Internationalization and Firm Performance

Mario Krist

Internationalization and Firm Performance The Role of Intangible Resources

With a foreword by Prof. Dr. Andreas Bausch

GABLER EDITION WISSENSCHAFT

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Dissertation Jacobs University Bremen, 2008

1st Edition 2009 All rights reserved © Gabler | GWV Fachverlage GmbH, Wiesbaden 2009 Editorial Office: Claudia Jeske / Anita Wilke Gabler is part of the specialist publishing group Springer Science+Business Media. www.gabler.de No part of this publication may be reproduced, stored in a retrieval system or transmitted, in any form or by any means, electronic, mechanical, photocopying, recording, or otherwise, without the prior written permission of the copyright holder. Registered and/or industrial names, trade names, trade descriptions etc. cited in this publication are part of the law for trade-mark protection and may not be used free in any form or by any means even if this is not specifically marked. Cover design: Regine Zimmer, Dipl.-Designerin, Frankfurt/Main Printed on acid-free paper Printed in Germany ISBN 978-3-8349-1550-4

To my parents Erhard and Anna

Foreword A large body of strategy and international business literature has examined the relationship between internationalization (regional diversification) and firm performance over the last decades. In essence, the current state of research on the internationalization-performance relationship must be characterized, however, as being heterogeneous and inconclusive. From a conceptual point of view, increasing levels of internationalization should have positive effects on firm performance due to economies of scale, market power effects, and risk reduction effects, to name but a few. At the same time, firms that expand internationally have to cope with substantial negative effects which are primarily associated with liabilities of foreignness. As a consequence, extensive empirical studies on the internationalization-performance relationship are somewhat mixed and contradictory. Against this background, Mario Krist highlights three central research objectives: First, he establishes if and why there should be a relationship between internationalization and firm performance. Second, he elaborates which intangible resources act as major success factors in the relationship between internationalization and performance and why this occurs. Third, he explores how these intangible resources act within the internationalization process concerning their ultimate impact on firm performance and how characteristics of the internationalization process itself have an impact on the focal relationship. Mario Krist chooses a topic which is of high practical relevance since internationalization is at the core of corporate and business strategy. His research objectives are well developed based on a sound description of the current research status. The empirical approaches chosen by the author reflect a suitable research design in order to answer the research questions at hand. The combination of meta-analysis and primary empirical research indicates the wide range of the author‘s methodological knowledge. Overall, with this thesis Mario Krist significantly contributes to a comprehensive understanding of the drivers that influence the success of internationalization. All empirical studies are based on sound theoretical analyses and argumentations. Furthermore, the conclusions the author draws add noticeably to the existing body of knowledge in the research field of corporate strategy and international business. Thereby, the study does not only inform a broad readership about a central topic, but also offers the expert new insights. The results may thus have important implications for future research and theory building. Prof. Dr. Andreas Bausch

Acknowledgements Man entdeckt keine neuen Weltteile, ohne den Mut zu haben, alle Küsten aus den Augen zu verlieren. André Gide (1869 - 1951)

First, I would like to thank my supervisor Prof. Dr. Andreas Bausch for the great inspiration and support he has given me. Not only has he provided valuable suggestions and ideas in various stages of this research but his trust and personal promotion reach far beyond this thesis. Many thanks also go to Prof. Dr. Welf Werner from Jacobs University and Prof. Dr. Joerg Freiling from the University of Bremen who agreed to co-supervise the thesis. Furthermore, I am grateful to Prof. Dr. Michael Frese from the University of Giessen for giving me the opportunity to work at his department in an interdisciplinary team and for sharing his passion of research. I also wish to thank my fellow colleagues from Jacobs University and the University of Giessen for many discussions on the topic. They provided valuable comments and shared their views in interesting talks. This research would not have been possible without the financial support by the Cusanuswerk. Thank you for funding my research and international conference participations but even more so for meeting wonderful people during that time. I am also especially grateful to Alexandre Segão Costa and Ulrich Koehler for proofreading parts of this thesis. Furthermore, I owe a lot to all of my friends. Especially the ‘law connection’ in Giessen has pushed me towards the completion of this thesis and often supported me emotionally with a late-night talk. Most of all, I want to thank my family, especially my mother and my father for their support and their belief in me throughout the years. Without their love, nothing would be as it is. This thesis is dedicated to them. Finally, internationalization has unclosed to me the kind of relationship it has with performance after a long time. At the same time, however, I found another relationship, one that is precious in itself. Frauke, I am thankful for proving that Martin Buber is right as he notes: „Der Erfolg ist keine Vokabel in der Sprache der Liebe“. Mario Krist

Summary of Contents

Chapter 1 Introduction

1

Chapter 2 The Effect of Context-Related Moderators on the Internationalization-Performance Relationship: Evidence from Meta-Analysis

23

Chapter 3 Intangible Resources and their Effect on the Internationalization-Performance Relationship

71

Chapter 4 Intangible Resources and the Internationalization Process: Path Dependence of Building a Profitable Multinational Company

131

Chapter 5 Conclusion

171

Appendix

183

Table of Contents

Chapter 1 Introduction 1.1 Internationalization and Firm Performance 1.2 Definition of Key Terms 1.3 Scientific Approach 1.4 Course of Work 1.5 Universality or Context Dependence 1.6 Curve Type and the Role of Intangible Resources 1.7 Intangible Resources – the Internationalization Process – and Performance Endnote References

Chapter 2 The Effect of Context-Related Moderators on the Internationalization-Performance Relationship: Evidence from Meta-Analysis

1 1 3 6 7 8 10 13 17 18

23

2.1 Introduction 2.2 Theoretical Background and Hypotheses 2.2.1 R&D Intensity 2.2.2 Product Diversification 2.2.3 Country of Origin 2.2.4 Age 2.2.5 Size

23 25 28 29 31 33 34

2.3 Method 2.3.1 Sample 2.3.2 Variable Coding 2.3.3 Analytical Approach 2.3.4 Consideration of Methodological Differences

35 35 38 41 43

2.4 Results 2.5 Discussion 2.6 Limitations

46 49 52

XIV

Table of Contents

2.7 Implications for Future Research 2.7.1 Key Moderator Variables 2.7.2 Understanding Contextual Interdependencies 2.7.3 Non-Linearity

53 53 54 55

2.8 Conclusions Endnote References

56 59 60

Chapter 3 Intangible Resources and their Effect on the Internationalization-Performance Relationship

71

3.1 Introduction 3.2 An Inquiry into a Non-Linear Internationalization-Performance Relationship 3.2.1 Previous Inquiries into a Non-Linear Relationship 3.2.2 Benefits of Internationalization 3.2.3 Costs of Internationalization 3.2.4 Synthesis and Hypothesis

71 72 72 74 76 77

3.3 The Moderating Impact of Intangible Resources 3.3.1 Theoretical Background 3.3.2 A Hedonic Approach to the Concept of Intangible Resources 3.3.3 The Multidimensional Nature of Intangible Resources 3.3.3.1 Technological Know-How 3.3.3.2 Market Know-How 3.3.3.3 Contract-Based Know-How 3.3.3.4 Top Management Team Demographics

81 81 84 85 88 89 90 91

3.4 Method 3.4.1 Sample 3.4.2 Variable Coding 3.4.3 Sources of Data and Process of Data Collection 3.4.4 Analytical Approach

92 92 94 98 102

3.5 Results 3.6 Discussion 3.7 Limitations

104 109 115

Table of Contents

3.8 Implications for Future Research 3.9 Conclusions Endnotes References

XV

116 117 120 122

Chapter 4 Intangible Resources and the Internationalization Process: Path Dependence of Building a Profitable Multinational Company 131 4.1 Introduction 4.2 Theoretical Background and Hypotheses 4.2.1 How Intangible Resources Shape the Internationalization Process 4.2.2 How Differences in Internationalization Paths Affect Performance

131 134 134 139

4.3 Method 4.3.1 Sample 4.3.2 Variable Coding 4.3.3 Analytical Approach

142 142 144 148

4.4 Results 4.5 Discussion 4.6 Limitations 4.7 Implications for Future Research 4.8 Conclusions Endnotes References

149 157 161 162 164 166 167

Chapter 5 Conclusion 5.1 Summary of Results 5.2 Implications and Recommendations for Future Research References

Appendix

171 172 176 181

183

List of Tables

Table 2.1 Table 2.2 Table 2.3 Table 2.4 Table 2.5 Table 2.6 Table 2.7 Table 2.8 Table 3.1 Table 3.2 Table 3.3 Table 3.4 Table 3.5 Table 3.6 Table 3.7 Table 3.8 Table 4.1 Table 4.2 Table 4.3 Table 4.4 Table 4.5 Table 4.6 Table 4.7 Table 4.8

Table 5.1

Summary of Primary Studies Sample Source over Time Degree of Internationalization over Time – across Countries – and by Firm Size Operationalization of Internationalization and Performance Analysis of Bias in Sub-Samples for Moderator Analysis Methodological Moderators – Internationalization and Performance Results of Meta-Analysis on Internationalization and Performance Shape of the Internationalization-Performance Relationship Selected Empirical Studies on the Relationship between Internationalization and Firm Performance Theoretical Perspectives and Performance Drivers of Internationalization Theoretical Perspectives and Cost Drivers of Internationalization Descriptive Statistics and Correlations (N = 789) Coefficients from Hedonic Regression Regression of Curve Type and Moderation of Tobin’s q Moderation of Hedonic q Moderation of Individual Intangible Resources Regional Dispersion of International Sales Descriptive Statistics and Correlations (N = 563) Regression of Intangible Resources on Degree of Internationalization Regression of Intangible Resources on Propensity to Internationalize Regression of Intangible Resources on Scope of Internationalization Regression of Intangible Resources on Scope of Expansion Moderation of Speed of Expansion Moderation of Scope of Expansion on Change of ROA over Two Years Summary of Hypotheses Pertaining to the Role of Intangible Resources

37 38 39 39 43 45 47 56

74 76 78 99 103 105 107 108 143 147 150 151 153 154 156 157

173

List of Figures

Figure 1.1 Theoretical Model for the Investigation of Context Related Moderators 9 Figure 1.2 Theoretical Model for Moderator Analysis of Intangible Resources 13 Figure 1.3 Theoretical Model of Intangible Resources – the Internationalization Process – and the Internationalization-Performance Relationship 16 Figure 2.1 Criteria for Moderator Variables of the Meta-Analysis Figure 2.2 Stem-and-Leaf Plot of Correlations (r) between Internationalization and Performance Figure 2.3 Key Findings from Meta-Analysis on Internationalization and Performance

28

Figure 3.1 Sigmoid Internationalization-Performance Relationship Figure 3.2 Categorization of Intangibles by the FASB and the Working Group ‘Intangible Assets in Accounting’ of the Schmalenbach Society Figure 3.3 Results for Moderator Analysis of Intangible Resources

80 86 118

Figure 4.1 Research Framework with Intangible Resources and Internationalization Process Characteristics

133

Figure 5.1 Mobility of Intangible Resources in the Context of Internationalization

176

48 58

Chapter 1 Introduction

1.1 Internationalization and Firm Performance The relationship between internationalization activities and firm performance has been the subject of extensive discussion in the strategy and international business literature over the course of the last thirty years. Unfortunately, with close to a hundred studies, little consensus has emerged among researchers as to the nature of the relationship between internationalization and firm performance. Studies in the 1970s emphasized the benefits of internationalization and thus hypothesized a linear positive relationship between the degree of internationalization and firm performance; however researchers in the 1980s and 1990s acknowledged that internationalization can be subject to risk and failure, thus recognizing possible drawbacks to success in internationalization. As a result of these divergent findings, researchers, in a search for an optimal degree of internationalization, have more recently begun to examine the benefit-cost trade-off of internationalization and its variations along the internationalization continuum. These researchers have tried to resolve empirical findings of either a significant positive linear effect (Vernon, 1971; Buhner, 1987) or significant negative linear effect (Brewer, 1981; Ramaswamy, 1992) by remodeling the shape of this relationship. Yet to date, researchers disagree on the exact shape of the curve. Significant results vary from u-shaped curves (Lu and Beamish, 2001; Capar and Kotabe, 2003) to inverted u-shaped curves (Hitt, Hoskisson, and Kim, 1997; Gomes and Ramaswamy, 1999) and cubic curves (Contractor,

2

Introduction

Kundu, and Hsu, 2003; Lu and Beamish, 2004). Empirical findings are even more diverse. The assertion of non-linearity is challenged by empirical studies that tested for but could not confirm a curvilinear relationship (Tallman and Li, 1996; Hsu and Boggs, 2003; Wan and Hoskisson, 2003). The heterogeneity of empirical results on different types of curves, effect sizes, and even overall direction lead to differing views and conclusions in contemporary research. While prior research set out to establish a single universal relationship between internationalization and firm performance, a discussion emerges among international business researchers as to whether such a relationship really exists or whether there are simply several context dependent relationships reflecting the conditions when and how internationalization and firm performance relate. The current state of research on the internationalization-performance relationship is often described as “inconsistent” (Harveston, Kedia, and Francis, 1999, p. 295), “mixed” (Gomez-Mejia and Palich, 1997, p. 310; Doukas and Lang, 2003, p. 154; Hsu and Boggs, 2003, p. 23), “decidedly mixed” (Hitt et al., 1997; Qian, 2002, p. 618), “contradictory” (Geringer, Tallman, and Olsen, 2000, p. 51), “inconsistent and contradictory” (Ruigrok and Wagner, 2003, p. 65), “inconclusive and contradictory” (Tallman and Li, 1996, p. 180), and “conflicting” (Annavarjula and Beldona, 2000, p. 48). The extant literature gives different explanations for this confusion. One recurrent explanation is based on theoretical shortcomings (Gomes and Ramaswamy, 1999) and differences in research methodology. Sullivan (1994), in his attempt to improve the content validity of measuring the degree of internationalization of a company, infers that measurement error seriously distorts estimates of effect sizes and precludes distinguishing trait variance from unwanted method variance. He therefore concludes that “theory testing remains ambiguous precisely because we cannot ascertain whether the acceptance or rejection of a hypothesis is the result of excessive error in measurement or the adequacy or inadequacy of prevailing theories of the internationalization of the firm” (Sullivan, 1994, p. 338). The work by Grant (1987) has stimulated another line of research. He classifies research on the performance consequences of internationalization into comparative studies that investigate whether or not multinational companies outperform their domestic rivals (e.g. Vernon, 1971; Brewer, 1981; Fatemi, 1984) and into research that uses control variables such as research and development, firm size, and industry to

Definition of Key Terms

3

examine the relationship between internationalization and performance (e.g. Kumar, 1984; Morck and Yeung, 1991; Tallman and Li, 1996). He concludes that contradictory findings on the direction and magnitude of the internationalization-performance relationship are mainly due to moderator variables considered by some researchers but not others. This piece of research incorporates the remarks of Grant as it seeks to make a contribution to the academic debate on the nature of the relationship between internationalization and performance with particular consideration of the role of different intangible resources. It addresses three successive research questions. First, it tries to establish if and why there should be a relationship between internationalization and firm performance. Building upon the seminal work by Morck and Yeung (1991) the second question focuses on the role of intangible resources. Specifically I distinguish between different facets of intangible resources in order to explore which intangible resources act as major success factors in the relationship between internationalization and performance and why they do so. This approach distinguishes between dimensions of intangible resources and elaborates on the specific mechanisms for why a specific resource should act as moderator of the focal relationship. Therefore it is more in line with the original work of the resource based view of the firm (Wernerfelt, 1984; Barney, 1991; Peteraf, 1993) as it considers the heterogeneous character of firm resources (Barney, 1991). The third question concerns how these intangible resources act in the internationalization process to ultimately impact firm performance and how characteristics of the internationalization process itself (i.e. the way how a firm arrives at its present state of internationalization) has an impact on the relationship between internationalization and performance.

1.2 Definition of Key Terms In order to guarantee a common understanding about the object of research and constructs under investigation it is mandatory to clarify key terms. Hence I would like to introduce three definitions of what constitutes (1) a multinational firm, (2) the underlying comprehension of performance as outcome variable and (3) intangible resources.

4

Introduction

Multinational Firms In the literature there are many different approaches to a definition of multinational companies. One of the first definitions of internationalization can be derived from Lilienthal, who defines multinational firms as “corporations which have their home in one country but which operate and live under the laws and customs of other countries as well” (Lilienthal, 1975, p. 119). The essence of this definition is ‘operation’ in more than one country. I will adopt this rather broad definition throughout this work by defining multinational firms as firms which undertake value creating activities in more than one country. In order to distinguish this definition from others I would like to discuss alternative definitions that have been suggested in the literature as well. For example Dunning defines multinational companies as follows: “Firms, which own and control income-generating assets in more than one country can be defined as Multinational Companies (MNCs)” (Dunning, 1974, p. 13). This definition restricts the status of multinationality to those companies that follow a certain form of international involvement, namely the physical presence in a foreign country. But Dunning does not mention whether this involvement is defined in the form of a sales subsidiary or production facility for example. Other researchers again narrow this definition in that they restrict multinational companies to those firms that engage in foreign production, such as Glaum: “Eine Unternehmung gilt als international, wenn sie in mehreren Staaten als Produzent tätig ist (A company is regarded international if it acts as producer in several countries)” (Glaum, 1996, p. 10) or Rugman, Lecraw, and Booth: “The essence of multinationality is foreign production” (Rugman, Lecraw, and Booth, 1985, p. 7). What these definitions do have in common is that they – more or less – implicitly restrict the scope of international activities. However, it is a commonly accepted research methodology that definitions differ. In this sense I agree with the notion of Buckley who writes that “definitions are not right or wrong, just more or less useful” (Buckley, 1981, p. 71) in that these narrow definitions are not wrong, but that they confine the scientific object of internationalization. For the purpose of the present peace of research they might consequently not be appropriate to capture the diversity of internationalization and allow a comprehensive examination of the phenomenon of internationalization and firm performance.

Definition of Key Terms

5

The definition of ‘value creating activities in more than one county’ seems to be more suitable for two reasons: First, ‘value creating activities’ instead of pure production broadens the scope for possible motivations for internationalization. Second, this definition encompasses all forms of international market entry (with the exception of indirect exports) and therefore offers the potential for conclusions that can be generalized across different structural configurations of doing business abroad. Firm Performance My definition of performance as the outcome variable is firm financial performance. The idea is that the net impact from ‘value creating activities in more than one country’, i.e. internationalization, should finally be reflected in the financial position and profitability of the firm. Metrics of financial performance are generally accepted as suitable proxies to measure the degree of satisfaction of a variety of stakeholders of the firm because they reflect their financial interests in the firm, such as income payments to employees, tax payments to official authorities, or interest and dividend payments to investors. Only sufficient funds to satisfy the claims of the diverse stakeholders of the firm guarantee their interest in the firm in the long run. Hence, internationalization is evaluated with respect to its contribution to the ultimate goal of a firm, which can be defined as the conservation and successful development of the firm (Hahn and Hungenberg, 2001). Profitability ratios of a company are typically able to indicate the degree of investors’ satisfaction after the claims of other stakeholders have been satisfied. I only consider the impact of internationalization on overall firm profitability and not on profitability of foreign units or activities. Overall firm profitability seems to be an appropriate level of measurement, since internationalization typically represents a strategic action that can have a fundamental impact on the corporate development. A restriction to the success or profitability of foreign activities would fall short of the possibility that ongoing activities abroad can have an impact on national businesses as well, the so called internationalization imprint (Sapienza, Autio, and Zahra, 2003) or that transfer price arrangements can allocate profits away from their point of origin. Intangible Resources As in other fields of research, a variety of competing terminologies exists. Despite researchers’ high interest in the topic of intangible resources, no consensus on one set of terms is obvious. Terms used include, but are not limited to, the following: Intangible resources, intangibles, intangible assets, intellectual capital, and intellectual

6

Introduction

property (Lev, 2001). There is not only a variety of terms but also a wide spectrum of definitions for intangible resources in the literature. In some cases the definitions remain abstract and offer little guidance for practitioners or researchers. In their literature review of different terms and definitions of intangible resources Kaufmann and Schneider (2004, p. 374) comment that “Most authors’ definitions – regardless of the term used – include knowledge in some way and refer to some form of economic value that is attached to intangible assets”. In a similar vein some authors point to the profit generating potential of intangible resources. Sullivan (2000, p. 228) calls intangible resources “knowledge that can be converted into profit” and Lev (2001, p. 5) posits that “an intangible asset is a claim to future benefits that does not have a physical or financial embodiment”. This definition describes the term intangible resources quite well as it reveals their specific character. In this work I will follow Lev’s definition of intangible resources as entitlements to future benefits without physical substance as the two constitutive elements.

1.3 Scientific Approach While production of new knowledge and theoretical advancement are the ultimate goals of scientific endeavors they are as well the most difficult ones to accomplish. This piece of research seeks to make a contribution not only to empirical evidence on the internationalization-performance relationship but also to an advancement of internationalization theory. The basic methodological approach to achieve these goals is explanatory-affirmative. In a first step I derive hypotheses based on theoretical reasoning. In a second step I test whether empirical data affirms these propositions or whether it does not. Accordingly, the relevant criterion for an assessment of the scientific contributions obtained from this piece of research is whether empirical evidence is able to reject the hypotheses proposed throughout the chapters. Two basic scientific principles serve as guiding paradigms in the following chapters: Rigor and relevance. “Only work that is rigorous both theoretically and methodologically and centered on issues of focal concern to a wide community of stakeholders (e.g. managers, government policy makers, trades unionists, and consumer groups) will truly bridge the relevance gap, thereby meeting the ‘double hurdles for management research’” (Hodgkinson, Herriot, and Anderson, 2001, p. 46) with reference to (Pettigrew, 1997). Rigor mainly applies to methodological considerations and demands the compliance with publication standards of leading international

Course of Work

7

journals. Relevance is the main principle for the recognition of phenomena surrounding the internationalization-performance relationship. If results shall be relevant for a wide community of stakeholders and decision makers then controllable variables are of primary concern. In this way scientific insights can be successfully converted into practically relevant and actionable information. This would be an important step to bridge the gap between scientists and practitioners towards an establishment of the concept of evidence-based management (Rousseau, 2007) in the domain of international business research.

1.4 Course of Work Although the chapters of this book can be read independently of each other it is also in their interplay and integration that they help to advance theory on the internationalization-performance relationship. The subsequent chapters are structured as follows: Chapter two analyzes prior empirical research on the internationalizationperformance relationship based on the method of meta-analysis. Given the diversity of empirical findings so far this chapter seeks to explore the reasons for these conflicting results. It investigates whether it is possible to model a systematic but context dependent relationship instead of a uniform relationship. Chapter three discusses in more detail the role of intangible resources. The first part of this chapter represents an investigation into which curve type best reflects the internationalization-performance relationship for a sample of German firms. In the second part I explore the moderating role of five different dimensions of intangible resources and introduce a novel concept of measuring the joint value of the different facets of intangible resources – the so called hedonic approach. Chapter four encompasses research on how intangible resources shape the internationalization process. The first part is an examination of the effect of intangible resources on the decision to internationalize while the second part examines if and how the internationalization process itself exerts an influence on the internationalization-performance relationship. Chapter five draws conclusions from the preceding chapters and outlines the implications for future research. For a better readability each chapter contains a separate list of references. However, before starting with the analysis of the main research topic I need to clarify further key areas of investigation which I will do in the remaining sections of chapter one.

8

Introduction

1.5 Universality or Context Dependence The question of whether there is a systematic relationship between the internationalization of firms and their performance is central to the field of international business. Despite the extensive amount of research that has been conducted on the internationalization-performance relationship a fundamental question remains: How universal is the internationalization-performance effect? For more than three decades researchers in the domain of international business try to assess whether there exists one universally valid relationship or whether this relationship is fundamentally context dependent, i.e. the direction and the magnitude of the relationship are depending on other variables. Given the number of empirical studies addressing the subject of internationalization and firm performance and given the diversity of the results to date, the need for a comprehensive analysis of past research is crucial for the advancement of research. What is missing to date is a systematic review and consolidation of research based on quantitative methods. Given the shortcomings of vote counting methods (Hunter and Schmidt, 1990), meta-analysis is a logical next step. Metaanalysis has its roots in the discipline of medicine. It offers unique possibilities for detecting the true relationship of variables and analyzing reasons for conflicting findings that are not available in any other study (Dalton et al., 1999). Meta-analysis integrates and statistically analyses prior research findings in an attempt to evaluate whether inconsistencies and contradictory findings in prior research are due to research artifacts (such as sampling error, or error of measurement) one cannot avoid in single studies or whether the differences in effect sizes are of substantial nature, i.e. due to moderator variables. Given the number of single studies in the area of internationalization and performance to date, meta-analytical procedures are more likely to offer further insight than would another single study (Hunter and Schmidt, 1990; Dalton et al., 1999). Therefore meta-analysis is a particularly suitable method to assess how universal the internationalization-performance relationship is and decisive for the direction of further inquiries. The meta-analytical survey in chapter two consequently addresses two major research questions: (1) What is the overall relationship between internationalization and firm performance? And (2) how is the relationship between internationalization and performance moderated by intervening variables? I address this question by metaanalyzing 36 studies with an overall sample size of N = 7,792 observations. This study

Universality or Context Dependence

9

is among the first to introduce the method of meta-analysis to international business research. To the author’s knowledge only one more working paper by Ruigrok and Wagner (2004) exists so far. However, these authors focus their meta-analytic analyses mainly on methodological moderators such as publication outlet, investigative time frame, and measurement of the internationalization and performance variables. Based on extant theory I will analyze the impact of five contextual moderator variables: R&D intensity, product diversification, country of origin, firm age, and firm size. I choose the set of moderator variables based on two criteria: (1) Whether there is ambiguity on the direction and magnitude of the effect and (2) whether sufficient data is available for meaningful analyses. Consequently, this list should not be considered an exhaustive enumeration of all possible moderator variables but rather an appraisal of key contextual variables. Figure 1.1 depicts the theoretical model used in chapter two. Furthermore, I will analyze to what extend differences in research methodology (such as conceptually different measures of the constructs of internationalization and performance, or time frame of investigation) are responsible for contradictory findings in prior research.

Figure 1.1 Theoretical Model for the Investigation of Context Related Moderators

Degree of Internationalization

Country of Origin

R&D Intensity

Firm Age Product Diversification

Firm Size

Firm Performance

10

Introduction

The study contributes to the literature in at least two important ways. First, I determine the magnitude and direction of the overall effect of internationalization on firm performance. Second, I establish the universality of the internationalizationperformance relationship as I test the relevance of key moderator variables. Knowledge about the direction, magnitude, and moderators of the internationalization effect on firm performance has important theoretical and practical implications. It is important for investors, policy makers, educators, and the managers themselves. The application of meta-analysis represents an important step towards evidence-based management (Rousseau, 2007) in the domain of international business and a practical tool for theory development. If the relationship is indeed fundamentally context dependent, future research should no longer search for generalizations, but instead investigate the conditions under which internationalization might be fruitful.

1.6 Curve Type and the Role of Intangible Resources One of the premises of meta-analysis is that it assumes linearity. However, recently the debate on the shape of the relationship between internationalization and performance has received increased attention. While in recent years there seemed to be some agreement in the research community that the trade-off between benefits and costs associated with internationalization is not constant but varies along the internationalization continuum there is still ambiguity about the kind of curve type that best reflects the internationalization-performance relationship. At present the notion of the ‘3-stage theory’ seems to become the prevailing paradigm in international business research (Glaum and Oesterle, 2007). Latest publications in leading international journals make all use of this sigmoid curve type model1. This proposition seems appealing because it integrates different aspects in terms of an ‘eclectic paradigm of curve type pattern’. Its proponents claim that the 3-stage theory can be interpreted as a ‘general theory’, i.e. a theory that encompasses other attempts to model the relationship between firm internationalization and performance. Yet it is challenged by empirical research that doubts a universally applicable curve type. Scholars like Ruigrok, Amann, and Wagner (2007) propose that the curve type that best fits the internationalization-performance relationship is depending upon the country of origin of a firm. The main arguments of these scholars center on the proximity to neighboring markets (in terms of culture, language, economic develop-

Curve Type and the Role of Intangible Resources

11

ment, etc.) and the size of the home market. While the first factor relates to the magnitude of liability of foreignness faced by an internationalizing firm and therefore the question whether the first steps of internationalization lead to a decline or rise of overall performance the size of the home market concerns the inflection points at which the benefit-cost trade-offs change. Based on a sample of German firms with n = 789 observations I investigate how the shape of the internationalization-performance relationship varies across different degrees of internationalization. This investigation contributes to the literature in that it challenges the idea of a general theory of a sigmoid curve type. The pioneers of the 3-stage theory based their arguments about curve type patterns on idiosyncratic home market characteristics of their respective samples (Japan and US). While Germany shares some commonalities with these countries it differs from both of these countries in one important way: Germany is one of the largest economies in the world, but it is as well member of a wider economic union, the single European market. Therefore I will reconsider the benefit-cost trade-off associated with internationalization and develop a coherent model for the shape of the internationalization-performance relationship in a German context. However, as Hennart (2007) notes, if one reasons about why there should be any relationship between internationalization and firm performance it is hard to deduct immediate and systematic performance consequences just from being international without considering the circumstances. This notion doubts the assumption that there should be a direct and universal relationship. Rather it seems plausible that third variables constitute relevant success factors that elevate firm performance and that internationalization might be a relevant vehicle to exploit these advantages in different markets. Against this background, internationalization is the result of rational actors’ behavior in reaction to favorable market conditions that allow the creation or exploitation of some competitive advantage – within the scope of a company’s own business. Right from the beginning of theory building researchers in the discipline of international business contended that a major justification for international business activities of a firm is the exploitation of a competitive advantage compared to domestic and foreign rivals (Caves, 1971). The multinational company (MNC) seems to be an effective medium to exploit competitive advantage in foreign markets because of market failure. Assuming that any performance consequences from inter-nationalization are context dependent, the question arises whether intangible resources can be a

12

Introduction

reason for doing business abroad. This perception has been proposed by different researchers; may it be in the notion of ‘ownership advantages’ within the eclectic theory by Dunning (1980) or the importance of ‘unique resources’ by scholars in favor of internalization theory (Buckley and Casson, 1976; Hymer, 1976). In his review of the resource based view and international business Peng (2001) concludes that the resource based view has become a highly influential theoretical perspective in contemporary international business research. If so, a second question follows, namely the question if intangible resources generally have a positive performance impact when applied internationally or if the importance of certain dimensions of intangible resources for internationalization success varies. While considerable attention has been dedicated to the first research question (e.g. Morck and Yeung, 1991; Mishra and Gobeli, 1998), until today research has mainly fallen short of dividing between different facets of intangible resources. Not only has theorizing about the value impact of intangible resources neglected that different dimensions of intangibles might be more valuable if exploited internationally than others but measuring intangible resources in empirical tests has remained underdeveloped as well (with R&D intensity being the most common conceptualization). I will investigate, (1) if and why intangible resources moderate the internationalization-performance relationship and (2) if particular dimensions of intangible resources contribute differently to performance. Consequently, this section is not an investigation on the plurality of possible moderator variables but rather an investigation on the role of intangible resources and their different facets in the domain of internationalization. Especially the second kind of inquiry uncovers a blind spot of the international business research landscape as it comes closer to the original literature of the resource based view of the firm. Already early contributions asserted that the value of resources varies in terms of ‘industry specific success factors’ (Amit and Schoemaker, 1993). If applied to the internationalization-performance relationship this would mean that the extent to which different dimensions of intangible resources offer ‘internationalization potential’ (i.e. enhance the performance impact of internationalization) might vary. This study contributes to the literature as it will introduce a novel approach of measuring the overall impact of intangible resources on the basis of Tobin’s q, the so called hedonic approach. The measure is derived from hedonic prizing models that aim to derive the overall value of an asset from the separate values of different components. Furthermore, I will differentiate five dimensions of intangible resources and

Intangible Resources – the Internationalization Process – and Performance

13

derive how each of them moderates the internationalization-performance relationship. These dimensions include: Technological know-how, market know-how, contractbased know-how, and top management team (TMT) demographic traits. Figure 1.2 depicts the research model for the moderating influence of different measures of intangible resources upon the internationalization-performance relationship.

Figure 1.2 Theoretical Model for Moderator Analysis of Intangible Resources

Degree of Internationalization

Technological Know-How Market Know-How

Tobin’s q

Contract-Based Know-How Hedonic q

TMT International Diversity TMT Education

Firm Performance

1.7 Intangible Resources – the Internationalization Process – and Performance The internationalization of firms, together with the existence of intangible resources within firms, has become the subject of extensive study over the last decade. Several internationalization theories have considered the availability of intangible resources owned by the firm to be a key factor in the internationalization of that firm (Delgado-Gómez, Ramírez-Alesón, and Espitia-Escuer, 2004). In the same manner the internationalization process has been a central research focus of international business

14

Introduction

scholars since the late 1970s (e.g. Johanson and Vahlne, 1977; Johanson and Mattson, 1988; McDougall and Oviatt, 1996). However, only a few empirical analyses have addressed these issues collectively and considered how intangible resources interact with the internationalization process of the firm, and even fewer in the case of German firms. Against this background, this study starts addressing this research gap. While chapter three assesses if intangible resources act as moderators of the relationship between internationalization and firm performance chapter four will explore how this occurs. Central to the research framework of chapter four is the introduction of the internationalization process into the discussion of contingency factors of the internationalization-performance relationship. Specifically I will seek to give answers to two interrelated research questions: (1) Do intangible resources explain different process patterns of internationalization for a sample of German firms between 2001 and 2006? And (2) how do differences in the internationalization process itself moderate the internationalization-performance relationship? There are three main differences with respect to previous research. First, I will open up the black box of how international expansion of the firm is dependent on the availability of intangible resources and how process patterns of international expansion again lead to different performance outcomes. Second, I analyze the impact of intangible resources on the decision by the firm to increase international diversification, rather than only on the degree of internationalization. Third, I distinguish between different facets of intangible resources again. While from a theoretical point of view it seems reasonable to differentiate certain characteristics of intangible resources most previous researchers have chosen to use simple variables that reflect some of the intangible resources, assuming – consciously or not – that they are representative of the stock of intangibles of a firm. As a consequence this study introduces a dynamic perspective and takes a closer look on how the internationalization of firms evolves over time. Concerning the first research question I will investigate the internationalization posture of German firms with respect to the impact that the availability of intangible resources has on the propensity to increase internationalization between 2001 and 2006 as well as the effect it has on the geographic location where increasing international commitment takes place. This kind of inquiry has been stimulated by a recent paper by Rugman and Verbeke (2004) who introduce the ‘regionalization hypothesis’ into international

Intangible Resources – the Internationalization Process – and Performance

15

business research. Their major argument is that multinational enterprises are regional, not global, which they define as balanced sales across America, Europe, and Asia. They propose that the sales of the majority of the largest multinational companies are concentrated either in the region in which their head offices are located or in that of one other region. This study seeks to contribute to the emerging debate on the regional profile of multinational companies in that it analyzes the importance that the availability of a firm’s intangible resources has on its decision to increase its presence in foreign markets, that is to say, its effect on international expansion into different regions of the world. As concerns the second research question only few studies have investigated the performance attributes of the international expansion process to date (Vermeulen and Barkema, 2002; Wagner, 2004). Consequently little is known to date about the moderating impact of different process characteristics on the internationalizationperformance relationship, and even fewer on how these process characteristics are affected by intangible resources. However, I suppose that not only the degree of internationalization matters with regard to the way how internationalization relates to firm performance but as well the way how a company arrives there. This is because firms have only limited capacity to handle new information. Drawing upon the notion of absorptive capacity (Cohen and Levinthal, 1990) and diseconomies of time compression (Dierickx and Cool, 1989) I will build a theoretical argument how the internationalization process might depress the performance effect from internationalization. Two major process characteristics can be distinguished, speed and scope of internationalization. While speed relates to the sheer amount of new information from internationalization scope relates to the diversity of new information. The study contributes to the literature on internationalization and performance in two ways. First, it opens up the black box of the triangular relationship between intangible resources, the internationalization process and how they jointly relate to the internationalization-performance relationship. Second, it explores if certain expansion characteristics are depending upon the availability of intangible resources. Knowledge of how the performance consequences of certain expansion patterns depend upon intangible resources will be important to understand better how intangible resources can be successfully deployed in international markets. The key objective of this study is to illuminate further the internationalizationperformance relationship by applying innovative temporal, black box, and contextual

16

Introduction

perspectives simultaneously. In doing so, this study promotes the research stream’s capability to effectively inform management practice as well. Figure 1.3 summarizes the proposed research framework.

Figure 1.3 Theoretical Model of Intangible Resources – the Internationalization Process – and the Internationalization-Performance Relationship Intangible Resources

Technological Know-How Market Know-How

Internationalization Process ' Int = I(t=n) – I(t=0)

Contract-Based Know-How

Speed

TMT Internat. Diversity

Scope

TMT Education

Degree of Internationalization

Firm Performance

Endnote

17

Endnote 1. For example see the Special Issue on internationalization and firm performance in ‘Management International Review’ 03/2007 with the contributions by (Ruigrok et al., 2007) and (Contractor, 2007) as well as other publications in A-journals such as Academy of Management Journal (Lu and Beamish, 2004) or Journal of International Business Studies (Contractor et al., 2003).

18

Introduction

References Amit,

R. and Schoemaker, P.J.H. (1993) 'Strategic Assets and Organizational Rent', Strategic Management Journal 14(1): 33-46.

Annavarjula, M.G. and Beldona, S. (2000) 'Multinationality-Performance Relationship: A Review and Reconceptualization', The International Journal of Organizational Analysis 8(1): 48-67.

Barney, J.B. (1991) 'Firm Resources and Sustained Competitive Advantage', Journal of Management 17(1): 99-120. Brewer, H.L. (1981) ' Investor Benefits from Corporate International Diversification', Journal of Financial and Quantitative Analysis 16(1): 113-124. Buckley, P.J. (1981) 'A Critical Review of Theories of the Multinational Enterprise', Aussenwirtschaft 36(1): 70-87. Buckley, P.J. and Casson, M. (1976) The Future of the Multinational Enterprise, Macmillan: London. Buhner, R. (1987) 'Assessing International Diversification of West German Corporations', Strategic Management Journal 8(1): 25-37.

Capar,

N. and Kotabe, M. (2003) 'The Relationship between International Diversification and Performance in Service Firms', Journal of International Business Studies 34(4): 345-355.

Caves, R.E. (1971) 'Industrial Corporations: The Industrial Economics of Foreign Investment', Economica 38(149): 1-27. Cohen, W.M. and Levinthal, D.A. (1990) 'Absorptive Capacity: A New Perspective on Learning and Innovation', Administrative Science Quarterly 35(1): 128-152. Contractor, F.J. (2007) 'Is International Business Good for Companies? The Evolutionary or MultiStage Theory of Internationalization vs. The Transaction Cost Perspective', Management International Review 47(3): 453-475. Contractor, F.J., Kundu, S.K. and Hsu, C.C. (2003) 'A Three-Stage Theory of International Expansion: The Link between Multinationality and Performance in the Service Sector', Journal of International Business Studies 34(1): 5-18.

Dalton,

D.R., Daily, C.M., Johnson, J.L. and Ellstrand, A.E. (1999) 'Number of Directors and Financial Performance: A Meta-Analysis', Academy of Management Journal 42(6): 674-686.

Delgado-Gómez, J.M., Ramírez-Alesón, M. and Espitia-Escuer, M.A. (2004) 'Intangible Resources as a Key Factor in the Internationalisation of Spanish Firms', Journal of Economic Behavior & Organization 53(4): 477-494. Dierickx, I. and Cool, K. (1989) 'Asset Stock Accumulation and Sustainability of Competitive Advantage', Management Science 35(12): 1504-1511. Doukas, J.A. and Lang, L.H.P. (2003) 'Foreign Direct Investment, Diversification and Firm Performance', Journal of International Business Studies 34(2): 153-172.

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Dunning, J.H. (1974) The Distinctive Nature of the Multinational Enterprise. In: Dunning, J. H., editor, Economic Analysis and the Multinational Enterprise, George Allen & Unwin: London, 1330. Dunning, J.H. (1980) 'Toward an Eclectic Theory of International Production: Some Empirical Tests', Journal of International Business Studies 11: 9-31.

Fatemi, A.M. (1984) 'Shareholder Benefits from Corporate International Diversification', Journal of Finance 39(5): 1325-1344.

Geringer, J.M., Tallman, S. and Olsen, D.M. (2000) 'Product and International Diversification among Japanese Multinational Firms', Strategic Management Journal 21(1): 51-80. Glaum, M. (1996) Internationalisierung und Unternehmenserfolg. Habilitation, University of Giessen, Gabler, Wiesbaden. Glaum, M. and Oesterle, M.J. (2007) '40 Years of Research on Internationalization and Firm Performance: More Questions Than Answers?' Management International Review 47(3): 307-317. Gomes, L. and Ramaswamy, K. (1999) 'An Empirical Examination of the Form of the Relationship between Multinationality and Performance', Journal of International Business Studies 30(1): 173187. Gomez-Mejia, L.R. and Palich, L.E. (1997) 'Cultural Diversity and the Performance of Multinational Firms', Journal of International Business Studies 28(2): 309-335. Grant, R.M. (1987) 'Multinationality and Performance among British Manufacturing Companies', Journal of International Business Studies 18(3): 79-89.

Hahn,

D. and Hungenberg, H. (2001) PuK, Wertorientierte Controllingkonzepte: Planung und Kontrolle. Planungs- und Kontrollsysteme. Planungs- und Kontrollrechnung, Gabler, Wiesbaden.

Harveston, P.D., Kedia, B.L. and Francis, J.D. (1999) 'MNE's Dependence on Foreign Operations and Performance: A Study of MNEs from the "Triad" Regions', International Business Review 8(3): 293-307. Hennart, J.F. (2007) 'The Theoretical Rationale for a Multinationality-Performance Relationship', Management International Review 47(3): 423-452. Hitt, M.A., Hoskisson, R.E. and Kim, H. (1997) 'International Diversification: Effects on Innovation and Firm Performance in Product-Diversified Firms', Academy of Management Journal 40(4): 767-798. Hodgkinson, G.P., Herriot, P. and Anderson, N. (2001) 'Realigning the Stakeholders in Management Research: Lessons from Industrial, Work and Organizational Psychology', British Journal of Management 12(Supplement 1): 41-48. Hsu, C.C. and Boggs, D.J. (2003) 'Internationalization and Performance: Traditional Measures and their Decomposition', Multinational Business Review 11(3): 23-49. Hunter, J.E. and Schmidt, F.L. (1990) Methods of Meta-Analysis: Correcting Error and Bias in Research Findings, Sage: Newbury Park, CA.

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Hymer, S.H. (1976) The International Operations of National Firms: A Study of Foreign Direct Investment, MIT Press: Cambridge, MA.

Johanson,

J. and Mattson, L.-G. (1988) Internationalisation in Industrial Systems - a Network Approach. In: Hood, N. and Vahlne, J. E., editors, Strategies in Global Competition, Croom Helm: New York, 287-314.

Johanson, J. and Vahlne, J.E. (1977) 'The Internationalization Process of the Firm - a Model of Knowledge Development and Increasing Foreign Market Commitments', Journal of International Business Studies 8(1): 23-32.

Kaufmann,

L. and Schneider, Y. (2004) 'Intangibles: A Synthesis of Current Research', Journal of Intellectual Capital 5(3): 366-388.

Kumar, M.S. (1984) 'Comparative Analysis of UK Domestic and International Firms', Journal of Economic Studies 11(3): 26-42.

Lev, B. (2001) Intangibles: Management, Measurement, and Reporting, Brookings Institution Press: Washington, DC. Lilienthal, D. (1975) The Multinational Corporation. In: Anshen, M. and Bach, G. L., editors, Management and Corporations 1985. A Symposium Held on the Occasion of the 10th Anniversary of the Graduate School of Industrial Administration, Carnegie Institute of Technology: Westport, 119-158. Lu, J.W. and Beamish, P.W. (2001) 'The Internationalization and Performance of SMEs', Strategic Management Journal 22(6/7): 565-586. Lu, J.W. and Beamish, P.W. (2004) 'International Diversification and Firm Performance: The S-Curve Hypothesis', Academy of Management Journal 47(4): 598-609.

McDougall, P.P. and Oviatt, B.M. (1996) 'New Venture Internationalization, Strategic Change, and Performance: A Follow-up Study', Journal of Business Venturing 11(1): 23-40. Mishra, C.S. and Gobeli, D.H. (1998) 'Managerial Incentives, Internalization, and Market Valuation of Multinational Firms', Journal of International Business Studies 29(3): 583-597. Morck, R. and Yeung, B. (1991) 'Why Investors Value Multinationality', Journal of Business 64(2): 165-187.

Peng,

M. (2001) 'The Resource-Based View and International Business', Journal of Management 27(6): 803-829.

Peteraf, M.A. (1993) 'The Cornerstones of Competitive Advantage: A Resource-Based View', Strategic Management Journal 14: 179-191.

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Pettigrew, A. (1997) The Double Hurdles for Management Research. In: Clarke, T., editor, Advancement in Organizational Behaviour: Essays in Honour of Derek S. Pugh, Darthmouth: London, 277-296.

Qian, G. (2002) 'Multinationality, Product Diversification, and Profitability of Emerging US Smalland Medium-Sized Enterprises', Journal of Business Venturing 17(6): 611-633.

Ramaswamy, K. (1992) 'Multinationality and Performance: A Synthesis and Redirection', Advances in International Comparative Management 7: 241-267. Rousseau, D.M. (2007) 'Educating Managers from an Evidence-Based Perspective', Academy of Management Learning & Education 6(1): 84-101. Rugman, A.M., Lecraw, D.J. and Booth, L.D. (1985) International Business, McGraw Hill: New York. Rugman, A.M. and Verbeke, A. (2004) 'A Perspective on Regional and Global Strategies of Multinational Enterprises', Journal of International Business Studies 35(1): 3-18. Ruigrok, W., Amann, W. and Wagner, H. (2007) 'The Internationalization-Performance Relationship at Swiss Firms: A Test of the S-Shape and Extreme Degrees of Internationalization', Management International Review 47(3): 349-368. Ruigrok, W. and Wagner, H. (2003) 'Internationalization and Performance: An Organizational Learning Perspective', Management International Review 43(1): 63-83. Ruigrok, W. and Wagner, H. (2004) 'Internationalization and Firm Performance: Meta-analytic Review and Future Research Directions', Working Paper, University of St. Gallen.

Sapienza,

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Sullivan, D. (1994) 'Measuring the Degree of Internationalization of a Firm', Journal of International Business Studies 25(2): 325-342. Sullivan, P.H. (2000) Value-Driven Intellectual Capital – How to Convert Corporate Assets into Market Value, John-Wiley & Sons Inc.: New York, NY.

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Introduction

Wagner,

H. (2004) 'Internationalization Speed and Cost Efficiency: Evidence from Germany', International Business Review 13(4): 447-463.

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Chapter 2 The Effect of Context-Related Moderators on the Internationalization-Performance Relationship: Evidence from Meta-Analysis

2.1 Introduction Empirical research in a certain domain typically involves three phases (Hunter and Schmidt, 1990). In the first phase researchers conduct individual studies with the ambition that their efforts will lead to a clear answer to the research question at hand. Inevitably, these single studies suffer from statistical bias such as sampling error, measurement error, and range restriction. As a consequence empirical results across studies might not be conclusive or even contradictory and lead to different interpretations of the phenomenon under investigation. During the second phase researchers typically ask for additional research to identify moderator variables, i.e. variables that caused the conflicting findings. This phase involves the validation of constructs and measurement instruments as well as contextual research on contingency factors of the focal relationship. Nevertheless, instead of solving the problem through contextual inquiries, scholars often conclude that the number of questions has instead grown. In the third phase researchers conclude that the phenomenon turned out to be too complex and doubt that consensus on the phenomenon can be reached at all. The moderator hypotheses from the initial studies are not borne out and no one can make

24

The Effect of Context

much sense of the conflicting findings. Consequently researchers resign from searching answers to the original research question and ask for different research paradigms that seem to be more tractable. However, research does not need to enter this last phase of resignation as Hunter and Schmidt (1990, p. 37) have pointed out: “Applications of meta-analysis to accumulated research literatures have generally shown that our research findings are not nearly as conflicting as we had thought and that useful general conclusions can be drawn from past research. Cumulative knowledge is possible in the behavioral and social sciences after all. [...] It means that cumulative understanding and progress in theory development is possible after all. It means that the behavioral and social sciences can attain the status of true sciences; they are not doomed forever to the status of pseudo-sciences, or even quasi-sciences.”

If this logic of academic progress is transferred to the internationalization-performance relationship early research can be traced back to the 1970s. Perhaps the influential papers of Sullivan (1994) and Hitt, Hoskisson, and Kim (1997) towards the mid 1990s mark the beginning of phase number two. Contemporary research might lead to the conclusion that the research community is still in stage number two with some indication that it might be at the edge of phase three (for example see Hennart (2007) who fundamentally doubts the theoretical rationale for a systematic relationship between multinationality and performance). Given the number of empirical studies addressing the subject and given the diversity of the results, the need for a comprehensive analysis of past research is crucial for the advancement of internationalization research. Although qualitative reviews of the literature have been conducted before (Ramaswamy, 1992; Annavarjula and Beldona, 2000), what is missing to date is a systematic review and consolidation of research based on quantitative methods. Due to the shortcomings of vote counting methods (Hunter and Schmidt, 1990), meta-analysis is a logical next step. Metaanalysis offers unique possibilities for detecting the true relationship of variables and analyzing reasons for conflicting findings (such as research artifacts or moderator variables) that are not available in any other study (Dalton et al., 1999). Given the high number of single studies in the area of internationalization and performance to date, meta-analytical procedures are more likely to offer further insight than would another single study (Hunter and Schmidt, 1990; Dalton et al., 1999) and are therefore crucial for the advance of research in this field. What is the relationship between internationalization and performance? I address this question by meta-analyzing 36 studies with an overall sample size of N = 7,792

Theoretical Background and Hypotheses

25

observations. This study is among the first to introduce the method of meta-analysis into international business research. It adds to existing knowledge as it investigates the relationship between internationalization and firm performance using the method of meta-analysis.

2.2 Theoretical Background and Hypotheses The present chapter addresses two major research questions: (1) What overall relationship exists between internationalization and firm performance? And (2) how is the relationship between internationalization and performance moderated by intervening variables? Analysis of relevant studies shows that one can distinguish three prevalent research streams for an explanation of internationalization decisions: Theories of foreign direct investment (Buckley and Casson, 1976; Hymer, 1976; Dunning, 1981), the learning theory (Johanson and Vahlne, 1977), and the resource-based view of the firm (Teece, 1977; Wernerfelt, 1984; Barney, 1991). Originally the first two research streams aimed to explain when, where and how a firm should go international, while the last research stream more generally characterizes resources as determining factors for the scope of firm activities. Nonetheless, they all imply theoretical mechanisms as to why a relationship to performance should exist. Since the overall direction and magnitude of internationalization’s effect on performance is fundamentally dependent on the benefits and costs associated with internationalization, I will dwell on the major factors that determine these. Theories of foreign direct investment aim to elaborate the conditions under which it might be beneficial for a firm to do business abroad. Factors both inside and outside a firm can provide the basis for ownership advantages. Theories that focus on the organization’s internal setting view the main source of benefits from internationalization in the opportunities it offers to leverage firm-specific resources. Internalization theory suggests that the multinational company (MNC) can be an effective means of transferring superior resources to foreign markets (Buckley and Casson, 1976; Hennart, 1982). Theories relying on external factors aim to explain why multinational firms exist, and postulate that market imperfections promote firms that internationalize (Caves, 1971; Morck and Yeung, 1998). Location theory stresses arbitrage opportunities in factor cost differentials and therefore advantages from local sourcing and

26

The Effect of Context

production (Kogut, 1985). Industrial organization theory highlights such market deficiencies as entry barriers, which potentially enable firms to earn economic rents via exploitation of their international market power (Hamel and Prahalad, 1985). If market imperfections favor internalization of activities over market transactions, multinational companies may benefit from transaction cost advantages (Williamson, 1975) or production cost advantages such as the potential for economies of scale and scope in international markets (Porter, 1985; Grant, 1987; Kim, Hwang, and Burgers, 1993; Capar and Kotabe, 2003). The learning theory (Johanson and Vahlne, 1977) views internationalization as an incremental process that fosters organizational learning and knowledge development (Hamel, 1991; Barkema and Vermeulen, 1998) not available to domestically operating firms. Through gradual acquisition, integration and use of knowledge about foreign markets the internationalization process offers the opportunity to gain a competitive advantage over less internationally active competitors. The critical kind of knowledge in this context is experiential knowledge that can be distinguished into general internationalization knowledge and market-specific knowledge. Johanson and Vahlne (1977) consider these two kinds of knowledge as dimensions of the human resources that should be reflected in improved products and services and that ultimately should contribute to superior firm performance. Much like the concept of ownership advantages, the resource-based view of the firm proposes that global dispersion and exploitation of core competencies generates economic rents as long as these resources retain their value (Amit and Schoemaker, 1993). Furthermore, internationalization makes it possible to tap otherwise locked resource pools and offers unique opportunities for the proactive creation of new resources. But costs associated with internationalization might, at least partly, offset the gains from going international. Theories of foreign direct investment assume that monopolistic advantages are necessary because multinational firms will encounter liabilities of foreignness and newness (Zaheer, 1995; Kostova and Zaheer, 1999) and other difficulties that might erect formidable barriers to successful business activities abroad. Internalization theory recognizes limits to the efficiency of organizational arrangements. Firms face organizational constraints such as absorptive capacity (Cohen and Levinthal, 1990) or the difficulty and expense of processing large amounts of information (Simon, 1955). Scholars of transaction cost theory (Williamson, 1975;

Theoretical Background and Hypotheses

27

Jones and Hill, 1988) and agency theory (Roth and O´Donnell, 1996) illustrate how growing complexity may eventually exhaust managerial capacity. The learning theory assumes that the complexity of managing widespread business units increases with heterogeneity in markets. Cross-cultural studies posit that geographical dispersion and cultural diversity of business activities lead to communication, coordination, and motivation problems (Hofstede, 1980). Furthermore, internationalization increases exposure to financial and political risks such as currency fluctuations, government regulations, and trade laws (Boddewyn, 1988; Brewer, 1992; Sundaram and Black, 1992; Reeb, Kwok, and Baek, 1998). As mentioned before empirical results show controversial results concerning the prevalence of either benefits or costs associated with internationalization. Together with reasoning from established theories that imply theoretical mechanisms for benefits and costs associated with internationalization I propose competing hypotheses: Hypothesis 1a. The overall relationship between internationalization and firm performance is positive. Hypothesis1b. The overall relationship between internationalization and firm performance is negative. Despite the extensive amount of research that has been conducted on the internationalization-performance relationship, a fundamental question remains: How universal is the internationalization-performance effect? The apparent inability to reach a broad consensus regarding the focal relationship is not entirely unexpected. In addition to methodological reasons, such as the ambiguity of constructs and substantial differences in the research methodologies applied and samples studied, there is still another possible reason. As already mentioned, it is likely that the internationalization-performance relationship is context-dependent and that an effect therefore exists only under certain conditions. If this is the case, then investigators should not be searching for internationalization-performance generalizations or principles, but rather focusing on the identification of moderators – variables that produce differential internationalization-performance effects. I selected the sample of moderator variables on the basis of two criteria. The first was whether there is ambiguity in the extant literature about the direction and strength

28

The Effect of Context

of the effect the moderator variable potentially has on the internationalization-performance relationship. The second criterion was availability – whether sufficient data from empirical studies were available for meaningful analyses. Figure 2.1 illustrates this classification of third variables as the basis for the present meta-analysis. The variables I was able to extract from the literature as moderating variables are research and development (R&D) intensity, product diversification, country of origin, firm age, and firm size. The variety of third variables that have been considered influential to the internationalization-performance relationship in empirical studies so far can be depicted from the column ‘(Relevant) Hypotheses’ in Appendix A 2.1. Contextual variables with an empirically established effect, i.e. without ambiguity, are commonly treated as control variables in single studies from a methodological point of view. Figure 2.1 Criteria for Moderator Variables of the Meta-Analysis Available

Ambiguous

Unavailable

Moderator Variables Variables for Future Research

Unambiguous

Established Contextual Variables

2.2.1 R&D Intensity The resource-based view and Dunning’s eclectic paradigm (Dunning, 1988, 1993) follow a similar logic. Firms with unique resources and capabilities (ownership advantage) should leverage their resources internationally as long as these resources enable them to earn economic rents. Intangible resources are a main source of competitive advantage (Kaufmann and Schneider, 2004). Caves (1982) and Franko (1989) emphasize the role of research and development efforts as a principal driver of internationalization. Morck and Yeung (1991) assert that internationalization per se is not a valuable strategy for investors, but that the impact of R&D spending on market value increases with a firm’s multinational scale. R&D expenditures are a common measure of a firm’s technology-based know-how (Caves, 1982) and innovative capabilities (Hitt et al., 1991). Intangible resources such as technological know-how do not tend to

Theoretical Background and Hypotheses

29

deteriorate when applied in multiple markets (Morck and Yeung, 1998), rather they very often tend to appreciate, as knowledge and information are cumulative (Grossman and Helpman, 1994). Although the majority of studies have found empirical support for a positive effect of R&D efforts on internationalization, some have not; contrary to theoretical expectations, Majocchi and Zuchella (2003) established in a sample of 220 Italian international small- and medium-sized companies that firms with higher R&D expenditures exhibit lower financial results. Hsu and Boggs (2003) found that for a sample of 118 large US multinational companies, spending on R&D had a significantly negative impact on ROE. Meta-analytic techniques might help to resolve these contradictions, i.e. help to establish whether the differences in effect sizes are of substantial nature or whether they might be attributed to statistical artifacts like sampling differences. McGuinness and Little (1981) argue that R&D intensity had a positive effect on export motivation, but that the impact on performance is marginal in comparison to that of other situational factors. Hitt et al. (1997) maintain that international diversification provides firms with incentives to invest in innovation and provides them with greater returns from innovation. Internationalization holds special benefits for firms with a high stock of technological-based know-how and innovative capabilities. Opportunities to exploit market imperfections in the trade of technological resources might give them a major competitive advantage over their competitors; consequently, internationalization should be a more valuable option for firms with high R&D efforts. Therefore I posit: Hypothesis 2.

