FOREIGNNESS AS AN ASSET OR A LIABILITY: THE EFFECT OF HOME-HOST COUNTRY DISTANCE ON SUBSIDIARY PERFORMANCE IN SOUTH AMERICA

FOREIGNNESS AS AN ASSET OR A LIABILITY: THE

EFFECT OF HOME-HOST COUNTRY DISTANCE ON

SUBSIDIARY PERFORMANCE IN SOUTH AMERICA

By

RICARDO ODIJK

Student No. Groningen: S2978199 Student No. Newcastle: 160747829

4 December 2017

/

University of Groningen

Newcastle University Business School

Advanced International Business Management and Marketing

Master Thesis

Dr. E. Alexander Dr. S.R. Gubbi

Word Count: 10.571

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Abstract

Despite the abundance of studies involving foreignness and subsidiary performance, the results remain inconclusive, raising questions whether foreignness is a liability or an asset. Several leading scholars call for more empirical evidence regarding this topic. Therefore, this thesis answers those calls by adding more empirical evidence to the literature of international business involving foreignness, measured with institutional distance and cultural distance, and performance of subsidiaries in South America, an under researched region. With a sample of 1040 foreign owned subsidiaries in South America, a multiple regression analysis was used to test the hypotheses. This study contributes significantly to the literature with evidence that institutional distance is the important hurdle to overcome for foreign subsidiaries in South America concluding that foreignness negatively influences subsidiary performance.

Keywords: Liability of Foreignness, Foreignness, Cultural Distance, Institutional Distance, Transaction Cost Theory

Acknowledgements

I would like to express my sincere gratitude towards the people who helped me during the past months to complete my thesis. Special thanks go to both my supervisors, dr. E. Alexander and dr. S.R. Gubbi, for their time, guidance and valuable feedback throughout the whole process. Furthermore, I would like to thank my study friends for the constructive discussions and revisions on my work. And finally, I thank my family and partner who gave me the moral support to be able to complete my thesis at the University of Groningen and the Newcastle University Business School.

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Table of Content

2.1 Foreignness as a Liability or an Asset ... 10

2.2 Home-Host Country Distance ... 11

2.3 Psychic Distance ... 12 2.4 Institutional Distance ... 13 2.5 Cultural Distance ... 16 3 Methodology ... 19 3.1 Sample Collection ... 19 3.2 Data Collection ... 20 3.2.1 Dependent Variable ... 21 3.2.2 Independent Variables ... 21 3.2.3 Control Variables ... 22 3.3 Descriptive Statistics ... 24 3.4 Analysis ... 25 4 Results ... 26 4.1 Hypothesis Testing ... 27 4.2 Robustness Checks ... 28 5 Discussion ... 30 5.1 Contributions ... 31

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5.3 Conclusion ... 34

Bibliography ... 35

Appendices ... 43

Appendix A – Sector Distribution ... 43

Appendix B – Preliminary Checks ... 44

Appendix C – Robustness Checks Institutional Distance ... 48

Appendix D – Robustness Checks Cultural Distance ... 51

Appendix E – Robustness Check Sample ... 55

List of Figures

Figure 2 – Histogram Dependent Variable.………47

List of Tables

Table 2 – List of Home Countries and Subsidiary Distribution…..………20

Table 3 – Descriptive Statistics....………..24

Table 4 – Regression Analysis: Subsidiary Performance as Dependent Variable………….…26

Table 5 – Sector Distribution…………...………..43

Table 6 – Pearson’s Correlation Matrix...………..46

Table 7 – Variance Inflation Factors………..47

Table 8 – Robustness Check 1: Governance Effectiveness..………..…48

Table 9 – Robustness Check 2: Rule of Law..……….…………..…48

Table 10 – Robustness Check 3: Corruption..………….….………..…49

Table 11 – Robustness Check 4: Regulatory Quality..………...…49

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Table 13 – Robustness Check 6: Voice and Accountability..………...…….…50

Table 14 – Robustness Check 7: Power Distance..……….51

Table 15 – Robustness Check 8: Individualism..………...…51

Table 16 – Robustness Check 9: Masculinity..………..…52

Table 17 – Robustness Check 10: Uncertainty Avoidance..………..…52

Table 18 – Robustness Check 11: Long Term Orientation..………..…53

Table 19 – Robustness Check 12: Indulgence..………..…53

Table 20 – Robustness Check 13: Linguistic Similarity.….………..…54

Table 21 – Robustness Check 14: Subsample Brazil..………...…55

List of Equations

Equation 2 – Institutional Distance...………..………21

Equation 3 – Cultural Distance….…………...………..………22

Equation 4 – Hypothesis 1a and b.…………...………..………25

Equation 5 – Hypothesis 2a and b.…………...………..………25

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1 Introduction

“It has been said that arguing against globalization is like arguing against the laws of gravity.”

Kofi Atta Annan, September 2000 (7th Secretary-General of the United Nations)

The statement above of former UN Secretary-General Kofi Annan is one of the many indicators that globalization is a concept of great importance in our daily lives. Over the years, globalization influenced the literature of international business (IB) significantly and it opened up plentiful new countries for firms to seek international expansion and growth. With going abroad, firms try to reach their internationalization goals and try to lower their cost with creating economies of scale. However, despite the advantages of market expansion across borders, entering a distant and unknown country is accompanied with extra costs. In the literature this phenomenon is known as the liability of foreignness (Zaheer, 1995).

When Zaheer (1995) introduced the concept of liability of foreignness (LOF), it was widely established in the literature that the LOF and the concepts of institutional-, cultural-, and geographical distance negatively influence firm performance (Miller and Parkhe, 2002; Miller and Richards, 2002; Luo and Mezias, 2002; Magnusson et al., 2008; Eden and Miller, 2004; Kostova and Zaheer, 1999). However, more recent studies found the opposite relationship (Evans, Mavondo and Bridson, 2008; Godley and Hang, 2008; Sousa, Ruzo and Losada, 2010; Stahl and Tung, 2015). They found that operating in distant locations may lead to potential benefits. From this perspective, foreignness and distance may result in advantages for the foreign subsidiary (Edman, 2016). These contradicting argumentations with the accompanied empirical evidence leave the literature of IB undecided regarding this topic.

