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Three essays on distance: examing the role of institutional distance on foreign firm entry, local isomorphism strategy and subsidiary performance

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Three essays on distance: examing the role of institutional distance on foreign firm entry, local isomorphism strategy and subsidiary performance

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Content THREE ESSAYS ON DISTANCE: EXAMINING THE ROLE OF INSTITUTIONAL
DISTANCE ON FOREIGN FIRM ENTRY, LOCAL ISOMORPHISM STRATEGY
AND SUBSIDIARY PERFORMANCE

by

Zheying Wu

A Dissertation Presented to the
FACULTY OF THE USC GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(MANAGEMENT AND ORGANIZATION)

December 2009

Copyright 2009 Zheying Wu

ii

DEDICATION

This dissertation is dedicated to my father Peiqi Wu, my mother Yongxu Chen

and my husband Jing Nie

iii
ACKNOWLEDGMENTS

The past six years have been the most important in my life. During this period, so
many people helped and guided me in identifying my true interests. I would not have
discovered my true passion if I had not received their support.
I owe a great debt to my advisor and dissertation committee chair, Professor
Robert Salomon. Although we were separated by 2,500 miles and three time zones for
four years, Rob was always there to teach, coach, correct, and encourage me, concerned
with not only the quality of my research but also the quality of my life. I cannot imagine
how much time and effort he has invested in me.
I would like to acknowledge the support of my entire committee: Professor Kyle
Mayer for inspiring my initial research question; Professor Jay Kim for continuously
providing challenging comments and valuable advice; Professor Nandini Rajagopalan for
providing many suggestions for improving this dissertation; and Professor Cheng Hsiao
for providing “first aid” whenever I became confused with empirical testing.
I would like to thank Professor Tom Cummings, the chair of the Management and
Organization Department, who has supported me through both the good and bad times;
Professor Carl Voigt and Professor Michael Coombs for teaching me how to teach; and
Professor Arturs Kalnins, a former member of our department, for demonstrating how
interesting strategy research can be. Last but not least, I would like to thank Professor
Xavier Martin of the University of Tilburg for serving as not only a co-author but also a
role model. I am deeply grateful to him for demonstrating to me the power of creative

iv
thinking and rigorous scholarship. All of these professors have been great assets to me
over the past six years, and I am deeply grateful for their contribution to my development.
As my most important source of enjoyment, I would like to thank all the students
in the MOR department for making study and research less of a struggle and more of a
pleasure. Moreover, I would like to thank the entire MOR department and the Marshall
School of Business, whose assistance and support allowed me to focus continuously on
my research.
I would like to express my gratitude for all the love that I have received from my
family. My parents expressed full trust in and support for all my decisions. Although I
could not celebrate any holiday with them over the past six years, they never complained,
only urging me to study hard and enjoy life. My husband has been the highlight of my
life since we married. To build our little family, he came to Los Angeles all the way from
Shanghai, leaving his family, friends, and promising job behind. Because of him, my
apartment has become a home. I feel so lucky to have his love, care, and endless patience.
Lastly, I would like to express my gratitude to Junping Tan, Siqi Li, Nan Xia,
Jenny Tian, Jade Lo, Rui Wu, and all my other friends who made the Ph.D. process into a
wonderful memory.

v
TABLE OF CONTENTS

DEDICATION…………………………………………………………………….. ii

ACKNOWLEDGEMENTS………………………………………………………. iii

LIST OF TABLES………………………………………………………………… viii

ABSTRACT………………………………………………………………………... x

CHAPTER 1 INTRODUCTION……………………………………………….…. 1
1.1 Institutional Distance and Foreign Firm……………………………………….. . 1
1.2 Motivations and Key Findings of the Dissertation……………………………… 2
1.2.1 Essay 1: Institutional Distance and Foreign Firm Entry…………………….. 2
1.2.2 Essay 2: Institutional Distance and Local Isomorphism Strategy…………….4
1.2.3 Essay 3: Institutional Distance, Local Isomorphism Strategy and Foreign
Subsidiary Performance……………………………………………………… 6
1.3 Outline of the Dissertation………………………………………………………. 7

CHAPTER 2 ESSAY 1: INSTITUTIONAL DISTANCE AND
FOREIGN FIRM ENTRY ........................................................................................ 8
2.1 Introduction……………………………………………………………………... 8
2.2 Theory and Hypotheses…………………………………………………………. 11
2.2.1 Liability of Foreignness and Institutional Distance…………………………. 11
2.2.2 Institutional Distance and Entry Decision…………………………………… 15
2.2.3 Institutional Distance, Vicarious Learning, and Entry Decision……………. 18
2.3 Research Design…………………………………………………………………. 21
2.3.1 Data…………………………………………………………………………. 21
2.3.2 Dependent Variable………………………………………………………… 26
2.3.3 Independent Variables: Institutional Distance……………………………… 26
2.3.3.1 Cultural Distance…………………………………………………….. 27
2.3.3.2 Economic Distance…………………………………………………… 28
2.3.3.3 Regulatory Distance………………………………………………….. 29
2.3.3.4 Political Distance……………………………………………………… 31
2.3.4 Moderating Variables……………………………………………………….. 31
2.3.4.1 Vicarious Experience………………………………………………….. 31
2.3.5 Control Variables……………………………………………………………. 33
2.3.6 Statistical Method……………………………………………………………. 37
2.4 Results ………………...………………………………………………………… 40
2.5 Discussions……………………………………………………………………… 49

vi
2.6 Limitations…………………………………………………………………….. 53

CHAPTER 3 ESSAY 2: INSTITUTIONAL DISTANCE AND LOCAL
ISOMORPHISM STRATEGY…………………………………………………….. 56
3.1 Introduction……………………………………………………………………... 56
3.2 Literature Review………………………………………………………………. 59
3.3 Hypotheses………………………………….………………………………….. 62
3.3.1 Institutional Distance……………………………………………………….. 62
3.3.2 Learning…………………………………………………………………….. 66
3.3.2.1 Vicarious Learning…………………………………………………… 66
3.3.2.2 Experiential Learning………………………………………………… 69
3.4 Research Design………………………………………………………………. 71
3.4.1 Data………………………………………………………………………… 71
3.4.2 Dependent Variable………………………………………………………… 75
3.4.2.1 Local Isomorphism Strategy………………………………………… 75
3.4.3 Independent Variables: Institutional Distance………………………………. 77
3.4.3.1 Cultural Distance…………………………………………………….. 77
3.4.3.2 Economic Distance…………………………………………………… 78
3.4.3.3 Regulatory Distance………………………………………………….. 80
3.4.3.4 Political Distance……………………………………………………… 82
3.4.4 Moderating Variables………………………………………………………. 83
3.4.4.1 Vicarious Experience………………………………………………… 83
3.4.4.2 Own Experience……………………………………………………… 84
3.4.5 Control Variables………………………………………………………….. 85
3.4.6 Statistical Method…………………………………………………………. 89
3.5 Results…………………………….…………………………………………… 90
3.6 Discussion……………………………………………………………………… 99
3.7 Limitations……………………………………………………………………… 103

CHAPTER 4 ESSAY 3: INSTITUTIONAL DISTANCE, LOCAL ISOMORPHISM
STRATEGY AND FOREIGN SUBSIDIARY PERFORMANCE……………. 105
4.1 Introduction………………………………………………………………......... 105
4.2 Literature Review……………………………………………………………… 108
4.3 Hypotheses…………………………………..………………………………… 114
4.3.1 Institutional Distance………………………………………………………. 114
4.3.2 Local Isomorphism Strategy……………………………………………….. 117
4.4 Research Design……………………………………………………………….. 119
4.4.1 Data………………………………………………………………………… 119
4.4.2 Dependent Variable……………………………………………………….. 124
4.4.2.1 Performance-ROA…………………………………………………… 124
4.4.3 Independent Variables……………………………………………………. 124

vii
4.4.3.1 Local Isomorphism Strategy………………………………………… 124
4.4.3.2 Institutional Distance………………………………………………… 126
4.4.3.2.1 Cultural Distance………………………………………….. 127
4.4.3.2.2 Economic Distance……………………………………….. 128
4.4.3.2.3 Regulatory Distance………………………………………. 129
4.4.3.2.4 Political Distance………………………………………….. 131
4.4.4 Control Variables………………………………………………………….. 132
4.4.5 Statistical Method………………………………………………………….. 135
4.4.5.1 H1: Foreign Subsidiary Performance……………………………….. 135
4.4.5.2 H2: Local Isomorphism Strategy……………………………………. 137
4.4.5.2.1 Instrumental Variables…………………………………….. 140
4.5 Results………………………………………………………………………… 143
4.6 Discussion and Conclusion………………………….………………………… 152

CHAPTER 5 DISCUSSION AND CONCLUSION………………………........ 158
5.1 Discussion of Key Findings…………………………………………………… 158
5.2 Contributions and Directions for Future Research………………….………… 160
5.3 Limitations…………………………………………………………………….. 162

REFERENCES ………………………………………………………………….... 166

viii
LIST OF TABLES
Table 2.1: Foreign Bank Origins .………………………………………………… 25
Table 2.2: Correlations …………………………………………………………… 42
Table 2.3: Regression Results-H1 ……………………………………………….. 44
Table 2.4: Regression Results-H2 (All past Entries)……………………………… 46
Table 2.5: Regression Results-H2 (Last 5-Year Entries) ………………………… 48
Table 2.6: Marginal Effects of Institutional Distance…………………………….. 50
Table 3.1: Foreign Bank Subsidiary Origins ……………………………………… 74
Table 3.2: Correlations .…………………………………………………………… 91
Table 3.3: Regression Results-H1 ………………………………………………… 93
Table 3.4: Regression Results-H2 ………………………………………………… 96
Table 3.5: Regression Results-H3 ………………………………………………… 98
Table 3.6: Marginal Effects of Institutional Distance ……………………………. 100
Table 4.1: Foreign Bank Subsidiary Origins …………………………………….. 123
Table 4.2: Correlations …………………………………………………………. 145
Table 4.3: Regression Results-H1 ……………………………………………….. 147
Table 4.4: Regression Results-H2 ……………………………………………….. 149
Table 4.5: First Stage Model of the 2SLS Regressions…………………………. 151
Table 4.6: Marginal Effects of Institutional Distance …………………………… 154

ix
ABSTRACT
This dissertation consists of three essays on the impact of institutional distance on
foreign firm entry, local isomorphism strategy and foreign subsidiary performance. These
studies employ two samples: the first one includes the foreign banks that entered the
United States from 61 home countries during 1956-2006. The second one includes all
foreign bank subsidiaries (83 in Essay 2 and 84 in Essay 3) that operated in the United
States from 1978 to 2006.
The first essay focuses on the impact of institutional distance on foreign firm
entry. It examines the relationship between the cultural/economic/regulatory/political
distances and the number of foreign entrants from a particular home country. Moreover,
it tests whether vicarious experience moderates the impact of institutional distance. The
results support the argument that fewer foreign firms enter the host country market as the
institutional distance increases. In addition, the finding also suggests that the negative
impact of institutional distance on foreign firm entry is likely to decrease as there are
more prior entrants from the same home country.
The second essay examines foreign firms’ decision to imitate local domestic
competitors, i.e. the local isomorphism strategy. In this essay, I argue that foreign firms
are likely to imitate local domestic incumbents more as the institutional distance
increases. Furthermore, this impact of institutional distance is likely to be moderated as
foreign firms learn from others’ experience and their own experience. The empirical
findings support the primary argument by showing that foreign banks imitate local U.S.
banks to a greater extent as the cultural/economic/regulatory distance between the home

x
country and the U.S. increases. Moreover, this impact of institutional distance persists
over time.
The third essay tests the performance impact of local isomorphism strategy.
Contrary to prior research, this study finds a positive association between local
isomorphism and foreign subsidiary performance. In this empirical test, local
isomorphism strategy is treated as a self-selected endogenous variable. The results
support the hypothesis that local isomorphism strategy, as a function of individual firm
characteristics and environmental conditions, has a positive impact on foreign subsidiary
performance.

1
CHAPTER 1
INTRODUCTION
1.1 Institutional Distance and Foreign Firms
Decades of research in the field of international business has indicated that
foreign firms operating abroad may face a specific disadvantage compared to domestic
firms (Hymer, 1960; Zaheer, 1995). This disadvantage, known as the liability of
foreignness, arises from a firm’s unfamiliarity with the host country environment (Hymer,
1960; Johanson and Vahlne, 1977) and lack of roots in the local environment (Zaheer,
1995; Zaheer and Mosakowski, 1997). One important source of the liability of
foreignness is the institutional distance between the host country and the home country
(Kostova and Zaheer, 1999). By institutional distance, scholars refer to the difference
between the countries in terms of their institutional environments (Kostova, 1996; Xu and
Shenkar, 2001). As the dissimilarity between the cultures, economies, regulations, and
political systems of the home and host countries increases, foreign firms from the host
country tend to experience greater difficulty in understanding the local environment,
communicating with local parties, and interpreting and transferring information
(Johanson and Vahlne, 1977; Hernart, 1982; Zaheer, 1995). Moreover, as the distance in
institutional background increases, foreign firms are more likely to be regarded by the
host country environment as less legitimate (Zaheer and Mosakowski, 1997), and thus
face greater barriers in acquiring legitimacy in the local environment (Kostova and
Zaheer, 1999).

2
Although the prior literature on international business and strategy has recognized
that institutional distance can have a negative impact on foreign firms, there remain gaps
in the research on institutional distance and foreign firms’ strategy and performance. This
dissertation aims to help narrow these gaps by conducting three studies, the first of which
explored the impact of multi-dimensional institutional distance on foreign-firm entry; the
second on the tendency of foreign firms to choose local isomorphism strategy according
to the institutional distance that they face; and the third on the impact of the adoption of
local isomorphism on foreign-subsidiary performance, depending on institutional
distance.

1.2 Motivations and Key Findings of the Dissertation
1.2.1 Essay 1: Institutional Distance and Foreign Firm Entry
This study was motivated by the limited view of institutional distance adopted by
prior studies in the field of international business. Specifically, although prior studies
explored the influence of institutional distance, most adopted cultural distance as the only
proxy (Dow and Karunaratna, 2006). However, the institutional environment consists of
both formal institutions, such as laws and regulations, and informal institutions, such as
culture, beliefs, and values (Scott, 1995), the exclusion of any of which could result in
misleading conclusions. To fill this gap, this study adopted a multi-dimensional
perspective of the measurement of institutional distance by assessing the distance
between national cultures, economies, regulations, and political systems in testing the
hypothesis that the number of foreign firms that enter a market increase as the multi-

3
dimensional institutional distance between the home country and the host country
decreases.
Moreover, few prior studies on foreign-firm entry examined the potential for
vicarious learning among foreign firms. According to organizational learning theory, by
observing the decisions, strategies, and practices of other firms, firms can learn from their
counterparts (Huber, 1991). Empirical research also indicates that foreign firms have a
higher probability of survival if there is a greater foreign presence in the host country
(Shaver, Mitchell, and Yeung, 1997). However, prior research has not examined whether
a firm entering a market learns how to overcome the barriers created by institutional
distance by examining the experience of earlier entrants. To fill this gap, this study tested
whether vicarious learning moderates the impact of institutional distance on foreign firms
entering a new market by examining the data on 61 home countries from which foreign
banks entered the U.S. market between 1956 and 2006. The results support the hypothesis
that foreign firms are more likely to enter a new market as the institutional distance
between the home country and the host country decreases. Specifically, the results
demonstrated that more foreign banks entered the United States as the cultural, regulatory,
and political distance between their home country and the United States decreased.
However, the results indicate that economic distance has no significant impact on
foreign-bank entry.
Moreover, the findings partially support the hypothesis that vicarious learning
occurs among firms such that the negative impact of institutional distance on foreign-
bank entry is moderated by the experience of prior entrants. Except for cultural distance,

4
the interactions between vicarious experience and economic/regulatory/political distance
have a significant and positive impact on foreign banks entering a new market.

1.2.2 Essay 2: Institutional Distance and Local Isomorphism Strategy
Prior research has explored how foreign firms offset the liability of foreignness
when operating within a foreign market. One solution to this challenge is adopting a
strategy of local isomorphism; that is, imitating the strategies and practices of local
domestic firms (Zaheer, 1995). Local isomorphism may help foreign firms enhance their
level of legitimacy in the local environment (Zaheer, 1995), as local players are likely to
regard firms that imitate the majority as legitimate (Meyer and Rowan, 1977). However,
prior empirical research has not found a positive association between local isomorphism
and foreign-subsidiary performance (Zaheer, 1995), implying that local isomorphism
may not be the optimal strategy for all foreign firms; that is, local isomorphism may be a
good strategy only under certain conditions.
This study argues that institutional distance is one condition that affects the
likelihood of foreign firms to adopt local isomorphism strategy. Specifically, it
hypothesizes that as institutional distance increases, foreign firms tend to experience
greater difficulty in establishing legitimacy in the local environment, as well as greater
difficulty understanding the local environment and designing their own unique strategy.
Due to this difficulty, foreign firms are more likely to rely on domestic firms as a model
of “fit” to the local environment—that is, they are more likely to imitate local domestic
firms—as institutional distance increases.

5
However, the impact of institutional distance on foreign firm strategy may
diminish overtime. As firms accumulate more experience in the foreign market and
establish more ties, they acquire more local knowledge and legitimacy, leading to a
decreased need to imitate the strategies and business practices of domestic firms and a
greater ability to implement their own strategies. Recognizing that firms learn from their
experience and that of other firms, this study hypothesizes that the tendency of firms to
adopt local isomorphism as a response to institutional distance is likely to decrease as
firms accumulate more experience in the host country or as the experience of competitors
in the host country increases.
Analysis of a sample of 83 foreign-bank subsidiaries operating in the U.S.
banking industry between 1978 and 2006 indicates that foreign banks tend to imitate their
local domestic competitors more as the cultural/economic/regulatory distance between
their home country and the United States increases. However, political distance has no
significant impact on their decision to adopt local isomorphism strategy. However, the
results do not support the organizational learning hypotheses. That is, neither the bank’s
own experience nor the accumulated experience of its competitors had a significant
moderating effect on its decision to imitate local domestic competitors. These findings
imply that institutional distance has a persistent influence on the strategies adopted by
foreign firms operating within a host country.

6
1.2.3 Essay 3: Institutional Distance, Local Isomorphism Strategy and Foreign
Subsidiary Performance
Prior studies have not found a positive association between the adoption of local
isomorphism and foreign-subsidiary performance (Zaheer, 1995; Miller and Eden, 2006).
This non-finding could imply that local isomorphism might not help foreign firms reduce
the liability of foreignness and thus improve their performance. However, an alternative
explanation could be that foreign firms choose a level of local isomorphism according to
their individual characteristics and institutional background. If local isomorphism is a
self-selected endogenous factor that affects performance, the impact of local
isomorphism on foreign-subsidiary performance could only be truly understood by
examining the underlying mechanism by which they choose this strategy.
To examine this alternative explanation, this study tests the hypothesis that the
adoption of local isomorphism, as the result of self-selection based on individual firm
characteristics and environmental conditions, is positively related to foreign subsidiary
performance. Using a two-stage instrumental variable simultaneous equation to address
the endogeneity of the local isomorphism strategy variable, I test this hypothesis by
examining the data on 84 foreign-bank subsidiaries operating in the United States
between 1978 and 2006. Confirming the hypothesis, the results indicate that local
isomorphism, as an endogenous variable, has a positive and significant impact on
foreign-bank subsidiary performance. They also indicate that according to the first-stage
selection model, foreign banks are more likely to imitate local domestic competitors as

7
cultural/economic/regulatory distance increases. This finding is consistent with the results
of essay 2.

1.3 Outline of the Dissertation
The dissertation is organized into five chapters. Chapter one, the current chapter,
provides a brief overview of this dissertation. Chapter two discusses the first study, which
examines the impact of multi-dimensional institutional distance on foreign firm entry.
Chapter three discusses the second study, which examines the conditions under which
foreign firms are likely to adopt local isomorphism strategy. Chapter four discusses the
third study, which examines the impact of local isomorphism on performance, based on
institutional distance and other factors. Chapter five summarizes the findings of the three
studies and discusses their contributions and limitations.

8
CHAPTER 2
INSTITUTIONAL DISTANCE AND FOREIGN FIRM ENTRY
2.1 Introduction
Operating abroad, foreign firms face a potential disadvantage compared to
domestic firms (Hymer, 1960; Zaheer, 1995). This disadvantage, known as the liability of
foreignness, arises from unfamiliarity with the local environment (Hymer, 1960;
Johanson and Vahlne, 1977) and lack of roots in the environment (Zaheer, 1995).
Furthermore, the liability of foreignness also results from the difficulty of coordinating
distant foreign subsidiaries. Research on international strategy suggests that the liability
of foreignness affects firms’ decisions to enter foreign markets (Johanson and Vahlne,
1977); that is, firms are less likely to enter a market of which they have limited
knowledge.
One important antecedent of the liability of foreignness is the institutional
distance between host country and home country (Kostova and Zaheer, 1999).
Institutional distance refers to the difference between two countries in terms of their
institutional contexts (Kostova, 1996; Xu and Shenkar, 2001). It arises from the
differences in both formal institutions and informal institutions (Scott, 1995). Institutional
distance affects the costs and risks of operating abroad. For example, the distance
between countries’ cultures, economies, and political systems makes it difficult for
managers to understand the local environment and thus, increases the cost of collecting,
interpreting, and transferring information (Hymer, 1960; Johanson and Vahlne, 1977;
Hernart, 1982; Zaheer, 1995). Moreover, a host country may perceive foreign firms from

9
a distant institutuional environment to be less legitimate than domestic firms (Zaheer,
1995; Kostava and Zaheer, 1999).
Because of the high risks and costs of entering an institutionally distant market,
scholars argue that firms are less likely to enter a distant foreign market with which they
are unfamiliar (Johanson and Vahlne, 1977). However, empirical evidence provides
limited support for this argument (e.g., Benito and Grisprud, 1992). The lack of evidence
may result, in part, from a narrow view of institutional distance. Institutional distance
consists of differences in multiple formal and informal institutions (Scott, 1995).
However, generally, most studies examine only one dimension of institutional distance:
cultural distance.
1
Research does little to address how other dimensions, such as the
distance between economies, regulations, and political systems, contribute to the liability
of foreignness. To fill this gap, this paper studies the impact of multidimensional
institutional distance on foreign subsidiary entry decisions. In particular, it focuses on
cultural, economic, regulatory, and political distance. The research question is: As
institutional distance increases, are there likely to be fewer entries from a home country
to a host country?
Prior studies on distance and entry decision have ignored factors that may
moderate the negative impact of distance: for example, competitors’ market experience in
the host country. Foreign entrants can benefit from their competitors’ experience, which
can be a good source of information about the host country market (Mitchell, Shaver, and
Yeung, 1994). An information source is especially important when foreign firms have no

1
For a summary of cultural distance studies, see Kirkman, Lowe, and Gibson (2006). For an exception,
please refer to Perkins (2008).

10
prior experience in the host country (Chung and Song, 2004). By learning vicariously,
firms that have no prior experience in a host country can reduce the negative impact of
distance.
Because prior studies have neglected the role of vicarious learning in foreign
subsidiary entry decisions, this paper studies whether or not the experience of home
country competitors in a particular host country moderates the relationship between
distance and foreign firm entry. I have tested these assertions using a sample of 61 home
countries to review the number of home country banks that entered the United States
from 1956 to 2006. The findings show that the as the cultural, regulatory, and political
distance between the home country and the United States decreases, more foreign banks
from a particular home country enter the United States. Economic distance has little
impact on firm entries. In addition, the results show that the interaction between
competitors’ experience and institutional distance has a positive impact on foreign bank
entries.
This paper makes several contributions to the literature on strategy and
international business. Theoretically, it broadens the reader’s view of institutional
distance. Though scholars have recognized institutional distance in both formal and
informal dimensions (Gaur and Lu, 2007; Scott, 1995), most studies have looked into
only one of its dimensions: cultural distance. This study suggests that differences in
industrial regulations and political systems impact firms’ decisions. In addition, the study
looks into whether or not firms with little host country experience of their own benefit
from their competitors’ experiences. Though prior studies have examined how firms learn

11
from their own experiences, they have paid little attention to the role of competitors’
experience, which may moderate the impact of distance. Empirically, this study provides
a country-level study of foreign market entry decisions. To my knowledge, this is the first
study of its kind. It complements firm-level studies on entry decisions.
The paper proceeds as follows: The first section reviews prior literature on foreign
firms’ entry decisions and presents a hypothesis based on this review. The following
section describes the data and methodology used to test the hypothesis. The next section
presents the results. The final section concludes the study.

2.2 Theory and Hypotheses
2.2.1 Liability of Foreignness and Institutional Distance
Literature on strategy and international business has long recognized that firms
incur additional costs, or the liability of foreignness, when operating abroad (Hymer,
1960; Kindelberg, 1969; Hennart, 1982; Zaheer, 1995). Research has demonstrated that
the liability of foreignness affects foreign subsidiaries’ survival and success in a host
country. For example, foreign currency trading rooms are less profitable than domestic
ones (Zaheer, 1995). Foreign players also have a higher hazard rate of failure than their
domestic competitors (Zaheer and Mosakowski, 1997). Foreign firms face more lawsuit
judgments in the United States than do U.S. firms (Mezias, 2002), and foreign banks
suffer from a lower x-efficiency (Miller and Parkhe, 2002). Foreign firms also are less
efficient in transferring knowledge to and implementing knowledge in their host country
businesses (Salomon and Martin, 2008).

12
The liability of foreignness arises from unfamiliarity with a host country’s local
environment, practices, and regulations (Hymer, 1960; Zaheer, 1995). Without sufficient
local knowledge, foreign firms operate less efficiently in the host country than do
domestic incumbents (Hymer, 1960; Johanson and Vahlne, 1977). The liability of
foreignness also results from a lack of legitimacy in the local environment (Hymer, 1960;
Zaheer, 1995). Foreign firms are likely to be perceived as less legitimate by the host
country environment than domestic firms (Hennart, 1982; Ghoshal and Barlett, 1990;
Zaheer, 1995). The legitimacy problem may negatively affect foreign firms’ survival and
performance (Kostova and Zaheer, 1999).
The problems of unfamiliarity and legitimacy are related to institutional distance
between home country and host country. Institutional distance is the difference between
two countries in terms of their institutional contexts (Kostova, 1996; Kostova and Zaheer,
1999; Xu and Shenkar, 2001). Institutional distance arises from dissimilarity in formal
and informal institutions (Scott, 1995). Formal institutions include regulatory, political,
and economic institutions. Informal institutions refer to social norms, beliefs, and values
(i.e., national culture). International business literature shows that foreign firms are likely
to incur greater risks and costs in host countries that are distant from the home country in
terms of institutional environments. Rangan and Drummond (2004) compared foreign
firms in Brazil and found that firms from a similar institutional context were more likely
to outperform firms from a distant one.
Institutions are defined as all “human devised constraints that structure political,
economic and social interactions” (North, 1991). Therefore, institutional distance

13
includes multiple dimensions such as political, economic and social institutions, which
could be formal laws and regulations and informal cultures and routines. In this study, I
focus on four dimensions of institutional distance: cultural distance, economic distance,
regulatory distance and political distance. These dimensions are important for two
reasons. First, these dimensions regulate human activities in political, economic and
social interactions (North, 1991). Second, these dimensions play a significant role in
foreign firm strategies and performance (Ghemawat, 2001).
Institutional distance between two countries impedes foreign firms from
collecting and interpreting information about the host country, understanding the business
practices in the local market, and making decisions effectively (Kindelberg, 1969;
Johanson and Valhne, 1977). Differences in cultures, social norms, and values increase
the difficulty of a foreign firm understanding the local environment (Ghemawat, 2001).
Therefore, foreign firms face more uncertainties in their local environment than do
domestic firms. Consequently, foreign subsidiaries may have higher rates of failure in
more distant environments. They may be reluctant to enter distant markets until they have
sufficient experience and knowledge to overcome their institutional distance (Johanson
and Vahlne, 1977; Davidson, 1980).
Institutional distance also makes it more difficult for firms to coordinate activities
of distant subsidiaries (Zaheer, 1995). For example, cultural distance impedes knowledge
transfer. Knowledge transfer between distant cultures can be ineffective, because the
mode of cognition in these cultures differs (Bhagat, Kedia, Harveston, and Triandis,
2002). Similarly, the differences between two political systems can make it difficult for

14
foreign firms to adapt to the political environment of the host country. Furthermore, the
distance between industrial regulations contributes to obstacles to the coordination of
foreign subsidiaries (Perkins, 2008). Because of differences in regulations, legitimate
business practices in one country might be illegal in the other. Foreign subsidiaries might
have to adapt to two or more distinct sets of regulations, which can cause ambiguity and
conflicts within the organization (Kostova and Zaheer, 1999). In a word, the distance of
regulations, business codes and administrations add costs to coordinate far-flung
subsidiaries (Ghemawat, 2001).
The distance between two economies affects foreign subsidiary strategy and
performance in various ways. Business routines and style of business communications
depend on the level of economic development (Ghemawat, 2001; Dow and Karunaratna,
2006). Therefore, two institutionally distant countries may have fairly different business
practices. Foreign firms with a unique set of routines may communicate and cooperate
less effectively with host country customers, suppliers, and business partners. In addition,
differences in infrastructure and economic institutions may affect managerial and
operational costs. For example, foreign firms might have difficulty obtaining financial
resources in a host country because of the difference in financial market systems.
Institutional distance increases the difficulty for foreign firms to obtain legitimacy
in the local environment (Kostova and Zaheer, 1999). Coming from an institutionally
distant place, foreign subsidiaries are more likely to have resources, routines, and
strategies that differ from those of most domestic competitors (Morosini, Shane, and
Kogut, 1998). Because of their dissimilarity, the activities of foreign subsidiaries are less

15
understood, less taken for granted, and less legitimized by the local environment (Meyer
and Rowan, 1977; DiMaggio and Powell, 1983; Haveman, 1993). Therefore, local
customers, suppliers, and other parties might discriminate against foreign subsidiaries
that are more institutionally distant (Kostova and Zaheer, 1999; Ghemawat, 2001).

2.2.2 Institutional Distance and Entry Decision
Because institutional distance raises additional costs and risks for foreign firm
operation (Kostova and Zaheer, 1999), scholars argue that it negatively impacts firms’
entry decisions. In other words, as the distance between home and host countries
increases, firms are likely enter a foreign market later (Johanson and Vahlne, 1977;
Benito and Gripsrud, 1992). When firms enter an unfamiliar market, they face difficulty
in collecting, interpreting, and transferring information about the market (Johanson and
Vahlne, 1977). This difficulty intensifies as the institutional distance between home and
host countries increases. Without sufficient knowledge, foreign firms may fail to
recognize and capture opportunities in the market. They may also be less able to react to
market-specific hazards and risks (Delios and Henisz, 2000). Therefore, distance
increases foreign firms’ costs and risks of making a commitment to a host country
(Johanson and Vahlne, 1977).
Institutional distance not only increases the difficulty of market entry, but also
relates to the demand of the host country. When the distance is large, host and home
countries share fewer institutional ties and similarities. Dissimilarities in institutional
environments may result in differences in customer preference. For example, because of

16
cultural distance, popular products in one country may be viewed as unnecessary or even
inappropriate in another market (Ghemawat, 2001). Therefore, it is likely that the host
country market has less demand for goods from an institutionally distant foreign country
(Rauch, 1999; Ghemawat, 2001). In addition, the host country market may have less
demand for the technology provided by foreign firms with dissimilar institutional origins
(Vernon, 1971; Davidson and McFetridge, 1985). Confirming this assertion, empirical
studies have shown that institutional proximity is positively associated with trade flows
between two countries (Rauch, 1999; Dow and Karunaratna, 2006). Therefore,
institutional distance may affect both the costs and benefits of entering a market.
Firms make the decision to enter a particular market by evaluating the
profitability of entry. A firm will decide to enter a market only if it expects a positive
return. As discussed above, institutional distance between the home country and the
potential target market influences costs and revenues. Costs, in particular, increase with
institutional distance, while revenues decrease. When institutional distance is too large, it
is likely that costs will be greater than revenue; that is, the profitability of entering that
distant market is negative. Therefore, firms are likely to decide not to enter a foreign
market when the institutional distance between home and host countries is too great.
Along with this argument, scholars have hypothesized that foreign firms may first
enter nearby markets and sequentially move to distant markets as they gain international
experience (Davidson, 1980; Benito and Gripsrud, 1992). However, there is little
empirical evidence to support this argument. For example, Benito and Gripsrud (1992)
found that early foreign direct investments (FDIs) were not culturally closer to the home

17
country than were later FDIs established by the same parent firm. Similarly, in a survey
of managers at various stages of internationalization, Sullivan and Bauerschmidt (1990)
found no significant difference in perceived barriers and incentives to internationalization.
These results suggest that institutional distance has little impact on the decision of foreign
market entry.
However, the lack of evidence may be due to a narrow measure of distance (Dow
and Karunaratna, 2006). On the one hand, empirical tests of distance use mostly cultural
distance as the only proxy (see Shenkar (2001)) and thus neglect other differences
between institutions, such as industrial development and regulatory barriers. On the other
hand, when making a market entry decision, firms might take into account other aspects
of institutional distance. For example, in addition to unfamiliarity with local culture,
foreign firms may also suffer from a lack of legitimacy as a result of their origin in a
different economic, regulatory, and political environment.
Because most studies focus only on cultural distance, they ignore the impact of
other dimensions of institutional distance. Xu and Shenkar (2002) argued that different
dimensions of institutional distance have different impacts on multinational enterprises’
entry decisions and entry mode choices. Moreover, firm experience gained in one context
may be helpful for operation in another with similar industrial regulations (Perkins, 2008).
These examples suggest that institutional distance can result in additional costs and risks
beyond the influence of cultural distance. In other words, each dimension of institutional
distance may affect foreign subsidiaries’ entry decisions.

