Journal of World Business xxx (xxxx) xxx–xxx
Contents lists available at ScienceDirect
Journal of World Business
journal homepage: www.elsevier.com/locate/jwb
National institutional systems, foreign ownership and firm performance: The
case of understudied countries☆
⁎
Michael Carneya, , Saul Estrinb, Zhixiang Lianga, Daniel Shapiroc
a
John Molson School of Business, Concordia University, Montréal, Québec, Canada
London School of Economics, London, United Kingdom
c
Beedie School of Business, Simon Fraser University, Vancouver, British Columbia, Canada
b
A R T I C LE I N FO
A B S T R A C T
Keywords:
Varieties of institutional systems
Comparative corporate governance
Firm performance
World Bank Enterprise Survey
Theory of the MNE
Eclectic paradigm
We analyse the relationship between institutional systems (configurations of countries with similar institutional
characteristics) and firm performance. We use a large sample of firms from understudied countries to explore
whether the performance impact of these configurations is the same (“equifinality”), whether this holds across
different measures of firm performance (“Tversky effect”), and whether some institutional configurations better
support foreign-owned firms. We find that it is possible to rank institutional systems according to their impact on
firm performance, but the ranking differs according to the performance measure. Although foreign ownership on
average confers performance advantages, the magnitude of the impact depends on the configuration. Our
findings contribute to the understanding of the importance of institutional similarities across countries, and to
the implications of these similarities for the theory of the MNE.
1. Introduction
A central tenet of the international business (IB) literature is that
institutions matter (Dunning & Lundan, 2008b; Peng, Wang, & Jiang,
2008; Peng, Sun, Pinkham, & Chen, 2009). In particular, institutional
differences across countries can help explain the existence of “country
effects” as determinants of differential firm performance (Bamiatzi,
Bozos, Cavusgil, & Hult, 2016; Gao, Murray, Kotabe, & Lu, 2010;
Makino, Isobe, & Chan, 2004) as well as location (Bevan, Estrin, &
Meyer, 2004; Bénassy-Quéré, Coupet, & Mayer, 2007; Globerman &
Shapiro, 2002) and entry mode choices by multinational firms
(Brouthers, 2002; Meyer, Estrin, Bhaumik & Peng, 2009). These institutional differences have arguably become more important as emerging markets add heterogeneity to the institutional spectrum
(Hoskisson, Wright, Filatotchev, & Peng, 2013; Peng et al., 2008).
At the same time, there is a long intellectual history built around the
analysis of the performance effects of economic systems: groupings of
countries that share similar institutional characteristics (Koopmans &
Montias 1971; Ostrom, 2009). One prominent example is the Varieties
of Capitalism (VOC) perspective (Hall & Soskice, 2001) where it is argued that even within a single economic system, capitalism, countries
could usefully be grouped in typologies based on institutional similarities, resulting in a “remarkable convergence on just a few configurations (Boyer, 2005, p. 13). Hall and Soskice looked at a relatively small
group of developed economies in North America and Europe and
identified two main variants of capitalism, Liberal Market (LME) and
Coordinated Market (CME) economies. Importantly, in their approach,
the two systems can generate the same levels of national and company
performance, resulting in an outcome termed equifinality.
Subsequent scholarship on capitalist variety relies less on establishing typologies such as the VOC, and more on the development of
empirically derived taxonomies of institutional systems (Hall &
Gingerich, 2009; Schneider & Paunescu, 2012; Witt & Redding, 2013).
To date, most scholars have restricted their analysis to developed
countries, where institutions are stronger and arguably have a different
impact from those in emerging markets (Peng et al., 2008). The major
exception is Fainshmidt, Judge, Aguilera, and Smith (henceforth FJAS,
2016) who exploit known features of institutional structures in understudied emerging and developing countries to create a novel framework, which they refer to as Varieties of Institutional Systems (VIS).
FJAS's focus on understudied countries is a welcome addition to the
literature on capitalist variety, as scholars have criticized the VOC for
☆
The authors acknowledge conversations with Klaus Meyer and Rajneesh Narula and guidance from the editor and anonymous referees. Rebeca Granda Marcos and Dustin Voss
provided excellent research assistance. Any errors are the responsibility of the authors. An earlier version of the paper was presented at the 2017 Global Strategy and Emerging Markets
Conference, at Northeastern University, Boston, June, 2017 and at the International Corporate Governance Society annual conference at the LUISS business school, Rome, September
2017. The first author acknowledges the financial support of the Canadian Social Science and Humanities Research Council.
⁎
Corresponding author.
E-mail address: michael.carney@concordia.ca (M. Carney).
https://doi.org/10.1016/j.jwb.2018.03.003
Received 25 April 2017; Received in revised form 5 March 2018; Accepted 6 March 2018
1090-9516/ © 2018 Elsevier Inc. All rights reserved.
Please cite this article as: Carney, M., Journal of World Business (2018), https://doi.org/10.1016/j.jwb.2018.03.003
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
the suggestion of FJAS that they provide an ‘improved platform for
scholars examining the implications of cross-national institutional differences for organizations embedded in different types of institutional
systems’ (FJAS, p. 2). In bringing together the FJAS taxonomy and the
World Bank microdata, we not only extend the theoretical and empirical understanding of institutional systems, but we also link that
understanding to the theory of the MNE.
We conclude that the study of national institutional systems, when
extended to understudied economies, reveals a considerable variation
in institutional architectures, which differentially affect the performance of firms, both foreign and domestic, embedded in them. While
we find that some systems better support firm performance than others,
we also find heterogeneity among the better-performing systems. Our
findings caution against the use of oversimplified categories to describe
these countries, but also suggest the theoretical and empirical relevance
of national institutional systems in analysing the country-specific (location) advantages of emerging markets.
its almost exclusive focus on mature OECD member economies (Allen,
2004). The VIS taxonomy consists of seven distinct, empirically derived
national institutional systems, henceforth termed configurations, and
incorporates factors considered to be relevant to the emerging market
context such as the role of the state and diversified family business
groups (Estrin, Meyer, Nielsen, & Nielsen, 2016; Carney, Van Essen,
Estrin, & Shapiro, 2017). However, to date, the performance implications of these systems have not been addressed.
In this paper, we pursue two related broad research questions that
both extend and link the literature on institutional systems and international business. Our first research question asks whether the institutional systems defined by FJAS exhibit equifinality, and if so whether that outcome holds for all performance measures (which we refer
to as the Tversky effect). We argue that, in contrast to VOC, when we
extend the scope of the analysis to emerging markets, equifinality as
measured by firm performance across national systems, will not hold.
We hypothesize that in the context of these understudied countries,
some configurations are better at supporting firm performance than
others – (H1) – and we test this hypothesis using firm-level data. Our
results establish that performance does vary across configurations and
equifinality is therefore rejected.
We extend the analysis in our first research question by building on
an insight of Tversky (1977) that the ranking of alternatives is context
dependent. We apply this argument to the relationship between firm
performance and institutional configurations. This extension leads us to
offer a novel theory-based hypothesis suggesting that the relative impact
(ranking) of the configurations on firm performance will differ according to the performance measure chosen. Specifically, we propose
that there will be variation in the extent to which different configurations support alternative dimensions of firm performance (H2). We also
find evidence confirming this hypothesis from our sample of understudied countries.
Our second research question asks whether national institutional
systems affect the performance of foreign-owned firms in these understudied countries. Here, we both extend the IB literature and link it to
the literature on institutions. Specifically, we first draw on the familiar
OLI (eclectic) paradigm, and its variations (Dunning, 1988; Hennart,
2009; Rugman & Verbeke, 1990) to explore whether the firm-specific
advantages associated with foreign-owned firms (FOEs) and internally
transfered through majority ownership provide these firms with performance advantages in understudied countries (H3). This proposition
has been widely supported for developed economies (Caves, 1996;
Estrin, Hanousek, Kočenda, & Svejnar, 2009) but has not been tested in
a cross-national sample of emerging market countries, where institutional heterogeneity is greater, instutional voids and regulatory barriers
are higher and therefore the liability of foreigness is higher (Khanna &
Palepu, 2010; Wright, Filtatotchev, Hoskisson, & Peng, 2005; Zaheer,
1995). Our results suggest that FOEs do display performance advantages over domestic firms, even in these understudied economies.
On this basis, we then extend the framework to account for the effects
of national institutional systems, by proposing that magnitude of the
positive foreign ownership performance effects are contingent on the
configuration to which the host economy belongs (H4). Thus we suggest
and find empirical support for the argument that, that some configurations provide better institutional support for the ownership advantages of FOEs than others. Our findings indicate that institutional
similarities among countries as captured in our configurations, are
important determinants of both domestic and foreign-owned firm performance, and should therefore be considered in addition to measures
of institutional distance as a component of host country location (L)
advantage.
From an empirical perspective, we develop a unique dataset that
combines the seven FJAS configurations (see Table 1) with firm-level
data from the World Bank Enterprise Survey (WBES), resulting in a
sample of over 50,000 firms from 57 understudied countries, including
emerging capitalist, former socialist and socialist ones. Thus, we pursue
2. Theory and hypotheses
National institutional systems provide the formal and informal rules
of the game to which domestic and foreign firms must adapt their
governance and ownership structures (North, 1990). One strand of the
corporate governance literature suggests that national and firm-level
systems of corporate governance were converging on a single ‘best’
form of economic governance, as manifested in an Anglo-Saxon, capital
market-driven investment regime characterized by a sharp separation
between ownership and control and secure legal protection for minority
investors (Hansmann & Kraakman, 2004). Related to this, a shareholder
value model emerged prescribing codes of best corporate governance
practice: a vigilant board of independent directors; the separation of
key leadership roles; and compensation systems aligning shareholder
and top management interests (Lazonick & O'Sullivan, 2000). This
liberal market economy (LME) view of national and firm-level corporate governance configuration encapsulates the notion of unifinality, in
which across the variety of possible institutional arrangements there
exists an optimal configuration of institutions for economic performance (Fiss, 2007). In contrast, Hall and Soskice (2001) argue that
within the developed capitalist world, other institutional systems, notably what they refer to as coordinated market economies (CME), can
be as high performing as LMEs, consistent with equifinality, whereby
different systems produce similar economic outcomes (see also Judge,
Fainshmidt, & Brown, 2014).
An earlier example of this type of debate arose in the 1920s over
whether socialist states could design an economic system that would
match the capitalist system (see Levy & Pert, 2008, for a summary). At
its heart was the question of whether two fundamentally different
economic systems could perform equally well; that is, whether there
could be equifinality of economic outcomes. The tenor of the argument
did not support the idea of equifinality, and neither did the actual
comparative performance of the systems, which suggested unifinality
(Kornai, 1992).