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this question and they encourage more studies encompassing different types of distance and subsidiary performance. Therefore, this thesis investigates the effect of institutional and cultural distance on subsidiary performance.

More specifically, this thesis examines the effect of distance on performance of subsidiaries in South America. The reason for choosing South America is twofold. First of all, South America has not got a lot of attention in the literature. In a literature review of “A”-journals1 in the strategic field, Xu and Meyer (2013) found that from the period of 2001 till 2010 a total of 260 emerging economy related papers got published. However, only 14 of those articles investigated South America. Second, since South America is an extreme due to its high crime and corruption rate (Gaviria, 2002; Frühling, Tulchin and Golding, 2003), the author believes that the effect of distance on subsidiary performance is better perceptible.

Consequently, the research question of this thesis is: What is the effect of home-host country

distance on subsidiary performance in South America? With the use of competing hypotheses,

this exploratory research contributes to the literature with gaining more insight in the field of IB regarding distance measures and subsidiary performance. Especially with investigating South America, this thesis adds useful evidence from an under researched region which will help to solve the puzzle called foreignness. In addition, this thesis contributes with giving practical implications for managers doing or seeking business across borders since distance is “vital” for the success of firms seeking successful internationalization (Beugelsdijk et al., 2017: p. 3).

The findings of this research imply that foreignness negatively influence subsidiary performance and that firms should consider the local institutions as the most important hurdle to overcome to do business in South America successfully. More specific, this thesis found a significant negative effect between institutional distance and subsidiary performance. In addition, no evidence was found for a significant relation between cultural distance and subsidiary performance.

In the next section an extensive literature review is given, incorporating an overview and explanation regarding the relevant literature for this thesis. Here the hypothesis building is included, as well as the conceptual model. In the section following, the methodology is

1 _{These are the top 8 journals consisting of Academy of Management Journal (AMJ), Academy of Management}

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2 Theoretical Review

In this section, a comprehensive overview is given regarding the relevant literature. First, the current state of foreignness in the literature is described. Second, the concepts of distance and how they are used in this thesis are explained. Moreover, definitions and relations are explained and put in a conceptual model. And finally, using the literature, competing hypotheses are created.

Several studies in the past have used competing hypotheses in order to attempt to solve ongoing debates (eg. Tan and Chow, 2009; Choi and Cho, 2011). In this study the use of competing hypotheses is the right approach since there is plenty of literature with evidence for a positive and a negative effect between home-host country distance and subsidiary performance. It is therefore impossible to make a clear and justified case for either the positive of the negative side. Since this thesis uses competing hypothesis in order to answer the research question, this research is an exploratory research.

2.1 Foreignness as a Liability or an Asset

Nowadays, internationalization objectives are of great importance in the strategy formulation of many firms all over the world. There are several methods in order to internationalize. One of those methods is foreign direct investment (FDI). FDI is an investment of a firm in a new, unknown country different than from the home country. The firm enters the market as a “foreigner” and this can have several implications on the performance of the subsidiary (Zaheer, 1995; Hymer, 1976; Kostova, 1999; Miller and Parkhe, 2002; Shenkar, 2001).

Foreignness implies the degree to which a firm is foreign (Edman, 2016). In other words, it constitutes the dissimilarity between the home country and the host country. As mentioned before, it was long believed in the literature of IB that being foreign negatively influences subsidiary performance. For example, Hymer (1976) introduced the theory of the cost of doing

business abroad (CDBA) in his dissertation. He assumed that subsidiaries in a foreign country

experience extra liabilities because of information asymmetries and an increase in the firm’s transaction costs.

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institutional distance is the key driver of LOF indicating that institutional distance would increase the LOF. Correspondingly, still a great deal of recent literature (eg. Hutzschenreuter, Kleindienst and Lange, 2014; Håkanson et al., 2016) assumes distance to be a hurdle which makes doing business in foreign distant countries difficult.

In contrast, a new perspective towards being foreign arose in the literature which underlines the potential benefits of being foreign (Stahl and Tung, 2015). Although not denying the existence of foreignness as being a liability, several recent papers have identified the advantages of being foreign. Rationale for this is, according to Edman (2016) who developed a framework drawing on the identity literature, that foreignness can be an advantage since it creates opportunities for innovation, offers access to unique human capital, opens up opportunities to develop new market segments, and attracts customer preference due to the positive image of the foreign identity, especially when the foreign firm comes from a highly developed country. Other explanations regarding the positive relation between foreignness and subsidiary performance comes from Stahl et al. (2016) who state that individuals, groups, and firms who are doing business in foreign distant countries pay better attention and are better prepared to overcome any possible differences. On the other side, for example with the psychic distance paradox of O’Grady and Lane (1996), firms operating in psychically close countries are not necessarily easy or easier to manage. The authors found that Canadian retail companies faced difficulties to operate successful in the United States.

This flow of literature lets questions arise whether foreignness is an asset or a liability. With widely used concepts as cultural distance and institutional distance (Stahl et al., 2016; Eden and Miller, 2004), this thesis tries to give more insight in how being foreign influences subsidiary performance. In the next section, the concepts of distance, which will be used to calculate foreignness, are introduced.

2.2 Home-Host Country Distance

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it. He also formulates the question whether difficulties with doing business abroad occur in the difference in the perceptions of managers and decision makers, in the difference between cultures, or in the difference between the institutions of countries. To avoid and tackle the problem of “lack of clarity” regarding the distance concepts in this thesis, and to be able to make a clear contribution to the literature, first it is explained what is meant with several types of distance, and how this thesis uses them. Therefore, the next subparagraphs briefly explain what is meant with psychic distance, institutional distance, and cultural distance.

