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dissertation entitled
Global Competitive Advantage in the Ethical Pharmaceutical
Industry: An Empirical Study.

presented by
Madhu Agrawal

has been accepted towards fulfillment
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Doctor ofihflnsnndeegree in jusinesstministration

jor professor

Date May 9, 1995

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GLOBAL COMPETITIVE ADVANTAGE IN THE ETHICAL PHARMACEUTICAL
INDUSTRY: AN EMPIRICAL STUDY

By

MADHU AGRAWAL

A DISSERTATION

Submitted to
Michigan State University
in partial fulfillment of the requirements
for the degree of

DOCTOR OF PHILOSOPHY

Department of Marketing and Logistics
1995

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ABSTRACT

GLOBAL COMPETITIVE ADVANTAGE IN THE ETHICAL PHARMACEUTICAL
INDUSTRY: AN EMPIRICAL STUDY

By

MADHU AGRAWAL

This study presents a theoretical and empirical investigation of the determinants of
global competitive advantage in the ethical pharmaceutical industry. Two major research
questions investigated in the study are: (1) Which country factors stimulate or inhibit a
nation's pharmaceutical industry to be globally innovative? and (2) Which country factors
stimulate or inhibit diffusion of pharmaceutical innovations into its markets?

The motivation for doing the study derives from the growing concern in the past
decade regarding national competitiveness issues in the new global economy. The global
pharmaceutical industry is especially suitable for examination of country factors that affect
competitiveness.

Two path models - the Global Innovation Model (GIM) and the Global Diffusion
Model (GDM) were tested using EQS - a structural equation modeling program on the
mainframe. Data was obtained from secondary sources, mainly from the Scrip League
Tables and United Nations publications. A sample of twenty—seven countries was used in
the analysis. Besides a review of the literature, talks with industry experts and responses
from a small-scale industry survey were also used as inputs in the study design.

Several significant results were obtained. A country's economic, regulatory and
market/industry environments were found to have significant effects on the ability of the
industry to innovate. Diffusion was found to be significantly related to a country's

environment for innovation. Industrialized and Developing countries were found to differ

significantly with respect to the effects of various factors affecting competitiveness of the
pharmaceutical industries in those countries.

The study makes several contributions to the theoretical, empirical, managerial and
public policy literature on global competitiveness; competitiveness in the pharmaceutical

industry; economic development issues; and global strategic management issues.

Copyright by
MADHU AGRAWAL
1995

To Sanjay

 

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ACKNOWLEDGEMENTS

I would like to thank all the members of my dissertation committee - Dr. Roger
Calantone, Dr. Tamer Cavusgil, Dr. Robert Nason and Dr. Stan Fawcett - for their
assistance and guidance in my dissertation research.

I am especially grateful to Dr. Calantone for his invaluable moral and academic
support throughout the course of my Ph.D. program. Without his constant guidance and
encouragement, this work would not have been possible.

I am thankful to Dr. Tamer Cavusgil and Dr. Robert Nason for their useful
suggestions which greatly contributed to improving the study. Their support and
encouragement during my four years in the program is also greatly appreciated.

I would also like to extend my special thanks and gratitude to Ms. Sharon Lehman -
Director of the Research Library of Parke-Davis for allowing me to use the library
resources which provided much of the data used in the study. I also appreciate the help
provided by Ms. Leona Williams - the librarian at Parke-Davis.

Finally, I would like to acknowledge my family. My parents - for their
innumerable sacrifices and unfailing support; my brothers - who have influenced and
inspired me to attain higher goals; my in-laws - for their confidence and pride in my
abilities; and my husband - Sanjay, without whose understanding, love and patience, this

work would not have been possible.

vi

 

List of '

List of .

Chaplet

 

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~_.__.

TABLE OF CONTENTS

List of Tables ...................................................................................... x
List of Figures ..................................................................................... xii
Chapter One: INTRODUCTION ................................................................ 1
1.1 Purpose of Study .................................................................. 1
1.2 Motivation for Study .............................................................. 1
1.3 Overview of Research Design and Conceptual Model ........................ 3
1.4 Expected Contributions of the Study ............................................ 5
1.5 Organization of the Study ........................................................ 7
Chapter Two: THE GLOBAL PHARMACEUTICAL INDUSTRY ........................ 8
2.1 Present Status and Environment ................................................. 8
2.2 Evolution of the Global Industry ................................................ 12
2.3 Unique Characteristics of the Industry .......................................... 16
2.4 Determinants of Competitiveness in the Global Pharmaceutical
Industry ............................................................................. 17
2.5 Summary ........................................................................... 19
Chapter Three: REVIEW OF LITERATURE ................................................. 20
3.1 National Competitiveness - Theoretical and Conceptual Perspectives ....... 20
3.1.1 Definition of National Competitiveness ............................. 21
3.1.2 Theory of Comparative Advantage ................................... 22
3.1.3 The Technology Factor Theory ...................................... 22
3.1.4 The Role of Government and Public Policy ......................... 24
3.2 Competitiveness in the Global Pharmaceutical Industry ..................... 28
3.2.1 Role of Regulation, R&D and Innovation ........................... 29
3.2 2 Pharmaceutical Diffusion and Competitiveness ..................... 32
3 2 3 Supply and Demand Factors in Pharmaceutical
Competitiveness ....................................................... 35
3.2.4 Developing Country Competitiveness Issues ....................... 52
3.2.5 Conceptual Model of Global Pharmaceutical
Competitiveness ........................................................ 55
3.3 Global Strategic Perspectives .................................................... 57
3 3 1 Core Competencies ..................................................... 57
3.3.2 Comparative Advantage-Based Competitive Advantage .......... 58
3 3 3 Collaborate to Compete ................................................ 61

vii

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Chapter Four: METHODOLOGY ............................................................... 63

4.1 Research Questions ................................................................ 63
4.1.1 Executive Survey ...................................................... 64
4.2 Model Development .............................................................. 66
4.2.1 The Global Innovation Model (GIM) ................................ 66
4.2.2 The Global Diffusion Model (GDM) ................................. 68
4.2.3 Constructs, Measures and Data Sources ............................. 68
4.2.4 Data Sources, Sample Size and Time Frame ........................ 72
4.3 Hypotheses ......................................................................... 74
4.4 Statistical Method of Analysis - EQS ............................................ 75
4.4.1 Uses of Structural Equation Modeling (SEM) ...................... 75
4.4.2 Steps in Structural Equation Modeling ............................... 78
4.4.3 Indirect Effects and Two-group Analysis ........................... 79
Chapter Five: RESULTS ......................................................................... 82
5.1 Global Innovation Model - Results .............................................. 82
5.1.1 Effect of GNP, Price regulation and Market size on
Innovation .............................................................. 83
5.1.2 Effect of GNP, Price regulation and Industry focus on
Innovation ............................................................... 90
5.1.3 Effect of GNP, Price regulation and Industry growth on
Innovation .............................................................. 93
5.1.4 Effect of GNP, Price regulation and Industry Concentration
on Innovation .......................................................... 96
5.1.5 Effect of Population, Approval time and Market size on
Innovation ............................................................... 99
5.1.6 Effect of Population, Approval time and Industry focus on
Innovation .............................................................. 102
5.1.7 Effect of Population, Approval time and Indusz growth on
Innovation .............................................................. 102
5.1.8 Effect of Population, Approval time, Industry concentration
and Foreign Commitment on Innovation ............................ 105
5.2 Group Differences - Industrialized and Developing Countries .............. 108
5.3 Significant Indirect Effects on Innovation and Global
Competitiveness ................................................................... 1 16
5.4 Global Diffusion Model - Results ............................................... 118
5.5 Conclusions ........................................................................ 123
Chapter Six: CONCLUSIONS .................................................................. 127
6.1 Summary of Results ............................................................... 127
6.1.1 Determinants of Global Innovation ................................... 127
6.1.2 Global Innovation Factors for Industrialized versus
Developing Country Industries ....................................... 128
6.1.3 Determinants of Global Diffusion .................................... 129
6.2 Implications of Study Results .................................................... 130
6.2.1 Managerial Implications ............................................... 130
6.2.2 Public Policy Implications ............................................. 138
6.3 Contributions of Study ........................................................... 143
6.3.1 Theoretical Contributions .............................................. 143

viii

 

 

 

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6.3.2 Empirical Contributions ............................................... 144

6.3.3 Methodological Contributions ................................ '. ....... 145

6.3.4 Managerial and Public Policy Contributions ........................ 146

6.4 Limitations of Study ............................................................... 146

6.5 Future Research Suggestions .................................................... 147

LIST OF REFERENCES ........................................................................ 149
APPENDD( A ..................................................................................... 159
APPENDIX B ..................................................................................... 191

 

 

Table

Table
Table
Table

Table
Table

Table
Table -
Table -
Table -
Table -
Table

 

 

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Table
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Table 2.1

Table 3.1
Table 3.2
Table 3.3

Table 3.4
Table 4.1a

Table 4.1b
Table 4.2

Table 4.33
Table 4.3b
Table 4.4a
Table 4.4b

Table 5.1
Table 5 .2

Table A]
Table A.2
Table A3
Table A4
Table A5
Table A6
Table A.7
Table A8
Table A.9
Table A. 10
Table All
Table A. 12
Table A. 13
Table A. 14
Table A.15
Table A. 16
Table A. 17
Table A. 18
Table A. 19
Table A.20
Table A.21
Table A.22
Table A.23
Table A.24
Table A.25
Table A.26

LIST OF TABLES

Leading Pharmaceutical Markets for 1992 ..................................... 10
Overview of Studies on Global Pharmaceutical Competitiveness ........... 33
Overview of Studies on Global Pharmaceutical Diffusion .................... 36
Environmental Conditions and Global Pharmaceutical

Competitiveness ................................................................... 53
Asian Pharmaceutical Markets by Size .......................................... 56

Constructs, Measures and Data Sources: The Global Innovation

Model ............................................................................... 71
Constructs, Measures and Data Sources: The Global Diffusion Model ..... 73
Countries in Sample ............................................................... 74
Hypotheses: The Global Innovation Model .................................... 76
Hypotheses: The Global Diffusion Model ...................................... 76
Program runs for the Global Innovation Model .............................. 77
Program runs for the Global Diffusion Model ................................ 77
Significant Path Differences Between Industrialized and Developing

Countries ........................................................................... 110
Summary of Results - Global Innovation Analysis ............................ 125
Global Innovation Model ......................................................... 159
Global Innovation Model ......................................................... 160
Global Innovation Model ......................................................... 161
Global Innovation Model ......................................................... 162
Global Innovation Model ......................................................... 163
Global Innovation Model ......................................................... 164
Global Innovation Model ......................................................... 165
Global Innovation Model ......................................................... 166
Global Innovation Model ......................................................... 167
Global Innovation Model ......................................................... 168
Global Innovation Model ......................................................... 169
Global Innovation Model ......................................................... 170
Global Innovation Model ......................................................... 171
Global Innovation Model ......................................................... 172
Global Innovation Model ......................................................... 173
Global Innovation Model ......................................................... 174
Global Innovation Model ......................................................... 175
Global Innovation Model ......................................................... 176
Global Innovation Model ......................................................... 177
Global Innovation Model ......................................................... 178
Global Innovation Model ......................................................... 179
Global Innovation Model ......................................................... 180
Global Innovation Model ......................................................... 181
Global Innovation Model ......................................................... 182
Global Innovation Model ......................................................... 183
Global Innovation Model ......................................................... 184

 

 

Table
Table
Table

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Table

Table

Table
Table
Table
Table
Table
Table

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Table A.27
Table A.28
Table A.29
Table A.30
Table A.31
Table A.31

Table B.1
Table 3.2
Table B.3
Table B.4
Table B.5
Table B.6
Table 8.7
Table B.8
Table 8.9
Table B. 10
Table B.11
Table B. 12

Global Innovation Model ......................................................... 185
Global Innovation Model ......................................................... 186
Global Innovation Model ......................................................... 187
Global Innovation Model ......................................................... 188
Global Innovation Model ......................................................... 189
Global Innovation Model ......................................................... 189
Global Diffusion Model ........................................................... 191
Global Diffusion Model ........................................................... 192
Global Diffusion Model ........................................................... 193
Global Diffusion Model ........................................................... 194
Global Diffusion Model ........................................................... 195
Global Diffusion Model ........................................................... 196
Global Diffusion Model ........................................................... 197
Global Diffusion Model ........................................................... 198
Global Diffusion Model ........................................................... 199
Global Diffusion Model ........................................................... 200
Global Diffusion Model ........................................................... 201
Global Diffusion Model ........................................................... 202

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Figure 1.2a
Figure 1.2b

Figure 2.1
Figure 2.2

Figure 2.3

Figure 3.1
Figure 3. 2

Figure 3.3
Figure 3. 4

Figure 3.5
Figure 3. 6

Figure 4.1

Figure 4. 2a
Figure 4. 2b

Figure 4.3a
Figure 4.3b

Figure 5.1
Figure 5. 2
Figure 5.3
Figure 5. 4

Figure 5.5
Figure 5.6

Figure 5.7
Figure 5.8
Figure 5.9

Figure 5.10

LIST OF FIGURES

 

Determinants of Global Market Share in the Pharmaceutical Industry ...... 4
The Global Innovation Model .................................................... 6
The Global Diffusion Model ..................................................... 6
Global Sales by Corporate Nationality .......................................... 9
Important Milestones in the Evolution of the Global Pharmaceutical

Inc .ustry ............................................................................. 13
NCE Introductions by US, Western Europe and Japan ...................... 18
Determinants of Global Market Share in the Pharmaceutical Industry ...... 38
World Consumption of Pharmaceuticals, 1992 ................................ 42
Risks in Pharmaceutical R&D .................................................... 44
Pricing Systems and Effects on R&D .......................................... 48
Conceptual Model of Global Pharmaceutical Competitiveness ............... 57
Value-Added Chain for Pharmaceuticals ........................................ 60
Executive Survey .................................................................. 65
The Global Innovation Model .................................................... 67
The Global Diffusion Model ..................................................... 67
The EQS Model for Global Innovation ......................................... 80
The EQS Model for Global Diffusion ........................................... 81
Effect of GNP, Price regulation and Market size on Innovation ............. 84
Effect of GNP, Price regulation and Industry focus on Innovation ......... 91
Effect of GNP, Price regulation and Industry growth on Innovation ....... 94
Effect of GNP, Price regulation and Industry Concentration on ............
Innovation ......................................................................... 97
Effect of Population, Approval time and Market size on Innovation ........ 100
Effect of Population, Approval time and Industry focus on

Innovation ......................................................................... 103
Effect of Population, Approval time and Industry growth on

Innovation .......................................................................... 104
Effect of Population, Approval time, Industry concentration

and Foreign Commitment on Innovation ....................................... 106
Significant Indirect Effects ....................................................... 1 17
Global Diffusion Model ........................................................... 120

xii

 

 

 

l.l T’L'RP

The n‘
competitive a,
research quet

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CHAPTER ONE
INTRODUCTION

1.1 PURPOSE QF STUDY

The main objective of the study was to examine the determinants of global
competitive advantage in the ethical1 pharmaceutical industry. Specifically, the two main

research questions of the study were:

(1) Which country factors stimulate or inhibit a nation's pharmaceutical industry
to be globally innovative?

(2) Which country factors stimulate or inhibit diffusion of pharmaceutical
innovations (N CEs)2 into its markets?

The above research questions were developed after a review of the literature, talking

to industry experts, and from the responses of an executive survey carried out to determine

the factors affecting global competitiveness in the pharmaceutical industry.

12 W

National competitiveness has become one of the central preoccupations of
government and industry in every nation, especially so in the US. The competitiveness of
the US economy in the global market became a growing concern during the 19803, due to

sustained deterioration in the US trade deficit. The loss of market share in products such as

 

1 An "ethical" pharmaceutical is one that is available only through prescription. Ethical products can be
either patented or non patented (i.e., generic).
2 An NCE is a drug for which the active ingredient has not been previously marketed (approved) for use in

a drug product

microelectronics, an industry thought invulnerable to foreign competition, began to raise
questions regarding the overall international competitiveness of the US economy.

In 1990, the US Senate Committee on Finance identified three industries which
were important for future US competitiveness in the global economy. The Committee
directed the US International Trade Commission to conduct investigations on these three
advanced-technology manufacturing industries of which one was the pharmaceutical
industry.

The global pharmaceutical industry is a multinational industry that is highly
regulated, capital intensive and driven by large R&D expenditures. The world market for
ethical pharmaceuticals in 1992 was estimated to be US $ 163.4 billion (Scrip Magazine
1994). Supported by an ever-increasing demand for health care, world production of
pharmaceuticals has grown at an exceptional pace throughout most of the post-war period.
Today nearly 60 countries have annual production levels of at least $100 million (Ballance,
Pogany and Forstner 1992).

World consumption of pharmaceutical preparations has doubled between 1975 and
1990 with the world's per capita consumption of drugs increasing almost 70 percent in the
same years. Very few industries can boast of such an impressive growth record.

However, other than the above factors, there is a more important reason for
examining factors affecting competitiveness of the pharmaceutical industry in different
countries. The industry is of great social and public importance in all the countries. A flood
of life-saving drugs has emerged from the world's pharmaceutical laboratories over the past
four decades. By combating many fatal diseases and eradicating others, drug producers

have helped to alter mortality patterns in many parts of the world.

1.3 RIEW FREEARHDEI AD PTALM E

For the purpose of developing the conceptual framework, the research design and
the hypotheses, three streams of literature were reviewed. These were: (1) Theoretical and
Conceptual Perspectives on National Competitiveness, (2) Competitiveness in the Global
Pharmaceutical Industry, and (3) Global Strategic Management Perspectives.

The conceptual model used to develop the statistical path models in the study is
illustrated in Figure 1.1. The model illustrates a number of supply and demand related
factors that affect global competitiveness in the pharmaceutical industry. The demand for
ethical pharmaceuticals is determined by demographic and socioeconomic factors.
Government policies and programs also affect the demand for drugs, directly or indirectly.
An important factor affecting the supply of ethical pharmaceuticals is R&D activity, i.e., the
level and productivity of R&D spending. Government actions ranging from
macroeconomic policies, treatment of product liability, and regulatory controls exert direct
and indirect effects (positive and negative) on the ability of firms and the industry as a
whole to produce pharmaceuticals.

Besides a review of the literature, talks with industry experts and responses from an
executive survey conducted before the actual data collection, provided insights into
development of the constructs and measures for the study. Data was obtained from
secondary sources, mainly from the Scrip League Tables and governmental publications
such as the United Nations. Pharmaceutical industry data for a total of twenty-seven
countries was used in this study. Of these, fifteen are industrialized countries and twelve
are developing countries. Two-group analysis will be done to examine differences in
competitiveness factors between the industrialized (I) and developing (D) nation
pharmaceutical industries.

The statistical package used to analyze the models was EQS - a structural equation

modeling program on the mainframe. The two path models developed are illustrated in

 

 

 

SOUrCe

Figure 1.1: Determinants of Global Market Share
in the Pharmaceutical Industry

Global Market
Share

 
     

 

    
    

Marketing!
Consumer
information

R&D Activity
Socio
nomic

External
900 Financing
factors
Demographic
factors I Profits I‘—

      
 
  

 
  

  
 
   

 

 

 

 

 

 

 

Health c are /
Reimbursement

and other health
care programmes

 

 

 

 

 

V acroeeonomoc
policies

    

Profit controls
00st Containmen'
Tax Policies

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Technology

 

 

 

Source: USITC (1991)

Education
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Marketing (in particular . - Iicies
Expertise R&D productivity)

 

 

 

Indirect & Direct
Funding

Basic Research
Development

Education
Other infrastructure

 

 

 

 

 

Figure

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Figures 1.2a and 1.2b. They will be referred to as the Global Innovation Model (GIM) and
the Global Diffusion Model (GDM) in this study.

1.4 RIB TI

Theoretical, empirical, and methodological contributions are expected from the
study. In addition important managerial and public policy implications of the study results
will also be examined.

Theoretical contributions to several streams of literature are expected. Theoretical
concepts from the literature on - national competitiveness, pharmaceutical innovation and
diffusion, economic development literature, and the global strategic literature are combined
in this study.

Significant empirical contributions to the global competitiveness research on the
pharmaceutical industry are expected since this study uses a far larger sample of countries,
a more comprehensive model, and greater sophistication in statistical method of analysis
than previous studies done in the area.

Managerial implications from the study results will be many. Strategic management
issues both from the perspective of industrialized country MNCs and developing country
MNCs will be discussed. These implications will be discussed with respect to type of core
competencies that global pharmaceutical firms should develop; the various types of
comparative advantages of countries that firms should exploit for developing competitive
advantage; and the strategic choices that firms should make when collaborating with
international firms.

Public Policy implications are expected to be extremely important since the
pharmaceutical industry is heavily regulated in most countries and such regulations have
far-reaching impact on its competitiveness. Public policy implications with respect to the

economic environment, the regulatory environment, and the market/industry environment

Figure 1.2a: The Global Innovation Model

‘ Economic Foreign Mkt
Environment Investment
4. (outbound)
+
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+ Regulation - Potential - - ' - - - Innovation

Mitt/Industry
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for pharmaceuticals will be explored on the basis of the study results. Recommendations
for industrialized and developing country policy makers will be made with respect to their

pharmaceutical industries in the global economy.

1.5 QBQANIZAIIQN QF THE STUDY

The study has six chapters. Chapter 2 presents an overview of the nature of global
competition in the pharmaceutical industry and discusses its evolution in the post World
War 11 period.

Chapter 3 reviews the literature on national competitiveness, global pharmaceutical
competitiveness, and global strategic management. Studies from these streams of literature
are reviewed to develop the constructs and hypotheses used in the research.

Chapter 4 presents the research questions; the statistical models and statistical
technique; and the constructs, measures and data sources used in the study. Hypotheses
developed to analyze the relationships are also discussed.

Chapter 5 is the results. Results from the global innovation and global diffusion
models are discussed. Indirect effects are also examined. The results of the two-group
analysis of industrialized (I) and developing country (D) groups are also discussed.

Chapter 6 presents the summary of results; managerial and public policy
implications of the study results; the theoretical, empirical and methodological contributions

of the study; limitations of study; and concludes with suggestions for future research.

 

 

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CHAPTER TWO
THE GLOBAL PHARMACEUTICAL INDUSTRY

This chapter has five sections. Section One presents an overview of the current
global environment for pharmaceutical products. Section Two traces the development of
the global pharmaceutical industry and the changes taking place especially in the post-
World War H period. Section Three discusses some of the unique characteristics of the
pharmaceutical industry. Section Four examines the determinants of competitiveness in the
global pharmaceutical industry. Finally, Section Five provides a summary of the present

chapter.

2.1 R T AD R MET

The global pharmaceutical industry is a multinational industry that is highly
regulated, capital intensive and driven by large R&D expenditures. The industry is
primarily privately owned and is technologically sophisticated.

The world market for ethical pharmaceuticals (excluding China and the former
Soviet Union) in 1992 was estimated to be US $163.4 billion (Scrip Magazine 1994). In
1990, the top 80 pharmaceutical firms worldwide accounted for about 90 percent of the
global sales of ethical pharmaceuticals. Of these 80 firms, US based companies
accounted for approximately 40 percent of global sales, European based firms accounted
for another 40 percent and Japan accounted for 20 percent of the world sales (USITC

1991, Figure 2.1).

 

 

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Figure 2.1: Global Sales by Corporate Nationality

20%
Japan

40%6
Western Europe

40%
USA

 

Source: Scrip League Tables

The largest pharmaceutical market for 1992 was the US — it accounted for twenty-
nine per cent of the world market. The second—largest market was Japan with eighteen per
cent world market share. Table 2.1 shows the ten leading markets in 1992 along with their
estimated market value, percentage share of world market and percentage growth. It can be
seen from the table that two of the developing countries, namely Brazil and South Korea
had the highest growth rates for 1992.

Of the fifteen leading companies worldwide in pharmaceutical sales for 1992/ 1993,
eight were US based, two were UK based, two German based and three were Swiss.
Merck & Co. of USA was the leading pharmaceutical company worldwide with an
estimated sales of $ 8,214.5 million (Scrip Magazine 1994).

Supported by an ever-increasing demand for health care, world production of
pharmaceuticals has grown at an exceptional pace throughout most of the post-war period.
Today nearly 60 countries have annual production levels of atleast $ 100 million (Ballance,
Pogany and Forstner 1992). The bulk of world production is however confined to only a

few countries.

10

Table 2.1: Leading Pharmaceutical Markets for 1992

 

 

 

 

 

 

 

 

 

 

 

 

Market Est. market value % world market % growth
(pounds billions)

US 32.6 29 6
Japan 19.9 18 3
Germany 9.5 9 5
France 8.2 7 8
Italy 6.8 6 5
UK 3 .6 3 13
Spain 3.0 3 11
Canada 2.4 2 9
Brazil 1.9 2 19
South Korea 1.8 2 15
Others 20.9 19 15

 

 

 

 

 

 

 

‘5

 

 

  
  

The I.
first emerge.
Netherlands.
pharmaceut;
production.
m’otit‘ths of 1

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11

The leaders continue to be those countries where modern pharmaceutical production
first emerged: Belgium, France, the Federal Republic of Germany, Italy, Japan, the
Netherlands, Sweden, Switzerland, the United Kingdom, and the United States. The
pharmaceutical industry in developing countries accounts for a fifth of the world
production. China is the largest producer among the developing countries, accounting for
two-fifths of this group's total in 1988 (Ballance, Pogany and Forstner 1992).

World consumption of pharmaceutical preparations (in constant 1980 US dollars)
was $ 70 billion in 1975 but had more than doubled, to $ 150 billion by 1990. However,
more than seventy per cent of all pharmaceuticals are sold in developed market economies.
The developing countries account for less than a fifth. Drug usage is growing most rapidly
in Japan and North America. The growth of the Japanese drug market has been
spectacular. The country's per capita consumption was already the highest of all
industrialized countries in 1975 and has continued to rise since then.

During the past decade, the pharmaceutical industry has undergone increasing
consolidation. Domestic and international mergers, joint ventures, and strategic alliances
proliferated in the global pharmaceutical industry in the 19803. The main reason for the
consolidation is the increase in R&D costs in recent years. Manufacturer's profits are also
being squeezed by increasing pressure from national governments to contain health costs.

Of the top ten leading companies in R&D expenditures, for 1993, seven were
European and three were US based. The average proportion of sales allocated to R&D by
these companies was 15.9 per cent. Of the top ten companies in terms of foreign
commitment (percent share of foreign to total sales), European companies dominated the

list with only one US company in the top ten (Scrip Magazine 1994).

 

Figur
pharmaceuu
One
inclusm' we
chemical 11
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12

2.2 EVQLUIIQE QE THE QLQBAL 131211513!

Figure 2.2 illustrates the important milestones in the evolution of the global
pharmaceutical industry1 .

One of the earliest milestones in the development of the global pharmaceutical
industry was the Pre-World War H development and commercial marketing by the German
chemical industry of a number of synthetically derived pharmaceutical products.

Many of the early chemical companies, such as those in Switzerland and Germany,
found that their technology to make synthetic dyes was readily transferable to
pharmaceuticals, resulting in the development and commercialization of a number of new
pharmaceutical products between 1908 and World War H. Advances in pharmaceutical
production technology were also made during this time.

The Swiss industry had established facilities early in the United States becoming
one of the first to become truly multinational in an effort to compensate for their relatively
small domestic market. After World War H, however, the US industry rapidly expanded
overseas.

The pharmaceutical industry worldwide became truly global in scope after World
War 11. Several interrelated factors contributed to this trend. Significant advances in
technology which led to the discovery of newer, more effective therapy took place in this
period. Manufacturing know-how increased, enabling production of pharmaceuticals in
huge quantities. Demand for medications increased world over because of their greater
effectiveness and availability. This was coupled with increase in economic growth leading
to greater purchasing power of consumers, helped by national health insurance systems in

some countries.

 

lSee Smith (1983) for a review

 

 

1899
1906
1908
1914
1931
1935
1939
1941
1951
196
197
197
191

191

Adapted fj

13

Figure 2.2: Important Milestones in the Evolution
of the Global Pharmaceutical Industry

1899 - Discovery of Aspirin

1906 - Pure Food and Drug Act (USA)
1908
1914 - World War I

Discovery of Salversan (Germany)

1931
1935
1939 - World War II

FDA established (USA)

Discovery of Sulfa Drugs

1940 - US spends $3 million on Penicillin research

1950-1960 - Multinational expansion by US firms

1962 - Kefauver-Harris Amendment to the FDCA

1975 - Revision of Japanese investment policies

1975-1985 - Dramatic rise in biotech firms in US

1989 - Mergers/Acquisitions

1990-1995 - Patents on approximately 200 products to expire in the
US

Adapted from USITC (1991)

14

However to better understand the tremendous changes taking place in the period,
the post World War II period can be divided into three important eras, namely, (a) 1940—
1960: The Golden Era (b) 1960-1980: Era of Regulation and (c) 1980 - to the present: Era
of Strategic Alliances which are discussed below (Agrawal 1993).

l - : 1d E

Several synthetic compounds were discovered in this period. The availability of a
wide range of synthetic compounds and the advent of public health care systems coupled
with a surge in economic prosperity and political stability, created a tremendous grth in
the international pharmaceutical market (Keller and Smith 1969).

During this period, the US drug firms dramatically increased their investment
abroad. Between 1950 and 1959, the value of total US. investment abroad rose from
twelve billion dollars to almost thirty billion dollars. A prominent observer during this
period dubbed this phenomenon of frenzied international expansion as the " gold rush"
(Moskowitz 1961).

The key factor in the early success of the American drug companies was their
technological leadership. A number of important pharmacologic innovations in United
States, particularly in the antibiotic and corticosteroid fields, produced a virtual revolution
in the pharmaceutical marketplace. Technological leadership coupled with adequate
resources and a lack of organized competition enabled many of the larger American drug
companies to secure important market positions. By 1960, the US. lead in the drug export
race, with Switzerland, Great Britain, West Germany, and France also in the race

(Chemical Engineering News 1960).

Waugh
This period was characterized by increasing discontent of the public with the

industry especially in the US and Britain leading to greater regulatory controls over the

 

 

pmuiccs (
iugx"ar
1

being in
1961 a]

amend:

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£11

15

practices of drug firms. Cries of "unethical promotion," "excess profits'" "soaring costs of
drugs," and the like were commonly heard (Chemical Engg News 1961).

The thalidomide disaster2 served as the catalyst for increased regulatory reforms
being implemented (Smith 1983). The US passed the Kefauver-Harris amendment in
1961 which imposed serious regulatory controls over the American based companies. This
amendment made pharmaceutical research a more expensive and time consuming process
by requiring substantial evidence of efficacy for approval of new drugs.

Germany introduced new regulations concerning advertising of pharmaceuticals and
related products during this period. Stringent governmental rules discouraged several

smaller firms from venturing abroad in the 19605 and 19705.

T t' The e '

In the past few years, the traditional strengths of the pharmaceutical companies -
patented products, pricing flexibility, and steady innovation - have begun to erode.
Today, it costs anywhere from a hundred million to a hundred and twenty-five million
dollars to develop a new drug, which is up from about ten million dollars just twenty years
ago (Financial World 1989).

These developments have led companies to form strategic alliances with each other
(James 1983; Financial World 1989; USITC 1991). This trend of acquisitions and mergers
is expected to continue in the future, in an attempt to reduce R&D costs and duplication of
efforts.

Japanese firms are also moving to set up joint ventures and subsidiaries as their
home market gets saturated. Japan already has two drug firms in the world top twenty,
and has overtaken America as the world's most innovative drug producer, ranked by the

number of new drugs (The Economist 1988).

 

2Thalidomide was a tranquilizer-sedative marketed by Chemie Grunenthal in West Germany as a non-
prescription drug. The product was distributed for approximately 3 years before Dr. Leng, a pediatrician at
the University of Hamburg, discovered and reported to the company that it caused phocomelia, a birth defect
in infants. By this time, several thousand infants had been affected.

 

  
 

detailed im'c
accomplishn
world's laho'
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the world.
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16

2.3 HA TER T F E I D TRY

There are a number of reasons why the global pharmaceutical industry merits a
detailed investigation. One is that although the industry's history is comparatively brief, its
accomplishments are impressive. A flood of life-saving drugs has emerged from the
world's laboratories over the past four decades. By combating many fatal diseases and
eradicating others, drug producers have helped to alter mortality patterns in many parts of
the world.

A second reason is the highly politicized environment in which drug companies
operate. Their performance, whether measured in terms of product development, prices,
safety or efficacy, is a vital determinant of health. Regulations vary from country to
country, but all governments intervene extensively to ensure that national standards are
met.

