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NOT ALL COMPETITORS ARE CREATED EQUAL:
THE HETEROGENEITY OF MNE COMPETITORS AND ITS
COMPETITIVE CONSEQUENCES
Lilach Nachum
Baruch College, City University New York
55 Lexington Avenue, New York, NY 10010, USA
Lilach_Nachum@baruch.cuny.edu
Marina Carnevale
Fordham University
113 West 60th street, New York, NY 10458, USA
mcarnevale3@fordham.edu
Helaine Korn
Baruch College, City University New York
55 Lexington Avenue, New York, NY 10010, USA
Helaine.Korn@baruch.cuny.edu
Key words: MNE competitors, competitors’ heterogeneity, MNE competitive position, nationality,
location of the competition, legal services
Acknowledgement
We acknowledge with gratitude thoughtful comments of Joel Baum, Mehmet Genc, Michael Hitt, Artur
Kalnins, Christine Parker, Christos Pitelis, Rajeev Sawant, Prakash Sethi, Carole Silver, the participants
at the 2009 Clifford Chance Conference on Professional Services Firms at Harvard Law School, in the
3rd Israeli Strategy Conference, and in seminars at the National University of Singapore and at the Center
of Business Research of Cambridge University on earlier drafts of the paper. We extend special gratitude
to Mr. Dario de Martino, then at Cravath, and Mr. Lowry, then of the American Lawyer Association, for
generously sharing with us their expertise of the industry.
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NOT ALL COMPETITORS ARE CREATED EQUAL:
THE HETEROGENEITY OF MNE COMPETITORS AND ITS
COMPETITIVE CONSEQUENCES
Abstract.
By virtue of their participation in multiple competitive settings, MNEs confront competitors with
different attributes and in different locations. These variations pose different challenges across
competitive settings. Building on competition and RBV theories, combined with MNE theory, we
hypothesize that the value of MNEs’ assets and the intensity of the competition they face vary in relation
to competitors of different nationalities, geographic scope, and locations. These predictions are tested on
US legal-services MNEs in competition with US domestic firms and non-US MNEs in the US and
abroad. The variations we find reconcile the puzzling varying competitive positions of MNEs across
countries.
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The business landscape is scattered with examples of MNEs developing prevailing advantages in
a certain country by exploiting their assets and building on them to establish strong competitive position,
whereas these same assets are far less potent of a competitive advantage in other countries, leaving the
MNE’s position short of its success elsewhere. What do these differences tell about the competitive value
of MNE assets and the ways by which they should be deployed? Why does the value of the same asset
vary in different countries? And what are the consequences of such variations for the competitive
intensity that MNEs confront across different countries?
Strategic management theory suggests that the competitive value of firms’ assets is relative to the
competition and can only be understood with explicit reference to the competition (Porter, 1985). The
resource based view (RBV) of the firm similarly emphasizes the relative aspect of firms’ assets, which
have to be rare and superior to those of the competition for them to be sources of competitive advantage
(Barney, 1991). The insight of this work, however, has not been fully incorporated in MNE theory.
MNE theory references to the competition have been made primarily in discussions of the
decision to invest abroad and the patterns of internationalization (Head, Mayer & Ries, 2002; Gimeno,
Hoskisson, Beal & Wan, 2005; Ghemawat & Thomas, 2008; Alcacer, 2012). They are also implicit in
research on the liability-of-foreignness (Zaheer, 1995), whereby MNEs’ competitive positions are studied
in relation to domestic firms (Nachum, 2010). These studies have made important contributions to the
understanding of competitors’ impact on MNEs, but they do not consider it as a factor that determines the
value of MNE assets and shapes their competitive position. The theory of MNE assets focuses on internal
assets as the prerequisite for foreign investment, and views their value as being determined endogenously,
based on the possession of certain capabilities (Hymer, 1960; Caves, 1996). Implicit in this
conceptualization is the assumption that these assets are constant and their value does not vary across
competitive settings. Discussions of the internalization of the cross-border market for knowledge as the
driver of foreign activity (Buckley & Casson, 1976), and the theory of monopolistic advantages (Lall,
1980) suggest that these assets are unique to the firms possessing them, but this notion has not been
employed in relation to the competition. MNE theory thus provides limited means to explain the
competitive dynamics that MNEs confront, and strategic management theory may not be suitable for
examination of variations in competitive dynamics across countries.
In this paper we seek to deepen the understanding of competitive dynamics in the context of the
MNE. Building on competition and RBV theories (Barney, 1991, 2001; Chen & Miller, 2012), combined
with MNE theory (Hymer, 1960; Caves 1996), we develop a theoretical framework whereby competitive
value is determined with explicit reference to the competition. We further assume that the competitors
that MNEs confront are heterogeneous in terms of the assets they possess, and hence the competitive
value of MNE assets is context-specific by its very nature and varies across competitive environments
(Priem & Butler, 2001; Arora & Nandkumar, 2012). We maintain that the most important distinguishing
features of MNE competitors are nationality, geographic scope (domestic firms or MNEs), and location,
and advance hypotheses that anticipate the value of MNE assets and the intensity of the competition in
competition with these competitor-groups and across locations.
The empirical testing is based on US legal-services MNEs as the focal MNEs in competition with
US domestic legal-services firms and non-US legal services MNEs in the US and abroad, observed over a
five-year period (2004 through 2008). We find support for the anticipated variations of the competitive
value of MNE assets and the intensity of the competition in competition with different competitor-groups
and in different locations. Of the three distinguishing attributes of the competition, the location of the
competitive engagement exercises the strongest impact on competitive value and on the intensity of the
competition, whereas competitors’ nationality and their geographic scope are of limited importance.
The study makes several important contributions to MNE theory. For one, studying the
competition as the factor that determines the competitive value of MNE assets is an important
contribution to a research tradition that, with its focus on the role of such assets in explaining the
existence of the MNE (Hymer, 1960; Caves, 1996) and the strategic challenges they confront (Bartlett &
Ghoshal, 1989), has paid limited attention to the competition. The recent interest in MNE interorganizational relationships (Contractor & Lorange, 2002; Beamish, 2008) has further marginalized
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research interest in the competition. This inhibits the ability to apprehend the range of relationships
among firms. Further, by virtue of their operations in multiple competitive settings, MNEs confront
competitors with varying characteristics, which pose different competitive challenges. The oligopolistic
structure of the industries in which MNEs compete (Caves, 1996) makes the competition particularly
detrimental in shaping MNEs’ competitive position. Disregard to the competition inhibits the ability to
comprehend the determinants of MNE competitive position.