18
Therefore, to understand how distance impacts firms’ decisions to enter foreign
markets, I will test the following argument:
H1: All else being equal, as the institutional distance between two countries
increases, a home country is likely to have fewer firms entering a host country.

2.2.3 Institutional Distance, Vicarious Learning, and Entry Decision
As institutional distance increases, the costs and risks of entering a foreign market
increase. Therefore, institutional distance may discourage firms’ entry decisions.
However, firms can reduce the negative impact of distance by accumulating experience.
Foreign firms acquire important market knowledge that can only be learned through
experience after operating in a host country over time (Johanson and Vahlne, 1977). This
experience helps to diminish the negative impact of distance.
However, firms cannot rely upon market experience before they first enter and
operate in a particular host country. That is, when they make a decision to enter a new
foreign market, they have no prior knowledge about the market to draw on. In this case,
competitors’ relevant experience may serve as an important competitive advantage
(Ingram, 2002). According to organizational learning theory, firms can learn from the
actions, strategies, and practices of their competitors (Huber, 1991). They imitate these
activities when the outcomes are desirable and avoid them otherwise (Cyert and March,
1963). As such, the experiences of competitors may provide a valuable source of
information about the host market (Levinthal and March, 1993; Baum and Ingram, 1998;
Baum, Li, and Usher, 2000; Ingram, 2002).

19
In particular, vicarious learning is likely to occur when organizations face
uncertainty, and managers may turn to other organizations for information (Mezias and
Lant, 1994; Haunschild and Miner, 1997). When firms have limited experience of their
own, they may learn from their competitors’ experience in a similar situation to reduce
uncertainty and to make decisions (Haunschild and Miner, 1997; Baum et. al., 2000).
Therefore, for foreign firms with little experience of their own, the experience of
competitors can help reduce environmental uncertainty and lower entry barriers (Baum et.
al., 2000).
For example, Japanese firms are more likely to locate their foreign subsidiaries
close to competitors when they make first entry into the U.S. (Chung and Song, 2004).
However, they are less likely to do so as their own market experience increases. In
addition, Henisz and Delios (2001) found that competitors’ choice of location of foreign
plants had a greater impact on Japanese firms’ plant location in foreign markets when
these firms had no experience in the host country. These findings suggest that just as
organizational learning theory predicts, firms that lack experience and face uncertainty
learn from their competitors’ experience in foreign markets.
Firms are likely to observe and learn from competitors that are comparable and
visible (Haunschild and Miner, 1997; Baum et al., 2000). Though firms may imitate the
frequently repeated activities of their most successful competitors, the experience of
comparable competitors in the same context is most relevant to firms’ decision making.
In international business, the experience of competitors from the same home country may
be more applicable than that of third-country competitors. With a unique national cultural

20
and institutional background, a firm may gain market experience and knowledge that is
specific to the home country (Chang and Park, 2005). This experience may be irrelevant
to the decisions of firms from another country. Moreover, firms may pay more attention
to the activities of competitors from their home country, because they share the trait of
country of origin. Therefore, firms are likely to learn from their home country
competitors when they decide to enter a new foreign market.
In addition, home country competitors’ experience may be more available than
third-country competitors’. Firms may generate spillovers of knowledge and experience,
which neighboring firms may absorb (Marshall, 1920; Porter, 1998). Firms that have
experience in foreign markets may reveal important information and knowledge of those
markets during spillovers (Aitken, Hanson, and Harrison, 1997). Although these
spillovers are an important source of information about unfamiliar foreign markets,
because they are localized, firms have limited access to spillovers in other countries and
may turn to the information spillovers of their home country competitors instead.
In a summary, competitors’ experience in a host country helps to reduce
uncertainty for firms deciding to enter a new market. Though distance increases the costs
and risks of entry, firms may use competitors’ experience to interpret the new
environment. In particular, firms may learn more from competitors from the same
country, because their experience is more relevant and accessible than that of competitors
from a third country. In other words, inexperienced firms may learn vicariously from
competitors of the same origin. Competitors’ experience may help to lower the costs and
risks of entering a distant new market.

21
H2: All else being equal, the negative relationship between institutional distance
and the number of entries from a home country is likely to decrease as the home country
has more entrants in the host country market.

2.3 Research Design
2.3.1 Data
To study foreign firms’ entry, I have chosen the empirical setting of the banking
industry of the United States for both theoretical and practical reasons. Theoretically, the
banking industry offers an appropriate setting to study the impact of institutional distance
on firms’ entry decisions. The U.S. banking industry is highly regulated and banks face
strong pressures to conform to the institutional environment (Scott and Meyer, 1991;
Deephouse, 1996; Miller and Eden, 2006). Banks are not only influenced by formal
regulations (Sponge, 1990), but must make an effort to obtain legitimacy as well
(Deephouse, 1996). Furthermore, foreign banks come from many different institutional
backgrounds, which offer rich variance in banking regulations, financial development
(Miller and Parkhe, 2002), cultures, and political systems. These conditions make the
banking industry an appropriate setting for this study.
The data archive of the U.S. banking industry keeps an almost complete record of
all foreign bank entries. The Federal Deposit Insurance Corporation (FDIC) collects data
on all foreign banks that have entered the United States. The complete records of 861
foreign banks from 69 countries from 1956 to 2006 allow me to track of the date of entry
and the home country of each entrant.

22
The FDIC creates a record for each new foreign bank that opens an office in the
United States. When a foreign bank first enters the United States, it may choose to build
the following institutions: agency, branch, subsidiary, representative office, New York
Investment Company (NYIC), or Edge and Agreement Corporation Subsidiary (Edge).
According to U.S. banking regulations, each institute operates differently and does
different banking business. However, a representative office can only work as a
communication channel between the parent bank and the U.S. banking industry. It is not
allowed to operate any “real” business. Because such an office does not make any
commitment to the host country and does not operate any substantial business, this study
holds that opening only a representative office does not count as bank entry. Instead, a
foreign bank has “entered” the U.S. only if it has built an office that is not a
representative office.
A foreign bank business unit in the United States may be owned by multiple
foreign banking institutions. For example, the New York subsidiary of the Mizrahi bank
(an Israel-based bank) is directly managed by Mizrahi bank and owned by both the
Mizrahi Holding Association and the United Mizrahi Overseas Holding Company B.V.
(registered in the Netherlands). The Mizrahi bank directly owns and manages its New
York subsidiary; the other two banking institutions are related to the subsidiary due to
their ownership structure. However, the FDIC records the aforementioned banking
institutions as different foreign banks. To eliminate the duplicate records, I ignored the
entries of the Mizrahi Holding Association and the United Mizrahi Overseas Holding
Company B.V. and only recorded the entry of the Mizrahi Bank.

23
The case of a foreign bank entering the United States may be the result of a merge
and acquisition of several banks with a footprint in the U.S. banking industry before the
acquisition. For example, the Bank of Tokyo entered the United Stated in 1956, as did the
Mitsubishi Bank in 1959. These two banks merged in 1995 and registered a new bank in
the United States in 2001: Mitsubishi Tokyo Financial Group. In this case, Mitsubishi
Tokyo Financial Group does not count as a new entrant.
Subtracting the multilevel ownership structure and merge and acquisition cases,
the dataset retains 650 foreign banks from 66 countries. However, FDIC does not report
all the ownership structural relationship among foreign banks. In addition, it does not
report the prior merger and acquisition situations of new foreign entrants. Therefore, this
study supplements the FDIC database with company profiles and the Bank Almanac
Yearbook to trace bank histories and ownership structures. However, there is no publicly
available information about 264 foreign banks in the United States. This results in a
sample of 386 foreign banks from 61 countries.
Finally, missing data of independent variables limits the size of this sample. For
example, this study uses Hofstede’s (2001) cultural index to measure the cultural distance
between two countries. However, Hofstede’s index does not provide information on
Bermuda and Bolivia. This study also bases the measure of regulatory distance on the
Banking Regulation Database (Barth, Caprio, and Levine, 2001a), which does not cover
the Dominican Republic, Iran, and Yugoslavia. Likewise, Panama was excluded from the
sample, because no historical information on its financial market was available for
calculating its economic distance. Finally, the Database of Political Institutions (Beck,

24
Clarke, Groff, Keefer, and Walsh, 2001; Keefer and Stasavage, 2003) is used to measure
political distance. This database does not cover Hong Kong, which is, therefore, not
included in the final sample. In summary, because of missing data of independent
variables, only 54 countries were included in the sample.
The sample only includes home countries from which banks have entered the
United States. In other words, there are no observations of home countries from which no
banks have entered the U.S. banking industry. Therefore, the sample does not represent
the whole population of home countries. Because the sample is selected with bias
(Greene, 2000), I have added all home countries with no banks in the U.S. to the sample.
When comparing the databases that are used to create the independent variables, only
seven countries (the Czech Republic, Ghana, Guatemala, Hungary, Kenya, Lebanon, and
Zambia) are fully represented in each database. Therefore, I added these countries to the
sample. The final sample includes 61 countries with banking institutions that did or did
not enter the United States from 1956 to 2006. Table 2.1 shows the results of a sample of
2,592 country–year observations.

25
Table 2.1: Foreign Bank Origins

Home Country Number of
Banks
Home Country Number of
banks
1. Argentina 7 31. Jordan 1
2. Australia 11 32. Kenya 0
3. Austria 4 33. Korea, South 13
4. Bahrain 3 34. Kuwait 3
5. Belgium 6 35. Lebanon 0
6. Brazil 19 36. Malaysia 2
7. Canada 13 37. Mexico 7
8. Chile 3 38. Netherlands 4
9. China 2 39. New Zealand 1
10. Colombia 5 40. Nigeria 1
11. Costa Rica 1 41. Norway 3
12. Czech 0 42. Pakistan 3
13. Denmark 7 43. Peru 1
14. Ecuador 3 44. Philippines 6
15. Egypt 2 45. Poland 1
16. El Salvador 1 46. Portugal 6
17. Finland 4 47. Qatar `1
18. France 18 48. Saudi Arabia 2
19. Germany 16 49. Singapore 5
20. Ghana 0 50. South Africa 1
21. Greece 2 51. Spain 17
22. Guatemala 0 52. Sweden 4
23. Hungary 0 53. Switzerland 9
24. India 3 54. Taiwan 15
25. Indonesia 12 55. Thailand 3
26. Ireland 3 56. Turkey 2
27. Israel 4 57. United Arab Emirate 4
28. Italy 14 58. United Kingdom 16
29. Jamaica 1 59. Uruguay 1
30. Japan 57 60. Venezuela 8
61. Zambia 0

26
2.3.2 Dependent Variable
To test the hypothesis, I compared the number of firm entries from each home
country in the same time period. To construct this dependent variable, I counted the
number of foreign banks in the United States from each home country every year from
1956 to 2006. The bank count begins at the year 1956, because the first operational
foreign bank office in the United States was established in 1956. Therefore, the
dependent variable BANK COUNT is the accumulated count of banks from each home
country that have entered the U.S. banking industry by time t.

2.3.3 Independent Variables: Institutional Distance
The main independent variable of interest to test hypothesis 1 is institutional
distance. Institutional distance is the extent of difference between two countries in terms
of institutional context, expressed in cultural, economic, political, and regulatory
dimensions. Cultural distance refers to the extent of similarity between the national
cultures of two countries. Economic distance captures differences in patterns of exchange,
market orientation, market stability, and the nature of economic organization across
countries. Political distance refers to differences in government. Regulatory distance
captures industry-specific differences in the way regulations are enacted and enforced
across countries. I measure each dimension of distance using established proxies.

27
2.3.3.1 Cultural Distance
Hofstede (2001) defined national culture as the “collective mental program” that
normalizes individual activities in a society. When a firm operates in a foreign country, it
becomes exposed to a new cultural environment, which may conflict with that of the
home country. Hofstede described the differences in national culture along five
dimensions: power distance, uncertainty avoidance, individualism and collectivism,
masculinity and femininity, and long-term orientation. Prior studies have used aggregated
differences across the dimensions to measure cultural distance (see Tihanyi, Griffith, and
Russell (2005)). However, a measure of long-term orientation was available for only a
small subset of countries. Following Kogut and Singh (1988), I measured the
CULTURAL DISTANCE between the parent firm’s home country and the United States
using only four dimensions: power distance, uncertainty avoidance,
individualism/collectivism, and masculinity/femininity.
2
This approach has been widely
adopted to measure cultural distance (e.g., Benito and Gripsrud, 1992; Li and Guisinger,
1991). The cultural distance measure is expressed as follows:
( ) [ ]
∑
=
− =
4
1
2
4 / /
j
j USj ij i
Var H H CD , (2.1)
where CD
i
represents the cultural distance between country i and the United States.
ij
H
captures cultural dimension j in country i ,
USj
H captures the cultural dimension j in the

2
Results did not change when the sample was limited to those countries for which all five cultural
dimensions were available.

28
United States, and Var
j
represents the overall variance on cultural dimension j across all
countries.

2.3.3.2 Economic Distance
Countries are not homogeneous in economic structure and market orientation.
Some countries are organized around private capital markets, while others allow banks to
play a larger role in markets. Miller and Parkhe (2002) described the former as “capital
market-oriented,” because firms generally rely on external capital markets to acquire
capital. The latter are “bank-oriented,” because they rely on a system of banks. As firms
build long-term relationships with a few banks in bank-oriented financial systems, they
may have more temporary ties with numerous shareholders in capital market-oriented
systems (Allen, 1993). Both systems can be an efficient source of external funding,
although they have different orientations. However, foreign banks may operate less
efficiently when the home country’s financial system differs markedly from that of the
host country (Miller and Parkhe, 2002). Therefore, this study uses financial market
orientation to measure ECONOMIC DISTANCE.
I measure market orientation using a ratio of market capitalization/GDP divided
by bank credits to private sector/GDP. This is a standard measure of financial market
orientation (Levine, 2002; Miller and Parkhe, 2002). The market capitalization, bank
credits, and GDP data come from the United Nations World Development Indicators
Database. ECONOMIC DISTANCE is defined as the absolute value of the difference
between a foreign firm’s home country orientation and U.S. orientation. A greater value

29
indicates greater differences between the home country’s financial market and that of the
U.S.

| )
/ Pr
/
/ Pr
/
( |
. . . .
. . . .
t S U t S U
t S U t S U
it it
it it
it
GDP Sector ivate to Credit Bank
GDP tion Capitaliza Market
GDP Sector ivate to Credit Bank
GDP tion Capitaliza Market
ED − =
(2.2)

2.3.3.3 Regulatory Distance
Although scholars have widely explored institutional environments, very few
studies have explicitly examined international differences in regulations (for a notable
exception, see Perkins, 2008). However, regulation is an important component of formal
institutions to normalize the activities of organizations (Scott, 1995). A comparison of
regulations across countries is especially important in this context, because banks operate
in a highly regulated industry. The banking industry has a greater level of regulation and
more laws governing firm behavior than most (Miller and Parkhe, 2002; Miller and Eden,
2006). Therefore, when foreign banks set up business units in the United States, they
potentially face a regulatory environment vastly different than the one that exists in their
home country. This difference may affect their operations in the U.S. To capture the
impact of the U.S. regulatory environment on foreign banks, I have created a regulatory
distance variable using the Banking Regulation Database (Barth et al., 2001a).
Barth et al. (2001a) collected comprehensive data on banking regulations in 107
countries. The authors measured the following dimensions of banking regulation: bank
activity regulations, banking/commerce mixing regulations, competition regulations,
capital regulations, official supervisory actions, official supervisory experience and

30
structure, private monitoring, deposit insurance schemes, and market structure. I have
used the bank activity regulations, banking/commerce mixing regulations, competition
regulations, and capital regulations dimensions to create the regulatory distance measure
for both practical and theoretical reasons. They focus on regulations that normalize bank
activities, ownership, competition, and strategy. The others (official supervisory actions,
official supervisory experience and structure, private monitoring, deposit insurance
schemes, and market structure) generally focus on the features of supervisory agencies
(e.g., the extent of their power and their level of expertise). Because I am interested in
how regulations shape the behavior of firms, the study adopts the regulation-related
dimensions.
The data collected by Barth et al. (2001a) are from 1998 to 2002. This study’s
data, by contrast, cover the activities of foreign banks in the United States between 1956
and 2006. Therefore, to be accurate in retrospectively applying the data from Barth et al.
(2001a), it is helpful to have relatively stable temporal dimensions. Because banking
regulations that normalize bank activities were relatively stable from the 1970s onward
(Barth, Caprio and Levine, 2001b), I chose to focus on these dimensions of regulation.
Although certainly far from ideal, this is a suitable approach that these authors
demonstrated in an earlier study, showing that banking regulations across countries did
not change significantly over time, even after serious banking crises (Barth, Caprio and
Levine, 2000). There is no report on the temporal stability of the supervision dimensions.
Thus, the measure given by Barth et al. is the best available measure of the regulatory
environment.

31
Finally, some dimensions are not available to the public, including several
indicators of supervision and deposit insurance schemes. Therefore, I am unable to
include these dimensions in the regulatory distance measure. The banking regulatory
distance measure used in this study includes only the following four dimensions: bank
activity regulations, banking/commerce mixing regulations, competition regulations, and
capital regulations. The REGULATORY DISTANCE variable is as follows:
4 / / ) (
4
1
2






− =
∑
= j
j USj ij i
Var R R RD (2.3)
where R
ij
refers to the jth regulatory dimension in country i, R
USj
captures to the jth
regulatory dimension in the United States, and Var
j
is the variance across all four
dimensions.
By construction, a greater value on this metric implies a greater regulatory
distance between the home country and the United States.

2.3.3.4 Political Distance
To operationalize political distance, this study uses the CHECKS index drawn
from the Database of Political Institutions (Beck et al., 2001; Keefer and Stasavage,
2003). The CHECKS index counts the number of veto players in a political system,
adjusting for political cohesiveness. With a greater number of veto players, more political
checks and balances are in place, and policies are less likely to change arbitrarily. In such
cases, the political environment is more predictable. With fewer constraints on politicians

32
(i.e., fewer players with veto power), the environment becomes less predictable. The
CHECKS index therefore captures the overall level of political volatility within a country.
As firms become accustomed to the political system in their home market, they
better understand the political environment and how it is likely to change, and they learn
how to operate effectively under such political conditions. When they enter politically
distant countries, it becomes more difficult for them to conduct business (e.g., Gaur and
Lu, 2007). I therefore have measured POLITICAL DISTANCE as the absolute value of
the difference in political volatility (as measured by the CHECKS index) between the
foreign firm’s home country and the United States. A greater value indicates greater
differences between the home country’s political environment and that of the U.S.
USt it i
CHECKS CHECKS PD − = (2.4)

2.3.4 Moderating Variable
2.3.4.1 Vicarious Experience
To measure the opportunity for foreign banks to learn from competitors, this
study uses a measure based on prior entries by banks from the same home country.
Though a bank could conceivably learn from nonbanking firms from its home country or
from third-country competitors in the host market, the potential to learn from these firms
is limited (Salomon and Martin, 2008). The experiences of these firms in the United
States are less relevant, because their experiences differ. A third-country competitor
encounters a different set of problems when entering the United States because it faces
different cultural, economic, political, and regulatory challenges. Similarly, routines and

33
regulations of the banking industry may not apply for nonbanking firms. Thus, insights
from nonbanking firms may not be as useful. Therefore, the experiences of comparable
organizations (from the same industry and home country) may prove more valuable to
foreign firms (Baum et al., 2000).
For this reason, I base the measure of vicarious learning on the experiences of
home country competitors operating in the United States. VICARIOUS EXPERIENCE is
defined as the number of banks from the same home country in the United States by time
t. This measure of vicarious experience has been widely adopted by prior studies on
foreign entrants (e.g., Chang and Park, 2005; Chung and Song, 2004).
However, the organizational learning theory predicts that organizations may
discard experience as it becomes obsolete (Huber, 1991). If banks do discard obsolete
vicarious experience, the measure above may over-estimate the effect of dated bank
experiences. Therefore, I adopt a second measure of vicarious learning, which is the
count of bank entries made in the last 5 years (from time t-5 to time t-1). I refer to this
measure as 5-YEAR VICARIOUS EXPERIENCE.
3

2.3.5 Control Variables
I control for home and host country characteristics that may influence the market
entry decision of foreign banks. First, I control for GDP of the home country at time t.
International banking literature shows that foreign banks are likely to have more activities
in a host country if the home country has a larger financial market (Grosse and Goldberg,

3
I use alternative experience measures, such as the count of bank entries in the last 3 years and the count of
bank entries in the last 10 years. The main results are similar to what presented in Table 4.

34
1999). To capture the size of the home country market, I use GDP, expressed in USD
10
11
. GDP data come from the World Bank Worldwide Development Indicators. The
growth of home country GDP is also likely to influence the performance and strategy of
foreign banks (Miller and Eden, 2006). A fast-growing market may attract banks to make
more investments in their home countries instead of in a host country. Therefore, I
control for the GDP GROWTH RATE of each country at time t.
Second, I control for the level of wealth of the home country. Scholars have
pointed out that level of wealth is positively correlated with financial sector development
of a country (Rajan and Zingales, 1998). Foreign banks from a more developed home
market operate more efficiently than competitors from weaker financial industries (Miller
and Parkhe, 2002). Banks from more developed home markets are more likely to enter
new foreign markets. Therefore, I control for GDP PER CAPITA, expressed in USD 10
4
,
at time t. As a measure of income per person, GDP per capita is a correlate of financial
sector development.
Third, foreign banks often follow their clients into a host country in order to
provide financial services to these clients in the new location (White, 1982; Aliber, 1984).
Consistent with this argument, prior empirical studies have shown that more foreign
banks enter the United States as foreign investments from their home countries increase
(Grosse and Goldberg, 1991). In addition, foreign banks are more active in the United
States as the bilateral trade between their home countries and the U.S. increases. To
control for this factor, I include three variables: FDI (expressed in USD 10
12
), TRADE
FLOW (expressed in USD 10
12
) and IMMIGRATION (expressed in 10
6
of immigrants).

35
FDI is the total foreign investment from the home country in the U.S. by time t. The FDI
data are drawn from the U.S. Bureau of Economic Analysis. Trade is the sum of imports
and exports between the U.S. and the home country at time t. The data come from the
United Nation Comtrade Database. Immigration is the count of immigrants from the
foreign bank’s home country into the United States in a given year. These data come
from the U.S. Census Bureau.
Fourth, I controls for the average FOREIGN EXCHANGE RATES of the U.S.
dollar to the currency of the home country in a given year. Foreign exchange rates affect
trade and foreign direct investment between two countries (Goldberg and Klein, 1997).
They also impact the relative wealth across countries (Klein and Rosengren, 1992).
Foreign exchange rates are also associated with other macroeconomic variables such as
inflation rates, interest rates, and international payments balances (Isard, 1995). Therefore,
foreign exchange rates may affect the entry decisions of foreign banks. The average rate
is measured by the annual average value of foreign exchange rates, which is expressed as
the ratio of x*10
6
units of home country currency to one U.S. dollar.
Finally, I control for the BANK LIQUID RESERVE RATIO of each home country.
Because deposit withdrawals are not perfectly predictable, banks are required by
regulators to reserve a certain level of liquid assets to ensure their safety. An insufficient
reserve may result in a high risk of bankruptcy. By contrast, an overabundant reserve may
cause low interest income, because the reserve has not been invested profitably (Koch
and MacDonald, 2006). Therefore, banks with a high level of liquid reserve may be less
profitable and more risk-averse than those with a low level, and they may be more

36
hesitant to enter a new market. The bank liquid reserve ratio equals the average rate of
bank liquid reserve divided by total assets in a home country at time t.
In addition to home country conditions, I control for several characteristics of the
U.S. banking industry. First, the size of the U.S. financial market provides an incentive
for foreign banks to enter (Terrell and Key, 1977). A larger market provides more
opportunities for foreign banks to make investments and profits. Prior studies have found
that the presence of foreign banks in the United States increased as the U.S. financial
market grew (Goldberg and Saunders, 1981). To control for the U.S. market size, I
include a variable of U.S. DEPOSITS, expressed in USD 10
9
, equal to the total deposits
provided by all banks in the United States at time t. The study draws the data from the
FDIC.
Second, I control for the profitability of the U.S. banking industry. All things
being equal, an industry with a higher rate of return is more likely to attract new entrants
and new investments (Porter, 1980). As the U.S. banking industry becomes more
profitable, it encourages more foreign banks to enter the industry. Therefore, I control for
the return on asset (ROA) of the U.S. banking industry, equal to the average ROA of all
banks operating in the United States at time t. This variable is labeled as U.S. BANK ROA.
The data source is the FDIC.
Finally, I control for the number of new banks entering the U.S. market each year.
It is likely that some unobserved factors of the U.S. banking industry may encourage or
discourage new entrants. To control for the impact of unobserved factors, the study

37
includes a control variable of U.S. NEW BANKS, which is the count of new banks that
entered the U.S. market at time t. The data source is the FDIC.

2.3.6 Statistical Method
Prior research on foreign firm entry decisions has used the survival analysis
model to study market entry decision or entry sequence at the level of individual firms
(e.g., Chang, 1995; Gaba, Pan, and Ungson, 2002; Guillen, 2003). This statistical method
allows researchers to investigate how various factors impact the market entry decisions of
individual firms. However, the survival analysis approach may not generate unbiased
estimates for this study. In order to estimate the impact of institutional distance on
individual bank entry decisions, the sample should appropriately represent all foreign
banks regardless of their status in the United States. In other words, the sample should
include the banks that have operational offices in the United States and banks that have
never entered the U.S. market. Unfortunately, there is no dataset that systematically
records the activities of all foreign banks over time. Without the observations of banks
that have never entered the U.S. market, the survival analysis model would produce
biased results for the individual bank-level study.
Therefore, I do not study foreign bank entries at the individual bank level. Instead,
this study focuses on the level of each home country. The country-level analysis allows
me to identify the countries that have not entered the United States. By incorporating
these countries, the sample does not suffer from selection bias, as would an individual
bank sample (Greene, 2000). In addition, a country-level study is consistent with the

38
tradition of international business studies. For example, Nachum and Zaheer (2005)
studied the FDI flows between the U.S. and other countries to examine the impact of
distance on different types of foreign investments. Anand and Kogut (1997) used a
negative binomial model to analyze the count of foreign firm entries into the U.S.
Following this tradition, this study focuses on country-level analysis.
In selecting an appropriate regression model to test the hypothesis, I first specify
the number of foreign bank entries from a home country (NBE) as a linear function (OLS)
of the independent variables.
NBE
it
= β
0
+ DIS
it
β
1
+ Z
it
β
2
+ μ
it
(2.5)
where DIS is a matrix of institutional distance variables, Z is a matrix of controls, and
it
μ
is the error term.
However, OLS may not be appropriate to test the hypothesis. First, the dependent
variable is typical of count data. That is, the numerical values of this variable are non-
negative integers. Although the linear regression can be applied to count data, it may not
be most efficient to analyze the data with all discrete values and many zeros (Greene,
2000).
Compared to linear regressions, the Poisson regression model is more efficient to
analyze count data (Kennedy, 1998). This model is commonly used to study count data in
strategy research, such the founding rates of organizations (e.g., Mezias and Mezias,
2000), market entries (e.g., Swaminathan, 1998), and FDI entries (e.g., Kogut and Chang,
1991). Therefore, I use the Poisson regression model instead of OLS to study foreign

39
bank entries. In the Poisson model, the probability of the event count is expressed by the
following equation:
Pr (NBE
it
= y) = exp (-λ
it
) λ
it
y
/ y ! (2.6)
where λ is the rate at which foreign banks enter the U.S.
λ is specified as follows:
ln λ = β
0
+ DIS
it
β
1
+ Z
it
β
2
+ μ
it
(2.7)
Although the Poisson regression model efficiently treats the non-negative integer
dependent variable problem, another problem remains. The sample is composed of
foreign bank entries by home country and year, and there are multiple observations of the
same home country over time. Given the feature of panel data, it is unlikely that the μ
it
in
equation 2.7 is independent across time or within firms (Greene, 2000). There are many
possible time-dependent factors associated with foreign bank entries. Because I may not
have identified all of these time-dependent effects, there exists the potential for a
systematic component to be embedded in
it
μ . Conceptually, I can decompose
it
μ into a
vector of systematic (fixed) time effects, labeled F
t
, plus a truly random error component,
labeled e
it
. In this case, F
t
represents time dummies. After extracting F
t
from
it
μ , I can
more confidently assume that e
it
is i.i.d. normal with zero mean.
ln λ = β
0
+ DIS
it
β
1
+ Z
it
β
2
+ F
t
+ e
it
(2.8)
However, because there are multiple observations per country, the possibility still
exists that e
it
in equation 2.8 will not be independent within banks over time. This would
occur if some countries systematically encouraged or discouraged banks to enter foreign

40
markets for reasons unobserved by this author. To solve this problem, e
it
is decomposed
into two parts: country effects (γ
i
) and the random error term. In theory, either a fixed or
random effects model can be used to correct for heterogeneity (Greene 2000). However,
for this study, it is not possible to estimate fixed effects, which perfectly correlate with
the time-invariant distance measures (such as cultural distance). Under this condition, a
random effects model is preferable (Kennedy 1998). Therefore, I arrive at the final
econometric specification:
ln λ = β
0
+ DIS
it
β
1
+ Z
it
β
2
+ F
t
+ γ
i
+ e
it
(2.9)
The Poisson model assumes that the mean of dependent variable equals its
variation (Greene, 2000). This strict assumption may not fit the sample, which may lead
to a problem of overdispersion (Kennedy, 1998). An alternative method that relaxes this
assumption is the negative binomial regression (Greene, 2000). However, when
analyzing panel data with random effects, the Poisson model and the negative binomial
model produce estimates by the same approach (Greene, 2000). Therefore, I use the
Poisson model with random effects to analyze this sample.
4

2.4 Results
Table 2.2 presents descriptive statistics and product moment correlations.
Although the correlations are generally as expected, some correlations among the
distance variables are elevated, hinting at a potential multicolinearity concern. However,

4
As a robustness check, I have run the negative binomial model with random country effects. The results
are the same as what is presented in Tables 3 and 4.

41
influence tests do not suggest multicollinearity. The maximum VIF score is 2.20, and the
mean VIF is 1.51, well below the suggested threshold (Belsley, Kuh, and Welsch, 1980).