A third noteworthy feature of the industry is that it combines a unique blend of
scientific knowledge, manufacturing skills and marketing tactics. At one end are large
teams of organic chemists, biochemists, biophysicists and pharrnacologists who use all the
tools of modern science in their search for new drugs. At the other are huge - and highly
competitive - networks for distribution and promotion which operate in markets where
performance is closely monitored by governments. Sandwiched between these two crucial
parts of the industry is the production of drugs.

A fourth characteristic of this industry is the extent of internationalization and
diversity which exists. A great deal of the industry's research and production occurs in
only a few countries. However the markets for drugs are global. The types of
pharmaceutical firms are just as varied and diverse as their markets. In addition to the
multinationals and their subsidiaries, there are many small and medium-sized firms, niche
producers, and other specialists identified by their research or marketing strengths or by the

Specific types of drugs they produce.

 

   
  

1er 1'5 con:
represents :
pharmaceut:

19911.

17

Finally, the pharmaceutical industry is especially important for the United States.
The US continues to be the world leader in discovering and developing new medicines and
represents the world's largest single market for pharmaceuticals. In 1991, US
pharmaceutical exports exceeded imports by about S 1 billion (US Industrial Outlook
1991).

2.4 ETER A T F MP TI E E I
PHARMACEUTICAL INDUSTR!

A study conducted by the US International Trade Commission in 1991 on the

global competitiveness of the US pharmaceutical industry concluded that:

(1) The competitiveness of the US pharmaceutical industry as well as of those
in other countries, depends largely on the ability of firms within the industry
to develop innovative products, and innovation in turn, depends on the
ability to finance R&D.

(2) Government policies, both domestic and foreign have a more significant

effect on the level of industry innovation than many of the other factors
studied (USITC 1991).

The USITC study concluded that the US pharmaceutical industry has maintained a
high degree of competitiveness during 1980-90, as compared with the industries in
Western Europe and Japan. The study found that the US industry was a leader in
innovation during 1975-89, developing the majority of the globally successful products
introduced during this time period.

This is in contrast to the conclusions published in the report of a study done by the
National Academy of Sciences (NAB 1983) to assess the competitive position of the US
pharmaceutical industry in the world economy. The study found a declining trend in the
US share of R&D expenditures and drugs entering clinical trials and predicted further

decline in US shares of pharmaceutical introductions, sales and exports.

 

  
  
  

Fun?
For examp'.
whereas L'S
SCllp - \‘ilflt‘
in which L’S

Figur
Western Eur
Europe shot!

an Upward t.

 

:1 “CF. Introduced

 

18

Further, more recent data indicates that Japanese companies may be catching on.
For example, for the years 1982 - 1993, Japan introduced 158 new chemical entities
whereas US introduced 123 new chemical entities in the same period (Author‘s estimates,
Scrip - various issues). Although these NCEs do not represent globally successful NCEs2
in which US is still a leader, the data should still be a cause for concern.

Figure 2.3 illustrates the pattern of NCE introduction from 1961 to 1990 by US,
Western Europe and Japan. The number of NCEs originating from the US and Western
Europe show a declining trend, whereas the number of NCEs originating from Japan show

an upward trend for the past decade.

Figure 2.3
NCE Introductions by US, Western Europe and Japan

 

 

I 1961-70

0)

O

O
I
I

[11971-80

I 1981-90

 

 

 

 

 

# NCE: Introduced

 

 

LS W.EUF10PE JAPAN

 

 

 

Source: Author's estimates based on various sources

2 A globally successful NCE or global NCE is defined as an NCE that has been approved/marketed in at
least seven of the major pharmaceutical country markets, i.e., France, Germany, Japan, Italy, Switzerland,
UK and the US.

 

 

   

It is dontinr
industry he»

recent past

marketing t;
tdevelop ne

markets.

19

2.5 SJLMMARX

The global pharmaceutical industry is highly multinational and research intensive.
It is dominated by companies from the US, Western Europe and Japan. Over the years, the
industry has faced increasing regulatory pressures from national governments and in the
recent past has been characterized by mergers and strategic alliance formation. The
industry combines a unique blend of scientific knowledge, manufacturing skills and
marketing tactics. Competitiveness in the global industry depends on ability to innovate
(develop new drugs) and overcome market and regulatory barriers of varying country

markets.

 

 

This
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Competitii

(1101131 Sty;

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expl'dir

CHAPTER THREE
REVIEW OF LITERATURE

This chapter reviews the theoretical, conceptual and empirical literature that
provided the basis for development of the conceptual framework for the study; the research
design - including the constructs, measures and hypotheses used in the research study; and
for drawing implications and conclusions from the study results. Three streams of
literature are discussed below: (1) Theoretical and Conceptual Perspectives on National

Competitiveness, (2) Competitiveness in the Global Pharmaceutical Industry and (3)

Global Strategic Perspectives.
3.1 MP I E - T RE AL AND
E E T

National competitiveness has become one of the central preoccupations of
government and industry in every nation, especially so in the US. The competitiveness of
the US economy in the global market became a growing concern during the 19808, due to
sustained deterioration in the US trade deficit. The loss of market share in products such as
microelectronics, an industry many thought invulnerable to foreign competition, began to
raise questions regarding the overall intemational competitiveness of the US economy. Yet
for all the discussion, debate and writing on the topic, there is still no persuasive theory to

explain national competitiveness (Porter 1990).

20

 

 
 
   

competitive:
rates. intere
function ot
competitix'e:
relations. 1’
competitiver
"cor
cont
vshi
(Cc
Th.
fact that c.
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indicator
Variables
t
lEVeL 11
etampr
or firn
SCCIOr;
Sll’eng
Wage.
comp
exam

r

dildn

21

3.1.1 Definition of National Competitiveness

An accepted definition of the term "competitiveness" is lacking. Some see national
competitiveness as a macroeconomic phenomenon, driven by variables such as exchange
rates, interest rates, and government deficits. Others argue that competitiveness is a
function of cheap and abundant labor. Another popular explanation for national
competitiveness is differences in management practices, including management-labor
relations. Porter (1990) identifies productivity as the major determinant of a nation's
competitiveness. According to the President's Commission on Industrial Competitiveness,

"competitiveness is the degree to which a nation can, under free and fair market

conditions, produce goods and services that meet the test of international markets

while simultaneously maintaining or expanding the real incomes of its citizens"

(Commission on Industrial Competitiveness, 1985).

The lack of clarity on the definition of national competitiveness is due in part to the
fact that competitiveness is a multidimensional concept that cannot be reduced to a single
variable or indicator. A second difficulty arises from the fact that it is difficult to consider
indicators of competitive position separately, without reference to underlying causal
variables (Hatzichronoglou 1991).

Although it is appropriate to consider international competitiveness at the national
level, it has a different meaning when applied at the industry or individual firm level. For
example, at the sectoral level, competitiveness may be defined as the ability of an industry
or firm to sustain and/or expand its market position. Competitiveness at the national
sectoral levels are intertwined, however, since the former depends on the competitive
strength of firms and/or industries to generate productivity levels needed to support high
wages and hence higher standards of living in the economy. Similarly sector
competitiveness depends on appropriate policy at the national level, that would, for
example, provide a framework for the promotion of high levels of skill through education

and maintenance and/or development of infrastructure.

22
Bruce Scott of the Harvard Business School has defined national competitiveness

"a nation state's ability to produce, distribute and service goods in the international
economy in competition with goods and services produced by other countries, and
to do so in a way that earns a rising standard of living" (Scott and Lodge 1985).
There are three critical aspects to this definition. First, it is mom, that is the
export performance of a nation is considered relative to that of others. Second, it is a
W concept, that is the ability of a nation to earn a higher standard of living
by production and marketing skills, rather than by international borrowings. Third, it is a

M15; concept as it evaluates the manner in which a nation seeks to increase and

distribute its welfare over time, given its international and domestic commitments.

3.1.2 Theory of Comparative Advantage

This theory also refened to as the classical theory explains the success of nations in
particular industries based on so-called factors of production such as land, labor and natural
resources. Nations gain factor-based comparative advantage in industries that make
intensive use of the factors they possess in abundance. Classical theory, however, has
been overshadowed in advanced industries and economies by the globalization of

competition and the power of technology.

3.1.3 WES!!!

Although there may be little agreement on the definition of competitiveness, there is
general consensus in the more recent literature that national competitiveness depends on
much more than the cost of production and prices of output. Technology is increasingly
recognized as the most important determinant to achieving competitive advantage in the
global economy (Niosi 1991; Scott 1985; Porter 1990; Ernst and O'Connor 1989). Recent

studies on international competitiveness emphasize the central role played by technology in

 

—

determining

been empha~

Gomullta t ‘1‘

 

 

1985'. Ernst .
The:

 

 

as the techno

The 11

 

innovative a;

 

in output an
command h
countries wi
level of Val
Louis Emrn
"Tc
har
dll‘
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ins.
\V
Particuja

Compare

natiOhs 1
the imp
“21110” S

ma9Var

23

determining the world market share (Davis 1991; Dosi and Soete 1991; Scott and Lodge
1985; Ernst and Connor 1989; Porter 1990).

The role of technology and innovation in economic growth of a nation has long
been emphasized by industrial economists since the time of Schumpeter. Posner (1961),
Gomulka (1971) and Cornwall (1976) developed this approach into what they referred to
as the technology gap theory.

The technology gap theorists relate the technological level of a country to its lelel_of
W. A high level of innovative activity means a high share of "new" goods
in output and an extensive use of "new" techniques in production. Since "new" goods
command high prices and "new" techniques imply high productivity, it follows that
countries with comparatively higher level of innovative activities also tend to have a higher
level of value-added per worker, or GDP per capita, than other countries. According to
Louis Emmerij, President of OECD,

"Today, oligopolistic competition and strategic interaction rather than the "invisible

hand" of market forces, condition comparative advantage and the international

division of labor. The introduction of new technologies plays an important role in
this process. Firms as much as nations are striving to utilize technology as an

instrument of global competition.."(Emst and O'Connor 1989, p. 8).

When one looks at any national economy, there are striking differences among a
nation's industries in competitive success. International advantage is often concentrated in
particular industry segments. In many industries and segments of industries, the
competitors with true international competitive advantage are based in only a few nations.

Porter's study (1990) examined high-technology industries in ten important trading
nations to investigate why nations gain competitive advantage in particular industries and
the implications for company strategy and national economies. The study found that a
nation's competitiveness in a particular industry depends on the capacity of its industry to

innovate and upgrade. Companies from such nations gain advantage against the world's

 

 

best compc

   
   
 
  

domestic rit
qu
competitite'
conditions
demandt‘. R
Differences
in addition 1
The
challenger
higher lEV
create an .
1

COmpetit
[CC 1100 l(

andtcw

comp-:-

llaVe 1
‘11 th.

3.1.4

30%:

10Wa

24

best competitors because of pressure and challenge. They benefit from having strong
domestic rivals, aggressive home-based suppliers, and demanding local customers.

Four broad attributes of a nation contribute to innovation and subsequent national
competitiveness, both individually as well as a system. These attributes are: Factor
conditions (labor, infrastructure, etc.); Demand conditions (nature of home-market
demand); Related and Supporting Industries; and Firm strategy, structure and rivalry.
Differences in national values, economic structures, institutions, and histories all contribute
in addition to competitive success.

The study also concluded that the proper role of government is as a catalyst and a
challenger; it is to encourage-or even push-companies to raise their aspirations and move to
higher levels of competitive performance. Government policies that succeed are those that
create an environment in which companies can gain competitive advantage.

The literature on international technology transfer also provides some insights on
competitiveness in the global economy (Robinson 1991). Competitiveness in high
technology industries depends on: (a) Supply of technology, (b) Demand for technology

and (c) Intermediaries and linking mechanisms.

3.1.4 W

The role of government and public policy in a nation's effort to achieve international
competitiveness has been a subject of much debate. Three major policy recommendations
have been offered in the literature as a whole: (1) the activist industrial policy perspective,

(2) the managed trade perspective and (3) the neoclassical or liberal economics perspective.

3.1.4.1 WW1:

The advocates of industrial policies in the early 19805 recommended an active
government role to enable all industries within an advanced economy to shift production

towards higher value-added and more competitive outputs (Wachter and Wachter 1982;

 

Magaziner z
industries ft
agreements 1
out to ease a
from impor
employees t
subsidies. l

abroad.

Ma
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agreement
€01'Emme
Goldstein
solely to 1
abroad. 1
1&8111C110n
113116 pen
5993' 011

Planned p

3.1.4, 3
11
and mam,

Competirir

HMSOPQU

25

Magaziner and Reich 1982; Adams and Klein 1982; Johnson 1984). For declining
industries for example, proponents of the activist industrial policies recommend that
agreements between the US and governments of other advanced nations should be worked
out to ease adjustment of less competitive firms by granting subsidies as well as protection
from imports for a limited period, as needed. For emerging businesses with high-skilled
employees characterized by rapid technological change, the US government should provide
subsidies, loan guarantees, and tax benefits to lure them to locate at home rather then

abroad.

3.1.4.2 T d d P iv

Managed trade can be broadly defined as trade that is controlled, directed, or
administered by government policies and conducted by either bilateral or multilateral
agreements (U SITC 1991). The proponents of managed trade recommend some form of
government involvement in high-technology industries (Reich 1983; Tyson 1990;
Goldstein and Krasner 1984). They suggest that the fate of these industries cannot be left
solely to market forces, particularly in the presence of activist government intervention
abroad. They recommend active intervention in the form of export subsidies and import
restrictions. Both the activist industrial policy and managed trade proponents use Japanese
trade performance to support their views since they consider Japan's success as a case
study of how a country can realize its trade-related goals through extensive, but carefully

planned protectionism.

3.1.4.3 W1:

The proponents of the liberal or neoclassical perspective reject the activist industrial
and managed trade policy recommendations for enhancing the US economy's international
competitiveness (President's Commission on Industrial Competitiveness 1985; Dixit 1986;

Hatsopoulos, Krugman and Summers 1988; Porter 1990; Landau 1990). They argue that

 

 

   
   
  

pursuing su.
about the ct
economists 3
economy an
in the econo

and increase

For e

 

national con
maintain an .
higher sat’ir
horizons on

R&D.

3.1.4.4
Sir
C9mpetitit
lllllm‘atim
T1
2m“emptir.
innmatte:
- 0r haw.
gOVEmU—
regularic
1
iYmOVau
Robfirtg
Thoma.

26

pursuing such a strategic trade policy would require vast, unknown amounts of information
about the economy and extemalities associated with interventionist policy. Also, most
economists believe that such policies could result in raised costs for other sectors within the
economy and in trade wars. The liberal economics view is perhaps the most accepted view
in the economics literature of promoting the US economy's international competitiveness
and increase the standard of living.

For example, Porter (1990) recommends the following government initiatives for
national competitiveness: maintain a strong antitrust policy to foster domestic competition;
maintain an open trade policy and avoid devaluation to boost exports; create incentives for
higher savings and allow interest rates to fall to encourage investment and longer time
horizons on R&D projects; and fund university research centers to rejuvenate national

R&D.

3.1.4.4 ndu ' v ' n i I'

Since innovation drives technological growth and therefore industrial
competitiveness, it is important to look at the effect regulation can have on industrial
innovation processes.

There have been more studies done on the factors endogenous to the firm in
attempting to explain innovative success or failure; that is they have considered the
innovation process more or less exclusively from the point of view of what managers have
- or have not - done and by and large neglected external factors such as the role of
government (Rothwell and Zegveld 1981). The studies that have examined the impact of
regulation on industrial innovation processes are reviewed below.

Perhaps more has been written about the effects of regulation on the rate of
innovation in pharmaceuticals than in any other single sector of the industry (Hauptrnan and
Roberts 1987; Young 1982; Grabowski and Vernon 1976; Grabowski, Vernon and
Thomas 1978; Hansen 1979; Peltzman and DiRaddo 1980; Peltzman, May and Trirnble

 

1982:1119;

 

1916; Lasai

1974'. Schar

 

regulation o
watershed.

significantlt

 

obsert'ed dil
1963 Amenr
A st
Chcmicals it
90111 quanti‘
also indica
beginning ;
Amefldmer
the United
“‘35 Opera
1116 rare 0'.
10 indlCatc
H.
quality. ‘
Stm’ard

\

27

1982; Wiggins 1981; 1983; Brownlee 1979;C1ymer 1970; 1975; Cooper 1969; 1976; Jaffe
1976; Lasagna 1969; 1972; Lasagna and Wardell 1975; Mitchell and Link 1976; Sarett
1974; Schankerrnan 1976; Schwartzman 1976; Wardell 1973; 1974)

Much that has been written has focused on the impact of the 1962 Kefauver-Harris
Amendments to the US Food, Drug and Cosmetics Act1 . Most analyses of the effects of
regulation on innovation in the US drug industry have treated the 1962 Amendments as a
watershed. According to Peltzman (1973), for example, the 1962 Amendments
significantly reduced the flow of New Chemical Entities (NCEs), and furthermore all the
observed differences between the pre- and post-1963 NCE flows could be attributed to the
1962 Amendments.

A study done by Steward (1977) of the new pharmaceutical products and new
chemicals introduced in the US between 1948 and 1975 demonstrated a marked decrease in
both quantities during the 19605. However when comparable data for the UK was used, it
also indicated a decline in total pharmaceutical products and in new chemical entities
beginning about 1960. Thus, it would appear from this evidence that the Kefauver—Harris
Amendments were not the only factor in causing a decline in pharmaceutical innovations in
the United States, but that the decline was part of a broader, underlying phenomenon which
was operating worldwide. Comparison of the US and UK data does show, however, that
the rate of decline was very much sharper in the US than in the UK, which might be taken
to indicate the added impact in the US of the 1962 Amendments.

However, it is not only the quantity of new drugs which is important, but also their
quality, that is their therapeutic significance. Using data for the years 1950 to 1973,

Steward (1977) examined the annual approval of NCEs by degree of therapeutic

 

1 Following the thalidomide tragedy, the US Congress passed the Kefauver-Harris Amendments. This
extended the mandate and regulatory control of the FDA in several ways:

- it required firms to provide documented scientific evidence of a new drug's efficiency in addition to
the proof-of-safety required by the original law.

- it gave the FDA, for the first time, discretionary power over the clinical research process. Thus,
prior to any tests on human beings, firms are now required to submit a new drug investigational
plan (IND) giving the results of animal tests and research protocols for human tests.

 

 

  
  
  
  

importance
modest gait
introductiot

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28

importance2 . It was found that while there was a general downward trend for drugs with
modest gain and little or no gain, the 1962 Amendments had little impact on the rate of
introduction of drugs offering an important gain. However, a marked decrease in new
introductions for all three classes of drugs was found to have occurred between 1966 and
1969. This might represent the true impact of the 1962 Amendments taking into account
the lead times inherent in new drug development.

Another effect of regulation on innovation of pharmaceuticals is in delaying the
market launch of new products and processes through lengthening approval times (Garrett
1974). There is also evidence to suggest that because of the greater severity of regulation
in the United States, important new drugs are sometimes marketed there, many years after
their acceptance in other countries. For example, in 1989, eighteen of the twenty-three new
products approved for marketing in the US had received their first marketing approval in
countries other than the US. During 1984-88, 88 of the 113 products introduced in the
United States were first approved in a foreign country (PMA Statistical Fact Book 1989).

Section 3.2 discusses additional regulatory effects such as patent laws, pricing

policies, and product liability laws on pharmaceutical innovation.

3.2 I l'E .1 EN ._ IN HE LAO} ' 5L ‘ TI ,2-
121111518!

Empirical analysis of competitiveness in the global pharmaceutical industry has
concentrated primarily on factors influencing the supply of ethical pharmaceutical products
(factors affecting innovation). Further, much of the analysis is related to or in response to
the debate regarding the effects of regulatory measures and other government policies on

the industry. For the most part, research has focused on the activities of US firms in the

 

2 NCEs are classified by the FDA into three categories: (1) drugs offering little or no gain, (2) drugs
offering modest gain and (3) drugs with important gains.

 

 

 

firms. Gro‘

 

successful
Phannaceuti
ill Bus
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29

US market. Empirical analysis of the US industry's competitive position in the

international market is relatively limited.

3.2.1 i v i
Research is the foundation of competitive strength for modern pharmaceutical

firms. Growth in sales and profits for major ethical drug companies are derived from

successful new products discovered and developed through industry research efforts.

Pharmaceutical research may be divided into four phases:

(1) Basic research - advancement of basic pharmacological knowledge. This is the
only phase not directly regulated by the government, although government
regulation has a substantial indirect impact.

(2) Discovery effort - the synthesis of active substances and the establishment of
biological effect.

(3) Applied research - the extensive biological (animal) and clinical (human) testing of
substances to determine pharmacological activity and risk of adverse effects.

(4) Development - the determination of dosage form, the development of manufacturing
processes, and the production of drug product.

Since investment in R&D is one of the most important criteria for success in the
pharmaceutical industry and since regulation is one of the most common factors affecting
R&D investment decisions of firms, most empirical studies have concentrated on the effect
of regulation on R&D as mentioned above. Some of these studies are reviewed below.

The most recent study to date was done by the US International Trade Commission
(USITC 1991). This study was done to assess the competitive position of the US

pharmaceutical industry in the global economy.

This study used two data sets. The first data set consisted of various annual
economic, demographic and health related measures from 1983-88 for seven countries
whose pharmaceutical industries are competitive. These were: France, Germany, Italy,
Japan, Spain, UK and US. This data set was used to do a country level analysis.

The second data set comprised of various measures relating to R&D, firm size and

sales for a sample of pharmaceutical firms from US, Western Europe and Japan. A total of

twenty-nine firms were used. This data set was used to do a regional comparison at the

 

 

 

  
 

firm level.

of the studs

13) Na .

131 11121

 

Grat
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30

firm level. The analysis consisted of a number of regression estimates. The main findings

of the study were:

(1) A growing national economy provides an important underlying base for the
pharmaceutical industry. Growth in national income, growth in GDP/capita, and a
higher life expectancy were used as indicators of a growing economy.

(2) National research efforts help foster the discovery of innovative NCEs and that
relatively higher prices for pharmaceuticals partially explain the larger number of
NCEs introduced into a country.

(3) Higher levels of R&D expenditures and R&D employees are important for global
market share and productivity.

Grabowski (1989) examined the competitiveness of the US pharmaceutical industry
with respect to indicators such as: (1) number of new products under development in 1986
by corporate nationality (2) new product introductions by corporate nationality during
1961-86 (3) number of global NCEs by nationality of originating firm during 1970-83 (4)
world wide sales by corporate nationality for 1980, 1984 and 1986. The countries for
which the above data was compared were US, Japan, West Germany, France, Italy,
Switzerland and UK.

However no statistical tests were conducted. The raw data was simply examined
for major trends in order to draw conclusions. Grabowski concluded that the US industry
is currently the leader in worldwide sales, R&D activity and new drug candidates under
development. The US industry was also found to be significantly more responsible for
commercially important new drugs and global N CEs.

However Grabowski also cautioned that foreign competitors particularly Japan
could provide a strong challenge to US leadership in pharmaceuticals over the next few
decades. The European pharmaceutical industries were found to have a generally declining
position in the 19805. This was attributed to control on drug prices in their domestic
markets. Grabowski also concludes by saying that current US policies in the health sector

are increasingly driven by priorities that could result in a less favorable economic

environment for new product introductions.

 

 

 

The

   
  

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production.

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31

The National Academy of Engineering conducted a study to evaluate the competitive
status of the US pharmaceutical industry in the international market (NAB 1983). The
study used six indicators to measure competitiveness: research effort, innovative output,
production, sales, market structure and international trade. Data for the US, Western
Europe and Japan was compared. The study found a decline in US based drug production
as a percentage of world drug production, and a decline in the US share of world
pharmaceutical R&D. A combination of factors were blamed for the decline. These were:
foreign nontariff barriers, US FDA regulations, patent laws, product liability laws, antitrust
policies, and R&D tax incentives.

The NAE study concluded that although the US industry was likely to remain a
significant force in the international market, decreases in various measures of industrial
performance relative to other major international pharmaceutical producers suggested that
the industry would lose its dominant position.

In a follow up study by the US Department of Commerce's International Trade
Administration (ITA 1984), it was concluded that US was and would continue to be
internationally competitive. However the study identified a number of policy issues that
could affect the global position of the industry. It concluded that US companies were likely
to be at a disadvantage because of the significantly longer US regulatory review periods.

Thomas (1989) compared the performance of the US industry to that of other
countries' industries using a ten nation sample. He concluded that firms competing
successfully in the international market do so by developing innovative new drugs that can
be successfully marketed in most major country markets. He suggested that a critical factor
contributing to a company's ability to compete successfully in the international market is the
degree of competition in the company's home market. Three factors contribute to

competitive home country markets: rigorous quality restrictions on market access; high

levels of publicly funded biomedical research; and unregulated domestic prices.

 

 

 

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issues in the
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32

A report issued by the Council on Competitiveness (1991) emphasizes that factors
such as science education, funding for R&D, and relative freedom from price control are
important to the continued competitiveness of the US industry.

Table 3.1 presents an overview of the studies on global pharmaceutical

competitiveness.

3.2.2 WWW

As mentioned earlier, most conceptual and empirical work on competitiveness
issues in the pharmaceutical industry has concentrated on supply factors, i.e., factors that
influence the extent and rate of pharmaceutical innovation.

However as recently pointed out in the report by the US International Trade
Commission, it is equally important to look at factors that affect the inter-country diffusion
of new pharmaceutical products, i.e., factors affecting demand for pharmaceutical
innovations across national markets. Knowledge of such factors provides the firm with a
competitive advantage with respect to choosing markets more strategically for introduction
of pharmaceutical innovations. It is also important from a public policy perspective to
examine factors that delay market introduction of therapeutically significant drug
innovations.

According to Redwood (1988), the ability to both innovate and market new drugs is
crucial for global competitiveness and that "one without the other is hardly a tenable
proposition for survival in the upper reaches of the ethical sector of the pharmaceutical
industry" (p. 72).

Only a handful of empirical studies have examined the factors affecting diffusion of
pharmaceutical innovations in the international context. The few, with the exception of
Parker's study (Parker 1984), have focused on the effect of regulatory conditions on the

international diffusion of new drugs.

 

 

 

NAE119§3

lTA llgfx‘:

momas

 

33

Table 3.1: Overview of Studies on Global Pharmaceutical Competitiveness

 

 

 

Study (a) Factors examined Determinants of
(b) Countries/Regions Competitiveness
(findings)

USITC (1991) (a) Economic, demographic and Innovation; growing economy,
social factors; R&D measures; R&D incentives; low price
firm size; and sales. control; R&D investment.

(b) France, Germany, Italy,
Japan, Spain, UK, and US.

Grabowski (1989) (a) Number of drugs under Innovation; R&D investment;
development; NCE introductions; commercial potential of NCE.
global NCEs developed; global
sales.

(b) US, Japan, Germany, France,
Italy, Switzerland, and UK.

NAE ( 1983) (a) Research investment; regulatory conditions -
innovative output; production; specifically FDA regulations;
sales; market structure and trade patent laws; product liability
balance. laws; antitrust policies; and R&D
(b) US, Japan and Western tax incentives.

Europe.

ITA (1984) (a) Sales; production; Innovation; productivity of R&D;
employment; productivity; R&D; regulatory approval time; quality
and profitability data. of NCE.

(b) Industrialized countries.
Thomas (1989) (a) Various regulatory and market Innovation; competitive markets;

Council on Competitiveness
(1991)

 

related factors
(b) Industrialized countries

(a) Various regulatory and
economic factors.
(b) Industrialized countries.

 

stringent quality regulations; high
research funding; and unregulated
domestic prices.

Science education; R&D funding;
and freedom from price control.

 

 

. _
.

   

 

1...... 2
:11...

e

 

   

 

 

34

Grabowski and Vernon (1977) analyzed the introduction of US discovered drugs
into the UK for 1960—1972, to see the effect of the Kefauver-Harris Amendment on US
firms' strategy on foreign NCE introductions. A dramatic shift was found to have occurred
as a result of the Amendment. For the early 19605, US firms introduced majority of the
new drugs into UK orgy after first introducing them into the US. For the period 1972-
1974, however, more than two-thirds of US discovered NCEs were first introduced into
the UK instead of the US.

Grabowski (1980) found a lag in foreign discovered NCE introductions into the US
with respect to Europe. More seriously, the lag with Europe was not confined to drugs
with little or modest therapeutic gain, but also included drugs that the FDA itself ranked as
significant therapeutic advances. He attributed regulatory changes as the major factor
contributing to the lag. Lag of foreign discovered NCEs was especially significant because
foreign discovered NCEs accounted for one half of the drugs rated therapeutically
significant by the FDA during the period analyzed (1968-1973). These medically
significant drugs of foreign origin were all introduced into the US with very long time lags
- three to six years after they were introduced into the UK

Popper and Nason (1993) examined the effect of various regulatory conditions
using NCE introduction data over a twenty year period, 1970-1989. The countries for
which the data was collected were France, Germany, UK, Italy, Japan and the US. The
regulatory aspects that were examined for their effect on extent and tinting of NCE
introductions were: generic substitution, national health insurance plans, national formulary
system, acceptance of foreign clinical testing, patent protection, compulsory out-licensing
and R&D pricing incentives.

Both generic substitution policies and presence of national health plans seemed to
increase diffusion lags. Compulsory out-licensing did not seem to affect number of
product introductions but significantly increased the time taken for products to reach the

market. Acceptance of foreign clinical data was associated with shorter time lag to

 

 

35

introduction as were R&D pricing incentives. Market size was found to be positively
related to number of product introductions but did not influence time lag for introduction.

The most comprehensive study to date on international diffusion of pharmaceuticals
is the study by Parker (1984). Parker used a sample of eighteen countries comprising of
nine industrialized and nine developing countries. The time frame used in the study was
from 1954 to 1978. A total of 192 brand name pharmaceuticals were included in the
analysis. The arrival time lag or diffusion lag was the dependent variable. This was
measured as the time between marketing of the drug for the first time in a country and its
subsequent marketing elsewhere. The independent variables examined were: regulatory
tightness of country, therapeutic importance of drug, market attractiveness, and type of
country.

Countries with the toughest regulatory environments had the lowest mean arrival
time lags. Parker attributed this surprising result to the relationship between market size
and regulatory environment. The countries with the stringent regulatory environments
were also the ones with the large market size. Therefore countries with a larger market size
seemed to attract products earlier than those with a smaller market size inspite of the
regulatory climate. Mean arrival time lags were shorter for more important drugs than for
less important drugs but the relationship was not significant. With respect to type of
country, drug introductions were fewer among the less developed economics as well as
having higher mean arrival time lags.

Table 3.2 presents an overview of the studies on global pharmaceutical diffusion.

3.2.3 ___._. 2H. _|'r_:na F 11. i Pr: m' il in' ..V‘_!T_
Figure 3.1 illustrates the various supply and demand factors affecting

competitiveness in the global pharmaceutical industry. As shown in the figure, the demand

for ethical pharmaceuticals is determined by demographic and socioeconomic factors, such

as age of the population, diet or access to health care, etc. Government policies and

 

 

36

Table 3.2: Overview of Studies on Global Pharmaceutical Diffusion

 

 

 

Study (a) Factors examined Findings
(b)Countries/Re£ions

Grabowski and Vernon (a) Regulatory approval Diffusion lag in the US due

(1977) time. to longer approval times.
(b) US and UK.

Grabowski (1980) (a) Regulatory approval Diffusion lag in the US due
time; and therapeutic to longer approval time.
importance of NCE.

(b) US and Europe.

Popper and Nason ( 1994) (a) Regulatory aspects; and Regulatory aspects affect
Market size. rate and extent of diffusion.
(b) France, Germany, UK,

Italy, Japan, and US.

Parker (1984) (a) Regulation; therapeutic Regulation and market size

importance of NCE; market interact to affect diffusion;

 

size; and type of country.
(b) Nine industrialized and
nine developing countries.

 

diffusion is faster for more
important NCEs; and
developing countries have
longer diffusion lags.

 

 

37

programs such as cost-containment, degree of health-care financing, and support for
health-related education may also affect the demand for drugs, directly or indirectly.

An important factor affecting the supply of ethical pharmaceuticals is R&D activity,
i.e., the level and productivity of R&D spending. Such activity requires sufficiently high
profits, the ability to secure external financing, or both. Government actions ranging from
macroeconomic policies, treatment of product liability, tax policy, and regulatory controls
exert indirect and direct effects (positive and negative) on the ability of firms and the
industry as a whole to produce pharmaceuticals.

The demographic, social, economic, political, legal, and market related
characteristics that affect the international supply and demand for pharmaceutical

innovations are discussed below.