2.1. Institutional configurations and firm performance
We first consider why differences in institutional and governance
systems might explain cross-national differences in firm performance
(Aguilera & Crespi-Cladera, 2016). The VOC literature (Hall & Soskice,
2001; Amable, 2003; Hancké, Rhodes, & Thatcher, 2007) identifies a
social democratic economic model of capitalism in north European
countries as a viable alternative architecture of national competitiveness to liberal market economies. There are two ideas at the heart of the
VOC model: complementarity and isomorphism. First, a nation-state can
provide a performance advantage to its firms if it achieves complementarity between institutional spheres, including the financial
sector, the labor, and industrial relations regime, and the educational
2
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
Table 1
Fainshmidt et al. (2016) VIS Configurations in 68 Understudied Countries.
Summey of classification scheme
Market-based
(LME)a
Collaborative
(CME)a
State-Led
Fragmented with
Fragile State
FamilyLed
Centralized
Tribe
Emergent
LME
Collaborative
Agglomerations
Hierarchically
Coordinated
Australia
Canada
Ireland
New Zealand
Switzerland
UK
USA
Austria
Belgium
Denmark
Finland
Franceb
Germany
Italyb
Japan
Netherlands
Norway
Portugalb
Spainb
Sweden
Argentina
Bangladesh
Belarus
China
India
Indonesia
Malaysia
Mongolia
Pakistan
Philippines
Russia
Sri Lanka
Thailand
Venezuela
Vietnam
Angola
Cameroon
D.R. Congo
Egypt
Ethiopia
Ghana
Kenya
Rwanda
Senegal
Sudan
Tanzania
Uganda
Algeria
Azerbaijan
Brazil
Colombia
Mexico
Morocco
Nigeria
Peru
Tunisia
Yemen
Bahrain
Iran
Kuwait
Qatar
Saudi Arabia
UAE
Botswana
Chile
Hong Kong
Israel
Namibia
Singapore
South Africa
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak Republic
Slovenia
Bulgaria
Georgia
Jordan
Kazakhstan
Korea (South)
Lebanon
Romania
Taiwan
Turkey
Ukraine
a
These economies have been classified by Hall and Soskice (2001) and subsequent literature. The LME group corresponds to the compartmentalized system in Whitley’s NBS, and the
CME encompasses various subtypes of collaborative systems included in NBS such as collaborative, highly coordinated, and coordinated industrial district.
b
These economies are often classified as unique subtypes of collaborative systems where there is more state dominance and, in some cases, relatively liberal labor relations (Hall &
Thelen, 2009; Grosvold & Brammer, 2011).
access resources in their local environment, they are likely to develop
similar practices adapted to their particular institutional configuration
(Hall & Soskice, 2001).
The original VOC arguments derived from studies of a limited group
of developed economies. Indeed, critics of the VOC seized on its Eurocentricity, noting that VOC did not adequately capture the variety of
institutional configurations found around the world (Allen, 2004).
Boyer suggested that there would be ‘an even larger diversity for
emerging economies’ (Boyer, 2005, p.15) and other theoretical approaches identified new typologies (Whitley, 1999; Amable, 2003). An
important methodological innovation was the application of clustering
and fuzzy set theory to derive taxonomies based upon multiple measurements of national institutional characteristics (Hotho, 2014). Applying fuzzy set analysis, FJAS identify seven distinct configurations
among emerging, developing and transition countries. Nevertheless,
with the growing interest in taxonomical elaboration, the question of
impact on firm performance at the heart of the earlier literature has
faded, and to our knowledge, very few have considered the firm-level
performance implications of different configurations.
The link between the capitalist taxonomy literature and their performance consequences remains central, however, because the VIS and
VOC literature both claim to explain the country-specific institutional
basis of firm-level competitive advantage. Hence it is a significant research question to explore the firm-level performance effects of these
new institutional configurations identified outside developed OECD
countries. VOC scholars have already raised questions about the relevance of complementarity amongst the institutional contradictions
and frictions of less developed economies and obvious cases of dysfunctional varieties of capitalism also challenge the idea of equifinality
(Howell, 2003; Hancké et al., 2007; Peck & Zhang, 2013).2 Widening
the geographic lens to emerging markets in Asia, Latin America and
Africa, a more variegated range of capitalisms come into view comprising dynamic ‘rising powers’ (Sinkovics, Yamin, Nadvi, & Zhang,
2014). Other scholars describe static capitalist economies mired in a
middle-income trap and low skill equilibria (Schneider, 2009); and
even outright failures (Wood & Frynas, 2005).
and skills training systems. Actors in each institutional sphere are
perceived as politically rational, having an acute sense of their interests
but recognizing the power of cooperation and negotiation to achieve
collective ends (Hall & Thelen, 2009). Thus, institutional variation
arises from the way different national institutional systems achieve
cohesion and ways of ‘hanging together’ (FJAS) to support high-performing firms and achieve high economic growth (Peck & Zhang,
2013).
The focus of this approach is therefore on the institutional complementarities within countries that co-evolve with those of other
countries to produce distinct governance configurations. Thus, no
single institutional characteristic is sufficient to explain outcomes; instead, the outcome is related to combinations of conditions (Fiss, 2007)
often identified via fuzzy set and clustering analysis (Hotho, 2014). This
strand of research has been able both to identify fine-grained configurations and to evaluate their impact on a number of different national
economic outcomes including foreign direct investment (FDI) inflows
(Pajunen, 2008), exports (Schneider, Schulze-Bentrop, & Paunescu,
2010), national growth rates (Hall & Gingerich, 2009), and economic
equality (Judge et al., 2014) as well as different national corporate
governance systems (Haxhi & Aguilera, 2017; Iannotta, Gatti, & Huse,
2016).
The second key concept is isomorphism. Each variety of capitalism
is said to produce an ‘emblematic firm’ (Boyer, 2005), an organisational
form particularly well adapted to its national institutional system. In
the LME, the emblematic firm is a capital market-governed, managerially controlled, shareholder value-maximizing firm, whereas the emblematic firm in CME is a bank-centered, stakeholder-oriented firm.
More recently, the high-performing Asian variety of capitalism model
views the diversified business group as the emblematic form of corporate organization (Carney, Gedajlovic, & Yang, 2009).1 The institutional
system, therefore, supplies firms with ‘institutional capital’ so that firms
fit, or become isomorphic with, prevailing modes of institutional
functioning. National institutional systems will differ in the way they
influence the structure of emblematic firms, and their capacity to accommodate non-emblematic firms, and isomorphic processes in different configurations, therefore, result in varied forms of comparative
institutional advantage (Schneider et al., 2010). Thus, as firms strive to
2
Even within the Europe, an underperforming group of Mediterranean varieties of
capitalism has been identified (Amable, 2003) while at the European periphery, Cernat
(2006) describes an incoherent form of “cocktail capitalism” and Nölke and Vliegenthart
(2009) refer to “dependent-market” capitalism.
1
There is also evidence to suggest that the adoption of best practice Western models of
corporate governance Is not effective in China (Chen, Li, & Shapiro, 2011).
3
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
In the OECD, we find some developed countries which have
achieved complementarity and firm isomorphism in one way or another, leading to higher levels of national and firm economic performance. In contrast, we expect to find greater variability in the extent to
which institutional systems are moving toward such complementarity
and firm isomorphism in emerging economies. This is because some
states are dynamically transforming their institutional systems with farreaching institution-building projects, while others have stagnated as
states appear to accept the existing institutional equilibrium. The resulting heterogeneity may lead to more significant differences in firm
performance across configurations. Using the VIS framework, (see
Table 1 for the composition of each configuration), we can identify
different institutional templates that might produce similar or different
effects on firm performance. For example, there is some evidence in the
literature that, the state and economic actors in FJAS’s emerging LME
and state-led configurations would seek resolution of institutional
contradictions, with firms dynamically adapting in the process (Peck &
Zhang, 2013). Alternatively, other VIS configurations may have already
settled into a stable institutional equilibrium; for example, the familyled configuration dominated by powerful rent-seeking business groups,
which resist institutional developments that challenge their rents
(Carney, Duran, van Essen, & Shapiro, 2017; Morck, 2010). In this institutional configuration, we expect that firms will face obstacles to
achieving efficiency because these countries lack the relevant complementarity and contain contradictions that fail to provide a sustained
institutional advantage. Hence, we expect that the configurations
identified by FJAS will vary in their capacities to provide the institutional frameworks that support competitive firms; as a result, we do not
expect equifinality across systems.
multiple attributes and derive from measures of distance, such as the
institutional configurations of VIS, must be considered as being context
dependent. Therefore, we hypothesize that rankings or comparisons of
configurations derived from firm performance may yield different results depending on the particular performance measure chosen.
Hypothesis 2. The impact (ranking) of any given configuration on firm
performance will vary according to the way that firm performance is
measured.
2.3. Foreign ownership
We now address the question of whether foreign-owned firms
(FOEs) have performance advantages over domestically owned firms
(DOEs), and most importantly whether these advantages (if they exist)
vary with the institutional context.
The traditional view in the IB literature is that FOEs benefit from the
ownership of tangible and intangible assets (O advantages) that can be
internally transferred to the host market to provide a performance advantage in the host market, a view summarized in Dunning’s OLI model
(Dunning, 1988; Rugman & Verbeke, 1990). Despite the liability of
foreignness associated with operating abroad (Zaheer, 1995), there is
ample empirical evidence from developed economy host markets that
foreign-owned firms do display such performance advantages (Bellak,
2004; Davies & Lyons, 1991). However, it is not at all clear that the
positive foreign ownership effect will hold in transitional, emerging and
developing markets, for two reasons. First, it is likely the case that the
institutional environment in these countries enhances the liabilities of
foreignness (Eden & Miller, 2004; Gaur, Kumar, & Sarathy, 2011), and
therefore dissipates the advantages of FOEs. For example, institutional
voids may result in the emergence of powerful business groups (Carney,
van Essen, Estrin, & Shapiro, 2018) whose structures and relations to
political elites may be quite different from those of FOEs. Thus, FOEs,
do not fit well in the local institutional environment, which may negatively affect their performance. Second, because many of the FOEs in
emerging markets may originate in other emerging markets, they may
lack the firm-specific assets underlying the positive performance effects
(Ramamurti, 2009, 2012; Rugman, 2009; Gammeltoft, Barnard, &
Madhok, 2010).3 As noted by Peng (2012, p. 99), a “big chunk of the O”
may be missing for EMNEs, thus resulting in limited performance advantages.
Despite these possibilities, we follow Dunning (1988) and Rugman
(2009) in proposing that all FOEs including EMNEs must possess some
FSA to overcome the liabilities of foreignness. At the same time, we
acknowledge that the nature of the FSAs may differ between FOEs from
emerging and developed countries (Bhaumik, Driffield, & Zhou, 2016;
Cuervo-Cazurra & Genc, 2008; Ramamurti, 2009). While MNEs from
developed countries may rely on more traditional sources of competitive advantage related to the ownership of internalized intangible assets, EMNEs may possess advantages related to their networking skills
and ability to navigate through more difficult institutional environments (Cuervo-Cazurra & Genc, 2008; Erdener & Shapiro, 2005). This
argument is stronger because knowledge-seeking motives for FDI in the
set of countries considered in this study are for the most part unlikely.
