。
M∇g(x’k)= Σ i =1 αiyiK(xi, x’k)(xi-x’k).
(10)
また、データ x’k が境界線にいるので、
Σ iM=1 αiyiK(xi, x’k)=0 という条件を満たす。つまり、式(10)は以下のように簡単化できる。
M∇g(x’k)= Σ i =1 αiyiK(xi, x’k)xi.
(11)
さらに、以下の式を使うと、境界線にいる
データ x’k を知らなくても∇g(x’k)を計算できる。
ここで、xi と xk は任意のデータであり、φiとφk は特徴空間における xi と xk の射影である。
また、x’k は境界線にいる xk に最も近いものであり、φ’k は x’k の射影である。そうすると、以下の式が成り立つ。
K(xi, x’k)=K(xi, xk)-θk Σ iM=1 αiyiK(xi, xj). (12)つまり、勾配ベクトル∇g(x’k)は以下のように得られる。
X=[x1…xM]はトレーニングデータからなる
N×M 行列であり、g=[g(x1)…g(xM)]T、Yαは M
×M 行列であり、その i 番目の対角線要素がαiyi である。そして、全ての勾配ベクトルは以下の式で一括に計算できる。
[∇g(x’1)…∇g(x’M)]=XYα(K-ggT/yαTKyα)/σ2. (13)続いて、式(6)の Σ ’DBFM の計算手順について、説明する。DBFM の計算には、トレーニ
ングデータの存在が多い区域にいるデータが望ましい。それゆえ、SVM で作ったマージンのなかに存在しているデータだけを使えばよい。また、マージンのなかに存在しているデータはサポートベクトルなので、勾配ベクトルの計算について、サポートベクトル以外のデータは省略できる。また、トレーニングデ
ータ xi がサポートベクトルの条件は対応した双対問題(3)の最適解αi が 0 ではない。双対問題(3)の最適解において、非零変数の数が少ないので、DBFM の計算に必要なデータを大幅に下げられる。
例えば、L 個のトレーニングデータ x1,…,xLがサポートベクトルとし、α 1=…=α L=0 である。また、L 次元のサブベクトル g*, yα*∈RL、サブ行列 Y α *, K*∈RL × L 、X*=[x1…xL]∈RM × Lとする。式(13)は以下のように変換できる。

Σ’DBFM =1/L(∇G∇GT).
(15)
最後は、それぞれの属性の重要さを計算することである。単位ベクトルの方向 v∈RN について、その重要さは以下の式で計算できる。
F(v)=vTΣ’DBFMv.
また、各属性 i=1,…,N について、ei∈RN がi 番目のユニットベクトルとすると、この i 番
目の属性の重要さは F(ei)=eiTΣ’DBFMei であり、
Σ’DBFM の対角線の i 番目要素の値である。

4. 数値実験
提 案 し た 手 法 に つ い て 、 Reuter-21578 、
WebKB、20 Newsgroups の三種類のデータベースに対する数値実験を行った。まずは SVM でそれぞれのデータベースにおける境界線を計算し、得られた境界線から DBFM の対角線要素の値を計算する。続いて、対角線の値の大きさの順によって、上位いくつかの属性だけを取り出す。最後は取り出したデータベースの一部を SVM の判別分析を行い、精度の評価
として BEP(break-even point)を計算する。また、
特徴選択をしない場合の BEP も比較として計算する。
Reuter-21578 のデータベースにおいて、トレーニングデータの数が 7063、テストデータの数が 2742、属性数が 9370 である。表 1 によると、10 個のカテゴリーのうち、3 個のカテ
ゴリーの BEP が同じ、7 個のカテゴリーのBEP が高くなる。さらに、抽出された属性数がもとの 10%以下である。
表 1 データベース Reuter-21578 における break-evenpoint

categoryearn
acqmoney-fx
grain
crude
trade
interest
ship
wheat
corn

BEP(%)
特徴選択
98.76
96.42
78.01
94.03
90.06
84.82
78.00
84.71
90.91
89.58

しない
98.76
95.80
78.01
88.06
90.06
83.93
76.00
82.35
83.33
83.33

属性数
(%)
5.34
5.34
6.40
3.20
5.34
6.40
9.61
7.47
0.43
0.75

WebKB のデータベースにおいて、データの数が 4199、属性数が 10949 である。また、(14)
トレーニングデータはランダムに選択された式(14)により、行列のサイズは L であり、全部の 65%であり、テストデータは残った
パソコンのメモリでも負担できる程度になる。 35%であり、選択された属性数が 1000 個と設
また、式を簡単化し、以下のように設定する定される。
と表 2 における BEP は 10 回ランダムサンプ∇G=[∇g(x’1)/||∇g(x’1)||…∇g(x’L)/||∇g(x’L)||],
リングの平均である。表 2 によると、4 個のカ
DBFM は行列の計算から簡単に得られるテゴリーのうち、半分のカテゴリーの BEP し[∇g(x’1)…∇g(x’L)]=X*Y α *(K*-g*g*T/y α *TK*y α *)/σ 2.

410

か高くならないが、抽出された属性数がもとの 9.13%である。

4. 結論
数値実験の結果から見ると、提案した特徴
選択の手法により、データセットからノイズを取り除くことによって、判別、予測などの更なる分析を行う際の精度を高めることができる。また、計算に必要なメモリを低減することができる。
特徴選択により重要さがある程度以上の属性を抽出し、、企業に対する診断する又は現象に対する分析を行うとき、より具体的な対策を立てることができる。

表 2 データベース WebKB における break-even point

category
student
facultycourseproject

BEP(%)
特徴選択
88.84
79.23
92.05
69.83

しない
89.56
79.89
91.78
71.72

References

20 Newsgroups のデータベースにおいて、データの数が 19466、属性数が 34746 である。
また、トレーニングデータはランダムに選択された全部の 65%であり、テストデータは残った 35%であり、選択された属性数が 1000 個と設定される。
表 3 における BEP は 10 回ランダムサンプ
リングの平均である。表 3 によると、全てのカテゴリーの BEP が低くなるが、最高でも7%しか落ちない。また、そのとき抽出された属性数がもとの 2.88%である。
表 3 データベース 20 Newsgroups における break-evenpoint

category
alt.atheism
comp.graphics
comp.os.ms-windows.misc
comp.sys.ibm.pc.hardwarecomp.sys.mac.hardwarecomp.windows.x
misc.forsale
rec.autos
rec.motorcycles
rec.sport.baseballrec.sport.hockey
sci.crypt
sci.electronics
sci.medsci.spacesoc.religion.christian
talk.politics.guns
talk.politics.mideast
talk.politics.misc
talk.religion.misc

BEP(%)
特徴選択
87.90
79.09
81.12
73.71
84.07
85.14
80.90
87.52
91.82
92.08
96.16
92.85
79.29
88.86
90.84
86.21
86.06
93.98
78.24
78.76

しない
91.29
83.65
83.63
78.59
86.79
87.31
82.52
90.60
93.65
93.46
97.27
94.29
85.63
91.38
93.81
89.28
90.69
95.84
85.46
84.62

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41, no. 6, pp. 391--407.

[2]Chen, L. et al., 2003. A new differential LSI
space-based probabilistic document classifier.
Information Processing Letters, vol. 88, pp.
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Fortuna, J., and Capson, D., 2004. Improved
support vector classification using PCA andICA feature space modification. Pattern
Recognition, vol. 37, pp. 1117--1129.

[4]

Shima, K. et al., 2004. SVM-based feature
selection of latent semantic features. Pattern
Recognition Letters, vol. 25, pp. 1051--1057.

[5]

Vapnik, V.N., 1998. Statistical Learning
Theory. John Wiley & Sons, 1998.

[6]

Joachims, T., 2002. Learning to Classify Text
Using Support Vector Machines. Kluwer
Academic Publishers, Boston.

[7]

Zhang, J., and Liu, Y., 2002. SVM decisionboundary based discriminative subspaceinduction. Technical Report CMU-RI-TR-0215, Carnegie Mellon University.

[8]

Lee, C., and Landgrebe, D. A., 1993. Feature
extraction based on decision boundaries. IEEE
Transactions on Pattern Analysis and MachineIntelligence, vol. 15, no. 4, pp. 388--400.

[9]Shawe-Taylor, J., and Cristianini, N., 2004.
Kernel Methods for Pattern Analysis,
Cambridge University Press, Cambridge.

[10] Joachims, T., 1999. Making large-scale
support vector machine learning practical, in
Advances in Kernel Methods, B.Schölkopf, C.
Burges, and A. Smola, Eds., pp. 169--184.
The MIT Press, Software available at
http://svmlight.joachims.org/.
[11] Yang, Y., and Pederson, J. O., 1997. Feature
selection in statistical learning of text
categorization, in the fourteenth international
conference on machine learning, pp. 412--420.

411

多クラス判別分析と SIMOT における応用
郭

天放*

*

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
kuo@me.titech.ac.jp
現在、データマイニング（data mining）は注目されている研究分野の一つである。
データマイニングとはデータベースについて分析を行い、効率的に隠された有用な知識を取り出し、現実の状況を判別、予測することである。
データベースに対して、一般的な多クラス判別分析には、最適化問題の変数が非常に多いため、実行不可能の可能性が高い。本研究では切除平面法を用いて、有限回数の繰り返しで最適化問題の近似解を求めることになる。また、数値実験の結果により、提案された方法は優れたパフォーマンスを持つことを示した。

1. はじめに
現在、データマイニング(data mining)は注
目されている研究分野の一つである。データ
マイニングとはデータベースについて分析を行い、効率的に隠された有用な知識を取り出し、現実の状況を判別、予測することである。
応用分野としては、文献分類、画像認識、蛋
白質とゲノム解析など、幅広い範囲に渡っている。
パソコンと記録媒体の進歩に従って、収集された情報が膨大なデータベースになる。データマイニングの大きな問題の一つとしては分析するときの計算時間である。例えば、マーケティング分析における一年間の販売デー
タ数は数十万から数百万に至る可能性が有り、かつ、各データにはまた数十種類の属性を含
むことになる。このような膨大なデータベースにおいて直接分析を行うと、計算時間が非常にかかるという問題がある。それゆえ、データマイニングの研究分野において、アルゴ
リズムの研究は一つの重要な課題である。
データマイニングの研究分野において、数多くの手法と方向がある。本研究では、多クラスの判別分析とそのアルゴリズムに注目している。
一般的な多クラス判別分析には、最適化問
題の変数が非常に多いため、実行不可能の可能性が高い。本研究では以上の問題点を解決するため、切除平面法による多クラス判別の手法とそのアルゴリズムを提案する。提案されたアルゴリズムにより、有限回数の繰り返
しで最適化問題の近似解を求めることになる。
また、数値実験の結果により、提案された方法は優れたパフォーマンスを持つことを示した。

412

2. 多クラス判別分析とSIMOTにおける応用
2.1 多クラス判別分析
一般的なデータベースには、各データに対していくつかの属性値（例えば、サイズ、重量などの数値）と一つの分類値（例えば、良いと悪い）が与えられる。
判別分析とは、トレーニングデータから判別器を生成し、テストデータまたは未分類のデータの分類値を判別、予測することである。
そのうち、SVM(support vector machine)は注目された方法の一つである。詳しく言えば、SVM はカーネル関数を使って判別器を生成する方法である。
また、カーネル関数を使う方法とは、有限次元のデータベースをより一層高い次元空間（無限次元空間）に射影して、このデータベースのなかに存在する特殊な性質を探す方法である。
SVM がデータベースの判別分析方法として有効であることはすでに検証されているが、SVM による判別分析は本来 2 クラス判別器（A に属するか否か）として設計されたものである。しかし、実際のデータは多数のクラスを有するものが多い。例えば、品質の尺度は良いと悪いから、3 段階あるいは 5 段階へ拡張する。それらのデータの判別を行うには、多クラス判別器へ拡張しなければならない。
多クラス判別へ拡張するには、多クラス判別
を 2 クラス判別の組合せと考えればよい。しかし、これらの従来法は一つのデータが 2 以上のクラスに属する、あるいは全てのクラスに属しない可能性がある。そのため、多クラス問題に対して一度の計算で多クラス判別を扱う手法を考える。
しかし、多クラス判別器を生成する最適化問題（二次計画問題）において、変数の量が 2クラスの問題より非常に多くなり、実行不可能の可能性が高い。それゆえ、最適な判別器の代わりに、近似的な判別器を求めることを考える。また、計算時間もかかるので、適切なアルゴリズムが必要である。
以上の課題を鑑みて、本研究では切除平面法を導入し、有限回数の繰り返しで多クラス判別分析における二次計画問題を解くアルゴ
リズムを提案する。
2.2 SIMOTにおける応用
SIMOT において、データベースから入力
因子(input)と出力結果(output)の関係を見出す
ことをひとつの目的とする。一般的な状況において、入力因子から出力結果への変換過程
はブラックボックスのような状態である。このブラックボックスを解明するため、入力因子から出力結果への変換過程又は入力因子同士の相互作用を可視化させることがひとつの手法である。
変換過程又は相互作用の可視化には、主成
分分析、判別分析など数多くの既存分析手法が適用される。
判別分析によるデータベースの解析には、まず収集されたデータベースから、決められたクラスに基づく判別分析を行い、適切な判別器、例えば、線形、非線形、2 クラス、多クラス判別器などを生成する。続いて、得られた判別器、詳しくはトレーニングデータから客観的に生成した判別器により、現象を予測すること、あるいは既存の課題に対する対策を提案することである。
そして、SIMOT の視点から見ると、入力因子から出力結果への変換過程と入力因子の相互作用とは判別器で解明される。新たなデータについて、判別器によりその入力因子から出力結果を判別、予測する。また、判別器
から入力因子における最も重要な因子も見つける。

また、非線形変換φにより、xi を特徴空間
F に射影してから、非線形の判別関数を求められる。特徴空間における内積<φ(xi),φ(xj)>は、xi と xj の射影の内積である。この内積はカーネル関数 K(xi, xj).で直接計算できることが既に知られている。本研究において、以下の式のRBF(radial basis function)カーネル関数を適用する。
(1)
K(xi, xj)=exp(-||xi-xj||2/2σ2).
ここで、σは変換φ(･)の非線形を制御する
パラメーターである。
つまり、双対問題における内積の部分をカーネル関数で入れ替えると、非線形関数は簡単に得られる。
しかし、この二次計画問題において、双対
変数ηir の量は m×k であり、最適解を求めるには計算時間が非常にかかる。一般的には、大規模のデータベースに対して、実行不可能の状態になる。

3.2 切除平面法の概念
切除平面法とは、最適化問題の繰り返しで近似解を求める手法である。この手法には、
まず最適化問題の制約式を緩和し、元の問題
より簡単に解ける緩和問題を作る。続いて、
この緩和問題を解いて、得られた緩和問題の最適解から切除平面を作る。そして、得られた切除平面を新たな制約式として緩和問題に
3. 切除平面法によるアルゴリズム
追加して、緩和問題を更新する。さらに、有3.1 多クラス問題の定式化
限回の切除平面の追加により、更新された緩和問題の最適解が元の最適化問題の最適解と与えられた m 個のトレーニングデータがなる。
D={(x1,y1),…, (xm,ym)}とし、xi∈Rn は n 個の属
また、この繰り返しの過程の終了基準を設性値がある i 番目のトレーニングデータであり、定することにより、元の最適化問題の近似解
yi∈{1,…k}は対応したラベルである。また、目を求められる。
的はトレーニングデータを判別できる関数
仮に s 個の切除平面が存在すると、以下のHM(x)=argmaxr<Mr,x>を探すことである。ここ最適解問題を解くことにより、非線形多クラで、M は k×n の行列、Mr は行列 M の r 番目
ス判別関数が得られる。
の行、<･,･>は内積とする。
Crammer は判別関数における行列 Mr を求めるために、以下の最適化問題を提案した。

ここで、C は trade-off、ξi は slack 変数である。また、yi=r ならばδyir=1、yi≠r ならばδyir=0。
双対変数η ir の導入により、以下の双対問
題が得られる。

ここで、ηuir は u 番目の切除平面から得られた変数である。

413

また、双対問題を解いてから得られた最適解λu により、(s+1)番目の元の最適化問題の最適解 Ms+1 が求められる。しかし、望ましいものは行列 Ms+1 ではなく、それぞれの行 Mrs+1 とテストデータ x の非線形射影との内積値< Mrs+1,
φ(x)>である。この値もカーネル関数と用いて、以下の式で計算する。

3.3 切除平面法のアルゴリズム
本研究では、3.2 の双対問題に対して、以下のように簡略化した。

変数の行列 Z とベクトル c は、行列の掛け算とトレースの計算で得られる。詳しくは以下のアルゴリズムで説明する。
また、K はカーネル関数から得られた m×m のカーネル行列とし、、Δはδyir からなる m
×k の行列とすると、以下のアルゴリズムで3.2 の双対問題を簡単に解ける。

4. 数値実験
提 案 し た ア ル ゴ リ ズ ム に つ い て 、 UCI
machine learning repository から入手する五種類のデータベースに対する数値実験を行った。
以下の表 1 でそれぞれのデータ名、トレーニ
ングデータ数、テストデータ数、及びクラス数を示す。
表 1 数値実験を行ったデータベース

DatasetOptdigit
Image
Pendigit
LetterForest

Train
3809
210
7494
4000
3500

Test
1797
2100
3498
16000
577512

Class
10
7
10
26
7

本 研 究 の 数 値 実 験 で は 、 5-fold crossvalidation でそれぞれのデータセットにおける最適の C と RBF カーネル関数 1/2σ2 を生成する。また、終了基準の閾値 tol は、データセッ
ト”optdigit”に対して tol=0.1 を設定し、ほかのデータセットに対して tol=0.01 を設定する。

414

また、比較としては、多クラスのデータセットからクラス数の二クラス問題を作って、二クラスの SVM を使って実験する。提案した
ア ル ゴ リ ズ ム と 同 じ よ う に 、 5-fold crossvalidation で最適の C と 1/2σ2 を生成する。
提案したアルゴリズムと SVM との実験結果は、以下の表 2 と表 3 で示す。

[2]

Bredensteiner, E. J. and Bennett, K. P., 1999.
Multicategory classification by support vector
machines. Computational Optimization andApplications, vol. 12, pp. 53--79.

[3]

Crammer, K. and Singer, Y., 2001. On thealgorithmic implementation of multiclasskernel-based vector machines. Journal of
Machine Learning Research, vol. 2, pp. 265-292.

[4]Inoue, T. and Abe, S., 2001. Fuzzy support
vector machines for pattern classification.
Proceedings of International Joint Conference
on Neural Networks, vol. 2, pp. 1449--1454.

[5]

Jia, X. and Richards, J. A., 1998. Two-classdecision classifier for optimization of classdiscriminations.
RemoteSensingofEnvironment, vol. 63, pp.289--297.

[6]

Joachims, T., 1999. Making large-scale
support vector machine learning practical, in
Advances in Kernel Methods, B.Schölkopf, C.
Burges, and A. Smola, Eds., pp. 169--184.
The MIT Press, Software available at
http://svmlight.joachims.org/.

[7]

Platt, J. C., 1999. Fast training of support
vector machines using sequential minimal
optimization. Advances in Kernel Methods.
The MIT Press. pp. 185--208.

[8]

Platt, J. C., Cristianini N., and Shawe-Taylor,J., 2000. Large margin DAGs for multiclassclassification. Advances in Neural Information
Processing System 12. The MIT Press. pp.
547--553.

[9]

Schapire, R. E., 1997. Using output codes toboost
multiclasslearning
problems.
Proceedings of 14th International Conference
on Machine Learning, pp. 313--321.

表 2 五種類のデータベースの正解率

DatasetOptdigit
Image
Pendigit
LetterForest

切除平面法*98.83*89.38*98.51*93.51*68.12

SVM
98.72
87.76
98.34
93.03
67.92

表 2 において、提案した切除平面法によるアルゴリズムは SVM より優れたパフォーマンスが出る。
表 3 五種類のデータベースの誤判別数

Dataset

切除平面
法

SVM

Optdigit
Image
Pendigit
LetterForest

21
223
52
1038
184124

23
257
58
1116
185260

誤判別数
の減少率
(%)
8.79
13.23
10.34
6.99
0.61

表 3 には誤判別のデータ数を示す。この結果により、提案した方法はテストデータを判別するとき、forest 以外のデータセットでは誤判別数が 5%以上減少した。

5. 結論
本研究では多クラスの判別分析におけるア[10] Tax, D. M. J. and Duin, R. P. W., 2002. Using
ルゴリズムを提案した。提案した方法は、二two-classclassifiersformulticlass
次計画問題において大量の変数を解くことをclassification.
Proceddingsof
16th
避けられる。また、切除平面法の導入により、International
ConferenceonPattern
有限回数の繰り返しで近似解を求められる。
Recognition, vol. 2, pp. 124--127.
また、提案したアルゴリズムにより、多クラス判別器は行列の掛け算とトレースの計算[11] Vapnik, V.N., 1998. Statistical Learning
で、効率的に求められる。
Theory. John Wiley & Sons, 1998.
さらに、数値実験の結果により、提案した[12] Weston, J. and Watkins, C., 1999. Multi-class
方法は既存の方法と比較すると、より高い効support vector machines. Proceedings of
果が得られることを確認した。
ESANN99
References[1]

Abe, S. and Inoue, T., 2002. Fuzzy support
vector machines for multiclass problems.
Proceedings of European Symposium on
Artificial Neural Networks, pp. 113--118.

415

半教師あり学習と SIMOT における応用
郭 天放**

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPAN
kuo@me.titech.ac.jp
現在、データマイニング（data mining）は注目されている研究分野の一つである。データ
マイニングとはデータベースについて分析を行い、効率的に隠された有用な知識を取り出し、現実の状況を判別、予測することである。
本研究は、従来では計算することが非常に困難であった大規模なカーネルを用いた半教師あり学習における判別問題に対し、高速に判別関数を求める計算手法を構築することである。さらにそれらをいくつかの大規模なデータに対して数値実験を行うことで、提案手法の有効性を実証的に確認した。

1. はじめに
現在、データマイニング(data mining)は注目されている研究分野の一つである。データマイニン
グとはデータベースについて分析を行い、効率的に隠された有用な知識を取り出し、現実の状況を判別、予測することである。応用分野としては、文献分類、画像認識、蛋白質とゲノム解析など、幅広
い範囲に渡っている。
情報技術の発達によって記憶できる情報の量が近年ますます大規模化するとともに、ネットワー
クの構築により容易に情報を収集し管理できるようになった。また、計算機の処理能力の向上から、それらの大規模なデータを用いたデータ分析が可能になってきた。しかし、データマイニングの大きな問題の一つとしては分析するときの計算時間である。
例えば、マーケティング分析における一年間の販売データ数は数十万から数百万に至る可能性が有り、かつ、各データにはまた数十種類の属性を含むことになる。このような膨大なデータベースにおいて直接分析を行うと、計算時間が非常にかかるという問題がある。それゆえ、データマイニングの研究分野において、高速の計算手法の研究は一つの重要な課題である。
データマイニングの研究分野において、数多くの手法がある。本研究では、半教師あり学習における多クラスの判別分析に注目している。
2. 教師あり学習と半教師あり学習
一般的なデータベースには、各データに対していくつかの属性値（例えば、サイズ、重量などの数値）と一つのラベル（例えば、良いと悪い）が与えられた。データを分析する手法として、サポートベ
クターマシン(SVM)、ニューラルネットワーク、決定木などをはじめとした教師あり学習の手法が近年めざましい勢いで発展してきた。教師あり学習とは、
データとそのラベルを用いた分析手法である。

416

近年の研究において、学習アルゴリズムの中でも最も多く研究されているもののひとつが SVMである。SVM は高い汎化性を持つとともに、複雑な分布をしたデータに対してもカーネル関数を用いて判別器を生成することで、判別を有効に行えることが示されてきた。
また、カーネル関数を使う方法とは、有限次元のデータベースをより一層高い次元空間（無限次元空間）に射影して、このデータベースのなかに存在する特殊な性質を探す方法である。
ただし、教師あり学習にはラベルの付与されたデータが必要である。また、データへのラベル付け作業は非常に手間がかかる。例えば、文章分類を例とすると、ある文章がスポーツニュースか否かのラベルを割り当てるには人間がその文章を読んで判断するしかない。また、画像認識を行う場合、人間で画像を見なければ、画像の種類をラベルとして与えることができない。このようにデータにラベルを付与する作業はきわめてコストが高い。さらに、教師あり学習では充分なラベル付きデータがなけ
れば、データに相応しい判別関数を推定することができない。
このような背景から、コストの高いラベル付きデータをなるべく使わずに判別の精度を向上させる
分析手法へのニーズが高まってきた。近年、これに対する手法として、半教師あり学習が注目を集めている。半教師あり学習とはラベル付きデータだ
けではなく、ラベルがないデータも学習に用いるアルゴリズムである。ラベル付きデータに比べれば、ラベルなしデータは比較的に収集が簡単であることから、半教師あり学習はラベル付きデータと大量のラベルなしデータによって、精度の高い判別を行うことを目標している。しかしながら、半教師あり
学習において、トレーニングとして使われるデータ数が非常に多い。
本研究では、カーネル関数に基づいた判別問
題を半教師あり学習に対して考え、それに対する計算手法を提案する。提案した手法は、ラプラシア

ン行列から派生するいくつかのカーネル行列を用い、SVM を半教師あり学習の枠組みへと拡張を行う。これらのカーネル行列を構築するためには、ラプラシアン行列の一般化逆行列あるいは固有値分解を求める必要があるため、通常の計算機環境では数万データの問題が限界であった。これに対して、提案手法ではラプラシアン行列をそのまま扱う
ため、数万を超えるような大規模な判別問題も容易に扱うことを可能とする。さらに、提案した枠組み
は、他の SVM にも容易に適用可能で、多クラス
SVM へと拡張を行う。
SIMOT において、データベースから入力因子(input)と出力結果(output)の関係を見出すことをひとつの目的とする。一般的な状況において、入力
因子から出力結果への変換過程はブラックボック
スのような状態である。このブラックボックスを解明するため、入力因子から出力結果への変換過程
又は入力因子同士の相互作用を可視化させることがひとつの手法である。
変換過程又は相互作用の可視化には、主成
分分析、判別分析など数多くの既存分析手法が適用される。
判別分析によるデータベースの解析には、まず収集されたデータベースから、決められたクラスに基づく判別分析を行い、適切な判別器、例えば、
線形、非線形、2 クラス、多クラス判別器などを生成する。続いて、得られた判別器、詳しくはトレー
ニングデータから客観的に生成した判別器により、現象を予測すること、あるいは既存の課題に対する対策を提案することである。
そして、SIMOT の視点から見ると、入力因子から出力結果への変換過程と入力因子の相互作用とは判別器で解明される。新たなデータについて、判別器によりその入力因子から出力結果を判別、予測する。また、SIMOT に関する分野から収集されたデータには、人間でラベルを付与しなけ
ればならないものが多いという現状である。そのため、半教師あり学習から生成された判別器のコストが低くて、精度が高い。また、これらの判別器から入力因子における最も重要な因子を見つけることが容易と考えられる。
3. 半教師あり学習における多クラスSVM与えられた l 個のラベル付きデータが{(x1,y1),…, (xl,yl)}とし、xi∈Rn は n 個の属性値がある i 番目のラベル付きデータであり、yi∈{1,…h}は対応したラベルである。また、u 個のラベルなし
データが{xl+1,…, xl+u}とし、M=l+u とする。
さらに、非線形変換がφとし、n 次元のデータ
xi を特徴空間 F に射影する。簡単化のため、φ(xi)をφi とする。
多クラスの判別問題の目的は、以下の最適化問題を解いて、h 本のベクトル wi∈F を探す。

ここで、C は trade-off、ξij は slack 変数である。
未知データ x のラベルについて、以下の判別関数
で判別する。
また、特徴空間における内積<φi,φj>は、xi とxj の射影の内積である。この内積はカーネル関数
K(xi, xj).で直接計算できることが既に知られている。
本研究において、以下の式のラプラシアン(Laplacian)カーネル関数を適用する。

ここで、L=D-W、W は k 最近傍法で作られた
M×M 対称行列であり、その要素は wij とする。この k 最近傍法を用いて、データ xi に対して、xj が
k 最近傍であるか、あるいは xj に対して xi が k 最近傍であるとき、i-j 間に重み wij を設定する。重みの値としては、wij=1 のような最も単純な方法を用いる。ゆえに、W は sparse 行列である。
D は対角行列であり、i 番目の対角要素 Dii は
行列 W の i 番目の行において、全ての要素の総和である。つまり、多クラスの判別について、各クラスに対応するベクトル wi∈F が全ての特徴空間に射影したデー
タの線形結合であることと仮定する。つまり、h 本の変数のベクトルを導入すると、以下の関係がある。
変数αi で表示されたベクトル wi を多クラスの判別問題に代入すると、以下の最適化問題になる。

さらに、βi=Kαi が成り立つ変数のベクトルの導入により、多クラスの判別問題は以下のような制約条件がない最適化問題になる。

h

この最適化問題の目標関数を F(β1,β2,…,β)とし、とすると、F(β 1,β 2,…,β h)は偏微分で以下のような最適解を求められる。

417

また、最適解が(β1*,β2*,…,βh*)とすると、ラベ
ルなしデータ xj のクラス以下のように判別される。

4. 数値実験
提案した手法について、四種類のデータベースに対する数値実験を行った。以下の表 1 でそれぞれのデータ名、データ数、クラス数、属性数、及び k 最近傍法で使われる k の値を示す。
図 2. データセット LETTER の平均正解率

表 1 数値実験を行ったデータベース

データ名
MNIST
LETTER
WebKB

データ数
70000
20000
4199

クラス数
10
26
4

属性数
784
16
10949

Newsgroups

18597

20

34746

k
5
5
1
3
6

本研究の数値実験では、提案した手法(MSVM) と 既 存 手 法 の 1 最 近 傍 法 (1NN) 、
quadratic energy minimization (EM)、及び local
and global consistency method (LG)とを比較する。
また、カーネル関数のパラメータ t=100 を設定し、trade-off のパラメータ C=1000 を設定する。さらに、
データセット MNIST におけるラベル付きデータ数
は 20 から 500 であり、他のデータセットにおけるラベル付きデータ数は 50 から 500 である。それぞれのデータ数について、ランダムでラベル付きデータを選択し、10 回の実験を行う。
10 回の判別実験の平均正解率は図 1 から 4に示す。

図 3. データセット WebKB の平均正解率

図 4. データセット Newsgroups の平均正解率
図 1. データセット MNIST の平均正解率418

図 1 から 4 のグラフから、提案した手法(MSVM)は既存手法より高精度ということを示した。
また、表 2 にはデータ数が最も多いデータセット
MNIST について、提案した手法(MSVM)と既存手法(LG)の平均計算時間を示す。この表 2 から、提案した手法は大規模のデータセットをより短い計算
時間で解ける。
表 2 データセット MNIST における平均計算時間

ラベル付きデータ数
20
100
500

MSVM
21.3
24.8
28.3

LG
40.5
41.5
43.0

以上の数値実験の結果により、提案した手法
は高速、そして高精度ということを確認した。
5. 結論
本研究では半教師あり学習において、多クラスの判別分析の手法を提案した。提案した方法において、解くことが必要の最適化問題は簡単な凸二次計画問題である。また、ラプラシアンカーネル行
列の使用により、sparse という特徴を生かして、大規模の多クラス判別問題も効率的に実行できる。
さらに、数値実験の結果により、提案した方法
は既存の方法と比較すると、より高い効果が得られることを確認した。
References[1]

Belkin, M., Matveeva, I., and Niyogi, P., 2004.
Regularization and semi-supervised learningon large graphs. Proceedings of the 17th
Annual Conference on Learning Theory.

[2]

Crammer, K. and Singer, Y., 2001. On thealgorithmic implementation of multiclasskernel-based vector machines. Journal of
Machine Learning Research, vol. 2, pp. 265-292.

[3]

Smola, A. and Kondor, I., 2003. Kernels andregularization on graphs. In Scholkoph, B. and
Warmuth, M., editors, Proceedings of theAnnual Conference on Computational
Learning Theory, Lecture Notes in Computer
Science. Springer.

[4]Zhou, D., Bousquet, O., Lal, T.N., Weston, J.,
and Scholkopf, B., 2004. Learning with local
and global consistency. Advances in Neural
Information Processing Systems, 16: pp. 321-328.

[5]Zhu, X., Ghahramani, Z., and Jafferty, J.,
2003. Semi-supervised learning using
Gaussian fields and harmonic functions.
Proceedings of the 20th International

419

Conference on Machine Learning, pp. 912-919.
[6]Zhu, X., Lafferty, J., and Ghahramani, Z.,
2003. Semi-supervised learning: From
Gaussian fields to Gaussian processer.
Technical Report CMU-CS-03-175, Carnegie
Mellon University.

顧客属性に基づく顧客満足度の日米比較
池庄司
*

雅臣*

(株)ニイウス金融エンジニアリング・グループ

顧客満足度そのものの大きさは，性別や年代といった顧客属性によって差があることが ACSI による過去 10 年のデータ調査からも報告されており，その原因として購買や使用経験の多寡が指摘されている．本研究では，日本の満足度データについても同様な分析を行うことで，ACSI と共通した傾向が示されており，さらには満足度指標の性質による差異についても考慮した知見を得ることができた．
１．はじめに消費者の顧客満足度（CS 度）という概念は，競争市場内での企業の経営戦略の在り方やその成果についての客観的指標にとどまらず，産業レベルでの市場間の動向についての比較，さらにはそれらを内包する国家レベルでの経済的背景に対しても大きな要因となっている．
これまでの研究では CS 度を構成する心理的要因とその生成メカニズムに着目することで，負の要因（景気感バイアス）と正の要因（消費活動）が互いに独立して影響を与えることが，日米両方の CS 度からも示されている．しかしこれらの知見は，一定のレベルで見た消費者集合による（aggregate な）CS 度に基づいたものであり，あくまで対象となる市場・製品レベルで見た場合の包括的な結果に過ぎない．
一方で，アメリカの代表的な CS 度である
American Customer Satisfaction Index(ACSI)では，
過去 10 年分のデータを総括した分析結果から，性別や年代といった顧客属性で分類した CS 度の傾向について報告がなされている 1)．結果，
男女や年齢による差の存在が認められ，製品・サービスに対する感じ方や，その背景にある購買傾向の違いについてまで言及されている．
以上の流れから，日本の耐久消費財におけるCS 度についても顧客属性によるセグメントを考慮した分析をすることで，主に性別や年代による差の存在について明らかにする．その上で製品の使用や購買に対する消費者の捉え方を
属性レベルでより詳細に考察することを目的とする．さらに，ACSI と同じ特性を持つ CS 度
指標としてメーカーCS 度を対象とした属性別の分析を行った結果，その傾向について ACSIと共通性があることについても述べる．
２．ACSI の説明と知見
ACSI は，アメリカにおける代表的な CS 度として，既に広く認知されている．これは開発者の Fornell らによって 1994 年の夏から公表され，この時期を baseline と位置づけて以降，10 年以上に渡り継続的な調査がされており，四半期ごとにデータが公開されている．
調査においては，対象顧客へのアンケートから，企業へのイメージを過去・現在・未来それ
ぞれの観点に基づいた項目で総合的に評価してもらうため，その特性から累積指標と呼ばれ420ている．さらにその算出対象は企業レベルだけにとどまらず，産業レベル，セクターレベル，
ひいては国家経済レベルに至る４つのステー
ジにおける CS 度について，それぞれ 100 段階で算出されている．
最近では 10 年という一定の期間を通して CS
データが蓄積されたのを受け，Fornell らが ACSI
に対するこれまでの総括を報告している 1)．それによれば，顧客属性で CS 度を捉えた場合，総じて女性の方が男性よりも平均的に高い傾向を示しているとされ（女性＝77，男性＝73），
同時に高齢になるほど平均的に高くなることも分かった（75 歳以上＝82，30 代前後＝72）．
女性の CS 度が相対的に高くなる原因として，
製品・サービスの購買頻度の高さによる経験が指摘されている．すなわち，経験的により良い製品・サービスを選ぶ能力が男性よりも備わっており，実際に購入したものに対して失敗や不満を感じにくいため CS 度も高くなるとしている．また一般的に年齢が高くなるほど経験も多くなるため，製品・サービスあるいはその企業に対する知識から同様な理由で CS 度が上がるとされている．さらに，より良い製品を買えるだけの予算の向上や，不確かな製品を回避する
傾向の高さも一因として指摘されている．
３．日本の CS 度の説明と知見
３．１ モナディク指標と累積指標
本研究における日本の CS 度とは，３種類の耐久消費財（冷蔵庫，テレビ，洗濯機）について，1977 年から 2004 年までの約 30 年間で，ほぼ３年ごとに計 10 回の調査によって得られたデータに基づいている．その測定尺度は 0「大変満足」から 4「不満」としており，冷蔵庫，
テレビ，洗濯機それぞれの性能・機能に対する評価概念として構成された品質項目について，
現在使用している製品を対象にして質問した結果である．こうして得られた各サンプルの結果を全項目で平均して反転させ，ACSI と同様に 100 段階に尺度化し直すことで，各個人の製品そのものへの品質 CS 度としている．このように測定された CS 度は，過去の購買経験に基づくとされており，価格や広告といった機能以外の購買動機に左右されるという特性からモナディク指標と考えられる．

一方で対象製品のメーカーに対する CS 度についても，最新の 2004 年の調査から同様の尺度（0「不満」から 4「大変満足」）で測定が行われている．このような評価データは，企業そのものに対する包括的なイメージとして考えられ，ACSI と同様に累積指標として区分する
ことができる．
３．２ 景気感バイアス
既に筆者らは，一般的な CS 度に影響を与えるとされる外的要因について明らかにしている．特に負の要因の存在は，日本の品質 CS 度を用いることで，日経平均株価に代表される景
気感との間に強い負の相関関係があったことがきっかけとなっている 2)．このような影響を考慮することで実際の企業のマーケットシェ
アなどの経営成果に対しても，CS 度が適切に反映できることが示されている．図１からも分かるように各製品の CS 度は株価と対称的な推移を示しており，それぞれの相関係数も冷蔵庫-0.917(p=0.0001) ， テ レ ビ -0.863(p=0.0006) ，
洗濯機-0.917(p=0.0001)と，非常に高い負の値が得られた．このような株価の動向を経年的な景気感と捉えた場合，CS 度とは景気感に対して負の影響を受けるという，いわゆる「景気感バイアス」とも呼べる存在が確認できる．
日経平均

株価

冷蔵庫

テレビ

洗濯機

65

35000

60

30000
55

25000

50

20000
15000

45

10000
40

5000
0
1977

1980

1983

1986

1989

1992

1995

1998

2001

男性

女性

65
60
55
50
45
40
35
1977

1980

1983

1987

1989

1992

1995

1998

2001

2004

図２. 冷蔵庫の品質 CS 度の男女別推移

一方，年代で見た場合，冷蔵庫（20 代 50.8，
40 代 50.4，60 代以上 58.8），テレビ（20 代 48.3，
40 代 49.3，60 代以上 50.4），洗濯機（20 代 47.3，
40 代 48.0，60 代以上 52.9）となり，年齢が高くなるほど概ね CS 度も上がる傾向が見られた．
同様に冷蔵庫における推移を見た場合，図３より 60 代以上の CS 度は全体的に他の年代層よりは高くなっているが，40 代と 20 代の CS 度は年度によって大小が変わり，明確な差は見られなかった．以上より ACSI による知見と比較した場合，年代ではほぼ同様だが，性別については対照的な結果が得られることになった．

CS度

40000

能である．そこで，製品の品質 CS 度（モナディク指標）を対象とし，特に性別と年代で層別したときの年度別 CS 度の傾向について比較した．その結果，性別による全調査年度の平均 CS
度は，冷蔵庫（男性 54.4，女性 50.2），テレビ（男性 51.7，女性 49.2），洗濯機（男性 49.8，
女性 47.5）となり，いずれの製品においても男性の方が高くなっていた．特に冷蔵庫ではその差が最も大きく，図２に示すように全調査年度
を通じて男性が高くなっているのが分かる．

35
2004

年

20代

図１. ３製品の品質 CS 度と株価の推移

40代

60代以上

85

一方で，アメリカの ACSI とダウ平均株価を対象にした同様の分析をした場合，相関係数は-0.221(p=0.086)となっており高度な負の有意性は必ずしも言えないものの，景気感バイアスの存在が認められている 3)．これは CS 度特性
として累積指標の方が，その構造上モナディク
指標よりも景気感を反映しにくいためであると考えられる．

75

65

55

45

４．顧客属性に基づく分析と傾向

35
1977

４．１ モナディク指標（品質評価）
耐久消費財の CS 度調査では，関連する品質項目の他に，フェースシートよりその消費者の属性についても回答してもらうため，それぞれの属性について層別した平均 CS 度の算出が可

1980

1983

1987

1989

1992

1995

1998

2001

2004

図３. 冷蔵庫の品質 CS 度の年代別推移

耐久消費財の CS 度について，特に男性の方が女性よりも高くなった背景には，その生活に421

おける使用形態の差が考えられる．例えば，冷蔵庫や洗濯機などは，普段の生活において女性の方が男性よりも深く関わっている分だけ使用頻度が高い．その結果，製品そのものの機能や性能に対する評価は相対的にシビアになると考えられる．また男性は，普段は使う機会の少ない製品・サービスについて評価するときは，
モナディク指標であっても企業へのイメージが相対的に多く組み込まれて，累積指標寄りのCS 度として算出されると考えられる．
モナディク指標と累積指標との違いを示唆する尺度基準のひとつとして，支払い意欲(WTP，willingness to pay)の存在が知られている．
すなわち累積指標に近づくほど，WTP との間に正の関連性があるとされているが 4)，このような指標は経年的なデータとして公表されていない．そこで，耐久消費財の WTP に関連があるとされる２つの指標として，個人消費支出（耐久消費財）と消費者態度指数（耐久消費財の買い時判断）を用いて主成分分析を行った．
得られた当該年度の主成分スコアを代用的に
WTP として用いて，各製品の男女別満足度との相関係数をとった場合，表１のように全ての製品において女性は負であるのに対して，男性は冷蔵庫と洗濯機において正に転じている．これは，男性の方が満足度と WTP の関連性が強い，
すなわち累積指標よりであることを間接的に示唆するものであり，テレビにおいては両者の使用に基づく評価の仕方に差が見られないと捉えることができる．
表１. 各製品の男女別品質 CS 度とWTP（主成分スコア）との相関