3.2.3.1 i Envir nm 11 om i '

National differences in population, density, life expectancy, birth rate, death rate,
composition, distribution, etc., create variations in market conditions which offer
opportunities as well as threats. They also influence supply and demand.

Larger the market potential for pharmaceuticals in a particular country, greater will
be the incentive for the firms in that country to innovate and introduce new products. A
key demographic factor affecting market potential for ethical pharmaceuticals is the
proportion of the elderly populace. Projections show that the population in many
industrialized countries is aging quickly.

The frequency of drug consumption is rising most rapidly in markets where the
population is aging. For example, data for Germany show that roughly 55 per cent of the
population aged over 44 years takes drugs at least once a week but only 15 per cent of
those between 14 and 44 years of age consume drugs this frequently (Ballance, Pogany
and Forstner 1992). Moreover, the types of drugs required by individuals aged under 45

years are different from those purchased by the elderly. They consist mainly of pain-

38

Figure 3.1: Determinants of Global Market Share
in the Pharmaceutical Industry

 

 

 

 

r1 Global flaunt
Shore

mm

2mm

2mm

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Source: USITC (1991)

 

 

39

killers, cough and cold preparations and digestives. These are frequently generics and are
less expensive than other drug types.

One-sixth of all Germans will be over 65 by the year 2000 and by 2010 half the
country's population will be 50 years or older. In contrast, in a developing country like
India only 25 per cent of the population will be fifty years or older by 2010 (Redwood
1988).

3.2.3.2 Soeial Eovironment god Commtitiveoess

These include the health care systems of the country - private and public,
dispensing practices of physicians, nature of consumer demand for pharmaceuticals, etc.
The types of national health care systems in industrialized and developing countries differ
greatly and their effects on the pattern of pharmaceutical consumption are equally disparate.

Governments in industrialized countries established very generous systems of
health care in periods when national income was rising and the proportion of old people in
the population was comparatively small. The public sector in most industrialized countries
accounts for more than half of all drug expenditures. The only exceptions are Canada and
the United States; in both countries a large portion of pharmaceutical expenditures is
covered by private medical insurance or involves direct payments by patients (Ballance,
Pogany and Forstner 1992).

Systems of public health care are a less significant determinant of consumption in
the developing countries. The main reason is the small proportion of total income available
for this purpose. Public expenditures on health care in most developing countries account
for between one and two per cent of gross national product (GNP), while in the
industrialized countries the figure is much higher, typically between six and eight per cent.
As much as two-thirds of the drugs purchased by patients in poor and medium-income

developing countries are paid for privately (Redwood 1987, p. 254-6).

40

Both the supply and demand for pharmaceutical innovations will be affected by the
nature of the public health systems. Greater the public health expenditure in a country,
greater will be the demand (hence diffusion) of new drugs as well as greater will be the
investments in the innovation process to generate N CEs due to the larger size of the market.

Several industrialized countries are now being forced to cut back on their health care
programs and pharmaceuticals are a favorite target. Reasons for the cutbacks include the
rising costs of caring for an aging population, the introduction of new and more expensive
drugs, and a general tightening of federal budgets. Because a large portion of the total
spending on drugs is paid for through public funds, the change in policy is having a
dramatic effect on consumption. The steps taken by policy makers include the introduction
of stricter policy controls, the withdrawal of reimbursements from selected products and
increases in patient contributions to the cost of drugs.

Doctors in several industrialized countries are now coming under pressure to
prescribe more economically and to use generic substitutes. This tactic is most popular in
the US where generics accounted for 29 per cent of all the country's drug sales in 1988.
The same is not the case in Western Europe. The slow rate of acceptance is partly due to
opposition from industry representatives and from the medical profession. Both groups

have vigorously resisted legislation to promote generic substitution.

3.2.3.3 WW

These include the overall level of development of the originating countries, per
capita income and distribution, disposable income, expenditure patterns, etc. The
pharmaceutical industry is highly research oriented and development of new ethical
pharmaceuticals runs into millions of dollars.

Developed country firms based in a growing or robust economy are the only ones

which can afford such costly investment. For example, Western European and American

41

dnrg companies have accounted for nearly 80 per cent of all NMEs (new molecular entities)
launched during 1961-90 (USITC 1991).

The economic attractiveness of markets is likely to be a significant influence on the
rate of inter-country spread of drugs. Wealthy countries with large markets for
pharmaceuticals may exert a strong commercial pull and attract foreign developed drugs
earlier than other poorer nations with less purchasing power.

For example, the US pharmaceutical industry has invested extensively throughout
the world. However, investment by the US pharmaceutical industry in the developed
nations accounted for about 75 percent of the total investment in 1986, with developing
countries accounting for only 25 percent. The major markets for US. drug exports in
1989 were Japan (21 percent of total), Germany (10 percent), Canada (8 percent) and Italy
(6 percent). The top seven pharmaceutical markets in the world accounted for 77 percent of
the world pharmaceutical sales in 1989. These countries were France, Germany, Italy,
Japan, Spain, the United Kingdom, and the United States. Thus the extent of diffusion is
clearly affected by market attractiveness (U .S. Department of Commerce, 1989).

More than 70 per cent of all pharmaceuticals are sold in developed market
economies. The developing countries account for less than a fifth, with the remainder
being consumed in East European countries and the USSR (Ballance, Pogany and Forstner
1992, Figure 3.2). Japan reports the largest share of per capita income spent on
pharmaceuticals (1.62 per cent in 1990) - almost twice the level in North America and some
parts of Western Europe. No similar increases have occurred in developing countries. In
fact the share of per capita gross domestic product (GDP) spent on pharmaceuticals has

actually declined in many of the poorer countries.

3.2.3.4 i’ vir t n iiv s
Factors such as political stability and continuity, ideological orientation,

government involvement in business, attitudes towards MNCs, national economic and

42

developmental priorities, etc., will affect a firm's ability and propensity to invest in R&D
and thus supply of innovative pharmaceutical products (Thorelli 1990; Toyne and Walters

1993). The industrialized countries are the most stable politically and emphasize basic

Figure 3.2: World Consumption of Pharmaceuticals, 1992

Eastern Europe
9.3%

    

Developing
economies
18.9%

Developed
Economies
71 .7°/o

research priorities. Firms from such countries are therefore likely to invest heavily in R&D
and produce more new chemical entities.

Political factors will also affect a firm's decision to introduce a new product in a
particular country (Thorelli 1990; Toyne and Walters 1993). Greater the number of
destination countries with high political instability, high government involvement in
business, high hostility of the government toward foreign firms or MNCs, and/or differing
ideologies of the governments, lower will be the extent and rate of global diffusion of the
product. For example, the pharmaceutical market share held by domestic firms in the
former Soviet Union in 1985 was a 100 percent with zero percent foreign involvement. In
comparison, market share by domestic firms in Canada was only 18 percent in 1985,

reflecting the high investment by foreign firms in Canada (Pradhan 1983, p. 21).

43

3.2.3.5 Envir en ' 'v

Government policies whether domestic or international can have a significant impact
both on the rate and extent of innovation in a country's industry as well as rate and extent
of diffusion of NCEs into the country, given the nature of the industry.

These government policies include regulatory approval procedures, pricing policies,
cost-containment efforts, patent law and intellectual property rights, product liability laws,
and tariff related matters such as granting of duty suspensions. Figure 3.3 illustrates the
entire drug development process cycle starting from basic research to its market approval to
patent expiry and finally re-investment in the research process. As seen in the figure, much
of the area of maximum risk is also that of maximum intervention by regulatory authorities,
reaching a financial climax when it comes to pricing and social security reimbursement.

As has been described in the previous sections, the role of regulation, in particular
the effect of changes in the US regulatory procedure for market approval of N CEs has been
the subject of analysis in majority of the studies on pharmaceutical innovation and
diffusion. The empirical studies examining this issue have been discussed above, thus the
section below will only focus on the regulatory approval procedures of other countries in
comparison to the US. Also other aspects of regulation mentioned above that affect the

supply and demand for innovation are discussed below:

Regulatory approval for new drugs: varies by country. Generally under the
FDCA, a new drug may not be commercially marketed in the United States, unless it has
been approved as safe and effective by the FDA. The average FDA review time for the 20
new drugs approved in the United States in 1988 was about 31 months, compared with an
average of approximately 15 months for foreign review of those of the 20 products that
were first approved overseas (PMA 1989). The drug development process from discovery

to FDA approval takes approximately 10 years. Any delays in the development and

44

Figure 3.3
Risks in Pharmaceutical R&D

Screenin

/—\. ,
Discovery,

Fiei vestment

Patent
protection

P fit \
IDEVELOPMENT I

  
 
  

 

 

Area of
Maximum
”"3““ clinical
Post-marketing 913“ trials,etc
surveillance
Registration
International
Marketing
\ Pricing
Lauk / Maximum intervention by
A h ..
\Fieimbursement ut ontres

 

 

 

Adapted from Redwood (1991)

45

marketing approval process shorten's a product's effective patent life, reducing the period
in which a company can recoup its R&D expenditures.

Regulatory approval procedures of different countries affect perceived market
attractiveness and thus affect the decision of a firm with respect to the choice of country for
first launch of a new product. Industry sources state that a perceived differential in
approval times prompts many companies to seek market approvals overseas first. For
example, in 1989, 18 of the 23 products approved in the United States had received their
first marketing approval in countries other than the United States. During 1984—88, 88 of
the 113 products introduced in the United States were first approved in a foreign country
(PMA 1989).

Drug approval regulations in Japan also inhibit diffusion of drugs into that country.
Foreign firms in Japan were prohibited from applying on their own for the first step of
drug approval, i.e., the demonstration of efficacy and safety review, and clinical trials had
to be conducted in Japan on native citizens. Both policies remained in effect until the mid-
19805, when discussions with the United States in bilateral trade negotiations resulted in
changes that allowed foreign firms to apply directly and permitted the submission of the
results of foreign clinical trials. However incompatibility of the data is still an issue in
many areas. Some human clinical studies must still be performed in Japan, to Japanese
standards, resulting in duplication of efforts for foreign firms (Medical Marketing 1990).

Efforts have been made for international harmonization of approval procedures in
the recent years. In 1991, the International Conference on the Harmonization of Technical
Requirements for Registration of Pharmaceuticals was held in Brussels. The objective of
the conference was to look at harmonizing current approaches to drug regulation and

minimizing future divergence of new registration requirements (Scrip Review 1991).

Patent Law and Protection of Intellectual Property Rights: Patents are the most

important of the statutorily created forms of intellectual property for the pharmaceutical

46

industry. According to one source, losses from patent, copyright and trademark
infringement were estimated to cost the industry $ 6 billion in 1986 resulting in a decrease
of S 720-900 million in R&D spending (Merck & Co. 1988).

Types of protection vary widely between nations. The average time taken to grant a
patent also varies by country. The average time it takes for the Japanese Patent Office to
grant a patent is about 5 years from date of filing compared to about 20 months in the
United States (The Japan Times, 1990). Firms in industrialized countries which have
stringent patent protection laws will have more incentive to invest in research and thus will
be more productive in discovering NCEs and other new pharmaceutical products.

According to the Pharmaceutical Manufacturer's Association (PMA), "hostile
governments, lack of patent protection and well-entrenched patent pirates are reducing the
market share and presence of US. pharmaceutical companies" in countries such as Bolivia,
Colombia, Ecuador, and Peru (PMA 1990, p.22). Developing countries in general offer

poor patent protection thus discouraging the diffusion of new drugs into the country.

Pricing and Cost-containment Policies: Pricing is considered to be one of the "main
determinants of margins, research capacities, and internationalization" (European Chemical
News, 1989, p. 20). Pricing policies of different countries vary depending on national
objectives and affect the market attractiveness of a nation and hence the rate and extent of
pharmaceutical innovation and diffusion.

The United States, for example, has to date not implemented price controls on
pharmaceuticals and is considered by many to be the country with the "last of the free
pricing" (USITC 1991, pp. 3-19). Pricing controls on pharmaceutical products marketed
in the EC are implemented by almost all of the member states.

According to Redwood (1991), the national pharmaceutical industries of countries
with low prices have gradually become less competitive internationally, both as originators

of genuinely innovative drugs and in their penetration of international markets. A study by

47

Barral (1987), demonstrated that the research output of national pharmaceutical industries
lines up more or less inversely to the severity of their drug pricing and reimbursement
systems.

Redwood (1991) also found a pattern between pricing freedom and trade balance.
Of the countries with pricing freedom, only the Netherlands had a trade deficit, whereas no
country with product by product price control had a pharmaceutical trade surplus. The
effect of price control was expressed by Redwood in medical language as follows:

"Drug price control is contra-indicated for high-risk and innovative R&D. Adverse

reactions include a propensity to concentrate on the domestic market and to abstain

from multinational investment. The result is competitive anemia, one symptom of
which is a negative trade balance. The disease is chronic rather than acute, and it

cannot be cured overnight. Long-term control breeds long-term debility" (p. 25).

Figure 3.4 illustrates the differential effects of the types of pricing systems (free
versus controlled) on pharmaceutical R&D and the political agencies. According to the
figure, the interaction of pricing and R&D is not an instant relationship, but one that works
its way through the system over the years as a kind of slow motion spiral, for whose twists
management and the authorities can be responsible at different times.

Cost containment programs have been implemented by a number of countries such
as EC member states, and Japan for health care expenditures. Among other things, these
programs are intended to lower the portion of health-care expenditures accounted for by
pharmaceuticals. The implementation of such programs is becoming more prevalent
worldwide as national health-care expenditures continue to increase in many countries.
Levels of R&D spending in the pharmaceutical industry have been found to decline as a
result of price controls and/or cost-containment programs on a national level. Reduced
level of R&D spending also leads to reduced innovativeness.

Most developing countries place price controls on pharmaceuticals reducing
perceived market potential and thus diffusion of new products into their markets. This

results from the fact that medicines are a "basic need." Drugs account for as much as half

Of all health care expenditures in these countries (compared to 8-10 percent in industrialized

48

Figure 3.4
Pricing Systems and Effects on R&D

 

 

 

 

[ PRICING SYSTEM [minnows—5|
Profits High Low
Risk Strong Weak
0 High, Rising Lower, rising
R&D Success Rare Very rare
NCE Price Very high As high as
permitted
Re-invest R&D Very high As high as
possible
Next NCE Price ‘ Still higher As high as
permitted
P Iitical
reiction —> More pressure More control

Source: Redwood (1991)

49

countries). Any increase in prices is extremely costly in terms of the health benefits
forgone. Policy makers therefore apply tight price controls, sometimes imposing price
freezes for extended periods of time (Ballance, Pogany and Forstner 1992). Such
measures can reduce market attractiveness and thus the supply and demand for

pharmaceutical innovations.

Product Liability : Product liability law deals with the right of a consumer to sue the
manufacturer of a product for injuries caused by a perceived defect in the product. Some
countries permit a manufacturer to defend against a product liability suit on the ground that
a governmental authority such as the FDA has tested and approved the product as safe.
US. courts generally do not recognize such a defense and producers face potentially
enormous liability even after the government has declared the product to be essentially free
of defects (USITC 1991, p. 3-27).

Innovation in the US. industry is stunted by concern over potential liability
because juries are more likely to find a new product defective than an old, familiar one
(Huber 1988). According to some sources, the specter of product liability exposure has led
pharmaceutical companies to shy away from research, particularly into areas such as
obstetrics and birth control (Council on Competitiveness 1991; Swazey 1991; Lasagna
1991).

Also US pharmaceutical companies are finding it more attractive to make their
products outside the US to escape US liability law, thus affecting supply of new therapies
in the US. Similarly, the diffusion of drugs into the US. from other countries is adversely

affected due to stringent product liability measures.

R&D Incentives: All the major pharmaceutical producer countries provide at least some
government support for pharmaceutical R&D through funding of basic medical research.

Federal government support for medical research in the US continues to exceed funds

50

allocated by other national governments. Developing countries can hardly afford such

largesse.

3.2.3.6 k tr t ti ivene

Market and/or industry structure can affect both supply and demand of innovative
pharmaceuticals. Factors such level of competition in national as well as international
markets, level of diversification in the industry, industry growth, etc., can have an effect
on the supply and diffusion of new drugs.

When the pharmaceutical industry is pictured in global terms, a handful of
multinationals are found to dominate. A high degree of concentration prevails in
international markets. The top 25 companies in the world account for 44 per cent of the
world market. Fourteen of these companies are based in the United States (Ballance,
Pogany and Forstner 1992).

Most multinationals are also engaged in a range of activities other than
pharmaceuticals. In fact most of the world's largest drug companies obtain the bulk of
their revenue from the sale of non-pharmaceutical products. For example, Hoechst, Ciba—
Geigy, Bayer and Rhone-Poulenc are primarily chemical firms with large pharmaceutical
departments. Diversification of this type is sometimes regarded as a strategic advantage.
That may be true in the sense that the very size of the company offers a degree of financial
support which specialized competitors do not enjoy. However the fact that Merck, Glaxo
and a number of other multinationals depend on pharmaceuticals for more than two-thirds
of their total revenue suggests that this advantage, if it exists, is far from decisive (Financial
World 1989).

The world's leading pharmaceutical companies are a select group. Entry into this
club is very difficult, requiring large teams of researchers as well as a marketing network

capable of distributing products on an international or even a global scale.

51

Product competition in individual markets is not always vigorous. This is because
some markets are dominated by a few, relatively efficient drugs which are patent-protected.
In other instances the patents of the leading brands have expired but the products continue
to be leader due to brand loyalty. Large pharmaceutical firms spend huge sums on product
promotion of brand name drugs, which is clearly a mechanism by which returns to
innovation are realized. Some analysts suggest that brand-name loyalty may be a more
effective method of guaranteeing high returns than the patent system itself (Lall 1985).

Demand can also be affected by factors such as the pharmaceutical distribution
systems in the country. For example, Japan has a complex wholesale pharmaceutical
distribution system and is considered a barrier by several foreign firms. An additional
factor that affects market demand (market potential) in Japan is that Japanese physicians
both prescribe and dispense medications, gaining income from the difference between their
dispensing price and the official reimbursement price. To reach these 180,000 physicians,
foreign pharmaceutical firms must supplement their own sales forces with wholesalers'
detailrnen. However, the above system indirectly increases the market for pharmaceuticals
for firms in Japan, since it provides an incentive to physicians in Japan to prescribe more
medications (USITC 1991).

The degree of market power and the extent of competition do not seem to differ
significantly between the industrialized and developing countries. A few companies are
world leaders and occupy prominent positions in the markets of both country groups.
Nevertheless the implications for policy makers and consumers in developing countries are
worrying. The domestic industry in these countries is relatively weak and consists
exclusively of small firms which can pose no challenge to the multinationals. This can
mean that markets are relatively vulnerable to the possible abuse of market power

(Redwood 1988).

 

3.2.3.8

 

T
belongs .
chemical

category

  
 

derelnpnx
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ofwofldu

Th
the new cl
nations. 1
have 3 hr
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lmIOduce

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were thi
infectivi

1991, p

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52

3.2.3.8 n v ' n i l f r o i iven ss

The market potential of the therapeutic category to which the new chemical entity
belongs will affect the level of R&D investment and consequently the number of new
chemical entities introduced in a given time period. For example, the leading therapeutic
category in terms of R&D investment in 1989 was anti-infectives with 1,215 products in
development worldwide. Neurologicals, anti-cancer, and cardiovasculars were the other
leading therapeutic categories. These were also the categories that topped the list in terms
of worldwide revenue (Scrip 1990).

Therapeutic category of innovation would also determine the nature of demand for
the new chemical entity. Disease patterns may vary widely between temperate and tropical
nations. Some drugs will have general clinical relevance across all nations. Others will
have a limited market because they treat medical conditions which are relatively rare and
specific to particular countries. The drugs that have a universal relevance are likely to be
introduced into many nations.

For example, in 1989, cardiovascular and central nervous system (CNS) products
were the two leading categories of ethical drugs in terms of US. sales whereas anti-
infective and cardiovascular products were the two leading categories overseas (USITC
1991, p. 1-2).

Table 3.3 lists the environmental conditions and factors that affect global

competitiveness in the pharmaceutical industry.

3.2.4 v ° n r ti iv n I s

As discussed above, international competitiveness in the pharmaceutical
industry depends on a complex interaction of demographic, economic, social, cultural,
market and legal characteristics. The many hurdles, delays and problems encountered by

the Japanese in countering competition from the traditionally dominating American and

53

Table 3.3: Environmental Conditions and Global

Pharmaceutical Competitiveness

 

Environment

Factors

 

 

(1) Demographic Environment

(2) Social Environment

(3) Economic Environment

(4) Political Environment

(5) Legal Environment

(6) Market/Industry Environment

(7) Innovation Specific Factors

 

Population, density, life expectancy, birth rate,
composition/distribution of population, etc.

Health care systems, nature of consumer demand,
dispensing practices of physicians, etc.

GNP/capita, percapita income, expenditure patterns
on health care, etc.

Government involvement in business,
developmental priorities, ideological orientation,
etc.

Regulatory approval times, patent laws, pricing
policies, product liability, R&D tax laws, etc.

Market concentration, industry focus, industry
growth market size, distribution systems, etc.

Demand for therapeutic category.

 

 

54

Western European multinationals are instructive when attention turns to developing
countries.

If Japan, a country with a huge domestic market, ample financial resources and
abundant technical skills, requires such a long time to build up a competitive pharmaceutical
industry, what are the strategic options available to firms in developing countries?

The choices are comparatively few, primarily because producers in developing
countries lack research expertise. China seems to be one exception. The country's
growing links with firms in industrialized countries reflect the latter's interest in developing
retail and OTC products from traditional Chinese herbal remedies. Some foreign
participants hope to make use of Chinese research on biological agents which they would
convert into drugs.

Few firms in developing countries have such a research option. Only a handful
have actually discovered an NCE and the instances of collaboration between pairs to firms
that are owned and operated from developing countries are few. A multinational usually
initiates such contacts; the objective is invariably to gain market access. The multinationals'
early moves into developing countries allowed little or no role for local industry. The
growth of domestic demand and the lure of larger public-health budgets has made the
markets of at least a few developing countries more attractive investment sites. That is the
case in several Asian countries where demand for medicines is growing by more than 10
percent each year (Ballance, Pogany and Forstner 1992).

Many developing countries such as India recognize patents only for processes.
Some of the companies in India specialize in developing new chemical processes yielding
drugs that are identical to those produced (at much greater expense) by multinationals. The
Indian firms begin by selling their new products domestically; later they scale up operations
to cut manufacturing costs.

The foreign markets which they select as targets are countries that recognize process

patents but not patents on the product itself. By the time the companies are ready to export

55

they can often sell the drugs at less than a tenth the price charged by competitors in
industrialized countries. This is one of the few means by which developing countries can
compete against multinationals. However, the growth of generic markets and the many
drugs which will soon come off patent mean that a greater portion of the world's markets
could soon be open to producers in developing countries.

The Southeast Asian market is also increasing in its importance both as a competitor
with respect to new multinationals from Southeast Asia as well as a potential investment
area for American, Japanese and European firms. According to Howe (1992), "to be
globally competitive into the twenty-first century, pharmaceutical companies will have to be
successful in the Southeast Asian market" (p.8).

The Southeast Asian region represents the fourth largest market for pharmaceuticals
and the fastest growing in the world (Howe 1992). The market tripled in size between
1989 and 1991 and expanded as a base for production as well as sales. The region,
together with China, currently consumes approximately eight percent of the world's
pharmaceuticals and accounts for over five percent of US pharmaceutical exports (Table
3.4).

Of the Southeast Asian countries likely to emerge as powerful competitors in the
future, are South Korea, Indonesia, Taiwan and China. Singapore, South Korea and
Taiwan, for example, have explicitly named biotechnology as a high priority. To foster
development, these countries have created technology centers, offered tax incentives, and

tried to improve basic research in order to develop more competent scientists.

3.2.5 it of l b l P rma ti 1 om titive e
As shown in Figure 3.5, the model uses the supply and demand framework shown
earlier (figure 3.1). The two components of the conceptual framework are: (a) Originating

country and industry factors (Supply factors), (b) Destination country factors (Demand

factors).

56

Table 3.4: Asian Pharmaceutical Markets by Size

 

 

 

 

 

Market Size (in US S millions, rounded)
Total world $350,000
Japan $33,000
(27.5% of world)
Southeast Asia
China 4,200
South Korea 2,448
Taiwan 852
Philippines 589
Indonesia 536
Thailand 478
Hong Kong 154
Malaysia 146
Singapore 73
Total Southeast Asia $9,500
(7.9% of world)

 

Source: The [MS Drug Market Manual (Asia), 1990

 

57

Figure 3.5: Conceptual Model of Global Pharmaceutical Competitiveness

 
  
  
 
 

    
   

  
 
 

Originating
country
factors

Global
Innovation &
Diffusion

   
   
     
 

Destination
country
factors

SUPPLY DEMAND

3.3 RA I E IV

Strategic management of the global supply and demand factors discussed above that
affect pharmaceutical sales is crucially important for multinational managers for sustained
international competitive advantage. Some of the strategies that were identified in the

literature and are applicable to the pharmaceutical industry are discussed below.

3.3.1 Musings:

According to Prahalad and Hamel (1990), the most powerful way to prevail in
global competition in the 19905 will depend on the ability to exploit core competencies.
Core competencies are "the collective learning in the organization, especially the
coordination of diverse production skills and integration of multiple streams of technology"
(p. 82).

Three important characteristics of a core competence in a corporation are: (1) a core
competence provides potential access to a wide variety of markets, (2) a core competence

should make a significant contribution to the perceived customer benefits of the end product

58

(3) a core competence should be difficult for competitors to imitate. Also core
competencies are built through a process of continuous improvement and enhancement that
may span a decade or longer.

Bogner and Thomas (1992) studied the core competencies in the pharmaceutical
industry using a sample of nine firms for intensive case study. They identified two types
of competencies in the pharmaceutical industry, namely: (1) competencies in R&D and (2)
competencies in marketing and promotion which include ability to handle regulatory
requirements. Further they found that the environment in the above areas is constantly
changing and that not all firms pick up on these changes. Additionally, firm specific
learning with respect to technology and marketing is critical for long term maintenance of
competitive advantage.

With respect to core competencies in R&D in the pharmaceutical industry, the
technological areas that successful firms exploited for discovering new drugs, since the
18705 to the present have been in organic chemistry, fermentation and soilscreening
(19405), rational drug design (19705) and biotechnology (19805). Competencies in
marketing and promotion have changed from direct selling to physicians (19505) to

blockbuster marketing (19805), to specialized selling and handling of regulatory

requirements.

 

A second concept made popular by Kogut (1985) and one which particularly
applies to this research study, in international strategic management is the concept of
comparative advantage-based competitive advantage. It implies the design of international
strategies based on the interplay between the comparative advantages of countries and the

competitive advantages of fn'ms.

 

COl‘.‘

influences t ,

 

referred tn=

teehnnlogi.

 

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59

Comparative advantage, sometimes referred to as location specific advantage,
influences the decision of where to source and market. Competitive advantage, sometimes
referred to as firm-specific advantage, influences the decision of what activities and
technologies along the value-added chain a firm should concentrate its resources in, i.e.,
the core competence of the firm. For example, a US based pharmaceutical firm with a core
competence in a certain therapeutic area could choose to locate in a country where there is a
greater demand for that therapeutic category and where the approval procedure for new
drugs is less stringent than that by the US FDA. This would enable the firm to exploit both
the comparative advantage of the foreign country as well as its own competitive advantage.
Several US companies for example with core competencies in R&D choose to locate their
R&D facilities in the UK rather than the US because of the faster approval process in the
UK.

Differences in comparative advantages of countries with respect to pharmaceuticals
arise due to differences in institutional, cultural, economic, legal, political, market and
industry environments. These differences result in differing factor costs thus contributing
to competitive advantage of firms that are able to take advantage of the lower factor costs.

Differences in the firm-specific advantages or core competencies arise depending on
which activities along the value-added chain the firm has invested in learning. The value
added chain for pharmaceuticals is illustrated in Figure 3.6. By examining the value-added
chain it can be determined which activities will be placed in countries where the
comparative advantage is most favorable, thus exploiting differences in input markets.

According to Ghoshal (1987), the same can be applied to exploiting differences in
output markets, i.e., different countries offer different comparative advantages in terms of
differences in consumer tastes and preferences, distribution systems, government
regulations, etc. It is also important to remember that comparative advantage is a dynamic

concept and can change with changes in government policies and economic or social

conditions.

60

Figure 3.6: Value-Added Chain for Pharmaceuticals

Basic
Research

\ Clinical
Tooting
\Drug
Approval

Bulk
Production

\ Formulation

Marketing

 

 

Adapted from Kogut (1985)

3.3.3

l

 

 

 

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1989‘). .-
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Pharma
1990. c
I990),

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i ICCQE

[he 1

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61

3.3.3 mm

In recent years, several experts have studied the effectiveness of alliances in
international business and found them to be an important weapon of competitive advantage
in the global competitive arena (Hamel, D02 and Prahalad 1989; Harrigan 1987; Ohmae
1989). According to Hamel, D02 and Prahalad, "it takes so much money to develop new
products and to penetrate new markets that few companies can go it alone in every
situation" (p. 133).

The accelerating rate of technological change and the broader range of technological
capabilities that firms must possess are also reasons for alliances between firms. Domestic
and international mergers, joint ventures, and strategic alliances proliferated in the global
pharmaceutical industry in the 19805. According to one source, approximately 131
pharmaceutical firms announced acquisitions or strategic alliances in the first six months of
1990, compared with a total of 51 in 1989 and 56 in 1988 (Medical Advertising Newsletter
1990).

i/ The reasons are increasing R&D costs, pressure by governments to contain health
costs, and longer drug approval procedures in many countries. One example of an early
strategic alliance was the 1983 copromotion agreement between Glaxo and Hoffman-
LaRoche. Under the agreement, Hoffman-LaRoche marketed Glaxo's antiulcer product
Zantac in the US under the Glaxo trade name, for a percentage of the sales revenue
generated. The result was beneficial to both companies, with “Glaxo establishing name
recognition in the US and Hoffman-LaRoche generating extra revenue to compensate for
the 1985 expiration of its patent on Valium.

France - dominated by domestic companies and involvement of the government in
pricing approval, has lead many overseas companies to forge alliances with French

companies. Italy's market is slightly less nationalistic, but the need to develop a close

 

relation

 

pricing t
protitie

lheretor

 

 

a Vehicle|

l
latrines:
advanta
relatior.

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high to

62

relationship with governmental agencies to obtain more timely approval and attractive
pricing makes marketing alliances with domestic companies attractive.

According to Shan and Hamilton (1991), such international cooperative ventures
provide a firm with access to country-specific advantages embedded in its partners.
Therefore "from this perspective, international cooperative relationships may be viewed as
a vehicle to tap into the comparative advantages of countries" (p. 419).

In their study of a sample of domestic and international cooperative relationships of
Japanese firms in the biotechnology industry, Shan and Hamilton found country-specific
advantage to be a significant variable in explaining differences between cooperative
relationships with partners of different countries. They concluded that interfirm
cooperation has implications for international competitiveness of both firms and nations in

high technology industries.

CHAPTER FOUR
METHODOLOGY

This chapter has four sections. The first section presents the development of the
research questions and objectives. The second section discusses the path models that were
tested in the study and the constructs, measures and data sources used. The third section
consists of the hypotheses proposed for both models. Finally, the fourth section is a
discussion of the statistical technique used (EQS) to analyze the models.

4.1 W

The specific research objectives for the study were developed after review of the
literature, talking to industry experts, and from the responses of an executive survey carried
out to determine the factors affecting global competitiveness in the pharmaceutical industry.

The broad objective of the study as indicated in the title of the study was to examine
the factors affecting global competitiveness in the pharmaceutical industry. The literature
review, expert opinions and the executive survey responses revealed that there are two
important factors underlying global competitiveness in the pharmaceutical industry. These

are: (1) ability to innovate and (2) ability to market innovations worldwide. These
observations led to the following two research objectives or questions:

(1) Which country factors stimulate or inhibit a nation's pharmaceutical industry

to be globally innovative?

(2) Which country factors stimulate or inhibit diffusion of pharmaceutical
innovations into its markets?

63

4.1.1 MM

As mentioned above, a survey of executives working for multinational
pharmaceutical companies was carried out to determine the factors that affect global
competitiveness in the pharmaceutical industry.

A sample of about 45 multinational pharmaceutical companies was chosen from the
1992 Pharmaceutical Marketers Directory. Two executives from each company were
selected for answering the survey. One of the executives was the CEO or President of the
company and the second executive selected was the Director for Market Research.
Therefore a total of ninety surveys were mailed out.