Intangible resources in terms of technological know-how moderate the relationship between internationalization and firm performance, such that the relationship between internationalization and performance is stronger for R&D intensive firms.

2.2.2 Product Diversification Vachani (1991) theorized that the construct of firm diversity comprises business and geographic diversity. The guiding paradigm postulates that related product diversification yields superior performance vis-à-vis unrelated diversification in a domestic setting (Rumelt, 1974; Bettis and Hall, 1982; Palepu, 1985). In their pioneering study,

30

The Effect of Context

Stopford and Wells (1972) determined that area diversification and product diversification are two of the critical success factors for MNC growth. Since then, a number of studies have examined the combined effects of product and international diversification on performance. A combination of the arguments brought forward by the resource-based view and transaction cost theory suggests that internationalization offers the opportunity to successfully leverage a firm’s strategic resources across different levels of product diversification as long as new businesses stay within the scope of the firm’s strategic resources and capabilities (Hitt et al., 1997). Unrelatedness, but also transaction costs, puts a cap on international and product diversification, as high levels of both dimensions of firm diversity incur rising governance costs (Jones and Hill, 1988; Geringer, Tallman, and Olsen, 2000). Egelhoff (1982) empirically supports this notion. He found that rising transaction costs and information processing demands associated with international activities together with high levels of product diversification depressed firm performance. Contrary to Egelhoff’s findings, Geringer, Beamish, and DaCosta (1989), using a sample of the largest 100 US and European MNCs, did not find support for the hypothesis that product diversification moderates the positive performance impact of international diversification. A few scholars found empirical evidence that is even opposed to the prevalent position in the literature. Harrison, Hitt, Hoskisson, and Ireland (1991) delineate that differences in resource allocation patterns across firms’ international business units are more beneficial than similarities. They reason that there seem to be unique merits in internationalization for firms with unrelated product portfolios. Unrelated product diversification and internationalization constitute complements that help a firm to achieve economies of scale and scope that are unavailable from either form of diversification alone (Hitt et al., 1997). Kim, Wang, and Burgers (1989) again found no support for the contention that firms with low product diversification perform better when they are more geographically diversified, but they found a positive effect from internationalization on performance for firms with higher product diversification. The predominant position in the literature, however, is that related product diversification enhances performance (Rumelt, 1974) and provides slack resources, which are available for geographical diversification (Penrose, 1959). Yet high levels of product diversification might cause excessive transaction costs that may eventually exceed management capabilities and therefore offset the benefits attributable to internationalization (Jones and Hill, 1988; Tallman and Li, 1996). Consequently, I

Theoretical Background and Hypotheses

31

hypothesize that the performance impact attributable to internationalization is stronger for firms with low levels of product diversification. Hypothesis 3.

Product diversification moderates the relationship between internationalization and firm performance, such that the relationship between internationalization and performance is stronger for firms with low levels of product diversification.

2.2.3 Country of Origin Although macro-level contextual settings might have an impact on the internationalization-performance relationship, only a few empirical studies have compared the benefit and cost trade-offs attributable to internationalization that firms from different countries face when going abroad. Firms in some countries are more internationalized than those in other countries and thus draw on a greater level of internationalization experience. Just because of restricted domestic market size firms from smaller countries, in particular, are forced to internationalize earlier in order to generate the same sales volumes as firms from larger countries. They therefore have the advantage of experience in dealing with foreign customers, unfamiliar government regulations, and trade laws. Familiarity with foreign markets should lead to higher efficiency in international transactions. Recent analysis by the United Nations has shown that European firms operate at a far higher degree of internationalization than do firms from the USA or Japan (UNCTAD, 2004). Empirically, Geringer et al. (1989) found a significant internationalization effect on performance only when they separated their data by region (USA vs. Europe). Their findings suggest that the size of the effect is significantly affected by country environment context. There are also differences among countries with respect to costs. The degree of similarity between the home business environment and that of neighboring countries varies. Greater differences in contextual settings create exponential complexity and inflate the costs of doing business abroad (Kostova and Zaheer, 1999). Institutional and cultural factors may erect formidable barriers to the transfer of competitive advantage across national borders (Kogut, 1985). These factors include heterogeneity in politico-regulatory environments (Delios and Henisz, 2000), levels of economic development (Woodward and Rolfe, 1993), and cultural conditions (Chang and

32

The Effect of Context

Rosenzweig, 2001). The ‘establishment chain’ concept of Johanson and Vahlne (1977) posits that market knowledge attributable to internationalization experience is vital for success in internationalization (Gomez-Mejia and Palich, 1997). At the outset of internationalization, a firm should serve markets that are culturally similar to its home market. By doing so, a firm can avoid unfamiliarity with local business customs, which can, for example, lead to friction in communication and coordination. Papadopoulos and Denisz (1988), Davidson (1983), and Eramilli (1991) found that psychic distance, cultural distance, and geographic distance are major criteria for initial international location choice. Ruigrok and Wagner (2003) support this ‘market familiarity’ principle using a sample of 80 Swiss multinational manufacturing companies. These firms overwhelmingly chose Germany for their initial foreign market entry, a large market quite similar to their home market. But firms from different countries differ in their ‘familiarity’ with neighboring countries. Firms in some countries are exposed to comparatively unfamiliar markets right from the outset of their expansion and cannot easily leverage their resources without considerable adaptation needs. Ronen and Shenkar (1985) identified culturally isolated countries such as Japan and Korea, which do not have any close cultural counterparts, such as Switzerland has with Germany. Another dimension of culture concerns differences in a societies’ time-horizon for performance goals. Harveston, Kedia, and Francis (1999) show that internationalization has a positive impact on short-term performance measures like ROA and ROS but not on market-share for North American and European firms and that it has a positive impact on long-term performance measures like market-share but not on ROA or ROS for firms originating from the Pacific Rim. Country-specific ‘givens’, i.e. idiosyncratic contextual settings, predetermine on a macro-scale the benefits and costs that firms will likely face when doing business abroad. Thus the relevance of internationalization as a strategic option for success might vary among countries. Therefore I conclude: Hypothesis 4.

Country of origin moderates the relationship between internationalization and firm performance, such that the relationship between internationalization and performance differs significantly for firms from different countries.

Theoretical Background and Hypotheses

33

2.2.4 Age Whether the age of a firm influences the internationalization-performance relationship is a matter of the nature of a firm’s resources rather than the quantity. While new ventures rely on resources that are less specialized (but flexibly deployable in changing environments), incumbent firms utilize a specialized resource base that enables them to efficiently operate under current market conditions (Amit and Schoemaker, 1993; Thornhill and Amit, 2003). Flexibility plays a central role in the internationalization process. Incumbent firms that remain in current trajectories and do not manage to adapt to environmental change may fail to keep up with competition (Sull, 1999; DeCarolis, 2003). Entering foreign markets involves high risks and uncertainties as well. Organizational and resource arrangements that facilitate a willingness to take risks and remain proactive and innovative are key success factors under these conditions (Lumpkin and Dess, 1996; Sapienza, Autio, and Zahra, 2003). Younger firms often display this entrepreneurial mode of behavior; management structures are more flexible and management maintains a proactive attitude towards opportunity exploitation (Penrose, 1959). Therefore younger firms might be at a flexibility advantage when it comes to the adaptation needs of internationalization. The ‘born global’ phenomenon (Oviatt and McDougall, 1994; Harveston et al., 1999) shows that since the 1990s new firms tend to internationalize earlier in their life cycle (Zahra, Ireland, and Hitt, 2000). Some firms are international from inception and display high international market commitment. The new venture internationalization theory (McDougall and Oviatt, 1996) and the learning theory (Johanson and Vahlne, 1977) both emphasize foreign market knowledge as a key to success in internationalization. Although these two theories assert different processes of internationalization, they both nevertheless emphasize that merits of internationalization arise from knowledge development and exploitation. While the new venture internationalization theory stresses the importance of knowledge resources and organizational learning in the pursuit of new opportunities, learning theory highlights how behavioral constraints emanating from uncertainty avoidance (Sapienza et al., 2003) are imposed by the firm’s existing knowledge base. Thus inflexible structures may hinder success in internationalization. In particular, older firms are at risk for organizational inertia. Since they have developed for a longer period of time in a domestic setting, they may find it difficult to turn opportunities in

34

The Effect of Context

international markets into financial results. Firms that have not developed a high stock of knowledge in a domestic setting are at a learning advantage of newness (Autio, Sapienza, and Almeida, 2000). Older firms owe a higher portion of performance to their competence in established tasks, whereas younger firms’ performance is more dependent on recognizing new business opportunities. Therefore I hypothesize that internationalization has a greater potential to affect firm performance for younger firms. Hypothesis 5.

Firm age moderates the relationship between internationalization and firm performance, such that the relationship between internationalization and performance is stronger for younger firms.

2.2.5 Size Small businesses differ fundamentally from large businesses, as has been documented by Shuman and Seeger (1986). Besides differences in ownership, organizational structures and processes, and management systems, they differ in resource availability (financial, management, and information) for expanding their business abroad (Smith et al., 1988; Carrier, 1994). Dhanaraj and Beamish (2003) use firm size as an indicator of managerial and financial resource availability. In support of Penrose (1959), they reason that firms will look for business opportunities abroad if excess resources are available. Bloodgood, Sapienza, and Almeida (1996) support the notion that resource availability plays a key role in the decision to internationalize. They found in a sample of 61 US venture capital-backed new ventures that firm size correlated to the degree of internationalization. Their findings suggest that early internationalization is neither favorable nor detrimental to firm performance, but rather contingent upon resource conditions. They conclude that internationalization has a positive impact on firm performance if resource constraints are not a major problem. However small firms often lack financial resources for investing in assets like internationalization experience – resources needed to overcome barriers such as the liability of foreignness (Zaheer, 1995; Coviello and McAuley, 1999). Tihanyi, Ellstrand, Daily, and Dalton (2000) found in a sample of 126 US firms that certain top management team characteristics, such as higher tenure heterogeneity and higher average international experience, are positively related to the decision to internationalize. The managerial constraints of small firms, such as a lack of international experi-

Method

35

ence in the upper management team, may exhaust the absorptive capacity of management at early stages of internationalization and limit the extent of international involvement. While one can generally assume a positive correlation between firm size and firm age it would be rewarding to separate these two effects with regard to their impact on the internationalization-performance relationship. Knowledge about the two individual effects is important since it might point to different and situation specific avenues for success in internationalization. But since the effects of firm age and firm size are probably confounded I have to restrict my hypothesis concerning the effect of firm size to classes of firms with similar age. Firms that possess larger stocks of resources are able to operate at higher levels of internationalization. Therefore internationalization should also be responsible for a higher portion of the performance variance of those firms. Assuming that smaller firms face more severe resource constraints than larger firms I hypothesize: Hypothesis 6.

Within classes of firms with similar firm age, firm size moderates the relationship between internationalization and firm performance, such that the relationship between internationalization and performance is stronger for large firms.

2.3 Method 2.3.1 Sample In order to arrive at a representative sample and assure the replicability of research results, meta-analytical methods require clear and coherent separation criteria as to which research reports they include or exclude. One advantage of meta-analytic procedures over narrative reviews is that they keep authors from – consciously or unconsciously – selecting and describing studies to support their own understanding of the literature and/or their own established theoretical positions (Rosenthal and DiMatteo, 2001). Consequently, I examined those published studies that explicitly investigate the relationship of internationalization and firm performance in order to establish a coherent body of literature on this research question. I only considered studies that focused on the impact of internationalization on the overall firm performance and that reported, at a minimum, the number of observations and an effect size that is transferable into the Pearson product-moment correlation r. Consequently I did not include

36

The Effect of Context

measures of association that capture the impact of internationalization on firm performance after accounting for the influence of third variables, such as beta-coefficients from multiple regression analysis or partial correlation coefficients. This procedure is appropriate if one wants to achieve a clear picture of the straightforward operation of individual components, as is the case with meta-analysis: “Whereas there is admittedly some loss of information when one concentrates on single effects in meta-analysis, a singular focus helps to target specific questions and to distill the essential elements of a phenomenon under study” (Rosenthal and DiMatteo, 2001, p. 67). In identifying the studies for inclusion in this meta-analysis, I initiated a computer-aided keyword search of the Business Source Premier, EconLit, and ABI/Inform databases and I reviewed all past issues of pertinent journals that showed a comparably high accumulation of relevant studies, namely Strategic Management Journal (7)1, Academy of Management Journal (5), Journal of International Business Studies (4), Journal of Business Venturing (4), Management International Review (3), and International Business Review (3). I furthermore culled the reference sections of the studies collected for additional studies and searched the home pages of researchers in the area of internationalization for additional published material. This procedure offered reasonable assurance that I had identified all relevant studies. To test for availability bias, I applied file-drawer analysis and calculated fail-safe N(x) according to Rosenthal (1979). This statistical procedure helps to resolve concerns about publication bias favoring significant results over non-significant results and represents a number that shows how many unlocated studies would have to exist to make the obtained effect size insignificant. I identified 71 articles that met my selection criteria, of which I had to exclude 34 that did not provide sufficient data that I could transfer into zero-order correlations. One article was removed because it shares its sample with the study by Grant (1987). My final sample consists of 36 articles that were published between 1979 and 2004. These articles report 41 independent samples with a total sample size of N = 7,792. These samples report 146 effect sizes. Because these samples usually relied on multiple operationalizations for internationalization and performance, I arrived at a ratio of effect sizes per sample of 3.6. Table 2.1 provides a list of all studies, year of publication and sample size used in the meta-analysis. For further information about these studies please refer to Appendix A 2.1. This section provides a comprehensive overview over the articles and covers research question(s), relevant hypotheses and results, sample characteristics and variable coding.

Method

37

Table 2.1 Summary of Primary Studies Author (s) Aggarwal Bloodgood, Sapienza, and Almeida Buhner Capar and Kotabe Chen and Martin Delios and Beamish Dhanaraj and Beamish Dragun Geringer, Beamish, and daCosta Geringer, Tallman, and Olsen Goerzen and Beamish Gomes and Ramaswamy Gomez-Mejia and Palich Grant Harveston, Kedia, and Francis Hitt, Hoskisson, and Kim Hsu and Boggs Knight

Yeara 1979 1996 1987 2003 2001 1999 2003 2002 1989 2000 2003 1999 1997 1987 1999 1997 2003 2000

nb 192 61 40 81 49 399 157 130 181 108 580 95 442 304 152 295 118 216

Author (s) Lu and Beamish Lu and Beamish Majocchi and Zucchella Mauri and Sambharya McDougall and Oviatt Qian Qian Qian and Li Qian and Li Ruigrok and Wagner Sambharya Siddharthan and Lall Simmonds and Lammont Tallman and Li Wan Wan and Hoskisson Zahra and Garvis Zahra, Ireland, and Hitt

Year

n

2001 164 2004 1,489 2003 220 2001 91 1996 62 1996 126 2002 71 2002 125 2003 67 2003 84 1995 53 1982 74 1996 156 1996 188 1998 81 2003 722 2000 98 2000 321

Note: Unless otherwise indicated, the tables, figures, and appendices of this book are original work of the author. a Year of publication. b Sample size. In the literature scanning process 34 more studies could be identified that are not included in this meta-analysis. Although they empirically investigate the internationalization-performance relationship, they did not provide data that could be transferred into zero-order correlations. These studies are as follows: Benvignati (1987); Brewer (1981); Buckley, Dunning, and Pearce (1977); Chang and Thomas (1989); Christophe (1997); Collins (1990); Contractor, Kundu, and Hsu (2003); Daniels and Bracker (1989); Denis, Denis, and Yost (2002); Doukas and Lang (2003); Errunza and Senbet (1984); Fatemi (1984); Garrod and Rees (1998); Haar (1989); Han and Lee (1998); Hirschey (1982); Kim, Hwang, and Burgers (1989); Kim and Lyn (1986); Kotabe, Srinivasan, and Aulakh (2002); Kumar (1984); Mathur, Singh, and Gleason (2001); Michel and Shaked (1986); Mishra and Gobeli (1998); Morck and Yeung (1991); Palich, Carini, and Seaman (2000); Ramirez-Aleson and Espitia-Escuer (2001); Reuber and Fischer (2002); Riahi-Belkaoui (1996; 1999); Riahi-Belkaoui and Alnajjar (2002); Severn and Laurence (1974); Vermeulen and Barkema (2002); Vernon (1971); Westhead, Wright, and Ucbasaran (2001).

Although the median year of publication was 1991, 36 of 41 samples were published later. While early studies relied heavily on samples of American companies, the focus widened in the second half of the investigation. Samples from Japan, and more recently Europe, were the focal point (see Table 2.2). Presently, there seems to be a general shift of emphasis in the samples studied in international business research, as Zhao, Luo, and Suh (2004) report similar findings for their meta-analysis on international entry mode choice.

38

The Effect of Context

Table 2.2 Sample Source over Time

Total

America

Sample source Europe

Japan

Rest of World

Number Sample Number Sample Number Sample Number Sample Number Sample of size of size of size of size of size samples samples samples samples samples Overall

d 1991

a

> 1991

d 1999b > 1999 a b

41

7,792

22

2,861

8

1,496

7

2,841

4

594

5 36

791 7,001

2 20

266 2,595

2 6

344 1,152

--7

--2,841

1 3

181 413

20 21

2,901 4,891

13 9

1,831 1,030

3 5

389 1,107

3 4

500 2,341

1 3

181 413

Median year of publication (1979-2004). Median studies’ publication year.

The average firm in this sample operated at a foreign sales to total sales (FSTS) ratio of 33.5 percent and had foreign direct investments (FDI) in 7.8 countries (see Table 2.3). A segmentation by the median studies’ publication year reveals that companies have consistently increased their degree of internationalization (up to 1999: 31.7 percent FSTS, FDI in 6.8 countries; 2000 and later: 34.8 percent FSTS, FDI in 8.8 countries; see Table 2.3) across all regional clusters (America, Europe, Japan). Furthermore, large firms from this sample show higher degrees of internationalization than do the small firms. See Table 2.3 for descriptive study characteristics on the degree of internationalization.

2.3.2 Variable Coding The studies included in this meta-analysis measure internationalization using a diverse set of variables that cover international sales or asset dispersion of a firm and operationalize performance via numerous quantitative measures that can be classified into financial accounting return-oriented, growth-oriented or capital market-oriented (Jensen alpha, Sharpe ratio, market-to-book ratio, Tobin’s q). The most common conceptualization modes for internationalization and performance from the samples make up Table 2.4.

Method

39

Table 2.3 Degree of Internationalization over Time – across Countries – and by Firm Size Foreign sales to total sales

Overall

d 1991

a

> 1991

d 1999b > 1999 America Europe Japan Rest of World MNC SME a b

Number of foreign countries

Degree of internationalization

Sample size

16

1,574

.33

13

2,777

7.8

1 15

192 1,382

.29 .34

1 12

188 2,589

14.5 7.3

7 9

689 885

.32 .35

6 7

1,396 1,381

6.8 8.8

10 3 1 2

1,061 210 20 283

.31 .50 .36 .24

8 3 2 ---

1,272 942 563 ---

7.2 10.0 5.4 ---

11 6

1,081 573

.37 .27

8 5

1,915 862

8.1 7.1

Number of samples

Sample size

Degree of internationalization

Number of samples

Median year of publication (1979-2004). Median studies’ publication year.

Table 2.4 Operationalization of Internationalization and Performance Performancea

Internationalization Operationalization Foreign sales to total salesb Number of foreign countries Various entropy measures Foreign subsidiary sales to total sales Number of foreign direct investments Various indices Export sales to total sales Foreign assets to total assets Other a

b

Times used 21 13 10 4 4 4 3 3 6

Operationalization Return on assets (ROA) Return on sales (ROS) Return on equity (ROE) Sales growth Various capital market oriented measures Market share Return on investment (ROI) Other return oriented measures Other growth oriented measures

Times used 26 15 13 11 8 6 3 4 1

Thirteen of 41 samples measured performance time lagged with a range of four years time lag (K = 1) to one year time lag (K = 8). The difference in the number of operationalizations reported in this table (k = 21) to the number of samples included in Table 2.3 (k = 16) is due to five samples that did not report foreign sales to total sales means and therefore could not be analyzed in Table 2.3.

40

The Effect of Context

The measure for R&D intensity is the portion of R&D expenses to total sales. I split the sample into sub-samples of studies with averages above or below five percent R&D intensity. Splitting the overall population based on the median samples’ R&D intensity results in exactly the same classification. I decided to dichotomize moderator variables as this procedure enhances inter-rater reliability. If taken continuously the power of the analysis would have been artificially higher. Product diversification is commonly computed as a Herfindahl-type entropy measure in the form of Hf(a) = 1 - 6 Si2 (Si is the ratio of sales in product group i to total sales) (Tallman and Li, 1996) or an entropy measure according to Palepu (1985) which is Pa(a) = 6i (Pi x ln(1/Pi) (Pi is the portion of sales in product group i to total sales). With regard to the Palepu measure, I focused on the unrelated ratio, which captures diversification across two-digit Standard Industrial Classification (SIC) codes, whereas the related ratio only captures diversification across four-digit SIC codes within a two-digit SIC industry. I considered samples with values higher than 0.5 to be highly product diversified and those with lower values to have low product diversification, since the Herfindahl measure and the unrelated ratio of the Palepu measure are standardized on an interval between zero and one (exactly 0 d Hf(a) d (k-1)/k and 0 d Pa(a) d 1). Splitting the population based on the median samples’ product diversification would require recoding one study and would only marginally change results. With regard to their country of origin, I was able to separate samples of firms that originated from North America, Europe, and Japan. Although the United Kingdom is geographically a part of Europe, its firms are somewhat special because of their strong ties to North America. The samples by Grant (1987), Harveston et al. (1999), and Wan and Hoskisson (2003) all contain British firms at least in part in their European samples. I was able to resolve my concerns that these samples could bias the results for the effect of contextual settings: An exclusion of these samples from the European sample would not significantly change the results. Researchers have used different cutoff points for the separation of young and old firms such as eight years (McDougall, 1989; Zahra, 1996) and six years for start-ups (Brush and Vanderwerf, 1992; Brush, 1995; Shrader, 1996). My definition of young firms parallels prior research on ‘new ventures’ (Biggadike, 1979; McDougall and Oviatt, 1996) and ‘adolescent firms’ (Miller and Camp, 1985). It classifies a firm as young if it is less than twelve years old (Covin, Slevin, and Covin, 1990).

Method

41

In accordance with the American Small Business Administration definition of small- and medium-sized enterprises (SMEs), I differentiated between firms with more than and less than 500 employees (Lu and Beamish, 2001). A second researcher and the author independently coded the relevant study characteristics. They agreed in 96.2 percent of the cases. After in-depth investigation and discussion of the remaining five cases, we were able to resolve all discrepancies. Consequently I judged that the data preparation process was providing reliable data.

2.3.3 Analytical Approach This study is among the first to investigate the relationship between internationalization and performance quantitatively based on the method of meta-analysis. Metaanalysis is a powerful tool to detect the real relationship between variables in a systematic way when findings are inconclusive (Hunter and Schmidt, 1990). Moreover, it allows for the correction of research artifacts one cannot avoid in single studies and the detection of moderator variables based on different sample characteristics. Given the number of single studies in the research area of internationalization and performance to date, meta-analytical procedures are more likely to offer further insight than would another single study (Hunter and Schmidt, 1990; Dalton et al., 1999). Therefore, metaanalysis is a crucial endeavor for the advance of research in this field. I focused on the meta-analytical techniques developed by Hunter and Schmidt (Hunter, Schmidt, and Jackson, 1982; Hunter and Schmidt, 1990). In order to determine the direction and magnitude of the relationship between internationalization and performance, I estimated effect sizes based on the Pearson product-moment correlation r. When other translatable statistics (e.g. d-value, t-test, F-test, etc.) were available, I used formulas given by Glass, McGaw, and Smith (1981) and Hunter et al. (1982) to convert these values into the r-statistic. If a study offered several effect sizes because of multiple operationalizations, I calculated the average effect size. This procedure guaranteed that information from identical samples contributed only once to the estimate of an effect size (Petitti, 2000). The population effect size estimate r offers considerably increased accuracy in estimating an effect size relative to an estimate obtained from any single study because the sampling error present in each single study can be deleted.

42

The Effect of Context

In the present study it was not possible to correct for statistical artifacts beyond sampling error due to a lack of available data. Consequentially, I divided the observed variance in effect sizes into variance resulting from sampling error and into remaining variance that is attributable to real variance in effect sizes of the population. A key question in meta-analysis is whether large effect size variance remains after accounting for study artifacts. I tested for population homogeneity in two ways. If 95 percent credibility intervals did not overlap zero (Koslowsky and Sagie, 1993) and more than 75 percent of the observed variance was due to sampling error, I considered the population homogeneous, because all effect size variance is likely due to artifacts (Hunter et al., 1982; Schmidt, Hunter, and Raju, 1988). I rejected applying a chisquare test for homogeneity as this test may infer sample homogeneity caused by chance in the case of small samples (Hunter et al., 1982). In order to distinguish the effects of firm age and firm size I performed hierarchical analyses, i.e. I separated the entire population into young firms and old firms and then tested the effect of firm size in both sub-samples. In a meta-analytical setting this procedure is comparable to testing for one effect while controlling for another (Hunter et al., 1982). The number of studies included into a moderator analysis is often a lot smaller than the overall number of studies, because not every moderator variable can be coded from each study. Analysis as to whether the main effect was also present in subsamples for moderator analysis revealed that effect sizes from these combined subsamples did not differ significantly from those of the whole population. None of the z-values for differences in effect sizes was significant (see Table 2.5). I applied two criteria in testing for significance of moderator variables. First, I calculated z-statistics to test for significance of differences in effect sizes. Second, the average residual variance of sub-samples was required to be less than the residual variance in the combined samples (Hunter et al., 1982). As a final step I calculated 95 percent confidence intervals to test whether the effect size estimates differed significantly from zero. 95 percent confidence intervals are based on the standard error from sampling error variance in case of homogeneous populations. When significant variance remained after correction of study artifacts, I calculated the confidence interval based on the standard error of the observed effect size variance (Whitener, 1990). A comprehensive description of the statistical formulas and meta-analytic calculations according to Hunter and Schmidt (1990) can be found in Appendix A 2.2.

Method

43

Table 2.5 Analysis of Bias in Sub-Samples for Moderator Analysis Variable

K

N

r

41

7,792

.059

H2: R&D Intensity High Low

6 6

846 2,922

.170 .021

.10

H3: Product Diversification Low High

7 9

557 3,219

.128 .001

1.25

H4: Country of origin America Europe Japan

22 8 7

2,861 1,496 2,841

.128 .081 .009

-0.44

H5: Age Young Old

5 29

582 6,370

.209 .040

.17

H6: Size Large Small

26 2

4,668 213

.066 -.053

-0.58

H1a, H1b: Overall

Critical z-value

Notes: K: number of samples, N: sample size ¦Ni, r : sample size weighted mean effect size, critical z-value: two-tailed test for significance of differences in effect sizes of the combined sub-samples compared to the overall sample. † p < .10. * p < .05. ** p < .01.

2.3.4 Consideration of Methodological Differences As is the case with every piece of empirical research, quantitative reviews of the literature can produce biased results and lead to erroneous conclusions. Researchers need to find ways to deal with this problem. I was able to identify three potential sources of bias. The first source is specific to the method of meta-analysis. The major source of bias in meta-analytical investigations stems from conceptual differences in measuring the independent and dependent variable – the so called ‘apples and oranges problem’. The remaining two conceptual differences that need to be considered are specific to the research question at hand. Second, the question if and how internationalization relates to firm performance might not be time stable but rather contingent about a certain period of investigation. Third, the performance consequences from

44

The Effect of Context

internationalization might only be observed after a certain period of time and hence require time lagged measurement designs. A common critique of meta-analysis is the argument that it mixes studies that examine ‘apples’ with those that examine ‘oranges’. Independent and dependent variables are conceptually different and thus results are not comparable across studies. However, this does not necessarily have to be the case as Wolf (1986, p. 54) notes: “Good meta-analysis capitalizes on this [criticism] by coding apples as apples and oranges as oranges in order to empirically test whether and how they are similar or different.” In doing so, it is possible to reveal important methodological moderator variables. Indeed, the variety of operationalizations of the independent and dependent variables raised concerns that differences in measurement might significantly influence estimates of effect sizes. I therefore performed moderator analyses on different classes of measures for internationalization and performance. Although prior research based on Sullivan (1994) has suggested that the internationalization construct is multidimensional, the degree to which these dimensions affect firm performance does not seem to differ significantly (see Table 2.6). Estimates of effect sizes based on sales-oriented measures of internationalization were not significantly different from effect size estimates based on asset-oriented measures of internationalization (z = 1.08). Therefore it can be concluded that differences in measurement of the diverse facets of the internationalization construct do not significantly contribute to an explanation of controversial results in prior empirical studies. The differences in effect size estimates for measures of firm performance were also not significant (z = 0.44 for financial accounting return-oriented measures vs. growth-oriented measures, z = 1.00 for financial accounting return-oriented measures vs. capital market-oriented measures, and z = 1.17 for growth-oriented measures vs. capital market-oriented measures). Interestingly, by meta-analyzing prior empirical research on the internationalization-performance relationship I do not find support that internationalization relates differently to certain aspects of firm performance either. Additional analyses of the mean effect sizes produced by every single measurement item for internationalization and firm performance can be found in Appendix A 2.3. Concerning the second possible source of methodological bias I did not find evidence that the time of publication of a study moderates effect size estimates. A separation of the samples by publication date did not reveal significant differences in effect sizes (z = .37, p > .10). Studies published before 1999 (K = 20, r = .068) showed similar effect sizes to those studies published after that date (K = 21, r = .053).

Method

45

Table 2.6 Methodological Moderators – Internationalization and Performance

Variable

K

N

r

sr2

se2

sU2

95 percent confidence interval

95 percent credibility interval

Critical z-value

Internationalization Sales-orienteda Asset-orientedb

28 21

3,186 .101 5,768 .060

.026 .011

.009 .017 .004 .007f

.041 : .161 .016 : .104

-.158 : .360 -.106 : .226

1.08

62 10,668 .069 16 2,576 .085 6 2,873 .020

.020 .016 .012

.006 .006 .002

.034 : .104 .022 : .148 -.068 : .109

-.166 : .304 -.113 : .283 -.177 : .218

-0.44g 1.00h 1.17i

Firm Performance Return-orientedc Growth-orientedd Capital market-or.e

.014 .010 .010

Notes: K: number of samples, N: sample size ¦Ni, r : sample size weighted mean effect size, sr2: variance in effect sizes, se2: sampling error variance, sU2: residual variance (sampling error corrected variance in effect sizes), 95 percent confidence interval: interval around sample size weighted mean effect size based on observed variance for heterogeneous populations and on sampling error variance for homogenous populations, 95 percent credibility interval: interval around sample size weighted mean effect size based on residual variance, critical z-value: statistic based on test for significance of difference in effect sizes – one-tailed if the direction of the effect size is hypothesized, two-tailed if the direction of the effect size is not hypothesized. † p < .10. * p < .05. ** p < .01. a Sales oriented measures include: Foreign sales to total sales, Sales based entropy measures, foreign subsidiary sales to total sales, export sales to total sales, sales based indices. b Asset oriented measures include: Foreign assets to total assets, number of foreign countries, asset based entropy measures, number of foreign direct investments, percentage of primary activities abroad. c Return oriented measures include: ROA, ROS, ROE, ROI, operating profit margin, EBITOA, subjective profitability assessment, risk adjusted return on invested capital. d Growth oriented measures include: Sales growth, profit growth, asset growth, subjective firm growth assessment, earnings-per-share growth. e Capital market oriented measures include: Realized economic value, market-to-book ratio, indices of various capital market oriented measures, Tobin’s q, Jensen alpha, Price-Earnings ratio. f Deviation to difference between observed variance and sampling error variance due to rounding. g Value for comparison of return oriented measures and growth oriented measures. h Value for comparison of return oriented measures and capital market oriented measures. i Value for comparison of growth oriented measures and capital market oriented measures.

I did not find support that the third possible source of bias systematically affects effect size estimates either. Although it can be argued that the performance consequences from internationalization might only materialize into firm financial performance over time I did not find support that different measurement designs moderate the internationalization-performance relationship (z = -1.02, p > .10). Studies that used time lagged measurement designs of the internationalization-performance relationship

46

The Effect of Context

(K = 12, r = .033) did not generate effect size estimates that were significantly different from those that did not apply time lagged measurement designs (K = 21, r = .076).

2.4 Results Table 2.7 and Figure 2.2 present the meta-analytic results. The average effect size across all studies is positive but small ( r = .06, see Table 2.7), with a range in effect sizes from -.28 to .43 (see Figure 2.2) indicating a positive association between internationalization and firm performance. The credibility interval includes zero and sampling error accounts for only 31.1 percent of observed variance and thus fails to fulfill the 75 percent rule proposed by Hunter and Schmidt (1990). This result leads me to suspect that other variables moderate the relationship between internationalization and firm performance and that it does not represent a single population. However, since the confidence interval does not include zero, one can conclude that there is an overall significant positive relationship between internationalization and firm performance and that this effect is not due to chance (p < .05). File-drawer analysis according to Rosenthal (1979) underlines the robustness of this finding. It requires K = 266 studies with effect sizes averaging zero to make these findings insignificant. In conclusion, internationalization is positively – yet marginally – related to firm performance and therefore my data support hypothesis H1a. Hypothesis two predicts that R&D intensity positively moderates the internationalization-performance relationship. My data support this hypothesis. The difference in effect size estimates for high and low R&D intensity samples is significant (p < .05) and the average residual variance of the sub-samples is lower than the combined residual variance. The mean corrected effect size for firms with low R&D intensity is insignificant. As the confidence interval overlaps zero one cannot infer that internationalization in the absence of technological know-how will have an impact on firm performance at all. Firms with low product diversification exhibit higher effect sizes than highly diversified firms. Although there is no reduction in the mean residual variance, the differences in effect sizes are significant (p < .05). These results confirm that the two dimensions of firm diversity significantly interact, i.e. the level of product diversification influences performance gains attributable to internationalization. Thus I cannot reject hypothesis three.

Results

47

Table 2.7 Results of Meta-Analysis on Internationalization and Performance 95 percent confidence interval

95 percent Critical credibility z-value interval

sr2

se2

sU2

7,792 .059

.017

.005

.012

6 6

846 .170 2,922 .021

.027 .005

.007 .002

.020 .040 : .300 .106 : .446 .003 .035 : .078 .084 : .127

2.05*

H3: Product Diversification Low 7 High 9

557 .128 3,219 .001

.040 .002

.012 .002

.028 .020 : .276 .200 : .454 .000 .027 : .028 .001 : .001

1.66*

H4: Country of Origin America Europe Japan

22 8 7

2,861 .128 1,496 .081 2,841 .009

.020 .008 .003

.007 .005 .002

.013 .069 : .188 .093 : .350 .003 .019 : .144 .023 : .186 .001 .028 : .045 .047 : .065

1.06b 1.88†c 3.20**d

H5: Age Young Old

5 29

582 .209 6,370 .040

.013 .015

.008 .005

.110 : .308 .072 : .346 .005 .010 .005 : .084 .159 : .238

3.06**

H6: Size (old firms) Large Small

26 2

4,668 .066 .017 213 -.053 .002

.006 .002

.012a .015 : .117 .149 : .280 .000 -.109 : .002 .053 : -.053

3.10**

Variable

K

H1a, H1b: Overall

41

H2: R&D Intensity High Low

N

r

.019 : .099 .152 : .270

Notes: K: number of samples, N: sample size ¦Ni, r : sample size weighted mean effect size, sr2: variance in effect sizes, se2: sampling error variance, sU2: residual variance (sampling error corrected variance in effect sizes), 95 percent confidence interval: interval around sample size weighted mean effect size based on observed variance for heterogeneous populations and on sampling error variance for homogenous populations, 95 percent credibility interval: interval around sample size weighted mean effect size based on residual variance, critical z-value: statistic based on test for significance of difference in effect sizes – one-tailed if the direction of the effect size is hypothesized, two-tailed if the direction of the effect size is not hypothesized. † p < .10. * p < .05. ** p < .01. a Deviation in difference between observed variance and sampling error variance due to rounding. b Value for comparison of American and European samples. c Value for comparison of European and Japanese samples. d Value for comparison of American and Japanese samples.

Analysis of country of origin reveals that American and European companies exhibit a significant positive relationship between internationalization and firm performance. Even though the mean effect size estimate for Japanese companies is positive, the 95 percent confidence interval includes zero. The mean residual variance

48

The Effect of Context

Figure 2.2 Stem-and-Leaf Plot of Correlations (r) between Internationalization and Performance Stem .4 .3 .2 .1 .0 -.0 -.1 -.2

Leaf

Summary statistics

23

Maximum: .43 Minimum: -0.28 Median: .05 Weighted Mean: .06 Standard Deviation: .02

1349 334 0001455699 1112223345566 23677 15 28

of the sub-samples declines compared to the combined samples and the z-statistic for differences in effect sizes is significant for the Japanese sample (p < .01 compared to American firms and p < .10 in comparison to the European sample). Although the mean performance impact of internationalization is stronger for American firms than for European firms, the differences in effect sizes are not significant. Firm age has a strong impact on the portion of performance variance attributable to internationalization. The difference in effect sizes is highly significant (p < .01) and the mean residual variance diminishes. Another strong indication is that the 95 percent confidence intervals for the mean effect sizes of young and old firms do not overlap. Younger firms show a mean effect size of .21, the highest correlation found in this analysis. Firm size moderates the relationship between internationalization and firm performance as well. This effect becomes apparent in both sub-samples of young firms and old firms. As shown in Table 2.7 the difference in effect sizes of large firms compared to small firms is highly significant (p < .01) for the sub-sample of old firms and the mean residual variance diminishes. The results for young firms are similar although only five studies were available for this investigation. Due to this fact I decided not to show them in Table 2.7 but to emphasize the results for old firms instead. Within the sub-sample of young firms the effect size for large firms is r = .40 and r = .19 for small firms and the difference in effect size estimates is significant as well (z = 4.20, p < .01). The fact that both effect sizes within the sub-sample of young firms are higher than those produced by the sub-sample of old firm justifies the separation of these two samples. Analysis on an aggregated basis would have caused

Discussion

49

ambiguity in the assignment of the performance effects to the two explanatory variables firm age and firm size. Consequently the effect of firm size would have been suppressed by the effect of firm age and would not have become obvious.

2.5 Discussion The major research objective in this chapter was to answer the important but as yet unresolved question of whether internationalization has an impact on firm performance. Given the obtained meta-analytic results with a sample size weighted mean effect size of r = .06 for the entire population, the answer must be yes. Although the effect size is small in magnitude (Cohen, 1977) there is a positive and statistically significant overall relationship between internationalization and firm performance. Perhaps even more important, I find evidence that this relationship is highly context dependent. Although this perception has been subject to growing research interest in recent years, it has not yet been investigated adequately enough to fully understand the extent to which interacting variables shape the internationalization-performance relationship. I found support for the proposition that five context related moderator variables significantly affect performance gains attributable to internationalization: R&D intensity, product diversification, country of origin, firm age, and firm size. Apparently, under certain conditions, effect sizes are much higher than indicated by the overall effect size. The highest effect sizes I found were those for the sub-samples of young firms ( r = .21), followed by firms with high R&D intensity ( r = .17), firms with low levels of product diversification or originating from North America ( r = .13), and large and old firms ( r = .07). Not only is the strength of the relationship significantly different for each moderator variable, the direction of the mean corrected effect size is positive for each sub-sample – with an exception of small and old firms. In this meta-analysis I corrected for sampling error, the most important statistical artifact in single studies (Hunter and Schmidt, 1990). It is also possible that there is error in measurements of the independent or dependent variable in the studies that I reviewed. While some scholars make use of estimates for population reliabilities (Combs and Ketchen Jr., 2003; Sturman, 2003), other researchers assume global reliabilities of .80 in measuring the independent and dependent variable in their metaanalyses (Dalton et al., 1998; Dalton et al., 1999; King et al., 2004). However, I could not accurately account for measurement error, as none of the articles reported information on data reliability. Altogether I do not consider my results to be seriously

50

The Effect of Context

biased as corrections for artifacts beyond sampling error generally account for very little variance in effect sizes in meta-analysis (Hunter and Schmidt, 1990). If I could have corrected for these artifacts, effect size estimates would probably have been slightly higher. Therefore, the magnitudes of effect sizes are rather conservative estimates of the real population values, underlining the robustness of the findings. Market imperfections are the basis for benefits gained from cross-border activities of firms. However, the extent to which these market imperfections offer opportunities for internationalization may not be stable over time, but rather conditional upon a certain period of investigation. For example, trade barriers in factor and financial markets have diminished over the last three decades and larger trade regions like NAFTA, MERCUSOR, ASEAN, and the single European market have emerged. Therefore, arbitrage opportunities in market imperfections might have had a greater impact on firm performance in earlier investigations. But as already noted, a separation of my samples by publication date did not reveal significant differences in effect sizes (z = .37, p > .10). There may be three different explanations for this: (1) Major market imperfections may still persist around the world, (2) contrary to theory, external conditions such as market imperfections may not be a main source of advantage for multinational firms, or (3) companies might have learned to compensate for the loss of arbitrage opportunities in market imperfections and have developed stronger internal capabilities. Firms with a strong effort in the generation of technologically based know-how can successfully leverage these resources through internationalization. Contrary to this finding, the effect of foreign business activities on firm performance is insignificant in the absence of technologically based know-how. Accordingly, efforts in research and development can be a major source of competitive advantage in the internationalization process; one that apparently can be transferred and exploited successfully by multinational firms. These results underline the importance of ownership advantages for successful internationalization (Dunning, 1988). In the two following two chapters I will therefore analyze in more detail, (1) which intangible resources act as moderators of the focal relationship, (2) why they offer potential for internationalization success and (3) how they contribute to superior firm performance. Geographic diversification and product diversification are two dimensions of firm diversity that significantly interact. The results indicate that the ability to manage complexity is a key success factor in internationalization. Greater levels of internation-

Discussion

51

alization contribute positively to firm performance only if there is sufficient absorptive capacity to cope with increasing complexity (Cohen and Levinthal, 1990). If a firm has already spread its activities across a variety of product markets, the additional performance effect of spreading its activities across different geographical markets as well is null. In contrast, firms that do not face constraints of coordinating and monitoring a variety of businesses have the opportunity to benefit from internationalization as long as they can avoid overextending their managerial capacity to handle complexity. Hence there seems to be a trade-off between forms of diversification. Managers should pay careful attention to which kind of expansion path they choose, because over-diversification might eventually exhaust managerial capacity. American, and to a lesser extent European, companies benefit more from internationalization than do their Japanese counterparts. But how does country of origin actually influence performance differences attributable to internationalization? Is it through cultural distance (Hofstede, 1980), environment familiarity and internationalization experience (Johanson and Vahlne, 1977), or liability of foreignness (Zaheer, 1995), or a combination of all three? Unlike European or Japanese companies, the average US MNC can draw on a huge home market and does not have to take the additional risk and costs of crossborder activities in order to gain from economies of scale. Companies from smaller countries must go abroad early on in order to take advantage of the same benefits. US firms, being larger and more mature at the time of their initial foreign market entry (UNCTAD, 2004), might therefore already enjoy benefits that firms from smaller countries are looking for internationally and therefore can be more successful in international competition. Furthermore, European and even more so Japanese firms are exposed to unrelated environmental contexts right from the outset of foreign expansion (Ronen and Shenkar, 1985). It seems that European firms can at least partly compensate for this disadvantage as compared to American firms. Assuming that the average degree of internationalization reflects the accumulated internationalization experience of a typical company, European firms are at an advantage with respect to their capacity or competence in managing internationalization. Japanese firms cannot draw on this kind of experience to the same extent and face substantial cultural barriers when going abroad. Nevertheless, causal inferences on the sources of differences in success (such as cultural, political, or geographic aspects) are difficult to draw, as the country of origin

52

The Effect of Context

variable may exert its influence on the relationship between internationalization and performance in many different ways. Therefore, the meta-analytical approach is more explorative than confirmative with respect to country of origin. Younger firms might have a learning advantage of newness as suggested by Autio et al. (2000). Their resources are not yet specialized and therefore can be more flexibly deployed (Amit and Schoemaker, 1993). Older firms that have grown up in a domestic setting may find it difficult to adapt organizational routines and management systems to environmental changes and might be seriously disadvantaged by organizational inertia. Therefore internationalization of business activities early on in the life cycle of a firm might be a particularly interesting strategic option. The way how firm size acts as a proxy for resource availability in the domain of internationalization is twofold. First, firms that possess a higher stock of resources show higher international involvement – expressed by their foreign sales to total sales ratio (see Table 2.3). Second, the relationship between internationalization and firm performance is stronger for the population of large firms as well. Internationalization requires considerable amounts of resources in order to become a successful endeavor. Another important insight is that the effects of firm size and firm age confound with respect to their impact on the internationalization-performance relationship. While the results indicate that internationally expanding firms might gain from both – greater firm size and younger firm age – it also becomes apparent that the relevance of the factors underlying firm age are more important for internationalization success than those underlying firm size. The effect sizes exhibited by younger firms are higher than those of older firms irrespective of whether these firms are large or small. Therefore I conclude that flexibility might be a key success factor for firms willing to broaden their scope of business abroad that cannot be simply compensated by sheer resource availability.

2.6 Limitations Meta-analytic methods cannot resolve questions of causality, i.e. one cannot infer whether internationalization leads to higher performance, whether firms with outstanding performance are more likely to internationalize, or whether the relationship is of a reciprocal nature. But the fact that 32 percent of the studies measure time lagged performance variables might indicate a certain causality in this relationship, i.e., there

Implications for Future Research

53

are performance gains attributable to internationalization. However, future research might further apply longitudinal designs in order to address this issue. I had to omit a number of studies from this meta-analysis because they did not contain sufficient information for the computation of effect sizes. This limitation in data from primary research highlights the need for more complete reporting of research results in published articles. In the future, authors and editors should report statistical tests or, at a minimum, zero-order correlations in their articles (Eden, 2002). With improved reporting of research results, the ability to compare and draw conclusions across studies will increase. With regard to my research framework, I focused on five context related moderators; I additionally tested whether three methodological moderators, i.e. differences in measurement of the independent and dependent variable, time of publication and consideration of time lagged effects, significantly moderate effect sizes. Consequently, this study is limited in how much it adds to an understanding of the extent to which other methodological differences in research design account for differences in effect sizes.

2.7 Implications for Future Research 2.7.1 Key Moderator Variables While this framework of moderator variables helps to resolve many prior conflicting findings surrounding the internationalization-performance relationship, a substantial amount of performance variance remains unexplained, as none of the subsamples for moderator analysis fulfilled the 75 percent rule for population homogeneity. Clearly there is no universal internationalization-performance relationship; therefore future research should no longer look for generalizations, but instead develop finer grained models, i.e., investigate the conditions under which internationalization might be fruitful. Of course, the set of moderators I investigated should not be considered an exhaustive enumeration of all possible moderator variables. Beside R&D intensity, product diversification, country of origin, firm age, and firm size, other contextual settings such as industry sector and competition, and exchange rate fluctuations might have a significant impact on effect sizes as well. Hansen and Wernerfelt (1989) and Powell (1996) have pointed to another promising avenue. They showed that differences at the company level count for twice as much in performance differ-

54

The Effect of Context

ences as uncontrollable external environmental factors. Therefore, future research should take a closer look at how strategic action variables such as market knowledge, composition of senior management and incentive systems, and differences in the internationalization process itself contribute to performance differences attributable to internationalization. Contextual research appears to be a promising start for a better understanding of the nature of the internationalization-performance relationship. In chapter three I will follow up this conception and will more closely investigate the moderating impact of one seemingly especially important construct – intangible resources.

2.7.2 Understanding Contextual Interdependencies Given that the focal relationship is highly context dependent, we need to better understand how different moderator variables interact with each other. This can be exemplified by my joint analysis of firm age and firm size. The range in average effect sizes from r = .40 for young and large firms to r = -.05 for old and small firms points to the fact that internationalization might not be a valuable option for any firm. Nevertheless, an investigation how firms might best try to benefit from both effects – low firm age and large firm size – i.e. staying flexible while trying to maximize profits from resource availability – cannot be answered in this work. While I think that this question is of elementary managerial relevance in the context of internationalization and firm performance it must be left for future inquiry. Due to a lack of data, I was not able to perform further hierarchical analyses on the basis of the meta-analytic methods developed by Hedges and Olkin (1985), such as an investigation of performance gains attributable to the interaction of R&D intensity and level of product diversification. Although the magnitude of the effect size offers some evidence on the potential impact of a moderator, investigations on interaction effects aiming to develop knowledge about how firms solve oppositional pressures would be very useful. The set of moderator variables developed in this study might be a good starting point for further inquiry, as all of the variables significantly influence effect sizes. Noteworthy is that country of origin, firm age, and size are not causal factors in and of themselves. Considering the variety of constructs they may approximate, researchers should ideally collect the underlying constructs of interest more specifically in the future. While imprecise constructs with limited relevance to managerial

Implications for Future Research

55

actions may be easier to collect, they will continue to hinder our understanding of the roots that ultimately shape the internationalization-performance relationship.

2.7.3 Non-Linearity In recent years empirical results have indicated that remodeling the curve type of the internationalization-performance relationship might explain additional variance in performance differences. Yet to date researchers disagree on the exact shape of the curve. As meta-analysis assumes linearity I could not account for differences in the internationalization-performance relationship across different degrees of internationalization within the bounds of meta-analysis. However, at the meta-level I was able to perform regression analysis testing for both quadratic and cubic curve types. In order to test for curvilinearity of the overall relationship, i.e. quadratic or cubic relationship, I centered the independent variable (degree of internationalization) and calculated a regression analysis of the effect size of the internationalization-performance relationship on average sample degree of internationalization (Sturman, 2003). I conducted this analysis with a subset of studies that report uniform operationalizations of the independent variable (i.e. foreign sales to total sales and number of foreign countries). The test for curvilinearity of the relationship reveals mixed results. A comparison between linear, quadratic, and cubic curve types indicates that a linear curve type arguably best reflect the regression slope of foreign sales to total sales on effect size estimates ('R2 = .11, F(1,14) = 1.64, p = .22, see Table 2.8). When it comes to the number of foreign countries an inverted u-shape curve type is the best approximation for the regression slope ('R2 = .35, F(1,10) = 5.37, p < .05). However, these propositions should be treated with caution. First, the results for the foreign sales to total sales measure are not supported at a statistically significant level. Second, this analysis is based on studies with samples from different countries. An analysis at this aggregate level might not be able to capture differences in the curve type by nationality. Indeed, the meta-analytic findings of significantly different effect sizes for American, European, and Japanese firms provide support for the contention

56

The Effect of Context

Table 2.8 Shape of the Internationalization-Performance Relationship R2

Model Foreign sales to total sales Linear Quadratic Cubic

Number of foreign countriesb Linear Quadratic Cubic a b

2

'F

.112 .117 .126

.112 .005 .009

.003 .351 .370

.003 .348 .019

'R

df1

df2

p

1.64 .07 .12

1 1 1

14 13 12

.22 .80 .74

.03 5.37 .27

1 1 1

11 10 9

.87 .04 .62

a

Analysis based on K = 16 samples, N = 1,574. Analysis based on K = 13 samples, N = 2,777.

that there appear to be strong boundary conditions which put the existence of a universalistic shape of the internationalization-performance relationship across company nationalities into question (Ruigrok and Wagner, 2003; Ruigrok, Wagner, and Amann, 2004; Ruigrok, Amann, and Wagner, 2007). For example, it might be proposed that a positive linear relationship between internationalization and performance may be achievable for firms pursuing culturally related strategies but not for companies following culturally unrelated internationalization strategies; or it could be argued that both are able to experience a positive linear form of the internationalization-performance relationship, but the likelihood to do so will be contingent upon the development of different intra-company capabilities (Wagner, 2001). Given these limitations of an analysis based on meta-analytic data I will elaborate on this issue thoroughly in the following chapter for a sample of German firms.

2.8 Conclusions This chapter makes two major contributions to the literature. My first aim was to synthesize the prior fragmented and contradictory findings on the direction and magnitude of the internationalization-performance relationship. I found solid evidence that internationalization and firm performance show a statistically significant correlation, although this relationship is low in magnitude.

Conclusions

57

Second, I explored the existence of moderator variables. The results show that the internationalization-performance relationship is indeed context dependent. Based on extant theory, I extracted five context related variables: R&D intensity, product diversification, country of origin, firm age, and firm size, all of which significantly moderate effect sizes. These variables constitute major determinants of success in the research domain of internationalization. Hence future research should view them as moderator or control variables to be taken into consideration in every single study. In addition, my results provide empirical evidence as to what constitutes a ‘typical,’ ‘large,’ or ‘small’ effect size of the internationalization-performance relationship in selected research situations. Consequently, researchers now have a reference of effect sizes against which to compare and evaluate their own research. Figure 2.3 depicts the results of this meta-analysis for the effect of methodological differences and for the five hypotheses on the role of contextual moderators of the internationalizationperformance relationship. Although this meta-analytical review takes an important step towards solving many apparent contradictions, the results provide evidence that we have only just reached the starting point for future inquiries. Theory building and empirical investigations in search of further theoretically based and methodological contextual factors and their interactions might yield valuable insights into the nature of the internationalization-performance relationship. In the following two chapters I will therefore analyze in more detail, (1) which intangible resources act as moderators of the focal relationship, (2) why they offer potential for internationalization success and (3) how they contribute to superior firm performance.

58

The Effect of Context

Figure 2.3 Key Findings from Meta-Analysis on Internationalization and Performance Sales-oriented

Asset-oriented

Degree of Internationalization

R&D Intensity

(+)

Product Diversification

(-)

(+A, +E, oJ)

Country of Origin

(-)

Firm Age

(+)

Firm Size

Firm Performance

Return-oriented

Notes: (+) Significant positive relationship. (-) Significant negative relationship. (o) No significant relationship. A America E Europe J Japan

Growth-oriented

Capital market-or.