男性
相関係数
p値
冷蔵庫
0.078
0.427
テレビ
-0.252
0.273
洗濯機
0.083
0.423

女性
相関係数
p値
-0.0990.408-0.2050.313-0.0970.410

４．２ 累積指標（企業評価）との比較
次にメーカーCS 度（累積指標）を対象にした比較分析を行う．前述したように，対象となるメーカーCS 度は 2004 年度の調査データのみのため経年的な観点からの考察はできないので，各製品を同列に置いた分析を行うことになる．同調査年度の品質 CS 度と比較するために，
100 段階で尺度化したスコアを製品別で算出し，両者を比較した．結果，図４のようにサンプル層は同一にも関わらず，全製品でメーカーCS
度の方が高くなっている．また平均による差は有意ではないものの(p=0.122)，製品 CS 度が 50.0に対してメーカーCS 度が 61.5 であった．
品質CS度（モナディク)
70
65
60
55
50
45
40
35
冷蔵庫

テレビ

洗濯機

図４. 各製品に対する CS 度（2004 年度）

この結果から，実際に使用している製品に対する評価よりも，その企業（メーカー）へのイ
メージの方が，それまでの経験や知識などが累積される分だけ全体的に高まると考えられる．
その上で，顧客属性による傾向の差について見るために，男女別で平均したメーカーCS 度を算出した結果が図５である．
男性

女性

68

さらに３．２で述べたように，株価との相関に基づく景気感バイアスは，累積指標の方が弱まると考えられる．そこで、同様に株価との相関係数を男女別で比較した結果，表２のように全ての製品において女性の方が負の傾向が強まっている．このことからも，同じモナディク
指標でも男性の方が累積指標寄りの傾向を示しており，その要因として企業イメージに対する評価が相対的に大きいと説明できる．

65
62
59
56
53
50
冷蔵庫

表２. 各製品の男女別品質 CS 度と
日経平均株価との相関

男性
相関係数
p値
冷蔵庫
-0.8260.006
テレビ-0.6490.041
洗濯機-0.7820.011

メーカーCS度（累積)

テレビ

洗濯機

図５. 男女別で見たメーカーCS 度（2004 年度）

このように，メーカーCS 度（累積指標）では，製品 CS 度（モナディク指標）と違って男女の大小関係が逆転し，ACSI と一致した傾向が得られている．言い換えれば女性は製品そのものに対する評価はシビアなのに対して，そのメーカー自体のイメージに対しては長年の購買経験などから必ずしも反映されにくく，むし

女性
相関係数
p値
-0.8490.004-0.7840.011-0.8690.003
422

ろ総体的に高まっている．また，全製品の平均は，男性 58.6 に対して女性 62.9 であり，その差が有意であることも分かった(p=0.044)．
次に３段階の年代で層別したメーカーCS 度
を見ると，図６のように高齢になるほど平均的に評価が高まっており，やはり ACSI と一致した傾向が得られた．このときの平均は 10~20 代
57.4，30~40 代 60.8，50 代以上 65.7 となり，同様にその差はほぼ有意であった(p=0.054)．
10～20代30～40代

６．おわりに
CS 度は既に ACSI に加えて，スウェーデンのSwedish Customer Satisfaction Barometer (SCSB)
やドイツの German Customer Monitor(GCM)が90 年代前後から算出・蓄積されている．これらはいずれも累積指標として考えられ，ACSI と同じく属性別で評価した知見についての報告等について調査することで，さらなる比較検討が可能であると考えられる．特に，性別や年代レベルで評価される CS の傾向を見ることで、消費者を介した国家的な文化や生活様式についての考察にもつながるであろう．
本研究の CS 度分析は消費者の属性レベルにとどまっているが，ACSI の報告では産業レベルで見た CS 度の差などについても，既に一定の見解を示している．それらのトピックについて着目した比較分析をすることなども，背後にあるインスティテューションの違いを解明する一助になると期待できる．

50代以上）

71
68
65
62
59
56
53
50
冷蔵庫

テレビ

洗濯機

図６. 年代別で見たメーカーCS 度（2004 年度）

５．考察とまとめCS 度は評価対象や調査方法によって指標特性が変わり，その評価傾向にも変化があることをまず尺度的な大きさから示し，その上で性別と年代に基づく顧客属性においても差がある
事を確認することが出来た．
結果として，実際に使用している製品自体の品質に関する CS 度（モナディク指標）では，
普段から使用する機会の多い女性の方が評価は厳しい．その一方で男性は，表面的な評価に留まる分だけ企業イメージが副次的に作用し，総合的に評価も緩和されると考えられる．
一方でメーカーCS 度（累積指標）に関して
は，その時点での使用製品に対する評価を必ずしも反映するものではなく，むしろそれまでの購買や使用に基づいた経験から培った知識やイメージによる要因が大きくなる．そのため実際のスコアも相対的に高くなり，同じ累積指標である ACSI にも通じるものがある．そして属性別で見た場合，女性や高齢層の方がより多くの製品・サービスを通じた情報から判断する分，
結果として評価も高くなると考えられる．この傾向も ACSI による報告結果と一致するものであり，累積指標という CS 度において，国家的に共通した知見を得ることが出来た．
今回の分析では累積指標となる CS 度があくまで単年度のデータであるため，今後の調査による継続的な蓄積が必要とされる．その上で，経年的な景気感バイアスによる影響も含めて，より多くの顧客属性で見た CS 度の動向についてモナディク指標との比較をする事で，評価における構造や背景の違いについてさらに解明することを課題のひとつとしたい．
423

参考文献
1) Fornell, C. (2005), “Discover the Most
Important Findings from 10years of ACSI
Analysis”
2) 池庄司雅臣，圓川隆夫，鈴木定省: ”品質向上期待度に基づく顧客満足の経年変化パタ
ー ン と マ ー ケ ッ ト シ ェ ア と の 関 係 ”, 品
質,Vol.33,No.3 (2003)
3) 池庄司雅臣，圓川隆夫: ”顧客満足度と景気感 と の 関 連 に 関 す る 研 究 ”, 品
質,Vol.34,No.4 (2004)
4) Homburg.C, Koschate.N, Hoyer.D.W(2005),“Do Satisfied Customer Really Pay More? A
study of the Relationship Between Customer
Satisfaction and Willingness to Pay”, Journal ofMarketing, 69, 84-96

特許明細書の定量的性質に注目した特許率の分析

½

東京工業大学（ミノル国際特許事務所）
東京工業大学¾

研究の背景・目的

特許
○
○
○
○
×

事業化
○
○
×
×

  

特許明細書の定量化と特許率

明細書は文章で書かれたものであるので、定量化することは困難であるし、そもそも定量化することに意味があるのかという疑問はつきまとう。もちろん、特許されるかどうかは技術そのものの新規性や進歩性の問題であるが、現実的に出願段階で全ての先行研究を自前で漏れなく調査することは難しいし、先行技術に対する微妙な差異や技術的特徴については自己判定しづらいという側面もある。そこで、ある程度の先行技術調査をする場合も含めてとりあえず特許出願し、実際の先行技術との比較、照合を改めて行い、一定の法的制限の下で認められた範囲で特許明細書を補正することにより、当該先行技術に対する技術的な差異、ひいては進歩性を出していくことが現実的な対応になる。
そうした中で、経験的に以下のような特許明細書の定量的要素が、最終的に特許権を取得できるかどうかに関係してくると考えられる。

創出された知的財産を戦略的に活用するための新たなビジネスモデルを構築して企業経営に結びつけ
企業価値の向上を図る、いわゆる知的財産経営の重要性が高まっている½ 。特に、特許権は有効活用することで、市場における独占排他的実施による収益向上や実施権設定によるロイヤルティ収入等、企業のキャッシュフローに直接的に大きな影響を与えるため、知的財産経営上も非常に重要なアイテムとなる。もちろん、特許権には、競合他社の新規参入阻止等を目的とした防衛的な活用、更にはＭ＆Ａ等を始めとした経営戦略上での活用や、金融資産としての活用等の目的があることも見過ごせない¾ 。もちろん下表のように、特許権が収益に結びつくためには、特許技術を活かした製品・商品の事業化や市場ニーズとの整合性なども重要な要素であるが、まずは特許権を取得できるかどうかは戦略上非常に大きなマイルストーンである。特許権を取得するためには、特許明細書の作成・
ケース
成功
事業戦略失敗
事業化失敗
知財戦略失敗
特許化失敗

安彦 元
中川 秀敏

明細書全体に書かれている発明概念（請求項となりうる発明概念）の数（ 

市場ニーズとの整合○
×○×

明細書の内容別グループの数  
請求項の数  、請求項を含むグループの数    、補正後も残っている請求項の数   
カッコ内の要素のうち、  と  は出願時に
     は確定されるものであるが、審査後の補正により変更することができる。そこで回目の補正後の各要素を表すために  のように表すことにする（出願時点は   とする。特に    ）。これらをまとめて、 回目の補 
正後の明細書の状態を                と表すことにする。各時点の    は非負の整数の５つ組で表される。
発明概念の数  や請求項の数
 が大きいということが特許化に有利になることは自然に予想される。また、 は対象となる技術をどの程度多くの視点から見ているかを表しており、その数が多いほど特許化の際に技術を活かす切り口が多いことを意味していると考えられる。ただし、グループの分け方は
恣意的になるため、実際に請求項を含む主要なグルー

特許出願・特許庁による審査・特許権の設定登録というプロセスを経るが、一般に審査期間は非常に長く、また審査の中で先行する文献を提示され、先行文献との差異を検討して「特許請求の範囲」を補正し、再審査にかけるというステップを何度か経験するのが通常である。
そこで本研究では、特許出願時に提出する「特許請求の範囲」「明細書」に注目し、これらを内容・構成の点から定量化する方法を提案し、特許明細書の定量的性質と特許権取得の成功の関係について分析を試
み、どのような形で特許出願し、さらに補正をはじめとした中間手続きをすることが望ましい戦略であるかを考察した。
½ 鮫島正洋著「特許戦略ハンドブック」（中央経済社）  
ページ参照

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プの数  の多寡も考慮することにした。さらに  は、先行文献との比較で差異が認められた請求項の数の累積値（ダブルカウントも含む）として定義するが、裏を返すと   の値が大きいことは、先行技術に対して新規性・進歩性が認められた請求項が残っていることを示しており、請求項全体の質を表現している要素と見なすことができる。
次に、特許率（成功確率）が    の状態のみの関数として与えられるという仮定¿ のもとに、以下のような条件付き確率の形で表す：   が     という非負の整数の５つ組で与えられるとするとき、

成功ケース        










特許         












 


成功ケース        

この成功確率の評価はベイジアン・スキームに沿って、事例が追加されるたびに更新していく。例えば成功事例が追加される場合、形式的に

特許  追加   
追加    特許 特許追加   










 


失敗ケース       という条件付き確率の見方を通じて    が追加される前の成功確率を事後的に評価した確率に変換していく。

¿

 

成功ケース             






















 


定量化の事例研究際に、この豊富な  の中から選んだ４つの発明概 化したところ、２つに関しては「特許性あ念をり」、残りの２つは「特許性なし」という特許庁の見解が下された。このため、特許性のある２つのに限定して補正を行った。その結果    への と  が減少、  が増加し移行時にた。  の影響を断定はできないが、今後も注意
すべき指標であると考えられる。
失敗ケース は、  が非常に少なく、次の    へ移行する際の、  の補正の選択肢が減り、引用文献との差異を見いだすことができず失敗に終わったと考えられる。しかし、一方で成功ケース は、   は少ないにもかかわらず、その少ない  の中に顕著な技術的特徴が含まれていたため、特許された事例である。このように単純に定量的な特徴だけで説明できないケースも少なくない。しかし一方で、定量的な性質を把握していく試みも無意味ではないと考えている。今後はさらにサンプル数を増やし、確率的な評価も行っていきたい。

予稿での詳細は割愛させていただくが、今回はまず４件の実例（特許化成功（表の成功ケース１〜３）、特許化失敗（表の失敗ケース））について、前節で提案したように特許明細書の要素ごとの定量化を行い、
     の推移を調べ、確補正回数と率モデル構築の可能性を調べた。
成功ケース  は、  は 、 も  と多い。
このため、   へ移行する際に、  の補正の選択肢を増加させることができ、特許化に結びついたと考えられる。また、補正後に  が増加している。ただし、実際に特許された理由は、メインク
レーム（第１請求項）に進歩性が認められたためであり、  の増加と特許の因果関係はこの一例だけ
では断定できない。しかしながら、この  は、
特許活用時の切り口の数を表しており、特許後の経営
環境の変化に対していかに柔軟に対応できるかを示
す指標と考えられるので、今後も注目したい。
成功ケース  は、  は  と多いが、 は とあまり多くない。この特許明細書は、少ない 内に  を多数設けて引用文献に対抗していく戦略が採用されているといえる。   に移行する¿ 本来は、対象となる技術分野、市場（グローバルかニッチか、   か   %）なども考慮したうえで成功確率を評価すべきである。今回はデータが量的に確保できていないため見送った。

特許請求の範囲の数値化表示方法の提案
安彦

元

東京工業大学大学院イノベーションマネジメント研究科〒108-0023 東京都港区芝浦3-3-6，キャンパスイノベーションセンター
fuku@minorutokkyo.com
１

決を直近の案件から計１９９件抽出した。東

概要

特許特有のクレーム記載パターンに着目し、 京高裁判決は、調査対象から除外した。また
数値限定により技術的範囲の広狭が左右され各構成要素において定義されている技術事項の限定度合いを文法上の文節構造体を単位とやすい化学、材料、生物等の分野の判決例はして抽出し、カウントする数値化スキームを調査対象から除外することとし、あくまでス提案した。提案した数値化スキームの各最小テップ数や動作数、条件数により技術的範囲

抽出単位１）構成要素、２）単語、３）格成の広狭が主に支配されると考えられる電気、分により実際の特許案件の特許請求の範囲を

機械分野を調査対象の中心に据えた。また、数値化し、これと技術的範囲捕捉成功／失敗

平成５年以降に提起された特許侵害訴訟を調と関係を調査したところ、最小抽出単位３）

査対象とし、それ以前に提起された判決例は格成分とした場合に最も良好なｔ値が得られ除外している。

た。このため、最小抽出単位を３）格成分と次に、このような条件の下で抽出した１９することにより、技術的範囲の広さに対応さ９件に亘る各裁判例について、その内容を精せてこれを高精度かつ客観的に定量化、数値査し、侵害被疑製品（イ号物件）に対して実化するスキームとすることができ、更にそこ際に直接侵害である旨を主張している本件特から技術的範囲の広さを客観的に測定し得る

許発明の特許請求の範囲を特定する。そして、“ものさし”に発展させることも可能となる

この特定した特許請求の範囲の記載に対して、ことが分かった。

各最小抽出単位１）構成要素、２）単語、
３）格成分とした数値化スキームにより、そ２の技術的範囲の数値化を行う。この数値化は、調査方法

上述した各最小抽出単位によるカウント方法

実際の特許侵害訴訟の対象となった特許発に則って、著者による手作業で行った。

明について、提案した数値化スキームの最小

さらに、判決文における「当裁判所の判抽出単位１）構成要素、２）単語、３）格成
分により、その技術的範囲の広さを数値化し、これと技術的範囲捕捉成功度数／失敗度数と断」の欄を精査し、侵害被疑製品が本件特許発明の技術的範囲に含まれているか否かの見解を読み取った。これにより、実際に数値化の関係を調査した。

スキームで技術的範囲の広さを数値化した特実際の調査は、裁判所ホームページの知的許請求の範囲により、侵害被疑製品を技術的財産裁判例集において、判例検索システムを範囲内に捕捉できたか否かを判断することに活用し、権利種別“特許権”、訴訟類型“民した。ちなみに侵害被疑製品を本件特許発明事訴訟”の条件の下で検索を行ったところ、の技術的範囲内に捉えることができても、被２００６年８月１１日現在で８８２件ヒット

告による各種抗弁（例えば、権利濫用の抗弁した。その中から、特許権侵害差止等請求事等）や無効審判の認容審決等により実際に侵件、特許権侵害損害賠償請求事件の地方裁判

害訴訟には負けてしまう場合もあるが、かか426

る要素までを考慮に入れると調査の目的から

単語数が少ないほど成功度数が高くなり、逆逸脱してしまう可能性がある。このため、本に単語数が多いほど成功度数が低くなり、失調査では、あくまで特許発明の侵害被疑製品

敗度数が高くなる傾向が表れていた。また、に対する技術的範囲捕捉成功／失敗か、のみ

成功率は、単語数が２５以下になると比較的に着目して判断することにしている。

高くなる傾向が表れていた。
図２

調査結果

単語数に対する技術的範囲捕捉成功／失敗の関係

図１は、最小抽出単位を１）構成要素とし成功（度数）
失敗（度数）
成功率

18
16値に対する技術的範囲捕捉成功度数／失敗度

14

数と関係を示している。また、技術的範囲捕12

捉成功の確率（＝成功度数／（成功度数＋失

10

度 数

た数値化スキームによる技術的範囲の測定数

敗度数）；以下、成功率という。）を三角形
構成要素数が少ないほど成功度数が多くなり、逆に構成要素数が大きいほど成功度数が

70
60
50

8

40
30

4

20

2

10

0

低くなり、失敗度数が増加する傾向は僅かな010がら表れていたが、成功率は、構成要素数に

20

30

40

50

60

70 80
単語数

90 100 110 120 130 140

対して明確な依存性は表れなかった。
図３は、最小抽出単位を３）格成分とした数

図１

値化スキームによる技術的範囲の測定数値に

構成要素数に対する技術的範囲捕捉成功／失敗の関係

30

100

している。最小抽出単位を１）構成要素数や9080２）単語とした場合と同様に、格成分数が小

20

70
60

度数

25

対する技術的範囲捕捉成功／失敗と関係を示

15

50
40

10

30
20

5

さいほど成功度数が多くなり、逆に格成分数が大きいほど成功度数が低くなり、失敗度数

成 功率

35

成功（度数）
失敗（度数）
成功率が増加する傾向は示されていた。また、最小抽出単位１）、２）と比較して、成功度数分
布と失敗度数分布とが、比較的明確に分離で

10
0

0

きている傾向が表れており、成功度数分布と失敗度数分布とがより明確に偏在していた。

1 2 3 4 5 6 7 8 9 10 11 12 13 14
構成要素数

このため、数値化スキームの最小抽出単位を
３）格成分とすることにより、最も理想的な“ものさし”に近づけることが可能となるも

図２は、最小抽出単位を２）単語とした数のと考えられる。特に格成分数が７以下の場

値化スキームによる技術的範囲の測定数値に合は成功率が極度に増加する傾向が現れてい対する技術的範囲捕捉成功度数／失敗度数とた。

関係を示している。特許請求の範囲における

427

90
80

6

のプロットで示す。

100

成 功 率

３

このため、最小抽出単位を３）格成分とす

図３

ることにより、技術的範囲の広さに対応させ

格成分数に対する技術的範囲捕捉成功／失敗の関係
成功（度数）
失敗（度数）
成功率

16
14

するスキームとすることができ、更にそこか

90
80

ら技術的範囲の広さを客観的に測定し得る“ものさし”に発展させることも可能となる

60

8

50

ものと考えられる。即ち、従来の解釈動向が

6

40

4

成 功 率

70

10
度 数

12

てこれを高精度かつ客観的に定量化、数値化
100

反映された信憑性の高い数値化スキームによ30

り、特許請求の範囲を、あくまで特許発明の20

2

技術的範囲の広さに対応させて数値化するこ

10

0

0

とができるため、特許権の持つ法的強度を定量的に測定することも可能となると考えられ

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33
格成分数る。その結果、特許価値評価における中心的リスクドライバーとしての特許権の持つ法的

４

強度を評価者の恣意的な要素を排除しつつ、まとめ

より定量的に測定することが可能となる。こ

本研究では、技術的範囲の広さを測定するのため、特許価値評価方法に新たな方向性を“ものさし”を目指した特許請求の範囲の数持たせることも期待できる。

値化スキームとして、１）構成要素、２）単語、３）格成分をその最小抽出単位として提

参考文献

案した。

[1] 経済産業省“知的財産の取得・管理指針”

また、提案した数値化スキームの各最小抽
出単位１）構成要素、２）単語、３）格成分[2] Ｒ.ラズガイティス“アーリーステージ知財の価値評価と価格設定”中央経済新聞社

により、特許請求の範囲を数値化し、これと技術的範囲捕捉成功／失敗と関係を調査した。 [3] 渡邊俊輔“知的財産―戦略・評価・会計” 東洋経済新報社
技術的範囲捕捉成功度数分布／失敗度数分布[4] 山本大輔、森智世“知的財産の価値評の有意差につきｔ値を介して比較したところ、価” 東洋経済新報社
最小抽出単位３）格成分とした場合に最も優[5] 鮫島正洋“特許戦略ハンドブック”中央
経済社 P190～P249

れていることが分かった。その理由として、[6]]特許庁編“特許価値評価指標(技術移転版)”

最小抽出単位３）格成分とした場合には、命題実現の条件数に一致させた格成分数として[7] 広瀬義州“特許権価値評価モデル(PatVM)”東洋経済新報社(2006)

これを表すことが可能となることから、ただ[8] 谷川英和、田中克己(2006)“3種類の特許
部品データベースに基づく特許明細書自動２）と比較して、技術的範囲を構成する文節
生成エンジンの構築”、情報処理学会論文
誌：データベース、Vol47 No.SIG8(TOD
構造体について文法的検討を踏まえて抽出し、30),pp90-104）
これを数値化することができるものと考えら[9] 永野周志 特許権侵害判断認定基準 ぎれるためである。また、最小抽出単位１）とょうせい
比較しても、より細かく構成上の相違を抽出[10] 益岡隆志 仁田義雄 郡司隆男 金水敏
言語の科学5 文法 岩波書店 P21～P39
することができる。
漠然と単語数をカウントする最小抽出単位428タイ国自動車部品企業の人材・技術発展と知的財産管理
ポンパンプーパックディチャンオーン

東京工業大学大学院 イノベーションマネジメント研究科 イノベーション専攻〒108-0023 東京都港区芝浦 3-3-6
bongsebandhu.c.aa@m.titech.ac.jp
タイの自動車部品産業は、その生産量が増大する中、技術レベルの向上や人材育成の強化により生産性を高めることとともに、技術を保護・活用するための知的財産管理の強化が必要である。自動車部品企業へのヒアリング、アンケートを行いその調査結果により、技術レベル向上や人材育成の手法、知的財産管理への取組みについて、日系外資企業と現地企業の対比、Tier 別の対比を行った。現地企業が成長する上で、品質管理技術の導入、従業員の定着率の向上の重要性が示唆された。
知的財産管理強化については、行政レベルでの取り組みが必要であろう。
1. はじめにEXPORT TRADE VALUE From Thailand to World 2001-2005(Automobile Section)

タイの自動車産業は、2003 年からのタイ政府による
1200「アジアのデトロイト」政策実施の結果、その生産高がH undred thous a nd dol l a rs

1000

著しく成長している。2006 年まで目標であった年間生
産台数100万台は、すでに2005年に達成されている、
1999～2006年タイ国自動車生産・国内卸売（台数）

800
600
400
200
0

2001

万台数

120

2002

spark ignition engine of <1000 cc
spark ignition engine of 1500-3000 cc
diesel engine of <1500 cc
diesel engine of >2500 cc

100

2003

2004

2005

spark ignition engine of 1000-1500 cc
spark ignition engine of >3000 cc
diesel engine of 1500-2500 cc
Automobiles including gas turbine powered80
Remark: Data of Year 2002 was unknown.

60

データ出所:「商品貿易データベース」国際連合統計部

4020

このような背景の中で、自動車部品企業は、その急

0
1999

2000

2001

2002

2003

2004

2005

2006

成長に対応すべく、品質管理など技術レベルの向上
生産台数

国内卸売

や技術を操作、管理する人材育成の強化に取り組んできていることが推測されるものの、自動車部品企業

データ出所:「タイ国自動車研究所

は中小企業がほとんどであり、そのような技術レベル
自動車生産の急成長とともに、自動車部品企業も急の向上や人材育成への取組みについての負担が大き

成長しているといわれている。タイ国内の自動車メーカ

いことが考えられる。

ーへの供給だけでなく、外国への輸出の増加も目標と

また、知的財産の管理についてみると、タイでは特しているところである。タイからの自動車関連部品の輸許制度の確立、模倣品対策の強化など知的財産制度

出額は、2003～2005 年で徐々に増加している傾向がの充実に向けて取組みが行われているものの、知的みられる。

財産を保護・活用するべき企業においては、その管理への意識が依然として低いといわれる。中小企業においては、より知的財産管理への取組みは弱いと考えられる。
本調査研究では、タイでの現地企業、日系外資企業
429

にヒアリング調査、アンケート調査を行うことにより、そアンケート項目

れらの企業での技術レベルの向上や人材育成強化へ① 従業員数の取組み、さらには知的財産管理の実態を調査し、そ② 売上高

れらの企業成長に与える影響を明らかにすることを目③ ビジネスにおける問題点的とする。

④ 知的財産管理の重視度（侵害等の発生への対応、特許事務所との連携、セ

2. 先行研究

ミナーへの参加などの知的財産活動、特許、商標等のWaldeck らは、米国企業の技術開発と人材育成につ出願の有無）

いて分析し、新技術の必要性に対する人材管理部門⑤ 顧客のマネジャーの認識が、全従業員の開発活動（個人の種別、顧客満足度、クレームの内容、顧客満足度の開発活動、経営上の開発）、プロセス開発活動に結び改善の方向性とその目的つくこと、を示している。（Waldeck ら（2005））⑥ 技術導入自動車産業を含むいくつかの産業について、日米の技術（固有技術、マネジメント技術）の採用

企業の比較をして、オーナーシップ構造がノベーショ

品質管理技術の採用

ンに影響を与え、日米においてそれらの関係に相違⑦ 人材育成があることが報告もされている。（P.M.Lee（2005））

雇用システム（雇用形態、学歴、最低賃金）、雇用期

Prajogoらは、オーストラリアの企業に着目し、TQMの間、オペレーターの質、トレーニングシステム

採用において、TQM と技術・研究開発マネジメントの3.2. ヒアリング

統合が品質管理やイノベーションマネジメントに重要

バンコク市内、工業地帯の現地自動車部品企業7 社であることを指摘している。（Prajogo ら（2006））

実施時期 2006 年 12 月 19 日～29 日

タイの産業に関して、 Ｎａｇｓｗａｓｄｉらは、自動車産業

上記ヒアリング対象企業には、2006年4月に実施したなどの製造業の組織成長のパターンを分析し、その組アンケート結果により、優良企業として選定した 2 社を織成長への TQM の採用の影響について報告してい含む。

る（Ｎａｇｓｗａｓｄｉら（1999））。

ヒアリング項目

自動車部品企業については、Laosirihongthong らが、① 人材育成手法

タイの自動車産業において新製造技術（NMT）の導入② 技術導入手法にあたっては、その NMT の使用方法とシステム実践の③ 知的財産管理手法

ための知識を理解することが重要であることを明らかに

3.3. 数値項目の算出手法

している。

アンケート回答により得られたデータから次の値をそれぞれの式にしたがって算出した。回答は、範囲によ

3. 調査手法

り示されている数値があるためそれぞれ数値範囲の中3.1. アンケート調査

央値を規準として用いた。

タイの現地企業、日系外資企業286 社にアンケートを①売上高成長率送付し、44 社（現地企業 21 社、外資企業 23 社）から回

売上高成長率＝売上高中央値（2004 年度）／売上高

答を得られた。アンケートを送付した企業は、タイ自動

中央値（2003 年度）

車自動車部品企業組合（TAPMA）のリストから選定し②平均勤続定着率た。

平均勤続定着率＝平均勤続年数の中央値／設立時

送付時期

点からの経過年数

第 1 回 2006 年 4 月 10 日 100 社に発送、回答期限③オペレーター人数成長率

2006 年 4 月 30 日

人数成長率＝現在のオペレーター数／設立時のオ

第 2 回 2006 年 12 月 18 日追加の 100 社に発送、回ペレーター数

答期限 2007 年 1 月 9 日④採用技術ランク430

CAM、CAD 等の固有技術と、MRP、バーコードシス

現地企業と外資企業とで、売上高成長率、品質管理

テム等のマネジメント技術にわけてそれぞれの採用技

ランク、オペレーター人数成長率、平均勤続定着率の術数を計数した。その数値で示す。

t-検定を行った。結果は、表のとおりである。

⑤品質管理ランク
品質管理システムについて、「採用していない」をランク 1 とし、5S をランク 2、ISO９００１をランク 3、ISO14001、QC をランク 4、QS9000、TS16949 をランク 5、
TQM、TPS をランク 6 として評価した。

表1

現地企業と外資企業の技術項目比較

項目名

外資企業

現地企業

売上高成長率

1.52

2.34

＊

4. 調査結果

品質管理ランク

4.95

4.21

＊

4.1.アンケート回答企業の概要

オペレーター人 3.67

2.07

＊

生産品種別による分類

数成長率
平均勤続定着率
＊

0.29

0.32

P<0.05

オペレータ人数成長率、品質管理ランクでは、現地企業が外資企業より値が低く、売上高成長率では、現地企業の方が値が高かった。
4.3.Ｔier 別対比

Tier１企業（25 社）と、Tier2・Tier3 企業（18 社）を対比した。4.2.と同様に相関を求めたが、Tier2・Tier3 では、
平均勤続定着率と売上高成長率で、高い正の相関がみられた（相関係数 0.70）が、その他の項目では相関
Tieｒ別による分類が低かった。
不良率と品質管理ランクとの相関でも、相関係数は低かった。
Tier１企業と、Tier2・Tier3 企業とで、売上高成長率、品質管理ランク、オペレーター人数成長率、平均勤続定着率の t-検定を行った。結果は、表のとおりである。
表 2 Tier 別技術項目比較

項目名

Tier１

Tier2・Tier3

売上高成長率1.99

1.83

品質管理ランク

5.32

3.58

＊

オペレーター人 3.48

1.92

＊＊

4.2.現地企業と外資企業との対比

数成長率

アンケート結果から売上高成長率を算出し、品質管平均勤続定着率

理ランク、平均勤続定着率、採用マネジメント技術数、＊

P<0.05採用トレーニングコース数との相関を求めた。

0.27

0.35

＊＊

P<0.01

Tier1 企業は、Tier2・Tier3 企業と対比して、品質管理

外資企業 22 社、現地企業 21 社である。

ランクが高く、オペレーター人数成長率も高かった。

外資企業では、平均勤続定着率と売上高成長率で、4.4. 優良企業について

高い正の相関がみられた（相関係数 0.65）が、その他優良企業として選定した条件は次のとおりである。

の項目では相関が低かった。
431

社内不良率

3.0％未満されるが、今後より詳細な分析が必要である。

採用しているマネジメント技術数

2 以上

調査企業の中で、売上高成長率などにおいて高い採用している固有技術数

5 以上

品質管理ランク
平均勤続定着率＊

オペレーター人数成長段階

優良現地企業が 3 社あった。それらに対する今回のヒ5.0 以上アリングでは、人材養成のための手法がいくつか採用

0.2 以上されているものの、いずれも特にその個別企業に特徴

1 ステップ以上的であるといえるものではなかった。

人数成長段階は設立時点から現在までの人数拡大ステップである。
０ステップ＝人数が変わらない。１ステップ＝人数が 1 段階拡大。
これらの条件に当てはまる現地企業として、金属鍛錬分
２ステップ＝人数が２段階拡大。３ステップ＝人数が３段階拡大。

＊

売上高成長の要因としても、特に個別企業に特有のものは見いだせなかった。今後より詳細なヒアリン

野の 2 企業、プラスチック部品分野の 1 企業を選定した。

グ調査の分析を行って、その共通点を見いだすこと

4.3. 優良企業ヒアリングにより、他企業への提案に結びつく具体的特徴的な優良企業として選定した現地企業 3 社に対して、ヒア手法を導き出す必要がある。

リングを行った。

知的財産管理については、優良企業においてもそ

それぞれ企業において、売上高成長率が高い要素の重要視度、関心度は依然として低く、これらの企業として、新しい取引先を開発できたこと、経済情勢がよの知的財産管理を強化するためには、個々の企業

くなったこと、製品を納品する顧客企業の売上高成長についての手法にとどまらない、行政レベルでの対が高かったことなどの回答があった。

策が必要なものと考える。

不良率が低下した理由として、社内研修において
QC の研修コース数を増やしたこと、研修の時間数を

6. 参考文献

増加したこと、グループ分けによるコンペティションを[1] Laosirihongthong, T., Paul H. and Speece M.W., 2003.
Evaluation of new manufacturing technology
implementation: an empirical study in Thai automotive
industry.. Technovation, 23(4) 321-331.

行わせたことなどの回答があった。
4.4.知的財産管理

現地企業、外資企業、Tier１企業、Tier2・Tier3 企業い[2] Lee P, 2005. A Comparison of Ownership Structuresand Innovations of US and Japanese Firms, Managerial
and Decision Economics, 26(1), 39-50.

ずれにおいても、知的財産管理への関心度は低く、特許事務所との連携や、知的財産関連セミナーへの参加などの活動についても重要視していないことがわか[3] Nagswasdi, M. and O’Brien, C., 1999. Patterns oforganizational and technological development in theThai manufacturing industry, International Journal of
Production Economics, 60-61(1), 599-605.

った。
知的財産権利化のための出願についても商標が中心であり、知的財産管理への取り組みは弱いことがわ[4] Prajogo, D. I. and Soha, A. S., 2006. The Integration of
TQM and technology/R&D management indetermining quality and innovation performance,
Omega, 34(3) 296-312.

かった。
優良企業についても同様であった。
5. 考察[5] Waldeck, N. E. and Leffakis, Z. M., 2007. HR
perceptions and the provision of workforce training inan AMT environment: An empirical study, Omega 35(2) 161-172.

アンケート結果による外資企業と現地企業の対比、Tier 別企業の対比から、平均勤続定着率と売上高成長率の相関性が、外資企業、Tier2・Tier3 企業でみられ、これらの企業では、従業員の定着率を高めることが企業の成長に正の影響を与えている。
品質管理ランク、オペレーター人数成長率についてみると、外資企業は、現地企業と対比して高く、Tier1 企業は、Tier2･Tier3 企業と対比して高い。
品質管理ランクを高めることと、企業の成長の一要素であるオペレーター人数の増加との関連性が推測
432

特許発明からみた知識の新結合の研究—要素技術の組合せの斬新さの分析手法—
高橋徹，中川秀敏，佐伯とも子
東京工業大学大学院 イノベーションマネジメント研究科 イノベーション専攻
東京都品川区港区芝浦３－３－６キャンパスイノベーションセンター９階
takahashi.t.ar@m.titech.ac.jp
市場で顕著な成長をもたらす製品には，革新的な技術が採用されるケースが多く，技術を構成する要素技
術の組合せが斬新なほど革新性が高いと言われている。革新的な技術を適切に創造・保護・活用する知的財
産マネジメントを実現するためには，技術的思想である発明について技術を構成する要素技術の組合せの斬新さを把握することは重要である。
そこで技術の革新性の一要素である要素技術の組合せの斬新さについて，特許発明を用いた分析手法を立案し，その分析手法の検証を行った。検証には，近年の環境保全の意識の高まり，法規制の強化などによって産業が飛躍的に発展し普及した光触媒酸化チタン技術の出願特許を用いて，①技術の特許性，②新たな自然科学の発見による影響，③技術の進展に対する特許出願の動向の観点から行った。

1. 研究の背景
科学・技術によるイノベーションにおいて，革新的な技

知識の新結合に着目し，知識の新結合を技術の要素技

術はイノベーションの促進に重要な役割を果たす術の組合せの斬新さとして捉え，これを特許情報から分(Schumpeter(1942)[8]，Kutznet(1970)[6])。そのため，創造析する手法を提案したので，その結果を報告する。

そこで，革新的な技術の一要素として挙げられている

された革新的技術を知的財産権などで的確に保護し，こ的財産を創造する知的財産マネジメントを実現することは，

2. 技術の特許性技術を独占排他的な権利として特許を受けるためには，

企業な ど の 競争力の 強化に 繋が る だ け で な く

新規性，進歩性または非自明性などの特許要件を満たす(Teece(1997) [10])，産業全体の発展にも寄与し，イノベー必要がある(日本国特許法 49 条，米国特許法 101 条など)。

ション促進に好循環な効果が生じると期待できる。

つまり，技術を特許によって保護を受けるためには，技術れをライセンス供与などによって活用し，さらに新たな知しかし，革新的な技術は，これを用いた製品などが飛が創造された発明について，または特許としての保護を躍的に普及することによって初めて認知される。また，技求めるために出願または（米国では）発明された時点に術の革新性を特許など知的財産の面から議論している研おいて，過去に創造・出願された技術より新しく，さらに過究は少なく，技術が創造される時点で，革新性の有無を去の技術から容易に創造できないほど技術的な進歩があ

客観的に判断することは難しい。そのため，革新的技術ることが求められている。また，日本の運用では，「容易を適切に権利化して保護し，活用しているか不明である。

に創造できない」とは，技術を構成するために必要と認めSchumpeter は，「イノベーションには知識の新結合を伴る事項が技術の構成にある場合，技術における構成の困う」と述べ(Schumpeter (1934)[9])，さらに「新結合が非連続難性をいい，これを基準にして，進歩性を判断することが的にのみ現れることができ，また事実そのように現れると多いとされる(吉藤(2002)[14]，特許庁(2006))[12])。

きに限り，発展に特有な現象(経済における革新)が成立

そのため、技術を構成する要素技術の組合せが斬新なするのである。」と記述している(Schumpeter (1939)[7]) 。

ほど，新規性，進歩性などの特許要件を満足しやすくなり、

また，Henderson は，「イノベーションは，構成要素が新た特許登録を受けた技術は，拒絶査定に比べ，技術を構成な方法によって互いに組み合わされ再構成されることにする要素技術の知識が過去に事例が少ない斬新な結合

よって起こる」と述べている(Henderson(1990) [4])。これらを有しているものと考えられる。

先行研究より，技術による革新は，知識の新結合を伴い，

3. 新たな自然科学現象による影響
Flemingは，技術を構成する要素技術を結合させるため

さらに知識の新結合は，技術の構成要素の技術の組合せが斬新であることが重要と考えられる。

433

には科学的な原則・法則が必要であるとの仮説を立て，保護されている発明の技術について，知識の新結合を評技術を構成する要素技術と組合せられた要素技術の種価するための項目を抽出し，これを数値化する手法を提類が少ないほど，その特許発明において科学的な論文案する。

を引用し，技術内容の説明に活用する機会が多いことを(2) 提案した手法により算出された数値に基づいて，技検証している(Fleming（2004）[2])。これは，特許出願される術の特許性，新たに発見された自然科学現象の影響，産時点において，その特許出願に係る発明のる技術を構成業の発展に対する特許発明の出願動向との関連性をみする要素技術がその要素技術以外と組合せることが容易ることによって，本数値化手法を評価する。

ではない場合，要素技術間の繋がりである自然科学現象の原理・原則の理解が不足し，科学的論文を引用し，そ6. 仮説の技術を説明する必要があると述べている。この結果か

本提案手法により算出した数値が要素技術の組合せのら，技術を構成する要素技術間の結合は，自然科学現象

斬新さを的確に示している場合，この数値を用いることにの原理・原則によって成し遂げられると説明している。

より，下記の仮説が検証される。

そのため，新たな自然科学現象の原理・原則を利用し(1) 要素技術の組合せの斬新さが大きいほど，技術の特

た技術の特許発明は，その原理・原則の発見前に比べ，許登録率は高くなる。

当該技術分野において，技術を構成する要素技術間で(2) 新たな自然科学現象原理・原則が発見された後，要斬新な結合が発生する頻度が高くなると考えられる。

素技術の組合せの斬新な特許発明の出願が多い。
(3) 要素技術の斬新な組合せを有する技術の特許発明

4. プロダクト・プロセス技術の発現推移
Abernathy らによると，ある産業分野の製品に関するプは，プロダクトに対するプロセスに関する技術の特許出願
比率の推移は，技術の発展に伴って小さくなる。

ロダクト技術と生産に関するプロセス技術は，技術に関すを 問わ ず 共通し た 推移が 見ら れ る と 述べ て い る

7. 分析方法
特許発明の技術を構成する要素技術には，特許発明（Abernathy and Utterback(1978)[1]）。図 1 にこの発展パタの書誌的事項に付与されている IPC (Internationalーンを示す。これによると，産業の創成期にはプロダクト

Patent Classifcation：国際特許分類)を用いた。これは，イノベーションの発生率が高く，産業の発展が進むにつIPCが特許情報の審査・調査を効率的に行うために設けれて，プロダクトイノベーションの発生率が減少し，これにた国際的な統一技術分類で，IPC をある特定の技術分伴いプロセスイノベーションの発生率が増加し始める。

野の一分類として扱えると考えたためである。図 2 に特イノベーションへの貢献に期待される革新性が高い技

許発明を構成する技術の体系の概念図を示す。

術は，プロダクトまたはプロセスに分けて，Abernathy らの次に，要素技術の組合せの斬新さは，特定の特許発説の発展パターンで発生すると考えられる。また，これら