It then follows that the internalization process should protect these
advantages. Given that weak institutions and market failures characterize the countries we study, internalization theory would suggest
that FOEs will transfer their FSAs abroad through majority ownership
(Dunning, 1988; Gatignon & Anderson, 1988; Makino & Neupert, 2000;
Rugman & Verbeke, 1990).4 We support this reasoning with property
Hypothesis 1. Firms operating in different institutional configurations will
display differentiated levels of economic performance (no equifinality).
2.2. Institutional configurations and different measures of performance
In a classic article, Tversky (1977) argued that similarity measures
based on distance could at times violate simple axioms of minimality,
symmetry, and triangle inequality (Tversky, 1977, p. 328). For example, symmetry would require that if country A is judged to be similar
to country B, then country B must also be similar to country A. In our
context, this implies that countries should belong to the same configuration regardless of whether one begins with A or B. Tversky provides
the counter-example of China and North Korea, whereby North Korea is
judged to be more similar to China than China is to North Korea and
suggests that the differences arise because China and North Korea have
multiple attributes, and depending on the context there may be asymmetrical judgments about which are relevant.
Thus, measures of similarity derived from multiple attributes and
created by using distance measures may fail these logical tests.
Taxonomies derived through cluster analysis fall into this category.
Indeed, FJAS rely on a two-step clustering procedure which uses loglikelihood distance rather than squared Euclidean distance, and this
includes both continuous and dichotomous variables (Fainshmidt et al.,
2016, p. 9). This procedure is appropriate to their data but, in using
them, it is important to carefully consider the implications of Tversky’s
arguments about the asymmetries of effects; namely whether two
configurations can be judged to be similar in one analytical context, but
not in another. Thus, two configurations found to be equally favourable
to enhancing one aspect of firm performance may not be equally favourable concerning another. That is, a configuration’s multiple attributes may be seen differently (asymmetrically) depending on the activity the firm is considering, and so the value (ranking) of any
configuration may vary according to the activity. This implies that
conclusions regarding equifinality will be contingent on the performance measure under consideration.
Thus, arguments drawing on classifications that are based on
3
Rather, emerging market multinationals (EMNEs) are often argued to be motivated by
other factors such as strategic asset seeking (Meyer, 2015) or learning (Mathews, 2006).
4
Majority control does not rule out some level of local minority ownership to assist in
navigating institutional voids (Meyer, Estrin, Bhaumik & Peng, 2009).
4
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
rights theory, which suggests that when a firm possesses distinct assets
that are internationally transferable, it should exercise greater control
over those assets since control provides the firm with safeguards that
can protect their assets from misappropriation (Driffield, Mickiewicz, &
Temouri, 2016; Grossman & Hart, 1986) and facilitates the operation of
internal capital markets (Gugler, Peev, & Segalla, 2013). Similarly, with
the diffusion of ownership and control, the firm may experience high
agency costs that dissipate its ownership advantage and negatively
impact its performance (Boardman, Shapiro & Vining, 1997; Douma,
George, & Kabir, 2006). There is limited direct evidence on the relative
performance of FOEs in emerging markets, but the available evidence
does point to a positive performance effects of FOEs in India (Douma
et al., 2006) and of privatization to FOEs in transition economies (Estrin
et al., 2009). Based on these arguments, we expect that majority-owned
FOEs will benefit from the internal transfer of valuable intangible assets
from their parents, and this will, in turn, provide them with performance advantages in emerging markets.
Hence, we argue:
assumption and suggests that the market for acquiring local complementary assets is imperfect so that some institutional structures are
more likely to facilitate firms’ access to CSAs than others. Regarding the
previous discussion, this would imply that some institutional systems
can more effectively generate complementarities for foreign firms and
assuming that countries in specific institutional configurations share
these qualities, then there will be systematic variation in the relationship between institutional configurations and FOE performance. Thus,
we expect some emerging market institutional configurations to present
particularly strong challenges to FOEs, while others provide a more
fruitful context supporting firm performance.
We, therefore, argue that the ownership advantage of (majority
owned) FOEs is moderated by the institutional configuration of the
country in which they operate; that is, FOEs operating in different institutional configurations will display differentiated levels of economic
performance. Hence, we hypothesise that:
Hypothesis 4. The performance benefits of majority foreign-owned firms
are moderated by the institutional configuration in which the host country
belongs.
Hypothesis 3. Firms with majority foreign ownership will display superior
levels of economic performance compared with other domestically owned
firms operating in the host economy market.
3. Data and methods
We use the World Bank Enterprise Survey (WBES) database for our
empirical analysis (http://data.worldbank.org/data-catalog/enterprisesurveys). This is a cross-section time-series panel of enterprise data
collected by surveys of over 120,000 firms in more than 130 countries
across Asia, Latin America, Eastern and Central Europe, and Africa
between 2006 and 2016 (World Bank, 2011). The sampling is stratified
and random with replacement, constructed to be representative of the
country-level with respect to firm size, business sector, and geographic
region and undertaken in waves at different dates over the period, with
some countries having only one wave (e.g. Brazil and India), most
having two and a few having three (e.g. Bulgaria and the DR Congo).
WBES data have been used widely in economics and development
economic studies (see, e.g. Harrison, Lin, & Xu, 2014; Mitton, 2016;
World Bank, 2018, Chap. 2) and are now beginning to be used in IB
research (Cuervo-Cazurra, 2016; Jensen, Li, & Rahman, 2010).
FJAS created their VIS typology of institutional systems for understudied economies to incorporate numerous emerging markets including many within the World Bank dataset. They rely on a panel of
experts to identify seven distinct national institutional systems that
categorize governance arrangement for 68 understudied countries. The
full list, which also encompasses the two developed economy VOC
2.4. Interaction of foreign ownership and institutional configurations
If FOEs possess performance advantages, do they vary across institutional systems? Many scholars argue that foreign firms are more
likely to succeed when they can match their FSAs with the host countryspecific locational advantages (CSAs), which include resources, market
size, and institutions (Driffield et al., 2016; Rugman & Verbeke, 1990).
Thus, it is the interaction between the FSAs of the firm and CSAs of the
host country that drives the performance of an FOE in any particular
country. Hennart (2009) refers to the “bundling” of firm-specific and
complementary country-specific advantages. This explanation is likely
to be of particular relevance in emerging markets, where MNEs need to
combine their proprietary assets with local country assets which are
often very specific, such as access to gatekeepers or knowledge of local
networks (Shi, Sun, Pinkham, & Peng, 2014). There is, in fact, already
some evidence that the performance of foreign-owned subsidiaries depends on the institutional characteristics of the host country (Gugler,
Mueller, Peev, & Segalla, 2013).
While FSAs are unique to a firm, CSAs are usually seen as public
goods freely available to all market participants within a country
(Dunning & Lundan, 2008a, p. 96). Hennart (2009, 2012) questions this
Table 2
World Bank Enterprise Survey Sample Countries within the VIS Configuration Structure and Number of Firms in each Country.
Config1
State-led
Config2
Fragmented/fragile state
Config3
Family led
Config5
Emergent LME
Config6
Collaborative Agglomerations
Config7
Hierarchically coordinated
Country
Freq.
Country
Freq.
Country
Freq.
Country
Freq.
Country
Freq.
Country
Freq.
Argentina
Bangladesh
Belarus
China
India
Indonesia
Malaysia
Mongolia
Pakistan
Philippines
Russia
Sri Lanka
Thailand
Venezuela
Vietnam
Total
2117
2946
633
2700
9281
2764
1000
722
2182
2661
5224
610
1000
820
2049
36,709
Angola
Cameroon
DR Congo
Egypt
Ethiopia
Ghana
Kenya
Rwanda
Senegal
Sudan
Tanzania
Uganda
785
363
1228
2897
1492
1214
1438
453
1107
662
1232
1325
Azerbaijan
Brazil
Colombia
Mexico
Morocco
Nigeria
Peru
Tunisia
Yemen
770
1802
1942
2960
407
4567
1632
592
830
Botswana
Chile
Israel
Namibia
South Africa
610
2050
483
909
937
Czech Republic
Estonia
Hungary
Latvia
Lithuania
Poland
Slovak
Slovenia
504
546
601
607
546
997
543
546
Bulgaria
Georgia
Jordan
Kazakhstan
Lebanon
Romania
Turkey
Ukraine
1596
733
573
1144
561
1081
2496
1853
Total
14,196
Total
15,502
Total
4989
Total
4890
Total
10,037
5
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
Table 3
Definitions and Sources of Variables.
Variable
Definition
Source
Productivity (Log)
Export (% of total sales that are
exported directly)
Firm Age(Log)
Firm Size (Log)
% of FDI stock from Developed
Economies (Log)
GDP per Capita (Log)
Labor productivity is real sales (using GDP deflators) divided by full-time permanent workers
Sales exported directly as percentage of total sales.
WEBS
WEBS
Year firm began operation to year of survey conducted
Log of number of permanent workers
Percentage of FDI from developed countries to source economy
WEBS
WEBS
UNCTAD's Bilateral FDI
Statistics
World Bank World
Development Indicators
Ownership Hybridity
FOE majority owned (Dummy)
SOE majority owned (Dummy)
FOE SOE JV (Dummy)
GDP per capita is gross domestic product divided by midyear population. GDP is the sum of gross value added
by all resident producers in the economy plus any product taxes and minus any subsidies not included in the
value of the products. It is calculated without making deductions for depreciation of fabricated assets or for
depletion and degradation of natural resources. Data are in current U.S. dollars. The variable is loaded in logs.
(
2
)
Cummulative ownership of type i bloc kholder ⎤
1/Σi ⎡
Where i can be state foreign or domestic non-state
Total ownership by all bloc kholders
⎢
⎥
⎣
⎦
Firms with foreign owner hold more than 50% of ownership
Firms with state hold more than 50% of ownership
Firms with foreign and state Joint Venture
Calculated from WEBS
variables
as GDP per capita, measured in logs to address potential non-linearity in
the impact of GDP per capita. We noted above that many FOEs in our
sample are themselves from other emerging markets so their firm specific advantages may not be adequately captured by either productivity
or exports (Cuervo-Cazurra & Genc, 2008; Ramamurti, 2012). To control for this, we use country-level data on the source of FDI, namely the
percentage of the FDI stock derived from developed economies, measured in logs.6 In addition to controlling for possible differences in
performance between FOEs from developing and developed countries,
this variable may also control for the possibility that FOEs from developed countries provide greater spillover benefits. For these reasons,
we expect firm performance to be higher the greater the percentage of
FDI to a host economy from developed economies. We also employ a
variety of firm-level controls for company performance, all entered in
logs. In particular, we follow the literature in including a measure of
firm size; larger firms are typically associated with higher levels of
productivity and exports (Bonaccorsi, 1992; Hall & Weiss, 1967). The
second control stressed by the literature is the age of the firm, with
older firms normally associated with better performance (Moen, 1999).