42

Table 2.2: Correlations

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16. 17. 18.
1. Bank count 1.00
2. GDP 0.85 1.00
3. GDP growth rate -0.12 -0.08 1.00
4. GDP per capita 0.43 0.40 -0.13 1.00
5. FDI 0.55 0.59 -0.10 0.42 1.00
6. Trade flow 0.53 0.54 -0.04 0.27 0.50 1.00
7. Immigration 0.11 0.17 -0.02 -0.03 0.07 0.47 1.00
8. Foreign exchange rate -0.01 0.01 0.02 -0.03 -0.02 -0.01 -0.01 1.00
9. Bank liquid reserve ratio -0.22 -0.21 0.01 -0.38 -0.20 -0.14 -0.03 -0.01 1.00
10. U.S. deposit 0.34 0.16 -0.08 0.21 0.24 0.31 0.14 0.10 -0.15 1.00
11. U.S. bank ROA 0.16 0.10 -0.01 0.13 0.19 0.22 0.11 0.08 -0.14 0.64 1.00
12. U.S. new banks -0.04 -0.03 -0.10 -0.01 -0.07 -0.07 -0.04 -0.03 0.09 -0.18 -0.38 1.00
13. Cultural distance -0.15 -0.21 0.12 -0.41 -0.27 -0.14 -0.03 0.01 0.27 -0.00 -0.00 -0.00 1.00
14. Economic distance -0.09 -0.04 -0.08 0.05 -0.13 -0.15 -0.07 -0.07 0.15 -0.30 -0.47 0.29 0.05 1.00
15. Regulatory distance -0.00 0.06 -0.13 0.27 0.15 -0.05 -0.04 -0.02 -0.17 -0.08 -0.05 0.02 -0.44 0.00 1.00
16. Political distance -0.14 -0.16 0.09 -0.22 -0.17 -0.10 -0.06 0.00 0.22 -0.07 -0.16 0.13 0.20 0.07 -0.15 1.00
17. Vicarious experience 0.99 0.84 -0.12 0.43 0.55 0.53 0.11 -0.01 -0.22 0.35 0.18 -0.05 -0.15 -0.11 -0.00 -0.14 1.00
18. 5-Year Vicarious experience 0.52 0.44 -0.09 0.20 0.11 0.16 0.02 -0.01 -0.11 -0.00 -0.15 0.18 -0.08 0.14 0.00 -0.02 0.51 1.00
Mean 3.29 2.38

4.24 0.92 0.01 0.01 0.25 0.04 11.46 2.21 0.008 2.30 1.22 1.73 1.80 20.14 3.15 0.67
Standard Deviation 6.23 5.19 4.49 0.93 0.03 0.04 0.80 0.71 12.97 1.73 0.003 1.28 0.73 1.53 1.43 51.76 6.11 1.92
Minimum 0.00 0.01 -42.45 0.01 0.00 0.00 0.00 0.00 -7.88 0.20 0.001 0.02 0.00 0.16 0.00 0.00 0.00 0.00
Maximum 57.00 50.90 38.20 5.92 0.41 0.54 14.50 1.51 135.80 6.73 0.013 6.32 7.50 7.96 13.00 358.00 57.00 29.00

43
Table 2.3 presents the multivariate regression results meant to test hypothesis 1.
Column 1 consists of the base model of controls. Results suggest that more foreign banks
enter the United States as the market size of their home country increases. However,
when the home country market expands, foreign banks are less likely to enter the U.S.
market. Marginally, foreign banks from richer home countries enter the U.S. market more
often. By contrast, the stock of foreign direct investment and the amount of bilateral trade
are negatively associated with foreign bank entries, which is contrary to prediction.
Moreover, to a marginal degree, foreign banks are more likely to enter the U.S. as home
country currency depreciates. In addition, the number of foreign banks in the U.S. is
negatively associated with the level of liquid reserve in the home country, as expected.
The features of the U.S. banking industry also affect foreign bank entry decisions.
According to the results, foreign banks are more attracted when the size of the U.S.
financial market increases. The profitability of the banking industry also has a positive
impact on foreign bank entries. Finally, the trend of foreign bank entry is consistent with
the trend of overall new bank entries in the industry.
Columns 2 through 5 of Table 2.3 introduce the institutional distance variables
meant to test hypothesis 1. The negative and significant coefficient on cultural distance
from column 2 indicates that foreign banks are more likely to enter the U.S. market as the
cultural distance between home country and the United States decreases. By contrast, the
results from column 3 do not demonstrate a link between the economic distance and the
number of foreign entrants. Column 4 introduces the banking regulatory distance measure.

44
Table 2.3: Regress Results-H1
DV: Bank count 1. 2. 3. 4. 5. 6.
Constant 0.43** 0.98*** 0.40** 0.49** 0.45** 1.07***
(2.12) (2.63) (1.91) (2.37) (2.20) (2.82)
GDP 0.02*** 0.03*** 0.02*** 0.03*** 0.03*** 0.03**
(4.41) (4.54) (4.41) (4.65) (4.50) (4.90)
GDP growth rate -0.01*** -0.01*** -0.01*** -0.01*** -0.01*** -0.01***
(-3.81) (-3.83) (-3.72) (-3.83) (-3.68) (-3.65)
GDP per capita 0.01* 0.01 0.01* 0.01* 0.01* 0.01
(1.31) (1.25) (1.37) (1.30) (1.56) (1.02)
FDI -1.68*** -1.70*** -1.70*** -1.81*** -1.69*** -1.86***
(-3.83) (-3.87) (-3.87) (-4.05) (-3.84) (-4.16)
Trade flow -2.04*** -2.05*** -2.03*** -2.09*** -2.00*** -2.06***
(-4.94) (-4.96) (-4.91) (-5.06) (-4.86) (-4.96)
Immigration 0.03 0.03 0.03 0.03 0.02 0.02
(1.15) (1.14) (1.20) (1.12) (1.01) (0.99)
Foreign exchange rate 0.34* 0.33* 0.35* 0.34* 0.34* 0.34*
(1.31) (1.30) (1.37) (1.31) (1.31) (1.33)
Bank liquid reserve ratio -0.003* -0.003 -0.003* -0.003* -0.003* -0.003
(-1.30) (-1.22) (-1.33) (-1.32) (-1.31) (-1.27)
U.S. deposit 0.09*** 0.10*** 0.09*** 0.09*** 0.09*** 0.09***
(6.01) (6.07) (5.92) (5.98) (5.86) (5.82)
U.S. bank ROA 36.31*** 36.45*** 38.76*** 36.60*** 35.97*** 38.41***
(5.53) (5.55) (5.65) (5.57) (5.47) (5.59)
U.S. new banks 0.002*** 0.002*** 0.002*** 0.002*** 0.002*** 0.002***
(9.08) (9.07) (9.14) (9.12) (9.22) (9.31)
Cultural distance -0.25** -0.27**
(-1.88) (-2.03)
Economic distance 0.04 0.03
(1.25) (1.01)
Regulatory distance -0.03** -0.03**
(-1.86) (-1.94)
Political distance -0.02** -0.02**
(-1.81) (-1.88)
Bank effect YES YES YES YES YES YES
Time effect YES YES YES YES YES YES
N 2592 2592 2592 2592 2592 2592
Log likelihood -3206.95
(12)
-3205.15
(13)
-3206.17
(13)
-3205.22
(13)
-3205.27
(13)
-3200.79
(16)

Note: p-values: * p < .1; ** p < .05; *** p < .01 (one-tailed tests)
t-statistics are in parentheses

45
Similar to the findings for cultural distance, the results suggest that foreign banks from
markets that have dissimilar regulations to the U.S. rules are less likely to enter the U.S.
market. Likewise, the results from column 5 demonstrate a negative link between
political distance and foreign bank entries. Column 6 presents the full specifications. The
direction and significance of coefficients are similar to the results in columns 1-5. In
general, the results presented are supportive of hypothesis 1. That is, foreign banks are
less likely to enter the United States as the cultural, regulatory, and political distance
between a bank’s home country and the United States increases.
Table 2.4 shows a test of the moderating impact of vicarious experience of all past
bank entries from a home country on foreign bank entry at time t. Given the substantial
correlations among interaction terms (Jaccard, Turrisi, and Wan, 1990), I introduce the
distance/experience interactions individually. Column 1 presents results on the main
effect of competitors’ experience. Consistent with prior studies, foreign banks are more
likely to enter the United States as more banks from the same home country enter the U.S.
Columns 2–5 present the models testing the moderating impact of vicarious experience
and each of the institutional distance variables. Except for the interaction of cultural
distance and vicarious experience, each of the interaction terms has a significant positive
impact on foreign bank entries. Column 6 presents the full model. The direction and
significance of coefficients are similar to the results in column 1–5. In general,
hypothesis 2 receives support. That is, the negative impact of institutional distance on
foreign firm entry is moderated by the host country’s experience of competitors from the
same home country.

46
Table 2.4: Regress Results-H2 (All Past Entries)
DV: Bank count 1. 2. 3. 4. 5. 6.
Constant 1.54*** 1.61*** 1.55*** 1.53*** 1.54*** 1.80***
(3.43) (3.50) (3.54) (3.50) (3.48) (4.10)
GDP -0.06*** -0.06*** -0.06*** -0.06*** -0.06*** -0.06**
(-6.84) (-6.81) (-6.19) (-6.38) (-6.52) (-5.93)
GDP growth rate -0.01** -0.01** -0.01** -0.01** -0.01** -0.08**
(-2.28) (-2.27) (-2.13) (-2.32) (-2.26) (-2.14)
GDP per capita 0.002 0.002 0.005 0.002 0.002 0.001
(0.34) (0.38) (0.08) (0.32) (0.31) (0.17)
FDI -0.85** -0.74** -0.60* -0.97** -0.82** -0.40
(-1.87) (-1.57) (-1.30) (-2.12) (-1.80) (-0.83)
Trade flow -1.77*** -1.74*** -1.72*** -1.69*** -1.78*** -1.50***
(-4.25) (-4.19) (-4.15) (-4.04) (-4.28) (-3.57)
Immigration 0.04* 0.03* 0.03* 0.04* 0.03* 0.02
(1.58) (1.47) (1.35) (1.60) (1.48) (0.98)
Foreign exchange rate 0.37* 0.37* 0.33* 0.39* 0.37* 0.35*
(1.44) (1.43) (1.28) (1.50) (1.42) (1.35)
Bank liquid reserve ratio -0.004** -0.004** -0.004** -0.004** -0.004** -0.004**
(-1.71) (-1.76) (-1.62) (-1.74) (-1.63) (-1.80)
U.S. deposit 0.11*** 0.11*** 0.11*** 0.11*** 0.11*** 0.10***
(6.96) (6.99) (6.46) (6.47) (6.79) (5.78)
U.S. bank ROA 23.68*** 23.96*** 24.67*** 23.27*** 23.68*** 24.96***
(3.40) (3.44) (3.53) (3.34) (3.40) (3.57)
U.S. new banks 0.002*** 0.002*** 0.002*** 0.002*** 0.002*** 0.002***
(7.76) (7.79) (8.04) (7.49) (7.90) (8.07)
Cultural distance -0.31** -0.34** -0.31** -0.30** -0.31** -0.38***
(-1.88) (-1.99) (-1.92) (-1.89) (-1.90) (-2.39)
Economic distance 0.03 0.03 -0.02 0.03 0.03 -0.01
(0.95) (0.92) (0.50) (1.14) (0.96) (-0.37)
Regulatory distance -0.03** -0.03** -0.02* -0.07*** -0.03** -0.09***
(-1.92) (-1.96) (-1.37) (-2.98) (-1.89) (-3.49)
Political distance -0.01* -0.01* -0.02** -0.01** -0.03** -0.02**
(-1.53) (-1.50) (-2.05) (-1.35) (-2.15) (-1.70)
Vicarious Experience 0.05*** 0.04*** 0.04*** 0.05*** 0.05*** 0.01
(12.03) (4.48) (8.28) (10.95) (11.05) (0.86)
Cultural distance* 0.003 0.01***
Vicarious experience (0.83) (2.52)
Economic distance* 0.01*** 0.01***
Vicarious experience (2.72) (2.79)
Regulatory distance* 0.004** 0.01***
Vicarious experience (2.30) (3.40)
Political distance* 0.001* 0.00
Vicarious experience (1.55) (0.65)
Bank effect YES YES YES YES YES YES
Time effect YES YES YES YES YES YES
N 2592 2592 2592 2592 2592 2592
Log likelihood -3126.38
(17)
-3126.04
(18)
-3122.68
(18)
-3123.70
(18)
-3205.27
(18)
-3116.08
(21)

47
Table 2.5 summarizes a test of the moderating effect of vicarious experience
measured by the recent 5-year bank entries. As mentioned above, I introduce the
distance/interactions individually. Column 1 adds the vicarious experience variable,
measured as the number of entries in the past 5 years. Consistent with theory, foreign
banks are more likely to enter the U.S. as more banks from the same home country have
entered the same market recently. Column 2-5 introduces each interaction separately.
Contrary to expectation, the interaction of cultural distance and vicarious experience has
a negative impact on bank entries. By contrast, all the other interactions have a positive
and significant coefficient, consistent with hypothesis 2. Column 6 presents the full
model. Cultural interaction and economic interaction are not significant. However, the
coefficients of the other two interaction terms are similar to the results presented in
column 4 and 5. In general, the results in table 2.5 are consistent with those in table 2.4.
Hypothesis 2 receives partial support when I focus on the recent vicarious experience.

48
Table 2.5: Regress Results-H2 (Last 5-Year Entries)
DV: Bank count 1. 2. 3. 4. 5. 6.
Constant 1.18*** 1.15*** 1.18*** 1.24*** 1.20*** 1.26***
(3.14) (3.01) (3.15) (3.27) (3.20) (3.30)
GDP 0.03*** 0.03*** 0.03*** 0.03*** 0.03*** 0.03***
(5.23) (4.34) (5.54) (4.55) (5.16) (4.26)
GDP growth rate -0.01** -0.01** -0.01*** -0.01** -0.01** -0.01**
(-3.24) (-3.10) (-3.13) (-3.04) (-3.24) (-3.01)
GDP per capita -0.01 0.01 -0.07 -0.07 -0.01 0.001
(-0.14) (0.20) (-0.12) (-0.01) (-0.19) (0.02)
FDI -1.41*** -1.04** -1.53*** -0.94** -1.40*** -0.93**
(-3.18) (-2.33) (-2.40) (-2.10) (-3.16) (-2.04)
Trade flow -2.11*** -2.04*** -2.09*** -2.18*** -2.13*** -2.16***
(-5.16) (-5.04) (-5.10) (-5.33) (-5.19) (-5.25)
Immigration 0.02 0.01 0.02 0.02 0.02 0.01
(0.77) (0.45) (0.67) (0.70) (0.73) (0.52)
Foreign exchange rate 0.30 0.30 0.29 0.30 0.30 0.30
(1.18) (1.17) (1.13) (1.17) (1.17) (1.15)
Bank liquid reserve ratio -0.001 -0.002 -0.004 -0.004 -0.001 -0.004
(-0.58) (-0.82) (-0.58) (-0.64) (-0.50) (-0.60)
U.S. deposit 0.09*** 0.08*** 0.09*** 0.08*** 0.09*** 0.08***
(5.75) (5.09) (5.66) (5.24) (5.69) (4.99)
U.S. bank ROA 36.34*** 37.58*** 36.84*** 36.02*** 36.13*** 36.22***
(5.28) (5.46) (5.35) (5.23) (5.25) (5.24)
U.S. new banks 0.002*** 0.002*** 0.002*** 0.002*** 0.002*** 0.002***
(9.59) (8.65) (9.52) (8.69) (9.72) (8.73)
Cultural distance -0.29** -0.25** -0.29** -0.28** -0.29** -0.27**
(-2.17) (-1.86) (-2.17) (-2.06) (-2.16) (-1.98)
Economic distance 0.04 0.04* 0.02 0.03 0.04 0.03
(1.25) (1.29) (0.64) (1.01) (1.24) (0.86)
Regulatory distance -0.03* -0.02* -0.02* -0.04** -0.02* -0.03**
(-1.43) (-1.42) (-1.56) (-2.16) (-1.43) (-2.03)
Political distance -0.03*** -0.03*** -0.03*** -0.03*** -0.04*** -0.04***
(-3.03) (-2.72) (-3.18) (-2.86) (-3.56) (-3.83)
Vicarious experience 5-year 0.02*** 0.08*** -0.00 0.01*** 0.02*** 0.02
(8.04) (6.94) (-0.09) (4.18) (4.84) (0.90)
Cultural distance* -0.02*** -0.01
Vicarious experience 5-year (-5.06) (-1.02)
Economic distance* 0.02** 0.005
Vicarious experience 5-year (1.99) (0.54)
Regulatory distance* 0.01*** 0.01***
Vicarious experience 5-year (6.01) (2.96)
Political distance* 0.002** 0.003***
Vicarious experience 5-year (1.96) (2.77)
Bank effect YES YES YES YES YES YES
Time effect YES YES YES YES YES YES
N 2592 2592 2592 2592 2592 2592
Log likelihood -3169.73
(17)
-3157.26
(18)
-3167.75
(18)
-3152.97
(18)
-3167.86
(18)
-3148.63
(21)

49
2.5 Discussions
International business research has long stated that foreign firms are at a
disadvantage when competing with the domestic firms in a host country. This
disadvantage, the liability of foreignness, arises from lack of knowledge of the local
market and lack of legitimacy in the local environment (Zaheer, 1995). Furthermore,
knowledge deficiency and legitimacy problems are associated with the institutional
distance between home and host countries (Johanson and Vahlne, 1977; Kostova and
Zaheer, 1999). That is, as the home and host countries are more dissimilar in terms of
their institutional contexts, it is likely that firms from the home country experience
greater difficulty of acquiring knowledge of the local market and building roots in the
local environment. Therefore, prior studies have suggested that foreign firms are less
likely to enter a more distant country (Johanson and Vahlne, 1977; Benito and Gripsrud,
1992).
Most prior studies that empirically test the above assertion focus on only one
aspect of the institutional environment: national culture (Dow and Karunaratna, 2006).
However, institutional environments are composed of both formal and informal
institutions and are not limited to national culture. It is likely that cultural distance alone
does not fully represent the difference in institutional contexts across countries.
To better understand the impact of institutional distance, I have examined the
relationship between institutional distance and foreign firm entries using a
multidimensional measure of institutional distance. Based on a sample of 61 home
countries, I examined the foreign banks that entered the U.S. banking industry from 1956

50
to 2006. The results showed that the number of foreign entrants from a home country was
negatively associated with the institutional distance in terms of culture, industrial
regulations, and political system. This finding was consistent with prior studies on the
liability of foreignness.
Based on this finding, I calculate the marginal effects of institutional distance and
report the results in table 2.6. Column 1 represents the marginal effect of institutional
distance variables. Column 2 reports the percentage change to the predicted value of the
dependent variable if any of institutional variable increases by 1 standard deviation while
all other independent variables are at their mean. According to the results, the number of
bank entries from a home country would decrease by 254.13% if the cultural distance
between this country and the United States increases by 1 standard deviation. Likewise,
bank entries will decrease by 21.65% and 12.69% if the regulatory and political distance
increases respectively. The results suggest that cultural distance is most influential in
foreign bank entry decisions compared to the other institutional distances.

Table 2.6: Marginal Effects of Institutional Distance

DV=Bank Count 1. dy/dx 2. dx=std.dev
Cultural distance -0.27** -254.31%
(-2.03)
Economic distance 0.03 14.50%
(1.01)
Regulatory distance -0.03** -21.65%
(-1.94)
Political distance -0.02*** -12.69%
(-1.88)

51
Furthermore, vicarious experience reduced the negative impact of institutional
distance between the home and host countries. Both the experience of all past bank
entries and the experience of recent entrants helped to moderate the impact of regulatory
distance and political distance. However, neither type of vicarious experience was an
effective solution to cultural distance. This finding suggested that foreign firms do not
overcome all barriers of institutional distance by learning from others. Johanson and
Vahlne (1977) argue that firms can overcome psychic distance, i.e. the difference in
cultures and values, only by accumulating their own operational experience in the local
market. The finding of this study was consistent with this argument. However, this
finding should be read with caution. As a country-level test, this study does not identify
individual bank’s decision to enter the U.S. market. In addition, the measures of vicarious
experience do not reflect the actual learning process that may occur within each bank.
Therefore, the findings on the moderating effect of vicarious experience may be the result
of a trend in which banks enter the U.S. regardless of institutional distance. In other
words, the test on vicarious experience may only capture the dynamic of bank entries,
instead of the real learning process.
Taken as a whole, this suggests that the difference in institutional environments
results in market entry barriers; however, vicarious learning helps to overcome a part of
these barriers.
This study makes several contributions to international business literature. First, it
complements prior studies on institutional distance and foreign firm entries. Most studies
of the distance between countries adopt one measure: cultural distance. The results of

52
those studies do not always show a negative impact of cultural distance on foreign firm
entries (Shenkar, 2001). Built on prior studies, this research incorporates multiple
dimensions of institutional distance. The findings suggest that other dimensions of
institutional distance (such as the distance in industrial regulations and political systems)
impact foreign firm entries. Therefore, exclusion of other dimensions of institutional
contexts may result in less comprehensive conclusions in studies of institutions across
countries.
Second, this study shows that institutional distance may not affect all foreign
firms in the same way. Although foreign firms have no experience in the local
environment, they may learn from the experiences of prior entrants. Through vicarious
learning, foreign firms may be able to overcome the barriers arising from institutional
distance. Given this result, future research to explore the strategy that foreign entrants
adopt to offset the impact of entry barriers would be valuable.
Third, this paper provides an example of a country-level empirical study of
foreign firm entries. It complements prior firm-level studies on decisions of market entry.
Consistent with the institutional theory, it shows the role of institutional distance as a
barrier to foreign market entry at the country level.
This study leads to many questions for future research on foreign firms’ entry
decisions. For example, because firms face barriers of institutional distance, it is likely
that managers use a variety of strategies to reduce negative affects. These strategies may
include choice of entry mode, choice of local partners, choice of level of commitment,
choice of location, political strategies, social networks, knowledge transfer, and more.

53
Questions about the relationships among country-level entry barriers, firm-level
organizational capabilities, and entry strategies are worth investigating. Moreover, it is
challenging to study the strategies adopted by foreign firms after they have established a
business in the host country. Examination of post-entry strategy and performance with
regard to foreign firm operations will lead to fruitful research.

2.6 Limitations
This essay has a few limitations. First, as mentioned above, it only looks into the
cultural, economic, regulatory, and political dimensions of institutional distance.
However, institutional distance is composed of the similarities and differences between
two contexts in terms of formal and informal institutions. The dimensions discussed in
this paper are only a part of two countries’ formal and informal institutions. In addition,
this study employs one proxy for one dimension, while arguably, many other proxies are
representative of each dimension as well.
Second, the sample of foreign banks entering the United States is biased. Ideally,
a sample for this study would include all host countries as well as home countries. Other
host countries may vary in their unique features and differ from the conditions of the
United States. Such a sample would represent the population of banks and countries in a
better way. However, the sample of this study represents only one host country: the
United States. I cannot rule out the possibility that banks enter the United States with a
specific purpose that is different from their purpose for entering other markets. Therefore,
the results drawn from this sample cannot be generalized to the global banking industry.

54
Third, the sample of home countries is limited. There are over 190 countries in the
world (United Nation, 2009). However, this sample includes only 61 because of data
limitation. Bounded by the data availability of distance measures, this study includes only
7 home countries with 0 bank entry in the United States, while the population of 0-entry
home countries is about 150 countries. As a result, this sample under-represents those 0-
entry home countries. More corroboratory study would be necessary before we generalize
the conclusions of this study.
Third, the banking industry is in a special setting. It is not only highly regulated,
but also places great pressure on banks to comply with the institutional requirements
(Deephouse, 1996; Scott and Meyer, 1991). It is crucial for banks to follow regulations
and to comply with social expectations (Deephouse, 1996). Because of their unique
settings, banks may be more sensitive to institutional distance than other firms.
Therefore, the generalizability of the results of this study is questionable.
Fourth, it is impossible for any foreign bank to enter the U.S. banking industry
until both the United States and the home country allow the home country bank to open a
business unit in the United States barrier-free. Therefore, in an ideal case, I would
compare the number of entrants from different home countries based on the time of
becoming barrier-free. However, there is no systematic information on this time.
Moreover, it is also likely that this barrier is associated with institutional distance; that is,
the barrier may dissolve earlier for home countries that institutionally resemble the U.S.
and share more institutional ties with the U.S. than countries that do not. This study does

55
not treat the problem of the potentially endogenous entry barriers between the U.S. and
home countries.
The aforementioned limitations notwithstanding, this study provides important
insights for international business literature. It shows that the impact of institutional
distance on foreign firm entries depends on the specific dimension of institutional
distance. According to the results, the impact of institutional distance on foreign firm
strategy is, in general, more complicated than the literature has assumed. Therefore, using
institutional distance as a general concept can be problematic. Future research on the
relationships between institutional contexts and foreign firm strategies is promising.

56
CHAPTER 3
INSTITUTIONAL DISTANCE AND LOCAL ISOMRPHISM STRATEGY

3.1 Introduction
Decades of research in international strategy suggest that foreign firms are at a
disadvantage vis-a-vis indigenous incumbents. This disadvantage, known as the liability
of foreignness, arises from a broad unfamiliarity with the local environment, local
practices, and local regulations (Hymer, 1960). The liability of foreignness is exacerbated
by the difficulty inherent in coordinating the activities of far-flung subsidiaries (Zaheer,
1995).
One means by which a foreign firm may be able to offset costs imposed by the
liability of foreignness is by imitating elements of domestic firms’ strategies (e.g., Zaheer,
1995; Miller and Eden, 2006). By imitating the strategy of local firms (i.e., pursuing a
strategy of local isomorphism), foreign subsidiaries may acquire legitimacy and thereby
reduce their liability of foreignness. Although prior literature has examined local
isomorphism as a strategy to overcome the liability of foreignness, we know less about
which firms (from which home nations) are likely to pursue such a strategy.
To fill that gap, this study examines whether variance exists in the level of local
isomorphism adopted by firms from different home countries. I argue that foreign firms
from home countries that are more similar to the host country are less likely to choose
isomorphic strategies. Conversely, firms from home countries that are more dissimilar
from the host country are more likely to pursue isomorphic strategies. I gage similarity
using the institutional distance (cultural, economic, regulatory, and political) between the

57
home and host country. Research suggests that as institutional distance increases, foreign
firms face a greater disadvantage and a greater liability of foreignness (Perkins, 2008).
Moreover, because firms from institutionally distant countries are at an increasing
disadvantage, it is more difficult for these firms to obtain legitimacy in the host country
(Kostova and Zaheer, 1999).
This is not to say however that the impact of institutional distance will be fixed.
The impact of distance may diminish with host country experience. Prior studies show
that market experience helps reduce the liability of foreignness (Zaheer and Mosakowski,
1997; Miller and Eden, 2006). Experience may therefore lessen the need for isomorphism.
A firm can benefit from experience in two ways. It may learn from the
accumulated experience of competitors from its home country that have entered the
foreign market prior to it – i.e., vicarious learning (e.g., Mitchell, Shaver, and Yeung,
1994; Henisz and Delios, 2001; Chung and Song, 2004). I therefore argue that foreign
firms from countries whose firms have prior experience in the host market will lessen the
impact of distance on isomorphism. A firm may also benefit from its own experience in
the host country – experiential learning. Although firms from distant home countries may
pursue an isomorphic strategy upon entry, experience may lead them to alter their
isomorphism strategy over time.
I test these assertions using a sample of 83 foreign bank subsidiaries operating in
the U.S. banking industry from 1978 to 2006. I find that foreign bank subsidiaries are
more likely to imitate the practices of local U.S. banks the greater the cultural, regulatory,
and economic distance between the home country and the United States. Political

58
distance between the home country and the United States has little impact on the choice
of local isomorphism. Moreover, vicarious and experiential learning do not significantly
influence foreign banks’ decisions to imitate local U.S. rivals.
This study makes several contributions to the international business and strategy
literatures. Theoretically, it explores heterogeneity in the choice of local isomorphism.
Moreover, this study examines how foreign firms change their local isomorphism
strategies based on the accumulated experience of others from their home country, and
also as they acquire more knowledge about the host country through first-hand
experience. This provides a dynamic view of foreign firm strategy in a local market.
Finally, from an empirical standpoint, this study adds to our understanding of institutional
distance as a multi-dimensional construct. Although prior studies have explored the
impact of institutional distance on the behavior of foreign firms (e.g. Kogut and Singh,
1988; Benito and Gripsrud, 1992; Brouthers and Brouthers, 2001; Henisz and Delios,
2001), most studies focus solely on one dimension of distance.
The paper proceeds as follows. The first section reviews prior literature on local
isomorphism strategies. Based on this review I develop hypotheses. The following
section describes the data and methodology used to test these hypotheses. I subsequently
present results. The final section concludes.

59
3.2 Literature Review
Foreign firms operating in a host country face disadvantages relative to their
domestic counterparts (Hymer, 1960; Zaheer, 1995). These disadvantages, known as the
liability of foreignness (Hymer, 1960), manifest as additional costs to foreign firms
operating in a host market. These costs include additional coordination costs, transaction
costs, labor costs, start-up costs, legal costs, legitimacy costs, and other costs that stem
from a broad unfamiliarity with the local environment (Hymer, 1960; Johanson and
Vahlne, 1977; Hennart, 1982; Mincer and Higuchi, 1988; Lipsey, 1994; Zaheer, 1995;
Mezias, 2002; Salomon and Martin, 2008). These additional costs stand to negatively
impact foreign subsidiary performance and survival (Zaheer, 1995; Zaheer and
Mosakowski, 1997).
Scholars point out that foreign firms can reduce their liability of foreignness by
imitating elements of the strategies and business practices of local competitors (Zaheer,
1995; Kostova and Zaheer, 1999; Henisz and Delios, 2001; Xu and Shenkar, 2002; Miller
and Eden, 2006). By pursuing a strategy of local isomorphism, foreign firms adopt
strategies that have been proven in the host country, and that are seen as legitimate.
There is a long tradition of studying the antecedents and consequences of
isomorphic strategies in institutional theory (DiMaggio and Powell, 1983; Zucker, 1987;
Davis, 1991; Mezias, 1990; Palmer, Jennings and Zhou, 1993; Suchman, 1995). The
institutional theory literature points out that firms experience social pressure to conform
(Meyer and Rowan, 1977). By conforming to various social norms via isomorphic

60
strategies, they achieve regulative, normative, and cognitive legitimacy (Meyer and
Rowan, 1977; DiMaggio and Powell, 1983; Scott, 1995).
Empirical studies demonstrate that organizations often use isomorphic strategies.
For example, Fligstein (1985) shows that large firms are more likely to adopt a
multidivisional organizational form if other firms in the same industry have done so.
Similarly, Greve (2000) finds that smaller banks imitate larger banks when making
branch location decision. Haveman (1993) finds that the U.S. savings and loan
associations tend to imitate successful competitors’ diversifying strategy. In addition,
firms have been shown to imitate similar competitors (Rhee, Kim, and Han, 2006), and
those in the same strategic niche (Garcia-Pont and Nohria, 2002).
With respect to consequences of isomorphic strategies, Deephouse (1996) tested
the links between the adoption of an isomorphic strategy and legitimacy. He examined
the U.S. commercial banking industry and found that banks conforming to broad industry
asset strategies acquired more legitimacy in the form of regulatory and public media
endorsement. Consistent with this finding, Staw and Epstein (2000) demonstrate that
companies imitating other firms and adopting popularized management techniques were
viewed as more reputable, though their performance was not appreciably better. Similarly,
Barreto and Baden-Fuller (2006) find that Portuguese banks imitate other banks’ branch
location decisions despite of the seeming unattractiveness of the location. In fact,
imitative decisions of the sort negatively affected bank profitability (Barreto and Baden-
Fuller, 2006). Therefore, although studies demonstrate that firms pursue isomorphic

61
strategies and that isomorphism enhances legitimacy, there is no clear link between
isomorphism and performance (e.g., Deephouse, 1999).
The aforementioned literature goes a long way in examining the antecedents and
consequences of isomorphic strategies. Moreover, it demonstrates that firms can increase
legitimacy by adopting isomorphic strategies. However, the focus of that work has
generally been on domestic firms. Few studies examine how foreign firms imitate
domestic competitors in a host country, and those that do generally focus more on the
consequences of isomorphism (i.e., the impact of isomorphism on firm performance) than
on its antecedents (i.e., the choice of isomorphism in the first place).
5
For example,
Zaheer (1995) studied the trading rooms of foreign banks and demonstrated that imitating
the practices of domestic competitors did not improve performance. Building upon that
finding, Miller and Eden (2006) suggest that the impact of isomorphic strategies on
performance is dependent upon characteristics of the local market. In particular, those
authors find that local isomorphism strategies benefit foreign banks when they enter cities
with few competitors. It decreases performance in cities with a large existing population
of banks.
Although those studies inform our understanding of the impact of isomorphism
strategies on the performance of foreign firms, both studies solely examine the
performance implications of isomorphism. Moreover, they treat foreign firms as
homogeneous. They do not consider heterogeneity in firm characteristics or country of

5
For a notable exception see Rosenzweig and Nohria (1994).

62
origin. I will argue that foreign firms vary in the level of local isomorphism they pursue
as a result of firm-specific and country-specific factors.
At the country level, one factor that stands to impact the local isomorphism
decision of foreign firms is the institutional distance between the host country and home
country. In the international business literature, institutional distance is defined as the
extent of similarity or difference between a host country and a home country in its
institutional context (Kostova, 1996; Xu and Shenkar, 2001). Institutional distance
between a pair of countries has been shown to impact the strategic choices of foreign
firms (e.g., Kogut and Singh, 1988; Kostova and Zaheer, 1999). However, to our
knowledge, no study has examined the impact of institutional distance on isomorphism.
I further argue that experience moderates the impact of institutional distance on
isomorphism. A better understanding of the local environment gained through experience
stands to offset the impact of distance on the imperative for imitative strategies.
Specifically, I will argue that foreign firms from distant countries need not rely as heavily
on the imitation of domestic firm strategy as experience increases. I consider how two
types of experience (vicarious and experiential) moderate the impact of institutional
distance on isomorphism.