2.3 Psychic Distance

The first concept which is elaborated on is psychic distance. Beckerman (1956) originally introduced this phenomenon arguing that it was an obstacle for trade. In his view, psychic distance was complementary to the concept of geographical distance. However, with regard to the literature of IB, psychic distance, introduced by the Uppsala University, was defined as “the sum of factors preventing the flow of information from and to the market [in terms of] differences in language, education, business practices, culture and industrial development” (Johanson and Vahlne, 1977, p. 24). In other words, psychic distance is a broad concept which is related to distance between two or more countries on the cultural level and the institutional level. For example, the higher the institutional distance between two countries, the greater the psychic distance (Johanson and Vahlne, 2009).

However, an important factor of psychic distance, which is limitedly addressed in the literature (Yildiz and Fey, 2016), is the perception of individuals. It is not only a concept encompassing cultural and institutional factors, but it also includes factors which affect the perceptions of individuals. Yildiz and Fey (2016, p. 832) therefore slightly improved the definition of Johanson and Vahlne (1977, p. 24) into the “sum of individuals’ perceptions regarding the differences between two countries in terms of language, education, business practices, culture, and industrial development”.

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Moreover, rather than using institutional distance and cultural distance as two separate concepts (eg. Håkanson et al., 2016), some studies (eg. Thomé, Medeiros and Hearn, 2017; Arregle et al., 2016) divide institutional distance into formal- and informal institutional distance. They argue that the formal part constitutes laws, policies, and regulations and that the informal part constitutes the more cultural aspects of an environment. However, due to its importance in the literature of IB, this thesis uses cultural distance as a concept on its own in addition to the concept institutional distance rather than, respectively, informal- and formal institutions. 2.4 Institutional Distance

Research in IB concerning the institutional theory has shown that incompatible institutions affect businesses (Kostova and Zaheer, 1999). Therefore, institutional distance is an important variable in studies regarding subsidiary performance (Thomé, Medeiros and Hearn, 2017; Dikova, 2009), internationalization strategies (Arregle et al., 2016; Peng, Wang and Jiang, 2008), and entry mode decisions (Schwens, Eiche and Kabst, 2011).

It is widely believed that institutional distance is one of the major factors which influences the degree of foreignness of firms (Eden and Miller, 2004). Hence, also in this study institutional distance is an important concept. Institutional distance is defined as the difference or similarity between the institutional environments consisting of regulatory, cognitive, and normative institutions of two countries (Kostova, 1999; Scott, 1995). The regulatory components of institutional environments reflect the laws, rules, and regulations in a particular society which encourage and discourage certain behaviours. The normative components of a society encompass the values and norms of individuals. And finally, the cognitive components reflect the frames and mental programs used by individuals through which meaning is made (Kostova, 1999; Kostova and Zaheer, 1999).

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Moreover, Kostova and Zaheer (1999) argued that weaker government institutions make it harder to build relationships with potential local business partners and the local government. This might be particularity relevant for the South American market since Vassolo, De Castro, and Gomez-Mejia (2011, p. 29) state in their analysis that the institutional environment is prone to informality due to its “limited enforcement and tacit complicity of the legal framework”. Another rationale for the negative effect between institutional distance and performance comes from Arregle et al. (2016). They point out that it is hard for firms to generate knowledge from unknown distant markets. In addition, they argue that the increasing challenges and costs to develop firm specific advantages in the new market is the main driver for this negative effect. This increases the transaction costs for firms who operate in alien markets, which on their turn reduce the performance.

Several scholars found empirical evidence supporting the statements of Kostova and Zaheer (1999) and Arregle et al. (2016). Chao et al. (2012), in their study of Fortune Global 500 companies in which they used institutional distance as a moderator, found that institutional distance has a negative effect on performance measures. Moreover, they found evidence that the regulative component, rather than the cultural components of foreignness, forms the greatest barriers for firms who operate in foreign countries. Two years earlier, Chao and Kumar (2010) also found a negative relation between institutional distance and subsidiary performance. In their study, similar to that of Chao et al. (2012), they state that their results stress the importance of institutional distance between two countries regarding subsidiary performance, and that managers need to study the regulatory environment closely in order to mitigate the negative effects arising from the host country institutions.

Moreover, due to the cumbersome procedures and bureaucracy from the governments and the political uncertainty in this region, doing business in South America is a challenge (Brenes and Haar, 2012; Carneiro and Brenes, 2014). It is for subsidiaries therefore difficult to operate in this region and this will simultaneously affect their performance. Taken this all together, it is expected that institutional distance negatively influences subsidiary performance. This leads to the following hypothesis:

Hypothesis 1a: Greater institutional distance between two countries results in lower subsidiary performance

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Europe (CEE) countries, found a positive effect between institutional distance and subsidiary performance. Though, the positive relation was only significant when the firm had no prior experience in CEE countries. According to her, rationale for this is that when having no experience managers put more effort in their preparation and information gathering before entering the country. In other words, having experience leads to complacency and overestimation which has negative effects on performance measures, especially when the experience is gained in another context. Better preparation leads to a better understanding of the foreign institutions and managers can adjust and customize their business best suited for the new foreign environment. This is in line with the reasoning of Chao and Kumar (2010) who state that better preparation leads to a greater control of the difference in institutions.

In addition, due to weak local capital markets and limited supply of trained professionals on the labour market (Carneiro and Brenes, 2014; Brenes and Haar, 2012), domestic firms in South America face several challenges to compete with foreign firms. Foreign firms have access to the international capital- and labour markets and can subsequently outcompete the domestic firms. Thomé et al. (2017) found evidence for this reasoning in the Brazilian market. They found that institutional distance positively influences performance of subsidiaries in Brazil. They explain that the Brazilian institutions are favourable for foreign firms. In other words, foreignness for firms in Brazil can be an asset because they have more freedom and more opportunities compared to domestic firms (Sibal, 2014). For domestic firms to finance growth, they need to use retained earnings, seek finance at the BNDES (the Brazilian development bank), or they need to seek finance at the local capital markets, which are underdeveloped. For MNEs, on the other side, it is easy to get access to the international capital market and the international labour market. Rottig (2016) calls this phenomenon institutional arbitrage. It is therefore that the South American institutions might accommodate foreign firms and positively influence their performance.