In understudied economies, where institutions are less developed
than in advanced market economies, some hybrid or mixed ownership
structures may be more beneficial for firm performance (Khanna &
Palepu, 1999). Bringing together diverse groups of owners (private,
state, foreign) with access to different resources may provide distinctive
channels for accessing and assembling the kinds of resources required
for effective performance. Accordingly, following Chen, Li, Shapiro,
and Zhang (2014), we introduce a control for ownership hybridity
which measures the degree to which ownership is diversified by type of
owner (foreign, state, private domestic). Ownership Hybridity is defined in Table 3 and is expected to have a positive effect on firm performance. Finally, we control for industry and year fixed effects.
Our base sample uses a sub-sample of the (relevant part of) the
WBES dataset in which small firms (fewer than 10 workers), and stateowned firms (the state owns more than 50% of the firm’s equity) are
excluded because these increase the heterogeneity of the sample
without increasing variation relevant to our hypotheses. In robustness
tests, we re-estimate both the productivity and export equations on
samples which include state-owned and small firms respectively (denoted the full WBES sample). In the former case, we also control for
state ownership through a dummy variable in the regressions, as well as
(separately) for state-owned firms which are also foreign-owned.
categories, is contained in their Appendix A1 and is reproduced as
Table 1 below. Of the 68 countries in VIS, the WBES dataset covers 57.
Table 2 lists them and shows how they fit into the seven VIS configurations of understudied economies, as well as providing information
about the number of firms in each country sample. Our maximum
sample contains over 86,000 firms, but the deletion of some firms described below results in a sample of some 55,000 firms. Since there are
no observations for any countries in configuration 4 (centralized tribe)
in the WBER sample, this configuration cannot be used in the tests of
our hypotheses.5
3.1. Dependent variables
We employ two different measures of firm-level performance. The
first is labor productivity, a measure of firm-specific advantage (Caves,
1996; Zaheer, 1995), defined in the WBES as real sales per worker. The
second is exports (percentage of sales exported), a measure of the firm’s
ability to compete in the global economy (He, Brouthers, & Filatotchev,
2013). Variable definitions and sources for all dependent and independent variables are reported in Table 3.
3.2. Independent variables
We use dummy variables to allocate each of the 57 countries in the
sample to the appropriate one of the six available VIS configurations
presented in Table 1. In our regressions, we always use as our point of
reference configuration 5, emergent liberal market economies (ELMEs);
this represents for our sample of understudied economies the institutional system closest to the traditional Anglo-Saxon governance model.
We thus have 5 dummy variables corresponding to the FJAS national
institutional systems or configurations, henceforth denoted configs. We
analyse foreign ownership in terms of majority ownership and so load it
as a dummy variable taking the value unity when foreigners own more
than 50% of the equity in the firm.
3.3. Control variables
To avoid omitted variable bias, we need to control for a large
number of other factors likely to influence firm performance, (see e.g.
Bhaumik et al., 2016; Hansen & Wernerfelt, 1989). The most important
of these for cross country studies is the level of national economic development (Meyer, Estrin, Bhaumik, & Peng, 2009), which we measure
5
In addition, WBES has no data on Hong Kong and Singapore and are not covered in
the emergent LME configuration 5, and for the same reason South Korea and Taiwan are
not covered in configuration 7.
6
6
We are not able to identify the home economy of FOEs in our dataset.
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
4.2. Hypothesis testing
Table 4
Descriptive Statistics.
Variable
Mean
Std. Dev.
Min
Max
Labor Productivity(Log)
Export (% of total sales that are
exported directly)
Firm Age
Firm Size
% of FDI stock from Developed
Economies
GDP per Capita
Ownership Hybridity
FOE majority owned (Dummy)
SOE majority owned (Dummy)
FOE SOE JV (Dummy)
13.60
7.548
2.79
22.06
−3.40
0
29.00
100
17.72
112.5
64.73
14.91
514.9
24.01
0
0
0
210
37,772
99
5597.76
1.0497
0.0558
0.0054
0.0003
5338.56
0.2261
0.2296
0.073
0.0183
246.803
1
0
0
0
36281.2
4
1
1
1
Given the fact that our data are not collected as a panel structure,
we treat them as cross-sectional regardless of the date of sampling
within one country. To test our hypotheses, we run regressions on the
base sample (excluding state-owned and small firms) for each of the
two dependent variables, productivity, and exports. We estimate five
models. In the first, we include only the control variables; for model 2
we add the five configuration dummy variables (configs 1, 2, 3, 6, and
7) and for model 3 we include only the control variables and the
ownership variables. Model 4, which is the basis for testing hypotheses
1, 2 and 3, includes all five configurations (config) dummies and
ownership variables as well as the control variables. Finally, in model 5,
which we use to test hypotheses 4 (as well as to provide additional
support for hypotheses 1 and 2), we add to the independent variables in
model 4 the five interaction terms between the configuration dummies
and the foreign ownership variable.
The test for hypothesis 1 is whether there are significant differences
in the value of the five coefficients on the configuration dummies within
each of the export and productivity equations in model 4. We first test
whether the configs are different from the omitted category, configuration 5, by observing whether the coefficient on each configuration is
statistically different from zero. We then test the null hypothesis,
namely whether they are different from each other, by constraining the
coefficients to equality using a nested F-test. We test hypothesis 2 by
using model 4 for the productivity and export equations respectively,
and performing a pairwise comparison of the productivity versus the
export equation coefficients for each configuration; that is, we compare
configuration coefficients pairwise, across the productivity and export
equations.
The test of hypothesis 3 depends on the sign and significance of the
coefficient on the foreign-owned dummy in model 4; we argue that this
will be positive and statistically significant. Finally, we base the test of
hypothesis 4 on model 5. For each performance equation, we test
whether the coefficients on the interactive ownership-configuration
terms are statistically significantly different from each other. Once
again, we first test whether they are each different from configuration
4. Results
4.1. Descriptive statistics
We report descriptive statistics in Table 4 and correlation coefficients in Table 5. Our sample of firms in understudied countries primarily comprise small/medium sized domestic private firms; in Table 4,
we note an average firm size of around 110 workers and a firm age of
18 years. Only 5.4% of firms are state-owned, and only 5.6% are
(majority) foreign owned, while the share of exports in revenues is
typically small, 7.5%. On average, around one-third of FDI derives from
other emerging and developing countries. Table 5 reveals that the
correlation coefficients between the independent variables are almost
all rather small, mostly well below 0.3, suggesting that multicollinearity is not a serious issue in our data. One exception is the positive correlation between FDI stock from developed economies and
GDP per capita. However, in unreported regressions we find that
omission of the former does not influence the results concerning the
hypotheses, so we include both variables in our reported regressions.
Table 5
Correlation Coefficients.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
8
9
10
11
12
13
14
15
Variable
1
2
3
4
5
6
7
8
Labor Productivity (Log)
Export
Firm Age (Log)
Firm Size (Log)
GDP per Capita (Log)
% of FDI stock (Log)
Ownership Hybridity
FOE majority owned
SOE majority owned
Con1 (State led)
Con2 (Fragmented)
Con3 (Family led)
Con5 (LME)
Con6 (Collaborative)
Con7 (Hierarchically)
1
−0.0031
0.0268*
0.0419*
−0.1895*
−0.0887*
0.0011
0.0545*
0.0313*
0.2104*
0.0378*
−0.1171*
0.0655*
−0.0878*
−0.2235*
1
0.0608*
0.2969*
0.0133*
0.0262*
0.1021*
0.1838*
−0.0028
0.0291*
−0.0686*
−0.0346*
−0.0235*
0.0558*
0.0524*
1
0.2712*
0.0668*
0.0755*
0.0427*
−0.0088
0.0390*
0.0602*
−0.1073*
0.0309*
0.0332*
0.0198*
−0.0445*
1
0.0574*
0.0011
0.1202*
0.1670*
0.0750*
0.1444*
−0.1277*
−0.0559*
0.0032
−0.0225*
0.005
1
0.4052*
0.0176*
0.0079
0.0087
−0.1114*
−0.4950*
0.0759*
0.2196*
0.3516*
0.2398*
1
−0.0175*
0.0108*
−0.0369*
−0.1294*
−0.2545*
0.1233*
0.0474*
0.1787*
0.1671*
1
0.1089*
0.1377*
−0.0334*
0.0064
0.0526*
−0.0067
−0.0032
−0.0108*
1
−0.0178*
−0.0588*
0.0484*
−0.0278*
0.0654*
0.0461*
−0.0129*
Variable
8
9
10
11
12
13
14
15
FOE majority owned
SOE majority owned
Con1 (State led)
Con2 (Fragmented)
Con3 (Family led)
Con5 (LME)
Con6 (Collaborative)
Con7 (Hierarchically)
1
−0.0178*
−0.0588*
0.0484*
−0.0278*
0.0654*
0.0461*
−0.0129*
1
0.0288*
−0.0090*
−0.0116*
−0.0141*
−0.0015
−0.0088*
1
−0.3816*
−0.4024*
−0.2130*
−0.2108*
−0.3120*
1
−0.2076*
−0.1099*
−0.1087*
−0.1609*
1
−0.1159*
−0.1146*
−0.1697*
1
−0.0607*
−0.0898*
1
−0.0889*
1
* p < 0.01.
7
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
suggested by Kingsley, Noordewier, and Bergh (2017), we test the
marginal effects of foreign ownership on productivity and exports in
each configuration, reported in Table 9, Panels B, and these are also
statistically significant.10 Thus, we find strong evidence in support of
H4.
Finally, turning to the control variables these largely conform to our
expectations. In most models, productivity is positively related to firm
age and size. However, it is interesting that we find that older firms
export significantly less. The share of the FDI stock from developed
economies raises both productivity and exports, while both are negatively associated with GDP per capita. Finally, ownership hybridity –
the inverse of the concentration of ownership by ownership type, acts to
reduce productivity but interestingly to increase exports.
5, via the significance of the coefficient on each ownership-configuration interaction. We go on to test whether all the other ownershipconfiguration interaction coefficients in model 5 are different from one
another by constraining the coefficients to equality.7
4.3. Results for the base specification
We report our results using the base specification sample in Table 6.
The control variables alone in model 1 provide an explanation of
around 16% of the heterogeneity of productivity in our sample and 14%
of exports. The explained variance increases to about 22% and 17%
respectively once we add the configuration and ownership dummies
and their interactions in model 5.
As outlined above, we use the results in models 4 and 5 to test our
hypotheses. Commencing with hypothesis 1 (non-equifinality), we note
that all five configuration dummies in both the productivity and export
equations are statistically significantly different from the omitted category at the 99% level, which provides strong support for the hypothesis. Furthermore, we find in Table 7 (Panel A) that the coefficients
on all the configuration dummies are statistically significantly different
from each other at the 10% level except for the pairs of coefficients on
configs 1 and 6 and on configs 2 and 3 in the productivity equation.