Endnote

59

Endnote 1. In parentheses: The number of studies included in the meta-analysis from the respective journal. Studies of the meta-analysis – in order that all citations show up in the reference section (Aggarwal, 1979; Siddharthan and Lall, 1982; Buhner, 1987; Grant, 1987; Geringer et al., 1989; Sambharya, 1995; Bloodgood et al., 1996; McDougall and Oviatt, 1996; Qian, 1996; Simmonds and Lamont, 1996; Tallman and Li, 1996; Gomez-Mejia and Palich, 1997; Hitt et al., 1997; Wan, 1998; Delios and Beamish, 1999; Gomes and Ramaswamy, 1999; Harveston et al., 1999; Geringer et al., 2000; Knight, 2000; Zahra and Garvis, 2000; Zahra et al., 2000; Chen and Martin, 2001; Lu and Beamish, 2001; Mauri and Sambharya, 2001; Dragun, 2002; Qian, 2002; Qian and Li, 2002; Capar and Kotabe, 2003; Dhanaraj and Beamish, 2003; Goerzen and Beamish, 2003; Hsu and Boggs, 2003; Majocchi and Zucchella, 2003; Qian and Li, 2003; Ruigrok and Wagner, 2003; Wan and Hoskisson, 2003; Lu and Beamish, 2004)

60

The Effect of Context

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Barkema, H.G. and Vermeulen, F. (1998) 'International Expansion through Start-up or Acquisition: A Learning Perspective', Academy of Management Journal 41(1): 7-26. Barney, J.B. (1991) 'Firm Resources and Sustained Competitive Advantage', Journal of Management 17(1): 99-120. Benvignati, A.M. (1987) 'Domestic Profit Advantages of Multinational Firms', Journal of Business 60(3): 449-461. Bettis, R.A. and Hall, W.K. (1982) 'Diversification Strategy, Accounting Determined Risk, and Accounting Determined Return', Academy of Management Journal 25(2): 254-264. Biggadike, R.E. (1979) 'The Risky Business of Diversification', Harvard Business Review 57(3): 103111. *Bloodgood, J.M., Sapienza, H.J. and Almeida, J.G. (1996) 'The Internationalization of New HighPotential U.S. Ventures: Antecedents and Outcomes', Entrepreneurship: Theory & Practice 20(4): 61-76. Boddewyn, J.J. (1988) 'Political Aspects of MNE Theory', Journal of International Business Studies 19(3): 341-363. Brewer, H.L. (1981) ' Investor Benefits from Corporate International Diversification', Journal of Financial and Quantitative Analysis 16(1): 113-124. Brewer, T.L. (1992) 'An Issue-Area Approach to the Analysis of MNE-Government Relations', Journal of International Business Studies 23(2): 295-309. Brush, C.G. (1995) International Entrepreneurship: The Effects of Firm Age on Motives of Internationalization, Garland: New York. Brush, C.G. and Vanderwerf, P.A. (1992) 'A Comparison of Methods and Sources for Obtaining Estimates of New Venture Performance', Journal of Business Venturing 7(2): 157-170. Buckley, P.J. and Casson, M. (1976) The Future of the Multinational Enterprise, Macmillan: London. Buckley, P.J., Dunning, J.H. and Pearce, R.D. (1977) 'The Influence of Firm Size, Industry, Nationality, and Degree of Multinationality in the Growth and Profitability of the World's Largest Firms', Weltwirtschaftliches Archiv 114: 243-257.

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Chapter 3 Intangible Resources and their Effect on the Internationalization-Performance Relationship

3.1 Introduction Meta-analytic evidence from chapter two strengthens the notion that a generally applicable form of the internationalization-performance relationship does not exist but that this relationship is highly context dependent. Two lines of inquiry can be distinguished in contemporary research that are based on such an understanding. One investigates performance consequences from varying degrees of internationalization while the other discusses firm specific differences as decisive factors that might be responsible for differences in the internationalization-performance relationship (Lu and Beamish, 2004). The first research stream examines the benefit-cost trade-off from internationalization. A fundamental statement is that this trade-off is not constant but varies along the internationalization continuum. Consequently there must be one (or several) optimal degree(s) of internationalization for every firm. Following this rationale scholars have tried to merge empirical findings of either a positive or a negative linear effect of internationalization on performance by remodeling the shape of this relationship. As already outlined in the introduction section of this book, results vary from u-shaped curve types to inverted u-shaped curve types and cubic curve types. But until now, there is no consensus on a universal form of the internationalization-performance relationship. Ruigrok, Wagner, and Amann (2004) propose that the shape of the

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relationship itself is context related, depending on the size of the home market and the possibility to pursue a cultural or institutional related kind of international expansion. The second research stream proposes that firm level characteristics constitute a major distinguishing feature if and how internationalization relates to firm performance. This line of research can be traced back to Hymer (1976) who identified firm specific advantage as a driver of internationalization and Dunning (1979) who refined the idea of Hymer by examining different kinds of production inputs that can lead to the growth of the MNC. Later on, scholars of the resource based view characterized intangible resources as major drivers of success in markets, as they accord to the VRIN1 criteria (Bloodgood, Sapienza, and Almeida, 1996). In their seminal work Morck and Yeung (1991) confirm this notion and assert that internationalization per se is not a valuable strategy for investors, whereas the impact of R&D spending and advertising expenditures on market value increases with a firm’s multinational scale. Other researchers like Christophe (1997) did not find empirical support for this proposition and doubt the generalization of the positive impact of intangible resources on success when expanding business abroad. In order to understand more fully the nature of the internationalization-performance relationship and resolve apparent contradictory empirical evidence more empirical research is advisable, particularly on samples beyond those from the US and across different periods of time. Therefore, this chapter addresses the question how internationalization relates to firm performance for a sample of publicly listed German firms. Specifically, the present chapter seeks to give answers to the following two research questions: (1) How does the shape of this relationship vary across different degrees of internationalization? And (2) how is the relationship between internationalization and firm performance moderated by intangible resources?

3.2 An Inquiry into a Non-Linear Internationalization-Performance Relationship 3.2.1 Previous Inquiries into a Non-Linear Relationship Studies in the 1970s emphasized the benefits of internationalization and thus hypothesized a linear positive relationship between the degree of internationalization and firm performance; however researchers in the 1980s and 1990s acknowledged that internationalization can be subject to risk and failure, thus recognizing possible

An Inquiry into a Non-Linear Internationalization-Performance Relationship

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drawbacks to success in internationalization. As a result of these divergent findings, researchers began to examine the benefit-cost trade-off of internationalization and its variations along the internationalization continuum in search for an ‘internationalization threshold’ (Geringer, Beamish, and DaCosta, 1989; Gomes and Ramaswamy, 1999). These scholars have tried to reconcile controversy empirical findings, i.e. those of positive or negative significant linear effect sizes, by remodeling the shape of this relationship. Significant findings vary from u-shaped curve types to inverted u-shaped curve types. But until now there is no consensus on a universal form of the internationalization-performance relationship. Empirical findings are even more diverse. The assertion of non-linearity is challenged by empirical studies that tested for but could not confirm a curvilinear relationship (Tallman and Li, 1996; Hsu and Boggs, 2003; Wan and Hoskisson, 2003). More recently, the debate on the shape of the relationship between internationalization and performance has received increased attention again. This is mainly due to the results of empirical studies that make use of new models. While previous empirical research has largely relied on linear or, in some cases, quadratic models, now several authors have postulated a so-called ‘3-stage theory’ based on a sigmoid model. This model has quickly established itself in the literature as a benchmark model. Its proponents claim that the 3-stage theory can be interpreted as a ‘general theory’, i.e. a theory that encompasses other attempts to model the relationship between firm internationalization and performance. However, even among these studies differences in patterns are notable. For instance, while Contractor, Kundu, and Hsu (2003), Lu and Beamish (2004), Thomas and Eden (2004), and Ruigrok, Amann, and Wagner (2007) report a horizontal s-shaped relationship, the sequence of the slopes reported by Thomas and Eden as well as Ruigrok et al. is quite opposite to the earlier two studies. The rationales underlying the different slopes are described in detail in the course of deriving hypothesis one in section 3.2.4. Table 3.1 depicts the range of findings of selected empirical studies on the shape of the internationalization-performance relationship. The pioneers of the 3-stage theory – consciously or not – base their arguments about the curve type patterns on idiosyncratic home market characteristics of their respective samples and therefore ignore the possibility that the shape of the relationship itself is context related, depending on the size of the home market and the proximity to neighboring markets (in terms of culture, language, economic development, etc.). Therefore I will in more detail review the benefit-cost trade-off associated with

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Table 3.1 Selected Empirical Studies on the Relationship between Internationalization and Firm Performance

Positive Relationship

Linear No Relationship

Negative Relationship

Author (s), and year

Author (s), and year

Author (s), and year

Vernon, 1971 Errunza and Senbet, 1984 Kim and Lyn, 1986 Buhner, 1987 Grant, 1987 Daniels and Bracker, 1989 Kim, Hwang, and Burgers, 1989 Han and Lee, 1998

Buckley, Dunning, and Pearce, 1977 Haar, 1989 Morck and Yeung, 1991

Brewer, 1981 Siddharthan and Lall, 1982 Kumar, 1984 Michel and Shaked, 1986 Chang and Thomas, 1989 Collins, 1990 Ramaswamy, 1992

U-Shaped

Curvilinear Inverted U-Shaped

Sigmoid / Cubic

Author (s), and year

Author (s), and year

Author (s), and year

Lu and Beamish, 2001 Capar and Kotabe, 2003 Ruigrok and Wagner, 2003

Hitt, Hoskisson, and Kim, 1997 Gomes and Ramaswamy, 1999 Zahra and Garvis, 2000 Qian, 2002

Riahi-Belkaoui, 1998 Contractor, Kundu, and Hsu, 2003 Lu and Beamish, 2004 Thomas and Eden, 2004 Chiang and Yu, 2005 Ruigrok, Amann and Wagner, 2007

internationalization and develop a coherent model for the shape of the internationalization-performance relationship in a German context throughout the following sections.

3.2.2 Benefits of Internationalization Analysis of relevant studies shows that two research streams in particular seem to have the strongest explanatory power for internationalization benefits: (1) Theories of market imperfection, and (2) theories of firm specific advantage. Originally these established theories aim to explain when, where and how a firm would go international. Nonetheless, they imply theoretical mechanisms as to why a relationship to performance should exist. Both research streams imply the idea of efficiency, i.e. that internationalization enhances overall firm performance. The difference between them consists in the origin of determinants for superior firm performance from internation-

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alization. Factors located outside and inside a firm arguably determine advantages of international expansion. Theories relying on external factors aim to explain why multinational companies exist and postulate that market imperfections promote firms that internationalize (Caves, 1971; Morck and Yeung, 1998). Early research in this manner has been conducted by trade theorists and has focused on factor cost differentials that promote international trade due to the immobility of factors of production (Heckscher and Ohlin, 1991). By the mid 1960s scholars started to focus on the phenomenon of foreign direct investment by pointing out the potentials from internalizing international business activities in the face of market imperfections. Vernon (1966) postulates that products pass different stages of development and that firms would be able to exploit economies of scale by expanding operations abroad. Hymer (1976) developed his arguments on the basis of industrial organization theory and postulates that international firms could exploit local structural market imperfections in product, factor, and capital markets. In a similar vein location theory stresses arbitrage opportunities in factor cost differentials and therefore advantages from local sourcing and production (Tesch, 1980). Industrial organization theory more generally highlights such structural market deficiencies as entry barriers, which potentially enable firms to earn economic rents via exploitation of their international market power (Hamel and Prahalad, 1985). Other scholars have stressed the benefits from the internalization of markets for intermediate products and knowledge in the face of transactional market imperfection. If market imperfections favor internalization of activities over market transactions, multinational companies may benefit from transaction cost advantages (Coase, 1937; Williamson, 1975). The argument is put forth that potential costs emerge in market transactions due to adverse selection or moral hazard (Akerlof, 1970; Stiglitz, 1989). Multinational firms might increase their performance as they avoid these costs by substituting external markets by internal markets in the form of foreign direct investment. Furthermore, capital market theory puts an emphasis on diversification advantages from internationalization (Markowitz, 1952; Rugman, 1976) and postulates the superior risk-return performance of multinational firms. Theories of firm specific advantage adopt a more managerial perspective and focus on the organization’s internal setting. In this view the main source of benefits from internationalization stems from a proactive creation and exploitation of firm specific advantage. Internationalization of activities holds benefits such as the utilization of relationships among different businesses and geographic areas (Porter, 1985).

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Therefore the multinational company can be an effective means to transfer superior resources to foreign markets (Bloodgood et al., 1996). Similarly, the resource based view of the firm proposes that the possibility of global dispersion of core competencies generates economic rents and fosters the development of new knowledge (Hamel, 1991; Barkema and Vermeulen, 1998). Internationalization enables firms to tap otherwise locked resource pools and offers unique opportunities for the proactive creation of new resources. The learning theory (Johanson and Vahlne, 1977) views internationalization as an incremental process that fosters organizational learning and knowledge development (Hamel, 1991; Barkema and Vermeulen, 1998) not available to domestically operating firms. Through gradual acquisition, integration, and use of knowledge about foreign markets the internationalization process offers the opportunity to gain a competitive advantage over less internationally active competitors. Table 3.2 summarizes the different theoretical perspectives of internationalization benefits.

Table 3.2 Theoretical Perspectives and Performance Drivers of Internationalization Theoretical Perspective

Author(s)

Performance Drivers of Internationalization

Product Life Cycle

Vernon, 1966

Economies of scale

Industrial Organization

Caves, 1971; Hymer, 1976

Exploitation of structural market imperfections

Transaction Cost Economics

Buckley and Casson, 1976; Hennart, 1982

Overcoming transactional market imperfections

Financial Economics

Markowitz, 1952; Rugman, 1976

Improvement of risk-return profile

Resource Based View

Barney, 1991; Peteraf, 1993; Amit and Schoemaker, 1993

Leverage of unique and firm specific resources

Organization Learning

Johanson and Vahlne, 1977; Ruigrok and Wagner, 2003

Learning curve effects, know-how transfer

3.2.3 Costs of Internationalization While early research within the field of international business solely emphasized the benefits of internationalization, scholars started to consider costs associated with internationalization that might, at least partly, offset the gains from going international by the 1980s. Theories of foreign direct investment assume that monopolistic advan-

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tages are necessary because multinational firms will encounter the so-called ‘liabilities of foreignness’ (Zaheer, 1995; Kostova and Zaheer, 1999). The learning theory assumes that the complexity of managing widespread business units increases with heterogeneity in markets, resulting in cross-cultural complexity (Siddharthan and Lall, 1982). Cross-cultural studies posit that geographical dispersion and cultural diversity of business activities lead to communication, coordination, and motivation problems (Hofstede, 1980). Organizational ecologists emphasize the cost of organizational change induced by the implementation of a radical shift in strategy, such as internationalization. These costs are rooted in the structural inertia of a firm and are manifested in sunk costs of non-transferable assets, costs of resource reallocation and firm internal political resistance towards change (Hannan and Freeman, 1984). Scholars of transaction cost theory (Williamson, 1975; Jones and Hill, 1988) and agency theory (Roth and O´Donnell, 1996) illustrate how growing complexity may eventually exhaust managerial capacity. Firms face organizational constraints such as absorptive capacity (Cohen and Levinthal, 1990) or the difficulty and expense of processing large amounts of information (Cohen and Levinthal, 1990). Internalization theory recognizes limits to the efficiency of organizational arrangements. Increasing transaction costs come along with higher diversity of foreign environments due to information asymmetries, asset specificity, and the potential for opportunistic behavior. Furthermore, internationalization increases the exposure to financial and political risks such as currency fluctuations, government regulations, and trade laws (Boddewyn, 1988; Brewer, 1992; Sundaram and Black, 1992; Reeb, Kwok, and Baek, 1998). Table 3.3 summarizes the different theoretical perspectives of internationalization costs.

3.2.4 Synthesis and Hypothesis A commonality among the above mentioned theories is that they treat either benefits or costs from internationalization as constant across different degrees of internationalization. More recently researchers have begun to recognize that certain kinds of costs are associated with specific stages of a firm’s internationalization process. The pioneers of the s-curve hypothesis (Contractor et al., 2003; Lu and Beamish, 2004) developed their conceptual framework in an attempt to reconcile and synthesize

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Table 3.3

Intangible Resources as Moderators

Theoretical Perspectives and Cost Drivers of Internationalization

Theoretical Perspective

Author(s)

Cost Drivers of Internationalization

Cultural Diversity

Hofstede, 1980; Siddhartan and Lall, 1982

Communication, coordination and motivation problems

Organizational Ecology

Hannan and Freeman, 1984

Organizational inertia

Transaction Cost Economics

Coase, 1937; Williamson, 1975

Transaction costs (information asymmetry, asset specificity)

Principal-Agent Theory

Jensen and Meckling, 1975

Agency costs (opportunism), governance costs

Political Science

Boddewyn, 1988; Brewer, 1992

Bargaining costs, risk of expropriation

prior findings of a u-shape curve type pattern and inverted u-shape curve type pattern. They propose that internationalizing firms face a performance downturn at the initial stage of internationalization because of barriers like liabilities of foreignness and newness (Zaheer, 1995; Kostova and Zaheer, 1999). After this first stage of internationalization firms enter a stage where benefits from internationalization prevail until they come into a third stage where escalating costs of complexity (such as limited managerial capacity or cultural diversity) erode the positive performance impact of internationalization. Two remarks are noteworthy that may limit the generalizability of this framework. First, as already pointed out in chapter two, ‘country of origin’ determines the benefits and costs and their trade-off associated with international expansion at a macro level. Consequently, a hypothesis of which curve type best reflects the internationalization-performance relationship in a German setting should take into account the heterogeneity of different countries as a starting point. Specifically as Ruigrok et al. (2007) have pointed out, the assumptions underlying the s-curve hypothesis appear particularly valid for companies that meet the following conditions: (1) Relatively large home market, (2) without larger similar neighboring markets, and (3) not part of a wider economic union. Second, the original s-curve hypothesis is – at its core – a fairly deterministic approach. Liabilities of foreignness outweigh benefits from internationalization only at low degrees of internationalization, and firms are doomed to diminishing performance once they have passed a certain level of internationaliza-

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tion, irrespective of their organizational configuration of international business activities. As regards the first remark, the first investigations of the s-curve hypothesis in fact relied on samples that fit the criteria set by Ruigrok et al. (2007) quite well. Contractor et al. (2003) used an international dataset of 103 service companies with 606 firm year observations taken from the ‘Directory of the World’s Largest Service Companies’ of which 42 percent were headquartered in the US. Lu and Beamish (2004) draw their results from a dataset of 1.489 Japanese firms. When investigating a German setting one has to take into consideration commonalities and differences of relevant home country characteristics as opposed to these studies. What these settings have in common is that Germany is among the largest economies in the world as well. What makes this setting different is that the German economy is more internationalized than the Japanese and US economies and that it is integrated into the single European market. German companies thus can draw on a wider international economic union with consistent institutional arrangements and uniform business regulations at the initial phase of internationalization. In addition, Germany has two close cultural and linguistic neighboring countries, Austria and Switzerland which might facilitate the initial foreign market entry for German firms there. Higher similarity to neighboring countries augments performance gains without incurring high reconfiguration costs. Irrespective of this proposition I would not want to argue that German firms face less cultural disaccords when doing business in France for example than a US based firm would encounter when doing business in the United Kingdom. However, as a result of the integrated single European market the initial learning costs particularly with regard to foreign institutional and regulatory settings might not necessarily constitute key internationalization hurdles at low degrees of internationalization any more. Therefore German firms will experience increasing performance at low degrees of internationalization. Nevertheless, as firms reach beyond a certain level of internationalization, reconfiguration costs might eventually depress firm performance. However, the notion that this performance downturn is irreversible is at odds with research suggesting the existence of ample benefits for firms that are internationally diversified into culturally heterogeneous markets. In such a process, it is conceivable that managers will look for new organizational solutions or relevant experience of other companies to match – at least to some extent – the new environmental requirements (Bartlett and Ghoshal, 1989). Hitt, Hoskisson, and Kim (1997) for example, argue that cognitive inputs from

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a culturally diverse workforce are essential for innovation and technological progress. Firms capable of transferring or generating intangible resources across a variety of cultural environments may obtain the most valuable internationalization benefits. Certainly, as Wagner (2001) points out, in contrast to initial benefits from internationalization such as economies of scale, benefits at higher degrees of internationalization and in multiple diverse markets must be proactively generated and managed. As noted before, this might require that firms have to be fundamentally reconfigured, concomitantly increasing costs. Following Bartlett and Ghoshal (1989) and Prahalad and Doz (1987) this means that firms would shift their strategic orientation from international (culturally related) to transnational (culturally unrelated). Reflecting this line of argument I expect that the curve type pattern that best fits the internationalization-performance relationship is depending on idiosyncratic home market characteristics. Figure 3.1 graphically depicts the hypothesized relationship. In a German setting the original proposition of the s-curve is shifted to the right, preceded by an initial stage of increasing performance. Furthermore, firms are not doomed to declining performance at a certain level of internationalization, but managers can proactively shift existing thresholds. Therefore I hypothesize: Hypothesis 1.

The relationship between internationalization and performance exhibits a sigmoid curve type pattern with increasing performance at low levels of internationalization, an upper-bound and a subsequent lower-bound inflection point at growing degrees of internationalization.

Figure 3.1 Sigmoid Internationalization-Performance Relationship Performance

Degree of Internationalization

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3.3 The Moderating Impact of Intangible Resources Although hypothesis one about the shape of the internationalization-performance curve should hold in general, the slope could vary across firms. Intangible resources are an important dimension that might moderate the performance consequences from any internationalization strategy. Indeed, I found meta-analytic evidence in chapter two confirming that technological know-how is an important moderator variable in the domain of internationalization and firm performance. But until now, knowledge about which intangible resources actually have an impact on internationalization success and why they do so is limited. Although the firm-specific intangible resource is a central construct in internalization theory and in the eclectic paradigm by Dunning, it has commonly been treated as unidimensional. Only recently has an attempt been made by Rugman and Verbeke (2003) to refine the concept of firm-specific intangible assets (or advantages). Specifically they distinguish between location bound and non-location bound firm-specific and country-specific advantages. Given that intangible resources arguably are a central construct within the relationship between internationalization and firm performance, a more thorough understanding of their role is crucial for an advancement of research. Hence, in the following section I will investigate (1) if and why intangible resources moderate the internationalization-performance relationship and (2) if particular dimensions of intangible resources contribute to differing performance outcomes.

3.3.1 Theoretical Background Arguably the most influential theory for an explanation of the motivation for foreign direct investment is internalization theory which has its roots in the Coasian transaction cost theory (Coase, 1937) and the theory of the growth of the firm by Edith Penrose (Penrose, 1959). Internalization theory establishes the ‘raison d’être’ for foreign subsidiaries and hence the multinational company. Essentially, internalization theory proposes that intangible resources such as superior production skills, management talent, consumer goodwill, or valuable trademarks are information sensitive and therefore their transaction is subject to market failure (Caves, 1982). In order to benefit from an exploitation of these resources the transaction of these resources must be internalized. Consequently, foreign direct investment is a promising strategy to leverage the value from intangible resources and gain from economies of scale and scope as long as the gains generated by these resources are sufficient to compensate

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for the higher costs of operating internationally. The central role of firm-specific intangible resources indicates that internalization theory is by and large equivalent to the resource or knowledge based view of the firm within the context of international business (Rugman and Verbeke, 2003). Dunning’s eclectic paradigm extends on this theory. He synthesizes internalization theory with other theories of foreign direct investment and suggests that, in addition to intangible resources and internalization benefits, location advantages also facilitate a firm’s internationalization benefits because of unique market opportunities and country-specific endowments (Dunning, 1980, 1988). The majority of empirical literature so far has supported the appropriability regime-based rationale of internalization theory (Delios and Beamish, 1999; Kotabe, Srinivasan, and Aulakh, 2002; Lu and Beamish, 2004) (see also chapter two on the effect of R&D intensity). In their pioneering empirical work in the late 1970s, Morck and Yeung (1991) conclude that multinational activity leads to enhanced firm value only because it allows the MNC to exploit its intangible resources on a larger scale. They find no evidence to support what they refer to as the ‘managerial objectives’ or the ‘tax avoidance and low cost inputs theory’ which would have suggested that performance consequences from internationalization are mainly determined by external factors. But the universality of this notion was challenged later on by Christophe (1997) who attributed the positive performance impact of intangible assets on internationalization to a specific period of investigation. In the late 1970s firms faced low exchange rate volatility. As the exchange rates became more volatile in the 1980s the picture changed. The performance impact of intangible resources for internationalizing firms became marginal in comparison to that of other situational factors. Moreover Hsu and Boggs (2003) found for a sample of 118 large US multinational companies that spending on R&D as a measure of technological know-how had a significantly negative impact on ROE. One potential shortcoming of prior research in this domain is the measurement of the construct of intangible resources. Researchers have used a diversity of proxies, with spending on R&D and advertising among the most common ones (e.g. Siddharthan and Lall, 1982; Morck and Yeung, 1991; Delios and Beamish, 1999; Lu and Beamish, 2001; Kotabe et al., 2002; Qian, 2002; Lu and Beamish, 2004; Thomas and Eden, 2004; Annavarjula, Beldona, and Sadrieh, 2005). Although these accounting

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measures are comparatively easy to collect, they only capture part of the intangible resource base of a firm. Tobin’s q has been proposed as an alternative measure (Villalonga, 2004). This ratio captures the intangibility of a firm’s resource base – or resource intangibility – as a whole. It is calculated as the ratio of a firm’s market value to the replacement cost of its assets. The market value of a firm is made up of the value of its tangible and intangible assets. The fair value of a firm’s tangible resources can be estimated as the replacement cost of these assets – the current cost of purchasing assets of equal productive capacity. The value of a firm’s intangible resources can be determined as the difference between the market value of a firm and the value of its tangible resources (Villalonga, 2004). The assumption of this concept of measuring the intangibility of a firm’s resource base is that investors take into account and evaluate the whole stock of intangibles as a bundle when they make investment decisions. If markets are efficient, securities prices provide the best estimates of the value of a firm’s resources (Fama, 1970). When markets can be assumed to be efficient in the aggregate, there is no reason to expect a systematic bias from this calculation in large cross-sectional samples. Empirically, Lev (2001) demonstrates that Tobin’s q proxies the intangible resources of a firm as a result of the accounting treatment of intangibles. Tangible assets can be capitalized, i.e. recognized as assets and reported in a firm’s balance sheet. In contrast, intangibles are generally expensed, i.e. written off in the income statement in the period when costs for their development occur. As a result, the book value of assets does not reflect the stock of intangibles from cumulative investments whereas market value does. Therefore, Tobin’s q is arguably the most comprehensive measure for the intangible resources of a firm and a superior measure for a general assessment of the role of intangible resources with respect to the internationalization-performance relationship. Following the propositions brought forward by the internalization theory I hypothesize: Hypothesis 2.

Intangible resources measured by Tobin’s q moderate the relationship between internationalization and firm performance, such that high resource intangibility increases the performance gains attributable to internationalization.

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3.3.2 A Hedonic Approach to the Concept of Intangible Resources Hypothesis 2, if empirically supported, may be subject to the alternative interpretation that Tobin’s q is simply capturing investor expectations of additional future growth opportunities or higher persistence of profits of firms that already operate successfully internationally. Furthermore, if this is the reason for the association, then the causal direction of hypothesis two might be opposite to the one proposed, i.e. it could be described as: ‘The stronger the relationship between internationalization and performance, the higher the intangibility of the resource base.’ I address the possibility of an alternative interpretation in that I apply a slightly different approach of measuring the combined impact of different dimensions of intangible resources, the so-called hedonic approach. This approach is derived from hedonic pricing models2. The basic concept is that the observable prices of different varieties of a good can be attributed to its various components or quality characteristics. Hedonic regression is typically used to estimate the marginal contribution of these individual characteristics. For example, in the case of digital cameras, a hedonic approach would require a function that estimates the prices of cameras based on certain quality measures, such as number of pixels, storage size, manufacturer reputation, size, etc. (Manninen, 2005). The obtained regression coefficients can then be interpreted as the marginal variation of the price of the product if the explaining variable changes by one unit. I restrict my measure of resource intangibility from Tobin’s q to the predicted value from the regression of Tobin’s q on several measures of intangibles that are available from accounting data. I will refer to this measure as hedonic q. Under the hedonic approach, any factor that could affect investors’ expectations other than the specific intangible resources considered remains in the disturbance of the regression and out of the main equation (Villalonga, 2004). In analogy with hypothesis two I propose: Hypothesis 3.

Intangible resources measured by hedonic q moderate the relationship between internationalization and firm performance, such that high resource intangibility increases the performance gains attributable to internationalization.

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3.3.3 The Multidimensional Nature of Intangible Resources While prior research has used a variety of constructs, all termed ‘intangible resources’ to test the propositions put forward by internalization theory, their universal representativeness for the different dimensions of intangible resources remains doubtful. In fact, such an assumption would run counter to the original paradigm of the resource based view of the firm that accentuates the idiosyncratic nature of different resources (Wernerfelt, 1984; Dierickx and Cool, 1989; Barney, 1991; Peteraf, 1993). Although undeniably numerous resources can be identified that positively influence performance (for a comprehensive review see Newbert (2007)), not all of them might hold ‘internationalization potential’. With this term I refer to the supposition that the differing attributes of intangible resources determine if and why certain categories of intangibles enhance the performance impact of internationalization and how they do so. Not only may the appropriability regimes or isolating mechanisms differ by which intangibles contribute to superior firm performance, but – maybe even more important – resources differ with respect to their potential for transferability, i.e. the value of resources is more or less location bound. Indeed, it was not until recently that international business scholars started to consider this phenomenon. Rugman and Verbeke (2007) differentiate between firmspecific advantages that are location bound and others, that are non-location bound. From this distinction they derive their regionalization hypothesis, i.e. that some firms are capable of exploiting their firm-specific advantage worldwide while many others are not capable of doing so and are confined to their home region. Consequently a more differentiated approach might generate valuable and actionable knowledge on distinctive characteristics of intangibles that determine why intangibles exert an influence on the internationalization-performance relationship. In the following section I will derive the theoretical rationales and hypotheses as to why a moderating impact of certain intangible resources should exist. As already noted, a variety of resources have been proposed to affect firm performance. Therefore, the question arises how to structure or to categorize them. A proper classification would be helpful for the systematic assessment of the different roles of intangible resources with respect to the internationalization-performance relationship. Several classifications have been proposed in the literature. Bukh, Larsen, and Mouritsen (2001) compare various taxonomies of intellectual capital and conclude that despite of a vast ambiguity they all have three things in common: The connection

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(1) to employees, (2) to processes and structures, and (3) to customers. In another review of prior attempts to categorize intangibles Kaufmann and Schneider (2004, p. 377) conclude that most researchers confirm this classification of three categories. Nevertheless they summarize: “In the end, all these categorizations stay at a very abstract level. They do not offer direct guidance on the management of intangibles. Which goods and resources belong to each category is also not clear. Furthermore, the categories are usually quite broad.”

Recently, two more promising approaches have been developed by the Schmalenbach-Gesellschaft für Betriebswirtschaft (Schmalenbach Society for Business Administration) (2001) and the American Financial Accounting Standards Board (FASB, 2001). Both taxonomies are rooted in financial reporting and offer a more detailed classification, with more specific categories. The Schmalenbach group differentiates human capital, customer capital, supplier capital, investor capital, process capital, location capital, and innovation capital. The FASB system includes technology-based assets, customer-based assets, market-based assets, contract-based assets, workforce-based assets, organization-based assets, and statutory-based assets. Figure 3.2 compares the two categorizations and highlights overlaps. Figure 3.2 Categorization of Intangibles by the FASB and the Working Group ‘Intangible Assets in Accounting’ of the Schmalenbach Society FASB Categories Technology-based Assets Customer-based Assets

Working Group Schmalenbach Society Human Capital Customer Capital

Market-based Assets

Supplier Capital

Contract-based Assets

Investor Capital

Workforce-based Assets Organization-based Assets Statutory-based Assets Source: Kaufmann and Schneider (2004, p. 378).

Process Capital Location Capital Innovation Capital

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Strength of both of these reporting models is that they provide detailed examples which serve as guidelines for distinguishing the categories because they were developed for financial reporting purposes. However, one deficiency remains: The categories they propose are not mutually exclusive of each other as the Schmalenbach group concedes (FASB, 2001, p. 991): “Jeder immaterielle Wert ist mindestens einer dieser sieben Kategorien zuzuordnen, wobei einzelne immaterielle Werte möglicherweise mehreren Kategorien zugeordnet werden können, da die Kategorien nicht überschneidungsfrei sind. (Each intangible resource can be assigned to one of the seven categories at least. However, a particular intangible resource might as well be assigned to more than one category, because the categories are not mutually exclusive of each other”.

In conclusion it seems that for the time being there is no selective and singlestaged classification available for a categorization of intangible resources. However, as can be seen from the two classifications above, it is possible to distinguish systematically between several different facets of intangible resources after all in order to investigate whether the multidimensional nature of intangible resources leads to differing performance consequences from internationalization. In consequence I decide to rely on the FASB categorization as a starting point. The FASB approach seems particularly helpful because it offers a comprehensive classification, based on a parsimonious set of variables. It involves few overlaps among the categories and gives a more concrete and complete perspective on intangibles than prior classifications (Kaufmann and Schneider, 2004). When it comes to the formulation of testable hypotheses the questions arises if the relevant dimensions of intangible resources can be operationalized validly. To the authors knowledge no single piece of empirical research exists to date that comprehensively embraces all of the categories that have been articulated by the FASB or the Schmalenbach group. I could differentiate four classes of intangible resources for which an operationalization is feasible. These form the basis for my assessment of the differing impact of intangibles on the internationalization-performance relationship. They comprise (1) technological know-how, (2) market know-how, (3) contract-based know-how, and (4) top management team diversity and education. Although this classification also lacks the characteristics of mutual exclusiveness and comprehensive exhaustion it is capable of capturing the majority of the categories that have been proposed by the FASB. As an example contract-based intangible resources such as purchased brands or technology licensing agreements doubtlessly involve overlaps

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with internally generated market know-how or technological know-how with respect to their application within the value chain of the firm. However, these resources differ with regard to another fundamental aspect, i.e. their appropriability regimes. While technological know-how and market know-how can be developed internally, contractbased intangible resources must be externally acquired by definition. Already Schneider and Kaufmann (2004) refer to the importance of the origin of an intangible resource. According to these authors whether an intangible resource is developed internally or whether it is externally purchased implicates different strategies how to deploy it successfully. Therefore the separate treatment of externally purchased intangible resources can be justified in the course of this study’s analysis.

3.3.3.1 Technological Know-How The rationale why technological know-how should enhance the profitability impact of internationalization has already been discussed at length in chapter two. Technological knowledge is a function of the proprietary technological knowledgegenerating activities within a firm (Chatterjee and Wernerfelt, 1991). It includes product, service, or process know-how as the result of research and development activities and the value of this know-how is often embedded in the product or service itself. Upstream intangible resources such as technological know-how are non-location bound in principle, i.e. they offer potential to be transferred across national borders, and therefore such resources do not tend to deteriorate quickly when applied in multiple markets (Morck and Yeung, 1998). They often rather tend to appreciate, as knowledge and information are cumulative (Grossman and Helpman, 1994). Consequently, multinational companies may not only achieve economies of scale from the exploitation of their know-how in multiple markets, but they may benefit from exploration activities and realize economies of scope as well. This is especially true in cases where the international transfer of technological know-how is complemented by location bound elements, that is, linkages with external parties or learning capabilities that allow subsidiaries to reap the benefits from local responsiveness (Rugman and Verbeke, 2003). In sum, the different opportunities to exploit market imperfections in the trade of technological resources might give multinational companies a major competitive advantage over their competitors; consequently, internationalization should be a

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valuable option for firms with strong efforts in the generation of proprietary technological knowledge. Therefore I hypothesize: Hypothesis 4.

Intangible resources in terms of technological know-how moderate the relationship between internationalization and firm performance, such that high levels of technological know-how increases the performance gains attributable to internationalization.

3.3.3.2 Market Know-How Market know-how is the capability to analyze markets, develop plans to sell products or services, and eventually build and maintain brands. Brands constitute intangible resources that are rare and difficult to imitate because they are built through cumulative investments in marketing over time (Rossiter and Percy, 1997). Expenses for marketing may therefore in the long run constitute superior knowledge to serve customer needs, build up customer relationships, and eventually result in customer goodwill, i.e. the reputation for an outstanding product or service quality. While customers are location bound this knowledge is non-location bound in principle (Fang et al., in press.). Nevertheless, market based know-how intangible resources differ from technological know-how in that market know-how is located at the downstream side of the value chain. Consequently, a firm has to make considerable investments in order to create a critical mass for customer attention. Therefore, the transfer of its value across national borders is more challenging because of the timeconsuming nature of brand building in new geographic markets (Katsikeas, Samiee, and Theodosiou, 2006). The consequence of this is that marketing based resources that are built on marketing knowledge accumulated in a firm’s home country might be less valuable, at least initially, in foreign expansion than technological or experiential knowledge. However, the value of a brand is likely to increase over time. Even with the difficulty to transfer brands internationally, such transfer does occur. Some prominent global brands are well known to foreign consumers even though familiarity with the product itself (e.g. Mercedes, Levis, and Coke) may be lacking (Owen, 1993). The general and procedural knowledge how to bring added value to customer needs or how to fit the supply to special customer needs that is developed in one market might be successfully transferred to others. Therefore I posit:

90

Hypothesis 5.

Intangible Resources as Moderators

Intangible resources in terms of market know-how moderate the relationship between internationalization and firm performance, such that high levels of market know-how increase the performance gains attributable to internationalization.

3.3.3.3 Contract-Based Know-How Contract-based know-how comprises a rather multifaceted category of intangibles. It mainly includes acquired knowledge such as brands, patents, and licenses. Contract-based intangible resources fulfill the requirements for recognition of financial reporting standards and consequently must be acknowledged in books. In fact the definition of contract-based know-how by the FASB is based upon these recognition criteria for intangible resources. IFRS defines intangible assets under their standard IAS 383 that is similar to the definition by US-GAAP laid out in Accounting Principles Board (APB) 17. Both regulations specify specific rules for the recognition of intangibles and the obligation to subsequently capitalize these resources as assets in balance sheets. According to IAS 38, intangible assets are identifiable non-monetary assets without physical substance that are controlled by the enterprise. Another important recognition criterion is that future economic benefits are expected to accrue to the firm from these intangible assets. In addition it is not sufficient that these benefits are only possible but instead they must be probable. In practice this is a crucial distinction between self-created and externally purchased intangible resources (Villalonga, 2004). Only in cases where the intangible resource is acquired (separately or as part within a business combination) the standard setters admit that the probability criterion is always fulfilled. If assets satisfy these requirements then they comply as well with the basic requirements for intangible resources according to the internalization theory (Caves, 1971) or ownership advantages (Dunning, 1980). Firms may generate economies of scale from the transfer of these resources to multiple markets, one of the major performance drivers of internationalization. Therefore I contend: Hypothesis 6.

Intangible resources in terms of contract-based know-how moderate the relationship between internationalization and firm performance, such that high intangible intensity increases the performance gains attributable to internationalization.

The Moderating Impact of Intangible Resources

91

3.3.3.4 Top Management Team Demographics According to the upper echelon perspective the top management team (TMT) of a firm makes up the most important part of the human capital of a firm (Hambrick and Mason, 1984). Hence, demographic characteristics such as top management team international diversity or education might be important success factors in the internationalization of a firm and enhance the performance outcome of internationalization processes. The reason being that demographic characteristics can be used as proxies for more elusive psychological team processes, member traits and capabilities, such as cognitive capacity, communication fluency, or quality of decision making (Lawrence, 1997). Consequently it would be an all too simplistic approach to expect a direct relationship between TMT demographic traits and performance but it is more important to expand upon certain TMT capabilities, which ultimately have an impact on performance. Already Hambrick and Mason (1984) underline the importance of organization context in the research of TMT demographics. They assume that TMT characteristics have the strongest effects on performance and strategic choice under conditions of high uncertainty. Carpenter (2002) identifies TMT international background and educational background as important demographic traits in the domain of international management. The international background of firms’ key decision makers is expected to be related to the way they manage the internationalization activities of their firms (Fischer and Reuber, 2003). International background matters because it influences the formation of the firm’s ‘dominant logic’ (Bettis and Prahalad, 1995), an information funnel through which managers’ attention is filtered. Different experiential contexts are likely to result in the formation of different types of dominant logics, which will result in different decisions and actions on the part of decision makers (Boeker, 1997; Tyler and Steensma, 1998). A team composition displaying high group heterogeneity (e.g. diversity in the TMT cognitive base expressed through heterogeneity in nationality or age) has been found to be associated with high levels of creativity and innovation (Wiersema and Bantel, 1992) and might be suitable to help a TMT to “overcome information overload, complexity and domestic myopia created by complex business environments” (Carpenter and Fredrickson, 2001, p. 534). Diversity in TMT educational background and diverse viewpoints will lead to originality and creativity in TMT problem-solution capacity (Chatman et al., 1998), high quality decision making, increased capability of scanning the environment for

92

Intangible Resources as Moderators

information, and interpretation of possible action alternatives (Hambrick and Mason, 1984). In turn, this leads to efficient information-processing and more accurate predictions, e.g. with respect to a firm’s position in a specific strategic setting (Westphal and Fredrickson, 2001). All of these attributes might be specifically important for internationalization success. Internationalization typically involves a plurality of foreign markets. Top management team traits that help to handle additional complexity and uncertainty might constitute a valuable human resource in this context. In sum, such TMT demography characteristics as internationality or educational background can be characterized as intangible resources that determine team processes. I expect that higher international diversity and higher educational background of the TMT positively influence the performance impact of internationalization. Therefore, I hypothesize: Hypothesis 7.

Intangible resources in terms of top management team international diversity and education moderate the relationship between internationalization and firm performance, such that higher levels of diversity increase the performance gains attributable to internationalization.

3.4 Method 3.4.1 Sample The analysis is based on a sample of publicly listed firms from Germany over the five year time frame between 2001 and 2006. A German setting provides an appropriate sample to test the hypotheses as it offers the potential to analyze firms at different stages of their international expansion. With respect to the research questions at hand it is adequate to apply a single country design since the country of origin might seriously bias results (see chapter two for a discussion of the moderating impact of the country of origin). Germany plays an important role in international business. For years it has been known as world-wide leading country in exports. Many of Germany’s firms are among the world market leaders in their industries. This makes Germany an ideal setting for an assessment of the role of intangibles. Furthermore, Germany is the largest European economy and the third largest worldwide (UNCTAD, 2004, 2005). Another important characteristic is that it is part of the single European market, which makes this setting

Method

93

different from prior samples. Prior research has largely relied on samples from the US, and to a lesser extent on other non-European samples, such as Japan. The only other study that tested the s-curve hypothesis beyond those settings so far is Ruigrok et al. (2007), who relied on a sample of N = 87 Swiss multinational companies with n = 696 firm year observations4. The initial sample consisted of all German companies that are listed under the prime standard of the Deutsche Boerse AG (N = 324). The prime standard is a EU regulated segment for companies also wishing to position themselves vis-à-vis international investors. Firms must comply with international transparency standards, such as (1) quarterly reports in German and English and (2) application of international accounting standards (IFRS/IAS or US-GAAP). These conditions guarantee the availability of comprehensive and reliable information. Firms from listing segments other than the prime standard in turn might not provide reliable data, since disclosure regulations for these firms are less rigorous. In addition, firms from other sectors do not have to adhere to international accounting standards and therefore do not (1) provide sufficient data on intangibles and international activities and (2) guarantee the comparability of the information to other firms. The selection process was fourfold. First, I eliminated firms that exhibited no foreign sales in their annual accounts. Second, I ruled out firms that operated in the banking and financial services sector (SIC codes between 6000 and 6999) and third, I excluded small firms with less than 500 employees with the goal of creating a validly comparable company sample (in terms of degree of internationalization, return oriented performance measures and especially intangible intensity) (Ruigrok et al., 2007). Finally, I had to erase those firms for which I could not retrieve the data for all items in a given year. Overall this procedure yielded N = 193 firms with n = 789 firm year observation that met these criteria. These firms can be considered representative of German medium to large non-financial multinational companies with international activities over the five year time frame between 2001 and 2006. A compilation of all firms with basic characteristics can be found in Appendix A 3.1. To the author’s knowledge the present study is based on the largest sample of firms not originating from the US or Japan so far that investigates the relationship between internationalization and performance. In addition, it is among the first to explore the role of intangible resources in a European context. One reason for this might be that disclosure regulations often prevented researchers from drawing upon

94

Intangible Resources as Moderators

non Anglo-American samples. This is especially true, since data on intangibles is often fragmented and seldom easily accessible for samples beyond Anglo-American ones in databases such as Datastream or Compustat.

3.4.2 Variable Coding Performance The dependent variable in this study is corporate performance. A variety of accounting-based return measures have been used in the domain of international business. In order to secure the comparability of the results to other studies I choose return on assets (ROA) as the measure of financial performance, since this is the most frequent used return measure (see chapter two, Table 2.4). ROA is computed as aftertax ratio in accordance with the formula applied in Datastream: [Net Income before Preferred Dividends + ((Interest Expense on Debt - Interest Capitalized) * (1 - Tax Rate))] / Last Year's Total Assets * 100. Internationalization The measure of internationalization is the ratio between foreign sales and total sales (FSTS). Although Sullivan (1994) suggested that the concept of internationalization is complex and multidimensional, firms are required to provide data on geographical sales dispersion only, not on asset or subsidiary dispersion between home country and foreign countries, under German company law. Thus, statistically reliable and complete internationalization data was only obtainable in FSTS form. Equally important, FSTS is the internationalization measure most often used in previous studies, facilitating cross-study comparison of findings (see chapter two, Table 2.4). Nevertheless I also calculated the ratio between foreign assets and total assets (FATA) for a sub-sample of firms, which provided the necessary information. Tobin’s q Lindenberg and Ross (1981) introduced the concept of Tobin’s q. The problem with their measure is that it is very complicated to calculate because it requires very detailed information, e.g. on long-ranging depreciation schedules. Modifications have been proposed by Lang and Litzenberger (1989) and Lewellen and Badrinath (1997), who proposed a superior and more pragmatic method. However, their method again is prone to a high percentage of missing observations and therefore results in the selec-

Method

95

tion of samples that are biased (Lee and Tompkins, 1999). Perfect and Wiles (1994) empirically compared five alternative constructions of Tobin’s q and found that results are method-sensitive for levels of q, but not for changes. This is why some researchers take a shortcut and employ the ‘market-to-book ratio’ instead of the more sophisticated versions of Tobin’s q. I calculated Tobin’s q following the procedure by Chang and Pruitt (1994) which does not require out-of-financial report data. They find that what they call ‘approximate q’ explains at least 96.6 percent of the variability of Tobin’s q – calculated as in Lindenberg and Ross (1981), which is generally acknowledged as the most accurate procedure. I refrained from using the even more simple measure of market-to-book ratio for two reasons: First, the magnitude of the market-to-book ratios is remarkably different to the values of Tobin’s q obtained from my sample of German publicly traded firms (average market-to-book ratio = 2.07 as opposed to Tobin’s q = 1.38, see Table 3.4). Second – and probably even more important – is the fact that this variable shows a correlation of only r = .78 with Tobin’s q in my sample (see Table 3.4). While researchers often refer to the studies by Perfect and Wiles (1994) as well as Chang and Pruitt (1994) to justify the use of the market-to-book ratio, my results doubt the equality of the market-to-book ratio as proxy for Tobin’s q as opposed to more sophisticated versions of this measure, at least for a sample of publicly listed companies from Germany. Consequently, I calculate Tobin’s q as follows: Tobin’s q = (MVE + PS + DEBT) / TA where MVE is the market value of common equity (calculated as the product of a firm’s share price and the number of common stock shares outstanding), PS is the liquidation value of the firm’s outstanding preferred stock, DEBT is the value of the firm’s short-term liabilities net of its short-term assets plus the book value of the firm’s long-term debt, and TA is the book value of the total assets of the firm. As stated above, all of these required inputs are readily obtainable from a firm’s basic financial and accounting information (Chung and Pruitt, 1994). Hedonic q This measure of resource intangibility is the predicted value obtained from the regression of Tobin’s q on five accounting measures of intangible resources: R&D intensity, marketing intensity, intangibles in books intensity, top management team

96

Intangible Resources as Moderators

internationalization, and top management team education. I am therefore attempting to capture the joint value of a firm’s technological know-how, market and customer know-how, contract-based know-how, and human capital of the top management team. I will describe the computation and obtained beta-coefficients in section 3.4.4. Technological Know-How The prevalent measure for intangible resources in the literature is research and development (R&D) intensity (Hitt et al., 1991; Morck and Yeung, 1991). In fact, this measure captures an important dimension of intangible resources, namely a firm’s technology based know-how. I calculated R&D intensity as the ratio of R&D expenditures to total sales. Market Know-How Analogous to a firm’s spending on research and development in order to build technological expertise the marketing or advertising expenses of a firm constitute a proxy for the creation of market know-how or customer goodwill (Morck and Yeung, 1991; Delios and Beamish, 1999; Kotabe et al., 2002). I calculated advertising intensity (ADV) as the ratio of marketing expenses to total sales. Contract-based Know-How Contract-based know-how comprises the capitalized intangible resources of a firm’s balance sheet exclusive of goodwill. They comprehend a diverse set of different accounting items which are (1) brands and patents, (2) licenses, (3) deferred costs, and (4) miscellaneous intangible fixed assets. I will refer to the sum of these items as ‘intangibles in books’. I decided to omit goodwill since goodwill is simply the result of merger and acquisition (M&A) activities and hence a residual item which contains a conglomeration of intangibles for which only an abstract entitlement can be specified. For the present research question an integration of goodwill would be misleading since only strategies of external growth result in goodwill as opposed to strategies of organic growth. Contract-based know-how (CONT) is calculated as the sum of the four items mentioned above divided by total assets. Top Management Team Demographics Generally, researchers have used a variety of different methods to arrive at a definition of a top management team (TMT). Constructs used include top-level executives (Murray, 1989) or positions such as vice-president or higher (Michel and

Method

97

Hambrick, 1992) and also the direct questioning of the CEO to nominate the persons they see as belonging to the TMT (Eisenhardt and Schoonhoven, 1990). Before describing the measures for TMT international diversity and TMT education, I want to indicate what a TMT in the German context is. This is of particular relevance as in contrast to Anglo-American countries firms listed in Germany usually do display a two-tier corporate governance system, i.e. the management board and the supervisory board. The top executives represent the management board that holds the responsibility to lead the company on a day to day basis and develop the strategy of the firm. In the German context, the management board incorporates a CEO (Vorsitzender / Sprecher) and members (Vorstandsmitglieder). The supervisory board represents the shareholders (and other interest groups such as employees) and has the task to monitor the management board. The control the supervisory board has over the management board is rather focused on financial control. Usually, board members monitor the financial performance, while strategic control is rather reserved for executives (Westphal and Fredrickson, 2001). I refer to the management board as the more appropriate institution for decision making with respect to internationalization. The measure of TMT international diversity (TMT_INT) is the portion of non-German executives among the management board. The measure of TMT education (TMT_ACD) is the percentage of executives holding an academic title such as professor or PhD (Papadakis, Lioukas, and Chambers, 1998; Carpenter, 2002). In addition, I calculated these two diversity measures for the supervisory board and the combined management and supervisory board. The results of the analyses did not reveal significant differences, if these slightly different measures were applied. Controls I include controls for several variables known to effect corporate performance. Descriptive statistics and a correlation matrix for several alternative operationalizations of all control variables can be found in Appendix A 3.2. Empirical studies have shown that firm size and internationalization are correlated (Morck and Yeung, 1991; Mishra and Gobeli, 1998). I measure firm size by the natural logarithm of the number of employees. The correlation of this measure with

98

Intangible Resources as Moderators

alternative measures of firm size such as total sales or total assets is very high, underlining the robustness of this measure. As a consequence of the meta-analytical results from chapter two I calculated a measure for level of product diversification that is based on the 4-digit SIC Code according to Gedajlovic and Shapiro (1998). Again, results for 2-digit SIC Codes provided similar results. Furthermore, I included a total debt-to-total capital ratio as measure of financial leverage. Finally, I introduced fixed effects for a firm’s main industry as based on a classification of the Economic Sector code (manufacturing, service, and other) according to the primary SIC code of each company. Table 3.4 provides descriptive statistics and a correlation matrix of the variables for the full sample of firms.

3.4.3 Sources of Data and Process of Data Collection To compile my sample I collected corporate information on international activities, intangible resources, and performance. Most of the information was obtained from the Thomson Extel Profile Cards database, which I supplemented with information from annual reports and data on market value of common equity from Datastream. The objective of the data collection process of this study was to create one single and consistent data base. In order to provide the necessary longitudinal data on all relevant variables I had to collect the data at two separate points in time since Extel Cards only covers data for up to five years in history and updates its database on an irregular basis during the year. The first time of assessment was in May 2006 and yielded data for the years 2000 to 2005. The second data scanning process was performed in May 2007, yielding addition as well as missing data for the period from 2001 to 2006. Although prior research has predominantly relied on databases such as Datastream or Compustat Global Vantage they bare some serious deficiencies with respect to my research questions and data requirements. While they offer ease of collecting financial statement items they only offer limited coverage of German firms, especially with respect to the level of detail and quality of information regarding (1) intangible resources and (2) regional dispersion of international activities (this information will be required in chapter four).

.096

.235

.216

.879

.270

1.94

.039

.036

.067

.153

.286

1.86

2.14

.177

.047

.517

.378

1.38

1.25

2.07

.043

.032

.041

.084

.318

8.63

4.55

.606

.581

.216

1. ROA

2. FSTS

3. FATA

4. Tobin’s q

5. Hedonic q

6. Market to book ratio

7. R&D

8. ADV

9. CONT

10. TMT_INT

11. TMT_ACD

12. Size_ln

13. Product Div.

14. Leverage

15. I1: Manufacturing

16. I2: Service

2

.01

.19**

-.05

-.03

.07†

5

.06

6

.01

.23** .10**

.11**

-.29** -.20** -.09* -.16** -.07*

.02 .08†

-.15** -.42** -.14** .16** .29**

.12** .32** .11*

-.01

-.05

.22** .20** -.09*

.08* -.30**

-.05

-.07

.06

-.05

.08*

-.03

7

-.04

-.02

.00

.12**

8

.05

.05

-.04

-.06

-.02

-.04

-.07

-.05

9

11

12

13

.01

.00

14

.12** .19** .13**

.14** .12** .39** .28**

.14** .15** .57**

.28** .26**

-.03

10

15

.11** .12** -.16** -.11** -.39** -.37** -.25** -.62**

-.06†

-.33** -.15**

-.07* .11**

-.12**

-.08* -.16** -.08* .15**

.08*

.01

.21** .66** .24**

.16** .29**

.78** .39**

.40**

4

.15** .34** .35** -.10** -.13**

.13**

-.06†

.01

.23** .28**

-.07*

.03

.06

.01

.10

.04

3

.04

-.10*

.11** -.15**

.05

.28**

.14**

.46**

.13** .57**

.15**

1

Notes: FATA: N = 565, Tobin’s q: N = 765, Market to book ratio: N = 763. † p < .10. * p < .05. ** p < .01 (all two-tailed tests).