Further, by drawing attention to competitors’ heterogeneity and explicitly accounting for its
impact on competitive dynamics, our study introduces a notion of MNE assets that vary across
competitive settings, and presents the variations in MNE competitive positions across countries as an
intrinsic attribute of international competition. This contribution is particularly important in the
contemporary business environment, where the competitors that MNEs confront have become more
heterogeneous than ever before. It also extends the range of competitors considered in MNE theory
beyond the traditional focus on domestic firms as the pertinent competition (Hymer, 1960). Notably, it
throws light on other MNEs, which in many competitive settings are the most significant competitors of
MNEs.
The focus on legal-services MNEs is another noteworthy contribution of the study. This industry
is important by itself and as representative of professional-services industries. According to a recent
McKinsey study, these industries are the largest contributors to the budget surplus in mature economies
(McKinsey Global Institute, 2012). Deepening the understanding of these industries is thus a contribution
of notable merit.
The study makes important contributions also for practice. The neglect of the competition could
result in strategic moves that differ from those that would have been undertaken had the competition been
explicitly taken into consideration. It could lead MNEs to select actions that maximize their performance
in the absence of competition, but not necessarily in its presence (Simonsohn, 2010). The variations we
illustrate in the competitive dynamics across different competitors call for different strategic responses,
and provide MNEs a basis for differentiating themselves in relation to different competitor-groups.
THEORY AND HYPOTHESES
Competition theory attributes the heterogeneity of the competitors that firms face to them
belonging to different strategic groups (Mas-Ruiz & Ruiz-Moreno, 2011), competing in varying product
and resource markets (Chen & Miller, 2012), or operating in different locations (Fuentelsaz & Gomez,
2006). Research in this tradition shows that competitor-groups share common attributes that distinguish
them from other groups, and as a result of this heterogeneity, they pose different competitive challenges,
such that the competitive dynamics across competitor-groups vary.
Extending this notion to the context of the MNE, we suggest that the most important
distinguishing features of competitors are nationality, geographic scope, and location. These three
attributes form the defining characteristics of the MNE, and hence exercise the most significant impact on
the competitive value of MNE assets and the resulting competitive dynamics. Nationality is impactful
because international competition brings together firms of different nationalities whose assets are shaped,
at least in part, by the resources of their home-countries (Porter, 1990), giving rise to asset-variations
across competitors of different nationalities (Makino, Isobe & Chan, 2004; Fabrizio & Thomas, 2012).
Shared nationality is also likely to lead firms to expand abroad in tandem (Head et al., 2002), resulting in
market similarity among them (Chen & Miller, 2012). The international expansion of firms often evolves
in a predictable manner based on the geographic, cultural, and psychic distance from their home
countries.
Geographic scope sets MNEs apart from domestic firms and establishes their distinctiveness.
MNEs are assumed to have technology, advertising, and managerial skills that are superior to those of
domestic firms (Hymer, 1960). These differences are further accentuated by international activity, which
affords MNEs access to resources worldwide and the flexibility to mobilize resources across countries
(Kogut & Kulatilaka, 1994). It also enables MNEs to grow large and enjoy strong market power and
economies of scale and scope (Caves, 1996), further differentiating them from domestic firms.
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Activity in multiple locations is the distinguishing characteristic of MNE activity. Location
shapes the vigor of MNE assets (Barney, 2001), and, as a result, the same competitor poses different
competitive challenges in different locations. Further, the competitive behavior of firms varies across
locations, in line with the position that locations occupy in their identity (Livengood & Reger, 2010),
accentuating differences in competitive dynamics across locations.
Competitors’ heterogeneity in terms of nationality, geographic scope and location entails that the
value of MNE assets varies in competition with different competitor-groups. This variation finds its
theoretical underpinning in RBV theory, whereby the environment external to firms is viewed as
exercising major impact on the competitive value of their resources (Barney, 1991, 2001; Priem & Butler,
2001), such that the sources of their competitive advantages vary across different environments (Miller &
Shamsie, 1996; Arora & Nandkumar, 2012). The focus of this tradition has been on product- and factormarkets as the environmental attributes that introduce this variation. Building on competition theory
(Chen & Miller, 2012), we extend this idea and bring the competition as an additional environmental
attribute that introduces variations in the value of firms’ assets across environments. We maintain that
different assets, or the same ones to different degrees, are of value in competition with competitor-groups
that vary by nationality, geographic scope and location. In what follows, we advance hypotheses that
outline the anticipated direction of this variation.
The Competitive Value of MNE Assets in Competition with Different Competitor-groups
MNEs possess three types of assets: firm-specific assets, originating in the proprietary possession
of intangible capabilities that are mobile within firms across countries (Hymer, 1960; Bloom, Sadun &
Reenen, 2012), multinationality assets, which derive from the ability to access resources and knowledge
in different countries and the flexibility that activity in multiple countries affords (Kogut & Kulatilaka,
1994), and home-based assets that are based on the privileged access that firms enjoy to their homecountry resources (Porter, 1990).
The three types of assets are interconnected but yet distinct, and exercise independent impact on
MNEs’ competitive performance. The distinction we make between firm-specific and home-based assets
is akin to the RBV distinction between resources (home-based) and capabilities (firm-specific) (Amit
& Schoemaker, 1993). The former are tradable and non-specific to the firm, whereas the latter are firmspecific and employed to engage resources within the firm (Barney, 2001; Adegbesan, 2009). While all
firms have access to their home-country resources, they vary in their ability to utilize these resources, in
line with their firm-specific capabilities. Governments on their part introduce additional differences by
granting some firms access to resources that is deprived of others. The multinationality assets and firmspecific assets differ in terms of the geographic scope that give them rise. The firm-specific assets are
derived from capabilities that are not related to international activity (Hymer, 1960; Caves, 1996),
whereas the multinationality assets originate in international activity itself, and firms’ ability to exploit
similarities and differences across countries (Bartlett & Ghoshal, 1989; Gupta, Govindarajan & Roche,
2001). Lastly, the multinationality and home-based assets share some affinity, in that home-country
affects the nature of international expansion, and shapes firms’ internationalization paths, but they vary in
the type of assets associated with them.
The hypotheses we develop below outline how the competitive value of the three MNE assets
varies in relation to different competitor-groups. They are underlain by the notion that competitive value
is determined by assets’ distinctiveness relative to the competition (Porter, 1985; Barney, 1991). Shared
assets are of limited value because they do not differentiate an MNE from the competition, but could
become potent competitive advantages in competition with competitors that lack such assets or cannot
access them on similar terms.
