The effect of board nationality diversity on the
relationship between institutional distance and
entry mode choice
Author:
Marc van Mensvoort S3269280 E.m.m.van.mensvoort@student.rug.nl
Supervisor:
Dr. M.J. Klasing Co-assessor: Dr. D.H.M. Akkermans
Faculty of Economics and Business University of Groningen
Duisenberg Building, Nettelbosje 2, 9747 AE Groningen, The Netherlands P.O. Box 800, 9700 AV Groningen, The Netherlands
Abstract
The aim of this research paper is to contribute to the existing literature regarding entry mode choice and institutional distance, as well as discerning factors which could influence the correlation between the two. Results from studies which have looked into the relationship between institutional distance and entry mode choice found ambiguous results. This could be because of the perceived distance differences of the executives making the entry mode decisions. This is based upon the upper echelons theory which state that managerial characteristics, including nationality, influences the decisions managers take. By using arguments from the upper echelon perspective this research paper will investigate the moderating effect board nationality diversity has on the relationship between institutional distance and the choice between a full or partial entry mode choice. The dependent variable is the chosen entry mode being ether full (1) or partial (0). Institutional distance is the independent variable and the national diversity in the top management team is the moderator. This study uses a sample of 222 FDI cases to 44 countries by 129 German firms in the years 2014-2018. The results will show that high institutional distance will lead to firms preferring a fully owned entry mode. With respect to the effect of the moderator variable, top management team international diversity, the results are insignificant and therefore no evidence for the moderating effect is found.
Table of content
Abstract 2
1. Introduction 4
2. Theoretical framework 8
2.1 Entry mode choice 8
2.1.1 Transaction Costs Economics 9
2.2 Institutions 10
2.2.1 Institutional distance 11
2.3 Upper echelons perspective 13
2.3.1 Nationality 14 2.4 Conceptual model 16 3. Research design 17 3.1 Data collection 17 3.2 Dependent variable 18 3.3 Independent variable 19 3.4 Moderator 19 3.5 Control variables 20 3.6 Methodology 21 4. Results 22 4.1 Descriptive statistics 22 4.2 Multicollinearity 22
4.3 Binary logistic regression 23
4.4 Robustness check 25
5. Discussion 28
5.1 Discussion 28
5.2 Limitations and recommendations for future research 29
6. Conclusion and Implications 32
References 34
Appendix 1 39
Appendix 2 40
1.
Introduction
How firms internationalize is a key question in international business research. In particular, given the liability of foreignness (LOF), choosing the right entry mode is of crucial importance for the success of the foreign expansion (Brouthers, Brouthers, & Werner, 2008).
One of the hazards facing firms is choosing a correct entry mode. An entry mode can be defined as the particular way a firm attempts to enter a foreign market, and is the organizational or institutional arrangement which is used to perform an international business activity (Welch, Benito, & Petersen, 2007). Transaction cost economics is one of the main theories explaining why firms choose a particular entry mode. Firms will choose between shared and full ownership of a subsidiary by comparing the cost and benefits of the two options (Williamson, 1985). Choosing the right entry mode is important because of the impact it has on the firm and the costs associated with it. The chosen entry mode can have a lasting effect on the MNC’s overall performance and survival (Brouthers et al., 2008). Also, the costs of switching between entry modes are significant, and the choice may lead to different organizational and cross-cultural issues (Agarwal & Ramaswami, 1992). Each ownership form has a multitude of risks and benefits, and is chosen because of various factors which influence the effectiveness and the compliance with the strategic goals of the firm. One of those factors are the differences between the institutional environments of the two countries.
When firms internationalize, they need to create legitimacy to operate in a foreign context (Zaheer, 1995). The institutional environment of the host country is part of that foreign context. Institutions are defined as the regulative, normative and cognitive structures and activities that regulate society (Scott, 1995), and govern the rules of the game (North, 1990). The difference between the intuitional environments of countries can be measured. The institutional distance between countries is a cross-country measure of differences between the host and home country (Kostova, 1999).
face a number of hurdles transferring organization practices to the host country (Kostova & Zaheer, 1999). These hurdles will create legitimacy problems which they can control by using a local partner (Xu & Shenkar, 2002). Contrary to Xu and Shenkar (2002), Contractor et al., (2014) found that high institutional distance will lead to full ownership. Firms want control to overcome the institutional dissimilarities. This control will enable them to implement changes and oversee the strategy of the subsidiary. Hutzschenreuter, Kleindienst and de Lange (2015) also documented these dissimilarities in the results regarding the effect institutional distance has on the chosen entry mode.