Taken this all together, it is expected that institutional distance positively influences firm performance. This leads the following hypothesis:

Hypothesis 1b: Greater institutional distance between two countries results in higher subsidiary performance

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The concept of cultural distance is extensively studied in the literature of international business. As Cho and Padmanabhan (2005, p 309) state “no international business study can be considered completed unless there is an explicit variable controlling for cultural distance”. Moreover, understanding the effects of differences in culture is vital to the success of internationalization strategies of firms (Beugelsdijk et al., 2017). Usage of cultural distance in this research is therefore inevitable.

Using Hofstede (1980) and Kogut and Singh (1988), two leading scholars regarding this topic, cultural distance is defined as the difference between the national culture of the home country and the host country. Since Hofstede (1980) developed his famous cultural dimensions, which made it possible to give measure to culture on a country level, cultural distance has been extensively used in several literature streams. Topics incorporating cultural distance measures are, among others; human resource practices across countries, dynamics in multicultural teams, and knowledge transfer. Moreover, cultural distance is a commonly used moderator between entry mode choice and performance (Stahl and Tung, 2015). Initially, Hofstede (1980) measured culture by using four dimensions, namely Power Distance, Individualism, Masculinity, and Uncertainty Avoidance. Later, two other dimensions, Long Term Orientation and Indulgence, were added.

Therefore, with cultural distance being an important indicator of foreignness and because of its practical usefulness this study adds cultural distance into the conceptual model in order to test its relation with subsidiary performance.

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Several studies found empirical evidence regarding the negative relation between cultural distance and firm performance. In a study, in which German firms are investigated, Hutzschenreuter et al. (2014) found a negative and significant relationship between cultural distance and performance. They argued that this occurred since it is difficult to learn when cultural differences between two countries are high. They also state that this negative effect is due to a bigger chance of misinterpretation of signals and customer preferences from the market. It also affects decision making, communication and interaction between parties and it impedes learning.

One of the most recent studies (Beugelsdijk et al., 2017) regarding cultural distance also found a negative relationship between cultural distance and subsidiary performance. They explain this effect by using the classical view (Hymer, 1976) and the behavioural view (Larsen, Manning and Pedersen, 2013) of cultural differences stating that this might be due to the costs of operating in culturally distant countries which exceed the benefits and that the true costs of cultural differences are underestimated. However, in the same study, the effect of cultural distance on the whole MNE network was positive, although not significant. They conclude that the effect of cultural distance is therefore very nuanced. This thesis only focuses on subsidiary performance, and therefore taken the above reasoning together, it is expected that cultural distance negatively influences subsidiary performance. This leads the following hypothesis:

Hypothesis 2a: Greater cultural distance between two countries results in lower subsidiary performance

In contrast to the above, Dikova (2009) found a positive relationship between cultural distance and performance. In this research she studied Western-European MNEs doing investments in Central- and Eastern European countries. However, the same as with institutional distance, this positive effect was only significant when the firm had no prior experience in the region. Without experience, managers face higher uncertainty and therefore spend more time on researching the new market. In addition, Evans and Mavondo (2002) also found a positive effect between cultural distance and performance in the retail business. However, an important finding in their study was that cultural distance is not a predictor of performance on its own, but in combination with business distance2 it is a significant predictor.

2 _{Business distance, according to Evans and Mavondo (2002, p 520) includes differences in “the legal and political}

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Moreover, the positive effect of cultural distance and subsidiary performance can be explained by the liability of origin of the local firms compared to that of foreign firms. Carneiro and Brenes (2014) state that local firms suffer from a sense of inferiority compared to the Americans and the Europeans. This leads to a preference of the products of foreign firms from developed countries due to a better image (Edman, 2016).

Taken the above reasoning together, it is expected that cultural distance positively influences firm performance. This leads the following hypothesis:

Hypothesis 2a: Greater cultural distance between two countries results in higher subsidiary performance

Finally, there are some studies which did not find a significant effect between cultural distance and performance. A study in Slovakia done by Dow and Ferencikova (2010) did not show a significant relation. This shows that the result regarding cultural distance and performance measures vary. In order to seek more understanding regarding doing business in foreign countries it is important to get a deeper insight and a better understanding of the effect of cultural distance on subsidiary performance. This is in line with the reasoning of Beugelsdijk et al. (2017) who state that understanding the effect of difference in culture is vital to the success of internationalization strategies of firms. The above hypotheses building resulted to a conceptual model, shown in figure 1.

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3 Methodology

For this thesis, South America is considered as the appropriate setting to seek more insight in the ongoing debate about being foreign and its effect on subsidiary performance. This region consist of countries ranging from Brazil to Suriname, with a population of, respectively, 205 million and 560 thousand. South America is, after Southeast Asia, the second most important emerging region in the world, and the total purchasing power has increased more rapidly than in most economies since 1950 (Vassolo, De Castro and Gomez-Mejia, 2011).

The sample consist of subsidiaries in South America with a parent firm from a country who is a member of the OECD, except Chile. The reason for choosing OECD countries is twofold. First of all, since Brouthers, Marschall, and Keig (2016) recently demonstrated that samples consisting of either one home country or one host country are highly vulnerable, this thesis seeks to test the conceptual model on a group of countries. Brouthers, Marschall, and Keig (2016) state that when using only one country as a host or home country, it is not sure what is driving the results; distance or country profile. Therefore, this study includes a group of countries for both home countries and host countries. The second reason is that the group of OECD countries consists of countries spread all over the world. With using this sample, the firms used are originating from the continents Asia (including Middle East), Europe, North America, and Oceania. This will give more variance into the sample which, on its turn, will result in clearer results.

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measures, and therefore the threshold is set at $25 million. This rules out the smaller firms, but still keeps the sample at an appropriate size.

Using this search protocol the final sample consisted of 1,040 subsidiaries distributed over ten host countries (see table 1) and 24 home countries (see table 2). The subsidiaries used are distributed over 18 sectors, see table 5 in appendix A for an overview.

TABLE 1

List of Host Countries and Subsidiary Distribution Host Country Amount of

Subsidiaries

Host Country Amount of Subsidiaries Argentina 24 Ecuador 9 Bolivia 2 Paraguay 4 Brazil 591 Peru 20 Chile 53 Uruguay 44 Colombia 290 Venezuela 3

Note: Guyana and Suriname are excluded in this research due to the unavailability of firm data.