Thus, we find evidence in support of hypothesis 1; by ranking the
configurations in terms of contribution to firm performance.8 In Panel B
of Table 7, we produce the ranking of configuration impact on performance, accounting for differences in statistical significance, and note
that the ranking differs depending on whether we measure performance
by productivity or exports.
We test hypothesis 2 (Tversky) by comparing the configuration
coefficients in model 4 in the productivity equation with those in the
export equation. We report the tests results based on a chi-squared test
Table 8, where we see that the coefficients are significantly different
from each other in every configuration, except config 2. This result
explains the different rankings of configuration reported in Table 7,
Panel C, and thus these tests provide strong support for hypothesis 2.
We test Hypothesis 3 through the sign and significance of the
coefficient on the FOE dummy in the productivity and export equations
in Model 4, Table 6. We note that both are positive and statistically
significant in model 4) for both equations, which provides strong support for hypothesis 3.9 We test Hypothesis 4 by comparing the coefficients on the interactive ownership-configuration terms in model 5
within each equation, and we report the results in Table 9. Panel A,
reports the regression coefficients that we test. Here, we test for significant differences using the nested-F test and find significant differences between the coefficients in both equations. Thus, in the productivity equation, all five interactive ownership-configuration terms
are significantly different from the omitted interaction term (FOE*configuration 5) at the 99% level. Furthermore, Table 9, Panel A shows
that the coefficients on all the interactive ownership-configuration
terms are statistically significantly different from each other except for
the pairs of coefficients FOE*config1/FOE*config6 and FOE*config3/
FOE*config6. The same applies to the export equation except that the
coefficient on FOE*config2 is negative and significant at the 95% rather
than at the 99% level. Thus, we establish that this interactive term is
significantly different from all the other interactive ownership-configuration terms without reference to the formal tests in Table 9. As
4.4. Robustness tests
We consider in unreported regressions11 the results from the two
broader samples. We first included small firms (< 10 workers), increasing the sample by around 30% on average, and more in fragmented and family-led configurations. The second sample included
SOEs and increased the sample by 10%, more so in the state-led and
hierarchically coordinated configurations. We re-estimated models 4
and 5 on these samples, and in both cases continued to find strong
support for all four hypotheses.
5. Discussion
In this paper, we first advance the literature on national institutional systems both empirically and theoretically, by focusing on the
impact of these systems on the performance of firms from emerging and
developing economies. At the same time, we contribute to the IB literature by exploring the performance of foreign-owned firms and the
interaction between configuration-specific and their firm-specific advantages in a sample of understudied countries. We begin by discussing
the implications of the relationship between national systems of institutions and host country firm-level performance for the literature on
institutional and governance systems, before considering the impact on
foreign-owned firms.
5.1. National institutional systems and firm-level performance
We first contribute to this literature by testing and validating
Fainshmidt et al.’s (2016) comprehensive taxonomy of institutional
systems and demonstrate that the configurations provide an independent and statistically significant explanation of the variation in
firm performance across countries. Thus, we show that these configurations matter in explanations of firm performance and thereby contribute to this line of research by addressing the comments that scholars
have given more attention to the task of critiquing institutional typologies than to testing the frameworks (Peck & Zhang, 2013). Furthermore, FJAS’s varieties of institutional systems perspective introduce for
understudied countries two new elements that are conspicuously absent
from the VOC perspective and which are likely to influence firm performance: a more prominent role for the state and ownership structure
notably in the form of concentrated and family ownership.
Secondly, our results shed light on the kinds of institutional arrangements that will support better enterprise performance. With its
depiction of path-dependent institutional change (Hall & Thelan, 2009),
the comparative capitalism literature has emphasized institutional
7
As a robustness test, we also used Model 5 to test hypotheses 1 and 2, but this does not
change the results discussed below.
8
It should be noted that while we chose to test the hypothesis using model 4, the
coefficients and standard errors on the configuration do not alter greatly between models
2, 4 and 5, underlining the robustness of this result.
9
The simple estimated coefficient on FOE is estimated to be negative in model 5 of the
productivity equation, but the full effect has to be calculated by taking into account the
interactive effect with each of the configurations. Thus, in fact, foreign ownership only
has a negative effect on productivity in the omitted configuration which is Emergent
LMEs.
10
As noted above, the omitted category in all models is configuration 5, ELME. Thus,
our marginal tests reported in Table 9 Panel B on the interactive ownership-configuration
in model 5 also treat omitted FOE* Con 5 as the reference category. We have graphed the
marginal effects across configurations but these provide no additional information and to
save space are not provided. They are available upon request.
11
Available from the authors on request.
8
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
Table 6
Regression Results; Base Sample Excludes Small and State Firms.
Variable
Firm Age (Log)
Firm Size (Log)
% of FDI stock
GDP per Capita
Labor Productivity(Log) as Dependent Variable
Export as Dependent Variable
Model 1
Model 2
Model 3
Model 4
Model 5
Model 1
Model 2
Model 3
odel 4
Model 5
0.0494***
(0.0151)
0.0600***
(0.0092)
0.3067***
(0.0254)
−0.8510***
(0.0152)
−0.0095
(0.0147)
0.0397***
(0.0089)
0.4882***
(0.0256)
−1.162***
(0.0215)
−2.234***
(0.0622)
−3.139***
(0.0703)
−3.108***
(0.0558)
−2.111***
(0.071)
−2.999***
(0.063)
0.0588***
(0.0152)
0.0498***
(0.0094)
0.3053***
(0.0254)
−0.848***
(0.0152)
−0.909***
(0.1285)
5.378***
(0.0782)
0.6621**
(0.2228)
−1.762***
(0.1846)
1.7866***
(0.5497)
−3.347***
(0.6204)
0.1095
(0.4959)
11.671***
(0.6213)
3.6029***
(0.5526)
−0.558***
(0.1273)
4.8621***
(0.0791)
0.5557**
(0.2125)
0.2021
(0.1267)
13.702***
(0.3807)
4.2128***
(0.5153)
−0.602***
(0.1273)
4.789***
(0.0788)
0.4739*
(0.2203)
−1.566***
(0.1826)
2.757***
(0.544)
−3.384***
(0.6134)
0.9798*
(0.4909)
11.33***
(0.6144)
4.172***
(0.5467)
13.699**
(0.3803)
4.7218***
(0.5131)
21.074**
(0.2071)
Yes
Yes
52966
345.71
0.1634
26.029**
(0.2758)
Yes
Yes
52966
431.66
0.2215
−0.0054
(0.0147)
0.0308***
(0.009)
0.4876***
(0.0256)
−1.154***
(0.0215)
−2.398***
(0.0648)
−3.379***
(0.0729)
−3.253***
(0.0587)
−2.310***
(0.075)
−3.136***
(0.0657)
−1.117***
(0.1359)
−0.1317*
(0.0583)
1.6183***
(0.1535)
2.1372***
(0.1659)
1.3612***
(0.1722)
1.5787***
(0.1906)
0.9731***
(0.1902)
25.896***
(0.2623)
Yes
Yes
52966
383.65
0.2242
−0.889***
(0.1285)
5.4289***
(0.0784)
0.5939**
(0.2149)
0.11
(0.1281)
0.4196***
(0.045)
−0.261***
(0.0603)
−0.0024
(0.0147)
0.0302***
(0.009)
0.4819***
(0.0256)
−1.153***
(0.0215)
−2.209***
(0.0623)
−3.127***
(0.0703)
−3.082***
(0.0558)
−2.119***
(0.071)
−2.993***
(0.0631)
0.3350***
(0.0436)
−0.1293*
(0.0583)
−11.03***
(1.666)
Yes
Yes
58894
372.82
0.1592
1.3804
(2.2493)
Yes
Yes
58894
343.11
0.1690
−0.534***
(0.127)
4.7424***
(0.0786)
0.5695*
(0.2197)
−1.829***
(0.1826)
1.1257*
(0.5658)
−3.447***
(0.6358)
−0.0176
(0.5154)
10.305***
(0.6464)
2.9316***
(0.5684)
6.6658***
(1.1964)
4.7354***
(0.5121)
13.9***
(1.3525)
−4.16**
(1.4441)
5.5532***
(1.5224)
9.7559***
(1.6572)
12.911***
(1.6466)
−1.7196
(2.2529)
Yes
Yes
58894
311.47
0.1741
Con1
(State led)
Con2
(Fragmented)
Con3
(Family led)
Con6
(Collaborative)
Con7
(Hierarchically)
FOE majority
Ownership
Hybridity
FOE* Con1
FOE* Con2
FOE* Con3
FOE* Con6
FOE* Con7
Constant
Industry Control
Year Control
Obs
F
Adj R-squared
18.962***
(0.1924)
Yes
Yes
52990
365.440
0.162
25.251***
(0.2669)
Yes
Yes
52990
454.670
0.220
−11.19***
(1.6814)
Yes
Yes
8923
339.05
0.1384
3.6492
(2.3271)
Yes
Yes
58923
311.07
0.1480
*p < 0.05, **p < 0.01, ***p < 0.001.
with proximity to, and growing economic integration with North European CME economies suggests a proces of national institutional isomorphism.
However, these are not the only relatively effective configurations
in VIS. Based on their firm performance rankings, we identify two intermediate configurations: state-led systems (config 1, joint second on
productivity and third in exporting), and hierarchically coordinated
(config 7, second in exporting but equal fourth in productivity). FJAS
characterize both as having a strong state, which plays a prominent role
in resource allocation and in shaping the economic ordering of society.
Concentrated and family ownership are also characteristic of both.
However, strong states retain what Evans’ (1995) describes as embedded autonomy, and avoid dependence upon powerful oligarchs or
family elites. Similarly, while the state mediates incentives and resources, concentrated owners and family businesses possess the autonomy to pursue economic competitiveness that promotes their productivity and economic performance. The prominent role of the state
and high exporting is suggestive of a government policy choice favoring
export-oriented development, a well-trodden path for late-industrializing states (Amsden, 1991). Importantly, neither appear to be
converging on either the CME or LME varieties of capitalism. Instead,
these variants may represent an alternative, hybridized form of state
capitalism. This heterogenous group of countries may be depicted as
autocratic and illiberal regimes pursuing liberal trade policies (Hankla
& Kuthy, 2013). Many of the countries in these configurations are
continuity and the persistence of variety in capitalist structures
(Jackson & Deeg, 2008). This characterization may be appropriate in
the context of mature institutional settings, but less so in understudied
countries which comprise a wide array of transitional, socialist, and
authoritarian regimes. A firm-centered approach, such as ours, can inform debates about the evolution of institutional systems, and in particular “incremental institutional adjustments, and potential hybridization” (Jackson & Deeg, 2008: 542) that may emerge over time.
