Home Country Environment and the Internationalization-Performance Relationship
The international performance of MNEs from emerging versus developed home markets and the effect of R&D intensity
Master Thesis MSc in Business Administration – International Management Track University of Amsterdam
Inge Kodden 10871330
Supervisor: Dr. L.E.D. DiVito
Second reader: Dr. M.K. Westermann-Behaylo
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Statement of Originality
This document is written by Inge Kodden, who declares to take full responsibility for the contents of this document.
I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it. The Faculty of Economics and Business is responsible solely for the supervision of completion of
Abstract
Although many scholars studied the existence of the Internationalization and Performance (I-P) relationship, the influence of a multinational enterprise’s (MNE) Home Country Environment is understudied. R&D Intensity was previously found to moderate the I-P relationship, but its potential moderating role via the MNE’s Home Country Environment moderation effect is unclear. Prior research suggests Emerging Market (EM) MNEs benefit more from internationalization and a focus on R&D than Developed Market (DM) MNEs because of 1) their potential to learn from established actors in the global market; 2) their higher flexibility resulting from more risky home country institutional environments. A quantitative database study is performed to research the moderation-moderation effect of Home Country Environment (EM vs. DM) and R&D intensity on the I-P Relationship. Results show Home Country Environment moderates the I-P relationship. The moderation effect for R&D intensity was not significant, although interaction effects indicate low-medium R&D intensity minimizes the differences in performance between EM and DM MNEs. The results contribute to International Business literature by mapping predictors of MNE success. Furthermore, the results contribute to institutional theory by showing isomorphism in informal institutional values between both markets, indicating home country formal institutional risk is a better predictor for MNE international performance.
Key words: Internationalization, Performance, Home Country Environment, R&D Intensity, Institutional Theory, Formal Institutions, Informal Institutions
Table of Contents
Abstract ... 2" List of tables and figures ... 5" 1. Introduction ... 6" 2. Literature review ... 10" 2.1 Internationalization drivers, costs and benefits ... 10"
2.2 The Internationalization and Performance relationship ... 15"
2.2.1 The moderating effect of R&D intensity ... 17" 2.2.2 Integrating perspectives ... 18" 2.3 Home country environment and the I-P relationship ... 19"
2.3.1 Institutional context ... 19" 2.3.1.1 Formal institutions ... 20" 2.3.1.2 Informal institutions ... 23" 2.4 Market types ... 25"
2.4.1.1 Developed market MNEs ... 25" 2.4.1.2 Emerging market MNEs ... 26" 2.4.1.3 Internationalization-Performance assumptions for EM versus DM MNEs ... 26" 2.5 Conceptual Framework and Hypotheses ... 28"
3. Methodology ... 31" 3.1 Research design ... 31"
3.1.1 Validity and reliability ... 31" 3.1.2 Sample ... 32" 3.1.3 Variables and measures ... 33"
3.1.3 Data analysis ... 36" 4. Results ... 41" 5. Discussion ... 47" 6. Conclusion ... 51" References ... 53" " "
List of tables and figures
Figure 1 Multinationality and Performance: a Three-Phase Model 17
Figure 2 Conceptual Framework 30
Table 1 Average firm size in net sales 32
Table 2 Variable definitions 35
Table 3 Means, Standard Deviations, Correlations 38
Table 4 DM MNE home countries and institutional values 39
Table 5 EM MNE home countries and institutional values 40
Table 6 Hierarchical Regression Analysis I 41
Table 7 Hierarchical Regression Analysis II 42
Table 8 Moderation-Moderation Analysis 44
Figure 3 Moderation effect of Market Type 45
1. Introduction
Multinational enterprises (MNEs) compete in the global market through their international network of subsidiaries and partnerships. The decision to internationalize into a foreign market is one of their most significant strategic decisions (Arregle, Miller, Hitt & Beamish, 2013; Hitt, Hoskisson & Kim, 1997). As a result, the relationship between an MNE’s level of internationalization and performance (I-P) has received ample academic attention (i.a. Bausch & Kist, 2007; Rugman & Oh, 2010; Arregle, Miller, Hitt & Beamish, 2013; Musteen, Datta & Francis, 2014). There is consensus in International Business literature on the existence of a relationship between Internationalization and Performance. Results on the direction and strength of the relationship are inconclusive, however, with different studies finding support for completely contradicting relationships based on different theoretical perspectives (Ruigrok & Wagner, 2003; Capar & Kotabe, 2003; Contractor, Kundu & Hsu, 2003).
One of these perspectives stresses the importance of institutional differences. Scholars solely studying the firm level of analysis neglect home country level institutional influences that have been found to significantly influence a firm’s international performance (Peng, 2002; 2009). Markets are not completely integrated or completely isolated, a result of different institutional rules and regulations (Ghemawat, 2003). Studies that do consider location specific institutional factors focus either on firms from developed markets or on firms from emerging markets (Douglas & Eden, 2004; Kumar & Singh, 2008; Luo & Tung, 2007). Surprisingly little attention has been given to the distinctive differences between firms from these market types in relation to internationalization and firm performance, and thus the potential role of the home country institutional environment in influencing successful internationalization. Even if a sample consists of firms from different market types, the difference between firms from emerging versus developed markets is not addressed (e.g.
Palich, Carini & Searman, 2000; Elango & Sethi, 2007). The importance of research on the home country environment effect was confirmed by the meta analytical studies conducted by Bausch and Kist (2007) and Marano et al. (2016), that found a more modest positive I-P relationship for EM MNEs compared to DM MNEs.
Furthermore, firm level assumptions of international business are designed to explain DM MNE activity but do not always apply to EM MNE behavior (Luo & Tung, 2007; Marano et al., 2016). Take for example the moderation effect of R&D Intensity on the I-P relationship: high R&D Intensity was found to moderate the I-P relationship (Lu & Beamish, 2004; Kotabe, Srinivasan & Aulakh, 2002; Musteen, Datta & Francis, 2014). Studies on the EM MNE’s internationalization process indicate successful internationalization is even highly dependent on a focus on technological innovation (Luo & Tung, 2007; Musteen et al., 2014 Purkayastha, Manolova & Edelman, 2016; Hsu, Lien & Chen, 2015). EM MNEs can learn from established market firms, creating the opportunity of using the DM MNEs’ experience as a springboard to successful rapid internationalization (Luo & Tung, 2007).
More research is required specifically to map the moderating effect of home country environment and R&D intensity on MNE performance at different levels of internationalization (Lu & Beamish, 2004; Marano et al., 2016; Bausch & Kist, 2007). The study’s main contribution thus will not be proving the existence of the I-P relationship itself, nor is it to add to the debate on its shape and direction. This thesis’ primary goal is to fill the gap in IB research by examining and comparing the effects of firm level and country level influences on the I-P relationship for firms from developed versus emerging markets (as categorized by the United Nations Trade and Development Report). The research question is:
“What is the effect of home country environment and R&D intensity on the internationalization and performance relationship for firms from developed versus emerging countries?”