Foreign expansion decisions do not happen in a vacuum, but are made by executive-decision makers (Nielsen & Nielsen, 2011). When undertaking these internationalization decisions, executive-decision makers take multiple factors into account, including the institutional distance. Hutzschenreuter et al. (2015) stress the issue of asymmetry in perceived distance. The same distance can be perceived differently by two different managers. This sparks the question; what influence do the characteristics of the executives making these decisions wield? This argument that the characteristics of executive decision makers influence organizational outcomes, such as the entry mode choice, of a firm is grounded in the upper echelon theory (UET).
UET was founded by Hambrick and Mason (1984) and states that the experiences, personalities, and values of the top management team have a large influence on the decisions they make and with that the actions the organization takes. Prior research has linked managerial characteristics like education, functional background, age, tenure, etc. to different strategic outcomes (Ancona & Caldwell, 1992; Barker III & Mueller, 2002; Lee & Park, 2006; Weinzimmer, 1997). This thesis focuses on the role played by the national diversity of the top management team (TMT), an aspect which has been largely ignored in research on entry mode choice. Nielsen and Nielsen (2011) is one of the few (if not only) papers that has looked at this relationship. They find that internationally diverse management teams have a tendency to opt for partial ownership when entering a foreign market. This is because an internationally diverse TMT has the confidence that they can overcome the differences between countries.
executive’s characteristics, such as nationality differences, influence that choice. By combining the relationship between institutional distance and the moderating effect of the top management team’s national diversity, this paper aims to provide new observations into the internationalization process of firms and by doing so contribute to the current international business literature. It will be rewarding to discover what the moderating influence is of a managerial decision-making theory like the UET on the relationship institutional distance and entry mode choice because it can provide new insights in the internationalization process of firms.
This sparks the following research question: What is the effect of board nationality diversity on the relationship between institutional distance and entry mode choice of German firms conducting FDI?
In addition, this paper will focus on the effect institutional distance between countries has on the entry mode choice, being either full or partial ownership. This paper argues that a larger institutional distance will lead to partial ownership, whereas full ownership is preferred when the institutional distance is small. A larger institutional distance will lead to partial ownership due to the higher cost of operating in that market, and local partners have more experience operating in that particular market. Furthermore, this paper argues that internationally diverse top management teams will choose for partial instead of full ownership when entering a foreign market. Internationally diverse top management teams will be convinced that they can overcome the various differences between countries.
The outcome of this study can be either a fully or partially controlled entry mode. Therefore, this study uses a binary logistic regression. Companies from developed and developing markets are increasingly seeking new opportunities to expand their businesses. Being the largest economy of the Eurozone, Germany is no exception. Therefore, this study will focus on Germany as the home country. A sample of 222 German firms conducting FDI to foreign countries between 2014-2018 is drawn from the Orbis/Zephyr database.
hypothesized. TMT national diversity strengthens the negative effect of institutional distance on the likelihood that firms will opt for full ownership.
2. Theoretical framework
This section will start with an overview of the literature on entry modes and transaction costs economics. Furthermore, I will review the literature on institutional theory and institutional distance in order to derive the first hypothesis linking institutional distance to entry mode choice. Following this, I will discuss upper echelons theory and develop the second hypothesis regarding the moderating effect role played by the composition of the TMT on the above-mentioned relationship. I will close this section with the presentation of the conceptual model.
2.1 Entry mode choice
One of the main questions in international business research is how firms enter foreign markets. An entry mode is the particular way a firm tries to penetrate a foreign market and can be defined as the organizational or institutional arrangement which is used to perform an international business activity (Welch et al., 2007). There are three reasons why the choice of market entry mode is important for internationalizing firms (Mukundhan & Nandakumar, 2016). First of all, certain market entry modes require significant capital investments and can have far-reaching effects on firm performance and survival (Brouthers et al., 2008). In addition, when an entry mode has been established, it is difficult to change and will have long-term consequences (Pedersen, Petersen, & Benito, 2002). This is due to the process of building and maintaining long-lasting partnerships with foreign parties which is a time-consuming and difficult process which requires significant costs for the firm (Mukundhan & Nandakumar, 2016). Lastly, the entry mode choice comes with challenges related to organizational issues and cross-cultural management. An example of these challenges in the case of acquisition is the integration failures which can be based on cross-cultural differences (Dikova & Van Witteloostuijn, 2007).
equity are greenfield, JV’s and acquisitions (Meyer, Estrin, Bhaumik, & Peng, 2009). When firms choose for an equity entry mode, they need to decide the level of control they want to assert over the subsidiary. Companies can either opt for full ownership or partial ownership when deciding to internationalize (Dikova & Van Witteloostuijn, 2007). When opting for full ownership, subsidiaries are established as greenfield investment, or an acquisition is made whereas in the case of a partially owned subsidiary joint ventures are the mode of entry (Ruiz-Moreno, Mas-Ruiz, & Nicolau-Gonzálbez, 2007). This study focuses solely on equity-based entry modes which will be further explained below. Equity-based entry modes differ in the level of control the firm has over the subsidiary.