.411

.494

S. D.

Mean

Variables

Table 3.4 Descriptive Statistics and Correlations (N = 789)

Method 99

100

Intangible Resources as Moderators

In a pre-test I compared different data sources based on three criteria: (1) Company coverage, (2) data reliability, and (3) data availability. I considered the following databases: Amadeus, Hoppenstedt Bilanzdatenbank, Datastream (together with Worldscope), Compustat Global Vantage and Extel Cards. All databases cover the majority of German stock-quoted firms, although at a different level of detail. I had to exclude Amadeus and Hoppenstedt, because these databases only provide basic financial information which does not include detailed information on international activities. I evaluated the reliability of the data provided by Datastream, Compustat, and Extel Cards as opposed to the companies’ published annual reports based on a randomly chosen sample of five firms (Deutsche Post, Gildemeister, Kontron, SGL Carbon, and Vossloh). I found no differences for the data delivered by Extel Cards to annual reports’ data whereas Datastream and even more so Compustat revealed considerable differences in the data they reported, especially for data back in history. This is a remarkable finding since prior research has extensively relied on these databases. Moreover, this finding lends support to the call for more valid and reliable measurement in empirical research in the domain of business administration and economics that has recently been expressed by the German Science Council (Wissenschaftsrat) (Solga and Wagner, 2007). They find fault with the tendency of quantitative analyses in business administration to be based on identical data from only few databases. Furthermore they complain that these data are of questionable quality. Appendix A 3.3 compares selected items that are drawn from different databases. The third criterion concerns the availability of data on international dispersion of sales and on intangible resources. Compustat does not provide detailed data on international activities beyond the amount of foreign sales or foreign assets and reports no data on top management team characteristics. Although Datastream provides this information in principle, it only distinguishes between up to five values. For example it only exhibits the five largest business units for a calculation of product diversification or only displays up to five members of the top management team. This is a rather serious shortcoming since it does not distinguish between the management board and supervisory board either. Given the deficiencies of other databases I decided to collect the necessary information from Thomson’s Extel Profile Cards database. It offers the highest coverage of information on all necessary variables and shows the highest reliability of

Method

101

data. Nevertheless this database has some minor weaknesses as well. It does not provide ratios like ROA, foreign sales to total sales or R&D intensity directly. It only provides financial accounting data from annual reports (balance sheet, income statement, etc.). Therefore one has to calculate these items manually which raises the potential for calculation errors. Furthermore Extel Cards does not offer the ease of collecting these data like Datastream or Compustat does. Since it does not comprehend an automatic company search tool, each company has to be retrieved manually. This deficit again is prone to missing company observations. Appendix A 3.4 exhibits the output screen from Extel Cards database for a showcase sample firm (SGL Carbon). A well-known problem in studies using R&D or advertising expenditures is the substantial amount of missing data for both of these variables from most company databases. Villalonga (2004) compared alternative solutions to deal with missing data5. I agree with her approach and applied the following procedure: When a data point was missing between two non-missing ones, I ‘filled in’ the data by interpolation. When the last data point of a series was missing, so that the interpolation could not be performed, I assumed it to be equal to the previous period expenditures, multiplied by the growth rate of the previous period (with respect to the one before). The reverse procedure was used when it was the first data point of a series that was missing. If data were missing after this method had been employed I excluded the respective observation. The international background of the TMT was the only other item for which I needed to collect additional information. German companies are not obliged to release comprehensive demographic information about their TMT and there is a reluctance to publish this information. However, since the discussion on corporate governance issues started at the end of the 1990s, also in Germany, companies have developed a higher degree of awareness of the issues of information transparency and started to add demographic information on TMTs to their web sites and company reports. As central sources for data on international TMT members, I used company web-sites to access current data. Demographic data on current TMTs obtained from companies’ web sites are usually reliable, of high quality and very comprehensive (covering a full TMT for the present situation), as in the best case it comes as complete CV documents. I coded place of birth and CV development as a proxy for nationality. Furthermore, I used company reports and sites of institutions or organizations where the TMT member in question holds an important position for retrieving both current and historical

102

Intangible Resources as Moderators

accounts. Appendix A 3.5 exemplifies this coding procedure for a sampling firm (SGL Carbon).

3.4.4 Analytical Approach I estimated two different econometric models: The hedonic regression of Tobin’s q, and a pooled time-series cross-sectional regression analysis in order to test my hypotheses. The hedonic equation was specified as follows:



ln q it

D E j

1j

* R & D  E * ADV  E * CONT  E * TMT _ INT  E * TMT _ ACD  H , it 2j it 3j it 4j it 5j it it

where q is Tobin’s q, R&D is expenses on research and development divided by sales, ADV is marketing expenses divided by sales, CONT is intangibles in books divided by assets, TMT_INT is the percentage of international members of the top management team, and TMT_ACD is the percentage of members of the top management team holding an academic title. Following Hall (1993), I took the natural logarithm of q, so that the coefficient estimates allow me to calculate the percentage change in q for a one unit change in the given variable. In contrast, a linear transformation would imply constant returns to scale from investments in intangibles, which is unlikely to be the case. The j subscripts in all coefficients indicate that this model was estimated separately for every industry based on the official classification by Deutsche Boerse AG. This allows for the fact that a specific intangible resource included in this equation may be more relevant in some industries than in others. Table 3.5 exhibits the beta-coefficients obtained from hedonic regression by industry. The hedonic q estimates for each firm year are the antilogarithms of the predicted values of q from the regression equation. I calculated beta-coefficients based on alternative industry classifications as well. Two alternative classifications can be based (1) on the primary one-digit SIC-Code and (2) on the technology versus classic segment by Deutsche Boerse AG. The R2 values obtained from these classifications were lower, which implies that these taxonomies reflect the essence of ‘strategic industry factors’ (Amit and Schoemaker, 1993) to a lesser extent. Results from hedonic regression with these industry classifications are depicted in Appendix A 3.6. Consequently, I draw my results from the classification shown in Table 3.5.

53 46 50 86

Automobile

Basic Resources and Construction

Chemicals

Consumer

42 52 75 26 56 61 107 37 44

- Heavy Machinery and Diversified

- Industrial Machinery

- Industrial Products

Media and Telecommunication

Pharmaceutical and Healthcare

Retail

Software

Technology

Transport, Logistics, and Utilities

Notes: N: Number of firm-year observations.

54

- Advanced Equipment and Renewables

Industrial

N

Industry

.141

.809

.232

-.273

-.311

1.34

.016

-.071

-.451

.752

-.073

.230

.129

-.468

Intercept

Table 3.5 Coefficients from Hedonic Regression

-2.25

-4.47

.717

.000

4.67

-33.30

-.629

.873

-.138

-7.63

.929

-6.38

1.56

7.36

R&D

2.48

-30.12

1.30

4.97

3.16

.899

15.21

-5.68

28.84

-3.23

4.32

12.01

-1.92

19.25

ADV

-1.22

-3.47

-.262

.191

1.26

-2.18

1.56

6.58

.998

.231

2.17

-.078

1.35

-3.32

CONT

-.140

1.61

1.76

1.10

.372

.269

-.596

.000

.540

-1.01

.611

-.202

-.390

-.243

TMT_INT

-.145

1.37

-.082

.654

-.095

-.167

.023

.025

-.207

.166

-.176

-.136

-.157

.074

TMT_ACD

.059

.603

.127

.441

.417

.259

.094

.306

.342

.170

.456

.203

.319

.220

R2

Method 103

104

Intangible Resources as Moderators

I chose panel data OLS regression analysis pooling time-series and cross-sectional data as the method to test my hypotheses. This procedure is well established in international business research (Gomes and Ramaswamy, 1999; Contractor et al., 2003; Ruigrok and Wagner, 2003; Ruigrok et al., 2007) as it offers some advantages compared to cross-sectional research designs. It enlarges the degrees of freedom of the statistical analysis and improves the reliability and stability of parameter estimates. As Aiken and West (1991) recommend, I mean-centered the variables before I created the interaction terms to minimize the effect of multicollinearity. A review of the correlation values in Table 3.4 indeed indicates that the risk of multicollinearity invalidating the results is minimal for the firm variables in the model. The two variables size and leverage show the highest correlation among the predictor variables of r = .57 (statistically significant), as one should expect. Therefore I checked the variance inflation factor (VIF) in each of the regression models. In the case of this study’s variables, the VIF is significantly lower (max. 2.26 for firm size) than the upper threshold value of ten recommended by Burns and Bush (2000) for each of the models. Additionally, it should be noted that many leading references in econometrics and statistical methodology have offered as a rule of thumb that collinear relationships under 0.7 should not create potential problems (or statistical confounds) related to multicollinearity (Andersen, Sweeney, and Williams, 1996). Based on the two reasons stated above I concluded that multicollinearity is not a concern for this study.

3.5 Results I report the results in three different tables. ROA is the dependent variable in all of the tables and models. Table 3.6 shows the results for the tests of hypotheses one and two. Model one is the base line model that includes only the control variables and Tobin’s q, the measure of intangible resources. All control variables except product diversification display significant effect sizes. This confirms the necessity to control for their effects in the domain of international business. Tobin’s q has a significantly positive effect, indicating the importance of intangible resources for success in general. I test hypothesis one stepwise throughout models two to four. In model two I add the term for internationalization, followed by the squared term in model three and lastly a cubic term in model

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Table 3.6 Regression of Curve Type and Moderation of Tobin’s qa Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service 7. Tobin’s q

1

2

3

4

5

-.014 (-.73) .013** (6.24) .000 (-.16) -.180** (-9.82) .015* (2.00) -.037** (-3.91) .046** (13.51)

-.011 (-.58) .013** (6.22) .000 (-.18) -.181** (-9.83) .015* (2.07) -.039** (-3.96) .046** (13.52) -.009 (-.68)

-.039† (-1.75) .013** (6.24) 0.00 (.03) -.183** (-9.96) .014† (1.92) -.036** (-3.65) .046** (13.67) .128* (2.35) -.138** (-2.61)

-.100** (-3.96) .014** (6.67) .000 (-.19) -.186** (-10.26) .016* (2.26) -.030** (-3.05) .045** (13.68) .703** (5.31) -1.57** (-5.13) .985** (4.75)

-.105** (-4.16) .013** (6.53) .000 (-.14) -.184** (-10.20) .016* (2.15) -.030* (-3.12) .048** (13.95) .721** (5.46) -1.59** (-5.25) 1.02** (4.85) -.038** (-2.71)

.354 .349

.355 .349 .001 59.47**

.361 .354 .007 53.28**

.379 .372 .025 51.21**

.385 .377 .031 47.22**

8. FSTS 9. FSTS (squared) 10. FSTS (cubic) 11. FSTS * Tobin’s q R2 Adjusted R2 ' R2 F-statistic

69.35**

†

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate; numbers in the parentheses are t-statistics.

four in order to test for a sigmoid curve type of the internationalization-performance relationship. The linear term in model two is insignificant, indicating that there is no simple linear relationship between internationalization and firm performance. In contrast, both internationalization terms in model three are significant, as well as the linear, squared in cubic terms in model four. While model three gives indication for an inverted u-shaped curve type pattern it becomes obvious that the addition of a cubic term significantly improves model fit and explains a far higher degree of performance variance ('R2 of .025 in model four versus 'R2 of only .007 in model three as compared to the base line model). Consequently the internationalization-performance relationship can be best described by a sigmoid curve type pattern and therefore hypothesis one can be supported. Performance increases at low levels of internation-

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alization and exhibits an upper-bound and a subsequent lower-bound inflection point with growing degrees of internationalization. As corroboration for this result, I calculated F-values to test model fit. The results confirm that the inclusion of additional terms significantly improves model fit throughout model one to four (p < .01). Note that this curve type pattern is consistent across different operationalizations of intangible resources in Tables 3.7 and 3.8. Hypothesis two predicts that intangible resources positively moderate the internationalization-performance relationship. I test this hypothesis by entering the interaction term of internationalization and Tobin’s q in model five. Although the coefficient for the interaction term is significant it is not in the hypothesized direction. Therefore I have to reject hypothesis two. Table 3.7 presents the results for the test of hypothesis three. It introduces hedonic q as an alternative measure of intangible resources that more purely comprises the value of intangible resources. Model one to four contain results for the shape of the internationalization-performance relationship that are similar to the ones reported in Table 3.6. However, the interaction term of internationalization and hedonic q is not significant in model five. Intangible resources measured by the overall measure of hedonic q do not significantly moderate the relationship between internationalization and performance. Therefore hypothesis three has to be rejected as well. Table 3.8 presents the results for the moderating impact of different facets of intangible resources upon the internationalization-performance relationship. Model one is the base line model again. As one can see, there is no uniform direct effect from intangible resources on ROA. Only market know-how constitutes a valuable resource that directly affects performance. In contrast, contract-based know-how and the academic background of the TMT have a negative impact. Rather surprisingly technological know-how does not exhibit a direct effect on performance while it appears more comprehensible that the international diversity of the TMT per se does not constitute a universal valuable resource that enhances performance. The curve type pattern in model two is consistent with the ones in the prior two tables (Table 3.6 and Table 3.7); yet after separate controlling for the influence of each dimension of intangible resources.

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Table 3.7 Moderation of Hedonic qa Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service 7. Hedonic q

1

2

3

4

5

.004 (.15) .014** (6.54) -.001 (-.47) -.231** (-12.15) .015† (1.87) -.036** (-3.35) .052** (4.34)

.004 (.15) .014** (6.33) -.001 (-.47) -.231** (-12.05) .015† (1.86) -.036** (-3.27) .052** (4.32) .000 (-.03)

-.007 (-.28) .014** (6.32) -.001 (-.38) -.232** (-12.10) .014† (1.80) -.034** (-3.06) .050** (4.14) .069 (1.15) -.069 (-1.20)

-.071* (-2.37) .015** (6.74) -.001 (-.67) -.234** (-12.38) .017* (2.16) -.028* (-2.52) .049** (4.06) .669** (4.64) -1.55** (-4.70) 1.03** (4.56)

-.070* (-2.36) .015** (6.71) -.001 (-.67) -.235** (-12.35) .017* (2.14) -.028* (-2.52) .049** (4.06) .670** (4.63) -1.55** (-4.70) 1.03** (4.56) -.006 (-.11)

.220 .214

.220 .213 .00 27.56**

.221 .213 .001 31.45**

.242 .233 .022 27.71**

.242 .232 .022 27.56**

8. FSTS 9. FSTS (squared) 10. FSTS (cubic) 11. FSTS * Hedonic q R2 Adjusted R2 ' R2 F-statistic

36.74**

†

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate; numbers in the parentheses are t-statistics.

In model three I test whether technological know-how moderates the internationalization-performance relationship. The effect size is positive and significant, and the addition of the interaction term increases the explanatory power of the model. Therefore hypothesis four can be supported. Although the moderator term in model four is positive, it just fails to become significant. As a consequence I have to reject hypothesis five. The interaction of market know-how and internationalization does not significantly contribute to an increase in firm profitability. In model five contract-based know-how represents a significant intervening variable that positively moderates the internationalization-performance relationship. Therefore, hypothesis six can be supported. Furthermore, the direct and negative effect from contract-based know-how

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Table 3.8 Moderation of Individual Intangible Resourcesa Variable

1

2

3

4

5

6

7

8

1. Intercept 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.

.025 .005 .075** .004 .034 .005 .001 .011 (.91) (.17) (3.56) (.139) (1.23) (.19) (.04) (.38) Size_ln .016** .015** .014** .016** .016** .011** .015** .011** (4.97) (6.74) (7.05) (6.79) (4.54) (6.24) (6.93) (6.90) Product Div. -.001 -.001 -.001 -.001 .000 -.001 -.001 -.001 (-.66) (-.62) (-.56) (-.67) (-.25) (-.58) (-.79) (-.40) Leverage -.244** -.246** -.238** -.246** -.250** -.231** -.246** -.229** (-12.14) (-12.26) (-11.92) (-12.29) (-12.52) (-11.75) (-12.25) (-11.72) I1: Manufacturing .017* .016* .018* .017* .016* .018* .017* .017* (1.98) (2.19) (2.07) (2.17) (2.06) (2.27) (2.15) (2.12) I2: Service -.020† -.015 -.025* -.016 -.010 -.012 -.015 -.012 (-2.36) (-1.51) (-1.08) (-1.44) (-1.12) (-1.90) (-1.42) (-.96) † † R&D -.153 -.132 -.101 -.130 -.295** -.253** -.129 -.157 (-1.20) (-1.52) (-2.77) (-1.51) (-1.84) (-1.83) (-1.53) (-3.33) .187* ADV .219* .234** .225* .196* .224* .288** .227** (2.63) (2.19) (2.50) (2.70) (2.59) (2.11) (2.60) (3.02) -.122** -.133** CONT -.168** -.134** -.134** -.130** -.075 -.057 (-3.63) (-2.89) (-2.91) (-2.80) (-1.51) (-2.69) (-2.85) (-1.18) -.008 .011 TMT_INT -.003 -.007 -.007 .020 -.001 -.005 (-.39) (.56) (-.12) (-.34) (-.33) (.91) (-.06) (-.26) † -.020 TMT_ACD -.026* -.034** -.026* -.019† -.025* -.027* -.024* (-2.95) (-2.23) (-2.19) (-2.38) (-2.13) (-1.77) (-2.24) (-1.67) FSTS .581** .584** .583** .515** .600** .579** .531** (3.46) (4.14) (3.69) (3.90) (3.91) (3.97) (3.93) FSTS (squared) -1.29** -1.25** -1.31** -1.17** -1.35** -1.30** -1.19** (-3.80) (-3.72) (-3.86) (-3.46) (-4.06) (-3.81) (-3.62) FSTS (cubic) .851** .808** .864** .790** .896** .857** .801** (3.42) (3.96) (3.57) (3.69) (3.67) (3.51) (3.73) 1.35** FSTS * R&D 1.47** (3.53) (3.75) .137 FSTS * ADV .607 (.37) (1.59) .637** .606** FSTS * CONT (3.70) (3.45) .286** .286** FSTS * TMT_INT (6.30) (6.31) -.048 FSTS * TMT_ACD -.044 (-.53) (-.47)

R2 Adjusted R2 ' R2 F-statistic †

.232 .222

.247 .261 .250 .259 .284 .247 .309 .235 .247 .236 .245 .271 .234 .293 .015 .029 .018 .027 .052 .015 .077 23.45** 19.58** 19.49** 18.40** 19.29** 21.93** 18.18** 19.12**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate; numbers in the parentheses are t-statistics.

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on performance becomes insignificant in this model. Empirically the low correlations to technological know-how (r = .08) and to market know-how (r = .12) justify a separate treatment of contract-based know-how (see Table 3.4). The first part of hypothesis seven predicts that the more international the composition of the TMT the higher the performance gains from internationalization. This part of the hypothesis is supported as well, as one can see from model six. The effect size is positive and highly significant. Furthermore the internationalization of the TMT makes up for the highest portion of additional performance variance explained from any of the single moderating variables which I investigate. In contrast, the top management educational background does not moderate the internationalization-performance relationship. Consequently hypothesis seven can only be supported partially. Model eight contains the entire set of variables and shows the moderating effects from different measures of intangible resources simultaneously. In combination these dimensions of intangible resources explain additional 6.2 percent points of performance variance; that is model eight has an explanatory power that is more than 25 percent higher than the one obtained by model two. Hence, the inclusion of the effects from different facets of intangible resources into the investigation of the internationalization-performance relationship increases the explanatory power of the sigmoid curve type model strongly.

3.6 Discussion The major research objective of this chapter was to address the important but yet unresolved question if and why internationalization does have an impact on firm performance in the context of intangible resources. This study is among the few that address this question analyzing a sample of firms beyond companies from the US. The results reveal two important findings. First, a sigmoid curve type pattern best explains the shape of the internationalization-performance relationship in a German context. Nevertheless, the coefficients are quite contrary than has originally been predicted by the pioneers of the so called ‘3-stage theory’. Second, the role of intangible resources is more complex than prior research has assumed. In fact this finding reflects the original theory on firm-specific advantage (Barney, 1991; Peteraf, 1993) or ownership advantages (Dunning, 1988) more precisely in that it captures the idiosyncratic nature of intangible resources, specifically with respect to their effect upon performance consequences from the international expansion of the firm.

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German firms face an initial phase of increasing performance followed by an upper and subsequent lower inflection point in their internationalization trajectory. This result challenges the idea of earlier studies that aimed to establish a ‘general model’ on the curve type that best fits the internationalization-performance relationship. Their line of inquiry has tended to assume that the curve type pattern is mostly independent of home-country attributes of internationalizing firms. In fact, I agree with Ruigrok et al. (2007, p. 362) who state: “Thus, while the s-shape curve should provide the conceptual starting point for analyses of the link between international expansion and firm performance, home-country effects should be taken into account as well.” These home country effects include (1) the size of the home market and (2) the similarity of neighboring markets. As an extension I contend that home market size does not influence the basic overall shape of the curve type pattern, but it determines the inflection points, i.e. the degrees of internationalization at which firms encounter reversing benefit-cost tradeoffs. This is simply true because of the composition of the measure of internationalization that is mostly used in these investigations – the ratio between foreign sales and total sales (FSTS). To illustrate this point, take a firm that sells 70 percent of its products in Germany and 30 percent in Switzerland. If this firm happens to be a German firm it will have a 30 percent FSTS ratio. However, if the firm is registered in Switzerland the ratio is 70 percent, and if it were to relocate its headquarters, its degree of internationalization would change even though nothing has changed economically. The present sample covers firms at different stages of internationalization (foreign sales to total sales ranging from .01 to .95). Indeed, I find the first inflection point to occur earlier for the German sample (at about 20-30 percent FSTS) than Ruigrok et al. (2007) found for their Swiss sample (between 40-49 percent FSTS interval, p. 362). The similarity to neighboring markets determines if and when firms face different stages of internationalization. While I do not doubt that there is something like a liability of foreignness, it does not necessarily have to be the case that the costs associated with being a foreigner outweigh benefits at low levels of internationalization. What really matters in this context is the degree of dissimilarity between business environments. Prior research has mainly attributed costs from dissimilarities to cultural differences (Contractor et al., 2003; Lu and Beamish, 2004). My results suggest that similarity to neighboring markets may also include the availability of a wider economic union. Therefore, not only culture is an important aspect with regard to international management but as well the commonality of institutional and regulatory

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arrangements. Once again, while I do not doubt that cultural dissimilarity creates additional costs of communication and coordination I contend that comparable institutional arrangements might compensate for these additional costs and enhance the performance prospects at low degrees of internationalization. Albeit the membership in the European Union might reduce the intra-regional liability of foreignness for German firms, increasing adaptation costs come along with rising degrees of internationalization and operations in several regions. In a similar vein, Rugman and Verbeke (2007) distinguish three regions (Europe, America, and Asia) and divide between intra- and inter-regional liabilities of foreignness. Nevertheless German firms might find ways to cope even with these costs by reorganizing their management systems and are not doomed to ever decreasing performance beyond a certain level of internationalization. The fact that firms from this sample generate on average 51.7 percent of their sales abroad (see Table 3.4) confirms the assumption that German firms can draw on considerable internationalization experience in comparison to firms from many other countries (UNCTAD, 2004). It would seem implausible to expect that more than half of the German firms have ‘over-internationalized’ (Contractor et al., 2003), i.e. systematically operate at degrees of internationalization that are detrimental to firm performance. With experience in adapting to local business customs these firms might have learned to avoid or at least to minimize frictions in communication and coordination. Another explanation might be that growing transaction and coordination costs are rather reflected in measures that cover international asset or subsidiary dispersion than in sales based measures of internationalization. I tested for this possibility with a subset of firms that report data on international asset dispersion (N = 565). The direction of the obtained regression coefficients is identical to the foreign sales to total sales measure although the significance of the effect size estimates diminishes. See Appendix A 3.7 for the results based on foreign assets to total assets as the measure of internationalization. Furthermore I tested whether time-lagged measurement of the performance variable would lead to different conclusions. I find that the results are robust across different measurement designs. Appendix A 3.8 displays the results for measuring the dependent variable ROA with one year and two year time lag. This is probably due to the fact that the measures for intangible resources such as spending on R&D or the composition of the management board are rather stable over time.

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The second research question approaches the influence of the availability of intangible resources on the s-shape curve type pattern found in hypothesis 1. The empirical evidence suggests that some but not all dimensions of intangible resources elevate the performance effect from internationalization. This finding is equally important to the result of an s-shape curve type pattern because it shows that prior operationalizations of the internalization theory have fallen short of distinguishing between different facets of intangible resources. Neither Tobin’s q as an overarching measure of intangible resources nor the more pure measure of hedonic q could confirm the notion that all intangibles hold ‘internationalization potential’, i.e. enhance performance when applied in multiple markets. Furthermore, the insignificant results from hypothesis three with hedonic q as a measure of intangible resources as compared to the negative effect from Tobin’s q in hypothesis two cast doubt upon the adequacy of Tobin’s q as a valid measure of intangible resources for my sample. The direction of the moderator term based on Tobin’s q is opposite to the one hypothesized, and therefore the alternative interpretation that Tobin’s q reflects – at least partially – investors’ expectations beyond the value relevance of intangible resources cannot be rejected. While prior tests of the internalization theory have largely assumed many different operationalizations of intangible resources to be valid and representative measures for other dimensions as well, researchers have only recently pointed to the multidimensional nature of intangible resources in the domain of international business (Lei, 2007; Rugman and Verbeke, 2007). The results from this study indicate that it is important to differentiate between different facets. One distinction is central for the explanation why certain intangible resources can be effectively deployed internationally while others can not. It is the distinction whether the value of a resource is location bound or whether it is not. Intangible resources in the form of technological know-how or the international composition of the top management team significantly determine performance consequences of any internationalization strategy. This finding demonstrates that internationalization can truly be a valuable strategy if the value of a certain resource does not stick to the market where it was originally created. Technology intensive firms face significant pressure to reduce costs but relatively less pressure to make changes in products (Prahalad and Doz, 1987). In such competitive environments, it has been argued that a firm failing to capitalize on these benefits is likely to face competitive disadvantage versus a rival who has internalized

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these benefits through international operations. Consequently internationalization seems to be an important vehicle to exploit firm specific competitive advantage for R&D intensive firms. The value from upstream intangible resources such as technological know-how is embedded in the product itself which in turn can be sold internationally while avoiding major adaptation needs to sustain the value derived from this specific resource. In contrast, I could not find support for the hypothesis that market know-how moderates the internationalization-performance relationship. It seems as though this kind of knowledge depreciates quickly when applied in foreign markets. Market knowhow originates from the downstream side of the value chain, where products and services need to be marketed to buyers. Therefore the value of this resource depends on location specific components as well. Market know-how, although non-location bound in principle, may consequently only be valuable in proximate markets, instead of having really global deployment and exploitation potential. Contract-based know-how positively moderates the internationalization-performance relationship. It seems as if the value from intangibles that is codified in contracts can be successfully deployed internationally. In large part these contract-based resources consist of externally purchased brands, patents, and licenses. Such knowhow in turn comprises recorded and explicit know-how that can be exploited in different environments in contrast to implicit know-how like experience that needs additional location specific resource commitments. The stake of international members of the top management team enhances the performance impact of internationalization. This is because different national backgrounds of the individual members affect a TMTs ‘dominant logic’. Prahalad and Bettis (1986, p. 491) define dominant logic as “the mindset [...] of the business and administrative tools to accomplish goals and make decisions [...] which is stored as a shared cognitive map among the dominant coalition.” Bringing greater diversity and international experience to the TMT dominant logic allows firms to draw on the benefits from geographical diversity, strengthening the relationship between internationalization and firm performance. Note that the value of this resource depends on the context in which it is applied, i.e. multinational firms. From Table 3.8 one can deduce that a more international dominant logic among the TMT does not directly affect firm performance. It is only in the context of firms with growing degrees of internationalization that this resource obtains its value and becomes crucial for internationalization

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success. The second measure of TMT demographic diversity, i.e. educative background, does not significantly moderate the internationalization-performance relationship. It seems as if this measure is too general to affect performance in the context of internationalization. This might be because educational background lacks reference to the specific abilities that are required for internationalization from the TMT. Compositional demographic traits are certainly rough surrogates for subjective concepts such as group conflict, group ingenuity, or group creativity (Michel and Hambrick, 1992) which influence the performance of teams and the ability to successfully manage an international company. As demographic proxies however, they are useful for measuring constructs that are otherwise almost impossible to measure or are prone to unreliable measurement. TMT demographic traits are not only directly observable and thus more reliable and valid replicable measures, but they also produce a simpler, more parsimonious model of human behavior and interaction within the respective TMT. The results for TMT demography yield two important insights: First, one should be aware of processes and factors that work within the link of TMT demographics and firm performance in order to understand why TMT traits such as international diversity influence performance effects from internationalization (Smith et al., 1994) and second, the specific organizational context may have an influence on the work of TMTs and their ability to influence firm performance (Keck, 1997). To sum up, the result that intangible resources are relevant in different extents in the context of internationalization and firm performance is in line with one essential finding already articulated in chapter two. The internationalization-performance relationship is complex and fundamentally context dependent. This perception is as well an extension and refinement of internalization theory. This established theory posits that internationalization is the result of market failure for the transfer of valuable resources. It does not specify what makes resources valuable and it does not indicate if resources that are valuable in a national context can be successfully deployed in international markets. Since the results obtained from this chapter corroborate the multidimensional nature of intangibles one is led to wonder whether it is still possible to talk about intangibles in general in the context of the internationalization-performance relationship. Can researchers studying intangibles in general offer suggestions that can be transferred into business life or must one focus on a specific kind of intangible resource in order to offer concrete descriptions and suggestions? This piece of research suggests that a distinction of intangible resources

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by their utilization within the value chain explains why some resources are more valuable in the context of internationalization than others. The practical additional insight from this chapter is that a firm’s internal setting is decisive for success in international markets. Therefore, future research should further explore how configurations of international activities – such as speed and scope of the international expansion process – moderate this relationship.

3.7 Limitations As with any study, this one has several limitations, and its findings should be interpreted within its context. First, this study is coarse-grained in nature, as it relies on a large sample of 789 firm year observations based on publicly available secondary data, and therefore suffers all the attendant limitations with conceptual and measurement issues related to such designs. Second, it focuses on one country to reduce the chance that country confounds would invalidate the findings. Therefore, this boundary condition should also apply to its findings. This concerns the curve type pattern as well as the role of intangible resources. Indeed, comparing the results on the s-shape curve type pattern found in this chapter to the results obtained from other countries it seems that mixed country samples probably would lead to spurious results. In international competition German firms are well-known for quality leadership. Therefore intangible resources are of primary importance for German firms. Firms from different environments such as developing or less munificent countries may find that different resources are more important in their context (Wan and Hoskisson, 2003). Nevertheless, the classification of intangible resources that I relied on is derived from an established classification by the FASB, therefore facilitating cross-country comparisons. I rely on foreign sales to total sales as the measure of internationalization. Although prior research has criticized the application of this measure for a couple of reasons, it is still the most widely used measure of internationalization in contemporary research. Nevertheless, a problem regarding the degree of internationalization arises that is inherent to the concept of this measure. As has been pointed out in chapter two, firms face different incentives and opportunities for internationalization depending on the size of the home market. Consequently, firms’ degrees of internationalization, if measured with conventional flow data (foreign sales, foreign assets, etc.) will depend on the size of their home markets. For instance, given that the US market is much larger than the German, or any other European market, US firms tend

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to have much smaller degrees of internationalization than European firms, all other things being equal. The interdependence between the size of firms’ home markets and their degrees of internationalization creates problems with comparisons of studies based on different national data. The results from this study reflect the internationalization of medium to large German firms. Therefore the findings may not be transferable one-on-one to smaller enterprises. As already pointed out in chapter two, firm size represents an important contextual characteristic. Entrepreneurship research has shown that smaller firms have different ownership structures or management styles (Coviello and McAuley, 1999) with the result that small firms may exhibit different internationalization patterns. For example, small firms are found to use differing entry modes such as equity jointventures to compensate for their lack of financial capital and human resource constraints (Inkpen and Beamish, 1997). Hence, future research might increasingly investigate differences in the internationalization patterns of small firms as well.

3.8 Implications for Future Research The 3-stage proposition is a theory that should ideally be tested over time. Future research may ideally employ different methods such as case study designs that cover a longer time frame to find out whether firms that increasingly expand abroad indeed face the different phases of increasing performance and subsequent adaptation and reconfiguration pressures. A central explanation of changing curve type patterns is that companies learn along their internationalization path. Future research might therefore analyze in more detail what kind of knowledge is critical at different stages of internationalization and how international learning occurs. How can knowledge obtained abroad be successfully transferred back to the parent company and how does it diffuse into the dominant logic of the company? Rugman and Verbeke (2003) have already developed a promising conceptual piece of research in this area. They delineate the decisive role of subsidiaries for learning and innovation. Another promising avenue will be research on firms operating at extreme degrees of internationalization. In this study I analyze established medium to large German firms. Some of them operate at rather low levels of internationalization. These firms must not necessarily be at initial stages of their internationalization process. Knowledge on international growth barriers would be worthwhile, i.e. why certain firms stop

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their internationalization process at rather low degrees of internationalization while others that already operate at extremely high degrees of internationalization still advance their internationalization. This would broaden our knowledge on different motives for internationalization and the strategic importance different managers attribute to internationalization. Recently, Ruigrok et al. (2007) for example investigated Swiss firms operating at extreme high degrees of internationalization. They found that firms face ‘screening forces’ at extreme degrees of internationalization. “For firms operating at extremely high DOIs, absorptive capacity constraints appear to be salient [...] The counterintuitive finding of this study is not that many MNCs at extreme DOIs face severe performance pressures. Rather, the interesting finding is that some companies at extreme DOI levels would appear to have found ways to deal with weak situations relatively successfully.” (Ruigrok et al., 2007, p. 363f.). Future research would ideally investigate if and how home country givens influence the availability and importance of intangible resources for internationalization success. For example samples could be drawn from developing countries. Do firms that derive their competitive advantage from cheap labor costs in their home country benefit from international diversity among the top management team? How does technological know-how intensity relate to the munificence of the home country or macro economic institutions such as different education systems? I was not able to capture more facets of intangible resources due to fact that the analyses are based on accounting data from annual reports. Future research would include the collection of survey data or conduct of case studies to more deeply understand which resources managers actually have in mind when considering internationalization as an option to generate value.

3.9 Conclusions In this chapter I tested a sigmoid curve type pattern and the role of intangibles resources in the context of the internationalization-performance relationship. Using a dataset of publicly listed German firms I find that the originally proposed s-shape curve is shifted to the right, preceded by an initial phase of increasing performance. In addition I do not find that firms necessarily face ever decreasing performance once they have passed a certain internationalization threshold. The second contribution of this chapter is that it makes use of a more comprehensive conceptualization of the

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construct of intangible resources and that it introduces a novel approach to measuring the value of intangible resources, the so called hedonic approach. I find support that the relationship under examination is fundamentally context dependent. This result backs those theories that stress the conditionality of success in internationalization and that emphasize the decisive role of intangible resources, especially in the form of technological know-how and top management team international diversity. Figure 3.3 summarizes the results for the moderating impact of intangible resources. Given the complexity and context-dependency of this relationship I think that future research might benefit from an integration of several theoretical approaches to more fully understand the nature of the internationalization-performance relationship.

Figure 3.3 Results for Moderator Analysis of Intangible Resources

Degree of Internationalization Technological Know-How Market Know-How

Tobin’s q

Contract-Based Know-How Hedonic q

TMT International Diversity TMT Education Firm Performance

Supported Not Supported

Conclusions

119

Furthermore, this study offers practical guidance to managers in internationalizing firms. It shows that one should not underestimate the importance of intangible resources. Just as many exporting activities started by unsolicited export orders the reputation of technological excellence or a strong brand name might precedent firms in an increasingly globalizing world. Customers, business partners or the press might already have determined the quality of a firm’s products or services before it actually ventures abroad. Although this study helps to refine the nature of the internationalization-performance relationship the results provide evidence that additional research is necessary, especially on samples beyond the US. Theory building and empirical investigations in search of moderating factors, their interactions and evolution along the internationalization process might yield valuable insights into the nature of the internationalizationperformance relationship. In the following chapter I will therefore analyze in more detail, how intangible resources influence the internationalization process and how different process dimensions influence the performance attributes of internationalization.

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Endnotes 1. According to Barney (1991) an item hast to satisfy four conditions, in order to be termed

‘resource’. These characteristics are called the VRIN-criteria (valuable, rare, imperfectly imitable, and non-substitutable). While the first two characteristics are constituent criteria for competitive advantage of a firm the later two criteria refer to the sustainability of a competitive advantage. 2. Hedonic pricing models have their roots in the calculation of prize indices, for example in such

diverse areas as real estate or digital cameras. Count (1939) is often cited to be the first who introduced the term ‘hedonic’. As economist for the Automobile Manufacturers’ Association, he developed a hedonic price index for automobiles. Court recognized that a single variable could not explain automobile demand. His hedonic model to explain prices included three variables: Dry weight, wheelbase and horsepower. 3. The objective of IAS 38 is to prescribe the accounting treatment for intangible assets that are not

dealt with specifically in another IAS. The standard requires an enterprise to recognize an intangible asset if, and only if, certain criteria are met. The standard also specifies how to measure the carrying amount of intangible assets and requires certain disclosures regarding intangible assets. For a comprehensive overview of accounting rules and regulations for intangibles see Lev (2001, p. 135-153). An intangible asset is defined as identifiable non-monetary asset without physical substance. An asset is a resource that is controlled by the enterprise as a result of past events (for example, purchase or self-creation) and from which future economic benefits (inflows of cash or other assets) are expected. Thus, the three critical attributes of an intangible asset are (1) identifiability, (2) control (power to obtain benefits from the asset), and (3) future economic benefits (such as revenues or reduced future costs). An intangible asset is identifiable when it is separable (capable of being separated and sold, transferred, licensed, rented, or exchanged, either individually or as part of a package) or arises from contractual or other legal rights, regardless of whether those rights are transferable or separable from the entity or from other rights and obligations. IAS 38 requires an enterprise to recognize an intangible asset, whether purchased or self-created (at cost) if, and only if (1) it is probable that the future economic benefits that are attributable to the asset will flow to the enterprise, and (2) the cost of the asset can be measured reliably. This requirement applies whether an intangible asset is acquired externally or generated internally. The probability of future economic benefits must be based on reasonable and supportable assumptions about conditions that will exist over the life of the asset. The probability recognition criterion is always considered to be satisfied for intangible assets that are acquired separately or in a business combination. 4. Given the size and prominence of the German economy it is surprising that comparatively few

studies have been published in leading international journals that investigate German samples. Selected empirical studies based on German samples during the last decade include: Wagner (2004), N = 83 manufacturing firms, Capar and Kotabe (2003), N = 87 largest German service

Endnotes

121

firms; Ruigrok and Wagner (2003), N = 84 manufacturing firms; and Gerpott and Walter (1999), N = 51 very large industrial firms. 5. According to Villalonga (2004, p. 227f.) two main alternative solutions have been adopted by

different researchers: “(1) Limit the sample to those firms for which no data are missing (e.g. Jensen, 1993); (2) Assume they are equal to zero (e.g. Morck and Yeung, 1991; Hall, 1993 - for advertising). A third solution that can complement either of the first two is to “fill in” the data by interpolation when there are only one or two missing values in an R&D or advertising series. This has been used for the construction of the R&D stock variable in the NBER Manufacturing Sector Master File (Hall, 1990), on which many subsequent studies are based. Solution one is the most straightforward, but creates two additional problems: sample selection bias, and sample size reduction. In my case, the sample selection problem is a serious one, because I am interested in comparing firms with different degrees of resource intangibility – including zero intangibility. As for sample reduction, excluding the observations with missing data would leave, after the necessary elimination of companies with less than three consecutive observations, a sample of less than 100 firms. For these two reasons, I discard solution one. Solution two, which is based on the assumption that firms that do not report R&D or advertising expenditures do not engage in those activities, may be acceptable when data are missing for the full series. However, it is typically untenable when there are only one or two missing values in the series. For these reasons, I have opted for combining solutions two and three for the construction of both the R&D and advertising stock variables. When a data point is missing between two non-missing ones, I follow Hall’s interpolation procedure. When the last data point of a series is missing, so that the interpolation cannot be performed, I assume it to be equal to the previous period expenditures, multiplied by the growth rate of the previous period (with respect to the one before), and adjusted for inflation using the wholesale price index for R&D, and the consumer price index for advertising. The reverse procedure is used when it is the first data point of a series that is missing.”

TABLE 3.1 – Zur Auffnahme in die Reference list (Vernon, 1971; Errunza and Senbet, 1984; Kim and Lyn, 1986; Buhner, 1987; Grant, 1987; Daniels and Bracker, 1989; Kim, Hwang, and Burgers, 1989; Han and Lee, 1998) (Buckley, Dunning, and Pearce, 1977; Haar, 1989; Morck and Yeung, 1991) (Brewer, 1981; Siddharthan and Lall, 1982; Kumar, 1984; Michel and Shaked, 1986; Chang and Thomas, 1989; Collins, 1990; Ramaswamy, 1992) (Lu and Beamish, 2001; Capar and Kotabe, 2003; Ruigrok and Wagner, 2003) (Hitt et al., 1997; Gomes and Ramaswamy, 1999; Zahra and Garvis, 2000; Qian, 2002) (Riahi-Belkaoui, 1998; Contractor et al., 2003; Lu and Beamish, 2004; Thomas and Eden, 2004; Chiang and Yu, 2005; Ruigrok et al., 2007) TABLE 3.2 (Markowitz, 1952; Vernon, 1966; Caves, 1971; Buckley and Casson, 1976; Hymer, 1976; Rugman, 1976; Johanson and Vahlne, 1977; Hennart, 1982; Barney, 1991; Amit and Schoemaker, 1993; Peteraf, 1993; Ruigrok and Wagner, 2003) TABLE 3.3 (Coase, 1937; Williamson, 1975; Jensen and Meckling, 1976; Hofstede, 1980; Siddharthan and Lall, 1982; Hannan and Freeman, 1984; Boddewyn, 1988; Brewer, 1992)

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Tallman, S. and Li, J. (1996) 'Effects of International Diversity and Product Diversity on the Performance of Multinational Firms', Academy of Management Journal 39(1): 179-196. Tesch, P. (1980) Die Bestimmungsgründe des internationalen Handels und der Direktinvestition, Volkswirtschaftliche Schriften 301: Berlin. Thomas, D.E. and Eden, L. (2004) 'What Is the Shape of the Multinationality-Performance Relationship?' The Multinational Business Review 12(1): 89-110. Tyler, B. and Steensma, K. (1998) 'The Effects of Executives' Experiences and Perceptions on Their Assessment of Potential Technological Alliances', Strategic Management Journal 19(10): 939965.

UNCTAD (2004) United Nations Conference on Trade and Development, World Investment Report 2004: The Shift Towards Services, United Nations: New York & Geneva. UNCTAD (2005) United Nations Conference on Trade and Development, World Investment Report 2005: Transnational Corporations and the Internationalization of R&D, United Nations: New York & Geneva.

Vernon,

R. (1966) 'International Investment and International Trade in the Product Cycle', The Quarterly Journal of Economics 80(2): 190-207.

Vernon, R. (1971) Sovereignty at Bay: The Multinational Spread of U.S. Enterprises, Basic Books: New York. Villalonga, B. (2004) 'Intangible Resources, Tobin's q, and Sustainability of Performance Differences', Journal of Economic Behavior & Organization 54(2): 205-231.

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Wagner, H. 2001 Towards a Contingency Theory on the Internationalization-Performance Relationship: Four Complementary Essays. Doctoral dissertation, University St. Gallen. Wagner, H. (2004) 'Internationalization Speed and Cost Efficiency: Evidence from Germany', International Business Review 13(4): 447-463. Wan, W.P. and Hoskisson, R.E. (2003) 'Home Country Environments, Corporate Diversification Strategies, and Firm Performance', Academy of Management Journal 46(1): 27-45. Wernerfelt, B. (1984) 'A Resource-Based View of the Firm', Strategic Management Journal 5(2): 171180. Westphal, J.D. and Fredrickson, J.W. (2001) 'Who Directs Strategic Change? Director Experience, the Selection of New CEOs, and Change in Corporate Strategy', Strategic Management Journal 22(12): 1113-1137. Wiersema, M.F. and Bantel, K.A. (1992) 'Top Management Team Demography and Corporate Strategic Change', Academy of Management Journal 35(1): 91-121. Williamson, O.E. (1975) Markets and Hierarchies: Analysis and Antitrust Implications, Free Press: New York.

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Chapter 4 Intangible Resources and the Internationalization Process: Path Dependence of Building a Profitable Multinational Company

4.1 Introduction The internationalization process has been a central research focus of international business research for a long time. Next to inquiries about different reasons for internationalization that seek to explore ‘why’ firms do business abroad, the internationalization process research stream has focused on the ‘how’ to become international as well. Arguably the most influential theory has been the learning theory by Johanson and Vahlne (1977). This theory describes internationalization as an incremental process of knowledge creation and foreign market commitment. One of its major contributions is that it achieves an interrelated explanation of ‘why’ and ‘how’ firms increase their presence in international markets. Concerning the question of causality it emphasizes that merits of internationalization arise from knowledge exploitation and development. As regards the question of modality the learning theory posits that firms would best follow a process of gradual expansion. This is mainly due to the fact that management has only limited capacity to absorb and integrate new information (Cohen and Levinthal, 1990). Despite its importance, little or no research exists about how intangible resources may interact with the internationalization process and how both may affect the relationship between internationalization and firm performance. As a result, little is known

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about how intangible resources influence the scope and speed of internationalization and thereby differentiate firm performance. Because of continuing increase in international competition, an investigation of the role of process characteristics offers substantial value and importance to practitioners as well. Moreover, an investigation of the interaction between intangible resources and process characteristics may refine our conceptual understanding of the internationalization-performance relationship. The present chapter consequently seeks to open up the black box of how intangible resources can be exploited worldwide and which internationalization steps firms should take in order to maximize the payoff from their intangible resources and international endeavors. In consideration with the overarching subject of this piece of research – the relationship between internationalization and firm performance – I address two interrelated research questions in particular: (1) Do intangible resources explain different process patterns of internationalization? And (2) how do differences in the internationalization process itself moderate the internationalization-performance relationship? Figure 4.1 depicts the theoretical framework of chapter four. Based on this model the theory section is structured as follows: In section 4.2.1 I investigate how intangible resources shape the internationalization process. Given the results obtained from chapter three I differentiate between five dimensions of intangibles. The first part of this analysis involves an assessment if intangible resources can also be interpreted as internationalization enablers, i.e. explain ‘why’ firms conduct business abroad and if intangible resources had an impact on the decision to internationalize for a sample of German firms during the period 2001 and 2006. In the second part I explore whether the availability of intangible resources has an impact on how multinational companies disperse their activities worldwide as well. To do so I differentiate between the general decision to conduct a higher portion of business abroad and the decision to increase the dispersion of international business activities around the globe. In section 4.2.2 I investigate how differences in the internationalization process moderate the internationalization-performance relationship. The central idea is that not only the degree of internationalization matters with regard to performance outcomes but as well the way how a company arrives there. Two fundamental process dimensions are differentiated; internationalization speed, i.e. the magnitude of change in internationalization during a given period, and international scope, i.e. the dispersion of international activities.

Degree of Internationalization

Chapter 4.2.1

Chapter 3

TMT Education

TMT Internat. Diversity

Contract-Based Know-How

Market Know-How

Technological Know-How

Intangible Resources

Chapter 4.2.1

Chapter 4.2.2

Scope

Speed

' Int = I(t=n) – I(t=0)

Internationalization Process

Figure 4.1 Research Framework with Intangible Resources and Internationalization Process Characteristics

Firm Performance

Introduction 133

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The central subject of the proposed model is that understanding the relationships among internationalization, its intangible antecedents, its performance consequences, and the role of the internationalization process can lead to a better understanding of the relationship between internationalization and firm performance. This chapter attempts to make two contributions. First, it addresses existing knowledge gaps by analyzing the influence of resource based antecedents upon the internationalization process. In other words, it posits that intangible resources are core enablers of international expansion as well as that they determine the degree to which a company can disperse its business activities worldwide. Second, by studying the moderating role of speed and scope and their relationship with intangible resources it enriches the debate on the internationalization-performance relationship conceptually.

4.2 Theoretical Background and Hypotheses 4.2.1 How Intangible Resources Shape the Internationalization Process In their pioneering study, Stopford and Wells (1972) determine that area diversification (i.e. geographic scope) and product diversification are two of the critical determinants of the success of a firm’s growth. Equally, Penrose’s work (1959, p. 250) concerned these two growth avenues: “The ‘productive opportunity’ which invites expansion is not exclusively an external one. It is largely determined by the internal resources of the firm: the products the firm can produce, the new areas in which it can successfully set up plants, the innovations it can successfully launch, the very ideas of its executives and the opportunities they see, depend as much on the kind of experience, managerial ability and technological knowhow already existing within the firm as they do upon external opportunities open to all.”

Nevertheless, as Hoskisson et al. (1993) indicate, as yet there is no consistent theoretical structure that explains the antecedents of diversification. Important theoretical contributions like the above quote by Edith Penrose however, base their explanation on a set of factors that are closely related to the characteristics of the firm and on the imperfections of the markets in which that firm operates (Buckley and Casson, 1976). It must be emphasized that the objective of this chapter is not to determine the factors that have an impact on increasing internationalization, but only to establish the relevance of intangible resources. As Caves (1982) notes, a firm’s motive for international expansion and its success are largely determined by its intangible resources.

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135

This notion is closely related to the results already obtained in Chapter three. Internalization theory posits that the ownership of information sensitive resources such as intangibles is a major motivation to do business abroad. This is because the transfer of these resources is subject to market failure (Hymer, 1976). Accordingly intangible resources are a major factor for conducting business abroad. Empirical research points to a positive relationship between a firm’s international involvement and its endowment with intangible resources (Dunning, 1993). This notion has been supported for the technological resources of US (Grubaugh, 1987) and Japanese (Kogut and Chang, 1991) based multinational companies. In sum, I suppose that international expansion by a firm represents an attempt to exploit valuable intangible resources, such as technological capabilities, established brand names, or management know-how. Therefore, intangible resources can be interpreted as antecedents to internationalization, i.e. firms with more intangible resources operate at higher degrees of internationalization and show greater propensities to increase internationalization. Such resources defy easy market transfer but are deployable in multiple markets at low cost (Teece, 1986). Therefore I hypothesize: Hypothesis 1.

Intangible resources are positively related to internationalization, such that more intangible resources are associated with higher degrees of internationalization as well as a higher propensity to increase the degree of internationalization.

The results from chapter three lend support for the notion that the construct of intangible resources is multifaceted and that not all intangible resources do enhance firm performance once they are applied in several foreign markets. For this reason I introduced the term of differing ‘internationalization potential’ of intangible resources. With this expression I refer to the possibility that the marginal performance impact of some intangible resources might deteriorate more quickly than the value of others with increasing degrees of internationalization. This argument should mainly hold for the diversity of international markets compared to the home market and not necessarily for the overall degree of internationalization. To illustrate this point, take a firm holding a valuable brand recognition that sells 40 percent of its products abroad, but only in one foreign market. The marginal value of its intangible resources would probably not deteriorate severely if this company sells another 20 percent of its overall sales in the identical foreign market. In contrast if the same company would increase its foreign sales ratio by 20 percent but sell this additional amount in another market, the mar-

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ginal value of its intangible resource would probably deteriorate more because of its idiosyncratic nature. In fact, this kind of reasoning corresponds to the underlying logic of the ‘regionalization hypothesis’ brought forward by Rugman and Verbeke (2004). Their major argument is that multinational enterprises are regional, not global. They propose that the sales of the majority of the largest multinational companies are concentrated either in the region in which their head offices are located or in that of one other region. Indeed, they find that 320, or 84 percent of the largest 380 firms worldwide are mainly home region oriented1, and another 25, or seven percent, are bi-regional (i.e. they operate in two of the three regions considered by Rugman and Verbeke)2. Only nine of the 380 firms (two percent) identified showed a balanced geographic distribution of sales across all the regions and – according to them – can be considered genuine global. In a recent paper the same authors develop a theoretical explanation for this pattern that is based on what they call the origin of ‘firm specific advantage’ (FSA) (Rugman and Verbeke, 2007, p. 201): “[...] many of these MNEs’ FSAs – although non-location bound in principle, that is, deployable and exploitable beyond home country borders – appear to be home region bound rather than having global deployment and exploitation potential. This holds especially for FSAs at the downstream side of the value chain, where products and services need to be marketed to buyers. In the case of markets seeking foreign direct investment (FDI), an MNE’s resource allocation to the host market can be interpreted as a set of onesided commitments without equivalent commitments from potential purchasers, and therefore carrying substantial risks, especially in cases where a high liability of interregional foreignness is present. In contrast, other types of FDI, focused on the upstream side of the value chain, especially sourcing and manufacturing, are often accompanied by resource commitments from other economic actors, thereby reducing the challenges posed by the liability of inter-regional foreignness, at least if these other actors are embedded in the relevant host region. Especially if inter-regional FDI in sourcing or manufacturing is meant primarily to facilitate home region sales, and is thus efficiency seeking (as is the case with much North American and European investment in China and India), the liability of inter-regional foreignness mostly does not constitute a major risk, but such investment will then not necessarily improve the MNE’s position in terms of sales in the host region either.”

The arguments by Rugman and Verbeke center on the upstream or downstream nature of international activities. While they generally question that international selling potential is truly global and argue that the downstream functions of firms are (at best) regional, the direction of the arguments brought forward in this section is

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137

somewhat different. The focus of this chapter is rather on the extent of internationalization (in terms of sales) and the way how it is influenced by intangible resources. The main argument is that the origin of intangible resources (i.e. from upstream or downstream operations) has an impact on the geographic scope of a firms’ internationalization – in terms of selling activities – as well. I suppose that this is true because upstream and downstream intangible resources differ along such dimensions as geographic fungibility or location specificity. Note that the terms geographic ‘scope’ and ‘dispersion’ are used synonymously in this chapter’s context. They both refer to the diversity of geographic regions whereas the ‘degree’ of internationalization more generally refers to international sales as portion of total sales irrespective of the regional distribution of international sales. While upstream intangible resources such as technological know-how carry the characteristics of geographic or cross-border fungibility, downstream resources presumably are not fungible to the same extent. Brands and market know-how tend to be more location bound than technological know-how. Part of this is driven by the greater degree of interaction with consumers among the marketing functions, as compared to technical activities. The same factors that make sales force systems difficult to build from scratch also limit its cross border transferability. Distribution systems tend not to be fungible across borders because of their physical nature as well as the idiosyncratic component found in the relationships between producer and consumer (Anand and Delios, 2002). Given its lack of fungibility, a strong domestic sales force system is not sufficient as an impetus for internationalization (Horst, 1974). One important insight from stage theory of internationalization (Stopford and Wells, 1972; Welch and Loustarinen, 1988) is that the more international experience a firm has the better able it will be to expand internationally. Since some of the international experience is as well located within individuals, firms that wish to expand globally might capitalize on a multinational composition of their top management team. The complexity of doing business in heterogeneous regions can thus be matched with higher diversity of the management systems. Ashby’s (1956) concept of requisite variety suggests a coherent logic. His law of requisite variety postulates that organizational adaptability and responsiveness is improved when the degree and nature of complexity extant in the environment is matched by or reflected in intra-company organizational design. Likewise, diversity in type of education may imply different skills, views, and ways of understanding and evaluating investments (Barkema and

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Shvyrkov, 2007). Therefore I suppose that TMT educational diversity increases the novelty of the geographic location of investments as well. As intangible resources differ with regard to their geographic fungibility I hypothesize that they determine the dispersion of international business activities. Therefore I contend: Hypothesis 2.

Intangible resources determine the scope of internationalization, such that upstream intangible resources relate to higher geographic diversity while downstream intangible resources relate to lower geographic diversity.

Building upon the notion of location or non-location bound value and hence fungibility of intangible resources, this chapter refines and extends the logic of Rugman and Verbeke and claims that intangible resources act as central explanatory variables that help to explain the ‘globalization vs. regionalization puzzle’. Specifically, I suppose that intangible resources do not only have an impact on the state of global sales dispersion, but that they determine as well the direction of further internationalization steps. Recently, Dunning, Fujita, and Yakova (2007) comment on the globalization vs. regionalization debate and posit that “much of the explanation for the regional concentration of FDI and MNE activity reflects that of the gross domestic product (GDP) and trade of the countries concerned, rather than any distinctive strategy on the part of investing firms” (Dunning et al., 2007, p. 177). Based on macro economic data they show that between 1990 and 2002 there is no “marked trend towards geographical diversification over the past decade” (p. 183). Nevertheless they conclude that, at least for the part of European firms, this is the case because of the novel opportunities offered by the completion of the European internal market, and the opening up of Eastern Europe. The diverse conclusions in contemporary research leave us to wonder whether the regional nature of the majority of multinational firms is mainly due to macroeconomic conditions and institutional realities in different regions of the world, or whether it is a constitutive part of the strategy of multinational firms. In order to address this issue I examine whether intangible resources can be determinants of a firm’s decision to increase its dispersion of international business activities, irrespective of its state of internationalization. As Barney (1986) notes, resources vary in terms

Theoretical Background and Hypotheses

139

of their usefulness to generate value in their application to different products or businesses, depending on their higher or lower specificity. As a consequence, the nature of resources is one of the determining factors in the direction taken by the diversification of the firm (Chatterjee and Wernerfelt, 1991; Montgomery and Hariharan, 1991). Intangible resources are easily transferable to other countries, but even more so to those markets that firms already know or to those with similar characteristics to the domestic market. Thus, firms prefer markets where they are already active to those where they are not (Davidson, 1980; Delgado-Gómez, Ramírez-Alesón, and Espitia-Escuer, 2004). This is especially true for intangible resources at the downstream side of the value chain which are less fungible (Anand and Delios, 2002). Part of this is driven by the path dependent development of downstream capabilities. In contrast intangible resources at the upstream side do not share these attributes to the same extent. These resources are more fungible as has already been laid out in the derivation of hypothesis 2. Since the value of these resources is embedded in the product itself it can be sold more easily in different regions of the world without incurring the need to be complemented with local commitments as is the case with downstream intangible resources (Rugman and Verbeke, 2003). Given that prior research has neglected the critical role of intangible resources for the direction of international diversification I reason that they might be an integral part to a solution of the regionalization debate that is still emerging among scholars in international business research. Hence I posit: Hypothesis 3.