Our ranking results shed some preliminary and admittedly tentative
light on these debates, suggesting a range of distinctive trajectories of
institutional change and firm performance. For example, our evidence
points to two relatively high-performing configurations: emergent LMEs
(config 2) in which firms rank first in productivity but 5th in exports,
and collaborative agglomerations (config 6) in which firms ranked joint
second in productivity and first in exports. We characterize the developmental trajectories of both configurations in dynamic terms where
relatively strong-states are proactive in building complementarities to
address institutional contradictions and seeking to develop a coherent
market-based institutional framework. In these settings, where markets
and other selection mechanisms are intensified, and domestic firms are
incentivized to adapt and improve their practices, high levels of performance can be achieved (Sinkovics et al., 2014). Indeed, FJAS’s
characterization of these configurations (emergent LME, collaborative
agglomerations) suggests convergence on the LME and CME varieties of
capitalism, respectively. In the latter, a group of former socialist states
9
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
Table 7
Test of Equality of coefficients on Configurations in Model 4.
Panel A. Within equation pairwise T-test
Con1
Con2
Con3
Con6
Labor Productivity as Dependent Variable
Con1
Con2
492.94***
Con3
516.97***
Con6
1.9
Con7
233.28***
0.84
180.84***
5.07*
229.94***
3.01
199.53***
Export as Dependent Variable
Con1
Con2
296.02***
Con3
28.35***
Con6
240.63***
Con7
10.88**
105.27***
535.68***
225.73***
366.7***
54.04***
191.82***
Con7
Panel B: Rankings
Configuration
Ranking (Labor Productivity)
Ranking (Exports)
Con1
Con2
Con3
Con5
Con6
Con7
Equal
Equal
Equal
1st
Equal
Equal
3rd
6th
4th
5th
1st
2nd
(State led)
(Fragmented)
(Family led)
(LME)
(Collaborative)
(Hierarchically)
2nd
4th
4th
2nd
4th
Note:
1. Table 7 provides additional results for non-equifinality hypothesis (H1) in model 4
2. Panel A presents pairwise T-test in Model 4 on five configurations dummies. The number denotes F-ratio as the difference between
two configuration dummies in the same model. The asterisks ***, ** and, * denote statistical significance at 1%, 5%, and 10% levels,
respectively.
3. Panel B depicts configuration impacts on two performance outcomes by ranking the coefficients of each configuration dummy with
the omitted Con5 (LME) at a value of zero.
* p < 0.05.
** p < 0.01.
*** p < 0.001.
economic systems with weak states that lack the capacities to furnish
resources or otherwise close institutional voids. As borne out in our
results, firms are very unlikely to achieve international levels of competitiveness in these economic systems. FJAS describe the diverse
economies located in North Africa, central Asia, and Latin America
comprising the family led systems in neutral terms. They suggest that
‘wealthy and dominant families take center stage in ownership, resource allocation and management’ and ‘wealthy families drive the
economic agenda’(2016:10). However, Fogel (2006) depicts many of
these states as oligarchic, where dominant families become entrenched
and protect their interests, which can be achieved by frustrating promarket policy initiatives and block entry from new rivals (Schneider,
2009). In these economic systems, the selection environment is relatively weak, and firms have few incentives to improve their competitiveness.
Thus, measuring institutional configurations regarding firm-level
performance suggests evidence of both institutional convergence and
persistence as well as pointing to the possibility of hybridized forms of
state capitalism, which hold the promise of improved levels of firmlevel and macroeconomic performance. In this sense, our findings address the question of institutional equifinality among emerging market
and transitional economies and confirm our hypothesis that firms in
different institutional configurations will operate at different levels of
economic performance.
Although our findings therefore strongly support our hypothesis
that there is non-equifinality between these novel VIS configurations,
the exact rankings depend on the performance measure chosen. We
explore this phenomenon more formally through what we refer to as
the Tversky effect, where we find evidence supporting our hypothesis
that the firm-level performance effects of institutional configurations
Table 8
Comparing Regression Coefficients between Labor Productivity and Export (H2).
Configuration
Chi2
P value
Rank
Con1
Con2
Con3
Con6
Con7
109.17
0.22
95.69
442.77
177.95
0.0000
0.6398
0.0000
0.0000
0.0000
3rd
5th
4th
1st
2nd
(State led)
(Fragmented)
(Family led)
(Collaborative)
(Hierarchically)
Note:
1. Table 8 provides primary results for the Tversky hypothesis (H2) in model 4
2. Post-estimation test compares the coefficient of each configuration across models on
two performance outcomes, respectively. Chi2 with statistical P-value denotes significant
difference between coefficients across the two models. Ranking of Chi2 indicates the
variance of difference also diverse among five configurations.
relatively stable single-party states with long time horizons and incentives to adopt open trade policies that improve long-term economic
performance. The implication is that state leadership of the economy
becomes a permanent feature of these economic systems.
A third category is also evident in the rankings, one that is consistent with those scholars who identify economic systems characterized by institutional inertia, and even outright failure (Schneider 2009;
Wood & Frynas, 2005). These institutional settings may have become
permanently settled into their foundations with the preservation of
institutional contradictions and non-complementarity. Our results
identify two underperforming configurations with these characteristics:
fragmented and fragile states (config 2) with lagging performance on
both exports and productivity, and family led systems (config 3) also
weak on productivity and exports. Fragmented and fragile states are
10
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
5.2. Institutional configurations and foreign ownership
Table 9
Tests of Equality of Coefficients on FOE*configuration Interactions in Model 5.
Our second contribution is to the IB literature. We build our analysis
on the OLI framework and the argument that for developing and
emerging economies as well as developed ones, FOE success abroad
depends on both the ability to create and transfer ownership advantages and on the ability of the firm to match its FSA to the location
advantages of the host market.
Thus, our third hypothesis was that FOEs translated their FSAs into
performance advantages when locating in understudied countries, a
hypothesis confirmed for both productivity and exports (Table 6, Model
4). It is important to establish theoretically and empirically that FOEs in
understudied countries characterized by challenging institutional circumstances nevertheless do on average enjoy a performance premium
associated with their FSAs transferred abroad, especially as a basis for a
more fine-grained analysis of the effects of national institutional systems on firm performance. Moreover, given that some one-third of FDI
in our sample countries originates from emerging economies, our results suggest that FSAs as a basis for internationalization are not unique
to MNEs from developed countries. Future research should focus on
achieving a better understanding of these FSAs giving particular attention to the non-traditional advantages of emerging market multinationals that previous studies have identified (Bhaumik et al., 2016;
Cuervo-Cazurra & Genc, 2008; Ramamurti, 2009).12 We interpret our
results as providing support for a traditional OLI approach to understanding the nature of the MNE operating in developing economies,
with the caveat that O advantages might be different for EMNEs.
The analysis around hypothesis 3 also contributes to the literature
on comparative corporate governance by showing that governance and
ownership are important in explaining firm performance. In this regard,
we follow Aguilera and Crespi-Cladera (2016) who call for increased
attention to ownership structure and its relationship to economic performance in different economies. Specifically, our data on performance
and ownership responds to their call for future research that uses firmspecific microdata on ownership structures to better understand the
cross-national diversity in performance outcomes. Because our dataset
applies a standard survey methodology across countries, we can make
reliable estimates of ownership and performance attributes of firms
located in very different institutional settings.
We go on in Hypothesis 4 to explore whether these performance
advantages of FOEs vary by configuration. Our analysis extends
Hennart’s (2009; 2012) argument that access to country-specific advantages is not free, and will vary by host country and so the performance of foreign firms is contingent on their ability to choose locations
that best match their FSAs. If configurations do indeed share important
institutional similarities, then this argument leads one also to expect
configuration-specific advantages, and hence that the performance of
FOEs will be configuration specific. Our results provide support for the
argument. Put differently; our results indicate that locational (L) advantages cannot be considered as solely country-specific because
groups of countries share certain institutional characteristics that distinguish them from others and impact firm performance. Thus, the
notion of country-specific advantage must be extended to include
configuration-specific advantages. Among other things, this way of
thinking also provides opportunities to re-examine the issue of locational and entry mode choice from a configuration perspective, and
suggests that the widespread use of institutional-distance measures
between countries as a determinant should be reconsidered to take into
account the institutional distance between configurations of countries.
By suggesting that some institutional systems are better able to
support FDI, our fourth hypothesis complements insights from hypothesis one and two, because it results in a ranking of institutional
Labor Productivity as Dependent Variable
FOE * Con1
FOE * Con2
FOE * Con3
FOE * Con6
Panel A. Within equation pairwise T-test (H4)
FOE * Con1
FOE * Con2
18.74***
FOE * Con3
4.04*
29.4***
FOE * Con6
0.07
11.5***
1.62
50.28***
5.19*
FOE * Con7
18.19***
10.29**
Export as Dependent Variable
FOE * Con1
FOE * Con2
305.74***
FOE * Con3
54.04***
60.59***
FOE * Con6
10.01**
97.62***
FOE * Con7
0.58
149.78***
3.83
7.99**
24.89***
FOE
*
Con7
Panel B. Marginal Effects of FOE (Model 5 Interaction)
Labor Productivity
Export
Marginal
Effect
P value|
Rank
Marginal
Effect
FOE * Con1
0.501
0.000
2nd
FOE * Con2
1.020
0.000
1st
FOE * Con3
0.244
0.023
4th
FOE * Con6
0.461
0.001
3rd
FOE * Con7
−0.145
0.279
5th
FOE *
Con1
FOE *
Con2
FOE *
Con3
FOE *
Con6
FOE *
Con7
P value|
Rank
20.566
0.000
1st
2.506
0.002
5th
12.219
0.000
4th
16.422
0.000
3rd
19.576
0.000
2nd
Note:
1. Table 9 provides primary result for moderation hypothesis (H4) in model 5
2. Panel A presents pairwise T-test in Model 5 on five interactive ownership-configuration
terms. The number denotes F-ratio as the difference between two interaction terms in the
same equation. The asterisks ***, ** and, * denote statistical significance at 1%, 5%, and
10% levels, respectively.
3. Panel B depicts marginal effects of five interaction terms vary on two performance
outcomes, respectively. The ranking is based on coefficients of interaction terms.
* p < 0.05.
** p < 0.01.
*** p < 0.001.
differ according to the performance measure chosen. An important
implication is that the attractiveness of a country may be evaluated
differently by a potential investor if the investment is part of an export
platform to feed a global supply chain rather than an investment in
capacity to meet local market demand. There are also relevant research
ramifications, especially for researchers who are interested in the performance attributes of institutional systems. Our arguments show that
the choice of performance measure to evaluate the comparative efficiency of different institutional systems may determine the conclusions
reached. Finally, there are implications for the generation of comparative institutional data. In practice, panels of experts or polls of
informed individuals derive many indicators of institutional systems
(including the FJAS indicators). The implication of our finding is
therefore that these expert ratings may be subject to unobservable
judgement bias when presented with different scenarios. Comparative
institutional research makes extensive use of institutional quality
measures applying expert rating methodologies; examples include the
World Bank Ease of Doing Business Rankings, International Country
Risk Guide, and Freedom House. In the light of our findings, these
measures need be selected carefully and interpreted cautiously.
12
Our data do not allow us to identify at the firm-level the home country of the foreign
investor.
11
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
vast data collection exercise at the enterprise level on understudied
economies. However, the WBES dataset also imposes some limitations.