Full-ownership based equity modes can be either acquisitions or greenfield investments. With a greenfield investment, the investing firm starts a new company from the ground up. This differs from an acquisition where the investing firm will buy all, or most of, the equity of the firm in the host country.
Partial ownership indicates that the ownership of a subsidiary is shared with a partner which can be in the form of a joint venture. Nielsen & Nielsen (2011) describe a joint venture as the pooling of assets by two or more firms in an entity in which the level of commitment is low, and ownership, control, and risk are shared by the partners. Joint ventures are generally speaking a collaboration driven by resource complementarity with the aim of achieving a common goal and are mostly short-lived (Choi & Beamish, 2013). The performance of the joint venture is driven by the synergy which can be achieved by pooling the complementary resources (Choi & Beamish, 2013). A joint venture is a relatively easy way to internationalize as the costs and risks are shared (Agarwal & Ramaswami, 1992). Ownership of the joint venture is shared by the partners, but minority or majority stakes are possible.
2.1.1 Transaction Costs Economics
frequency (Williamson, 1979). The transaction costs a firm is exposed to are composed of the costs of finding a partner, negotiating, and monitoring the performance (Agarwal & Ramaswami, 1992; Williamson, 1985). When firms internationalize, they choose between shared and full ownership of an affiliate by comparing the cost and benefits of sharing equity, compared to maintaining full ownership (Williamson, 1985). Because different entry modes are associated with different costs, high or low transaction costs will influence the chosen entry mode. Scholars found that firms opt for wholly owned subsidiaries when the transaction costs of finding, negotiating and monitoring are high. If these costs decrease, firms are more likely to depend on the market to deliver their objectives (Brouthers, 2013; Williamson, 1985).
2.2 Institutions
North described institutions in his 1990 paper as “the rules of the game in a society” and the humanly devised constraints that structure human interaction (North, 1990). Scott (1995) adds to this by defining institutions as the regulative, normative and cognitive structures and activities that regulate society. Regulative structures are the existing laws and regulations that exist in the host country. The normative structures state what should be done according to social norms and beliefs. Lastly, cognitive structures influence human behavior because they are the social knowledge which is shared among the inhabitants of a country. Together these institutions make up the institutional environment which can be defined as the set of rules which govern the behavior of individuals (North, 1990).
2.2.1 Institutional distance
Formal and informal institutions differ between countries. Therefore, when countries internationalize, they need to adapt to the institutional environment of the host country and overcome the institutional distance between the countries. Institutional distance between countries is a cross-country measure of differences between the host and home country (Kostova, 1999). Institutional distance affects the firm in a number of ways including performance (Dikova, 2009), internationalization strategies (Peng, Wang, & Jiang, 2008) and entry mode decisions (Contractor, Lahiri, Elango, & Kundu, 2014; Xu & Shenkar, 2002). This study will focus on the effect institutional distance has on entry mode decisions.
Foreign firms need to create legitimacy in order to operate in a foreign context (Zaheer, 1995). Legitimacy is needed to overcome the liability of foreignness which results in the firm having more costs compared to its domestic counterpart. These costs of operating in a foreign market, influences the entry mode that is chosen (Williamson, 1989). To manage and control these costs firms can choose between a partial or full controlled entry mode. The right entry mode decision can help overcome these legitimacy problems. Institutional distance is a model which can provide information to help firms choose the right entry mode.
However, scholars found conflicting reports about the influence of institutional distance on the chosen entry mode (Hutzschenreuter, Kleindienst, & Lange, 2015). Hutzschenreuter et al. (2015) found that the few studies that focus on institutional distance found a negative effect (Castellani et al., 2013; Xu et al., 2004) but also a positive effect (Contractor et al., 2014; Schwens, Eiche, & Kabst, 2011). This is due to the different actions firms can take in order to overcome the LOF or to protect their intellectual property.
the firm (Xu & Shenkar, 2002). Firms need legitimacy in order to operate. In order to gain legitimacy in the host country, the firm is forced to give up some internal control and legitimacy (Xu et al., 2004). thus firms choose local partners, which in turn give them local legitimacy. The article of Contractor et al., (2014) suggested a different approach to the effect of institutional distance on entry mode choice. It argued that when the institutional distance is high firms will opt for fully controlled entry modes to control the targets assets and operations in order to limit the institutional dissimilarities. Higher ownership will give the acquiring firm the ability to implement changes, strategy and synergy, in order to achieve the economic goals (Contractor et al., 2014). When the institutional distance is low firms don’t need to control for institutional dissimilarities and thus can engage in low cost shared control entry modes (Contractor et al., 2014).
The aforementioned ambiguous results and arguments have led to entry mode choice literature falling short of a clear answer of what the effects are of institutional distance on entry mode choice. This study follows the reasoning of Xu & Shenkar (2002) in that a higher institutional distance will lead to collaborative entry modes. Firms need to overcome the legitimacy issues and therefore seek a local partner to help them overcome those issues. The different arguments given above have led to the following hypothesis.