明Ａに付与されている各 IPC の相互の組み合わせ頻度の技術については，出願・登録される特許発明の中で革を求め，これを用いて算出する。組合せ頻度は，次のよ

新性が高い特許発明は同様の発展パターンに従って，うに算出する。まず，特許発明に付与されている複数の出願され，登録されるものと推察できる。

IPC i，j，k･･･の１つである i に着目し、対象となる特許

ｲﾉﾍﾞｰｼｮﾝの発生率

るイノベーションの発生パターンを観察すると，産業分野発明が出願される以前に出願された特許群について，

ﾌﾟﾛﾀﾞｸﾄｲﾉﾍﾞｰｼｮﾝ

その IPCi が付与されている特許出願の件数の中，IPCi

ﾌﾟﾛｾｽｲﾉﾍﾞｰｼｮﾝともう１つの IPC（j）の両方が付与されている特許出願件数の頻度Ｆi-j を以下の式から求める。

時間
産業の創成期 ⇒ ﾌﾟﾛﾀﾞｸﾄｲﾉﾍﾞｰｼｮﾝが多発
ﾄﾞﾐﾅﾝﾄﾃﾞｻﾞｲﾝの確率 ⇒ 生産の効率化 ⇒ ﾌﾟﾛｾｽｲﾉﾍﾞｰｼｮﾝが盛ん

IPC iに対する jとの組み合わせ頻度 Fi − j=

図 1 Abernathy and Utterback(1978)[1]の説

5. 研究の目的(1) 特許発明に関する情報に基づいて，その特許により特許出願以前の IPC iと jを含む特許出願件数
特許出願以前の IPCi を含む特許出願件数・・・(1)

上記式より，特許発明Ａに付与されている IPC の全組み合わせ数 N の組み合わせ頻度の平均 F の逆数を特許

434

9. 分析結果
(1) 技術の特許性

発明Ａにおける要素技術の組合せの斬新さの度合いとして表せる。本提案における特許発明の要素技術の組合せの斬新さの度合いを NCK 値(New Coupling of

図 3 より，特許査定を受けた出願特許の技術は，NCK

Knowledge)と表す。NCK 値は以下の式より算出する。

値が 10 から 20 の範囲でピークを有する分布を示した。

特許発明Aの要素技術の斬新さの度合い NCKA =しかし，拒絶査定を受けた出願特許は，NCK 値が０から

1
N=・・・(2)F ∑ Fi − j

10 の範囲が最も頻度が高かった。また，NCK 値が 2０以

i , j∈Ai≠ j

上の特許出願件数の頻度は，特許査定を受けた特許出

なお，優先権主張を伴う特許出願については，出願の願発明の技術が 45.6%に対して，拒絶査定を受けた特時期的基準を優先権主張の基礎となる出願の最先の出

許発明出願が 29.2%であった。拒絶査定を受けた特許願の日として分析を行った。

出願に比べて，特許査定の方が，平均値の対比では有意な結果が得られなかったものの，NCK 値の平均値，

特許発明中央値ともに高い傾向であった（表１）。
以上の結果から，特許発明の技術を構成する要素技
術の組合せの斬新さが大きいほど，技術の特許登録率は高くなることがわかった。
自然科学の原理

表1 登録査定および拒絶査定特許のNCK値の統計量

要素技術(IPC)

統計量
平均値
中央値 （メジアン）
標本数
t検定
p値
メジアン検定図2 特許発明を構成する技術の概念

8. 分析対象技術の選定
本研究を進めるにあたり，近年自然科学現象の原理・

登録査定
84.4
16.9
90
0.06
0.05

拒絶査定
17.3
12.6
80

50%
登録査定
拒絶査定

40%
特許発明件数頻度

原則の発見を伴った技術の産業分野を選定した。近年の環境保全の意識の向上，法規制の強化などで 1990 年以降産業が発展した光触媒酸化チタン技術に着目した。
光触媒酸化チタン技術に関する代表的な研究として，

30%

20%

10%

1972 年に Nature 誌に発表された本多・藤嶋効果が発見

100-

80-90

90-100

70-80

60-70

50-60

40-50

30-40

20-30

0-1０

10-20

0%

(Honda, K. and Fujishima, A. (1972)[5])されてから，研究NCK値

論文数は徐々に増え，1994 年に発見された光励起親水化現象(Hashimoto K, Fujishima A, et al.(1995)[3])を契機に

図 3 登録・拒絶査定の出願特許の NCK 値の分布
(2) 新たな自然科学現象の発見による影響

急激に増加した(特許庁(2004)[11]) 。

1994 年前および後に出願された光触媒酸化チタン技

また、国内の市場規模は，1994年の光触媒製品の上市術の特許発明，東陶㈱が所有する光励起親水化現象を以降着実に増加し，2002 年に約300 億円の市場を形成し利用した技術の特許発明の抽出を行い，特許発明のた(特許庁(2004)[11]，㈱シーエムシー出版(2002) [13])。

NCK 値の比較検討を行った。結果次の通りである。

なお，光触媒酸化チタン技術に関連する産業の発展に

図４より，1993 年以前に出願された光触媒酸化チタン

伴い、戦略的に特許による保護、活用を図り、東陶㈱では技術に関する特許発明の NCK 値の特許発明件数の頻ライセンス提供を積極的に行っており(渡辺(2003)[1５]）、度分布は，主に 0 から 50 の範囲の単一の分布を示す。

光触媒酸化チタン技術は適切に特許出願されているもの

それに対して，1994 年以降に出願された特許発明のと考えられる。

NCK 値は，0 から 50 と 40 から 80 の範囲に二つの分布

そこで，光触媒酸化チタン技術は，本仮説を検証する上を有している。また，NCK 値が 50 以上の頻度は，1994

で適した技術分野であると考え，本技術に関連する出願

年以降に出願された光触媒酸化チタン技術全般の特許

特許発明を用いて分析することとした。

発明が 17.8%に対して，光励起親水化現象を利用した技
術が 43.8%であった。NCK 値の中央値は，1993 年以前

435

に出願した光触媒酸化チタン技術の特許発明が 11.1，の比率が高くなる傾向であった。一方，プロセス技術に1994 年以降に出願した特許発明が約16.9，光励起親水関する特許発明は，中央値以上の NCK 値の特許発明

化現象に関する技術の特許発明が 39.5 となり，光励起の比率が 1997 年付近から増える傾向を示した。

親水化現象の発見以降の方が NCK 値の中央値が高い

よって，要素技術の斬新な組合せを有する技術の特ことがわかった（表 2）。新たな自然科学現象である光励

許発明について，プロダクトに対するプロセスに関する

起親水化現象を明らかに利用した技術の方は，光励起技術の特許出願比率の推移は，技術の発展に伴って小親水化現象の発見前，つまり 1993 年以前に出願された

さくなることがわかった。

技術の特許発明との間で差異を示すことができた。

れた後に出願された特許発明の NCK 値が高いという結果を得ることができた。
表 2 1994 年前および後に出願された特許発明、東陶㈱が所有する光励起親水化現象に関する特許発明の NCK 値
の統計量
統計量

1985-1993年
出願特許発明1994-2000年
出願特許発明

光励起親水化技術
の特許発明

平均値

19.5

84.4

44.4

中央値 （メジアン）

11.1

16.9

39.5

標本数

33

90

16

1994-2000年
出願特許発明
光励起親水化技術の特許発明
1994-2000年
出願特許発明
光励起親水化技術の特許発明

p値
メジアン検定

40%
20%

0.083
0.050

0.294

0.022
0.003

0.103

1985年-1993年特許出願
1994年-2000年特許出願
光励起親水化現象関連技術特許発明

30%

20%

100%

80%

60%

40%

20%

2002

2001

2000

1999

1998

1997

1996

1995

1994

1993

1992

1991

1990

1989

1988

1985

1987

0%

10%

1986

特許発明件数頻度

60%

出願年(1)プロダクト

50%

40%

80%

0%

NCK値中央値以上の特許発明出願件数の比率

t検定

100%

1985
1986
1987
1988
1989
1990
1991
1992
1993
1994
1995
1996
1997
1998
1999
2000
2001
2002

術分野では，新たな自然科学現象原理・原則が発見さ

NCK値中央値以上の特許発明出願件数の比率

よって，新たな自然科学現象原理・原則を活用する技

出願年(2)プロセス

100-

80-90

90-100

70-80

60-70

50-60

40-50

30-40

20-30

0-10

10-20

0%

NCK値

図５ プロダクトおよびプロセス技術に対する NCK 値の中央値以上の特許発明の出願件数比率の推移

図４ 光励起親水化現象発見年(1994 年)前後および
光励起親水化現象を用いた技術の特許発明の NCK
値の分布

図５より，1993 年以前は NCK 値の中央値以上の特許

10. 結論以上より，技術の特許性，新たな自然科学現象の発現，

発明はほとんど出願されておらず，1993年以降NCK値

産業の進展に対する特許出願の推移の傾向の三つ観点

が中央値以上の特許発明が出願された。また，1993 年

から，仮説を検証することができ，本提案手法による NCKに出願された NCK 値が中央値以上の特許発明のうち

値は特許発明の要素技術の組合せの斬新さを表してい

プロダクト技術の特許発明出願件数の比率はほぼ 8 割ると考える。

(3) 産業の進展に対する特許出願の推移・動向

であり，1994 年から 1996 年までは中央値以上の特許発明の全てがプロダクト技術に関する特許発明であった。
その後，プロダクト技術の比率が低くなり，プロセス技術

436

参考文献
[1]

Abernathy, J. and Utterback, M.”Patterns of Industrial
Innovation”, Technology Review, June/July,
pp.40-pp.56, 1978.

[2]

Fleming, L. and Sorenson, O.“Science as a map intechnological search” Strategic Management Journal,
25, p.p909-928, 2004.

[3]

Hashimoto K, Fujishima A, et al. “Light-Induced
Amphiphilic Surfaces” Nature, 388, pp.431-432, 1997.

[4]

Henderson, R. M. and Clark, K. B”Architectural
Innovation”, Administrative, Science Quartery, 35,
New York, pp.9-30, 1990.

[5]

Honda, K. and Fujishima, A.” Electrochemical
photolysis of water at a semiconductor electrode”
Nature, 238, p.p37-38, 1972.

[6]

Kuznets, T.”Secular Movements in Production andPrice” Houghton Miflin, Boston. 1970.

[7]

Schumpeter, J, A. “Business Cycles.” McGraw-Hill
Book Company,Inc., New York, 1939.

[8]

Schumpeter. J. A.”Capitalism, Socialism
Democracy” Harper & Row, NewYork, 1942.

[9]

Schumpeter, J, A.” The Theory of Economic
Development: An Inquiry into Profits, Capital, Credit,
Interest, and Business Cycle” Cambridge: Harvard
University Press. 1934.

and[10] Teece, D. J., Pisano, G. and Shuen,A.”Dynamic
Capabilities and Strategic Management”Strategic
Management Journal,Vol.18:7,NewYork, pp.509-533,
1997.
[11] 特許庁「特許出願技術動向調査報告書－光触媒－」，2004.3.
[12] 特許庁 「特許・実用新案審査基準 2007.3.23」,
2007.
[13] ㈱シーエムシー出版「光触媒応用製品の市場実態と展望 」，東京，2002.2.
[14] 吉藤幸朔 「特許法概説(第 13 版)」，有斐閣，2002.7.
[15] 渡辺俊也 「理工系のための特許・技術移転入門」
岩波書店，東京，2003.1.

437

On the Development of the High Pressure Steam Engine in
the 19th Century
KOBAYASHI MANABU
kobayashi.m.ac@m.titech.ac.jp
1, Introduction
cylindrical boilers were superior to thermal efficiency ofThis paper studies the development of the steam engine
low pressure steam engine combined with box boilers.
in the 19th century, especially focusing on the
Box Boiler
Cylindrical Boiler
connection of “means of labor” with the steam engine
the quantity of water evaporated
the quantity of water evaporated
and the theories of steam and heat.
per pound of coal=8.7lbs．Boiler
per pound of coal= 8.1lbs． Boiler
Studies of the steam engine often presuppose that
efficiency=60％
efficiency=56％
there was a linear development from low pressure system
High pressure steam
Low pressure steam
to high pressure system. But this assumption is simplistic,
as the story was more complicated. I argue that
EngineBox Boiler
Engine Cylindrical
Screw
Screw
relationship between means of labor and form of power,
Coal consumption3.0lbs/(IHP.h)
Coal consumption2.5lbs/(IHP.h)knowledge of steam and heat engineers used, andThermal efficiency: Low
Thermal efficiency: highstrength of boilers.
2, A Comparative Analysis of Steam Engines with
5, Some technological problems of the development ofrespect to their workings
the high-pressure stationary steam engine
In terms of work they perform, there are four typesof steam engines: pumping engines, rotative engines formills, locomotive engines, and marine engines. The firsthigh pressure steam engine was a pumping engine. The
marine engine which used high pressure steam emergedin the 1860’s.
3, From the theory of water wheel to the theory of thesteam engine
The theory of the steam engine in the early 19th
century was based on the caloric theory and influenced
by analogy of hydraulic engine. This theory could
explain the usefulness of the high pressure steam engine.
But caloric theory had a limit. British engineers also
adopted what was known as “Watt law.” Even thisFig 2. Trevithick’s Boilers: Left one was made of castsophisticated caloric theory could no longer explain theiron without any joints. Right one was made of wrought
efficiency of the high pressure steam engine.
iron. This was consisted of some plates with many rivets.

Fig 1. Watt’s laws: a given weight of steam always
contains the same amount of heat whatever pressure it iscreated.
4, Marine compound engine and applied
thermodynamics
Saturated steam expanded adiabatically in thecylinder cannot keep saturated, it is condensed into water.
It became the most important problem for thedevelopment of the high pressure steam engine. Scottish
engineers John Elder and William John Macquorn
Rankine solved this problem by applying the first low ofthermodynamics.
They applied thermodynamics to the steam engine
and recognized that the high pressure steam engine
improved thermal efficiency. The shape of high pressure
steam boilers was the most crucial. A change in shape,for instance from box to cylindrical made great
difference in boilers’ resistance to pressure. Thermal
efficiency of high pressure steam engines combined with

Bessemer steel process was invented in 1856 andthis process could make stronger and larger steel plates
than paddle plates. So I re-evaluate an important
Bessemer steel process.
6, Some technological problems of the development of
the high pressure marine steam engine
With the knowledge of thermodynamics,
ship-owners effected the development of the highpressure steam engine such innovations as water tube
boilers and triple expansion engines. However, it is too
difficult to make steel tubes for marine water tube boiler
at that time. So steel cylindrical boiler became popular
type in the end of 19th century. Economical constraints offuel strongly worked and decided a form of the marine
steam engine.
7, Conclusion
Finally, the development of high pressure steam
engine in the 19th century was depended on theconnection of “means of labor” with the steam engine.
A close relationship between demand for “power” and“efficiency” had a huge impact on the development of
the high pressure steam engine.
438

小林

学は次の 4 レポートを SIMOT Pre-Doctoral Interim Report のために提出した．

1, 小林

学「19 世紀初期における各用途に起因する蒸気機関の発展の相違について」SIMOT Pre-Doctoral Interim Report, The Science of Institutional Management of Technology
Research Center: SIMOT REC, Tokyo Institute of Technology, Vol3. No.1 (Spring), 2007,(April 23, 2007): 57-60.
2, 小林

学「ベルヌーイの定理から蒸気機関の理論へ」 SIMOT Pre-Doctoral Interim

Report, The Science of Institutional Management of Technology Research Center: SIMOT REC,Tokyo Institute of Technology, Vol.2 No.2.(Fall),2006, (October 20, 2006): 5-13.
3, 小林

学「19 世紀イギリスにおける技術者への熱力学の普及について」 SIMOT

Pre-Doctoral Interim Report, The Science of Institutional Management of Technology ResearchCenter: SIMOT REC, Tokyo Institute of Technology, Vol.2 No.1 (Spring, 2006): 1-4.
4, 小林

学「ボイラへの鋼の使用による蒸気圧力向上について」 SIMOT Per-Doctoral

Interim Report, The Science of Institutional Management of Technology Research Center:
SIMOT REC, Tokyo Institute of Technology, Vol.1 (Fall, 2005): 19-22.
うち，1，2，4 のレポートの内容は，大幅に改稿した上で学術雑誌への投稿を準備しているので，SIMOT 最終報告書での公表は控えさせていただいた．
3 のレポートは，
小林

学「19 世紀舶用ボイラ発達過程―ボイラ史の研究方法によせて―」『科学史研究』

第 44 巻

No.236(2005 年)，191-202 頁．

で発表したものを大幅に改稿したものである．SIMOT 最終報告書では，
3, 小林

学「19 世紀イギリスにおける技術者への熱力学の普及について」 SIMOT

Pre-Doctoral Interim Report, The Science of Institutional Management of Technology ResearchCenter: SIMOT REC, Tokyo Institute of Technology, Vol.2 No.1 (Spring, 2006): 1-4.
のみを掲載することとした．
東京工業大学 21 世紀 COE 研究員

439

小林

学

19 世紀イギリスにおける技術者への熱力学の普及について
小林 学*
On the Popularization of Thermodynamics among British Engineers in the 19th Century.
*

Manabu KOBAYASHI*
Department of Industrial Engineering and Management, Tokyo Institute of Technology
manabu@me.titech.ac.jp

The author discusses how thermodynamics became popular among British engineers in the
19th century. The heartland of shipbuilding in Britain moved from London to Glasgow in the
mid-19th century. Besides the University of Glasgow become an academic center for the study ofthermodynamics. In Glasgow, the shipbuilding industry and academic scholars formed a close
relationship. This relationship illustrates how technology co-evolves with science.
In conclusion, a technical problem stimulated the development of a scientific theory, but it was
not opposite. The co-evolution between technology and science involves also institutional settings,
such as geographical, social and economic conditions.
1. 熱力学の通史と問題点，および研究目的
本報告は，科学と技術の共進化の過程の一例
として，イギリスにおける熱力学の蒸気機関への応用を取り上げ，この共進化のメカニズムを明らかにすることで，SIMOTへ示唆を与えることを目的とする．
熱力学と蒸気機関との関係は，科学と技術の関係としては，非常に典型的事例であり，また史上初の熱機関である蒸気機関の熱効率改善の試みを歴史的に解明することは，現代のエネル
ギ問題を新技術の採用によって解決しようとする場合にも，有用な示唆を与えると思われる．
まず科学史，もしくは物理学史における熱力
学成立の記述を簡単に見ておきたい．そして
その問題点を指摘する．熱現象を学問的に扱う試みは，ブラック(Joseph Black, 1728-1799)が熱量保存の原理を前提として熱容量や潜熱の概念を提唱したときに始まる．熱量保存則の前提は，熱は物質的実体であるとするものであった．ラボアジェ(Antoine-Laurent Lavoisier,1743-94)は，元素の一つとして熱物質を導入し，これを熱素(calorique)と名付け，熱素説を確立した．蒸気機関に関連した最も画期的な前進は 1824 年 サ デ ィ ・ カ ル ノ ー (Nicolas Léonard
Sadi Carnot, 1796-1832)によってなされる．カ
ルノーも熱素説を採用し，熱機関を水車とのアナロジーによって考察した．そしてカルノーの定理を発見した．
一方，熱素説を否定し，熱力学第1法則の基礎を 作 っ た の が ジ ュ ー ル (James Prescott Joule,
1818-89)である．彼は1847年英国科学振興協会
で熱の仕事当量について発表し，その発表を聞いたウィリアム・トムソン(William Thomson,
1824-1907. 後 の ケ ル ビ ン 卿 ,Baron Kelvin ofLargs)がその重要性を認めたのであった．
熱力学第2法則は，前述のカルノーの仕事の中にすでに含まれており，また1834年にクラペイ
ロン(Benoît Paul Émile Clapeyron, 1799-1864)はカルノー理論に数学的表現を与えたはしが，トムソンがその重要性を指摘するまでは，一般には認識されなかった．しかしトムソンは，
カルノーとともにジュールも高く評価してい440たので，この両者の統合にかなりの困難を感じた．すなわちジュールが，熱が発生するとき力学的仕事が消費される，と主張するとき，
これが熱素の保存を前提としたカルノーの定理と矛盾することは誰の目にも明らかであった か ら で あ る ． こ こ で 1850 年 ク ラ ウ ジ ウ ス(Rudolf Julius Emmanuel Clausius, 1822-88)が，トムソンの困難を軽々と乗り越えた．すなわ
ち熱量保存則を捨てれば，カルノーの定理は，
熱力学第1法則に矛盾するものではないとして，
熱力学第2法則を定式化することに成功するので あ る ． ラ ン キ ン (William John Macquorn
Rankine, 1820-72)もクラウジウスとは独立に，
熱力学第2法則を定式化した1．
以上が熱力学成立に関する定説である．筆者がここでランフォード伯，クレマン，ドゾル
ム，マイヤー，ヘルムホルツなど熱力学成立に関与した多くの科学者について述べていな
いのは，本報告で特に関係している事実だけを取り上げたからであって，決して無視しているわけではないということを断っておく．
このような科学内部の因果関係の記述する学
説史・内部史においては，蒸気機関のような科学外部の問題は取り扱われていない．蒸気機関が熱力学の発達に影響を与えたという主張は度々されてはきたが，これについて積極的に述べた研究は，カードウェルの労作 2 以外にはほとんど見あたらない．しかしこのカードウェルでさえ，19世紀の英国の主要な技術
者の熱の理解についてはあまり検討していないのである．さらに熱力学がどのように技術者に普及していったかについては，カードウ
ェル，ヒルズ 3 以外には研究されていないように思われる．また企業が熱力学に基づいた蒸気機関を採用した経緯については，これまでの科学史研究では着目されてこなかった．
また熱力学の発達に蒸気機関が関係していたとすれば，蒸気機関の作業流体である水蒸気の性質についての研究が重要であったはずだと容易に推定できる．しかし，これまでの熱力
学史において，水蒸気の問題はほとんど顧みられてこなかった．特にクラウジウスは理想

気体を中心に理論を展開したとされている 4．
ただこの点については，高山，道家が，クラウジウスの1850年論文の意義を水蒸気の問題を中心とする視点から捉え直そうとしている5．
ただ高山は，熱力学が蒸気機関の理論と深く結びついていたと指摘してはいるが，基本的には学説史に限定した議論であり，蒸気機関の問題を具体的には述べてない．
また山本は，高山・道家の論文を受けて，これを「注目すべき見解」と評した．さらに山本
は，1830～40年代蒸気機関における膨張作動
原理の実用化により飽和蒸気の断熱膨張の問
題が，当時現実的な問題になっていたことを指摘するとともに，飽和蒸気の断熱変化の問
題が，熱素説と熱力学で正反対の結果になることを正しく指摘している 6 ．しかし，山本も，当時の技術者が蒸気機関の問題をどのように理解・解決したかまでは述べていない．
以上のような先行研究およびその問題点から，筆者は次のような目標を立てた．第一に19世
紀中葉のイギリスの技術者の水蒸気と熱に対する理解の検討．第二に熱力学の成立が，イギリスの技術者・企業に普及した過程について．この二点を明らかにすることで，蒸気機関と熱力学の共進化の過程と，その共進化を可能にした条件について明らかにしたい．

圧蒸気は必然的により大きな出力を生み出すという有力な意見がある．これは，しかしながら，間違いである．なぜなら，もし蒸気の密度が上がるとすれば，蒸気圧の増加に比例してその蒸気の体積は減っていく．よって出力は同じままとなる12．」
蒸気は理想気体ではないので，フィールドが言うようなボイルの法則に厳密には従わない．
近似的にボイルの法則が成り立つとしても，蒸気が機関を通して行う仕事が，高圧蒸気と低圧蒸気とで同じになるのかは簡単には分からないはずである．このフィールドの発言は，熱素説とワットの法則を考えれば説明できる．
すなわち単位重量あたりの蒸気に含まれる「全熱量」は一定（ワットの法則）であるとすれば，蒸気の重量が同じである限り，どんな圧力であってもその中に含まれる熱素の量は一定であろう．蒸気の弾性力が熱素の大小による（熱素説）のであれば，蒸気の重量が同じである限り圧力の大小によって蒸気の弾性力は変わらないという結果が導かれる．
以上の記述から，当時，舶用機関の技術者の間で高圧蒸気の利点は必ずしも明らかではなかったことが分かる．熱素説やワットの法則を使っている限り，高圧蒸気機関の高効率を説明することは不可能なのである．一方同年6月6日，ジュールは王立協会に論文「熱の仕事当
2. 当時の船舶技術者の熱に対する考え方―
量について 13 」を提出し，その中で水1ポンド
熱素説とワットの法則(真空中の重量でかつ華氏55度から60度の温度
19世紀，舶用機関では高圧蒸気の使用が遅れ範囲にある)を華氏1度上昇させるのに必要な熱た．理由は，熱素説とワットの法則を船舶技
量を，772ポンドの物体を1フィートの高さに術者が信じていたからである．熱素説による上げるときになされる仕事と同等であるとし，と，高圧蒸気が大きな弾性力を持っているの
熱力学第1法則を定量的にも確立したのである．
は，それだけ多くの熱素を含んでいるからで
7
しかし技術者は，ジュールの仕事に直接的にあった ．ワットの法則とは，飽和蒸気は蒸発
は何の影響も受けなかったと思われる．熱のする圧力によらず同じ重さについて同量の熱
8
理論は19世紀初頭蒸気機関によって強烈に刺素を含んでいる とするものである．例えば，
激されたが，ここにきて熱の理論は，実際の蒸気の温度と圧力が増すと潜熱は減少する．
ワット(James Watt, 1736-1819)はこの事実から， 蒸気機関を追い越したのであった．
3. 蒸気機関改良の具体的問題
水は圧力が低ければ低温でも沸騰するが，そ3.1. イギリスにおける新しい技術革新の土台の分潜熱が増加するので，燃料の節約にはな
フランスでは，石炭価格が比較的高かったた
らないことを見いだした．さらにワットは顕め，蒸気機関の効率の問題は，イギリスより熱の増加と潜熱の減少が完全に埋め合わされ関心があった．大陸封鎖終了後，英国からウることで，蒸気の全熱量(total heat) が常に一定
ルフの2段膨張機関（英国ではその後使われなになるのでは9，と考えたのであった．
当時の技術者の熱や蒸気に関する見解が分かくなったのだが）が輸入され普及した理由や，る資料がある．1849年6月19日シーワード(John
カルノーに代表される熱の理論的研究がフラSeaward, 1786-1858)が英国土木技術者協会(Theンスでなされた理由は，フランスでの高い燃Institution of Civil Engineers)で発表した際の会料費にあったことはほぼ間違いがない．後者
議録10である．英国海軍本部はいくつかの会社に関しては，エコール・ポリテクニークのよに高圧蒸気の使用および膨張作動原理についうな工学の高等教育機関が設置されたこともて質問をしており，報告の内容は彼の回答で大きい．カルノーもエコール・ポリテクニーある．その概要は当時艦艇の蒸気圧は約クの卒業生であった．フランスでは，技術革
8psi(0.56 kgf / cm 2 )11 であり，出力，重量とス
新を生み出す要因として地域的特性による需
ペ ー ス の 経 済 性 は 10 ～ 12psi(0.70 ～ 0.84
要と高等教育機関があった．足りないのは実
kgf / cm 2 )を使う事でわずかに増えるので，10際に技術革新を遂行する技術力を持った産業～12psiでの使用を勧告するものであった．
だけであった．
この発表の議論で，Maudslay, Sons and Field社
一方，イギリスでは良質な石炭が大量に産出の共同経営者であったフィールド(Joshua Field,
したため，熱効率の問題はコーンウォールの1787-1863)は次のような発言をしている．「高ような金属鉱山地帯を除いて，あまり問題と441

圧でなくても燃料消費量が減少した理由は，力のバランスをとるように複数のピストンで軸を駆動することで軸受の摩擦を減らしたからであった25．
以上のことから，エルダーは舶用2段膨張機関の導入当初は，熱力学を理解していなかったと考えられる．
3.3. 初期復水の解決―熱力学第1法則の理解
一方，ワットが考案した膨張作動原理は当時
すでに実用化されており，断熱膨張過程での飽和蒸気の振る舞いは極めて現実的な問題になってきていた．この問題は，熱力学と熱素説で正反対の結果を生んだのである26．
飽和蒸気の持つ熱量が蒸発する温度によらず常に一定だとするワットの法則は，飽和蒸気の断熱膨張の際にも「膨張の潜熱」という概念の導入によって拡大されて適用されるようになった．すなわち，飽和蒸気が断熱膨張する
時，蒸気温度(顕熱)は低下するが，「膨張の潜熱」はその減少分だけ増加する．よって，飽和蒸気が断熱変化する時，常に飽和状態を保つ27という結果が導かれる．
しかし実際に高圧の飽和蒸気を断熱膨張させると，その一部は復水してしまう．これを初期復水と称するが，ワットの法則からはこの原因を説明できない．当時，この原因はボイラからの蒸気の中に水滴が混入しているためだとされていた28．
この水は，シリンダが復水器に接続したときに低温で沸騰し，ピストンにバックプレッシ
ャーを与えるなどして，動力を浪費する原因になる．これを防ぐ方法の一つとして蒸気ジャケット(steam jacket)がある．これはワットが考案・使用したもので，気筒の周りを二重にし，この中に高温の蒸気を入れることで，シリンダを保温するものである．しかし舶用機関
において蒸気ジャケットは，誤った熱素説による推論によって不要とされたのである．このことは19世紀中頃の多くの技術者が正しいとしたことであった29．
この蒸気ジャケットを舶用機関で導入したのがエルダーであった．エルダーはシリンダ内の水が熱の損失になることと，そしてその復水の原因が，蒸気がその膨張過程で仕事をしたために起こる熱の消費にあることをはっきりと認識していた30．そこで彼は，蒸気がその膨張過程で失った分の熱を加えるために，蒸気ジャケットを使用したのである．
熱力学第1法則は，熱が仕事に転換しうることを明らかにした．飽和蒸気の断熱膨張問題の解
決こそ熱力学第1法則が，当時の工学分野にもたらした最大の恩恵だと考えられる．
またエルダーに初期復水の原因を理解させたのは，ランキンだと筆者は推定している．
1850年ランキンは飽和蒸気の比熱が負であること（飽和蒸気が断熱膨張する際に消滅する熱は温度降下によって放出される熱より大きいこと）を指摘し31，断熱膨張する飽和蒸気の復水を証明している．ランキンがエルダーにこならなかった．イギリスでの技術者教育は基
本的には徒弟制度によってなされていた．教
養主義的教育を中心にしたケンブリッジ大学
やオックスフォード大学は何の工学研究も生み出し得なかった14．したがってイギリスの技術において，実地と理論は完全に切り離されていたと言って良い．19世紀イギリスは世界一の工業生産能力を持っていた．海軍力も世界一であった．そしてこれらは，特に海軍において保守主義を生んだ．例えば，1845年の英国海軍保有艦船は，帆走軍艦276隻，一方蒸気軍
艦は37隻で，うちスクリュー艦は1隻のみであった15．イギリスの海上覇権は，トラファルガ
ー海戦以前に確立された帆走軍艦によって築き上げられたもので，それが少しも揺らいでいないのだから，それを交換しないのは正当な判断であった16．イギリス国内には技術革新のための土壌は，あまり無かった．
イギリスにおける新しい市場は，国内ではなく遠い海上に見いだされた．1850年代，英国における貿易の範囲は，大西洋から石炭補給が困難な南米太平洋岸へと拡大していき，大西洋航路よりも燃料の効率が重要視されるようになったのである．また船体材料の木材から鉄材への移行に伴い，造船業の中心は，ロンドンから鉄材の供給地に近いグラスゴーに移っていた17．またグラスゴー大学は，ブラック，ワットらが活躍した熱学の先進地であったし，さらに1846年トムソンがグラスゴー大
学の自然哲学の教授に就任し18，1855年にはランキンもグラスゴー大学の工学と機械学の教授に就任する19など，熱学における一大拠点を形成した．こうしてイギリスではスコットランド・グラスゴーに，市場と産業と工学の高等教育機関を見いだしたのである．
3.2. 舶用2段膨張機関の導入
このような状況の中，舶用機関の効率を改善する最初の成功した試みが，スコットランドの技術者，エルダー(John Elder, 1824-1869)とランドルフ(Charles Randolph, 1809-1878)によってな さ れ た ． 1854 年 彼 ら は ， ブ ラ ン ド ン 号(Brandon)に2段膨張機関に搭載した．燃料消費量は従来の最低が4～4.5 lbs /( IHP ⋅ h) 20 であった の に 対 し ， ブ ラ ン ド ン 号 は 3.25
lbs /( IHP ⋅ h) 21であった．
最初に2段膨張機関を採用した蒸気船会社は，
1856 年 太 平 洋 蒸 気 船 会 社 (Pacific SteamNavigation Company)で，インカ号(Inca)とヴァ
ルパライソ号(Valparaiso)にエルダー・ランド
ルフ社によって製造された2段膨張機関が搭載さ れ た ． ヴ ァ ル パ ラ イ ソ 号 の 蒸 気 圧 は 26psi(1.8 kgf / cm 2 )，燃料消費量は3.08 lbs /( IHP ⋅ h)であった 22 ．次に2段膨張機関を採用した会社
は，1859年ペニンスラー・オリエンタル蒸気船会社(Peninsular and Oriental Steam Navigation
Company)で，蒸気圧力は26psi 23 であった．このころ商船では20psi程度の蒸気圧を使うようになってきていた 24 ので，26psiは2段膨張機関としてはさほど高いとは言えないだろう．高442

れを教えたとする直接的証拠を筆者は見つけることができなかったが，早世したエルダーに対しランキンが丁寧な回想録32を出版し，その中でエルダーがシリンダ内復水の原因を学んでいたことが述べられているので，エルダ
ーとランキンが学問的に緊密な関係にあったと考えて間違いないだろう33．
エルダーによる蒸気ジャケット採用時期だが，1854年ブランドン号には蒸気ジャケットが無かった．1856年インカ号とヴェルパライソ号には，シリンダ頂部と底部に蒸気シリンダが採用された．1858年アドミラル号 (Admiral)とカラオ号(Callao)にはシリンダを完全に覆う蒸気ジャケットが採用された34．したがってエル
ダーは遅くとも1858年には熱力学第1法則を認識していたと言える．
4. 結論
以上の歴史的事実の検討から，次のことが言える．すなわち，熱力学は蒸気機関の問題に刺激されて発達したが，逆の関係は直接的には成り立たず，熱力学が成立したからといって自動的に蒸気機関の技術革新を生み出すわけではないということである．科学的成果を技術に応用するためには，産業の立地・大学など
地理的社会的制度的経済的条件としてのinstitutionが必要なのである．また同時に次のことも言える．すなわち技術とは社会的な存在
であり，様々な社会的現象と関連を持っているので，意図的に技術革新を産みだそうとする場
合には，単に技術的科学的発明だけではなく，適切な地理的社会的制度的経済的条件も準備しなければならない，ということである．
References[1] 以上のような熱力学成立に関する通史については，広重徹『物理学史Ⅰ』培風館，昭和 43 年やカードウェル(金子務監訳)『蒸気機関からエントロピーへ』，平凡社，1989
年や山本義隆『熱学思想の史的展開』現代数学社，1987 年などを参照されたい．
[2] カードウェル(金子監訳)『前掲書』．
[3] D.S.L. Cardwell, Richard L. Hills,“Thermodynamics and Practical Engineering in
the Nineteenth Century,” History of Technology,
1, (1976): 1-20.
[4] 広重徹『物理学史Ⅰ』，213 頁．
[5] 高山進，道家達将「Clausius の熱力学形成過程における水蒸気論の位置付け」『東京工業大学人文論叢』2(1976): 51-67.
[6] 山本『熱学思想の史的展開』，395-400 頁．
[7] ヒルズは，ファーレーやアルバンの著作を取り上げて当時の熱に関する理解と熱素説
について説明している．Richard Hills, Powerfrom Steam: A history of the Stationary steam
engine (Cambridge University Press, 1989),
162-165.
[8] サジ・カルノー(広重徹訳と解説)『熱機関の研究』みすず書房，1973 年，67 頁．
[9] カードウェル(金子監訳)『前掲書』，75 頁．
443[10] John Seaward, “On the Employment of HighPressure Steam, working expansively, in
Marine Engines,” Minutes of Proceedings
Institution of Civil Engineers, (1849): 305. 以
後同雑誌を M.P.I.C.E.と略す．
[11] 本論記載の圧力はすべてゲージ圧力である．
[12] Seaward, “ibid,” M.P.I.C.E., (1849): 308.
[13] James Prescott Joule, “On the MechanicalEquivalent of Heat,” PhilosophicalTransactions (1850): 61-82.
[14] 三好信浩『明治のエンジニア教育』中公新書，1983 年，10 頁．
[15] 杉浦昭典『蒸気船の世紀』NTT 出版，1999
年，266 頁．
[16] W・マクニール(高橋均訳)『戦争の世界史』
刀水書房,2002 年,305-309 頁．
[17] L.T.C.ロルト(高島平吾訳)『ヴィクトリアン
エンジニアリング』鹿島出版会，1988 年，
99-100 頁．
[18] 山本『熱学思想の史的展開』354 頁．
[19] “Rankine, William John Macquorn”,
Dictionary of Scientific Biography, 11(1975):
291-295.
[20] 以後「石炭消費量」と言う場合，「1 馬力・
1 時間あたりの石炭消費量」とする．
[21] William John Macquorn Rankine, A Memoir ofJohn Elder, Engineer and Shipbuilder(Edinburgh, 1871), 37-38.
[22] Report of Research in Science, “Second Reportof the Committee on Steam-ship Performance,”
Report of the 30th meeting of the British
Association for the Advancement of Science,30(1861): 199. Supplementary Appendix.
[23] E.C.Smith, A Short History of Naval andMarine Engineering (Cambridge: Babcock andWilcox, LTD., 1937), 180.
[24] “ibid,” the British Association for the
Advancement of Science, 30(1861): Appendix
No. I, Table 1.
[25] Rankine, A Memoir of John Elder, 28-30.
[26] 山本『熱学思想の史的展開』，396-400 頁．
[27] R. Clausius, translated by W.A. Browne, The
Mechanical Theory of Heat (London:
Macmillan, 1879), 193.
[28] Rankine, A Memoir of John Elder, (1871), 21.
[29] Rankine, A Memoir of John Elder, (1871), 21.
[30] Rankine, A Memoir of John Elder, (1871), 28.
[31] “Rankine”, Dictionary of Scientific Biography,
11(1975): 291-295.
[32] Rankine, A Memoir of John Elder[33] カードウェル，ヒルズも，エルダーの熱力学の知識はランキンから得たにちがいないとしている．Cardwell, Hills, “ibid,” History ofTechnology, 1 (1976): 11.
[34] Rankine, A Memoir of John Elder, (1871)37-38.