Firms of the same nationality tend to develop similar types of firm-specific assets, based on the
characteristics of their home environment and in response to the demand of their home consumers (Porter,
1990). Substantial research shows that firm-specific assets vary systematically across MNEs of different
nationalities in a manner that reflects the characteristics of their home environment (Wan & Hoskisson,
2003; Makino, Isobe & Chan, 2004). Hence, the value of firm-specific assets is weak in competition with
competitors of the same nationality that similarly can access them, but it is most compelling in
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competition with MNEs of different nationalities that do not share similar assets (Fabriozio & Thomas,
2012).
Further, the privileged access of firms to their home-country assets distinguishes the home-based
assets of firms of different nationalities and makes them potent sources of competitive advantage in
competition with MNEs of other nationalities. Foreign MNEs are not as able to connect with local
resources and mobilize them, nor can they interpret local demand and respond to it as effectively as local
MNEs can (Dahl & Sorenson, 2012; Fabrizio & Thomas, 2012). Assets based on home-country resources
thus give MNEs advantage over firms of other nationalities. The multinationality assets are of limited
value in competition with MNEs of different nationalities because in competition among MNEs, all the
participants are assumed to have them. Formally:
H1: MNEs’ competitive performance relative to competitors of nationalities other than their own
is positively determined by firm-specific and home-based assets.
The geographic scope of competitors is also expected to introduce variations in the competitive
value of MNE assets. The multinationality assets, which MNEs possess by virtue of their international
activity, provide them competitive advantages in competition with domestic firms. The narrow
geographic scope of the latter inhibits their access to the multinationality assets, awarding these assets
distinctive value in competition with these firms. The firm-specific assets are also likely to be sources of
powerful competitive advantages in competition with domestic firms because the firm-specific assets of
MNEs are assumed to be stronger than those of domestic firms (Hymer, 1960; Caves, 1996). When the
competition is studied between domestic firms and MNEs of the same nationality, as we do here, the
home-based assets are unlikely to be of competitive significance because firms of the same nationality are
assumed to enjoy similar access to these assets. Formally:
H2: MNEs’ competitive performance relative to domestic firms is positively determined by
multinationality and firm-specific assets.
Location affects the competitive value of MNE assets, and hence different assets are of value in
competition (with the same competitors) in different locations. Support for anticipating such variation is
provided by the notion that firms’ assets are shaped in an interaction with their external environment such
that they are often context-specific (Johns, 2006) and change their value across different locations. RBV
theory is explicit in articulating such variations, as originating in the interaction between firms’ assets and
environmental resources (Barney, 2001; Priem & Butler, 2001), and suggests that as a result, advantages
vary in different environments (Miller & Shamsie, 1996; Arora & Nandkumar, 2012).
Such variations are expected across locations in general, but we confine our scope to the
distinction between home and abroad, and suggest that the competitive value of the home-based assets is
likely to be more significant at home than abroad. These assets are often built based on country resources
and in response to the characteristics of local demand (Fabrizio & Thomas, 2012). Many of these are
immobile and may lose their value in other competitive settings (Liker, Fruin & Adler, 1999; Maitland &
Sammartino, 2012). Hence, these assets are effective sources of competitive advantages in competition at
home, but may be of limited competitive value abroad. Firm-specific assets are likely to be powerful
sources of competitive advantages both at home and abroad. MNE theory is explicit in relation to the
critical role of these assets in enabling MNEs to operate in foreign markets. MNEs are assumed to employ
these assets in multiple locations and use them to overcome the additional costs of foreign operations
(Hymer, 1960; Zaheer, 1995). The multinationality assets are unlikely to be valuable in such competitions
because all the participants are MNEs. Formally:
H3: MNEs’ competitive performance at home is positively determined by firm-specific assets and
home-based assets.
H4: MNEs’ competitive performance abroad is positively determined by firm-specific assets.
The Intensity of the Competition with Different Competitor groups
The variations in the competitive value of MNE assets in competition with different competitorgroups advanced in the previous hypotheses are likely to be associated with differences in competitive
intensity. Below we advance hypotheses that outline our expectations in relation to the nature and
direction of these differences. We base our theorization on competition theory which suggests that
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competitive intensity is determined by the similarity among firms. Whereas this assumption is wellestablished, the theory is inconclusive in relation to the nature and direction of the impact.
Some theoretical strands provide basis for anticipating that greater similarity is associated with
more intense competition because similar firms tend to compete for the same resources and markets
(Fuentelsaz & Gomez, 2006; Chen & Miller, 2012). This theorization suggests that because MNEs of the
same nationality share similar attributes that distinguish them from MNEs of other nationalities, they are
likely to compete more intensely with each other than with MNEs of other nationalities. Moreover, firms
tend to regard competitors of their own nationality as stronger competitors and perceive their competitive
position in relation to them central to their pride and image (Porter, 1990). Competitors of the same
nationality often pose the most significant threat to firms’ competitive position at home. Given the
importance of this market for firms’ identity (Livengood & Reger, 2010), they are likely to compete most
fiercely with them.
Other theoretical perspectives, however, suggest that firms that are more similar to each other
compete less intensely. The similarity among firms of the same nationality (Porter, 1990) entails that they
often have common suppliers, distributors, and customers. They also have a sense of shared identity and
common fate, affected by developments in their home countries, including their government policies.
They are also more likely to meet each other in multiple markets, as their international expansion often
evolves in tandem and along similar paths (Head et al., 2002). These multimarket contacts make them
realize dependency and shared interest, and tend to lessen competitive pressure to prevent retaliation,
what is known as mutual forbearance (Korn & Baum, 1999; Fuentelsaz & Gomez, 2006). Yu,
Subramaniam and Cannella (2009) found support for the prevalence of mutual forbearance in
international competition and show that as the degree of multimarket contacts among MNEs increases,
their competitive aggressiveness diminishes. Formally:
H5a: MNEs compete more intensely with MNEs of their own nationality than with MNEs of other
nationalities.
H5b: MNEs compete less intensely with MNEs of their own nationality than with MNEs of other
nationalities.
Competing predictions arise also in relation to the impact of competitors’ geographic scope on the
intensity of the competition. On the one hand, differences between MNEs and domestic firms in terms of
their characteristics and the assets they have (Hymer, 1960; Caves, 1996) lessen the competition between
them for consumers, suppliers, and resources. In contrast, for domestic competitors, a given market is by
definition the only one, whereas for MNEs it is one of many. This introduces differences in terms of the
importance of the market in question and the costs of entry and exit. Domestic firms are likely to protect
their single market more fiercely than MNEs, accentuating the intensity of the competition with them. In
addition, the mutual forbearance impact is prevalent among MNEs, which meet each other in multiple
markets, but is absent in competition with domestic firms. This lessens the intensity of the competition
among MNEs, leading to more intense competition between them and domestic firms. Formally:
H6a: MNEs compete more intensely with other MNEs than with domestic firms.