3.3 Hypotheses
3.3.1 Institutional Distance
Institutional distance, the extent of difference between two countries in terms of
its institutional context, plays an important role in the strategy and performance of firms

63
that operate in multiple countries (Kostova and Zaheer, 1999; Xu and Shenkar, 2001).
Institutional distance arises from the dissimilarity in both formal and informal institutions
(Scott, 1995). Formal institutions include regulatory, political, and economic institutions.
Informal institutions refer to social norms, beliefs, and values – i.e., national culture.
Although formal and informal factors together make up the institutional
environment, most prior studies on international institutional difference have focused on
a single dimension (e.g. Kogut and Singh, 1998; Henisz and Delios, 2001).
6
We know
less about how various dimensions of institutional distance, individually and jointly,
impact international business activities. To fill this gap, I adopt a multi-dimensional
approach. I employ the cultural, economic, political, and regulatory distances between
countries to capture the impact of both formal and informal institutions on isomorphism.
These dimensions not only constrain human activities in political, economic and social
interactions (North, 1991) but also have important influence on foreign firm strategy and
performance (Ghemawat, 2001).
As institutional distance (on any dimension) increases, so does the liability of
foreignness (Kostova and Zaheer, 1999; Ghemawat, 2001). Institutional distance impedes
a foreign firm’s understanding of the local market and makes it more difficult to interact
with customers, suppliers, and other agents (Johanson and Vahlne, 1977). Distance
makes it more difficult to interpret market signals since norms and practices in the host
country are unfamiliar to the foreign firm. It is not only difficult for a foreign firm to
understand a more distant local market, but it is similarly difficult for participants in the

6
See Perkins (2008) for a notable exception.

64
local market to understand the foreign firm. For this reason, foreign firms from more
distant institutional contexts are seen as less legitimate, and large institutional distances
create significant barriers for foreign firms (Kostova and Zaheer, 1999).
To overcome the liability of foreignness, it is critical for foreign firms to be seen
as legitimate (Kostova and Zaheer, 1999). Using a local isomorphism strategy represents
one possible means of achieving legitimacy (Rosenzweig and Singh, 1991; Zaheer, 1995).
Domestic firms provide a good model of “fit” in the local market, and provide an
example of the types of strategies that are likely to work. Their activities and strategies
are more compatible with the local cultural, economic, regulatory, and political demands
than are those of their foreign competitors. By imitating domestic firms, foreign firms
adopt practices that have been established as legitimate in the host environment.
Therefore, isomorphism strategies may help foreign firms acquire the legitimacy that they
lack.
Choosing an isomorphism strategy however does not come without cost. As more
firms use the same strategy and business practices, there is greater competition for scarce
resources (Carroll, 1985; Baum and Mezias, 1992). This intensified competition increases
the likelihood of failure (Hannan and Freeman, 1977; Baum and Singh, 1994). As
Deephouse (1999) argued, firms should choose an appropriate level of isomorphism that
balances the pressure of legitimacy versus increased competition. Extending the logic to
foreign firms would suggest that while local isomorphism legitimizes foreign firms, it
also leads to greater competition with domestic rivals.

65
For this reason, foreign firms are not likely to benefit equally from a local
isomorphism strategy. Although foreign firms from institutionally distant countries are at
a decided disadvantage at the outset, foreign firms from home countries that are similar to
the host market do not bear as great a liability of foreignness (e.g., Perkins, 2008). As a
result, firms from institutionally similar countries have more latitude in strategy selection.
They may therefore prefer to adopt the practices of their parent rather than imitate local
firms. When the institutional environment of the firm’s home country is similar to that of
the host country, the parent firm’s business practices are likely more compatible with
those in the new environment (Barlett and Ghoshal, 1989). In addition, because the firm
is at less of an informational disadvantage, they can make strategic decisions without
worrying as much about their perceived legitimacy in the host nation.
Integrating the above arguments, my expectation is that foreign firms from
institutionally distant countries will be more likely to select a strategy of institutional
isomorphism. This is because the marginal benefit in terms of local legitimacy exceeds
the marginal cost from increasing competition. By contrast, foreign firms from home
countries that are institutionally similar to the host country will be less likely to select an
isomorphism strategy. For these firms, the initial costs of liability of foreignness that they
face in terms of legitimacy are lower than the costs in terms of increased competition
with local firms. I therefore hypothesize,

H1: All else equal, foreign firms are more likely to adopt a local isomorphism strategy as
the institutional distance between the home country and the host country increases.

66
3.3.2 Learning
Although I hypothesize that foreign firms from more distant institutional contexts
are more likely to adopt isomorphic strategies, the impact of institutional distance may
not be the same for all firms from the same home country. The impact of distance on the
selection of isomorphic strategies may vary as firms learn about, and gain experience in,
the host country. In this study I view learning as the accumulation, encoding, and
leveraging of insights gleaned through experience (Fiol and Lyles, 1985; Levitt and
March, 1988; Huber, 1991; Argote, 1999). Accordingly, there are various forms of
learning that can be helpful to foreign firms. I will focus on two: vicarious learning and
experiential learning. Vicarious learning is a form of learning based on the experience of
others. It refers to the insight that a firm gains as others ‘do’ – i.e., a firm learns about the
foreign country by observing, accumulating, and encoding experiences that similar others
have had in the same host country (Ghemawat and Spence, 1985; Lieberman, 1987;
Argote, Beckman, and Epple, 1990; Ingram and Baum 1997). The second form of
learning accumulates as the firm gains first-hand experience – i.e., learning from its own
experience in the host country (Argote, 1999).

3.3.2.1 Vicarious Learning
Although a foreign firm may have no direct experience in a host country prior to
entry, they may learn about the local environment from competitors that operate in that
market (e.g., Mitchell, Shaver, Yeung, 1994; Shaver, Mitchell, Yeung, 1997; He, 2002;
Guillén, 2003; Martin and Salomon, 2003; Chung and Song, 2004; Chang and Park, 2005;

67
Salomon and Martin, 2008). Firms can learn from the actions, strategies, and practices of
their competitors (Huber, 1991). As such, the experiences of competitors may provide a
valuable source of information about the host market (Levinthal and March, 1993; Baum
and Ingram, 1998; Baum, Li, and Usher, 2000; Ingram, 2002). Competitors may
experiment with a variety of strategies and practices, which generates spillovers of
information about the market and organizational routines (Miner and Haunschild, 1995;
Baum and Ingram, 1998). This reveals important information about the external
environment, and those organizational practices that are likely to work. Therefore, for
foreign firms with little experience of their own, the experience of competitors can help
reduce environmental uncertainty and lower entry barriers (Baum, Li, and Usher, 2000).
However, foreign firms do not benefit from the experience of all firms in the host
market. Studies in the international business literature suggest that a foreign firm first
looks to those firms that are more similar to it. That is, foreign firms benefit from the
accumulated experience of competitors from the same home country (Chang and Park,
2005). This is because firms that originate from the same institutional environment share
common traits, face similar challenges, and share a common language and understanding
(Chang and Park, 2005; Perkins, 2008). For example, Henisz and Delios (2001) find that
Japanese entrants are more likely to imitate the plant location choice of other Japanese
firms when they invest in unfamiliar countries. Similarly, Chung and Song (2004) find
that Japanese entrants with little experience in the host country tend to locate close to
prior Japanese entrants. However, they avoid collocation after they gain more
experienced in the local market (Chung and Song, 2004). Likewise, Korean firms in

68
China are likely to adopt ownership structures similar to those used by firms in the same
business group (Guillén, 2003). The experiences of competitors from the same home
country also enable later entrants from that country to learn from success and failure
(Mitchell, Shaver, and Yeung, 1994). Specifically, foreign firms are more likely to
survive when there is a greater presence of firms from that home country in the host
country market (Shaver, Mitchell, and Yeung, 1997).
Taken together, the experiences of early entrants spills over to later entrants,
providing useful insights about the local landscape – customers, suppliers, and
competitors; local customs and norms; and thereby to design strategies and practices that
better fit the local environment. For this reason, firms might rely less on the practices of
domestic firms as a model of appropriate business practices and activities.
In addition to the learning effect, later entrants may also benefit from a greater
level of initial legitimacy as the presence of comparable firms from the host country
increases. Actors in the host country often judge foreign firms by referring to the actions
and patterns of behavior exhibited by organizations that are similar to it (Kostova and
Zaheer, 1999). For example, actors in the host country may view the foreign firm as more
legitimate if other firms from that home country generally behave in reasonable manner.
This “legitimacy spillover” is particularly important for new entrants because agents in
the host country environment have little information with which to judge it (Kostova and
Zaheer, 1999).
Since foreign firms stand to benefit from the experiences of competitors from the
same home country, I argue that vicarious learning moderates the impact of distance on

69
the choice of isomorphism. Although firms from institutionally distant countries are more
likely to mimic domestic rivals, firms from countries whose firms already have a
presence in the host country have a more relevant peer set from which to draw inferences
about the host country. This knowledge is especially valuable for firms from more
institutionally distant countries, which start from a more disadvantaged institutional
position. The more competitors in the destination market with the same country of origin,
the lower the initial liability of foreignness, and the less the pressures to imitate the
practices of domestic firms. As a result, learning about the host market from the
experiences of competitors from the same home market allows firms from institutionally
distant countries greater latitude in their strategy selection upon entry. Stated formally,

H2: All else equal, the positive relationship between institutional distance and local
isomorphism is likely to decrease as the experience of competitors from the firm’s home
country increase.

3.3.2.2 Experiential Learning
In addition to learning about the host market from competitors, firms learn about
host markets from their own experiences in that market. As foreign firms interact in the
local market, they become connected in the domain and acquire information about
customers, suppliers, competitors, and the broader environment at large. This experience
helps reduce the impact of distance.
With greater experience, foreign firm managers are better able to recognize, and
capitalize on, opportunities that exist in the local market (Johanson and Vahlne, 1977).
They also more accurately perceive, and respond to, environmental uncertainties and

70
risks (Henisz and Delios, 2001). Moreover, they gain a greater familiarity with the norms
of the local market, and are more likely to make additional investments in that market
(Mudambi, 1998). Ultimately, they improve decision-making, more efficiently coordinate
operations, and overcome distance-related costs. Therefore, although foreign firms from
institutionally distant countries initially may imitate the strategies and practices of
domestic firms, over time they become less reliant on domestic firms as a guide for the
types of strategies and practices that work in the host market.
With experience, foreign firms build ties and become connected in the local
environment. They are therefore also more likely to be perceived as legitimate by actors
in the host nation (Zaheer and Mosakowski, 1997). Institutional distance makes it more
difficult for foreign firms to operate using the strategies they use at home, as these
strategies are not viewed as legitimate in the local market (Xu, 2001). However, this
disadvantage decreases in the host country market experience of the firm. As such,
although foreign firms use local isomorphism strategies to establish legitimacy, they are
likely to become less dependent on those strategies over time.
Taken together, operational experience in a market reduces the disadvantages
arising from institutional distance. Market experience decreases the impact of distance on
the isomorphism strategies of foreign firms. Moreover, experience establishes the firm as
legitimate in the host environment and allows it to become less reliant on isomorphic
strategies. As with vicarious learning, I expect the impact of experiential learning on
strategic isomorphism to be greater for firms from institutionally distant, versus
institutionally similar, countries. This is because firms from institutionally similar

71
countries are less disadvantaged from the outset, and have the latitude to pursue strategies
other than those employed by domestic firms. Formally stated,

H3: All else equal, the positive relationship between institutional distance and local
isomorphism is likely to decrease in the foreign firm’s market experience.

3.4 Research Design
3.4.1 Data
To study foreign firms’ local isomorphism strategies, I have chosen the empirical
setting of foreign bank subsidiaries operating in the United States from 1978 to 2006. The
U.S. banking industry is highly regulated and banks face strong pressures to conform to
the institutional environment (Scott and Meyer, 1991; Deephouse, 1996; Miller and Eden,
2006). Banks are not only influenced by formal regulations (Sponge, 1990), but at the
same time must make an effort to obtain legitimacy (Deephouse, 1996). Therefore, this
industry offers an appropriate setting to study the isomorphic strategies of foreign firms.
My initial dataset comes from the Reports of Condition and Income (known as the
Call Reports) from the Federal Reserve Bank of Chicago. The Federal Reserve Bank
provides these reports for all commercial banks in the United States from 1976 to 2006.
Call Reports provide financial data on each commercial bank regulated by the Federal
Reserve System, Federal Deposit Insurance Corporation, and the Comptroller of the
Currency. I use these Call Reports to measure the presence of foreign banks in local
markets, and to estimate the asset strategy of banks in each of those markets. An

72
examination of the Call Reports yielded an initial list of 278 foreign banks from 62
countries that operated 399 banking institutes in the United States countries between
1976 and 2006.
When a foreign bank establishes a presence in the United States, it may choose
one of six organizational types (institutes): agency, branch, subsidiary, representative
office, New York Investment Company (NYIC), or Edge and Agreement Corporation
Subsidiary (Edge). Each institute operates slightly differently, and each must comply
with a different set of regulations. Only subsidiaries can offer a full range of commercial
products and services. They are therefore subject to the same level of regulation as U.S.
commercial banks. These types of institutes have the discretion to either imitate domestic
commercial bank strategies or adopt a differentiating strategy. The other institutions
(agencies, branches, representative offices, etc.) are constrained by their charters. For this
reason I use only the subset of foreign bank subsidiaries to study local isomorphism,
consistent with prior studies of foreign banks operating in the United States (DeYoung
and Nolle, 1996; Miller and Parkhe, 2002, Miller and Eden, 2006). This reduced the
initial sample to 121 foreign banks with 257 subsidiaries.
A foreign bank subsidiary in the United States can conduct the same banking
activities as a U.S. commercial bank. As U.S. commercial banks, a foreign bank
subsidiary needs to obtain national or state charters before its establishment. It may
commence and operate multiple banking offices – i.e., facilities that provide services to
customers (Sponge, 2000). A foreign bank may have more than one subsidiary in the
United States. However, as Chang (1995) points out, the first is generally of greatest

73
consequence. The first investment is at a decided knowledge disadvantage and faces
greater legitimacy concerns than subsequent investments (Chang, 1995). Moreover,
initial strategic decisions constrain future strategic behavior. Because this study examines
local isomorphism strategy as a firm response to the liability of foreignness, I follow the
extant research to focus on the sample that includes only the first foreign bank subsidiary
built by a foreign parent in the U.S. banking industry. If a foreign bank established
several subsidiaries simultaneously, both subsidiaries are included in the sample. This
reduced the sample to 121 foreign banks with 135 subsidiaries.
The United States Congress enacted the International Banking Act (IBA) in 1978
to uniformly regulate foreign bank operations (Goldberg and Saunders, 1981). For
example, the requirements for establishing agencies became more stringent than before
1978, a period when foreign banks were subject to little supervision. I therefore limit my
sample to the period 1978-2006 to keep the regulatory environment constant. This results
in a sample of 99 foreign banks with 113 subsidiaries.
As a result of missing data on several of the independent variables (described
below), data were not available for all foreign banks. For example, some of the home
country cultural, political, economic, and regulatory measures were unavailable from data
sources used to complement the Call Reports. I was therefore able to compile complete
information on 79 foreign banks with 83 subsidiaries from 24 distinct home countries
over the period 1978-2006. This resulted in an unbalanced panel of 891 firm-year
observations.

74
Table 3.1: Foreign Bank Subsidiary Origins

Home Country Number of
banks
1. Australia 1
2. Brazil 1
3. Canada 5
4. Colombia 1
5. Denmark 1
6. France 1
7. Germany 1
8. Greece 2
9. India 1
10. Ireland 2
11. Israel 4
12. Italy 3
13. Japan 23
14. Korea 8
15. Mexico 1
16. Netherlands 2
17. Philippines 3
18. Portugal 1
19. Slovenia 1
20. Spain 5
21. Switzerland 1
22. Taiwan 3
23. United Kingdom 7
24. Venezuela 1

75
3.4.2 Dependent Variable
3.4.2.1 Local Isomorphism Strategy
Following prior studies (e.g., Miller and Eden, 2006), I have constructed the
strategic isomorphism dependent variable by comparing the asset strategy of a foreign
bank subsidiary with that of U.S. banks. Asset strategy refers to a bank’s asset portfolio -
i.e., how a bank allocates its assets across various products such as commercial loans,
residential loans, and securities (e.g., Haveman, 1993; Deephouse, 1999). A bank’s asset
strategy is crucial to performance and survival. The bank’s asset allocation not only
influences revenue, but also its risk exposure. Although government regulators (via the
Federal Reserve Board, Federal Deposit Insurance Corporation, and the Comptroller of
the Currency) supervise the operations of banks operating in the United States and pay
particular attention to the security of a bank’s financial capital and assets (Sponge 2000),
U.S. banking regulations have no particular requirements on the allocation of bank assets.
That is, as long as banks can meet their regulatory capital requirements, they have
substantial latitude in determining their asset mix. Therefore, a bank’s asset portfolio is
reflective of its operational strategy (e.g. Haveman 1993; Mehra, 1996; Deephouse 1999).
The local isomorphism strategy is measured as the similarity between a focal
foreign bank subsidiary’s asset portfolio and that of the local U.S. banks. To measure
bank asset portfolio, Miller and Eden (2006) defined eight categories of bank assets:
commercial loans, real estate loans, loans to individuals, other loans and leases, cash,
overnight money, securities, and fixed assets. Following Miller and Eden (2006), I also

76
build these eight asset variables for each foreign bank subsidiary and each U.S.
commercial bank. Each asset strategy is measured as a proportion of this subsidiary’s
total assets.
To capture local isomorphism strategy, I compare a foreign bank subsidiary’s
asset strategy with the average asset strategy of U.S. banks in the same local market. I
define a local market as a metropolitan statistical area (MSA). Bank regulators identify
bank competitive markets by MSAs (Barnett, Greve, and Park, 1994). Scholars studying
commercial banks also widely adopt MSAs to define the boundary of markets (Barnett,
Greve, and Park, 1994; Berger, 1995; Miller and Eden, 2006). I then compare the asset
strategy of a foreign bank subsidiary to the average strategy used by its U.S. rivals in the
same MSA. This comparison method is similar to Miller and Eden (2006), which is
adapted from Deephouse (1999) and Finkelstein and Hambrick (1990).
For each foreign bank subsidiary (i), I calculate its asset strategy (A
ni
) (n=1…8) as
a proportion of subsidiary (i)’s total assets. Then I calculate the mean of this asset
strategy of all the U.S. banks in the same area: A
nUS
. I compare A
ni
with this mean, and
then divide this difference by the standard deviation of the asset strategy of the local U.S.
banks. This measure then reflects how a foreign bank subsidiary’s asset strategy n
deviates from the local average. I then multiply this difference by -1 to convert deviation
to isomorphism for ease of interpretability (Finkelstein and Hambrick, 1990; Miller and
Eden, 2006). This measure represents a foreign bank subsidiary’s overall local

77
isomorphism strategy (LIS). A larger value of LIS represents greater local isomorphism –
i.e., the bank more closely resembles domestic banks in the local market.
( ) ( ) ( ) [ ] ( ) 1 * /
8
1
−






− =
∑
= n
nUS nUS ni i
A SD A M A ABS LIS (3.1)

3.4.3 Independent Variables: Institutional Distance
The main independent variable of interest to test hypothesis 1 is institutional
distance. Institutional distance is the extent of difference between two countries in terms
of its institutional context – expressed on cultural, economic, political, and regulatory
dimensions. Cultural distance refers to the extent of similarity between the national
cultures two countries. Economic distance captures differences in patterns of exchange,
market orientation, market stability, and the nature of economic organization across
countries. Political distance refers to differences in government. Regulatory distance
captures industry-specific differences in the way regulations are enacted and enforced
across countries. I measure each dimension of distance using established proxies.

3.4.3.1 Cultural Distance
Hofstede defined national culture as the “collective mental program” that
normalizes individual activities in a society (Hofstede, 2001). When a firm operates in a
foreign country, it becomes exposed to a new cultural environment, which may conflict
with that of its home country. Hofstede described the differences in national culture along

78
five dimensions: power distance, uncertainty avoidance, individualism and collectivism,
masculinity and femininity, and long-term orientation. Prior studies have used aggregated
differences across the dimensions to measure cultural distance (for a summary see
Tihanyi, Griffith and Russell, 2005). However, a measure for long-term orientation was
available for only a small subset of countries. Following Kogut and Singh (1988), I
therefore measure the CULTURAL DISTANCE (CD) between the parent firm’s home
country and the United States using only four dimensions: power distance, uncertainty
avoidance, individualism/collectivism, and masculinity/femininity.
7
This approach has
been widely adopted to measure cultural distance (e.g., Li and Guisinger, 1991; Benito
and Gripsrud, 1992). The cultural distance measure is expressed as follows:
( ) [ ]
∑
=
− =
4
1
2
4 / /
j
j USj ij i
Var H H CD , (3.2)
where CD
i
represents the cultural distance between country (i) and the United States.
ij
H
captures cultural dimension j in country i and
USj
H the cultural dimension j in the United
States. Var
j
represents the overall variance on cultural dimension j across all countries.

3.4.3.2 Economic Distance
Countries are not homogeneous in economic structure and market orientation.
Some countries are organized around private capital markets while in others; banks play a

7
Results did not change when I limited the sample to those countries for which all five cultural dimensions
were available.

79
larger role in markets. Miller and Parkhe (2002) describe the former as “capital market-
oriented” because firms generally rely on external capital markets to acquire capital and
the latter as “bank-oriented” because they rely on a system of banks. While firms may
build long term relationships with a few banks in bank-oriented financial systems, they
may have more temporary ties with numerous shareholders in capital market-oriented
systems (Allen, 1993). Both systems can be an efficient source of external funding,
although they have different orientations. However, foreign banks may operate less
efficiently when the home country’s financial system differs markedly from that of the
host country (Miller and Parkhe, 2002). Therefore, I use financial market orientation to
measure economic distance.
I measure market orientation using a ratio of market capitalization/GDP divided
by bank credits to private sector/GDP. This is a standard measure of financial market
orientation (Levine, 2002; Miller and Parkhe, 2002). The market capitalization, bank
credits, and GDP data come from the United Nation World Development Indicators
Database. I then define ECONOMIC DISTANCE (ED) as the absolute value of the
difference between the foreign firm’s home country orientation and the U.S. orientation.
A greater value indicates greater differences between the home country’s financial
market and that of the U.S.
| )
/ Pr
/
/ Pr
/
( |
. . . .
. . . .
t S U t S U
t S U t S U
it it
it it
it
GDP Sector ivate to Credit Bank
GDP tion Capitaliza Market
GDP Sector ivate to Credit Bank
GDP tion Capitaliza Market
ED − =
(3.3)

80
3.4.3.3 Regulatory Distance
Although scholars have widely explored institutional environments, very few
studies explicitly examine international differences in regulations (for a notable exception,
see Perkins, 2008). However, regulation is an important component of formal institutions
that normalize the activities of organizations (Scott, 1995). A comparison of regulations
across countries is especially important in this context because banks operate in a highly
regulated industry. The banking industry has a greater level of regulation and more laws
governing firm behavior than most (Miller and Parkhe, 2002; Miller and Eden, 2006).
Therefore, when foreign banks set up business units in the United States, they potentially
face a regulatory environment vastly different than that which exists in their home
country. This difference may affect their operations in the U.S. To capture the impact of
the U.S. regulatory environment on foreign banks, I create a regulatory distance variable
using the Banking Regulation Database (Barth, Caprio and Levine, 2001a).
Barth et. al. (2001a) collect comprehensive data on banking regulations in 107
countries. Those authors measure the following dimensions of banking regulation: Bank
Activity Regulations, Banking/Commerce Mixing Regulations, Competition Regulations,
Capital Regulations, Official Supervisory Actions, Official Supervisory Experience and
Structure, Private Monitoring, Deposit Insurance Schemes, and Market Structure.
I use the Bank Activity Regulations, Banking/Commerce Mixing Regulations,
Competition Regulations, and Capital Regulations dimensions to create my regulatory
distance measure. I choose these dimensions for both practical and theoretical reasons.

81
First, the aforementioned dimensions focus on regulations that normalize bank
activities, ownership, competition, and strategy. The others (Official Supervisory Actions,
Official Supervisory Experience and Structure, Private Monitoring, Deposit Insurance
Schemes, and Market Structure) generally focus on the features of supervisory agencies –
e.g., the extent of their power and their level of expertise. Since I am interested in how
regulations shape the behavior of firms, I adopt the regulation-related dimensions.
Second, the Barth et. al. (2001a) data are from the years 1998 to 2002. My data,
by contrast, cover the activities of foreign banks in the United States between 1978 and
2006. Therefore, to be more accurate in applying the Barth et. al. (2001a) data
retrospectively, it is helpful to have relatively stable temporal dimensions. Since banking
regulations that normalize bank activities were relatively stable from the 1970s onward
(Barth, Caprio, and Levine, 2001b), I focus on these dimensions of regulation. Although
certainly far from ideal, I believe that this is a suitable approach these authors
demonstrate in an earlier study that banking regulations across countries did not change
significantly overtime, even after serious banking crises (Barth, Caprio, and Levine,
2000). There is no report on the temporal stability of the supervision dimensions. All
things considered, the Barth et. al. (2001a) measure is the best available measure of the
regulatory environment.
Finally, and more practically, some dimensions are not available to the public,
including several indicators of supervision and deposit insurance schemes. Therefore, I
was not able to include these dimensions in my regulatory distance measure.

82
For the reasons described above, my banking regulatory distance measure
includes only the following four dimensions: Bank Activity Regulations,
Banking/Commerce Mixing Regulations, Competition Regulations, and Capital
Regulations. I build the REGULATORY DISTANCE (RD) variable as follows:
4 / / ) (
4
1
2






− =
∑
= j
j USj ij i
Var R R RD , (3.4)

where R
ij
refers to the jth regulatory dimension in country i, R
USj
captures to the jth
regulatory dimension in the United States, and Var
j
is the variance across all four
dimensions. By construction, a greater value on this metric implies a greater regulatory
distance between the home country and the United States.

3.4.3.4 Political distance
To operationalize political distance, I use the CHECKS index drawn from the
Database of Political Institutions (Beck, Clarke, Groff, Keefer, and Walsh, 2001; Keefer
and Stasavage, 2003). The CHECKS index counts the number of veto players in a
political system, adjusting for political cohesiveness. With a greater number of veto
players, more political checks and balances are in place, and policies are less likely to
change arbitrarily. In such cases, the political environment will be more predictable. With
fewer constraints on politicians (fewer players with veto power), the environment

83
becomes more unpredictable. The CHECKS index therefore captures the overall level of
political volatility within a country (Beck, et.al. 2001; Keefer and Stasavage, 2003).
Firms become accustomed to the political system in their home market; they
better understand the political environment and how it is likely to change; and they learn
how to operate effectively under such political conditions. When they enter politically
distant countries, it becomes more difficult for them to conduct business (e.g. Gaur and
Lu, 2007). I therefore measure POLITICAL DISTANCE (PD) as the absolute value of the
difference in political volatility (as measured by the CHECKS index) between the foreign
firm’s home country and the United States. A greater value indicates greater differences
between the home country’s political environment and that of the U.S.
USt it i
CHECKS CHECKS PD − = (3.5)

3.4.4 Moderating Variables
3.4.4.1 Vicarious Experience
To measure the opportunity for the foreign bank to learn from competitors, I
create a measure based on the accumulated experience of prior entries by banks from the
same home country. Though a bank from a given home country could conceivably learn
from non-banking firms from its home country or third-country competitors in the host
market, the potential to learn from these firms is limited (Salomon and Martin, 2008).
The experiences of these firms in the United States are less relevant because their
experiences differ. A third-country competitor and a non-banking firm from the same

84
home country encounter a different set of problems when entering in the United States
because they face either different cultural, economic, political and regulatory challenges
(in the case of the former), or because insights from an industry other than banking may
not be as useful (in the case of the latter). Therefore, the experiences of comparable
organizations (same industry, same home country) may prove more valuable for the
foreign firm (Baum, Li, and Usher, 2000).
For this reason, I base my measure of vicarious learning on the experiences of
home country competitors operating in the United States. I define VICARIOUS
EXPERIENCE as the cumulative years of experience by all banks from the same home
country in the United States prior to the focal bank’s entry. I focus on the years of
experience of competitors because studies of foreign market experience emphasize the
role of time (e.g., Miller and Eden, 2006).

3.4.4.2 Own Experience
To test the moderating impact of a firm’s own experience in a market, I adopt a
proxy for foreign bank experience in the U.S. banking industry. I define OWN
EXPERIENCE as the cumulative years of experience of all U.S. banking institutes owned
by the same parent bank before time t. This is a slightly different measure than that used
in Miller and Eden (2006). Miller and Eden (2006) measure bank experience using the
cumulative number of years in which a foreign subsidiary operated in the United States.
Although that measure captures the length of experience of a bank subsidiary, it does not

85
account for the potential for banks to learn from their other institutes. A bank with
multiple institutions maintains a greater variety of contacts with customers, partners, and
regulators for longer. Moreover, if the focal bank opens other types of institutes before
opening a full-fledged subsidiary, that experience provides the opportunity for the foreign
bank to learn about the local market and the basis for firms to employ differing strategies.
I therefore modify the Miller and Eden (2006) measure to include the cumulative years of
experience of any U.S. institution established by the parent bank.
8

3.4.5 Control Variables
I control for several other subsidiary-, parent-, and country- level variables that
have the potential to influence local isomorphism strategies.
First, I control for the performance of the local subsidiary. Organizations that
perform better are more likely achieve legitimacy on their own, and therefore less likely
to need to rely on isomorphic strategies to acquire such legitimacy (Deephouse, 1996). I
measure PERFOREMANCE using the lagged value of Return on Assets (ROA) of the
focal subsidiary at time t-1. For the first year of operation (time t), I use the average ROA
of all subsidiaries from the same home country (at time t-1) in the U.S. For the first
subsidiary from a particular home country, I code performance as the average ROA (at
time t-1) of all foreign bank subsidiaries in the U.S.