Intangible resources determine the direction of the internationalization process, such that the availability of upstream intangible resources is associated with increasing scope of international expansion.

4.2.2 How Differences in Internationalization Paths Affect Performance In chapter three I already discussed the benefits and costs associated with internationalization and how the trade-off between them varies with growing degrees of internationalization. However, the actual benefit-cost trade-off does not only depend on the present degree of internationalization but it depends as well on the way how a company arrived there. This is because a firm’s capacity to absorb expansion is subject to constraints (Penrose, 1959; Cyert and March, 1963). Some expansion patterns increase profitability more than others. Firms that pursue extreme expansion paths face

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constraints such as absorptive capacity (Cohen and Levinthal, 1990) that together with diseconomies of time compression (Dierickx and Cool, 1989) have a negative moderating impact on the performance consequences of internationalization. Firms that expand internationally at high speed and into diverse regions – maybe with several new foreign subsidiaries at a time – will have little time to evaluate their foreign experience, understand and assimilate it and turn it to commercial ends (Cohen and Levinthal, 1994). In consequence I posit that the two elementary process dimensions speed and scope of international expansion moderate the performance consequences that are typically associated with differing degrees of internationalization. This line of argument fit into recent findings of Vermeulen and Barkema (2002) as well. These scholars apply a longitudinal design that covers 26 years and find for a sample of N = 22 Dutch multinational firms that pace, rhythm, as well as product and geographic scope of internationalization all negatively moderate the internationalization-performance relationship in a linear way. Their research framework is based on the concept of time compression diseconomies by Dierickx and Cool (1989) which describes the mechanism of diminishing returns when – everything else equal – the pace of processes increases. This assumption is based on the belief that, due to limits of absorptive capacity (Cohen and Levinthal, 1990), individuals as well as companies effectively can only handle a certain degree of increase in organizational and environmental complexity within a certain time frame. Furthermore, due to organizational inertia, organizations are slow to adjust to new environmental configurations (Hannan and Freeman, 1984). The internationalization process is subject to time compression diseconomies because it is accompanied by an increase in organizational and environmental complexity. That is, too rapid a firms’ internationalization within a given time frame will exhaust firm absorptive capacity, thereby causing inadequate adaptation of mental maps, organizational structures, systems, and processes (Calori, Johnson, and Sarnin, 1994; Nohria and Ghoshal, 1994). This, in turn, eventually triggers negative performance effects. However there are ample arguments to believe as well that the impact of expansion speed is not simply negative in a linear way but that it can be actually approximated by an inverted u-shaped pattern. In particular, this chapter contends that firms pursuing gradual expansion speeds experience performance gains because gradual expansion allows them sufficient time to: (1) effectively absorb new information and level of complexity, (2) adapt to it

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141

through suitable organizational restructuring, and then (3) reap the opportunities while holding the threats under control (Wagner, 2004). Further progression of internationalization speed at some point will lead to diminishing performance gains. Finally, firms pursuing extreme levels of internationalization speed will face a critical edge at which performance consequences start to be negative. Firms progressing in such internationalization rushes can be overstrained by the significant complexity increase within a short, compressed time frame. This is because learning and adaptation to new environments cannot be endlessly compressed in time (Dierickx and Cool, 1989). Consequently, even if higher degrees of internationalization might be associated with positive performance attributes, it requires balanced expansion to realize this potential. To conclude, this study’s conceptual framework suggests that internationalization is accompanied by benefits and costs and that the trade-off between these two elements – i.e. the net performance outcome – is moderated by internationalization speed. Most important, this moderation effect is expected to be non-linear. That is, the impact of international expansion speed on performance is argued to be positive at low and modest expansion speeds but negative at extreme expansion speeds. Thus I infer: Hypothesis 4.

Speed of the internationalization process moderates the internationalization-performance relationship, such that low and modest speed elevates the performance gains attributable to internationalization whereas high expansion speed has a negative impact.

Concerning the moderating impact of the internationalization process the preceding hypothesis deals with the amount of foreign expansion within a given period of time. The second hypothesis focuses on the regions in which the expansion takes place. Just as higher speed of the internationalization process might tax managerial and absorptive capacity so does the scope of international expansion. This is because higher diversity of markets and more heterogeneous environments necessitate additional adaptation and reconfiguration processes. Rugman and Verbeke (2007) differentiate between what they call the triad regions of the world (Europe, America, and Asia) and contend that the liability of inter-regional foreignness is considerably higher than the liability of intra-regional foreignness. Diseconomies of time compression occur when the organization is less able to absorb expansion. This may not only be the case because of the sheer amount of new information from higher internationalization speed, but may also be due to the dispersion of international activities into different regions of the world. Empirically, Hitt, Hoskisson and Kim (1997) as well as Barkema

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and Vermeulen (2002) support this notion and find a negative moderating impact of geographic scope on the relationship between foreign subsidiaries and firm performance. Nevertheless, as I already distinguish between the effects of different intangible resources on the direction of international expansion in the derivation of hypotheses two and three, this effect should also be considered with regard to performance consequences. Drawing upon this chapter’s framework about the role of intangible resources within the internationalization process and its performance consequences, it is logically consistent to expect, that the direction and magnitude of the moderating performance effect of scope of international expansion is depending upon the availability of intangible resources. While I suspect that upstream intangible resources enable firms to broaden the geographic scope of business activities to a greater extent (hypotheses two and three) this assumption is based on rational actors’ behavior, i.e. that managers’ decisions to leverage intangible resources in different regions of the world are based on the objective of maximizing firm value. To summarize I expect that the geographic scope of international expansion moderates the internationalization-performance relationship. Even more so, this moderation effect is expected to be contingent upon the availability of intangible resources. That is, a negative impact of higher geographic scope is not observable in the presence of upstream intangible resources. Consequently I hypothesize that this effect is only associated with downstream intangible resources. Hypothesis 5.

Scope of the internationalization process moderates the internationalization-performance relationship, such that higher scope of expansion has negative performance consequences in the presence of downstream intangible resources.

4.3 Method 4.3.1 Sample For practical reasons this chapter is based on the same sample as chapter three. This sampling procedure guarantees the connectivity and comparability of the results obtained in this chapter to the results from the chapter before. Hence, the analyses are based on publicly listed firms from Germany over the five year time frame between

Method

143

2001 and 2006, yielding N = 193 firms with n = 789 firm year observation. These firms can be considered representative of German medium to large non-financial multinational companies with international activities over the five year time frame between 2001 and 2006. A German setting offers an ideal setting to test the hypotheses since it offers some uniqueness as compared to other countries. First, Germany is one of the largest economies worldwide that is integrated into a wider economic union, the single European market. Second, intangible resources generally play a crucial role for the competitiveness of German firms in international markets. Data on the regional dispersion of international sales (scope) was available for a subset of n = 563 firm year observations. Table 4.1 displays the regional dispersion of international activities of firms from this studies’ German sample compared to the 500 largest firms worldwide from the pioneering study of the regionalization hypothesis by Rugman and Verbeke (2004).

Table 4.1 Regional Dispersion of International Sales

Type of MNCa

a b

German sample (N = 563) Percentage No. of Percentage intra-regional MNCs of 563 sales

Fortune 500 (N = 365)b Percentage No. of Percentage intra-regional of 365 MNCs sales

Global

23

4.1

40.5

9

2.5

38.3

Bi-regional

16

2.8

43.4

25

6.8

42.0

Host region oriented

22

3.9

30.6

11

3.0

30.9

Home region oriented

502

89.2

79.9

320

87.7

80.3

Total

563

100.0

75.3

365

100.0

71.9

Classification according to Rugman and Verbeke (2004, p. 7). See endnote one for the definitions. Data are for 2001. Data source: Rugman and Verbeke (2004, p. 7).

Although the firms from the German sample are on average smaller than the 500 largest firms in the world their sales are not less dispersed worldwide. Remarkably, the internationalization – or regionalization – pattern of the German sample is very similar to the sample of the Fortune 500 firms by Rugman and Verbeke. While a higher percentage of German firms are genuine global (i.e. four percent), the vast majority of firms is still home region oriented. Appendix 4.1 exhibits a list of global, bi-regional,

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and host region oriented firms including detailed data on their international sales dispersion. This globalization pattern corroborates the results by Rugman and Verbeke (2004) in that the majority of German firms are home region oriented as well, although they generally operate at high degrees of internationalization if compared internationally. Furthermore, it extends their notion as it shows that this pattern is not only typical for the largest firms in the world. While global business to date is frequently believed to be a domain of large multinational corporations the results indicate that large and even medium sized German firms are not less internationalized but do instead exhibit similar globalization patterns.

4.3.2 Variable Coding The measure of performance is return on assets (ROA). Internationalization is defined as the ratio between foreign sales and total sales (FSTS). Furthermore I distinguish between five individual dimensions of intangible resources: technological know-how (R&D), market know-how (ADV), contract-based know-how (CONT), top management international diversity (TMT_INT), and top management education (TMT_ACD). Chapter three, section 3.4.2 contains the coding schemes as well as detailed descriptions of these measures. Next to these measures, three other variables are introduced in this chapter: The first variable captures the geographic diversity of internationalization in terms of a firm’s present state while the other two variables are dynamic in nature as they describe characteristics of the internationalization process, i.e. speed and scope of international expansion. Geographic Diversity Geographic diversity is measured as the dispersion of sales across three different regions: Europe, America, and Asia-Pacific3. This categorization complies with the regional classification by Rugman and Verbeke (2004) who developed their regionalization hypothesis based on this scheme. Its underlying logic is the concept of ‘triad power’ that has been articulated by Ohmae (1985). Triad power refers to the fact that – by the time Ohmae published his book – the world’s largest MNCs were concentrated in the US, Europe, and Japan. The problem faced by many of these MNCs was that they sell engineered commodities, i.e. innovative and differentiated products and services, resulting from capital intensive production and knowledge development. Unfortunately, these products quickly lose their monopoly status when transferred

Method

145

across these regions. According to Ohmae (1985) this is because of ‘global impasse’. With this term he describes the problem that even the largest companies face constraints to repeat their home triad base market share in the two other triad regions. In Ohmae’s view a strong presence in all three regions is necessary to recover substantial innovation costs and in order to avoid surprises, i.e. unanticipated strategic moves by rivals from other regions (Rugman and Verbeke, 2004). I considered alternative regional classifications as well. One influential classification has been developed by Ronen and Shenkar (1985) and has recently been applied by Dunning et al. (2007) in their contribution to the ongoing debate about the regionalization hypothesis. It is based on six regional clusters: an Anglo cluster, a Latin European cluster, a Nordic and Germanic cluster, a Latin American cluster, a Far Eastern cluster, and one cluster named ‘Other’. Nevertheless, as Rugman and Verbeke (2007, p. 203) note: “It is clear that the cultural clusters adopted are merely an academic artifact, intellectually appealing but relatively far removed from the practice of international corporate strategy and geo-political reality.” Consequently I refrained from using this classification and instead relied on the distinction of the triad regions. Furthermore the later classification requires less detailed information on the international dispersion of company sales and therefore augments the amount of available firm year observations. In order to estimate the dispersion of sales across the triad regions I calculated the distribution of international sales accounted for by each of the three regions. In a second step I calculated the standard deviation of the distribution and subtracted in from 1. The presumption is that the nearer the standard deviation approaches 0 (which would mean that international sales are equally distributed, i.e. 33 percent in each of the triad regions), the more globalized are the sales of a firm and hence the measure of international scope would take a value of 1. I will term this measure foreign sales dispersion (FS_Disperison). Note that the denominator of the ratios is the sum of foreign sales and that the numerators are the foreign sales derived from Europe, America, and Asia from the perspective of a German firm. Next to this variable I calculated a slightly different measure that will be termed total sales dispersion (TS_Dispersion). In this case the denominator is the sum of total sales and the numerators are the total sales derived from Europe, America, and Asia. The difference is that foreign sales dispersion captures the dispersion of sales across the triad regions irrespective of the degree of internationalization (measured as foreign sales to total sales) while the total sales dispersion is, by definition, not independent of the degree of

146

Intangible Resources and the Internationalization Process

internationalization. Hence, the measure of foreign sales dispersion permits the separation of two effects, namely that of being more international in terms of scale from the effect of being more globally dispersed, in terms of higher scope. Therefore I decide to rely on the measure of foreign sales dispersion as measure of geographic diversity of internationalization in the first place. However, since the correlation of these two measures is very high (r = .91, see Table 4.2) results based on the measure of total sales dispersion are very similar to the ones obtained from foreign sales dispersion. Speed of expansion Internationalization speed is derived from the measure of internationalization that I already introduced in chapter three, i.e. foreign sales to total sales (FSTS). Internationalization speed is then proxied with the change in FSTS over a two year time frame ('FSTS_2year). The larger the change of this ratio over the two year period, the higher the expansion speed. The narrow investigation time frame of two years has been explicitly chosen because of two reasons. First, the pursued internationalization speeds of firms show a wide range of variation (i.e. some firms progressed slowly and others rapidly), and second, the short time frame facilitates the capture of expansion speed effects on firm performance because it makes the absorptive capacity constraints as well as diseconomies of time compression identifiable. Overall, the chosen time frame allows a valid test of the impact that international expansion speed has on firm performance. For validation purposes I calculated these variables as three year and five year differences as well. Scope of expansion Just like the measure of speed is based on the FSTS ratio, the measure for scope of international expansion is based on the dispersion of foreign sales (FS_Dispersion). Scope of expansion ('S.D._FS_2year) is defined as change of FS_Dispersion over a two year time frame. It is coded as dummy variable that takes the value of one if the standard deviation of foreign sales becomes smaller within the two year time frame, i.e. firms become more global. Again, I calculated this variable as three year and five year differences as well. Table 4.2 provides descriptive statistics and a correlation matrix of the variables for the sample of firms that report data on the regional dispersion of international sales.

.566

.678

.616

.061

.089

.264

.445

.448

.494

.494

.509

.485

.043

.030

.042

.089

.340

1. FSTS

2. FS_Dispersion

3. TS_Dispersion

4. 'FSTS_2year

5. 'FSTS_3year

6. 'FSTS_5year

7.'S.D._FS_2year

8.'S.D._FS_3year

9.'S.D._FS_5year

10.'S.D._TS_2year

11.'S.D._TS_3year

12.'S.D._TS_5year

13. R&D

14. ADV

15. CONT

16. TMT_INT

17. TMT_ACD

.290

.159

.072

.037

.041

.504

.501

.501

.503

.498

.498

1.43

.543

.431

.150

.169

.237

S. D.

2

3

4

5

-.03 -.07 -.11 .05 -.01 -.11 -.04

.31**

.19** .19** .15** .23** .18** .17* .22†

.27** .27** .34**

.16

.18

-.07

.03

.05

.21

-.12

-.06

-.08

-.06

.09

.08

.03

-.11

-.10

-.10

6 8

9

.03

.05 .11*

.13 .16

.09† .03

.18** .14** .19** .11* .03

-.01

-.03

-.03

-.11*

-.08†

.29** .18** .16**

11

-.01

.05

.16

.12†

07 .06

.

.04

-.01

.09

.08

.00

-.08

.08

.06

-.09

-.10

.16** .16*

.36** .58** .67** .59** .76**

-.06

-.08*

10

.51** .64** .48** .71**

.61** .45** .46**

.70** .77**

.69**

7

-.12** -.19** -.17** .15** .12* .42** -.09† -.13* -.21†

.26*

.25*

.10

.18**

.18**

.18**

.11* .16**

-.36** -.24* -.24* .94** .98**

-.30** -.21** -.23** .92**

-.26** -.18** -.19**

.79** .91**

.06*

1

Notes: 'FSTS_2year: N = 353, 'FSTS_3year: N = 257, 'FSTS_5year: N = 77. 'S.D._FS_2year: N = 353, 'S.D._FS_3year: N = 257, 'S.D._FS_5year: N = 77. 'S.D._TS_2year: N = 330, 'S.D._TS_3year: N = 230, 'S.D._TS_5year: N = 66. † p < .10. * p < .05. ** p < .01 (all two-tailed tests).

Mean

Variables

Table 4.2 Descriptive Statistics and Correlations (N = 563)

.01

-.05

.14

-.10

.14

12

-.07*

.16**

.06

-.10*

13

-.02

.00

.14**

14

-.01

-.13**

15

-.05

16

Method 147

148

Intangible Resources and the Internationalization Process

4.3.3 Analytical Approach In order to test hypotheses one to three I regressed measures of internationalization on five intangible resources (technological know-how, market know-how, contract-based know-how, TMT diversity, and TMT education) after controlling for firm size, product diversification, leverage, and industry. Hypothesis four was tested using moderated regression analysis. This procedure has already been applied in chapter three and has been thoroughly described there (section 3.4.4). Speed of internationalization is the moderator variable. Because a curvilinear moderation is hypothesized, the interaction term between degree of internationalization and internationalization speed is tested in a linear as well as a squared form. I tested hypotheses five by regression analysis as well. Explicitly, the research equation is specified as follows: 5

'ROAt 2 t0

f(

5

¦ Int.resource , FS _ Dispersion, 'S .D. _ FS _ 2 year, ¦ 'S.D. _ FS _ 2 year * Int.resource , H ), j

1

j

1

where 'ROA is the change of firm performance, Int.resource with its j subscript denotes the different intangible resources, FS_Dispersion is the dispersion of foreign sales and 'S.D._FS_2year describes the scope of expansion over the two year period. The performance impact of scope of expansion is estimated in a two step procedure. In the first step I tested whether foreign sales dispersion and expansion scope are associated with performance differences. In the second step I add an interaction term and explore whether the performance impact of expansion scope is contingent upon the availability of intangible resources. I tested all the models using panel data OLS regression with pooled time-series, cross-sectional data. As already noted, this procedure is well established in international business research and several researchers that rely on multiyear data items draw upon this statistical procedure (Gomes and Ramaswamy, 1999; Contractor, Kundu, and Hsu, 2003; Ruigrok and Wagner, 2003; Ruigrok, Amann, and Wagner, 2007). Furthermore, multicollinearity of variables was not a concern in this chapter. I checked the variance inflation factor (VIF) in each of the models of which none exceeds the threshold of ten (Burns and Bush, 2000). Additionally all of the relevant correlations were lower than 0.7.

Results

149

4.4 Results Table 4.3 and table 4.4 provide the statistical results for hypothesis one. Foreign sales to total sales is the dependent variable in table 4.3 and the propensity to increase internationalization (two year change of foreign sales to total sales) is the dependent variable in table 4.4. In table 4.3 model one includes the control variables in which firm size, leverage, and industry relate to the degree of internationalization of the firm. The impact of intangible resources is tested throughout models two to six. All intangible resources significantly interact with internationalization. However market knowhow and contract-based know-how are negatively related to the degree of internationalization. In contrast technological know-how and top management team international diversity are strongly associated with higher degrees of internationalization and all of the models in table 4.3 are highly significant. The joint explanatory power of the individual facets of intangibles is 13.1 percent, as one can see from model seven. That is, intangible resources are important antecedents to the internationalization of the firm. In contrast the measures of Tobin’s q and hedonic q do not relate significantly to the degree of internationalization. This finding is in line with the results obtained from chapter three. The construct of intangible resources is multidimensional and the effects of intangible resources on outcome variables that relate to the internationalization of the firm vary because of their different characteristics. Therefore I refrain from applying measures of Tobin’s q and hedonic q to test the hypotheses, but report the results for these two measures for information only in Appendix 4.2. Table 4.4 contains the results for dynamic aspects of internationalization during the period 2001 and 2006. Market know-how and TMT international diversity are the only two variables that positively relate to firms increasing their presence in international markets during that time. All other intangible resources that relate to degree of internationalization do not relate to increasing degrees of internationalization during this five year period. I tested for different time frames as well. The results are robust for three year change of internationalization and five year change of internationalization (see Appendix A 4.2). However one should treat the results for five year time frame with caution, since the number of observations is often low compared to the number of variables under consideration in the analysis. In sum, market know-how is the strongest predictor for increasing internationalization during this period. Given the different effects of intangible resources on the degree of internationalization and the propensity to increase internationalization during 2001 and 2006 hypothesis one can be partially supported.

150

Intangible Resources and the Internationalization Process

Table 4.3 Regression of Intangible Resources on Degree of Internationalizationa (Foreign Sales to Total Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

.356** (6.86) .028** (4.63) -.002 (-.49) -.167** (-3.17) .156** (7.26) -.070* (-2.25)

.233** (4.36) .029** (5.11) -.004 (-.78) -.060 (-1.13) .131** (6.21) -.077* (-2.58) 1.50** (6.65)

.389** (7.48) .026** (4.45) .001 (0.13) -.188** (-3.56) .153** (7.19) -.067* (-2.18)

.363** (6.98) .028** (4.71) -.003 (-.50) -.172** (-3.27) .157** (7.33) -.064* (-2.08)

.403** (7.95) .019** (3.27) -.001 (-.19) -.197** (-3.86) .162** (7.78) -.059† (-1.96)

.366** (7.09) .022** (3.52) -.002 (-.32) -.163** (-3.11) .157** (7.35) -.071* (-2.30)

.097** (2.97)

.338** (6.28) .015* (2.41) .001 (.21) -.123* (-2.37) .140** (6.98) -.059* (-2.08) 1.27** (5.60) -.526* (-2.23) -.164 (-1.39) .396** (7.11) .086** (2.67)

.220 .212 .012 26.17**

.339 .327 .131 28.28**

7. R&D 8. ADV

-.745** (-3.00) -.214† (-1.71)

9. CONT 10. TMT_INT

.371** (6.44)

11. TMT_ACD R2 Adjusted R2 ' R2 F-Statistic †

.208 .201 29.22**

.266 .258 .058 33.61**

.220 .212 .012 26.20**

.212 .203 .004 24.92**

.263 .255 .055 33.02**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Results

151

Table 4.4 Regression of Intangible Resources on Propensity to Internationalizea (Two Year Change of Degree of Internationalization) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

-.123 (-.92) .005 (.30) -.015 (-1.14) .344 (2.51) -.052 (-.97) .200 (2.52)

-.148 (-1.05) .005 (.30) -.015 (-1.14) .367* (2.56) -.057 (-1.05) .201* (2.53) .342 (.54)

-.233† (-1.74) .010 (.67) -.026* (-1.99) .409** (3.01) -.046 (-.88) .193* (2.48)

-.109 (-.82) .005 (.35) -.014 (-1.14) .333* (2.44) -.050 (-.93) .213** (2.67)

-.100 (-.76) -.007 (-.43) -.013 (-1.06) .359** (2.64) -.051 (-.95) .199** (2.53)

-.116 (-.86) .004 (.22) -.014 (-1.12) .339* (2.46) -.051 (-.95) .201* (2.53)

.045 (.29)

-.217 (-1.46) -.002 (-.10) -.025* (-1.98) .430** (3.01) -.045 (-.84) .211** (2.70) .302 (.46) 2.55** (3.94) -.488† (-1.65) .188* (2.08) .094 (.61)

.058 .042 .000 3.57**

.117 .092 .059 4.55**

7. R&D 8. ADV

2.30** (3.60)

9. CONT

-.440 (-1.50)

10. TMT_INT

.194* (2.30)

11. TMT_ACD R2 Adjusted R2 ' R2 F-Statistic †

.058 .044 4.28**

.059 .043 .001 3.61**

.092 .076 .034 5.84**

.064 .048 .006 3.95**

.072 .056 .014 4.49**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

152

Intangible Resources and the Internationalization Process

The results for the test of hypothesis two are presented in Table 4.5. Geographic diversity, measured by foreign sales dispersion, is the dependent variables in all models. The effects of intangible resources are similar to the ones obtained from table 4.3. Although foreign sales dispersion is independent from the degree of internationalization from a conceptual point of view the same variables that relate to higher internationalization are as well associated with higher dispersion of international business activities across the triad regions. Upstream intangible resources such as technological know-how, TMT international diversity, and TMT education relate to higher geographic diversity while contract-based know-how and downstream intangible resources such as market know-how relate to lower geographic diversity. Again all of the models are significant and intangible resources jointly explain 8.1 percent of the regionalization vs. globalization of German firms after controlling for other effects known to relate to foreign sales dispersion. Therefore hypothesis two can be supported. For the results of Tobin’s q and hedonic q please refer to Appendix A 4.3. Table 4.6 reports the results for hypothesis 3. Scope of expansion (i.e. the change of foreign sales dispersion) is the dependent variable in all of the models. Technological know-how as well as the international diversity of the top management team are positively related to higher dispersion of international activities across the triad regions, as can be seen in models two and five. While German firms with downstream intangible resources in the form of market know-how increased their degree of internationalization between 2001 and 2006 (see table 4.4), this apparently does not automatically come along with higher dispersion of international activities. Indeed, only firms that possess a high stock of upstream intangibles in relative terms compared to the rest of the firms at a given moment in time have a greater tendency to increase their scope of international business activities in the two subsequent periods. Therefore hypothesis three can be supported. Again I tested whether the selection of different time frames has an impact on effect size estimates. The results are depicted in Appendix A 4.4. They confirm the results obtained by two year change of scope of international expansion, although at lower significance. Furthermore I applied an alternative measure of scope of expansion, i.e. the change in total sales dispersion. As one would expect the results are not materially different to the ones obtained by change in foreign sales dispersion because of their high correlation. Please refer to Appendix A 4.4 for the results of alternative time frames.

Results

153

Table 4.5 Regression of Intangible Resources on Scope of Internationalizationa (Dispersion of International Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

.424** (12.61) .029** (7.50) -.002 (-.63) -.144** (-4.23) .168** (12.08) -.006 (-.28)

.342** (9.93) .030** (8.10) -.003 (-.94) -.074* (-2.15) .151** (11.12) -.011 (-.55) .990** (6.78)

.459** (13.69) .028** (7.29) .001 (.43) -.167** (-4.96) .165** (12.14) -.003 (-.14)

.429** (12.78) .029** (7.62) -.002 (-.64) -.148** (-4.36) .169** (12.20) -.001 (-.07)

.433** (12.78) .027** (6.92) -.002 (-.54) -.150** (-4.39) .169** (12.17) -.004 (-.18)

.429** (12.81) .026** (6.38) -.002 (-.49) -.142** (-4.18) .168** (12.17) -.006 (-.31)

.055* (2.57)

.400** (11.19) .026** (6.34) .001 (.16) -.110** (-3.20) .154** (11.51) -.002 (-.12) .851** (5.66) -.658** (-4.20) -.137† (-1.75) .082* (2.23) .029 (1.38)

.355 .348 .008 51.02**

.428 .417 .081 41.27**

7. R&D 8. ADV

-.826** (-5.21)

9. CONT

-.180* (-2.23) .073† (1.90)

10. TMT_INT 11. TMT_ACD R2 Adjusted R2 ' R2 F-Statistic †

.347 .342 59.31**

.397 .391 .050 61.09**

.378 .371 .031 56.28**

.353 .346 .006 50.60**

.352 .345 .005 50.26**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

154

Intangible Resources and the Internationalization Process

Table 4.6 Regression of Intangible Resources on Scope of Expansiona (Two Year Change of Dispersion of Foreign Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

.243 (1.52) .018 (.94) -.022 (-1.44) .116 (.67) .198** (3.07) .063 (.65)

.084 (.50) .019 (1.01) -.024 (-1.57) .263 (1.46) .155* (2.35) .066 (.69) 2.15** (2.74)

.281† (1.70) .016 (.84) -.019 (-1.19) .096 (.55) .194** (2.99) .061 (.63)

.241 (1.50) .018 (.93) -.022 (-1.44) .118 (.68) .198** (3.06) .062 (.64)

.290† (1.78) .012 (.60) -.022 (-1.42) .085 (.48) .202** (3.13) .067 (.70)

.254 (1.58) .010 (.50) -.022 (-1.41) .133 (.77) .197** (3.05) .066 (.68)

.132 (1.30)

.190 (1.04) .004 (.20) -.021 (-1.30) .212 (1.15) .160* (2.42) .069 (.71) 1.88* (2.24) -.555 (-.61) .112 (.30) .356† (1.93) .096 (.86)

.044 .026 .005 2.46*

.070 .041 .031 2.42**

7. R&D 8. ADV

-.808 (-.90)

9. CONT

.040 (.11) .317† (1.77)

10. TMT_INT 11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic

.039 .024 2.61*

.061 .043 .021 3.47**

.041 .023 .002 2.31*

.039 .021 .000 2.17*

.048 .031 .009 2.74*

†

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Hypothesis four and five concern the moderating impact of internationalization process characteristics upon the internationalization-performance relationship. The results for speed of internationalization are illustrated in table 4.7. Model one is the base line model. It comprises the control variables and the direct performance impact of the change of degree of internationalization over the past two years in its linear in quadratic form. Change in internationalization does not exhibit a direct effect on firm performance. Model two adds the effect of internationalization on firm performance. The sigmoid curve type pattern already found in chapter three becomes obvious again. Model three and four explore the moderating impact of the speed of international expansion on the internationalization-performance relationship. Both, the linear term in model three as well as the linear and quadratic terms in model four are significant.

Results

155

The results indicate that the moderating impact can best be described by an inverted u-shaped pattern, i.e. international expansion speed has a positive impact at low and modest expansion speed that eventually becomes negative at high internationalization speeds. As all of the models are significant, hypothesis four can be supported. Results for the moderating impact of change of internationalization for three years and five years in history are available in Appendix A 4.5. The direction of the effect size estimates is similar, although at lower levels of significance. Table 4.8 exhibits the results for the test of hypothesis five. Model one comprises the effects of intangible resources on the change of profitability during the subsequent two periods. Model two investigates whether the scope of internationalization and the change of international scope predict performance changes. None of these variables becomes significant. These results do not lend support for the position that higher scope of international expansion would automatically trigger negative performance pressures. Models three to seven test the joint effects of higher scope of international expansion in combination with the existence of intangible resources. The moderating term with market know-how and contract-based know-how is associated with declining performance at a significant level. In contrast the negative performance impact of higher scope of international expansion does not become significant in conjunction with technological know-how and TMT education. All the more, the direction of the moderator term of expansion scope and TMT international diversity becomes positive although not at a significant level either. Given that higher scope of international expansion only relates to negative performance consequences in the presence of downstream intangible resources hypothesis five can be supported. Again I tested whether the choice of different time frames has an impact on effect size estimates. As has been the case with analyses of change aspects before, the results for three year and five year time frames resemble the ones displayed in table 4.8. These tables are depicted in Appendix A 4.6. Models with Tobin’s q and hedonic q in turn do not become significant (see also Appendix A 4.6). This again supports the superiority of analyses based on individual dimensions of intangible resources.

156

Intangible Resources and the Internationalization Process

Table 4.7 Moderation of Speed of Expansiona (Change of Internationalization over Past Two Years) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service  'FSTS_past2years 8. 'FSTS_past2years (squared)

1

2

3

4

.122** (5.49) .009** (3.48) .003 (1.63) -.260** (-11.97) .006 (.73) -.008 (-.68) -.017 (-.48) .144 (.96)

.094** (2.86) .009** (3.68) .003 (1.45) -.262** (-11.96) .009 (1.02) -.007 (-.60) -.014 (-.37) .108 (.71) .293 (1.64) -.774† (-.196) .545* (2.06)

.080* (2.40) .010** (3.94) .002 (1.26) -.269** (-12.22) .008 (.97) -.007 (-.59) .004 (.09) -.152 (-.83) .377* (2.07) -.901* (-2.27) .598* (2.26) .515* (2.41)

.075* (2.27) .010** (3.90) .003 (1.34) -.271** (-12.33) .008 (.87) -.007 (-.57) .053 (1.12) -.310 (-1.53) .407* (2.24) -.950* (-2.39) .628* (2.38) .564** (2.62) -1.61† (-1.85)

.240 .229

.248 .232 .008 15.34**

.258 .240 .018 14.62**

.263 .244 .023 13.76**

9. FSTS 10. FSTS (squared) 11. FSTS (cubic) 12.  13. 

FSTS* 'FSTS_past2years FSTS* 'FSTS_past2years (squared)

R2 Adjusted R2 ' R2 F-statistic †

21.06**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Discussion

157

Table 4.8 Moderation of Scope of Expansiona on Change of ROAb over Two Years (Two Year Change of Dispersion of Foreign Sales) Variable 1. Intercept 2. R&D 3. ADV 4. CONT 5. TMT_INT 6. TMT_ACD

1

2

3

4

5

6

7

8

.031** (2.92) -.268* (-2.11) -.059 (-.37) .114† (1.80) .016 (.53) -.026 (-1.54)

.022 (1.33) -.248† (-1.87) -.060 (-.36) .112† (1.76) .016 (.51) -.026 (-1.50) .015 (.47) .007 (.74)

.015 (.86) -.118 (-.74) -.044 (-.27) .106† (1.66) .010 (.32) -.026 (-1.47) .020 (.65) .007 (.77) -.388 (-1.47)

.014 (.85) -.219† (-1.65) .076 (.43) .117† (1.85) .016 (.54) -.026 (-1.49) .020 (.67) .004 (.43)

.020 (1.21) -.274* (-2.08) -.066 (-.41) .240** (3.07) .018 (.58) -.026 (-1.48) .008 (.27) .006 (.67)

.024 (1.41) -.240† (-1.80) -.057 (-.35) .110† (1.73) -.003 (-.08) -.026 (-1.51) .013 (.42) .007 (.74)

.015 (.83) -.252† (-1.90) -.051 (-.31) .112† (1.77) .015 (.49) -.008 (-.37) .019 (.62) .008 (.79)

-.042 (-1.24)

.024 (1.48) -.255 (-1.23) -.277* (-2.05) .089 (1.41) .014 (.46) -.025 (-1.48) .024 (.77) .006 (.66) -.264 (-.97) -.708† (-1.62) -.340* (-2.61) .022 (.36) -.045 (-1.30)

.046 .022 .007 1.92†

.084 .050 .045 2.41**

7. FS_Dispersion 8. 'S.D._FS_2year 9. 'S.D._FS_2year* R&D 10. 'S.D._FS_2year* ADV 11. 'S.D._FS_2year* CONT 12. 'S.D._FS_2year* TMT_INT 13. 'S.D._FS_2year* TMT_ACD R2 Adjusted R2 ' R2 F-statistic

-.980* (-2.21) -.352** (-2.76) .038 (.62)

.039 .024 2.63*

.041 .020 .002 1.97†

.047 .024 .008 2.00*

.055 .032 .016 2.36*

.063 .040 .024 2.71**

.042 .018 .003 1.77†

†

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics. b Change of ROA is calculated as the difference between ROAt+2 and ROAt=0.

4.5 Discussion This chapter addresses the important but as yet unresolved question if intangible resources affect patterns of the internationalization process and how differences in the internationalization process itself moderate the internationalization-performance relationship. Given that intangibles constitute major success factors for the internationalization of the firm this question is of foremost relevance to advance our understanding with respect to the internationalization process from a conceptual point of

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view as well as for practitioners willing to expand abroad. This study makes an important contribution as it opens up the black box of how intangible resources frame the internationalization process and how different process patterns ultimately affect firm performance. Furthermore, it develops the mechanisms through which this occurs. One pattern can be observed throughout the analysis; the idiosyncratic nature of the different intangible resources prevents from determining a universal effect. Instead the individual characteristics of intangibles matter with regard to the internationalization process and performance consequences. The results yield some essential insights. First, they demonstrate that intangible resources are a fundamental ‘raison d’être’ of multinational companies, especially if these intangibles originate from the upstream side of the value chain. Not only do these intangible resources determine the degree of internationalization at which a firm ideally operates but also the propensity to increase internationalization during the five year period between 2001 and 2006. Second, intangible resources do not only explain why firms can augment performance by doing business abroad but their very nature determines as well the direction and optimum scope with regard to breath of internationalization in terms of regions served. Third, not only the scale and scope of internationalization have an impact on firm performance but as well the way how a company arrives there. While low and modest speeds of international expansion have a positive impact on performance, this effect eventually becomes negative for firms progressing in rushes. Furthermore, higher scope of international business activities must not necessarily result in performance pressures as has been proposed by Vermeulen and Barkema (2002). Instead the negative performance consequences from higher scope of internationalization will be encountered only if higher scope of expansion involves substantial amounts of intangibles at the downstream side of the value chain. This is because the development of these resources is path dependent and consequentially more location bound in nature. Hypothesis one lends support to internalization theory. Intangible resources refuse market transfer but are deployable in multiple markets if the transfer occurs within the firm. Therefore, the stock of intangibles is a fundamental driver of internationalization and the value of internationalization stems from an increase in the economic rents that accrue to these firm specific resources (Teece, 1986). With regard to downstream intangible resources the results differ for state aspects of internationalization and dynamic aspects of the propensity to increase internationalization between 2001 and 2006. Downstream intangible resources are associated with lower absolute

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levels of internationalization. Nevertheless, this does not have to mean that these resources impede internationalization. Market know-how is a strong predictor of increasing levels of internationalization during the five year time frame. An explanation of this phenomenon can be based on the different mobility of resources. While imperfect inter-firm mobility is a prerequisite for the sustainability of competitive advantage (Barney, 1991), upstream and downstream resources differ with respect to their intra-firm mobility, i.e. the mobility between diversified units. According to Fang et al. (in press.) the transfer of marketing capabilities within business units of a firm occurs more slowly as compared to the transfer of technological capabilities. Considering that the transfer of market know-how across national borders with concurrent cultural and linguistic barriers is toilsome, it is plausible that the internationalization process of firms with considerable downstream intangible resources progresses more slowly as compared to other firms. This could be true for entire industry sectors as well. Although I control for industry affiliation in this analysis, i.e. manufacturing and service sector, I cannot rule out that more specific industry or competitive patterns have an impact when and to what extent internationalization takes place. Hypotheses two and three reveal that differing ‘internationalization potential’ of intangible resources is an essential explanatory variable for the scope of international selling activities. This has important implications for managerial practice as well. Without doubt there are several motivations for internationalization. While the internationalization of upstream activities such as research and development or production is motivated by knowledge or efficiency seeking, internationalization at the downstream side is mainly motivated by market seeking (Dunning, 1993). In consideration of this chapters’ finding that intangible resources matter with regard to the optimum scope of business activities, one important managerial implication is that executives should carefully evaluate their stock of intangibles at hand. Specifically it suggests that intangible resources should be an integral part of the process of strategy development, especially with regard to the formulation of regional strategies. This again implies recurrent evaluation and permanent controlling of the different dimensions of intangibles with regard to opportunities as well as threats they provide in international markets. The insight of this chapters’ analysis is that this is not only an important strategic task because internationalization offers potential for the generation of valuable intangible resources (described by knowledge or efficiency seeking motives) but that intangibles are important determinants with regard to the optimum strategy in

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terms of the number and diversity of geographic regions a firm should serve with its products or services. Intangible resources such as technological know-how and TMT international diversity do not only relate to higher levels of global integration of business activities but they are associated with continuing rise of globalization during the five year period between 2001 and 2006 as well. The value from technological know-how is embedded in the product or service itself. Selling products of this kind across multiple countries and regions needs fewer location specific investments and is less risky as compared to products where the value of intangible resources is based on customer relationships. Upstream intangible resources are driving forces of globalization and might ultimately enable more firms’ achieving a status of balanced sales across all major regions in the world. Although market know-how is the strongest predictor for increasing internationalization between 2001 and 2006 this does not imply that firms increased their scope of internationalization in terms of the distribution of their international sales across the triad regions. Instead these firms followed a strategy of concentration, i.e. they headed for a stronger presence in the regions in which they were already active. This result demonstrates that downstream intangible resources do not lack internationalization potential in general, but that their potential for quick and easy transfer into many numerous different environments is constrained. With downstream intangible resources an international strategy of concentration seems more promising than a strategy of diversification. These results are in line with those obtained from other regions of the world. Yu (1990), in an analysis of investment decisions by US firms in Japan, found that previous experience in one country induces subsequent investments in the same country. Hennart and Park (1994) confirm this result for Japanese firms. A strategy of concentration is beneficial because of already existing relationships with customers or other types of synergies obtained from the activities carried out in previous investments. Moreover, the availability of customer and market related intangible resources allows firms to exploit these resources to erect entry barriers. The explanation for the moderating effect of speed upon the relationship between internationalization and firm performance is based on the concept of absorptive capacity in conjunction with diseconomies of time compression. Given that extreme pace of international expansion is detrimental to firm performance, firms willing to expand internationally should take care to avoid frictions from suboptimal reconfigu-

Limitations

161

ration and alignment of systems, structures, and processes. Learning and the integration of new knowledge obtained from international markets into firm routines becomes a crucial success factor within the internationalization process. Firms that accomplish to develop their potential and realized absorptive capacity (Zahra and George, 2002) can reap higher benefits from internationalization. Potential absorptive capacity relates to the effective acquisition and assimilation of relevant information while realized absorptive capacity is related to the transformation and exploitation of the obtained knowledge into competitive advantage. Given that German firms have a relatively high internationalization experience (Wagner, 2001) these findings may also be interpreted to suggest that speed of expansion remains an important factor for internationalization success even for organizations with considerable experiential knowledge. The results of hypothesis five lend support for the notion that the application of contingency approaches can be a fruitful avenue to expand knowledge on different factors that have an impact on the way how internationalization relates to firm performance and especially on how these factors interact. I could not find support for a uniform pattern of the moderating role of scope of expansion such as has been proposed by Vermeulen and Barkema (2002). The inclusion of intangible resources within this research framework allows a more fine-tuned analysis and reveals that benefits from higher scope of internationalization might more than compensate for the costs associated with more heterogeneous environments under certain circumstances. The positive sign of the moderating effect of higher scope of expansion in combination with an international diverse composition of the top management team supports this assumption. Higher international diversity at the part of the top decision makers may be a proxy for higher absorptive capacity and therefore already hint to a promising way how to handle growing international complexity.

4.6 Limitations The empirical approach is akin to the one already applied in chapter three. Consequently the same limitations also apply to this chapter with regard to the sample and methodological approach. Although German firms represent a fruitful setting for this studies’ research framework, the focus on German firms is, like any other single country investigation, simultaneously a study limitation.

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I investigate the internationalization process for a five year time frame. Consequently this study is limited in how much it adds to an understanding how internationalization patterns evolve over longer time horizons. Longitudinal analyses based on samples that cover the entire internationalization history of firms from the first international market entry on might yield valuable insights how the exploitation and creation of intangible resources takes place in international markets and how they interact with each other. However, all databases cover only a limited number of years back in history and therefore the analyses in this study were bounded by the availability of data. Furthermore it is noteworthy that the firms in this sample do not form a random sample. They all survived the five year period between 2001 and 2006. Consequently I was not able to analyze whether extreme internationalization paths with regard to speed or scope of international expansion increase the risk of going bankrupt or being taken over. Future research is welcome to investigate the effects of extreme paths of internationalization on profitability and survival. The research setting with regional dispersion of international activities prevents from using measures of international diversification other than foreign sales to total sales because of data unavailability. Firms are required to provide data on geographical sales dispersion only, not on asset or subsidiary dispersion between home country and foreign countries, under German company law. Thus, statistically reliable and complete internationalization data especially with regard to detailed regional and country specific operations is only obtainable for the sales based dispersion of international activities. However, this study is the first that distinguishes between regional activities of German firms, since data on these activities was generally not availability until firms started to adopt to international accounting standards in the late 1990s. Furthermore, this study is based on German large to medium sized firms. It may be argued that its findings are not transferable to smaller firms. Smaller firms often lack financial and managerial resources (Shuman and Seeger, 1986; Smith et al., 1988; Carrier, 1994). Research how resource constraints limit the speed and scope of international expansion or lead to differing internationalization paths altogether is therefore highly appreciated.

4.7 Implications for Future Research The findings from this chapter suggest two key implications for future research on the internationalization-performance relationship. The first is temporality, i.e. the

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163

tendency of cross-sectional analyses to look at the degree of internationalization of a company at a particular point in time. This kind of research design inevitably fails to capture the dynamic nature of the contemporary business reality with regard to internationalization. Although genuine global firms are still a rare species, the results of this chapter indicate that there is a trend towards globalization that is associated with the availability of upstream intangible resources. Whether this trend will eventually lead to a higher portion of firms becoming global with balanced sales across all major regions of the world must be left to future investigation. Maybe though, Rugman and Verbeke (2004, p. 16) are right in the end as they conclude: “When globalization does occur, it is restricted to the upstream end of the value chain. Some of the world’s largest MNEs master the art of connecting globally dispersed inputs. These can be in the form of financial capital, human capital, R&D knowledge, components, etc., and can be integrated to better serve home region clients. Hence it appears possible to be global at the upstream end of the value chain, and much can undoubtedly be learned from observing and imitating the routines of global leaders in this portion of the value chain.”

The second implication for future research concerns the introduction of contingency approaches to the research question if, why, and how internationalization relates to firm performance. For example a firm that currently operates at a 50 percents FSTS ratio may have rushed there within two years from a scale of 20 percent, or may have already been operating at this level of internationalization for several years. In other words, performance implications may differ greatly between such firms. Again, such patterns will not be identifiable through cross-sectional analyses. Thus, as the results of this study indicate, future research may benefit from the application of longitudinal research designs. There are several areas where knowledge on contingencies and path dependencies are central to understand how internationalization exerts its influence on performance. For example this study shows that low and moderate expansion speeds are more beneficial to firm performance than extreme speed of internationalization. None the less firms will still be confronted with a trade-off between either accepting frictions from higher expansion speed or being left with fewer foreign subsidiaries to benefit from. Low expansion speed will help to avoid misalignment between international diversified units and guarantee proper evaluation and integration of new information obtained from foreign markets but at the same time it will leave the company with slower penetration of international markets at the expense of international market

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share. Research how managers solve this apparent conflict will be a valuable endeavor and enrich theories of international management as well as managerial practice, especially if it comes along with the consideration of additional strategic motives such as first mover advantages and the like. Another suggestion for future research concerns measurement although not as a direct implication of the results obtained from this chapter. While already Sullivan (1994) called for adequate variables to capture the multidimensional construct of internationalization, prior research has extensively relied on the ratio between foreign sales and total sales. This is mainly due to limited data availability in major databases such as Datastream or Compustat. However since the beginning of this century an increasing number of databases such as Extel Cards report more detailed information in their ‘geographical analyses’ sections. With more firms adapting to international reporting standards the data availability for the construction of more precise and sophisticated measures of internationalization will improve. This in turn will enable researchers to conduct more fine-grained analyses of the internationalization-performance relationship.

4.8 Conclusions Chapter three investigated if intangible resources have an impact on the internationalization-performance relationship. This chapter builds upon findings of a positive performance impact of several intangible resources. It explores how and why this occurs. Numerous internationalization theories have considered the availability of intangible resources owned by the firm to be the key factor in the internationalization of that firm (Delgado-Gómez et al., 2004). However, only a few empirical analyses have addressed this issue and even fewer in the case of German firms. Against this background this chapter makes several important contributions to the literature as it opens up the black-box of the triangular relationship between intangible resources, the internationalization process and how both relate to the internationalization-performance relationship. First, it demonstrates that the presence of intangible resources within the firm has an impact not only on the degree of international diversification, but also on the direction that such diversification takes. An important insight is that intangible resources differ with respect to their internationalization potential because of their

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165

idiosyncratic nature. Distinguishing intangible resources by their origin in the value chain explains why some resources are more valuable in the context of the internationalization of the firm than others. Upstream intangible resources enable firms to expand their scope of internationalization to a greater extent – in terms of business activities across the triad regions Europe, America, and Asia – than do downstream intangible resources. Second, this chapter expands knowledge on contingency factors that have a moderating impact on the internationalization-performance relationship. It demonstrates that speed and scope of internationalization are two crucial process dimensions of internationalization. Consequently, not only the degree of internationalization matters with regard to the performance impact of internationalization but as well the way how a company arrives there. Finally, these results have important managerial implications. Managers should carefully consider their intangible resource base and develop their internationalization strategy according to it. Furthermore they must keep in mind that building a profitable MNC is a path dependent endeavor. Systems, structures, and processes that are suitable to develop the effectiveness of absorptive capacity might constitute an important competitive advantage over rivals under conditions of worldwide competition.

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Endnotes 1. Rugman and Verbeke define ‘home region oriented’ firms if they have at least 50 percent of their sales in their home region of the triad. ‘Bi-regional’ firms are defined as firms with at least 20 percent of their sales in each of two regions, but less than 50 percent in any one region. ‘Host region oriented’ firms are defined of having more than 50 percent of their sales in a triad market other than their home region. ‘Global’ firms are defined as having sales of 20 percent or more in each of the three parts of the triad, but less than 50 percent in any one region of the triad (see Rugman and Verbeke, 2004, p. 7). 2. The three regions they differentiate are NAFTA (US, Canada, and Mexico), Europe (including Central and Eastern Europe), and Asia-Pacific. 3. Dunning et al. (2007) suggest to include a fourth region termed ‘Other’ because they identify some firms in their sample that “recorded more of their sales in this region [Other] than in some of the three identified” (Dunning et al., 2007, p. 188). However for the sample of German multinational firms sales from other than the triad regions account for only for 3.2 percent of total sales on average. Assigning an additional category for this portion seemed disproportionate to the author.

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Chapter 5 Conclusion

Internationalization of firms and the way how it relates to firm performance has been a focus of academic research in international business for a long time. After thirty years of research on the relationship between internationalization and firm performance findings on the direction and magnitude are still contradictory. This work sought to explore if, how, and why the two constructs of internationalization and performance should have a relation with each other with an explicit consideration of the role of intangible resources in this context. Chapter two analyzed prior empirical research based on the method of meta-analysis. Given the diversity of empirical findings so far this chapter explored if there is one uniform relationship between internationalization and firm performance or whether this relationship is rather context dependent. Chapter three and four discussed in detail the role of intangible resources. In chapter three I explored the moderating role of five different dimensions of intangible resources and adopted a novel concept of measuring the joint value of the different facets of intangible resources – the so called hedonic approach. In chapter four I include the internationalization process in order to assess how it is shaped by intangible resources and how they both relate to the internationalization-performance relationship. In this concluding chapter I briefly summarize and comment on the main results and scientific contributions of this piece of research. Subsequently, I will highlight some of the practical and theoretical implications.

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5.1 Summary of Results I started with a quantitative review of prior research on the internationalizationperformance relationship in an attempt to reconcile the fragmented results. Given the diversity of empirical findings on the direction and magnitude of this relationship I applied meta-analysis. Meta-analysis is an innovative approach to the discipline of international business research and is particularly helpful whenever there is ambiguity on the real nature of a relationship. In fact, recently scholars such as Hitt et al. (2006) recognized the urgent need to make sense of the extant body of empirical research by means of innovative methodological approaches as they comment in their narrative review of the literature: “The empirical tests of this relationship [international diversification and performance] have reached a critical mass, allowing meta-analyses to be completed” (Hitt et al., 2006, p. 854). In fact, meta-analysis proved to be an important endeavor to advance knowledge on the actual relationship. I was able to extract findings from 36 studies (41 samples), comprising N = 7,792 observations and found empirical support for a significant positive relationship at the aggregate level ( r = .06). Maybe even more important is the fact that this relationship is highly context dependent. I investigated whether two different kinds of moderators explain the inconsistencies in prior research; methodological differences and context related variables. I could not find support for the notion that differences in research designs, time frame of analysis, or variable measurement such as different scales for internationalization and firm performance explain a significant part of the conflicting results in past research. In contrast I found strong support that context related moderators explain why prior research has not been able to reach a consensus on the question how internationalization and performance relate. Meta-analysis reveals that the relationship between internationalization and firm performance is moderated by R&D intensity, product diversification, country of origin, firm age, and firm size. These results highlight the need for future inquiry to consider these moderating variables as major determinants of success in the research domain of internationalization. In the following chapter I examined the benefit-cost trade-off from internationalization and explored its incremental variation across the internationalization continuum. As has been suggested before, I assessed that the performance impact of internationalization is not stable but that the benefit-cost trade-off varies depending on the stage of internationalization. However, unlike the pioneers of the ‘3-stage theory’ (Contractor, Kundu, and Hsu, 2003; Lu and Beamish, 2004) I found that the benefitcost trade-off a firm faces in its internationalization process depends on the accessibil-

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ity of similar foreign markets. Similarity concerns cultural heritage but institutional arrangements as well. The curve type that best explains the internationalizationperformance relationship for a sample of German firms can be described by a sinus curve. Internationalization is associated with increasing performance at low stages of internationalization. Similar institutional arrangements such as the single European market disburden the extra costs from investing abroad as opposed to the home market and facilitate the initial foreign market entry. With increasing international commitment German firms face performance pressures; however these firms are not doomed to declining performance once they have passed a certain level of internationalization. Instead firms may have the ability to proactively shift existing thresholds or avoid them altogether. Throughout the remaining sections of this book I explored in detail the role of one important category of contextual factors – the intangible resources of a firm. Despite the significant contributions of the eclectic paradigm (Dunning, 1980, 1988) and internalization theory (Buckley and Casson, 1976; Hymer, 1976), there are three weaknesses in contemporary research that limit their capacity to adequately capture intangible resources as determinants of a firms’ internationalization and explain how they moderate the internationalization-performance relationship. First, although the firm specific intangible resource is a central construct of the eclectic paradigm as well as internalization theory, it has not been fully developed to complete our understanding of multinational strategies and operations (Itaki, 1991; Hitt, Hoskisson, and Kim, 1997). Prior research has largely treated intangible resources as a unidimensional construct (Lei, 2007). Second, the two theories have paid little attention to the cost side of multinationality (Eden and Miller, 2001). This is in part due to the implicit assumption that multinational companies accumulate sufficient intangible resources prior to foreign market entry and that these intangibles at least outweigh the liability of foreignness (Zaheer, 1995). However, the value of intangible resources might vary depending on characteristics of the foreign market as compared to the market where the intangible resource was originally developed, a situation in which firms will inevitably incur extra costs when investing abroad. Third, the eclectic paradigm as well as internationalization theory have fallen short of providing insights into how international activities and performance of multinational companies evolve over time. Against this background I developed a novel approach of measuring the value of the stock of intangibles as a whole – the so-called hedonic approach. In a second step I differentiated between five different intangible resources, based on a comprehensive

174

Conclusion

classification by the FASB. I did so in order to explore whether intangible resources differ regarding the way how they affect the performance outcome of internationalization and how this occurs. Based on a sample of n = 789 observations of medium to large publicly listed firms from Germany I ascertained that intangible resources as a hole (measured by hedonic q) do not systematically moderate the internationalizationperformance relationship. Furthermore, although prior research has advocated Tobin’s q as a measure of intangible resources (Ross, 1983; Hirschey and Weygandt, 1985; Delgado-Gómez, Ramírez-Alesón, and Espitia-Escuer, 2004) the results of this study cast doubt whether this variable constitutes a valid measure of the set of intangible resources in the context of international business research. However, once I separated between different facets I found that intangible resources not only moderate the internationalization-performance relationship but explain differing patterns of the internationalization process as well. One distinction is crucial regarding the impact of intangible resources. It is the differentiation whether the value of a resource is location bound or whether it is non-location bound. The results of this analysis indicate that the value of intangible resources that originate from the upstream side of the value chain is (in tendency) less location-bound than that of intangibles that originate from the downstream side. Such intangible resources as technological know-how and the international diversity of the top management team do not only positively moderate the internationalization-performance relationship, they are also associated with (1) higher degrees of internationalization and (2) higher dispersion of international activities worldwide and even (3) a higher tendency to increase global commitment during 2001 and 2006. In contrast, downstream intangible resources such as market know-how and contract-based know-how (which comprehends such resources as purchased brands) are associated with lower degrees of internationalization and less dispersion of international sales across the major regions of the world. In the case of downstream intangible resources higher scope of international expansion is associated with performance decline as well. Table 5.1 summarizes the results of those hypotheses that relate to the different facets of intangible resources. Finally, I found support that not only the degree of internationalization matters with regard to performance outcomes but as well the way how a company arrives there. Speed and scope of international expansion constitute two critical process dimensions. Slow and modest internationalization speed does not cause performance pressures whereas an extreme pace of international expansion might tax the absorptive

Summary of Results

175

Table 5.1 Summary of Hypotheses Pertaining to the Role of Intangible Resources

Hypotheses

Technological Know-How

Market Know-How

ContractBased Know-How

TMT Internat. Diversity

(+)

(+)

(–)

(+)

TMT Education

Chapter 3: H4-7:Moderating impact on internationalizationperformance relationship

(+)

Chapter 4: H1: Degree of internationalization H1: Two year change of internationalization

(+)

(–) (+)

H2: Scope of internationalization

(+)

H3: Scope of expansion

(+)

H5: Moderating impact of scope of expansion

(–)

(+)

(+)

(–)

(+)

(+)

(+)

(–)

(–)

Notes: (+) Significant positive relationship. (–) Significant negative relationship.

capacity of an organization and affect firm performance negatively. The effect of a higher scope of international expansion depends on the availability of appropriate resources. While a higher scope of expansion is not associated with declining performance in the presence of upstream intangible resources it is in the case of downstream intangible resources. In summary, this work advances existing knowledge on the role of intangible resources as it takes a more differentiated approach to the concept of intangible resources with the consideration of differing ‘internationalization potential’. It makes six contributions to the literature: First, meta-analysis provides evidence that the relationship between internationalization and firm performance is highly context dependent. Second, this piece of research shows that the curve type of this relationship depends on home country characteristics, especially concerning the similarity to neighboring countries. Third, it introduces the hedonic approach into international business research, a novel concept of measuring intangible resources. Forth, it distin-

176

Conclusion

guishes the moderating role of different facets of intangible resources. Fifth, it contributes to the ‘regionalization hypothesis’ introduced by Rugman and Verbeke (2004), as it explores the role of intangible resources regarding the scope of internationalization, and sixth, it introduces speed and scope of internationalization as important moderator variables and discloses how the performance impact of scope is contingent on intangible resources.