Most importantly, though there are a few countries surveyed three
times, the bulk of the dataset comprises either single year observations
or observations from only two waves. This has made it impossible to use
empirical methods that distinguish between firm-level, country-level,
and configuration effects. Future work may, therefore, need to seek
either panel data for understudied economies or focus primarily on the
countries with three waves to explore these distinctions. Furthermore,
the data do have certain limitations, with respect to performance and
ownership measures, and future research should investigate ways to
improve these measures. Our analysis would, in particular, be improved
by using a measure of total factor productivity and by being able to
identify the country of origin of foreign-owned firms. Moreover, while
our results point to the effective transfer of FSAs, even in an environment where transaction costs are high, as the explanation for the superior performance of majority-owned FOEs, we cannot in this study
identify the nature of the FSAs, nor distinguish those possessed by
EMNEs from other foreign investors. At the same time, while we
identify clear configuration-specific effects on the performance of FOEs,
these differ by performance measure, and we have not at this stage been
able to identify the exact reasons. These are important limitations of our
analysis.
configurations that depends on the performance measure chosen
(Table 9, Panels B). However, it also extends the analysis by suggesting
a mechanism through which configurations differ, and it introduces a
possible link between firm governance and systems governance that
researchers have not yet studied. Both offer opportunities for future
research.
As a starting point, future research could focus on spillovers from
FOEs to the host economy (Meyer & Sinani, 2009). If foreign ownership
performance effects are sensitive to the particular configuration in
which a country is located, then domestic performance effects may also
be further enhanced by spillovers from foreign-owned firms (Witt &
Jackson, 2016; World Bank, 2018). Our results are suggestive in this
regard. For example, considering productivity, we note that the performance of majority-owned FOEs is highest in config 2, the fragmented
economies of Sub-Saharan Africa, and lowest in config 5, emergent
LMEs; the opposite of the rankings found in the estimates without
foreign ownership interactive effects (Table 9, Panel B). This result
suggests the possibility that spillover benefits are lower in Sub-Saharan
Africa, in turn suggesting a mechanism explaining the poor productivity
performance of that configuration.
At the same time, our results also suggest that the export performance of majority-owned FOEs is strongest in the state-led, collaborative agglomeration, and hierarchically-coordinated configurations
(Table 9, Panel B), the same ranking as was found in the estimates
without the foreign ownership interactive terms (Table 7, Panel B).
These results suggest possible links between institutional governance at
the configuration level, namely the degree of state involvement in export-driven industrial policy, and the relative performance of firms by
ownership type. The prominent role of the state in these institutional
systems suggests that state involvement can be particularly advantageous for FOEs. We have emphasised the potential for both direct effects on FOE performance and the strong possibility for indirect ones
because national institutional systems may influence spillovers. The
possibility leads us to suggest that the institutional theory of the supply
side of the economy that examines how institutions shape the supply of
inputs such as skills and capital collectively available to firms (Jackson
& Deeg, 2008) might be extended to encompass configurations. Thus,
the MNE might be considered part of the supply-side in understudied
countries notably concerning productivity-enhancing skills and practices.
We conclude by acknowledging some limitations of this study and
providing some further guidance for future research. Our study faces
limitations at both the theoretical and empirical levels. Commencing
with theory, we have followed the literature in basing our classification
of institutional systems upon taxonomies, which derive their classificatory distinctions from empirically observed clusters of characteristics,
rather than from an underlying conceptualization as would be the basis
for a typology. Given that understudied economies are typically evolving rapidly and are often subject to significant institutional changes,
sometimes related to revolution, civil war or major economic and social
development (Collier, 2007), our taxonomies may provide an unstable
basis for long-term analysis. Furthermore, we have chosen to base our
study on the VIS classification, with our contribution primarily focused
towards exploring the complex inter-relationships among institutional
systems, enterprise governance system, and firm performance. While
our research has provided some evidence of the validity of the VIS
taxonomy in explaining firm performance in understudied economies,
future researchers may wish to revisit the taxonomy itself to explore
whether cluster analysis based on a richer characterization of institutions can provide an equally valid but more fine-grained specification of
institutional systems in understudied economies. Also, we have not
addressed the question of institutional dynamics and institutional
change, which can affect firm performance (Kafouros & Aliyev, 2016)
and firm ownership (Driffield et al., 2016), and in turn change configuration identity and impact.
On the empirical side, we have benefitted from the World Bank’s
6. Conclusions
In summary, we propose and find evidence for the argument that
national institutional systems provide an additional and significant
explanation of the firm performance in understudied countries. We do
not observe equifinality in that some configurations are more supportive of positive firm performance than others. Moreover, the degree to
which configurations impact firm performance depends on the performance measure chosen; we use two key measures – productivity and
exporting. Thus, we find configurations to be important, but their effects to be context dependent. Finally, we provide evidence that one
mechanism contributing to the heterogeneous impact of configurations
on firm performance is that some configurations are better able to
support the FSAs of foreign-owned firms. Our analysis indicates that the
traditional focus on the interaction of firm and country effects as joint
determinants of FOE performance may have to be augmented to include
configuration-specific advantages.
References
Aguilera, R. V., & Crespi-Cladera, R. (2016). Global corporate governance: On the relevance of firms’ ownership structure. Journal of World Business, 51(1), 50–57.
Allen, M. (2004). The varieties of capitalism paradigm: Not enough variety? SocioEconomic Review, 2(1), 87–108.
Amable, B. (2003). The diversity of modern capitalism. Oxford: Oxford University Press.
Amsden, A. H. (1991). Diffusion of development: The late-industrializing model and
greater East Asia. The American Economic Review, 81(2), 282–286.
Bénassy-Quéré, A., Coupet, M., & Mayer, T. (2007). Institutional determinants of foreign
direct investment. World Economy, 30, 764–782.
Bamiatzi, V., Bozos, K., Cavusgil, S. T., & Hult, G. T. M. (2016). Revisiting the firm,
industry, and country effects on profitability under recessionary and expansion periods: A multilevel analysis. Strategic Management Journal, 37(7), 1448–1471.
Bellak, C. (2004). How domestic and foreign firms differ and why does it matter? Journal
of Economic Surveys, 18(4), 483–514.
Bevan, A., Estrin, S., & Meyer, K. E. (2004). Foreign investment location and institutional
development in transition economies. International Business Review, 13(1), 43–64.
Bhaumik, S. K., Driffield, N., & Zhou, Y. (2016). Country specific advantage, firm specific
advantage and multinationality –sources of competitive advantage in emerging
markets: Evidence from the electronics industry in China. International Business
Review, 25(1), 165–176.
Boardman, A. E., Shapiro, D. M., & Vining, A. R. (1997). The role of agency costs in
explaining the superior performance of foreign MNE subsidiaries. International
Business Review, 6(3), 295–317.
Bonaccorsi, A. (1992). On the relationship between firm size and export intensity. Journal
of International Business Studies, 23(4), 605–635.
Boyer, R. (2005). How and why capitalisms differ. Economy and Society, 34(4), 509–557.
Brouthers, K. D. (2002). Institutional, cultural and transaction cost influences on entry
mode choice and performance. Journal of International Business Studies, 33(2),
12
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
Hall, P. A., & Gingerich, D. W. (2009). Varieties of capitalism and institutional complementarities in the political economy: An empirical analysis. British Journal of
Political Science, 39(3), 449–482.
Hall, P. A., & Soskice, D. W. (2001). Varieties of capitalism: The institutional foundations of
comparative advantage. Oxford: Oxford University Press.
Hall, P. A., & Thelen, K. (2009). Institutional change in varieties of capitalism. SocioEconomic Review, 7(1), 7–34.
Hall, M., & Weiss, L. (1967). Firm size and profitability. The Review of Economics and
Statistics, 49(3), 319–331.
Hancké, B., Rhodes, M., & Thatcher, M. (2007). Beyond varieties of capitalism: Conflict,
contradictions, and complementarities in the european economy. Oxford, UK: Oxford
University Press.
Hankla, A. C. R., & Kuthy, D. (2013). Economic liberalism in illiberal regimes:
Authoritarian variation and the political economy of trade. International Studies
Quarterly, 57, 492–504.
Hansen, G., & Wernerfelt, B. (1989). Determinants of firm performance: The relative
importance of economic and organizational factors. Strategic Management Journal,
10(5), 399–411.
Hansmann, H., & Kraakman, R. (2004). The end of history for corporate law. In J. N.
Gordon, & M. J. Roe (Eds.). Convergence and persistence in corporate governance (pp.
33–68). Cambridge: Cambridge University Press.
Harrison, A. E., Lin, J. Y., & Xu, L. C. (2014). Explaining Africa’s (dis) advantage. World
Development, 63, 59–77.
Haxhi, I., & Aguilera, R. V. (2017). An institutional configurational approach to crossnational diversity in corporate governance. Journal of Management Studies, 54(3),
261–303.
He, X., Brouthers, K. D., & Filatotchev, I. (2013). Resource-based and institutional perspectives on export channel selection and export performance. Journal of
Management, 39(1), 27–47.
Hennart, J. F. (2009). Down with MNE-centric theories! Market entry and expansion as
the bundling of MNE and local assets. Journal of International Business Studies, 40(9),
1432–1454.
Hennart, J. F. (2012). Emerging market multinationals and the theory of the multinational enterprise. Global Strategy Journal, 2(3), 168–187.
Hoskisson, R. E., Wright, M., Filatotchev, I., & Peng, M. W. (2013). Emerging multinationals from mid-range economies: The influence of institutions and factor markets. Journal of Management Studies, 50(7), 1295–1321.
Hotho, J. J. (2014). From typology to taxonomy: A configurational analysis of national
business systems and their explanatory power. Organization Studies, 35(5), 671–702.
Howell, C. (2003). Varieties of capitalism: And then there was one? Comparative Politics,
36(1), 103–124.
Iannotta, M., Gatti, M., & Huse, M. (2016). Institutional complementarities and gender
diversity on boards: A configurational approach. Corporate Governance: An
International Review, 24(4), 406–427.
Jensen, N. M., Li, Q., & Rahman, A. (2010). Understanding corruption and firm responses
in cross-national firm-level surveys. Journal of International Business Studies, 41(9),
1481–1504.
Judge, W. Q., Fainshmidt, S., & Brown, J. L., III (2014). Which model of capitalism best
delivers both wealth and equality? Journal of International Business Studies, 45(4),
363–386.
Kafouros, M., & Aliyev, M. (2016). Institutional development and firm profitability in
transition economies. Journal of World Business, 51(3), 369–378.
Khanna, T., & Palepu, K. (1999). The right way to restructure conglomerates in emerging
markets. Harvard Business Review, 77, 125–135.
Khanna, T., & Palepu, K. G. (2010). Winning in emerging markets: A road map for strategy
and execution. Harvard Business Press.
Kingsley, A. F., Noordewier, T. G., & Bergh, R. G. V. (2017). Overstating and understating
interaction results in international business research. Journal of World Business, 52(2),
286–295.