The survey was one page and consisted of two open-ended questions (Figure 4.1).
There was also a cover letter explaining the nature of the study with an assurance that all
replies would be kept confidential. The respondents were also promised a report of the
study results if interested. The executives had the option of filling out the one-page
questionnaire and simply faxing the sheet back to the number provided on the sheet or
mailing it back in an envelope to the address provided on the same sheet. The
questionnaire also indicated that handwritten responses were acceptable. The above
measures were designed to increase the response rate by making the task as simple as

possible for the executives.

4.1.1.1 rv Re It

The exective responses obtained served to confirm the observations from the
literature regarding factors affecting global competitiveness in the pharmaceutical industry.
Some of the responses from the survey are presented below.

(1) In your opinion, what factors make a country's pharmaceutical industry globally
competitive?

Responses:
0 "Innovation - by far and away the single most important factor."

- "Resources to competitively access various markets."

umnwu.\

(1)

 

 

65

Figure 4.1: Executive Survey

 

 

   
    
 

xii-$5 Global Compaitivm in the Phamceutical Industry
" {isS'N‘

    

(l) hymopinmmchfmmbaoamfiphmnicdindmyglohflyoompdfiw?

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fordpmarkatsfqimroducingduirproducts?

ledwfimncommareacccpmble
PleaseFaxRepflestoMs. MadhuAgrawalat(517)-432-1112 MICHIGAN STATE
orMailto:DeptofMarkatingandLogi5tics,MSU,Easthsingm48824 UNIVERSITY

 

 

66

- "Innovative differentiated products."

0 "the quality and scope of medical research."

0 "ability to disuibute products on a global scale."

(2) In your opinion which are the important criteria that a firm must consider when
selecting foreign markets for introducing their products?

Responses: Market potential; regulatory environment; competition; reimbursement/pricing

systems; patent protection; return on investment, etc.

4.2 E P T

Path models were developed to test the above research questions. Based on the
conceptual model presented in Chapter 3, two models were designed to test the supply
(innovation) and the demand (diffusion) factors affecting global competitiveness in the

pharmaceutical industry.

4.2.1 The Global Innovation Model (GIM)

Figure 4.2a illustrates the GM model. As shown, three major factors are proposed
as affecting the extent of investment in innovation by a country's pharmaceutical industry.
These factors are: (a) the economic environment, (b) the regulatory environment, and (c)
the market/industry structure. The market/industry environment in also directly affected by
the country's economic environment.

The extent of innovation investment is proposed as affecting both outbound foreign
investment by a country's pharmaceutical industry as well as its success in global
innovation. Global innovation is also hypothesized as being affected directly by the extent
of foreign investment. Global innovation in turn is proposed as directly affecting the global

competitiveness of the country's pharmaceutical industry.

67

Figure 4.2a: The Global Innovation Model

500mm“ Foreign Mkt
Environment Investment
+ (outbound)
+
4..

_ Innovation + . . ' . . +
Regulation investment Innovation
+ IIIIIII

 

         

 

 

+
Mitt/Industry
Structure

Figure 4.2b: The Global Diffusion Model

Economic Foreign Mkt
Envrronment lnvestrnent
+ (inbound)
Market + ‘ ' + Global
+ Regulation ' Potential ' Diffusion ' Innovation
Mitt/Industry
Structure

 

   
    

 

68

42-2 WM (GDM)

Figure 4.2b illustrates the global diffusion model. As shown, three major factors

are proposed as affecting the market potential for pharmaceutical innovations in a country.

’ These factors are: (a) the economic environment, (b) the regulatory environment, and (c)
the market/industry structure. The market/industry environment in also directly affected by
the country's economic environment.

The market potential is proposed as affecting both Lnllqund foreign investment in
the country's pharmaceutical industry as well as global diffusion of innovations into the
country. Global diffusion is also hypothesized as being affected directly by the extent of
inbound pharmaceutical foreign investment. An additional factor hypothesized as affecting
global diffusion is global innovation. That is extent of NCE diffusion into a country is
directly affected by the extent of innovation by the country.

The individual constructs, measures and data sources for both the above models are

discussed below.

4.2.3 Constructs. Measures and Data Sources

4.2.3.1 W

(a) W - As discussed in Chapter 3, countries on a higher level of
economic development are characterized by more innovative pharmaceutical industries
compared to countries that are economically less developed. Several indicators are
available by which the economic status of a country can be assessed. Two indicators or
measures used in this study were:

(1) GNP/Capita (GNP): The average Gross National Product per country's population

measured in US dollars for the years under study.

(2) Population (POP): The average absolute population for the country for the years
under study.

69

(b) W: This is one of the most important factors affecting global
innovation. Chapter 3 reviews the literature and empirical studies demonstrating the effects
of various regulatory mechanisms on innovation in the pharmaceutical industry. This study
uses two regulatory measures:

(1) Price regulation (PRICEREG): This is the extent of price control exerted on
pharmaceuticals by the government of the country. A seven-point scale, where 1
reflects low price control and 7 reflects high price control is used to measure price
control.

(2) Approval time (APPTIME): This is the time taken by the drug regulatory agencies
to approve an application of a new pharmaceutical product or NCE for marketing in
the country. This is measured using a seven-point scale, where 1 reflects short
approval time and 7 reflects long approval time.

The above measures for regulatory environment are subjective measures determined
by the researcher. Although objective values for PRICEREG and APPTIME would have
been desirable, the unavailability coupled with the unreliability (due to differences in
reporting systems of countries) of the existing objective data on the above indicators made
it necessary to resort to subjective measures. An abundance of anecdotal and other

information was available to facilitate development of the subjective measures for

PRICEREG and APPTINIE.

(c) Wm: As was discussed in Chapter 3, the structural aspects of

the market and industry can significantly affect the country's innovation potential in
pharmaceuticals. Four indicators of market and industry structure were used in this study:

(1) Market size (MKTSIZE): This was measured as the average annual sales (in US
dollars) of pharmaceuticals for the country for the years under study.

(2) Industry focus (INDFOCUS): This was measured as the average percentage ratio
of pharmaceutical sales to total sales for the country's industry.

(3) Industry growth (INDGRWTH): This was measured as the average annual
percentage change in pharmaceutical sales for the country's industry.

(4) Industry concentration (INDCONC): This was measured as the percentage of total
pharmaceutical sales accounted by the top 25 firms in the industry for the country.

70

(d) Wet: This is the investment in R&D activities by a country's
industry. It is a significant predictor of innovative success, since greater the investment in
innovation greater should be the success with respect to discovery of new products. One
indicator was used for the above construct.

( l) R&D Expenditure (R&DEXPD): This was the average annual expenditure (in US
dollars) on pharmaceutical research and development by the country's industry.

(e) Qeteeene Eeeeign Investment: Internationalization by a country's pharmaceutical

industry is a significant indicator of its size and research potential and has been shown to be
positively linked to innovation in most high-technology industries. Two indicators were
used to measure outbound foreign investment.

(1) Absolute foreign investment (FRGINVST): This was the average annual foreign
sales (in US dollars) of pharmaceuticals by the country's industry.

(2) Foreign Commitment (FRGCOMM): This was the average percentage ratio of
foreign pharmaceutical sales to total pharmaceutical (foreign + domestic) sales for
the country's pharmaceutical industry.

(e) Glebel Ingevation: This construct reflects the success of the country's industry in

developing successfully a new pharmaceutical or NCE. This was measured as:

(1) Number of NCEs developed (INNOVAT): This was measured as the total number
of NCEs developed by a country's industry for the years under study.

(0 W: This reflects the market power of the country's industry in the

global market. This was measured as:

(1) Global Sales (GBLSALES): This was measured as the average annual worldwide
pharmaceutical sales (in US dollars) by the country's pharmaceutical industry.
Table 4.1a lists the constructs, measures and data sources used in the Global

Innovation Model.

71

Table 4.1a: Constructs, Measures and Data Sources:

 

 

 

The Global Innovation Model
CONSTRUCTS MEASURES SOURCES
(l) Macroeconomic (1) GNP per capita (GNP) World Development Reports, UN

Environment

(2) Regulation

(3) Market/Industry Structure

(4) Innovation investment

(5) Foreign Market
Investment
(Outbound)

(6) Global Innovation

(7) Global Competitiveness

 

(2) Population (POP)

(1) Price control (PRICEREG)

(2) Approval time (APPTIME)

(1) Market size (MKTSIZE)

(2)1ndustry focus (INDFOCUS)

(3) Industry growth (INDGRWTH)

(4) Industry concentration
(INDCONC)

( l) R&D Expenditure (R&DEXPD)

( 1) Absolute foreign investment
(FRGINV ST)

(2) Foreign commitment
(FRGCOMM)

(1) Number of NCEs developed
(INN OVAT)

(1) Global Sales (GBLSALES)

 

Publication.

World Development Reports, UN
Publication.

Author's estimates, various
sources.

Author's estimates, various
sources.

Scrip Review (various issues).
Scrip League Tables.

Scrip League Tables.
Ballance, Pogany and Forstner
(1992).

Scrip League Tables.

Scrip League Tables.

Scrip League Tables.

Scrip Review (various issues).

Scrip League Tables.

 

 

72

4.2.3.2 The filehal Diffusion Medel

Four constructs used in the GIM model are also used in the diffusion model (see
Figure 4.2a & b). The same indicators were also used. Therefore only those constructs

and corresponding measures that are different are discussed below:

(a) Marlee; Petential: As discussed in Chapter 3, market potential or market attractiveness is
a significant determinant of the country's ability to attract companies desirous of
introducing NCEs in that country. This was measured as follows:

(1) Market potential (MKTPOT): This was measured as the average annual sales (in
US dollars) of pharmaceuticals for the country for the years under study.

(b) WM: As discussed in the earlier chapter, the extent of

pharmaceutical foreign investment in a country will positively affect the number of new

pharmaceuticals introduced into the country every year. This construct was measured as:

(1) INFRGN: The average annual value of pharmaceutical imports (in US dollars)
into the country.

(c) Glebel Diffusien: This construct indicates the recipient country's attractiveness as a

market for introduction of new pharmaceutical products. This was measured as:

(1) DIFF: The total number of NCEs introduced into the country for the years under
study.

Table 4.1b lists the constructs, measures and data sources used in the Global Innovation

Model.

4.2.4 i 11 Tim 1‘ c

All data used in this study was obtained from secondary sources since most data
used was objective data. These sources were identified after a thorough review of the
literature - both academic and trade journals; consultation with industry experts such as

pharmaceutical associations such as the Pharmaceutical Manufacturers Association; and

73

Table 4.1b: Constructs, Measures and Data Sources

 

 

 

The Global Diffusion Model
CONSTRUCTS MEASURES SOURCES
(l) Macroeconomic (1) GNP per capita (GNP) World Development Reports, UN

Environment

(2) Regulation

(3) Market/Industry Structure

(4) Market Potential

(5) Foreign Market
Investment
(inbound)

(6) Global Diffusion

(7) Global Innovation

 

(2) Population (POP)

(1) Price control (PRICEREG)

(2) Approval time (APPTIME)

(1) Industry focus (INDFOCUS)

(2) Indusuy growth (INDGRWTH)
(3) Industry concentration
(INDCONC)

(1) Market potential (MKTPOT)

(1) Foreign imports (INFRGN)

(l) # of NCEs introduced
(DIFF)

(1) # of NCEs developed
(INNOVAT)

 

Publication.

World Development Reports, UN
Publication.

Author's estimates, various
sources.

Author's estimates, various
sources.

Scrip League Tables.

Scrip League Tables.
Ballance, Pogany and Forstner
(1992).

Scrip Review (various issues).

World Trade Annual.

Scrip Review (various issues).

Scrip Review (various issues).

 

 

74

talks with pharmaceutical market research firms such as Scrip, IMS, etc. Tables 4.1 a&b
lists the data sources used for the measures in each of the models.

The total sample size used in the study was twenty-seven countries (Table 4.2).
Data from 202 multinationals representing the above countries was aggregated to obtain
country level estimates. The time frame over which the data was examined was for a four
year period (1990 to 1994). This time frame was considered appropriate as a longer time
frame would involve confounding effects due to the dynamic environmental changes taking
place in the industry before the 1990 period, and a shorter time frame would be ineffective
in measuring effects such as innovation and diffusion which take place over a period of
several months. Also, resource constraints with respect to time available to the researcher
for collecting and inputting the data in a usable form prevented use of a longer time frame

for the study.

Table 4.2: Countries in Sample

4.3 W

Argentina Japan
Australia Korea
Belgium Netherlands
Canada New Zealand
China Norway
Denmark Portugal
Finland South Africa
France Spain
Germany Sweden
Hungary Switzerland
India Turkey
Indonesia UK

Israel US

Italy

A total of thirty hypotheses corresponding to thirty different path relationships were

proposed for the global innovation model. Since several of the constructs in the global

75

diffusion model were the same as in the innovation model, resulting in similar paths, only
seven unique hypotheses (paths) were applicable to the global diffusion model.

The hypotheses were developed from a review of the literature and results of
previous empirical studies. Table 4.3a and Table 4.3b list the hypothesized paths, their
expected significance and direction for the global innovation model and the global diffusion
model respectively. The rationale for each of the hypotheses and the actual result is
discussed in detail in the next chapter on results.

In order to test the above hypotheses a total of 32 program runs were canied out for
the global innovation model and 12 program runs for the global diffusion models. The
number of program runs reflects the number of measures used and the paths tested. Table
4.4a and Table 4.4b lists the combination of variables used in each run for the global

innovation and the global diffusion models respectively.

4.4 T IALME D AL I -E

EQS - a structural equation modeling (SEM) software was used for statistical
analysis. Structural equation modeling is an extension of several multivariate techniques
(such as multiple regression and factor analysis). It provides a straightforward method of
dealing with multiple dependence relationships simultaneously while providing statistical

efficiency (Hayduk 1987).

4.4.1 i lin E

( 1) understand the role of causal relationships in statistical analysis.
(2) represent a series of causal relationships in a path diagram.
( 3) translate a path diagram into a set of equations for estimation.

(4) assess overall model fit using goodness-of-fit measures.

76

Table 4.3a: Hypotheses: The Global Innovation Model

 

 

 

 

 

Paths Expected Direction Expected Significance
H1: GNP --> MKTSIZE + significant
H2: GNP --> R&DEXPD + significant
H3: PRICEREG ---> MKTSIZE - significant
H4: PRICEREG —-> R&DEXPD - significant
H5: MKTSIZE --—-> R&DEXPD + significant
H6: R&DEXPD -—> FRGINVST + significant
H7: R&DEXPD -—> INNOVAT + significant
H8: FRGINVST --> INNOVAT + significant
H9: INNOVAT -—> GBLSALES + significant
H10: GNP --—> INDFOCUS + insignificant
H11: PRICEREG ---> INDFOCUS - significant
H12: INDFOCU S --> R&DEXPD + significant
H13: GNP --> INDGRWTH + insignificant
H14: PRICEREG ---> INDGRWTH - significant
H15: INDGRWTH --——> R&DEXPD + insignificant
H16: GNP ---> INDCONC - insignificant
H17: PRICEREG ---> INDCONC + insignificant
H18: INDCONC ---> R&DEXPD + insignificant
H19: POP --—> MKTSIZE + significant
H20: POP -—> R&DEXPD + significant
H21: APPTIME --—> MKTSIZE - significant
H22: APPTIME -—> R&DEXPD - significant
H23: POP --> INDFOCU S + significant
H24: APPTIME ---—> INDFOCUS - insignificant
H25: POP ---> INDGRWTH + insignificant
H26: APPTIME ---> INDGRWTH - significant
H27: POP —-> INDCONC - insignificant
H28: APPTIME --> INDCONC + insignificant
H29: R&DEXPD ~—> FRGCOMM + significant
H30: FRGCOMM ---> INNOVAT - insignificant
Table 4.3b: Hypotheses: The Global Diffusion Model
Paths Expected Direction Expected Significance
H1 : INDFOCU S ---> MKTPOT + significant
H2: INDGRW'I'H -—-> MKTPOT + significant
H3: INDCONC --—> MKTPOT - significant
H4: MKTPOT ---> INFRGN + significant
H5: MKTPOT --> DIFF 4» significant
H6: INFRGN ---> DIFF + significant
H7: INNOVAT ---> DIFF + significant

 

77

Table 4.4a: Program runs for the Global Innovation Model

 

(1)

(2)

(3)

(4)

(5)

(6)

(7)

(8)

(9)

(10)
(1 1)
(12)
(13)
(14)
(15)
( 16)
(17)
(18)
(19)
(20)
(21)
(22)
(23)
(24)
(25)
(26)
(27)
(28)
(29)
(30)
(31)
(32)

v1=gnp; v2=pricereg; v3=mktsize; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=gnp; v2=pricereg; v3=mktfocus; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=gnp; v2=pricereg; v3=mktgrwth; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gb|sales
v1=gnp; v2=pricereg; v3=mktconc; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsale5
v1=gnp; v2=apptime; v3=mktsize; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=gnp; v2=apptime; v3=mktfocus; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=gnp; v2=apptime; v3=mktgrwth; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=gnp; v2=apptime; v3=mktconc; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=pop; v2=pricereg; v3=mktsize; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gbl5ales
v1=pop; v2=pricereg; v3=mktfocus; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=pop; v2=pricereg; v3=mktgrwth; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=pop; v2=pricereg; v3=mktconc; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3antsize; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3=mktfocus; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3=mktgrwth; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3=mktconc; v4=r&dexpd; v5=frginvst; v6=innovat; v7=gblsales
v1=gnp; v2=pricereg; v3=mktsize; v4q&dexpd; v5=frgcomm; v6q'nnovat; v7=gblsales
v1=gnp; v2=pricereg; v3=mktfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=gnp; v2=pricereg; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat;v7=gblsales
v1=gnp; v2=pricereg; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=gnp; v2=apptime; v3=mktsize; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=gnp; v2=apptime; v3=mktfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=gnp; v2=apptime; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=gnp; v2=apptime; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2wricereg; v3=mktsize; v4q&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2=pricereg; v3mnktfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2=pricereg; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2=pricereg; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3=mktsize; v4q&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3=mktfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales
v1=pop; v2=apptime; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gbl5ales

 

Table 4.4b: Program runs for Global Diffusion Model

 

( 1)
(2)
(3)
(4)
(5)
(6)
(7)
(8)
(9)
( 10)
( l 1)
C 12)

v1=gnp; v2=pricereg; v3=indfocus; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=gnp; v2=pricereg; v3=indgrwth; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=gnp; v2=pricereg; v3=indconc; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=gnp; v2=apptime; v3=indfocus; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=gnp; v2=apptime; v3=indgrwth; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=gnp; v2=apptime; v3=indconc; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=pop; v2=pricereg; v3=indfocus; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=pop; v2=pricereg; v3=indgrwth; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=pop; v2=pricereg; v3m’ndconc; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=pop; v2=apptime; v3=indfocus; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=pop; v2=apptime; v3=indgrwth; v4=mktpot; v5=infrgn; v6=diff; v7=innovat
v1=pop; v2=apptime; v3=indconc; v4=mktpot; v5=infrgn; v6=diff; v7=innovat

 

78

4.4.2 Stepe in Struetuel Egeetien Medeling

The following steps are involved in analyzing a path model using structural
equation modeling:

(a) Asseseing identifieatien ef the model: Very often during the estimation
process, the computer program is likely to "blow up", i,e., produce meaningless or

illogical results resulting in what is termed as "identification problems." In simple terms,
an identification problem is the inability of the proposed model to generate unique
estimates. Usually there are three sources of identification problem which need to be
explored and corrected. (1) A large number of estimated coefficients relative to the number
of covariances or correlations, indicated by a small number of degrees of freedom, (2) the
use of reciprocal effects (two-way causal arrows between two constructs); or (3) failure to
fix the scale of a construct.

(b) W: Structural Equation Modeling shares three
assumptions with the other multivariate methods: independent observations, random
sampling of respondents, and the linearity of all relationships. In addition, Structural
Equation Modeling is more sensitive to the distributional characteristics of the data,
particularly the departure from multivariate normality or a strong kurtosis (skewness) in the
data. A lack of multivariate normality is particularly troublesome because it substantially
inflates the chi-square statistic and creates upward bias in critical values for determining
coefficient significance. The above assumptions will be tested using options available in
EQS.

Once the assumptions have been satisfied at acceptable levels, the results will be
examined for any offending estimates such as negative error variances, large standard
errors, etc. Once it is established that the data meets the assumptions and there are no
offending estimates, overall model fit will be assessed by examining goodness-of-fit
measures. Goodness-of-fit is a measure of the correspondence of the actual or observed

input (covariance or correlation) matrix with that predicted from the proposed model.

79

Finally, the statistical significance and direction of the paths will be examined and

interpreted in light of the hypothesized causal relationships.

(c) ldtet‘preting and Medifyidg the Model: Once the model is deemed acceptable,

modifications to the model may have to be made to improve its fit further based on

theoretical justification. Modification indices will be examined to improve model fit.

4.4.3 Igdieeet Effects end Ewe-green Adelysis

Two additional steps in this analysis will involve examination of significant indirect
effects and differences between groups, in this case the two groups used are the
industrialized country group (I) and the developing country group (D).

Indirect effects are important for interpretation purposes. For example,
PRICEREG affects GBLSALES indirectly through R&DEXPD and INNOVAT. EQS is
able to decompose the total effect into direct and indirect effects and provide significance
estimates for both.

A second useful feature using EQS which will be used in this study is the analysis
of multiple groups to test for significant differences in parameters between two or more
groups of interest. In this case, the sample of twenty-seven countries will be divided into
two groups, one group consisting of industrialized countries and the other group consisting
of developing countries. This will be done to examine if there are significant differences in
the relationships between variables for the two groups and whether the models developed,
fit the two groups equally well as indicated by the goodness-of-fit indices.

Figures 4.3a and Figure 4.3b illustrate the EQS models and structural equations

used in the program for the global innovation and the global diffusion models respectively.

80

Figure 4.3a
The EQS Model for Global Innovation

 

 

Model Equations:

V3 = *Vl - *V2 + E3;

V4: *V1 - *V2+ *V3 +E4;
V5 = *V4 + E5;

V6 = *V4 + *V5 + E6;

V7 = *V6 + E7;

81

Figure 4.3b
The EQS Model for Global Diffusion

 

 

 

Model Equations:

V3 = *Vl - *V2 + E3;

V4 = *Vl - *V2 + *V3 +E4;
V5 = *V4 + E5;

V6 = *V4 + *V5 + *V7 + E6;

CHAPTER FIVE
RESULTS

This chapter is divided into five sections. First, results from the analysis of the
global innovation models are discussed. Second, results of the two-group analysis, i.e.,
analysis of the differences between the industrialized (I) nations versus the developing (D)
nations are discussed. Third, significant indirect effects on innovation and global sales are
discussed. Fourth, the results from the global diffusion model are presented. Finally,

some conclusive comments are offered.
5 .1 - E T

A total of thirty-two path models were run using EQS in order to analyze the factors
affecting innovation in the global pharmaceutical industry for the entire sample of
industrialized plus developing (I+D) countries. The overall results are illustrated in Figures
5.1 - 5.8. Appendix A contains the tables showing the standardized path coefficients, t-
values, standard errors and the fit indices for the thirty-two runs. All of the individual runs
of the model showed a good fit with the hypothesized model. The goodness of fit indices
varied from 0.998 to 1.000. The chi-square statistic was also indicative of a good fit to the

hypothesized model. The results of the individual hypotheses are discussed below.

82

83

5.1.1 __ - f P "'r'q illt it! 'zen r tvatt

(see Figure 5.1).

H1: GNP---->MKTSIZE

It was hypothesized that countries with a higher GNP/capita would have a larger
market size for pharmaceuticals. More than seventy percent of all pharmaceuticals are sold
in developed market economies. The developing countries account for less than a fifth of
the sales, with the remainder being consumed in East European countries and the Soviet
republics (Ballance, Pogany and Forstner 1992). Spending on pharmaceuticals in the
developed market economies has been rising. Average pharmaceutical consumption as per
cent of per capita GDP rose from 0.65 in 1975 to 0.95 in 1990. No similar increases have
occurred in developing countries. In fact the share of per capita gross domestic product
(GDP) spent on pharmaceuticals has actually declined in many of the poorer countries
(Ballance, Pogany and Forstner 1992).

Another factor which affects the market size in the industrialized countries is the
demographic characteristics of the population. As the population of a country ages, the
need for drugs grows. For the industrialized countries, it is estimated that by the year
2015, over forty percent of the population will be over 45 years old. In comparison, only
25 per cent of the developing countries' population will be over 45 years of age by 2015.
Public expenditures on health care in the industrialized countries are also higher as
compared to in the developing countries.

As the figure illustrates, the relationship between GNP and MKTSIZE was found

to be significant and positive as expected.

H2: GNP---->R&DEXPD
According to the technology gap theory of development (Fagerberg 1987; Posner
1961; Gomulka 1971; Cornwall 1977), there is a close correlation between level of

 

84

Figure 5.1

Effect of GNP, Price regulation and Market size on Innovation

Hypothesized model
4.
+
4.
PRICEREG - m + GBLSALES
' +

——O significant path
-~—----#’ insignificant path

 

 

Result

+
PRICEREG ' .+

_’ significant path
..._-....._.. 443» insignificant path

85

economic development of a nation (measured as GNP or GDP per capita) and level of
technological development measured using R&D statistics.

It was therefore hypothesized that countries with a higher GNP/capita would be
associated with a more research intensive pharmaceutical industry reflected in terms of
dollar expenditures on pharmaceutical research and development by the respective
country's industry. For example, for the period 1980-83, one study estimated that the
developed country industries accounted for ninety-six percent of global R&D expenditure
on pharmaceuticals whereas the rest of world accounted for just four percent of global
research expenses (Redwood 1988). The US. pharmaceutical industry's total R&D
expenditure was estimated to be $7.3 billion in 1989 (USITC 1991).

As the figure illustrates, the relationship between GNP and R&DEXPD was found

to be significant and positive as expected.

H3: PRICEREG---->MKTSIZE

It was hypothesized that the extent of price controls on pharmaceuticals would be
negatively related to market size for pharmaceuticals for a country.

In the USITC study, price was found to be inversely related to demand and price
elasticities of -1.12 and -1.28 were found suggesting that if the price (in real terms) of
pharmaceutical products decreases by 1 percent, the quantity demanded of those products
would increase by 1.12 to 1.28 percent (USITC 1991). US's large market for
pharmaceuticals is in a large part due to the freedom in pricing that manufacturers enjoy. A
recent report by the Council on Competitiveness (1991) emphasized freedom from price
control as one of three major factors important for continued competitiveness of the US
industry.

As the figure illustrates, the relationship between PRICEREG and MKTSIZE was

found to be significant and negative as expected.

86

H4: PRICEREG---->R&DEXPD

It was hypothesized that the extent of price controls on pharmaceuticals would be
negatively related to pharmaceutical R&D expenditure for a country.

Pharmaceutical industries in countries with higher prices have more revenues to
reinvest in R&D and have generally well-established and stronger R&D programs as
compared to industries with lower-priced products (European Chemical News 1989;
Redwood 1989; USITC 1991).

Price controls in France have been held responsible for the weak domestic industry.
In France, much of the costs of drugs for individual patients is reimbursed by the country's
social security fund. Since French governments reportedly have kept drug prices
artificially low and the industry has traditionally been dependent on its home market for a
large share of its revenues, the flow of research funds to companies has been reduced
(Chemical Marketing Reporter 1990).

As the figure illustrates, the relationship between PRICEREG and R&DEXPD was

found to be significant and negative as expected.

H5: MKTSIZE---->R&DEXPD

It was hypothesized that larger the market size for pharmaceuticals for a country,
greater will be its share of global expenditure on pharmaceutical R&D.

Pharmaceutical industries in countries with larger markets have more revenues to
reinvest in R&D and have generally well-established and stronger R&D programs as
compared to industries located in countries with smaller market size (Parker 1984; Pradhan
1983; USITC 1991).

As mentioned earlier, developed country industries (having larger country markets)
accounted for ninety-six percent of global R&D expenditure on pharmaceuticals whereas
the rest of world accounted for just four percent of global research expenses in the period

1980-83 (Redwood 1988). Among the developed countries for example, in the period

87

1980-83, US and Japan were the two largest country markets for pharmaceuticals and
simultaneously the top two spenders on pharmaceutical R&D (Redwood 1988).
As the figure illustrates, the relationship between MKTSIZE and R&DEXPD was

found to be significant and positive as expected.

H6: R&DEXPD---->FRGINVST

It was hypothesized that greater the expenditure by a country's pharmaceutical
industry on R&D, greater will be the extent of foreign investment by the industry.

This is because companies look to recouping their investments by seeking new
markets. Also more research intensive the company, greater is its propensity to take risks
and venture into foreign markets. It is also generally the case that high technology
industries are more multinational in nature (Porter 1990; Dosi and Soete 1991; Niosi and
Faucher 1991).

One study (Ballance, Pogany and Forstner 1992) examined the correlation between
R&D expenditures and pharmaceutical exports for 17 industrialized countries and found the
rank correlation to be positive and statistically significant. The relationship was also
examined at the company level and was found to be significant. Therefore, substantial
research expenditures apparently provide the basis for a pharmaceutical industry's
international success as reflected in the large share of sales in foreign markets.

As the figure illustrates, the relationship between R&DEXPD and FRGINVST was

found to be significant and positive as expected.

H7: R&DEXPD---->INNOVAT
It was hypothesized that greater the expenditure by a country's pharmaceutical
industry on R&D, greater will be its success in originating new chemical entities, in other

words higher R&D expenditures will lead to greater R&D productivity (Franko 1989).

88

The study carried out by the US International Trade Commission examined the
detemrinants of national competitiveness in pharmaceuticals comparing the industry in the
US, Western Europe and Japan using a sample of twenty multinational firms. The study
found a significant relationship between R&D commitment and NCE origination (USITC
1991). The researchers concluded that "pharmaceutical firms must make a considerable
commitment to research and development, both in terms of the size of their R&D budget
and R&D staff to remain competitive" (p. 6-5).

As the figure illustrates, the relationship between R&DEXPD and INNOVAT was

found to be significant and positive as expected.

H8: FRGINVST---->INNOVAT

It was hypothesized that greater the extent of foreign investment (both exports and
FDI) by a country's industry, greater will be the number of NCEs originated by industry.

This is because companies that invest abroad are able to exploit the pool of research
talents of another country. For example, the Swiss companies in the early 19805 spent
almost forty percent of their total research funds abroad (Dunning 1988). American
member firms of the Pharmaceutical Manufacturers Association spent about 20 percent of
their combined R&D budget in 1980 outside the US.

Also, with respect to this particular study, INNOVAT represents not only the
number of NCEs originated by a country's pharmaceutical industry in the period 1990-
1994 but also those NCEs that were approved for marketing either at home or abroad. A
higher degree of foreign investment should therefore facilitate getting market approval
quicker than a lower degree of foreign investment and hence familiarity with foreign
markets.

An additional factor that motivates locating R&D facilities abroad is that many
products have to be sold worldwide to recoup their development costs, and clinical studies

conducted in the host country ensure speedier approval for marketing of the product.

89

However as the figure indicates, the relationship between FRGINVST and
INN OVAT was found to be significant but negative. Prior studies done with respect to
other industries have examined the relationship between degree of internationalization and
MNE performance measured as profit-to-sales ratio or some other performance measure
(Hymer 1960; Franko 1987; Grant 1987; Thomas and Grant 1987). These studies reported
a positive relationship between foreign investment and performance.

However, a study done by Geringer et a1. (1989) using a sample of 200 MNEs
consisting of the 100 largest firms from the US. and Europe found that as extent of
foreign investment increased, performance also increased but it then peaked and exhibited a
downward trend. The authors concluded that there is some critical "internationalization
threshold" for the companies and that the relationship between degree of internationalization
and performance is more complex than previously examined.

Several explanations are possible for this phenomenon. As firms encompass
increasingly broader geographic markets, the costs associated with geographic dispersion
begin escalating thus eroding performance (in this study innovative success). With respect
to the pharmaceutical industry, in the recent past, most foreign investment has taken place
in the form of licensing or joint venture arrangements for the purposes of market access
rather than FDI or investment in foreign R&D laboratories by the multinationals. This
could explain why increased foreign penetration may not necessarily result in greater

success with originating NCEs.

H9: INNOVAT---->GBLSALES

It was hypothesized that greater the number of NCEs originated by a country's
industry, greater will be its share of global pharmaceutical sales.

The relationship between technological innovation and performance has been found
to be true of all high technology industries (Rugman 1985; Porter 1990; Niosi 1991).