5.2 Implications and Recommendations for Future Research The studies reported in this book have a number of practical and theoretical implications. Their results are important for researchers, investors, policy makers, educators, and the management of multinational companies. The particular findings and implications of the three main chapters have been extensively treated in the discussion sections of the respective chapters (chapter two, three, and four). The remaining part of the present chapter seeks to put the findings in a broader perspective and to point out directions for future research. This work proposes that the relationship between internationalization and firm performance is fundamentally context dependent. Therefore researchers should no longer look for generalizations but instead develop more fine-grained models that investigate the circumstances when and how internationalization and performance relate. The results give support to theories that stress the conditionality of success in internationalization and that emphasize the decisive role of intangible resources. I think that an integration of different theoretical approaches might be helpful to advance knowledge on the nature of the internationalization-performance relationship. However, first and foremost this piece of research represents one step towards the development of evidence-based management (Frese et al., 2005). I applied metaanalytic techniques to establish the status of the concepts of internationalization and firm performance. The study reviewed more than three decades of research. Findings may assist researchers in their choice of variables, measurements and control variables. Managers in turn should be conscious that their organizational context has an impact on the profitability attributes of internationalization. As an example, especially older firms should be aware of organizational change because of organizational inertia. This is not trivial, because prior knowledge may also lead to rigidity and inflexibility (Audia, Locke, and Smith, 2000). In changing environments knowledge may also

Implications and Recommendations for Future Research

177

become obsolete quickly and require the owner to unlearn (Reuber and Fischer, 1999). Although a number of moderators could be identified, heterogeneity in the effects which cannot be attributed to research artifacts is still remaining. This fact strongly suggests the need for more rigorous contingent approaches to internationalization and performance. To be practically beneficial, an evidence-based approach for the domain of international business research requires further meta-analyses that specify the size and generalizability of other effects of concepts discussed in literature. Another step towards evolving evidence-based management is the development of cumulative evidence from individual studies as well as the examination of new individual concepts. The distinction of different characteristics of intangible resources (chapter three and four) represents such a concept that promises to be theoretically and practically useful. The present study is among the first to simultaneously address the relationships between (1) different characteristics of intangible resources, (2) the internationalization process and (3) performance as the outcome of that process. Maybe the most critical process is the successful deployment of intangible resources in foreign markets (Kogut and Zander, 1993). The findings from this work have important implications for the conceptual development and refinement of the resource based view within international diversified firms. One important conclusion from this research concerns the importance to bear in mind the idiosyncratic nature of intangible resources (with respect to value, rareness, inimitability, and non-substitutability), which has an effect on the effectiveness of such resources in international markets. As intangible resources are imperfectly mobile (Kogut and Zander, 1992), a firm may find it difficult to transfer knowledge to its foreign subsidiaries – especially if this knowledge is valuable and rare. Thus, the paradox of value and challenges to transferability is created. Figure 5.1 displays a conceptualization of the resource based view of the firm, as adapted from Mata, Fuerst, and Barney (1995). This conceptualization can be applied to this study’s results as well. As shown in this figure, resources that conform to the criteria value, rareness, and imperfect mobility across firms might enable a firm to achieve sustained competitive advantage. However, some intangible resources such as market know-how have a positive effect on firm performance only after a considerable period of time. This is because their transfer across units of a firm is toilsome and time-consuming. This issue has important managerial implications. It highlights the challenges associated with the successful deployment of the firm’s know-how base across different markets. Hence, even though a multinational company

178

Conclusion

Figure 5.1 Mobility of Intangible Resources in the Context of Internationalization

N

Y

Is a resource valuable?

N

Competitive Disadvantage

N

Is it imperfectly mobile across firms?

Competitive Parity International Experience

Paradox of Resource Mobility

Y

Is it rare?

N

Y

Is it imperfectly mobile across business units?

Y

Temporary Competitive Advantage Host-country Experience

Rapid Building of Sustained Competitive Advantage

Slow Building of Sustained Competitive Advantage

Technological Know-How

Market Know-How

Source: Adapted from Mata, Fuerst, and Barney (1995).

might possess valuable intangible resources, the complexity of the embedded knowhow might defy immediate performance gains. This perception has recently been emphasized by Fang et al. (in press.) as well. They describe a trade-off between the immediacy of performance gains and the sustainability of competitive advantage. “The more complex a firm’s knowledge, the more difficult it will be to transfer effectively. Managers should not look to short-term performance when an expansion is predicated on the transfer of complex firm-specific knowledge. Managers with the patience to stick through short-term instability in international diversification may be rewarded by long-term gains” (Fang et al., in press., p. 9).

It is important, however, to comment on the limits inherent in using secondary data in international business research as well, especially regarding intangible resources. While a more detailed reporting of international segment data on the regional dispersion of firm activities in recent years allows future research to develop more fine-grained models of the internationalization-performance relationship, company reporting on intangible resources in annual reports or databases will probably remain limited. As this study’s test for data quality of different databases discovers, even recognized data sources such as Datastream and Compustat reveal deficiencies regarding the reliability of historic data they report. Future research should be aware of

Implications and Recommendations for Future Research

179

the flaws pertaining to archival data and adapt appropriate procedures to avoid them. Finally, I encourage future research to draw on more diverse samples as well, especially from countries other than the US. Some samples such as the Fortune 500 have been heavily applied in prior research (e.g. Sambharya, 1995; Gomez-Mejia and Palich, 1997; Qian and Li, 2002). A broader empirical base will help to avoid misinterpretations and over-simplistic generalizations of results that rest on only a few different samples, comprising similar firms. Therefore I suggest that the field of international business would definitely benefit from more in-depth field research. Case studies that focus on firm level differences or studies conducted at an industry level might reveal important differences in the internationalization process and how international experience evolves over time. Ideally, such research should be based on longitudinal research designs, relating firm specific internationalization processes to performance over time. Research of this kind could address the multidimensional nature of the internationalization process. One fundamental insight from this piece of research is that the question of how internationalization and performance relate cannot be answered straightforwardly. It seems no simple and direct relationship is awaiting its discovery by international business scholars. If this is true and this research question is not suited for (over-) simplistic research models then researchers should focus on certain facets of this question and use integrative theoretical approaches to eventually arrive at a comprehensive explanation of this phenomenon. This work represents a start in this vein and develops a model that focuses on the role of intangible resources with regard to the internationalization-performance relationship. I propose that future research should apply more particularistic research models in this domain. This might include research on further explanatory variables at individual and firm level, industry and regional differences, and research on intermediate outcome variables. Seemingly, learning plays a critical role in the domain of internationalization. For example the ‘3-stage model’ is based on learning arguments. Hence, it should be tested whether this learning actually takes place and how it works. Ultimately, to end here in this outlook, I strongly recommend moving the internationalization-performance research stream away from bivariate and universalistic propositions towards a new premise that is based on multivariate and particularistic perspectives. In particular, I suggest that contingency theory represents a promising and applicable theoretical foundation for this line of inquiry (Drazin and Van de Ven, 1985; Venkatraman and Prescott, 1990). It became obvious throughout the preceding

180

Conclusion

chapters that particularistic interaction models which make use of moderator variables have the ability to isolate precisely specified theoretical links. Therefore they might be valuable to advance research in this field in the near future. Once a sufficient volume of such research is generated, researchers could start to aggregate and integrate the results with the help of more holistic systems approaches (Miller and Friesen, 1980; Miller, 1981). Antecedents of internationalization, moderators and mediators might form the building blocks of a contingency theory on internationalization and performance (Hitt et al., 2006). Finally, new meta-analyses may help to establish the generalizability of individual findings towards the development of a mid-range theory of the internationalization-performance relationship.

References

181

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Buckley, P.J. and Casson, M. (1976) The Future of the Multinational Enterprise, Macmillan: London. Contractor,

F.J., Kundu, S.K. and Hsu, C.C. (2003) 'A Three-Stage Theory of International Expansion: The Link between Multinationality and Performance in the Service Sector', Journal of International Business Studies 34(1): 5-18.

Delgado-Gómez, J.M., Ramírez-Alesón, M. and Espitia-Escuer, M.A. (2004) 'Intangible Resources as a Key Factor in the Internationalisation of Spanish Firms', Journal of Economic Behavior & Organization 53(4): 477-494. Drazin, R. and Van de Ven, A.H. (1985) 'Alternative Forms of Fit in Contingency Theory', Administrative Science Quarterly 30(4): 514-539. Dunning, J.H. (1980) 'Toward an Eclectic Theory of International Production: Some Empirical Tests', Journal of International Business Studies 11: 9-31. Dunning, J.H. (1988) 'The Eclectic Paradigm of International Production: A Restatement and Some Possible Extensions', Journal of International Business Studies 19(1): 1-31.

Eden,

D. and Miller, S. (2001) 'Opening the Black Box: Multinationals and the Costs of Doing Business Abroad', Academy of Management Proceedings.

Fang, Y., Wade, M., Delios, A. and Beamish, P.W. (in press.) 'International Diversification, Subsidiary Performance, and the Mobility of Knowledge Resources', Strategic Management Journal. Frese, M., Schmidt, P., Bausch, A., Rauch, A. and Kabst, R. (2005) 'Evidence Based Entrepreneurship: A Systematic Approach to Cumulative Science', University of Giessen: Technical Report.

Glaum, M. and Oesterle, M.J. (2007) '40 Years of Research on Internationalization and Firm Performance: More Questions Than Answers?' Management International Review 47(3): 307-317. Gomez-Mejia, L.R. and Palich, L.E. (1997) 'Cultural Diversity and the Performance of Multinational Firms', Journal of International Business Studies 28(2): 309-335.

Hirschey,

M. and Weygandt, J.J. (1985) 'Amortization Policy for Advertising and Research and Development Expenditures', Journal of Accounting Research 23(1): 326-335.

Hitt, M.A., Hoskisson, R.E. and Kim, H. (1997) 'International Diversification: Effects on Innovation and Firm Performance in Product-Diversified Firms', Academy of Management Journal 40(4): 767-798. Hitt, M.A., Tihanyi, L., Miller, T. and Connelly, B. (2006) 'International Diversification: Antecedents, Outcomes, and Moderators', Journal of Management 32(6): 831-867. Hymer, S.H. (1976) The International Operations of National Firms: A Study of Foreign Direct Investment, MIT Press: Cambridge, MA.

Itaki,

M. (1991) 'A Critical Assessment of the Eclectic Theory of the Multinational Enterprises', Journal of International Business Studies 22(3): 445-460.

182

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Kogut, B. and Zander, U. (1992) 'Knowledge of the Firm, Combinative Capabilities and the Replication of Technology', Organization Science 3(3): 383-397. Kogut, B. and Zander, U. (1993) 'Knowledge of the Firm and the Evolutionary Theory of the Multinational Corporation', Journal of International Business Studies 24(4): 625-645.

Lei,

L. (2007) 'Multinationality and Performance: A Synthetic Review and Research Agenda', International Journal of Management Reviews 9(2): 117-139.

Lu, J.W. and Beamish, P.W. (2004) 'International Diversification and Firm Performance: The S-Curve Hypothesis', Academy of Management Journal 47(4): 598-609.

Mata, F.J., Fuerst, W.L. and Barney, J.B. (1995) 'Information Technology and Sustained Competitive Advantage', MIS Quarterly 19(4): 487-505. Miller, A. (1981) 'Toward a New Contingency Approach: The Search for Organizational Gestalts', Journal of Management Studies 18(1): 1-26. Miller, D. and Friesen, P. (1980) 'Archetypes of Organizational Transitions', Administrative Science Quarterly 25(2): 268-299.

Qian, G. and Li, J. (2002) 'Multinationality, Global Market Diversification and Profitability among the Largest US Firms', Journal of Business Research 55(4): 325-335.

Reuber,

A.R. and Fischer, E. (1999) 'Understanding the Consequences of Founders’ Experience', Journal of Small Business Management 37(1): 30-45.

Ross, S.A. (1983) 'Accounting and Economics', The Accounting Review 58(2): 375-380. Rugman, A.M. and Verbeke, A. (2004) 'A Perspective on Regional and Global Strategies of Multinational Enterprises', Journal of International Business Studies 35(1): 3-18.

Sambharya, R.B. (1995) 'The Combined Effect of International Diversification and Product Diversification Strategies on the Performance of U.S.-Based Multinational Corporations', Management International Review 35(3): 197-218.

Venkatraman,

N. and Prescott, J.E. (1990) 'Environment-Strategy Coalignment: An Empirical Examination of its Performance Implications', Strategic Management Journal 11(1): 1-23.

Zaheer, S. (1995) 'Overcoming the Liability of Foreignness', Academy of Management Journal 38(2): 341-363.

Appendix

Appendix Chapter 2 The Effect of Context-Related Moderators on the Internationalization-Performance Relationship: Evidence from Meta-Analysis

184

Appendix Chapter 3 Intangible Resources and their Effect on the Internationalization-Performance Relationship

211

Appendix Chapter 4 Intangible Resources and the Internationalization Process: Path Dependence of Building a Profitable Multinational Company

242

184

Appendix Chapter 2

Appendix Chapter 2

A 2.1 Studies of the Meta-Analysis

185

A 2.2 Meta-Analytic Procedure and Statistical Formulas

206

A 2.3 Methodological Moderators

209

Table A 2.3.1 Independent Variable: Internationalization

209

Table A 2.3.2 Dependent Variable: Performance

210

Research Question(s) Do U.S. investors reward U.S. companies for going overseas?

What are the antecedents and outcomes of the internationalization of new highpotential ventures? How is a firm's decision to internationalize and the subsequent performance affected by its set of resources available?

Author(s) Year Aggarwal, 1979

Bloodgood, Sapienza, Almeida, 1996

Greater international work experience among top managers, pursuit of product differentiation, and larger firm size are strongly associated with greater internationalization of new ventures. Internationalization is marginally related to earnings two years after IPO. Early internationalization is not good or bad but rather contingent upon industry and resource conditions.

Internationalization is positively related to Price/Earnings-ratio (P/E-ratio) and negatively to firm beta. Investors are willing to pay a premium for multinationals and systematic risk decreases as firms go international.

Capital markets are not fully integrated on an international level, therefore investors value firms international diversification, because they cannot do so themselves.

H7: Top management international exposure, sources of competitive advantage, innovativeness, and size at IPO will have the same relationship with subsequent performance as they had with initial internationalization. H8: The level of internationalization of the new U.S. venture at the time of the IPO is positively related to its subsequent performance.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis

N=61 venture capital backed firms that were less than five years old at the time of IPO.

N=192 U.S. multinationals from Business International.

Sample

Independent: Percent of primary activities (according to Porter, 1985) that were at least partially international activities. Dependent: Sales growth, EBIT.

Variable Coding Independent: FSTS, FATA, Foreign income to total income. Dependent: Firm beta, P/E-ratio, Cost of capital.

The Effect of Context 185

Research Question(s) What is the effect of international diversification of firms in Western Germany on market performance? What is the difference compared to a strategy of product diversification?

What is the effect of international diversification on performance in service firms?

Author(s) Year Buhner, 1987

Capar, Kotabe, 2003

H: Supported. Lower inflection point at FSTS = ca. 18%.

Results show significant positive relationships between geographic diversification and both market performance and accounting performance. While domestic product diversity appears to be motivated by internal "push" stimuli such as risk reduction and poor profitability in traditional lines of business, internationalization appears to be "pulled" by external stimuli of prospective market opportunities.

Capital market inefficiencies benefit firms that internationalize. Market failure, asset specificity, and indivisible physical assets are further benefits for internationalization.

H: The relationship between international diversification and performance in service firms will be U-shaped curvilinear, with performance decreasing up to a certain point, beyond which higher levels of international diversification will increase performance.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=81 major German service firms from the largest 500 German Companies Directory by “Die Welt”.

N=40 large West German corporations of the top 300 firms in Western Germany, all stock exchange noted in Frankfurt.

Sample

Independent: FSTS. Dependent: ROS, ROA.

Variable Coding Independent: Herfindahltype index of international sales dispersion. Dependent: Jensen alpha, ROA, ROE.

186 Appendix Chapter 2

Research Question(s) When encountering competitive threats, what causes firms to use foreign expansion to overcome the difficulties? How is a strategy of internationalization related to strategies of domestic expansion and product expansion?

Is there value intrinsic to a wide geographic scope of operations? Is internationalization per se valuable or are proprietary assets the ultimate source of superior firm performance?

Author(s) Year Chen, Martin, 2001

Delios, Beamish, 1999

H4a,b: Supported. H5: Supported. The effect of internationalization and the effect of proprietary assets are separated through a path analytic approach. Ownership advantages as well as internationalization itself lead to superior performance.

H1: Supported, small firms with prior foreign business involvement are more likely to use foreign expansion to deal with the problems. H2,3: Supported, foreign activities of small firms are closely related to their non-foreign strategies and cannot be considered separate strategic choices. Because of resource scarcity, SMEs should either engage in product or international diversification.

H1: When encountering difficulties, small firms that already have foreign operations are more likely to engage in foreign expansion. H2: Product expansion activities negatively affect foreign expansion of small firms. H3: Domestic expansion activities negatively affect the foreign expansion of small firms.

H4a: R&D intensity of a firm is positively related to its geographic scope. H4b: Advertising intensity of a firm is positively related to its geographic scope. H5: The geographic scope of a firm is positively related to corporate performance.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=399 Japanese publicly traded firms from Analyst’s Guide; firms are listed at the first section of the Tokyo stock exchange.

N=49 SMEs randomly selected from US electronic components industry (SIC36). SME: sales less than the industry average for at least half of the periods.

Sample

Independent: Index of number of FDI and number of countries. Dependent: ROA, ROE, ROS. All items are 5year averages.

Variable Coding Independent: dummy (0/1) depending on the formation of a new foreign business unit in a year. Dependent: Firm sales change, ROA change.

The Effect of Context 187

Research Question(s) What is the relationship between degree of internationalization and firm performance? Are differences between US and Canadian SMEs observable?

What is the impact of international spread (‘globalisation’) on financial and value performance? What characteristics do international retailers with corresponding sound financial performance display? What strategic recommendations on the appropriate international expansion mode can be offered?

Author(s) Year hanaraj, Beamish, 2003

Dragun, 2002

Higher proportion of international sales leads to lower profitability and lower risk-adjusted cash returns. The more global the company is, the greater its earnings volatility. A "sound financial performance" retailer has the following characteristics: reasonably big, modestly international (FSTS: 18%), regionally focused (1-2 regions), lightly leveraged.

H5,6: Supported. Enterprise, technological intensity and firm size are good predictors of export strategy and export strategy influences firm performance positively. The path coefficients for American and Canadian SMEs are comparable, except for the path from enterprise to degree of internationalization, where the US sample is not significant.

H5: The greater the technological intensity of a firm, the greater the degree of internationalization. H6: The higher the degree of internationalization of a firm, the higher the performance.

No Hypotheses offered.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=130 of World's largest 500 retail companies, from 19 countries.

N=70 US SMEs from an industrial midwestern state. N=87 Canadian SMEs from the whole country. Questionnaire survey.

Sample

Independent: IMG - integrative measure of globalization. Dependent: Operating profit margin, Realized economic value.

Variable Coding Independent: Export intensity, number of foreign countries. Dependent: Profitability, Market share, Market share growth.

188 Appendix Chapter 2

Research Question(s) How can performance differences of MNCs be explained by their diversification strategy and internationalization? How should an MNC deploy its resource base to generate economic rents?

What is the relationship between product diversification and performance and internationalization and firm performance over different periods of time for Japanese keiretsu and nonkeiretsu manufacturing firms?

Author(s) Year Geringer, Beamish, DaCosta 1989

Geringer, Tallman, Olsen, 2000

H2: Negative coefficient for the first two periods for ROS, not significant for sales growth in period 2-3. H3: Supported for ROS in first period, not significant in period 2-3. H5a,b: Not supported, signs contrary to those predicted.

H2: Supported, internationalization enhances performance.

H2: Relative performance of a MNE will tend to be positively related to the degree of internationalization of the firm's operations.

H2: Performance levels of Japanese multinational manufacturing firms should vary positively and linearly with the degree of multinationality. H3: Performance levels of Japanese multinational manufacturing firms should vary positively with the level of export sales by the firm from the home country compared with total sales. H5a,(b): The interaction of multinational diversity and product diversity (squared) should be negatively (positively) related to performance for Japanese multinational manufacturing firms.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=108 largest manufacturing multinationals from Japan in 1981, Data from Daiwa Securities Co., Ltd. Analyst´s Guide und Japan company handbook. Timeframe: 1977-1993.

N=181 largest American and European multinationals from World directories of multinational enterprises.

Sample

Independent: Foreign subsidiary sales to total sales, export sales to total sales. Dependent: ROA, ROS, Sales growth.

Variable Coding Independent: Foreign subsidiary sales to total sales. Dependent: ROS, ROA, 5-year averages.

The Effect of Context 189

Author(s) Year Goerzen, Beamish, 2003

Research Question(s) What are the latent subcomponents of geographic scope and how are they related to firm success? International asset dispersion and country environment diversity are differentiated. Results H1: Supported. H2: Supported. Global Competitiveness entropy score is dominant, while the Cultural Diversity entropy score has modest impact - a great variance in the levels of economic development has an important negative effect on performance, cultural effects are more modest. H3a,b: The combination of the two geographic scope constructs yields an overall positive effect on firm performance. Explanation for some non-linearity findings: Organizations complexity effect is based on the magnitude of country environment diversity. Greater dispersion of assets is positively related to firm performance.

(Relevant) Hypotheses

H1: The relationship between an MNE's International Asset Dispersion and its Economic Performance is positive. H2: The relationship between an MNE's Country Environment Diversity and its Economic Performance is negative. H3a,b: Interaction of International Asset Dispersion and Country Environment Diversity.

A 2.1: Studies of the Meta-Analysis (continued) Variable Coding Independent: Entropy measure of international asset dispersion, Environment Diversity: Index consisting of four entropy measures: 1. Global Competitive Index, 2. Culture according to Hofstede (1980), 3. Economic Freedom Index, 4. Political Constraint Index. Dependent: Profitability Index consisting of Jensen alpha, Sharpe ratio, Marketto-book ratio.

Sample N=580 Japanese MNEs, that have operations in six or more countries.

190 Appendix Chapter 2

Research Question(s) What is the form (linear - nonlinear) of the relationship between internationalization and performance? Is this relationship timestable, because some found positive results that could not be replicated in later studies?

What are the performance implications of culturally related vs. unrelated internationalization?

Author(s) Year Gomes, Ramaswamy, 1999

GomezMejia, Palich, 1997

Regression tests using nine indicators of cultural diversity revealed no significant cultural effects on any of the indicators. The negative impact of greater cultural diversity can be overcome through deliberate strategies and benefits through cultural heterogeneity.

H: Supported. Adding the squared term significantly increased the proportion of variance explained.

H: The relationship between multinationality and performance will be nonlinear with performance increasing up to an optimal level beyond which higher levels of multinationality lead to performance decline. Theoretical shortcomings led to "inconclusive" results, because they did not consider that benefits and costs of internationalization change with the degree of internationalization. Culturally related international diversification will be positively associated with firm performance. Conversely, culturally unrelated global diversification will be negatively associated with firm performance. Cultural diversity is supposed to have a negative impact on production synergies, innovation, technology implementation, organizational transformation processes, market response, interpersonal dynamics, organizational control systems, and human resource programs.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=442 companies from Fortune 500.

N=95 US companies from chemical (28), pharmaceutical (14), IT (24), and electronic equipment (29) industries.

Sample

Independent: Dispersion of subsidiaries across Hofstedes (1980) dimensions. Dependent: ROA, Market-to-book ratio. 10-year averages.

Variable Coding Independent: Index of FSTS, FATA, Number of countries. Dependent: ROA, Operating costs to total sales.

The Effect of Context 191

Author(s) Year Grant, 1987

Research Question(s) The purpose of this paper is to examine more carefully than hitherto the relationship between multinationality and firm performance. Sample N=304 quoted, British owned, manufacturing companies taken from the Times 500 list of Britain's largest companies.

Results 1. Static analysis: Overseas production ratio has a highly significant positive influence which is consistent across all three profitability measures. 2. Dynamic Analysis: Significant positive coefficient of changes in overseas production to changes in performance variables 3. Geographical influences: Lack of consistent differences between the regression coefficients on the regional overseas production ratios. Result: The primary source of the superior performance of multinationals is competitive advantage rather than the higher rate of profit in the industries of other countries.

(Relevant) Hypotheses Reasons for superior performance: 1. Return to intangible assets, 2. Market power conferred by international scope, 3. Capacity to undertake risky investments, 4. Broadening of investment opportunities. Ha: Because of similarities in language and culture, investment in the Commonwealth countries of the Rest of the World and, to a lesser extent, in North America might be expected to be more successful than investment in Western Europe. Hb: Because of differences in levels of economic development and differences in the intensity of competition, UK firms might find it easier to compete in the Rest of the World than in North America, Hc: because of geographical proximity, UK firms might find international integration easier with their European subsidiaries than with those in North America or the Rest of the World.

A 2.1: Studies of the Meta-Analysis (continued) Variable Coding Independent: Sales of overseas operating subsidiaries as proportion of total sales. Dependent: Sales Growth, ROA, Operating profit growth, ROE, ROS.

192 Appendix Chapter 2

Research Question(s) What is the relationship between the extent of foreign dependence and performance? Is this relationship different for firms originating either from the Pacific Rim, Western Europe or North America?

How is the relationship between internationalization and performance moderated by productdiversification and innovation (R&D)? In what direction are the causal relationships?

Author(s) Year Harveston, Kedia, Francis, 1999

Hitt, Hoskisson, Kim, 1997

H1: Supported. International diversification is beneficial because internal resource and capabilities can earn rents on market imperfection. On the contrary costs of internal and external communication rise. H3: Supported. Experience with diverse product portfolios helps to handle rising complexity.

H1: Significant for ROS, not significant for ROA and marketshare. H2: Supported. North America, Europe: significant for ROA, ROS, not significant for market share. Pacific Rim: not significant for ROS, ROA, significant for market share. The performance differences are depending upon the time-horizon of the performance measure.

H1: Dependence on foreign activities of MNC will be positively related to MNC performance. H2a(b): Short-term - ROA, ROS (long-term - market share) orientation measures of performance of European and North American (a Pacific Rim) MNCs will be positively related to the degree of MNC dependence on foreign activities but will have no relationship with the degree of MNC dependence on foreign activities for a Pacific Rim (European and North American) MNC. H1: The relationship between international diversification and firm performance is nonlinear, with the slope positive at low and moderate levels of international diversification but negative at high levels of international diversification. H3: Product diversification positively moderates the curvilinear relationship between international diversification and firm performance.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=152 firms from the regions Pacific (20), Western Europe (45), and North America (87). Large MNCs from the top 500 global manufacturing and service corporations and 100 largest transnational corporations. N=295 manufacturing firms with sales higher than $100 Mio.

Sample

Independent: Entropy measure of sales dispersion. Dependent: ROA.

Variable Coding Independent: FSTS. Dependent: ROS, ROA, Market-share

The Effect of Context 193

Research Question(s) What is the relationship of internationalization on different performance measures and their decomposition? Theory suggests that these are different constructs therefore differing relationships are expected (linear, ushaped, inverted ushaped).

What are the interrelationships of entrepreneurial orientation, marketing strategy, tactics, and firm performance among SMEs affected by globalization?

Author(s) Year Hsu, Boggs, 2003

Knight, 2000

H6: Supported. H7: Supported. SMEs that respond to globalization and prepare in advance to enter foreign markets tend to enjoy better performance.

H1-4: When measured via FSTS a linear curve type explains the relationship for ROA, ROE, Profit Margin best (not an inverted ushape). Only for Total Asset Turnover a standard u-shaped curve has highest explanatory power. When measured via number of countries an inverted u-shape curve type explains a far higher degree of performance variance for ROA, ROE and Total Asset Turnover. Again, a linear curve type fits best the relationship with Profit Margin.

H1-4: All else being equal, for multinational companies, the relationship between the degree of internationalization and firm performance, measured by H1: ROE, H2: ROA, H3: Profit Margin, H4: Total Asset Turnover will be characterized by an inverted Ushape, with a slope that is positive at lower levels of internationalization and negative at higher levels of internationalization.

H6: The more the firm responds to globalization, the better is the performance of the firm. H7: The more the firm prepares in advance to enter foreign markets the better is the performance of the firm.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=216 internationally active firms. Survey method

N=118 US firms from Hoover's 750 US Major Public Companies list.

Sample

Independent: Globalization Index consisting of six items. Dependent: Comparison with competitors based on five items.

Variable Coding Independent: Number of countries, FSTS. Dependent: ROE, ROA and their decomposition according to the DuPont scheme.

194 Appendix Chapter 2

Author(s) Year Lu, Beamish, 2001

Research Question(s) What is the relationship between the extent of FDI, exporting activity, and relative use of alliances, to the corporate performance of internationalizing SMEs? Sample N=164 Japanese SMEs listed on the first or second section of the Tokyo stock exchange.

Results H1: Not supported, negative relationship. H2: Supported. H3a: Supported. H3b: Domestic joint ventures have a negative impact. H4: Supported. Additional comment on liabilities of foreignness: There is a negative impact on performance with a more than two percent reduction in ROA when the number of FDI countries reaches five.

(Relevant) Hypotheses H1: An SME's performance is positively related to its level of exporting activities. H2: The relationship between the level of FDI and an SME's performance is nonlinear, with the slope negative at low levels of FDI but positive at higher levels of FDI. Resource constraints lead to H3a(b): An SME's performance is positively (negatively) related to its level of alliances with local (home country) partners formed in the process of internationalization. Export and FDI demand different capabilities, therefore: H4: Exporting activities will exert a negative moderating effect on the relationship between FDI and performance.

A 2.1: Studies of the Meta-Analysis (continued) Variable Coding Independent: Export intensity (percent of parent sales derived from export revenues), Number of FDI, Percentage of foreign joint ventures. Dependent: ROS, ROA.

The Effect of Context 195

Author(s) Year Lu, Beamish, 2004

Research Question(s) What is the form of the relationship between internationalization and performance? What is the performance impact of intangible assets? Results H1: Supported. The inclusion of the cubic term significantly improved the model fit. H2: Linear positive effect of R&D on ROA and Tobin's q.

(Relevant) Hypotheses H1: The relationship between geographic diversification and firm performance is nonlinear, with the slope negative at low levels of geographic diversification, positive at medium levels of geographic diversification and negative at high levels of geographic diversification. H2: A firm’s intangible assets moderate the relationship between geographic diversification and firm performance such that high levels of intangible assets increase the performance gains attributable to geographic diversification.

A 2.1: Studies of the Meta-Analysis (continued)

N=1489 Japanese firms of which 1059 are engaged in FDI activities.

Sample

Variable Coding Independent: Index from number of FDI, number of countries. Dependent: ROA, Tobin's q.

196 Appendix Chapter 2

Research Question(s) Has the process of upgrading the level of international commitment (in order to be rooted in the core world markets, close to key customers) created value for the enterprises involved? Are there country specific factors? Does the form of internationalization (export, FDI) matter?

What impact does the amount of integration of the global operations of a firm have on performance?

Author(s) Year Majocchi, Zucchella, 2003

Mauri, Sambharya, 2001

H1: Supported, for low levels of integration firm performance tends to increase positively with the level of global integration. The climax is reached at a relatively high level of global integration as it represents 1.3 standard deviations beyond the sample mean.

H1: Rejected. H2: Supported. In order to access the American market SMEs must develop high capabilities that finally lead to higher financial performance. H3: Supported. Because of liability of foreignness of SMEs. H4: Supported. Firms that have intensely exported in distant markets generated a value creation process that can be beneficial because of the cumulated knowledge useful and applicable on other internationalization modes.

H1: A positive relationship exists between SMEs financial performance and its level of export intensity. H2: SMEs exporting in the US are consistently more profitable than SMEs operating in the EU domestic market. H3: The relationship between FDI and profitability is negative. H4: The relationship between FDI and profitability is positive, thus overcoming the “liability of foreignness”, if FDI follows a high level of export activities by firms. Prior studies focused on the distribution of company activities across countries and overlook at the global exchange of resources among differentiated corporate units. H1: The relation between global integration and firm performance follows an inverse Ushaped curve.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=91 US companies from four industries with revenues higher than $50 Million. Data source: Compustat

N=220 Italian SMEs in the manufacturing sector.

Sample

Independent: Global integration index, shows inter area sales inbetween the company. Dependent: 3 year average ROS.

Variable Coding Independent: Export sales to total sales, Number of countries, FDI dummy (has FDI / has no FDI). Dependent: ROS, ROA.

The Effect of Context 197

Qian, 1996

Author(s) Year McDougall, Oviatt, 1996

Research Question(s) What is the impact of internationalization on new venture performance? As new ventures internationalize, are changes in their strategies necessary? How are changes in percentage of international sales related to changes in strategies (relative market share) and performance (ROI)? What is the effect of a firm's overseas activities upon its riskreturn performance by using different multinationality measures? H1a,b: Supported. H2a,b: Supported. H3: Not supported. Any firm which belongs to the multinational category based upon the criterion of multinationality (FSTS) can provide a similar riskreturn performance independent of the number of countries or geographic areas in which it operates.

H1: Supported for relative market share, not supported for ROI. H2: Supported. Ventures with an increase in internationalization have significantly higher correlations between strategic change and both relative market share and ROI.

H1: Technology-based new ventures with higher levels of international sales subsequently have higher levels of performance. H2: Strategic change will be more positively related to performance among technology-based new ventures that have increased their internationalization than among technology-based new ventures that have not increased their internationalization.

H1a(b): On average, the profitability of high international market diversifiers - HI (medium international market diversifiers MI) is greater than that of both MI and low market diversifiers - LI (LI) diversification. H2a(b): On average, the profit stability of HI (MI) is greater than that of both MI and LI (LI). H3: The riskreturn performance of the highest international market diversification group is greater than that of the other MNCs.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=126 largest US industrial firms.

N=62 US manufacturing new ventures that are younger than eight years.

Sample

Independent: FSTS. Dependent: ROA, ROE.

Variable Coding Independent: FSTS. Dependent: ROI, Relative market share.

198 Appendix Chapter 2

Research Question(s) What are the individual and joint effects of multinationality and product diversification on profit performance for a sample of US emerging small- and mediumsized enterprises?

What strategic combination of geographic scale (foreign involvement, multinationality) and scope (different world regions or markets) of foreign operations yields highest performance for large US firms?

Author(s) Year Qian, 2002

Qian, Li, 2002

H1: Not supported. HGM strategy did not produce a better return performance as suggested, and even performed poorly relative to the MGM strategy. HFI contributed significantly to a higher profitability (when compared to both MFI and LFI). H2: "may lend support" - no clear statement, afterwards: e.g. HFI/MGM (MFI/MGM) outperforms HFI/HGM (MFI/HGM). H3: Supported. Foreign involvement plays an important role in increasing returns.

H2: Supported. Curvilinear relationship. H3: Supported. Firm performance will be positive at low and moderate levels of product diversification and multinationality, but may be adversely affected with further increase in the degree of multinationality and product diversification.

H2: Performance should positively vary, to a certain extent, with degrees of multinationality. H3: The curvilinear (inverted Ushaped) relationship between multinationality and/or product diversification, and profit performance becomes weaker at high levels of these two dimensions. H1: On the average, profitability of high global market diversification (HGM) is higher than that of both medium global market diversification (MGM) and low global market diversification (LGM). H2: On the average, profitability of the HGM/High foreign involvement (HFI) combination is higher than that of other strategic combinations. H3: Increased geographic scale of foreign operations has positive influence on profit performance.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=125 US firms out of the largest 500 from Fortune 500.

N=71 US firms in the manufacturing sector from Hoover´s handbook of emerging companies.

Sample

Independent: Geographic scale: FSTS; Geographic scope: GMD (Global Market Diversification) - Entropy measure. Dependent: ROA, ROS, ROE.

Variable Coding Independent: FSTS. Dependent: ROS, Aftertax profit-tosales. 5-year averages.

The Effect of Context 199

Research Question(s) What are the profitability determinants of small- and medium-sized enterprises in high-tech industries? Especially: What is the role of innovator position, market awareness, niche operation and internationalization?

What is the form of the relationship between internationalization and performance?

Author(s) Year Qian, Li, 2003

Ruigrok, Wagner, 2003

Supported. Several analysis techniques are applied, all of which have been applied in research of a non-linear relationship to date. These are ANOVA (grouping of observations and analysis of the significance of mean differences), multiple regression and pooled time-series/cross-sectional regression analysis. Regression analysis reveals global minimum at 61% FSTS (dependent variable ROA).

H4: Supported. Internationalization generates additional sales; it helps SMTEs split the investments across various markets. It also provides more opportunities for SMTEs to maximize profits before their innovations become obsolete.

H4: An SMTE's profitability is positively associated with its internationalization. Reasons: 1. R&D investments associated with innovator strategy afford that products are sold across many markets in order to sustain largescale R&D-operations 2. Increase in economies of scale, and experience.

The relationship between "degree of internationalization" and "performance" exhibits a standard-U form, with performance being high at low degrees of internationalization, low at medium degrees of internationalization, and high again at high degrees of internationalization.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=84 German manufacturing companies from 500 largest manufacturing companies.

N=67 Biotech firms. Firms are older than 5 years and have more than 10 employees.

Sample

Independent: FSTS. Dependent: ROA, Operating costs to total sales.

Variable Coding Independent: FSTS. Dependent: ROA, ROE, ROS, Sales growth.

200 Appendix Chapter 2

Research Question(s) What are the individual and joint effects of product and international diversification on firm performance?

How may multinationality affect firm growth?

Author(s) Year Sambharya, 1995

Siddharthan, Lall, 1982

Multinationality exercises a uniformly negative effect on growth in all the equations. This seems to run counter to what the received wisdom on MNCs would lead us to expect, though it may be in conformity with expectations raised by the managerial literature.

H1: Not supported. High international diversifiers are not significantly different than those with less international diversification. H2: Supported. MNCs do have a preferred mode of diversification either in terms of markets or products. H3: Strong support. The individual strategies by themselves have no effect on firm performance but their interaction exerts a tremendous influence on firm performance.

H1: MNCs which are highly diversified internationally will perform better than those which are less diversified internationally. H2: Product diversification will be inversely related to international diversification in MNCs. H3: The interaction between international and product diversification influences performance in MNCs.

Greater multinationality will be positively associated with growth, and the existence of large minimum economies of scale in the relevant industry would strengthen the ability of large MNCs to grow. But: physical distance, linguistic and cultural differences, legal barriers, etc. may increase the costs of assimilating new management over those experiences by a similar-sized purely domestic firm.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=74 largest US MNCs in manufacturing during 19761979.

N=53 US MNCs from the Fortune 500 Industrial list Mailing questionnaire.

Sample

Independent: Foreign affiliate sales to total company sales. Dependent: Growth of consolidated sales revenue, ROE.

Variable Coding Independent: FSTS, FATA, Number of FDI, GMD (Global market diversification index). Dependent: ROS, ROA, ROE.

The Effect of Context 201

Tallman, Li, 1996

Author(s) Year Simmonds, Lamont, 1996

Research Question(s) What is the impact of product-market diversification and level of foreign involvement on corporate financial performance? What are the theoretical linkages between product-market and geographic diversification and three important performance categories? What is the relationship among international diversity, product diversity, and firm performance? Specifically: How interact different aspects of international diversity (scale - FSTS and scope – number of countries) with each other and how are they related to product diversity, and firm performance? H2: Not supported. H3: Supported. Weak positive effect of country scope, but a quadratic term was not significant. H4: Not supported. H5: Not supported.

H1: Cannot be rejected. H2: Cannot be rejected although it appears interactive results were influenced by certain product-market diversification categories. H3: Cannot be rejected.

H1: Product-market and international diversification are independent determinants of firm profitability. H2: Product-market and international diversification are interactive determinants of firm risk adjusted returns. H3: Productmarket and international diversification are interactive determinants of firm growth.

H2: Performance should vary positively and linearly with the degree of multinationality. H3: Performance level should vary positively with the geographical scope of international operations. H4: Performance should vary positively with the interaction of multinationality and country scope. H5: The interaction of international and product diversity should reduce the effects of varying levels of product diversity on performance.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

N=188 large US industrial multinationals from Directory of Multinationals.

N=156 US corporations.

Sample

Variable Coding Independent: FSTS. Dependent: Sales Growth, Earnings per share growth, ROIC, ROA, ROE, Riskadjusted return on invested capital. Independent: FSTS, Number of countries. Dependent: ROS.

202 Appendix Chapter 2

Research Question(s) What is the relationship of internationalization and performance in an Asian context, i.e. for Hong Kong MNCs?

How is the corporate diversification - performance link related to home country environments? What factors facilitate transformational activities and how foster institutions these transactional activities? Three strategies are differentiated: product, outbound international and inbound international diversification.

Author(s) Year Wan, 1998

Wan, Hoskisson, 2003

H2a: Supported. Firms in more munificent environments are able to show strong performance when they engage in foreign operations. H2b: Not supported. H3a: Partially supported. H3b: Not supported. H4a: Supported. H4b: Supported.

H1: Not supported. H2: Not supported. Internationalization has no impact on profitability but a significant positive impact on stability of profitability and sales growth.

H1: On average, locally incorporated MNCs outperform domestic firms in Hong Kong. H2: For MNCs from Hong Kong, the relationship between international diversification and firm performance is nonlinear and inverted Ushaped.

H2a(b): In more (less) munificent home country environments, outbound international diversification is positively (negatively) related to firm performance. H3a(b): In more (less) munificent home country environments, inbound international diversification is negatively (positively) related to firm performance. H4a(b): In more (less) munificent home country environments, the interaction between product diversification and outbound international diversification is negatively (positively) related to firm performance.

Results

(Relevant) Hypotheses

A 2.1: Studies of the Meta-Analysis (continued)

Highly munificent countries: N=499 - Sweden (115), France (177), England (207). Less munificent countries: N=233 - Ireland (40), Italy (133), Portugal (50).

N=81 MNCs from Hong Kong, listed on the Stock Exchange of Hong Kong.

Sample

Independent: Outbound international diversification: Number of countries, Inbound international diversification: Number of foreign partners. Dependent: ROA, Earnings before interest and taxes / assets.

Variable Coding Independent: International sales concentration according to Palepu (1985). Dependent: ROE, Sales Growth.

The Effect of Context 203

Author(s) Year Zahra, Garvis, 2000

Research Question(s) (1) What is the effect of international corporate entrepreneurship (ICE) effort on company performance? (2) How does perceived hostility of the international environment moderate the relationship between ICE and company performance? Results H1: Supported. ICE has a significant impact on ROA, revenue growth, foreign profits, and foreign revenue. H2: Supported. Environment hostility has a negative (but not significant) impact on ROA. The interaction term with ICE was significantly and positively associated with ROA - similar results for sales growth. The impact of ICE on ROA and sales growth is greater under higher levels of environment hostility.

(Relevant) Hypotheses H1: ICE will be positively associated with a firm's financial performance. H2: The relationship between ICE and a company's performance will be moderated by international environmental hostility. Firms that pursue ICE in international environments with higher levels of hostility will have higher profits and higher growth.

A 2.1: Studies of the Meta-Analysis (continued)

N=98 US manufacturing companies.

Sample

Variable Coding Independent: ICE - International corporate entrepreneurship, Global scope: Number of countries. Dependent: ROA, Sales Growth.

204 Appendix Chapter 2

Author(s) Year Zahra, Ireland, Hitt, 2000

Research Question(s) How do new venture firms that are internationalizing use technological learning gained through internationalization? What is the impact of this learning on the firm's financial performance? What is the impact of the firms' technological learning on their modes of entry into international markets? How does knowledge integration moderate the relationship between international expansion activities and technological learning? Results H4a,c: Supported. H4b: Partially supported. H5a: Not completely supported. Two of the five measures of international diversity were positively related to ROE. H5b: Supported. Generally: The results show a strong relationship between international diversity and the breadth, depth, and speed of a new venture firm's technological learning, especially when the firm undertakes formal knowledge integration.

(Relevant) Hypotheses H4a-c: The (a) breadth, (b) depth, and (c) speed of technological learning in international markets are positively related to new venture performance. H5a,b: International expansion is positively related to new venture profitability (sales growth).

A 2.1: Studies of the Meta-Analysis (continued)

N=321 US firms from high-tech industries; Age: younger than six year.

Sample

Variable Coding Independent: Entropy measure of number of countries. Dependent: ROE, Sales growth.

The Effect of Context 205

206

Appendix Chapter 2

A 2.2: Meta-Analytic Procedure and Statistical Formulas The meta-analysis applied in Chapter 2 can be divided into five main steps: Calculation of the mean effect size and observed variance, division of the observed variance into sampling error variance and residual variance, calculation of credibility interval, subgroup test, and calculation of confidence interval. The formulas used for these statistical analyses are all provided by Hunter and Schmidt (Hunter, Schmidt, and Jackson, 1982; Hunter and Schmidt, 1990). First the sample-size weighted mean effect size r corrected for sampling error is estimated. Following Hunter and Schmidt (1990), the best estimate of the population correlation () is the sample size weighted mean effect size ( r ) (1). The observed variance of correlations across studies (sr2) is defined as the sample size weighted average squared error (2).

(1) r

¦ >N * r @ ¦N i

i

i

2 (2) sr

¦

>N

* ri  r

2

i

¦ Ni

@

where: ri = observed effect size for each sample Ni = number of observations per sample. The second step involves a separation of the observed (sr2) into its two different components. It should be noted that the variance of observed effect sizes (sr2) is composed of the true variance (sU2) and variance stemming from sampling error (se2); thus, sr2 = sU2 + se2. The variance stemming from sampling error is calculated by the following formula (3):

1  r

2 2

2 (3) s e

*K N ¦ i

where: K = number of samples.

Accordingly, sU2 is the residual variance after the variance stemming from sampling error has been removed from the observed variance (i.e. sU2 = sr2 - se2).

The Effect of Context

207

In the third step, the existence or non-existence of sub-populations – i.e., moderators of the internationalization-performance relationship – is determined by calculating the credibility interval around the sample size weighted mean effect size corrected for sampling error. The range of the 95 percent credibility interval is based on the corrected standard error (sU2) in effect sizes. It is estimated by the following formula (4): (4) r - 1.96 * (sU2/K)1/2 < r < r + 1.96 * (sU2/K)1/2 I applied two criteria to determine whether my data set is homogeneous (no subgroups exist) or heterogeneous (subgroups or moderators exist). Homogeneity is assumed if credibility intervals do not overlap zero and at least 75 percent of the observed effect size variance is explained by sampling error. If these two criteria are not fulfilled, the fourth step involves subgroup analyses to quantitatively identify individual moderator variables. The z-test used produces critical values that indicate whether effect sizes between subgroups are significantly different. Z-test significance is determined by a one-tailed test if the direction of the effect size is hypothesized and a twotailed test if the direction of the effect size is not hypothesized. The critical value z is calculated by the following formula (5):

(5) z

r1  r2 2

2

s r1 s  r2 K1 K2

where: r(1,2) = mean effect size for compared subgroups weighted by sample size and uncorrected for sampling error sr(1,2)2 = observed variance of the effect sizes for compared subgroups weighted by sample size and uncorrected for sampling error K(1,2) = number of samples for compared subgroups.

208

Appendix Chapter 2

The final step implies the calculation of 95 percent confidence intervals in order to test for the significance of the obtained effect sizes. If an effect size is obtained from a homogeneous population (95 percent credibility intervals did not overlap zero and more than 75 percent of the observed variance was due to sampling error) the confidence interval is calculated around the sample size weighted mean effect size r corrected for sampling error based on the standard error from sampling error variance (se2) (6). (6) r - 1.96 * (se2/K)1/2 < r < r + 1.96 * (se2/K)1/2 But in the case of this meta-analysis all effect sizes are based on heterogeneous populations, since the criteria for population homogeneity were not met in any of the calculations. In such a case the confidence interval is calculated around the sample size weighted mean effect size r corrected for sampling error around the standard error from observed variance (sr2) (7). (7) r - 1.96 * (sr2/K)1/2 < r < r + 1.96 * (sr2/K)1/2

1,755 2,777 2,959 1,805 665 667 340 492 780

7,792

N

.159 .093 .063 -.053 -.006 .030 -.017 .024 .109

.059

r

.033 .012 .011 .004 .005 .019 .004 .006 .018

.017

sr2

.011 .005 .003 .002 .006 .006 .009 .006 .008

.005

se2

.022 .008a .008 .002 .000b .013 .000b .000b .011a

.012

sU2

.080 .032 -.003 -.118 -.076 -.105 -.090 -.064 .000

: : : : : : : : :

.239 .153 .128 .011 .064 .164 .056 .111 .217

.019 : .099

95% confidence interval

-.130 : .449 -.081 : .266 -.110 : .235 -.144 : .038 -.006 : -.006 -.191 : .251 -.017 : -.017 .024 : .024 -.094 : .312

-.152 : .270

95% Credibility interval

Notes: K: number of samples, N: sample size ¦Ni, r : sample size weighted mean effect size, sr2: variance in effect sizes, se2: sampling error variance, sU2: residual variance (sampling error corrected variance in effect sizes), 95% confidence interval: interval around sample size weighted mean effect size based on observed variance for heterogeneous populations and on sampling error variance for homogenous populations, 95% credibility interval: interval around sample size weighted mean effect size based on residual variance. a Deviation to difference between observed variance and sampling error variance due to rounding. b Zero values are possible in cases where only few studies are included into the estimate of an effect size.

20 13 10 4 4 4 3 3 6

41

H1a, H1b: Overall

Foreign sales to total sales Number of foreign countries Entropy measures Indices Number of foreign direct investments Foreign subsidiary sales Foreign assets to total assets Export sales to total sales Others

K

Variable

Table A 2.3.1 Independent Variable: Internationalization Comparison of effect sizes from different single measurement items

A 2.3: Methodological Moderators

The Effect of Context 209

5,420 1,973 1,797 1,260 218 1,851 725 2,873 371 344

7,792

N

.034 .086 .135 .078 .202 .064 .139 .020 .134 .119

.059

r

.015 .016 .019 .036 .020 .016 .009 .012 .009 .033

.017

sr2

.005 .007 .006 .006 .013 .005 .008 .002 .016 .009

.005

se2

.010 .009 .013 .029a .007 .010a .001 .010 .000b .025a

.012

sU2

-.014 .019 .056 -.054 .042 -.014 .063 -.068 .058 -.087

: : : : : : : : : :

.081 .153 .214 .208 .362 .141 .215 .109 .210 .326

.019 : .099

95% confidence interval

-.162 -.103 -.088 -.260 .202 -.134 .139 -.177 .134 -.188

: : : : : : : : : :

.230 .276 .357 .413 .202 .262 .139 .218 .134 .427

-.152 : .270

95% Credibility interval

Notes: K: number of samples, N: sample size ¦Ni, r : sample size weighted mean effect size, sr2: variance in effect sizes, se2: sampling error variance, sU2: residual variance (sampling error corrected variance in effect sizes), 95% confidence interval: interval around sample size weighted mean effect size based on observed variance for heterogeneous populations and on sampling error variance for homogenous populations, 95% credibility interval: interval around sample size weighted mean effect size based on residual variance. a Deviation to difference between observed variance and sampling error variance due to rounding. b Zero values are possible in cases where only few studies are included into the estimate of an effect size.

25 14 12 8 3 10 6 6 6 3

41

H1a, H1b: Overall

ROA ROS ROE Other return oriented measures ROI Sales growth Other growth oriented measures Capital market oriented measures Market Share Other

K

Variable

Table A 2.3.2 Dependent Variable: Performance Comparison of effect sizes from different single measurement items

A 2.3: Methodological Moderators (continued)

210 Appendix Chapter 2

Intangible Resources as Moderators

211

Appendix Chapter 3

A 3.1 Compilation of Sampling Firms

212

A 3.2 Descriptive Statistics of the Control Variables

224

A 3.3 Comparison of Selected Data from Different Databases

225

A 3.4 Output Screen of Extel Cards for SGL Carbon

226

A 3.5 Coding Procedure of TMT Demographics

234

A 3.6 Coefficients from Hedonic Regression (alternative)

236

A 3.7 Results for Foreign Assets to Total Assets

237

Table A 3.7.1 Regression of Curve Type and Moderation of Tobin’s q

237

Table A 3.7.2 Moderation of Hedonic q

238

Table A 3.7.3 Moderation of Individual Intangible Resources

239

A 3.8 Results for Time-Lagged Measurement Designs

240

Table A 3.8.1 Moderation of Individual Intangible Resources – ROA = t+1

240

Table A 3.8.2 Moderation of Individual Intangible Resources – ROA = t+2

241

A.S.CREATION TAPETEN O.N. 3U TELECOM AG 4 SC AG AAP IMPLANTATE AG AAREAL BANK AG ABIT AG O.N. AC-SERVICE AG NA O.N. ADIDAS-SALOMON AG O.N. ADVA AG OPT.NETW.O.N. ADVANCED PHOTONICS O.N. AHLERS AG ST O.N. AIG INTL REAL ESTATE AIXTRON AG O.N. ALLIANZ AG VNA O.N. ALPHAFORM O.N. ALTANA AG O.N. AMADEUS FIRE AG AMB GENERALI HOLDING AG ANALYTIK JENA AG O.N. ARBOMEDIA AG O.N. ARQUES INDUSTRIES AG ARTICON INTEGRALIS AG ARXES NETW.COMM.CONS.AG ATOSS SOFTWARE AG AUGUSTA TECHNOLOG.AG AWD HOLDING AG O.N. BAADER WP.HDLS.BK.AG O.N. BALDA AG O.N.