The sample consists of 600 MNEs from developed and emerging markets collected from the UNCTAD Trade and Development Reports over a three-year period to account for temporal influences (2010-2012). After accounting for missing data and inactive firms, the sample consists of 422 data entries in total. The assumed relationship between variables is a moderation-moderation effect of the moderator R&D intensity on the moderator home country environment for the I-P relationship. The three-way interaction is tested by multiple regression analysis, more specifically by using Hayes’ (2012) PROCESS tool for SPSS.
The overall I-P relationship was negative. The home country environment was found to moderate the Internationalization and Performance relationship, with EM MNEs generally benefitting more from internationalization than DM MNEs. R&D intensity did not appear as a statistically significantly moderator in this three-way interaction model. Inspection of the Johnson-Neyman scores indicated low to medium R&D intensity minimizes the differences between EM and DM MNE performance. This study’s main contribution to literature is that it proofs the moderating effect of Home Country Environment on the I-P relationship, showing the considerably higher performance potential of internationalization for EM MNEs compared to DM MNEs. Additionally, the study finds that informal institutional values are almost the same for EM versus DM countries while formal institutional values differ greatly. This indicates that home country formal institutional risk is a better predictor of international performance.
First, the literature review lays the foundation for this thesis by offering the detailed theoretical background for the empirical study. Core concepts and their relation as studied in previous research are reviewed, resulting in the theoretical framework on which the research question hypotheses are based. The quantitative data and research methodology are described in chapter three. In chapter four, the results of the statistical analysis are provided and the applied models are specified. Also, the result discussion includes a short discussion on the
limitations of the data and the performed analyses. In the following chapter the significance of the findings is discussed and the answer to the research question is provided, as well as the study’s implications to the academic debate. Finally, chapter six concludes this thesis by summarizing the highlights and the key research contributions.
2. Literature review
The following literature review forms the foundation of this study by reviewing how core concepts have previously been found to be related. In the next section (2.1) a review of existing theories on the drivers, costs and benefits of internationalization follows. The basic considerations for internationalization decisions are defined here, setting the stage for a more critical review of the current status of the literature on the I-P relationship specifically in Section 2.2. In this section, the way the advantages and risks of internationalization have been found to impact MNE performance are addressed and compared, and the moderating effect of R&D Intensity is specified. In section 2.3 the current status in academic literature regarding the moderating influence of home country environment on the I-P relationship will be discussed. In the same section, R&D intensity will be defined in relation to the home country environment – specifically its potential moderating effect on EM versus DM MNE performance. In 2.4, finally, the review ends with the conceptual framework of the thesis and hypotheses.
2.1 Internationalization drivers, costs and benefits
Firms internationalize by entering foreign markets and conducting parts of their business across borders (Hitt, Hoskissen & Kim, 1997). The general motive is to exploit market imperfections and to generate economies of scope and scale. To exploit market imperfections and be successful internationally, firms have to be able to deploy their capabilities across different contexts. Firms base their entry decision on coordination costs of the entire network and costs of operating in the foreign market versus the benefits that accessing the new market bring, for example the opportunity to access resources (Dunning, 2000; 2001).
Classic IB theory holds that internationalization impacts performance positively when MNEs are able to recombine their Firm Specific Advantages (FSAs) with foreign Country Specific Advantages (CSAs) (i.a. Rugman & Verbeke, 1992; Birkinshaw, Hood & Jonsson, 1998; Rugman, Verbeke & Nguyen, 2011). FSAs are defined as specific capabilities of a firm, for example proprietary know-how and optimal coordination and control mechanisms. Consider, for example, a firm that has the specific technological capabilities to offer a good or service with improved durability vis-à-vis competitors: it has a competitive advantage compared to other firms in the same market. CSAs, on the other hand, are not tied to a firm but to the MNE’s home country or host country. Different locations bring different advantages and risks - from knowledge spillovers due to proximity to other firms, to differences in government regulation (Rugman & Verbeke, 1992). Firms therefore aim for a fit between their own capabilities and the potential risks and advantages of a host country when considering internationalization to drive performance and minimize costs of internationalization. In other words, firms aim to exploit market imperfections by redeploying and recombining FSAs in multiple countries (Rugman & Verbeke, 1992). IB scholars generally agree on the basic drivers of internationalization. The considerations for operating internationally, however, can be divided into two main perspectives: the internalization theory (Dunning, 2000; 2001) and the Uppsala model (Johansson & Vahlne, 1990; 2013).
2.1.1 Internationalization: OLI advantages and experiential learning
An MNE can in theory chose to expand in any market it seems fit. Foreign market entry enables a firm to gain access to resources outside of the home market environment, creating the opportunity of improving its competitive advantage. Dunning’s (2000; 2013) eclectic paradigm specifically points out three motives for internationalization, also referred to as OLI advantages: 1) Ownership advantages; 2) Location advantages, and; 3) Internalization
advantages (Rugman et al., 2011) Ownership advantages include tangible and intangible assets, but also transactional variables that come from benefiting from operating and geographically dispersed network. Location advantages, or CSAs, influence the location decision of MNEs. Specific countries have CSAs that are a better fit with the firm’s FSAs or goals than others, making some countries more attractive than others. Internalization advantages relate to the advantages of recombining FSAs internally as compared to dealing with external parties via contractual arrangements (Dunning, 2000; 2001; Rugman et al., 2011). Dunning’s (2000; 2001) theory falls in the wider stream of theory called ‘internalization theory’, which focuses on the costs and advantages related to internalizing business processes through FDI compared to other entry modes in international markets. Four accepted FDI motives based on Dunning’s (2000; 2001) eclectic paradigm are:
1. Market seeking: to satisfy specific foreign markets; 2. Resource seeking: to gain access to natural resources;
3. Efficiency seeking: to more efficiently organize the division of labor or specialization of the existing portfolio of foreign and domestic assets;
4. Strategic asset seeking: to make optimal use of, and protect, the O-specific advantages and to reduce the advantages of competitors (Dunning, 2000). These four motives imply internationalization decisions are made step-by-step and assessed per host country environment. Other authors like Johansson and Vahlne (1990; 2013) take on a process view on internationalization and argue decisions are interrelated. Johansson and Vahlne (1990; 2013) agree with internalization theory that firms will internationalize into markets that are relatively familiar to the home market, since risk and thus costs will be lower. Over time, however, firms will invest in more foreign environments in terms of geographic, cultural and institutional distance. Instead of the driving force being related to one or more of the OLI advantages, the driving force for internationalization
decisions is considered to be ‘experiential market knowledge’ in their Uppsala model (Johansson & Vahlne, 1990; 2013). The strategic assets seeking driver of Dunning (2000; 2001) is strikingly similar to the experiential market knowledge driver: both of these drivers revolve around learning and improving the MNEs position by partnering with parties in the new business environment. The difference is, again, that the strategic asset seeking driver assumes it as an advantage of a specific internalization decision whereas the experiential market knowledge drives assumes it is the basis of all internationalization decisions of an MNE.