TABLE 2

List of Home Countries and Parent Firm Distribution Home Country Amount of

Firms

Home Country Amount of Parent Firms

Australia 11 Korea 9

Austria 4 Luxembourg 27

Belgium 26 Mexico 19

Canada 42 Netherlands 56

Denmark 4 New Zealand 4

Finland 5 Norway 23

France 97 Portugal 28

Germany 61 Spain 152

Ireland 8 Switzerland 54

Israel 1 Sweden 11

Italy 52 United Kingdom 47

Japan 45 United States 254

Note: the OECD countries Czech Republic, Estonia, Greece, Hungary, Iceland, Latvia, Poland, Slovak Republic, Slovenia, Turkey are excluded in this research due to the unavailability of firm data.

3.2 Data Collection

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3.2.1 Dependent Variable

The dependent variable in this study is Subsidiary Performance. Subsidiary performance is extensively used in the IB literature (eg. Thomé, Medeiros and Hearn, 2017; Dikova, 2009). There are different proxies available to calculate the performance of a subsidiary. This thesis will use return on assets (ROA). ROA includes partly profitability and partly efficiency since it calculates how the subsidiary generates its assets into income (eg. Thomé, Medeiros and Hearn, 2017). ROA is calculated using equation 1. Both the net income and the total assets of the subsidiaries are extracted from Orbis.

(1) 𝑆𝑢𝑏𝑠𝑖𝑑𝑖𝑎𝑟𝑦 𝑃𝑒𝑟𝑓𝑜𝑟𝑚𝑎𝑛𝑐𝑒 = 𝑅𝑂𝐴 = 𝑁𝑒𝑡 𝐼𝑛𝑐𝑜𝑚𝑒

𝑇𝑜𝑡𝑎𝑙 𝐴𝑠𝑠𝑒𝑡𝑠

3.2.2 Independent Variables

First, the World Governance Indicators (WGI) from the World Bank are used to calculate

Institutional Distance. The WGI, constructed by Kaufmann, Kraay and Mastruzzi (2011),

consist of six different measures based on surveys completed by firms, citizens, and experts and is widely used in the literature of IB (eg. Yildiz and Fey, 2016; Håkanson et al., 2016; Dikova, 2009). The indicators are Voice and Accountability, Political Stability and Absence of Violence,

Government Effectiveness, Regulatory Quality, Rule of Law, and Control of Corruption. Their

values range from -2.5 till 2.5. In order to calculate institutional distance the Euclidean distance formula is used (see equation 2). This formula is also used by other scholars (eg. Gaur and Lu, 2007; Powell and Rhee, 2016; Dikova, 2012; Dikova, 2009).

(2) 𝐼𝑛𝑠𝑡𝑖𝑡𝑢𝑡𝑖𝑜𝑛𝑎𝑙 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = ∑ {(𝐼_{𝑖,ℎ𝑜𝑠𝑡}− 𝐼_{𝑖,ℎ𝑜𝑚𝑒})2/𝑉_𝐼} /6

6

𝑖=1

Where I refers to the institutional indicator for country host or home at time i. V is the variance of indicator I.

It is possible to aggregate the six scores of the WGI into one formula due to the high correlation between the indicators. A Cronbach’s Alpha reliability test (α = 0.971), exceeding the threshold of 0.7 (Peterson, 1994), approved the use of the six indicators into one factor. Finally, the measures per country pair per year are added in the database in order to compute further analysis.

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alternative measures of culture are the cultural indicators of Schwartz. However, Drogendijk and Slangen (2006) found that the measures based on Hofstede and Schwartz have similar explanatory power.

In order to calculate the cultural distance between countries the Euclidean Distance based formula of Kogut and Singh (1988) is used. Kogut and Singh used this formula to calculate cultural distance using the variables of Hofstede. A Cronbach’s Alpha reliability test (α = 0.986), exceeding the threshold of 0.7 approved the use of the six cultural indicators of the countries into one factor.

(3) 𝐶𝑢𝑙𝑡𝑢𝑟𝑎𝑙 𝐷𝑖𝑠𝑡𝑎𝑛𝑐𝑒 = ∑ {(𝐼𝑖,ℎ𝑜𝑠𝑡− 𝐼𝑖,ℎ𝑜𝑚𝑒) 2

/𝑉𝑖} /6 6

𝑖=1

Where I refers to the cultural dimension for country host or home at time i. V is the variance of dimension I.

3.2.3 Control Variables

Firms Size – In the literature of IB a wide range of control variables are available. For subsidiary

performance, the most common one is Firm Size. This variable is normally measured using a logarithm of total employees (eg. Bobillo, López-Iturriaga and Tejerina-Gaite, 2010; Dikova, 2009) or a time-lagged logarithm of total assets. However, due to a lack of data availability in the sample, this thesis uses a proxy extracted from Orbis of Bureau van Dijk. Bureau van Dijk classifies firms into 4 different categories (1 = Small Firms, 2 = Medium Sized Firms, 3 = Large Firms, and 4 = Very Large Firms). Although firm size measures by total amount of employees or total assets are more accurate, the measure used in this thesis is a good alternative.

International Experience – Another extensively used control variable is International Experience (eg. Chao and Kumar, 2010; Thomé, Medeiros and Hearn, 2017). It is widely

recognized in the literature that international experience of a firm positively influences firm performance due to learning effects (Zaheer and Mosakowski, 1997; Cho and Padmanabhan, 2005). It is therefore important to control for international experience when doing research in subsidiary performance. A proxy used in the literature (Dikova, 2009) for this control variable is the amount of subsidiaries a firm has over the world. The data is extracted from the database Orbis of Bureau van Dijk.

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Geographical Distance – For research in distance measures, it is important to control for

geographical distance. Geographical distance can increase the costs for transporting goods and increase difficulties in communication and monitoring. Therefore, this thesis controls for geographical distance. The data for this control variable is extracted from a database of the

Centre d'Études Prospectives et d’Informations Internationales (CEPII), a French research

institution who conducts research in international economics. This database contains bilateral country distance, measured between the most important cities of both countries in the country pair (Mayer and Zignago, 2011).