Company Name

Consumer Telecommunication Pharma & Healthcare Pharma & Healthcare Banks Software Software Consumer Technology Industrial Consumer Financial services Technology Insurance Industrial Pharma & Healthcare Industrial Insurance Industrial Media Industrial Software Software Software Industrial Financial services Financial services Industrial

Industry

A 3.1: Compilation of Sampling Firms

Home Construction & Furnishings Fixed-Line Telecommunication Biotechnology Medical Technology Mortgage Banks Software IT-Services Clothing & Footwear Communications Technology Advanced Industrial Equipment Clothing & Footwear Real Estate Semiconductors Insurance Industrial Products & Services Pharmaceuticals Industrial Products & Services Insurance Advanced Industrial Equipment Advertising Industrial, Diversified Software IT-Services Software Advanced Industrial Equipment Diversified Financial Securities Brokers Industrial Products & Services

Industry Group

missing missing missing missing 2006-2001 missing missing 2006-2001 2006-2001 missing 2006-2000 2005-2002 2006-2000 2006-2001 missing 2006-2001 2006-2002 2006-2001 2006-2001 missing 2005-2002 2006-2001 missing missing 2006-2000 2006-2001 2005-2004 2006-2001 missing 0.36 0.51 missing

0.36 missing missing 0.43 0.75

0.12

missing

0.36 0.90

0.83 0.00 0.56 0.67 0.74

0.16

0.25

FATA (2003)

0.47 0.87

Data FSTS Availability (2003)

IFRS

US standards (GAAP)

IFRS IFRS

IFRS

IFRS IFRS

US standards (GAAP)

Local standards

IFRS US standards (GAAP)

Accounting Standard followed

212 Appendix Chapter 3

BASF AG O.N. BASLER AG O.N. BAUVEREIN HAMBURG O.N. BAY.HYPO-VEREINSBK.O.N. BAY.MOTOREN WERKE AG ST BAYER AG O.N. BAYWA AG NA. BEATE UHSE AG BECHTLE AG O.N. BEIERSDORF AG O.N. BERTRANDT AG O.N. BETA SYST.SOFTW.AG O.N. BHW HOLDING AG O.N. BILFINGER BERGER AG BIOLITEC AG O.N. BIOTEST AG ST O.N. BMP AG BOEWE SYSTEC AG O.N. BROADNET AG BRUEDER MANNESM.AG O.N. CAATOOSEE AG CANCOM IT SYSTEME AG CARL-ZEISS MEDITEC AG CASH.LIFE AG CCR LOGISTICS SYSTEMS AG CDV SOFTWARE O.N. CE GLOB.SOURCING AG O.N CEAG AG

Company Name

Chemicals Industrial Financial services Banks Automobile Chemicals Industrial Retail Software Consumer Automobile Software Financial services Construction Pharma & Healthcare Pharma & Healthcare Industrial Industrial Telecommunication Retail Software Software Pharma & Healthcare Financial services Industrial Media Industrial Consumer

Industry Chemicals, Speciality Advanced Industrial Equipment Real Estate Credit Banks Automobile Manufacturers Chemicals, Speciality Industrial Products & Services Retail, Catalog IT-Services Personal Products Auto Parts & Equipment Software Diversified Financial Construction & Engineering Medical Technology Pharmaceuticals Industrial, Diversified Industrial Machinery Fixed-Line Telecommunication Retail, Specialty IT-Services IT-Services Medical Technology Diversified Financial Industrial Products & Services Movies & Entertainment Industrial Products & Services Consumer Electronics

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 missing missing 2006-2001 2006-2001 2006-2001 2006-2001 2006-2001 2006-2000 2006-2001 2006-2001 missing 2006-2001 2006-2001 2006-2001 2006-2000 2005-2001 2006-2000 missing missing 2006-2001 2006-2000 2006-2001 2006-2001 missing missing 2005-2000 2006-2001

0.59

0.61 missing 0.31 0.47 0.46 missing 0.14

0.46 missing 0.15 missing 0.69

0.61 0.13 0.28

missing missing

0.73 0.58 0.34 0.56 0.32 0.25 0.14

0.65 0.51 0.65 missing 0.84

0.91 0.19 0.92

0.90 0.42

FATA (2003)

0.80

Data FSTS Availability (2003)

IFRS IFRS

US standards (GAAP) US standards (GAAP) US standards (GAAP)

IFRS US standards (GAAP) IFRS Local with EEC guidelines Local with EEC guidelines

IFRS IFRS IFRS Local standards US standards (GAAP) IFRS IFRS

Local standards

Accounting Standard followed

Intangible Resources as Moderators 213

CELESIO AG O.N. CENIT AG SYSTEMH.O.N. CENTROTEC SUSTAINABLE O.N CEOTRONICS AG O.N. CEWE COLOR HOLDING O.N. COLON.REAL ESTATE AG COMBOTS AG NA O.N. COMDIRECT BANK AG COMMERZBANK AG O.N. COMPUTERLINKS AG COMTRADE AG CONERGY AG O.N. CONSTANTIN FILM AG O.N. CONTINENTAL AG O.N. CTS EVENTIM AG CURANUM AG CURASAN AG D + S EUROPE AG D. LOGISTICS AG O.N. DAB BANK AG DAIMLERCHRYSLER AG NA O.N DATA MODUL AG O.N. DEAG DT.ENTERTAINM. DEGUSSA AG O.N. DEUTSCHE BANK AG NA O.N. DEUTSCHE BOERSE NA O.N. DEUTSCHE EUROSHOP AG O.N. DEUTSCHE POST AG NA O.N.

Company Name

Retail Software Industrial Technology Consumer Financial services Software Financial services Banks Software Software Industrial Media Automobile Media Pharma & Healthcare Pharma & Healthcare Media Transportation & Logistics Financial services Automobile Technology Media Chemicals Banks Financial services Financial services Transportation & Logistics

Industry Retail, Food & Drug IT-Services Industrial Products & Services Communications Technology Leisure Goods & Services Real Estate Internet Securities Brokers Credit Banks IT-Services IT-Services Renewables Movies & Entertainment Auto Parts & Equipment Movies & Entertainment Health Care Biotechnology Advertising Logistics Securities Brokers Automobile Manufacturers Electronic Components & Hardware Movies & Entertainment Chemicals, Speciality Credit Banks Securities Brokers Real Estate Logistics

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2006-2000 2006-2000 missing 2006-2000 missing 2006-2001 2006-2001 2006-2001 2006-2001 missing 2006-2002 2006-2001 2006-2001 2006-2000 missing missing missing 2006-2000 2006-2001 2006-2001 2006-2000 2006-2000 2006-2001 2006-2001 2006-2001 2005-2001 2006-2001

0.93 0.03 missing missing missing

0.56 0.06 missing 0.56 missing

0.56 missing 0.07 0.15 0.47

0.16

0.41 0.10

0.51 0.06 0.14 0.67 0.05

0.46 0.84 0.23 0.54 0.72

0.48

FATA (2003)

0.82 0.03 0.18

Data FSTS Availability (2003)

IFRS

US standards (GAAP) US standards (GAAP) IFRS IFRS

US standards (GAAP)

IFRS IFRS US standards (GAAP) IFRS

IFRS

US standards (GAAP)

IFRS

IFRS IFRS IFRS

Accounting Standard followed

214 Appendix Chapter 3

DEUTSCHE POSTBANK AG DEUTZ AG O.N. DIS DEUT.IND.SERV.O.N. DOCCHECK AG DOUGLAS HOLDING O.N. DR. HOENLE AG O.N. DR.SCHELLER COSM.O.N. DRAEGERWERK VORZ.A.O.N. DRILLISCH AG O.N. DT.BETEILIG.AG O.N. DT.EFF.U.WECH.-BET.G.O.N. DT.TELEKOM AG NA DUERR AG O.N. DYCKERHOFF ST O.N. E.ON AG O.N. ECKERT+ZIEGLER AG O.N. ELEXIS AG O.N. ELMOS SEMICONDUCTOR AG ELRINGKLINGER AG NA O.N. EM.TV AG EMPRISE MANAG.CON.AG O.N. E-M-S NEW MEDIA AG EPCOS AG NA O.N. EPIGENOMICS AG ERSOL SOLAR ENERGY AG ESCADA AG O.N. ESSANELLE HAIR GROUP O.N. EVOTEC AG O.N.

Company Name

Banks Industrial Industrial Software Retail Industrial Consumer Pharma & Healthcare Telecommunication Industrial Financial services Telecommunication Industrial Construction Utilities Pharma & Healthcare Industrial Technology Automobile Media Software Media Technology Pharma & Healthcare Industrial Consumer Retail Pharma & Healthcare

Industry Credit Banks Heavy Machinery Industrial Products & Services Internet Retail, Specialty Advanced Industrial Equipment Personal Products Medical Technology Wireless Telecommunication Industrial, Diversified Diversified Financial Fixed-Line Telecommunication Industrial Machinery Building Materials Multi-Utilites Medical Technology Industrial Machinery Semiconductors Auto Parts & Equipment Movies & Entertainment IT-Services Movies & Entertainment Electronic Components & Hardware Biotechnology Renewables Clothing & Footwear Retail, Specialty Biotechnology

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2006-2000 2006-2001 2006-2000 2006-2001 missing missing 2006-2001 2006-2000 2006-2001 2005-2001 2006-2001 2006-2001 2006-2001 2006-2001 2006-2000 missing 2006-2001 2006-2000 2006-2003 2005-2000 missing 2006-2001 2006-2001 2006-2002 2006-2001 missing 2006-2001 missing missing missing missing

0.61 0.00 missing 0.48 0.33 missing 0.47 missing 0.34 0.54 0.03 missing 0.84 missing missing 0.64 0.78

0.75 0.00 missing 0.39 0.75 0.47 0.39 0.57 0.46 0.61 0.03 missing 0.73 missing 0.32 0.87 0.90

FATA (2003)

0.75 0.03 missing 0.30

Data FSTS Availability (2003)

US standards (GAAP)

US standards (GAAP) IFRS IFRS IFRS

US standards (GAAP) Local with EEC guidelines IFRS IFRS

Local with EEC guidelines IFRS IFRS US standards (GAAP) US standards (GAAP)

IFRS IFRS missing

Local with EEC guidelines IFRS IFRS Local with EEC guidelines

Accounting Standard followed

Intangible Resources as Moderators 215

FIELMANN AG O.N. FJH AG O.N. FLUXX AG FORTEC ELEKTRO. O.N. FRAPORT AG FFM.AIRPORT FREENET.DE O.N. FRESEN.MED.CARE KGAA ST FRESENIUS AG O.N. ST FUCHS PETROLUB AG O.N. FUNKWERK O.N. GEA GROUP AG GERATHERM O.N. GERRY WEBER INTERNAT.O.N. GESCO AG O.N. GFK AG O.N. GFT TECHNOLOGIES AG GILDEMEISTER AG O.N. GPC BIOTECH AG GRAMMER AG O.N. GRAPHIT KROPFMUEHL AG GRENKELEASING AG O.N. H+R WASAG AG HANN.RUECKVER.AG NA O.N. HAWESKO HOLDING AG SVG HCI CAPITAL NA O.N. HEIDELBERG.DRUCKMA.O.N. HEIDELBERGCEMENT AG O.N. HEILER SOFTWARE O.N.

Company Name

Retail Software Retail Technology Transportation & Logistics Software Pharma & Healthcare Pharma & Healthcare Chemicals Technology Industrial Pharma & Healthcare Consumer Industrial Industrial Software Industrial Pharma & Healthcare Automobile Basic resources Financial services Chemicals Insurance Retail Financial services Industrial Construction Software

Industry Retail, Specialty Software Retail, Internet Electronic Components & Hardware Transportation Services Internet Health Care Health Care Chemicals, Speciality Communications Technology Industrial, Diversified Medical Technology Clothing & Footwear Industrial, Diversified Industrial Products & Services IT-Services Industrial Machinery Biotechnology Auto Parts & Equipment Mining Diversified Financial Chemicals, Speciality Re-Insurance Retail, Food & Drug Diversified Financial Industrial Machinery Building Materials Software

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2005-2000 missing 2006-2001 2006-2001 2005-2001 2006-2001 2006-2001 2006-2001 missing 2005-2002 missing 2006-2001 missing 2006-2001 2006-2001 2006-2001 2006-2001 missing 2006-2001 2006-2004 missing 2006-2001 missing 2006-2002 2006-2001 2006-2001 missing

0.16 0.09 missing 0.09 missing missing missing missing missing missing 0.28 0.21 0.38 missing 0.30

missing missing

missing 0.15 0.01 missing 0.61 0.39 missing 0.40 0.65 0.33 0.41 0.02 0.44

0.59 0.88

FATA (2003)

0.18 0.15

Data FSTS Availability (2003)

IFRS IFRS

IFRS

US standards (GAAP) IFRS IFRS US standards (GAAP)

Local with EEC guidelines

US standards (GAAP)

International standards IFRS IFRS missing US standards (GAAP) IFRS

Local with EEC guidelines IFRS

Accounting Standard followed

216 Appendix Chapter 3

HENKEL KGAA ST O.N. HOCHTIEF AG HOEFT+WESSEL AG O.N. HORNBACH HOLD.VZO O.N. HORNBACH-BAUMARKT O.N. HUGO BOSS AG ST O.N. HYPO REAL ESTATE HLDG ST IBS AG EXC.COLL.MANU.O.N. IDS SCHEER AG O.N. IKB DT.INDUSTRIEBANK O.N. IM INTERNATIONALMED. O.N INDUS HOLDING AG INFINEON TECH.AG NA O.N. INIT INNOVATION O.N. INTERHYP AG INTERSHOP COMM. INTERTAINMENT O.N. INTICOM SYSTEMS AG ISRA VISION O.N. ITELLIGENCE AG O.N. IVG IMMOBILIEN AG O.N. IVU TRAFFIC TECHN.AG O.N. IWKA AG O.N. JACK WHITE PRODUCT.AG JENOPTIK AG O.N. JERINI AG JETTER AG O.N. JUNGHEINRICH AG O.N.VZO

Company Name

Consumer Construction Technology Retail Retail Consumer Banks Software Software Banks Media Industrial Technology Technology Financial services Software Media Technology Software Software Financial services Software Industrial Media Industrial Pharma & Healthcare Industrial Industrial

Industry Personal Products Construction & Engineering Electronic Components & Hardware Retail, Specialty Retail, Specialty Clothing & Footwear Mortgage Banks Software IT-Services Credit Banks Movies & Entertainment Industrial, Diversified Semiconductors Electronic Components & Hardware Diversified Financial Internet Movies & Entertainment Communications Technology Software IT-Services Real Estate IT-Services Industrial Machinery Movies & Entertainment Advanced Industrial Equipment Biotechnology Advanced Industrial Equipment Industrial Machinery

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2006-2001 2006-2000 2006-2001 2006-2001 2006-2001 missing 2006-2000 2006-2001 2006-2001 2006-2000 2006-2001 2006-2001 missing 2006-2002 2006-2000 2005-2000 missing 2006-2001 2006-2000 2006-2003 2006-2000 2006-2001 missing 2006-2001 missing missing 2006-2001

missing 0.52 missing 0.24 0.28 0.61 missing 0.38 missing 0.08 0.45

0.12 missing 0.08 0.38 0.00 0.41 missing

0.36

0.43 0.59 0.78 0.35 0.77

0.20 missing 0.51 0.50 0.16 0.62 0.52

0.72

FATA (2003)

0.81 0.81 0.60 0.29 0.31 0.74

Data FSTS Availability (2003)

US standards (GAAP)

IFRS

IFRS IFRS

IFRS IFRS

US standards (GAAP) IFRS

IFRS Local with EEC guidelines US standards (GAAP)

US standards (GAAP) US standards (GAAP)

IFRS IFRS IFRS IFRS Local with EEC guidelines IFRS

Accounting Standard followed

Intangible Resources as Moderators 217

K+S AG O.N. KARSTADT QUELLE AG O.N. KLOECKNER-WERKE O.N. KOENIG + BAUER AG ST O.N. KONTRON AG O.N. KRONES AG O.N. KWS SAAT AG O.N. LANXESS AG LEIFHEIT AG O.N. LEONI AG NA O.N. LINDE AG O.N. LINOS O.N. LION BIOSCIENCE AG O.N. LLOYD FONDS AG LOEWE AG O.N. LPKF LASER+ELECTRON. LUDW.BECK A.RATHAUSECK LUFTHANSA AG VNA O.N. MAGIX AG NA O.N. MAN AG ST O.N. MARSEILLE-KLINIKEN AG MASTERFLEX O.N. MAXDATA AG MEDICLIN AG MEDIGENE NA O.N. MEDION AG O.N. MENSCH UND MASCH.O.N. MERCK KGAA O.N.

Company Name

Chemicals Retail Industrial Industrial Technology Industrial Industrial Chemicals Consumer Automobile Chemicals Industrial Pharma & Healthcare Financial services Consumer Industrial Retail Transportation & Logistics Software Industrial Pharma & Healthcare Industrial Industrial Pharma & Healthcare Pharma & Healthcare Industrial Software Pharma & Healthcare

Industry 0.22 0.21 0.06 0.19 missing 0.28 missing 0.52 0.32 0.60 0.81 0.08 0.32 missing 0.24 missing 0.22 0.00 0.27 0.24 0.00 0.00 0.39 0.62

0.49 0.80 0.36 0.75 0.00 0.47 0.41 0.00 0.00 0.39 0.90

FATA (2003)

0.76 0.24 0.72 0.86 0.48 0.82 0.73 0.76 0.57 0.58 0.79 0.11 0.81

Data FSTS Availability (2003)

Chemicals, Commodity 2006-2001 Retail, Multiline 2006-2001 Industrial Machinery 2006-2002 Industrial Machinery 2006-2001 Electronic Components & Hardware 2006-2001 Industrial Machinery 2006-2000 Industrial Products & Services 2006-2001 Chemicals, Commodity 2006-2002 Household Appliances & Housewares 2006-2000 Auto Parts & Equipment 2006-2001 Industrial Gases 2006-2001 Advanced Industrial Equipment 2006-2000 Biotechnology 2005-2001 Diversified Financial 2006-2002 Consumer Electronics 2006-2001 Advanced Industrial Equipment 2006-2000 Retail, Specialty missing Airlines 2006-2001 Software missing Industrial, Diversified 2006-2001 Health Care 2006-2001 Industrial Products & Services 2006-2000 Industrial Products & Services 2006-2001 Health Care 2006-2001 Biotechnology 2006-2000 Industrial Products & Services 2006-2001 Software missing Pharmaceuticals 2006-2001

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

IFRS

IFRS Local with EEC guidelines IFRS IFRS Local standards US standards (GAAP) IFRS

IFRS

IFRS IFRS

Local standards IFRS Local with EEC guidelines IFRS IFRS missing Local with EEC guidelines IFRS IFRS US standards (GAAP) IFRS IFRS US standards (GAAP)

Accounting Standard followed

218 Appendix Chapter 3

METRO AG ST O.N. MLP AG MOBILCOM AG O.N. MORPHOSYS AG O.N. MPC MUENCH.PET.CAP.O.N. MTU AERO ENGINES NA O.N. MUEHLBAUER HOLD.O.N. MUELLER-DIE LILA LOGISTIK MUENCH.RUECKVERS.VNA O.N. MVV ENERGIE AG O.N. MWB WERTPAPIERHAND.AG NEMETSCHEK AG O.N. NET AG NEUE SENTIM.FILM O.N. NEXUS AG O.N. NORDDT.AFFINERIE O.N. NORDEX AG O.N. NOVEMBER AG O.N. NUERNBERGER BET.AG VNA OHB TECHNOLOGY O.N. ONVISTA O.N. ORBIS AG O.N. P U.I PER.U.INFO.AG O.N. PAION O.N PANDATEL AG O.N. PARAGON AG PARSYTEC AG PATRIZIA IMMOBILIEN NA ON

Company Name

Retail Financial services Telecommunication Pharma & Healthcare Financial services Industrial Technology Transportation & Logistics Insurance Utilities Financial services Software Software Media Software Basic resources Industrial Pharma & Healthcare Insurance Technology Software Software Software Pharma & Healthcare Technology Technology Software Financial services

Industry Retail, Multiline Diversified Financial Wireless Telecommunication Biotechnology Diversified Financial Heavy Machinery Electronic Components & Hardware Logistics Re-Insurance Multi-Utilites Securities Brokers Software Software Advertising IT-Services Steel & Other Metals Renewables Biotechnology Insurance Communications Technology Internet IT-Services Software Biotechnology Communications Technology Electronic Components & Hardware Software Real Estate

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2006-2001 2005-2001 2006-2001 2006-2004 2006-2002 2006-2001 missing 2006-2001 2006-2001 missing 2006-2000 2006-2001 missing missing 2006-2001 2006-2002 2006-2000 2006-2001 missing 2006-2000 missing missing 2006-2001 2005-2001 missing 2006-2000 missing

0.52 0.00 missing 0.02 missing

missing 0.41 0.00

missing missing missing

missing

missing missing 0.21

0.00 0.83 0.74 0.59

missing 0.50 0.04

0.38 0.51 0.14

0.16

missing missing 0.78

FATA (2003)

0.50

Data FSTS Availability (2003)

US standards (GAAP)

IFRS US standards (GAAP)

IFRS

IFRS IFRS IFRS

IFRS US standards (GAAP)

IFRS

IFRS US standards (GAAP)

IFRS IFRS

IFRS

Accounting Standard followed

Intangible Resources as Moderators 219

Industry

PC-WARE INFOR.TECHNOLO.AG Software PFEIFFER VACUUM TECH.O.N. Industrial PFLEIDERER AG Industrial PLAMBECK N.ENERG.NA O.N. Industrial PLASMASELECT AG Pharma & Healthcare PLENUM AG O.N. Software PONGS + ZAHN AG O.N. Chemicals PRAKTIKER BAU-U.H.HLDG ON Retail PREMIERE NA O.N. Media PRIMION TECHNOLOGY O.N. Industrial PROCON AG O.N. Media PROGRESS-WERK OBERK. O.N. Automobile PROSIEBENSAT.1 O.N.VZO Media PSI AG F.PR.U.SYS.O.N. Software PULSION ST O.N. Pharma & Healthcare PUMA AG Consumer PVA TEPLA AG O.N. Industrial Q-CELLS AG Industrial QSC AG NA O.N. Telecommunication R. STAHL AG O.N. Industrial RATIONAL AG Industrial REALTECH AG O.N. Software REPOWER SYSTEMS AG Industrial RHEINMETALL AG Industrial RHOEN-KLINIKUM O.N. Pharma & Healthcare ROHWEDDER AG O.N. Industrial RUECKER AG O.N. Automobile RWE AG ST O.N. Utilities

Company Name IT-Services Advanced Industrial Equipment Industrial Products & Services Renewables Health Care IT-Services Chemicals, Commodity Retail, Specialty Broadcasting Industrial Products & Services Movies & Entertainment Auto Parts & Equipment Broadcasting Software Medical Technology Clothing & Footwear Advanced Industrial Equipment Renewables Fixed-Line Telecommunication Industrial Machinery Industrial Products & Services IT-Services Renewables Industrial, Diversified Health Care Industrial Machinery Auto Parts & Equipment Multi-Utilites

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2006-2001 2006-2001 2006-2000 2006-2001 2005-2001 missing missing 2006-2001 missing missing 2006-2000 2006-2001 2006-2000 missing 2006-2001 missing 2006-2002 2006-2001 missing 2006-2001 2006-2001 missing 2006-2001 2006-2001 missing 2006-2001 2006-2001

0.45 0.32 missing missing missing 0.00

0.00

0.19 0.00 0.00 missing missing 0.00 0.37 0.29 0.42 0.00 missing 0.62

0.00

0.34 0.00 0.17 0.32 0.26 0.00 0.84 0.55 0.64 0.00 0.25 0.45

FATA (2003)

0.35 0.42 0.54 missing 0.24 0.00

Data FSTS Availability (2003)

US standards (GAAP) IFRS

IFRS IFRS

IFRS US standards (GAAP)

IFRS US standards (GAAP)

IFRS

IFRS IFRS IFRS

IFRS

IFRS US standards (GAAP) US standards (GAAP) IFRS IFRS US standards (GAAP)

Accounting Standard followed

220 Appendix Chapter 3

SALZGITTER AG O.N. SANACORP PHARMAHAN.VZO SAP AG O.N. SARTORIUS AG O.N. SCHERING AG O.N. SCHLOTT GRUPPE AG O.N. SCHWARZ PHARMA AG O.N. SECUNET SECURITY AG O.N. SGL CARBON AG O.N. SHS AG O.N. SIEMENS AG NA SILICON SENSOR INT. O.N. SINGULUS TECHNOL. SINNERSCHRADER O.N. SIXT AG ST O.N. SOFTING AG O.N. SOFTM SOFTW.U.BER.O.N. SOFTWARE AG O.N. SOLAR-FABRIK AG O.N. SOLARWORLD AG O.N. SOLON AG F.SOLARTECH.AG SPL.MEDIEN AG O.N. STADA ARZNEIMITT.VNA O.N. STEAG HAMATECH AG O.N. STRATEC BIOMED.SY.EO 1 SUEDZUCKER MA./OCHS. O.N. SUESS MICROTEC O.N. SUNWAYS AG O.N.

Company Name

Basic resources Retail Software Industrial Pharma & Healthcare Media Pharma & Healthcare Software Chemicals Software Industrial Technology Industrial Software Transportation & Logistics Industrial Software Software Industrial Industrial Industrial Media Pharma & Healthcare Industrial Pharma & Healthcare Food & Beverages Technology Industrial

Industry Steel & Other Metals Retail, Food & Drug Software Advanced Industrial Equipment Pharmaceuticals Publishing & Printing Pharmaceuticals IT-Services Chemicals, Speciality IT-Services Industrial, Diversified Semiconductors Advanced Industrial Equipment IT-Services Transportation Services Advanced Industrial Equipment Software Software Renewables Renewables Renewables Movies & Entertainment Pharmaceuticals Advanced Industrial Equipment Medical Technology Food Semiconductors Renewables

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2006-2001 2006-2001 2006-2001 2006-2001 2006-2001 2006-2001 2006-2001 2006-2001 missing 2006-2001 missing 2006-2001 2006-2001 2006-2004 missing missing 2006-2001 missing 2006-2001 missing missing 2006-2001 2006-2000 missing 2006-2001 2006-2001 missing

0.09 0.00 0.53 missing missing 0.08 0.64 missing 0.68 0.61 missing missing 0.22

missing 0.03

missing missing missing missing

0.63 0.90 missing 0.14

0.42 0.30

0.53 0.89 0.00 0.71

FATA (2003)

0.53 0.00 0.75 0.42 0.52 0.27 0.67 0.03 0.85

Data FSTS Availability (2003)

IFRS US standards (GAAP)

IFRS IFRS

IFRS

IFRS

IFRS US standards (GAAP) Local with EEC guidelines

US standards (GAAP)

IFRS IFRS US standards (GAAP) IFRS IFRS International standards US standards (GAAP) IFRS IFRS

Accounting Standard followed

Intangible Resources as Moderators 221

SURTECO AG SYNAXON AG SYSKOPLAN AG SYZYGY AG O.N. TA TRIUMPH-ADLER AG TAG TEGERNSEE IMMOB. TAKKT AG O.N. TDS INFORMATIONSTECH. TECHEM O.N. TECHNOTRANS AG O.N. TELEGATE AG O.N. TELES AG INFORM.TECHN. THIELERT NA O.N. THYSSENKRUPP AG O.N. TIPP24 AG NA O.N. TIPTEL AG TOMORROW FOCUS AG T-ONLINE INTERN. NA O.N. TRAVEL24.COM AG KON. TRIA IT-SOLUTIONS AG TRIPLAN AG O.N. TUI AG NA TV-LOONLAND O.N. UMS O.N. UNITED LABELS O.N. USU SOFTWARE AG UTD.INTERNET AG NA UTIMACO SAFEW.AG O.N.SVG

Company Name

Basic resources Retail Software Software Industrial Financial services Retail Software Industrial Industrial Telecommunication Software Industrial Industrial Retail Technology Software Software Retail Software Construction Transportation & Logistics Media Pharma & Healthcare Retail Software Software Software

Industry Forest & Paper Products Retail, Specialty IT-Services IT-Services Industrial Products & Services Real Estate Retail, Catalog IT-Services Industrial Products & Services Advanced Industrial Equipment Telecommunication Services Internet Industrial Machinery Industrial, Diversified Retail, Internet Communications Technology Internet Internet Retail, Internet IT-Services Construction & Engineering Transportation Services Movies & Entertainment Medical Technology Retail, Specialty Software Internet Software

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

2006-2001 2006-2000 missing 2006-2000 2006-2001 2005-2003 2006-2001 2006-2000 2006-2001 2006-2001 2006-2001 2006-2000 2005-2002 2006-2001 2005-2001 2005-2001 2006-2000 2005-2001 missing 2006-2001 missing 2006-2001 2005-2000 2006-2001 2006-2000 2006-2000 2006-2001 2006-2001

0.15 missing 0.48 0.14 0.63 0.11 0.14 0.26 0.25 0.07 missing missing missing 0.20 0.00 0.28 0.00 0.61 0.22 0.32 missing 0.01 0.21 0.44

0.50 0.29 0.75 0.11 0.13 0.54 0.18 0.70 0.73 0.67 0.09 0.48 0.00 0.11 0.00 0.91 0.90 0.77 0.60 0.09 0.23 0.41

FATA (2003)

0.30 missing

Data FSTS Availability (2003)

IFRS IFRS IFRS IFRS IFRS IFRS IFRS

IFRS

IFRS US standards (GAAP) IFRS IFRS US standards (GAAP) IFRS IFRS US standards (GAAP) IFRS IFRS IFRS IFRS

US standards (GAAP) IFRS

IFRS IFRS

Accounting Standard followed

222 Appendix Chapter 3

VARETIS AG VCL FILM+MEDIEN AG KONV. VILLEROY + BOCH AG VZ VIVACON AG O.N. VOLKSWAGEN AG ST O.N. VOSSLOH AG O.N. W.O.M. O.N. WACKER CHEMIE O.N. WAPME SYSTEMS O.N. WASHTEC AG O.N. WAVELIGHT AG O.N. WCM BET.-U.G. O.N. WESTAG + GETALIT ST O.N. WINCOR NIXDORF O.N. WIRE CARD AG ZAPF CREATION AG O.N.

Company Name

Technology Media Consumer Financial services Automobile Industrial Pharma & Healthcare Chemicals Software Industrial Pharma & Healthcare Industrial Consumer Industrial Software Consumer

Industry

missing 0.52 0.49 0.64 missing

0.06 0.13 0.60 missing

0.72 0.68 0.77

0.63 0.16 0.67 0.68

FATA (2003)

missing 0.70

Data FSTS Availability (2003)

Communications Technology missing Movies & Entertainment 2005-2000 Household Appliances & Housewares 2006-2001 Real Estate missing Automobile Manufacturers 2006-2001 Industrial Products & Services 2006-2001 Medical Technology missing Chemicals, Speciality 2006-2000 Internet missing Industrial Machinery missing Medical Technology missing Industrial, Diversified 2005-2000 Home Construction & Furnishings 2006-2000 Industrial Products & Services 2006-2002 IT-Services missing Leisure Goods & Services 2005-2000

Industry Group

A 3.1: Compilation of Sampling Firms (continued)

US standards (GAAP)

Local with EEC guidelines Local with EEC guidelines International standards

missing

IFRS IFRS

missing IFRS

Accounting Standard followed

Intangible Resources as Moderators 223

224

Appendix Chapter 3

A 3.2: Descriptive Statistics and Correlations Matrix of the Control Variables (N = 789) Variables

Mean

S. D.

1

2

3

4

5

6

1. Total Assets_ln

6.89

2.08

2. Employees_ln

8.63

1.86

.93**

3. Total Sales_ln

6.97

1.98

.97** .94**

4. Prod. Div._2digitSIC

2.87

1.46

.53** .52** .53**

5. Prod. Div._4digitSIC

4.55

2.14

.58*

6. Total Debt / Total Assets

.606

.177

.34** .39** .38** .31** .51**

7. Long Term Debt / Total Assets

.131

.116

.21** .21** .18** .18** .56** .51**

.58** .58** .77**

Notes: Bold correlations are those of alternative operationalizations of the control variables. † p < .10. * p < .05. ** p < .01 (all two-tailed tests).

-19,0 -37,8 -28,4 -19,2 -8,6

R&D expenses Deutsche Post Gildemeister Kontron SGL Carbon Vossloh -19,0 -43,1 -26,3 -19,0 -7,4

6.404 99,8 76,0 99,0 272,8

154.933 874,9 272,0 1.246,9 880,3

40.017 977,8 229,3 915,8 912,5 40.016.990 977.762 229.244 1.046.200 919.800

missing 37.800 28.430 19.200 8.600

6.845.997 98.911 83.514 84.800 276.000 19.000 43.100 26.312 20.900 7.400

6.403.997 99.795 87.140 101.400 271.000

152.781.000 154.134.000 915.198 845.414 259.047 265.701 1.184.599 1.122.099 1.000.500 914.000

43.167.980 1.051.499 262.134 926.200 922.200

Datastream 2004 2003 45.286.038 1.106.505 259.429 1.183.953 1.040.910

missing missing 35.359 23.880 10.696

8.629.357 101.453 76.550 115.221 364.142

missing missing 29.776 23.652 8.374

7.641.797 95.772 81.318 124.841 341.737

208.372.268 195.374.009 1.277.208 1.103.284 1.227 0.000 1.786.471 1.572.369 1.387.681 1.162.158

45.745.969 1.307.792 326.026 1.151.951 1.146.976

Compustat 2004 2003

-19,0 -37,8 -28,7 -19,2 -8,6

6.846 98,9 83,5 84,8 276,0

153.235 970,7 278,7 1.314,8 1.021,3

43.168 1.051,5 262,1 944,0 921,8

-19,0 -43,1 -26,3 -19,0 -7,4

6.404 99,8 76,0 99,0 272,8

154.933 874,9 272,1 1.246,9 880,3

40.017 977,8 229,3 916,0 912,5

Extel Cards 2004 2003

Notes: Bold figures indicate deviations between the data reported in the database as compared to the figures derived from the annual report. a Data reported in annual report and Extel cards are in million, data from Datastream and Compustat are in thousand.

6.846 98,9 83,5 84,8 276,0

153.357 970,7 278,8 1.314,8 1.021,3

Total Assets Deutsche Post Gildemeister Kontron SGL Carbon Vossloh

Intangible Assets Deutsche Post Gildemeister Kontron SGL Carbon Vossloh

43.168 1.051,5 262,1 944,0 922,2

Turnover Deutsche Post Gildemeister Kontron SGL Carbon Vossloh

Annual Reporta 2004 2003

A 3.3: Comparison of Selected Data from Different Databases

Intangible Resources as Moderators 225

* * * * * * * * * * CORPORATE STRUCTURE * * * * * * * * * * SUBSIDIARIES Company Country Owned Main Consolidated SGL Carbon AG Germany 100,00% SGL Carbon Beteiligung GmbH Germany 100,00% SGL CARBON GmbH Germany 100,00% SGL TECHNOLOGIES GmbH Germany 100,00% SGL BRAKES GmbH Germany 100,00% SGL Carbon Holding GmbH Germany 100,00% SGL PanTrac GmbH Germany 100,00% SGL Carbon Holding S.L Spain 100,00% KCH Beteiligungs GmbH Germany 100,00% SGL CARBON SA Poland 100,00% ZEW Zaklady Elektrod Weglowych SA Poland 97,20%

* * * * * * * * * * COMPANY INFORMATION * * * * * * * * * * OPERATING STATUS: Active

* * * * * * * * * * COMPANY IDENTIFIERS * * * * * * * * * * TICKER: SGL EXTEL REF. NO: 00032015 SEDOL: 4818351 ISIN: DE0007235301

* * * * * * * * * * COMMUNICATIONS * * * * * * * * * * TELEPHONE: +49 611 60 29 0 FAX: +49 611 60 29 101 URL: http://www.sglcarbon.com

Rheingaustrasse 182 65203 Wiesbaden GERMANY

SGL Carbon AG

LAST AMENDED: May 1, 2006

May 19, 2006

Copyright 2006 Thomson Financial Thomson Extel Cards Database

A 3.4: Output Screen of Extel Cards for SGL Carbon

Chairman Vice Chairman Member Member Member Member Member Member

Position

SUPERVISORY BOARD Name Max D. Kley Josef Scherer Prof. Dr. Utz-Hellmuth Felcht Peter Fischer Dr. Claus Hendricks Juergen Kerner Dr. Hubert Lienhard Jacques Loppion

* * * * * * * * * * EXECUTIVES * * * * * * * * * *

27 Apr 2005 Appointed

Appointed/Ceased

SGL CARBON spA Italy 99,70% SGL CARBON SA Spain 100,00% SGL CARBON SA France 100,00% SGL CARBON GmbH & Co Australia 100,00% RK Carbon International Ltd United Kingdom 100,00% SGL TECHNIC Ltd United Kingdom 100,00% PG Lawton Ltd United Kingdom 100,00% SGL TECHNIC SA France 100,00% SGL Risomesa SpA Italy 100,00% SGL CARBON Ltd United Kingdom 100,00% SGL CARBON LLC United States 100,00% MGP LLC United States 100,00% HITCO CARBON Composites Inc United States 94,00% SGL TECHNIC Inc United States 100,00% SGL Canada Inc Canada 100,00% SGL ACOTEC Sarl France 100,00% SGL ACOTEC Sarl Maroc Morocco 100,00% SGL ACOTEC Ltd United Kingdom 100,00% SGL ACOTEC SpA Italy 100,00% SGL ACOTEC Polska Spzoo Poland 51,00% Ceilcote Ing Corrosion SA de CV Mexico 51,00% SGL ACOTEC Singapore Pte Ltd Singapore 100,00% SGL ACOTEC Inc United States 100,00% SGL ACOTEC Ltda Brazil 100,00% SGL ACOTEC Wuhan Co Ltd China 90,00% Note: O = Owned; C = Controlled. If neither is indicated then the company has not reported the owned and controlled proportions being different.

226 Appendix Chapter 3

MANAGEMENT BOARD Name Robert J. Koehler Sten Daugaard Theodore H. Breyer Dr. Hariolf Kottmann

Edelbert Schilling Andrew H. Simon Heinz Will Hans-Werner Zorn

Appointed/Ceased

28 Apr 2005 Appointed

* * * * * * * * * * FINANCIALS * * * * * * * * * * FISCAL YEAR DATE: 12/31

* * * * * * * * * * MARKET AND INDUSTRY * * * * * * * * * * PRIMARY SIC: 3624 - Carbon and graphite products SECONDARY SIC: 3624 - Carbon and graphite products 1629 - Heavy construction, nec 3674 - Semiconductors and related devices 3561 - Pumps and pumping equipment 3295 - Minerals, ground or treated 3823 - Process control instruments PRODUCTS: Carbon & graphite accounted for 60% of 2005 revs; Special graphite, 25%; Technical products, 15% & Others nominal. MARKETS: GERMANY -

SGL Carbon AG. The Group's principal activity is to manufacture carbon, graphite and composite materials. The Group operates in three divisions: Carbon and Graphite: develops graphite electrodes designed for industrial steel production in electric arc furnaces; Graphite Specialties: supplies products made of isostatically pressed, extruded, die and vibrationmolded graphite, carbon/carbon, felt, graphite foils and laminated sheets, carbon and graphite yarns for a variety of applications and SGL technologies: develops new business opportunities based on the Group's competencies for high technology materials, processes and applications. The Group has operations in Europe, North, Central and South America.

* * * * * * * * * * DESCRIPTION * * * * * * * * * *

Position Chairman & Chief Executive Chief Financial Officer Member Member

Member Member Member Member

CREDS due within 1 yr Short term debt Pble-group cos Trade creditors Accruals & defd inc Payments on account Revenue tax Tax & social security Current provisions Misc creditors

MISC ASSETS CURRENT ASSETS Stocks Rcble-eqty A/c cos Intra-group recbles Trade debtors Prepays/accrued inc Tax recoverable Misc debtors Cash & near cash Cash & equivalents Trading investments Misc current assets

FIXED ASSETS Intangible assets Tangible assets Financial assets

66,3 90,3 6,5 10,3 4,8 131 59,8 -------369 --------

256,4 6,9 178,2 3,5 9,8 10,7 128 67,5 9,9 -------670,9 --------

280,6 3,7 192,3 4,1 9,9 14,7 93,4 4,3 -------603 -------5,8 89,2 7,9 16,1 5,9 151 40,4 -------316,3 --------

84,8 353,1 11,5 -------449,4 -------195,4

Eurom 31 Dec 2004

86,6 346 14,9 -------447,5 -------132,8

Eurom 31 Dec 2005

83,9 5,5 98,9 7,6 1,8 9,5 8,2 153,6 105,9 -------474,9 --------

258 28,7 204,2 3,3 17,5 25,7 46,1 -------583,5 --------

99 408,5 28,7 -------536,2 -------127,2

Eurom 31 Dec 2003

CONSOLIDATED BALANCE SHEETS

* * * * * * * * * * BALANCE SHEET * * * * * * * * * *

A 3.4: Output Screen of Extel Cards for SGL Carbon (continued)

193,1 6 110,5 0,8 6,4 6,7 131,3 -------454,8 --------

288,4 12,9 198,1 7 19,8 21,4 0,1 31 -------578,7 --------

103,8 477,3 33,2 -------614,3 -------93,4

Eurom 31 Dec 2002

300,7 3,8 107,7 7,3 12,5 5,2 168,4 -------605,6 --------

394,2 6,4 256 11,6 0,5 47,2 -------715,9 --------

111,2 553,5 34 -------698,7 -------80,4

Eurom 31 Dec 2001

Intangible Resources as Moderators 227

NET ASSETS

SHAREHOLDER S' FUNDS Minority interests

SHARE CAPITAL Share premium Retained earnings Profit for the year Currency apprecn res Misc reserves

NET ASSETS

PROVISIONS MISC LIABILITIES

CREDS due after 1 yr Long term debt L/T trade creditors Misc other L/T liabs

TOTAL ASSETS LESS CURRENT LIABILITIES

NET CURRENT ASSETS

353,3 1 36,7 -------391 221,4 65,2

-------269,1 -------142,9

274 -25,2 -86,4 -39,6 1,6 -------267,3

1,8 -------269,1 --------

-------323,4 -------144,9

280,6 -111,6 28,2 -19,1 -0,9 -------322,1

1,3 -------323,4 --------

--------

--------

336,3 0,4 0,2 -------336,9 206,7 -

301,9

-------946,7

286,7

-------867

0,3 -------116,9 --------

111,5 -51,7 -------116,6

-------116,9 -------56,8

410,6 -------410,6 244,5 -

--------

-------772

108,6

1,4 -------197,7 --------

111,3 37,8 -8,8 -------196,3

-------197,7 -------56

255,4 -------255,4 378,5 -

--------

-------831,6

123,9

1,6 -------256,8 --------

111,3 88,7 -------255,2

-------256,8 -------55,2

238,2 -------238,2 394,4 -

--------

-------889,4

110,3

Cap w-i-p NBV c/f

Cap w-i-p gross c/f Cap w-i-p written off

Other tangible FA NBV

Oth tangible FA-cost Oth tangible FA depn

Property NBV

Property NBV

Property - cost Property depreciation

Misc intang FA, net

Misc intang FA, gross Misc intang FA amortn

Brands, patents, net

66,8 -------66,8 ---------------------42,5 -22,7 -------19,8 --------------86,6 -------321,7 -199 -------122,7 --------------122,7 -------1.111,30 -907,3 -------204 -------19,5 -0,2 -------19,3 --------

Eurom 31 Dec 2005 61,6 -------61,6 ---------------------41 -17,8 -------23,2 --------------84,8 -------312,9 -188,1 -------124,8 --------------124,8 -------1.063,30 -853,8 -------209,5 -------19 -0,2 -------18,8 --------

Eurom 31 Dec 2004 114,6 -36,5 -------78,1 ---------------------44,3 -23,4 -------20,9 --------------99 -------355,5 -204,4 -------151,1 --------------151,1 -------1.091,70 -851,6 -------240,1 -------17,5 -0,2 -------17,3 --------

Eurom 31 Dec 2003

Eurom 31 Dec 2002 120,8 -29,9 -------90,9 ---------------------34,4 -21,5 -------12,9 --------------103,8 -------372 -203,7 -------168,3 --------------168,3 -------1.155,30 -875,7 -------279,6 -------29,6 -0,2 -------29,4 --------

NOTES TO CONSOLIDATED BALANCE SHEETS

Brands/patents, gross Brands/patents amortn

Goodwill, net

INTANGIBLE ASSETS Goodwill, gross Goodwill, amortn

A 3.4: Output Screen of Extel Cards for SGL Carbon (continued)

132,3 -26,6 -------105,7 -------24 -18,5 -------5,5 ----------------------------111,2 -------395,8 -214,5 -------181,3 --------------181,3 -------1.249,10 -929,6 -------319,5 -------52,9 -0,2 -------52,7 --------

Eurom 31 Dec 2001

228 Appendix Chapter 3

DEBT BY TYPE Convertible loans Credit institutions Bills & notes Misc debt

Due after one year

DEBTORS includes L/T trade debtors Misc L/T debtors

STOCKS Raw materials etc Work in progress Finished gds & resale Advance stock pmts Misc stocks

Long term receivables Misc financial assets

Trade investments

Invs in assoc cos Trade investments

Investments

FINANCIAL ASSETS

Tangible assets

320 119,9 -20,3 -------419,6 --------

--------

--------

270 88,1 -16 -------342,1 --------

0,3 -------0,3

64,4 134,9 57,1 -------256,4 --------

-------2,4 -------4,4 -------4,4 -------4,7 -------11,5 --------

-------353,1 --------

0,1 -------0,1

85,2 138,5 56,9 -------280,6 --------

-------2,4 -------7,7 -------7,7 -------4,8 -------14,9 --------

-------346 --------

133,7 360,8 -------494,5 --------

--------

2,2 0,2 -------2,4

71,8 138,5 47,1 0,6 -------258 --------

-------2,5 -------21 -------21 -------5,2 -------28,7 --------

-------408,5 --------

135 313,5 -------448,5 --------

--------

0,3 -------0,3

83,1 147,9 54,5 -6,4 9,3 -------288,4 --------

-------2,5 -------25,6 -------25,6 -------5,1 -------33,2 --------

-------477,3 --------

135 359,5 37 7,4 -------538,9 --------

--------

0,4 -------0,4

109,1 200,9 71 0,6 12,6 -------394,2 --------

-------2,7 -------26,1 -------26,1 -------5,2 -------34 --------

-------553,5 --------

SHARE CAPITAL Ordinary shares SHAREHOLDERS' FUNDS Eqty s/holders funds COMMITMENTS AND CONTINGENCIES Lease commitments PENSION BENEFITS Pension benefit oblig. Fair value - plan assets Unfunded pension liab PENSION BENEFIT COSTS Pension service costs Pension interest cost Exp return - plan assets Oth net pension

Short term debt PROVISIONS Tax provisions Deferred taxation Pension provisions Severance provisions Misc provisions

DEBT BY MATURITY Debt due within 1 yr

A 3.4: Output Screen of Extel Cards for SGL Carbon (continued)

47,4 169,4

63,9 205

-6,7

-6,6

-5,2 -11,8 3,4

216,8

268,9

-5,1 -12,8 4,9

7,7

-

8,1

142,9

-

45,3 133,5 13,2 29,4 -------221,4 --------

66,3 -------66,3

144,9

0,9 34,7 134,2 13,8 23,1 -------206,7 --------

5,8 -------5,8

-

-4,7 -13,6 3,2

193,1

40,9

234

-

-

56,8

1,3 43 161 15,3 23,9 -------244,5 --------

83,9 -------83,9

-3,5

-5,5 -14,2 4,5

199,5

45,3

244,8

11,1

196,3

56

2,3 38,7 218,5 75,8 43,2 -------378,5 --------

193,1 -------193,1

-

-

-

-

-

9,4

255,2

55,2

10,5 36,7 216,1 71,1 60 -------394,4 --------

300,7 -------300,7

Intangible Resources as Moderators 229

NET INCOME Ordinary dividends

Net credits Extraordinary losses

PROFIT AFTER TAX Minority interests Discont ops inc net

PROFIT BEFORE TAX Tax

TRADING PROFIT Equity A/c profits Interest/inv income Interest payable Net interest expense Other expenses net

GROSS PROFIT Distribution costs Administration exps Provisions Other trading exps Other trading inc net Exceptional chgs-tdg

TURNOVER Cost of sales

Eurom 31 Dec 2004 1.066,70 -779 -------287,7

-119,1 -86,2 1,8 -23,7 -19,1 -------41,4

-0,8 4,9 -38,9 -4,6 -27,1 --------25,1

-0,4 --------25,5

-0,1 --------0,1 -60,8 --------86,4 0

Eurom 31 Dec 2005 1.068,80 -746,7 -------322,1

-126,8 -48,1 0,1 -26,2 2,8 -11,1 -------112,8

0,8 5,5 -43,8 -28,1 -------47,2

-19,1 -------28,1

0,1 -------0,1 -------28,2 0

-0,1 -21,5 --------21,6 --------50,3 0

14,1 --------50,2

3,3 -42,8 -3,3 -35,5 --------64,3

-121,8 -65,9 2,8 -27,2 1,9 -27,4 -------14

Eurom 31 Dec 2003 1.046,20 -794,6 -------251,6

---------------23,6 0

3,6 --------23,6

12,3 -37,8 --------27,2

-139,4 -47,5 -25,4 15,1 -30,3 --------1,7

Eurom 31 Dec 2002 1.112,30 -886,5 -------225,8

CONSOLIDATED PROFIT AND LOSS ACCOUNT

* * * * * * * * * * INCOME STATEMENT * * * * * * * * * *

-0,2 --------0,2 --------95,2 0

-29,2 --------95

5,7 -54,2 --------65,8

-154,5 -57,8 -31,1 10,6 -76 --------17,3

Eurom 31 Dec 2001 1.233,30 -941,8 -------291,5 --------

-------28,2 --------

--------86,4 --------

--------50,3 --------

--------23,6

INTEREST/INV INCOME Investment income Interest income

OTHER TRADING INC NET Misc other tdg inc EXCPL CHARGES-TDG FA disposal gain-tdg Reorg costs-tdg Misc excpl chgs-tdg

OTHER TRADING EXPS Net exchange losses Research & dev Misc other tdg exps

5,5 -------5,5 --------

4,9 -------4,9 --------

0,6 -19,7 --------19,1 --------

2,8

-1,2 -19,2 -3,3 --------23,7 --------

3,1 -1,3 -------1,8 --------

Eurom 31 Dec 2004

9,7 -20,8 --------11,1 --------

-2 -18 -6,2 --------26,2 --------

3 -2,9 -------0,1 --------

Eurom 31 Dec 2005

3,3 -------3,3 --------

2,5 -10,4 -19,5 --------27,4 --------

1,9

-2,8 -19 -5,4 --------27,2 --------

4,2 -1,4 -------2,8 --------

Eurom 31 Dec 2003

-1,8 14,1 -------12,3 --------

-8,3 -22 --------30,3 --------

15,1

-25,4 --------25,4 --------

---------------

Eurom 31 Dec 2002

NOTES TO CONSOLIDATED PROFIT AND LOSS ACCOUNT

PROVISIONS Provns written back Misc provisions

RETAINED PROFITS

A 3.4: Output Screen of Extel Cards for SGL Carbon (continued)

3,2 2,5 -------5,7 --------

-41 -35 --------76 --------

10,6

-31,1 --------31,1 --------

---------------

Eurom 31 Dec 2001

--------

--------95,2

230 Appendix Chapter 3

-------5.257 5.263

-60,8 -------5.399 5.265

-16,7 15,5 1,2 --------0,4 --------

-0,2 -0,7 --------0,9 -0,3 1,2 --------0,4 --------

0,7 0,1 -------0,8 -19,9 --------19,1 --------

-26,3 7,2 --------19,1 --------

-27,1

-28,1

-------7.077 6.926

-14,3 33,1 -4,7 -------14,1 --------

-0,3 27,2 -------26,9 -8,1 -4,7 -------14,1 --------

-35,5

Staff expenses by type Directors emoluments FEES ETC Auditors remuneration Non-audit fees

STAFF EXPENSES BY GRADE Wages & salaries Social security Staff pensions

-

--------

-1,6 -0,3 --------

-209,9 -59,4 -20,2 --------289,5 --------

-

-236 -53,8 -19,7 --------309,5 --------

--------

-

-207,7 -51,5 -20,5 --------279,7 --------

-

-------7.704 7.360

-7,8 11,4 -------3,6 --------

-2,1 11,1 -------9 -5,4 -------3,6 --------

--------

-1,9

-298,1 -51,4 -18,7 --------368,2 --------

PROFIT BEFORE TAX IS AFTER (CHARGING) CREDITING

Av no of staff No of staff at y/e

EXTRAORDINARY LOSSES Xord discont bus cost

TAX BY TYPE Current taxation Deferred taxation Misc tax by type

Domestic tax Overseas tax Misc tax by country

OTHER EXPENSES NET Misc expenses net TAX BY COUNTRY Domestic current tax Domestic deferred tax

--------

-

-326 -59,9 -17,3 --------403,2 --------

-------8.491 8.197

-22,4 -6,8 --------29,2 --------

-5,6 -1,6 --------7,2 -22 --------29,2 --------

-

-60,7 -4,4 -7,6 -

-62,3 -4,6 -7,6 -

-64,5 -3,9 -3,8 -

-71,3 -5,1 -4,8 -9,8 -0,2 0,6

-78,9 -4,4 -3,5 -9,7 -5,6 -2,2

Your use of this service is governed by Terms and Conditions. Please review them. Copyright ©2006 LexisNexis Group a division of Reed Elsevier (UK) Ltd. All rights reserved.