第二次大戦後の米合衆国における軍事研究開発体制の再編成の歴史的研究
栗原岳史 (KURIHARA Takeshi)

東京工業大学 社会理工学研究科 経営工学専攻
kurihara.t.ab@m.titech.ac.jp
1. 序
第二次世界大戦期の米国において，民間(civilian)科学者と軍が協力して兵器開発を行う科学動員の体制が構築された．科学動員体制の中心となった組織は，科学研究開発局(The Office of Scientific Research andDevelopment, 以下 OSRD)と陸軍のマンハッタン工兵管区(Manhattan Engineering District, 以下 MED)であった．OSRD は，軍と民間科学者が協力してレーダーや近接信管などの研究開発を行う体制を構築した．MED
は，OSRD による基礎研究を引き継ぎ，民間科学者と軍が協力して原子爆弾の開発を行った．この戦時の科学動員の経験によって，軍は戦後も民間科学者と協力して兵器開発を行うことが重要だと考えるようになった．
OSRD と MED は戦時の臨時組織だったので，戦争が終結すると解散することになっていた．そのことは軍と民間科学者が協力して兵器の研究開発を行う体制の終結を意味した．冷戦の危機が高まりつつあった時期において，新兵器の研究開発を継続することが不可欠だと考えていた軍は，新たな体制を構築し，民間科学者と協力して研究開発活動を行う必要に迫られた．
2. 国立科学財団(NSF)と軍事研究
1945 年 7 月，民間科学者出身の科学行政官として OSRD の局長を務めていた Vannevar Bush は，Science: The
Endless Frontier を発表し，戦後も政府が科学研究を支援することを訴え，それを統轄する政府機関として国立科学財団(National Science Foundation, 以下 NSF)を設立することを主張した．
当初の Bush の構想では，NSF は基礎研究だけでなく軍事研究も支援することになっていた．軍もまた，
NSF が民間科学者と軍事研究を結びつける機関となることを期待していた．しかし，1950 年に設立された
NSF から軍事研究を支援する部門がなくなり，NSF は基礎研究のみを支援することになった．その理由として， NSF が軍事研究部門を持つと軍が科学を支配することになると考え，NSF が軍事研究に関わることを批判する多くの科学者たちによる運動があったことがあげられる．
3. 原子力委員会(AEC)と軍
戦争終結直後の 1945 年 10 月，原子力委員会(Atomic Energy Commission, 以下 AEC)を設立するための原子力法案が議会に提出された．この法案では，軍の代表も AEC の運営の責任を負う AEC の委員になれることになっていた．しかし，軍が原子力を管理することを強く批判する科学者たちの運動が起こり，その結果，軍の代表は AEC の委員になれないことになった．
軍の代表が AEC の委員になれなくなったことは，核兵器を含む原子力分野における軍の発言力が低下することを意味した．しかし軍は，1947 年 1 月に特殊兵器計画(Armed Forces Special Weapons Project, 以下
AFSWP)を設立し，原爆の保管と組み立てを行うための人員の養成や，放射能戦兵器に関する研究開発などを行い，原子力分野において軍の果たす役割の拡大をめざした．
4. 国防省研究開発委員会(RDB)と軍の研究開発活動
軍は，1946 年に，研究開発委員会(Joint Research and Development Board, JRDB．以下 RDB)を設立し，軍が RDB を設立することを主張していたに Bush を RDB の委員長任命した．Bush は，戦時に引き続き，戦後も民間科学者と軍が協力して兵器開発を行う体制を構築することを目指していたのであった．
RDB は，陸海軍長官(1947 年以降は国防長官)直属の委員会で，軍全体の研究開発活動に関する助言や調整を行う責任を担った．RDB は民間科学者と軍の代表で構成されており，その下部組織として，基礎研究や原子力などの専門の小委員会が設置され，民間科学者と軍代表で構成された．軍は RDB を設立することで，民間科学者と軍が協力して研究開発を行う体制を構築したのであった．
5. 結論
RDB の活動によって，軍事研究部門をもたない NSF や軍の代表が委員になれない AEC が設立されても，民間科学者と軍を結びつきが弱まることはなかった．軍は，RDB に設置された基礎物理科学委員会を通じて，民間の科学者と軍事に関する基礎研究活動を行った．また，同じく RDB に設置された原子力委員会や
AFSWP の活動を通じて，軍は民間科学者と共に原子力に関する研究開発活動を行った．
444

第二次世界大戦期における科学動員と科学者―米国の原爆開発の場合―
栗原岳史**東京工業大学大学院社会理工学研究科経営工学専攻

技術構造分析講座 山崎研究室
t-kuri@me.titech.ac.jp
第二次世界大戦期において米合衆国で行われた原子爆弾の開発は，民主主義的な組織の下でなされたのではなかった．原子爆弾の研究開発体制は上から強い権限で管理され，科学者たちの間の情報交換は厳しく制限されており，科学者たちの意見を広く下から汲み上げるような体制ではなかった．米合衆国の原子爆弾の開発は，民主主
義的な科学動員政策だったから成功したのではなかった．
1. 序論
1.1 背景第二次世界大戦期において，アメリカ合衆
国(以下米国)は，科学者を大量に動員して原子爆弾(以下原爆)やレーダーなど最先端の科
学知識を利用した兵器開発に成功し，実戦でその威力を発揮させた．それに対して，日本
やドイツは実戦で使用できるような兵器の研究開発に成功しなかった．米国で成功し，日本やドイツで成功しなかった理由として，科学者を動員する政策の違いが，これらの差を生んだと考えられている．
これまで，米国の科学動員政策が民主主義的に行われたため，科学動員に成功したと言われることが多かった.それに対し，豊富な人
材や知識がありながら，ドイツや日本が原爆やレーダーの開発に成功しなかったのは，科学動員政策が全体主義的であったためだと言われている．
第二次大戦期終結直後から，米国の科学動
員の歴史研究は盛んに行われている．冷戦が終結するころになると，米国以外の科学動員の歴史研究も盛んに行われるようになってきた．近年，多くの研究成果が蓄積され，各国の比較研究が可能となった．それに伴い，各国の科学動員に対する評価の見直しがすすんでいる．

に活用できず，原爆開発が成功しなかったのだと主張した．
また，米国の科学動員を統轄したOSRD(科学研究開発局，The Office of Scientific Researchand Development) の 局 長 を 務 め た ブ ッ シ ュ(Vannevar Bush)は，米国の科学動員が成功したのは，科学動員政策において，研究開発活動
が民主主義的に行われたためだと主張する．
ここでブッシュの述べる民主主義的とは，研究開発活動が，科学者たちが自由に意見を交換し，現場で研究する科学者たちの意見を下から適切に汲み取る体制だったということを意味している．ブッシュは，そのような研究開発体制において，軍部が科学者の意見を尊重して積極的に科学者に協力し，軍による情報管理などの研究の管理が適切に行われたと主張する．そして，戦時における科学動員の成功は，軍人と科学者が協力することができることを示したとブッシュは主張する．
近年，米国の科学史家のマーク・ウォーカ
ー(Mark Walker)のように，ハウトスミットやブッシュの評価に異論を提起するものが表われている．ウォーカーは，ドイツが原爆開発に成功しなかったことについて，ドイツにおける原爆開発の政策上の優先順位の重要性を指摘している．また，ドイツの科学史家たち
も，戦時中のドイツの研究開発活動は，新兵器の大量生産に結びつけることには成功しなかったとしても，航空機やロケット開発など
多くの研究開発の分野で目覚しい成果を出してきたと主張する．全体主義と呼ばれた国家体制においても，研究開発に成功しているのである．
枢軸国側の戦時動員において，ドイツのロケットや航空機開発，日本の生物化学兵器開発に見られるように，枢軸国側の科学動員において重要な成果を出し，戦後，連合国が強い関心をもって情報収集をおこなったことが明らかにされている．研究開発活動にとって，

1.2 既存研究レビュー
米国の科学動員に対する初期の代表的な評価として，米国の物理学者ハウトスミット(Samuel A. Goudsmit)の評価があげられる．ハウトスミットは，欧州戦線終結前から，原爆開発を含むドイツの研究開発状況の調査活動に従事していた．その経験から，ハウトスミットは，「ドイツ核物理学の失敗は，それをおおっていた全体主義的雰囲気に大幅に帰せられる」と，ドイツの科学動員政策が全体主義的であったため，豊富な人材や知識を十分
445

国家が民主主義か全体主義かどうかを問題にすることは，適切でなくなってきているといえよう．

2.2 科学者と最高政策グループ
ブッシュは，科学動員の政策決定において，科学者の意見が尊重され，民主主義的に政策決定がなされたと主張する．しかし，科学者
1.3 ねらいの意見がそのまま最高政策グループによる意
その一方で，民主主義を標榜する米国の科思決定に直接反映されたわけではなかった．
学動員における研究開発体制を詳細に検討す全米科学アカデミーを代表して原爆の可能ると，ブッシュの主張するような，民主主義性を研究していたシカゴ大学のアーサー・コ
的な研究開発体制とはいえない体制だったこ
ンプトンに宛てた1941年10月9日付の手紙の中とが明らかになる．本稿では，第二次世界大で，ブッシュは「(科学者の)課題は技術的問戦期の米国の原爆開発を検証し，米国の科学題」であり，「この計画における政府の政策
動員が，ブッシュの主張するような民主主義がどうあるべきか，どうであらざるべきかと的な体制で行われたのではなかったことを示いう問題ではない」と述べ，科学者の役割はす．
政策の問題ではないとしている．ブッシュは，今後，筆者は第二次大戦期の主要各国にお科学者の役割が限定されたものであることをける科学動員政策の比較を行うつもりである． 明確に述べている．
そのための準備として，国家の体制が民主主
つまり，科学者の役割は科学や技術の問題義であるのか全体主義であるのかどうかは，に答えるだけであり，原爆に関する政治的決
科学動員政策が成功するかどうかの指標とな定に関する意思決定を行うのは最高政策グル
らないことを本稿は論じる．
ープであったのである．
原爆を使用する際において，科学者たちの2. 米国の原爆開発組織
意見が尊重されたと言われている．スティム
2.1 最高政策グループ
ソン陸軍長官は，原爆使用する前に，原爆に米国の原爆開発の最高責任を担ったのは，関する問題を審議するために暫定委員会を設
1941年10月9日に大統領によって設置された最置し，そこで科学者たちの意見も尊重して原高政策グループである．この日，濃縮したウ爆の使用が決定されたと戦後に述べている．
ラン235を使用し，速い中性子のみを利用した
1945年6月に，シカゴ大学の物理学者ジェー
核分裂連鎖反応による原子爆弾が実現可能で
ムズ・フランクを中心として，原爆の無警告あることを記した英国のモード委員会報告を， 使用に反対する報告書が原爆開発の指導部に
OSRD局長のブッシュが大統領に提出したこと提出された．提案者の名前を取ってフランクを受けて，米国が原爆開発を行うことが決定報告と呼ばれている．スティムソン陸軍長官
された．
は，暫定委員会において，フランク報告が慎
その責任を担う組織として設置されたのが重に審議されたと述べている．
最高政策グループである．最高政策グループ
しかし，戦後に公開された暫定委員会の議は，ルーズベルト大統領，ウォーレス副大統事録の中で，当時提出されていた原爆の無警
領，マーシャル参謀総長，スティムソン陸軍
告使用に反対する科学者たちの意見が，事実長官，ブッシュOSRD局長，コナントNDRC委員
上無視されていたことが明らかになった．正長で構成された．最高政策グループは，大統式な会議ではなく，昼食休憩の中で数分間話
領直属であるため，強い権限をもった．また， 題になっただけであったのである．
原爆開発の予算が大統領の特別の予算から支原爆開発の体制は，ブッシュが主張するよ
出されることとなった．つまり，原爆開発の
うな，科学者の意見を下から汲み取り，科学予算について，議会の承認を得る必要がなく者の意見を尊重する民主主義的な体制ではななったのである．原爆開発は，既存の政府機かった．強力な権限をもち，少数の軍と科学
関や議会から干渉されずに，強い権限の下で行政官で構成された最高政策グループによっ行われることとなった．最高政策グループのて，上から管理される体制だったのである．
設置は，原爆関連の政策を大統領，軍，科学行政官の少数のグループで管理することを意
3. 原爆開発における情報管理
味した．
3.1 米国の情報管理政策
1942年6月，最高政策グループの下に，陸軍陸軍の管理下に置かれたマンハッタン工兵
マ ン ハ ッ タ ン 工 兵 管 区 (Manhattan
管区において，科学者たちの間の情報交換はEngineering District)が設置され，司令官に厳しく制限されていた．司令官のグローブス
レ ス リ ー ・ グ ロ ー ブ ス 陸 軍 少 将 (Leslie R.
は原爆の情報が枢軸国(特にドイツ)に漏れる
Groves)が任命された．原爆開発は，陸軍が直ことを警戒し，情報管理に注意を払っていた．
接管理することになったのである．
グローブスは，マンハッタン工兵管区におけ
原爆開発のための組織は変遷をするが，最る情報管理政策について，「知識を局限する高政策グループは常に最上位で原爆開発を管ことが機密保持の要件」であり，「人びとは理した．
自分の仕事を実施するのに必要なことだけを知ればよいので，その他は知る必要がない」
446

と述べている．グローブスは研究を区分化し，ほとんどの科学者たちは，区分化された中で，研究の全体像を把握することなく，自分に与えられた研究に従事するように組織された．
このような情報管理政策に対して，多くの科学者に反感を持った．しかし，原爆開発を優先するため，多くの科学者は不満抱きつつも軍の指導に従った．戦争が終結すると，多くの科学者が戦時中の軍による情報管理を厳しく批判した．
原爆開発のために，ロスアラモス研究所など，各地に新たな研究所が設置された．研究所は人里離れた僻地に設置され，研究所外部との連絡は厳しく制限されていた．
研究所内部において，科学者たちの中には
比較的自由に情報交換ができたと戦後に証言するものも多い．しかしその自由は，自分たちに与えられた原爆開発に関する個別の問題に限って，しかも閉ざされた研究所内部に限られた自由にすぎなかったのである．

的に，ドイツが原爆開発を行っていないことを科学者たちに伝えなかったのである．
3.3 日本降伏の情報
1945年5月，原爆に関する問題を議論するため，陸軍長官の下に暫定委員会が設置された．
暫定委員会では，日本に対する原爆使用などが議論された．暫定委員会は，スティムソン
陸軍長官の他に，ブッシュ，コナントら最高政策グループのメンバーと，軍や政府の指導部で構成された．
暫定委員会において，科学者の代表も科学顧問として暫定委員会に参加した．科学者の代表として，ロスアラモス研究所所長のオッ
ペンハイマー，シカゴ大学のアーサー・コン
プトンとエンリコ・フェルミ，カリフォルニ
ア大学のアーネスト・ローレンスが任命された．
スティムソン陸軍長官は，戦後，暫定委員会で日本に対して無警告で原爆を使用することが決定されたことについて，科学顧問の科学者たちもその方針に異論を唱えなかったと述べている．つまり，暫定委員会において，日本に対して無警告で原爆を使用することは，
科学者の意見も十分に尊重された上決定されたとスティムソンは述べているのである．
しかし，暫定委員会の政府指導部と科学顧問の科学者たちの間には，重要な政治決定を行うための情報量に差があった．当時，日本はソ連を仲介として連合国に降伏する道を探っていた．米国指導部は，日本の暗号電報を解読し，日本が降伏しようとしていることを知っていた．暫定委員会に参加する政府や軍の指導部の者たちは，そのことを知っていた．
それに対して，科学顧問として暫定委員会に参加した科学者たちは，日本が降伏しようとしていることを知らされていなかった．科
学者たちは，原爆を使用しなければ戦争を終結させられないと理解していたのであった．
暫定委員会の委員たちと，科学顧問の科学者たちは，対等な立場で議論をして政策決定に参加したわけではなかったのである．戦局に関する十分な情報を知らされた上で，科学者たちがそのような判断をしたのではなかったのである．
ブッシュの主張するように，民主主義的に意思決定がなされたというならば，科学者たちに十分な情報を与えた上で,政策判断に参加させるべきであろう．しかし，ドイツの原爆情報や日本の降伏情報など，重要な情報が科学者に伝えられることはなかった．科学者の役割は与えられた課題に関する研究を行い，指導部に対して技術的なアドヴァイスをすることだけであったのである．

3.2 ドイツの原爆開発情報
原爆開発に参加した科学者たちの多くは，ドイツが原爆を開発することを恐れていた．
特にユダヤ人科学者たちは，激しいユダヤ人排斥を行うファシズム国家であるドイツが米国より先に原爆を開発してしまうと，民主主義国家が戦争に敗北してしまうと信じていた．
彼らは一刻も早く原爆を完成させるために，強い熱意を持って研究に従事していた．
しかし今日において，第二次大戦期のドイ
ツの原爆開発はほとんど進んでいなかったことが明らかになっている．ドイツは初歩的な実験用原子炉を建設したが，終戦までにそれが臨界に達することすらなかったのである．
米国の指導部は，ドイツの原爆開発状況を早い段階から正確に察知していた．1944年1月
17日付の英国のJ. ディル元帥あての手紙において，グローブス将軍は，「我々は(ドイツによる)TA兵器の使用はありそうにないことに同意した」と述べている．TA兵器とは原爆の暗号名である．つまり，ドイツが降伏する一年以上前の1944年初頭までに，米英の指導部は，
ドイツが原爆開発を行っていないことを正確に理解していたのである．
米国指導部が理解していたドイツの原爆開発の情報は，科学者たちに伝えられなかった．
そのことについてドイツの原爆開発状況を調査していたアルソスと呼ばれた機関のメンバーだったハウトスミットが，戦後に重要な証言をしている．1944年にドイツに向かう際に，
ハウトスミットは「ロスアラモスの科学者たちの熱意を冷却させないため」，アルソス調査団の得たドイツ原爆の情報を科学者たちに伝えないようにグローブスから指示されたと述べている．つまり，ドイツの原爆開発を恐
4. まとめれて原爆開発に従事する科学者たちの意欲を
4.1 米国の原爆開発体制の特徴
失わないようにするため，グローブスは意図447

以上述べたように，第二次世界大戦期における米国の原爆開発体制は，OSRD 局長のブッシュが主張するような民主主義的な体制ではなかった．原爆開発全体は最高政策グループ
によって強い権限で上から管理され，現場の科学者の意見を下から広く汲み取る体制ではなかった．研究活動において，研究の従事する科学者たちは情報交換を厳しく制限されていた．隔離された研究所において，原爆開発に関わる情報は比較的自由に交換できたが，研究所外部との連絡は制限されていた．科学者に知らされる情報も，科学者たちの意欲を失わないように，管理された情報だった．
日本に対する原爆の無警告使用に反対する
科学者の意見は意見は事実上無視された．科学顧問として政策決定に参加した科学者たちも，日本が降伏しようとしていることのような重要な情報を知らされることはなかった．
ブッシュやハウトスミットが主張するように，米国の原爆開発は，民主主義的な研究開発体制であったとは言えないのである．
前回の報告書において，筆者は，第二次世界大戦期の各国の科学動員が成功した要因として，1) 強力な権限をもった機関によって運営されること，2) 異なる分野間の情報の交換が適切に行われたこと，3) 研究者たちに意欲があったことを挙げた．米国の原爆開発の成功においても，これらの基準は当てはまる．
ただし，それは研究開発体制が民主主義的であったかどうかに関わらないのである．
むしろその反対に，科学者たちが自由に情報交換を行い，科学者たちの意見を政治決定に反映させるような民主主義的な研究開発体制の下では，原爆のような大量殺戮兵器の開発は不可能だったことを，米国の原爆開発は示しているといえよう．

とすればいいのかを，今後は具体化することを課題とする．
References[1]

James Phinney Baxter 3rd, Scientists Against
Time, Little, Brown and Company, 1947

[2]

Vannevar Bush, Pieces of the Action, William
Morrow and Company, 1970

[3]

レスリー R. グローブス『原爆はこうしてつくられた』恒文社，1974 年[4]

S. A. ハウトスミット『ナチと原爆』海鳴社，1977 年[5]Richard G. Hewlett and Oscar E. Anderson,
Jr., New World: A History of the UnitedStates Atomic Energy Commission, Volume I,
1939-1946, University of California Press,
1990

[6]

リチャード･ローズ『原子爆弾の誕生 上下』紀伊国屋書店，1995 年[7]

M. シャーウィン『破滅への道程』TBS
ブリタニカ，1978 年[8]

Irvin Stewart, Organizing Scientific Research
for War, Arno Press, 1980

[9]Mark Walker, Nazi Science: Myth, Truth, and
the German Atomic Bomb, Perseus
Publishing, 1995

[10] Mark Walker ed., Science and Ideology: A
Comparative History, Routledge, 2002[11] 山崎正勝，日野川静枝編『原爆はこうして開発された』青木書店，1997 年

4.2 今後の展望
筆者は，第二次世界大戦期における主要各
国の科学動員の比較を行うことを目的とする．
戦時科学動員において，レーダーや原子爆弾のように，イノベーションが多々生み出された．その過程において，科学と工学，物理学と電気工学，物理学と化学のように，普段交流の少ない分野間で，共通の目的に向けた共同研究が行われたことがイノベーションが生み出された要因であると筆者は考える．その異分野間の情報交換を，どのようにして支えたのか，研究者や行政官や政治家たちは，
どのようにして研究開発を支えたのかを明らかにすることを，今後の課題とする．
今後は，日本，ドイツ，米国，英国におけるレーダー，原爆，ロケットや航空機，生物化学兵器の研究開発を取り上げる予定である．
これらは個別の歴史研究として，豊富な研究が蓄積されつつある．これらの歴史研究の成果を元に，国際比較を行うために，何を指標448

第二次世界大戦期における科学動員の国際比較―軍と大学の共生関係―
栗原岳史**

東京工業大学大学院社会理工学研究科
経営工学専攻技術構造分析講座山崎研究室
t-kuri@me.titech.ac.jp
第二次世界大戦に参戦した主要国において科学動員が実施され，それまでほとん
ど交流の無かった軍と大学が，新兵器の研究開発で協力した．各国で行なわれた科学
動員を比較すると，軍と科学者の共生関係が成立するかどうかが，科学動員で成果を出せるかどうかの条件だったことが明らかとなる．
1. 序論
第二次世界大戦期に実施された科学動員によって，米国はレーダーや原子爆弾の開発に成功し，戦局の推移に大きく貢献した．日本も米国のように各種の科学動員が行われたが，米国のように実戦で大規模に使用され，戦局を転換するほどの兵器を開発することはな
かった．
米国と日本の科学動員の違いについて，米国の科学動員は民主主義的に行われたので短期間に大きな成果を出せた，とする見解が多かった．日本の生物兵器開発やドイツのロケット(ミサイル)開発のように，ある程度の成果を出した科学動員は，例外的とみなされていた．
本稿は，そのような見解とは異なる見解を提示する．米国の科学動員と日本の生物兵器開発を比較することで，科学動員で成果を出すためには，科学動員の体制が民主主義的であったかどうかというよりも，軍と科学者の共生関係の成立が重要であったことを明らかにする．
科学者は軍に対して知識や手法を提供したのに対し，軍は科学者に対して研究資金を提供した．この研究資金によって，科学者は兵器開発を行うとともに，自身の研究活動を繁栄させることが来た．軍と科学者の双方にとって，利益を生み出す研究体制を構築することが，科学動員で成果を出すために重要だったのである．
日本の生物兵器開発は，捕虜を人体実験に使用し，多くの中国人やロシア人を殺害したことで知られている．筆者は，そのような人
道的・政治的問題はきわめて重要な歴史研究の課題であると理解しているが，本稿では，
研究開発組織としての評価・分析のみを行う
こととする．

2. 米国の科学動員と OSRD
1940 年に設立された国防研究委員会を元にして，1941 年に設立された OSRD(Office of
Scientific Research and Development, 科学研究開発局)が，米国の科学動員を統轄した．
OSRD 局長に就任したのは，科学行政官のブッシュ(Vannevar Bush)であった．科学行政官とは，学位を取得した科学者であるが，研究活動を行う研究者としてではなく，研究活動を管理する行政官のことである．科学者出身なのだから，科学行政官は科学者の気質や，研究活動が実際にどのように進められるのかをよく理解していた．
OSRD は大統領直属の機関で，独自の予算を執行する権限をもった．そのため OSRD は，軍やその他の行政機関から独立して研究計画を決定することができた．
OSRD は自身の研究所をもたず，大学など
既存の研究機関との契約を通じて研究活動を調整する機関であった．つまり，OSRD は科学者の研究組織をそのまま動員することができたのである．レーダー開発を行ったのは，MIT に設置された放射線研究所であった．原爆開発 1に使用されたサイクロトロン建設に，
ローレンスの研究グループが丸ごと動員された．OSRD は，研究者が日々行ってきた研究
活動や研究組織を，ほとんどそのままの形で動員したのである．
OSRD は，学術的な基礎的研究から兵器の1

1942年8月，原爆開発はOSRDから陸軍のマン

ハッタン工兵管区(MED)に移管された．しかしブッシュはMEDの最高政策グループの一員として，最高レベルの意思決定をおこなった．

449

開発まで，兵器の研究開発全体を管理した．
レーダー開発において，科学者たちが戦場や艦船上でレーダーの試作品を試験的に運用し，実戦での成果を放射線研究所にただちに反映させることができた．原爆開発においても，広島や長崎に原爆を投下するまで，科学者たちが原爆の部品や観測機器の整備や調整を行った．大学で行う基礎研究から，これまで軍人が行っていたような戦場での試験的使用
まで，兵器の研究開発全体が文民である科学者の管理下におかれたのである．
科学動員を通じて，大学に多額の研究資金が流入した．その結果，大学は研究設備を充実させることができた．科学動員に参加することで，大学は大きな利益を得ることができたのである．
OSRD は戦時の臨時組織だったので，戦争が終結した後に消滅した．科学動員に参加した科学者たちの多くは，戦争終結後に元の研究活動に戻った．科学動員で業績を挙げた科学者は多くの大学や研究機関から誘われ，戦前よりも高い地位につくことができた．つまり，科学動員に参加しても研究キャリアに大きな穴が開くことはなかったのである．
戦後，科学動員に参加した科学者たちは，戦時中に得た豊富な資金で設備を充実させた大学で，高い地位について研究活動を行うことができるようになった．
米国の戦時動員において，科学行政官が統括する OSRD の下，軍と大学との共生関係が成立したのである．

ュと，よく似た経歴をもっていたのである．
科学動員全体を統括したブッシュと異なり生物兵器開発に限ってであるが，石井は科学行
政官として研究活動を組織した．
石井は，研究を行なう部隊の設立において，陸軍全体の予算配分を行なう陸軍省軍事課長の永田鉄山や，関東軍作戦主任参謀の石原莞爾ら，陸軍の有力者から支援を受けた．石井は特に永田の胸像を自室に飾り，部隊設立の「恩人」として称えていた．陸軍参謀本部
作戦課長の鈴木率道大佐(当時)は，石原からその地位を引き継ぐとき，石井のことをよろし
く頼むと，石原から直接頼まれたと証言している．
陸軍省軍務局軍事課所属で陸軍中佐の新妻
清一(1910-1997)の証言によると，石井機関の予算は，大蔵省のチェックが入らないようにするため，陸軍省軍務局軍事課の予算に付け替えていた．その結果，石井機関は，議会や大蔵省から独立して，莫大な予算を獲得することができた．
石井機関は，強力な権限をもち，事実上自由に莫大な予算を使うことができたのである．大統領直属で独自の予算を執行することのできた，米国の OSRD とよく似ていたといえる．
石井は，研究活動を組織するため，自身の所属する医学者のネットワークを利用した．
石井は，「嘱託制度」を通じて医学者ネット
ワークの研究者を獲得した．嘱託制度とは，軍の制度で，軍人に身分を変えなくとも，民間人が一時的に軍の組織に加わることができた．この嘱託制度によって，民間の科学者が，軍人になることなく，軍の研究機関に参加することができた．
その結果，研究者たちは，医学者ネットワークに所属したまま，つまり研究者としてのキャリアをとめることなく，石井機関に参加したのである．
研究者組織をそのまま動員した，米国のOSRD とよく似た科学者の獲得方法だったと言える．
石井機関の研究成果は，若手研究者たちを通じて，医学者ネットワークの中に還元された．陸軍軍医学校の研究会で報告された石井機関の研究成果は，石井機関に参加した医学者の所属する大学の研究室にも届けられた．
石井機関は，医学者ネットワークに多額の研究資金を提供した．この資金を受けるため

3. 日本の生物兵器開発
日本の生物兵器開発を行ったのは，軍医中将となった石井四郎が組織した，通称「石井機関」と呼ばれた機関であった．石井自身が研究活動を行うことは少なく，石井は研究活
動全体を組織していた．
日本軍の軍医は，一般の医学教育を受けて医者になった者が，軍医学校に入学して一定の教育や訓練を受けた後，軍医となることができた．石井も京都大学医学部で医者としての教育を受けた後，陸軍軍医学校を経て軍医となった．軍医となった石井は京都大学へ派遣され，研究者として研究活動を行い学位を取得した．つまり，石井は研究者として教育や訓練を受けた研究者であった．
日本の生物兵器開発を組織した石井は，米国で OSRD の局長を務めた科学行政官ブッシ

450

には，特に課題が定められることなく，1 年に1 回の研究発表会に参加するだけでよかった．
こうして，医学者ネットワークは，石井機関を通じて多額の研究資金と最新の研究成果を手にすることができた．石井機関も，若く有能な研究者を獲得することができたのである．
終戦までに，日本は生物兵器を実戦で大規模に使用することはなかった．1941 年から
1942 年にかけて，試験的に中国の都市や戦場に散布したことはあったが，大きな成果をあげることなく，都市へ散布することは中止された．また，中国各地の井戸に撒くなど謀略
的に小規模に散布することはあったが，実戦で大規模に使用することはなかった 2．その理由として，生物兵器がジュネーブ議定書で禁止されていることに加えて，戦局を転換するほどの兵器を開発できなかったことが大きな理由であったと考えられる3．
有効な生物兵器を開発できなかったが，石井機関が行った各種微生物の人体に対する影響の詳細な研究を，米国は高く評価した．日本の生物兵器開発を調査した米国のヒルとビクターは，石井機関における人体実験を高く評価し，情報を入手することの重要性を訴えた．彼らは報告書において，「こうした情報
は，人体実験に対するためらいがあり，われ
われの研究室では得ることはできない」と書いている．米国政府はこれらの研究情報をソ連に先駆けて入手するため，捕虜を人体実験2に使用した石井らの戦争犯罪を免責することで，石井機関による生物兵器開発の研究情報を入手した．米国がそうまでして入手するほど，石井機関の研究成果は当時の最先端をい
くものであったのである．
4. 結論
米国の科学動員と，日本の生物兵器開発を比較することで，科学動員で成果を出すため，軍と科学者の共生関係の成立が重要であったことが明らかとなった．
そのような共生関係が成立するためには，
まず第一に，既存の組織を上から動かせるだけ強力な権限を持つ機関や組織が研究開発を管理する必要があった．米国の科学動員において，大統領直属で独自の予算を執行する権限をもつ OSRD が科学動員全体を管理していた．日本の生物兵器開発において，石井機関は陸軍首脳の支援を得て，自由に使える予算を獲得していた．
次に，科学者の気質や実際の研究活動をよく理解した科学行政官が，科学動員を管理したことである．OSRD 局長のブッシュも石井四郎も共に科学者出身であった．彼らは，これまでの軍の組織では，最新の科学を利用した研究開発を行うことはできず，科学者を主体とした研究組織を構築しなければならないと理解していた．
米国の科学動員と日本の生物兵器開発の組織は，双方共に，既存の研究組織をほとんどそのまま利用していた．OSRD は自身の研究組織を持たず，大学等の既存の研究機関で行う研究を調整することで科学動員を管理した．OSRD は戦時の一時的な機関であり，戦争が終結すると科学者たちは元の科学者ネット
ワークに帰った．石井機関は嘱託制度を通じて民間の研究者を獲得したが，多くの研究者は数年で元の医学者ネットワークに帰っていった．米国でも日本でも，科学者たちは研究者としてキャリアを止めることなく，科学動員に参加できる組織だったのである．
米国でも日本でも，科学動員を通じて大学に多額の資金が流入した．レーダーの研究開発を行うために設置された放射線研究所を通じて，MIT に多額の資金が流入した．原爆開発のために建設されたロスアラモス研究所は，カリフォルニア大学が運営されることになっていたため，研究所の建設や運営のために大学に多額の資金が流入した．その結果，科1944年4月26日の陸軍省局長会報に石井四郎が呼ばれ，生物兵器攻撃の実施を検討したことはあった．実際にサイパン島に細菌兵器を散布するために石井機関から人員が派遣されたが，サイパン島に着く前に，海上で船舶が米軍に撃沈された．
3

1943年末から1944年春にかけて，石井機関の開発したペスト菌を散布する爆弾の実験が行われた．その結果，爆弾の破片で傷ついた者のうち，10-30%がペストを発症させたという報告がある．筆者にはこの数字を評価する能力は無い
が，この程度の発症率で有効な兵器として使用できたとは思えない．終戦後，米軍もこの兵器を有効な兵器と評価していない．

451

[12] 常石敬一『七三一部隊: 生物兵器犯罪の真実』講談社，1995 年

学者たちは自身の研究を行うための設備を充実させることができた．日本の生物兵器開発
において，石井機関では多額の研究費を自由に使うことができた．その研究成果は嘱託制
度を通じて元の大学にも還元された．
軍は優秀な科学者たちの協力を得ることで，新兵器の研究開発に必要な知識や人材を入手することができた．大学もまた，多額の資金や資材を優先的に得ることができ，自信の研究活動を促進させることができた．つまり，軍と科学者の共生関係が成立していたのである．
科学動員で成果を出せるかどうかは，政治
体制が民主主義であったかどうかというよりも，研究活動を実際に行なう科学者たちを効率的に管理することが重要だったのである．

[13] 常石敬一『医学者たちの組織犯罪』朝日文庫，1999 年[14] S. A. ハウトスミット『ナチと原爆』海鳴社，1977 年[15] 秦郁彦「日本の細菌戦: 七三一部隊と石井四郎」『昭和史の謎を追う 上』文芸
春秋，1999 年，535-558 頁[16] 秦郁彦「日本の細菌戦: 中国大陸とサイパンで」『昭和史の謎を追う 上』文芸
春秋，1999 年，559-585 頁[17] 松村高夫編『「論争」731 部隊 増補版』
晩声社，1997 年[18] リチャード･ローズ『原子爆弾の誕生 上下』紀伊国屋書店，1995 年

参考文献
[1]

James Phinney Baxter 3rd, Scientists Against
Time, Little, Brown and Company, 1947

[2]

Vannevar Bush, Pieces of the Action, William
Morrow and Co., 1970

[3]

Richard G. Hewlett and Oscar E. Anderson,
Jr., New World: A History of the UnitedStates Atomic Energy Commission, Volume I,
1939-1946, University of California Press,
1990

[4]

Irvin Stewart, Organizing Scientific Research
for War, Arno Press, 1980

[5]

Mark Walker, Science and Ideology: A
Comparative History, Routledge, 2002

[6]

太田昌克 『731 免責の系譜: 細菌戦部隊と秘蔵のファイル』日本評論社，1999 年[7]

レスリー R. グローブス『原爆はこうしてつくられた』恒文社，1974 年[8]近藤昭二 編『731 部隊・細菌戦資料集成』柏書房，2003 年[9]常石敬一『標的・イシイ: 七三一部隊と米軍諜報活動』大月書店，1984 年[19] 吉見義明，伊香俊哉『七三一部隊と天皇・陸軍中央』岩波書店，1995 年[10] 常石敬一『消えた細菌戦部隊: 関東軍第七三一部隊』筑摩書房，1993 年[11] 常石敬一「石井部隊」中山茂 他編『通史日本の科学技術 1 占領期 1945-1952』学陽書房，1995 年，103-110 頁

452

第二次世界大戦期の科学動員の歴史研究―戦後の米国における核開発体制の転換―
栗原岳史

東京工業大学大学院 社会理工学研究科
経営工学専攻 山崎研究室
t-kuri@me.titech.ac.jp
第二次大戦期が終結すると，米国の核兵器開発体制は大きく転換された．その中で，戦時中に民間科学者と軍が共同で行なっていた「兵器工学」が，軍人だけで構成され，軍によって管理される組織になった．科学の研究活動を軍に管理されることを批判する科学者たちの批判を受けて，軍は科学者の協力を得られるようにするために，「兵器工学」を研究開発活動から分離したのであった．
物理学者であるA. Einsteinや，原子爆弾を開発

1. 序論
第二次世界戦争が終結すると，大学と軍がした研究所の一つであるLos Alamos研究所の所協力して新兵器の研究開発活動を行った戦時長を務めた物理学者のR. Oppenheimerらにも支中の科学動員体制が解除されたが，新たに政持され，多くの科学者たちから支持されてい府が科学研究活動を支援する体制が確立した． た．マクマホン法の成立において，科学者た
核兵器を開発した陸軍マンハッタン工兵管区

ちのロビー活動が影響したと言われている．

(Manhattan Engineering District, 以下 MED)も消

しかし，科学者たちの運動の歴史を研究し滅し，科学者たちの動員は解除された．そのたAlice K. Smith やJessica Wang は，AECの文後，MEDの資産は新たに設立された原子力委

民管理をめぐるAECの全般的な性格に対する員会(Atomic Energy Commission, 以下AEC)に引

FASの活動については論じているが，実際の核

き継がれ，米国の核開発体制の再編が行われ開発活動については，ほとんど何も言及してた．本稿は，この米国の核開発体制の再編にいない．

おいて，科学者と軍の対立の影響があったこ

第二次大戦が終結すると，大学などの民間とを論じる．

の研究機関に対して，軍部が研究資金を提供

戦後AECを設立する際に，議会において激するようになった．大型加速器の建設など，しい論争があったことはよく知られている．

多額の資金を必要とする研究活動に対しても，その論争において，民間の科学者の団体であ軍は資金を提供した．今日に至るまで，米国

る 米 国 科 学 者 連 盟 (Federation of Americanの政府支出による研究開発費の半数を軍部がScientists, 以下 FAS)は，原子力を管理する機支出しているが,そのような軍主導の研究開発関であるAECの委員に軍の代表が就任するこ体制がこのとき成立したのである．第二次大とを批判し，AECの委員を文民のみで構成す

戦後の科学研究体制全般に関する歴史研究にることでAECを文民管理の機関とすることをおいて，既存の研究の多くは，戦後に米国の主張し，活発にロビー活動に取り組んだ．議軍部が民間の科学研究に対して研究資金を支会における論争は，最終的に陸軍の影響下で援するようになったことを指して，軍と大学作成され，軍の代表がAEC委員になることをや科学者の協力・共生の関係を強調している．

規定した原子力法案(通称，メイ・ジョンソン

しかし，これらの先行研究者たちは，軍部と法案)が廃案となり，FASの支持する法案(通称

民間科学者との対立を軽視している．

マクマホン法案)が成立した．FASは，著名な

本稿は，戦後の核開発体制に着目し，軍主453

導の研究開発に批判的だった科学者の果たしMED に お け る 兵 器 工 学 を 行 っ た 組 織 は ，た役割を明らかにすることを通じて，戦後のProject Alberta(以下 Project A)である．Project A

米国の研究開発体制の内部に存在する対立をは，1945年3月に編成され，原爆を空輸可能な論じる．

爆弾にすること，模擬爆弾を使用しての野外演習の指揮を行った．また，サイパン島に原

2. 兵器工学

爆のメンテナンスや組み立てを行うための設議論を進めるために，本稿は「兵器工学」

備を準備し，広島や長崎で使用された原爆をを定義する．兵器工学とは，大学等で行われ組み立てた．Project Aは，民間科学者と軍の技るアカデミックな研究の体系と，実際の兵器

術者の共同で編成され，軍の技術者であるとして使用される軍事技術の体系を連結する

William S. Parsons提督の指揮下に置かれた．

研究開発活動のことである．兵器工学は基本1945 年 7 月 ， Z-division( 以 下 Z-div) が Los

的に軍事技術の一部であるが，アカデミック

Alamos 研 究 所 に 設 立 さ れ ， 同 年 9 月 ま で にな研究活動によって得られた成果を，実際にProject Aをひきついだ．Z-divは，原爆の部品使用可能な軍事技術にするプロセスを担う．

を 保 管 し ， メ ン テ ナ ン ス を 行 った．Z-divは

核開発活動におけるアカデミックな研究活

Project Aと同様に，軍と民間科学者との協同組

動とは，MEDにおいては，核物理学研究，核織だった．戦後，爆発事故などに備えて，Z-

分裂連鎖反応の研究，シカゴCP-1(実験用原子

divはアルバカーキ近郊のSandia基地に移動し炉)の研究開発，ウラン濃縮技術(気体拡散，熱た．しかし，戦争が終結すると，多くの科学

拡散，電磁分離)の開発，プルトニウム生産技

者がZ-divを離れたため，Z-divの組織がほとん

術(生産原子炉と核燃料処理技術)の開発，主とど機能しなくなった．

して爆縮型原爆(長崎型．プルトニウム原爆)の起爆装置開発が含まれる．MEDにおいては，

4. 戦後における兵器工学の転換

民間科学者によって行われた．

4.1 軍に対する科学者の不信

MEDにおける兵器工学の活動とは，アカデ戦争が終結すると，科学者運動が米国各地

ミック研究の成果から，実際に航空機に積みで急速に広まった．この運動に参加した科学

込んで投下できるような爆弾をにする研究開者たちは，原爆を一般市民に対して使用した

発活動のことである．具体的には，起爆装置

軍を強く批判し，原子力の国際管理と文民管を点火するための電子機器装置の開発，弾道

理の原子力委員会の設立を主張した．また，の安定化，運搬用の航空機の改良，爆弾組み科学の研究活動を軍が管理することに批判し

立て手順の標準化，部品の標準化や信頼性のた．この科学者たちは，MEDをひきつぐAEC

向上，部品の保管とメンテナンス，要員の訓から軍の代表を除くことを主張したり，戦時練やそのための施設や器具の開発である．

の科学動員全体を統括した科学研究開発局

MEDにおいては，アカデミックな研究は民(OSRD) を ひ き つ ぐ 国 立 科 学 財 団 (National

間科学者の手によって行われた．兵器工学のScience Foundation)が機密の軍事研究を行なう

活動は，民間科学者と軍の技術者の共同で行べきでないと主張した．軍に対する不信感が，われた．

科学者運動の重要な原動力だったのである．
この科学者運動には，Los Alamos研究所の所長を務めたRobert Oppenheimerや，著名な物理3. マンハッタン管区における兵器工学の活動学者であるAlbert Einsteinをはじめ，多くの著

454

名な科学者たちが関わり，科学者の中で大き

科学者の会議が開かれ，Sandia基地を軍によっな影響力をもっていた．

て運営される「兵器活動」の場とすることが1946年8月に文民管理を定めた原子力法が成決定された．「兵器活動」とは，原爆の部品立した後においても，Oppenheimerの後を継いの保管やメンテナンス，爆弾の各種機器の開でLos Alamos研究所の所長に就任したBradbury

発や整備のことで，本稿で言う兵器工学のこは，1946年11月に，「陸軍に対する(科学者の)とである．つまり，ロスアラモス研究所は，不信感がまだ残っている．陸軍がMEDを引き

AECによって管理され，民間科学者によって継ぐという懸念がまだ存在する」と多くの科運営される研究所となり，そこから軍によっ

学者が，研究活動を軍が管理することを批判て管理される兵器工学が分離されたのであっしているとAECに述べている．

た．
1946年7月，Groves将軍は，陸軍工兵隊の将

4.2 科学者に対する軍の期待
一方軍は，戦時の科学動員を高く評価して校60人で編成された第2761工兵大隊(特別)をいた．1946年4月23日，Eisenhower陸軍参謀総

Sandia基地に設立した．1946年9月にGrovesの長は，平時から民間科学者と協力することを副官のKenneth D. Nichols大佐は，民間の科学指示するメモを陸軍と海軍の軍指導部に廻し者が(兵器である)爆弾を組み立てる状況は，いた．MED司令官のLeslie R. Grovesもまた，核

つまでも続けるべきでないと述べている．つ

開発活動を続けるために，民間の科学者と協まり，軍は，兵器工学の分野を民間の科学者力することが重要性だと理解し，「ロスアラに頼らなくとも，軍人だけで実施できるよう

モス研究所を持続することは，とくに大事なにすることをめざしたのであった．

こと」「原爆開発計画の職場を離れていく人

5.2 AFSWPの設立

たちの今後の協力を確保することが大切」とMEDがAECに引き継がれる1947年1月1日付
で ， AFSWP(Armed Forces Special Weapons

述べている．
またGrovesは，陸軍の米国の核開発計画がProject)が設立された．陸海(空)軍直属の軍の機

AEC に 引 き 継 が れ た 後 も ， 核 兵 器 に 関 す る関で，初代の責任者に，MEDに続いてGroves「研究，開発，生産，使用」に「陸軍が役割将軍が就任した．AFSWPの任務は，「マンハをはたすべき」と述べ，陸軍が核開発に関与