H6b: MNEs compete less intensely with other MNEs than with domestic firms.
We further suggest that competitive intensity with the same competitors varies across locations,
notably at home and abroad. MNEs tend to protect their competitive position with greater rigor at home
than abroad. Competition theory suggests that competitive arenas vary in terms of their importance for
firms’ identities, and this variation shapes competitive behavior. Firms are likely to defend more
aggressively competitive arenas they regard as central to their identity, even when such behavior is at
odds with anticipated financial rewards (Livengood & Reger, 2010). The home market is the competitive
arena that captures and reinforces firms’ sense of identity (Dahl & Sorenson, 2012), and hence they are
likely to compete more aggressively at home than abroad.
Further, the competitive value of MNE assets is usually more at home than abroad, enabling them
to respond more fiercely to competitive threats at home. Some MNE assets are location-specific and
imperfectly mobile, and their competitive value may diminish, or even disappear, when taken outside the
home-market context in which they are most often developed (Maitland & Sammartino, 2012). In
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addition, in their international operations, MNEs often confront liabilities of foreignness and newness,
and these too reduce the competitive vigor of their assets (Zaheer, 1995). The superior performance of
MNEs in their home countries (Victer, 2007) is indicative of the strength of their assets in this location,
and suggests that they can defend it more rigorously. Formally:
H7: MNEs compete more intensely (with the same competitors) in their home country than
abroad.
In Table 1 we present a summary of the hypotheses.
Table 1 about here
METHODOLOGY
The Empirical Setting
We confine the study to a single industry to control for structural effects at the industry level that
influence the dynamics of the competition. This industry-focused enriches the understanding of theories
by illustrating how industry characteristics affect organizational dynamics and firm strategy, and at the
same time also provide rich basis for further theoretical development. The legal-services industry was
selected for the empirical analysis because it has several characteristics that make it appropriate for our
study. For one, it offers the range of competitors required for the testing of the hypotheses, competing
with each other, a requirement that is not met by industries dominated by a few large global players or
else by those in which MNEs and domestic firms are not in direct competition. Further, notwithstanding
substantial consolidation of the industry in recent decades (Galanter & Palay, 1991), the level of
concentration is low compared with other industries in which international activity proliferates, providing
large numbers of firms for observation. The industry’s professional requirements and accreditation
processes create well-defined boundaries of the sphere of the competition so that competitive dynamics
can be studied meaningfully (Empson, 2007). The relatively homogeneous product mix and the welldefined geographic markets in which firms operate (Harper, 1997) provide further basis for meaningfully
identifying the competition.
We adopt a narrow definition of the industry and study only firms that provide legal services to
businesses, known in the industry jargon as ‘corporate law’. The industry is split between corporate and
private legal-services and firms seldom cross the line between them (Galanter & Palay, 1991). This
narrow definition is imperative in our study in order to study firms that compete with each other.
US MNEs were selected as the focal MNEs for the study. The US is home for the largest numbers
of legal-services MNEs, providing a large number of observations while enabling us to control for homecountry effects. We believe that we studied all US legal-services MNEs in existence during the studyperiod (2004-2008), reducing concerns regarding sample selection bias. US MNEs were drawn for the
study from the American Lawyer Magazine (ALM) database, the most comprehensive database of US
legal-services firms. The database provides detailed annual documentation of the activities of the largest
(by number of attorneys) US firms. We verified the ALM data based on a comprehensive survey of all the
major industry publications, including The American Lawyer, The National Law Journal, MartindaleHubbell Directories, Lawyer's Almanac, Insider's Guide to American Law Firms, Vault Guide to Leading
Law Firms, and Hudson Legal Survey. The study’s population includes 118 - 128 MNEs in different
years, resulting in a database of 614 firm-year observations. The database is an unbalanced panel as firms
enter and exit the market and change classifications as domestic and MNEs. MNEs are firms that have at
least one office outside the US.
The testing of the hypotheses is based on comparisons of US MNEs as the focal MNEs with the
various competitor-groups, as follows:
- Nationality (H1, H5a+b) – US MNEs in competition with non-US MNEs (MNEs whose HQs
resides outside the US). We focus on MNEs only in order to remove the effect of geographic
scope (that is, domestic or MNE), and observe them in competition worldwide. Non-US MNEs
were identified based on the ALM Global 100 annual ranking of the world’s largest (by number of
attorneys) legal-services firmsi. After excluding from this list US MNEs and domestic firms, we
were left with a sample of 28-32 MNEs in different years. The share of the market collectively
held by these MNEs is not known precisely. Industry analysts we consulted suggested that with
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US MNEs, these firms account for most of the market for cross-border legal services, enabling us
to consider this sample as a reasonable approximation of the population of non-US competitors.
- Geographic scope (H2, H6a+b) – US MNEs in competition with domestic US firms (firms that do
not have offices outside the US). We compare only US firms in competition in the US, holding
constant nationality and location so that the impact of geographic scope can be examined free
from these other influences. The domestic US sample comprises the 142 – 182 largest (by number
of attorneys) US domestic legal services firms in different years, drawn from the ALM database.
We exclude smaller domestic firms because they tend to serve different clients than those that the
focal MNEs studied serve, and are not in direct competition with them (Galanter & Palay, 1991).
- Location (H3, H4, H7) – US MNEs in competition with non-US MNEs in the US and abroad.
Statistical Analyses
We conduct two sets of statistical analyses to test the variations in the competitive value of MNE
assets (H1-H4) and in competitive intensity (H5-H7) across different competitor-groups.
Variations in the competitive value of MNE assets
This testing is based on a model that links competitive performance as the response variable with the
three types of MNE assets. The significance of these assets in explaining competitive performance is
taken as an indication of their competitive value:
n
Yijt [CPit   CPjt / n]   it ; 1FSASit ;  2MNEASit ;  3HAS it ;  4CVit ;  t
j
where Yijt is competitive performance (CP) of a focal US MNE i in relation to the average of competitorgroup j in time t; FSAS, MNEAS and HAS represent respectively the firm-specific, multinationality, and
home-based assets. CV is a vector of control variables that includes firm-specific characteristics that,
according to theory, affect competitive performance. εt accounts for specification errors that could result
from idiosyncratic firm-characteristics and sampling errors, such as inappropriate identification of
competitors.