H1; Higher institutional distance will increase the likelihood that firms will opt for a collaborative entry mode.
upper echelon theory, which is one of the main theories that describes the influence of managerial characteristics on the decision-making process.
2.3 Upper echelons perspective
Hambrick and Mason introduced the upper echelon theory (UET) in 1984 arguing that the experiences, personalities, and values of the top management team have a big influence on the decisions they make and with that the actions the organization takes. This focus on the top management team comes from research in the field of organizational psychology. Cyert & March (1963) introduced the concept of the dominant coalition as the main focus of organizational leadership. Decisions are made by different executives who share responsibility and tasks with each other, which makes their combined characteristics of importance (Hambrick & Mason, 1984). There are two important steps in the UET, namely; the influence of the composition of the TMT on organizational outcomes and the influence of antecedents on the composition of the TMT (Nekhili & Gatfaoui, 2013). This study will focus on the composition of the TMT and the influence it has on organizational outcomes, especially entry mode choice. The composition of the TMT is of importance because the different demographics of each manager such as age and nationality influences the decisions the TMT takes.
These demographic characteristics are connected with the social, cognitive and psychological characteristics of the TMT (Hambrick & Mason, 1984). It are the cognitive schemas of the managers which determine the approaches they take (Prahalad & Bettis, 1986). The cognitive base of an executive influences the decision-making process in a number of different ways: by directing attention; limiting the perception to focus only on a limited number of stimuli; and by functioning as the lens through which the manager views and interprets the stimuli (Hambrick & Mason, 1984).
UET states that managers in the TMT are characterized by bounded rationality (Hambrick, 2007). In order to understand the direction the firm takes it is necessary to look at the characteristics of the TMT and the influence it has on organizational outcomes.
Caldwell, 1992), firm performance (Weinzimmer, 1997) and R&D spending (Barker III & Mueller, 2002). It is the characteristics of each manager which influences the decision makers. The characteristics of the decision makers such as age, specialization, tenure, nationality, demographic, and gender become more important as the decision becomes more complex (Ting, Azizan, & Kweh, 2015). This means that in the case of such complex decisions as the preferred entry mode into a foreign market these characteristics will be important predictors of the outcome. Although the different characteristics of the managers will wield different results on organizational outcomes, this study will focus on the characteristic of nationality.
2.3.1
Nationality
Nationality based differences have been researched by many scholars of which Hofstede is one of the most commonly used sources. Hofstede found that national origin influences managers underlying values, orientations and cognitions (Hofstede, 1980). These values, orientations, and cognitions affect the decision-making process of the managers. Characteristics like international exposure can surmount nationality-based differences, but nationality is not easily eliminated (Hambrick, Davison, Snell, & Snow, 1998). Despite the influence nationality can have on the cognitive schemas of managers, it had received little academic attention, especially in the form of nationality differences between the TMT. Nationality differences between the TMT have been mainly linked with the performance of the team (Fiedler, 1966). There has been little attention given to the link between nationality differences in the TMT and the entry mode choice.
Institutional distance has ambiguous and sometimes conflicting reports (Hutzschenreuter et al., 2015). Institutional distance will provide managers with information about the distance between the countries, whether it is high or low. But how managers interpret those results is not taken into account. Nielsen and Nielsen (2011) state that prior studies on entry mode choice fail to take into account the effect of managerial characteristics and influences and mainly focus on the rational choice. It could be that the different outcomes of studies looking into the relationship between institutional distance are due to how different TMT interpret the information and act on the basis of that information. As Hambrick and Mason (1984) state, the personalities, values, and experiences of the managers influence the decisions they take. In order to shed new light on the entry mode literature, this study will combine the aforementioned arguments.
The aforementioned scholars and description of the theories have led to questioning whether the ambiguous results in the institutional distance literature regarding entry mode choice have their origins in the different compositions of the TMT. Therefore, this study will focus on the influence that the TMT composition has on the relationship between institutional distance and the entry mode choice, looking specifically at nationality differences. This had led to the following hypothesis:
H2: TMT National Diversity strengthens the negative effect of Institutional distance
2.4 Conceptual model
The literature review has led to the construction of a conceptual model which is presented below. The dependent variable is Entry Mode Choice which can be either fully owned, such as an acquisition or Greenfield, or partially owned, such as JV. The independent variable is Institutional Distance which is hypothesized as increasing the likelihood of firms opting for a partially owned entry mode. So, when Institutional Distance is high, firms will most likely opt for a partially owned entry mode. This relationship is moderated by the TMT National Diversity. When TMT National Diversity is high, its effect on the relationship between institutional distance and entry mode choice will be that the likelihood of firms which has a negative effect on the relationship between Institutional Distance and Entry Mode Choice.