ッタン計画に関わるすべての軍事機能の責

す る べ き だ と 述 べ て い る ． 陸 軍 は，MEDが任」を担うこととされた．他に，「特別人員AECに引き継がれた後も，核開発に関与するの技術訓練」「原子兵器の研究開発へ参加」

ことを考えていたのである．

「放射線安全対策」「原子兵器の保管と保以上のことから，軍は，平時から民間科学衛」を行うことも定められた．AFSWPは，す者の協力が得られるようにすることを考慮す

ぐに第2761工兵大隊(特別)を編入した．

るようになった．その結果，軍が管理する軍

つまり，軍は，MEDがAECに引き継がれる

事機密の必要な兵器工学を，民間科学者が参と同時に，軍だけで兵器工学を実施するため加する研究活動から分離することになったのの組織を設立したのであった．

である．
6. 結論
5. 兵器工学の分離

第2次世界大戦が終結すると，米国の核開発

5.1 Sandia基地における兵器工学

体制は大きく転換され，原子爆弾を開発した

1946年5月2日，ロスアラモス研究所で軍と陸軍のマンハッタン工兵管区(MED)が，新設455

された文民機関である原子力委員会(AEC)に引[3]

Doris M. Condit, The Test of War, 1950-1953,
History of the Office of the Secretary of
Defense, 1988

[4]

Defense Threat Reduction Agency, Defense's
Nuclear Agency 1947-1997, Defense Threat
Reduction Agency, 2002

[5]

Necah Stewart Furman, Sandia National
Laboratories: The Postwar Decade, The
University of New Mexico Press, 1990

[6]

Leslie R. Groves, Now It Can Be Told, Da
Capo Press, 1962

[7]

Richard G. Hewlett and Oscar E. Anderson,
Jr., The New World: A History of the UnitedStates Atomic Energy Commission, Volume 1,
1939-1946, University of California Press,
1990

[8]

Richard G. Hewlett and Francis Duncan,
Atomic Shield: A History of the United States
Atomic Energy Commission, Volume II, 19471952, University of California Press, 1990

[9]David E. Lilienthal, The Journals of David E.
Lilienthal, Vol. II, The Atomic Energy Years
1945-1950, Harper & Row, 1964

き継がれた．しかし，軍は核開発体制に関与し続ける意図をもちつづけていた．
戦争が終結すると，マンハッタン計画に参加した民間の科学者たちを中心にして，科学者たちは，研究活動を軍に管理されることを批判した．自身の研究の成果を軍事利用されることに批判的だったからである．
科学者たちの批判に直面した軍は，基礎研究を中心に民間科学者に委ねる一方で，それらの研究の成果から使用できる兵器にするために必要な，兵器工学の活動を手にすることを目指した．そのために，軍はMEDがAECに引き継がれると同時に，兵器工学の役割を担わせるために，AFSWPを設立したのであった．
本稿が論じたように，第二次大戦期における科学動員を高く評価した軍部は，戦争が終結すると，大学などの民間の研究活動に対し[10] Kenneth D. Nichols, The Road to Trinity: A
Personal Account of How America's Nuclear
Policies Were Made, William Morrow andCompany, 1987て研究資金を提供するようになり，科学者の多くもその資金を受け入れた．しかし，科学者たちは決して諸手をあげて歓迎していたわ[11] Steven L. Rearden, The Formative Years,
1947-1950, Office of the Secretary of Defense,
1984

けではなかった．第二次大戦後の米国の科学研究体制は，その内部において，軍部と科学[12] Alice K. Smith, A Peril and A Hope, The
Scientists' Movement in America: 1945-47,
The University of Chicago Press, 1965

者の対立を孕んできたのである．
本稿は，核兵器開発体制にのみ着目してきた．しかし，言うまでも無いことだが，軍部[13] Jessica Wang, American Science in an Age ofAnxiety: Scientists, Anticommunism, and theCold War, University of North Carolina, 1999と大学との関係は核開発だけではない．戦後の科学研究開発体制の成立と戦時動員との関その他，米国科学者連盟，米国国立公文
書館，米国エネルギー省科学技術情報局
所蔵の文書係を歴史的に分析するためには，レーダーな
どの電子機器開発，航空機開発，医学や生化学の分野の場合を研究する必要がある．これ
らの分野については，今後の課題としたい．
主要参考文献[1]

James L. Abrahamson, et. al., Vanguard ofAmerican Atomic Deterrence: The Sandia
Pioneers, 1946-1949, Praeger, 2002

[2]

AFSWP, “First History of AFSWP 19471954,” 1954456

第二次世界大戦終結後の米国における核開発体制の再編成―文民と軍と対立―
栗原岳史
t-kuri@me.titech.ac.jp
第二次大戦終結後，米国の核兵器開発体制は再編成され，文民の委員のみで構成される原子力委員会(Atomic Energy Commision)が米国の核開発を管理することとなった．一方で，軍は核兵器を使用できるようにするため，AFSWP(Armed Forces Special
Weapons Project)を設立し，原爆の保管をめぐって AEC と対立した．この核兵器開発における軍と AEC の対立は，軍部と文民の間で，核兵器の使用に関する認識の違いが背景にあった．
Commission, AEC)の委員に，軍人がなれるかど
うかの問題だった．つまり，核開発の管理における軍の影響力の大きさが問題だったのであった．
原子力法案をめぐって，議会は大きく分裂した．原子力の文民管理を主張する人々は，軍人がAECの委員になれないようにすることを主張した．彼らは，軍という巨大な政府機関を代表する軍人がAECの委員になることは，
核開発が軍の管理下に置かれることなると考えた．AECの委員に軍人がなれることを支持する人々は，その多くが原子力の文民管理を主張してはいたが，事実上，核開発における軍の発言力を強くすることを目指していた．
議論は翌年までつづき，最終的に，軍人がAECの委員になれないことになった．この論争が示すように，核兵器を含む核開発において，文民と軍の対立は大きな問題となっていたのであった．
1946年8月，Truman大統領が原子力法に署名して原子力法が成立され，AECが設立された．AECの委員長には，Roosevelt政権下でテ
ネシー河谷開発公社の総裁を務めた法律家のDavid Lilienthalが任命された．Lilienthalは原子力の文民管理を強く支持しており，軍人がAECの委員になることに反対していた人々から強く支持された．また，Lilienthalは核開発を国際管理下におくべきだと主張していた．このようなLilienthalの立場は，とくに軍から強く批判されていた．
1946年12月31日，AECがMEDの「すべての1
核開発には兵器と原子炉の双方が含まれるが， 資産」を引き継いだ．つまり，核開発が軍か
本稿があつかう時代には明確に区別されていら文民へ移管されたのであった．米国の原子なかった．また，当時は核エネルギー(nuclear
力は文民管理の下に置かれたと言われるよう
energy)のことを一般的に原子力(atomic energy)， になった．
核兵器のことを原子爆弾(原爆)と称していた．
しかし，後述するように，原爆を保管する
本稿では適時使い分けることとする．

1. 序: 米国の核開発体制の変遷
1941年10月9日，科学動員の責任者であった
Vannevar Bushによる核兵器開発の提言を大統領が承認し，米国の核兵器開発が決定された．
この日以降，核開発1 は，Bushが局長を務める
科学研究開発局(The Office of Scientific Researchand Development, OSRD)の下に置かれることになった．OSRDは文民(civilian)の科学行政官であるであるBushが局長を務める組織であった
ので，米国の核開発は文民管理であったと言える．
1942年に米国陸軍がマンハッタン工兵管区(Manhattan Engineering District, MED)を設立し，その年の末までに，MEDがOSRDから核開発計
画を引き継いだ．核開発が研究の段階から開発・生産中心に移行して大規模な施設の建設や莫大な予算が必要となり，そのような大規模組織の運営に慣れた軍が運営する方が適切だと判断されたためであった．核開発の責任がOSRDからMEDに移管したことは，核開発が文民から軍の管理下に置かれたことを意味した．
1945年8月に広島と長崎に原爆が使用され，その翌週に日本が降伏し，第二次世界大戦が終結した．米国では，戦後の核開発の体制を定めた原子力法案が議会に提出され，核開発をめぐる論争が始まった．この論争の主要な争点となったのは，核開発を管理するために新たに設立される原子力委員会(Atomic Energy

457

ため，上記の機器類の使用・運用マニュアルを作成した．AFSWPの行ったことは，核兵器を実際に使用できるようにすること，つまり，科学知識を実際的に利用できる技術にすることだったと言える．
1947年11月，AFSWPは核物質を取り除いた
模擬爆弾を使用して，最初の原爆投下演習を実施し，それに成功した．AFSWPは，科学者
2. AFSWPの設立とその活動でなくとも軍人でも原爆を扱えることを実証開発されたばかりの原爆は，使用するたびしたのであった．しかし，原爆を扱える部隊に組み立てなければならない装置であり，そはまだ一つしか存在せず，実戦で原爆を使用の保管には専門的な知識と技能を必要としてできる状況ではなかった．
いた．原爆は，一旦組み立てても，数日以内
その後，AFSWPは空軍や海軍の原爆部隊のに再び分解し，起爆装置を構成する電子機器養成に着手した．そして1948年末までに，最や高性能爆薬，および核物質の点検を行い，初の部隊の養成が修了し，原爆を部品から組バッテリーの充電を行わなければならなかっみ立て，航空機に積み込み，標的に投下し，た．部品も規格が統一されておらず，すべて起爆装置を爆発させる演習に成功した．
手作業で組み立てなければならなかった．長AFSWPは，1948年末までに，軍による原爆の崎に投下されたものと同じタイプの原爆(Mark保管・組み立てを可能にしたのであった．
III)の場合，すべての部品から原爆を組み立て
後述する1948年7月21日のホワイトハウスでるまでに，原爆を開発した専門の科学者と技開催され，Truman大統領，AEC委員，陸海空術者のグループでも30日かかっていた．
軍長官の参加した会議で，国防長官のForrestal
MEDで原爆開発を行った科学者たちは，そは，あと「4ヶ月」で軍が原爆を扱えるようにのほとんどが民間の大学に所属する科学者でなると大統領に述べた．この時点から4ヶ月後あった．そのため，第二次世界大戦が終結すは1948年末であることから，Forrestalの主張は，
ると，多くの科学者たちが元の職場に帰って
AFSWPの活動によって，1948年末までに軍だ
いった．その結果，戦争終結後，核兵器をそけで原爆を組み立て，航空機に積み込み，投の部品から組み立てて使用できる状態を維持下することができるようになることを意味すすることが，極めて困難な状況となっていた． るものと考えられる．
そのような状況に危機感を抱いた軍指導部
は，MEDの司令官であったLeslie R. Groves少3. 原爆の保管をめぐる軍とAECの対立 1将が中心となって，軍人による原爆組み立て―原爆を保管するのは軍かAECか？
部隊の設置に取り組んだ．その組織が最終的1946年に制定された原子力法は，「すべてに AFSWP(Armed Forces Special Weaponsの原子力」をAECが管理すると規定していた．
Project)となった．AFSWPは，AECがMEDを引
そして実際に原爆を使用するときには，大統き継いだ翌日の1947年1月1日付で，陸軍と海領がAECに原爆を軍に移管する指令を出すと軍の共同で設立された．1947年1月29日に発行定めていた．
されたAFSWPチャーターには，「原子力に関
しかし，原爆を実際に使用するために，軍するすべての軍事機能の責任を担う」ことががどのような準備をするべきなのか，明確に明記された．
されていなかった．原爆を使用するためには，
AFSWPは，わずかにMEDに残った科学者や常に原爆を使用できる状態に保つことが必要
残された仕様書から，原爆の組み立て技術やであり，そのためにどこまで軍が核兵器開発
原爆保管技能の習得に従事した．AFSWPは，に関与するのか，明確にされていなかったの爆弾を組み立てるための道具類，起爆装置のであった．
電子機器類，核兵器を航空機に積み込むため
原子力法の成立する前から，軍内部では，の装置などの改良や開発にとりくんだ．また， 軍が原爆を保管し，使用の際に組み立てるべ
放射線測定機器の改良や開発も行った．
きだと主張されていた．しかし，そのことを
AFSWPは，高度な科学や技術の専門知識を持大統領やAECに対して軍が要求することはほたない軍人でも，核兵器を扱えるようにする
とんどなかった．軍だけでは原爆を扱うことのが軍であるのかAECであるのかについて，
曖昧さが残っていた．その後，AECと軍との間で，原爆の保管をめぐって論争が行われることになった．
原子力法の成立により核開発に対する発言力が低下した軍であったが，軍は開発に関与し続けることを意図していた．

458

の見解を推進し，大統領に対する進言を起草し た の は ， MED 司 令 官 で AFSWP チ ー フ のGrovesやKenneth D. Nichols少将ら，戦時中から核開発を指揮していた者たちであった．
そのような軍指導部の見解に対して，AECの委員たちは軍とは異なる考え方をしていた．
AEC委員長のLilienthalは，「原爆は単なる兵器のひとつではない」と主張していた．当然のことながら核兵器は兵器の一つであり，実際にそれを戦場で使用するのは軍であった．しかしLilienthalは，軍事的理由だけで原爆を使用してはならないと主張していた．Lilienthalは，
その理由を，核兵器の破壊力が他の兵器と比べて桁外れに強力であるため，核兵器を使用する場合には国際関係や世論を慎重に考慮する必要があるからだと述べた．
また，Lilienthalは，AECが核兵器を軍に渡すだけの機関であってはならないとも主張した．
Lilienthalは，核兵器を使用する場合には，核兵器使用に対する国内の世論や，その使用が国際関係に与える影響を慎重に考慮した上で大統領に助言しなければならず，軍事的理由だ
けで核兵器の使用を決定してはならないと主張した．Lilienthalは，それができるのは軍ではなく文民であると主張した．Lilienthalは，核兵器の使用それ自体に反対していたわけではな
かったが，核兵器の使用に極めて慎重な立場をとっていた．
Lilienthalの立場は，EinsteinやOppenheimerら，
指導的な著名な科学者を含む，原子力の文民管理を提唱する人々から強く支持された．彼
らは，核開発を国際管理の下に置くことを主張していたLilienthalの立場を支持しており，
4. 原爆の保管をめぐる軍とAECの対立 2
LilienthalのAEC委員長への任命を歓迎していた―軍とAECの原爆観の違い
人々でもあった．また，彼らの立場は，当時
原 爆 の 保 管 を め ぐ る AEC と 軍 の 対 立 は ，の広範な世論に支えられていた．先述した
AECと軍の間で，核兵器に対する異なる考え
1948年7月21日のホワイトハウス会議の翌日，方があったからであった．
大統領側近の予算局長のWebbは，Truman大統
軍は，軍が原爆を保管するべきだと主張し領に対して原子力の文民管理を支持する「広ていたが，その理由として，原爆は 「単なる範な世論」があるとして，軍の要請を却下し，兵器のひとつ(just another weapon)」であるから原爆を軍に移管すべきでないと進言した．
だと，たびたび主張した．普段兵器を管理し，1948年7月24日のTruman声明は，軍の原爆保戦場でその使用の判断を行うのは軍であった． 管 を 批 判 し ， 原 子 力 の 文 民 管 理 を 支 持 す る軍は，核兵器も当然その範疇に含まれるとみ「広範な」人々に支えられたものだったのでなしていたのであった．軍にとって，AECのあった．
役割は，軍が必要だと判断したときに，核兵以上のように，米国内部の核兵器に対する器を軍に渡すだけであった．そのような軍の考え方は，核兵器を通常の兵器と同一にする
見解は，Forrestal国防長官や陸海空軍の長官ら， べきかどうかをめぐり分裂していたのであっ
軍指導部の統一した見解であった．また，そた．1948年7月のTrumanの決定は，核兵器を通が出来なかったからだと考えられる．
1947 年 末 ご ろ か ら ， 定 期 的 に 開 催 さ れ る
AECと軍幹部との会合において，軍幹部たち
は，AECに対して軍が原爆を保管するべきだと主張するようになった．原爆を使用するのは軍なのだから，平時から軍が原爆を保管す
るのでなければ，原爆を使用するときに必要な技術や技能を十分に修得できないと軍は主張した．1947年の末になってAECに対してこのような主張を明確にするようになったのは，
AFSWPが実施した最初の原爆組み立て・投下演習が成功したことが，軍幹部の自身を強めたからだと考えられる．
軍側の要請に対して，AECの委員たちは，原子力法が「すべての原子力」をAECが管理すると規定していると主張した．さらに，原爆は非常に複雑な装置であり，その取り扱いには核物理学などの高度な専門知識が必要であるため，軍人には原爆を扱うことができな
いとも主張した．
論争の決着はつかず，最終的に，Truman大統領の前で決着がつけられることになった．
1948年7月21日，ホワイトハウスでTruman大統
領，AEC委員，陸海空軍長官の参加した会議が開催された．AECと軍の双方が自身の立場を主張した後，Truman大統領は，原爆を保管するのはAECであると発言し，軍の要請を却下 し た ． そ の 数 日 後 の 7 月 24 日 の 声 明 で ，Truman大統領は「原子力の文民管理の継続」を宣言した．この声明で，「原子力の文民管理」に原爆保管も含まれることが明確にされたのであった．

459

常の兵器と区別することを明確にしたのであ
った．

[6]

Necah Stewart Furman, Sandia National
Laboratories: The Postwar Decade, The
University of New Mexico Press, 1990.

5. 結論
1946 年に原子力委員会(AEC)が設立し，米国の原子力開発はすべて AEC の管理下におかれることになった．しかし，軍は AFSWP を設立
し，軍が原爆を扱う能力をもつことを目指した．1948 年末までに，軍だけで原爆を組み立てられるようになった．それゆえ，軍は原爆保管の軍への移管を強く要請することになったのであった．
原爆の保管をめぐる軍と AEC の論争は，1948 年 7 月の Truman 大統領の声明で決着がつけられた．Truman は，「原子力の文民管理」の継続を宣言し，その結果，原子力の文民管理に核兵器の保管も含まれることが明確となった．
AEC と軍のどちらが原爆を保管するかの議論の背景に，米国内部の核兵器観の違いがあった．AEC と AEC の立場を支持する人々は，核兵器の使用には極めて慎重であった．彼ら
は，核兵器を他の兵器と区別し，軍事的な必要性だけでその使用を判断してはならないと主張した．それに対して，軍は，核兵器を他の兵器と同じように，軍がその使用の可否を判断するもとのみなしていたのであった．
1948 年 7 月の Truman 大統領の声明は，米国が AEC の立場，すなわち核兵器を他の兵器と区別し，その使用の判断に極めて慎重である
ことを明確にしたことを意味した．現在に至るまで核兵器使用に慎重な米国の核政策の起源となったと言えよう．

[7]

Leslie R. Groves, Now It Can Be Told, Da
Capo Press, 1962.

[8]

Richard G. Hewlett and Francis Duncan,
Atomic Shield: A History of the United States
Atomic Energy Commission, Volume II, 19471952, University of California Press, 1990.

[9]

Richard G. Hewlett and Oscar E. Anderson,
Jr., The New World: A History of the UnitedStates Atomic Energy Commission, Volume 1,
1939-1946, University of California Press,
1990.

References[16] その他，米国科学者連盟，米国国立公文
書館，米国エネルギー省科学技術情報局
所蔵の公文書.

[1]

山崎正勝他編『原爆はこうして開発された』青木書店，1997 年.

[2]James L. Abrahamson, et. al., Vanguard ofAmerican Atomic Deterrence: The Sandia
Pioneers, 1946-1949, Praeger, 2002.

[3]

AFSWP, “First History of AFSWP 19471954,” 1954.

[4]

Doris M. Condit, The Test of War, 1950-1953,
History of the Office of the Secretary of
Defense, 1988.

[5]

Defense Threat Reduction Agency, Defense's
Nuclear Agency 1947-1997, Defense Threat
Reduction Agency, 2002.

[10] David E. Lilienthal, The Journals of David E.
Lilienthal, Vol. II, The Atomic Energy Years
1945-1950, Harper & Row, 1964.
[11] Kenneth D. Nichols, The Road to Trinity: A
Personal Account of How America's Nuclear
Policies Were Made, William Morrow andCompany, 1987.
[12] Steven L. Rearden, The Formative Years,
1947-1950, Office of the Secretary of Defense,
1984.
[13] Alice K. Smith, A Peril and A Hope, The
Scientists' Movement in America: 1945-47,
The University of Chicago Press, 1965.
[14] Jessica Wang, American Science in an Age ofAnxiety: Scientists, Anticommunism, and theCold War, University of North Carolina, 1999.
[15] The Development of an Atomic Weapons
Program following World War II, Dennis
Merrill ed., The Documentary History of the
Truman Presidency, University Publicationsof America,1998, Volume 21

460

第二次世界大戦終結後の米国における放射能戦の研究開発
栗原岳史**

東京工業大学大学院社会理工学研究科経営工学専攻
t-kuri@me.titech.ac.jp

第二次世界大戦後の米国においてなされた核開発体制の再編成は，核開発に体制
における軍の立場の低下を招いた．軍は，核開発体制における自身の立場を向上させようとした．その一環として，軍は，放射能戦の研究開発を自身の管理下におこうとした．しかし，結局，放射能戦の研究開発における軍の立場は限られたものになった．
1. 序論: 第二次大戦終結後の米国の核開発体
制の再編成
1945 年 8 月に第二次世界大戦が終結すると，原子爆弾を開発するための戦時の臨時組織として設立された陸軍のマンハッタン工兵管区(Manhattan Engineering District, MED)は，その任務を終え解体されることになっていた．
翌年の 1946 年 8 月，戦後の核開発を実施するために原子力法が新たに制定された．その法に も と づ い て 原 子 力 委 員 会 (Atomic Energy
Commission, AEC)が設立され，AEC が MED のす
べての資産を引き継ぐことになった．
原子力法の制定時において，米国議会で原
子力開発における軍の役割をめぐって激しい論争があったことはよく知られている．最終
的に，AEC の最高意志決定機関である 5 人の委員には，すべて文民が就任することになり軍の代表はその委員になれないことになった．
また，すべての核兵器とその部品，すべての核分裂物質，その他原子エネルギーにの生産や研究開発に関するすべての施設，データ，
設計図，特許，契約を AEC が所有することとなった[1][2]．
以上のような MED から AEC への転換という
第二次世界大戦後の新たな核開発体制において，軍の立場はきわめて低下したのであった．
軍はこの状況に満足せず，「巻き返し」を計り，自身の立場の向上させることをめざした．
2. 放射能戦の研究: 核開発体制における軍の「巻き返し」
軍は，AEC設立後も，原子力関連の研究開発に関与し続けることを意図していた．戦時において実際に兵器を使用するのは軍であるから，兵器である原子爆弾を開発する原子力関連の研究開発に，軍は関与し続けることがで461

きると軍は理解していたのであった．MEDの司令官を務めたLeslie R. Groves将軍は，原子力法成立直後の1946年9月，軍の将校を集めて行われた原子力に関する会議において，原爆を含めた「あらゆる新兵器の研究開発を続けることは陸軍の政策である」と主張した．つまり，原子力委員会設立後も，原子力関係の兵器開発に軍が関与し続けることを宣言したのである．この会議は，戦時中を通じて機密とされていた原子力に関する知識を軍内部に普及するために，陸軍長官の命令で開催されたものであるので，この見解はGroves個人の見解ではなく，軍指導部の見解であったといえる．
1947年1月，AECがMEDの資産を正式に引き継ぐ と 同 時 に ， 陸 軍 と 海 軍 は 共 同 で Armed
Forces Special Weapons Project(AFSWP)を設立した．AFSWPは，軍内部の原子力に関するす
べての事柄の責任を負うことになった．AFSWPの初代責任者には，MED司令官のGroves将軍が任命された．Grovesは，戦争終結後も軍の原子力開発の責任を担うことになったのである．
AFSWPの主な任務は次の通りであった．
1) 原爆組み立て施設の管理と運営．それに必要な人員の訓練や機器の開発．
2) 核兵器のもつ能力や影響の調査や研究．
3) 放射能戦の研究．
1) は，精密機械である原子爆弾の部品を使用できる状態で保管し，その使用時に速やかに組み立てて，爆弾を投下する空軍に引き渡すことである．そして，原爆の保管と組み立てに必要な，原子力に関する専門的で高度な技能をもつ軍の人員の訓練が行われた． 2) は，核兵器のもつ破壊力の能力や効果を調査し，戦闘に対する核兵器の能力を明らかにすることである．3) は，原子炉で生成される放射能た，Crossroad作戦と呼ばれる南太平洋における原爆実験において，艦船に対する放射線の影響とその防御方法について調査していた．
それらの経験から，米国は本格的に攻撃用の放射能戦の研究に取り組む必要があると，Hamiltonは考えたのであった．
1947年7月30日，軍全体の研究開発計画を調整することを任務とする国防省研究開発委員会(Research and Development Board, RDB)2が人体に対する放射線許容量の調査をAFSWPが行うことを要請した(JRDB 92/1)．同日，RDBは放射能戦の研究をAFSWPが行うことを勧告した(JRDB 88/4)．
RDBの委員長は，第2次大戦期の米国の科学動員を統括した科学研究開発局(The Officeof Research and Development, OSRD) の 局 長
3. AFSWPと放射能戦の研究体制を務めた文民行政官のVannevar Bushであった．
原子炉で生成される放射性物質散布し，特RDBの下には各種の小委員会が設置され，個別定の地域やそこにいる人間を汚染することをの研究開発活動の調整を行ったが，そのうち，目的とした放射能戦(Radiological Warfare)
放射能戦を含む原子力関係の研究開発を担当の研究は，戦時中の原爆の研究・開発の初期
す る 原 子 力 委 員 会 (Committee of Atomic
においても行われていた．しかし，原爆開発
Energy, CAE)の委員長には，Bushとともに戦に重点がおかれるようになると，攻撃用の放時の科学動員を指導した，James B. Conantが射能戦の研究よりも，ドイツが放射能戦を行就任していた．BushとConantは，ともにMEDのったことに備えるための防御方法の研究に重最高政策委員会のメンバーであり，MED全体を点が移された．戦場において放射性物質を検指揮する立場にあった．またBushとConantは，出する部隊の養成や，人体に対する放射線の1
原子力法の制定時における議会の論争におい影響が研究された ．ドイツの食料を放射性物ても，AECに軍の代表が参加できるようにする
質で汚染することも提案されたが，実戦でのことを支持していた．つまり，BushとConant
使用を真剣に検討された形跡はない．
は，原子力開発対する軍の立場を強めるとい攻撃用の放射能戦の研究は，第二次大戦終結後に本格的に開始された．1946年12月31日， う，軍の立場を支持していたのであった．戦争が終結しMEDが閉鎖された後にっも，Bushとマンハッタン工兵管区(MED)の科学者Joseph
Conantは，共に協力して，Grovesの指揮下にHamilton 博 士 は ， MED の 副 司 令 官 Kenneth
あるAFSWPが，放射能戦の研究を行うことを決Nichols大佐に手紙を書き，放射性物質を，都定したのであった．
市や都市への食糧供給に対する戦略的兵器と
1947年9月，AFSWPに放射能戦の研究を実施
して使用できると提案した．Hamiltonは，そするために，放射線防護部門が新たに設置さの年の6月にMEDの最後の任務として実施されれた．放射線防護部門の任務は，を帯びた核物質を散布し，特定の地域やそこにいる人間を放射能で汚染させることを目的とした放射能戦の研究である．原子力法の規定に従えば，これらはすべて本来AECが行うはずの任務であったので，AFSWPの任務はAECからしばしば批判された．
これらのAFSWPの活動を通じて，軍は，低下した核開発体制における軍の役割を再び増大させ，核開発における自身の立場の向上をめざしたのであった．
以下，本稿では，AFSWPを通じた第二次大戦後の核開発体制における軍の活動において，放射能戦の研究体制に焦点をあてて論じる．
原爆の保管と組み立てに関するAFSWPの活動については，別の機会に譲りたい．

1

2

人体に放射性物質を直接埋め込む人体実験がRDBは，1946年に陸軍と海軍の合同で設立されなされていたことが1990年代に明らかになった．文た，陸軍海軍合同研究開発委員会(Joint Research

献[3]参照．当時のクリントン大統領の命令により，and Development Board, JRDB)を前身とする組織

放射線人体実験の大規模な調査が実施され，マである．1947年に国家安全保障法が制定され，空ンハッタン計画から現在までの核開発に関連する

軍と国防省が設立されると，JRDBに空軍が加わり，文書が大量に情報公開された．本研究は，そのとRDBと改称された．混乱を避けるため，本稿では，

きに公開された文書に多くを依拠している．

国防省研究開発委員会(RDB)で統一する．

462

おり，それゆえ，軍も研究開発に関与するのは当然であると反論した．原子力法において，大統領が原子兵器の使用が必要だと判断した
とき，大統領はAECに対して兵器を軍に移管することを指示すると書かれている．軍はこの規定にもとづき，原子力に関する研究開発にも軍は関与できると主張した．
放射能戦の研究を実施するために，科学者のパネルをAECと軍の合同で設置することになった．そのパネルの性格をめぐりAECと軍は対立 し た ． 1947 年 10 月 14 日 ， AEC 委 員 長 David
Lilienthalは，軍に対して，放射能戦の実現
可能性を研究する科学者パネルを設置し，軍代表がこのパネルに参加することを提案した．
翌 11 月 17 日 ， 軍 が AEC に 返 答 し ， AEC の 方 が
AFSWPの放射能戦パネルに参加することを提案した．1948年2月2日，AECと軍の合同会議が開催され，科学者パネルの設置について議論がなされた．AECは，AECが設置する科学者のパネルに軍が助言者として参加することを主張した．AECの主張に対して，軍は軍が実施する研究にAECが助言するような研究組織とすることを主張した．つまり，AECと軍は，それぞれ自身の組織が放射能戦の研究を主導することを主張したのであった．結局，科学者のパネルは設置するが，放射能戦の研究はAECと軍の双方がそれぞれ個別に実施することになった．
1948年8月31日，AECと軍の会議が開催された．この会議の結論にもとづき，放射能戦の研究における軍(AFSWP)の責任が次のように明4. 放射能戦の研究におけるAECと軍の主導権確にされた．
争い(1) 軍は，放射能戦の散布手段の開発の主要
原子力に関するすべての研究・開発は，AECな責任を負う．
が行うと原子力法に明記されている．放射性(2) 軍は，防御手段，検出手段，汚染除去手
物質を軍事的に利用する放射能戦に関しても，段の開発の主要な責任を負う．
原 子 力 法 の Sec. 3 (A) 3 に お い て ， AEC は(3) AECは，放射性物質の生産，や生物学的，「軍事目的の...核分裂物質と放射性物質の利
医学的観点に関する計画全体の主要な責任を用...に関する研究開発活動を実施する」責任追う．
を負うとされている．この原子力法の規定に
つまり，軍は放射能戦の散布手段，防御手
もとづいて，放射能戦の研究におけるAFSWPを段，検出手段，汚染除去手段の開発に責任を通じた軍の活動をAECは批判した．
負うことになった．人体に対する放射線の影
それに対して，軍は，原子力法でも実際に響に関する研究は，AECが行うことになった．
兵器を使用するのは軍であることを明記してまた，AECは放射性物質の生産の責任を負うこととなった．
軍は，放射能戦の研究における自身の役割
3
日本の被爆者たちから収集されたデータが攻撃が制限されるとしてこの役割分担を批判した．
用の放射能戦の研究に利用されていたことは，筆この会議に出席したMcCormack将軍は，この役
割分担に対して，「この修正では軍の責任が者による調査で初めて明らかになった．
1) 原子爆弾のさまざまな影響を評価すること，
2) 放射線防護のために使用される装置の研究開発計画を評価すること，
3) 放能戦の可能性の諸研究を行うこと，とされた．
軍は，AFSWPの放射能戦の研究のために，広島や長崎の被爆者たちから集めたデータを利用した．1948年6月16日，国防省の統合参謀本部(Joint Chiefs of Staff, JCS)は，被爆者たちから収集したデータが，「現在の放射能戦の研究にとって重要な情報をAFSWPに与えるだろう．特に，長期間にわたる実際的な被害者の扱いの観点に加えて，放射線汚染物質の攻撃的使用から予想される被害者に関する情報を与える」と述べ，被爆者のデータをAFSWPの放射能戦の研究に利用すること指示している．米国が終戦直後から日本の被爆者たちを調査し，様々な医学的データを収集していた．
軍は，これらのデータを放射能戦の研究にも利用したのであった3．
軍における放射能戦の研究・開発は，AFSWP
によって行われることとなった．それを主導したのは，戦時中の原爆開発を指揮する立場にあり，戦後の核開発体制において軍が重要な役割を果たすべきだと考えていた，Bush，
Conant，Grovesであった．彼らに主導されて，軍における放射能戦の研究・開発体制が整えられていったのである．

463

に辿ると，決して見かけのような盤石なものではなく，多くの内部対立を含んだ脆弱さを持った体制であったのである．

制限される」と述べている．
しかし，最終的にこのような責任分担となることで，軍とAECの双方が合意した．
5. 結論
第2次世界大戦終結後の米国において，核開発体制が再編され，文民管理の原子力委員が設置された．その結果，核開発における軍の立場が弱まった．
軍は核関連の研究開発に関与し続けた．そうすることで，核開発における軍の立場の向上を目指したのであった．その中で，軍は，
AFSWPに放射能戦の研究開発をすすめさせた．
AECと軍は，放射能戦の研究開発体制の主導権をめぐって争った．最終的に，放射能戦の研究における軍の役割は制限されることとなった．
その後，攻撃用の放射能戦の研究や大規模な野外演習が実施された．しかし，1950年代
半ば以降，放射能戦の研究が攻撃用から防御用に重点が移されるようになり，大規模な攻撃用の放射能戦の演習も行われなくなった．
その理由はまだ明らかにされていない4．
本稿を作成するまでに十分に資料を分析できなかったので論じることができなかったが，放射能戦の研究開発体制をめぐるAECと軍の争
いは，単なる管轄権争いではなく，原子力兵器に対する両者の認識の違いがあったと筆者
は考えている．軍は，原爆を単なる兵器の一つと見なしていたのに対して，AECは原爆を特
別は兵器とみなしており，できる限りその使用を控えるべきだと考えていたのであった 5．
この原爆に対する認識の違いが，放射能戦の研究開発体制をめぐるAECと軍の対立にも現れていたと筆者は考えているが，この論証は次の機会に行いたい．
冷戦期の米国の核開発体制は盤石なものとのように見える．しかし，その起源を歴史的

4

放射能戦の研究が防御手段中心となった事に対して，米国の公式文書は，朝鮮戦争後の国防費の削減を理由の一つに挙げているが，理由は明らかではないとしている．文献[3]参照．
5

たとえば，拙稿「第二次世界大戦終結後の米国における核開発体制の再編成―文民と軍と対立―」2007年4月提出SIMOT報告書を参照．

464

References[1]

Alice K. Smith, A Peril and A Hope, The
Scientists' Movement in America: 1945-47,
The University of Chicago Press, 1965

[2]

Richard G. Hewlett and Oscar E. Anderson,
Jr., The New World: A History of the UnitedStates Atomic Energy Commission, Volume 1,
1939-1946, University of California Press,
1990

[3]

United States Advisory Committee on Human
Radiation Experiments, Final Report of theAdvisory Committee on Human Radiation
Experiments, Oxford University Press, 1996

[4]

Adri De La Bruheze, "Radiological Weapons
and Radioactive Waste in the United States:
Insiders' and Outsiders' View," The British
Journal for the History of Science 25(1992),
207-217.

[5]

Allan A. Needell, Science, Cold War and theAmerican State: Lloyd V. Berkner and theBalance of Professional Ideals Harwood
Academic Pub (2000)[6]

First History of AFSWP 1947-1954, Volume
1, 1947-1948[7]

その他，米国国立公文書館所蔵の国防省研究開発委員会文書，原子力委員会文書，
AFSWP 文 書 ， 米 国 エ ネ ル ギ ー 省 所 蔵 のOpenNet 文書

第二次世界大戦後の米国における研究開発体制の再編成― ヴァネヴァー・ブッシュと国防省研究開発委員会 ―栗原岳史 Takeshi Kurihara**東京工業大学大学院社会理工学研究科
経営工学専攻技術構造分析講座
t-kuri@me.titech.ac.jp
第二次世界大戦が終結した後，米国の研究開発体制が大きく改革され，政府が研究開
発の大規模な支援をするようになった．戦時中の科学動員を指導したヴァネバー・ブッシュ(Vannevar Bush)は，国防省研究開発委員会(Reseach and Development Board)を設立し，民間で行われる最新の科学研究と，新兵器の開発を結びつけるために奮闘した．Bush の活
動は，軍指導部から歓迎された一方で，軍が科学を支配するとして批判するものも多かった．
1. 序論
第二次世界大戦が終結した後，米国の研究開
発体制が大きく改革され，政府が研究開発の大規模な支援をするようになった．特に軍部は，戦時中の科学動員を指導した Vannevar Bush と共に，民間科学者と協力して新兵器の研究開発を行う体制を構築した．本研究は，1946 年設置された国防省
研究開発委員会(Reseach and Development Board,
RDB)に着目し，それに関わる Bush の活動を通じて，第二次大戦後の米国の研究開発体制の再編期の過程における矛盾や対立を明らかにする．
Bush に関する先行研究の多くは，Bush が局長を務め，第二次大戦期の科学動員を統轄した科学研究開発局(The Office of Scientific Researchand Development, OSRD)と，大戦後に設立された
全米科学財団(National Science Foundation, NSF)に着目している．NSF の公史を含め，NSF の起源
は Bush が 1946 年 に 発 表 し た Science: The
Endless Frontier であり，NSF を OSRD の後継組
織としみなしていおり，軍の研究開発委員会に言及した歴史研究はほとんどない．また，Bush とOSRD についての論じたものは多数あるが，そのほとんどは科学と政府の関係について論じており，Bush と戦後の軍事研究体制については多くを論じられていない[7][8][15]．
軍の研究開発委員会(RDB)に関する本格的な歴史研究としては，米国のスミソニアン協会のAllan A. Needell の研究があげられる．Needell は，
RDB の初代事務局長を務めた Lloyd V. Berknerの伝記を通じて，シヴィリアン科学者と軍を結びつけるための RDB の活動を明らかにした．Needell
は，レーダーなどの研究開発を行った電子機器開発小委員会に特に注目し，戦後の研究開発体制における RDB の重要性を指摘した[10]．Needellの研究は，Berkner の関わった電子機器開発と軍の関係に焦点が当てられており，RDB の全体像を明らかにしたものではない．
2. Bushと軍事研究
Bushが政府機関に関わるようになったきっかけ
は，そもそも兵器開発であった．Bushは，第一次大465

戦期にドイツの潜水艦を探知するための装置を開発し，軍にそれを採用することを働きかけた．しかし，この装置は実際に使用されることなく終戦を迎えた．Bushは，軍が民間の科学者と兵器開発を結びつけるための体制が整っていなかったために，重要なアイデアが生かされなかったと考えた．そして，民間の科学者が強い権限を持って軍の兵器開発に関与する必要性をBushは痛感したのであった．[3]
1930年代になると，欧州とアジアで新たな世界
戦争の危機が起こった．Bushは，第一次大戦期のようなことを繰り返さないために政府に働きかけ，その結果，1940年に科学者を責任者とする国防研究委員会(National Defense Research Committee,
NDRC)の設立に結実した．NDRCは，1941年にOSRDに改組され，大学で行われている最新の科学研究と兵器開発を結びつけるための組織として，
第二次大戦期の科学動員を指導した．OSRDは大統領直属の機関であり，また，独自の予算を執行できるため，強力な権限を持った．Bushの指揮するOSRDは，全国の民間の大学や産業界と研究契約を交わすことでシヴィリアン科学者を軍事研究に動員し，レーダー，近接信管，原子爆弾を開発した．
Bushの関わった軍事研究と民間の科学研究を
結 び つ け た 機 関は， OSRDだけではなかった．
1942 年 ， 統 合 参 謀 本 部 (JCS) の 下 に ， Joint
CommissiononNew
WeaponsandEquipment(JNW)が設置され，Bushが委員長に就任した．JNWは，陸軍長官のHenry Stimsonが，新兵器の研究開発に関して，陸軍と海軍の活動とシヴィリアンのそれを合同させる必要性を考え設置された軍の機関である．軍内部の機関であったが，委員長をシヴィリアンのBushが勤め，軍の代表が委員を勤めるシヴィリアンと軍人で構成される組織であった．JNWは，兵器システムの，戦略計画と戦争努力に対する新しい兵器システムの効果を評価し，それに関する陸海軍間の調整をおこなった．
軍の組織であったJNWは，大統領直属の組織であったOSRDとは独立に運営された．Bushは後に，
JNWはOSRDと同様に "(innovations)革新的" な組織であったと高く評価している．[3][10][12]2. 終戦と研究開発体制の再編
OSRD は戦時の臨時組織であったので，戦争が終結すると閉鎖されることになっていた．Bush
は，戦後も民間の大学などで行われている科学の研究に対する政府の支援を継続させることが必要だと考えた．
Bush は ， 1945 年 に 大 統 領 に 提 出 し た
Science: The Endless Frontier [1]において，科学研究を支援するための政府機関の設立を勧告した．
この機関は基礎研究，国防研究，医学研究部門を持つことを想定していた．すぐに議会に法案が提出され，その審議の過程で，この機関は全米科学財団(National Science Foundation, NSF)と呼ばれるようになった．
NSF を設立するための法案は，1950 年に議会を通過した．当初の Bush の構想と異なり，NSF
は基礎研究だけを支援する政府機関となった[9]．
戦時中から戦後にかけての Bush の経歴や著
作，公的発言を見る限り Bush の主要な関心が軍事研究にあったことは明らかである．Bush と政府機関との関係は，そもそも軍の兵器開発と大学な
どの民間の科学研究をむすびつけることで始まっており，戦時中の OSRD 局長としての活動も兵器開発のためであった．戦後も，多くの著作を通じて，Bush は最新の科学研究を利用した新兵器の開発の必要性を訴え続けた．
Bush は，戦争終結前後から激しくなった米国とソ連の対立に強い危機感を抱いていた．米国の「自由」や「民主主義」を，ソ連の「共産主義」の脅
威から守るためには，最新の科学の研究を用いた強力な新兵器の開発が不可欠だと考えていた．この危機感が，民間の研究機関と軍事研究を結び付けようとする Bush の原動力だったのである．軍事研究への Bush の関心は戦争終結で終わることなく，戦後の研究開発体制の再編における主要な関心事であった[2][3][4][5][13][14]．
3. 国防省研究開発委員会の設立
1946 年 6 月，陸軍長官と海軍長官の合同で
統 合 研 究 開 発 委 員 会 (Joint Research andDevelopment Board, JRDB)が設立された．JRDBのチャーターにおいて，JRDB の任務は，陸軍と海軍が行うすべての研究開発活動を調整(coordinate)するとされた．JRDB 委員長はシヴィリ
アンで，その他，陸軍と海軍から 2 人ずつの代表で構成されることになった．委員長には，JNW のと引き続き，Bush が任命された．1946 年 6 月 27 日，
JRDB の設立がトルーマン大統領に承認された．
JRDB は，JNW から人員や文書を引き継いだ．また，JRDB は，OSRD からも文書と人員をひきついだ．少なくとも事務的には，OSRD の後継組織はNSF ではなく JRDB だったといえる．
1947 年に国家安全保障法が成立し，陸軍と海軍が統合され，新たに設立された国防省の下に置かれることになった．JRDB も， "Joint" が取れ，研究開発委員会(Research and Development Board,