As MNEs learn from their environment, new growth opportunities open up and thus their potential next step in the internationalization process. Whether the costs outweigh the benefits of entering a market through FDI cannot be determined solely up front according to this process view on internationalization. The potential benefits of the learning experience should be considered as well. MNEs operate as part of a network and are dependent on their environment. Not only are products and goods exchanged in (international) business, knowledge and information also flow between the parties of the entire business network (Johansson & Vahlne, 1990; 2013). The MNE has to learn to operate in the new environment, however, and build relationships to tap into the existing body of knowledge. If a market is more foreign, Dunning (2000; 2001) would argue FDI is less likely as it becomes more complex for an MNE to leverage its FSAs effectively to reach OLI advantages. Johansson and Vahlne (1990; 2013) look beyond CSAs and FSAs, emphasizing the importance of the process of internationalization and the network a firm can gain access to. After a firm is familiar with the foreign business network and has established relationships, it can leverage that experience and use it in new environments. Knowledge spillovers and information externalities explain the spatial agglomeration of MNEs (Mariotti, Pscitello & Elia, 2010). The potential knowledge inflow is balanced with the potential knowledge outflow, resulting
in the decision to either join the agglomeration or not. Firms operating in similar environments tend to have access to similar knowledge and information, which explains isomorphism in international business activity.
Internalization theorists argue the decision to internationalize through FDI should depend on the OLI advantages outweighing the benefits of other entry modes (e.g exports or joint ventures) (Dunning, 2000; 2011; Rugman et al., 2011). Other authors argue the decision depends on the market knowledge, which influence the costs of internationalization into a specific market (Zaheer, 1995; Lu & Beamish, 2004; Rugman & Verbeke, 2012). Costs of internationalization are argued to come from a lack of knowledge and information on how to operate in the foreign environment compared to operating in known environments. Three core concepts of internationalization costs are Liability of Foreigness (LoF), Liability of Newness (LoN) and coordination costs (Zaheer, 1995; Lu & Beamish, 2004; Contractor, Kumar & Kundu, 2007; Rugman & Verbeke, 2012; Joardar, Kostova & Wu, 2014).
Liability of Foreigness (LoF) stems from differences in conducting business in the foreign environment, specifically political, economic and cultural differences (Zaheer, 1995; Rugman & Verbeke, 2012). From an institutional perspective, LoF comes from the MNE’s “lack of isomorphism with the host-country’s environment” (Sethi & Judge, 2009). This lack of isomorphism makes the firm vulnerable to institutional pressures, incurring additional costs compared to home country MNEs. Section 2.3.1 offers a more elaborate review on institutional context. Liability of Newness (LoN) comes from the initial costs an MNE incurs by entering the foreign market and setting up its organization in the new environment. The start-up costs from LoN are completely mitigated over time, whereas LoF merely decreases over time as an MNE learns the rules of the game and gets more experience in the context (Vermeulen & Barkema, 2002; Rabiosi & Santangelo, 2013). Finally, coordination costs are those costs a firm incurs to manage its network of foreign assets. The larger the international
network, the harder it will be to know what is going on in different units of the company and for the different units to be on the same page. The increase of international units increases coordination costs, which can exceed the benefits of internationalization (Hitt, Hoskissen & Kim; 1997). At the same time, internationalization enables firms to spread risks over different countries and thus reduce fluctuations in revenue (Lu & Beamish, 2004). Operating in multiple contexts also enables an MNE to learn from operating in different contexts, and different organizational units can contribute its knowledge base by sharing best practices from all over the globe (Zahra, Ireland & Hitt, 2000; Lu & Beamish, 2004).
Classic (OLI) motivations for an MNE to identify the right market might play a crucial role in determining the host country, but liabilities change over time due to experience in international markets (Johansson & Vahlne, 1990; 2013; Dunning, 2000; 2001; Rugman, 2011; Lu & Beamish, 2004). This suggests there is an optimal point of the number of foreign compared to total operations (the level of internationalization) - after liabilities diminish and before internationalization costs outweigh the benefits. This is the focus of the next section: a review of the literature on the I-P relationship.
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2.2 The Internationalization and Performance relationship
Studies on the internationalization and performance (I-P) relationship found support for different shapes. Support has been found for a positive linear relationship (Bausch & Kist, 2007; Marano et al., 2016), an (inverted) U-curved relationship (Lu & Beamish, 2001; Ruigrok & Wagner, 2003; Capar & Kotabe, 2003), and for an S-curved relationship (Contractor, Kundu & Hsu, 2003; Lu & Beamish, 2004). Studies finding a positive linear relationship all focused on the benefits of internationalization, e.g. the access to new markets, resources, knowledge opportunities et cetera. Critics of this approach argue it simplifies international business activity, since it ignores its complexity and therefore part of the costs of internationalization (Cardinal, Miller & Palich, 2011). The U-shaped relationship studies do
include a balance between both the costs and benefits of internationalization and how their impact differs over time. Time is the key word in these studies, where the benefits and costs of internationalization impacting performance are researched over a longer period. The benefits of internationalization are more likely to outweigh the costs in the long term (Douglas, 2004). As MNEs learn to navigate new contexts, their costs of internationalization lower and performance is impacted positively. International market experience has thus been found to impact performance, in line with Johansson and Vahlne’s process view (1990; 2013). Still, studies found support for both an U-shaped as well as an inverted U-shaped relationship: complete opposites. Proponents of the inverted U-shaped relationship argue that the costs of internationalization can exceed its benefits when the international network becomes too large. The costs of coordinating the international network exceed the benefits, implying only moderate levels of internationalization result in positive performance (Lu & Beamish, 2001). The argument makes sense, but does not explain why a polar opposite relationship has been found as well.
An important reason for the different results lies in the period in which firms are studied. Studying a longer period of time allows for capturing different stages of internationalization and showing how different levels of internationalization impact performance differently over time. Lu and Beamish (2004) were able to integrate the U-shaped and inverted U-U-shaped relationships into one S-curved relationship. Their large sample of Japanese firms was studied over a ten-year period, ensuring it captured firms in all stages of internationalization. The S-curved relationship essentially combines the U-curved and inverted U-curved relationships into one three-stage model (figure 1), making a convincing argument for its existence. In the first phase of internationalization, firms experience more costs than benefits. LoF, LoN and coordination costs outweigh the returns. In phase 2, however, the benefits of internationalization outweigh the costs. LoN lowers as a firm
establishes its operation in the new environment, just as LoF lowers due to learning to operate in the new environment. When a firm over-internationalizes, phase 3, the coordination costs become too high for a firm to effectively manage its international network. In that phase, the performance goes down and the relationship becomes negative (Lu & Beamish, 2004).