We operationalize competitive performance by growth, an appropriate indicator in international
competition because it captures expansion, a prominent objective of international activity. We selected
growth rate of the number of attorneys, the major component of value creation and costs of legal-services
firms, and hence a concrete indicator of competitive performance. This measure is appropriate also
because it is available for the different geographic levels of analysis needed for the testing of the
hypotheses, and it is meaningfully comparable across themii.
MNE assets are operationalized as follows:
- Firm-specific assets: Qualifications of firms’ partners. Partners collectively embody the two most
important assets of legal-services firms. They represent the collective knowledge held by a firm in an
industry where human capital is the primary value-creating asset (Hitt, Bierman, Shimizu & Kochhar,
2001), and they hold the firms’ relationships with clients (Empson, 2007). Following Hitt et al. (2001)
and Hitt, Bierman, Uhlenbruck and Shimizu (2006), we measure partners’ educational background and
industry experience, two important indicators of their qualifications. Educational background is measured
by the quality-ranking of the law schools in which a firm’s senior partners earned their JD, based on the
US News & World Report Best Law Schools Rankings and experience by the number of years since
graduation. Both measures were constructed based on data reported in the Law Firm Yellow Book
Directory. We combine the averages of the two measures using factor analysis and employ the
standardized factor scores as the measure of firm-specific assets.
- Multinationality assets: Country characteristics in MNE portfolio. This measure captures the variety of
resources MNEs can access via their international activity. It is also informative of the similarity among
the countries in MNE portfolios and the transferability of their knowledge across them. The integration of
assets across countries, which underlain the multinationality assets, is somewhat constrained in the legal
services industry by country-specific legal requirements and regulations (Drolshammer & Pfeifer, 2001).
Notwithstanding these barriers, legal-services MNEs base their international activity to a large extent on
shared knowledge-base and expertise (Silver, De Bruin & Rabinowitz, 2009). Such sharing is possible
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due to their focus on cross-border issues that are handled in a similar manner around the world, based on
New-York law (Harper, 1997). The multinationality measure is calculated as the standard deviation of the
characteristics of the countries comprising the portfolio:
n
DIVit 
2
 ( Lict  Lit )
c
n
Where DIVit is the diversity of the portfolio of MNE i in time t; L stands for country characteristics, and c
represents countries (c=1…n). The country characteristics employed to calculate the measure are major
indicators of country resources, including number of attorneys, graduates of law schools, prevalence of
local and foreign MNEs, as the main clients of legal-services MNEs, the legal system, and the
institutional environmentiii. We assign equal weight to the various characteristics because there are no
theoretical reasons for weighing them differently.
- Home-based assets: The number of members of management committees by US states. This measure is
indicative of the distribution of MNEs’ economic activity and their utilization of home-based resources
(Hitt et al., 2001). Bases on data from the Yellow Book , we calculate the time-varying share of committee
members in each US state in an MNE’s total, weighted by the number of states in which a focal MNE has
offices.
The control variables include:
a) Size, measured by total revenues.
b) Age, the number of years since establishment.
c) Profits per partner.
d) International experience, years since the establishment of the first office abroad.
e) Product and geographic markets overlap, to control for differences that constrain or eliminate actual
competition among competitors. We follow a common approach in multi-market competition research
and aggregate the proportions of firm i's markets jointly occupied by other firms j in respective
competitor-groups. We conduct two analyses for product- and geographic-markets:
 ( Dimt xD jmt )
MOit   m
 Dimt
j i
m
where MO signifies Market Overlap, m denotes product- or geographic-markets, Dimt equals one if firm i
is active in market m in year t and zero otherwise, and Djmt equals one if firm j is active in market m in
year t and zero otherwise. MO can vary from zero, where there is no overlap between a focal MNE and
other competitors, to one, when a focal MNE competes with all other competitors in the same product- or
geographic-markets. These measures were constructed based on data from the Law Firms Yellow Book.
f) Year dummies to control for exogenous cyclical fluctuations in the external environment.
The independent variables are time-lagged one year from the dependent variables, reflecting the
assumption that a period of time is required for them to affect the outcome. The lag structure partially
addresses reversed causality concerns. We add to the model a GLS firm-level random effect to control for
unobserved heterogeneity across firms. A random effect specification is appropriate for our study because
the average number of time observations per firm in our sample is smaller than the number of panels
(118-128 firms in different years and 614 firm/year observations). In such cases fixed-effect estimate
tends to be inconsistent and increases the measurement error bias, a shortcoming that does not
characterize the random effect. In addition, a random-effect specification is more appropriate for slowly
changing explanatory variables, typical of some of the variables in the model that display little withinpanel variation compared with cross-panel variation. A random effect is also more in agreement with our
interest in the differences among competitor-groups rather than within them.
A major concern in the model is the possibility of reversed causality between firms’ assets and
performance. The model is based on the assumption that causality goes from asset-possession to
11
performance, but the opposite could also be the case. For instance, poor performance may drive firms to
upgrade their assets and enhance their efforts to differentiate themselves from the competition, which in
turn affects performance. If this is the case, performance and asset-possession are jointly determined in a
circular causation with feedback loops between them, rather than in a sequential order as we assume. This
implies that reversed causality is driving the results, and the explanatory variables and the error term are
correlated and the regression estimates are biased.
To address this concern we employ the two-stage least squares estimation (2SLS), using resourceslack as an instrument. The possession of slack resources enables firms to invest in the development of
new skills and capabilities, which provide the basis for their assets, but at least in the short-run, it does not
have direct consequences for performance. We measure resource-slack as the ratio of associates to equity
partners, known in the industry jargon as ‘leverage’, a common indicator of the stock of human assets and
organizational capabilities in the industry (Hitt et al., 2001, 2006).
In Table 2, we present summary statistics and correlation coefficients of the variables included in
the model. Most coefficients are low, removing concerns regarding correlations among the explanatory
variables.
Table 2 about here
Variation in competitive intensity
For this testing we employ the Euclidean distance, a common measure of competitive intensity in research
in this area (e.g., Baum & Mezias, 1992). This measure is based on the assumption that distance
represents similarity among firms, which is a major determinant of competitive dynamics (Chen & Miller,
2012):
k
Di  (

t 1
n
 ( Ci  C j ) 2 ) / N
j i
where Di is the distance between MNE i and competitors in group j on the competitive dimension C,
j=1…n. n represents the number of competitors in group j, and k is the number of years observed (k=5,
2004 – 2008). Since competitor-groups vary by size, we take the averageiv. When j=US MNEs, j=j-i. To
control for dependency among repeated observations of the same MNE over time we calculate the
measure separately for each year and sum across the years. Larger values of D imply greater distance
between a focal MNE and respective competitor-groups, that is, less similarity, and hence less intense
competition.