466RDB)となり，統合参謀本部(JCS)の下から離れ，国防長官直属の組織となった．[11][16]
RDB の任務は，国家安全保障に関する科学
研究に状況について国防長官に助言し，安全保障に関する科学上の問題に関する研究開発のために適切な準備を保証することされた．RDB の主要な任務は次のように定められた．
1. 統合された軍事研究開発計画を準備する．
2. 国家安全保障に関する科学研究の傾向と，一定の進歩を保証するための諸段階について国防長官に助言する．
3. 軍の間の研究開発を調整(coodinate)し，統合計画の責任を割り当てる．
4. 国防省の政策を立案する．
5. 研究開発と戦略の相互作用を検証し，それについて JCS に助言する．[11] [16]
RDB は，傘下に多くの小委員会やサブパネル
やワーキング・グループを設置し，それらの活動を通じて，各分野の研究開発活動を行った．RDB の設立当初において，次の 12 の小委員会が設置され た ． Ad Hoc Committee on Scientific andSynthetic Analysis, 航空委員会，原子力委員会，
基礎物理科学委員会，電子委員会，誘導ミサイル
委員会，人的資源委員会，医科学委員会，航海委員会，軍需委員会，生物化学兵器委員会，地球物理科学と地理学探査委員会．各小委員会の委員長もシヴィリアン科学者が任命され，委員は科学者と軍人で構成された．[11] [16]
軍は Bush と共に，戦後も民間の科学者と協力して戦時中のように軍事に関する研究開発活動を行うための体制を構築したのであった．
4. Bush の軍事研究体制の構想
1947 年 4 月，大統領科学委員会の John R.
Steelman への手紙で，Bush は軍事研究における基礎研究と兵器開発の関連について述べている．
Bush は，この手紙は個人的な見解と断っているが，
JRDB 内部で手紙内容が検討されており，事実上，JRDB 委員長としての立場で書かれていると思われる． Bush は，「兵器開発のステップとして」基礎
研究，開発，生産の段階を区別している．まず，大学など民間の研究機関で行われる基礎研究(basic
research) を お き ， そ の 次 に 応 用 研 究 (appliedresearch)，初期開発(primary development)おき，の つ ぎ に 「 工 学 的 開 発 評 価 (engineeringdevelopment and evaluation)」があるとした．「工学的開発評価」とは，「軍が使用するための明確な手段である生産の準備を提供する」ことだとしている．
Bush は，これらの諸段階のバランスが重要だと指摘した．Bush は，戦時中にはこれらのステップの後半に重点が置かれていたが，戦争の終わった平時には，前半の基礎研究も重視しなければならないと述べた1．
1Bush to Steelman, "Draft of Final Letter," April 4,
1947, Box 93, Folder 2144: President's Scientific
Research Board, 1946-1947, Bush Papers, LibraryBush は，基礎研究と兵器開発を結びつけることが重要であると考え，研究開発をいくつかのプロセスに分け，それぞれ適切な支援が必要だと考えていたのであった．
5. NSF と国防省研究開発委員会
Bush は，NSF が設立されれば，JRDB の基礎
研究活動を NSF に移管すると周囲に述べていた．
Bush は ， 1946 年 12 月 23 日 に 共 和 党 のAlexander Smith 上院議員に対して，「軍は，NSFが軌道に乗れば，これを放棄するつもりであると私は確信している」2と述べている．Smith 上院議員はBush の NSF 法案を支持する有力な議員で，Bushと共に NSF 法の実現のために活動していた．
しかし同時に，Bush は，NSF が設立しても軍は基礎研究活動を継続するべきだとも述べていた．
前述の 1947 年 4 月 4 日に大統領科学委員会委
員長の John R. Steelman に対して，Bush は NSF
設立後も軍は基礎研究を実施するべきと主張した．
その理由として，軍事的に重要だが科学者たちが関心をもたない基礎研究の分野があること，軍が最新の基礎科学の動向を知るために重要であるとした．ただし軍が実施，もしくは支援する基礎研究の規模を大きくしないとも Bush は述べていた3．
Bush は，JRDB の創設がシヴィリアン科学と軍の間のつながりを促進したとして高く評価している．
そして，議会で審議されている NSF 法案と JRDBの関係について，軍事研究と NSF と結び付けることを期待していた．前述の 1946 年 12 月 23 日に共和党の Alexander Smith 上院議員への手紙において，「提案されたシンプルな NSF の構造の結果，軍事研究が NSF とより密接に結びつけられるであろう」と述べている．ここで，「シンプルな NSFの構造」とは，自身の構想に従った NSF のことを指している．Bush は，JRDB と NSF が，民間の科学者の研究活動と軍事研究を結びつけることを期待していたのであった．
NSF が軍事研究に関わることについて，当時の有力な民間の科学者の団体であった米国科学者連盟(Federation of American Scientists)が，科学が軍に支配されるとして批判する活動を展開していた．米国科学者連盟の代表的な活動家であった
物理学者の Philip Morrison は，戦時中の科学動員で軍の管理下にあった科学研究の活動を，NSFが「動員解除」させることを主張していた．つまり，NSF が軍の影響を受けないようにすることを主著していた．
of Congress
2
Bush to Alexander Smith, Dec. 23, 1946, Box 87,
Folder 1912: National Science Foundation (Dec.
1946) General, Bush papers, Library of Congress
3
Bush to Steelman, "Draft of Final Letter," April 4,
1947, Box 93, Folder 2144: President's Scientific
Research Board, 1946-1947, Bush Papers, Libraryof Congress

米 国 科 学 者 連 盟 の 物 理 学 者 の Edward
Condon は，Bush の構想に従った NSF 法案では，NSF が軍に支配されると非難していた．Bush の構
想では，NSF 自体は直接軍の管理を受けるのではなく，科学者で構成される運営委員会によって運営される機関であったが，Condon をはじめ，当時の多くの人々は，そのようには理解していなかった．Bush は戦時動員を指揮した人物であると同時に，戦後も民間の科学研究を軍事研究のために利用することを構想し，そのために行動していたことは当時の Bush の発言や，公的な行動からも明らかであった．そのような Bush の構想では，民間の科学研究活動が，戦時中のように軍の強い支配下に置かれると，Condon らは批判していたのであった．[14]Bush は，このような科学者たちの批判に苦慮していた．Bush が，JRDB など軍の基礎研究活動を
NSF に移管すると発言していたのは，軍が科学を支配しようとしているという批判を打ち消すためであった．Bush は，海軍長官の Forrestal に対して，軍が支援する基礎研究を NSF に移管することを歓迎する声明を出すこを要請した．その中で，Bush は，海軍長官と陸軍長官が，NSF が基礎研究に対する政府の支援を引き継ぐことを歓迎する
明確な声明を出すこと．そのような声明が，軍が科学を支配しようとしているというおしゃべりを静めることができると考える．原子力法案における文民管理と軍管理の対立のような馬鹿げた議論を避けるべきである．NSF 法の進展にとって，そのような声明は大きな助けとなるであろう4．
と述べた 5 ．Bush が基礎研究を支援する活動を
NSF に移管するとしたのは，RDB など軍が軍が科学を支配しようとしているという批判を打ち消すためであった．実際，NSF が設立されても，RDB から基礎研究部門がなくなることはなく，軍による基礎研究活動は継続した．
6. 結論
RDB の活動は，これまでほとんど注目されてきたことがなかった．しかし，戦後の研究開発体制を構築した Vannevar Bush にとって，国防省の研究開発委員会は，民間の科学者と軍事研究を結びつけるための重要な組織であった．
これまで，戦後の Bush の活動について，「科学と国家」「科学の自由と政府」といった，ひろく一
4Bush to Forrestal, Dec. 11, 1946, Box 87, Folder
1912: National Science Foundation (Mar. - Dec.
1947) General, Bush Papers, Library of Congress
5
陸軍と海軍の長官が実際にそのような声明を出したということは，筆者は現時点で確認できていない．

467

般的な課題について述べられることが多かったが，
Bush の公的活動や発言から，Bush の主要な関心
が，兵器開発と最新の科学を結びつけることにあったことは明らかである．
Bush の活動は，当時の科学者たちから，科学を軍が支配されるとして批判されており，Bush はそれらの対策に苦慮し，軍事研究と基礎研究を見か
け上切り離すように見せかけようとした．
筆者は，国防省研究開発委員会による具体的な研究活動の内容について，資料を収集，および分析している最中である．基礎研究から実用的な兵器に至るまでのプロセスを，具体的な研究プロ
ジェクトに焦点を当て明らかにすることを今後の課題としている．また，原子力委員会(Atomic Energy
Commission, AEC)や NSF など，研究開発に関わる他の政府機関とどのように役割分担をしてきたのか，同時にその過程においてどのような対立や矛盾を孕んできたのかを調査する予定である．
References[1]

Vannevar Bush,
Frontier (1945)

Science:The[2]

Vannevar Bush, Modern Arms and Free Men(Simon and Schuster, 1949)[3]

Vannevar Bush, Pieces of the Action (William
Morrow and Company, 1970)[4]

Vannevar Bush, Endless Horizons (1946)[5]

Vannevar Bush, "Science and National
Defense," Science 94(Dec., 1941): 571-574.

[6]

Vannevar Bush, Science: The Endless
Frontier, National Science Foundation 40th
Anniversary, 1950-1990 (NSF, 1990)[7]

Merton J. England, A Patron for Pure Science,
The National Science Foundation's Formative
Years, 1945-57 (National Science Foundation,
1982)

[8]

Daniel J. Kevles, "The National Science
Foundation and the Debate over Postwar
Research Policy,1942-1945," Isis 68(1977), 526.

[9]栗原岳史「全米科学財団の非軍事的性格と米国科学者連盟―米合衆国における科学研
究支援体制をめぐる論争: 1945-1950 年」『科学史研究』第 42 巻(2004 年): 140-148 頁[11] Steven L. Rearden, The Formative Years,
1947-1950 (Historical Office, Office of theSecretary of Defense, 1984)[12] James F. Schnabel, The Joint Chiefs of Staffand National Policy 1945-1947, History of the
Joint Chiefs of Staff, Volume I (Office of Joint
History Office of the Chairman of the Joint
Chiefs of Staff: Washington DC., 1996)[13] 歌田明弘『科学大国アメリカは原爆投下によって生まれた: 巨大プロジェクトで国を変えた男』平凡社，2005 年[14] Jessica Wang, American Science in an Age ofAnxiety: Scientists, Anticommunism, and theCold War (University of North Carolina Press,
1999)[15] G. Pascal Zachary, Endless Frontier:
Vannevar Bush, Engineer of the American
Century (MIT Press, 1999)[16] 米合衆国公文書館 Record Group(RG) 330,
Entry 341: Office of Securetary Defense,
Research and Development Board

Endless[17] 米合衆国議会図書館 Manuscript Division,
Vannevar Bush 文書[10] Allan A. Needell, Science, Cold War and theAmerican State: Lloyd V. Berkner and theBalance of Professional Ideals (Harwood
Academic, in association with the National
Air and Space Museum, Smithsonian
Institution, 2000)

468

第二次大戦後の米国における研究開発体制の再構築―冷戦期米国のインスティテューションにおける軍と科学者の共生と対立―
栗原 岳史(KURIHARA, Takeshi) **技術構造分析講座 山崎研究室
東京工業大学大学院社会理工学研究科経営工学専攻
kurihara.t.ab@m.titech.ac.jp
本研究が明らかにしたことは，冷戦期の米国の研究開発体制に関するインスティ
テューションの主要な特徴は軍と大学の民間科学者との共生関係であったが，決してそれだけではなく，両者の間には対立があり，その対立が第二次大戦終結後の米国の研究開発体制の再構築の過程に影響を及ぼしていたことである．
1. 序論
冷戦期の米国の研究開発体制に関するインスティテューションの特徴は，軍と大学の共生関係である．このことは，政府支出の研究開発費の約半数を国防省によって占められていたことによって象徴的に示されている．民間の大学に国防省の予算が投入されて多くの研究所が設置され，新兵器の研究開発活動にとって不可欠なものとなってきた．大学の民間科学者たちにとっても，国防省からの研究
支援は自身の研究をすすめるために不可欠な場合が多かった[3][4]．
しかし，軍と大学の関係は，決して友好なものだけではなかった．民間科学者の中には，軍と協力することに批判的な者も存在した．
本研究はそのような批判的な科学者たちに注目する．そして，第二次大戦期から冷戦初期の米国における研究開発体制の再構築の課
程を，米国の公文書館や議会図書館の所蔵する文書資料[1][2]を利用して歴史的に分析し，米国のインスティテューションに包含された軍と民間科学者の対立軸を明らかにする．
2. 第二次大戦期の科学動員: 軍と科学者の共生と対立の萌芽12.1 科学動員体制と OSRD
第二次大戦期に米国は，民間科学者を動員
し，レーダーや原子爆弾など，最新の科学を応用した新兵器の研究開発を行った．この研究開発活動は科学動員と呼ばれている．科学
動員を統轄したのは，政府機関の科学研究開発 局 (The Office of Scientific Research andDevelopment, OSRD)であった．OSRD の局長を務めたのは，民間(civilian, 文民ともいう)の科学者出身で，MIT の教授，副学長を務め，ワシントン DC のカーネギー研究所の所長を務めていた Vennevar Bush であった．
OSRD は兵器の研究開発を統轄する機関であったが，民間の科学者出身の行政官と軍人で構成された OSRD の指導部は民間科学者が1

拙稿「第二次世界大戦期における科学動員と科学者－米国の原爆開発の場合－」SIMOT RA
Report, Vol.1, Fall 2005

469

多数を占め，局長も文民であったことから，文民主導の組織であった．OSRD は自身の研究所を持たず，大学などの民間の研究機関と研究契約を結ぶことで兵器開発活動を統轄した．OSRD は大統領直属であり，独自に予算を執行できる権限をもっていた，強力な権限をもった機関であった2．
OSRD は，軍と大学などに所属する民間の科学者を結びつける仲介者の役割を果たしたといえる．OSRD は，冷戦期における軍と大学の共生関係の基礎を生み出したのであった．
OSRD は戦争の趨勢に大きな影響を与えたレーダーや原子爆弾の開発に成功し，軍指導部から高い評価を受けた．軍指導部は，戦後も民間科学者と協力して新兵器の研究開発を行うことが必要であると考えるようになった．
2.2 原子爆弾開発と MED
原子爆弾の研究開発は，1941 年に Bush の指導の下で基礎的な研究が開始され，開発・生産の段階になると，1942 年に陸軍が新たに設立 し た マ ン ハ ッ タ ン 工 兵 管 区 (Manhattan
Enginerring District, MED)に移管され，軍の管理下で行われるようになった．
Bush は，MED の最高意思決定機関である「最高政策グループ」と，後に設置された「軍事政策委員会」の一員として，MED の最高位の地位にありつづけ，軍と協力して科学者を管理する側に立ち続けた．
OSRD のように，多くの民間の科学者たち
が MED に参加したが，彼らは軍の指揮命令系
統とは区別され，軍籍を持たずに研究開発に従事した．科学者たちは，ドイツが米国よりも先に原爆を開発することを恐れ，日夜献身的に研究開発に取り組んだ．
しかし，軍管理の研究開発に対する民間科
学者の不満もあった．研究の情報は区分化され，戦争の趨勢に関する重要な情報も科学者
2

このOSRDの特徴は，第二次大戦期の日本における生物戦兵器の研究開発体制も共通点が多い．
拙稿「第二次世界大戦期における科学動員の国際比較－軍と大学の共生関係－」SIMOT RA
Report, vol. 2, no. 1, Spring 2006

に与えられず，科学者たちは原爆開発に必要な研究活動だけを行うことを強いられた．たとえば，ドイツの原爆開発がほとんど進展していなかったことや，日本がソ連を仲介して終戦を模索していることを軍指導部は知っていたが，研究に対する熱意が冷めることを恐れた軍指導部は，研究に従事する科学者たちにそれらのことを知らせなかった．
MED での研究開発活動に従事した多くの科学者たちは，軍による研究管理に不信を持つようになった．軍に対する科学者の不信は，
戦後の研究開発体制の再構築の過程で表面化することになった．
3 戦後の研究開発体制の再構築: 民間科学者と軍の対立の表面化
3.1 原子力委員会(AEC)をめぐる対立
戦争が終結すると，MED の民間科学者たちが中心となって，米国科学者連盟(Federation ofAmerican Scientists, FAS)が結成された FAS は，
原子力の国際管理を主張し，そのためには，
原子力の研究開発を管理する組織として新たに設立されることになっていた原子力委員会(Atomic Energy Commission, AEC)を文民管理(civilian control)にするべきだと主張した．
FAS に参加した科学者の多くは，原爆が使用された広島や長崎の実態を知ったことで，原爆の使用に対して批判的になっていた．今後原爆が安易に使用されないようにするためには，1 国が原爆を保有するのではなく，原爆を含む原子力の研究開発全体を国際管理の下におくべきだと FAS は主張した．そして，そのためには，原爆を単なる兵器の一つと考えている軍に原子力を任せることはできないと考えるようになっていたのである．
FAS は，軍の代表が AEC の委員になることを強く批判し，積極的にロビー活動を展開したり，雑誌などで世論に訴えた．
FAS の科学者たちは，OSRD 指導部の Bushらに批判的であった．Bush が，OSRD や MEDにおける軍の協力を賞賛しており，軍の代表が AEC の委員になることを積極的に支持していたからである．
FAS の主張は議会や世論に大きな影響力をもち，最終的に 1946 年に原子力法が制定され
AEC が設立されると，軍人が AEC の委員になれないこととなった．
FAS の活動は原子力にとどまらず，科学研
究活動全体に広がり，科学と軍の関係をめぐり積極的に活動した．
3.2 全米科学財団(NSF)をめぐる対立
1945 年 7 月，OSRD 局長の Bush は，大統領宛に報告書，Science: The Endless Frontier を提出した．Bush はこの報告書で，戦後も政府が科学の研究開発活動を支援するべきだと主張し，戦時の科学動員を統括した OSRD の後継
組 織 と し て ， 全 米 科 学 財 団 (National Science
Foundation, NSF)を設立することを提唱した．

470

この報告書において，NSF は基礎研究を支援するだけでなく，国防研究部門を設置することになっていた．国防研究部門は軍の代表と民間学者で構成され，軍の行う新兵器に関する研究開発活動を管理することとなっていた．Bush は，OSRD に統轄されたした戦時の科学動員のように，NSF の下で，軍と民間科学者が協力して軍事研究開発を行うことを構想していたのであった．
軍もまた，Bush の構想する NSF を支持した．
軍は，NSF を通じて民間科学者と協力して軍事研究開発活動に取り組む体制を構築することを期待した．
NSF の運営形態をめぐり議会で論争が続いていたが，軍は大学など民間の研究機関で行われている研究活動に多額の資金を提供するようになった．その額は，1947 年の段階で，全国の大学の物理学の研究費の 8 割を軍の資金が占めるまでになった．FAS の科学者たち
は，このままでは科学が軍に支配されると考えた．
Bush の構想した NSF は文民管理の機関であったが，FAS の科学者たちは，Bush の構想した NSF では科学が軍に支配されると考えた．
FAS の科学者たちは NSF を，戦時中に軍に動員されていた研究活動を動員解除し，科学を軍の管理から解放するための機関とすることを主張した．
そのような科学者たちの批判に対し，Bushと軍の指導部は，NSF が設立されたら軍の支援する基礎研究活動を NSF に移管すると主張
し，科学者たちの批判を抑えようとした．
しかし結局，1950 年に制定された NSF 法によって設立した NSF からは，当初の Bush の構想にあった国防研究部門がなくなった．
戦後，大学などの民間の研究機関に多額の軍の資金が流入するようになり，その後の軍と大学の共生関係の基礎となったことは事実である．しかし，戦後の研究開発体制の再構
築の過程の歴史を分析すると，そのような軍と科学者の共生関係だけではなかったことが明らかとなる．AEC の委員に軍の代表がなれなくなったことや，NSF から国防研究部門がなくなったことに示されるように，一部の批判的な民間科学者と軍の対立もまた，戦後の研究開発体制の再構築の過程で生じたのであった．
4 戦後の研究開発体制の再構築: 軍の巻き返しの始まり
4.1 原子力研究開発における軍の活動と AEC33

拙稿「第二次世界大戦期の科学動員の歴史研
究－戦後の米国における核開発体制の転換－」
SIMOT RA Report, vol. 2, no. 2, Fall 2006；同「第二次世界大戦終結後の米国における核開発体制の再編成－文民と軍と対立－」SIMOT RA Report,
vol. 3, no. 1, Spring 2007；同「第二次世界大戦終MED で原子爆弾の研究開発，爆弾の保管，爆弾の組み立てを行ったのは民間科学者たちであった．戦争が終結すると，彼らのほとん
どは MED を離れ，元の職場や，新しい職場に帰っていった．また，FAS の活動に示される
ように，軍が原子力に関する研究開発活動を管理することに批判的な科学者が多く現われれいた．
軍は，原子爆弾の管理を，民間科学者の手を借りることなく軍自身の手で行えるようにすることを目指した．1947 年 1 月 1 日，大統
領指令で AEC が MED の資産を引き継くと同時に，軍は陸軍と海軍の両長官直属の組織とし て AFSWP(Armed Forces Special Weapons
Project)を設立した．AFSWP の任務は，原子力に関する軍のすべての任務を担うことで，爆弾の保管やメンテナンス，使用時に速やかに爆弾を組み立てることと，そのために必要な技術開発をすることだった．また，放射線防護に関する研究開発も AFSWP の任務とされた．
1946 年に制定された原子力法では，原子力に関するすべての事柄の責任を AEC が担うことになっていた．しかし軍は，原爆は兵器であるのだから，軍が責任を担うのが当然であると主張して，軍と AEC のどちらが原爆を保管する責任を担うのかをめぐり，AEC と争った．結局，1948 年 7 月の Truman 大統領の決定で，原爆を保管する責任を AEC が担うこととなり，原爆使用時には，大統領が AEC に対して原爆を軍に移管する指令を出すことが明確にされた．軍の要請は完全に通らなかったが，原爆使用に関する責任を担うことが明確にされたことで，それまで曖昧だった軍の活動が正当化された．
AFSWP は，陸海空軍の原爆を扱う部隊の養成をおこない，1948 年の末までに必要な装置の開発や，必要な規模の原爆部隊の養成を完了した．軍は，AFSWP の活動によって，民間科学者の手を借りることなく，原爆の保管や組み立てを行えるようになったのである．
放 射 性 物 質 を 利 用 し た 戦 闘 (Radiological
Warfare)に関する研究開発を行う責任は，原子力法では AEC が担うことになっていた．しかし軍は，軍が主導して RW の研究開発を行うべきだと主張し，AFSWP がその任務を担った．
AEC と軍は RW の研究開発の主導権をめぐり争った．1948 年 10 月までに，放射線の人体への影響に関する研究は AEC が担うことになったが放射性物質の散布方法や，爆弾や弾頭の研究開発を軍が担うこととなった．
原爆の保管や放射能戦の研究開発おける軍と AEC の間の任務の分担をめぐる対立の背景には，原子力の認識に関する意見の対立があった．軍は原爆や放射能戦兵器を「単なる兵器の一つ "just another weapon"」にすぎないと結後の米国における放射能戦の研究開発」
SIMOT RA Report, vol. 3, no. 2, Fall 2007

471

みなしており，これをいつでも使用できるよ
うにすることをめざしていた．それに対して
AEC は，これらの兵器は単なる兵器ではなく，米国の安全が危機でない限り，できる限り使用しないようにするべきだと考えていたのである．
核兵器開発において，主要な研究開発の責
任は AEC が担うことになったが，軍は，実際にそれを兵器として使用することに関して，
AEC や民間の科学者たちの手助けなしで，軍が責任を担えるような体制を構築したのであった．
4.2 国防省研究開発委員会の活動と NSF4
1946 年 6 月，OSRD による戦時の科学動員を高く評価した軍は，陸軍と海軍の両長官直属 の 組 織として，統合研究開発委員会(Joint
Research and Development Board, JRDB)を設立した．研究開発委員会の任務は，軍による研究開発活動を調整することだった．JRDB の委員長には，OSRD 局長を務めた Bush が任命された．
研究開発委員会は 3 人の民間科学者と陸海軍の代表それぞれ 2 名ずつで構成された．つまり，文民が指導部の過半数を占めた OSRDとは異なり，軍人が指導部の過半数を占める
軍優位の体制だった．
1947 年に国家安全保障法が制定され，国防省と空軍が設立されると，JRDB に空軍の代表
も 加 わ り ， 研 究 開 発 委 員 会 (Research andDevelopment Board, RDB)となった．
研究開発委員会は，下部組織として基礎物
理科学，原子力，化学戦，生物戦，電子機器，
誘導ミサイルなどの研究開発活動を担当する
各種小委員会が設置され，それぞれ民間科学者と軍の代表で構成された．軍は，軍独自で民間科学者と協力して兵器に関する研究開発を行う体制を構築したのであった．
RDB の原子力委員会(Committee on Atomic
Energy, CAE)は，AFSWP の上位の機関として，
RW の研究開発を AFSWP が行うことを指令した組織であった．
議会において，基礎研究を支援する政府機関として NSF を設立するための法案についての議論が続いていた一方で，陸軍と空軍は，NSF が設立されたら，軍の支援している基礎研究を NSF へ移管するべきと主張していた．
それに対して，海軍は NSF が設立されても軍に基礎研究の支援を継続すること，また，NSFとは別に，軍の研究所でも基礎研究を行うことを主張していた．RDB は，軍内部の基礎研究に関する意見の違いの調整を要請された．
国防研究部門のなくなった NSF 法の成立がほぼ決定した 1950 年 2 月，RDB の基礎物理科
4「第二次世界大戦後の米国における研究開発体
制の再編成－ヴァネヴァー・ブッシュと国防省
研究開発委員会－」SIMOT RA Report, vol. 4, no.
1, Spring 2008

学委員会(Committee on Basic Physical Sciences,
CBPS)は，NSF が設立されても，軍による基礎研究活動を支援する活動を継続することを決定した(PS 29/2)．この決定は，1951 年 1 月 17日に研究開発委員会に承認された(RDB 173/9)．
この決定に従って，軍による基礎研究活動の支援は NSF の設立後も継続することとなった．
この RDB の決定によって，軍は NSF に頼らなくとも，それまで継続していた民間科学
研究活動への支援や，自身に必要な基礎研究活動を継続するようになった．
5 結論
本稿は，米国のインスティテューションの
底流に潜む対立軸の一つを明らかにした．第二次大戦期の科学動員政策を起源とし，終戦後に再構築された米国の研究開発体制において，軍と大学の民間科学者との共生関係が成立したと同時に，軍に批判的な一部の民間科学者たちと軍の間の対立軸も成立したのであった．
AEC の委員に軍の代表がなれなくなったことや，NSF から国防研究部門がなくなったことは，この軍と民間科学者との対立の結果だ
った．
軍は，原子力や基礎研究の分野で AEC や
NSF だけに頼らずに，独自に民間科学者と協力して研究開発活動を行うことをめざした．
軍が大学の民間科学者に研究資金を提供することに加えて，RDB を設立し，民間の科学者と協力して研究開発を行う体制を構築した．
また，軍は AFSWP を設立し，原爆の保管や組み立て，RW の研究開発など，本来 AEC の民間科学者が行う原子力に関する軍事活動の一部を，軍の人員だけでおこなえるようにした．
軍に批判的な科学者と軍との対立は，冷戦期を通じて，その後もしばしば表面化してきた．たとえば，1950 年代の放射性降下物の危険性をめぐる論争，1963 年の部分核実験禁止
条約，現代までつづくミサイル防衛の有効性をめぐる論争など，軍事技術に関する論争がなされたとき，軍に対して批判的な科学者が批判的な議論を展開してきた．その結果，軍事技術の研究開発を含む米国の科学行政が，大きく転換されたことも少なくなかった．
本稿で論じた軍と批判的な科学者との対立
は，米国のインスティテューションの底流として，21 世紀にも脈々と受け継がれている．
References∗[1]

米合衆国公文書館文書群[1c] AEC 文書 RG 326: Records of the Atomic
Energy Commission, 1923-75 (AEC)[2] 米合衆国議会図書館, Manuscript Division,
Vannevar Bush 文書[3] Paul Forman, "Behind Quantum Electronics:
National Security as Basis for PhysicalResearch in the United States, 1940-1960,"
HSPS 18:1(1987), 149-229.
[4] Daniel J Kevles, "Cold War and Hot Physics:
Science, Security, and the American State,
1945-56," HSPS 20:2(1990), 239-264.
[5] Merton J. England, A Patron for Pure Science,
The National Science Foundation's Formative
Years, 1945-57 (NSF, 1982)[6] Steven L. Rearden, The Formative Years, 19471950 (Historical Office, Office of the Secretaryof Defense, 1984)[7] 栗原岳史「全米科学財団の非軍事的性格と米国科学者連盟―米合衆国における科学研
究支援体制をめぐる論争: 1945-1950 年」『科学史研究』第 42 巻(2004 年): 140-148頁[8] Jessica Wang, American Science in an Age ofAnxiety: Scientists, Anticommunism, and theCold War (University of North Carolina Press,
1999)[9] Alice K. Smith, A Peril and A Hope, The
Scientists' Movement in America: 1945-47 (The
University of Chicago Press, 1965)[10] Richard G. Hewlett and Oscar E. Anderson, Jr.,The New World: A History of the United States
Atomic Energy Commission, Volume 1, 19391946 (University of California Press, 1990)[11] AFSWP, “First History of AFSWP 19471954,” 1954
[12] Doris M. Condit, The Test of War, 1950-1953(History of the Office of the Secretary of
Defense, 1988)[13] Defense Threat Reduction Agency, Defense's
Nuclear Agency 1947-1997 (DTRA, 2002)[1a] RDB 文書 Record Group(RG) 330, Entry 341:
Office of Securetary Defense, Research andDevelopment Board∗[1b] AFSWP 文 書 RG 374: Records of the
Defense Threat Reduction Agency, 1943-73[14] Richard G. Hewlett and Francis Duncan,
Atomic Shield: A History of the United States
Atomic Energy Commission, Volume II, 19471952 (University of California Press, 1990)

主要な文献資料のみ掲載した．

472

「場のマネジメント論」検討－インスティテューショナル技術経営学的観点から
葉山

雅*

*

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-406 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANmiyabi@me.titech.ac.jp
インスティテューションの類似概念とみなしうる「場」の概念に注目して「場のマネジメント論」の検討を行ない、そのインスティテューション技術経営学に貢献するところを抽出した。組織を情報的相互作用の束としてとらえ、その作用プロセスをマネジメントするとする「場のマネジメント論」の組織観は、インスティテューショ
ンのイノベーションとの共進を解明する上で有効であるものと考えられる。

1. 序論
本報告は、「インスティテューション」の“文化的共同体における規範的性格“に注目し、社会科学におけるインスティテューションの類似概念を検討することによってインスティテューショナル技術経営学（以下、SIMOT）の理論的基盤を考察しようとする立場に基づく研究の一環にあたる。
これまでの研究においては、インスティテューションの類似概念として、特に T.Kuhn によるパラダイム論の「パラダイム」をとりあげ、インスティテューションの変容のしくみをパラダイム・チェンジと比較して説明することを試みており、歴史的事例としては「電子計算機の発明と実用化」を題材に検討を行ったが、その中で SIMOT に対して以下のような示唆が得られた：・インスティテューションの動的な変化そのものを適切に記述する論理は何かといった問題が提起される。
そこで、このような問題提起についての答えを探るために、伊丹敬之による「場のマネジメント論」をとりあげてインスティテュー
ションの類似概念としてみなすことのできる「場」の概念の検討を行ったが、ここでは、その結果得られた「場のマネジメント論」がSIMOT の理論的基盤の形成に貢献するところについて報告する。

2. 「場のマネジメント論」
この章では「場のマネジメント論」を概観する。
2.1 場の定義
・イノベーションとインスティテューション
まず『場のマネジメント論 －経営の新パの共進を可能にする技術育成の要因としては、ラダイム』（伊丹敬之、NTT 出版、1999 年）
創造的発想を現実的問題へ応用しようとするによれば、場の定義は、以下のようにまとめ
着想と、それに基づく理論的基盤の整備およられる。
び工学的実現とがあげられる。
・人々が参加し、意識・無意識のうちに相互に観察し、コミュニケーションを行い、相互に理解し、相互に働きかけ合い、共通の体験をする、その状況の枠組み（前掲書 p.23）

・理論的基盤の整備と工学的実現を担う者はそれぞれ、認識論的に異なる文脈におかれている可能性がある。
そしてこのことからは、・人々の間の情報的相互作用の容れもの（前掲書 p.23）

・インスティテューションの変容はインスティテューション内部からはどのように認識さ
れるのか
473

・そこに参加するメンバーが次の四つの「場の基本要素」をある程度以上に共有することによって、さまざまな様式による密度の高い
情報的相互作用が継続的に生まれうるような状況的枠組みのことをいう

情報的相互作用は、「共通理解、整合性ある意思決定」といった思考に関することがらと、「心理的共振、心理的エネルギー」なる
心に関することがらとに分けて説明される。
「共通理解、整合性ある意思決定」は、人々がそれぞれにもっている情報の総和の中に何らかの秩序が生まれ、各人の情報集合の共通度・整合度が高くなることによって生じるとされる。
一方、「心理的共振、心理的エネルギー」とは、情報のやりとりによって生じ、人々を行動に向かわしめる働きをもつものとして説明されている。
これらより成る情報的相互作用がよく活用された例としては、「本田技研工業における第設備投資と大部屋役員室の設置」「セブンイレブンジャパンの毎週会議」等があげられていた。

A アジェンダ（情報は何に関するものか）B 解釈コード（情報はどう解釈すべきか）
C 情報のキャリアー（情報を伝えている媒体）
D 連帯欲求（前掲書 p.41）
2.2 組織の場と経営組織における場と経営との関係は、図 1 のよ
うにあらわされる。企業は「組織の業績」を目的として「経営の手段、設計変数」を定めるが、それは「場」を基盤とする目には見えない「情報的相互作用」の過程を経て、業績を生む「事業行動と学習活動」に結びつくものとされている。

2.3 ミクロマクロループ「場」が機能し、情報的相互作用において「共通理解」「心理的エネルギー」等が生じるメカニズムは、「ミクロマクロループ」によって説明される。ミクロマクロループとは、
図 2 に示される、場のメンバーという「個」と場の「全体」とを結ぶフィードバックルー
プのことである。
外部から扱われるべき情報がもたらされた
後、「人々の個別の理解」から周囲の共感者
同士の相互作用を経て「ローカルな共通理解の形成・心理的共振」がもたらされ、さらにそれを全体的なものに統合しようとする努力によって「全体の有力な共通理解の台頭・全体での心理的共振」が生じるとされる。この結果はさかのぼって「人々の個別の理解」へ
フィードバックして影響を与え、このようなループがまわっているうちに、情報に対する「全体の共通理解という秩序への収斂」「全体の心理的エネルギーの発生」がおこるものと説明されている。
なお、このミクロマクロループにおける個と全体の関係性のあり方は、生命関係学（清水博）に基づいて提唱されたものである。

組織の業績

事業行動と学習活動

整合性ある意思決定

心理的エネルギー

共通理解

心理的共振

情報的相互作用場

経営の手段、設計変数（戦略、組織構造、管理システ
ム、インセンティブシステム、経営理念、リーダーシップなど）

2.4 「場のマネジメント論」の組織観
ミクロマクロループに表現されるような、個と全体の相互作用のプロセスを重要視する「場のマネジメント論」は、組織を「意思決定する個人の集合体」とみなす近代組織観と図 1 組織の場と経営.
出典：前掲書 p.21 に基づき葉山が作成．

474

は異なる組織観に立っている。つまり、「場3.1 疑問点のマネジメント論」においては、組織は「情まず、情報的相互作用については思考に関
報的相互作用の束」としてとらえられている。 することがらと心に関することがらとを分けて説明がなされていたが、前掲書においては
特に心理的問題について比喩的表現が散見され、問題の扱い方が科学的であるとはいえな
外部からのいのでないかという疑問が生じる。
シグナル受信ミクロマクロループについても、生命科学の分野では妥当であるにせよ、それを社会科学に応用した場合のモデルとして適切である
かどうかについては、さらなる分析の余地が人々の個別の理解あると考えられる。
全体から個人へのフ
周囲の共感者とのまた前掲書においてとりあげられたケース
ィードバック
相互作用
ミクロマクロは「場のマネジメント論」の妥当性を説明すループ
るものではあったが、「場のマネジメント
・ローカルな論」の意義を真に値踏みするためには、論を・有力な全体の共通理解の形成
体の共通理解の反証しうるケース等を含めてより多様なケー・ローカルな台頭
スを用いての検討がなされるべきと思われる。
心理的共振
・全体での心理的共振
総じて、「場のマネジメント論」は、SIMOT の目標、すなわちインスティテューシ
ョンとイノベーションとの共進ダイナミズム
全体での統合努力の「解明」および「可視化・操作化」、をかんがみると、理論的基盤が脆弱である印象が持たれた。
・全体の共通理解という秩序への収斂・全体の心理的エネルギーの発生

3.2 評価できる点「場のマネジメント論」における「場」は、SIMOT 的観点においては、SIMOT で扱うインスティテューション、なかでもとりわけ「企業組織・風土」に対応していると見ることができよう。「場のマネジメント論」は、インスティテューションを情報的相互作用の「場」ととらえることによって、インスティ
テューションの構成要因の内的な動きを強調しえた考え方だということができる。
また組織を情報的相互作用の束としてとらえ、その作用プロセスをマネジメントするという観点は、SIMOT の探ろうとする望ましい
技術経営において有効なのではないかと考えられる。
ミクロマクロループについても、さらに概念理解の深化をはかる必要があるにせよ、経営学の分野において、個と全体に関するモデルを提出したという意味では評価できるのではないかと思われる。

図2
ミクロマクロループ
出典：前掲書 p.83 に基づき葉山が作成．

そしてそのため、「場のマネジメント論」における経営行動の焦点は、「情報的相互作用の生じる場を生成し、方向性を与えること」にあてられることになる。
こうした「場のマネジメント論」は、技術基盤が社会に浸透し技術変革を担うのは個人
ではなくグループである現代の社会に適切な経営のあり方を示すことを意図したものである。つまり、組織の「構造」ではなく、組織内部の作用の「プロセス」を扱おうとするところが「場のマネジメント論」の特徴的な点となっている。

3. 「場のマネジメント論」の検討
この章では、前章で見た「場のマネジメント論」についての検討を行う。

3.3 心理的問題と社会科学の論理について
3.1 で指摘したように、「場のマネジメント
論」は心理的表現が多用された説となってお475

り、科学的・合理的議論によって検討・批判できる場合が少ないものであるように見受けられるが、このような問題は、K.ポパーによって提唱された「状況論理」を用いて解決をはかることができるものと考えられる。「状況論理」とは、人間の行動を十分に分析することによって客観的な状況として説明し、主観的ないし心理的諸観念による説明を排除しようとする手法である。

ことによって、より有意義な議論の展開が可能になるものと期待される。

主要参考文献[1]アドルノ／ポパー他『社会科学の論理
ドイツ社会科学における実証主義論争』（河出書房出版社、1979[2]伊丹敬之『場のマネジメント論 －経営の新パラダイム』（NTT 出版、1988）…初めのうちは心理学的な要素にみえたもの、たとえば願望、動機、記憶、連想といったものを、状況の要因に変換するに至るまで状況を分析するのである。これこれの願望をもった人は、これこれの客観的な目標を追及するような状況にある人となる。またこれこれの記憶や連想をもつ人は、客観的にこれこれの理論、これこれの情報をあたえられた状
況にある人となるのである。
（アドルノ／ポパー他『社会科学の論理』、
河出書房出版社、1979 年、pp.125-126）[3] 今井賢一･金子郁容『ネットワーク組織論』（岩波書店，1999）[4]小河原誠『現代思想の冒険者たち 第
14 巻 ポパー －批判的合理主義』（講談社，1997）[5]クルト･ レヴィン『社会科学における場の理論』（誠信書房，1956）[6]清水博『生命に情報を読む』（三田出版会、1986）[7]清水博『場の思想』（東京大学出版会、
2003）「場のマネジメント論」においても、状況論
理の方法を導入することによって、心理的な要因をより客観的な要因として扱うことができるようになるのではないだろうか。そしてその際には、心理的要因についてのプロセスを何らかの「情報」についての作用プロセスに帰し、情報的相互作用を「情報」という概念によって一元的に説明することが可能にな
るのではないかと考えられる。