8
The results do not change if I use the Miller and Eden (2006) measure instead of the one used herein.

86
Second, I control for whether the local subsidiary is a joint venture between a U.S.
and foreign firm. I define a dummy labeled JOINT VENTURE that receives the value of 1
if the bank is jointly owned by a foreign bank and a U.S. bank. It equals 0 otherwise.
With a domestic partner, the foreign bank may be more likely to adapt to host market
practices.
Third, larger organizations have greater resources, a better reputation, and greater
legitimacy ex ante (Pfeffer and Salancik, 1978; Deephouse, 1996). They therefore may
have greater flexibility in determining their strategy. For this reason, I control for
subsidiary bank size. I use the total assets of the subsidiary (BANK SIZE), expressed in
millions of U.S. dollars.
Fourth, I include a measure of the competition that the foreign subsidiaries are
likely to face in the local market. As Miller and Eden (2006) point out, foreign bank
subsidiaries in metropolitan cities face stiffer competition. They found that foreign banks
benefit less from imitating competitors in locations with a higher density of banks. To
control for the competition effect associated with location, I included the variable
NUMBER OF LOCAL RIVALS. The measure is defined as the number of rival
commercial banks in the local market (i.e., the MSA) in which the focal subsidiary is
located.
Although the number of local firms increases competition in the host market, a
stronger presence of foreign competitors may legitimize the focal foreign bank (Kostova
and Zaheer, 1999). To control for the impact of foreign presence in the local market, I

87
include a measure of FOREIGN RIVAL MARKET SHARE. It captures the deposits of all
foreign rivals, as a percentage of deposits for all banks in a local market.
Kostova and Zaheer (1999) point out subsidiaries of multinational firms with a
greater international presence face fewer legitimacy challenges in a given host country.
This is because multinational firms are able to leverage their experience in other
countries across different environments (Zaheer and Mosakowski, 1997; Kostova and
Zaheer, 1999; Martin and Salomon, 2003; Salomon and Martin, 2008). For this reason,
foreign bank subsidiaries may have more latitude to choose a differentiating strategy if its
parent bank has greater international experience (irrespective of the institutional context).
I therefore include a measure of INTERNATIONAL PRESENCE. It is defined as the
number of host countries in which the parent bank has opened banking institutes through
time t. This measure comes from the Banker’s Almanac.
In addition to the parent- and subsidiary- level controls, I include several macro
(country-level) factors that have to potential to impact foreign bank operations.
Specifically, I include a measure of bilateral FDI FLOW between the bank’s home
country and the United States. This measure comes from the Bureau of Economic
Analysis and captures the total amount (in 10
12
of U.S. dollars) of inward and outward
foreign direct investment (FDI) between the United States and a particular home country.
Scholars suggest that banks generally follow their clients when expanding to foreign
markets (Aliber, 1976, 1984; White, 1982; Grosse and Goldberg, 1991). When a foreign
bank subsidiary has more clients with headquarters in its own home country, it may elect

88
not to imitate local U.S. competitors because its clients may require services that are not
amenable to the current practices in the local market.
I complement the FDI flow measure with one that accounts for bilateral trade
flows between the bank’s home country and the United States. Again, when a foreign
bank establishes a subsidiary in the United States for the purpose of serving clients that
engage in trade with the home country, it may choose not to imitate local banks because
it is specifically tailored to meet the needs of typical, home-based clients. The variable
TRADE FLOW is therefore defined as the total amount (in 10
12
of U.S. dollars) of import
and export between the United States and the foreign bank’s home country in a given
year. This measure is drawn from the U.S. Census Bureau Foreign Trade Division Data
and the United Nations Comtrade database.
Finally, I control for the level of IMMIGRATION (in 10
6
of immigrants) from the
foreign bank’s home country into the United States in a given year. These data come
from the U.S. Census Bureau. As with FDI and trade, immigrants from the same home
country as the foreign bank may prefer a mix of services that are different than those
offered by local banks to local customers. Foreign bank subsidiaries may therefore be less
likely to adopt the strategies and practices of U.S. banks when more of its citizens live in
the host country.

89
3.4.6 Statistical Method
In selecting an appropriate multivariate statistical method, I first specify a foreign
bank’s local isomorphism strategy (LIS) as a linear function (OLS) of the independent
variables:
( )
it it it it it it it
Z EXP DIS EXP DIS LIS μ β β β β β + + + + + =
4 3 2 1 0
* (3.6)
where DIS is a matrix of institutional distance variables, EXP is a matrix capturing the
experience measures, Z is a matrix of controls, and
it
μ is the error term.
Given the panel data structure, with multiple firm observations over time, the
possibility arises that
it
μ in equation (3.6) will not be independent across time or within
firms (Greene, 2000). There are many possible time-dependent factors associated with
isomorphism – i.e., the propensity to imitate the strategy of domestic rivals is likely to
change over time. Should I be unable to identify and measure all of these time-dependent
effects, there exists the potential for a systematic component to be embedded in
it
μ .
Conceptually, I can decompose
it
μ into a vector of systematic (fixed) time effects, which
I label F
t
, plus a truly random error component, which we label e
it
. In this case, F
t

represents time dummies. After I extract F
t
from
it
μ , I can more confidently assume that
e
it
is i.i.d. normal with zero mean.
( )
it t it it it it it it
e F Z EXP DIS EXP DIS LIS + + + + + + =
4 3 2 1 0
* β β β β β

(3.7)
However, because there are multiple observations per bank, the possibility still
exists that e
it
in equation (3.7) will not be independent within banks over time. This

90
would occur if some banks systematically adopt isomorphism strategies for reasons
unobserved by this author. In theory, either a fixed effects or a random effects model may
be used to correct for heterogeneity of this sort (Greene 2000). However, in my data,
some countries only have one foreign bank operating in the U.S. market. It is therefore
not possible to estimate fixed effects, as they perfectly correlate with the time-invariant
distance measures (such as cultural distance) for those firms. Under this condition, a
random effects model is preferred (Kennedy 1998). I therefore arrive at the final
econometric specification:
( )
it i t it it it it it it
v D F Z EXP DIS EXP DIS LIS + + + + + + + =
4 3 2 1 0
* β β β β β (3.8)
In equation (3.8), D
i
represents the individual firm disturbance, and
it
v is i.i.d. normal
error term with zero mean. The efficient estimator employed is generalized least squares,
and nested models can be compared via adjusted R-squared.

3.5 Results
Table 3.2 presents descriptive statistics and product moment correlations.
Although correlations are generally as expected, some correlations among the distance
variables are elevated, hinting at a potential multicollinearity concern. However,
influence tests were not suggestive of multicollinearity. The maximum VIF score was
4.85 and the mean VIF was 1.92, well below the suggested threshold (Belsley, Kuh and
Welsch, 1980).

91

Table 3.2: Correlations

1. 2. 3. 4. 5. 6. 7. 8. 9. 10. 11. 12. 13. 14. 15. 16.
1. Local isomorphism 1.00
2. Performance -0.10 1.00
3. Bank asset 0.07 0.00 1.00
4. Joint venture 0.02 -0.01 0.04 1.00
5. Number of local rivals 0.12 -0.12 -0.16 -0.27 1.00
6. Foreign rival market share 0.19 -0.11 -0.09 -0.04 0.07 1.00
7. International presence 0.06 0.02 0.36 -0.10 0.01 -0.02 1.00
8. FDI flow -0.03 0.09 0.34 -0.19 -0.02 0.03 0.53 1.00
9. Trade flow 0.00 0.06 0.11 -0.24 0.00 0.14 0.25 0.73 1.00
10. Immigration 0.05 -0.01 -0.04 -0.04 0.08 0.09 -0.09 -0.04 0.07 1.00
11. Cultural distance 0.14 -0.08 -0.19 -0.02 0.16 0.23 -0.30 -0.25 0.08 0.06 1.00
12. Economic distance 0.05 0.02 0.08 0.05 -0.16 -0.08 0.11 0.09 -0.17 0.09 -0.30 1.00
13. Regulatory distance 0.00 0.00 0.19 0.01 -0.14 -0.18 0.32 0.16 -0.29 0.06 -0.64 0.42 1.00
14. Political distance -0.01 -0.04 -0.05 0.01 0.06 0.15 -0.08 -0.06 0.00 0.05 0.18 -0.08 -0.13 1.00
15. Vicarious experience -0.06 0.09 0.17 -0.07 -0.01 0.00 0.11 0.43 0.40 -0.05 0.16 -0.01 -0.21 0.00 1.00
16. Own experience -0.01 0.05 0.39 -0.07 -0.05 -0.03 0.64 0.48 0.23 0.05 -0.17 -0.04 0.14 -0.03 0.19 1.00
Mean -7.44 0.01 2.27 0.15 103.23 0.10 18.39 0.07 0.10 0.38 2.16 0.38 1.22 1.40 20.14 74.16
Standard Deviation 6.91 0.04 5.01 0.36 63.99 0.06 13.07 0.08 0.09 0.74 1.15 0.47 1.20 1.39 51.76 69.07
Minimum -141.42 -0.26 0.03 0.00 2.00 0.00 0.00 0.00 0.00 0.01 0.08 0.00 0.21 0.00 0.00 0.00
Maximum -1.27 0.71 51.20 1.00 458.00 0.79 76.00 0.36 0.48 9.18 4.37 2.73 6.79 13.00 358.00 555.00

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The multivariate regression results meant to test hypothesis 1 are presented in
Table 3.3. Column 1 consists of the base model of controls. Results suggest that the better
managed foreign bank subsidiaries are less likely to imitate their local U.S. rivals.
However, larger foreign bank subsidiaries (those with more assets under management)
are more likely to imitate local domestic competitors. In addition, joint ventures tend to
adopt local practices more than wholly-owned bank subsidiaries. In local markets with
more competitors, foreign subsidiaries also tend to adopt the practices of domestic firms.
Consistent with the findings of Miller and Eden (2006), foreign subsidiaries are more
likely to imitate local U.S. rivals when local competition is less severe.
The results from column 1 also suggest that FDI flows between the home country
and the U.S. increase are negatively related with foreign banks’ isomorphism strategy in
the United States. This suggests that firms that enter foreign market to service
multinationals from their home country are less likely to imitate domestic firms.
Interestingly however, although FDI flows have a negative impact on isomorphism; trade
flows have a positive impact. One possible explanation could be that foreign bank
subsidiaries require different resources to serve FDI clients versus foreign trade clients.

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Table 3.3: Regression Results-H1

DV=Local isomorphism 1. 2. 3. 4. 5. 6.
Constant -10.23*** -11.72*** -10.55*** -10.88*** -10.18*** -14.03***
(-8.32) (-8.39) (-8.53) (-8.34) (-8.23) (-8.71)
Performance -8.85* -8.21* -8.40* -8.43* -8.80* -6.71
(-1.43) (-1.32) (-1.35) (-1.36) (-1.42) (-1.09)
Bank size 0.20*** 0.21*** 0.20*** 0.21*** 0.21*** 0.21***
(3.86) (3.91) (3.85) (3.87) (3.87) (3.95)
Joint venture 1.23** 1.14* 1.19* 1.37** 1.23** 1.29**
(1.66) (1.54) (1.62) (1.84) (1.66) (1.73)
Number of local rivals 0.02*** 0.01*** 0.02*** 0.02*** 0.02*** 0.02***
(3.72) (3.32) (3.89) (3.92) (3.68) (3.65)
Foreign rival market share 16.61*** 14.91*** 16.94*** 17.33*** 16.67*** 15.63***
(4.00) (3.54) (4.09) (4.12) (3.99) (3.70)
International presence 0.03 0.03* 0.03 0.02 0.03 0.03
(1.06) (1.28) (1.13) (0.77) (1.03) (0.99)
FDI flow -14.00*** -8.58* -16.80*** -18.80*** -14.20*** -15.90***
(-2.50) (-1.41) (-2.91) (-2.98) (-2.52) (-2.45)
Trade flow 6.89* 3.09 9.46** 11.80** 7.00* 11.40**
(1.51) (0.64) (2.00) (2.16) (1.52) (2.06)
Immigration 0.22 0.32 0.11 0.05 0.22 0.01
(0.58) (0.84) (0.28) (0.14) (0.58) (0.02)
Cultural distance 0.65** 1.08***
(2.22) (3.27)
Economic distance 1.12** 1.04**
(2.02) (1.84)
Regulatory distance 0.48* 0.80***
(1.63) (2.46)
Political distance -0.10 -0.15
(-0.59) (-0.88)
Bank effect YES YES YES YES YES YES
Time effect YES YES YES YES YES YES
N 891 891 891 891 891 891
R-sq
(d.f.)
0.086
(14)
0.098
(15)
0.092
(15)
0.088
(15)
0.086
(15)
0.118
(18)

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Columns 2 through 5 introduce the institutional distance variables meant to test
hypothesis 1. The positive and significant coefficient on cultural distance from column 2
indicates that foreign bank subsidiaries are more likely to adopt local isomorphism
strategies as the cultural distance between the home country and the United States
increases. Column 3 adds the economic distance measure. Similar to the findings for
cultural distance, the results suggests that foreign banks from markets that are more
economically distant from the United States are more likely to imitate local banking
practices. Column 4 introduces the banking regulatory distance measure, which is
likewise positively related to local isomorphism strategy. By contrast, the results from
column 5 do not demonstrate a link between political distance and local isomorphism.
Column 6 presents the full specification. The direction and significance of coefficients
are similar to the results in columns 1-5. In general, the results presented are generally
supportive of hypothesis 1. That is, foreign banks are more likely to imitate their local
U.S. competitors as the cultural/economic/regulatory distance between the bank’s home
country and the United States increases.
In Table 3.4 I test the moderating impact of vicarious learning on isomorphism. Given the
substantial correlations among interaction terms (Jaccard, Turrisi, and Wan, 1990), I
introduce the distance/learning interactions individually. Column 1 presents results on the
main effect of vicarious learning. Consistent with prior studies, foreign banks are less
likely to imitate local banks as the experience of similar foreign banks (from the same
home country) accumulates. Columns 2-5 present the models testing the moderating
impact of vicarious learning and each of the institutional distance variables. Although the

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main results are consistent with those presented in Table 3.3, the results across columns
2-5 are inconsistent with hypothesis 2. Except for the interaction of economic distance
and vicarious experience, none of the interaction terms have a significant negative impact
on local isomorphic strategy. Although firms are less likely to choose local isomorphism
strategies as the experience of firms from their own home country increases, that effect is
constant throughout the sample. That is, firms from more institutionally dissimilar home
countries are no more likely to change their isomorphism decisions than firms from more
institutionally similar home countries as a result of that experience. Hypothesis 2 is
therefore not supported.

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Table 3.4: Regression Results-H2

DV=Local isomorphism 1. 2. 3. 4. 5. 6.
Constant -14.03*** -13.89*** -14.13*** -13.97*** -13.88*** -13.66***
(-8.89) (-8.73) (-8.90) (-8.78) (-8.73) (-8.34)
Performance -6.53 -5.96 -6.89 -6.47 -6.14 -5.94
(-1.06) (-0.96) (-1.11) (-1.04) (-0.99) (-0.96)
Bank size 0.22*** 0.22*** 0.24*** 0.22*** 0.22*** 0.24***
(4.09) (4.13) (4.38) (4.10) (4.18) (4.44)
Joint venture 1.30** 1.37** 1.42** 1.30** 1.32** 1.45**
(1.78) (1.86) (1.93) (1.75) (1.79) (1.92)
Number of local rivals 0.02*** 0.02*** 0.02*** 0.02*** 0.02*** 0.02***
(3.69) (3.55) (3.70) (3.64) (3.64) (3.50)
Foreign rival market share 15.65*** 15.37*** 15.37*** 15.47*** 15.42*** 14.83***
(3.72) (3.64) (3.65) (3.66) (3.66) (3.50)
International presence 0.03 0.03 0.03 0.03 0.03 0.03
(1.06) (0.98) (1.10) (1.03) (1.10) (0.95)
FDI flow -13.10** -12.30** -12.90** -13.30** -13.30** -12.40**
(-2.00) (-1.86) (-1.97) (-2.02) (-2.02) (-1.86)
Trade flow 11.90** 11.60** 11.50** 12.00** 11.70** 11.50**
(2.19) (2.12) (2.11) (2.18) (2.13) (2.05)
Immigration -0.06 -0.06 -0.05 -0.05 -0.04 -0.04
(-0.61) (-0.15) (-0.14) (-0.13) (-0.12) (-0.10)
Cultural distance 1.21*** 1.14*** 1.21*** 1.20*** 1.23*** 1.08***
(3.72) (3.41) (3.69) (3.64) (3.73) (3.00)
Economic distance 1.18** 1.13** 1.38*** 1.17** 1.19** 1.32**
(2.08) (2.00) (2.39) (2.06) (2.10) (2.26)
Regulatory distance 0.72** 0.73** 0.67** 0.71** 0.70** 0.63**
(2.22) (2.24) (2.06) (2.13) (2.16) (1.85)
Political distance -0.16 -0.16 -0.19 -0.15 -0.26* -0.24*
(-0.94) (-0.95) (-1.13) (-0.91) (-1.41) (-1.28)
Vicarious experience -0.01** -0.07 0.01 -0.01* -0.02*** -0.11
(-1.90) (-1.03) (0.59) (-1.34) (-2.32) (-1.07)
Cultural distance 0.02 0.04
*Vicarious experience (0.87) (1.10)
Economic distance -0.04** -0.03*
*Vicarious experience (-1.85) (-1.36)
Regulatory distance 0.00 0.02
*Vicarious experience (0.09) (0.64)
Political distance 0.00* 0.00
*Vicarious experience (1.36) (0.82)
Bank effect YES YES YES YES YES YES
Time effect YES YES YES YES YES YES
N 891 891 891 891 891 891
R-sq
(d.f.)
0.123
(19)
0.123
(20)
0.127
(20)
0.123
(20)
0.125
(20)
0.127
(23)

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In Table 3.5, columns 1-6 present results of tests examining the moderating
impact of experiential learning. Again, I introduce each of the interaction terms
individually. Column 1 presents the main effect of experiential learning. Although the
negative coefficient is consistent with an interpretation that firms become less likely to
choose isomorphic strategies with experience, the effect does not statistically differ from
zero. Moreover, the results across columns 2-6 do not suggest that a foreign bank’s own
experience moderates the impact of cultural distance, economic distance, regulatory
distance, or political distance. Therefore, hypothesis 3 fails to receive support.
In sum, the results provide support for hypothesis 1. That is, foreign bank
subsidiaries are more likely to imitate local U.S. banks as the institutional distance
between the home and the host countries increases. By contrast, hypotheses 2 and 3 do
not receive support. Experience (both vicarious and own-firm) had no appreciable
moderating impact on the relationship between institutional distance and isomorphism.
Taken together, these findings are indicative of the strong inertia of strategic decisions.

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Table 3.5: Regression Results-H3

DV=Isomorphism 1. 2. 3. 4. 5. 6.
Constant -13.68*** -13.37*** -13.73*** -13.68*** -13.71*** -13.07***
(-8.15) (-7.62) (-8.09) (-7.99) (-8.11) (-6.60)
Performance -6.56 -6.33 -6.61 -6.55 -6.74 -6.29
(-1.06) (-1.02) (-1.07) (-1.06) (-1.09) (-1.01)
Bank size 0.21*** 0.21*** 0.21*** 0.21*** 0.22*** 0.21***
(4.02) (3.86) (3.99) (3.95) (4.06) (3.90)
Joint venture 1.26** 1.22* 1.26** 1.26** 1.25** 1.20*
(1.68) (1.62) (1.68) (1.67) (1.66) (1.57)
Number of local rivals 0.02*** 0.02*** 0.02*** 0.02*** 0.02*** 0.02***
(3.58) (3.56) (3.54) (3.57) (3.58) (3.44)
Foreign rival market share 15.43*** 15.56*** 15.35*** 15.39*** 15.35*** 15.27***
(3.64) (3.65) (3.62) (3.62) (3.61) (3.56)
International presence 0.04 0.03 0.04 0.04 0.04 0.04
(1.17) (1.08) (1.23) (1.15) (1.16) (1.14)
FDI flow -15.40*** -14.80** -15.20** -15.30** -16.20*** -15.70**
(-2.33) (-2.22) (-2.29) (-2.28) (-2.42) (-2.29)
Trade flow 11.10** 10.50** 10.90** 11.00** 11.60** 10.90**
(1.99) (1.85) (1.93) (1.94) (2.06) (1.86)
Immigration 0.05 0.05 0.07 0.05 0.04 0.06
(0.13) (0.11) (0.17) (0.13) (0.11) (0.13)
Cultural distance 1.06*** 0.92** 1.07*** 1.06*** 1.01*** 0.75*
(3.17) (2.22) (3.16) (3.15) (2.94) (1.53)
Economic distance 0.99** 0.86* 1.30* 0.97* 0.99** 1.25*
(1.74) (1.42) (1.45) (1.58) (1.73) (1.34)
Regulatory distance 0.77*** 0.82*** 0.74** 0.79** 0.77*** 0.66*
(2.36) (2.42) (2.21) (1.79) (2.33) (1.38)
Political distance -0.14 -0.13 -0.14 -0.14 0.03 0.06
(-0.84) (-0.80) (-0.86) (-0.84) (0.09) (0.20)
Own experience -0.004 -0.008 -0.002 -0.003 -0.002 -0.009
(-0.66) (-0.86) (-0.32) (-0.50) (-0.25) (-0.56)
Cultural distance 0.002 0.004
*Own experience (0.58) (0.75)
Economic distance -0.006 -0.007
*Own experience (-0.45) (-0.54)
Regulatory distance -0.000 0.001
*Own experience (-0.06) (0.34)
Political distance -0.002 -0.002
*Own experience (-0.69) (-0.77)
Bank effect YES YES YES YES YES YES
Time effect YES YES YES YES YES YES
N 891 891 891 891 891 891
R-sq
(d.f.)
0.118
(19)
0.118
(20)
0.117
(20)
0.117
(20)
0.118
(20)
0.117
(23)

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3.6 Discussion

Research in international business suggests that foreign firms are at a
disadvantage when operating abroad. This liability of foreignness stems from a broad
unfamiliarity with the local environment, and results in a lack of legitimacy. Although
scholars suggest that foreign firms may imitate local firms to achieve legitimacy, there
has been little systematic research into which firms we might expect to pursue such
strategies, and why. Moreover, we know less than we should about which firms, from
which home nations, stand to benefit from pursuing such strategies. To fill that gap, this
study examined whether variance exists in the level of local isomorphism adopted by
firms from different home countries. Specifically, I examined the impact of institutional
distance between home and host countries on the imitation of domestic firm strategies.
I argued that the difficulty of operating in a given host country is likely to
increase with the institutional distance between the host and home country. As a result,
foreign firms from institutionally distant countries face greater legitimacy challenges in a
new market. As a result, I hypothesized that they would be more likely to engage in local
isomorphism as a mitigating strategy.
Consistent with that hypothesis, I find that the asset strategy adopted by of foreign
banks operating in the United States more closely resembles the average asset strategy of
local U.S. banks as the cultural, economic, and regulatory distances between the home
country and the U.S. increase. More broadly, the findings suggest that the institutional
distance between two countries affects the strategy selection of foreign firms. The
economic magnitude of institutional distance effects are reported in table 3.6. Column 1

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shows the marginal effect of institutional distance on local isomorphism choice. Column
2 reports the percentage changes to local isomorphism as each dimension of institutional
distance increase 1 standard deviation. The results show that the extent of local
isomorphism will increase by 16.79% if the cultural distance between the home country
and the United Stated increases by 1 standard deviation. Likewise, if the economic and
regulatory distances increase by 1 standard deviation, local isomorphism in asset strategy
will increase by 6.68% and 12.99%, respectively.

Table 3.6: Marginal Effects of Institutional Distance
DV=LIS 1. dy/dx 2. dx=1 std.dev
Cultural distance 1.08*** 16.79%
(3.27)
Economic distance 1.04** 6.68%
(1.84)
Regulatory distance 0.80*** 12.99%
(2.46)
Political distance -0.15 2.74%
(0.87)

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I then conditioned the arguments regarding the main effects of institutional
distance to suggest that vicarious and experiential learning would moderate the impact of
distance on isomorphism. Specifically, I suggested that foreign firms from distant home
countries benefit from the experiences of home country competitors that entered before
them. I hypothesized that ex ante market knowledge garnered from those competitors
would lessen the impact of institutional distance on isomorphism, and make it less likely
that a foreign firm from an institutionally distant country would adopt an isomorphism
strategy. Similarly, I argued that foreign firms would benefit from their own market
experience. Such market experience would allow them greater strategic latitude in the
host market. As such, I hypothesized that foreign firms from institutionally distant
countries would adjust their isomorphic practices as they learned about the host country
through their own experiences.
The empirical results did not bear out either claim. Rather, taken together, the
findings suggest that the strategies of foreign banks are relatively stable over time. That is,
institutional distance has a strong, direct influence on strategy choice. Moreover firms are
bound to those initial commitments – i.e., there are strong inertial tendencies.
The findings from this study offer useful insight for scholars and practitioners.
First, this study demonstrates that substantial heterogeneity exists in isomorphic
strategies. The findings suggest that local isomorphism strategies are be better suited for
some firms than others. Specifically, foreign firms from distant institutional contexts will
find it more advantageous to imitate local competitors. Future research would be well

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served to examine other sources (both national and firm level) of heterogeneity in the
choice of local isomorphism strategy.
Second, this study explicitly treats institutional distance as a multi-dimensional
construct. Although prior studies have explored the impact of institutional distance on the
activity of foreign firms (e.g. Kogut and Singh, 1988; Benito and Gripsrud, 1992;
Brouthers and Brouthers, 2001; Henisz and Delios, 2001; Perkins, 2008), most studies
focus solely on the impact of one dimension of distance. That is, scholars often study
culture, economics, regulation, or politics in isolation. To my knowledge, none examine
the joint impact of these dimensions simultaneously – recognizing that they stand to
explain a unique portion of the variance in firm behavior. Given that I find that different
dimensions of institutional distance impact firm strategy in complex ways, future
research would be well served to incorporate such a multi-dimensional distance construct.
Moreover, future theoretical and empirical work should seek to explain why different
dimensions of distance impact firm strategy differently.
Finally, for practitioners, this study highlights the impact of institutional distance
on the strategic choices that firms make. Managers should therefore make decisions of
this type with these considerations in mind. In particular, managers should keep in mind
that while a strategy of local isomorphism may help firms from institutionally distant
countries quickly establish legitimacy, strategic decisions of this sort usually bind a firm
to a given strategic direction. That is, the choice of a local isomorphism strategy in the
near term may constrain a firm’s ability to change that strategy moving forward.

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This is not to say however that choosing a strategy of local isomorphism will be
optimal for all firms from institutionally distant countries. In fact, I do not explicitly
address firm performance in this study. However, if we assume that firms choose
strategies based on their expected impact on performance (e.g., Shaver, 1998), I would
expect firms from distant countries that pursue isomorphic strategies to perform better.
Future research would therefore be well served to examine the performance
consequences of isomorphic strategies, conditioned on the first stage impact of
institutional distance on isomorphism.

3.7 Limitations
At this point, I draw several caveats. First, although I discuss local isomorphism
strategies throughout this study, I examine one specific type of isomorphism strategy –
i.e., the imitation of asset allocation strategies by banks. Although this has been described
as an important strategic consideration for firms in the banking industry (Haveman, 1993;
Mehra, 1996; Deephouse, 1999), this is not the only strategic variable over which firms
have discretion. However, I would broadly expect the strategic choice examined here to
extend to other types of strategic decisions.
Second, I acknowledge that I examine isomorphism in one specific context – the
banking industry. This industry is highly regulated in most countries. Though the data
allow me to observe the strategy and performance of foreign banks from a number of
countries, the unique industry setting may overstate the effect of regulatory distance.
Therefore, it calls generalizability of the findings into question.

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Third, the measure of local isomorphism strategy may not capture the imitative
activities of foreign banks appropriately. To measure local isomorphism, I compare the
asset strategy of a focal foreign bank with the average asset strategy of local U.S. banks.
However, the average may not represent the strategy of the majority. Though the standard
deviation controls for the variance of local practices, it is still not clear whether the
average value faithfully reflects the asset strategy of the major local U.S. banks.
Fourth, both the cultural distance and the regulatory distance variables are time-
invariant. To the extent that banking regulations and cultural characteristics change
frequently, the results may be inhered with some bias. However, as international business
scholars note, banking regulations have been relatively stable over time (Barth, Caprio
and Levine, 2000), and cultures are generally slow to change.
Ultimately, further corroboratory research is needed before stronger conclusions
can be drawn. However, the aforementioned limitations notwithstanding, this study
provides insight into a novel strategic phenomenon. Although this study represents a first
attempt to examine what is surely a much more complex phenomenon, I hope others will
improve upon my contribution by examining the interplay among country institutions,
firm-specific characteristics, and strategy.

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CHAPTER 4

INSTITUTIONAL DISTANCE, LOCAL ISOMORPHISM STRATEGY AND
FOREIGN SUBSIDIARY PERFORMANCE

4.1 Introduction
International business scholars have long recognized that foreign firms face
disadvantages when competing with domestic firms in a host country (Hymer, 1960;
Zaheer, 1995). Foreign firms originate from environments that differ than the host
country. They therefore know less about the local market, have fewer ties in the host
country environment, and incur greater costs of cross-country coordination and operation
(Hymer, 1960; Zaheer, 1995). Known as “liability of foreignness” (Zaheer, 1995), these
disadvantages adversely impact foreign subsidiary profitability and survival rates (Zaheer,
1995; Zaheer and Mosakowski, 1997).
Prior literature has demonstrated the liability of foreignness from various
perspectives (e.g. Zaheer, 1995; Lipsey, 1994; Mezias, 2002; Salomon and Martin, 2008).
However, only a few studies examined whether foreign firms’ origin (their home country)
affected their performance in the host country. Moreover, many studies focus on the
cultural background of foreign firms (for a summary, see Tihanyi, Griffith and Rusell,
2005), while the economic, regulatory, and political environments of the home country
may impact foreign firms’ operation abroad as well. As a result, we know less about how
foreign firms’ heterogeneous origin is associated with their performance in the host
country. To fill this gap, I examine whether the institutional distance

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(cultural/economic/regulatory/political distance) between the home country and the host
country affects foreign firm performance in the host country market.
To overcome the liability of foreignness, firms may adopt mitigating strategies.
Prior international business literature explores the strategies that foreign firms may adopt
to offset this liability and improve performance. One important strategy is to imitate
elements of the strategies and business practices of the domestic competitors in the host
country (Zaheer, 1995), i.e. to adopt a local isomorphism strategy. By adopting local
business practices, foreign firms better fit the host country institutional environment.
Conforming helps firms acquire legitimacy in the local market and therefore offset the
disadvantages that the firms face. Based on this argument, scholars predict a positive
impact of local isomorphism on foreign subsidiary performance (Zaheer, 1995). However,
prior empirical studies did not demonstrate the predicted positive effect (Zaheer, 1995;
Miller and Eden, 2006).
Though these studies provide important insights on the performance consequence
of local isomorphism strategies, they do not explore how foreign firms make
isomorphism decisions, and therefore treat strategy selection as exogenous. Foreign firms
may choose the level of isomorphism according to a variety of firm attributes and
environmental conditions. The selected strategy in turn impacts firm operation and
performance. In other words, local isomorphism strategy is endogenous (Shaver, 1998).
Since prior studies have not examined the antecedents of isomorphism strategy, we know
little about the underlying mechanism by which this strategy, as an endogenous variable,
impacts foreign subsidiary performance.

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To complement prior studies, I argue that local isomorphism, as a strategic
decision contingent on the institutional distance between the home country and the host
country and other factors, positively impacts foreign subsidiary performance.
I test the hypotheses on institutional distance, local isomorphism strategy, and
foreign subsidiary performance on a sample of 84 foreign bank subsidiaries in the U.S.
banking industry from 1978 to 2006. As expected, cultural, economic and regulatory
distances have a negative impact on foreign subsidiary performance. I then use an
instrumental variable two-stage least square regression model to estimate the impact of
local isomorphism strategy on performance. The results show that, once accounting for
endogeneity, local isomorphism strategies have a positive and significant impact on
foreign bank subsidiary performance. This finding suggests that as a decision based on
firm-level and country-level factors, local isomorphism strategies help to improve foreign
subsidiary performance.
This study makes several contributions to the strategy and the international
business literature. First, it examines the impact of the multi-dimensional institutional
distance on foreign subsidiary performance. The results suggest that cultural, economic,
and regulatory distances negatively impact performance. Although prior studies have
noted this potential impact, most studies examine only one dimension of distance, e.g.
cultural distance. This study demonstrates that other dimensions are no less important
than cultural distance. Second, it adds to our knowledge how local isomorphism, as a
strategic decision based on firm characteristics, market conditions, and institutional
distance, affects foreign subsidiary performance. Though prior literature has studies

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performance consequence of local isomorphism, it did not explore how foreign firms
choose this strategy by considering firm and environmental factors and anticipating its
impact on performance. By contrast, this study shows that local isomorphism strategy, as
an endogenous decision, is positively related to performance. Interestingly, the negative
effect of institutional distance on performance remains even though isomorphism strategy
has a positive impact. Taken together, it suggests that local isomorphism, while helpful,
does not completely eliminate the impact of institutional distance. Foreign firms may use
other strategies in combination with local isomorphism to offset distance-related
disadvantage.