We selected size as the competitive dimension for the measurement of competitive intensity. Size
is an appropriate indicator of competitive intensity because firms of similar size tend to draw on the same
resources and often exhibit similar strategic and competitive behavior (Mas-Ruiz & Ruiz-Moreno, 2011).
It is the only competitive indicator that legal-services firms break down by geographic areas, enabling
comparisons across different geographic levels. We operationalize size by number of attorneys, a
common measure of size in the legal-services industry. As the major component of value creation and
costs, the number of attorneys is an appropriate indicator of the magnitude of a firm’s activities (Hitt et
al., 2001).
STATISTICAL ANALYSES AND DISCUSSION
The testing of the competitive value of MNE assets in competition with different competitorgroups (H1 – H4) is based on estimates of the model constructed above by means of cross-sectional timeseries analysis (Table 3). The results differ substantially across competitor-groups, in support of the
impact that competitors’ heterogeneity exercises on the competitive value of MNE assets.
Table 3 about here
H1, which outlines a rationale for the significance of MNE assets in relation to MNEs of different
nationalities, is supported. As predicted, the firm-specific and the home-based assets are significant and
positive in agreement with our suggestion that national variations in the possession of these assets turn
them to valuable advantages in competition with MNEs of different nationalities. The results are
indicative of the advantages that US legal-services MNEs have in relation to MNEs of other nationalities.
12
US MNEs benefit from the dominance of the US (New-York) legal system in international legal disputes
and international commerce (Drolshammer & Pfeifer, 2001), which give them an advantage over non-US
MNEs in handling cross-border legal issues. In addition, variations of laws across US states afford US
firms experience in dealing with different legal systems at home on which they build in international
competition. The large size of the US market enables them to develop organizational capabilities needed
to manage activities spread geographically, which provides basis for international expansion (Hitt et al.,
2001).
None of the three MNE assets is significant in competition with domestic competitors, providing
no support for H2. The analyses show that the differences between US MNEs and domestic firms rest
mostly on profits-per-partner and the explanatory power of the model is weak. This finding could be
attributed to the tendency of some of the most prestigious US legal-services firms to remain domestic,
with some of them providing international coverage via alliances and networks (Sherer, 2007). These
practices diminish major differences between MNEs and domestic firms anticipated based on MNE
theory. The multi-domestic nature of competition in the industry could also explain this finding. Value
lies primarily in local knowledge and embeddedness (Empson, 2007), undermining the importance of
geographic coverage that underpins the differences between domestic firms and MNEs.
The competitive value of US MNE assets varies significantly across locations. Different assets
are significant in the US and abroad and the differences between the two analyses are highly significant.
In agreement with H3, the home-based assets are significant in the US. This finding probably reflects the
favorable access of US firms to their home-country assets, which puts non-US MNEs in the US at a
disadvantage in accessing these resources. US clients exhibit preference for US legal-service providers,
and local employees prefer employment opportunities with US firms (Taylor, 2002), curtailing the ability
of non-US MNEs to engage with them. Such liabilities are not confined to the US. Morgan and Quack
(2005) describe difficulties experienced by US and UK MNEs in Germany, where knowledge of the local
jurisdiction could only be obtained through recruitment of German attorneys, who were not keen on
working for foreign firms. The home-based assets lose their value outside the US, supporting the
argument regarding the immobility of these assets, which are often developed in response to the specific
nature of home-demand and are less valued elsewhere. For instance, UK legal-services firms have
developed skills in finance-related issues, associated with the role of London as a financial center,
whereas German firms have specialized in areas related to large industrial corporations, and following the
opening up of Eastern Germany, in privatization (Morgan & Quack, 2005).
Inconsistent with H4, the firm-specific assets are not significant abroad. The nature of the firmspecific assets of legal-services MNEs probably explains these findings. Technological innovations and
price competition are not major differentiating factors (Empson, 2007). All the US MNEs we study are
organized as partnerships, which during the study-period is the only governance form legally permitted in
US states, undermining potential advantage on that ground. Organizational structure and product line are
also similar (Sherer, 2007). The major firm-specific assets of these firms are the ability to attract and
retain high-quality human capital and relationships with clients which are often associated with social
relationships (Hitt et al., 2001, 2006). Uzzi and Lancaster (2004) show that social relationships determine
the prices legal-services firms charge their clients. Such assets are tied to particular locations and have to
be established in each country (Liu, 2008), typically over long time-periods. The high human component
of the service delivery further constrains the transferability of the firm-specific assets.
Inconsistent with our predictions, the multinationality assets are significant in competition
abroad, and appear to provide the major basis for US MNEs in competition outside the US. This finding
probably reflects the dominant position of US legal-services MNEs in global competition accrue to them
due to the dominance of US (New-York) law in handling cross-border legal issues. As noted above, they
have also benefited from the size of their home-market that enables them to develop organizational
capabilities needed for international expansion. Indeed, in London, US MNEs charge higher fees than
those charged by their UK competitors and those they themselves charge in the US (IFSL, 2009).
13
The results of the control variables vary across different models, providing additional
confirmation for the varying determinants of competitive performance in relation to different competitors
and in different locations.
As robustness tests, we repeated the analyses with alternative measures of the multinationality
assets, using counts of countries and offices overseas. We also employed different measures of the homecountry assets, based on the number of US states and US cities with offices. There are small changes in
the results but the general conclusions hold in these modified tests.
In Table 4 we present the results of the testing of H5 through H7. These analyses show substantial
variations in competitive intensity across competitor-groups, in support of the argument underlying our
study, but the differences are not always in agreement with our predictions.
Table 4 about here
US MNEs compete more intensely with other US MNEs than with non-US MNEs, consistent
with H5a, but the small and insignificant differences provide no support for the impact of nationality on
the intensity of the competition. These results are in agreement with the diminishing preferences of clients
for their home-country legal-service providers observed recently, which lessens differences associated
with nationality. Baker and Parkin (2006) found a growing tendency for clients to select their legalservices providers based on professional and business considerations rather than on personal relationships
that tends to flourish among people of the same nationality. The findings might also be the result of the
similarity of the home countries of the MNEs we studied, the majority of whom originate in Englishspeaking countries that are similar in terms of their institutions, culture, and level of economic
development, and are guided by the common-law legal system (La-Porta, Lopez-de-Silanes & Schleifer,
2008). UK, Australian, and Canadian MNEs account respectively for 60%, 18% and 12% of the sample of
non-US MNEs and the remaining 10% are taken by MNEs from Spain, the Netherlands, and France. This
similarity may undermine the anticipated differences across firms of different nationalities.