Figure 1: Conceptual model
Institutional Distance Entry Mode Choice
3. Research design
The following section will introduce the research methodology of this study. This will be done by first describing the data collection and the sample. After that, the variables and existing measurements will be explained, and finally, the chosen statistical technique will be introduced, which will be used to analyze the data and test the hypothesis. Furthermore, this section will provide the reasoning behind the chosen methodology.
3.1 Data collection
The aim of this research is to examine what the influence of institutional distance and board member nationality is on FDI entry mode choice. In order to examine the relationship, a sample will be taken from German multinationals undertaking FDI to foreign countries in the time period of 2014 till March-2018. This time slot was chosen to include recent samples, in order to test the hypothesis in the present-day business environment. Germany was chosen as the main focus of this study due to the availability of data and size of its economy.
The drawn sample chosen to test the hypotheses had to comply with a number of selected criteria in order to be included in the sample. The companies had to:
● Be from Germany
● Have a subsidiary in a foreign country ● Be publicly listed
● Have a deal that is completed
● Have information on the board of directors and subsidiaries publicly available
The firms that met the above-stated criteria were included in the sample. Besides those criteria, additional information about the firms needs to be included in the final sample. It is necessary to have data regarding the location of the subsidiary, entry mode type, total assets at the moment of completion of the FDI decision, industry, nationality and international experience of the TMT for each firm.
a database provided by Bureau van Dijk, which contains information about over 79 million private and public MNCs and their directors. Zephyr provides information on FDI for most countries from the years 2008 on. The initial sample consisted of 134 German firms conducting 481 FDI decisions. Given the scope of this study, an entry mode that was not an acquisition or a joint venture was deleted. Increases of ownership were also deleted since the entry mode decisions were made before the decision to increase the ownership level. In cases in which no data was available that met the criteria threshold, the observation was dropped.
Information about the TMT was taken from Orbis and the Boardex database. This database has information about the individual members of the TMT for several European countries. The Database of BoardEx provided most compositions of the TMT over a number of years. The nationality of the members was not present for most firms. When data about the nationality or international experience was incomplete, annual reports, firm websites, and other online sources where used. The most commonly used sources to find the nationality and international experience of managers were Bloomberg, LinkedIn, and annual statements. When the nationalities of the TMT were not accessible through secondary data or annual reports, the firms were excluded.
The final sample consisted of 222 entry decisions made by 129 different firms distributed over 44 host countries. The subsidiaries used are distributed over a number of different sectors.
3.2 Dependent variable
3.3 Independent variable
This study will use formal institutions to measure the institutional distance. This can be measured by looking at the differences between the cognitive, regulatory, and normative institutions of countries (Xu & Shenkar, 2002). One common way to measure the differences between the institutional environment of countries is by the World Bank that categorized six governance indicators that value the institutional environment (Kaufmann, Kraay, & Mastruzzi, 2009). These six indicators are; voice and accountability, political stability, government effectiveness, regulatory quality, rule of law, and control of corruption (Kaufmann et al., 2009). According to Kaufmann et al. (2009), the six indicators refer to the following: Voice and accountability captures the ability of the citizens to choose their own government and express themselves; Political stability is capturing the stability of the government and absence of terrorism; The quality of services and the ability of the government to implement policies is captured by government effectiveness; Rule of law captures the extent to which the law is being abided to and complied with; Regulatory quality captures the respect for the institutions that the citizens and state have; And lastly, control of corruption is capturing if public power is used to improve private gains.
To measure institutional distance, a Euclidean distance calculation has been used. The formula for measuring the institutional distance is:
𝑗 =#$% &(()* ,()- )^0 1 )2 3 $
45#
This formula reflects the institutional distance j between the host and home country. Iij is the value for the home country j, Ijh the value for the host country h and i is the value for the six dimensions of the World Bank. Lastly, σ I is the variance in the equation.
3.4 Moderator
The moderator of this study is the national diversity of the TMT. Board national diversity was measured by looking at the country of origins of the top executives. The Blau index (Blau, 1977) was used to measure the degree of national diversity of the TMT. The formula B= [1-Σ(pi)2] measures the dispersion of the TMT, where p is the share of all TMT
close to 1 indicate a highly heterogeneous group. This means that when the value is close to 1, the TMT consists of multiple nationalities.
3.5 Control variables
Firm Size
This study controls for firm size because it has been proven in prior research that firm size has an impact on entry mode choice (Brouthers & Brouthers, 2003; Ferreira et al., 2017). The main reason behind this is that larger firms have more resources and better backup processes from the head office (Inkpen & Beamish, 1997). In order to measure Firm Size, this research will look at the assets of the firm. Assets will be measured as the logarithm of the total asset, with data will be derived from the Orbis database. Other research on entry mode choice also had firm size as a control variable (Ferreira et al., 2017; Nielsen & Nielsen, 2011).