Importance of Subsidiary – The importance of a subsidiary for the HQ is important to control

for when investigating firm performance. When a subsidiary is considered as important by the parent firm, it gets more extensive positive attention in the form of resources. As a proxy for the importance of the subsidiary the importance of the local market is calculated using a measure which is also used by Bouquet and Birkinshaw (2008). They used the proportion of the total GDP of a sector which is generated in the local market of the subsidiary. Translating this for this thesis; the proportion of the GDP of a sector in South America which is realised in the local market of the subsidiary is used as a proxy to determine the importance of the subsidiary. The bigger the proportion of the GDP which is realized in the market of the subsidiary, the more important is the local market and, subsequently, the more important is the subsidiary. The data used for this variable, GDP per country per sector, is extracted from CEPALSTAT, published by the Economic Commission for Latin America and the Caribbean (ECLAC).

Location-Specific Advantage – In the same study, Bouquet and Birkinshaw (2008) used the

ratio of FDI inflows and outflows as an indicator of the presence of a location-specific advantage. The presence of a location-specific advantage can influence firm performance and should therefore be controlled for. When more FDI flows in to a country, rather than flowing out, the market attracts foreign firms which indicates that there is a location-specific advantage. This variable is calculated by dividing the FDI outflow by the FDI inflow of year t of country

i. The data is extracted from the World Bank database.

Economic Growth – Another measure which can influence firm performance is the economic

24

Extractive Subsidiaries – Because of the nature of the sample and due to the abundance of

natural resources in South America (Vassolo, De Castro and Gomez-Mejia, 2011), it is important to control for extractive firms. For these firms, the main rationale for investing in South America is to extract resources despite the eventual distances between the host and the home country of the firm. The way these subsidiaries are managed are quite different to, for example, manufacturing or service subsidiaries. For extractive subsidiaries profitability might not be the most important target. This can influence the results incorrectly and therefore this thesis controls for these kind of firms. In this thesis, firms which are typified by Orbis as active in the Mining and Quarrying industry are considered an extractive subsidiary. This variable is a dummy variable where extractive subsidiaries are typified as “1”, and other firms are typified as “0”.

3.3 Descriptive Statistics

The descriptive statistics of the sample are presented in table 3. One can see that some subsidiaries in the sample have a negative return on assets. However, most of the firms have a positive ROA since the mean is positive. Further, as indicated before, for Firm Size the categories are ranging from small firms till very large firms. Examining table 3, one can see that only large and very large firms are present in the sample since the minimum value is 3. This is due to the minimum threshold of $25 million on total assets for firms in this sample. Also, 4% of the sample exists of extractive subsidiaries.

TABLE 3 Descriptive Statistics

Variables N Minimum Maximum Mean S. D.

Subsidiary Performance 2072 -0.3665 0.3793 0.0157 0.1131 Institutional Distance 2080 0.0449 6.3149 2.5974 1.4727 Cultural Distance 2050 0.2729 4.0948 1.727 0.9438 Firm Size 2080 3 4 3.5800 0.4940 International Experience 2080 2 2139 568.5900 517.2200 Geographical Distance 2080 3089.9590 14817.3 8438.3420 2541.1497 Importance of Subsidiary 2074 0.0010 0.5695 0.2251 0.1558 Location-Specific Advantage 2074 -0.0504 0.5331 0.2496 0.1028 Economic Growth 2074 -4.5864 3.8441 -0.49116 2.9367 Extractive Subsidiary 2080 0 1 0.0400 0.1900

25 3.4 Analysis

Taking into account the conceptual model, this thesis tries to explain the relationship between a dependent variable, and an independent variable. Therefore, an OLS linear regression analysis (regression analysis) is conducted. However, before executing the analysis, a set of preliminary tests is executed to make sure several assumptions and requisites are met. The results of these preliminary test can be found in appendix B.

All the assumptions and requisites are met, except the normality test. This indicates that during the analysis of the data, the non-normality issue has to be taken into account while assessing the significance of the variables.

After conducting the preliminary tests, the analysis is executed. The equations 4, 5 and 6 are used to answer hypothesis 1a and 1b, 2a and 2b and the research question.

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4 Results

In this section the results of the analysis will be discussed and it will be assessed whether the hypotheses are confirmed or not. Below, in table 4, the results of the regression analysis are provided. Model 1 till 4 are established in order to answer hypothesis 1a, 1b, 2a, and 2b.

TABLE 4

Regression analysis – Subsidiary Performance as Dependent Variable

Model 1 Model 2 Model 3 Model 4

Control Variables

Constant 5.193E-5 0.015 0.011 0.014

(0.003) (0.704) (0.477) (0.648)

Firm Size 0.005 0.005 0.005 0.005

(1.004) (1.006) (0.968) (1.003)

International Experience 8.046E-6* 7.888E-6* 7.891E-6 7.605E-6

(1.681) (1.651) (1.631) (1.574)

Geographical Distance 1.056E-7 2.433E-7 2.111E-7 2.058E-7

(0.107) (0.246) (0.210) (0.205) Importance of Subsidiary 0.017 0.014 0.006 0.017 (0.798) (0.654) (0.263) (0.719) Location-Specific Advantage -0.023 -0.034 -0.022 -0.034 (-0.913) (-1.335) (-0.815) (-1.266) Economic Growth 0.005*** 0.005*** 0.006*** 0.005*** (4.192) (4.314) (4.414) (4.150) Extractive Subsidiaries -0.088*** -0.084*** -0.088*** -0.084*** (-6.803) (-2.829) (-6.717) (-6.382) Independent Variables Institutional Distance -0.005*** -0.005** (-2.829) (-2.498) Cultural Distance -0.005 0.001 (-1.476) (0.126) N 2080 2048 2018 2018 R squared 0.038 0.041 0.039 0.041 Adj. R squared 0.034 0.038 0.035 0.037 F 11.485*** 11.084*** 10.158*** 9.749***

27 4.1 Hypothesis Testing

To start, in all the models the constant is positive. This indicates that when all the predictors are set to 0, the subsidiary will have a positive return on assets. One might infer from this that being foreign does not lead to negative performance. However, obviously more insight is necessary before making conclusions.