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2.2.1 The moderating effect of R&D intensity
In this model, R&D intensity had a positive moderating influence on the I-P relationship (Lu & Beamish, 2004). R&D intensity is defined as a firm’s focus on technological innovation (Kotabe, Srinivasan & Aulakh, 2002; Musteen, Datta & Francis, 2014). International business scholars found high R&D intensity drives performance for MNEs in general, since it enables a firm to benefit from the latest technological advancements that generally relate to higher efficiency and thus higher returns over time. Firms investing heavily in R&D capabilities can for example generate efficient procedures in managing the international network. Although initial investment is required, the procedure can in time be
Figure 1. Multinationality and Performance: A Three-Phase Model. From: Lu & Beamish (2004; 600)
implemented throughout the network. Technological assets can generally be deployed across markets without significant value depreciation, therefore becoming an important source of potential significant competitive advantage (Luo & Tung, 2007; Kotabe et al., 2002; Musteen et al., 2014). Moreover, high R&D intensity is positively related to internationalization itself (Purkayastha, Manolova & Edelman, 2016; Hsu, Lien & Chen, 2015). It means that R&D intensity does not only influence the I-P relationship, but that firms with high R&D Intensity tend to be more internationalized. This is not surprising considering high R&D investment pays off the most for firms being able to implement their technological innovations throughout their international network.
2.2.2 Integrating perspectives
The inconclusive results on the shape and direction of the I-P relationship are addressed by Lu and Beamish (2004) study that integrated different views by taking a process view on internationalization. The different stages of internationalization create a picture that is consistent with classic IB literature regarding LoF, LoN and coordination costs. The moderating effect of R&D intensity was supported in Lu and Beamish’ (2004) study. Still, their sample brings up some concerns and with that, opportunities for further research. The study was based on a large sample, but studied firms from one country only (Japan). As Lu and Beamish (2004) point out in their article, this brings up the concern that the findings might be country specific. The assumptions underlying their study are clearly focused on developed markets and might not apply to emerging market environments. Moreover, the study does not consider the influence of the institutional environment at all. A comparative study looking into international firms from different type of home markets and considering the impact of their home country environment is thus a relevant addition to academic research on the I-P relationship.
2.3 Home country environment and the I-P relationship
The advantages and risks of internationalization outlined above apply to developed markets, studied heavily over the past decades. Recent studies suggest there are significant differences in the drivers, costs and risks of internationalization for MNEs from developed versus emerging markets (Johansson & Vahlne, 2013; Musteen, Datta & Francis, 2014; De Clerq, Zhou & Wu, 2014). The home country environment, also referred to as country of origin, has been found to influence the MNE’s international strategy and its international performance. Just like a host country’s CSAs, the home country’s CSAs enable a firm to access certain resources. The next section reviews the impact of home country environment in relation to internationalization and performance. First, the potential impact of the institutional context is discussed in 2.3.1. Then, contemporary academic theories on formal and informal institutions are reviewed in sections 2.3.1.1 and 2.3.1.2. Finally, the characteristics of developed markets (2.3.1.1) and emerging markets (2.3.1.2) and their implications for international business activity are reviewed.
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2.3.1 Institutional context
The Institution Based View (IBV) in international business holds that institutions influence the differences in performance of firms, besides industry differences and differences in resources (Peng, 2002). Home country environments have been found to shape firm’s strategies, specifically as access to home country CSAs can be linked to an MNE’s FSAs (Peng, 2002; Marano et al., 2016). The institutional environment shapes interaction in a certain context, defined by Peng as “the set of fundamental political, social and legal ground rules that establish the basis for production, exchange and distribution” (2002; 252; North, 1990). The political and legal ground rules can be categorized as the formal institutional context, whereas the social ground rules fall under the informal context (see sections 2.3.1.1 & 2.3.1.2). Home country institutions can reduce uncertainty and enable efficiency,
effectively influencing the costs of doing business abroad and therefore directly influencing a firm’s performance. Different institutional environments have clear implications for MNEs: firms have to adjust to differences in government regulations, political structures and social norms to be able to operate internationally.
The influence of home country environments has not been studied in depth in relation to the I-P relationship, besides Marano et al.’s recent study on home country effects. A modest positive I-P relationship was found when taking country of origin effects into account, defined as differences in institutional context. Section 2.3.1.1 and 2.3.1.2 zoom in on the formal institutions and informal institutions that shape the rules of the game of a certain environment. Marano et al. (2016) did not, however, make a specific distinction between market type in their study.
2.3.1.1 Formal institutions
The formal institutional environment is made explicit through codified rules, laws and regulations, and through the political structure of a society (North, 1990; Peng, 2002). It can provide firms with a stable foundation via rules that make it easier to start and operate a business, and with political structures that make it easier for firms to make long term decisions.
In contexts with underdeveloped formal institutions, rules are not codified or change frequently (Peng, 2009). Developed formal institutions indicate a stable business environment and thus minimize risk of operating in that environment, whereas underdeveloped formal institutions imply higher uncertainty and risk. This view is quite biased, however. Underdeveloped formal institutions might imply higher uncertainty and risk for firms from contexts with developed formal institutions, while firms that are from these contexts experience the ‘stable’ environments to be more risky. Where some authors relate weak home
country formal institutions to lower competitiveness (Porter, 1990), others indicate firms from these contexts are simply used to more politically risky environments (Chacar, Newburry, & Vissa, 2010). It does not mean they are less competitive, but rather that firms from contexts with weak formal institutions will have developed capabilities to navigate it successfully.
Business regulations can still make it easier for firms to start up and operate a business, for example through antitrust regulations and contract enforcement (Chacar et al., 2010). In environments with weak business regulations, it is more complex to start up a business and it will be less clear how to navigate the system. Marano et al. (2016) point to two perspectives regarding the impact of business regulations, similar to the discussion above on the impact of strong and weak formal institutions. The first perspective holds that strong business regulations positively moderate the I-P relationship, while the second perspective expects strong business regulations to negatively moderate the I-P relationship (Marano et al., 2016). Scholars arguing for the first perspective assume strong business regulations reduce uncertainty and create a stable business environment (Chacar et al, 2010; Wan & Hoskisson, 2003). Opportunistic behavior is minimized, and a stronger national economy offers firms better access to resources (Marano et al., 2016). Studies following the second perspective argue that firms develop coping mechanisms when faced with weak business regulations, enabling them to deploy these skills across markets. This skill itself can become an FSA, creating a potential competitive advantage compared to firms from countries with strong formal institutions (Luo & Tung, 2007; Marano et al., 2016).