TMT Size
In addition, I control for the size of the TMT. Prior research found that a bigger size of the board of directors influences the level of nationality diversity (Blau, 1977; Frijns, Dodd, & Cimerova, 2016). This could have an impact on the results of this study since smaller firms with smaller TMT are included. This variable is measured by looking at the total size meaning the number of executives, of the executive board (Dayan, Ozer, & Almazrouei, 2017). The data will be taken from the Orbis database and added with information from company websites.
Firm age
Industry
Following Brouthers and Brouthers (2003) this study controls for industry. Firms from different industries may react differently to the transaction costs associated with a market entry. This may result in firms from certain industries opting for collaborative entry modes more often compared to other industries. Industry sector is controlled for by dummy variables. Appendix 2 shows the different industries used in the sample.
TMT International Experience
Following the study of Nielsen and Nielsen (2011), which found that prior international experience of the TMT affects the chosen entry mode, this study controls for the international experience of the TMT members. This is consistent with other research, which also found a relationship between entry mode choice and international experience (Herrmann & Datta, 2006). The data is derived from Orbis and online sources such as LinkedIn and company websites. Due to the lack of availability of data, this study will only use this control variable in a robustness check. The variable is measured by adding the international experience of each member of the TMT and dividing it by the amount of TMT members.
3.6 Methodology
4. Results
This section will start with the descriptive statistics of the variables used in the binary logistic regression. Then the results of the regression will be discussed to assess if there is support for the hypothesis. Finally, robustness checks will be performed in order to check the validity of the regression results.
4.1 Descriptive statistics
Table 1 shows all the variables with the number of entries, range, minimum and maximum, and the mean. A full model contains 222 entries. The number of observations could be higher when looking at the information available for the other variables, but information about the nationality of the executive was not always publicly available. The dependent variable, Entry Mode Choice, consists of 82% full ownership and 18% partial ownership. The majority of entry modes are in the developed world which according to the first hypothesis will result in a fully owned subsidiary. Appendix 1 shows the distribution of the FDI cases along with the frequencies and percentages across the target countries. It proved difficult to collect information for the variable TMT International Experience, which explains its relatively low number of observations. Because of the low number of observations this variable is only included in the robustness check.
Variables Obs Mean SD Min Max
Entry Mode Choice 222 0,81 0,40 0 1
Firm Total Assets 222 1.07e+07 2.07e+07 25 1.42e+08
Board Size 222 4,17 2.01 0 11 Industry 222 7,02 3.58 1 14 TMT International Experience 64 4.01 4.01 0 18 Firm Age 222 61.93 55.67 1 256 Institutional Distance 222 0,86 1.46 0,01 10 TMT Nationality Differences 222 0,24 0,26 0 .75
Table 1 Descriptive Statistics
4.2 Multicollinearity
correlation table for the variables used. There seems to be a high correlation between Board Size and Firm Total Assets (0,612), as well as between TMT Nationality Differences and TMT International Experience (0,688). Previous studies used a threshold of 0,7 to indicate a high correlation between variables. None of the correlations recorded between the variables exceeds the thresholds used. It can, therefore, be concluded that there is no high correlation between the variables used in this study.
Variables 1 2 3 4 5 6 7 8
1. Entry Mode Choice 1,00
2. Total Assets -0,143** 1,00 3. Board Size -0,022 0,612*** 1,00 4. Industry 0,016 -0,192*** -0,142** 1,00 5. TMT International Experience 0,013 0,101 0,133 -0,158 1,00 6. Firm Age -0,001 0,293*** 0,242*** -0,249*** 0,069 1,00 7. Institutional Distance -0,302*** 0,228*** 0,200 -0,140** 0,167 0,147** 1,00 8. TMT Nationality Differences 0,055 0,110 0,176** 0,135** 0,688*** 0,191*** 0,127* 1,00 Table 2 Pearson correlations table
4.3 Binary logistic regression
As explained before, the dependent variable entry mode choice is binary, defined as being either 1 (full) or 0 (partial). Given this, I estimate binary logistic regressions. The values will be given as odds-ratios with the p values only given if the effect is significant. The regression is divided among four models which are stated below in table 4. The robustness check is done on model 4 and can be found in the second regression output, table 5.
Model 1: Control Variables
Model 2: Control Variables + Institutional Distance
Model 3: Control Variables + Institutional Distance + TMT Nationality Diversity
Model 4: Control Variables + Institutional Distance + TMT Nationality Diversity + Interaction Effect
Board Size (0.836) increases the likelihood of firms entering through a JV. Industry (1.018) has an effect which is small, but it increases the likelihood of firms from a certain industry choosing a fully owned entry mode. When the effect of a variable is 1, the variable will not increase or decrease the likelihood of any of the outcomes. This is the case for the control variable Company Age (1.000) of which the effect does not increase the likelihood of choosing either a partial or full owned entry mode.