Dozens of studies in econometrics, industrial organization economics, and corporate

90

strategy reveal a significant positive relationship between various indicators of R&D
performance/ R&D commitment and performance indicators such as world market share or
firm sales growth.

Also, according to the technology growth theory, technology is the principal
driving force of the growth of industrialized countries, therefore by extension it should also
drive the growth of the individual industrial firms based in those countries (Schumpeter
1934; Denison 1967; Carre et al 1975; Harberger 1984).

According to Grabowski (1989) - a leading authority on pharmaceutical innovation
and competitiveness, "competition in the multinational pharmaceutical industry centers
around the discovery and development of important new drug therapies" (p. 27). The
USITC study also found a significant positive relationship between number of R&D drugs
and global market share of a firm (USITC 1991, p. 5-6).

As the figure illustrates, the relationship between INNOVAT and GBLSALES was

found to be significant and positive as expected.

5.1.2 Effect ef GNP, Peiee regulation and Industry foeus en Innevatien
(see Figure 5.2)

H10: GNP---->INDFOCUS

It was hypothesized that there is no significant relationship between level of
economic development (GNP) of a country and the extent of concentration or focus of its
pharmaceutical industry on pharmaceuticals.

There is no evidence to suggest that richer country industries are any less
diversified or more diversified than poorer country industries. European pharmaceutical
firms are more highly diversified than American and Japanese firms in general. This
pattern of concentration as against diversification has historical roots rather than any

relation to GNP. American and Japanese firms were mainly pharmacy based or

 

91

Figure 5.2
Effect of GNP, Price regulation and Industry focus on Innovation

Hypothesized model
+ w
+
- +
‘1' ——> significant path
.......-.-..........® insignificant path
M

 

 

Result

+x ——> significant path
...-......_m.tb insignificant path

92

pharmaceutical in origin, whereas many European firms came into the industry through
chemicals and dyestuffs (Redwood 1988).

However, as the figure illustrates, the relationship between GNP and IN DFOCUS
was found to be significant and negative. A possible explanation for this result is that
when both industrialized and developing countries are included in the analysis, the
relationship between GNP and INDFOCUS becomes significant since developing country
pharmaceutical industries are generally less diversified as compared to the industrialized
country industries. For the industrialized group the average percentage of sales that was
due to pharmaceuticals in this sample was 63 percent, whereas for the developing country

group, the average percentage of sales that was due to pharmaceuticals was 83 percent.

H11: PRICEREG---->INDFOCUS

It was hypothesized that greater the level of price control on pharmaceuticals, lower
would be the concentration of the industry on pharmaceuticals.

More favorable the conditions for pharmaceutical profitability, greater would be the
focus on sales of pharmaceutical products. However, as the figure illustrates, the
relationship between PRICEREG and INDFOCUS was found to be positive instead of
negative as expected.

Again, this result is possible due to the nature of the sample consisting of both
developing and industrialized countries and the large differences in the nature of the
industries between the two. The developing countries have a higher degree of price control
but are also more focused on pharmaceuticals as compared to the industrialized country
group, simply because of the nature of the economic and political conditions, thus resulting

in the positive relationship between PRICEREG and INDFOCUS.

93

H12: INDFOCUS---->R&DEXPD

It was hypothesized that greater the focus on pharmaceuticals by a country's
industry, greater would be the expenditures on pharmaceutical research and development.

This is because pharmaceutical industries are generally found to increase their
concentration on pharmaceutical related products when the climate for pharmaceutical
profitability is favorable. Since R&D is an important aspect of pharmaceutical profitability,
therefore by extension a higher focus should result in higher R&D investment. As the
figure illustrates, the relationship was positive but insignificant.

The insignificance of the relationship could again be attributed to the effect of the
developing countries in the sample, i.e., a high focus but low R&D expenditure as
compared to the industrialized countries.

5.1.3 _i,' t L' P ' Jalztnmt n 1th ll_ “HOVi

(see Figure 5.3)

H13: GNP---->INDGRWTH

It was hypothesized that there is a positive but insignificant relationship between
GNP and industry growth (measured as average percentage change in sales during 1990-
1994). However, as the figure illustrates the relationship between GNP and INDGRWTH
was found to be negative but not significant.

This could be because the pharmaceutical industry in the developing countries has
been growing at a much faster rate (particularly in the recent past) than the industry in the
industrialized countries which is fairly stable and well established. For example, the
average percentage change in sales for the developing country sample in this study was 13

percent, whereas for the industrialized countries the change was 12 percent.

94

Figure 5.3
Effect of GNP, Price regulation and Industry growth on Innovation

Hypothesized model

+ w
+
- f
+/ -—.> significant path
--.............£br insignificant path

 

 

Result

     

__> significant path
Hammer» insignificant path

 

95

H14: PRICEREG---->INDGRWTH

It was hypothesized that greater the level of price control on pharmaceuticals, lower
would be the average growth in pharmaceutical industry sales for the country.

There is anecdotal evidence to suggest that industry sales growth is affected by level
of price controls. However as the figure illustrates, the relationship was found to be
positive although insignificant

This could be due to a couple of reasons. First, countries that have a very profitable
industry have also been the ones to be subjected to greater price controls in the recent past
thus accounting for the positive direction of the relationship. This is especially true in the
case of industrialized countries. The two group analysis discussed later in the chapter
reveals this to be the case.

Second, as explained above, developing country industries are the ones
experiencing greater growth but also have a higher degree of price control as compared to
the industrialized countries, thus resulting in the positive direction of the relationship.
When the developing countries are analyzed separately as a group the relationship is

negative as hypothesized.

H15: INDGRWTH---->R&DEXPD

It was hypothesized that growth in industry sales would be positively but
insignificantly related to R&D expenditures. The link between corporate R&D and firm
sales growth has been tested in the industrial organization literature both across and within
industries. Results have typically shown an association between measures of R&D input
and firm growth (Franko 1989; Scherer 1976; Mansfield 1968; Leonard 1971; Jarrell 1983;
Comanor 1986). These studies however used mono-national U.S. samples, so the
relationship has not been tested for a world-wide international sample.

As the figure illustrates, the relationship was found to be negative and insignificant.

Again, the effect of the developing countries in the sample is the possible culprit, i.e., the

96

high industry growth rates in recent years coupled with the lower R&D expenditures in the
developing country group when compared to the industrialized group giving us the negative
relationship between INDGRWTH and R&DEXPD. Later in the two group analysis it will

be seen that the relationship is positive for the industrialized country group alone.

5.1.4 Effect at GNP, Price regulatieu and Industry Qeueeutration on
Innevatieu (see Figure 5.4)

H16: GNP---->INDCONC

It was hypothesized that there is a insignificant relationship between a country's
GNP/capita and the concentration of the pharmaceutical industry in that country.

This was based on prior literature which showed little difference in the
concentration ratios of the industry for countries with varying ranges of economic
development. For example Redwood (1988) examined the market share held by the top
twenty firms for thirteen industrialized and thirteen developing countries using 1984 data.
He found no significant pattern in the relationship between concentration and level of
development and concluded that this was because the leading multinational firms have a
commanding position in both groups of nations.

However, as the figure illustrates, GNP was found to be significantly inversely
related to INDCONC, implying that the more developed countries had a less concentrated
industry structure.

Examination of more recent data on concentration ratios reveals that the degree of
oligopoly power is more pronounced in developing countries than the industrialized
countries. For example, the 25-firm concentration ratios using 1988 data were compared
for industrialized versus developed country groups by Ballance, Pogany and Forstner
(1992). The average 25-firm concentration ratio for developing countries was 63 as

compared to 57 for the industrialized group.

97

Figure 5.4
Effect of GNP, Price regulation and Indusz concentration on Innovation

Hypothesized model

+ w
+
- + @+ w

———> significant path
----—F insignificant path

 

 

 

 

Result

———-> significant path
-—-—--—br insignificant path

 

 

98

A possible reason for this difference is that the domestic industry in the poorer
countries is relatively weak along with the incomplete regulatory system in these countries
which allows abuse of market power by the multinationals. The implications of this are

however worrying for policy makers and consumers in the developing world.

H17: PRICEREG---->INDCONC

It was hypothesized that there is no significant relationship between degree of price
control and industry concentration for a country.

This is because there is lack of any research study with respect to the
pharmaceutical industry that examines the above relationship even with single country
samples, let alone multicountry samples such as this one. Although the industrial
organization and economics literature generally points to the negative effects of regulation
on market competition (Kamien and Schwartz 1982; Rothwell and Zegveld 1981), there
was insufficient anecdotal or empirical evidence with respect to the pharmaceutical industry
that the relationship would be significant.

As the figure illustrates, PRICEREG had a positive but insignificant impact on
INDCONC.

H18: INDCONC---->R&DEXPD

The relationship between market structure and indicators of innovation has been
statistically tested by industrial organization economists.

Schumpeter's hypothesis that a "competitive oligopoly" is most conducive to
innovation provided the impetus for several studies in this area (Niosi 1991). Other
researchers also argued a similar position, the argument being that since research is
generally not a profitable activity, only sufficiently large firms can carry out research
knowing they will benefit from its results (Villard 1958; Phillips 1956; Kamien and
Schwartz 1970; Loury 1979).

99

Experts in the pharmaceutical industry also generally concede to the oligopolistic
characteristics of the industry due to its research intensive nature (Grabowski 1976;
Schwartzman 1976). Based on the above, it was therefore hypothesized that INDCONC
would be positively related to R&DEXPD.

As the figure illustrates, the relationship was found to be negative although
insignificant. However, as will be discussed later, the two-group analysis revealed a
positive relationship between INDCONC and R&DEXPD. That is, when the industrialized
and developing country samples are tested separately, the relationship is in the direction as
expected. Therefore, pooling the two groups results in confounding effects for certain

variables.

5.1.5 Eff t, 'H latt Artrtv: tt‘ in, AL! .' __ ‘ It titvztt

(see Figure 5.5)

H19: POP---->MKTSIZE
Generally larger the population, greater is the market size for pharmaceuticals. As

expected the relationship was positive and significant.

H20: POP---->R&DEXPD

Larger populations should result in larger market size (as explained above) and
consequently greater revenues to invest in R&D. It was therefore hypothesized that more
populated countries would be associated with greater levels of expenditure on
pharmaceutical R&D. As the figure shows, the relationship was positive and significant as

expected.

Figure 5.5
Effect of Population, Approval time and Market size on Innovation

Hypothesized model

+ __.’ significant Path
“mm-a» insignificant path

 

+ w
4.
+

 

Result

   

——5 significant path
~--~---+ insignificant path

 

101

H21: APPTIME---->MKTSIZE

Intuitively, a high degree of regulation should have a negative effect on market size.
That is, greater the stringency of the approval procedure for marketing of new
pharmaceuticals, longer it will take for the new product to reach the market, thus reducing
market availability of new products and therefore reducing potential market size.

Therefore, a negative relationship was hypothesized between APPTIME and
MKTSIZE. However, as the figure illustrates, APPTIME was positively associated with
MKTSIZE although the path was statistically insignificant.

Most studies in the pharmaceutical industry literature have examined the relation of
APPTIME to innovation rate. The only study examining the APPTIME---->MKTSIZE
relationship is by Parker (1984), where be ranked countries by regulatory tightness and
examined a series of rank correlations between the former and various indicators of market
size. All correlations were significant and positive. This is because countries that have
large markets for pharmaceuticals are also the ones which are most stringent in their
approval procedures for marketing of new pharmaceuticals thus possibly explaining the

above result.

H22: APPTIME---->R&DEXPD

Delays in the marketing approval process can reduce a product's effective patent life
thus reducing the period in which a company can recoup its R&D expenditures. Studies
done on pharmaceutical innovation indicate the negative effects of long approval times on
the rate of innovation (Grabowski and Vernon 1976; Baily 1972; Grabowski, Vernon and
Thomas 1976; Wardell 1973; 1975).

APPTIME should therefore have a negative effect on R&DEXPD. However, as the
figure illustrates, the relationship was positive although statistically insignificant. Again,
the confounding effect of the sample was suspected. That is, industrialized countries have

longer approval times but also larger R&D expenditures as compared to developing

102

countries resulting in the positive relationship. When two group analysis was done, the

effect was negative but insignificant for the two groups (I & D).

5.1.6 Effeet at Papulatien, Appzeval time and Industry feeus an
Innovatian (see Figure 5.6)

H23: POP---->INDFOCUS
It was hypothesized that larger the population, greater would be the focus of the
industry on pharmaceuticals due to the larger market for pharmaceuticals. The relationship

was found to be positive and significant as expected.

H24: APPTIME---->INDFOCUS

There is little in the literature to suggest that regulatory stringency has a direct effect
on the level of industry focus or diversification. Therefore it was hypothesized that the
effect would be negative but statistically insignificant. As the figure illustrates, the

hypothesis was confirmed.

5.1.7Effc fP ultin vlim nInutr rwhn

mm (see Figure 5.7)

H25: POP---->INDGRWTH
It was hypothesized that a larger population size would have a positive effect on
growth in industry sales, however, the effect would not be statistically significant. As the

figure illustrates, the above hypothesis was confirmed.

103

Figure 5.6
Effect of Population, Approval time and Industry focus on Innovation

Hypothesized model

 

4g». + ——-D significant path
/ a» insignificant path

 

' . INDRIUS

 

Result

 

-——-> significant path
W4» insignificant path

   

 

104

Figure 5.7
Effect of Population, Approval time and IndusU'y growth on Innovation

Hypothesized model

   

—> significant path
M insignificant path

 

 

Result

 

——p significant path
4» insignificant path

 

 

 

105

H26: APPTIME---->INDGRWTH

As mentioned earlier, the relationship between APPI‘HVIE and rate of innovation has
been the subject of examination by most researchers. One can speculate that a higher rate
of innovation would fuel higher sales growth and therefore approval times should affect
INDGRWTH.

Based on the above, it was hypothesized that APPTIME is negatively related to
INDGRWTH. However, as the figure illustrates, the relationship was found to be positive
but insignificant.

This may be because, approval times for most countries have remained fairly stable
atleast for the past decade, rendering it difficult to isolate the effect of changes in regulatory
approval times on changes in sales growth. A longer time frame would be needed to isolate

this effect.

5.1.8 __ - f It- lin Arut 1111‘ In _ JD nr in .

Fereigu Cammitment an Innovatieu (see Figure 5.8)

H27: POP---->INDCONC

Theoretically, in a competitive industry, a larger market size should stimulate more
entries into the industry. Therefore, if a large population translates to a larger potential
market, then INDCONC should be lower as POP is higher.

However, no firm conclusions are possible due to the oligopolistic nature of the
global pharmaceutical industry in individual countries. It was therefore hypothesized that
there is a negative but insignificant relationship between POP and INDCONC. As the
figure illustrates, the relationship is positive but insignificant.

The positive direction of the relationship could be explained due to the inclusion of
the developing countries in the sample which have a much larger population but also show

higher INDCONC as compared to industrialized countries. Two group analysis (discussed

106

Figure 5.8

Effect of Population, Approval time, Industry concentration and
Foreign Commitment on Innovation

Hypothesized model

    

——> significant path
we» insignificant path

 

 

Result

    

—-> significant path
MM insignificant path

 

 

later in this se

industrialized

328: APP'I
As mer
been the suhje
stringent app
resulting in g;
Howt
global phar
multination;
but insignif

the relation

H29: R8
It '
country's]
10 invegm
Tl
Possible.
TClalionS]
home ma
[ho-Se Wit
F
dense m
became

hand She

107

later in this section) reveals a negative relationship between POP and INDCON C for the

industrialized countries as would be expected.

H28: APPTIME---->INDCONC

As mentioned earlier, the relationship between APPTIME and rate of innovation has
been the subject of frequent examination by most researchers. One can speculate that more
stringent approval procedures would deter firms from entering the industry therefore
resulting in greater industry concentration.

However, no firm conclusions are possible due to the oligopolistic nature of the
global pharmaceutical industry in individual countries and the domination of a few
multinational firms in most countries. It was therefore hypothesized that there is a positive
but insignificant relationship between APPTIME and INDCONC. As the figure illustrates,

the relationship is positive but insignificant.

H29: R&DEXPD---->FRGCOMM

It was hypothesized that level of investment in research and development by a
country's pharmaceutical industry would be positively associated with level of commitment
to investment in overseas markets.

This is because firms need to recoup their R&D investment in as many ways as
possible, one of which is greater sales in foreign markets. As the figure shows, the
relationship was found to be positive but insignificant. This can be explained on basis of
home market size. Countries whose industries show a high percentage of foreign sales are
those with relatively smaller domestic markets.

For example, industries in countries like Switzerland, Belgium, Denmark etc.,
derive more than eighty percent of their pharmaceutical sales from non-domestic sources
because of their smaller home market size. Countries such as US and Japan on the other

hand show a much smaller degree of foreign commitment due to their huge home markets.

108

Thus R&D investment does impact the absolute level of foreign investment (see
H6) but not necessarily the level of foreign commitment expressed as share of foreign to

total sales.

H30: FRGCOMM---->INNOVAT

Despite the multinational character of the industry, most of the basic research is still
done in the laboratories of the home country. A higher level of commitment to foreign
markets may not therefore necessarily result in greater innovative success. In fact it could
have the opposite effect of diverting attention and resources away from basic research to the
increased complexity of managing diverse foreign investments. This was found to be the
case in H8 (FRGWVST---->NNOVAT).

Another factor is the knowledge and familiarity required with the local FDA
approval procedures. Most FDA agencies are likely to approve home country applications
quicker than applications from foreign companies. INNOVAT in this study represents not
only the number of new NCEs originated by a country's industry but those NCEs that were
approved for marketing either at home or abroad. INNOVAT is likely to be higher when
most of the NCEs have been originated and approved for marketing in the same country.

Therefore, it was hypothesized that the relationship between FRGCOMM and
INN OVAT would be negative but insignificant. The figure shows that the hypothesis was

confirmed.

5.2 1| _' I -,_.LL _-’ D .Ti__i_._ _"1\_" 1'“;

The sample of twenty-seven countries was divided into two groups. The countries

were classified based on Ballance, Pogany and Forstner's (1992) classification of

countries' pharmaceutical industries. The above researchers grouped countries into four

109

groups (A, B, C and D) based on the technological sophistication of a country's
pharmaceutical industry'. The country sample in this study was divided into two groups.
Group 1 consisted of Group A countries which were mostly industrialized countries
(fifteen in all) and Group 2 consisted of Group B and C countries which were mostly
developing countries (twelve in all).

The research question of interest here was: is there a difference in the direction and
magnitude of influence of various factors that affect innovation and hence global
competitiveness of the pharmaceutical industry of industrialized nations versus that of the
developing nations? Again, thirty-two runs on EQS were carried out with the two groups
(Tables in Appendix A show the results of the 32 program runs).

Table 5.1 lists the paths which were significantly different in the two groups. N 0
specific hypotheses for the two-group analysis were developed since this analysis was
exploratory in nature due to lack of similar studies in the literature. The paths for which

significant differences were found are discussed below.

(a) GNP---->MKTSIZE

The gross national product of a country was found to have a significant positive
effect on the market size for pharmaceuticals for the industrialized (1) country group. The
relationship was insignificant and negative for the developing (D) country group.

This effect seen for the D-group can be explained based on the nature of the health
care systems in developing countries. First, poorer developing countries spend a greater
proportion of their health care budget on pharmaceuticals. There is also greater public
expenditure on pharmaceuticals in the relatively poorer developing countries (especially the

Third World countries). Thus GNP of a developing country may not be a significant factor

 

1Group A - Countries with a sophisticated pharmaceutical industry and a significant research base, Group B
- Countries with innovative capabilities, Group C - Countries with reproductive capabilities and Group D -
Countries without a pharmaceutical indusu'y.

110

Table 5.1: Significant Path Differences Between Industrialized (I) and

 

 

 

Deve10ping (D) Country Groups
Path Significance Direction
I D I
(l) GNP-->MKTSIZE Significant Insignificant +

(2) PRICEREG---->R&DEXPD Significant Insignificant -

(3) MKTSIZE ----- >R&DEXPD Significant Insignificant +

(4) R&DEXPD-~——>INNOVAT Significant Insignificant +

(5) FRGINVST-—-->INNOVAT Significant Insignificant -

(6) INNOVAT-——>GBLSALES Significant Insignificant +

(7) PRICEREG----->INDCONC Significant Insignificant -

(8) INDCONC-«->R&DEXPD Insignificant Significant +

(9) POP ----- >R&DEXPD Significant Insignificant +

(10) POP----->INDFOCUS Significant Insignificant +

 

 

 

 

rum——

 

in deterrrr

oi reduei

(h) PR‘

expent

D-gro

the it
more
indu

man

101

ch:

 

1c

 

111

in determining market size for pharmaceuticals and may well have a negative effect by way

of reducing public health expenditures on pharmaceuticals.

(b) PRICEREG---->R&DEXPD

The level of price controls on pharmaceuticals had a significant negative effect on
expenditures on R&D for the I-group but the effect was opposite and insignificant for the
D-group.

This difference is not surprising in view of the fact that pharmaceutical industries in
the industrialized countries are heavily research based and their R&D activities would be
more sensitive to future profits and therefore pricing regulation. The pharmaceutical
industries in the D-group are not based on basic research but concentrate heavily on the
manufacture of bulk pharmaceuticals and formulations.

The positive (although insignificant) effect observed for the D-group could be due
to the presence of Group B type countries which do have a small research base but are also

characterized by greater price regulation.

(c) MKTSIZE ----- >R&DEXPD

A larger market for pharmaceuticals had a strong positive effect on innovation
investment, i.e., R&D expenditures for the I-group; the effect was insignificant and
negative for the D-group.

This result is indicative of the vast difference in the nature of the pharmaceutical
industries in the two groups. As explained earlier, the research-based industry in the
industrialized countries will be more sensitive to the underlying factors affecting innovation
as compared to the industry in the developing countries. Since research is a costly and
time-consuming process, market size would greatly affect the level of investment in

research.

 

 

 

Ho
higher luv:
the result.
protectior
drug dew
greater 1
technolc

of bulk ‘

(d) R8

SUCCCSE

the LE

dueto
Statist
inabil
gr on;
(e) F
grOUI
ReQe

explt

path

112

However, a larger market in developing countries does not necessarily mean a
higher investment in innovation and may even reduce the investment in R&D as shown by
the result. This may be because of several reasons. For example, the absence of patent
protection in countries in the D- group reduces the incentive for spending on R&D for new
drug development. A larger market size in the such countries would therefore result in
greater concentration of efforts in other activities such as improving manufacturing
technology for basic chemicals, acquiring distribution channels, greater foreign exporting

of bulk formulations, etc.

((1) R&DEXPD---->INNOVAT

The level of investment in innovation has a strong positive effect on innovative
success for the I-group countries; the effect is insignificant and negative for the D-group.

This implies that investment in R&D is more efficiently and productively utilized in
the I-group than in the D-group. The difference is not surprising as previously explained
due to the research-based nature of the industry in the I-group.

The negative effect of R&D expenditure on innovation for the D-group was not
statistically significant but is important for interpretation purposes, since it indicates either
inability to utilize R&D resources efficiently or that R&D resources in countries in the D-

group are more efficiently utilized in other activities rather than basic research.

(e) FRGINVST---->INNOVAT

The level of foreign investment had a strong negative effect on innovation for the I-
group; the effect was insignificant and positive for the D-group.

The pharmaceutical industry of industrialized countries is multinational in character.
Recent cost-containment pressures in national markets has driven the industry further to
explore alternative markets abroad. However, as explained in the discussion of the above

path for the overall group analysis, over-expansion into foreign markets can result in

113

diversion of resources from basic research to managerial activities, thus affecting
innovative success (INN OVAT).

The same is not true for developing country industries, since their extent of foreign
involvement is restricted to exports of mainly bulk formulations and generic
pharmaceuticals. Besides, the industry is not primarily research based in this group, thus

the insignificant effect of FRGINV ST on INN OVAT for the D—group is not surprising.

(f) INNOVAT---->GBLSALES

The number of new drugs developed (INN OVAT) has a strong positive effect on
global competitiveness (GBLSALES) of the pharmaceutical industries in the I-group. The
effect is insignificant and negative for the D-group.

This result has serious implications for developing countries and challenges the
generalized assumption in the literature that all countries (regardless of their stage of
economic development) need to invest in innovation for global competitiveness.

The negative and insignificant relationship between IN N OVAT and GBLSALES
for the D—group implies that there are other avenues by which developing country industries
can be globally competitive and that, atleast for now, ability to develop NCEs is not one of
them. The prospects and strategies that developing countries should follow are discussed

in greater detail in the final chapter on conclusions.

(g) PRICEREG---->INDCONC

Price regulation had a strong negative effect on extent of industry concentration for
the I-group countries; the effect was insignificant for the D-group.

The strong significant effect of regulation on market structure in industrialized
countries versus the weak effect of regulation in the developing countries is expected, since

the markets for pharmaceuticals are larger and more competitive in the developed

114

economies. However, the negative effect of PRICEREG is surprising since greater price
pressure should result in higher concentration in the industry.

However, this effect is plausible, due to the presence of competition from the
generic pharmaceutical industry. Greater price control on patented drugs (as is normally
the case in I-group countries) will induce more generic firms to enter the industry thus

possibly lowering overall concentration ratios for the industry.

(h) INDCONC---->R&DEXPD

Industry concentration levels had a significant positive effect on level of R&D
expenditures for the D-group countries; the effect was insignificant for the I-group.

In recent years, the pharmaceutical industry in the developing countries has been
experiencing increasing concentration ratios, this upward trend has been more pronounced
for the developing countries than the industrialized countries where the ratio has remained
fairly stable. Pharmaceutical industries in the developing world have been increasing
spending on research, and as we have seen earlier the oligopolistic nature of the industry is
especially favorable for greater research spending.

Thus, the level of concentration in the developing countries which are still
dominated by a handful of multinationals has a more significant effect on level of R&D
expenditures than seen in the industrialized countries where there is not as much variation

with respect to concentration ratios in the sample.

(i) POP---->R&DEXPD

Population size has a strong positive effect on research spending in the industry for
the industrialized countries; the effect is insignificant and negative for the developing
countries.

A larger population for an industrialized country translates into a larger market size

for pharmaceuticals; the same is not true for developing countries as the more populated

115

developing countries are characterized by low purchasing power. A larger market size
should therefore be associated with greater spending on R&D for the I-group countries,
which is the effect observed in this case.

Therefore, pharmaceutical industries in large industrialized countries such as the US
are at an advantage, compared to industries in small industrialized countries such as

Switzerland with a small home market.

(j) POP---->INDFOCUS

Population size was significantly associated with level of industry focus for the I-
group countries; the effect was insignificant for the D-group.

A larger population as explained above in industrialized countries implies a larger
home market. Larger the market for pharmaceuticals, greater should be the focus of the
industry on pharmaceutical products than on non-pharmaceuticals. This also explains why
the pharmaceutical industry in countries like US and Japan with larger home markets have
less diversified pharmaceutical industries than countries such as Switzerland or Belgium

with more diversified pharmaceutical industries due to their small home markets.

v I v ' he Di r n w I- -

In general, the global innovation model showed a better fit for the industrialized
group than for the developing country group in terms of the number of significant paths
found. This result is interesting and has serious implications for further research with
respect to economic development. Most research done on industrialized country samples
generalizes the findings to developing countries since data on developing countries is
scarce. This study results show that generalization of models and findings used for
industrialized countries cannot be universally applied.

According to Lall (1990), a leading expert on economic development and an advisor

to the OECD, developed economies have often tried to apply the same neoclassical

116

principles to developing countries with negative results. The structure of incentives, factor
markets, policies, institution and infrastructure in the developing countries is far too
different to be subjected to the same economic policies as those applied to the industrialized
econonries. In addition, differing social, economic, political and cultural traditions cast
their own influence on the direction and pace of capability development.

A study by Fagerberg (1987) tested the technology gap models using a sample of
OECD and non-OECD countries, where he examined the relationship between technology
variables such as growth in innovative activity and economic development of the country.
He found the models "better suited" for industrialized countries than the developed
countries. He concluded that the developing countries have followed a separate way of
development and that if differences in growth between these countries had to be explained,
a much more detailed analysis of "economic, social and institutional structures needed to be

carried out" (p. 64).

5.3 I I NT INDIRE T EFFE T I VATI A D
WES

Several constructs had significant indirect effects on innovation and global sales
(global competitiveness).

As seen in Figure 5.9, pharmaceutical innovation (INNOVAT) was affected by a
country's macroeconomic environment (GNP and POP); the regulatory environment
(PRICEREG); and its market/industry structure (MKTSIZE).

Both GNP and POP had significant positive effects on innovation, implying that
pharmaceutical industries based/located in countries with a higher GNP/capita and a larger

Population are more successful at developing NCEs.

 

117

Figure 5.9
Significant Indirect Effects

 

 

 

 

 

 

 

 

 

 

 

 

 

 

118

PRICEREG had a significant negative indirect effect on innovation as expected,
i.e., the less favorable the regulatory environment in a country for its pharmaceutical
industry, lower is the innovative success of the industry.

The home market size (MKTSIZE) of a country had a significant positive effect on
innovation; i.e., industries based in countries with a large market potential for
pharmaceuticals are more successful at developing and introducing innovative new drugs
(NCEs).

Global competitiveness (GBLSALES) was also indirectly affected by a country's
economic environment (GNP and POP); regulatory environment (PRICEREG);
market/industry structure (MKTSIZE); investment in innovation (R&DEXPD); and the
level of foreign investment (FRGINVST).

In general, pharmaceutical industries based in countries with a higher gross national
product per capita, larger population, lower price regulation, larger market size, higher
investment in research and development, and moderate foreign investment were more

globally competitive.

5.4 L A DIF INM L-RE LT

As discussed in Chapter 4, the global diffusion model had several constructs in
common with the global innovation model since several of the factors that affect supply
also affect demand. In all, seven paths were of interest in the global diffusion model as
listed in Table 4.3b. To test for the seven hypothesized paths, twelve separate runs on
EQS were carried out. Appendix B shows the table of results for the global diffusion
model.

The global diffusion model was tested only for the industrialized group of countries

since few developing countries in the sample were recipients of new drug introductions.

119

Thus results of the global diffusion model apply only to the industrialized group of
countries.

Figure 5.10 shows the results of the global diffusion analysis. The hypotheses
specific to the diffusion model are discussed below.

H1: IN DF OCUS---->MKTPOT

It was hypothesized that a higher industry focus on pharmaceutical products would
be positively associated with market potential.

As the figure illustrates, this hypothesis was confirmed. The underlying causal
effects on market potential are important when analyzing diffusion models, since larger
markets should attract greater diffusion of new products. Thus foreign pharmaceutical
firms can benefit by choosing countries which show a higher overall industry focus on
pharmaceuticals when introducing new drugs.

A higher host country focus on pharmaceuticals can also have other positive effects
such as greater familiarity of regulatory agencies with new drug development procedures,

pricing mechanisms, and other public policy issues related to pharmaceuticals.

H2: INDGRWTH---->MKTPOT

Industry growth was found to have an insignificant effect on market potential. This
is because most industrialized countries have had fairly stable growth rates in recent years
with not much variation among the countries with respect to growth rates.

Therefore market potential is not significantly affected by growth in sales of the
pharmaceutical industry. However, even though the relationship is insignificant, positive
grth reflects a healthy industry and therefore a viable market. Pharmaceutical firms will
in general be better off introducing their products into countries where the pharmaceutical

industry shows positive percentage changes in annual sales.

120

Figure 5.10
Global Diffusion Model

 

$1" ——> significant path

M insignificant path
“WP“ INDmCUS

 

121

H3: INDCONC---->MKTPOT

Level of industry concentration was insignificantly related to market potential. It
was hypothesized that countries with industries characterized by greater concentration
would be associated with smaller market size for pharmaceuticals.

However, the relationship between industry concentration and market size is not
established in the literature. Due to the supposedly oligopolistic nature of the industry, it is
difficult to predict the effect of concentration on market potential. Therefore, foreign
pharmaceutical companies looking to introduce products in other countries should not be
deterred by concentration ratios of the industry in those countries, since there still could be

a large untapped market out there for investment.

H4: MKTPOT---->INFRGN
A larger market potential was hypothesized to have a significant positive effect on
inbound foreign investment. As shown in the figure, the hypothesis was confirmed.
Larger markets are bound to attract greater foreign investment into the industry. US
is a particularly attractive market and has attracted a great deal of foreign investment by

Swiss, British and other Western European pharmaceutical firms.

H5: MKTPOT---->DIFF

It was hypothesized that market potential would have a significant positive effect on
the number of NCEs introduced into the country (DIFF). However as the figure illustrates,
the relationship was insignificant.