Model 1, which acts as the base model of the analysis, tests the control variables on the dependent variable. Two of the control variables are highly significant (at the 0.01 level). First, the economic growth of the host country is an important predictor of subsidiary performance (β = 0.005). This indicates that the performance of a subsidiary is closely tight to the economic development of the host market. The second variable with a high significance in the base model is the dummy variable Extractive Subsidiaries. As initially proposed, for extractive subsidiaries profitability is not as important as it is for other non-extractive subsidiaries. The main goal of those firms is to extract commodities, rather than making profit. This is in line with the direction of the coefficient in this study (β = -0.088). Finally, having experience has a small positive effect on firm performance at a significance level of 0.1.

Model 2, which included institutional distance to the base model, tests hypothesis 1a and hypothesis 1b. Hypothesis 1a predicts a negative effect of institutional distance on subsidiary performance. Contradictory, hypothesis 1b, predicts a positive effect between institutional distance and subsidiary performance. The results of model 2 provide support for hypothesis 1a since the independent variable Institutional Distance shows a significant negative effect (β = -0.005) at the significance level of 0.01. This suggest that an increase in the institutional distance between the home country and the host country results in lower performance of the subsidiary in that host country. Hence, hypothesis 1a is confirmed.

Model 3, which included cultural distance to the base model, tests hypothesis 2a and hypothesis 2b. Hypothesis 2a predicts a negative effect of cultural distance on subsidiary performance. Contradictory, hypothesis 2b, predicts a positive effect between cultural distance and subsidiary performance. The results of model 3 do not support the hypotheses since the independent variable Cultural Distance does not show a significant effect. However, it shows a small negative effect (β = -0.005), which is in favour of hypothesis 2b. Nevertheless, no conclusions can be drawn from this result.

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distance on subsidiary performance. However, where the positive effect of cultural distance (β = 0.001) is not at a significant level, the negative effect of institutional distance (β = -0.005) is at a significant level of 0.05. Consequently, from this result conclusions can be drawn.

For assessing how well the independent variables explain the variation of the dependent variable, R-square is added in the table. However, since this regression analysis has multiple variables included it is more appropriate to look at the adjusted version of the R-square. Either way, the value of R-square is low, ranging from 0.034 to 0.038. This indicates that the models explain between 3.4 and 3.8% of the total variation. In addition, taking into account the F-tests of the model, it can be concluded that the models in this analysis are a better fit than the intercept-only model.

4.2 Robustness Checks

In other to assure the quality of the results, several robustness checks are conducted. According to Lu and White (2014) when the coefficients in the robustness checks do not vary much from the results in the main analysis, for example when the sign and magnitudes stay relatively the same, the results can be interpreted as “robust”.

This research conducted several robustness checks involving both the independent variables and the sample. In order to assess the robustness of the regression analysis, the institutional distance and cultural distance variables are interchanged with comparable measures. Regarding the sample, the model was ran on firms locating in Brazil. Brazil is chosen for this robustness check because the size of this subsample is big enough (591 firms). In addition, as explained in the literature section, Thomé, Medeiros, and Hearn (2017) found a positive effect of institutional distance on firm performance. In this research this effect was not found. This might indicate that the positive effect found by them was country specific. However, looking at the robustness check, no evidence was found which support their arguments.

First, the independent variable Institutional Distance is assessed. In the original models, institutional distance is measure as an aggregate of the six World Governance Indicators by the use of an Euclidean Distance formula. For the robustness check, the six WGI’s are tested separately. In order to calculate the distance between the individual indicators of two separate countries, the Manhattan Distance was calculated. The results of this robustness check are shown in appendix C.

29

which occurred was an increase of 0.012 of the magnitude of the negative effect (see table 13). Thus, it can be concluded that the independent variable Institutional Distance is robust.

The second robustness test is conducted on the independent variable Cultural Distance. This variable was calculated as an aggregate measure of the six cultural dimensions of Hofstede using the Euclidian based formula of Kogut and Singh (1988). For the robustness check, the six dimensions are tested separately. In order to calculate the distance between the dimensions of two separate countries, the Manhattan distance was calculated. The results of this robustness check are presented in appendix D.

Moreover, the variable Linguistic Similarity is added to the model. Culture and language are closely related to each other (West and Graham, 2004). Therefore the difference in language between the home and the host countries can influence the effect of cultural distance on subsidiary performance. The variable Linguistic Similarity is created with data of Melitz and Toubal (2014) extracted from CEPII.

Comparing the robustness checks 7 till 12 with model 3 in table 4, which tests cultural distance without including institutional distance, only two out of six robustness checks turn out to be robust. Their coefficients point towards the same directions, and their magnitudes are relatively equal. The other four robustness checks found coefficients pointing into the other direction. These checks involve Power Distance, Masculinity, Uncertainty Avoidance and Individualism. In addition, examining robustness check 13, which adds language to the model, the magnitude does not variate substantially and the sign is pointing in the same direction. Thus, overall, this indicates that some robustness issues regarding cultural distance are present.

30

5 Discussion

With investigating 1040 foreign subsidiaries located in South America, this study investigates the effect of foreignness, measured as institutional- and cultural distance, on subsidiary performance. With the use of competing hypotheses, this study sheds light on the ongoing discussion whether foreignness is a liability or an asset. This section functions as an extent on the previous section, offering a deeper insight and to draw conclusions based on the results of the models ran in order to answer the hypotheses.

The negative effect of institutional distance on the performance of subsidiaries located in South America has several implications. Due to the state of the institutions in South America (Vassolo, De Castro and Gomez-Mejia, 2011), it is harder for firms, from institutional diverse countries, to generate the necessary knowledge for their subsidiaries to operate successfully. This makes it harder and more costly to develop firm specific advantages (Arregle et al., 2016). In order to fit in the different institutional environment, the subsidiary needs to adapt its behaviour, governance, and managerial capabilities. This will increase the costs of doing business (Kostova and Zaheer, 1999).