The second model adds the independent variable Institutional Distance to the model. The effect of Institutional Distance (0.444, p=0.000), which is significant at p<0.01, implies that firms are more likely to choose a partially owned entry mode when the institutional distance is high. Hypothesis one, which states that higher institutional distance increases the likelihood of opting for a collaborative entry mode, is therefore supported. This is in line with the reasoning of Contractor et al., (2014) who found that higher institutional distance will lead to firms using a collaborative entry mode. Looking at the control variables, the effect of Industry (0.991) is contrary to that of the previous model in that firms from a certain industry are more likely to choose for a collaborative entry mode. The only significant control variable is still Total Assets (1.231, p=0.053) of which the effect has increased, meaning a larger likelihood of choosing a fully owned entry mode. The effect sizes of Board Size (0.985) and Company age (1.002) are still fairly the same.
Model 3 adds the moderator Board National Diversity to the regression. The effect of the moderator (1.234, p=0.321) is not significant. However, the size of the coefficient indicates that a high TMT national diversity would increase the likelihood of firms opting for a fully owned entry mode. This is contrary to the findings of Nielsen and Nielsen (2011) who found that firms tend to opt for a partially owned entry mode when international diversity in the TMT is high. The effect of the control variables stays relatively similar.
in the TMT compared to firms with a low TMT national diversity. The other variables showed little change in the effect size with Institutional distance and Total Assets still significant.
4.4 Robustness check
In order to test for consistency in the results, the regression is rerun adding the control variable International experience of TMT. The variable is added to see if the results are robust. Because of the limited time available for this study and the difficulty in obtaining some types of data, not all variables have enough observations. Because there was limited information available regarding the international experience of TMT members, this variable is only included in the robustness check. The sample then consists of 64 observations. When rerunning the same tests with a smaller sample, the results should stay relatively similar in order to have consistent results. The results of the robustness check are shown in table 5.
used for the regression. The last variable is the interaction effect. To assess the differencem the regression coefficients will be used instead of the odds-ratios. The coefficient size changed from (-.0174) to (-1.048) in the robustness check. Meaning that the effect still has the same result but only the effect size changed.
Table 3 Logistic Binary Regression Output
Dependent variable Entry Mode Choice Partial (0) Full (1) Model 1 Model 2 Model 3 Model 4
Control variables Company Age 1.000 1.002 1.001 1.002 (0.003) (0.004) (0.004) (0.004) Industry 1.018 0.991 0.977 0.976 (0.052) (0.056) (0.058) (0.058) Board Size 0.836 0.895 0.896 0.892 (0.099) (0.113) (0.114) (0.112) Total Assets 1.203* 1.231* 1.204* 1.211* (0.114) (0.132) (0.130) (0.130) Independent variable Institutional Distance 0.444*** 0.433*** 0.440*** (0.080) (0.079) (0.080) Moderator
Board Nationality Diversity 1.234 1.284
(0.257) (0.282)
Interaction effect
Institutional Distance * Board Nationality Diversity 0.801
Table 4 Regression output Robustness check
Dependent variable Entry Mode Choice Partial (0) Full (1) Model 1 Model 2 Model 3 Model 4
Control variables Company age 0.994 0.992 0.988 0.988 (0.006) (0.008) (0.009) (0.001) Industry 0.879 0.806 0.866 0.823 (0.113) (0.123) (0.147) (0.143) Board size 0.809 0.629 0.671 0.636 (0.224) (0.208) (0.238) (0.249) Total assets 1.103 1.399 1.481 1.394 (0.259) (0.397) (0.459) (0.448) International experience of TMT 1.009 1.020 1.225 1.247 (0.105) (0.113) (0.203) (0.218) Independent variable Institutional distance 0.287* 0.382* 0.493 (0.134) (0.188) (0.268) Moderator
Board nationality diversity 0.248 0.262
(0.225) (0.252)
Interaction effect
Institutional distance * Board Nationality Diversity 0.382
5. Discussion
The following section will discuss the results of the binary logistic regression and compare them with the research hypotheses of this study. When a hypothesis is rejected, an explanation will be given based on previous research. Finally, limitations of the study and areas for future research will be presented.