This could be explained on the basis of Parker's study (Parker 1984) where he
found that larger markets did not necessarily attract more new drug introductions than
smaller markets. He speculated that such an effect was possible because most large
country markets are also the ones with the most stringent regulatory procedures, thus the

effect of regulation canceled out the effect of market size.

122

In this study DH7F represents the number of new drugs launched for the first time
in any country. Generally pharmaceutical companies choose those countries for first
launch of a new drug, whose regulatory procedures they are most familiar with. Usually
this is the home country, however there can be exceptions such as the US where in recent
years more US based companies choose other countries for first launch due to the
unusually long approval periods in the US.

Once the drug has achieved market success in the country of first launch, then it is
generally easier for the firm to obtain approval for marketing in other more attractive (larger
market size) countries. Therefore, a higher MKTPOT may not necessarily be positively

related to DIFF in this case.

H6: IN FRGN ----- >DIFF

It was hypothesized that greater the incoming foreign investment in the country's
pharmaceutical industry, higher will be the number of NCEs introduced into the country.

This is, because firms would invest in countries which offer attractive returns in
terms of large market size or easier approval procedures or to exploit local talent in research
or other areas. Some of the above factors would favor NCE introduction into the country's
markets.

As the figure shows, the relationship was positive but insignificant. As explained
in the previous hypothesis, a firm's choice of the country for first launch of an NCE
depends on a complex set of factors, especially a combination of various regulatory policies
such as patent protection policies, product liability issues, acceptance of foreign clinical
data, etc.

In this study, only two regulatory variables were used, namely price control and
approval time for marketing of NCE. Although it would have been desirable to test as
many regulatory variables as possible, constraints on data availability and other resources

made this difficult.

123

Also increasingly in the past, most foreign investment by pharmaceutical companies
has been in the form of informal alliance arrangements, such as licensing or other
marketing agreements for gaining market access for drugs that have already been approved
elsewhere. Therefore, extent of inbound foreign investment may lead to greater number of

first time NCE launches, but the effect may be insignificant due to the above factors.

H7 : INNOVAT---->DIFF

It was hypothesized that a higher number of NCEs developed by a country's
pharmaceutical industry (INNOVAT) would be associated with higher number of NCEs
first launched into the country (DIFF).

This is because as explained previously, most firms choose the home country or the
country in which the NCE was developed (originating country) as the country for first
launch. This is due to the ease in getting marketing approval from the local regulatory
agency.

This could also be explained on basis of demand creating supply. A higher
perceived demand for a product would lead a firm to develop such a product for that market
in which it is located, thus making it more likely for the originating country to be the
recipient country for the NCE.

As the figure illustrates, INNOVAT had a strong positive effect on DIFF

confirming the relationship between supply and demand factors of innovation.

5.5 W

The results of the global innovation model analysis provide interesting insights into
the factors affecting innovation in the pharmaceutical industry. A country's economic,
regulatory and market/industry environment has significant effects on the innovativeness of

its pharmaceutical industry. The results also indicate that greater innovation overall leads to

124

greater global competitiveness. Analysis of the GIM model also reveals the need for
analyzing the industrialized and developing countries separately.

Two-group analysis of the industrialized and developing countries reveals
significant differences between the determinants of innovation for the two groups. In
general, the GIM model shows a better fit for the industrialized countries and a poor fit for
the developing country group. The managerial and public policy implications of the above
results are discussed in Chapter 6.

Global innovation and global competitiveness are significantly affected indirectly by
a number of factors. In general, pharmaceutical industries based in countries with a higher
gross national product per capita, larger population, lower price regulation, larger market
size, higher investment in research and development, and moderate foreign investment
were more globally competitive.

Results of the global diffusion model analysis revealed that level of global
innovation had a far greater impact on the extent of diffusion of NCEs into a country than
the market potential or level of inbound foreign investment for the country. This
relationship confirms the theory that supply and demand factors of innovation strongly
affect each other. The result also implies that factors that impact global innovation can also
impact global diffusion.

Table 5.2 provides an overall summary of the results for the three groups analyzed

(I+D; I; and D) for the global innovation model.

125

Table 5.2: Summary of Results

Global Innovation Analysis

 

 

Path relationships

(1) Economic Env ----> I+D
Mkt/Industry structure

GNP---> Mkt size 5i g
GNP-->Industry focus 5i g
GNP-->Industry growth insi g
GNP-->Industry conc si g
Population-~->Mkt size si g
Population-->Industry focus si g
Population-->Industry growth insig
Population-->Industry conc insi g

(2) Economic Env---->
Innovation Investment

GNP—--->R&D Expend sig
Population---> R&D Expend si g

(3) Regulatory Env---->
Mkt/Industry Structure

Price control---> Mkt size sig
Price control--->Indusu'y focus si g
Price control-->Industry growth insi g
Price control-->Industry conc insi g

Approval time--->Mkt size insi g
Approval time--->Indusuy focus insi g
Approval time-->Industry growth insig
Approval time-«>Industry conc insi g

(4) Regulation---->
Innovation Investment

Price control--—>R&D Expend 51 g
Approval time-«> R&D Expend insi g

(5) Mkt/Industry structure---->
Innovation Investment

Mkt size--->R&D Expend si g
Industry focus»-—>R&D Expend in si g
Industry growth—«>R&D Expend insig

Industry conc—-—>R&D Expend insig insig sig

sig

insig
insig
insig

sig
sig
insig
insig

sig
sig

insig
sig
insig
sig

insig
insig
insig
insig

sig
insig

sig
insig
insig

Significance of Paths

D

insig
insig
insig
insig

sig

insig
insig
insig

5i g
insig

insig
insig
insig
insig

insig
insig
insig
insig

insig
insig

insig
insig
insig

Direction
I+D I
+ +
- +
+ +
+ +
+ +
+ -
+ +
+ +
+ +
+ +
+ _
+ +
+ +
+ +
+ +
+ -
+ +
+ +
- +
- +

++

++++

 

 

Table 5.2 (cont'd)

126

 

 

(6) Innovation Investment
---> Foreign Investment

R&DExpend---> frgn invst
R&D Expend-~> frgn com

(7) Innovation Invst-->
Global Innovation

R&DExpend——>Innovat

(8) Foreign Invst--->
Global Innovation

Frgn invst---->Innovat
Frgn comm-~->Innovat

(9) Global Innovation--->
Global Sales

Innovat ------ > Gbl Sales

I+D I

sig sig
insig insig

sig sig
sig sig
insig sig

sig sig insig

5i g
insig

insig

insig
insig

I+D

 

CHAPTER SIX
CONCLUSIONS

This chapter has five sections. The first section provides a summary of the results
of the study. Section 6.2 discusses the managerial and public policy implications of the
study results for industrialized and developing countries. Section 6.3 examines the
theoretical, empirical, and methodological contributions of the study. Section 6.4 presents

the study limitations. The last section has suggestions for future research.

6.1 M RY RE LT

6.1.1 Deteeminants ef filehal Innovatiuu

One of the research objectives of the study was: Which country factors stimulate or
inhibit a nation's pharmaceutical industry to be globally innovative? The mautfiudimgs as a
result of the analyses of the global innovation models are listed below.

(1) The economic environment of a country has a significant impact on the
market and industry structure of its pharmaceutical industry as well as on
pharmaceutical innovation investment.

(2) The regulatory environment of a country has a significant effect on
pharmaceutical market and industry structure as well as on pharmaceutical

innovation investment.

(3) A large market size for pharmaceuticals is associated with greater investment
in pharmaceutical innovation.

(4) Increases in innovation investment lead to increased global innovation.
(5) Only moderate levels of foreign investment lead to increased global

innovation. A high level of foreign diversification has a negative effect on
global innovation.

127

128

(6) Global innovation is positively associated with global competitiveness, i.e.,
greater the number of NCEs developed, greater is the global market share of
the country's industry.

(7) Global competitiveness of the pharmaceutical industry was significantly
indirectly affected by it's national economic, regulatory and market/industry
envrronments.

Of the economic variables, GNP had a greater effect on market and industry
structure variables than POP. Market size, industry focus and industry concentration were
all affected by economic factors. Industry growth was the only aspect of market/industry
structure which was not influenced. Both GNP and POP also affected R&DEXPD.

Of the regulatory variables, only PRICEREG was significant. APPTIME did not
have a significant effect on any of the dependent variables. Pricing regulation had a strong
negative effect on market size. It also affected industry focus. Pricing regulation also had
the effect of lowering innovation investment.

Market size was the only significant variable of all the market/industry structure
variables to have an effect on innovation investment. A larger pharmaceutical market size
had the effect of increasing investment in innovation.

Higher levels of innovation investment seemed to drive higher levels of total foreign

investment and global innovation. Finally, global innovation was a strong determinant of

global competitiveness.
6.1.2 filahal Innavatien Factars far Industrialized vetsus Develeplug
W

The mainjndlugs as a result of analyzing the two groups (industrialized and

developing) of countries are presented below.

(1) The economic environment of industrialized countries had a greater impact
on the market and industry structure of its pharmaceutical industry as well
as on pharmaceutical innovation investment, as compared to developing
countries.

(2)

(3)

(4)

(5)

(6)

(7)

129

The regulatory environment of industrialized countries had a more
significant effect on pharmaceutical market and industry structure as well as
on pharmaceutical innovation investment, as compared to developing
countries.

A large market size for pharmaceuticals is associated with greater investment
in pharmaceutical innovation in the case of industrialized country firms; the
effect is negative and not significant for developing country firms.

Increases in innovation investment lead to increased global innovation for
the industrialized counuy industries; the effect is negative and not significant
for the developing country industries.

A high level of foreign investment has a negative effect on global innovation
for industrialized countries; the effect is opposite but insignificant for
developing country industries.

Global innovation drives global competitiveness of industrialized country
firms; but has a negative although insignificant effect on developing country
competitiveness.

Global innovation in the pharmaceutical industry in industrialized countries
is significantly inditectly affected by it's national economic, regulatory and
market/industry environments; no significant indirect effects are obtained for
the developing country industries.

In general, the global innovation model had a better fit for the I—group in terms of

the number of significant paths than for the D-group. More significantly, perhaps, none of

the direct causal variables of global innovation and global competitive advantage had any

significant effects for the developing country group. This implies that factors other than

those related to innovation are responsible for global competitive advantage of the

developing country pharmaceutical industries. Also a second important implication of the

above findings is that results for industrialized country markets cannot be generalized to

developing country markets both for managerial and especially for public policy purposes.

6.1.3 e ' l I Diffui

A second research objective of the study was: Which country factors stimulate or

inhibit diffusion of pharmaceutical innovations into its markets? The global diffusion model

130

was analyzed only for I-group, therefore the results apply only to industrialized countries.

The mundiugs are listed below.

(1) The nation's economic, regulatory and market/industry environment, all had
a significant effect on the market potential for diffusion of NCEs.

(2) Greater market potential for pharmaceutical diffusion led to increased
inbound foreign investment into a country's pharmaceutical industry.

(3) Global diffusion of pharmaceuticals was not directly affected by market
potential or inbound foreign investment but was strongly affected by the
level of global innovation.

With respect to the economic environment, only GNP had a significant effect on
market potential for diffusion. The effect of Population size was absent. Of the regulatory
variables, only PRICEREG was an important factor affecting market potential, APPTIME
had no effect. Of the market/industry structure variables, industry focus was the only
factor significantly affecting market potential.

Contrary to expectations, global innovation was a more significant explanatory
variable of global diffusion than market potential and inbound foreign investment. That is,
countries characterized by a highly innovative pharmaceutical industry were also more

likely to be recipients of pharmaceutical innovations. That is, NCE originating countries

are also the destination countries for NCEs.

6.2 W

6.2.1 mm:

Although the study examines factors affecting competitiveness at the national level
and some at the industry level, the results have implications at the firm level since both
national level policies can affect firm strategy as well as vice versa. Managerial

implications of study results for firms from industrialized countries and developing

131

countries are discussed separately due to significant differences found between the two
groups.
6.2.1.1 i f r n iz nt
As discussed in Chapter 3 in the Review of Literature, the global strategic
management literature was reviewed to draw implications for pharmaceutical MNCs from
the study results. Three streams of thought in the literature were found to be applicable to
this study. These were: (1) Core Competencies, (2) Comparative advantage-based

competitive advantage and (3) Collaborate to compete.

(1) WM: As defined earlier, core competencies are "the collective
learning in the organization, especially the coordination of diverse production skills and
integration of multiple streams of technology" (Prahalad and Hamel 1990, p. 82).

According to most experts in global strategy and competitiveness, firms must
possess some core competency which is difficult for competitors to imitate in order to have
sustained competitive advantage.

The results of this study show that ability to innovate is causally related to global
sales or global competitiveness in the pharmaceutical industry. Further, the environment
for innovation is affected by the home country's economic, regulatory and market/industry
environments. Thus the key to competitive advantage for industrialized country
pharmaceutical fums will be in developing core competencies in R&D as well as being able
to strategically manage their R&D programs with respect to changing economic, regulatory
and market/industry conditions of the countries in which they operate.

A good example would be the Japanese MNCs. In response to a stagnating
economy, increasing price pressures from the Japanese government, and greater foreign
competition in the home markets, several Japanese pharmaceutical firms have in the recent

past invested heavily in R&D research units in the US and abroad, along with marketing

132

agreements with major US and European multinational companies involving licensing and
co-marketing agreements (Yoshikawa 1989).

Several US multinationals are now focusing their R&D efforts on only a few
therapeutic categories with more research being disease-based rather than symptom-based.
This is in response to the increasing costs of research and the increasing regulatory and
competitive pressure such as competition from generic manufacturers (Financial World
1989).

A second area of core competency in the pharmaceutical industry is in marketing
(Bogner and Thomas 1992). Analysis of the global diffusion model revealed that the
market potential for diffusion is significantly affected by a nation's economic, regulatory
and market/industry environments. Thus selection of international markets for investment
or introduction of new products should be undertaken only after a careful evaluation of the
above environmental factors. Firms can develop core competencies with respect to being
able to identify changes in environmental conditions for investment purposes.

The dynamic environment in the European Community offers an especially
appropriate illustration of the above problem. Due to the unification of the European
community markets and the effort towards harmonizing the various environments,
pharmaceutical firms in the EC have been faced with great uncertainties with respect to
future market conditions. Firms that can strategically manage their marketing programs in
coordination with these changing environmental conditions will be at a distinct competitive
advantage in the future.

An example to illustrate the above, is the alliances developed by small local
companies in the EC to attract foreign multinationals for licensing purposes. For example,
Derma Alliance is an alliance of dermatological companies comprising of small local firms
from Norway, UK, Germany, Spain and France, formed in direct response to the changing
EC environment. The idea of this alliance is to offer big multinationals development,

regulatory and marketing help (Longman 1994) with their licensed products. By licensing

133

a product to one of the Alliance members, a licensor can acquire local partners in all major

European markets and speed its time to market.

 

(2) 2' - a, = =_ '- 111.1; iiv 2 ~:This concept implies
the design of international strategies based on the interplay between the comparative
advantages of countries and the competitive advantages of firms (Kogut 1985).

Comparative advantage, sometimes referred to as location specific advantage, arises
out of the differences across national markets in factor costs. Thus a firm can gain cost or
other advantages by configuring its value chain such that its activities are located in those
countries that have lowest cost for a particular factor. National differences can also arise in
the markets for fum outputs. Some of these differences arise from varying consumer tastes
and preferences, as well as different institutional arrangements that affect the output
markets (Kochhar and Hitt 1995).

Competitive advantage, sometimes referred to as firm-specific advantage,
influences the decision of what activities and technologies along the value-added chain, a
fum should concentrate its resources in, i.e., the core competence of the firm.

Industrialized countries differ with respect to the environmental conditions of their
markets for the global pharmaceutical industry. Differences in national economic,
regulatory, and market/industry environments can be sources of comparative advantage to
industrialized MN Cs.

For example, with respect to regulatory environment, firms based in the US have a
comparative advantage as they can benefit from the freedom from price controls on
pharmaceuticals. PRICEREG was found to be a significant variable affecting both
innovation investment as well as the market potential for diffusion. At the same time,
APPTIME - time taken by the regulatory agencies to approve a new drug for marketing was

found to have little effect on the innovation environment as well as on the market potential

134

for diffusion. Thus companies need be less cautious of national differences with respect to
the above regulatory aspect in their strategic location decisions.

Population (POP) for example, was found to be a significant determinant of both
market size (MKT SIZE) and R&D expenditure (R&DEXPD). Industrialized countries with
large populations could be a source of comparative advantage to firms based in those
countries. The large populations in the US and UK as compared to countries such as
Belgium or Switzerland are definite sources of comparative advantage to pharmaceutical

frrrns looking for large markets.

(3) mm: In recent years, several experts have studied the

effectiveness of alliances in international business and found them to be an important
weapon of competitive advantage in the global competitive arena (Hamel, D02 and Prahalad
1989; Harrigan 1987; Ohmae 1989). According to Hamel et al., "it takes so much money
to develop new products and to penetrate new markets, that few companies can go it alone
in every situation" (p. 133).

According to Shan and Hamilton (1991), such international cooperative ventures
provide a firm with access to country-specific advantages embedded in its partners. In the
opinion of the above researchers, "international cooperative relationships may be viewed as
a vehicle to tap into the comparative advantages of countries" (p. 419). In an empirical
study of a sample of domestic and international cooperative relationships of Japanese firms
in the biotechnology industry, Shan and Hamilton found country-specific advantages to be
a significant variable in explaining differences between cooperative relationships with
partners of different countries.

The case for collaboration is particularly strong in the global pharmaceutical
industry in the present environment. The combined effects of patent erosion, new research
methodology, competition from generics and a rise in the real costs of R&D are forcing

companies into mergers, acquisitions and alliances. The case for mergers and acquisitions

135

is stronger when attention turns to marketing. Larger operating units are a logical way to
cut marketing costs and gain access to new buyers. Few drug producers (particularly
European ones) have distribution systems in place in both Japan and the United States, the
world's two biggest markets.

Japanese MNCs have been especially active in taking advantage of country—specific
differences in their choice of collaborations. For example, results of the global innovation
and diffusion models reveal the effect of national environmental differences on the markets
for developing and introducing N CEs. Firms based in these varying national environments
have these effects embedded in them to a certain extent and are better able to deal with the
environments in which they are located.

Japanese firms, by entering into strategic alliances with US and Western European
firms manage to get access to registration and development systems in these countries. For
example, Takeda, a major Japanese multinational established a joint venture in the United
States with Abbott Laboratories to develop and market ethical drugs. Takeda also has ties
with firms in Germany, France, and Italy, and funds research at Harvard and Tulane
Universities (Business Week 1990).

Merck, the US based multinational formed an alliance with Sigma Tau of Italy in
1982 to co-market a number of products in Italy (USIT C 1991). Italy's market is highly
nationalistic and foreign firms need to develop a close relationship with governmental
agencies to obtain more timely approval and attractive pricing. This can be possible only
through marketing alliances with domestic companies. Merck and Sigma Tau have also
entered into a research joint venture agreement, with the Italian company seeking to tap into

the comparative advantage in research of the US-based company.

6212 WWW

As discussed in the Chapter on Results, the analysis of the global innovation model

revealed a poor fit with respect to developing country pharmaceutical industries. In

136

addition, several significant differences as well as opposite effects were found between
industrialized country group and the developing country group.

This result has important implications. Most research done on industrialized
country samples generalizes the findings to developing countries since data on developing
countries is scarce. The results of this study show that such generalizations cannot be
made.

The negative and insignificant relationship between INNOVAT and GBLSALES
for the D-group implies that innovation is not a significant determinant of global sales for
developing country firms and that there may be other sources of competitive advantage that
developing country MNCs can employ. Some recommendations with respect to the

strategies that such MNCs can employ are discussed using a similar framework as above.

(1) Wales: The pharmaceutical industry in the developing countries

consists mostly of reproductive firms (Ballance, Pogany and Forstner 1992). These firms
are mostly locally-owned or subsidiaries of multinationals or joint ventures between
indigenous and foreign companies. In several of these countries, the firms do no more
than produce the finished product from imported inputs.

However, there are certain core competencies that developing country firms can
develop in order to compete in the global market place. The example of Indian
pharmaceutical firms is illustrative.

Like many other developing countries, India recognizes patents only for processes.
Some of its companies specialize in W yielding drugs that
are identical to those produced (at much greater expense) by multinationals. The Indian
firms begin by selling their new products domestically; later they scale up operations to cut
manufacturing costs. The foreign markets which they select as targets are countries that
recognize process patents but not patents on the product itself. By the time the companies

are ready to export, they can often sell the drugs at less than a tenth the price charged by

137

competitors in industrialized countries (Ballance, Pogany and Forstner 1992; Narayana
1984).

The growth of generic markets and the many drugs which will soon come off patent
mean that a greater portion of the world's markets could soon be open to producers in
developing countries.

Some of the newly industrializing countries such as Singapore, South Korea and
Taiwan are aggressively targeting the biotechnology market for the future (Howe 1992;
1993). These countries have created technology centers, offered tax incentives, and tried to
improve basic science research in order to develop more competent scientists. Korea has
been able to compete on high-volume, low-cost products throughout the Southeast Asian

region.

. : Developing countries

 

differ significantly among themselves with respect to their national economic, regulatory
and market/industry environments for pharmaceuticals. That is, countries differ with
respect to their comparative advantages. As explained previously, such differences can be
exploited for purposes of gaining competitive advantage by multinational firms.

For example, Hong Kong is looking into developing a partnership with China,
offering its business skills and tapping China's scientific expertise, low wages and plentiful
natural resources. The Hong Kong Institute of Biotechnology has partnered with the
Chinese Academy of Sciences to identify marketable compounds from traditional Chinese
remedies (Howe 1993). Hong Kong may then use the expertise it gains to launch its own
industry and as a result become competitive in the future.

Third World MNCs can take advantage of the booming economies of the NICs and
their growing markets for pharmaceuticals. For example, Singapore has attracted new

material production, formulation and packaging plants because of the attractive incentives

138

offered by the Singapore government. Singapore is poised to become the medical treatment

and distribution center for the Southeast Asian region.

(3) Waste: For developing country MNCs, competing via
participation in joint ventures or alliances is a particularly useful mode for entering the
global market. Since most firms from such countries are small with insufficient research
and production resources, collaboration can provide the means to pool resources and
acquire access to new markets.

Most Western pharmaceutical companies for example, choose to enter developing
country markets through joint ventures. Developing country firms can gain important
technological know-how from the more advanced multinationals in return for their
marketing expertise and familiarity with local governmental agencies.

China for example, is establishing growing links with fnms from industrialized
country who are interested in developing retail and OTC products from traditional Chinese
herbal remedies. Some foreign participants hope to make use of Chinese research on
biological agents which they could convert into drugs. Other arrangements call for Chinese
scientists to conduct the research and the collaborator to develop the products. Later the
Chinese are expected to test the prototypes in research facilities provided by their overseas

partner (Ballance, Pogany and Forstner 1992).

62-2 W

The pharmaceutical industry is unique in that it is one of the few industries
in which, in almost all countries, the government plays an important role and takes a keen
interest in industry operations. Because the industry is of such social importance, the
government sees itself as a major regulating force and acts by formulating a variety of

policies affecting the industry in critical ways.

139

6.2.2.1 ’c ' I i ti r 'liz un ri

The results of the study reveal that a country's economic, regulatory and
market/industry environment have a significant impact on the factors that directly affect
global competitiveness. Further, the above environments are also found to exert significant
indirect effects on global competitiveness in the pharmaceutical industry.

With respect to the economic environment, GNP was found to be a significant
variable affecting market size, industry focus and industry concentration. It was also found
to impact investment in innovation. Thus industrialized country governments need to
evaluate the nation's economic environment before taking policy measures with respect to
the pharmaceutical industry. A robust economy seems necessary for a thriving industry.

Population size was also a significant factor affecting both market size and industry
focus. The large industrialized countries with significant populations should take
advantage of this in promoting the pharmaceutical industry further.

With respect to the regulatory environment, price control was the only significant
factor affecting competitiveness. It had a significant negative effect on market size and
R&D investment for innovation. It also had a significant indirect negative effect on both
innovation and global sales. Further it also had a significant negative impact on the market
potential for diffusion of new drugs.

Industrialized countries need to develop creative means of price control such that
incentives for industrial innovation are not affected and health care is accessible to all at the
same time. UK is one country that has been successful in this attempt. It uses a program
called PPRS. This is a voluntary program and is intended to maintain price levels that
allow for a "reasonable return on capital," to ensure that prices of pharmaceutical products

are not raised arbitrarily, and to limit the cost of drugs to the National Health Service

140

(N HS). The PPRS is credited with having increased investment in the British
pharmaceutical industry (Taggart 1993).

In contrast, the price control program used in Germany is expected to negatively
impact innovation in the future. The program utilizes the concept of therapeutic clustering,
and has reportedly resulted in a 25-40 percent decrease in pharmaceutical prices in
Germany. Therapeutic clustering, or the grouping of drug products for similar indications
for reimbursement at similar price levels by either health insurance plans or national health
systems, regardless of whether the products are patent protected, is expected to exacerbate
the impact of cost-containment efforts.

Pricing controls have also been enacted in almost all of the EC countries. The
implementation of price controls in the EC has resulted in price differentiation in the
individual countries, which has, in turn, resulted in increased parallel trade. The
undercutting in price that results from parallel trade results in decrease in revenue, which
could in turn have a potentially negative impact on R&D.

With respect to market/industry environment, market size was the most important
factor affecting R&D expenditures as well as outbound foreign investment. A large home
market size promoted greater investment in innovation and had a significant indirect effect
on global competitiveness. Thus industrialized country governments need to maintain
market demand in the home country by implementing appropriate policies that have the
effect of increasing pharmaceutical market size. One of the means by which this can be
achieved has already been discussed, namely restrict policies that implement stringent price
controls.

Innovation investment or R&D expenditure had a direct effect on global innovation
(number of NCEs developed) which in turn was a strong explanatory variable of global
sales (global competitiveness). Policies in industrialized countries should therefore be
geared to increase industrial investment in innovation. National funding agencies such as

the NIH in the US have been important sources of R&D funding for the industry. Japan

141

reportedly has 19 different tax incentive systems to encourage technological innovation,
including an R&D tax credit similar to that of the United States. Federal government
support for medical research in the US continues to exceed funds allocated by other
national governments (USI'I'C 1991).

Global innovation was also the most important determinant of global diffusion.
This implies that factors that encourage global innovation will also encourage global
diffusion. To be frequent first-time recipients of new drug discoveries (NCEs) is
obviously an important social goal for all industrialized countries. Introduction of NCEs
into the market also has the effect of increasing industry competition and thus driving
innovation. Thus all of the above policy issues relevant for industrial innovation are also
relevant for increasing diffusion of NCEs into the country.

In sum, public policies in industrialized country markets must be geared towards
increasing GNP, increasing market demand for pharmaceuticals, restricting price control
measures and increasing investment in R&D in order to promote global competitiveness of

its pharmaceutical industry.

6.2.2.2 l’ P 'c Im i i D v I r

As discussed earlier, policies that work for industrialized countries are assumed to
be universally applicable for all developing and under-developed countries in order to
achieve the same level of economic development.

Lall (1990) advisor to the OECD, is of the view that such conventional approaches
lead to wrong policy responses. For example, the World Bank's structural adjustment
policy recommendations for industry in developing countries have little directly to say
about the time lag between policy changes and supply response, human resource
development or the needs of institution building. They barely differentiate among

countries' different levels of development.

142

In most studies related to technology and economic growth, "technology" is taken
to be freely available to all countries and, within countries, to all firms. To the extent that
technology lags are admitted, developing countries are taken to receive all relevant
improvements from developed country innovators; there is no problem in assimilating the
transferred technology; there are no adaptations required, etc.

The results of this study show that the causal variables for global competitive
advantage in the pharmaceutical industry not only have opposite effects for developing
country industries but also that these effects overall may not be significant in being able to
explain the determinants of competitiveness. This has significant implications for public
policy makers and consultants to the pharmaceutical industry in developing countries.

Policy makers in developing countries need to focus on the following aspects to
improve the position of the firms both nationally and internationally.

(1) Improve and strengthen the scientific base for development and production
of the traditional medicine and household remedies.

(2) Invest in development of repackaging and formulation plants.

(3) Advance development and production of bulk drugs, including
immunologicals and antibiotics.

(4) Establish regulations relating to domestic and foreign corporate ventures and
the importation of foreign drugs, intermediates and know-how.

(5) Review pricing and patent protection policies for increasing market
attractiveness for foreign investment.

(6) Promote exports of pharmaceutical preparations and encourage international

collaborations with both developing and developed country firms.

Public policy makers are often guilty of being too enamored of the gadgetry and
high technology, thus distorting the pattern of investment in health care supplies and
pharmaceuticals. Governments in these countries need to appreciate that they cannot
achieve quickly the same level of sophisticated technology as the United States or Japan.
They will have to make the best use of what is currently available, because advanced

innovation is beyond their means or not as important as other needs atleast for now.

143

6.3 TRIB T N F HE
6.3.1 IhecretieaLflontribLticus

The present study makes significant theoretical contributions to several streams of
literature, namely the literature on national competitiveness; literature on pharmaceutical
innovation and diffusion; the economic development literature; and the global strategic
management literature.

With respect to the national competitiveness literature, it tests theoretical concepts in
the Theory of Comparative Advantage, the Technology Factor theory; Porter's theory of
the National Diamond of Competitiveness; and the role of government in national
competitiveness.

Comparative advantages of countries with respect to their economic, regulatory and
market/industry environments are found to be important for competitiveness in the
pharmaceutical industry. Technology - ability to innovate is found to be a significant factor
in global competitive advantage for the pharmaceutical industry. Both factor and demand
conditions in Porter's diamond of national competitive advantage were tested empirically
with regards to the pharmaceutical industry and found significant.

The debate on the role of government in national competitiveness was tested in this
study with respect to a single industry. The regulatory factors were found to significantly
affect the determinants of competitiveness.

With respect to the theoretical literature on pharmaceutical innovation and diffusion;
it makes a contribution by considering factors beyond just the effect of regulatory variables

that most studies in the above literature have examined. This study tests a comprehensive

144

model considering a variety of supply and demand factors affecting pharmaceutical
innovation and diffusion.

The contributions of this study to the theories on economic development are also
important. By empirically testing the same model for both industrialized and developing
countries, the results show that determinants of competitive advantage vary significantly for
the two groups. The results refute the generalized assumption of the Technology factor
theory that developing countries can simply imitate the developed country model of
technology and increase their rate of economic growth.

The study results also provide interesting insights for the global strategic
management literature. Most importantly, the study points to the importance of national
environments and the need for firms to be able to adapt to varying economic, regulatory,
and industry environments to be competitive. Most global strategic management research
has tended to focus on factors endogenous to the firm and ignored the more macro factors

affecting frrrn competitiveness in the global economy (Bolton and Boyacigiller 1993).

6.3.2 Empiricalfirmtrjhuticns

The present study makes significant empirical contributions to the global
competitiveness literature on the pharmaceutical industry.

According to the US International Trade Commission report (USITC 1991), most
studies in the above literature have focused on US firms, using mono-national samples or
bi-national samples at the most. There are just a handful of studies using several country
samples focusing on overall factors affecting all countries taken together, not just one
country.

A second shortcoming in the research on global competitiveness in the
pharmaceutical industry is that most studies have considered only regulatory factors in

exclusion to additional factors which are as important if not more.

145

A third weakness in previous research on global competitiveness in the
pharmaceutical industry, identified by USITC, is the primary focus on supply related
factors of innovation. Demand related factors have been ignored, i.e., factors affecting
demand for pharmaceutical innovations across national markets, which are of great strategic
importance.

A fourth shortcoming in the research on global competitiveness in the
pharmaceutical industry is the predominant focus on the industrialized countries.
Admittedly, it is the industrialized country firms that play a major role in the global
competition in pharmaceuticals, however one cannot forget the enormous social importance
of the industry and its role in improving quality of life for all humans. Competitiveness
issues with respect to the developing countries' pharmaceutical industry deserve more
attention and research.

The present study attempts to overcome the above limitations as follows:

(1) The study utilizes a sample of over 200 firms representing twenty-seven
countries which is far more than the USITC study which used twenty-nine
firms representing seven countries for assessing competitiveness.

(2) The study examines the effect of several variables in addition to regulatory
variables, such as GNP, population size, market size, industry focus,
industry concentration, industry growth, foreign investment, foreign
commitment, etc., on pharmaceutical innovation.

(3) The study examines both supply related and demand related factors affecting
global competitiveness in the pharmaceutical industry as recommended in
the USITC report.