Besides business regulation, research indicates the political structure of a country can influence the I-P relationship (Wan & Hoskisson, 2003; Stevens, Xie & Peng, 2015). Similar to the effect of business regulation, more transparent political systems offer a stable home environment for MNEs to build their international network from (Wan & Hoskisson, 2003). Others add that the political structure is the way governments establish the rules and standards
that shape the nature of the political process, especially concerning how power is distributed and which stakeholders are allowed to participate in the system (Holmes, Miller, Hitt & Paz Salmador, 2012). Autocratic regimes create an uncertain environment and involve less stakeholders, resulting in higher uncertainty and thus a more risky business environment.
Two approaches are dominant in research into political risk according to Stevens et al. (2015): 1) the bargaining power approach (BPA); and 2) the political institutions approach (PIA). The bargaining power approach focuses on the balance between the bargaining power of the firm and the government. Political risk associated with BPA stems from the erosion of the bargaining power of the firm over time, as its investment into the country pave the way for other actors (Boddewyn, 2016). The MNEs power to stop the initial bargain from changing goes down, resulting in an increase of political risk (Stevens et al., 2015). In other words, political risk increases from the moment resources are committed and the MNE has set up its organization in the country. The PIA focuses on “the degree of checks and balances in a country’s political institutions” (Stevens et al., 2015; 1). This approach takes on a more structural perspective on political risk. Instead of focusing on a specific MNEs bargaining power, it looks at the reliability of a specific country’s political structure over time. Henisz (2000) argues that governments are inherently tempted to change policies to their advantage. A higher degree of checks and balances in a country’s political structure decreases political risk, since it constrains the governments’ ability to alter existing policies (Stevens et al., 2015; Henisz, 2000).
Wan and Hoskisson (2003) found that firms with headquarters in strong political environments were found to profit more from internationalization than their counterparts from less strong institutional environments. Their argument is that firms from strong political environments have developed the capabilities to participate in the political structure, since they were offered a chair at the table. Firms from countries with weaker political structures
have developed capabilities to navigate the complex environment and were likely able to generate competitive advantage through leveraging them. These are location-bound capabilities, however, specific to that political structure (Wann & Hoskisson, 2003; Marano et al., 2016). Other authors argue unpredictable political systems force firms to develop coping mechanisms to navigate complex institutional contexts. These skills enable firms to manage the challenges they face in foreign operations as well (Elango & Sethi, 2007). This perspective focuses on the positive impact of weak home country institutions on MNE internationalization, and thus expects home country political risk to positively moderate the I-P relationship.
2.3.1.2 Informal institutions
The informal institutional environment is formed by the shared norms that guide accepted behaviors in a certain context. Where formal constraints fail, the informal constraints will take over to establish ‘a way of doing things around here’ (North, 1990). The values and norms in a country are embedded in its culture (Hofstede, 1994; Caprar, Devinney, Kirkman & Caligiuri, 2015). Culture provides a long-term measure of informal institutions and is the basis for the development of formal institutions (Holmes et al., 2013). Culture informs the way managers set up their organization and thus operate both on a national and international level (Marano et al., 2016). Previous research identified specific dimensions of culture that influence MNE performance and thus help explain the differences between MNEs from different home country environments (Holmes et al., 2013; Marano et al., 2016; Elango & Sethi, 2007). Various authors found that some cultural gaps are more disruptive than others in international business (Hofstede, 1991; Barkema & Vermeulen, 1998; Shenkar, 2001). Future Orientation and Uncertainty Avoidance are expected to be the most important for
international business, since they translate into different tolerances for risk and formal structures (Shenkar, 2001; Marano et al., 2016)
Future orientation can be related to a focus on either long –term versus short-term outcomes. Higher degrees of future orientation suggest more planning and investing activities that consider long-term outcomes. When a country’s future orientation is low, short-term results will be more important (Hofstede, 1994). When relating future orientation to international business and institutional environment, high degrees of future orientation may encourage firm investments in the country and thus benefit its position in the international market. Furthermore, Marano et al. (2016) argue high degrees of future orientation can impact supply and demand if the country’s investment options are framed as long-term growth opportunities. That way, the country’s long-term perspective turns into a CSA the firm can tap in to.
The degree of uncertainty avoidance has also been found to impact the I-P relationship, since it reflects how well individuals in a country deal with uncertain situations (Hofstede, 1994). Organizations from countries with low degrees of uncertainty avoidance are assumed to be used to dealing with vague situations and thus used to being very flexible: they are open to uncertain outcomes (Venaik & Brewer, 2010). High uncertainty avoidant societies tend to avoid ambiguous situations, on the other hand, which exist more in international cooperation than in domestic cooperation (Venaik & Brewer, 2010; Shenkar, 2001). Thus, firms from high uncertainty avoidant countries prefer rules and regulations that guide their actions, but limit their flexibility. Since international business consists of dealing with unknown environments and adapting to foreign contexts, low flexibility can harm an organization to learn to operate in foreign contexts successfully. Relating this to the experiential market knowledge concept of Johansson and Vahlne (1990; 2013) suggests that low flexibility reduces a firm’s ability to learn from new business behavior in local contexts,
thus negatively impacting performance. Following these authors’ line of argumentation, it can be expected that low uncertainty avoidance in the home country positively moderates international performance.
2.4 Market types
Home country environment was defined in the previous section as a country level concept, but this thesis looks to identify the moderation effect of market types specifically in relation to internationalization and performance. Home country environment is related to market type, as it expected that specific home country environment scores correspond to either developed or emerging markets. The next two sections clarify the assumed characteristics of developed markets (2.4.1.1) and emerging markets in relation to MNE behavior (2.4.1.2), building on Marano et al.’s (2016) work.
2.4.1.1 Developed market MNEs
Developed markets (DM) are characterized by relative economic and social stability, promoting the acceptance of the rules of trade and investment. Additionally, developed market MNEs can usually benefit from more established partnership activity. The structures for business activity are well established and transparent. Moreover, these DM MNEs tend to have better access to resources and are generally better equipped to generate higher financial assets as compared to other market MNEs (Hitt, Dacin, Levitas, Arregle & Borza, 2000). Institutional environments in developed countries are generally more stable, resulting in more predictable business environments. Reduced complexity and uncertainty reduce costs of doing business, offering firms from developed countries a safe platform to build their international network and translate it into higher performance. The general assumptions of international business literature apply to developed markets. Emerging market MNEs, however, might
follow slightly different paths due their institutional differences and opportunity to tap into existing market knowledge.