4.2 Literature Review
Foreign firms face disadvantages when competing with domestic firms in a host
country. Empirical studies have indicated the various impacts of the liability of
foreignness. For example, foreign trading rooms are less profitable and more likely to fail
than domestic trading rooms (Zaheer, 1995; Zaheer and Mosakowski, 1997); foreign
banks have lower levels of x-efficiency (Miller and Parkhe, 2002); foreign firms face
more lawsuit judgments (Mezias, 2002); and foreign firms take longer to start-up
operations than their domestic competitors (Salomon and Martin, 2008). Overall, these
findings show that foreign firms have competitive disadvantages compared with domestic
firms (Miller and Eden, 2006).
This disadvantage arises from the additional costs and risks of operating in a
foreign country (Zaheer, 1995). For example, with a psychic distance, foreign firms incur

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high cost of collecting, interpreting, and transferring the information about the host
country market (Johanson and Vahlne, 1977); a great institutional distance between two
countries decreases foreign firms’ legitimacy in the host country (Kostova and Zaheer,
1999); and the host country environment may therefore discriminate against these firms
(Zaheer, 1995). In addition, the difference in culture and other institutions also prevents
foreign firms to get access to and learn from local domestic firms (Makino, Isobe, and
Chan, 2004). In a summary, prior literature suggests that the differences among various
institutional environments, i.e. multiple dimensions of institutional distances, increase the
difficulty of operating business abroad and adversely impacts foreign subsidiary
performance.
However, the overwhelming majority of extant literature focuses on a single
dimension of institutional distance (namely, culture) when estimating the link between
distance and foreign subsidiary performance. For example, Li and Guisinger (1991)
found that the international joint ventures are more likely to fail when the cultural
distance between the U.S partner and the other party is great. Similarly, Barkema,
Shenkar, Vermulen, and Bell (1997) found that the longevity of international joint
ventures decreases with cultural distance when experience is under control (For a
summary of the literature on cultural distance, please see Tihanyi, Griffith and Russel,
2005).
In the study of institutional distance, Gaur and Lu (2007) found that foreign
subsidiary survival rate is positively associated with institutional distance between two
countries when this distance is low. At high levels of institutional distance, this

110
relationship becomes negative. Although their measures of institutional distance employ
indicators of political systems and legal systems, they did not account for the distance in
economic systems, industrial regulations, and cultures. Perkins (2008) takes a more
comprehensive view of institutional distance. While she focuses on the impact of firm
experiences in countries with various industrial regulations, she also controls for cultural,
political, legal distance between two countries in the regressions. Each of these
dimensions has different impact on firm survival rate. Therefore, her study implies that
more investigation in the institutional distance, as a multi-dimensional construct, is
important.
The findings above broaden our knowledge on the impact of institutional distance.
However, we know less than we should about the impact of institutional distance as a
multi-dimensional concept. Focusing on a single dimension of distance—e.g., cultural
distance—may generate biased results because of the uncontrolled potential impact of
other distance dimensions. Building on these prior studies, I measure institutional
distance as the cultural, economic, regulatory, and political distances between the home
country and the host country. I would like to test the link between these dimensions and
the foreign subsidiary performance.
Although foreign firms face disadvantages associated with distance, they may
adopt strategies to reduce the negative impact of distance. One strategy they adopt is to
imitate elements of strategies and business practices of local competitors in a host
country (Rosenzweig and Nohria, 1994; Zaheer, 1995; Miller and Eden, 2006). As
institutional theory suggests, organizations may imitate others’ activities because they

111
face the social pressures to comply with dominant norms, because they have limited
ability to make decisions in uncertain environment, and/or because they are affected by
the prevalent professional knowledge (DiMaggio and Powell, 1983). By adopting the
activity of the majority, organizations obtain legitimacy as the social environment views
their practices to be rational and efficient (Meyer and Rowan, 1977). Consistent with this
theory, Deephouse (1996) finds that local isomorphism is positively related to the level of
legitimacy that banks obtain from regulators and public media.
Legitimacy is an important resource that affects organization performance and
survival (Meyer and Rowan, 1977; Hannan and Freeman, 1988). A firm that lacks
legitimacy experiences difficulty acquiring resources and external support (DiMaggio
and Powell, 1983). For example, customers and suppliers may require higher risk
premium if the firm becomes less legitimate (Cornell and Shapiro, 1987). Prior research
also shows that more legitimate organizations are more likely to survive when facing
intense competition (Baum and Oliver, 1991). Overall, legitimacy enables firms to get
access to external resources that can be critical for performance and survival.
For foreign firms operating in a host country, legitimacy is even more crucial
because they lack roots in the local environment (Zaheer, 1995; Kostova and Zaheer,
1999). Lacking legitimacy, foreign firms face barriers to obtain resources from potential
partners such as regulators, customers and suppliers (DiMaggio and Powell, 1983).
Therefore, obtaining legitimacy in the local environment is important for foreign firms to
survive and grow in the host country (Rosenzweig and Singh, 1991).

112
To test the impact of local isomorphism strategy on foreign subsidiary
performance, Zaheer (1995) examined the performance of foreign trading rooms. The
results showed that imitating local competitors does not necessarily lead to better
performance. Similarly, Miller and Eden (2006) find no direct relationship between the
isomorphism strategy and subsidiary performance in a study on foreign bank subsidiaries
in the United States.
There are several possible explanations to the lack of support for the predicted
positive effect of isomorphism strategy. First, the strategy of imitating practices of local
competitors may have both positive and negative impacts on firm performance
(Deephouse, 1999). On the one hand, isomorphism enhances a firm’s legitimacy in the
local environment (DiMaggio and Powell, 1983), which is an important resource for
success. On the other hand, by mimicking competitors, a firm may demand the same
resources as its competitors. Among these firms, the competition for same resources
therefore intensifies. Competition, in turn, leads to deteriorated performance. Second,
and based on the aforementioned insights, Miller and Eden (2006) argue that the impact
of isomorphism is context specific. That is, depends on the level of local competition. In
a study on foreign banks in the U.S., they find that foreign banks benefit from imitating
their domestic local competitors only when they locate in a city with fewer competitors
(Miller and Eden, 2006). As competitors increase, this positive impact diminishes. This
finding also suggests that other environmental conditions and firm attributes besides
location may affect the role of isomorphism. Third, foreign firms may use other strategies
to improve their performance in the host country, which could be incompatible with local

113
isomorphism. For example, foreign firms might be better able to establish a competitive
advantage in the host country if they transfer superior resources developed in the home
country rather than imitate local firms (Buckley and Casson, 1976; Caves, 1996). Foreign
subsidiaries may therefore use different strategies and practices than local domestic
competitors.
For all these reasons, a clear link between isomorphism strategy and performance
has yet to be established. Moreover, a more fundamental explanation remains unexplored.
That is, we know little about the underlying mechanisms by which foreign firms choose
local isomorphism to reduce their liability. Local isomorphism, as all other strategies, is a
decision made by managers. The self-selected strategic choice should be treated as an
endogenous variable when the research tests the strategy-performance relationship
(Shaver, 1998). In other words, foreign firms are heterogeneous when they choose the
level of isomorphism. It is important to study and account for this heterogeneity in a
study on the performance impact of isomorphism. However, most studies on foreign firm
local isomorphism strategy do not explicitly examine this heterogeneity, but rather, treat
this local isomorphism as exogenous.
Miller and Eden (2006) control for unobserved heterogeneity using a fixed effects
model to examine the impact of local isomorphism strategy on foreign bank performance.
With some simplifying assumptions, the fixed effects model can account for endogeneity
(Hsiao, 2003). However, their model did not explicitly examine how foreign firms choose
this strategy based on a host of factors both internal, and external, to the firm. To account
for the underlying mechanism of strategy selection, I propose to adopt the simultaneous-

114
equations model to estimate the relations between the local isomorphism strategy and
foreign subsidiary performance.
In a summary, there are two gaps in prior studies on foreign subsidiary
performance. First, no prior study has examined the performance impact of institutional
distance as a multi-dimensional construct. Second, prior studies on local isomorphism
strategy have not studied and accounted for the underlying mechanisms of how foreign
firms choose the level of local isomorphism. To fill this gap, I propose two research
questions: how does the multi-dimensional institutional distance impact foreign
subsidiary performance? How does local isomorphism strategy, as an endogenous choice
of the firm, affect foreign subsidiary performance?

4.3 Hypotheses
4.3.1 Institutional Distance
Scholars in the field of international business have defined the liability of
foreignness as the additional costs and risks of doing business in a foreign country
(Zaheer, 1995). An important source of these costs and risks is the difference between
two countries in their institutional environment: the institutional distance (Johanson and
Valhne, 1977; Kostova and Zaheer, 1999).
Institutional distance is defined as the similarity or difference between two
countries in terms of their institutional context (Kostova and Zaheer, 1999; Xu and
Shenkar, 2001). The institutional context includes both formal and informal institutions
(Scott, 1995). Formal institutions include regulations, politics, economic systems, and

115
laws, while informal institutions refer to social norms, values, and beliefs, such as
cultures and customs.
As institutional distance increases, foreign firms may have less knowledge of the
local environment (Johanson and Vahlne, 1977). Moreover, the host country environment
is likely to perceive foreign firms to be less legitimate than domestic firms as they origin
from more distant institutional contexts (Kostova and Zaheer, 1995). Therefore, foreign
firms, from a distant home country, may face greater difficulty to acquire knowledge of
the local market and build local ties. With greater difficulty, these foreign firms may thus
incur higher costs and greater risks, which in turn lower their performance in the host
country. Each dimension of institutional distance contributes to the costs and risks of
foreign firms.
Cultural distance leads to the difference in organizational practices across
countries (Kogut and Singh, 1988). Facing a large cultural distance, foreign firms may
have difficulty understanding and complying with the social norms of the local market.
On the other hand, local parties, such as suppliers and customers, may be less familiar of
the strategies and practices adopted by foreign firms. Therefore, these local partners are
likely to perceive foreign firms less legitimate as the cultural distance increases (Zaheer
and Mosakowski, 1997). Cultural distance may thus increases the costs and risks of
foreign firms.
With a great economic distance, the host country market may appear more
uncertain for foreign firms. Originating from a different economic environment, foreign
firms lack important knowledge of the local market that is accessible only through

116
experience (Johanson and Vahlne, 1977). Without this experiential knowledge of the
market, foreign firms are less capable of capturing the opportunities and interpreting the
uncertainties of the local market. Therefore, the costs and risks of operating in this market
increases with economic distance.
Because of regulatory distance, the business practices and strategies adopted by
foreign firms in the home country may not be transferable to the host country. Foreign
firms may have to develop new routines and strategies that comply with the regulations in
the new market. Therefore, foreign firms may incur costs of developing, testing, and
implementing new practices.
Likewise, political systems also vary across countries. Embedded in a particular
political environment, firms develop routines and practices that conform to the context.
As firms establish business in a different environment, they have to adapt their practices
to this new context. The adaptation costs increase with political distances.
Overall, the costs and risks of operating business in a foreign country increase
with institutional distance. From a distant institutional environment, foreign firms are less
familiar with the new market. Moreover, institutional distance decreases foreign firms’
legitimacy in a host country (Kostova and Zaheer, 1999). As institutional distance
increases, foreign firms incur higher costs of acquiring local knowledge, building ties
with local parties, and adapting business practices to the local environment. Furthermore,
they also experience greater risks because they are less capable of understanding the local
market and adapting to it accordingly. In a summary, institutional distance may be
associated with higher costs and risks for foreign firms, the performance of which

117
decreases as a consequence. Therefore, it is likely that foreign firms with different origins
face different levels of disadvantages in a host country.
H1: All else being equal, foreign subsidiary performance is lower as the
institutional distance between the host country and the home country increases.

4.3.2 Local Isomorphism Strategy
Facing the liability of foreignness, foreign firms adopt strategies reduce this
disadvantage. For example, foreign firms may attempt to comply with the demand of the
host country environment in order to achieve legitimacy. To adapt to this environment,
foreign firms may imitate elements of strategies and business practices used by their
competitors in the local market because these activities are likely to be regarded as
appropriate and rational by this environment (Rosenzweig and Singh, 1991). Therefore,
isomorphism strategies may help foreign firms to acquire legitimacy that they lack in the
host country.
However, isomorphism strategy does not legitimize foreign firms without a cost.
On one hand, competition for similar resources intensifies as more firms choose the same
strategy (Carroll, 1985). Intensified competition in turn increases the likelihood of firm
failure (Hannan and Freeman, 1977; Baum and Singh, 1994). Consistent with this
argument, Deephouse (1999) finds that too much isomorphism is negatively related to the
performance of U.S. banks. On the other hand, as foreign firms imitate more of local
strategies in the host country, they become more localized. However, they are less
capable to follow the standard strategies and practices that their parent firms use in the

118
home country. The difference between subsidiary strategy and headquarter strategy may
increase the cost of coordination. Moreover, parent firm strategies and practices could
represent an important resource that generates economic rents. By local isomorphism,
foreign subsidiaries do not fully exploit the benefit of this resource.
The above argument suggests that local isomorphism does not benefit foreign
firms equally. Therefore, foreign firms may choose the level of isomorphism by
considering their firm-specific features, industrial conditions, and environmental
attributes. For example, the institutional distance between the home and the host country
may be one of these considerations. Foreign firms from a more distant institutional
context may find the local isomorphism more helpful. On the one hand, these firms face a
greater legitimacy disadvantage in the host country, compared with the foreign firms
from countries that are similar to the host country. Therefore, it is more crucial for the
firms with a distant origin to build legitimacy in the local environment. Since
isomorphism leads to legitimacy, these firms may find the isomorphism strategy more
beneficial. On the other hand, foreign firms from a more distant institutional environment
are less familiar with the local cultures, norms, and customs in the host country. Lacking
local knowledge, they are less capable of applying resources such as routines and
strategies from parent firms in the local environment. Therefore, they may benefit less
from using parent firm strategies. Overall, foreign firms with a distant origin are more
likely to benefit from local isomorphism.
Foreign firms, considering their unique features (such as the institutional distance),
may choose the level of isomorphism that enables them to improve performance in the

119
host country. If we did not explore the mechanisms by which foreign firms make this
strategic decision, we might not be able to truly understand how the local isomorphism
strategy affects foreign subsidiary performance. Assuming that foreign firms choose local
isomorphism to improve their performance in the host country, I argue that this strategy,
as an endogenous decision, positively impacts foreign subsidiary performance. State
formally:

H2: All else being equal, local isomorphism strategy is likely to be positively
related to foreign subsidiary performance.

4.4 Research Design
4.4.1 Data
To study foreign firms’ local isomorphism strategies, I have chosen the empirical
setting of foreign bank subsidiaries operating in the United States from 1978 to 2006. The
U.S. banking industry is highly regulated and banks face strong pressures to conform to
the institutional environment (Scott and Meyer, 1991; Deephouse, 1996; Miller and Eden,
2006). Banks are not only influenced by formal regulations (Sponge, 1990), but at the
same time must make an effort to obtain legitimacy (Deephouse, 1996). Therefore, this
industry offers an appropriate setting to study the isomorphic strategies of foreign firms.
My initial dataset comes from the Reports of Condition and Income (known as the

120
Call Reports) from the Federal Reserve Bank of Chicago. The Federal Reserve Bank
provides these reports for all commercial banks in the United States from 1976 to 2006.
Call Reports provide financial data on each commercial bank regulated by the Federal
Reserve System, Federal Deposit Insurance Corporation, and the Comptroller of the
Currency. I use these Call Reports to measure the presence of foreign banks in local
markets, and to estimate the asset strategy of banks in each of those markets. An
examination of the Call Reports yielded an initial list of 278 foreign banks from 62
countries that operated 399 banking institutes in the United States countries between
1976 and 2006.
When a foreign bank establishes a presence in the United States, it may choose
one of six organizational types (institutes): agency, branch, subsidiary, representative
office, New York Investment Company (NYIC), or Edge and Agreement Corporation
Subsidiary (Edge). Each institute operates slightly differently, and each must comply
with a different set of regulations. Only subsidiaries can offer a full range of commercial
products and services. They are therefore subject to the same level of regulation as U.S.
commercial banks. These types of institutes have the discretion to either imitate domestic
commercial bank strategies or adopt a differentiating strategy. The other institutions
(agencies, branches, representative offices, etc.) are constrained by their charters. For this
reason I use only the subset of foreign bank subsidiaries to study local isomorphism,
consistent with prior studies of foreign banks operating in the United States (DeYoung
and Nolle, 1996; Miller and Parkhe, 2002, Miller and Eden, 2006). This reduced the
initial sample to 121 foreign banks with 257 subsidiaries.

121
A foreign bank subsidiary in the United States can conduct the same banking
activities as a U.S. commercial bank. As U.S. commercial banks, a foreign bank
subsidiary needs to obtain national or state charters before its establishment. It may
commence and operate multiple banking offices – i.e., facilities that provide services to
customers (Sponge, 2000). A foreign bank may have more than one subsidiary in the
United States. However, as Chang (1995) points out, the first is generally of greatest
consequence. The first investment is at a decided knowledge disadvantage and faces
greater legitimacy concerns than subsequent investments (Chang, 1995). Moreover,
initial strategic decisions constrain future strategic behavior. Because this study examines
local isomorphism strategy as a firm response to the liability of foreignness, I follow the
extant research to focus on the sample that includes only the first foreign bank subsidiary
built by a foreign parent in the U.S. banking industry. If a foreign bank established
several subsidiaries simultaneously, both subsidiaries are included in the sample. This
reduced the sample to 121 foreign banks with 135 subsidiaries.
The United States Congress enacted the International Banking Act (IBA) in 1978
to uniformly regulate foreign bank operations (Goldberg and Saunders, 1981). For
example, the requirements for establishing agencies became more stringent than before
1978, a period when foreign banks were subject to little supervision. I therefore limit my
sample to the period 1978-2006 to keep the regulatory environment constant. This results
in a sample of 99 foreign banks with 113 subsidiaries.
As a result of missing data on several of the independent variables (described
below), data were not available for all foreign banks. For example, some of the home

122
country cultural, political, economic, and regulatory measures were unavailable from data
sources used to complement the Call Reports. I was therefore able to compile complete
information on 81 foreign banks with 84 subsidiaries from 24 distinct home countries
over the period 1978-2006. This resulted in an unbalanced panel of 887 firm-year
observations.

123
Table 4.1: Foreign Bank Subsidiary Origins
Home Country Number of
banks
1. Australia 1
2. Brazil 1
3. Canada 5
4. Colombia 1
5. Denmark 1
6. France 1
7. Germany 1
8. Greece 2
9. India 1
10. Ireland 2
11. Israel 4
12. Italy 3
13. Japan 24
14. Korea 8
15. Mexico 1
16. Netherlands 2
17. Philippines 3
18. Portugal 1
19. Slovenia 1
20. Spain 5
21. Switzerland 1
22. Taiwan 3
23. United Kingdom 7
24. Venezuela 1

124
4.4.2 Dependent Variable
4.4.2.1 Performance-ROA
Following prior studies of bank performance, I create the dependent variable ROA
of a foreign bank subsidiary by the ratio of return (net income) on assets (ROA) in a
given year. This measure has been commonly adopted in strategy and finance literature to
capture bank performance (Gilbert, 1984; Barnett, Greve, and Park, 1994; Deephouse,
1999; Miller and Eden, 2006). This data is derived from the Call Reports.

4.4.3 Independent Variables
4.4.3.1 Local isomorphism strategy
Following prior studies (e.g., Miller and Eden, 2006), I have constructed the
strategic isomorphism dependent variable by comparing the asset strategy of a foreign
bank subsidiary with that of U.S. banks. Asset strategy refers to a bank’s asset portfolio –
i.e., how a bank allocates its assets across various products such as commercial loans,
residential loans, and securities (e.g., Haveman, 1993; Deephouse, 1999). A bank’s asset
strategy is crucial to performance and survival. The bank’s asset allocation not only
influences revenue, but also its risk exposure. Although government regulators (via the
Federal Reserve Board, Federal Deposit Insurance Corporation, and the Comptroller of
the Currency) supervise the operations of banks operating in the United States and pay
particular attention to the security of a bank’s financial capital and assets (Sponge 2000),
U.S. banking regulations have no particular requirements on the allocation of bank assets.

125
That is, as long as banks can meet their regulatory capital requirements, they have
substantial latitude in determining their asset mix. Therefore, a bank’s asset portfolio is
reflective of its operational strategy (e.g. Haveman 1993; Mehra, 1996; Deephouse 1999).
The local isomorphism strategy is measured as the similarity between a focal
foreign bank subsidiary’s asset portfolio and that of the local U.S. banks. To measure
bank asset portfolio, Miller and Eden (2006) defined eight categories of bank assets:
commercial loans, real estate loans, loans to individuals, other loans and leases, cash,
overnight money, securities, and fixed assets. Following Miller and Eden (2006), I also
build these eight asset variables for each foreign bank subsidiary and each U.S.
commercial bank. Each asset strategy is measured as a proportion of this subsidiary’s
total assets.
To capture local isomorphism strategy, I compare a foreign bank subsidiary’s
asset strategy with the average asset strategy of U.S. banks in the same local market. I
define a local market as a metropolitan statistical area (MSA). Bank regulators identify
bank competitive markets by MSAs (Barnett, Greve, and Park, 1994). Scholars studying
commercial banks also widely adopt MSAs to define the boundary of markets (Barnett,
Greve, and Park, 1994; Berger, 1995; Miller and Eden, 2006). I then compare the asset
strategy of a foreign bank subsidiary to the average strategy used by its U.S. rivals in the
same MSA. This comparison method is similar to Miller and Eden (2006), which is
adapted from Deephouse (1999) and Finkelstein and Hambrick (1990).

126
For each foreign bank subsidiary (i), I calculate its asset strategy (A
ni
) (n=1…8) as
a proportion of subsidiary (i)’s total assets. Then I calculate the mean of this asset
strategy of all the U.S. banks in the same area: A
nUS
. I compare A
ni
with this mean, and
then divide this difference by the standard deviation of the asset strategy of the local U.S.
banks. This measure then reflects how a foreign bank subsidiary’s asset strategy n
deviates from the local average. I then multiply this difference by -1 to convert deviation
to isomorphism for ease of interpretability (Finkelstein and Hambrick, 1990; Miller and
Eden, 2006). This measure represents a foreign bank subsidiary’s overall local
isomorphism strategy (LIS). A larger value of LIS represents greater local isomorphism –
i.e., the bank more closely resembles domestic banks in the local market.
( ) ( ) ( ) [ ] ( ) 1 * /
8
1
−






− =
∑
= n
nUS nUS ni i
A SD A M A ABS LIS (4.1)

4.4.3.2 Institutional Distance
The main independent variable of interest to test hypothesis 1 is institutional
distance. Institutional distance is the extent of difference between two countries in terms
of its institutional context – expressed on cultural, economic, political, and regulatory
dimensions. Cultural distance refers to the extent of similarity between the national
cultures two countries. Economic distance captures differences in patterns of exchange,
market orientation, market stability, and the nature of economic organization across
countries. Political distance refers to differences in government. Regulatory distance

127
captures industry-specific differences in the way regulations are enacted and enforced
across countries. I measure each dimension of distance using established proxies.

4.4.3.2.1 Cultural Distance
Hofstede defined national culture as the “collective mental program” that
normalizes individual activities in a society (Hofstede, 2001). When a firm operates in a
foreign country, it becomes exposed to a new cultural environment, which may conflict
with that of its home country. Hofstede described the differences in national culture along
five dimensions: power distance, uncertainty avoidance, individualism and collectivism,
masculinity and femininity, and long-term orientation. Prior studies have used aggregated
differences across the dimensions to measure cultural distance (for a summary see
Tihanyi, Griffith and Russell, 2005). However, a measure for long-term orientation was
available for only a small subset of countries. Following Kogut and Singh (1988), I
therefore measure the CULTURAL DISTANCE (CD) between the parent firm’s home
country and the United States using only four dimensions: power distance, uncertainty
avoidance, individualism/collectivism, and masculinity/femininity.
9
This approach has
been widely adopted to measure cultural distance (e.g., Li and Guisinger, 1991; Benito
and Gripsrud, 1992). The cultural distance measure is expressed as follows:
( ) [ ]
∑
=
− =
4
1
2
4 / /
j
j USj ij i
Var H H CD , (4.2)

9
Results did not change when I limited the sample to those countries for which all five cultural dimensions
were available.

128
where CD
i
represents the cultural distance between country i and the United States.
ij
H
captures cultural dimension j in country i and
USj
H the cultural dimension j in the United
States. Var
j
represents the overall variance on cultural dimension j across all countries.

4.4.3.2.2 Economic Distance
Countries are not homogeneous in economic structure and market orientation.
Some countries are organized around private capital markets while in others; banks play a
larger role in markets. Miller and Parkhe (2002) describe the former as “capital market-
oriented” because firms generally rely on external capital markets to acquire capital and
the latter as “bank-oriented” because they rely on a system of banks. While firms may
build long term relationships with a few banks in bank-oriented financial systems, they
may have more temporary ties with numerous shareholders in capital market-oriented
systems (Allen, 1993). Both systems can be an efficient source of external funding,
although they have different orientations. However, foreign banks may operate less
efficiently when the home country’s financial system differs markedly from that of the
host country (Miller and Parkhe, 2002). Therefore, I use financial market orientation to
measure economic distance.
I measure market orientation using a ratio of market capitalization/GDP divided
by bank credits to private sector/GDP. This is a standard measure of financial market
orientation (Levine, 2002; Miller and Parkhe, 2002). The market capitalization, bank
credits, and GDP data come from the United Nation World Development Indicators

129
Database. I then define ECONOMIC DISTANCE (ED) as the absolute value of the
difference between the foreign firm’s home country orientation and the U.S. orientation.
A greater value indicates greater differences between the home country’s financial
market and that of the U.S.
| )
/ Pr
/
/ Pr
/
( |
. . . .
. . . .
t S U t S U
t S U t S U
it it
it it
it
GDP Sector ivate to Credit Bank
GDP tion Capitaliza Market
GDP Sector ivate to Credit Bank
GDP tion Capitaliza Market
ED − =
(4.3)

4.4.3.2.3 Regulatory Distance
Although scholars have widely explored institutional environments, very few
studies explicitly examine international differences in regulations (for a notable exception,
see Perkins, 2008). However, regulation is an important component of formal institutions
that normalize the activities of organizations (Scott, 1995). A comparison of regulations
across countries is especially important in this context because banks operate in a highly
regulated industry. The banking industry has a greater level of regulation and more laws
governing firm behavior than most (Miller and Parkhe, 2002; Miller and Eden, 2006).
Therefore, when foreign banks set up business units in the United States, they potentially
face a regulatory environment vastly different than that which exists in their home
country. This difference may affect their operations in the U.S. To capture the impact of
the U.S. regulatory environment on foreign banks, I create a regulatory distance variable
using the Banking Regulation Database (Barth, Caprio and Levine, 2001a).
Barth et. al. (2001a) collect comprehensive data on banking regulations in 107
countries. Those authors measure the following dimensions of banking regulation: Bank

130
Activity Regulations, Banking/Commerce Mixing Regulations, Competition Regulations,
Capital Regulations, Official Supervisory Actions, Official Supervisory Experience and
Structure, Private Monitoring, Deposit Insurance Schemes, and Market Structure.
I use the Bank Activity Regulations, Banking/Commerce Mixing Regulations,
Competition Regulations, and Capital Regulations dimensions to create my regulatory
distance measure. I choose these dimensions for both practical and theoretical reasons.
First, the aforementioned dimensions focus on regulations that normalize bank
activities, ownership, competition, and strategy. The others (Official Supervisory Actions,
Official Supervisory Experience and Structure, Private Monitoring, Deposit Insurance
Schemes, and Market Structure) generally focus on the features of supervisory agencies –
e.g., the extent of their power and their level of expertise. Since I am interested in how
regulations shape the behavior of firms, I adopt the regulation-related dimensions.
Second, the Barth et. al. (2001a) data are from the years 1998 to 2002. My data,
by contrast, cover the activities of foreign banks in the United States between 1978 and
2006. Therefore, to be more accurate in applying the Barth, Caprio, and Levine (2001a)
data retrospectively, it is helpful to have relatively stable temporal dimensions. Since
banking regulations that normalize bank activities were relatively stable from the 1970s
onward (Barth, Caprio, and Levine, 2001b), I focus on these dimensions of regulation.
Although certainly far from ideal, I believe that this is a suitable approach these authors
demonstrate in an earlier study that banking regulations across countries did not change
significantly overtime, even after serious banking crises (Barth, Caprio, and Levine,

131
2000). There is no report on the temporal stability of the supervision dimensions. All
things considered, the Barth et. al. (2001a) measure is the best available measure of the
regulatory environment.
Finally, and more practically, some dimensions are not available to the public,
including several indicators of supervision and deposit insurance schemes. Therefore, I
was not able to include these dimensions in my regulatory distance measure.
For the reasons described above, my banking regulatory distance measure
includes only the following four dimensions: Bank Activity Regulations,
Banking/Commerce Mixing Regulations, Competition Regulations, and Capital
Regulations. I build the REGULATORY DISTANCE (RD) variable as follows:
4 / / ) (
4
1
2






− =
∑
= j
j USj ij i
Var R R RD , (4.4)
where R
ij
refers to the jth regulatory dimension in country i, R
Usj
captures to the jth
regulatory dimension in the United States, and Var
j
is the variance across all four
dimensions. By construction, a greater value on this metric implies a greater regulatory
distance between the home country and the United States.

4.4.3.2.4 Political Distance
To operationalize political distance, I use the CHECKS index drawn from the
Database of Political Institutions (Beck, Clarke, Groff, Keefer, and Walsh, 2001; Keefer
and Stasavage, 2003). The CHECKS index counts the number of veto players in a

132
political system, adjusting for political cohesiveness. With a greater number of veto
players, more political checks and balances are in place, and policies are less likely to
change arbitrarily. In such cases, the political environment will be more predictable. With
fewer constraints on politicians (fewer players with veto power), the environment
becomes more unpredictable. The CHECKS index therefore captures the overall level of
political volatility within a country (Beck, et.al. 2001; Keefer and Stasavage, 2003).
Firms become accustomed to the political system in their home market; they
better understand the political environment and how it is likely to change; and they learn
how to operate effectively under such political conditions. When they enter politically
distant countries, it becomes more difficult for them to conduct business (e.g. Gaur and
Lu, 2007). I therefore measure POLITICAL DISTANCE (PD) as the absolute value of the
difference in political volatility (as measured by the CHECKS index) between the foreign
firm’s home country and the United States. A greater value indicates greater differences
between the home country’s political environment and that of the U.S.
USt it i
CHECKS CHECKS PD − = (4.5)

4.4.4 Control Variables
I control for several micro-level and macro-level variables that may influence
foreign bank local isomorphism strategy.
First, I control for the performance of the focal subsidiary at time t-1 (LAGGED
ROA). Including the lagged dependent variable controls for potentially omitted variables

133
(Kennedy, 1998). In addition, in the case that the time-variant independent variables have
effects distributed over time, the lagged dependent variable reflects these effects (Fomby,
Hill, and Johnson, 1984).
Second, I control for the size of a foreign bank subsidiary. Larger organizations
have greater resources, a better reputation, and greater legitimacy ex ante (Pfeffer and
Salancik, 1978; Deephouse, 1996). They therefore may improve subsidiary performance.
This variable, BANK SIZE, represents a total asset of the subsidiary, expressed in 10
6
of
U.S. dollars.
Third, I control for the equity ownership of each foreign bank subsidiary by
including a dummy variable, JOINT VENTURE. This variable equals 1 if this institute is
jointly owned by a foreign bank and a U.S. bank. It equals 0 otherwise. With a domestic
parent bank, a foreign bank subsidiary may adapt to the host country environmental more
easily and obtain more legitimacy. JOINT VENTURE may therefore improve subsidiary
performance.
Fourth, I control for the cost efficiency of foreign bank subsidiaries. As prior
studies on performance of banks (e.g. Deephouse, 1999; Miller and Eden, 2006), this
paper focuses on bank asset strategies. This measure does not account for cost efficiency
of each bank. However, more cost efficient banks may perform better than others
(Deephouse, 1999). Therefore, following the prior studies, I include a measure of cost
efficiency. EXPENSE RATIO is measured by the ratio of total expense to total assets in a
given year (Miller and Eden, 2006; Deephouse, 1999).