(4) The study examines both industrialized countries and developing countries,
finding significant differences between the two, with crucial managerial and

public policy implications for developing countries emerging as a result of
the analysis.

6.3.3 It i t'
This study uses structural equation modeling (SEM) to test the path diagrams
developed from the theoretical literature. SEM is an extension of several multivariate

techniques and provides a means of dealing with multiple dependence relationships

146

simultaneously while providing statistical efficiency (Hayduk 1987). To the best of this
researcher's knowledge, there are no studies using the above statistical method in the
research on pharmaceutical innovation and diffusion. The few empirical studies in this area

use regression techniques at the most.

63.4 W

The results of this study make significant contributions with respect to the
managerial and public policy literature. These have been discussed previously in section

6.2.

64 W

The major limitation is with respect to the nature of international data used in the
study. Differences in accounting terms and techniques exist. The definition of
pharmaceutical business is also notoriously varied. Shifts in exchange rates have affected
performance; for example in recent years the Europeans and Japanese have particularly
benefited from the depreciation of the dollar. Therefore, some of the data may not be
capable of direct comparison. However, maximum effort has been made where ever
possible to correct for inconsistencies and ensure the comparability of the data used in this
study.

A second limitation is with respect to the time frame used in the study. Data over a
four year period (1990 to 1994) was used. Resource constraints with respect to time
available to the researcher for collecting and inputting the data in a usable form prevented
use of a longer time frame for the study. However, this is not considered as a major
limitation but may in fact have been the appropriate time frame to use. This is because a
longer time frame would have introduced confounding effects due to the significant

changes in the global environment of the pharmaceutical industry taking place in the late

147

19805. Availability of a longer time frame would have necessitated splitting the analysis
into two time periods to weed out the confounding effects. It would of course be
interesting to do a two period analysis to observe differences if any with respect to the
effect of the various factors tested.

A third limitation of the study is that it focuses on a single industry - the
pharmaceutical industry. Results may not be generalizable to other industries. However,
the path models and the variables tested are general enough to be applied to other industries
as well. Thus, future research could be done for other industries as well.

Finally, a greater number of regulatory variables need to be tested with respect to
their effect on innovation and diffusion of NCEs. Difference between countries with
respect to their product liability laws, patent protection legislation, licensing and joint-
venture policies, etc. have important effects on rate of inter country innovation and
diffusion of NCEs. Inclusion of each additional variable to the models used in this study
would have greatly increased the complexity of the research design and rendered

interpretation of the results difficult.

6.5 W

Some suggestions for future research have been discussed in the section on study
limitations. Other suggestions are discussed below.

The global pharmaceutical industry has been undergoing increasing international
consolidation in the past decade. The consolidation has ranged from mergers to strategic
alliances. Such corporate strategies have changed the structure of the global industry with
respect to industry concentration and definition of national corporate identity. It has also
obviously affected the nature of competition in the industry. Greater empirical and
theoretical research on the above issue is needed to extend the state of knowledge on

competitiveness in the global pharmaceutical industry.

148

A second area of research closely related to pharmaceuticals is the area of
biotechnology. According to the USITC study, biopharrnaceuticals are expected to account
for an increasing share of pharmaceutical production within the next decade. Several
countries, especially Japan have identified biotechnology as the most important industry for
competitiveness in the future (Tokyo Business Today 1990). The Japanese biotechnology
industry is reportedly in a position to become a major competitor in the world market.
Thus, the role of the biotechnology industry in the global competitiveness of a country's

pharmaceutical industry needs to be researched.

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149

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APPENDIX A

159

APPENDIX A

Table A.1 Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. Paths Overall Industrialized Developin
v3,v1 0.19021 0.423 -.129
Economic env ---> (0.167)b 0.225 .265
Mkt/Ind structure 1.08 4c 1.725 -.486
V 3, v 2 -0.365 -0.397 -.030
Regulation ---> (0.167) 0.225 .265
Mkt/Ind structure -2.087 -1.618 -.113
v 4, v T 0.026 0.192 .483
Economic env --—> (0.066) 0.090 .233
Innovation Invst 0.374 1.850 2.208
V4,V2 -0.165 -0.330 .180
Regulation --> (0.070) 0.089 .231
Innovation Invst -2. 128 -3 .217 . 8 32
van? 0.856 0.685 -.218
Mkt/Ind structure --> (0.075) 0.107 .232
Innovation Invst 11.307 6.049 -.995
V5,V4 0.901 0.846 .890
Innovation Invst—--> (0.085) 0. 167 . l 20
Foreign Mkt invst 10.777 5.263 7.319
v6,v4 1561 1.537 -.885
Innovation Invst---> (0.170) 0.235 .497
Global Innovation 9.310 6.882 -1.672
v6,v§ ofi -O.885 .9_47
Foreign Mkt Invst--> (0.168) 0.226 .504
Global Innovation -4.627 -3 .962 1 .790
v 7 , v6 0.896 0.848 -.008
Global Innovation--> (0.086) 0.164 .267
Global Sales 10.489 5.306 -.031
Fit Indices
Chi-square, df 22.16,12 7.207,]2 13.007,12
p—value 0.046 0.843 .368
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1 .000
CFI 1.000 1.000 1.000

 

a = standardized coefl'rrcient, b = standard error, c =t-va1ue
v1= gnp; v2= pricereg, v3= mktsize, v4: r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

160

Table A.2

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Develo in
v3,v1 03363 -0.67 -.256 1
Economic env --> 0 168b 0.287 .247
Mkt/Ind structure ' -0.573 -1.008
-1.91 1c
——3_2v ,v 0.726 019‘? .181
Regulation ---> 0.168 0.287 .247
Mkt/Ind structure 1.287 0.664 .714
v4,vI 0.241 0.558 .417—
Economic env --> 0.163 0.130 .224
Innovation Invst 1.385 3.680 1.980
v4,v2 -0.511 -0.685 .252
Regulation ---> 0.158 0.131 .221
Innovation Invst -3 .044 -4.545 1 .217
v4,v3 0.147; 0.418 -.372
Mkt/Ind structure --> 0.176 0.135 .234
Innovation Invst 0.825 2.732 -1.735
‘_"'_5v ,v4 0.901 0.847 .890
Innovation Invst-nu) 0.084 0. 1 66 . 1 20
Foreign Mkt invst 10.79 5.274 7.319
v6,v4 1.561 1.538 -.885
Innovation Invst—--> 0.170 0.234 .497
Global Innovation 9.312 6.886 -1.672
v*6,v§ 07—76 0885 .947—
Foreign Mkt Invst--> -0.779 0.226 .504
Global Innovation -4.627 -3.962 1.790
v7 , v6 0.896 0.848 -.008
Global Innovation--> 0.904 0.164 .267
Global Sales 10.498 5.313 -.031
F‘it Indices
Chi-square, (if 22. 15, 12 6940,12 12.40, 12
p-value 0.035 0.861 .413
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

 

a = standardized coefficient, b = standard error, c = t-value

v1= gnp; v2= pricereg, v3= mktfocus, v4= r&dexpd, v5= frginvst, v6= innovat, v7: gblsales

161

Table A.3

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developin
v3,v1 -o,191a -0.079 -.l86
Economic env ---> 0.190!) 0.296 .258
Mkt/Ind structure -10037c -0.226 -.746
__T‘Zv ,v 02—12 0.137 “3713
Regulation ---> 0.190 0.296 .258
Mkt/Ind structure —l.147 0.461 -1.258
v4 , v 1 0.182 0.500 .468
Economic env --> 0.158 0.158 .235
Innovation Invst 1.085 2.759 2.1 18
v4,v2 -0.490 -063? .115
Regulation ---> 0.159 0.159 .244
Innovation Invst -2.905 -3.467 .501
v4,v3 0057 0.209 -.i30
Mkt/Ind structure --> 0.157 0.160 .239
Innovation Invst -0.334 1.143 —.987
V5,V4 0.901 0.847% .890
Innovation Invst-----> 0.084 0. 166 . 1 20
Foreign Mkt invst 10.794 5.283 7.319
v6,v4 1.562 1.539 -.885
Innovation Invst-~--> 0.170 0.234 .497
Global Innovation 9.3 13 6.889 -1 .672
v 6,3 ~0.776 -0.885 .947
Foreign Mkt Invst--> 0.168 0.226 .504
Global Innovation -4.627 -3 .962 1 .790
v 7,V6 0.896 0.849 -.008
Global Innovation--> 0.904 0.163 .267
Global Sales 10.502 5.318 -.031
Fit Indices
Chi-square, df 2280,12 6641,12 12.485,12
p-value 0.046 0.88 .407
BBFI 1.000 1.000 0.995
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= gnp; v2= pricereg, v3= mktgrwth, v4= r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

162

Table

A.4

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing ‘
v 3 , v 1 -,421a 0.069 .036
Economic env --> . 18 4b 0.284 .262
Mkt/Ind structure -2.408° 0.242 . 135
v3,v2 -.171 -0.300 -.164
Regulation --—> . 184 0.284 .262
Mkt/Ind structure -.978 -1.047 -.621
v4,v1 .114 0.499 .489
Economic env ---> .171 0.157 .182
Innovation Invst .628 2.763 2.863
v4,v7 -.510 -0.671 .2——78
Regulation ---> . 158 0. 164 . 184
Innovation Invst -3.042 -3.549 1.606
V4,v3 -.186 -0.225 .553
Mkt/Ind structure --> .165 0.166 .185
Innovation Invst - l .008 -1.188 3.191
' v3,v4 .901 0.847 .890
Innovation Invst-«—> .086 0. 166 . 1 20
Foreign Mkt invst 10.598 5.275 7.319
V6,V4 1.562 1.538 -.885
Innovation Invst---> .173 0.234 .497
Global Innovation 9.140 6.887 -1.672
v6,vT -.776 0885 94—7
Foreign Mkt Invst--> .172 0.226 .504
Global Innovation -4.540 -3 .962 1 .790
V ’,V6 .896 0.848 -.008
Global Innovation-m) .088 0.164 .267
Global Sales 10.310 5.314 -.031
Fit Indices
Chi-square, df 33.73,l2 8.76,12 13.62
p-value 0.001 0.72 .325
BBFI 1.000 1.000 0.999
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= gnp; v2= pricereg, v3= mktconc, v4= r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

163

Table A.5

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developin
v3,v1 0.431a 0.578 -.029
Economic env ---> 0.174b 0.241 .262
Mkt/Ind structure 2.4830 2.382 -.112
V3,V2 -0.009 0.130 -.175
Regulation ---> 0. 174 0.241 . 262
Mkt/Ind structure -0.051 0.534 -.666
V4,V1 0.140 0.261 .576
Economic env --> 0.074 0.127 .220
Innovation Invst 1.893 2.049 2.536
V 4 , V2 -0.055 -0.058 -.329
Regulation ---> 0.067 0.104 .223
Innovation Invst -0.820 -0.55 8 -1.595
v4,v3 0.868 0.768 -.262
Mkt/Ind structure --> 0.074 0.129 .224
Innovation Invst 1 1.774 5.975 -1.267
V5,V4 0.913 0.877 .893
Innovation Invst ----- > 0.079 0.145 . 1 18
Foreign Mkt invst 1 1.599 6.043 7.416
v6,v4 1.589 1.612 -.896
Innovation Invst-«--> 0.168 0.226 .496
Global Innovation 9.433 7. l3 1 -1 .676
V 6 , V5 -0.7—79 -0.896 .957
Foreign Mkt Invst--> 0.168 0.226 .504
Global Innovation -4.627 -3.962 1.790
v 7 , v6 0.906 0.868 -.008
Global Innovation—--> 0.082 0.150 .267
Global Sales 1 1.089 5.807 -.031
Fit Indices
Chi-square, df 32.41,12 13.76,12 11.622,12
p—value 0.001 0.315 .476
BBFI 1.000 1.000 0.998
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t—value

v1= gnp; v2= apptime, v3= mktsize, v4= r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

164

Table A.6

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing
‘ v 3, v 1 -0. 530a -0.322 -.342
Economic env --> 0.16313 0.252 .250
Mkt/Ind structure 3394‘: -1.306 -1.363
'—3—'v ,v2 0.247 0.476 -.035
Regulation —--> 0.163 0.252 .250
Mkt/Ind structure 1.583 1.928 -.141
v4,vI 0.572 0.821 .404
Economic env ---> 0.198 0.208 .225
Innovation Invst 2.927 3.938 1.942
v4,v2 -009 -0130 -.294
Regulation ---> 0.173 0.224 .21 1
Innovation Invst —0.523 -0.578 -1.502
v4,v3 0.110 0.359 -.353
Mkt/Ind structure --> 0.195 0.232 .226
Innovation Invst 0.547 1.5 16 -1.696
fiv ,v4 0.913 0.8% .893——
Innovation Invst-«-> 0.079 0.145 .1 18
Foreign Mkt invst 1 1.602 6.043 7.416
v6,v4 1.589 1.612 -.896
Innovation Invst-«--> 0.168 0.226 .496
Global Innovation 9.433 7.131 -1.676
v 6, v5 -0.779 -0.896 .957 ‘
Foreign Mkt Invst--> 0.168 0.226 .504
Global Innovation -4.627 -3 .962 1 .790
V7 , V6 0.906 0.868 -.008
Global Innovation----> 0.082 0.150 .267
Global Sales 1 1.092 5.807 -.031
Fit Indices
Chi-square, df 17.5,12 1151,12 1129,12
p-value 0.1303 0.485 .503
BBFI 1.000 1.000 0.998
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= gnp; v2= apptime, v3= mktfocus, v4= r&dexpd, v5: frginvst, v6= innovat, v7: gblsales

165

Table A.7

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industfialized DeveIoping ,
v 3 , v 1 -0.0663 -0.197 .033
Economic env --> 0.192!) 0.281 .267
Mkt/Ind structure -0.346C -0.706 .123
‘ V3, V2 0.058 0.329 -.054
Regulation ---> 0.192 0.281 .267
Mkt/Ind structure 0.300 1.180 -.202
v4,vl 0314 0:31 .53—2
Economic env --> 0.167 0.214 .220
Innovation Invst 3.1 16 3.403 2.61 1
V4,V2 -0.062 -0.002 -.297
Regulation ---> 0.167 0.222 .220
Innovation Invst -0.378 -0.009 -1.455
v4,v§ 0.001 0.171 -.253
Mkt/Ind structure --> 0.167 0.225 .220
Innovation Invst 0.008 0.577 -1 .241
_—5v ,v4 0.913 0.877 89—3
Innovation Invst-—--> 0.079 0.145 .1 18
Foreign Mkt invst 1 1.603 6.043 7.416
v€,v4 1.589 1.613 -.896
Innovation Invst—--—> 0.168 0.226 .496
Global Innovation 9.433 7. 13 1 -1 .676
v6,v§ 0.779 -0.896 .957
Foreign Mkt Invst--> 0.168 0.226 .504
Global Innovation -4.627 -3.962 1.790
v7 , v6 0.906 0.868 -.008
Global Innovation----> 0.082 0.150 .267
Global Sales 1 1.092 5.807 -.031
Fit Indices
Chi-square, df 48.79,12 7.726,12 10.357,12
p-value 0.001 0.8061 .584
BBFI 1.000 1.000 0.996
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

 

a = standardized coefficient, b = standard error, c = t-value

v1= gnp; v2= apptime, v3= mktgrwth, v4: r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

166

Table A.8

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing
v 3, v 1 -o,352a 0.225 .086
Economic env ~-> 0 180b 0.293 .263
Mkt/Ind structure ' 0.768 .327
-2.05c
‘ v3,v2 0.166 0.033 .113
Regulation ---> 0.180 0.293 .263
Mkt/Ind structure 0.938 0.1 13 .429
v 4 , v 1 0.474 0.722 .478
Economic env --> 0.178 0.217 .172
Innovation Invst 2.699 3.31 1 3.003
V 4 , V2 -0.044 0.044 -.342
Regulation ---> 0.168 0.212 .172
Innovation Invst -0.264 0.205 -2.143
v4,v3 -0.111 -0.071 .5718
Mkt/Ind structure --> 0.177 0.217 .174
Innovation Invst -0.621 -0.326 3.420
v3,v4 0.913 0.877 .893
Innovation Invst—--> 0.079 0.145 . 1 18
Foreign Mkt invst 1 1.604 6.043 7.416
v6,v4 1.58 1.613 -.896
Innovation Invst—«-> 0.168 0.226 .496
Global Innovation 9.433 7.131 -1.676
v 6, v5 -0.779 -0.896 .957
Foreign Mkt Invst--> 0.168 0.226 .504
Global Innovation -4.627 -3.962 1.790
V 7, V6 0.906 0.868 -.008
Global Innovation—-> 0.082 0.150 .267
Global Sales 1 1.093 5.807 -.031
Fit Indices
Chi-square, df 41.26,12 10.631,12 13.007,12
p-value 0.001 0.560 .368
BBFI 1.000 1.000 .999
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= gnp; v2= apptime, v3= mktconc, v4= r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

 

167

Table A.9

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall IndustrIaIized Developing
v3,v1 0372a 0.984 .618
Economic env --> 0. 15313 0.054 .221
Mkt/Ind structure 2.7269 18.48 3.263
1 v3 , v2 -0.60 0.034 -.340
Regulation ---> 0. 153 0.054 . 221
Mkt/Ind structure -4.406 0.630 -1.792
v4,v1 0.048 0.613 -.03_2
Economic env --> 0.073 0.479 .337
Innovation Invst 0.744 1.095 -.096
vai -0.184 0859 -.105
Regulation ---> 0.084 0.086 .282
Innovation Invst -2.481 -3.564 -.371
v4,v3 0.817 0.267 -.300
Mkt/Ind structure --> 0.081 0.469 .308
Innovation Invst 10.207 0.476 -.835
V5 , V4 0.929 0.842 .878 ‘
Innovation Invst----> 0.070 0. 169 . 1 28
Foreign Mkt invst 13.031 5.186 6.867
V6,V4 1.62 1.528 -.830
Innovation Invst---> 0.165 0.236 .504
Global Innovation 9.600 6.853 —1.649
v6,v? -0785 -0.884 .901
Foreign Mkt Invst--> 0.168 0.226 .504
Global Innovation -4.627 -3.962 1.790
1 V ’,V6 0.920 0.846 -.008
Global Innovation----> 0.074 0.165 .267
Global Sales 12.157 5.258 -.031
Fit Indices
Chi-square, (1f 2729,12 9499,12 11.604,12
p-value 0.007 0.659 .477
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

 

a = standardized coefficient, b = standard error, c = t-value

v1= pop; v2= pricereg, v3= mktsize, v4= r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

168

Table A.10

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

‘ Paths Overall Industrialized DeveIoping
v3,vl 0155:: 0.503 . 17
Economic env --> 0.171b 0.250 .244
Mkt/Ind structure 0.8809 2.459 1.265
——'3_2v ,v 0.3—76 0.534 .139
Regulation ---> 0. 171 0.250 .244
Mkt/Ind structure 2.137 2.609 .554
v4,v1 0.346 0.876 -.07T—*
Economic env --> 0.144 0.106 .247
Innovation Invst 2.736 7.013 -.295
V4,V2 -0.689 -.350 .060
Regulation ---> 0.153 .109 .237
Innovation Invst -5.1 12 -2.746 .25 1
v4, v 3 0.039 -.000 -.454
Mkt/Ind structure --> 0.159 .103 .257
Innovation Invst 0.285 -.002 -1.817
—v5,v4 0.929 .842 .87—8
Innovation Invst-~-> 0.070 . 170 . 1 28
Foreign Mkt invst 13.03 5.168 6.867
v6,v4 1.62 1.526 -.830
Innovation Invst—-> 0.165 .236 .504
Global Innovation 9.60 6.846 -1.649
v6,v5 -0.785 -.883 .901
Foreign Mkt Invst--> 0.168 .226 .504
Global Innovation -4.627 -3.962 1.790
V 7, V6 0.920 .845 -.008
Global Innovation—--> 0.074 0.166 .267
Global Sales 12.159 5.247 -.031
Fit Indices
Chi-square, df 983,12 823,12 13.09,12
p-value 0.070 0.766 .362
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

 

a = standardized coefficient, b = standard error, c = t-value

v1= pop; v2= pricereg, v3= mktfocus, v4= r&dexpd, v5= frginvst, v6= innovat, v7: gblsales

Table A.ll

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing
v 3 , v 1 0,093a .089 .25 I
Economic env --> 0 1911) .296 .256
Mkt/Ind structure ° .306 1.036
.489c
_flv ,v -.120 .271 -347—
Regulation ---> .191 .296 .256
Mkt/Ind structure -.630 .793 -1.434
v4,v1 .358 .863 -.146
Economic env --> . 141 .079 .260
Innovation Invst 2.882 9.365 -.559
v4,v2 -.686 -.383 -.104
Regulation .....> . 142 .080 .269
Innovation Invst -5.507 -4.054 -.388
VLW -.088 .138 -.290
Mkt/Ind structure -—> .141 .080 .262
Innovation Invst -.700 1.454 -1.043
‘fiv ,v4 .929 .842 .878
Innovation Invst----> .070 . 170 . 1 28
Foreign Mkt invst 13.040 5.172 6.867
v6,v4 1.629 1.527 -.830
Innovation Invst----> 0.165 .236 .504
Global Innovation 9.601 6.848 - l .649
V6,V5 -. 85 -.883 .901
Foreign Mkt Invst--> 0.168 .226 .504
Global Innovation -4.627 -3.962 1.790
v7,v6 .920 .845 -.008
Global Innovation----> .074 .166 .267
Global Sales 12.163 5.249 -.031
F'it Indices
Chi-square, df 2081,12 7932,12 1229,12
p—value 0.053 .790 .422
BBFI 1.000 1.000 1 .000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= pop; v2= pricereg, v3= mktgrwth, v4: r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

170

Table A.12
Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Indust_rialized Developing ‘
v 3,v 1 00298 -.304 .092
Economic env -—-> 0 1941) .273 .262
Mkt/Ind structure ' -1.227 .356
.149c
v3,v2 .117 -.484 -.243
Regulation —--> .194 .273 .262
Mkt/Ind structure .601 - l .957 -.944
v4,v1 .356 .876 ‘ -.280
Economic env --> . 139 .091 .205
Innovation Invst 2.907 8.208 -1.366
v4,v2 -.655 -.349 .148
Regulation ---> . 140 .099 .210
Innovation Invst -5.307 -3.001 .703
v4,v3 -.174 .001 .628
Mkt/Ind structure -—> .141 .094 .208
Innovation Invst -1.409 .01 1 2.970
v3,v4 .929 .842 .878 ‘
Innovation Invst-—-> .07 1 . 170 . 128
Foreign Mkt invst 12.799 5.172 6.867
v6,v4 1.629 1.527 -.830
Innovation Invst---> . 168 .236 .504
Global Innovation 9.420 6.849 -1.649
V6,V5 T785 -.884 .901
Foreign Mkt Invst--> .172 .226 .504
Global Innovation -4.540 -3.962 1.790
V1,, V6 .920 .846 -.008
Global Innovation--> .076 . 165 .267
Global Sales 1 1.936 5.252 -.031
Fit Indices
Chi-square, df 2544,12 8476,12 13.59, 12
p-value 0.012 .746 .327
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= pop; v2= pricereg, v3= mktconc, v4= r&dexpd, v5= frginvst, v6: innovat, v7: gblsales

 

Table A.l3

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overafi Industrialized Developing
v3,v1 0.1272! .983 .4 7
Economic env --> 0 189b .055 .235
Mkt/Ind structure ' 17.934 1.928
.676c
‘ V3,V2 .158 .024 -.070
Regulation ---> . 189 .055 .235
Mkt/Ind structure .839 .434 -.297
v4,v1 -.074 .888 -.142"'_"
Economic env --> .070 .609 .285
Innovation Invst - 1.05 1 .469 -.501
v4,vT -031 -.040 -.118
Regulation ---> .071 .1 12 .254
Innovation Invst -.446 -.365 -.468
V4,V3 .943 .043 -.232
Mkt/Ind structure --> .071 .612 .288
Innovation Invst 13.24 .07 l -.8 16
‘ v3,v4 .911 .879 .880
Innovation Invst--> .079 . 144 . 1 27
Foreign Mkt invst 1 1.49 6.106 6.920
v6,v4 1.58 1.618 -.837
Innovation Invst---> . 168 .226 .503
Global Innovation 9 .41 7. 148 -1 .652
v6,v5 -.7_79 -.897 .907
Foreign Mkt Invst--> .168 .226 .504
Global Innovation —4.62 -3.962 1.790
v7,v6 .904 .870 -.008
Global Innovation-«9 .082 .149 .267
Global Sales 1 1.009 5.849 -.031
Fit Indices
Chi-square, df 27.9,12 9.691,12 9972,12
p-value 0.005 .643 . 18
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1 .000

 

a = standardized coefficient, b = standard error, c = t-value

v1= pop; v2= apptime, v3= mktsize, v4= r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

Table A.14

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

, Paths Overall Industrialized Developin
v3,v1 0,343a .138 .369
Economic env --> 0.18013 .267 .245
Mkt/Ind structure 1951‘: .511 1.496
v3 , v2 .144 .423 «.099
Regulation ---> . 180 .267 .245
Mkt/Ind structure .807 1.569 -.399
v4,v1 .136 .949 -.075
Economic env --> . 199 . 106 .249
Innovation Invst .686 9.021 - . 301
V4,fi .153 .017 -.l48
Regulation ---> .189 .116 .233
Innovation Invst .809 . 148 -.639
v4,v3 -.229 -.133 -.468
Mkt/Ind structure --> .199 .118 .253
Innovation Invst -1.14 -1. 149 -1.880
, v3,v4 .911 .879 .880
Innovation Invst--> .079 . 144 . 127
Foreign Mkt invst 1 1.493 6.106 6.920
v6,v4 1.58 1.618 -.837
Innovation Invst----> .168 .226 .5 03
Global Innovation 9.418 7.148 -1.652
v6,v5 -.779 -.897 90—7
Foreign Mkt Invst--> .168 .226 .504
Global Innovation -4.627 -3.962 1.790
V17 , V6 .904 .820 —.008
Global Innovation—~> .082 .149 .267
Global Sales 1 1.012 5.849 -.031
Fit Indices
Chi-square, df 15.92,12 7.790,12 1 196,12
p-value 0.19 .780 .448
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= pop; v2= apptime, v3= mktfocus, v4= r&dexpd, v5: frginvst, v6= innovat, v7= gblsales

 

173

Table A.15
Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

, Paths Overall Industrialized Developing
v3,vI 0.0463 -.115 .024 ‘
Economic env --> 0 192b .285 .267
Mkt/Ind structure ' -.406 .091
.237c
v3,v2 .045 .325 -.033
Regulation —--> . 192 .285 .267
Mkt/Ind structure .234 1.148 -.123
v4,v1 .058 .941 —.241
Economic env ---> . 19 1 . 109 .250
Innovation Invst .305 8.723 -.971
v4,vf .121 -.069 -.110
Regulation —---> . 191 . 1 14 .250
Innovation Invst .634 -.606 -.443
v4,v3 40372 .090 -.2—52
Mkt/Ind structure --> .191 .114 .250
Innovation Invst -. 168 .786 -1.015
V5,V4 .911 .879 .880
Innovation Invst----> .079 . 144 . 1 27
Foreign Mkt invst 11.49 6.106 6.920
V6,V4 1.58 1.618 -.837
Innovation Invst----> .168 .226 .5 03
Global Innovation 9.41 7 . 148 -1 .652
_v6,v5 -.7_79 -.897 .907—
Foreign Mkt Invst--> .168 .226 .504
Global Innovation -4.62 -3 .962 1 .790
V 7,V6 .904 .870 -.008
Global Innovation---> .082 .149 .267
Global Sales 1 1.01 5.849 -.031
Fit Indices
Chi-square, df 15.66, 12 8.064,12 10.876,12
p-value 0.20 .780 .539
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1 .000

 

a = standardized coefficient, b = standard error, c = t-value

v1: pop; v2= apptime, v3= mktgrwth, v4= r&dexpd, v5: frginvst, v6= innovat, v7= gblsales

 

174

Table A.16
Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overfil jndustriglizefi Develo in
v3,vf 0,095a -.017 -.021
Economic env --> 0 1911) .301 .264
Mkt/Ind structure ° -.057 -.078
.498c
v 3, v 2 .066 .065 .148
Regulation ---> .191 .301 .264
Mkt/Ind structure .347 .215 .560
v4,v1 .083 .922 -.235 1
Economic env --> .184 .106 .200
Innovation Invst .450 8 .838 -1 . 179
V4,V2 .138 -.046 -.193
Regulation -----> .184 .106 .203
Innovation Invst .750 -.437 -.961
V4,V3 -.2_75 .104 .618
Mkt/Ind structure ...> . 185 . 106 .203
Innovation Invst -1.49 .984 3.072
—_—5v ,v4 .911 .879 .880
Innovation Invst----> .079 . 144 . 127
Foreign Mkt invst 1 1.49 6.106 6.920
V6,V4 1.58 1.618 -.837 ‘
Innovation Invst----> . 168 .226 .503
Global Innovation 9 .4 1 7 . 148 - 1 .652
v6,v5 -.7‘79 -897 .907—__—
Foreign Mkt Invst--> .168 .226 .504
Global Innovation -4.62 -3.962 1.790
V ’,V6 .904 .870 -.008
Global Innovation----> .082 . 149 .267
Global Sales 1 1.01 5.849 -.031
Fit Indices
Chi-square, df 1643,12 8804,12 13.483.12
p—value 0.17 .719 .334
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1= pop; v2= apptime, v3= mktconc, v4= r&dexpd, v5= frginvst, v6= innovat, v7= gblsales

 

175

Table A.l7
Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

. Paths Overall Industpialized Developin
v3,v1 0.190%: .423 -.129
Economic env --> 0.16713 .225 .265
Mkt/Ind structure 1.08 4c 1.725 -.486
v3,v2 -.362 -.397 -.030
Regulation ---> .167 .225 .265
Mkt/Ind structure -2.078 -1.618 -.113
v4,v1 .026 .192 .48_3 ‘
Economic env --> .066 .090 .233
Innovation Invst .374 1.850 2.208
v4,v2 -.165 -.330 .180
Regulation ----> .070 .089 .231
Innovation Invst —2.2 1 8 -3.217 .832
V4,V3 .856 .685 —.218
Mkt/Ind structure --> .075 .107 .232
Innovation Invst l 1.30 6.049 -.995
v5,v4 .135 -.241 .580
Innovation Invst-«--> .203 .334 .209
Foreign Mkt invst .710 -.825 2.665
V6,V4 .876 .691 -.220
Innovation Invst----> .098 . 155 .298
Global Innovation 9. 1 0 1 4.677 - .694
v6,v§ -.105 -.402 .308
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation - l .089 -2.720 .972
‘ v7,v6 .896 .848 -.008
Global Innovation----> .086 . 164 .267
Global Sales 10.489 5.306 -.031
Fit Indices
Chi-square, df 24.99,12 9.8,12 13.889,12
p-VEtlue 0.014 .633 .307
BBFI 1.000 1.000 1 .000
BBNFI 1.000 1 .000 1 .000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1=gnp; v2=pricereg; v3=mktsize; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

176

Table A.18

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Tndustfiafized Develo in
v3,v1 -.3363 -.164 -.256 ‘
Economic env --> 0 1689 .287 .247
Mkt/Ind structure ' -.562 -1.008
-1.911°
‘ V3,V2 .226 .191 .181
Regulation ——--> .168 .287 .247
Mkt/Ind structure 1.287 .655 .714
v4,vl .241 .32 .417
Economic env --> .163 .130 .224
Innovation Invst 1.385 3.695 1.980
v4,v2 -.511 -.684 .252
Regulation ---> . 158 . 13 1 .221
Innovation Invst -3.044 -4.554 1.217
v4,v3 .147 .416 -.372 ‘
Mkt/Ind structure --> .176 .135 .234
Innovation Invst .825 2.732 - l .735
‘ v5,v4 .136 -.2712 .580
Innovation Invst--> .203 .332 .209
Foreign Mkt invst .71 1 -.829 2.665
v6,v4 87-7 .693 -.220
Innovation Invst----> .098 .155 .298
Global Innovation 9.1 11 4.699 -.694
v6,v5 -.105 -.401 .308
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .896 .849 -.008
Global Innovation—-> .086 .163 .267
Global Sales 10.498 5.323 -.031
Fit Indices
Chi-square, df 22.35,12 7.819,]2 11.934,12
p—value 0.033 .799 .450
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1=gnp; v2qyricereg; v3antfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