As expected, the MNEs we study compete more intensely with other MNEs than with domestic
firms, in support of H6a, but the low level of significance provides weak support for our hypothesis. As
noted above, some of the largest and most profitable legal-services firms have remained domestic (Sherer,
2007), eliminating some of the differences between MNEs and domestic firms anticipated by theory.
Furthermore, the theoretical arguments for variation in competitive intensity between MNEs and domestic
firms rest in part on the varying impact of multi-market competition on these firms. This impact,
however, is more pronounced in competitive settings dominated by a few large firms (Haveman &
Nonnemaker, 2000), and may not materialize due to the low level of concentration in the industry.
Further, the impact of multimarket competition requires centralized decision making and coordinated
responses that spur mutual forbearance among firms that confront each other in multiple markets (Korn &
Rock, 2001). The decentralized structure typical of legal-services MNEs (Silver, De Bruin & Rabinowitz,
2009) is likely to weaken this effect. Low levels of ownership also tend to reduce the likelihood of
affiliates following strategies formulated at the HQs that is imperative for this impact to materialize (Yu,
Subramaniam & Cannella, 2009). The MNEs we study are organized as partnerships with no ownership
ties among them.
In support of H7, the findings show that the competition (with the same competitors) is more
intense in the US than abroad. These findings are in agreement with the predominance of the home
market in firms’ identity that drive them to protect their competitive position in this market more
aggressively than abroad, and also support the superior value of MNE assets in their home countries.
We tested the robustness of the findings to narrower definitions of competitor-groups, to reduce
the likelihood of the inclusion of firms that are not in direct competition with each other. Following Baum
and Mezias (1992) we narrowed down the range of competitors based on size, experimenting with size
ranging between 0.5 through 0.25 the figure of a focal MNE. The results of the testing of the value of
MNE assets (H1-H4) based on these narrower definitions of the competition are similar to those reported
earlier. Competitive intensity (H5-H7) is stronger in these analyses but the differences between
competitor-groups follow similar patterns.
14
Future Research
The study opens up a large area for future research. We believe that we have made substantial
progress in advancing a nuanced view of the competition that MNEs confront, but finer distinctions are
warranted. Future research may examine variations within the competitor-groups we studied, for instance
among competitors of different nationalities, and across different locations, and may also study those
variations in interaction with attributes of individual firms.
Further, our study is based on the simplifying assumption that competitive engagements with
different competitor-groups are independent of each other. In reality, however, these competitions often
evolve in tandem with interactions and cross-influences that are likely to affect the relationships we
studied, and should be accounted for by future research. The employment of alternative measures of
competitive performance is another task for future research. Growth rates provide a limited indication of
competitive performance because they are informative only on the demand side but silent on costs and the
resulting performance. They might also be biased because smaller firms grow faster than larger ones.
The validity of our findings beyond the legal-services industry also warrants additional research
attention. The multi-domestic nature of the competition, with its distinctive nature of interactions among
sub-units, may restrict the validity of the findings to settings in which the competition takes place on a
global level. National differences in attorneys’ qualifications and legal systems restrict the ability to
employ foreign resources, and increases firms’ dependent on their home-country talent pool to an extent
that may not hold in other industries. The prevalence of partnership as the dominant governance form in
the industry is another characteristic that would justify more research attention. Partnerships are
associated with high level of autonomy for local offices, which weakens the interaction among sub-units
and affects the competitive dynamics.
CONCLUSION
In this paper we examined how the heterogeneity across MNE competitor-groups affects
competitive dynamics. We classified MNE competitors based on nationality, geographic scope, and
location, and suggested that these are critical distinguishing factors of the competition in the context of
the MNE. The location of the competitive engagement introduces the strongest impact on competitive
dynamics, indicating that the competitive value of MNE assets varies across locations. These findings
provide explanation for the puzzling differences in a focal MNE’s competitive positions across countries
that triggered this research. They also call for more attention to location as an important determinant of
competitive dynamics. The distinction we introduce among the three types of MNE assets, and the
differences we find in their competitive value in relation to different competitor-groups speak for the
importance of distinguishing among them, as they appear to signify varying theoretical constructs and to
require different strategic responses.
Taken together, the findings confirm the underlying premise of the study, namely that different
competitor-groups matter in different ways and pose different competitive challenges to MNEs. That in
turns suggests that MNE assets are inherently relative and their value varies across competitive settings,
introducing variations of competitive dynamics across them. This represents an important shift to the
implicit notion of these assets as absolute whose value does not change across competitive settings that
underlain MNE theory. This modified notion of MNE assets needs to be explicitly incorporated in theory
and practice. Global competition should be viewed as a portfolio of competitive settings that differ in
terms their competitive dynamics, with different assets, or the same one to varying degrees, being of
competitive value in different countries.
Some of our findings deviate from the predictions of MNE theory and point to a need for
theoretical extensions. Notable are the eroding value of nationality, and the partial immobility of homecountry and firm-specific assets. It appears that under certain circumstances, these assets do not convey
benefits outside MNEs’ home country, questioning a fundamental assumption that underlain MNE theory
regarding the nature of these assets.
15
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18
Table 1. Summary of the Theoretical Framework and the Hypotheses
Competitor Groups
Nationality
(Own-nationality vs. others)
Geographic scope
(Domestic vs. MNEs)
Location
(At home vs. abroad)
Assets Value
Hypotheses
Home-based assets
Firm-specific assets
(H1)
Multinationality assets
Firm-specific assets
(H2)
At home (H3):
Firm-specific assets
Home-based assets
Abroad (H4):
Firm-specific assets
Competitive Intensity
Hypotheses
Own-nationality >,< Others
(H5a+b)
MNEs >,< Domestic
(H6a+b)
At home > Abroad
(H7)
19
Table 2. Descriptive Statistics and Pearson Correlation Coefficients
Mean s.d.