134
Fifth, the location of foreign bank subsidiaries may influence its performance. As
illustrated by Carroll and Hannan (1989), competition intensifies increasingly as local
density grows. Collocated with many competing banks, a foreign bank subsidiary may
experience severe competition. Competition can affect its performance adversely. Miller
and Eden (2006) found that in metropolitan cities, foreign bank subsidiaries benefit less
from imitation in the host country. To control for the competition effect associated with
location, I include the count of competitors. NUMBER OF LOCAL RIVALS counts the
numbers of all commercial banks in a local market in a given year. I expect this variable
to be negatively associated with foreign bank subsidiary performance.
In addition, I control for the size of the local market. According to Miller and
Eden (2006), the profitability of each commercial bank depends on the size of the local
market. MARKET SIZE is measured by the total bank assets in the MSA in a given year.
To control for the case that some unobserved local market conditions affect all
bank performance in that area, I control for the performance of local U.S. banks in a
given year. This variable may reflect the effects of some unobserved environmental
conditions on all commercial banks in the same area. LOCAL U.S. RIVAL
PERFORMANCE is the average ROA of all U.S. banks in the same MSA in a given year.
Finally, I include some control variables at the country level. First, I control for
the average FOREIGN EXCHANGE RATE of U.S. dollar to the currency of the home
country in a given year. Foreign exchange rates affect trades and foreign direct
investment between two countries (Goldberg and Klein, 1997). They also impact the

135
relative wealth across countries (Klein and Rosengren, 1992). Foreign exchange rates are
also associated with other macroeconomic variables such as inflation rates, interest rates,
and international payments balances (Isard, 1995). Therefore, foreign exchange rates may
affect the performance of foreign bank subsidiary in the United States. It is measured by
the annual average value of foreign exchange rates, which is expressed as the ratio of X
units of home country currency to 1 US dollar.
In addition, I include a variable FDI FLOW. It equals the total amount of inward
and outward foreign direct investment between the U.S. and a particular home country in
a given year. Scholars have argued that banks expand to foreign markets in order to
follow their clients, i.e., to serve their clients in the new markets (Aliber, 1976, 1984;
White, 1982). They found that FDI between two countries was positively associated with
the volume of foreign bank activities (Grosse and Goldberg, 1991). Therefore, this
variable FDI FLOW is expected to have a positive impact on bank performance. The data
of inward and outward direct investment is provided by the Bureau of Economic Analysis.

4.4.5 Statistical Method
4.4.5.1 H1: Foreign Subsidiary Performance
To test H1, I build a regression model to examine the impact of the institutional
distance variables on foreign bank subsidiary performance (ROA). In this model, foreign
bank subsidiary’s performance (ROA) is a function of the multi-dimensional institutional
distance (DIS), a vector of control variables (Z), and an error term at time t.

136
H1:
it it it it
Z DIS ROA μ β β β + + + =
2 1 0
(4.6)
However, ordinary least squares regression (OLS) may not be appropriate to
specify this model. The data employed in these tests violate the assumptions of OLS. My
sample is composed of foreign bank subsidiary observations by year and by subsidiary.
Each subsidiary may operate several years and thus provide several observations over
time in the sample. Therefore, this is a pooled cross-sectional time-series panel dataset.
This dataset violates a basic assumption of OLS. That is, the error term μ
it
may not be
independent within observations. However, in the panel dataset, some unobserved
features of a bank subsidiary, which are not captured by control variables, may cause
systematic correlations of the error terms within group.
To correct this issue, I need to decompose the error term into two parts: one part
stands for the systematic bank effect (γ
i
), and the other represents the random error that is
independent across observations (e
it
). This solution ensures that the new error term does
not correlate with dependent variable and independent variables/control variables
simultaneously (Kennedy, 1998). Both a fixed-effects model and a random effect model
can solve the problem of unobserved heterogeneity. However, a fixed-effects model is
less suitable for my test because the test includes time-invariant variables such as cultural
distance. Therefore, I use a random effects model to decompose the error terms and
generate unbiased estimates. In addition, I add fixed time dummies into the regression to
control for possible time-dependent (F
t
) trends of bank operation and performance. The
revised model is as follows:

137
H1:
it t i it it it
e F Z DIS ROA + + + + + = γ β β β
2 1 0
(4.7)

4.4.5.2 H2: Local Isomorphism Strategy
H2 predicts the effect of local isomorphism strategy on foreign bank subsidiary
performance. If we assumed this strategy (LIS) to be an exogenous variable, a regression
model to test H2 would be as follows:
H2:
it t i it it it it
e F Z LIS DIS ROA + + + + + + = γ β β β β
3 2 1 0
(4.8)
Similar to equation 4.7, equation 4.8 controls for the unobserved heterogeneity
issues by using a random effects model. However, this model does not account for the
endogeneity of the strategy variable. A bank selects strategies based on its individual
characteristics, the environmental conditions, and its expected impact on performance.
Meanwhile, its performance also depends on these contingencies and the potential impact
of its strategy. In other words, the disturbance term in equation 4.8 is likely to be
correlated with the LIS variable. For the random effects model to generate unbiased
estimates, the error term and independent variables are assumed to be uncorrelated (Hsiao,
2003). Because this assumption is likely to be violated, this model is inappropriate to test
H2.
To control for the endogeneity of a firm’s local isomorphism strategy choice, I
use a simultaneous equations method, in which the endogenous variable is a function of
the independent variables of interest, plus a set of instrumental variables (Greene, 2000;
Hsiao, 2003). Instrumental variables have two features: they are uncorrelated with the

138
error term, and they are correlated with the endogenous independent variables (Greene,
2000; Hsiao, 2003). These endogenous variables are regressed on all variables (including
instruments) to get fitted values. These fitted values replace the endogenous variables in
the original model. Finally, the dependent variable (profitability) is regressed on all
independent variables (including the fitted values of endogenous variables) (Kennedy,
1998). Because these fitted values have a high correlation with the original variable and
have no correlation with the error terms, they are efficient “instruments” for the focal
endogenous variable (Kennedy, 1998). I therefore adopt the following simultaneous
equations model to test H2:
LIS
it
= DIS
it
β
1
+ X
it
α
1
+ ε
it
; (4.9)
ROA
it
= LIS
it
γ + DIS
it
β
2
+ W
it
α
2
+ η
it
; (4.10)
In equation 4.9 and 4.10, LIS
it
refers to the local isomorphism strategy adopted by
a focal foreign bank subsidiary i at time t, ROA
it
is the performance of bank i at time t,
DIS
it
is the vector of institutional distance between bank i’s home country and the United
States at time t, X
it
is a vector of firm-specific and environmental factors that affect the
bank’s choice of imitation, W
it
is a vector of internal and external factors that affect bank
performance, ε
it
and η
it
are error terms, respectively. This simultaneous equations model
allows for the correlation between the endogenous strategy variable and the error term
(Hsiao, 2003; Baltagi, 2008).
Equation 4.9 and 4.10 above can fit panel data in an instrumental variable two-
stage least square regression under different assumptions. If we assume that all

139
independent variables are uncorrelated with the error terms, then a random effects model
will be most efficient. This model uses a generalized least square regression to obtain
consistent estimates in both the first and the second stage regressions to control for
unobserved heterogeneity and obtain consistent estimates (Hsiao, 2003; Baltagi, 2008).
However, if independent variables are correlated with the error terms, then a fixed effects
model will generate the consistent estimates (Baltagi, 2008). The fixed effect two-stage
least square models introduce fixed firm effects to both the first and the second stage
regressions (Baltagi, 2008). Since it is possible that unobserved heterogeneity exists
across foreign bank subsidiaries, I cannot exclude the assumption that X
it
and W
it
are
correlated with ε
it
and η
it
. Therefore, a fixed effects two-stage least square model should
be adopted.
However, this model cannot estimate the coefficients of time-invariant variables.
Given that some institutional distance variables are time-invariant in my study, I need to
the use the random effects two-stage least square model.
To make sure of consistent and efficient estimates, I finally use both the fixed
effects and the random effects model to estimate the impact of local isomorphism
strategy on foreign bank subsidiary performance. I compare the following three models: a
general random effects model that treats LIS as exogenous, a random effects two-stage
least square model, and a fixed effects two-stage least square model in which I combine
institutional variables into a composite, time-varying construct. This composite
institutional distance is calculated as follows:

140
DIS
it
= (CD
i
2
+ ED
it
2
+ RD
it
2
+ PD
it
2
)
1/2
(4.11)

4.4.5.2.1 Instrumental Variables
There are two essential criteria for instrumental variables. First, instrumental
variables should be correlated with the endogenous variable. Second, they should be
uncorrelated with the idiosyncratic error term (Kennedy, 1998; Greene, 2000; Hsiao,
2003). Following these two criteria, I adopt three instrumental variables. First, I include
the market share of all foreign bank subsidiaries in the MSA. FOREIGN RIVAL
MARKET SHARE is measured by the ratio of total assets owned by all foreign bank
subsidiary competitors to the total bank assets of the MSA market. Theoretically, a strong
presence of foreign banks may legitimize the focal foreign bank subsidiary (Kostova and
Zaheer, 1999). Therefore, a foreign bank subsidiary that is collocated with strong foreign
banks may feel less pressure to imitate the U.S. bank strategies to obtain legitimacy.
Statistically, the correlation between this variable and ROA is -0.05, while its correlation
with LIS is 0.15. I therefore use foreign rival market share as one of the instrumental
variables. However, I acknowledge that the presence of foreign banks in the market may
be associated with the error term. For example, a strong presence of foreign banks
implies more competition from these rivals. The level of competition could be a
component of the error term. Although I have controlled for the number of local rivals in
the model, this control variable may not fully capture the effect of foreign bank presence.

141
Second, I include the total variances of asset strategies of local U.S. banks. Prior
study shows that firms are less confident in imitating a business practice as their
reference group exhibits greater variances in adopting this practice (Rhee, Kim and Han,
2006). Therefore, the variances of local U.S. banks’ asset strategy may affect the
likelihood of local isomorphism by foreign banks. This instrumental variable equals the
sum of the standard deviations of all eight asset strategies adopted by local U.S. banks. I
build the LOCAL U.S. BANK STRATEGY VARIANCE (SV) as follows:
∑
=
=
8
1
) (
n
nUS i
A SD SV (4.12)
Here, A
nUS
represents the asset strategy of all U.S. commercial banks in the same
local market as foreign bank subsidiary i. SV therefore captures the breadth of asset
strategies that adopted by local U.S. banks. The correlation between SV and ROA is 0.06,
while the SV-LIS correlation is 0.29. Moreover, SV measures the local U.S. bank strategic
variance. Theoretically, this variable has little relation with the idiosyncratic features of
the focal foreign bank subsidiary.
Third, prior studies have demonstrated that organizations are more likely to
imitate the activities of others that are similar to themselves (e.g. Haveman, 1993).
Extending the logic to this study, I assume that foreign bank subsidiaries may be more
likely to adopt the practices and strategies of local U.S. banks that are more similar to the
focal subsidiary. Following Haveman (1993), I compare banks by their size. The
instrumental variable is constructed as follows:

142
Similarity
it
= [ABS (Asset
it
– M(Asset
USt
))/SD(Asset
USt
)] *(-1) (4.13)
In this formula, I take the absolute difference between the Asset
it
(total assets of
focal bank subsidiary at time t) and M(Asset
USt
) (average total assets of all U.S. banks in
the local market at time t). I divide this difference by SD(Asset
USt
) (the standard deviation
of all local U.S. banks total assets). This value then represents the difference between the
focal subsidiary and average local U.S. banks. I multiply this value by -1. The transposed
value captures the similarity between focal bank subsidiary size and average local U.S.
banks size.
An instrumental variable should be exogenous and uncorrelated with the
idiosyncratic term (Greene, 2000). However, the instrumental variable SIMILARITY is
built based on the focal foreign bank’s asset, which is not an exogenous variable. .
Therefore, I acknowledge that this measure may be associated with the idiosyncratic
feature of the focal bank. However, the correlation between SIMILARITY and ROA is low
(-0.018), while the correlation between SIMILARITY and LIS is relatively high (0.085).
This may relieve some concern about this proxy.
In the two-stage simultaneous equation model, I treat the institutional distance
variables as independent variables rather than extra instruments. This is because I expect
institutional distance to affect both the bank performance and isomorphic behavior.
Although adopting local practices helps foreign firms offset the distance-related
disadvantage, this strategy may not effectively reduce this disadvantages completely.
First, firms may try other ways to deal with its liability of foreignness. For example, they

143
may build ties with legitimate parties to improve their own legitimacy. These links
successfully decreases the risk of failures (Baum and Singh, 1994). Since such strategies
are not included in my model, I expect there to remain a negative impact of institutional
distance on performance. Second, isomorphism strategy may not solve all problems
related to institutional distance. For example, the coordination between a subsidiary and
firm headquarter may incur higher costs if the subsidiary follows local practices rather
than adopt the internal standard practices. Local isomorphism may exacerbate, rather than
relieve, this problem. As a result, I expect institutional distance, in addition to
isomorphism, to have a negative impact on performance.
Therefore, the list of total “instruments” for local isomorphism strategy is as
follows: the institutional distance variables, the vector W
it
of control variables, and three
additional instrumental variables: FOREIGN RIVAL MARKET SHARES, LOCAL U.S.
BANK STRATEGY VARIANCE and SIMILARITY. In the first stage, local isomorphism
strategy is regressed on these instruments to generate the fitted value. This fitted value is
then used in the second stage to estimate the impact of local isomorphism on foreign
bank performance.

4.5 Results
Table 4.2 presents descriptive statistics and product moment correlations.
Although correlations are generally as expected, some correlations among the distance
variables are elevated, hinting at a potential multicollinearity concern. However,

144
influence tests were not suggestive of multicollinearity. The maximum VIF score was
4.25 and the mean VIF was 1.99, well below the suggested threshold (Belsley, Kuh and
Welsch, 1980).

145

Table 4.2: Correlations

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15
1.ROA 1.00
2.LIS -0.07 1.00
3.Lagged ROA 0.11 -0.10 1.00
4.Bank size 0.00 0.07 -0.00 1.00
5.Expense ratio -0.01 -0.02 -0.03 -0.04 1.00
6.Joint venture -0.03 0.02 -0.01 0.04 -0.03 1.00
7.Market size 0.04 -0.03 -0.02 0.09 -0.03 -0.11 1.00
8.Number of local rivals -0.06 0.13 -0.12 -0.16 0.05 -0.26 -0.01 1.00
9.Local U.S. rival performance 0.46 -0.10 0.04 0.02 -0.02 -0.03 0.17 -0.06 1.00
10.Foreign exchange rate -0.10 0.08 -0.09 -0.14 -0.02 -0.16 0.04 0.27 -0.03 1.00
11.FDI flow 0.07 -0.03 0.08 0.35 0.04 -0.21 0.13 -0.02 0.07 -0.28 1.00
12.Cultural distance -0.05 0.13 -0.08 -0.20 0.00 -0.02 0.26 0.17 0.03 0.22 -0.26 1.00
13.Economic distance -0.03 0.05 0.02 0.08 -0.01 0.05 -0.04 -0.16 0.00 -0.13 0.08 -0.31 1.00
14.Regulatory distance -0.04 0.01 -0.00 0.19 -0.01 0.01 -0.08 -0.13 -0.03 -0.32 0.17 -0.64 0.42 1.00
15.Political distance -0.03 -0.02 -0.04 -0.05 0.02 0.01 -0.03 0.07 -0.14 -0.08 -0.06 0.18 -0.08 -0.13 1.00
Mean 0.01 -7.41 0.01 0.002 0.13 0.01 0.15 103.27 0.008 0.02 0.07 2.16 0.38 1.22 1.40
Standard deviation 0.04 6.96 0.04 0.005 0.64 0.01 0.36 63.16 0.014 0.03 0.08 1.15 0.48 1.20 1.40
Minimum -0.26 -141.42 -0.26 0.000 0.00 -0.04 0.00 2.00 -0.04 0.00 0.00 0.08 0.00 0.21 0.00
Maximum 0.71 -1.27 0.71 0.051 16.08 0.09 1.00 458.00 0.08 0.19 0.36 4.37 2.73 6.79 13.00

146
The regression results of hypothesis 1 are reported in Table 4.3. In addition to
random bank effects, I also include fixed time dummies to control for a general time
trend in foreign bank subsidiary performance. Not reported here, the fixed time dummies
were insignificant as a set. There is no evidence that foreign bank subsidiary performance
improves or worsens over time.
Column 1 reports the base model including all control variables. Results suggest
that the lagged dependent variable is positively associated with bank subsidiary
performance, consistent with expectations. In larger local markets, foreign bank
subsidiaries perform relatively worse. However, foreign bank subsidiaries have better
performance if their U.S. local competitors perform better. In addition, as the U.S. dollar
depreciates relative to the foreign currency, the foreign bank subsidiary experiences
better performance in the United States.
Columns 2 through 5 introduce the institutional distance variables individually.
The negative and significant coefficient of cultural distance in column 2 suggests that
foreign banks with a more different cultural background than the U.S. are likely to
perform worse in the U.S. banking industry. Column 3 shows the coefficient of economic
distance. Similar to the results reported in column 2, the finding shows a negative
association between economic distance and foreign bank subsidiary performance.
Consistent with prior findings, the coefficient of regulatory distance is negative and
significant in column 4. Column 5 introduces the political distance variable. Contrary to
prior results, the results do not show a significant relation between political distance and

147
Table 4.3: Regression Results-H1
DV: ROA 1. 2. 3. 4. 5. 6.
Constant 0.01 0.01* 0.01 0.01 0.00 0.02***
(0.79) (1.34) (0.92) (1.20) (0.70) (2.75)
Lagged ROA 0.09*** 0.09*** 0.09*** 0.09*** 0.09*** 0.07**
(2.51) (2.41) (2.44) (2.46) (2.51) (2.08)
Bank size -0.20 -0.26 -0.19 -0.14 -0.20 -0.20
(-0.76) (-0.97) (-0.71) (-0.52) (-0.74) (-0.73)
Expense ratio -0.00 -0.00 -0.00 -0.00 -0.00 -0.00
(-0.06) (-0.02) (-0.05) (-0.08) (-0.06) (-0.02)
Joint venture -0.00 -0.00 -0.00 -0.00 -0.00 -0.00
(-0.95) (-0.93) (-0.89) (-1.03) (-0.93) (-1.01)
Market size -14.90* -10.50 -14.80* -15.70* -14.80* -5.33
(-1.42) (-0.97) (-1.41) (-1.50) (-1.41) (-0.49)
Number of local rivals -0.00 -0.00 -0.00 -0.00 -0.00 -0.00
(-0.50) (-0.29) (-0.56) (-0.54) (-0.49) (-0.12)
Local U.S. rival performance 1.28*** 1.28*** 1.29*** 1.28*** 1.29*** 1.29***
(14.31) (14.28) (14.34) (14.32) (14.21) (14.26)
Foreign exchange rate -1.02*** -0.96*** -1.06*** -1.20*** -0.98*** -1.27***
(-2.47) (-2.32) (-2.56) (-2.81) (-2.37) (-2.94)
FDI flow 0.57 -7.48 2.49 2.92 1.51 -12.00
(0.03) (-0.41) (0.14) (0.17) (0.09) (-0.66)
Cultural distance -0.002** -0.005***
(-1.69) (-3.44)
Economic distance -0.004* -0.003
(-1.35) (-0.90)
Regulatory distance -0.002** -0.004***
(-1.65) (-2.85)
Political distance 0.001 0.001
(0.55) (0.74)
Bank effect YES YES YES YES YES YES
Time effect YES YES YES YES YES YES
N 887 887 887 887 887 887
R-sq 0.227
(14)
0.230
(15)
0.229
(15)
0.230
(15)
0.227
(15)
0.241
(18)

148
foreign bank subsidiary performance. Finally, column 6 includes all independent
variables. The results of the full model are similar to the results in column 2-5. The only
exception is the economic distance variable. In the full model, it is insignificant though
the direction of its coefficient is consistent with the prior findings. Overall, the results
generally support the hypothesis 1. That is, the cultural/economic/regulatory distance
between the home country and the U.S. is negatively related with foreign bank subsidiary
performance as these subsidiaries operate in the United States.
Table 4.4 reports the results of the test on hypothesis 2: the impact of
isomorphism strategy on foreign bank subsidiary performance.
10
Column 1 replicates the
column 6 of table 4.3. It shows the baseline model that includes all control variables and
the institutional distance variable. Column 2 reports the results of the random effects
model, which treats the local isomorphism strategy (LIS) as an exogenous variable.
Consistent with the findings of Miller and Eden (2006) and Zaheer (1995), this strategy
has no significant association with foreign subsidiary performance. Column 3 presents
the random effects instrumental variable two-stage least square model (RE-2SLS). By
contrast to the random-effects model in column 2, the coefficients of isomorphism
strategy in column 3 is both positive and significant. This result is consistent with
hypothesis 2, which predicts a positive impact of isomorphism as an endogenous strategy
on performance.

10
The results of first stage models of these 2SLS regressions are reported in Table 4.5.

149
Table 4.4: Regression Results-H2
DV: ROA 1.Baseline 2. Random effects 3. RE-2SLS 4.FE-2SLS
Constant 0.02*** 0.02*** 0.04*** 0.01
(2.75) (2.77) (3.33) (1.08)
Lagged ROA 0.07** 0.07** 0.08*** 0.02
(2.08) (2.10) (2.05) (0.54)
Bank size -0.20 -0.21 -0.49* -1.21***
(-0.73) (-0.77) (-1.58) (-2.65)
Expense ratio -0.00 -0.00 0.00 -0.00
(-0.02) (-0.01) (0.09) (-0.12)
Joint venture -0.00 -0.00 -0.01* -0.02**
(-1.01) (-1.04) (-1.42) (-2.29)
Market size -5.33 -4.98 3.10 -6.69
(-0.49) (-0.46) (0.25) (-0.27)
Number of local rivals -0.00 -0.00 -0.00 -0.00
(-0.12) (-0.18) (-0.76) (-0.58)
Local U.S. rival performance 1.29*** 1.29*** 1.32*** 1.29***
(14.26) (14.25) (14.06) (13.28)
Foreign exchange rate -1.27*** -1.28*** -1.53*** -0.74
(-2.94) (-2.96) (-3.15) (-0.47)
FDI flow -12.00 -1.23 -13.40 9.69**
(-0.66) (-0.68) (-0.66) (1.99)
Cultural distance -0.005*** -0.006*** -0.008***
(-3.44) (-3.47) (-3.75)
Economic distance -0.003 -0.003 -0.004
(-0.90) (-0.93) (-1.18)
Regulatory distance -0.004*** -0.004*** -0.005***
(-2.85) (-2.89) (-3.18)
Political distance 0.001 0.001 0.001
(0.74) (0.76) (0.72)
DIS -0.002*
(-1.57)
LIS 0.000 0.001** 0.002***
(0.48) (2.26) (3.18)
Bank effect YES YES YES YES
Time effect YES YES YES YES
N 887 887 887 887
R-sq 0.241
(18)
0.241
(19)
0.204
(19)
0.118
(16)

150
Column 4 presents the fixed effects instrumental variable two-stage least square
model (FE-2SLS). Because some institutional distance variables are time-invariant, they
will be dropped off in a fixed effects model. To avoid this problem, I constructed a
composite institutional distance index
½
as described earlier. This composite measure of
distance is time variant, which can now be used in a fixed effects model. By introducing
COMPOSITE DISTANCE into this model, I hope to roughly capture the impact of
institutional distance in this strategy-performance relationship. Consistent with the RE-
2SLS model in column 3, there is a positive link between the local isomorphism strategy
and foreign bank subsidiary performance. Similarly, the composite index of institutional
distance (DIS) has a negative impact on performance.
In a summary, both instrumental variable two-stage least square models indicate
that local isomorphism strategy, once endogeneity has been accounted for, has a
significant and positive impact on foreign bank subsidiary performance. This finding
supports the theoretical prediction that local isomorphism helps foreign firms to reduce
their disadvantage when operating in a host country. In general, hypothesis 2 receives
empirical supports.

151
Table 4.5: First Stage Models of the 2SLS Regressions
DV: LIS 1. RE-2SLS 2.FE-2SLS
Constant -27.30*** -24.61***
(-12.55) (-8.67)
Lagged ROA -8.88* -4.46
(-1.46) (-0.74)
Bank size 168.00*** 270.00***
(3.38) (4.17)
Expense ratio -0.15 -0.11
(-0.45) (-0.34)
Joint equity ownership 1.77*** 3.30***
(2.57) (3.09)
Market size -323.00* -46.90
(-1.53) (-0.13)
Number of local rivals 0.01** 0.00
(1.72) (0.15)
Local U.S. rival performance -27.53** -18.60
(-1.74) (-1.25)
Foreign exchange rate 165.15** 108.60
(2.11) (0.45)
FDI flow -146.00 -1810.00***
(0.04) (-2.53)
Cultural distance 1.44***
(4.83)
Economic distance 0.70*
(1.32)
Regulatory distance 0.85***
(3.14)
Political distance -0.37**
(-2.23)
DIS -0.27*
(-1.31)
Foreign rival market share 5.55* -4.01
(1.45) (-0.95)
Local U.S. bank strategy variance 18.79*** 25.84***
(9.34) (9.48)
Similarity -0.30** -0.96***
(-1.67) (-4.86)
N 887 887

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4.6 Discussion and Conclusion
Research in international business suggests that foreign firms are at a
disadvantage when operating abroad. This liability of foreignness stems from a broad
unfamiliarity with the local environment and a lack of legitimacy. Because of this
liability, foreign firms have difficulties to improve their performance in the host country.
Although prior studies have widely examined this liability (e.g. Zaheer, 1995; Mata and
Portugal, 2002; Mezias, 2002; Salomon and Martin, 2008) and the strategies to reduce it
(e.g. Morck and Yeung, 1991; Zaheer, 1995), two questions remain unexplored.
First, we do not know whether the origin of foreign firms affects their
performance. Though the international business theory associates many aspects of the
LOF with the multiple dimensions of institutional distance between the host country and
the home country, no prior studies have tested the direct impact of institutional distance
on performance. To fill this gap, I examine the relations between institutional distance
and foreign subsidiary performance, adopting a multi-dimensional construct of
institutional distance.
Second, prior literature suggested and tested local isomorphism strategy as one of
the method to reduce the liability of foreignness and improve foreign subsidiary
performance. However, no evidence has been found to support this view. I argue that the
lack of evidence may be caused by prior regression models that did not account for the
selection of isomorphism as a strategy. To re-examine this theoretical argument, I employ

153
an instrumental variable two-stage least square regression model to correct for the
endogeneity issue when testing the strategy-performance relationship.
Based on the sample of foreign bank subsidiaries operating in the U.S. banking
industry from 1978 to 2006, I find that cultural/economic/regulatory distances between
the home country and the United States have a negative impact on the performance of
foreign bank subsidiaries. This finding is consistent with prior theory on the liability of
foreignness. That is, foreign firms with a more institutionally distant background face
greater disadvantages in a host country.
To estimate the economic magnitude of institutional distance, I calculate the
marginal effects and report the main results in table 4.6. Column 1 represents the
marginal effects. Column 2 reports the percentage change to ROA as any of these
independent variables increases by 1 standard deviation. According to the results, ROA
of a foreign bank subsidiary will decrease by 63.27% if the cultural distance increases by
1 standard deviation. Likewise, 1 standard deviation increases in the economic and
regulatory distance are associated with a decrease in ROA by 13.14% and 51.85%,
respectively. Taken together, institutional distance not only has significant impact on
foreign subsidiary statistically but also has powerful economic influences on foreign
subsidiary performance.

154
Table 4.6: Marginal Effects of Institutional Distance
DV=ROA 1. dy/dx 2. dx=1 std.dev
Cultural distance -0.005*** -63.27%
(-3.44)
Economic distance -0.003 -13.14%
(-0.90)
Regulatory distance -0.004*** -51.85%
(-2.85)
Political distance 0.001 10.17%
(0.74)

155
Moreover, I compare the regression models that treat local isomorphism strategy
as an exogenous variable and an endogenous variable respectively. The model that
controls for endogeneity shows a positive and significant impact of this strategy on
foreign subsidiary performance, while the random effects model regression does not
show any link between the two. This finding confirms the theoretical prediction about the
performance effect of local isomorphism strategy. More importantly, it indicates the
important of accounting for endogeneity when examining the strategy-performance link.
This paper makes several contributions to both the researchers and practitioners of
the international business field. First, it shows the impact of foreign firm origin on its
performance in a host country. Although theories predict that the liability of foreignness
arises from the differences between institutional contexts, most studies only test the
impact of cultural distance on foreign subsidiary performance. By examining the cultural,
economic, regulatory, and political distances across countries, this study provides a
relatively comprehensive view of how the multi-dimensional institutional distance affects
foreign subsidiary performance. It suggests that foreign firms from more distant
institutional contexts are likely to face a greater disadvantage than foreign firms from
similar institutional contexts.
Second, building on prior studies of local isomorphism strategy, this paper takes a
step further to study the impact of this strategy on foreign subsidiary performance while
accounting for endogeneity. Adopting an instrumental variable two-stage least square
model, it explores the underlying mechanism by which foreign firms choose the level of

156
isomorphism strategy. Prior studies did not show a significant link between isomorphism
and performance. By contrast, the results here suggest that local isomorphism, as the
outcome of an endogenous process, is likely to improve the performance of foreign firms
in a host country. Interestingly, the negative impact of institutional distance on
performance remains even though firms adopt local isomorphism strategies. Taken
together, this finding implies that local isomorphism, as a strategic decision, helps foreign
subsidiary perform better. However, it does not completely offset the negative impact of
a distant origin. Therefore, foreign firms must adopt other strategies, in addition to local
isomorphism, to create a competitive advantage in the host country.
An interesting question for future research could be how foreign firms use
different portfolio of strategies in a host country. Rather than adopting isomorphism,
foreign firms may attempt to differentiate themselves from domestic firms to create a
competitive advantage in the host-country market. Therefore, it is important to study the
conditions under which foreign firms can successfully create competitive advantage
despite facing the liability of foreignness. Future research should focus more greatly on
the strategies and performance of foreign firms, which may differ greatly from those of
their domestic competitors.
For practitioners, this study highlights the impact of institutional distance on
foreign subsidiary performance. Managers of foreign firms should proactively look for
strategies to reduce negative impact of distance. More importantly, it is necessary for
managers to take into account a variety of distances in institutional context, such as

157
different culture, different economic systems, and different industrial regulations. The
difference in each environment could increase the difficulty of operating business abroad.
In addition, this study suggests that adopting local strategies and practices could be one
effective method to improve foreign firm performance in a host country. Foreign firms
may acquire legitimacy and learn from the local firms’ experience by imitating the
practices of the local domestic competitors. However, the level of isomorphism should be
chosen according to both firm-specific attributes and environmental conditions.
However, this is just a first step to study foreign firm strategies of operating
subsidiaries in a host country. In addition to isomorphism, foreign firms may also attempt
to differentiate themselves from the domestic firms and therefore create a competitive
advantage in the host country market. It is important to study the conditions under which
foreign firms can successfully create competitive advantage despite of the liability of
foreignness they face. I hope future research to pay more attention on foreign strategies
and foreign subsidiary performance, which could be different than what we know about
domestic firm competitions.