177

Table A.19

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overail Industrialized Developing ‘
v3,v1 -0.191a -.079 -.186
Economic env --> 0.190!) .296 .258
Mkt/Ind structure -1.037c -.266 -.746
"fifl ,v -.21_2 .137 -.313
Regulation ---> . 190 .296 .258
Mkt/Ind structure -1.147 .461 -1.258
v4,vl .182 .500 .468
Economic env --> .158 .158 .235
Innovation Invst 1.085 2.759 2.1 18
v4,vf -.490 —.63T .115
Regulation ---> . 159 . 159 .244
Innovation Invst ~2.905 —3.467 .501
v4,v3 -.057 .209 T230
Mkt/Ind structure --> .157 .160 .239
Innovation Invst -.334 1.143 -.987
v3,v4 .136 -.2_2 .580
Innovation Invst---> .203 .333 .209
Foreign Mkt invst .71 1 -.828 2.665
v6,v4 87—7 .692 -.2T—2 ‘
Innovation Invst----> .098 . 155 .298
Global Innovation 9.1 15 4.693 -.694
v6,v5 -.105 -.401 .308
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .896 .849 -.008
Global Innovation-«9 .086 .163 .267
Global Sales 10.502 5.318 -.031
Fit Indices
Chi-square, df 20.87,]2 7.267, 12 13.028,12
p—value 0.05 .839 .366
BBFI 1.000 1.000 0.980
BBNFI 1.000 1.000 0.997
CFI 1.000 1.000 0.998

 

a = standardized coefficient, b = standard error, c = t-value

v1=gnp; v2=pricereg; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat;v7=gblsales

Table A.20

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Path OveralI Industrialized Develofin
v3,v1 -,421a .069 .036
Economic env --> 0. 1819 .284 .262
Mkt/Ind structure -2. 4 54c .242 .135
___an ,v -.171 -300 -.164
Regulation ---> . 18 1 .284 .262
Mkt/Ind structure —.996 -1.047 -.621
V4,V1 .114 .499 .489
Economic env --> .168 .157 .182
Innovation Invst .640 2.763 2.863
v4,v2 45710 -.671 .278
Regulation --—-> . 155 . 164 . 184
Innovation Invst -3. 100 -3.549 1.606
V4,V3 -.186 -.225 .553
Mkt/Ind structure --> .162 .166 .185
Innovation Invst -1.027 -1. 188 3 . 191
V5,V4 :136 -.242 .580
Innovation Invst---> .202 .333 .209
Foreign Mkt invst .71 1 -.827 2.665
v6,v4 .877 .692 -.220
Innovation Invst---> .098 .155 .298
Global Innovation 9. 12 4.687 -.694
v6,v§ -.105 -.401 .308
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .896 .848 -.008
Global Innovation—-> .086 . 164 .267
Global Sales 10.506 5.314 -.031
Fit Indices
Chi-square, df 2083,12 11.399,12 14.227, 12
p-value 0.05 .49 .286
BBFI 1.000 1.000 0.991
BBNFI 1.000 1.000 0.998
CFI 1.000 1.000 0.999

 

a = standardized coefficient, b = standard error, c = t-value

v1=gnp; v2=pricereg; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

 

Table A.2]

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrjplized Developing ,
v 3,v 1 0,432a .578 -.029
Economic env —-> 0. 174b .241 .262
Mkt/Ind structure 2.486c 2.382 -.112
v3,v2 -.009 .130 -.175
Regulation ---> . 1 74 .24 1 .262
Mkt/Ind structure -.051 .534 -.666
v4,vl .140 .261 .576 1
Economic env -~> .074 .127 .220
Innovation Invst 1.901 2.048 2.536
V4,V2 -.053 -.058 -.329
Regulation ----> .067 .104 .223
Innovation Invst -.799 -.557 -1.595
v4,v3 .8627 .768 -.262
Mkt/Ind structure --> .074 .129 .224
Innovation Invst 1 1.773 5.975 -1.267
‘ v3,v4 .146 -.275 .585
Innovation Invst—«-> . 1 88 .291 . 206
Foreign Mkt invst .764 -.947 2.700
v6,v4 .892 .7—25 -.223
Innovation Invst—m) .09 1 . 136 . 295
Global Innovation 9.785 5.321 -.700
v6,vr -.099 -.371 .310
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .906 .868 -.008
Global Innovation-«0 .082 .150 .267
Global Sales 1 1.094 5.807 -.031
Fit Indices
Chi-square, df 22. 10,12 10.005,12 10.647 , 1 2
p-value 0.036 .615 .559
BBFI 1.000 1.000 0.990
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

 

 

a = standardized coefficient, b = standard error, c = t-value

v1=gnp; v2=apptime; v3=mktsize; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

Table A.22

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industfialized Developing
v3,vl -.529a -.322 -.342
Economic env —--> 1639 .252 .250
Mkt/Ind structure ' - 1 .306 -1 .363
-3.38c
v3 , vT .277 .476 -.035
Regulation ---> . 163 .252 .250
Mkt/Ind structure 1.58 1.928 -.141
v4,vl .371 .821 .404
Economic env --> .195 .208 .225
Innovation Invst 2.932 3.938 1.942
v4,v2 -.09 -.130 -.294
Regulation ---> . 173 .224 .21 1
Innovation Invst -.526 -.578 -1.502
V4,“ .110 .59 -.353
Mkt/Ind structure --> .195 .232 .226
Innovation Invst .547 1 .5 16 -1 .696
V5,V4 .146 -.275 .585
Innovation Invst---> . 1 88 . 291 . 206
Foreign Mkt invst .765 -.947 2.700
v6,v4 .892 .725 -.223
Innovation Invst---> .09 1 . 1 36 .295
Global Innovation 9.786 5.321 -.700
v6,v5 -.099 -.371 .310
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation - l .089 -2.720 .972
V 7,V6 .906 .868 -.008
Global Innovation--> .082 . 150 .267
Global Sales 1 1.094 5.807 -.031
Fit Indices
Chi-square, df 1911,12 9440,12 11.309,12
p—value 0.08 .664 .502
BBFI 1.000 1.000 0.983
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, e = t-value

v1=gnp; v2=apptime; v3=mktfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

 

 

181

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Table A.23
Global Innovation Model
Paths Overall Industrialized Develo in
v3,vl -.0653 -.197 .033
Economic env --> .1921) .281 .267
Mkt/Ind structure _339‘: -.706 .123
v3,v2 .058 .329 -.054
Regulation ---> . 192 .281 .267
Mkt/Ind structure .301 1.180 -.202
v4,v1 .515 .721 .532
Economic env ---> . 167 .214 .220
Innovation Invst 3.1 19 3.403 2.611
NEW -.063 -.002 -297"—
Regulation ---> .167 .222 .220
Innovation Invst -.3 82 -.009 -1.455
v4,v3 .001 .131 -.2—53 "
Mkt/Ind structure --> .167 .225 .220
Innovation Invst .008 .577 - 1 .241
‘ v5,v4 .146 -275 .585
Innovation Invst--> . 188 . 29 1 . 206
Foreign Mkt invst .765 -.947 2.700
v6,v4 .892 .725 -.223
Innovation Invst---> .09 1 . 1 36 . 295
Global Innovation 9.786 5.321 -.700
v6,v5 -.099 -371 .310
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation - l .089 -2.720 .972
‘ V17,V6 .906 .868 -.008
Global Innovation—-> .082 . 150 .267
Global Sales 1 1.094 5.808 -.031
Fit Indices
Chi-square, df 1682,12 9373,12 9937,12
p-value 0.156 .67 .62
BBFI 1.000 1.000 0.990
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, e = t-value

v1=gnp; v2=apptime; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

182

Table A.24

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths OveraTl Industrialized Developing
v ,vl -,361a .225 .086
Economic env --> .180b .293 .263
Mkt/Ind structure _2.041c .768 .327
v3,v2 .166 .033 .113
Regulation ---> . 180 .293 .263
Mkt/Ind structure .938 .1 13 .429
v4,v1 4'3 .722 .4—78 ‘
Economic env ---> .178 .217 .172
Innovation Invst 2.703 3.31 1 3.003
vIvT -.045 .044 -.342
Regulation ---> . 168 . 2 12 . 172
Innovation Invst -.273 .205 -2.143
v4,v3 -.110 -.071 .548
Mkt/Ind structure --> .177 .217 .174
Innovation Invst -.621 -.326 3.420
v3,v4 .146 -.2 5 .585
Innovation Invst---> . l 88 . 29 1 . 206
Foreign Mkt invst .765 -.947 2.700
v6,v4 .892 .225 -.223
Innovation Invst----> .09 1 . 136 .295
Global Innovation 9.786 5.321 -.700
v6,vf -.099 -.371 .310
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
V 7, V6 .906 .868 -.008
Global Innovation--—> .08 1 . 150 .267
Global Sales 1 1.095 5.807 -.031
Fit Indices
Chi-square,df 41.93,12 11.771,12 13.316,12
p-value 0.001 .464 .346
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

 

a = standardized coefficient, b = standard error, c = t-value

v1=gnp; v2=apptime; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

Table A.25

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing .
v3,vr 0,371a .984 .618
Economic env --> 0 1531) .054 .221
Mkt/Ind structure ' 18.48 3.263
2.726
v3,v2 -.601 .034 -.340
Regulation ---> . 153 .054 .221
Mkt/Ind structure -4.412 .630 -1.792
v4,v1 .046 .612 -.032
Economic env --> .073 .479 .337
Innovation Invst .714 1.095 -.096
v4,vf -.186 -.359 -.105
Regulation ---> .084 .086 .282
Innovation Invst -2.507 -3.564 -.371
V4,V3 .816 .267 -.300
Mkt/Ind structure --> .081 .469 .308
Innovation Invst 10.20 .476 -.835
v5,v4 .163 338 .256
Innovation Invst---> . 168 .339 .222
Foreign Mkt invst .859 -.813 2.500
v6,v4 .914 .6fi -.——207
Innovation Invst----> .081 .157 .3 1 1
Global Innovation 10.966 4.61 3 -.665
v6,v5 -.091 -.405 .302—
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
_—‘7v ,v6 mo .846 -.008
Global Innovation---> .074 .165 .267
Global Sales 12.165 5.258 -.031
‘ Fitjndices
Chi-square, df 21.24,12 11.216,12 12.237,12
p—value 0.046 .5 1 .426
BBFI 1.000 1.000 0.992
BBNFI 1.000 1 .000 1.000
CFI 1.000 1.000 1.000

 

 

 

a = standardized coefficient, b = standard error, c =t-va1ue

v1=pop; v2=pricereg; v3=mktsize; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

Table A.26

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

‘ Paths Overall Industrialized Developing ,
v3,v1 0.155a .5_03 .317
Economic env --> 0 1711) .250 .244
Mkt/Ind structure ' 2.459 1.265
.880c
V3,V2 .376 .534 .1329
Regulation --> . 17 1 .250 .244
Mkt/Ind structure 2.137 2.609 .554
v4,vl .346 .876 -.073
Economic env --> .144 .106 .247
Innovation Invst 2.736 7.01 3 -.295
v4 , VT -.689 -.350 .060
Regulation ~--> . 1 53 . 109 .237
Innovation Invst -5.1 12 -2.746 .251
v4 , v3 .039 -.000 -.454
Mkt/Ind structure ---> .159 .103 .257
Innovation Invst .285 -.002 -1 .8 l 7
v 5 , v4 . 163 -.237 .556 1
Innovation Invst---> . 168 .340 .222
Foreign Mkt invst .859 -.810 2.500
VCV4 .914 .687 -.207
Innovation Invst---> .081 . 158 .3 1 1
Global Innovation 10.961 4.597 - .665
v6,v5 -.091 -.406 .302—
Foreign Mkt Invst--> .092 .136 :31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .920 .845 -.008
Global Innovation—«> .074 . 166 .267
Global Sales 12.161 5.247 -.031
Fit Indices
Chi-square, df 25.61,12 8.982,12 13.709,12
p-value 0.012 .704 .319
BBFI 1.000 1.000 0.990
BBNFI 1.000 1.000 0.998
CFI 1.000 1.000 0.999

 

 

a = standardized coefficient, b = standard error, e = t-value

v1=pop; v2=pricereg; v3=mktfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

185

Table A.27

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Develo in
v 3, v 1 0,095a .089 .250
Economic env --> 0 1911) .296 .256
Mkt/Ind structure ° .306 1.036
_501c
_ij ,v -.119 .231 -347—

Regulation ---> . 191 .296 .256

Mkt/Ind structure -.625 .793 - l .434
V4,V1 .360 .863 -.146
Economic env --> . 141 .079 .260
Innovation Invst 2.893 9.365 -.559
V4,?2 -.686 -.383 -.104
Regulation ---> .142 .080 .269
Innovation Invst -5.502 -4.054 -.388
V4,V3 -.088 .138 -.290
Mkt/Ind structure --> .141 .080 .262

Innovation Invst -.700 1.454 -1.043
v5,v4 .163 -.23’7 .556
Innovation Invst---> .168 .340 .222

Foreign Mkt invst .859 -.811 2.500
v6,v4 .914 .687 -.207
Innovation Invst--> .081 . 158 .3 1 1
Global Innovation 10.963 4.601 -.665
V6,V5 -.091 -.406 .302
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972

v 7 ,v6 .920 .845 -.008

Global Innovation--> .074 .166 .267
Global Sales 12. 163 5.249 -.03 1

Fit Indices
Chi-square, df 21.06,12 8.792,12 1333,12

p—valuc 0.049 .720 .345

BBFI 1.000 1.000 1.000

BBNFI 1.000 1.000 1.000

CFI 1.000 1.000 1.000

 

 

 

a = standardized coefficient, b = standard error, c = t-value

v1=pop; v2=pricereg; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

Table A.28

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing
v3 , v 1 0,029a -.304 .092
Economic env ----> 0 191b .273 .262
Mkt/Ind structure ' -1.227 .356
. 152°
——3_2v ,v .117 -.484 -.243
Regulation --«> . 191 . 273 .262
Mkt/Ind structure .612 -1.957 -.944
v4,v1 .356 .87? -.280
Economic env --> . 137 .091 .205
Innovation Invst 2.962 8.208 -1.366
v4,v2 -.655 -.349 .148
Regulation ---> . 138 .099 .2 10
Innovation Invst -5.408 -3.001 .703
v4,v3 -.174 .001 .628
Mkt/Ind structure ...> .138 .094 .208
Innovation Invst - 1.436 .01 1 2.970
‘ v5,v4 .163 -.238 .556
Innovation Invst---> .168 .340 .222
Foreign Mkt invst .859 -.811 2.500
v6,v4 .914 .682 -.207 ‘
Innovation Invst---> .081 . 158 .3 1 1
Global Innovation 10.967 4.604 -.665
V6,Vr -.091 -.406 .302
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
V ’,V6 .920 .846 -.008
Global Innovation----> .074 . 165 .267
Global Sales 12.167 5 .252 -.031
‘ Fit Indices
Chi-square, df 20.95, 12 10.551,12 14.020,12
p-value 0.05 .567 .299
BBFI 1.000 1.000 0.994
BBNFI 1.000 1.000 0.998
CFI 1.000 1.000 0.999

 

a = standardized coefficient, b = standard error, e = t-value

v1=pop; v2=pricereg; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

187

Table A.29
Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing
v3,vl 0.127a .983 .457
Economic env --> 0 189° .055 .235
Mkt/Ind structure ° 17.935 1.929
.676°
v3,v2 .158 .024 -.070
Regulation ---> . 189 .055 .235
Mkt/Ind structure .839 .434 -.297
v4,vl -.063 .888 -.141
Economic env --> .071 .609 .285
Innovation Invst -.896 1.468 -.500
v4,v2 -.029 -.041 -.118
Regulation ---> .071 . 1 12 .254
Innovation Invst -.411 -.366 -.467
v4,v3 .942 .043 -.232
Mkt/Ind structure --> .071 .612 .288
Innovation Invst 13.157 .071 -.816
‘__5v ,v4 .144 5277 .559
Innovation Invst---> . 190 .288 . 22 1
Foreign Mkt invst .757 -.957 2.519
V6,V4 .890 .728 -.208
Innovation Invst----> .092 .135 .3 10
Global Innovation 9.693 5.372 -.668
v6,v5 -.100 -.368 .303
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .904 .870 -.008
Global Innovation---> .082 .149 .267
Global Sales 1 1.012 5.849 -.031
Fit Indices
Chi-square, df 28.09.12 10.842,12 1 120,12
p—value 0.005 .542 .51 1
BBFI 1.000 1.000 0.991
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1=pop; v2=apptime; v3antsize; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

 

Table A.30

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing
‘ v3,v1 0,343a .138 .370
Economic env ---> 0. 1801’ .267 .245
Mkt/Ind structure 1_951c .512 1.497
v3,v2 .144 .423 -.099
Regulation ----> . 180 .267 .245
Mkt/Ind structure .806 1.568 -.399
V4,Vl .136 .949 -.074
Economic env ---> . 199 . 106 .249
Innovation Invst .686 9.023 -.300
v4,v2 .153 .012 -.148
Regulation -----> . 189 . 1 16 .233
Innovation Invst .809 .146 -.638
V4,V3— -.229 -.133 -.468
Mkt/Ind structure ---> .199 .118 .253
Innovation Invst -1. 140 -1.149 -1.880
v5,v4 .144 -.27'_7 .559
Innovation Invst ----- > . 190 .288 .22 1
Foreign Mkt invst .757 -.957 2.519
V6,V4 .890 .728 -.208
Innovation Invst---> .092 . 135 .3 10
Global Innovation 9.69 5.374 —.668
va5 -.100 -.368 .303
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .904 8W -.008
Global Innovation----> .082 .149 .267
Global Sales 11.012 5.850 -.031
Fit Indices
Chi-square, df 3582,12 8.947,12 12.63,12
p—value 0.001 .707 .396
BBFI 1.000 1.000 0.991
BBNFI 1.000 1.000 0.999
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1=pop; v2=apptime; v3=mktfocus; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

 

Table A.31

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industrialized Developing .
v3,v1 0.0463 -.115 .024
Economic env ---> 0 1921) .285 .267
Mkt/Ind structure ' -.406 .091
.238°
v3,v2 .045 .325 —.033
Regulation ---> .192 .285 .267
Mkt/Ind structure .234 1.148 -.122
v4,vl .058 .941 -.241
Economic env ---> . 19 1 . 109 .250
Innovation Invst .305 8.724 -.971
v4,vf .121 -.069 -.110
Regulation ---> .191 .1 14 .250
Innovation Invst .634 -.606 -.443
v4,v3 -.032 .090 -.252
Mkt/Ind structure --> .191 .114 .250
Innovation Invst -.168 .786 -1.015
v5,v4 .144 -. 77 .559
Innovation Invst-«~> . 190 . 288 . 22 1
Foreign Mkt invst .757 -.957 2.519
V6,V4 .890 .728 -.208
Innovation Invst-«-> .092 . 135 .3 10
Global Innovation 9.693 5.374 -.668
v6,v5 -.100 -.368 .303
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
v7,v6 .904 .870 -.008
Global Innovation-«9 .082 . 149 .267
Global Sales 11.012 5.850 -.031
Fit Indices
Chi-square, df 1752,12 9960,12 10.413,12
p-value 0.131 0.619 .579
BBFI 1.000 1.000 1.000
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1.000

 

a = standardized coefficient, b = standard error, c = t-value

v1=pop; v2=apptime; v3=mktgrwth; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

 

Table A.32

Global Innovation Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Overall Industriglized Developing .
v3,v1 0.095a -.017 -.021
Economic env ---> 0.191b .301 .264
Mkt/Ind structure . 498° -.057 -.078
1 v3,v2 .066 .064 .148
Regulation ---> . 191 . 301 .264
Mkt/Ind structure .347 .214 .561
V4,V1 .083 .932 -.235
Economic env -«> . 184 . 106 .200
Innovation Invst .450 8.839 -1 . 180
v4,v22 .138 -.046 —.193
Regulation ---> . 1 84 . 106 .203
Innovation Invst .750 -.437 -.960
V4,V3 -.275 .103 .618
Mkt/Ind structure ---> . 185 . 106 .203
Innovation Invst - 1 .491 .984 3 .072
v5,v4 .144 -.277 .559
Innovation Invst----> . 190 .288 .22 1
Foreign Mkt invst .757 -.957 2.519
V6,V4 .890 .728 -.208
Innovation Invst----> .092 . 135 .3 10
Global Innovation 9.693 5.373 -.668
V6,R -.100 -.368 .303
Foreign Mkt Invst--> .092 .136 .31 1
Global Innovation -1.089 -2.720 .972
_'—'7v ,v6 .904 .870 -.008
Global Innovation----> .082 .149 .267
Global Sales 1 1.012 5.849 -.031
Fit Indices
Chi-square, df 16.12,12 10.455,12 12.44,12
p-value 0.18 .576 .410
BBFI 1.000 1.000 0.997
BBNFI 1.000 1.000 1.000
CFI 1.000 1.000 1 .000

 

a = standardized coefficient, b = standard error, c = t-value

v1=pop; v2=apptime; v3=mktconc; v4=r&dexpd; v5=frgcomm; v6=innovat; v7=gblsales

 

APPENDIX B

191

APPENDIX B
Table B.l Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
v3,vl
Economic env ----- m>MktIIndustry structure -.167, .287, -.572
v3,v2
Regulation -------- >Mkt/Industry structure .192, .287, .658
v4,v1
Economic Env ----- >Market Potential .503, .187, 2.472
v4,v2
Regulation-------->Market Potential -.493, .188, -2.410
v4,v3
Mkt/Industry structure- ------ >Market Potential .484, .194, 2.336
v5,v4
Market Potential ------- >Incoming foreign invst .582, .259, 2.374
v6,v4
Market Potential-~---->Global Diffusion -.1 15, .136, -1.003
v6,v5
Incoming foreign invst-------—>Global Diffusion .035, .129, .306
v6,v7
Global Innovation-«~«->Global Diffusion .946, .102, 10.179
Fit Indices
Chi-square, df 8.393.12
p—value .753
BBFI .990
BBNFI 1.000
CFI 1.000

 

 

v1= gnp, v2= pricereg, v3= indfocus, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

192

Table B.2
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
v3,vl
Economic env-«~—->Mkt/Industry structure -.082, .296, -.275
v3,v2
Regulation---—->Mktl1ndustry structure .138, .296, .464
v4,vl
Economic Env—-—-->Market Potential .426, .226, 1.734
v4,v2
Regulation >Market Potential -.406, .227, -1.643
v4,v3
Mkt/Industry structure >Market Potential .046, .229, .186
v5,v4
Market Potentia1-—--->Incoming foreign invst .582, .259, 2.374
v6,v4
Market Potential—~-—->Global Diffusion -.1 12, .136, -.976
v6,v5
Incoming foreign invst-m—->Global Diffusion .035, .129, .304
v6,v7
Global Innovation--o--->Global Diffusion .946, .102, 10.143
Fit Indices
Chi-square, df 8.587,12
p—value .737
BBFI .999
BBNFI 1.000
CFI 1.000

 

 

v1= gnp, v2= pricereg, v3= indgrwth, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

193

Table B.3
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths . Coefficients, Standard error, t-value
v3,vl
Economic env---—-->Mkt/Industry structure -,O67, .284, .234
v3,v2
Regulation >Mkt/Industry structure -.301, .284, -1.048
v4,vl
Economic Env------>Market Potential .434, .221, 1.807
v4,v2
Regulation--—-->Market Potential -.454, .231, -1.805
v4,v3
Mkt/Industry structure ->Market Potential -. 180, .234, -.713
v5,v4
Market Potential-«-»->Incoming foreign invst .582, .259, 2.374
v6,v4
Market Potential----->Globa1 Diffusion -.104, .137, -.905
v6,v5
Incoming foreign invst--—--->Global Diffusion .034, .129, .297
v6,v7
Global Innovation------>Global Diffusion .946, .102, 10.088
Fit Indices
Chi-square, df 9,636,12
p-value .647
BBFI 1.000
BBNFI 1.000
CFI 1.000

 

 

v1= gnp, v2= pricereg, v3= indconc, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

194

Table B.4
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
v3,vl
Economic env >Mkt/Industry structure -.332, .252, -1.306
v3 ,v2 .
Regulation >Mkt/Industry structure .476, .252, 1.928
v4,vl
Economic Env ->Market Potential .721, .231, 3.092
v4,v2
Regulation—«m->Market Potential -.081, .249, -.321
v4,v3
Mkt/Industry structure---«->Market Potential .442, .257, 1.668
v5,v4
Market Potential----—>Incoming foreign invst .61 1, .240, 2.561
v6,v4
Market Potential-—---->Globa1 Diffusion -.1 12, . 130, -.949
v6,v5
Incoming foreign invst-—--->Global Diffusion .035, .129, .297
v6,v7
Global Innovation--««-->Global Diffusion .946, .102, 10.090
Fit Indices
Chi-square, df 6.426, 12
p-value .893
BBFI .990
BBNFI 1.000
CFI 1.000

 

 

v1= gnp, v2= apptime, v3= indfocus, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

195

Table B.5
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
v3,vl
Economic env- >Mkt/Industry structure -.197, .281, -.706
v3,v2
Regulation >Mkt/Industry structure .329, .281, 1.180
v4,v1
Economic Env ->Market Potential .570, .246, 2.299
v4,v2
Regulation-~—-->Market Potential .144, .255, .558
v4,v3
Mkt/Industry structure---->Market Potential -.042, .258, -.161
v5,v4
Market Potentia1-—--->Incoming foreign invst .61 l, .240, 2.561
v6,v4
Market Potential ->Global Diffusion -. 1 39, . 130, - 1 .216
v6,v5
Incoming foreign invst---->Globa1 Diffusion .037, .129, .323
v6,v7
Global Innovation- ->Globa1 Diffusion .946, .102, 10.441
Fit Indices
Chi-square, df 7.848,12
p—value .796
BBFI .990
BBNFI 1.000
CFI 1.000

 

 

v1= gnp, v2= apptime, v3= indgrwth, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

196

Table B.6

Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
Economic envu-uzi’lt‘ilit/Indusuy structure .225, .293, .768
Regulation :iril‘d/zlndusn'y structure .033, .293, .1 13
Economic Env—ZillMarket Potential .597, .246, 2.405
Regutauon—u-V-iéiiarkct Potential .132, .240, .548
Mkt/Industry suucmieili>Market Potential -.081, .246, -.325
Market Potentialm-Y-S-gntoming foreign invst .61 1, .240, 2.561
Market Potenfial-fiiGlobal Diffusion -.147, .130, -1.298
Incoming foreign inJSiS-ii—filobal Diffusion .038, .129, .331
V 6 , V 7

Global Innovation-—-->Global Diffusion

.946, .102, 10.551

 

 

Fit Indices
Chi-square, df
p—value
BBFI
BBNFI
CFI

 

8265,12
.764
1.000
1.000
1.000

 

v1= gnp, v2= apptime, v3= indconc, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

197

Table B.7
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
v3,vl
Economic env >Mkt/Industry structure .502, .250, 2.455
v3,v2
Regulation >Mkt/Industry structure .536, .250, 2.618
v4,vl
Economic Env----->Market Potential 1.002, .067, 15.281
v4,v2
Regulation-~-->Market Potential .054, .069, .81 1
v4,v3
Mkt/Industry structure--—->Market Potential -.036, .065, -.461
v5,v4
Market Potential----->Incoming foreign invst .623, .233, 2.641
V6,V4
Market Potential---—->Global Diffusion —.134, .127, - l . 147
v6,v5
Incoming foreign invst----->Global Diffusion .037, .129, .314
v6,v7
Global Innovation—--—-->Global Diffusion .946, .102, 10.322
Fit Indices
Chi-square, df 9.387, 12
p-value .669
BBFI 1.000
BBNFI 1.000
CFI 1.000

 

 

v1= pop, v2= pricereg, v3= infocus, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

198

Table B.8
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
v3,vl
Economic env >Mkt/Industry structure -.087, .296, .297
v3,v2
Regulation---->Mkt/Indust1y suucmre .233, .296, .797
v4,vl
Economic Emma-«>Market Potential .987, .053, 18.880
v4,v2
Regulation---—->Market Potential .044, .055, .821
v4,v3
Mkt/Industry structure»-—-->Market Potential -.037, .054, -.695
v5,v4
Market Potential----->Incoming foreign invst .623, .233, 2.641
V6,V4
Market Potential >Global Diffusion -.131, .127, -1.1 19
v6,v5
Incoming foreign invst—--->Global Diffusion .037, .129, .311
‘ v6,v7
Global Innovation--~—>Global Diffusion .946, .102, 10.285
Fit Indices
Chi-square, df 8.13 1,12
p-value .774
BBFI 1.000
BBNFI 1.000
CFI 1.000

 

 

vl= pop, v2= pricereg, v3= indgrwth, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

199

Table 13.9
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coeffiiients, Standard error, t-filue
v3,vl
Economic env >Mkt/Industry structure -.304, .273, -l.233
v3,v2
Regulation >Mkt/Industry structure -.488, .273, -l.979
v4,vl
Economic Env----.>Market Potential 1.016, .050, 20.656
v4,v2
Regulation---->Market Potential .088, .055, 1.633
v4,v3
Mkt/Industry structure~-—>Market Potential .107, .052, 1.906
v5,v4
Market Potential--—--->Incoming foreign invst .623, .233, 2.641
V6,V4
Market Potential———-->Global Diffusion -. 134, .127, -l.146
v6,v5
Incoming foreign invst----—>Global Diffusion .037, .129, .314
v6,v7
Global Innovation—---—->Globa1 Diffusion .946, .102, 10.326
Fit Tndices
Chi-square, df 9724,12
p-value .6401
BBFI 1.000
BBNFI 1.000
CFI 1.000

 

 

v1= pop, v2= pricereg, v3= indconc, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

200

Table B.10
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

fiths Coefficients, Standard error, t-value
Economic envum:3>1\‘111vlndusuy structure .138, .267, .511
Regulation :mdmny structure .423, .267, 1.569
Economic Env—V4’Y>1Market Potential .986, .055, 17.856
Regulanonmzéiiaikei Potential .032, .060, .532
Mkt/Industry snucm‘iiifmmmei Potential -.020, .061, -.321
Market remnaniinionnng foreign invst .613, .239, 2.574
Market Poientiailflgciobai Diffusion -.148, .129, -1.305
Incoming foreign invvsgii-ociobai Diffusion .038, .129, .331
v6,v7

Global Innovationu- ----- >Global Diffusion

.946, .102, 10.547

 

 

Fit Indices
Chi-square, df
p-value
BBFI
BBNFI
CFI

 

6.223.12
.904
1.000

1.000

1.000

 

vl= pop, v2= apptime, v3= indfocus, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

201

Table B.11
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coaficients, Smlfiard error, t-value
Economic env V3>1t‘rilh/Industty structure -.115, .285, -.406
Regulation :mt/zlndmw structure .325, .285, 1.148
Economic Env—flgMarket Potential .978, .054, 18.176
Regulation—«ggdzarket Potential .038, .056, .672
Mkt/Industry sn'ucmvrg’vs >Market Potential -.044, .056, -.765
Market Pomnun-uugéirionung foreign invst .613, .239, 2.574
Market Potential V6’V:Global Diffusion -.149, .129, -1.297
Incoming foreign in:s:::-5-—>Global Diffusion .038, .129, .330
v6,v7

Global Innovation---->Global Diffusion

.945, .102, 10.405

 

 

F-it Indices
Chi-square, df
p-value
BBFI
BBNFI
CFI

 

6.753,12
.873
1.000
1.000
1.000

 

v1= pop, v2= apptime, v3= indgrwth, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

202

Table B.12
Global Diffusion Model

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Paths Coefficients, Standard error, t-value
v3,vl
Economic env----->Mkt/Industry structure -.017, .301, -.057
v3,v2
Regulation-«~«->Mkt/Industry structure .065, .301, .215
v4,v1
Economic Env---«->Market Potential .984, .051, 19.360
v4,v2
Regulation- >Market Potential .019, .051, .381
v4,v3
Mkt/Industry structure—--->Market Potential .068, .051, 1.339
v5,v4
Market Potential ----- ->Incoming foreign invst .613, .239, 2.574
V6,V4
Market Potential ----- >Global Diffusion -. 1 5 3, .129, -1.341
v6,v5
Incoming foreign invst ----- >Global Diffusion .038, .129, .335
v6,v7
Global Innovation-—---->Global Diffusion .945, .102, 10.460
Fit Indices
Chi-square, df 7.107.12
p-value .8504
BBFI 1.000
BBNFI 1.000
CFI 1.000

 

 

v1= pop, v2= apptime, v3= indconc, v4=mktpot, v5=infrgn, v6=diff, v7=innovat

 

HICHIG

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