"
2.4.1.2 Emerging market MNEs
Emerging markets (EM) went through significant structural transformation relatively recently. Their national economies have grown rapidly and are showing promise despite weaker legal systems and volatility compared to developed markets. EM MNEs are defined as “international companies that originated from emerging markets and are engaged in outward FDI, where they exercise effective control and undertake value-adding activities in one or more foreign countries” (Luo & Tung, 2007). Emerging markets are usually smaller compared to developed markets, with a deficit in resources and at considerable distance from major European and North American markets. The generally young nature of the emerging market’s structure in terms of institutions and legal systems means that management capabilities and decision-making processes are not as developed as compared to firms in advanced markets (Hitt et al., 2000; Luo & Tung, 2007, Contractor et al., 2007). Additional EM challenges stem from the rapid changes in economic, political and social institutions, according to Wu (2013). CSAs that firms from the more established developed markets have access to (Wan & Hoskisson, 2003).
2.4.1.3 Internationalization-Performance assumptions for EM versus DM MNEs
Previous studies on EM MNE activity showed that these firms can benefit greatly from international expansion, as the importance of spreading risk over multiple countries enables them to deal with uncertainty of their home country’s CSAs. Luo and Tung (2007) developed the springboard perspective. EM MNEs internationalize to benefit from more developed countries and their firm network and infrastructure. Firms can overcome latecomer
markets (Luo & Tung, 2007). At the same time, it can be argued that the costs of international expansion might be higher due to the lack of access to similar home country. Successful early internationalization from emerging market firms implies gaps in traditional assumptions of experiential learning and internalization theory that both advocate an incremental internationalization process. These firms instead rapidly internationalize successfully, while tradition theory would predict negative performance consequences. Firms from transitioning economies that internationalize into developed economies have the opportunity to tap into the same existing market knowledge as developed firms, which is in line with Dunning’s (2000; 2001) strategic asset seeking and Johansson and Vahlne’s (1990; 2013) experiential market knowledge drivers. In this theory, experiential market knowledge of other firms can be an advantage to new MNEs entering the network. Luo and Tung (2007) found that early internationalization from MNEs from emerging economies is facilitated by a reliance on international networks. The relationship, however, is contingent on technological innovation and a firm’s perceived environmental hostility (Musteen et al., 2014; Luo & Tung, 2007). This contingency is quite logical when considering that EM MNEs offering technologically advanced services or goods will be more in line demand in the global market. Furthermore, consider that EM MNEs tapping in to the international networks need to match their technological know-how with that of DM MNEs to have it be mutually beneficial.
De Clerq et al., (2014) found that internationalization of emerging market MNEs can positively impact their performance. Especially in more turbulent markets, international learning efforts are proven to be essential early on. Turbulent markets and less well-established institutional environments bring unpredictability and uncertainty - thus effectively increasing risk and making it harder for firms to operate in the environment. These theories imply internationalization does not become a driver after a firm has established a network in a few countries, but as soon as possible to spread institutional risk.
The new insights of international business studies pointing out differences between the internationalization of EM and DM MNEs are the foundation of this study. Previous studies of the I-P relationship have assumed relatively similar motivations for internationalization, reflected in the research design. This study expects the home country environment of successfully internationalized MNEs to moderate the I-P relationship,
2.5 Conceptual Framework and Hypotheses
The meta-analytical studies of Marano et al. (2016) and Bausch & Kist (2007) both resulted in significant statistical support for at least a modest positive I-P relationship for both EM and DM MNEs. Therefore, the first hypothesis of this study assumes a positive linear I-P relationship for MNEs from both market types.
Hypothesis 1: The relationship between internationalization and firm performance is positive.
Current academic literature has studied the I-P relationship, but reviewing the literature made clear that the potential country of origin effect was not taken into account. Often a sample consisted of firms from one country or, when more firms from more countries are included, only focusing on firms from developed markets. The limited amount of studies that did examine the I-P relationship in emerging market economies have been found to in turn only focus on those markets, equally not applying the same methods to MNE activity from other type of markets. Therefore, effectively comparing results is difficult. Different studies have used slightly different measures of the main variables, resulting in unreliable cross-study comparison. Marano et al. (2016) found that the strength of the relationship was moderated by the country of origin, resulting in a more modest positive I-P relationship for EM MNEs
compared to DM MNEs. At the same time, the springboard perspective of Luo and Tung (2007) suggests the I-P relationship to be stronger for EM MNEs than traditional IB literature implies as it enables them to tap into the existing network and more stable institutional environment Therefore, this study reviews the potential moderating effect of the Home Country Environment by assuming a more positive I-P relationship for EM MNEs compared to DM MNEs. Hypothesis 2 is formulated as follows:
Hypothesis 2: The relationship between internationalization and firm performance is moderated by the home country environment, displaying a stronger positive effect for EM MNEs compared to DM MNEs.
Following the literature review, a focus on technological assets is related to high performance for both market types. Studies have, again, been inconclusive on the moderating effect of R&D intensity on firm performance. It is usually studied as a separate moderator for the I-P relationship. The literature review suggests, however, that the effect might be different for EM MNEs and DM MNEs. Therefore, R&D intensity is studied as a moderator on the moderation effect of Home Country Environment, resulting in the following two hypotheses:
Hypothesis 3a: The firm’s level of R&D intensity moderates the effect of the home country environment in such a way that high R&D intensity increases MNE performance
Hypothesis 3b: Firms from emerging market environments benefit more from a focus on technological assets, i.e. the moderation effect of R&D intensity is stronger for EM MNEs compared to developed market MNEs.
Figure 2. Conceptual Framework H3a + H3b +/++ H2 +/++ H1 + Performance
! ROA as Net Sales/Total Assets Level of Internationalization
! Foreign Assets/Total Assets ! Foreign Sales/Total Sales ! Foreign Employees/Total
Employees
Home Country Environment ! Emerging Markets vs. Developed Markets
R&D intensity ! R&D Expenditures/Total
3. Methodology
The following chapter outlines the research methodology and design in order to answer the research question. Section 3.1 details the research design in terms of validity and reliability (3.1.1), Sample (3.1.2), Variables and measures (3.1.3) and finally, Data analysis in section 3.1.4
3.1 Research design
The research question will be examined by testing the hypotheses through a quantitative databased research design. This study’s main objective is to test existing theories, thus following deductive reasoning. The total dataset is the result of combining several public databases. The first part consists of the UNCTAD top 100 MNEs for developed country plus the UNCTAD top 100 MNEs for emerging countries annex tables to the Trade and Development Reports of 2010, 2011 and 2012. Company information from the COMPUSTAT WRDS database was added, as well as country level information from the GLOBE project, the Economic Freedom Index of the Heritage Foundation, and the Witold Henisz Political Constraint Index. The specific measures included in the dataset are addressed in relation to the variables in section 3.1.2. A quantitative approach is the preferred way to answer the research question, because it concerns a relationship and impact of variables on that relationship. The results are generalizable, because of the large amount of observations in the sample (n = 419).