In addition, the positive effect of cultural distance on subsidiary performance has several implications. Regarding the home country side of the sample, which consists of mainly firms from developed and high developed countries, the results indicates that the foreign nature of the subsidiaries attracts customer preferences (Edman, 2016). In other words, customers in the foreign markets prefer products from the well-developed countries due to the better image of the organization originating from that country. The image functions as a lens (Smith, 2011) through which partners, suppliers, customers and regulators see and evaluate the subsidiary (Edman, 2016). Moreover, firms from cultural distant countries pay more attention and try harder to fit in to exploit the positive opportunities from cultural differences.

31

and Miller, 2004), institutional distance is the biggest hurdle for firms to overcome when doing business internationally.

With regard to the main research question of this thesis; “What is the effect of home-host country

distance on subsidiary performance in South America?”, hardly a definitive answer can be

given. On the one hand side, foreignness negatively influences subsidiary performance since institutional distance is negatively related with subsidiary performance. But on the other side, cultural distance positively influences subsidiary performance. However, the final conclusion of this thesis is that the effect of home-host country distance on subsidiary performance in South America is negative. One can argue that, when examining the standardized coefficients, the institutional distance coefficient (beta = -0.066) rules out the cultural distance coefficient (beta = 0.004). When the standardized coefficients are added up (-0.066 + 0.004 = -0.062), the final result regarding distance is -0.062, and therefore it negatively influences subsidiary performance. In addition, the institutional distance variable has significant results and the cultural distance variable has not. Therefore, the only conclusion which can be made is that home-host country distance has a negative effect on subsidiary performance.

5.1 Contributions

To conclude, this study makes several contributions to the international business literature and the results have some implications for practitioners and policy makers.

First of all, this study contributes to the international business literature regarding the ongoing debate of foreignness with empirical evidence in an under researched environment. With the conclusion that being foreign in South America negatively influences the performance of subsidiaries this thesis adds valuable empirical evidence that foreignness is still an important hurdle firms need to overcome. It implies that when seeking internationalization into the South American market, firms need to be prepared for a lower return on assets compared to their activities in their home country.

In addition, this study adds to the literature with evidence that institutional distance, rather than the cultural distance, is the main barrier for businesses to overcome. This research suggests that cultural distance matters less since it does not find significant results. On the contrary, institutional distance does matter and is the main driver for the negative relation between distance and subsidiary performance.

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are prepared for the expected differences in the new business environment mitigate the negative effects of distance (Stahl et al., 2016). Also, managers and decision makers of firms can use these results to formulate their entry strategies.

Finally, this thesis has some implications for policy makers. In order to make it more attractive for foreign firms to enter the South American markets, policy makers should lower the hurdles which emerge from the differences in institutional profiles between countries and encourage firms to enter the market (Lenartowicz and Johnson, 2003). Attracting more firms has positive implications for the economic development of the country (Borensztein, De Gregorio and Lee, 1998). Referring to appendix C, this study found evidence that corruption (table 10) is the main driver of the negative effects of institutional distance. Policy makers should initially focus on ruling out corruption in order to make it more attractive for firms to do business in South America.

5.2 Limitations and Further Research

This study did not find significant coefficients regarding culture. Moreover, the coefficient of cultural distance shows a positive value running together with institutional distance, and shows a negative value when running on its own. Therefore more research is necessary to make the effects of culture conclusive. In addition, since it is now clear how foreignness influences firm performance on a country level in South America, the next step involves adding individual perceptions of managers and decision makers. With doing so, the results in this study can be better rationalized since more will be known about foreignness on a personal and individual level.

This research also opens up new research possibilities regarding entry mode decisions. Since this thesis found evidence that the differences in institutions negatively influences performance, new context specific insights regarding the South American market give a new dimension to the discussion of foreignness and performance.

On a methodological level some concerns need to be taken into account in order to be able to properly interpret the above findings and conclusions. Despite the relatively big sample size, this thesis suffers from generalizability issues. Due to the insignificant results of the independent variable Cultural Distance, the use of the cultural dimensions of Hofstede as a measure for the corporate culture of the firms used in this sample is questionable. Messner

33

the cultural profiles used are measured on a country level, however, the corporate profiles of firms within the same country differ as well. Running the same models using cultural measures on the corporate level might lead to different results. These problems with Hofstede’s cultural dimensions are known and well documented, however, Hofstede’s cultural dimensions are still widely used (Cho and Padmanabhan, 2005; Beugelsdijk et al., 2017). Nonetheless, it is important to keep this in mind during the reflection of the results. Further research regarding cultural distance and firm performance should investigate cultural difference on the corporate level, rather than on the country level. Moreover, for studies in the future regarding this topic should take into account other measurements (e.g., GLOBE and the Cultural Dimensions of Schwartz). This will give the ongoing puzzle of foreignness a whole new dimension.

Another limitation is the non-normally distributed sample. Non-normality increases the probability of making the wrong decision to reject or accepting the null hypotheses. Also, the R-Squared of the models is low, explaining only 3.4% till 3.8% of the variation. Although, having added the most used variables in this regression as control variables, there is still a lot to learn and explore regarding the variables affecting firm performance. Therefore, more research is necessary.

Other limitation regarding the data involves the distribution of countries in the sample. This distribution is not representative for whole South America since 57% of the sample consists of Brazilian firms, 28% of Colombian firms and the rest of the sample (15%) represents the rest of the countries of South America. This unequal distribution of countries occurred due to the lack of available data for this region (Thomé, Medeiros and Hearn, 2017).

The final limitation is that the sample consists only of large and very large subsidiaries. Large subsidiaries are found to perform better (Halkos and Tzeremes, 2007). A dataset including more small and medium sized firms might present different results. For further research opportunities, scholars need to test the effect of distance on performance with a sample including a fair size of small and medium sized subsidiaries.

34 5.3 Conclusion

The aim of this study was to test the effect of home-host country distance on subsidiary

performance in South America. This interesting and peculiar environment had been overlooked

35

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