LOAD-DATE: May 22, 2006

DATE 09-Mar-2006 25. Apr 06 28. Apr 06 26. Jul 06 26-Oct-2006

CALENDAR: EVENT Prelim First Quarter Annual General Meeting Second Quarter Third Quarter

--------

Eurom 31 Dec 2001 --------

----------------------------a) Restated to confirm with current presentation or current accounting policies

TRADING PROFIT

-29,1 --------13,5

Eurom 31 Dec 2002 --------

--------

-42,6 --------17,6

--------

Eurom 31 Dec 2003 130,4 -113,8 -------16,6

--------

GROSS PROFIT Distribution costs

TURNOVER Cost of sales

Eurom 31 Dec 2004 122,7 -97,7 -------25

Eurom 31 Dec 2005 --------

CONSOLIDATED PROFIT AND LOSS ACCOUNT - DISCONTINUED - EXISTING

Depreciation Goodwill amortisation Brands amortisation Licences amortisation Duties & taxes Net exchange losses FA disposal gain-tdg

A 3.4: Output Screen of Extel Cards for SGL Carbon (continued)

Intangible Resources as Moderators 231

B/S CASH& EQVT INCR

Currency appreciation

CASH& EQVTS INCREASE

OTHER INFLOWS

FINANCING Debt raised Share capital issued Debt repaid Dividends paid ord Misc financing inflow

INVESTING ACTIVITIES Invests acquired Property acquired Equip & vehs acquired Tangibles acquired Intangibles acquired Trade invs sold Investments sold FA sold Misc investing inflow

OPERATIONS

38,6 244,1 -89,3 0 -23,9 ------169,5 -------24,6

------149,7

-------0,3 ------149,4

-------

-------104,1

------2 -------102,1

-------

-0,8 -46,3 2 4,5 -------40,6 -------

Eurom 31 Dec 2004 45,4 -------

2,5 -92,7 0 -0,8 -------91 -------

-2,3 -6,2 -33,2 -5,3 0,3 16,1 -------30,6 -------

Eurom 31 Dec 2005 17,5 -------

-------

-------0,3 ------24,6

------24,9

60,5 1 0 -15,9 ------45,6 ------0,7

-1,7 -43,4 5,7 1,5 -------37,9 -------

Eurom 31 Dec 2003 16,5 -------

CONSOLIDATED STATEMENT OF CASH FLOWS

* * * * * * * * * * CASHFLOW STATEMENT * * * * * * * * * *

-------

-------1,7 ------9,4

------11,1

0,8 -87,6 -0,2 -------87 -------

-41,5 -12,1 7,8 4,9 -------40,9 -------

Eurom 31 Dec 2002 139 -------

-------

-------6,2 ------2,3

------8,5

36,5 2,2 -0,1 ------38,6 -------

-96,1 5,5 3,8 -5,7 -------92,5 -------

Eurom 31 Dec 2001 62,4 -------

Carbon & graphite Special graphite Technical products Other Corrosion protection Intra-group TURNOVER

BUSINESS ANALYSIS:

-2,9 -14,2 67,6 16,3 -48,2 -0,6 -4 0,9 3,5 27 ------45,4 -------

Eurom 31 Dec 2004 -47,5 -4,2 69,5 24,2 1 -3,4 0,3 -31,2 -4,1 11,9 ------16,5 -------

Eurom 31 Dec 2003

BUSINESS ANALYSIS - TURNOVER Eurom Eurom Eurom 31 Dec 31 Dec 31 Dec 2005 2004 2003 657.0 572.2 921.0 267.2 253.2 280.7 166.2 136.0 128.8 41.9 33.8 50.5 (63.5) (51.2) (465.2) 1,068.8 944.0 915.8 -------------------1.068,80 944 915,8 --------------------

47,2 -22,6 65,1 13 -64,9 -9,7 -10,1 -8,2 -4,8 12,5 ------17,5 -------

Eurom 31 Dec 2005

Eurom 31 Dec 2002 947.2 240.4 154.8 47.3 228.7 (506.1) 1,112.3 -------1.112,30 --------

-27,2 81,4 -2,8 -32,4 -3,8 82,7 44,7 6,8 -10,4 ------139 -------

Eurom 31 Dec 2002

NOTES TO CONSOLIDATED STATEMENT OF CASH FLOWS

OPERATIONS Profit before tax Taxation Net income Depn & amortn incr Provision increases Other tdg adj incr Asset disposal Decrease in stocks Decrease in debtors Increase in creditors Other wkg cap decr

A 3.4: Output Screen of Extel Cards for SGL Carbon (continued)

Eurom 31 Dec 2001 984.4 297.6 377.6 42.2 (468.5) 1,233.3 -------1.233,30 --------

-65,8 86,8 19,8 -3,8 1 -21,5 65,8 17 -36,9 ------62,4 -------

Eurom 31 Dec 2001

232 Appendix Chapter 3

-------64,3 -------

BUSINESS ANALYSIS - TOTAL ASSETS

-------25,1 -------

-------47,2 --------

Eurom 31 Dec 2003 65,5 12,4 -13,6 -36,8 0 -91,8 -64,3 --------27,2 --------

Eurom 31 Dec 2002 51,9 1,9 -11,7 -18,3 4,8 -30,3 -25,5 -27,2

Eurom Eurom Eurom Eurom 31 Dec 31 Dec 31 Dec 31 Dec 2005 2004 2003 2002 Carbon & graphite 513,8 520,1 531,3 Special graphite 227 204,9 224,8 Technical products 220,3 201,1 203,2 Total 961,1 926,1 959,3 a) Restated to confirm with current presentation or current accounting policies

Carbon & graphite Special graphite Technical products Other Corrosion protection Intra-Group Discontinued ops Exceptional charges Assoc cos profit Net interest expense Misc PROFIT BEFORE TAX

Eurom 31 Dec 2004 86,4 13,9 -10,6 -30,7 -22,2 -0,8 -50,6 -10,5 -25,1

Eurom 31 Dec 2005 121,6 19,8 0,2 -28,8 0,8 -52,2 -14,2 47,2

BUSINESS ANALYSIS - PROFIT BEFORE TAX

Eurom 31 Dec 2001 -

--------65,8 --------

Eurom 31 Dec 2001 78,9 26 -24,8 -21,4 -76 -48,5 -65,8

Total

Rest of Europe Germany Rest of Europe North America Asia

Western Europe Germany Rest of Europe North America South America Asia

Eurom 31 Dec 2004 390,1 313,9 229,1 10,9 ------944 -------

Eurom 31 Dec 2003 632,4 469,6 279 -465,2 ------915,8 -------

Eurom 31 Dec 2002 692,4 588,9 324,6 5,1 7,4 -506,1 -------1.112,30 -------Eurom 31 Dec 2004 320,2 140 250 233,8 ------944 -------

Eurom 31 Dec 2003 306,9 137,6 250,7 49,4 171,2 ------915,8 ------Eurom 31 Dec 2005 330,6 328,6 275,8 26,1 -------961,1 --------

Eurom 31 Dec 2004 365,2 296,3 237,3 27,3 ------926,1 -------

Eurom 31 Dec 2003 -------------

GEOGRAPHICAL ANALYSIS - TOTAL ASSETS

Eurom 31 Dec 2005 142,7 380,4 283,8 261,9 -------1.068,80 --------

Eurom 31 Dec 2002 ---------------

Eurom 31 Dec 2002 216,6 373,8 281,6 63,4 176,9 -------1.112,30 --------

GEOGRAPHICAL ANALYSIS - TURNOVER BY MARKET

Eurom 31 Dec 2005 358,1 440,7 264,6 5,4 -------1.068,80 --------

GEOGRAPHICAL ANALYSIS - TURNOVER BY SOURCE

Rest of Europe Germany Rest of Europe North America South America Asia Intra-group Adjustment accounts

A 3.4: Output Screen of Extel Cards for SGL Carbon (continued)

Eurom 31 Dec 2001 ---------------

Eurom 31 Dec 2001 246 409,2 315,8 63,1 199,2 -------1.233,30 --------

Eurom 31 Dec 2001 676,8 636,1 372,2 8 8,7 -468,5 -------1.233,30 --------

Intangible Resources as Moderators 233

234

Appendix Chapter 3

A 3.5: Coding Procedure of TMT Demographics The following section exemplifies the procedure to obtain top management team demographic information from internet resources (specifically company web sites) for SGL Carbon. In the first step the names of the members of the top management team are obtained from Extel Cards.

* * * * * * * * * * EXECUTIVES * * * * * * * * * *

Chairman Vice Chairman Member Member Member Member Member Member Member Member Member Member

SUPERVISORY BOARD Name Max D. Kley Josef Scherer Prof. Dr. Utz-Hellmuth Felcht Peter Fischer Dr. Claus Hendricks Juergen Kerner Dr. Hubert Lienhard Jacques Loppion Edelbert Schilling Andrew H. Simon Heinz Will Hans-Werner Zorn

Position Chairman & Chief Executive Chief Financial Officer Member Member

MANAGEMENT BOARD Name Robert J. Koehler Sten Daugaard Theodore H. Breyer Dr. Hariolf Kottmann

Position

Appointed/Ceased 27 Apr 2005 Appointed

28 Apr 2005 Appointed

Appointed/Ceased

Source: Extel Cards

In the second step these names are cross-checked with information obtained from the company web site and annual reports. In the third step the same company web resources are searched for information on the national and educational background of members of the top management team. Based on this information the two variables ‘top management team international diversity’ (TMT_INT) and ‘top management team education’ (TMT_ACD) are calculated in a final step. For SGL Carbon the result would be as follows:

TMT_INT: Two out of four members are internal. TMT_ACD: One out of four members holding an academic title.

Intangible Resources as Moderators

235

The following screenshots are taken from the company web site of SGL Carbon and depict the members of the management board. (http://www.sglcarbon.de/company/executive.html, date: 30.07.2007)

.101 .382

-.129 .153

1.50 1.07

-.466

.145 4.66

1.92

-.228

161

- Other

.062 -.053

.802

.924

.275

217

- Technology Sector

Notes: N: Number of firm-year observations.

.208 -.113

.263

.782 -.738

4.03

2.24 -.060

-.034

548

- Classic Sector

Classification by German Stock Exchange

.118

-.124

.007

.685 -.154

3.14

R2

1.21

TMT_ACD

.672

TMT_INT

.247

CONT

.082

ADV

169

RD

435

Intercept

- Service

N

- Manufacturing

Classification by 1-digit SIC-Code

Industry

A 3.6: Coefficients from Hedonic Regression – Alternative Industry Classifications (N = 765)

236 Appendix Chapter 3

Intangible Resources as Moderators

237

A 3.7: Results for Foreign Assets to Total Assets Table A 3.7.1 Regression of Curve Type and Moderation of Tobin’s qa Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service 7. Tobin’s q

1

2

3

4

5

.013 (.64) .012** (5.87) -.002 (-1.32) -.185** (-9.24) .012† (1.69) -.036** (-3.47) .041** (12.18)

.013 (.64) .012** (5.50) -.002 (-1.32) -.184** (-9.16) .012† (1.66) -.036** (-3.47) .041** (12.15) .003 (.22)

.005 (.23) .012** (5.36) -.003 (-1.46) -.181** (-8.94) .012† (1.66) -.036** (-3.45) .041** (12.12) .070 (1.31) -.080 (-1.29)

-.009 (-.34) .012** (5.41) -.002 (-1.29) -.181** (-8.92) .014† (1.82) -.034** (-3.26) .041** (12.17) .188 (1.59) -.415 (-1.36) .258 (1.12)

-.009 (-.36) .012** (5.43) -.002 (-1.27) -.180** (-8.90) .014† (1.82) -.034** (-3.23) .042** (12.18) .182 (1.53) -.400 (-1.30) .246 (1.06) -.011 (-.63)

.398 .391

.398 .390 .000 51.32**

.400 .391 .002 45.17**

.401 .391 .003 40.31**

.402 .391 .004 36.28**

8. FATA 9. FATA (squared) 10. FATA (cubic) 11. FATA * Tobin’s q R2 Adjusted R2 ' R2 F-statistic †

59.97**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

238

Appendix Chapter 3

A 3.7: Results for Foreign Assets to Total Assets (continued) Table A 3.7.2 Moderation of Hedonic qa Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service 7. Hedonic q

1

2

3

4

5

.027 (.95) .013** (5.75) -.002 (-.99) -.242** (-11.53) .013 (1.55) -.035** (-3.03) .056** (4.26)

.027 (.96) .013** (5.39) -.002 (-.98) -.242** (-11.46) .012 (1.54) -.035** (-3.03) .056** (4.19) .002 (.14)

.019 (.66) .012** (5.25) -.002 (-1.10) -.239** (-11.18) .012 (1.53) -.035** (-3.00) .056** (4.16) .067 (1.14) -.077 (-1.15)

.007 (.23) .013** (5.28) -.002 (-.99) -.238** (-11.12) .013 (1.63) -.034** (-2.88) .057** (4.21) .160 (1.26) -.344 (-1.04) .206 (.82)

.002 (.07) .012** (5.22) -.002 (-.95) -.237** (-11.09) .013 (1.55) -.035** (-2.94) .063** (4.25) .152 (1.19) -.323 (-.98) .190 (.76) -.059 (-.98)

.267 .259

.267 .258 .000 29.00**

.269 .258 .002 25.53**

.270 .258 .003 22.76**

.271 .258 .004 20.58**

8. FATA 9. FATA (squared) 10. FATA (cubic) 11. FATA * Hedonic q R2 Adjusted R2 ' R2 F-statistic †

33.86**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Intangible Resources as Moderators

239

A 3.7: Results for Foreign Assets to Total Assets (continued) Table A 3.7.3 Moderation of Individual Intangible Resourcesa Variable

1

1. Intercept 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12.

.092** (4.01) Size_ln .015** (6.28) Product Div. -.002 (-1.18) Leverage -.252** (-11.34) I1: Manufacturing .015† (1.89) -.022† I2: Service (-1.90) -.045 RD (-.50) .398** ADV (3.86) -.197** CONT (-3.61) .001 TMT_INT (.03) -.033** TMT_ACD (-2.69) FATA

13. FATA (squared) 14. FATA (cubic) 15. FATA * RD 16. FATA * ADV 17. FATA * CONT 18. FATA * TMT_INT 19. FATA * TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

2

3

4

5

6

7

8

.085** .092** .087** .089** .097** .088** .112** (3.12) (3.22) (3.38) (3.19) (3.26) (3.59) (4.15) .014** .013** .014** .014** .012** .014** .010** (5.71) (5.58) (5.19) (3.94) (5.62) (5.65) (4.77) -.002 -.002 -.002 -.002 -.002 -.003 -.003 (-1.23) (-1.18) (-1.30) (-1.40) (-1.31) (-1.16) (-1.40) -.248** -.247** -.245** -.247** -.241** -.250** -.237** (-11.00) (-11.03) (-10.83) (-10.98) (-10.81) (-11.07) (-10.66) .015† .016† .014† .016† .010 .011 .015† (1.93) (1.82) (1.73) (1.84) (1.93) (1.25) (1.33) -.021† -.022† -.023* -.020† -.020† -.025* -.024* (-1.88) (-1.82) (-1.98) (-1.75) (-2.20) (-1.72) (-2.07) -.039 -.051 -.116 -.084 -.066 -.040 -.128 (-.43) (-.56) (-1.24) (-.91) (-.72) (-.44) (-1.38) .393** .380** .449** .388** .403** .391** .459** (3.99) (3.81) (3.71) (3.77) (3.80) (3.96) (4.18) -.192** -.211** -.198** -.172** -.176** -.190** -.185** (-3.50) (-3.84) (-3.60) (-3.08) (-3.24) (-3.46) (-3.33) -.001 -.001 .007 .001 .012 .003 .024 (-.04) (-.05) (.30) (.04) (.50) (.12) (1.01) † -.032** -.028* -.032** -.030* -.031* -.023 -.016 (-2.64) (-2.32) (-2.67) (-2.42) (-1.88) (-2.54) (-1.31) .055 .031 .067 .096 .045 .063 .018 (.44) (.24) (.52) (.75) (.35) (.50) (.14) -.019 .024 -.084 -.155 -.019 -.093 .092 (-.06) (.07) (-.26) (-.47) (-.06) (-.28) (.27) -.036 -.063 .023 .077 -.031 .042 -.116 (.09) (-.15) (-.24) (.31) (-.13) (.17) (-.46) 1.17** 1.18** (2.89) (2.86) -.621 -.810 (-1.25) (-1.64) .441* .320 (2.05) (1.44) .237** .248** (4.08) (4.30) -.124 -.111 (-1.28) (-1.16)

.288 .275

.289 .300 .291 .294 .310 .291 .330 .272 .282 .273 .276 .292 .273 .308 .001 .012 .003 .006 .022 .003 .042 22.36** 17.22** 16.80** 16.12** 16.38** 17.64** 16.13** 14.94**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

240

Appendix Chapter 3

A 3.8: Results for Time-Lagged Measurement Designs Table A 3.8.1 Moderation of Individual Intangible Resourcesa – ROA = t+1 Variable

1

2

3

4

5

6

7

8

.025 .018 .019 .042 .043 .079** .021 .021 (.74) (.54) (.56) (1.28) (1.30) (3.20) (.63) (.63) Size_ln .008** .008** .007* .004 .004 .008** .008** .008** (2.90) (3.06) (2.60) (1.44) (1.37) (2.89) (2.88) (2.89) .002 Product Div. .001 .002 .002 .002 .002 .002 .002 (.90) (.62) (.78) (.82) (.89) (1.00) (.78) (.78) Leverage -.165** -.169** -.164** -.169** -.171** -.153** -.169** -.152** (-6.99) (-7.13) (-6.90) (-7.13) (-7.21) (-6.56) (-7.12) (-6.49) .008 I1: Manufacturing .008 .009 .007 .007 .006 .008 .008 (.88) (1.01) (.86) (.73) (.79) (.69) (.90) (.90) -.013 I2: Service -.012 -.015 -.019 -.013 -.020 -.015 -.015 (-.98) (-1.17) (-1.04) (1.53) (-1.19) (-1.03) (-1.61) (-1.23) .087 RD .002 .102 .075 -.002 .110 .099 .100 (.84) (.02) (.98) (.74) (-.02) (.96) (1.08) (.96) † † † † .207 ADV .208 .273* .168 .197† .224* .209 .210 1.96) (1.95) (1.94) (1.93) (1.76) (2.41) (1.60) (2.10) -.088† -.084 -.051 -.088† -.034 CONT -.084 -.079 -.114* (-.87) (-.60) (-1.52) (-1.65) (-2.16) (-.166) (-1.57) (-1.58) .017 .018 .021 .018 .042 TMT_INT .020 .034 .013 (.69) (.68) (.85) (.72) (1.60) (.79) (1.40) (.55) † † † -.023 -.023 -.022 -.022 -.017 TMT_ACD -.025 -.017 -.031* (-2.34) (-1.68) (-1.59) (-1.83) (-1.63) (-1.25) (-1.68) (-1.23) .529** .548** .532** .493** .542** .529** .519** FSTS (2.97) (2.99) (2.96) (3.07) (2.74) (2.95) (3.11) -1.27** -1.28** -1.29** -1.20** -1.33** -1.27** -1.28** FSTS (squared) (-3.11) (-3.13) (-3.16) (-2.94) (-3.32) (-3.11) (-3.19) .870** .861** .888** .837** .923** .872** .899** FSTS (cubic) (3.12) (3.18) (3.11) (3.09) (2.99) (3.27) (3.38) .905† .604 FSTS * RD (1.70) (1.15) † .745 .436 FSTS * ADV (1.69) (1.00) .311 .317 FSTS * CONT (1.55) (1.60) .284** FSTS * TMT_INT .290** (5.23) (5.39) -.040 -.010 FSTS * TMT_ACD (-.37) (-.09)

1. Intercept 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.

R2 Adjusted R2 ' R2 F-statistic †

.127 .113 8.96**

.141 .123 .014 7.72**

.145 .125 .018 7.40**

.145 .125 .018 7.39**

.144 .125 .017 7.36**

.180 .161 .053 9.57**

.141 .121 .014 7.16**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

.188 .163 .051 7.79**

Intangible Resources as Moderators

241

A 3.8: Results for Time-Lagged Measurement Designs (continued) Table A 3.8.2 Moderation of Individual Intangible Resourcesa – ROA = t+2 Variable

1

2

3

4

5

6

7

8

1. Intercept 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18. 19.

.075* .075* .073* .077* .092** .092** .076* .095** (2.13) (2.13) (2.08) (2.18) (3.64) (2.65) (2.17) (2.72) Size_ln .001 .001 .001 .001 .001 -.002 .001 -.002 (.42) (.48) (.21) (.48) (.45) (-.54) (.43) (-.84) Product Div. .002 .002 .002 .002 .003 .002 .002 .003 (1.09) (1.04) (1.06) (1.11) (1.22) (1.02) (1.12) (1.27) Leverage -.116** -.117** -.113** -.117** -.118** -.105** -.116** -.104** (-4.76) (-4.75) (-4.59) (-4.76) (-4.81) (-4.31) (-4.74) (-4.26) I1: Manufacturing .003 .003 .005 .003 .002 .002 .004 .004 (.33) (.36) (.47) (.34) (.23) (.19) (.43) (.46) I2: Service -.009 -.009 -.006 -.007 -.011 -.012 -.007 -.005 (-.72) (-.73) (-.47) (-.57) (-.85) (-.96) (-.52) (-.40) † RD .166 .166 .061 .152 .177 .136 .163 .043 (1.68) (1.53) (1.52) (.50) (1.40) (1.27) (1.50) (.35) .504** .511** .501** .490** .510** .488** .499** .435** ADV (4.36) (4.38) (4.04) (4.30) (4.37) (4.24) (4.25) (3.62) -.092† CONT -.084 -.086 -.080 -.053 -.079 -.080 -.040 (-1.78) (-1.60) (-1.52) (-1.64) (-.89) (-1.53) (-1.52) (-.68) .056* TMT_INT .057* .056* .060* .057* .068** .067* .081** (2.23) (2.22) (2.17) (2.34) (2.23) (2.69) (2.46) (2.98) -.021 TMT_ACD -.018 -.018 -.017 -.017 -.014 -.018 -.011 (-1.54) (-1.27) (-1.18) (-1.23) (-1.21) (-.97) (-1.29) (-.78) FSTS .172 .175 .195 .153 .177 .170 .172 (.92) (.93) (1.04) (.81) (.96) (.91) (.93) -.447 FSTS (squared) -.446 -.458 -.416 -.486 -.465 -.476 (-1.04) (-1.07) (-1.04) (-.97) (-1.15) (-1.08) (-1.12) .327 FSTS (cubic) .324 .320 .315 .371 .350 .372 (1.11) (1.10) (1.09) (1.07) (1.28) (1.19) (1.28) † FSTS * RD .928 .665 (1.74) (1.25) FSTS * ADV -.309 -.441 (-.66) (-.95) FSTS * CONT .225 .256 (1.13) (1.30) FSTS * TMT_INT .217** .219** (3.89) (3.88) FSTS * TMT_ACD -.128 -.138 (-1.09) (-1.19)

R2 Adjusted R2 ' R2 F-statistic †

.132 .114 7.14**

.135 .111 .003 5.58**

.140 .114 .008 5.42**

.135 .109 .003 5.20**

.137 .111 .005 5.27**

.162 .137 .030 6.42**

.137 .111 .005 5.27**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

.172 .140 .040 5.34**

242

Appendix Chapter 4

Appendix Chapter 4

A 4.1 Regional Dispersion of Sales

244

A 4.2 Additional Results for Hypothesis One

247

Table A 4.2.1 Regressions of Intangible Resources on Degree of Internationalization (Foreign Sales to Total Sales) - TQ

247

Table A 4.2.2 Regressions of Intangible Resources on Propensity to Internationalize (Three Year Change of Degree of Internationalization) 248 Table A 4.2.3 Regressions of Intangible Resources on Propensity to Internationalize (Five Year Change of Degree of Internationalization) 249

A 4.3 Additional Results for Hypothesis Two Table A 4.3.1 Regression of Intangible Resources on Scope of Internationalization (Dispersion of International Sales) - TQ

250 250

Intangible Resources and the Internationalization Process

A 4.4 Additional Results for Hypothesis Three

243

251

Table A 4.4.1 Regression of Intangible Resources on Scope of Expansion (Three Year Change of Dispersion of Foreign Sales)

251

Table A 4.4.2 Regression of Intangible Resources on Scope of Expansion (Five Year Change of Dispersion of Foreign Sales)

252

Table A 4.4.3 Regression of Intangible Resources on Scope of Expansion (Two Year Change of Dispersion of Total Sales)

253

Table A 4.4.4 Regression of Intangible Resources on Scope of Expansion Three Year Change of Dispersion of Total Sales)

254

Table A 4.4.5 Regression of Intangible Resources on Scope of Expansion (Five Year Change of Dispersion of Total Sales)

255

A 4.5 Additional Results for Hypothesis Four

256

Table A 4.5.1 Speed of Expansion – Descriptive Statistics and Correlations

256

Table A 4.5.2 Moderation of Speed of Expansion (Change of Internationalization over Past Three Years)

257

Table A 4.5.3 Moderation of Speed of Expansion (Change of Internationalization over Past Five Years)

258

A 4.6 Additional Results for Hypothesis Five

259

Table A 4.6.1 Moderation of Scope of Expansion on Change of ROA (Three Year Change of Dispersion of Foreign Sales)

259

Table A 4.6.2 Moderation of Scope of Expansion on Change of ROA (Five Year Change of Dispersion of Foreign Sales)

260

Table A 4.6.3 Moderation of Scope of Expansion on Change of ROA (Two Year Change of Dispersion of Foreign Sales) - TQ

261

Table A 4.6.4 Moderation of Scope of Expansion on Change of ROA (Three Year Change of Dispersion of Foreign Sales) - TQ

262

Table A 4.6.5 Moderation of Scope of Expansion on Change of ROA (Five Year Change of Dispersion of Foreign Sales) - TQ

263

ALTANA AG O.N. CARL-ZEISS MEDITEC AG CARL-ZEISS MEDITEC AG ESCADA AG O.N. ESCADA AG O.N. HEIDELBERG.DRUCKMA.O.N. HOCHTIEF AG HOCHTIEF AG INFINEON TECH.AG NA O.N. INFINEON TECH.AG NA O.N. INFINEON TECH.AG NA O.N. INFINEON TECH.AG NA O.N. MERCK KGAA O.N. MERCK KGAA O.N. MERCK KGAA O.N. SGL CARBON AG O.N. SGL CARBON AG O.N. SGL CARBON AG O.N. SINGULUS TECHNOL. SINGULUS TECHNOL. SINGULUS TECHNOL. SINGULUS TECHNOL. SINGULUS TECHNOL.

Company Name

‘Global’ MNCs

Pharma & Healthcare Pharma & Healthcare Pharma & Healthcare Consumer Consumer Industrial Construction Construction Technology Technology Technology Technology Pharma & Healthcare Pharma & Healthcare Pharma & Healthcare Chemicals Chemicals Chemicals Industrial Industrial Industrial Industrial Industrial

Industry

A 4.1: Regional Dispersion of Sales

2006 2004 2006 2004 2005 2002 2004 2005 2003 2004 2005 2006 2004 2005 2006 2004 2005 2006 2002 2003 2004 2005 2006

Year 82.8 92.5 95.0 86.7 87.2 62.6 81.4 83.4 75.0 76.7 80.0 83.3 90.5 90.3 91.0 85.2 86.6 84.9 94.1 94.7 89.9 86.7 88.3

Foreign sales to total sales

America percentage of total sales 20.7 46.7 43.7 32.7 32.5 33.2 47.3 43.9 22.6 21.2 22.3 26.8 26.0 22.6 22.9 26.5 26.6 24.7 33.5 21.3 24.3 20.1 28.0

Intra-regional percentage of total sales 48.5 25.4 30.7 46.3 45.6 43.0 23.2 21.7 43.0 40.8 37.9 33.9 45.5 47.0 46.2 48.8 48.9 49.0 37.1 36.7 40.2 49.8 41.9

23.0 27.9 25.7 21.0 22.0 20.7 29.3 34.2 33.8 36.5 37.8 37.3 20.9 23.3 24.5 24.8 24.5 26.3 29.4 40.2 33.7 25.9 27.5

Asia-Pacific percentage of total sales

244 Appendix Chapter 4

Industrial Consumer Consumer Consumer Consumer Pharma & Healthcare Industrial Pharma & Healthcare Pharma & Healthcare Pharma & Healthcare Pharma & Healthcare Pharma & Healthcare Pharma & Healthcare Chemicals

Chemicals

Construction

WACKER CHEMIE O.N.

HOCHTIEF AG

Industry

DUERR AG O.N. ESCADA AG O.N. ESCADA AG O.N. ESCADA AG O.N. ESCADA AG O.N. EVOTEC AG O.N. HEIDELBERG.DRUCKMA.O.N. MERCK KGAA O.N. MERCK KGAA O.N. MERCK KGAA O.N. SCHERING AG O.N. SCHERING AG O.N. SCHERING AG O.N. SGL CARBON AG O.N.

Company Name

‘Bi-regional’ MNCs

A 4.1: Regional Dispersion of Sales (continued)

2006

2006

2004 2001 2002 2003 2006 2003 2001 2001 2002 2003 2001 2002 2003 2003

Year

86.3

80.3

74.7 87.1 87.9 86.2 88.0 94.0 64.6 90.4 90.9 90.3 75.2 75.1 75.0 85.0

Foreign sales to total sales

37.3

43.3 19.3

28.8 19.8

48.5

13.8 17.0 19.2 19.0 17.7 0.0 18.5 11.7 13.9 14.7 18.1 16.0 14.8 18.7

38.2 35.2 36.0 32.7 27.1 46.0 36.2 47.7 41.5 37.8 33.5 34.1 32.9 32.8

48.0 42.6 44.8 48.3 43.5 49.0 42.7 36.3 39.8 41.9 45.1 46.9 49.4 48.5

Asia-Pacific percentage of total sales

America percentage of total sales

Intra-regional percentage of total sales

Intangible Resources and the Internationalization Process 245

Pharma & Healthcare Pharma & Healthcare Automobile Automobile Automobile Automobile Automobile Automobile Construction Construction Construction Technology Industrial Industrial Industrial Industrial Industrial Pharma & Healthcare Pharma & Healthcare

Software Industrial Industrial

CAATOOSEE AG STEAG HAMATECH AG O.N. STEAG HAMATECH AG O.N.

Industry

CARL-ZEISS MEDITEC AG CARL-ZEISS MEDITEC AG DAIMLERCHRYSLER AG NA O.N DAIMLERCHRYSLER AG NA O.N DAIMLERCHRYSLER AG NA O.N DAIMLERCHRYSLER AG NA O.N DAIMLERCHRYSLER AG NA O.N DAIMLERCHRYSLER AG NA O.N HOCHTIEF AG HOCHTIEF AG HOCHTIEF AG KONTRON AG O.N. MTU AERO ENGINES NA O.N. MTU AERO ENGINES NA O.N. MTU AERO ENGINES NA O.N. MTU AERO ENGINES NA O.N. MTU AERO ENGINES NA O.N. SCHWARZ PHARMA AG O.N. UMS O.N.

Company Name

‘Host region oriented’ MNCs

A 4.1: Regional Dispersion of Sales (continued)

2003 2000 2005

2002 2003 2001 2002 2003 2004 2005 2006 2001 2002 2003 2001 2002 2003 2004 2005 2006 2003 2002

Year

76.1 96.8 90.8

91.2 93.0 84.9 84.6 82.5 84.3 86.0 85.4 83.3 85.0 81.8 65.0 81.5 77.1 73.9 77.6 81.2 81.1 73.2

Foreign sales to total sales

40.0 13.3 27.2

26.1 24.0 29.9 31.1 35.0 34.4 31.6 33.1 20.3 19.3 23.1 38.7 29.5 35.7 38.3 33.8 29.9 33.8 46.1

Intra-regional percentage of total sales

60.0 65.6 64.1

15.4 23.7 4.1 4.2 4.9 7.1 8.4 8.2 22.6 26.0 25.6 10.4 6.7 7.8 7.7 10.9 11.8 1.8 0.0

58.5 52.4 62.0 60.0 54.3 53.2 54.0 52.2 57.1 54.7 51.3 50.9 62.0 53.6 53.1 54.8 57.3 64.4 53.9 0.0 19.9 4.4

Asia-Pacific percentage of total sales

America percentage of total sales

246 Appendix Chapter 4

Intangible Resources and the Internationalization Process

247

A 4.2: Additional Results for Hypothesis One Table A 4.2.1 Regressions of Intangible Resources on Degree of Internationalizationa (Foreign Sales to Total Sales) - TQ Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

.371** (7.03) .025** (4.01) .001 (.15) -.176** (-3.22) .152** (6.98) -.069* (-2.21)

.358** (6.37) .025** (3.96) .001 (.12) -.165** (-2.89) .152** (6.96) -.072* (-2.28) .007 (.67)

.390** (5.47) .024** (3.84) -.002 (-.30) -.178** (-3.06) .142** (6.41) -.097** (-2.93)

7. Tobin’s q 8. Hedonic q R2 Adjusted R2 ' R2 F-Statistic †

.010 (.31) .200 .193 27.10**

.201 .192 .001 22.64**

.207 .198 .007 21.96**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

248

Appendix Chapter 4

A 4.2: Additional Results for Hypothesis One (continued) Table A 4.2.2 Regressions of Intangible Resources on Propensity to Internationalizea (Three Year Change of Degree of Internationalization) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

-.195 (-.98) .014 (.59) -.017 (-.92) .421* (2.06) -.101 (-1.29) .278* (2.36)

-.201 (-.95) .014 (.59) -.017 (-.92) .426* (2.00) -.101 (-1.28) .278* (2.35) .072 (.08)

-.314 (-1.56) .017 (.75) -.032† (-1.67) .550** (2.66) -.099 (-1.28) .252* (2.16)

-.163 (-.83) .015 (.64) -.017 (-.90) .402* (1.98) -.100 (-1.29) .312** (2.64)

-.173 (-.87) .002 (.06) -.017 (-.90) .445* (2.18) -.099 (-1.27) .280* (2.38)

-.189 (-.94) .013 (.53) -.017 (-.91) .417* (2.03) -.099 (-1.26) .279* (2.36)

.040 (.18)

-.275 (-1.23) .004 (.16) -.033† (-1.73) .577** (2.65) -.096 (-1.24) .288* (2.47) .153 (.16) 2.99** (3.18) -.919* (-2.30) .211* (1.74) .082 (.36)

.075 .053 .000 3.37**

.136 .101 .061 3.88**

7. R&D 8. ADV

2.58** (2.78)

9. CONT

-.896* (-2.27) .206† (1.73)

10. TMT_INT 11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

.075 .056 4.05**

.075 .052 .000 3.36**

.102 .081 .027 4.75**

.093 .072 .018 4.29**

.084 .062 .009 3.84**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Intangible Resources and the Internationalization Process

249

A 4.2: Additional Results for Hypothesis One (continued) Table A 4.2.3 Regressions of Intangible Resources on Propensity to Internationalizea (Five Year Change of Degree of Internationalization) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

-.397 (-.43) -.082 (-.72) -.073 (-.90) 2.88* (2.59) -.233 (-.67) .988† (1.71)

-.545 (-.55) -.081 (-.70) -.074 (-.90) 3.03* (2.59) -.259 (-.73) .985† (1.70) 1.83 (.41)

-1.20 (-1.49) -.013 (-.13) -.176* (-2.40) 3.14** (3.26) -.269 (-.90) .683 (1.37)

-.383 (-.41) -.083 (-.71) -.074 (-.89) 2.88* (2.57) -.236 (-.67) .980† (.67)

-.348 (-.38) -.132 (-1.12) -.068 (-.84) 2.97* (2.70) -.249 (-.73) 1.010† (1.77)

-.184 (-.20) -.114 (-.97) -.064 (-.79) 2.72* (2.44) -.207 (-.60) 1.011† (1.76)

1.23 (1.23)

-.913 (-1.01) -.109 (-1.01) -.161* (-2.21) 3.09** (3.13) -.277 (-.92) .713 (1.43) .694 (.17) 17.06** (5.12) -.470 (-.28) 1.06† (1.97) 1.49† (1.69)

.204 .136 .017 2.99*

.462 .380 .275 5.66**

7. R&D 8. ADV

16.98** (5.05) -.164 (-.08)

9. CONT

.911† (1.75)

10. TMT_INT 11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

.187 .129 3.26*

.189 .119 .002 2.71*

.404 .353 .207 7.90**

.187 .117 .000 2.68*

.217 .150 .030 3.23**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

250

Appendix Chapter 4

A 4.3: Additional Results for Hypothesis Two Table A 4.3.1 Regression of Intangible Resources on Scope of Internationalizationa (Dispersion of International Sales) - TQ Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

.431** (12.66) .028** (6.97) -.001 (-.35) -.147** (-4.16) .167** (11.86) -.008 (-.37)

.398** (11.06) .027** (6.87) -.002 (-.46) -.120** (-3.27) .167** (11.88) -.014 (-.70) .017* (2.60)

.452** (9.62) .026** (6.16) -.003 (-.69) -.131** (-3.40) .158** (10.82) -.040† (-1.81)

7. Tobin’s q 8. Hedonic q R2 Adjusted R2 ' R2 F-Statistic †

.005 (.24) .344 .338 56.64**

.352 .344 .008 48.82**

.345 .337 .001 44.30**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Intangible Resources and the Internationalization Process

251

A 4.4: Additional Results for Hypothesis Three Table A 4.4.1 Regression of Intangible Resources on Scope of Expansiona (Three Year Change of Dispersion of Foreign Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

.191 (1.00) .045* (1.98) -.025 (-1.38) -.209 (-.98) .236** (.3.10) .160 (1.36)

.053 (.26) .047* (2.07) -.027 (-1.46) -.093 (-.43) .195* (2.49) .161 (1.38) 1.86† (1.89)

.260 (1.30) .044† (1.90) -.019 (-.99) -.269 (-1.23) .226** (2.96) .161 (1.37)

.215 (1.12) .047* (2.07) -.026 (-1.39) -.242 (-1.14) .238** (3.13) .179 (1.52)

.247 (1.26) .039† (1.65) -.025 (-1.39) -.244 (-1.14) .239** (3.15) .163 (1.39)

.196 (1.02) .041† (1.71) -.025 (-1.38) -.196 (-.92) .234** (3.07) .162 (1.38)

.066 (.53)

.170 (.76) .043† (1.67) -.023 (-1.20) -.199 (-.87) .194* (2.47) .184 (1.57) 1.93† (1.85) -.950 (-.74) -.591 (-1.47) .307 (1.36) -.021 (-.15)

.056 .030 .002 2.19*

.091 .049 .037 2.19

7. R&D 8. ADV

-1.49 (-1.18)

9. CONT

-.601 (-1.55)

10. TMT_INT

.294 (1.33)

11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

.054 .033 2.58*

.069 .044 .015 2.77*

.060 .035 .005 2.38*

.064 .039 .010 2.56*

.062 .037 .008 2.45*

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

252

Appendix Chapter 4

A 4.4: Additional Results for Hypothesis Three (continued) Table A 4.4.2 Regression of Intangible Resources on Scope of Expansiona (Five Year Change of Dispersion of Foreign Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

.109 (.30) .029 (.63) -.038 (-1.12) .219 (.45) .240† (1.73) .147 (.64)

-.108 (-.26) .037 (.79) -.044 (-1.30) .403 (.79) .180 (1.22) .133 (.59) 2.41 (1.16)

.096 (.24) .030 (.63) -.038 (-1.06) .226 (.45) .242† (1.70) .149 (.64)

.019 (.05) .032 (.69) -.036 (-1.09) .229 (.47) .261† (1.88) .194 (.85)

.101 (.27) .030 (.64) -.037 (-1.11) .227 (.46) .240† (1.71) .146 (.64)

.119 (.33) .038 (.79) -.038 (-1.12) .155 (.31) .252† (1.79) .136 (.59)

-.147 (-.62)

-.256 (-.54) .060 (1.13) -.046 (-1.22) .377 (.70) .205 (1.34) .146 (.62) 2.96 (1.29) .295 (.08) .780 (1.00) -.170 (-.40) -.263 (-.97)

.078 .000 .006 .84

.130 .000 .058 .83

7. R&D 8. ADV

.255 (.07)

9. CONT

.982 (1.33)

10. TMT_INT

-.042 (-.10)

11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

.072 .000 .94

.093 .001 .021 1.01

.073 .000 .001 .77

.099 .008 .027 1.08

.073 .000 .001 .77

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Intangible Resources and the Internationalization Process

253

A 4.4: Additional Results for Hypothesis Three (continued) Table A 4.4.3 Regression of Intangible Resources on Scope of Expansiona (Two Year Change of Dispersion of Total Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

.158 (1.02) .016 (.87) -.014 (-.91) .175 (1.10) .168** (2.69) .015 (.16)

.126 (.77) .016 (.87) -.014 (-.91) .203 (1.22) .162* (2.54) .017 (.18) .415 (.57)

.205 (1.29) .013 (.73) -.009 (-.58) .148 (.92) .166** (2.66) .018 (.19)

.159 (1.02) .016 (.87) -.014 (-.91) .175 (1.09) .168** (2.69) .016 (.17)

.205 (1.31) .008 (.44) -.012 (-.83) .144 (.90) .176** (2.82) .025 (.27)

.166 (1.06) .012 (.62) -.013 (-.89) .180 (1.13) .169** (2.70) .015 (.16)

.066 (.67)

.267 (1.51) -.001 (-.07) -.007 (-.45) .122 (.72) .175** (2.74) .025 (.27) -.011 (-.01) -.977 (-1.26) .107 (.30) .320† (1.68) .101 (.94)

.037 .030 .002 2.20*

.052 .024 .017 1.86†

7. R&D 8. ADV

-.973 (-1.28)

9. CONT

-.017 (-.05)

10. TMT_INT

.270 (1.44)

11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

.035 .022 2.55*

.036 .020 .001 2.18*

.040 .023 .005 2.41*

.035 .019 .000 2.12*

.042 .025 .007 2.48*

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

254

Appendix Chapter 4

A 4.4: Additional Results for Hypothesis Three (continued) Table A 4.4.4 Regression of Intangible Resources on Scope of Expansiona (Three Year Change of Dispersion of Total Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

.019 (.10) .025 (1.13) -.013 (-.77) .218 (1.14) .188* (2.57) .160 (1.45)

.020 (.10) .025 (1.13) -.013 (-.77) .216 (1.08) .188* (2.54) .160 (1.44) -.024 (-.03)

.088 (.46) .023 (1.03) -.005 (-.26) .142 (.73) .187** (2.56) .175 (1.59)

.021 (.11) .025 (1.12) -.013 (-.77) .216 (1.13) .188* (2.57) .162 (1.46)

.074 (.39) .016 (.71) -.012 (-.69) .183 (.96) .198** (2.71) .171 (1.55)

.022 (.12) .023 (.98) -.013 (-.76) .222 (1.16) .188* (2.57) .160 (1.45)

.035 (.30)

.207 (.97) .008 (.32) -.003 (-.17) .072 (.35) .206** (2.77) .182 (1.63) -.585 (-.62) -1.59† (-1.78) .075 (.20) .393† (1.81) .084 (.64)

.038 .015 .000 1.65

.062 .024 .024 1.63†

7. R&D

-1.51† (1.72)

8. ADV 9. CONT

-.058 (-.16) .348† (1.65)

10. TMT_INT 11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

.038 .019 1.97†

.038 .015 .000 1.64

.049 .026 .011 2.15*

.038 .015 .000 1.64

.048 .025 .010 2.11†

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Intangible Resources and the Internationalization Process

255

A 4.4: Additional Results for Hypothesis Three (continued) Table A 4.4.5 Regression of Intangible Resources on Scope of Expansiona (Five Year Change of Dispersion of Total Sales) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service

1

2

3

4

5

6

7

-.278 (-.83) .067 (1.57) -.038 (-1.28) .287 (.70) .264* (2.08) .137 (.65)

-.371 (-1.02) .068 (1.59) -.039 (-1.29) .364 (.86) .248† (1.91) .136 (.64) 1.14 (.71)

-.177 (-.52) .058 (1.37) -.025 (-.82) .255 (.63) .269* (2.13) .176 (.83)

-.335 (-.98) .068 (1.61) -.038 (-1.25) .291 (.71) .279* (2.18) .168 (.79)

-.222 (-.65) .058 (1.34) -.036 (-1.19) .245 (.59) .271* (2.12) .143 (.68)

-.278 (-.82) .067 (1.52) -.038 (-1.27) .287 (.70) .264* (2.06) .137 (.64)

-.004 (-.02)

-.214 (-.54) .050 (1.07) -.022 (-.70) .252 (.58) .283* (2.14) .213 (.98) .478 (.26) -2.18 (-1.49) .686 (.93) .316 (.82) .020 (.09)

.113 .037 .000 1.49

.165 .039 .052 1.31

7. R&D 8. ADV

-2.14 (-1.51)

9. CONT

.690 (.96)

10. TMT_INT

.328 (.89)

11. TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

.113 .051 1.82

.120 .044 .007 1.59

.141 .068 .028 1.92†

.125 .050 .012 1.66

.123 .048 .010 1.64

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

.15** .08* -.30** .12** -.15**

1.86 2.14 .177 .494 .411

.029

.044

8.63

4.54

.606

.581

.216

4. 'FSTS_past3years

5. 'FSTS_past5years

6. Size_ln

7. Product Div.

8. Leverage

9. I1: Manufacturing

10. I2: Service

Notes: 'FSTS_past2years: N=475. 'FSTS_past3years: N=341. 'FSTS_past5years: N=98. † p < .10. * p < .05. ** p < .01 (all two-tailed tests).

-.14

.100

.014 .113

.090

.235

.13** -.25**

.28** .19** -.37**

.58** .39** .12** -.39**

.03 -.05 -.07 -.08 .00

-.07 -.13* .04 -.05 .06

-.11* -.01 -.05 .04

.06 .32** -.42**

8

.22**

7

.49**

6

-.02

5

.47**

.71**

4

.34**

.19**

3

.12

.17**

-.04

2

-.09†

.15**

.517

3. 'FSTS_past2years

1

2. FSTS

.096

.047

1. ROA

S. D.

Mean

Variables

Table A 4.5.1 Speed of Expansion – Descriptive Statistics and Correlations (N = 789)

A 4.5: Additional Results for Hypothesis Four

-.62**

9

256 Appendix Chapter 4

Intangible Resources and the Internationalization Process

257

A 4.5: Additional Results for Hypothesis Four (continued) Table A 4.5.2 Moderation of Speed of Expansiona (Change of Internationalization over Past Three Years) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service  'FSTS_past3years 8. 'FSTS_past3years (squared)

1

2

3

4

.125** (5.21) .007* (2.51) .004† (1.78) -.240** (-9.97) .007 (.81) .001 (.09) -.057† (-1.67) .236* (2.29)

.105** (2.77) .008** (2.68) .004† (1.65) -.242** (-9.96) .010 (1.06) .000 (.04) -.050 (-1.41) .228* (2.22) .217 (1.04) -.579 (-1.29) .405 (1.38)

.085* (2.23) .009** (3.10) .003 (1.50) -.253** (-10.33) .009 (.96) .001 (.05) -.029 (-.79) -.017 (-.12) .304 (1.44) -.679 (-1.52) .426 (1.46) .523* (2.55)

.086* (2.24) .009** (3.02) .003 (1.50) -.250** (-10.20) .008 (.87) .001 (.05) .001 (.02) -.019 (-.14) .287 (1.36) -.637 (-1.43) .401 (1.38) .588** (2.78) -.644 (-1.22)

.245 .229

.251 .229 .006 11.08**

.266 .241 .021 10.84**

.269 .243 .024 10.07**

9. FSTS 10. FSTS (squared) 11. FSTS (cubic) 12. FSTS* 'FSTS_past3years 13. FSTS*  'FSTS_past3years (squared) R2 Adjusted R2 ' R2 F-statistic †

15.41**

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

258

Appendix Chapter 4

A 4.5: Additional Results for Hypothesis Four (continued) Table A 4.5.3 Moderation of Speed of Expansiona (Change of Internationalization over Past Five Years) Variable 1. Intercept 2. Size_ln 3. Product Div. 4. Leverage 5. I1: Manufacturing 6. I2: Service  'FSTS_past5years 8. 'FSTS_past5years (squared)

1

2 †

†

.115 (1.85) .007 (1.47) .001 (.37) -.131** (-2.97) .000 (.01) .010 (.52) -.117† (-1.76) .201 (.74) -.220 (-.63) .307 (.41) -.102 (-.21)

.080 (1.23) .009† (1.85) .001 (.35) -.139** (-3.15) .001 (.08) .012 (.63) -.069 (-.95) -.033 (-.11) -.102 (-.29) .147 (.19) -.056 (-.11) .595 (1.63)

.081 (1.25) .009† (1.93) .001 (.27) -.145** (-3.23) .003 (.22) .014 (.72) -.100 (-1.21) .076 (.22) -.090 (-.25) .099 (.13) -.021 (-.04) .474 (1.20) 1.62 (.79)

.133 .066

.149 .052 .016 1.53

.175 .069 .042 1.66†

.181 .065 .048 1.56

10. FSTS (squared) 11. FSTS (cubic) 12. FSTS* 'FSTS_past5years 13. FSTS* 'FSTS_past5years (squared)

†

4

.070 (1.88) .008† (1.84) .002 (.43) -.137** (-3.20) .000 (.02) .013 (.66) -.117† (-1.82) .180 (.67)

9. FSTS

R2 Adjusted R2 ' R2 F-statictic

3

1.97†

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics.

Intangible Resources and the Internationalization Process

259

A 4.6: Additional Results for Hypothesis Five Table A 4.6.1 Moderation of Scope of Expansiona on Change of ROAb over Three Years (N = 241) (Three Year Change of Dispersion of Foreign Sales) Variable 1. Intercept 2. R&D 3. ADV 4. CONT 5. TMT_INT 6. TMT_ACD

1

2

3

4

5

6

7

8

.048** (3.60) -.231 (-1.39) -.183 (-.95) .054 (.73) .032 (.80) -.047* (-2.07)

.057** (2.65) -.255 (-1.46) -.181 (-.93) .057 (.76) .031 (.77) -.049* (-2.08) -.018 (-.44) -.005 (-.37)

.046* (2.04) -.056 (-.27) -.141 (-.72) .053 (.71) .019 (.46) -.047* (-2.04) -.010 (-.26) -.004 (-.36) -.628† (-1.80)

.043† (1.95) -.175 (-1.00) -.024 (-.12) .064 (.86) .027 (.68) -.044† (-1.91) -.005 (-.12) -.011 (-.90)

.056** (2.60) -.263 (-1.51) -.188 (-.96) .133 (1.44) .032 (.79) -.049* (-2.10) -.022 (-.55) -.005 (-.40)

.058** (2.67) -.244 (-1.37) -.179 (-.91) .056 (.74) .016 (.27) -.049* (-2.10) -.018 (-.45) -.005 (-.38)

.042† (1.80) -.262 (-1.50) -.147 (-.75) .059 (.78) .033 (.82) -.018 (-.58) -.007 (-.18) -.004 (-.29)

-.070 (-1.56)

.024 (1.00) -.086 (-.41) .004 (.02) .124 (1.34) .019 (.34) -.017 (-.54) .004 (.09) -.010 (-.78) -.340 (-.93) -1.53* (-2.36) -.180 (-1.14) .007 (.09) -.063 (-1.34)

.055 .023 .011 1.69

.094 .047 .050 1.98*

7. FS_Dispersion 8. 'S.D._FS_3year 9. 'S.D._FS_3year* R&D 10. 'S.D._FS_3year* ADV 11. 'S.D._FS_3year* CONT 12. 'S.D._FS_3year* TMT_INT 13. 'S.D._FS_3year* TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

-1.74** (-2.73) -.218 (-1.42) .029 (.36)

.044 .024 2.16†

.045 .017 .001 1.58

.058 .026 .014 1.80†

.075 .043 .031 2.35*

.053 .021 .009 1.64

.046 .013 .002 1.39

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics. b Change of ROA is calculated as the difference between ROAt+3 and ROAt=0.

260

Appendix Chapter 4

A 4.6: Additional Results for Hypothesis Five (continued) Table A 4.6.2 Moderation of Scope of Expansiona on Change of ROAb over Five Years (N = 72) (Five Year Change of Dispersion of Foreign Sales) Variable 1. Intercept 2. R&D 3. ADV 4. CONT 5. TMT_INT 6. TMT_ACD

1 .047* (2.25) .210 (.79) -.167 (-.62) -.004 (-.03) .071 (1.06) -.085* (-2.43)

7. FS_Dispersion 8. 'S.D._FS_5year 9. 'S.D._FS_5year* R&D 10. 'S.D._FS_5year* ADV 11. 'S.D._FS_5year* CONT 12. 'S.D._FS_5year* TMT_INT 13. 'S.D._FS_5year* TMT_ACD R2 Adjusted R2 ' R2 F-statistic †

2

3

.075* .046 (2.10) (1.25) .120 .564† (1.73) (.44) -.018 -.107 (-.07) (-.39) -.070 -.018 (-.60) (-.16) .046 .060 (.71) (.90) -.100** -.096** (-2.77) (-2.77) -.057 -.084 (-.89) (-1.31) .020 .016 (1.07) (.81) -1.29* (-2.35)

4 .056 (1.52) .195 (.71) .029 (.11) .003 (.03) .063 (.96) -.084* (-2.31) -.069 (-1.08) -.001 (-.05)

5

6

.076* .076* (2.12) (2.07) .205 .121 (.70) (.43) -.075 -.107 (-.27) (-.39) -.217 -.019 (-.85) (-.16) .057 .058 (.86) (.60) -.102** -.100** (-2.83) (-2.74) -.080 -.085 (-1.24) (-1.30) .018 .016 (.89) (.81)

7

8

.049 (1.23) .133 (.48) -.043 (-.16) -.032 (-.27) .063 (.95) -.052 (-1.08) -.063 (-.96) .018 (.94)

-.100 (-1.46)

.024 (.60) .712* (2.00) .152 (.55) -.366 (-1.44) .062 (.66) -.071 (-1.46) -.032 (-.50) .010 (.49) -1.17* (-2.00) -1.88 (-1.46) .399 (1.41) -.031 (-.24) -.036 (-.51)

.169 .064 .062 1.60

.269 .120 .162 1.81†

-2.46† (-1.97) .251 (.88) .004 (.03)

.107 .039 1.58

.141 .047 .034 1.50

.211 .110 .104 2.10*

.191 .088 .084 1.86†

.152 .044 .045 1.41

.141 .032 .034 1.30

p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics. b Change of ROA is calculated as the difference between ROAt+5 and ROAt=0.

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261

A 4.6: Additional Results for Hypothesis Five (continued) Table A 4.6.3 Moderation of Scope of Expansiona on Change of ROAb over Two Years (Two Year Change of Dispersion of Foreign Sales) - TQ

Variable 1. Intercept 2. Tobin’s q

1

Tobin’s q 2

3

4

Hedonic q 5

6

.028** (3.45) -.010* (-2.02)

.009 (.67) -.009† (-1.93)

.003 (.18) -.006 (-1.02)

,025 (1.29)

,005 (.25)

-.014 (-.58)

-,010 (-.65)

-,010 (-.69) ,047† (1.68) ,011 (1.17)

.003 (.19) .054† (1.91) .019† (1.79)

3. Hedonic q .050† (1.78) .005 (.56)

4. FS_Dispersion 5. 'S.D._FS_2year 6. 'S.D._FS_2year* Tobin’s q 7. 'S.D._FS_2year* Hedonic q R2 Adjusted R2 ' R2 F-statistic

.054† (1.89) .005 (.54) -.020 (-1.60)

-.068† (-1.79) .013 .010 4.10*

.023 .014 .010 2.48†

.031 .019 .018 2.50*

.001 .000 .42

.014 .004 .013 1.40

Notes: Tobin’s q: N=320, Hedonic q: N=300. † p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics. b Change of ROA is calculated as the difference between ROAt+2 and ROAt=0.

.025 .011 .024 1.86

262

Appendix Chapter 4

A 4.6: Additional Results for Hypothesis Five (continued) Table A 4.6.4 Moderation of Scope of Expansiona on Change of ROAb over Three Years (Three Year Change of Dispersion of Foreign Sales) - TQ

Variable 1. Intercept 2. Tobin’s q

1

Tobin’s q 2

3

4

Hedonic q 5

6

.044** (3.78) -.017* (-2.25)

.037* (2.10) -.017* (-2.27)

.020 (1.07) -.003 (-.40)

.029 (1.22)

.025 (.91)

.001 (.03)

-.007 (-.35)

-.006 (-.33) .002 (.06) .006 (.53)

.011 (.51) .011 (.30) .015 (1.16)

3. Hedonic q 4. FS_Dispersion

.026 (.71) -.003 (-.26)

5. 'S.D._FS_3year 6. 'S.D._FS_3year* Tobin’s q 7. 'S.D._FS_3year* Hedonic q R2 Adjusted R2 ' R2 F-statistic

.024 (.65) -.003 (-.26) -.049** (-2.96)

-.079† (-1.70) .022 .017 5.07*

.024 .011 .002 1.88

.060 .044 .038 3.64**

.001 .000 .13

.002 .000 .001 .13

Notes: Tobin’s q: N=233, Hedonic q: N=217. † p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics. b Change of ROA is calculated as the difference between ROAt+3 and ROAt=0.

.015 .000 .014 .83

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263

A 4.6: Additional Results for Hypothesis Five (continued) Table A 4.6.5 Moderation of Scope of Expansiona on Change of ROAb over Five Years (Five Year Change of Dispersion of Foreign Sales) - TQ

Variable 1. Intercept 2. Tobin’s q

1

Tobin’s q 2

3

4

Hedonic q 5

6

.041* (2.02) -.013 (-1.02)

.046 (1.51) -.011 (-.88)

.015 (.48) .014 (.96)

.003 (.10)

.011 (.25)

.028 (.62)

.020 (.76)

.023 (.84) -.064 (-1.08) .023 (1.22)

.011 (.39) -.074 (-1.24) .015 (.75)

3. Hedonic q -.038 (-.62) .011 (.52)

4. FS_Dispersion 5. 'S.D._FS_3year 6. 'S.D._FS_3year* Tobin’s q 7. 'S.D._FS_3year* Hedonic q R2 Adjusted R2 ' R2 F-statistic

-.056 (-.95) .004 (.19) -.082** (-3.08)

.082 (1.03) .015 .000 1.03

.026 .000 .011 .59

.152 .099 .137 2.88*

.009 .000 .57

.054 .008 .045 1.17

Notes: Tobin’s q: N=70, Hedonic q: N=65. † p < .10. * p < .05. ** p < .01 (all two-tailed tests). a Upper number in a cell is a parameter estimate, numbers in the parentheses are t-statistics. b Change of ROA is calculated as the difference between ROAt+5 and ROAt=0.

.071 .009 .062 1.14