3.1.1 Validity and reliability
Validity is the extent to which the measurement method or instrument measures what it is intended to measure (Field, 2013). In the case of this study, validity was increased by several factors. It was based on the research design of previous studies. Two key studies that
form the foundation of this research design are the studies of Lu and Beamish (2004) study and Marano et al. (2016). Building on the findings of these studies means the design was tested and the measurements were proven to be fit for the study’s objective. Furthermore, data checks were performed and appropriate models were chosen based on that, increasing the trustworthiness of the results.
Reliability can be defined as the extent to which a measurement method or instrument leads to the same results when the study is repeated (Field, 2013). The reliability was increased because it is exactly documented which variables, data and methods were used. A repeat study can thus be performed based on the documented results.
3.1.2 Sample
The sample consists of the world’s top 100 non-financial MNEs from developed and emerging countries (UNCTAD 2011; 2012; 2013). Data was collected from the reports over a three-year period from 2010 to 2012 to improve reliability of results. The company information per year was supplemented with financial company information from COMPUSTAT (Wharton Research Data Services) needed to measure performance. The total sample consisted of 600 firms. After correcting for missing values and inactive firms, the sample consists of 422 data points: 197 for developed markets and 225 for emerging markets. The dataset consists of firm and country level measures (see variables section 3.1.2). Table 1 offers an overview of the range in terms of size in net sales of the MNEs in the sample.
Table 1
Average firm size in net sales
Developed Market MNEs Emerging Market MNEs
Small $36.450,85 $13.271,34
Medium $68.013,68 $50.150,84
Previous studies have established there is at least some relationship between Internationalization and Performance. The main objective of this study is to identify potential moderator effects of the home country environment and R&D intensity on the I-P relationship. The sample therefore does not consist non-MNEs versus MNEs as in other studies on the I-P relationship, but only of MNEs to allow for a more detailed inspection of the moderation effect. The companies in the sample are all industrial companies, based on the industry indicator of the COMPUSTAT database. Table 1 offers an overview of the HQ locations of the companies in the sample.
3.1.3 Variables and measures
Internationalization (IV) The independent variable, Internationalizatio, was first measured in three separate ratios: foreign sales to total sales (INTSA), foreign assets to total assets (INTAS), and foreign employees to total employees (INTEMP). A composite measure for internationalization was computed following the method used by Sanders and Carpenter (1998). The sum of the three ratios forms the Internationalization variable, taking a value between 0 and 3. The three measures demonstrated high reliability (α = .827) and the corrected item-total correlations display good correlation with the total score of the scale (all >.30). Furthermore, none of the items would substantially be affected if they were deleted.
Performance (DV) The dependent variable is performance, for which the commonly used measure Return on Assets is computed. ROA was calculated as the ratio of net sales and total assets, following Bertrand and Schoar’s method (2003).
Home country environment moderator Home country environment is measured first of all by market type, measured as a dichotomous, binary variable (EM = 0, DM = 1). The classification is based on the UNCTAD classification of MNEs from developed versus emerging economies. To test whether the market type corresponds to the assumption of
institutional environment of the literature review, measures for formal and informal institutions are included. Formal institutions are measured in two separate variables: Political Constraints and Business Freedom. Political Constraints is defined as “the degree to which the country’s political structures create political risks for firms and investors” (Marano et al., 2016; 1089). The Witold Henisz Political Constraint Index data set (POLCON V) ranges from 0 (most risky) to 1 (most stable) and is time variant. The index was reverse coded (POLCON) so the high values represent more politically risky home country environments. The second measure of formal institutions is Business Freedom, defined as “the extent to which regulatory and infrastructure environments constrain the efficient operation of businesses” (Heritage Foundation, 2017). The data is obtained from the Index of Economic Freedom from the Heritage Foundation. It captures the ease of starting, operating and closing a business within a specific country.The measure is a number between 0 and 1, with 1 indicating the freest business environment and is time variant. This variable is recoded (RBFREE) to have lower valuables represent a more transparent and thus less risky business environment. Informal institutions are captured by two variables: Future Orientation (FUTOR) and Uncertainty Avoidance (UNAVOI). Both measures are obtained via the GLOBE project and are widely used in IB studies. Future Orientation is a time invariant variable and can be defined as “the extent to which individuals engage (and should engage) in future-oriented behaviors such as planning, investing in the future, and delaying gratification” (GLOBE, 2016). Uncertainty Avoidance is also a time invariant variable, defined as “the extent to which a society, organization, or group relies (and should rely) on social norms, rules, and procedures to alleviate unpredictability of future events.” (Globe, 2016). Higher values for both of these measures indicate strong informal institutions, originally measured on a 7 point scale. The scales were divided by 7 to allow for comparison with the formal institutional
measures. The scores take on values between 0 and 1. An overview of the EM and DM MNEs home country institutional values is given in table 4 and 5.
R&D Intensity moderator R&D intensity is calculated by the total R&D expenditures per year divided by the total sales in one year, following Bertran & Schoar’s method (2003). Table 2
Variable Definitions
Variable Definition
DATA_YEAR Reporting year for the company’s financial data (2010, 2011, 2012)
INTEMP A ratio calculated by dividing foreign employees by total employees (0 to 1) INTAS A ratio calculated by dividing foreign assets by total assets (0 to 1)
INTSA A ratio calculated by dividing foreign sales by total sales (0 to 1)
INTTOTAL A composite measure of the combined ratios of INTEMP, INTAS and INTSA. (0 to 3)
ROA Return on Assets, a ratio calculated by dividing net sales by total assets POLCON Political Constraints measure on a 0 to 1 scale as defined by the Witold Henisz
Political Constraint Index data set. Recoded so high values represent high political risk
RBFREE Recoded Business Freedom measure on a 0 to 1 scale. Based on the Index of Economic Freedom from the Heritage Foundation. High values represent higher business risk
FUTOR Future Orientation measure on a 0 to 1 scale as defined by the GLOBE project. High values indicate strong informal institutions
UNAVOI Uncertainty Avoidance measure on a 0 to 1 scale as defined by the GLOBE project. High values indicate strong informal institutions
ECON Market type indicator taking on a 0 for Emerging Markets and 1 for Developed Markets
RDINT R&D Intensity measure, calculated by dividing the R&D expenditures by the total sales
FSIZE Firm size measure as the logarithm of Net Sales
TRADE_HOME The home country's Trade in Goods, a control variable obtained from the World Bank
Control variables The logarithm of Net Sales was included to control for Firm Size. Also, logarithms of MNEs home country’s GDP per capita as well as Trade in Goods were included as control variables to measure the effect on performance by factors outside of the firm’s control (obtained from the World Bank).