[8] K.Popper, ”The Open Society and its
Enemies” （Routadge，1945）

4. 結論「場のマネジメント論」は、インスティテューション、とりわけ企業組織･風土を、「情報的相互作用の場」としてとらえているものと分析できる。この観点からすると、 組織を
情報的相互作用の束としてとらえ、その作用プロセスをマネジメントしようとする「場のマネジメント論」的組織観は、インスティテューションの変容に際しての内部的変化のあり方について、その解明に示唆するところが大きいものと考えられる。情報的相互作用のプロセスの詳細、特に組織の中での個と全体のあり方についてはさらなる検討を要するものであるが、「情報」を分析の中心にすえる476

科学方法論的観点からのインスティテューション概念検討－平均律の普及を事例として－
葉山

雅*

*

Department of Industrial Engineering and Management
Tokyo Institute of Technology
2-12-1 W9-406 O-okayama, Meguro-ku ,Tokyo, 152-8552 JAPANmiyabi@me.titech.ac.jp「インスティテューション」という語の語源に注目し、特に「人間が設定したものの見方の枠組み」の意である「人的な設定（institutio humana）」という語をとりあげた。そして「社会的制度（institution）」とはそのような人的な設定が社会制度化したものがであると位置付け、『理論上の「人的な設定」が制度化するためにはソフト面のみならずハード面での技術革新を必要とする』という仮説をたてた。さらに、西欧音楽における平均律の普及を分析することによってこの仮説の検証を行った。

1. 序論
1.1 背景「インスティテューション（institution）」という語の語源はラテン語の”institutio”である。”institutio”は、「もはや何かがそこから出られない」という意味をもつ”in-“という接頭辞と、「立つことの原因となる」と意味の”stutiere”という動詞を組み合わせてできた言葉であるが、ここでは特に 8 世紀頃から使用されるようになった科学方法論上の語”institutio-humana”に注目した。”institutiohumana”とは「人間が設定したものの見方の枠
組み、人的な設定」といった意である。そしてさらに、本報告においてはこの人的な設定(institutio-humana)が社会制度･規範として定着したものが”institution”であると位置づけた。
人的な設定(institutio-humana)の例としては、
例えば、音楽における「音律」があげられる。
人間は自然界に無数に存在する音の中から、音楽の構成要素として有限個の音を選び出しさまざまな音階をつくってきた。音律とは、音階を構成するそれぞれの音程を定める約束のことであり、したがって音律は音を把握する上での人的な設定であるといえよう。
1.2 仮説
本報告においてはまず、「人間が自然を把握する為には人的な設定(institutio-humana)が必要である」ということを仮定した。そしてさらに、「理論上の人的な設定は技術的実践との相互作用の過程をへて、社会的制度(institution)」として定着する；設定が社会的制
477

度として定着するためには、ソフトのみならずハード面での技術革新を必要とする」という仮説をたて、西欧音楽における平均律の普及を分析することによって仮説の検証を試みた。

2. 音律の種類
2.1 純正律
純正律とは、自然倍音の系列である純正音
程を組み合わせて、音階の各音の周波数を決定する音律である。例として、古くは紀元前 5
世紀頃に発明されたピタゴラス音律、また 16
世紀のツァルリーノ音律などがあげられる。
純正律の長所としては、自然倍音を基にしているため音階内の音程間に協和感があるということがあげられるが、一方で、転調に不自由であるという短所もあげられる。同じ音名の音でも演奏する調によって異なる周波数を決定しなければならず、特に鍵盤楽器に際しては不便であるとされる。
2.2 不等分平均律
不等分平均律は、純正律の短所を考慮して、音程をなるべく純正に保ちつつ、12 の全ての調を演奏できるように調整されている音律のことである。例としては、16 世紀半ばに考案された中全音律や 17 世紀末のヴェルクマイス
ター音律などがあげられる。不等分平均律は、鍵盤楽器が発達した 17 世紀から 18 世紀にかけてよく用いられた。

2.3 等分平均律
等分平均律とは、1 オクターブを 12 の音に
数学的に等分する音律であり、すなわち、隣り合う音の周波数の比は「1 対 2 の 12 乗根」となっている。そのため、自由な転調が可能であるという長所をもつ一方で、音階内の音
程間に協和感が乏しいという面をももつ。等
分平均律は、19 世紀半ば以降、広く普及するようになったが、現在では社会制度･規範として定着したといえる状況であす。したがって、
等分平均律の使用は社会的制度（institution）の一例であるとみなすことができる。

これはキリスト教が、キリスト教的宇宙観に一元化しえない民間の宇宙観をキリスト教にとりこもうとする運動において、音楽の重要性が認識されたことによる。民間の宇宙観に基づく音をポリフォニーという形でキリスト教の中にとりこもうとしたのであった。そしてその結果 14 世紀には、単旋律の教会音楽を基盤として多声音楽の技法が洗練されることとなった。

3.2 近世多声音楽の発展を受けて、ルネサンス期･バロック期には、同時に多数の弦を奏でることのできるリュートがさかんに使われるようになった。

3. 音律の歴史とピアノの発明
等分平均律が社会的制度化しえた原因としては、ピアノという楽器との関連性が指摘されている。ここでは鍵盤楽器、あるいはピアノの発達を中心に西欧音楽および音律の歴史を検討し、等分平均律の使用が社会制度化した過程を追う。
3.1 中世まで
西欧音楽の源流として遡れるのはキリスト教の発生以降であると言われている。初期キリスト教の音楽はキリスト教が広がるにつれ、
現地の音楽の影響を受けながら発達したものと考えられるが、特に重要なトピックとしては 6 世紀頃にグレゴリオ聖歌がローマ・カト
リック教会公式の音楽と定められたことがあげられる。これは教会が宗教儀式の様式を統一しようとした試みの一環であったが、これ以降西欧音楽はグレゴリオ聖歌を基盤として発達していくことになる。グレゴリオ聖歌は単旋律（モノトニー）の音楽であり、そのような音楽の伴奏としてはモノコードが使用されていた。

図 1 モノコード
出典：
http://www.pianoprogress.co.jp/history_w.html

しかし、9 世紀頃から多声音楽（ポリフォニー）の必要性が指摘されはじめるようになる。
478

図 2 リュート
出典：
http://www.uenogakuen.ac.jp/data/museum/mu

リュートはコースにそって弦が張られており、中世にヨーロッパヘ伝えられた頃は 4 ま
たは 5 コースであったが、音楽が多声化する
につれて弦の数が増え、17 世紀には 14 コースにまで達する。楽器が大型化するにつれて片手で弦をはじくのは困難となり、リュートに代わって、さらに多くの弦をならすことのできる鍵盤楽器が発達することとなる。その代
表的なものとしては、撥弦楽器であるハープ
シコード、打弦楽器であるクラヴィコードがあげられる。このような鍵盤楽器の発明、改良は近世における技術革新そのものであった。
また音律に関しては、多声音楽の洗練に伴って、16 世紀には平均律が合奏に適しているのではないかと考えられるようになった。1 オ
クターブを等分する方法についてはヨーロッ
パではこの頃から工夫が始まるが、等分平均律の数学的な記述が厳密になされたのは 1636年のことであり、フランスの僧侶、数学者･物理学者でもあったマラン･メルセンヌによると言われている。

といえる。また 18 世紀には平均律の導入された鍵盤楽器を利用した作曲によって、さらに転調の多い和声が発達することとなった。多声音楽と鍵盤楽器とは相互作用的に発達したものと結論づけられる。
3.3 近現代
19 世紀には、市民社会の成立をうけて音楽のあり方にも大きな変化が見られた。音楽の担い手は貴族から市民になり、また場もサロンからコンサートホールへと移行した。これによりピアノにも大音量、きらびやかな音色といった性能が要求されるようになったが、産業革命による金属部品の技術革新によってその実現が可能となり、現代ピアノが誕生したのであった。
図 3 ハープシコードとクラヴィコード
出典：http://www.pianoprogress.co.jp/history_w.html

現代において鍵盤楽器の代表的な位置を占めるピアノは、その原型は 1709 年頃にイタリ
アのクリストフォリによって発明された。当時ハープコードは大きい音を出せるが音の強弱に乏しく、一方でクラヴィコードは音の強弱をつけることはできるが小さい音しか出せなかったので、両者の長所を重ね合わせた楽器として、ハープシコードの弦をハンマーで打つ仕組みが考案され、ピアノが誕生したのであった。

図 4 現代のピアノ
出典：
http://www.bosendorfer-jp.com/

そして 19 世紀後半にはピアノの大量生産が可能となり、この時ピアノメーカーが揃って等分平均律を採用して出荷を行ったことから、
等分平均律が広く普及したと言われている。
これはピアノが素人にとってより調律の困難な大型楽器となったために、都度の頻繁な調律を必要としない等分平均律の利便性が評価されたためと考えられる。
また、この頃から音楽教育の制度化が進みピアノが音楽教育の重要な一端を担う楽器として位置付けられたこと、アップライト型のピアノが実用化され一般市民家庭に普及する
図 3 クリストフォリによるピアノようになったこと、等も等分平均律の一般的出典：使用を確立する大きな要因となった。
http://www.pianoworld.com/gallery/piano_pictu
res2.htm
音楽作品に関しては、19 世紀後半から 20 世
紀初頭にかけて内部転調が頻繁となり調性感
ピアノをはじめとする鍵盤楽器は非常に多の希薄となる傾向がみられ、20 世紀前半にいくの弦を備えており調律に手間がかかるため、 たっては調性の崩壊した音楽が出現するよう曲の調性によって調律の必要のない平均律はになった。こうした作品群は不等分平均律に
鍵盤楽器において特に望まれた音律であった
比べてさらに自由な転調を許す等分平均律を479

また本報告では特に西欧音楽をとりあげたが、世界の歴史的な音律という観点からは、純正律が一般的であり、等分平均律はかなり人工的で特殊な音律であるとみることもできる。他の音楽文化に目を向けることによって、各々の文化的インスティテューションの性格を明らかにすることができるのではないかと考えている。
またさらに長期的な課題としては、科学方法論における他の人的な設定および社会的制度についての研究を行い、現代の学問的方法
論に文化史的位置付けを与えることを目標としている。

志向するものであり、固定的な音律設定のもとで用いられるピアノという楽器の影響を受けて作り出されたといわれている。また一方で、このような作品が等分平均律の普及に拍車をかけたとも考えられる。近現代においてもやはり音楽作品と楽器とは相互作用の関係にあって発達してきたものと推察されよう。
4. 結論
4.1 総括人間は音を把捉するために音律を設定したが、多声音楽と鍵盤楽器とが相互作用的に発達したことをきっかけとして、ピタゴラス音
律に比べより人工的な設定である平均律が 17
世紀に発案された。特に 19 世紀以降、市民社会の成立および産業革命の影響によってより洗練された鍵盤楽器として誕生した現代ピア
ノは等分平均律の採用にたいへん適した楽器であり、等分平均律が広く普及する契機となった。
つまり、等分平均律が社会制度として定着する為には，音楽理論の変化のみならず、鍵盤楽器、特にピアノに関する技術革新が必要であった。したがって、等分平均律という理論上の人的な設定は技術的実践との相互作用の過程をへて、社会的制度(institution)」として定着した、と結論づけることができよう。

主要参考文献[1]阿部謹也、1987．中世賎民の宇宙ッパ原点への旅－、筑摩書房．

–ヨーロ[2]大蔵康義、1999．音と音楽の基礎知識、国書刊行会．
[3]音楽の友社、1954．音楽事典
楽の友社

楽語篇、音

[4]Cohen, H.F., 1984. Quantifying Music, D.Reidel
Publishing Company

4.2 示唆
まず、SIMOT におけるインスティテューシ
ョン概念においても、技術そのものにインス
ティテューションを成立させる重要な役割を見出せるのではないだろうか。
また検討を通して、音楽理論の発達と楽器開発の両方の相互作用のもとで鍵盤楽器の発明がなされたことが確認できたが、理論と技術とが有機的にかみあうところに技術革新が生まれるものと考えられよう。
しかし今日においては、等分平均律の使用が制度として固定化したことによって、現代においては音楽上の理論的発展と技術開発とが相互作用を及ぼしあいにくい状況がもたらされたのではないかという印象ももたれる。
固定的な社会制度とイノベーションとの関係についてさらなる調査検討が必要であるように思われる。
4.3 今後の課題
まず、本報告で示した「社会的制度(institution)」の概念と SIMOT におけるインス
ティテューション概念との関係を考察したい。
そしてさらに、理論的発展と技術開発とが有機的な相互作用のもので成長しうる条件について考えたい。
480

政府主導による研究開発の問題点
テクノスーパーライナーのプロジェクトを例に
加治木 紳哉**

東京工業大学 大学院社会理工学研究科 経営工学専攻 技術構造分析講座 博士課程
s-kajiki@me.titech.ac.jp

運輸省の主導により研究開発が実施された超高速貨物船テクノスーパーライナー
は，開発には成功し，航海実験では目標以上の成果を挙げた．しかし，開発終了後に船価と運航経費の問題が表面化し，意図したような実用化に障壁が発生した．この 2つの問題は実験船の建造前の段階で既に予測されていたが，必要な対策が講じられな
いまま，プロジェクトは遂行されたのである．このような，ある意味無責任とも言える事態が生じるメカニズムは，一体，どのようなものなのだろうか．本稿は，開発の背景から実用化決定までのプロセスを明らかにし，政府主導による研究開発が抱える問題点の一端を解明することを試みる.

た．以下で具体化する時速 50 ノット，貨物積
載量 1000 トンという高度な目標は，キャッチアップからフロントランナーへという研究開発政策の転換が，造船業でも起こったことを示していると言えよう．

１．はじめに
研究開発は，民間企業だけでなく，政府関係の研究機関や，政府主導の下で結成された技術研究組合でも実施されているのは周知であろう．しかし，それらの中には，当事者からは成功とされながらも，その評価の正当性に疑念を抱かざるを得ないものがある．何らかの問題を含んだ研究開発が遂行されていたとすれば，それを指摘するだけでなく，如何なる経緯でそのような研究が開始され，継続されたのかというメカニズムを解明する必要があるのではないだろうか．

２．２ 開発目標の設定
前述の海運造船合理化審議会の意見書を基に，超高速貨物船としてのTSLの研究開発が，1989年度から開始された．開発目標は，技術的に高度であるが，しかし，実現の可能性がありそうな分野に設定されていた．つまり，
TSLのプロジェクトは，シーズ先行の研究開発であった．

本稿では，このような問題意識を基に，運輸省の主導で行われたテクノスーパーライナー（以下では TSL の略称を用いる）の研究開発を分析する．

開発目標の決定を受け，造船大手7社で構成されるTSL技術研究組合が1989年7月に設立された． 1993年度まで5年間の研究では，最初の3年で要素技術の研究，残りの2年で実海域模型船の試験研究を予定していた． この段階
では，具体的な用途までは示されず，開発目
標のみの決定であった．そして，研究開発がプロトタイプによる技術の実証で終わるのか，あるいは実用化を直接目指すのかという点も，明確にはされなかった．

２．研究開発の背景
２．１ 造船業の活性化対策
1973年の石油危機を発端に，わが国の造船業は未曾有の長期不況に突入した．この沈滞した造船業の再建を図るべく，運輸省海運造
船合理化審議会が1988年8月23日に提出した意見書が，「今後の造船対策のあり方について」である．この中では，脆弱化した造船産業の活性化対策の必要性が指摘され，その一環として，技術開発の促進が提示された．この意見書を受け，わが国の造船行政を所管してきた運輸省海上技術安全局を中心に，TSLの研究開発に着手することになった．

３．TSLの具体化
３．１ 検討委員会の設置
研究開発の決定を受け，運輸省や関係団体には，TSL の導入条件を検討するための委員会が設置された．日本造船振興財団は，1989 年から「超高速船の導入の円滑化に関する調査」に着手した．また，運輸省港湾局も「新形式超高速船に対応した港湾の在り方に関する調査」を翌年から実施した．

TSL は，造船技術の高度化と海上輸送の効率化を図ることを目標とし，最終的には，1990
年代後半の実用化が可能であると想定してい481

しかし，日本造船振興財団の調査は，TSL の必要性に的確な判断を下せるはずの海運会社ではなく，荷主を対象としたものであった．また，運輸省
港湾局の調査は，TSL ターミナルの配置を検討するための基礎資料の作成が主たる目的であった．
大変興味深いことに，実用化の障壁として開発終了後に，表面化する船価や運航コストの問題は，
この 2 つの調査でも既に予測されていた．開発目
標を達成すべく，従来型の船舶とは全く異なる技術を搭載することになった TSL が相当高価になることは，容易に予測されたのである．しかし，具体的な解決策は講じられずに，プロジェクトは加速していくことになった．
３．２ 用途の出現
1980 年代後半，このように技術主導で始まった研究開発に，用途が突然出現した．それが，モーダルシフトである．長期不況で低迷する造船業とは対照的に，わが国にはバブル経済の時代が到来した．景気の上昇に伴って国内貨物輸送量が急
激な伸びを示す一方で，労働力不足，交通渋滞の激化，環境問題等が表面化した．これらはトラッ
ク輸送に起因するところが大きく，その解決策として浮上したのがモーダルシフトであった．1990 年
12 月の運輸政策審議会答申を受けて，モーダル
シフトが運輸省全体の取り組みとして実施され，TSL の具体的な用途も決定することになった．
1991 年 6 月の運輸政策審議会答申では，モーダ
ルシフト推進のための基盤整備として，TSL 導入
等の施策を検討することの必要性が指摘された．
また，翌年 3 月の海運造船合理化審議会答申では，内航海運のニューフロンティアとして，TSL の導入による内航貨物輸送の発展方策の検討も求めていた．造船業の活性化策として，海運会社のニーズとは関係なく，シーズ先行でスタートした
TSL の研究開発は，同時代の物流を取り巻く環境によって，その用途が政治的に決定されたのである．

内航海運への投入が政治的に決定された TSLであるが，エンドユーザーとなる海運会社側の認
識は，政治の期待とは大きく異なっており，その実用化を楽観視するものではなかった．TSL の実用化と将来展望について検討を行った井上誠一は，海運業界に TSL に対する懐疑感が漂っていることを指摘している 1．また，内航海運の業界誌『内航海運』（1992 年 12 月号）の中では，「200～300 億円の建造コストをかけて積載量が 1000 トンではかなり運賃負担能力のある貨物を運ぶ必要がある」「なぜ 50 ノットものスピードで走らなければならな
いのか．そのスピードを必要としている貨物があるのか」「TSL の欠点は積荷が 1000 トンと小さいこと．
これだけの積荷に船価 100～200 億円もかけては採算がとれないはず」等の海運会社側の意見が掲載されている．これらの意見から，エンドユーザーとなるはずの海運会社側は，TSL に対して冷めた見方をしていたと言えるだろう．
４． TSL開発の進展
４．１ 輸送システムの具体化
要素技術の確立に続き，1992 年からは TSL の実験船の設計・建造が開始された．そして，運輸省港湾局やシップ・アンド・オーシャン財団（旧日本造船振興財団）も，TSL に対応した荷役装置の研究開発に着手した．また，輸送システムを具体化するための調査も，運輸省によって実施されることになった．運輸政策局の「テクノスーパーライナーを活用した輸送システムに関する調査」と，海上交通局の「テクノスーパーライナーの事業運営シス
テムに関する調査」である．しかし，いずれの調査
も，TSL の導入を前提にしており，TSL が本当に必要かを問う性格のものではなかった．これ以後，総合実験が終了するまで，新たな調査は実施されていない．すなわち，本来のユーザーである海運会社側の懐疑的な声に耳が傾けられることは，ついになかったのである．

３．３ 誘致活動の開始

４．２ 実験船の完成

TSL の用途が具体化すると，自民党の国会議員による TSL 実用化促進議員連盟が，1991 年 10月に結成された．そして，翌月からは，全国各地の自治体が中心となって誘致活動が開始された．つ
まり，実験船の建造（1992 年 4 月開始）によって技術が実証される前から，既に TSL の実用化を前提とした誘致活動が開始されていたことになる．このように，国会議員や地方自治体が積極的に誘致活動を行う輸送技術としては，新幹線が有名である
が，TSL のニックネームは「海の新幹線」であった．
各地域の活動は，研究開発に直接影響を及ぼすような力は持っていない．しかし，細かな潜在的需要を明らかにしたことで，TSL の存在意義を強調する役割を果たしたと言えよう．後述の総合実験では，実験船が全国各地に寄航している．

1994 年に入ると 2 種類の実験船が完成し，いずれの技術成果も，開発目標をほぼ満足するものであった． 石川島播磨重工業，川崎重工業，住友重機械工業，日本鋼管，日立造船の 5 社が研究開発を行った「TSL-F」は，最大速力 41 ノットを記録した．また， 三菱重工業と三井造船が担当した「TSL-A」は，最大速力 54.25 ノットを達成した．
４．３ 総合実験の成果
これらの技術成果を踏まえ，「TSL-A」を用いた総合実験が1995年から開始された．この実験では，
TSLをドア・ツー・ドアの一貫輸送システムの中に組み込む際の諸課題を検討するための基礎デー
タの取得が目的であった．実験の結果，現行の陸上・海上輸送と比べて大幅な時間短縮が可能であることや，荷傷み，荷崩れもなく良好な輸送環境であることが確認された2．

３．４ 異なる認識

482

TSL が開発目標を達成し，高速輸送と荷役装置も計画通りの成果が得られた点を考慮すると，輸送システムの構築に一定の目処が付いたと言えるだろう．なお，事業運営に関する研究は，就航率や燃費の推定，保守整備体制等に必要なデータの取得･解析・評価が目的であり，事業の採算性を調査するものではなかった．

対する競争力を完全に失っていた．

５．問題の表面化

1996 年に TSL 技術研究組合が解散した後も，運輸省内では実用化に向けた方策の検討が続いていた．そして，TSL を救うことになったのは，1999
年 12 月に策定されたミレニアムプロジェクトである．
このプロジェクトによる実用化の決定については，十分な説明がないまま，多額の国費を投入することの是非が，国会でも議論されている 6．しかし，その第一船の用途は，環境問題というミレニアムプロ
ジェクトとの本旨とは直接関係のない，小笠原航路の貨客船であった．そして，2005 年秋の就航に向け，建造の最終段階を迎えていたが，最近になって困難に突き当たっている 7．これまでの経過を見ると，モーダルシフトにせよ，ミレニアムプロジェクトにせよ，TSL は政治に翻弄されてきたことになる．

また，研究開発の途上で積極的に行われていた全国各地の誘致活動も，総合実験の終了後は下火になっていた．その背景としては，バ
ブル経済の崩壊に伴う地域経済の低迷があると考えられる．
５．３ TSL への再注目

５．１ 障壁の出現
1995年度に実施された総合実験をもって，TSLの研究開発は終了した．そして，事業化を支援するための調査委員会が運輸省内に設置された．しかし，この調査により，それまでの動きを完全に停止させる問題が，表面化することになった．
TSL事業化支援調査の目的は，TSL事業に関心のある民間事業者へのヒアリング等を通して，取り組みの状況と，TSL事業に係わる事業推進上の課題を探ることであった．ここで初めて，TSLに対するエンドユーザーのニーズを問うたことになる．

６．プロジェクトの問題点

そして，事業化の課題として，船価と運航経費の問題が浮上した．調査では，TSL（貨物積載量 1000～1600 トン）1 隻の価格を 120 億円，予備エンジン 2 基で 12 億円と予測していた．つまり，最低でも 130 億円前後の初期投資を必要としたことになる．同規模の内航貨
物船（貨物積載量 1300～1800 トン）1 隻の価格が 4 億 5000 万円前後であることを考えると，
いかに高価であるかが分かるだろう 3．また，通常の一般的なフェリーの運航費用に占める
燃料費の割合が 10～15％である点と比較すると，30～40％という TSL の燃料費の数値は非常に大きいものであった 4．この 2 つの問題により，当初意図したような純民間ベースでの事業化は，非常に困難なことが判明した．前述の要素技術の研究段階における調査で指摘された課題と，業界紙で示された海運会社の懸念が，そのまま表面化する形になったと言えよう．
５．２ モーダルシフトの停滞
前述の問題に加え，TSLの具体的な用途を決定する背景となったモーダルシフトも，停滞する状況にあった．運輸政策審議会の答申が意図したようには，物流の効率化が進展しなかったのである．研究開発当初は低かったモーダルシフト化率は，TSLの具体的な用途が決定した1991年には，1987年を上回るレベルにまで回復した．しかし，それ以後は停滞することになった．景気の後退に伴って国内の貨物輸送量が減少する一方で，規制緩和の推進
によって運輸業者の数が増加したことで需給関係が逆転し，業者間の競争が激化したのである5．運賃の下落によって，TSLはトラックに

483

これまで，TSLの研究開発の背景から，実用化決定までの経緯を見てきたが，プロジェク
トの問題点として，明確に指摘出来ることは2つある．
まず1つ目は，このプロジェクトが，エンドユーザーのニーズを考慮しない技術主導型の研究開発であったということである．TSL実用化の最大の障壁は，高い船価と運航コストであった．この問題は，要素技術の研究段階の調査で指摘され，業界紙でも海運会社側の懸念とされていた．しかし，技術研究組合は，一度開発目標を設定すると，途上で認識された問題点をフィードバックする機能を備えていないのである．
問題点の2つ目は，政治の影響である．これまで見てきたように，TSLのプロジェクトは，重要な局面で政治の介入を受けてきた．内航海運へ投入という具体的な用途は，モーダル
シフトの流行によって政治的に決定された．
また， TSLは，「海の新幹線」として着目され，陸の新幹線と同様の積極的な誘致活動が行われた．しかし実際は，陸の新幹線とは，輸送技術としての性格が根本的に異なることは注意を要する．具体的に述べると，陸の新幹線は，開発主体と運行主体が同一（国鉄・JRで設計・運用）であるため，シーズとニーズの溝は最初から存在しない．また，場当たり的だったTSLとは異なり，実用化への道筋は開発当初から既に描かれている．この相違点を考慮せずに，実験船の建造前から誘致活動
によって需要が強調されたことで，技術の実証で終わるのか，実用化を目指すのかが不透明であった研究開発が，完全に後者へ移行し[7]たと考えられる．
７．おわりに以上のことから，TSLの研究開発は，プロトタイプで終了するのか，実用化を目指すのかが不明確なままスタートし，場当たり的に対策が講じられてきたことが明らかになった．
これは，政府主導の研究開発におけるマネジ
メント能力の未熟さを露呈したと言うことが出来よう．また，実用化への具体的なビジョンが欠如しているため，政治の介入を許した，
或いは、政治に頼らざるを得なかったというのが正直なところであろう．
このような事態のもう一つの背景は，わが国がキャッチアップからフロントランナーに立場を変えたこともあろう．キャッチアップ
期であれば，場当たり的なマネジメントでも，目標とする技術は海外に存在した．しかし，フロントランナーになると，場当たり的な対応では，混乱と無駄を引き起こしてしまうのである．
この問題に対処するには，技術のマネジ
メントをフロントランナー型にする必要がある．例えば，開発主体となる官庁の所管を考慮して，技術の実証で終えるのか，実用化まで至るのかという開発目標を明確に設定すべきである．実用化を前提としたプロジェクトに着手する場合，実用化までの明確な道筋を構築することが必要であろう．

References[1]

井上誠一，1991 年「テクノスーパーライナーの実用化と将来展望（下）」『港湾』第 68 巻 8号，p.30-36.

[2]

テクノスーパーライナー技術研究組合，1996
年『テクノスーパーライナー総合実験研究成果報告書』，p.19-22.

[3]

この価格は，海事産業研究所『内航海運コスト分析研究会報告書』2002 年，p.16 による．
そのため，1996 年当時とは若干の変動があることが予想される.

[4]

運輸経済研究センター，1997 年，『平成 8 年
度 テクノスーパーライナー事業化支援調査報告書』，p.92-3.

[5]

内藤靖夫「モーダルシフト推進への課題」『TECHNO MARINE』第 841 号，p.498-501.

[6]

衆議院運輸委員会（平成 12 年 3 月 22 日），
参議院交通・情報通信委員会（平成 12 年 4月 18 日）.

484

2005 年 6 月 5 日の読売新聞朝刊では，「TSL の運航を予定している小笠原海運が，原油高で年間 20 億円の赤字が出ると試算し，国や都に経営支援を求めている」と伝えられた．これに続く，2005 年 6 月 10 日には，朝
日新聞朝刊が「TSL には膨大な赤字が見込まれるのに，約束した国の支援策が示されないとして，運航を予定している小笠原海運が，船舶の保有会社にリース契約の解除通知を送った」と報道した．そして，2005 年 7 月 25
日の読売新聞朝刊では，「115 億円最速船就航断念」という記事が掲載された．また，2005
年 8 月 19 日の日本経済新聞朝刊も，「次世代高速船に暗雲」と報じている.

政府主導による輸送技術開発に関する考察
STOL実験機「飛鳥」とテクノスーパーライナーを例に
加治木 紳哉**

東京工業大学 大学院社会理工学研究科 経営工学専攻 技術構造分析講座 博士課程

s-kajiki@me.titech.ac.jp
本研究は，政府主導の研究開発の中で，技術的には成功したにもかかわらず，実用化の段階で障壁が生じた輸送技術に焦点を当てる．具体的には，科学技術庁航空
宇宙技術研究所（以下，航技研の略称を用いる）の STOL 実験機「飛鳥」，運輸省のTSL 技術研究組合による新形式超高速貨物船テクノスーパーライナー（以下，TSL の略称を用いる）を取り上げる．そして，輸送技術という共通の性格を有した国家プ
ロジェクトを分析・比較することにより，その問題点を考察し，研究開発における政府の役割の検討を行う．

る通商産業省，研究開発を行う科学技術庁の意図
は，2 つの点で一致していた．近距離都市間という
近年，研究開発に対する政府の期待は，ま用途と，国際共同開発を有利に進めるための自主すます高まっている．そのため，社会の様々技術の確保という点である．それまで試験研究にな面で構造改革に伴う「痛み」が生じたにも止まっていた航技研が，実用化に向けた研究開発
かかわらず，研究開発投資だけは拡充が進めに踏み出した背景には，この一致があったと言えるられてきた．だが，過去に実施された政府主だろう．なお，この時期は，航空機の運航・検査を導の研究開発の中には，技術的には成功した
所管する運輸省も STOL 機を推進する立場にあっものの，実用化に結びつかない例も存在する． た．1971 年の運輸省航空審議会の答申では，離そして，その原因は十分に分析されないまま， 島等の空港を中心に，STOL 性を有する航空機の技術的成果のみが強調されている．政府主導就航が可能なように整備することが求められている．
の研究開発は，民間企業では実施が困難な，
しかし，一方で運輸省は，滑走路の延長と周辺環大規模あるいは長期を要する分野に取り組む
境の整備のための空港整備 5 ヵ年計画を 1967 年
ことが本旨である．しかし，多額の国税を投から開始した．これに加え，機材の改良や運航方
入する以上，この状況を放置することも問題
法の改善等の発生源対策にも着手していた．
であろう．
２．２ STOLの具体化と各省庁の認識の変化
本研究は，このような問題意識をもとに，
1975 年 ， 科 学 技 術 庁 航 空 技 術 審 議 会 は ，
政府主導の研究開発の中で，技術的には成功「STOL輸送システムの具体的推進方策についしたにもかかわらず，実用化段階で障壁が生て」の建議を行った．そして，輸送機に加えじた輸送技術に焦点を当てる．具体的には，て，航法，管制・保安，空港等のサブシステ
科学技術庁航空宇宙技術研究所のSTOL実験機
ムからなるSTOL輸送システム技術を確立し，「飛鳥」，運輸省のTSL技術研究組合による新1980年代中期の実用化を見込んでいた．また，
形式超高速貨物船テクノスーパーライナーの
通商産業省は，科学技術庁とSTOL機に関する
1
プロジェクトを取り上げる ．そして，輸送技
認識で一致する一方で，航空機の国際共同開術という性格を共有したプロジェクトを比発という，別のプロジェクトも具体化した．
較・分析することにより，その問題点の考察
1971年，同省航空機工業審議会は，超大型機を行う．
につぐ大型を含む機体を外国メーカーとの国
際共同で行う旨を政府に答申し，その相手と２．STOL実験機「飛鳥」の研究開発
して，アメリカのボーイング社を選定した．
これに加え，1979年と80年の2回に渡って中間
２．１ 背景と各省庁の意図報告を行い，一定規模以上の民間航空機の開1971 年，通商産業省航空機工業審議会，科学発に関しては，技術と販売リスクの分散・軽技術庁航空技術審議会の答申に，そろって STOL
減を図る観点から，国際共同開発を主体とすの文言が出現した．背景には，航空需要の増大，る旨が報告された．
騒音の社会問題化，海外での STOL 機の研究開発の流行があった．また，航空機の生産を所管す
１．研究の背景485

２．３「飛鳥」の挫折

から国際共同開発へ政策をシフトしていく．
そして，「飛鳥」が初飛行に成功した1985年
航技研が研究開発に没頭している間に，運には，国際共同開発への一本化が図られた．
輸省の空港整備 5 ヵ年計画は次々に実施された．「飛鳥」が初飛行に成功した 1985 年には， 結果的に航技研は，STOL機の研究開発のみに終始することになったのである．以上の点か
ほとんどの滑走路が 2000ｍ以上となり，中型
ジェット機まで就航可能な環境になっていた． ら，STOL輸送システム技術の確立と，1980年
一方，ジェット・エンジンの低騒音化技術も， 代中期の実用化という意図にもかかわらず，
実際に航技研が最後まで対応できたのは，大幅な進歩を遂げ，低騒音新型機の導入が促
STOL機の研究開発のみであったことが分かる．
進されたことで，騒音が社会問題化した時代
そのため，「飛鳥」の最終的な評価は，技術の航空機は引退の時期を迎えていた．通商産的成果のみが残されることになった．
業省と科学技術庁が意図した STOL 機を活用する機会は，運輸省独自の行動のために失われまた，飛行試験が終了する1987年に，中部ていたのである．
空港調査会が出した報告書『航空技術の進歩に関する調査』や，飛行試験が終了した年のまた同年には，通商産業省航空機・機械工
毎日新聞（1989年2月28日）における日本エア業審議会が中間報告を提出し，国際共同開発
システム広報部の意見では，技術や経済的なを優先する旨が報告された．これを受けて翌観点から，STOL機に対する懐疑的な意見が述年には，航空機工業振興法が改正され，従来べられている．この2つの意見は，滑走路の延の国産化促進の方向を改め，国際共同開発に長等が進まない状況でSTOL機が当初の技術目
よる航空機工業の振興を図ることになった．
標を満たしても，経済性などを理由に，エア
この時点で，通商産業省と科学技術庁の，ラインが使用しない可能性があったことも示
STOL機に対する研究開発・生産の歩調は完全
唆する．これは，開発した成果を利用するこに崩壊したのである．また，飛行試験で得らとになる側の立場を考慮せず，ユーザー不在
れたデータを基に「飛鳥」の技術を適用したのままプロジェクトを進行させた結果と言え場合を想定した結果，実際にSTOL機が最も効よう．
率よく運用されるのは，コミューター機であることが判明した．この結果をもとに航技研
は，座席数50人のコミューター機の概念設計を行っている．これは，座席数60以下という運輸省のコミューター政策と，ほぼ一致するものであった．しかし，航技研はSTOL機を実用化する手段を持っていなかった．そのため，
当 初 計 画 さ れ て い た STOL 輸 送 シ ス テ ム の 調
査・検討，技術研究は行わず，1991年に全プ
ロジェクトが終了した．1980年代の実用化を目指したプロジェクトは，本懐を果たす事は無かったのである．

以上のことから，この当時の航技研のように技術移転機関や調整機能を持たない組織では，実用化に向けた研究開発を実施することが非常に難しいことが明らかになった．これに加え，開発した成果を利用することになる側の立場を考慮せず，ユーザー不在のままプ
ロジェクトを進行させることの危険性も浮かび上がってきた．

２．４ プロジェクトの問題点

３．１ 研究開発の背景

これまで見てきたように，航技研の活動を中心に置くと，通商産業省と運輸省との連携が機能していれば，STOL機の活躍の場が存在したことになる．しかし，運輸省や通商産業省の政策の変化に対する調整機能を，航技研は持っていなかった．

1973年の石油危機を発端に，わが国の造船業は未曾有の長期不況に突入した．この沈滞した造船業の再建を図るべく，運輸省海運造
船合理化審議会が1988年に提出した意見書を受け，新形式超高速貨物船 TSLの研究開発が実施されることになった．そして，造船大手7社によるTSL技術研究組合が1989年に設立された．なお，この段階では，具体的な用途までは示されず，開発目標のみの決定であった．
そして，研究開発がプロトタイプによる技術の実証で終わるのか，実用化を直接目指すのかという点も，明確にはされなかった．

科学技術庁航空技術審議会は，STOL輸送シ
ステム技術の確立を目指していた．これを，システム工学の概念に当てはめてみると，
STOL輸送システムは，STOL機，空港，空港施設の3つで構成されることになる．しかし，この中で実際に航技研が対応できるのは，STOL機の研究開発のみであった．

２．５ 小結３．新形式超高速船TSLの研究開発

３．２

次に，科学技術庁と通商産業省の関係を振り返ってみよう．STOLの文言が出現した1971
年，研究開発を行う科学技術庁と，開発・生産を行う通商産業省のSTOL機に対する認識は一致していた．しかし，プロジェクトが開始された1975年以降，通商産業省は，自主開発

TSLの具体化研究開発の開始を受け，関係部局や関連団体
は，TSL に関する調査を開始した．大変興味深い
ことに，実用化の障壁としてプロジェクト終了後に，表面化する船価や運航コストの問題は，この 2 つの調査でも既に予測されていた．しかし，具体的な486

解決策は講じられずに，プロジェクトは加速してい
くことになった． そして，このように技術主導で始まった研究開発に，内航海運という用途が出現した．その背景となったのは，1980 年代後半のバブ
ル経済に伴うモーダルシフトの流行である．1991
年 10 月には，自民党の国会議員による TSL 実用化促進議員連盟が結成され，翌月からは，全国各地の自治体が中心となって誘致活動が開始された．
しかし，エンドユーザーとなる海運会社側の認識は，政治の期待とは大きく異なっており，その実用化を楽観視するものではなかった．
３．３

TSL 開発の進展

要素技術の確立に続き，1992 年からは TSL の実験船の設計・建造が開始された．そして，関係部局や関連団体も新たな調査に着手した．しかし，いずれの調査も，TSL の導入を前提にしており，
TSL が本当に必要かを問う性格のものではなかった．これ以後，総合実験が終了するまで，新たな調査は実施されていない．結果的に，最初から最後まで，本来のユーザーである海運会社側の懐疑的な声に耳が傾けられることはなかったのである．
1994 年に入ると 2 種類の実験船が完成し，いずれも，開発目標を満足するものであった．そして，
このうち 1 隻を用いた総合実験が 1995 年から開始され，現行の陸上・海上輸送と比べて大幅な時間短縮が可能であることや，荷傷み，荷崩れもなく良好な輸送環境であることが確認された 2．TSL が開発目標を達成し，高速輸送と荷役装置も計画通りの成果が得られた点を考慮すると，輸送システムの構築に一定の目処が付いたと言えるだろう．
３．４

問題の表面化

1995年度に実施された総合実験をもって，TSLの研究開発は終了した．そして，事業化を支援するための調査委員会が運輸省内に設置された．しかし，この調査により，それまでの動きを完全に停止させる問題が，表面化することになった．具体的には，船価と運航経費の問題である．要素技術の研究段階における調査で指摘された課題と，業界紙で示された海運会社の懸念が，そのまま浮上したと言えよう．また，内向貨物船というTSLの具体的な用途を決定する背景となったモーダルシフ
トも，停滞する状況にあった．しかし，技術研究組合が解散した後も，運輸省内では実用化に向けた検討が続いていた．そして，TSLを復活させる要因になったのは，1999年12月に策定されたミレニアムプロジェクトである．
だが，第一船の用途は，環境問題という本旨とは関係ない，小笠原航路の貨客船であった.
最終的には，2005年秋の就航を予定していたが，現在は，困難に直面している 3 ．これまでの経過を見ると，TSLは政治に翻弄されてきたことになる．

３．５

プロジェクトの問題点

これまでTSLの研究開発を見てきたが，問題点として，明確に指摘出来ることは2つある．
まず1つ目は，このプロジェクトが，エンドユ
ーザーのニーズを考慮しない技術主導型の研究開発であったということである．実用化の最大の障壁は，高い船価と運航コストであった．この問題は，要素技術の研究段階の調査で指摘されていた．しかし，技術研究組合は，一度開発目標を設定すると，途上で認識された問題点をフィードバックする機能を備えていないのである．2つ目は，政治の影響である．
これまで見てきたように，TSLのプロジェクトは，重要な局面で政治の介入を受けてきた．
内航海運へ投入という具体的な用途は，モーダルシフトの流行によって政治的に決定された．また，TSLは，海の新幹線として，陸の新幹線と同様の積極的な誘致活動が行われた．
しかし，陸の新幹線は，TSLとは異なり，実用化への道筋は開発当初から既に描かれている．
この相違点を考慮せずに，実験船の建造前から誘致活動によって需要が強調されたことで，技術の実証で終わるのか，実用化を目指すのかが不透明であった研究開発が，完全に後者へ移行したと考えられる．
３．６

小結

以上のことから，TSL の研究開発は，プロトタイプで終了するのか，実用化を目指すのかが不明確なままスタートし，場当たり的に対策が講じられてきたことが明らかになった．
これは，政府主導の研究開発におけるマネジ
メント能力の未熟さを露呈したと言うことが出来よう．また，実用化への具体的なビジョンが欠如しているため，政治の介入を許した，
或いは、政治に頼らざるを得なかったというのが正直なところであろう．