158
CHAPTER 5

DISCUSSION AND CONCLUSION

5.1 Discussion of Key Findings
The first essay studies the impact of multi-dimensional institutional distance on
foreign-firm entry and the moderating effect of vicarious learning. The findings indicate a
negative correlation between institutional distance (particularly
cultural/regulatory/political distance) and the number of foreign entrants; that is, as the
institutional distance between a home and host country increases, the number of firms
from the home country entering the host country decreases. Moreover, the findings
suggest that vicarious experience moderates the negative impact of institutional distance,
but that the influence of cultural distance is not reduced by vicarious learning. Taken
together, these findings imply that institutional distance does impede the entrance of
foreign firms into a new market. Although the experience of earlier entrants assists firms
in reducing the institutional distance barriers when making decisions regarding market
entry, not all distance-related problems can be resolved by vicarious learning.
The second study examines the level of local isomorphism adopted by foreign
firms after they enter a particular host country. It focuses on the boundary conditions
under which foreign firms are more likely to imitate their local domestic competitors. The
results suggest that foreign firms choose a level of local isomorphism based on the
institutional distance that they face. In particular, greater cultural/economic/regulatory

159
distance motivates foreign firms to imitate local business practices to a greater extent.
Interestingly, the impact of institutional distance is found to be more persistent than
expected; foreign firms are not likely to modify their level of local isomorphism even
after acquiring greater knowledge of the local market and gaining more operating
experience.
Based on the findings of the second study, the third essay examines the impact of
the level of local isomorphism on foreign-subsidiary performance. Contrary to prior
studies, the findings of this study indicate a positive association between the adoption of
local isomorphism and foreign-subsidiary performance, while local isomorphism is a
self-selected strategy. The results also indicate that institutional distance has a negative
impact on foreign-subsidiary performance, as the international business literature implies.
Taken together, the findings of the second and the third studies imply that foreign firms
choose a particular level of local isomorphism as a strategy for improving their
performance in the host country based on a variety of factors, one of which is the
institutional distance between the home country and the host country.
A comparison of the findings from these three studies suggests that institutional
distance has a persistent impact on foreign-firm strategy and performance, and that this
impact is more complex than indicated by prior research. First, although institutional
distance is an entry barrier that may impede firms from entering a foreign market, firms
may access the experience of prior entrants to overcome some of difficulties arising from
institutional distance. Second, institutional distance continues to influence foreign firms’

160
strategy after entry; greater institutional distance motivates foreign firms to imitate more
of the strategies and business practices of local domestic competitors, and foreign firms
tend not to modify their level of local isomorphism even after accumulating more local
experience over time. Third, adopting local isomorphism does indeed improve foreign-
subsidiary performance. If viewed as a strategy self-selected by foreign firms according
to their unique characteristics and institutional distance, local isomorphism has a positive
impact on foreign-subsidiary performance.

5.2 Contributions and Directions for Future Research
First, this dissertation complements prior studies on institutional distance and
foreign firm strategy. Most prior studies of the institutional distance between countries
have only assessed cultural distance. The results of these studies have not always shown
the expected impacts of cultural distance on foreign-firm strategy and performance
(Shenkar, 2001). Building on prior studies, this research incorporates multiple
dimensions of institutional distance. The findings of this study suggest that other
dimensions of institutional distance, such as the distance between economies, industrial
regulations, and political systems, impact foreign-firm entry, post-entry strategy, and
performance. Therefore, excluding these dimensions in studies of institutions across
countries may result in less reliable findings. Future research could continue to examine
the impact of institutional distance by determining why each dimension of institutional
distance has a different impact on foreign-firm strategy and performance. A field study of

161
how managers react to different degrees of institutional distance and the corresponding
organizational consequences could be particularly enlightening.
The first study indicates that institutional distance may not affect the entry of all
foreign firms into a new market in the same manner. Through vicarious learning, foreign
firms may be able to overcome the barriers arising from institutional distance, but, and
even more importantly, such vicarious learning does not moderate the impacts of all the
dimensions of institutional distance. However, this study only focused on the country
level, and did not consider firm-specific factors that may also impact entry decisions. A
complementary study should examine how firm characteristics, along with environmental
factors, affect firms’ decisions regarding market entry. It would be valuable to consider
firm-level, industry-level, and country-level conditions in a study of foreign-firm entry to
assess the impact of each factor and explore the interaction among them.
To my knowledge, the second essay is the first study to examine the heterogeneity
in firm choice regarding the adoption of local isomorphism as a strategy. It demonstrates
that substantial heterogeneity exists. Specifically, it found that local isomorphism may be
better suited for some firms than others, such that foreign firms from distant institutional
contexts may find it more advantageous to imitate local competitors. Future research
should examine other sources of heterogeneity at both the national and firm level in
decisions regarding the adoption of isomorphism. As prior research has shown that
domestic firms can acquire legitimacy by local isomorphism (Deephouse, 1996), it would

162
be interesting to compare the strategies adopted by domestic firms and foreign firms to
obtain legitimacy and the consequences of adopting those strategies.
Building on prior research, the third study assessed the impact of local
isomorphism on foreign-subsidiary performance while accounting for endogeneity.
Adopting an instrumental variable two-stage least square model, it explored the
underlying mechanisms by which foreign firms choose to adopt isomorphism. In contrast
to the results of prior studies, which did not indicate a significant link between
isomorphism and performance, the results of this study indicate that local isomorphism,
as the outcome of an endogenous process, is likely to improve the performance of foreign
firms operating within a host country.
However, rather than adopting isomorphism, foreign firms may attempt to
differentiate themselves from domestic firms to acquire a competitive advantage in the
host-country market. Therefore, it is important to study the conditions under which
foreign firms can successfully create competitive advantage despite facing the liability of
foreignness. Future research should focus more greatly on the strategies and performance
of foreign firms, which may differ greatly from those of their domestic competitors.

5.3 Limitations
First, this dissertation did not explore the difference among cultural, economic,
regulatory, and political distance. While most of prior studies focus on only one
dimension of institutional distance, this study employed multiple dimensions of

163
institutional distance. However, this study did not explain why one dimension may have a
different impact on foreign firm strategy and performance than another dimension. The
underlying mechanisms by which each dimension of institutional distance may have
unique impact foreign firms are not theorized. As a result, the empirical tests did not
explain the difference in the results of each distance variable. Future research is needed to
explain the heterogeneity of institutional distance.
Second, although this dissertation assessed the impact of institutional distance, it
only measured and tested four dimensions of this factor: the cultural, economic,
regulatory, and political dimensions. It did not consider other important dimensions, such
as religion, education, and infrastructure. In addition, it employed only one proxy for
each dimension in the empirical test, while other measures may also capture these
dimensions of institutional distance.
Third, this dissertation did not test the underlying mechanisms by which
institutional distance affects firms’ decision and activities. Although the theoretical
arguments in this dissertation address how institutional distance intensifies the liability of
foreignness, this dissertation did not directly measure and test these underlying
mechanisms.
Fourth, because the banking industry is highly regulated in most countries, the
firms in this industry may be more sensitive to regulatory differences than are those in
other industries. Based on this industry, the findings of this dissertation may over-
estimate the effect of regulatory distance. Moreover, regulations of the banking industry

164
focus on bank stableness and reliability, which may lead to high level of structural inertia
(Hannan and Freeman, 1984). Therefore, firms in this industry may have more difficulty
to change their strategies (Hannan and Freeman, 1984). Although banks could learn from
their competitors, they might be bound by their stabilized structure and standardized
activities and thus lack the flexibility of adjusting their strategies accordingly. Therefore,
more corroboratory evidence is needed before the findings of organizational learning
effects in this dissertation become generalizable to firms in other industries.
Fifth, several measures obtained in this dissertation are imprecise. For example,
the measure of cultural distance is time-invariant. If national cultures changed
significantly over the 40 years examined in this dissertation, this measure would not
capture the true cultural distance between countries. In addition, the measure of
regulatory distance is based on the Banking Regulation Database (Barth et. al, 2001a),
which surveyed banking regulations across countries in the late 1990s. Although banking
regulations are relatively stable over time, the measurement of regulatory distance prior
to the 1990s may not reflect the real regulatory differences in the banking industry.
In a conclusion, the three studies examined how institutional distance impacts
foreign-firm entry, foreign-firm local isomorphism strategy, and foreign subsidiary
performance. The results indicate that institutional distance has a persistent effect on
various aspects of foreign-firm activities. Although this research only serves as a first
step in the examination of a complex phenomenon, it lays the foundation for future

165
research exploring the interplay among institutional distance, firm-specific characteristics,
and foreign-firm strategy and performance.

166
REFERENCES

Aitken, B., Hanson, G.H., and Harrison, A.E. 1997. Spillovers, foreign investment and
export behavior. Journal of International Economics. 43: 103-132.

Aliber, R.Z. 1976. Towards a theory of international banking. Federal Reserve Bank of
San Francisco Economic Review. Spring: 5-8.

Aliber, R.Z. 1984. International Banking: A Survey. Journal of Money, Credit and
Banking, 16 (4-2): 661-678.

Allen, F. 1993. Stock market and resource allocation. In Mayer, C., and Vives, X. (Eds.)
Capital Markets and Financial Intermediation: 81-107. Cambridge, UK:
Cambridge University Press.

Argote, L. 1999. Organizational Learning: Creating, Retaining and Transferring
Knowledge. Boston, MA: Kluwer.

Anand, J. and Kogut, B. 1997. Technological capabilities of countries, firm rivalry and
foreign direct investment. Journal of International Business Studies, 28 (3):
445-465.

Argote, L., Beckman, S.L., and Epple, D. 1990. The persistence and transfer of learning
in industrial settings. Management Science, 36 (2): 140-154.

Baltagi, B. 2008. Econometric Analysis of Panel Data (4
th
Ed.). New York: John Wiley &
Sons.

Barkema, H.G., Shenkar, O., Vermeulen, F., and Bell, J.H.J. 1997. Working abroad,
working with others: How firms learn to operate international joint ventures.
Academy of Management Journal. 40 (2, Special research forum on alliances
and network): 426-442.

Barlett, C.A. and Ghoshal, M.Y. 1989. Managing across Borders: The International
Enterprises. Boston, MA: Harvard Business School.

Barreto, I. and Baden-Fuller, C. 2006. To conform or to perform? Mimetic behavior,
legitimacy-based groups and performance consequences. Journal of
Management Studies, 43 (7): 1559-1581.

Barnett, W.P., Greve, H., and Park, D.Y. 1994. An evolutionary model of organizational
performance. Strategic Management Journal, (Winter Special Issue) 15: 11-28.

167

Barth, J.R., Caprio, G. Jr., and Levine, R. 2000. Bank systems around the globe: Do
regulation and ownership affect performance and stability? World Bank Policy
Research Working Paper 2325.

Barth, J.R., Caprio, G. Jr., and Levine, R. 2001a. The regulation and supervision of banks
around the world: A new Database. World Bank Policy Research Working Paper
2588.

Barth, J.R., Caprio, G. Jr., and Levine, R. 2001b. Bank regulation and supervision: What
works best? World Bank Policy Research Working Paper 2725.

Baum, J.A.C., and Ingram, P., 1998. Survival-enhancing learning in the Manhattan hotel
industry, 1898-1990. Management Science, 44 (7): 996-1016.

Baum, J.A.C., Li, S.X. and Usher, J.M. 2000. Making the next move: How experiential
and vicarious learning shape the location of chains’ acquisitions. Administrative
Science Quarterly. 45 (4): 766-901.

Baum, J.A.C., and Mezias, S.J. 1992. Localized competition and organizational failure in
the Manhattan hotel industry, 1898-1990. Administrative Science Quarterly. 37
(4): 580-604.

Baum, J.A.C. and Oliver, C. 1991. Institutional linkages and organizational mortality.
Administrative Science Quarterly, 36 (2): 187-218.

Baum, J.A.C. and Singh, J. 1994. Organizational niches and the dynamics of
organizational mortality. American Journal of Sociology. 100: 346-380.

Beck, T., Clarke, G., Groff, A. Keefer, P. and Walsh, P. 2001. New tools in comparative
political economy: The database of political Institutions. World Bank Economic
Review, 15 (1): 165-176.

Belsley, D.A., Kuh, E. and Welsch, R.E.. 1980. Regression Diagnostics. John Wiley and
Sons: New York.

Benito, G.R.G. and Gripsrud, G. 1992. The expansion of foreign direct investments:
Discrete rational location choices or a cultural learning process? Journal of
International Business Studies. 23 (3): 461-476.

168
Berger, A. 1995. The profit-structure relationship in banking: Tests of market power and
efficient-structure hypotheses. Journal of Money, Credit, and Banking, 27: 404-
431.

Bhagat, R.S., Kedia, B.L., Harveston, P.D., and Triandis, H.C. 2002. Cultural variations
in the cross-border transfer of organizational knowledge: An integrative
framework. Academy of Management Review, 27 (2): 204-221.

Brouthers, K., and Brouthers, L. 2001. Explaining the national cultural distance paradox.
Journal of International Business Studies, 32 (1): 177-189.

Buckley, P.J. and Casson, M. 1976. The Future of Multinational Enterprise. New York:
Holmes & Meier Publishers.

Carroll, G.R. 1985. Concentration and specialization: Dynamics of niche width in
populations of organizations. American Journal of Sociology, 90: 1263-1283.
Carroll, G.R., and Hannan, M.T. 1989. Density dependence in the evolution of
populations of newspaper organizations. American Sociological Review, 54 (4):
524-541.
Caves, R.E. 1996. Multinational Enterprise and Economic Analysis. New York:
Cambridge University Press.

Chang, S.-J. 1995. International expansion strategy of Japanese firms: Capability building
through sequential entry. Academy of Management Journal, 38 (2): 383-407.

Chang, S.-J., and Park, S. 2005. Types of firms generating network externalities and
MNCs’ co-location decisions. Strategic Management Journal, 26 (7): 595-615.

Chung, W., and Song, J. 2004. Sequential investment, firm motives and agglomeration of
Japanese electronics firms in the United States. Journal of Economics &
Management Strategy, 13 (3): 539-560.

Cornell, B. and Shapiro, A.C. 1987. Corporate stakeholders and corporate finance.
Financial Management, 16 (1): 5-14

Cyert, R.M., and March, J. 1963. A behavioral theory of the firm. Englewood Cliffs, N.J.:
Prentice Hall.

Davis, G.F. 1991. Agents without principles? The spread of poison pills through the
intercorporate network. Administrative Science Quarterly, 38: 583-613.

169

Davidson, W.H. 1980. The location of foreign direct investment activity: Country
characteristics and experience effects. Journal of International Business Studies,
11 (2): 9-22.

Davidson, W.H., and McFetridge, D.G. 1985. Key characteristics in the choice of
international technology transfer. Journal of International Business Studies, 16
(2): 5-21.

Deephouse, D.L. 1996. Does isomorphism legitimate? Academy of Management
Journal, 39 (4): 1024-1039.

Deephouse, D. L. 1999. To be different, or to be the same? It’s a question (and theory) of
strategic balance. Strategic Management Journal, 20 (2): 147-166.

Delios, A., and Henisz, W.J. 2000. Japanese firms’ investment strategies in emerging
economies. Academy of Management Journal, 43 (3): 305-323.

DeYoung, R., and Nolle, D.E. 1996. Foreign-owned banks in the United States: Earning
market share or buying it? Journal of Money, Credit and Banking, 28 (4-1): 622-
636.

DiMaggio, P.J., and Powell, W.W. 1983. The iron cage revisited: Institutional
isomorphism and collective rationality in organizational fields. American
Sociological Review, 48(2): 147–160.

Dow, D., and Karunaratna, A. 2006. Developing a multidimensional instrument to
measure psychic distance stimuli. Journal of International Business Studies, 37
(5): 578-602.

Fiol, C.M. and Lyles, M.A. 1985. Organizational learning. Academy of Management
Review, 10 (4): 803-813.

Finkelstein, S., and Hambrick, D.C. 1990. Top-management-team tenure and
organizational outcomes: The moderating role of managerial discretion.
Administrative Science Quarterly, 35 (3): 484-503.

Fligstein, N. 1985. The spread of multidivisional form among large firms: 1919-1979.
American Sociological Review, 50 (3): 377-391.

Fomby, T.B., Hill, R.C. and Johnson, S.R. 1984. Advanced Econometric Methods. New
York: Springer-Verlag.

170

Gaba, V., Pan, Y., and Ungson, G.R. 2002. Timing of entry in international market: An
empirical study of U.S. Fortune 500 firms in China. Journal of International
Business Studies, 33 (1): 39-55.

Garcia-Pont, C., and Nohria, N. 2002. Local versus global mimetism: The dynamics of
alliance formation in the automobile industry. Strategic Management Journal, 23
(4): 307-321.

Gaur, A.S. and Lu, J.W. 2007. Ownership strategies and survival of foreign subsidiaries:
Institutional distance and experience. Journal of Management, 33 (1): 84-110.

Ghemawat, P. 2001. Distance still matters. Harvard Business Review, 79 (8): 137- 149.

Ghemawat, P., and Spence, A.M. 1985. Learning curve spillovers and market
performance. Quarterly Journal of Economics, 100: 839-852

Ghoshal, S., and Bartlett, C.A. 1990. The multinational corporation as an
interorganizational network. Academy of Management Review, 15 (4): 603-625.

Gilbert, R.A. 1984. Bank market structure and competition: A survey. Journal of Money,
Credit, and Banking, 16 (4-2): 617-644.

Goldberg, L.G., and Saunders, A. 1981. The determinants of foreign banking activity in
the United States. Journal of Banking and Finance, 5: 17-32.

Goldberg, L.S. and Klein, M.W. 1997. Foreign direct investment, trade and real exchange
rate linkages in developing countries. NBER Working Paper No. 6344.

Greene, W.H. 2000. Econometric Analysis. Upper Saddle River, NJ: Prentice Hall.

Greve, H.R. 2000. Market niche entry decisions: Competition, learning, and strategy in
Tokyo banking, 1894-1936. Academy of Management Journal, 43 (5): 816-836.

Grosse, R. and Goldberg, L.G. 1991. Foreign bank activity in the United States: An
analysis by country of origin. Journal of Banking and Finance, 15: 1093-1112.

Guillén, M.F. 2003. Experience, imitation, and the sequence of foreign entry: Wholly
owned and joint-venture manufacturing by South Korean firms and business
groups in China, 1987-1995. Journal of International Business Studies, 34 (2)
Focused issue: The future of multinational enterprise: 25 years later: 185-198.

171
Hannan, M.T., and Freeman, J. 1977. The population ecology of organizations. American
Journal of Sociology, 82 (5): 929-964.

Hannan, M.T. and Freeman, J. 1984. Structural inertia and organizational change.
American Sociological Review, 49: 149-164.

Hannan, M.T. and Freeman, J. 1988. The ecology of organizational mortality: American
labor unions, 1836-1985. American Journal of Sociology, 94 (1): 25-52.

Haunschild, P.R., and Miner, A.S. 1997. Modes of interorganizational imitation: The
effects of outcome salience and uncertainty. Administrative Science Quarterly,
42 (3): 472-500.

Haveman, H.A. 1993. Follow the leader: Mimetic isomorphism and entry into new
markets. Administrative Science Quarterly, 38 (4): 593-627.

He, C. 2002. Information costs, agglomeration economies and the location of foreign
direct investment in China. Regional Studies, 36: 1029-1036.

Henisz, W.J. 2002. The institutional environment for infrastructure investment.
Industrial and Corporate Change, 11(2): 355–389.

Henisz, W.J., and Delios, A. 2001. Uncertainty, imitation and plant location: Japanese
multinational corporations, 1990-1996. Administrative Science Quarterly, 46 (3):
443-475.

Hennart, J.-F. 1982. A Theory of Multinational Enterprise. Ann Arbor, MI: University
of Michigan Press.

Hofstede, G. 2001. Culture’s Consequences: Comparing Values, Behaviors,
Institutions, and Organizations Across Nations (2nd ed.). Sage Publications:
Thousand Oaks, CA.

Hsiao, C. 2003. Analysis of Panel Data. Cambridge: Cambridge University Press.

Huber, G.P. 1991. Organizational learning: The contributing Processes and the literatures.
Organization Science, 2 (1, Special issue: Organizational learning: Papers in
honor of (and by) James G. March. (1991)): 88-115.

Hymer S. 1960. The International Operations of National Firms: A Study of Direct
Foreign Investment. Cambridge, Mass: The MIT Press.

172
Ingram, P. 2002. Interorganizational learning. In Baum, J.A.C. (Ed.), Companion to
Organizations: 642-663. New York: Blackwell.

Ingram, P., and Baum, J.A.C. 1997. Opportunity and constraint: Organizations’ learning
from the operating and competitive experience of industries. Strategic
Management Journal, 18 (Special issue: Organizational and competitive
interactions): 75-98.

Isard, P. 1995. Exchange Rate Economics. Cambridge: Cambridge University Press.

Jaccard, J., Turrisi, R., and Wan, C.K. 1990. Interaction Effects in Multiple Regression.
Thousand Oaks: Sage Publications.

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.

Keefer, P. and Stasavage, D. 2003. The limits of delegation: Veto players, central bank
independence, and the credibility of monetary policy. American Political
Science Review, 97 (3): 407-424.

Kennedy, P. 1998. A Guide to Econometrics (4th ed.). Cambridge, MA: MIT Press.

Kindleberger, C. 1969. American Business Abroad. New Haven, CT: University Press.

Klein, M.W. and Rosengren, E.S. 1992. The real exchange rate and foreign direct
investment in the United States: Relative wealth vs. relative wage effects. Federal
Reserve Bank of Boston Working Paper No. 92-2.

Kogut, B. and Chang, S.J. 1991. Technological capabilities and Japanese foreign direct
investment in the United States. Review of Economics and Statistics, 73: 401-413.

Koch, T.W. and MacDonald, S.S. 2005. Bank Management. (6
th
Ed) Boston: South-
Western College Pub.

Kogut, B. and Singh, H. 1988. The effect of national culture on the choice of entry mode.
Journal of International Business Studies, 19 (3): 411-432.

Kostova, T. 1996. Success of transnational transfer of organizational practices within
multinational companies. University of Minnesota Doctoral dissertation.

173
Kostova, T., and Zaheer, S. 1999. Organizational legitimacy under conditions of
complexity: The case of the multinational enterprise. Academy of Management
Review, 24 (1): 64-81.

La Porta, R., Lopez-de-Silanes, F., Shleifer, A., and Vishny, R.W. 1998. Law and finance.
Journal of Political Economy, 106 (6): 1113–1155.

Levine, R. 2002. Bank-based or Market-based Financial Systems: Which is better?
William Davidson Working Paper No. 442.

Levitt, B., and March, J.G. 1988. Organizational learning. Annual Review of Sociology,
14: 319-340.

Levinthal, D.A., and March, J.G. 1993. The myopia of learning. Strategic Management
Journal, 14 (Winter special issue): 95-112.

Li, J. and Guisinger, S. 1991. Comparative business failures of foreign-controlled firms
in the United States. Journal of International Business Studies, 22 (2): 209-224.

Lieberman, M. 1987b. The learning curve, diffusion, and competitive strategy. Strategic
Management Journal, 8 (5): 441-452

Lipsey, R. E. 1994. Foreign-owned firms and US wages. NBER Working Paper, 4927.

Makino, S., Isobe, T., and Chan, C.M. 2004. Does country matter? Strategic
Management Journal, 25 (10): 1027-1043.

Martin, X., and Salomon, R. 2003. Tacitness, learning and international expansion: A
study of foreign direct investment in a knowledge-intensive industry.
Organization Science, 14 (3): 297-311.

Marshall, A. 1920. Principle of Economics. London: Macmillan.

Mata, J. and Portugal, P. 2002. The survival of new domestic and foreign-owned firms.
Strategic Management Journal, 23:323-343

Mehra, A. 1996. Resource and market based determinants of performance in the U.S.
banking industry. Strategic Management Journal. 17 (4): 307-322.

174
Meyer, J.W., and Rowan, B. 1977. Institutionalized organizations: Formal structure as
myth and ceremony. American Journal of Sociology, 83: 340–363.

Mezias, S.J. 1990. An institutional model of organizational reporting practice: Financial
reporting at the Fortune 200. Administrative Science Quarterly, 35: 431-457.

Mezias, J.M. 2002. Identifying liabilities of foreignness and strategies to minimize their
effects: The case of labor lawsuit judgments in the United States. Strategic
Management Journal, 23 (2): 229-244.

Mezias, S., and Lant, T. 1994. Mimetic learning and the evolution of organizational
populations. In Baum, J.A.C., and Singh, J. (Eds.) Evolutionary Dynamics of
Organizations: 179-193. New York: Oxford University Press.

Mezias, J.M. and Mezias, S.J. 2000. Resource partitioning, the foundation of specialist
firms and innovation: the American feature film industry, 1912-1929.
Organization Science 11: 306-322.

Miller, S.R., and Eden, L. 2006. Local density and foreign subsidiary performance.
Academy of Management Journal, 49 (2): 341-355.

Miller, S.R., and Parkhe, A. 2002. Is there a liability of foreignness in global banking?
An empirical test of banks’ x-efficiency. Strategic Management Journal, 23 (1):
55-75.

Mincer, J. and M. Higuchi. 1988. Wage structures and labour turnover in the US and
Japan. Journal of the Japanese and International Economies, 2: 97-133.

Miner, A.S., and Haunschild, P.R. 1995. Population level learning., In Cummings, L.L.,
and Staw, B.M. (Eds.) Research in Organizational Behavior: 115-166.
Greenwich, CN: JAI Press.

Mitchell, W., Shaver, J.M., and Yeung, B. 1994. Foreign entrant survival and foreign
market share: Canadian companies’ experience in United States medical sector
markets. Strategic Management Journal, 15 (7): 555-567.

Morck, R. and Yeung, B. 1991. Why investors value multinationality. Journal of
Business, 64 (2): 165-187.

175
Morosini, P., Shane, S., and Singh, H. 1998. National cultural distance and cross-border
acquisition performance. Journal of International Business Studies, 29 (1): 137-
158.

Mudambi, R. 1998. The role of duration in multinational investment strategies. Journal
of International Business Studies, 29 (2): 239-251.

Nachum, L. and Zaheer, S. 2005. The persistence of distance? The impact of technology
on MNE motivations for foreign investment. Strategic Management Journal, 26:
747-767.

North, D. 1991. Institutions. Journal of Economic Perspectives, 5 (1): 97-112.

Palmer, D.A., Jennings, P.D., and Zhou, X. 1993. Late adoption of the multidivisional
form by large U.S. corporations: Institutional, political, and economic accounts.
Administrative Science Quarterly. 38 (1): 100-131.

Perkins, S. 2008. Why does prior experience pay? Institutional experience and the case of
multinational corporation. Working Paper.

Pfeffer, J., and Salancik, G.R. 1978. The External Control of Organization. New York:
Harper & Row.

Porter, M.E. 1980. Competitive Strategy. New York: Free Press.

Porter, M.E. 1998. On competition. Boston: Harvard Business School Press.

Rajan, R.G., and Zingales, L. 1998. Financial dependence and growth. American
Economic Review, 88 (3): 559-586.

Rangan, S., and Drummond, A. 2004. Explaining outcomes in competition among
foreign multinationals in a focal host market. Strategic Management Journal, 25
(3): 285-293.

Rauch, J.E. 1999. Networks versus markets in international trade. Journal of
International Economics, 48: 7-35.

Rhee, M., Kim, Y-C., and Han, J. 2006. Confidence in Imitation: Niche-width strategy in
the UK Automobile industry. Management Science, 52 (4): 501-513.

176
Rosenzweig, P.M., and Nohria, N. 1994. Influences on human resource management
practices in multinational corporations. Journal of International Business
Studies, 25 (2): 229-251.

Rosenzweig, P.M., and Singh, J.V. 1991. Organizational environments and multinational
enterprise. Academy of Management Review, 16 (2): 340-361.

Salomon, R. and Martin, X. 2008. Learning, Knowledge Transfer, and Technology
Implementation Performance: A Study of ‘Time-to-Build’ in the Global
Semiconductor industry. Management Science. Forthcoming.

Scott, W.R. 1995. Institutions and Organizations. Thousand Oaks, CA: Sage
Publications.

Scott, W.R. and Meyer, J.W. 1991. The organization of societal sectors. In Powell, W.W.
and DiMaggio, P.J. (Eds), The New Institutionalism in Organizational Analysis:
108-140. Chicago: University of Chicago Press.

Shaver, J.M. 1998. Accounting for Endogeneity When Assessing Strategy Performance:
Does Entry Mode Choice Affect FDI Survival? Management Science, 44 (4):
571-585.

Shaver, J.M., Mitchell, W., and Yeung, B. 1997. The effect of own-firm and other-firm
experience on foreign direct investment survival in the United States, 1987-92.
Strategic Management Journal, 18 (10): 811-824.

Shenkar, O. 2001. Cultural distance revisited: Towards a more rigorous conceptualization
and measurement of cultural differences. Journal of International Business
Studies, 32 (3): 519-535.

Sponge, K. 1985. Banking Regulation: Its Purposes, Implementation, and Effects (2
nd

ed.). Kansas City: Federal Reserve Bank of Kansas city.

Sponge, K. 1990. Banking Regulation: Its Purposes, Implementation, and Effects (3
rd

ed.). Kansas City: Federal Reserve Bank of Kansas city.

Sponge, K. 2000. Banking Regulation: Its Purposes, Implementation, and Effects (5
th

ed.). Kansas City: Federal Reserve Bank of Kansas city.

177
Staw, B. M. and Epstein, L.D. 2000. What bandwagons bring: Effects of popular
management techniques on corporate performance, reputation, and CEO pay.
Administrative Science Quarterly, 45 (3): 523-556.

Suchman, M.C. 1995. Managing legitimacy: Strategic and institutional approaches.
Academy of Management Review, 20 (3): 571-610.

Sullivan, D., and Bauerschmidt, A. 1990. Incremental internationalization: A test of
Johanson and Vahlne’s Thesis. Management International Review, 30 (1): 19-
30.

Swaminathan, A. 1998. Entry into new market segments in mature industries:
Endogenous and exogenous segmentation in the U.S. brewing industry. Strategic
Management Journal, 19: 389-404.

Terrell, H.S. and Key, S. 1977. The U.S. activities of foreign banks: An analytic survey.
Board of Governors of the Federal Reserve System, International Finance
Division Paper No. 113.

Tihanyi, L., Griffith, D.A., and Russell, C.J. 2005. The effect of cultural distance on entry
model choice, international diversification, and MNE performance: A meta-
analysis. Journal of International Business Studies, 36 (3): 270-283.

United Nations. 2009. Member states of the United Nations.
http://www.un.org/en/members/index.shtml

Vernon, R. 1971. Sovereignty at Bay: The Multinational Spread of U.S. Enterprises.
New York: Basic.

White, B.B. 1982. Foreign banking in the United States: A regulatory and supervisory
perspective. Quarterly Review (Federal Reserve Bank of New York), Summer:
48-58.

Xu, D. 2001. The effect of institutional distance on multinational enterprise strategy.
York University Doctoral Dissertation.

Xu, D., and Shenkar, O. 2002. Institutional distance and the multinational enterprise.
Academy of Management Review, 27 (4): 608- 618.

Zaheer, S. 1995. Overcoming the liability of foreignness. Academy of Management
Journal, 38 (2): 341-363.

178
Zaheer, S., and Mosakowski, E. 1997. The dynamics of the liability of foreignness: A
global study of survival in financial services. Strategic Management Journal, 18
(6): 439-463.

Zhao, M. 2006. Conducting R&D in countries with weak intellectual property rights
protection. Management Science, 52: 1185-1199.

Zucker, L.G. 1987. Institutional theories of organization. In Scott, W. R. and Short, J.F.
Jr. (Eds.) Annual Review of Sociology, 13: 443-464. Palo Alto, Ca: Annual
Reviews.

Abstract (if available)

Abstract This dissertation consists of three essays on the impact of institutional distance on foreign firm entry, local isomorphism strategy and foreign subsidiary performance. These studies employ two samples: the first one includes the foreign banks that entered the United States from 61 home countries during 1956-2006. The second one includes all foreign bank subsidiaries (83 in Essay 2 and 84 in Essay 3) that operated in the United States from 1978 to 2006.

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Asset Metadata

Creator Wu, Zheying (author)

Core Title Three essays on distance: examing the role of institutional distance on foreign firm entry, local isomorphism strategy and subsidiary performance

School Marshall School of Business

Degree Doctor of Philosophy

Degree Program Business Administration

Publication Date 10/02/2009

Defense Date 09/01/2009

Publisher University of Southern California (original), University of Southern California. Libraries (digital)

Tag entry,foreign subsidiary performance,institutional distance,international business,local isomorphism strategy,OAI-PMH Harvest,strategy

Place Name USA (countries)

Language English

Contributor Electronically uploaded by the author (provenance)

Advisor Mayer, Kyle J. (committee chair), Salomon, Robert (committee chair), Hsiao, Cheng (committee member), Kim, Jay (committee member), Rajagopalan, Nandini (committee member)

Creator Email Z.Wu1@uvt.nl,zheying.wu.2008@marshall.usc.edu

Permanent Link (DOI) https://doi.org/10.25549/usctheses-m2634

Unique identifier UC1235327

Identifier etd-Wu-3247 (filename),usctheses-m40 (legacy collection record id),usctheses-c127-599523 (legacy record id),usctheses-m2634 (legacy record id)

Legacy Identifier etd-Wu-3247.pdf

Dmrecord 599523

Document Type Dissertation

Rights Wu, Zheying

Type texts

Source University of Southern California (contributing entity), University of Southern California Dissertations and Theses (collection)

Repository Name Libraries, University of Southern California

Repository Location Los Angeles, California

Repository Email cisadmin@lib.usc.edu