3.1.4 Data analysis
SPSS was used to empirically test and analyze the data. First, the descriptive statistics were computed (table 3). These statistics include the means and standard deviations for all non-dummy variables in the dataset. Then, a closer inspection of the distribution of the data was conducted. First, skewness and kurtosis tests were performed to test for normality. The variables are not normally distributed, which is not surprising considering the dataset used for this study (e.g. RDINT is positively skewed, platykurtic; INTTOTAL slightly negatively skewed, normal kurtosis). Histograms were created to test whether the distribution was bell shaped, another indicator of normality. Non-normality was further confirmed by these tests. Non-normality is not a big issue considering the tests used and the sample size (n = 422). Therefore, non-normality is accepted. The Firm Size variable, which showed substantial positive skewness, was normalized by transforming it into a logarithm value (Field, 2013). R&D intensity values are missing for a large amount of firms (147). Only when R&D intensity is added to a model (models 2 and 3), the missing data points are excluded.
Finally, a correlation analysis was performed to test for the direction of the relation between the main variables. Table 3 also includes the correlation values in the diagonal. The correlation matrix shows that variables are significantly correlated, allowing for further analysis (Field, X).
The first tested model, to test Hypothesis 1, was a hierarchical regression to test whether Internationalization predicts performance, when controlling for firm size, home country GDP
and home country Trade in Goods. Model 2 was a similar hierarchical regression model, this time controlling for GDP_HOME, TRADE_HOME, POLCON, BFREE, FUTOR and UNAVOI. This test was done to test the individual effect of a focus on R&D Intensity to explain ROA in general, without the effect of internationalization. Then, the numerical Independent Variable (INTTOTAL) and Moderator (RDINT) were standardized to allow for the main moderation-moderation analysis, required since the ECON moderator is categorical (Field, 2013). The statistical equation of Hayes’ (2012) third PROCESS model was modified to apply to this study’s third model:
Table 3
Means, Standard Deviations, Correlations
Variables M SD 1 2 3 4 5 6 7 8 1. Internationalization 1.741 .653 (.827) 2. ROA .777 .483 -.097* - 3. Firm Size a 4.817 1.001 -.109* .283** 4. Political Constraints .384 .295 -.295** .081 -.192** 5. Business Freedom 78.916 17.731 .354** -.056 .107* -.024 6. Future Orientation 5.255 .361 -.185** -.171 -.012 -.271** -.328** 7. Uncertainty Avoidance 4.536 .602 -.469** .139** .035 .474** -.351** .228** 8. R&D Intensity .027 .041 .119* -.150* -.007 -.083 .086 -.309** .228** 9. Market type .47 .499 .504** -.120* .024 -.576** .342** -.300** -.768** .198**
*. Correlation is significant at the 0.05 level (2-tailed) **. Correlation is significant at the 0.01 level (2-tailed)
Table 4 ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
DM MNE home countries and institutional values !! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
2010 2011 2012
POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI
Developed Markets .196 .127 .731 .573 .201 .130 .731 .573 .200 .134 .731 .573 Australia .153 .097 .735 .569 .160 .099 .735 .569 .160 .081 .735 .569 Austria .260 .264 .731 .522 .260 .272 .731 .522 .260 .297 .731 .522 Belgium .107 .071 .724 .464 .107 .074 .724 .464 .107 .077 .724 .464 Switzerland .146 .188 .684 .451 .146 .198 .684 .451 .147 .221 .684 .451 Germany .150 .104 .747 .563 .150 .104 .747 .563 .150 .095 .747 .563 Denmark .225 .021 .619 .545 .225 .003 .619 .545 .227 .009 .619 .545 Spain .164 .242 .804 .680 .164 .228 .804 .680 .152 .187 .804 .680 Finland .225 .050 .724 .550 .225 .050 .724 .550 .223 .051 .724 .550 France .135 .137 .709 .609 .135 .144 .709 .609 .132 .163 .709 .609 Great Britain .255 .051 .723 .588 .251 .054 .723 .588 .251 .053 .723 .588 Israel .219 .336 .749 .626 .219 .339 .749 .626 .219 .356 .749 .626 Italy .243 .221 .845 .638 .243 .227 .845 .638 .243 .226 .845 .638 Japan .252 .155 .750 .619 .252 .162 .750 .619 .252 .182 .750 .619 Luxembourg .235 .249 .724 .464 .235 .236 .724 .464 .235 .241 .724 .464 Netherlands .222 .174 .724 .464 .310 .181 .724 .464 .313 .181 .724 .464 Norway .232 .112 .698 .515 .232 .117 .698 .515 .232 .116 .698 .515 Sweden .232 .045 .698 .515 .304 .050 .698 .515 .304 .054 .698 .515 ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! ! !
Table 5
EM MNE home countries and institutional values
2010 2011 2012
POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI POLCON RBFREE FUTOR UNAVOI
Emerging Markets .550 .283 .766 .709 .568 .280 .766 .709 .484 .265 .766 .709 U. Arab Emirates .333 .326 .829 .765 .333 .327 .829 .765 .333 .320 .829 .765 Brazil .264 .455 .812 .713 .319 .457 .812 .713 .319 .463 .812 .713 China 1.000 .503 .675 .755 1.000 .502 .675 .755 1.000 .536 .675 .755 Egypt .680 .350 .829 .765 1.000 .355 .829 .765 1.000 .362 .829 .765 Hong Kong 1.000 .013 .675 .755 1.000 .013 .675 .755 1.000 .011 .675 .755 India .298 .637 .800 .675 .298 .631 .800 .675 .298 .645 .800 .675 South Korea .245 .081 .814 .667 .245 .084 .814 .667 .245 .064 .814 .667 Kuwait .820 .342 .820 .681 .820 .356 .820 .681 .297 .382 .820 .681 Mexico .289 .170 .837 .751 .289 .127 .837 .751 .289 .180 .837 .751 Malaysia .163 .301 .841 .697 .163 .303 .841 .697 .163 .219 .841 .697 Russia .269 .478 .782 .725 .269 .493 .782 .725 .248 .349 .782 .725 Singapore .967 .018 .787 .602 .967 .018 .787 .602 .316 .028 .787 .602 Turkey .627 .311 .833 .667 .627 .313 .833 .667 .627 .329 .833 .667 Taiwan .276 .170 .743 .758 .276 .153 .743 .758 .276 .115 .743 .758 South Africa .588 .270 .742 .684 .588 .277 .742 .684 .588 .242 .742 .684