1
2
3
4
5
6
7
8
9
10
1. Growth US MNEs/non-US MNEs
(Nationality)
1.23
.17
2. Growth US MNEs/domestic
(Geographic scope)
-.01
.12
.56**
3. Growth US MNEs in the US
(Location)
1.03
.12
.62** .35**
4. Growth US MNEs outside the US
(Location)
1.04
.14
.10*
.54** .49**
5. Firm-specific assets:
Partners’ educational background
15.16 7.59
.25
.32
.39
.35
6. Multinationality assets:
Diversity of countries in portfolio
2.69
4.92
.09
.63
-.54
.42
.57
7. Home-based assets:
Employment distribution by US state
3.82
2.30
-.26
-.21
-.31
-.09
-.77
8. Size (Revenues, mil.)
434.00 317.50 .23
.11
.01
.03
-.09* -.23
9. Age (Years since establishment)
103.80 41.08 .29*
.22*
.18*
.32*
-.02
-.17
.01
.33*
10. Profits-per-partner (‘000)
996.36 546.06 .14
.22
.25
.14
.38*
.34
.20
.51** -.11**
.01
.08
.17
-.06
.13
.06
-.41** .17** -.31**
*
11
12
13
14
15
.27**
.18**
11. Experience (Years investment abroad)
20.51 17.13 .11
12. Geographic overlap - US MNEs
17.08 106.57 -.09
-.03
-.11
-.16
.13** -.40
.10
-.09* .06
-.08* .04
13. Geographic overlap – non-US MNEs
.14
.21
.27
.19
.32** .07
.05
-.14** -.01
-.16** -.01
.23**
14. Product overlap – US MNEs
47.88 26.10 -.06
.01
.00
-.16
-.13** -.19
.06
-.10* -.05
.00
.02
-.06
.10**
15. Product overlap – non-US MNEs
.27
-.00
.10
.05
-.09
-.11** -.11
.09
.01
.15** .00
-.04
.11** .59**
16. Product overlap – US domestic
51.49 29.86 -.06
.01
.00
-.16
-.10** .34
.07
-.12** -.09* -.03
-.05
.13** .53** .44**
17. Slack resources (partners/associates)
2-tailed significance test:
*
p<.05
**
p<.01
.87
-.02
-.11
-.15
.04
.17
.15
-.41** .07*
.34
.20
.47
.13
-.05
16
-.06
.01
-.64** .31** -.03
-.07
-.05
-.13** -.05
20
Table 3. The Competitive Value of MNE Assets (H1-H4)
DV: Competitive performance - Annual growth rates (relative to respective competitor groups)
Nationality (H1)
Firm-specific assets
Multinationality assets
Home-based assets
Size
Profits-per-partner
Age
Experience
Geographic overlap US MNEs
Geographic overlap non-US MNEs
Product overlap US MNEs
Product overlap non-US MNEs
Product overlap domestic
1.57
(2.59)**
1.59
(.28)
-.31
(-2.48)**
-.21
(-.39)
-.66
(-.78)
.41
(2.69)**
-.33
(-.50)
-.69
(-.01)
.43
(2.44)**
1.34
(1.29)
1.19
(2.84)**
1.67
(2.54)**
1.21
(0.95)
-.32
(-1.99)*
-.45
(-.71)
-.66
(-.82)
.59
(2.82)**
-.39
(-.43)
-.35
(-.32)
Geographic Scope (H2)
-1.87
(-1.73) †
2.57
(2.89)**
-.29
(-1.69)
-.39
(-.10)
-.59
(-.60)
-.73
(-1.19)
.41
(.88)
None sig.
(1.13)
.33
17.29*
.21
(1.47)
.49
(.1.41)
1.19
(1.16)
-2.42
(-2.89)**
2.14
(2.22)*
-.32
(-1.69) †
-.63
(-1.14)
-.74
(-.82)
Location (H3-H4)
In the US
Outside the US
.26
.07
(2.15)**
(.84)
.52
1.68
(1.16)
(2.82)**
1.89
1.22
(1.97)*
(1.37)
2.73
1.78
1.82
1.33
(2.99)*** (2.58)**
(2.52)**
(2.11)*
2.46
2.21
1.51
1.15
(1.95)*
(1.76) †
(0.87)
(0.69)
-.42
-.31
-.40
-.40
(-2.53)**
(-1.77) †
(-.67)
(-.61)
.53
-.60
-.16
-.32
(0.16)
(-1.05)
(-.64)
(-.17)
.37
(2.84)**
.31
(2.43)**
-.18
(-1.39)
-.28
(-1.97)*
-.69
(-1.79) †
-.16
(-2.64)**
-.23
(-2.34)**
-.31
(-2.51)**
Some sig.
(2.66)**
.59
27.13***
None sig.
(2.39)**
.29
8.14*
None sig.
(2.47)**
.35
13.34*
-.69
(-1.38)
.27
(.60)
None sig.
(1.29)
.37
19.44**
Year dummies (4)
None sig.
Some sig.
None sig.
Constant
(2.47)**
(2.15)**
(2.17)*
R2 (overall)
.43
.49
.39
Wald χ2 (Prob > χ2)
20.99***
22.95**
20.80***
N(years/firms) = 614
†
p<.10; * p<.05; ** p<.01; *** p<.00
a
Test of difference between the coefficients of the two location regressions – in the US and abroad.
Chow testa
1.93*
-2.57**
3.09***
21
Table 4. Competitive Intensity (H5-H7)
Euclidean Distancea
Nationality (H5)
Geographic
Scope (H6)
Location (H7)
A Focal US MNE in Competition with: [N]
US MNEs worldwide 1.41 Non-US MNEs
[614]
worldwide [149]
US MNEs in the US
1.15 US Domestic firms
[614]
[823]
Non-US MNEs in the 1.22 Non-US MNEs outside
US [149]
the US [149]
Friedman test of
difference
(Q statistics)b
1.54 23.17
1.31 16.91†
1.61 12.15**
†
p<.10
p<.05
**
p<.01
*
a
Larger values = less similarity and less intense competition.
Friedman Two-Way Analysis of Variance test compares dependent samples that are repeated on the
same subjects. The samples we compare are both measured in relation to a focal US MNE. The Q
statistics approximate Chi-sq. distribution.
b
Several sources offer rankings of the industry’s largest firms, but the ALM is the only source that ranks firms
globally (rather than on a regional or national level), and across different specializations, as needed for our study.
ii
Alternative measures of competitive performance, such as profits-per-partner, a common indicator of performance
in the industry, are only available in total. Billing rates, another indicator of a firm’s position relative to its
competitors, are only available at a national level and, due to national variations, may not be comparable across
them.
iii
A detailed list of the measures, the rationale for their inclusion, and their sources is available from the authors
upon request.
iv
As a robustness test we conducted the analyses without normalizing for groups’ size, because the number of
competitors by itself affects competitive dynamics. There are small changes in the results but no qualitative changes
of the conclusions.
i