Koopmans, T. C., & Montias, J. M. (1971). On the description and comparison of economic systems. In A. Eckstein (Ed.). Comparison of economic systems (pp. 27–78). .
Kornai, J. (1992). The socialist system: The political economy of communism. Oxford: Oxford
University Press.
Lazonick, W., & O'Sullivan, M. (2000). Maximizing shareholder value: A new ideology for
corporate governance. Economy and Society, 29(1), 13–35.
Levy, D., & Pert, S. (2008). Socialist calculation debate. In S. Durlauf, & L. E. Blume (Eds.).
The new palgrave dictionary of economics(2nd ed.). .
Makino, S., & Neupert, K. E. (2000). National culture, transaction costs, and the choice
between joint venture and wholly owned subsidiary. Journal of International Business
Studies, 31(4), 705–713.
Makino, S., Isobe, T., & Chan, C. M. (2004). Does country matter? Strategic Management
Journal, 25(10), 1027–1043.
Mathews, J. A. (2006). Dragon multinationals: New players in 21st century globalization.
Asia Pacific Journal of Management, 23(1), 5–27.
Meyer, K. E., & Sinani, E. (2009). When and where does foreign direct investment generate positive spillovers? A meta-analysis. Journal of International Business Studies,
40(7), 1075–1094.
Meyer, K. E., Estrin, S., Bhaumik, S. K., & Peng, M. W. (2009). Institutions, resources, and
entry strategies in emerging economies. Strategic Management Journal, 30(1), 61–80.
Meyer, K. E. (2015). What is ‘strategic asset seeking FDI’? The Multinational Business
Review, 23(1), 57–66.
Mitton, T. (2016). The wealth of subnations: Geography, institutions: And within-country
development. Journal of Development Economics, 118, 88–111.
Moen (1999). The relationship between firm size, competitive advantages and export
performance revisited. International Small Business Journal, 18(1), 53–72.
Morck, R. (2010). The riddle of the great pyramids. In A. M. Colpan, T. Hikino, & J. R.
203–221.
Carney, M., Gedajlovic, E., & Yang, X. (2009). Varieties of Asian capitalism: Toward an
institutional theory of Asian enterprise. Asia Pacific Journal of Management, 26(3),
361–380.
Carney, M., Van Essen, M., Estrin, S., & Shapiro, D. (2018). Business groups reconsidered:
Beyond paragons and parasites. Academy of Management Perspectives [in press].
Carney, M., Duran, P., van Essen, M., & Shapiro, D. (2017). Family firms and national
competitiveness: Does family firm prevalence matter? Journal of Family Business
Strategy, 8(3), 123–136.
Carney, M., Van Essen, M., Estrin, S., & Shapiro, D. (2017). Business group prevalence and
impact across countries and over time: What can we learn from the literature?
Multinational Business Review, 25(1), 52–76.
Caves, R. E. (1996). Multinational enterprise and economic analysis. Cambridge: Cambridge
University Press.
Cernat, L. (2006). Europeanization, varieties of capitalism and economic performance in
Central and Eastern Europe. Basingstoke: Palgrave Macmillan.
Chen, V. Z., Li, J., & Shapiro, D. M. (2011). Are OECD-prescribed good corporate governance practices really good in an emerging economy? Asia Pacific Journal of
Management, 28(1), 115–138.
Chen, V. Z., Li, J., Shapiro, D. M., & Zhang, X. (2014). Ownership structure and innovation: An emerging market perspective. Asia Pacific Journal of Management, 31(1),
1–24.
Collier, P. (2007). The bottom billion. Oxford: Oxford University Press.
Cuervo-Cazurra, A., & Genc, M. (2008). Transforming disadvantages into advantages:
Developing-country MNEs in the least developed countries. Journal of International
Business Studies, 39(6), 957–979.
Cuervo-Cazurra, A. (2016). Corruption in international business. Journal of World
Business, 51(1), 35–49.
Davies, S., & Lyons, B. (1991). Characterising relative performance: The productivity
advantages of foreign-owned firms in the UK. Oxford Economic Papers, 43(4),
584–595.
Douma, S., George, R., & Kabir, R. (2006). Foreign and domestic ownership, business
groups, and firm performance: Evidence from a large emerging market. Strategic
Management Journal, 27(7), 637–657.
Driffield, N., Mickiewicz, T., & Temouri, Y. (2016). Ownership control of foreign affiliates: A property rights theory perspective. Journal of World Business, 51(6), 965–976.
Dunning, J. H., & Lundan, S. M. (2008a). Multinational enterprises and the global economy.
Cheltenham, UK: Edward Elgar Publishing.
Dunning, J. H., & Lundan, S. M. (2008b). Institutions and the OLI paradigm of the multinational enterprise. Asia Pacific Journal of Management, 25(4), 573–593.
Dunning, J. H. (1988). The eclectic paradigm of international production: A restatement
and some possible extensions. Journal of International Business Studies, 19(1), 1–31.
Eden, L., & Miller, S. R. (2004). Distance matters: Liability of foreignness, institutional
distance and ownership strategy. In M. A. Hitt, & J. Cheng (Eds.). Theories of the
multinational enterprise: Diversity, complexity and relevance (pp. 187–221). Bingley, UK:
Emerald Group Publishing Limited.
Erdener, C., & Shapiro, D. M. (2005). The internationalization of Chinese family enterprises and Dunning's eclectic MNE paradigm. Management and Organization Review,
1(3), 411–436.
Estrin, S., Hanousek, J., Kočenda, E., & Svejnar, J. (2009). The effects of privatization and
ownership in transition economies. Journal of Economic Literature, 47(3), 699–728.
Estrin, S., Meyer, K. E., Nielsen, B. B., & Nielsen, S. (2016). Home country institutions and
the internationalization of state owned enterprises: A cross-country analysis. Journal
of World Business, 51(2), 294–307.
Evans, P. (1995). Embedded autonomy: States and industrial transformation. Princeton, N.J:
Princeton University Press North, D. C. 1990. Institutions, Institutional Change and
Economic Performance. Cambridge: Cambridge University Press.
Fainshmidt, S., Judge, W. Q., Aguilera, R. V., & Smith, A. (2016). Varieties of institutional
systems: A contextual taxonomy of understudied countries. Journal of World Business.
http://dx.doi.org/10.1016/j.jwb.2016.05.003.
Fiss, P. C. (2007). A set-theoretic approach to organizational configurations. Academy of
Management Review, 32(4), 1180–1198.
Fogel, K. (2006). Oligarchic family control, social economic outcomes, and the quality of
government. Journal of International Business Studies, 37(5), 603–622.
Gammeltoft, P., Barnard, H., & Madhok, A. (2010). Emerging multinationals, emerging
theory: Macro-and micro-level perspectives. Journal of International Management,
16(2), 95–101.
Gao, G. Y., Murray, J. Y., Kotabe, M., & Lu, J. (2010). A strategy tripod perspective on
export behavior: Evidence from domestic and foreign firms based in an emerging
economy. Journal of International Business Studies, 41, 377–396.
Gatignon, H., & Anderson, E. (1988). The multinational corporation's degree of control
over foreign subsidiaries: An empirical test of a transaction cost explanation. Journal
of Law, Economics, & Organization, 4(2), 305–336.
Gaur, A. S., Kumar, V., & Sarathy, R. (2011). Liability of foreignness and internationalisation of emerging market firms. In C. G. Asmussen, & T. Pedersen (Eds.).
Dynamics of globalization: Location-Specific advantages or liabilities of foreignness? (pp.
211–233). Bingley, UK: Emerald Group Publishing Limited.
Globerman, S., & Shapiro, D. (2002). Global foreign direct investment flows: The role of
governance infrastructures. World Development, 30(11), 1899–1919.
Grossman, S. J., & Hart, O. D. (1986). The costs and benefits of ownership: A theory of
vertical and lateral integration. Journal of Political Economy, 94(4), 691–719.
Gugler, K., Mueller, D. C., Peev, E., & Segalla, E. (2013). Institutional determinants of
domestic and foreign subsidiaries’ performance. International Review of Law and
Economics, 34, 88–96.
Gugler, K., Peev, E., & Segalla, E. (2013). The internal workings of internal capital
markets: Cross-country evidence. Journal of Corporate Finance, 20, 59–73.
13
Journal of World Business xxx (xxxx) xxx–xxx
M. Carney et al.
Lincoln (Eds.). The oxford handbook of business groups (pp. 602–628). Oxford: Oxford
University Press.
Nölke, A., & Vliegenthart, A. (2009). Enlarging the varieties of capitalism: The emergence
of dependent market economies in East Central Europe. World Politics, 61(4),
670–702.
North, D. C. (1990). Institutions, institutional change and economic performance. Cambridge:
Cambridge University Press.
Ostrom, E. (2009). A general framework for analyzing sustainability of social-ecological
systems. Science, 325(5939), 419–422.
Pajunen, K. (2008). Institutions and inflows of foreign direct investment: A fuzzy-set
analysis. Journal of International Business Studies, 39(4), 652–669.
Peck, J., & Zhang, J. (2013). A variety of capitalism… with Chinese characteristics?
Journal of Economic Geography, 13(3), 357–396.
Peng, M. W., Wang, D. Y., & Jiang, Y. (2008). An institution-based view of international
business strategy: A focus on emerging economies. Journal of International Business
Studies, 39(5), 920–936.
Peng, M. W., Sun, S. L., Pinkham, B., & Chen, H. (2009). The institution-based view as a
third leg for a strategy tripod. Academy of Management Perspectives, 23(3), 63–81.
Peng, M. W. (2012). The global strategy of emerging multinationals from China. Global
Strategy Journal, 2(2), 97–107.
Ramamurti, R. (2009). What have we learned about emerging—market MNEs? In R.
Ramamurti, & J. V. Singh (Eds.). Emerging multinationals in emerging markets (pp. 399–
426). Cambridge: Cambridge University Press.
Ramamurti, R. (2012). What is really different about emerging market multinationals?
Global Strategy Journal, 2(1), 41–47.
Rugman, A. M., & Verbeke, A. (1990). Global corporate strategy and trade policy. London:
Routledge.
Rugman, A. (2009). Theoretical aspects of MNEs from emerging economies. In R.
Ramamurti, & J. V. Singh (Eds.). Emerging multinationals in emerging markets.
Cambridge: Cambridge University Press.
Schneider, M. R., & Paunescu, M. (2012). Changing varieties of capitalism and revealed
comparative advantages from 1990 to 2005: A test of the Hall and Soskice claims.
Socio-Economic Review, 10(4), 731–753.
Schneider, M. R., Schulze-Bentrop, C., & Paunescu, M. (2010). Mapping the institutional
capital of high-tech firms: A fuzzy-set analysis of capitalist variety and export performance. Journal of International Business Studies, 41(2), 246–266.
Schneider, B. R. (2009). Hierarchical market economies and varieties of capitalism in
Latin America. Journal of Latin A...
Purchase answer to see full
attachment