４．結論
本研究は，政府主導の研究開発の中で，技術的には成功したにもかかわらず，実用化の段階で障壁が生じた輸送技術に焦点を当て，その問題点を考察してきた． 第2節では，航技研のように対応出来る範囲の限られた組織
では，実用化に向けた研究開発を実施することが非常に難しいことが明らかになった．そして，航空機の生産を所管する通商産業省，運航を担当する運輸省の政策は，様々な背景
によって変化したが，これに対応する術を，
航技研は持っていなかった．第3節では，TSL
技術研究組合のように，技術開発に特化した組織が研究開発を行うことの危険性が明らかになった．モーダルシフトの流行を受け，TSLの用途は政治的に決定された．そして，実験船が建造される前から，運航コストや船価の問題が指摘されていたにもかかわらず，これを反映する機能を技術研究組合は有していな
かった．

487

このように，第2節，第3節の分析結果を見ると，実用化の段階で障壁が生じる背景には，所管と組織の2つが存在することが明らかにな[2]
る．「飛鳥」の研究開発では，プロジェクトの途上で，生産を所管する通商産業省，運航を担当する運輸省の政策は大きく変化した．
[3]
これは，もし「飛鳥」の技術が，航空会社あるいは航空機メーカーのニーズと一致しても，実用化を図ることは厳しい状況にあったことを意味する．これに対しTSLは，計画当初の段階から問題点が指摘され，エンドユーザーである海運会社側も懐疑感を抱いていた．それにもかかわらず，研究開発・生産・運航を一括して所管する運輸省は，プロジェクトを続行することが可能であった．このように，シーズとニーズの関係ではなく，省庁の所掌する範囲の差異により，実用化の可否が決定されることになる．また，途上で実施された研究開発評価や，運輸省内に設置された検討委
員会は，導入が所与となっており，その必要性を問い，問題点のフィードバックを行う性格のものではなかった．近年，様々なイノベーションモデルが存在するが，両プロジェク
トは，基礎から応用までの研究が直線的に進行するリニア型のそれであった．フロントラ
ンナー型技術の実用化を目指す場合，技術開発と同時に，如何に受容させるかという視点が重要性を持つはずである．だが，航技研のような国立研究機関や技術研究組合では，それが難しい．その結果が，「飛鳥」やTSLであったと考えられる．以上のことから，政府主導の研究開発で，実用化を直接的に目指すには，社会情勢に加え，所管と研究開発を行う
組織の協調が必要であることが分かる．しかし，それは非常に難しい．この点を考慮すると，輸送技術の研究開発における政府の役割
は，技術的な可能性の確認にあるのではないだろうか．
なお，今後は，国家的プロジェクトとしての輸送技術開発の最大の成功例である東海道新幹線を比較対照に加え，さらに考察を深めていきたい．

References[1]

STOL とは，Short Take Off and Landing（短距離離着陸）の略称である．日本航空広報部『航空実用事典』朝日ソノラマ,1997 年,p. 24 によれば，「STOL の短い滑走距離については，いまのところはっきりした定義はないが，輸送用では長さ 460～550m の滑走路から離着陸が可能であり，滑走を始めてから地上 15m の高度に達するまでの水平距離（離陸距離），およびその高度から接地して完全に停止するまでの水平距離（着陸距離）が，いずれも 610m 以下であることが一般的である．」となっている．これに加え，離着陸時の角度が大きいため，騒音影響

488

域が従来の航空機より小さくなるという利点もある．

テクノスーパーライナー技術研究組合，1996
年『テクノスーパーライナー総合実験研究成果報告書』，p.19-22
2005 年 6 月 5 日の読売新聞朝刊では，「TSL の運航を予定している小笠原海運が，原油高で年間 20 億円の赤字が出ると試算し，国や都に経営支援を求めている」と伝えられた．これに続く，2005 年 6 月 10 日には，朝
日新聞朝刊が「TSL には膨大な赤字が見込まれるのに，約束した国の支援策が示されないとして，運航を予定している小笠原海運が，船舶の保有会社にリース契約の解除通知を送った」と報道した．そして，2005 年 7 月 25
日の読売新聞朝刊では，「115 億円最速船就航断念」という記事が掲載された．また，2005
年 8 月 19 日の日本経済新聞朝刊も，「次世代高速船に暗雲」と報じている．

国家プロジェクトによる輸送技術開発に関する考察
東海道新幹線を例に
加治木 紳哉

東京工業大学 大学院社会理工学研究科 経営工学専攻 技術構造分析講座 博士課程
kajiki.s.aa@m.titech.ac.jp
国家プロジェクトによる輸送技術の開発は，技術的には成功しても実用化には繋がらない，
いわゆる「死の谷」が生じる例が多い．これまで筆者が，その 2 つの例（科学技術庁の短距離離着陸機「飛鳥」，運輸省の超高速貨物船「TSL」）の分析を試みた結果，この背景には，研究開発を実施する組織と，実用化という目標の不一致に原因があるのではないかという仮説を得た．具体的には，①所管省庁と研究開発主体②研究開発主体と運航（運行）主体③研究開発主体と輸送システムの構成要素の 3 つである．そこで，本研究は，国家プ
ロジェクトによる輸送技術開発の中で，技術的にも経営的にも成功した例である東海道新幹線に焦点を当て，前述の 3 つの枠組みから考察する．

車両の増備が計画された．しかし，昭和 30（1955）
年 7 月の実績によれば，１日当りの列車の通過回
数は，大船－平塚間 110 回，静岡－島田間 86 回，であり，特急，急行，準急，普通，さらに貨物列
車と，速度の異なる列車の混合交通のため，増発
余裕はわずかしか残っていなかった．
このような状況に対して国鉄は，昭和 31（1956）
年 5 月 10 日，
本社内に東海道線増強調査会を設置
し，東海道線の将来についての検討を開始した．
これに加え，運輸大臣の諮問機関としての日本国
有鉄道幹線調査会も，昭和 32（1957）年 8 月 30
日に運輸省内に設置された．国鉄に加え，運輸省にも調査会が設置されたのは，巨額の投資を必要とするものであり，単に国鉄内部の問題として考えるだけでなく，全国主要幹線道路の計画など，
国内交通政策に積極的に取り組み始めた政府の交通政策の一環として取り扱うことが妥当と考えられたためである 1．また，これより 1 ヶ月前の 7
月には，東海道新線の調査・計画及びこれに関連する幹線の輸送力増強に関することを専門に所掌するための幹線調査室が，国鉄本社内に発足した．
調査や測量に加え，幹線調査室では東海道新幹線の採算性に関する検討も行われた．後の議論のために補足すると，これまで分析を行った「TSL」
では，運航主体の海運会社側ではなく，研究開発主体である運輸省側が独自に採算性の議論を行っており，両者の乖離の一因になっていた．また，「飛鳥」では，プロジェクト全体を通じて運航会

１．研究の背景
国家プロジェクトとして進められた東海道新幹線の技術的・経営的成功は，航空機や自動車等の影響による斜陽化が危惧されていた鉄道を復権させ，同時に，フランスやドイツ等の高速鉄道技術にも影響を及ぼすことになった．
「高速鉄道」という鉄道のスピード概念を変革させる新しい概念を生み出したという点で，東海道新幹線は，日本が世界に誇ることのできる技術革新として評価されている．そして，「死の谷」は発生していない．
これまで新幹線の成功は，島秀雄技師長の先見性や十河信二総裁のリーダーシップ，鉄道技術と航空技術の融合等によって説明されてきた．これ
らは重要な指摘であるが，本研究では，先の 2 つのプロジェクトの分析において「死の谷」の要因であると仮定された①所管する省庁と研究開発主
体②研究開発主体と運航（運行）主体③研究開発
主体と輸送システムの構成要素の 3 つの枠組みから，このプロジェクトを考察してみよう．
２． 国鉄と東海道新幹線計画
２．１ 新幹線計画の浮上
戦前から東海道線は国の大動脈であり，増え続ける旅客と貨物の需要に対して機能の維持・拡大を図るため，様々な対策が講じられてきた．しかし，戦後も増加の勢いは衰えず，昭和 30（1955）
年より開始された第 1 次 5 カ年計画では，東京－
大船，
平塚－国府津等間の線増や，停車場の改良，489

社側の意見等は考慮されていなかった．これに対し東海道新幹線では，運行主体である国鉄が採算性を意識していたことが分かる.そして，
この計画
を理論や技術の面で支えたのが，付属機関である
鉄道技術研究所であった．
２.２ 鉄道技術研究所の設立と活動
鉄道技術研究所は，明治 40（1907）年 4 月 1 日に創設された帝国鉄道庁鉄道調査所が起源であるが，昭和 24（1949）年に日本国有鉄道が公共企業として誕生すると，
国鉄本社の付属機関になった．
そして，運輸省や国鉄本社内で新幹線についての検討が行われる前から，個人的なレベルではあるが，鉄道の高速化や車両の振動に関する研究も行われていた．また，研究所全体でも，鉄道の高速化に関する研究へのシフトが図られていた．
そして，昭和 32（1957）年は，研究所の創立
50 周年という節目の年であり，一般向けの講演会を開催することになった．同年 5 月に開かれた講演の要旨は，「東京－大阪間に 450～500km の広軌新幹線を建設し，カーブは最小半径 1500m におさえ，車両は軽構造，低重心，空気ばねの電車とし，馬力は 3500～4000 馬力，しかも振動は現在の数分の 1 程度となり，乗心地も現在の電車では創造も出来ない快適なものとなる．
」であった 2．
この時点では，新幹線は計画に過ぎず，鉄道技術研究所も開発を主導する立場にはない．しかし，鉄道の高速化という点で，運行主体である国鉄と研究開発主体である鉄道技術研究所が，同じ方向を向きつつあったという点を指摘しておきたい．
３ 東海道新幹線の建設
３.１ 建設着工の決定
昭和 32（1957）年 8 月に運輸省内に設置された
日本国有鉄道幹線調査会は，同年 11 月に，「東海
道に新規路線を建設する必要があり，かつ輸送の行き詰まりの時期と建設に必要な期間を考慮する
とき，これが着手は喫緊のことであると認む」という中間答申を行った 3．そして，昭和 33（1958）
年 7 月 7 日，各分科会の報告を総合的に審議した
日本国有鉄道幹線調査会は，最終答申を永野護運
輸大臣に提出した．同年 12 月，永野大臣が閣議に報告した答申は，経済企画庁に設置された交通関係閣僚協議会に付議された．同協議会は，新幹線の必要性について，当時建設中であった高速自動車道路と関連して検討を行った結果，「東海道新幹線計画は早期に着工する必要がある」と閣議に報告した．この報告を受けた閣議は，「早期に着工し短期間に完成することが望ましい」として，東海
道新幹線の建設着工を正式に決定した．
３．２ 国鉄本社の対応
昭和 33（1958）年 3 月 27 日，運輸省内に設置された日本国有鉄道幹線調査会の第一分科会が「広軌別線案が妥当である」という結論を出すと，
東海道新線建設の調査・測量ならびに用地や施設の保存・管理を担当させるために，幹線調査室内に幹線調査所（4 月 1 日付）が設けられた 5.続いて，昭和 33（1958）年 4 月には，国鉄本社内に新幹線建設基準調査委員会が設置された 6．
そして，
昭和 33（1958）年 8 月 16 日には，幹線調査所を発展的に廃止し，これに代わる幹線調査事務所が設置され，東海道新幹線の調査，測量，設計，線路用地の保存管理等の活動を開始した．また，翌年 4 月 18 日に運輸大臣の東京・大阪間の線路増設工事の許可が下りると，本社の幹線調査室は幹線局に昇格した．この組織の所掌は，東海道新線の調査および計画から予算の管理，電力・信号・通信・車両の製作・新設・改良，土地の取得・管理まで多岐に渡るものであった 7．このように，国鉄だけで，輸送システム構築の全てを担う体制が作られていたのである.
３．３ 鉄道技術研究所の対応
鉄道の高速化という点で，運行主体である国鉄と同じ方向性を有していた鉄道技術研究所は，新幹線の建設着工が決定すると，全面的な支援体制をとった．これは，既存の研究室組織を超越した
特別な重点研究班を置き，班長の指揮の下に種々の研究分野に渡る専門研究者を集め，能率的かつ強力に研究を進めるためであった 8．
そして，東海道新幹線の研究を本格的に実施する段階になると，研究所の経常費の他に，新幹線
工事経費が研究所に配布され，試験機材類，計測器，消耗品類などが整えられた 9．以上の点から，
東海道新幹線の建設着工決定後は，運行主体である国鉄と，研究開発主体である鉄道技術研究所の連携体制が構築されていたと言うことができよう．
４ 東海道新幹線の開通
４．１ 新幹線開業
東海道新幹線では，橋梁・トンネル・軌道・電気等の工事と，車両・信号等の研究開発が同時に進められた．昭和 34（1959）年 4 月 18 日付けで
東京幹線工事局が設置され，新幹線は，調査から490

には，もう 1 つ別の意味が込められていたのである．借款には，2 つの契約があった．1 つは，国鉄
が世界銀行から 8000 万ドルを借り受ける契約，
そして，もう 1 つは，国鉄が借り入れた計画が予定通り完成するよう，政府が資金上，行政上のあらゆる努力を保証するという保証契約であった 16．
この契約により，東海道新幹線の建設は，必要に応じて政府の支援を得ることが可能な体制を将来に渡って確保していたことになる．

施工の段階へ移行した．トンネル工事は，昭和 34（1959）年 9 月に新丹那トンネルに着手し，橋梁工事は翌年 1 月の相模川，酒匂川から開始された
10．また，軌道・電気等の工事は全線同時着工となり，最盛期の現場従業員は，軌道・電気関係を含めて毎日 4～5 万人に上った 11．一方，車両の開発は，国鉄本社の臨時車両設計事務所が中心になり，鉄道技術研究所，民間会社の協力により進められた 12.そして，昭和 37（1962）年 6 月 20 日に，
試作車両 6 両の組み立てが完了し，同月からは，各種の試験をモデル線において開始した．同年 10月31日には時速200km，
翌年3月30日に時速256km
13を記録した ．後の議論ために補足すると，「飛鳥」とは異なり，研究開発から運行まで一貫した体制
が，新幹線では構築されていたのである.
橋梁・トンネル・軌道・電気等の工事と，車両・信号等の研究開発が同時に進められた結果，昭和39（1964）
年10月1日に東海道新幹線は開業した．
以来 40 年以上に渡り，大規模な事故は発生していない．また，黒字経営も確保し続けている．これ
らの点を考慮すると，東海道新幹線は，技術的にも経営的にも成功したと言えるだろう．
４．２ 世界銀行からの借款
順調に進んだように見える東海道新幹線のプロジェクトであるが，工事と研究開発が同時進行する中では，工事費の膨張が問題になっていた．工事費の総額は，計画当初に予想された 1972 億円から，
ほぼ 2 倍に近い 3800 億円にまで増加したのである．この背景には，工事期間中の著しい経済成
長に伴う用地費の高騰，賃金・資材価格の上昇のほか，騒音問題等に配慮した計画の変更による線
路の高架化等が指摘されている 14．
このような状況にもかかわらず，工事を遂行できた要因の一つが，世界銀行からの借款であった．
国鉄が制度的に認められている借入財源には，財政融資と鉄道債権による民間資金借入があるが，これにも限度があるため，世界銀行からの借款が考えられたのである 15．そして，昭和 34（1959）
年 10 月に，国鉄の新幹線計画としての 1 億ドルの借款が，担当官庁である大蔵省を通じて正式に世界銀行に申請された．昭和 35（1960）年 5 月に，世界銀行の調査団が来日し，約 1 ヶ月に渡って新幹線に関する調査が行われた．その結果，翌年 5月に総額 8000 万ドルの借款契約が結ばれた．
これは，額から見れば，当初予想された工事費総額
1972 億円の 14.6％に過ぎない．しかし，この借款

５．考察
５．１ ３つの枠組みによる検証
これまで東海道新幹線の建設を通史的に述べてきた.以下では，3 つの枠組み①所管する省庁と研
究開発主体②研究開発主体と運航（運行）主体③
研究開発主体と輸送システムの構成要素から，このプロジェクトを考察してみよう.
東海道新幹線の建設は，国鉄本社と付属機関である鉄道技術研究所が中心になって実施された．
しかし，計画段階では，監督官庁である運輸省にも，調査を行うための日本国有鉄道幹線調査会が設置された．つまり，この時点では，「飛鳥」やTSL と同様に，所管省庁の認識や政策の変化等によっては，プロジェクトが変わる危険性を含んでいたことになる．だが，建設決定後は，国鉄側が設定した技術目標とスケジュールで進められた．
この背景には，次の 2 つの要因が考えられる．まず 1 つ目は，国鉄という組織である．運輸省は監
督官庁の立場にあるものの，国鉄は公共企業体であり，研究開発から建設に至るまで，独自の活動が可能だった．そして 2 つ目は，世界銀行からの借款である．この借款によって国鉄は，運輸省の政策変化等の影響は受けないにもかかわらず，必要になれば支援を得られるという，プロジェクト推進に都合の良い体制を構築していたのである．
次に，研究開発主体と運航（運行）主体の関係を見てみよう．東海道本線の需要の逼迫を受け，運行主体である国鉄は，
昭和 31 年に東海道線増強
調査会を設置し，新たな輸送手段についての検討を開始した．これに対し，研究開発主体である鉄道技術研究所では，鉄道の高速化に関する研究が，個人的なレベルから研究所全体へと移行する時期にあった．しかし，新幹線は計画段階に過ぎず，
鉄道技術研究所も開発を主導する立場にはないため，両者の認識には多少の相違点が見られた．ところが，昭和 33 年に，東海道新幹線の建設着工が491

要の逼迫という問題に対し，運行主体である国鉄と研究開発主体である鉄道技術研究所が協同で出した答えが，東海道新幹線だったのである．そのため，自ら採算性を検討した上で最適な技術を開発し，それを導入することが可能であった．
また，鉄道は，車両と線路（軌道）が結合して初めて機能する技術であるため，両者のいずれかが欠落し，輸送システムが未完成になることもな
かった．これに加え，監督官庁である運輸省の介入も最小限に留まっており，建設への影響も限定的であった．つまり，①所管する省庁と研究開発
主体②研究開発主体と運航（運行）主体③研究開
発主体と輸送システムの構成要素の 3 つが完全に一致していたのである．この点を考慮すると，3つの不一致を全て解決出来れば「死の谷」が生じないという仮説は，有効性を持つと言えよう．

決定すると，両者は急速に接近し始める．鉄道技術研究所には，新幹線に関する研究を促進するための重点研究班が新たに創設され，全面的な支援体制が整えられた．このように研究開発主体と運行主体の良好な関係の構築が可能であった最大の要因は，当然のことながら，鉄道技術研究所が国鉄の付属機関だったことにある．研究開発主体と運行主体が主従関係にあるため，鉄道技術協議会
や新幹線建設基準調査委員会等の活動を通じて最適な技術を抽出し，その具体化を図る体制の構築が可能であった．研究開発主体が研究開発した技
術の受け取りを，最終段階で運行主体が拒否する
ような状況は，
最初からありえなかったのである．
最後に，研究開発主体と輸送システムの構成要
素の関係からプロジェクトを見てみよう．東海道
新幹線では，橋梁・トンネル・軌道・電気等の工事と，車両・信号等の研究開発が同時に進められた．
「飛鳥」のように，輸送システムの構成要素ごとに所管省庁が異なることはなく，また，TSL のように担当部局が異なることもなかった．
しかし，
このように輸送システムの構築を同時に進めることが出来た要因は，研究開発から建設，運行までの全てを担うことが可能だった国鉄という組織に加え，鉄道という輸送技術の性格にもあるだろう．
同じ輸送技術でも，航空機や船舶は，空港や港湾等の代わりとなる広場や河川・海等があれば，飛行や航行は可能である．そのため，機体や船体だけを製作することも可能であった．これに対し鉄
道は，線路（軌道）が欠落すると，それに代替する手段がない．つまり鉄道は，車両と線路（軌道）の両者が結合して初めて機能する技術であり，両者の研究開発と建設の足並みが揃わない事態は，
通常では考えられないのである．
以上の点から，東海道新幹線では，「飛鳥」やTSL において「死の谷」を生じさせた要因が存在しないことが明らかになった．この点を考慮すると，東海道新幹線の成功は，先見性やリーダーシップ，鉄道技術と航空技術の融合だけでなく，国鉄という組織や鉄道という技術の性格も大きな役割を果たしているという指摘も可能だろう．

References[1]

日本国有鉄道『日本国有鉄道百年史 第 12 巻
（復刻版）』，成山堂，p.117．

[2]

鉄道技術研究所監修『高速鉄道の研究』研友社，
1967 年，p.633．

[3]

日本国有鉄道『 東海道新幹線工事し 電気編』,p.5.

[4]

前掲『東海道新幹線工事誌 電気編』，p.10．

[5]

前掲『日本国有鉄道百年史 第12 巻（復刻版）』，
p.238．

[6]

前掲『日本国有鉄道百年史 第12 巻（復刻版）』，
p.121．

[7]

前掲『日本国有鉄道百年史 第12 巻（復刻版）』，
p.239．

[8]

前掲『高速鉄道の研究』，p.633．

[9]

前掲『高速鉄道の研究』，p.633．

[10] 角本良平『新幹線開発物語』中公文庫,2002 年，
p.139．
[11] 日 本 国 有 鉄道 新 幹 線 総局 『 新 幹 線開 発 物語』,p.150．
[12] 日本国有鉄道『日本国有鉄道百年史 第 14 巻
（復刻版）』，p.543．
[13] 前掲『新幹線十年史』，p.14．

６．結論
以上の点から，技術的・経営的にも成功したとされる東海道新幹線では，「飛鳥」や TSL のプロジ
ェクトにおいて「死の谷」を生じさせた要因が存在しないことが明らかになった．東海道本線の需[14] 前掲『新幹線開発物語』,p.158．
[15] 前掲『新幹線開発物語』,p.155．
[16] 兼松学「東海道新幹線と整備新幹線」『運輸と経済』，運輸調査局，第 48 巻第 11 号，1988 年，
p.63-70．
492

国家プロジェクトによる輸送技術開発の歴史的分析
加治木 紳哉**

東京工業大学 大学院社会理工学研究科 経営工学専攻 技術構造分析講座 博士課程
s-kajiki@me.titech.ac.jp

なぜ，国家プロジェクトによる輸送技術の研究開発は，実験機や実験船の建造には成功しても，意図していたような実用化に結びつかないのだろうか．このような「死の谷」が生じる原因については，具体的な分析は行われず，通説も評論の域を出ていない．本研究は，この問題に対し，科学技術庁の短距離離着陸実験機「飛鳥」，
通商産業省のジェット・エンジン「FJR710」，運輸省の新形式超高速貨物船テクノス
ーパーライナーのプロジェクトを歴史的に述べ，比較・分析することにより，その原因の考察を試みたものである.

１．課題の設定
政府関係の研究機関や政府主導の下で結成された技術研究組合等によって実施される国家プロ
ジェクトの中には，技術開発には成功したものの，実用化に結びつかないという状況が発生した例がある．国家プロジェクトは，大規模あるいは長期を要する分野に取り組むことが本旨であると同時に，新技術の開発は，常に困難で不確定な要素を孕んでいる．従って，本質的に失敗する可能性が高いという指摘も可能であろう．しかし，多額の国税を投入する以上，この状況を放置することは問題である．どうすれば，困難なプロジェクトを成功に導くことが出来るのか．その出発点として，個々を精緻に分析することも重要であろう．
そこで，本研究で具体例として取り上げるのは，
科学技術庁航空宇宙技術研究所の短距離離着陸（STOL：Short Take Off and Landing)実験機「飛鳥」，運輸省のテクノスーパーライナー技術研究組合による新形式超高速貨物船テクノスーパーライ
ナーのプロジェクトである．また，国家プロジェクトに順ずる国家的プロジェクトの成功例として，日本国有鉄道の東海道新幹線も取り上げ，前述のプロジェクトと比較する．
２．STOL実験機「飛鳥」の研究開発
２．１ 背景と各省庁の意図
1971 年，通商産業省航空機工業審議会，科学技術庁航空技術審議会の答申に，そろって
STOL の文言が出現した．背景には，航空需要の増大，騒音の社会問題化，海外での STOL 機の研究開発の流行があった．また，航空機の生産を所管する通商産業省，研究開発を行う科学技術庁の意図は，2 つの点で一致していた．近距離都市間という用途と，国際共同開発を有利に進めるための自主技術の確保という点である．なお，この時期は，航空機の運航・検査を所管する運輸省もSTOL 機を推進する立場にあった．1971 年の運輸省航空審議会の答申では，離島等の空港を中心に，STOL 性を有する航空機の就航が可能なように整備することが求められている．しかし，一方では，滑走路の延長と周辺環境の整備のための空
港整備 5 ヵ年計画を 1967 年から開始した．これに加え，機材の改良や運航方法の改善等の発生源対策にも着手していた．
２．２ STOLの具体化と各省庁の認識の変化
1975 年， 科学技術庁航空技術審議会は，「STOL 輸送システムの具体的推進方策について」の建議を行い，1980 年代中期の実用化を目指すことになった．また，通商産業省は，科学技術庁と STOL 機に関する認識で一致する一方で，航空機の国際共同開発という，別のプロジェクトも具体化した．同省の航空機工業審議会は，1979 年と80 年の 2 回に渡って中間報告を行い，一定規模以上の民間航空機の開発に関しては，国際共同開発を主体とする旨が報告された．
２．３「飛鳥」の挫折
航技研が研究開発に没頭している間に，運輸省の空港整備 5 ヵ年計画は次々に実施された．「飛鳥」が初飛行に成功した 1985 年には，ほとんどの滑走路が 2000ｍ以上となり，中型
ジェット機まで就航可能な環境になっていた．
一方，ジェット・エンジンの低騒音化技術も，大幅な進歩を遂げ，低騒音新型機の導入が促進されたことで，騒音が社会問題化した時代の航空機は引退の時期を迎えていた．通商産業省と科学技術庁が意図した STOL 機を活用する機会は，運輸省独自の行動のために失われていたのである．
また同年には，通商産業省航空機・機械工業審議会が中間報告を提出し，国際共同開発を優先する
旨が報告された．これを受けて翌年には，航空機

493

工業振興法が改正され，従来の国産化促進の方向を改め，国際共同開発による航空機工業の振興を図ることになった．この時点で，通商産業省と科学技術庁の，STOL 機に対する研究開発・生産の歩調は完全に崩壊したのである．また，飛行試験で得られたデータを基に「飛鳥」の技術を適用した場合を想定した結果，実際に STOL 機が最も効率よく運用されるのは，コミューター機であることが判明した．この結果をもとに航技研は，座席数 50 人のコミューター機の概念設計を行っている．これは，
座席数 60 以下という運輸省のコミューター政策と，ほぼ一致するものであった．しかし，航技研はSTOL 機を実用化する手段を持っていなかった．
そのため，当初計画されていた STOL 輸送システ
ムの調査・検討，技術研究は行わず，1991 年に全プロジェクトが終了した．1980 年代の実用化を目指したプロジェクトは，本懐を果たす事は無かったのである．
２．４ プロジェクトの問題点
これまで見てきたように，航技研の活動を中心に置くと，通商産業省と運輸省との連携が機能していれば，STOL機の活躍の場が存在したことになる．
しかし，運輸省や通商産業省の政策の変化に対する調整機能を，航技研は持っていなかった．
科学技術庁航空技術審議会は，STOL輸送シス
テム技術の確立を目指していた．これを，システム工学の概念に当てはめてみると，STOL輸送システ
ムは，STOL機，空港，空港施設の3つで構成されることになる．しかし，この中で実際に航技研が対応できるのは，STOL機の研究開発のみであった．

３．２ TSL の具体化
研究開発の開始を受け，関係部局や関連団体
は，TSL に関する調査を開始した．大変興味深い
ことに，実用化の障壁としてプロジェクト終了後に，表面化する船価や運航コストの問題は，この 2 つの調査でも既に予測されていた．しかし，具体的な解決策は講じられずに，プロジェクトは加速してい
くことになった． そして，このように技術主導で始まった研究開発に，内航海運という用途が出現した．その背景となったのは，1980 年代後半のバブ
ル経済に伴うモーダルシフトの流行である．1991
年 10 月には，自民党の国会議員による TSL 実用化促進議員連盟が結成され，翌月からは，全国各地の自治体が中心となって誘致活動が開始された．
しかし，エンドユーザーとなる海運会社側の認識は，政治の期待とは大きく異なっており，その実用化を楽観視するものではなかった.
３．３ TSL 開発の進展
要素技術の確立に続き，1992 年からは TSL の実験船の設計・建造が開始された．そして，関係部局や関連団体も新たな調査に着手した．しかし，いずれの調査も，TSL の導入を前提にしており，
TSL が本当に必要かを問う性格のものではなかった．これ以後，総合実験が終了するまで，新たな調査は実施されていない．結果的に，最初から最後まで，本来のユーザーである海運会社側の懐疑的な声に耳が傾けられることはなかったのである．
1994 年に入ると 2 種類の実験船が完成し，いずれも，開発目標を満足するものであった．そして，
1995 年から開始された総合実験では，現行の陸上・海上輸送と比べて大幅な時間短縮が可能であることや，荷傷み，荷崩れもなく良好な輸送環境であることが確認された．TSL が開発目標を達成し，高速輸送と荷役装置も計画通りの成果が得られた点を考慮すると，輸送システムの構築に一定の目処が付いたと言えるだろう.

次に，科学技術庁と通商産業省の関係を振り返ってみよう．STOL の文言が出現した 1971 年，研究開発を行う科学技術庁と，開発・生産を行う通商産業省の STOL 機に対する認識は一致していた．
しかし，プロジェクトが開始された 1975 年以降，通商産業省は，自主開発から国際共同開発へ政策をシフトしていく．そして，「飛鳥」が初飛行に成功した 1985 年には，国際共同開発への一本化が図られた．結果的に航技研は，STOL 機の研究開発のみに終始することになったのである．以上の点か
ら，STOL 輸送システム技術の確立と，1980 年代
中期の実用化という意図にもかかわらず，実際に航技研が最後まで対応できたのは，STOL 機の研
究開発のみであったことが分かる.
２．５

石油危機を発端に長期不況に突入した造船業の再建を図るべく，運輸省海運造船合理化審議会が 1988 年に提出した意見書を受け，新形式超高速貨物船 TSL の研究開発は，実施されることになった．そして，造船大手 7 社による TSL 技術研究組合が 1989 年に設立された．なお，この段階では，具体的な用途までは示されず，開発目標のみの決定であった．そして，研究開発がプロトタイプによる技術の実証で終わるのか，実用化を直接目指すのかという点も，明確にはされなかった

小結

以上のことから，この当時の航技研のように技術移転機関や調整機能を持たない組織では，実用化に向けた研究開発を実施することが非常に難しいことが明らかになった．これに加え，開発した成果を利用することになる側の立場を考慮せず，ユーザー不在のままプロジェクトを進行させることの危険性も浮かび上がってきた.

３．４

問題の表面化1995 年度に実施された総合実験をもって，TSLの研究開発は終了した．そして，事業化を支援するための調査委員会が運輸省内に設置された．しかし，この調査により，それまでの動きを完全に停止させる問題が，表面化することになった．具体的には，船価と運航経費の問題である．要素技術の研究段階における調査で指摘された課題と，業界紙で示された海運会社の懸念が，そのまま浮上したと言えよう．また，内航貨物船という TSL の具体

３．新形式超高速船TSLの研究開発
３．１ 研究開発の背景

494

的な用途を決定する背景となったモーダルシフトも，停滞する状況にあった．しかし，技術研究組合が解散した後も，運輸省内では実用化に向けた検討が続いていた．そして，TSL を復活させる要因になったのは，1999 年 12 月に策定されたミレニアムプ
ロジェクトである．だが，第一船の用途は，環境問題という本旨とは関係ない，小笠原航路の貨客船であった．最終的には，2005 年秋の就航を予定していたが，現在は，困難に直面している．これまでの経過を見ると，TSL は政治に翻弄されてきたことになる.
３．５ プロジェクトの問題点
これまで TSL の研究開発を見てきたが，問題点として，明確に指摘出来ることは 2 つある．まず 1
つ目は，このプロジェクトが，エンドユーザーのニーズを考慮しない技術主導型の研究開発であったということである．実用化の最大の障壁は，高い船価と運航コストであった．この問題は，要素技術の研究段階の調査で指摘されていた．しかし，技術研究組合は，一度開発目標を設定すると，途上で認識された問題点をフィードバックする機能を備えていないのである．2 つ目は，政治の影響である．
TSL のプロジェクトは，重要な局面で政治の介入を受けてきた．内航海運へ投入という具体的な用途は，モーダルシフトの流行によって政治的に決定された．また，TSL は，海の新幹線として，陸の新幹線と同様の積極的な誘致活動が行われた．
実験船の建造前からの誘致活動によって需要が強調されたことで，技術の実証で終わるのか，実用化を目指すのかが不透明であった研究開発が，完全に後者へ移行したと考えられる.

術開発の成功例とされる東海道新幹線のプロジェ
クトを，この 3 つの枠組みから考察してみよう.
５．３つの枠組みによる検証
東海道新幹線の建設は，国鉄本社と付属機関である鉄道技術研究所が中心になって実施された．
しかし，計画段階では，監督官庁である運輸省にも，調査を行うための日本国有鉄道幹線調査会が設置された．つまり，この時点では，「飛鳥」や TSLと同様に，所管省庁の認識や政策の変化等によっては，プロジェクトが変わる危険性を含んでいたことになる．だが，建設決定後は，国鉄側が設定した技術目標とスケジュールで進められた．この背景には，次の 2 つの要因が考えられる．まず 1 つ目は，国鉄という組織である．運輸省は監督官庁の立場にあるものの，国鉄は公共企業体であり，研究開
発から建設に至るまで，独自の活動が可能だった．
そして 2 つ目は，世界銀行からの借款である．この借款によって国鉄は，運輸省の政策変化等の影
響は受けないにもかかわらず，必要になれば支援を得られるという，プロジェクト推進に都合の良い体制を構築していたのである.
次に，研究開発主体と運航（運行）主体の関係を見てみよう．東海道本線の需要の逼迫を受け，運行主体である国鉄は，昭和 31 年に東海道線増強調査会を設置し，新たな輸送手段についての検討を開始した．これに対し，研究開発主体である鉄道技術研究所では，鉄道の高速化に関する研究
が，個人的なレベルから研究所全体へと移行する時期にあった．しかし，新幹線は計画段階に過ぎず，鉄道技術研究所も開発を主導する立場にはな
いため，両者の認識には多少の相違点が見られた．
ところが，昭和 33 年に，東海道新幹線の建設着工が決定すると，両者は急速に接近し始める．鉄道技術研究所には，新幹線に関する研究を促進するための重点研究班が新たに創設され，全面的な支援体制が整えられた．このように研究開発主
体と運行主体の良好な関係の構築が可能であった最大の要因は，当然のことながら，鉄道技術研
究所が国鉄の付属機関だったことにある．研究開
発主体と運行主体が主従関係にあるため，鉄道技術協議会や新幹線建設基準調査委員会等の活動を通じて最適な技術を抽出し，その具体化を図る
体制の構築が可能であった．研究開発主体が研究開発した技術の受け取りを，最終段階で運行主体が拒否するような状況は，最初からありえなかったのである.

３．６ 小結以上のことから，TSL の研究開発は，プロトタイ
プで終了するのか，実用化を目指すのかが不明確なままスタートし，場当たり的に対策が講じられてきたことが明らかになった．これは，政府主導の研究開発におけるマネジメント能力の未熟さを露呈したと言うことが出来よう．また，実用化への具体的なビジョンが欠如しているため，政治の介入を許した，
或いは、政治に頼らざるを得なかったというのが正直なところであろう.
４．「死の谷」の原因の分析
これまで，国家プロジェクトによる輸送技術の研究開発の中で，技術開発に成功したにもかかわらず，実用化に結びつかない状況が発生した，
STOL 実験機「飛鳥」と超高速貨物船 TSL に焦点を当て，その原因を考察してきた．その結果， ①
研究開発主体を一貫して支える所管省庁，②研究開発主体と運航（運行）主体の密接なコミュニケー
ション，③研究開発主体による輸送システムの構築体制への関与という 3 つの要因から，「死の谷」の発生の有無を判断できることが明らかになった．
つまり，この 3 つを全て満足できれば，「死の谷」は生じないのに対し，1 つでも欠落すれば，生じることになる．そこで，国家的プロジェクトによる輸送技

最後に，研究開発主体と輸送システムの構成要
素の関係からプロジェクトを見てみよう．東海道新
幹線では，橋梁・トンネル・軌道・電気等の工事と，車両・信号等の研究開発が同時に進められた．
「飛鳥」のように，輸送システムの構成要素ごとに所管省庁が異なることはなく，また，TSL のように担当部局が異なることもなかった．しかし，このように輸送システムの構築を同時に進めることが出来た
要因は，研究開発から建設，運行までの全てを担うことが可能だった国鉄という組織に加え，鉄道と495

いう輸送技術の性格にもあるだろう．同じ輸送技術
でも，航空機や船舶は，空港や港湾等の代わりとなる広場や河川・海等があれば，飛行や航行は可能である．そのため，機体や船体だけを製作することも可能であった．これに対し鉄道は，線路（軌道）が欠落すると，それに代替する手段がない．つまり鉄道は，車両と線路（軌道）の両者が結合して初めて機能する技術であり，両者の研究開発と建設の足並みが揃わない事態は，通常では考えられない
のである.
６．結論
以上の点から，技術的・経営的にも成功したとされる東海道新幹線では，「飛鳥」や TSL のプロジ
ェクトにおいて「死の谷」を生じさせた要因が存在しないことが明らかになった．つまり，①所管する省
庁と研究開発主体②研究開発主体と運航（運行）主体③研究開発主体と輸送システムの構成要素の 3 つが完全に一致していたのである．この点を考慮すると，3 つの不一致を全て解決出来れば「死の谷」が生じないという仮説は，有効性を持つと言えよう.
以上のことから，国家プロジェクトによる輸送技術の研究開発で，技術開発に成功しても実用化に結びつかない状況が生じる原因は，実用化という目標と，研究開発を実施する組織が対応出来る範囲の根本的な相違に起因することが，本研究で明らかになった．従来，このような状況が生じる原因については，「プロジェクトに関与した省庁の政策の相違」や，「政府が実施すると失敗する例が多い」等の通説によって説明がなされてきた．しかし，実際には，技術開発に特化した組織である国立試
験研究機関や技術研究組合が，直接，実用化を目指した研究開発を実施すること自体に問題があったことになるのである.
近年，研究開発に対する政府の期待は，ますま
す高まり，その重要性が強調されている．そして，昨年度（2006 年）から実施された第 3 期科学技術基本計画では，「知の大競争時代を先導する科学技術戦略」として，「基礎研究」や「技術革新」等の5 項目が挙げられ，成果を社会へ還元することが問われている．しかし，成果のみを追求するあまり，実施する組織の対応能力や，開発する技術の性格が軽んじられるという危険性は否定できない．このように成果を重視する傾向が強まる中で，本研究の結論は，担当組織や技術の性格を考慮して，
国家プロジェクトの目標を設定することの重要性を示唆するものである.
技術や経済等への波及効果からではなく，問題が発生した個々のプロジェクトを精緻に分析することにより，このような結論は得られるのである.

496

工学教育の形成における日本型文化の役割：工部大学校の場合について―The Role of the Japanese Cultural Background in the Formation of Engineering Education:in the Case of the Imperial College of Engineering―
和田 正法

東京工業大学大学院社会理工学研究科経営工学専攻
152-8552 東京都目黒区大岡山 2-12-1 W9-79
wada.m.ae@m.titech.ac.jp
和田正法は、2008年4月から2009年3月の東京工業大学21世紀COEプログラムSIMOTの所属期間中にRAとして「工学教育の形成における日本型文化の役割：工部大学校の場合について」をテーマに研究調査を行なった。その成果について、現在加筆修正のうえ学術雑誌への投稿を準備している。そのため、COE『最終報告書』における公表は控えさせていただく。なお、これまでにCOE-SIMOTにおいて報告を行なった内容は以下の通り、若手・RA 研究成果報告 Pre-Doctoral Interim Report が2点、ポスター
報告が1点、プレゼンテーション報告が2点である。

若手・RA 研究成果報告 Pre-Doctoral Interim Report「工部大学校生徒の入学動機に関する研究 (Motives of Entering the Imperial
College of Engineering in Tokyo)」(2008年秋)「工部大学校生徒の統計的分析 (A Statistical Analysis of Students at the Imperial
College of Engineering)」(2009年春)
ポスター報告"Social and Personal Orientation of Students at the Imperial College of Engineering inTokyo in Early Meiji Japan," 第5回年次国際シンポジウム, (2009年2月21, 22日,
東京工業大学)
プレゼンテーション報告"Motives of Entering the Imperial College of Engineering in Tokyo," 若手・RA研究報
告会, (2008年9月25日, 東京工業大学)"Imitation or Originality? ―Engineering in Early Meiji Japan from Henry Dyer’s
Viewpoint," 第5回年次国際シンポジウム, パネルディスカッション部門,(2009年2月23日, 東京工業大学)

497

Tokyo Institute of Technology, 21st Century COE Program, SIMOT,“5-year Pre-Doctoral Report of the Science of Institutional Management of Technology,”
2009, Tokyo Institute of Technology, Tokyo.

Tokyo Institute of Technology, 21st Century Center of Excellence Program

The Science of Institutional Management of Technology
Dept. of Ind. Engineering & Management, Tokyo Institute of Technology
2-12-1 W9-51, Ookayama, Meguro-ku, Tokyo 152-8552 Japan
TEL：03-5734-3606
FAX：03-5734-2251
Email： tou.y.aa@m.titech.ac.jp
URL：http://www.me.titech.ac.jp/coe/