5.1 Discussion
The fact that institutional distance has an effect on entry mode choice has been documented by numerous researchers (Contractor et al., 2014; Xu & Shenkar, 2002). The studies that looked into the effect institutional distance has on entry mode choice are not unanimous on the effect it has (Hutzschenreuter et al., 2015). This, combined with the relatively little academic attention the theory has received, has led to this study aiming to provide new light on the discussion. Therefore, hypothesis one was drafted to test the effect institutional distance has on entry mode choice. The results of the regression support the first hypothesis. The odds-ratio of the effect of Institutional Distance (0.444, p=0.000) is significant and below 1. This means that when institutional distance is high firms are more likely to opt for a collaborative entry mode. The results support Xu and Shenkar (2002) reasoning, which argued that higher institutional distance will drive to firms enter foreign market using a collaborative entry mode. There are several reasons why a larger institutional distance will lead firms to opt for a collaborative entry mode. Large institutional distances between countries make it difficult to transfer organizational practices to the host country (Kostova & Zaheer, 1999). These difficulties affect the legitimacy of the firm operating in a host country creating internal and external legitimacy problems (Kostova & Zaheer, 1999; Xu & Shenkar, 2002). To overcome these legitimacy problems, firms will enter the host market through a collaborative entry mode.
entry mode. To say something about the moderating effect of TMT national diversity the results of the interaction effect must be looked at. The regression coefficient results (-0.174, p=0.198) will be used instead of the odds-ratios. The results mean that the negative effect of Institutional Distance on the likelihood of firms choosing a fully owned entry mode will be stronger for firms with a high national diversity in the TMT compared to firms with a low TMT national diversity. Because the results are not significant, it is hard to provide a final answer to the hypothesis. Therefore, the second hypothesis has to be rejected on the basis of the results being insignificant although the direction of the effect is as hypothesized.
To conclude, hypothesis one is supported and the results significant. The second hypothesis is supported as well, but the results are not significant. The hypothesis is therefore rejected. The results shed new light on the relationship between entry mode choice and institutional distance. Although there is no significant support for the second hypothesis, the fact that the effect is the same as hypothesized could indicate that more research can provide significant results for its effect.
5.2 Limitations and recommendations for future research
This research has several limitations which are important to recognize and could provide areas for future research. The first limitation is that this study only focused on FDI from Germany to foreign countries. Germany has characteristics which make it unique as a country. Therefore, using another country may provide different results. As Germany is a European country, it would be interesting to see what the effect would be of using a country from a different geographical region like Africa or the Americas. It will also be interesting to look at FDI coming from a developing country. Future research could, therefore, focus on different countries.
This study looked at the effect TMT characteristics have on the perception of institutional distance. The argument could be made that the perception managers have of institutional distance could be made to other forms of distance. Besides institutional distance, scholars found other distance measures that have an influence on entry mode choice. Two of the most common used distant measures in IB research are psychic distance (Johanson & Vahlne, 1977), and cultural distance (Kogut & Singh, 1988). Another less used measurement which could be interesting to use is economic distance. Economic distance measures the level of economic development of the host country compared to the home country. Using the same moderator effect on the relationship between one of these distances and entry mode choice could provide new insights into the entry mode choice literature.
Institutional distance in measured by using the WGI index of Kaufmann et all (2009). The WGI index is composed of six different dimensions. This study used a distance comprised of the average across those dimension in one index. However, the effect of one dimension, for example level of corruption, could be higher compared to another dimension. It would be interesting to see what the effect is for each dimension, instead of all the dimensions bundled together. Therefore, future research should focus on each of the dimension on its own or uncover other dimensions.
This study includes all the industries Germany has. Some industries like the machinery, equipment, furniture and recycling industry are more present in the sample (28%) than other industries. Industries like the pharmaceutical industry could be more likely to engage in JV compared to other industries. Looking into the effect different industries have on entry mode choice would be interesting.
6. Conclusion and Implications
This study looked into the effect institutional distance has on the chosen entry mode, being full or partial owned, of German firms conducting FDI. In addition, the moderating effect of nationality differences in the TMT on the aforementioned relationship is examined. The main research question of this study is: What is the effect of board nationality diversity on the relationship between institutional distance and entry mode choice?
Hutzschenreuter et al., (2016) found that the limited number of studies that looked into this relationship found ambiguous results regarding the relationship between institutional distance and entry mode choice. This research aims to contribute to the existing research on entry mode decisions. Furthermore, this research tried to look into the effect managerial characteristics have on the perception of distance. Nielsen and Nielsen (2011) state that studies focus on the rational choice and fail to take into account the effect of managerial characteristics on that choice.
The results of this study indicate that firms tend to opt for a partially controlled entry mode when institutional distance is high. The results are highly significant (0.444, p=0.000). This effect is in line with the first hypothesis, and therefore hypothesis one is supported. Hypothesis one follows the reasoning of Shenkar and Xu (2002) which argues that firms will choose a collaborative entry mode when institutional distance is high. The reasoning behind it is that a large institutional distance will make it difficult to transfer organizational practices to the host country (Kostova & Zaheer, 1999). This will affect the legitimacy of the firm operating in the host country and create internal and external legitimacy problems (Kostova & Zaheer, 1999; Xu & Shenkar, 2002). To overcome these legitimacy problems, firms will want a local partner and therefore enter by a collaborative entry mode.
Nielsen (2011) were one of the first scholars that found a direct effect of high TMT national diversity on the chosen entry mode. International managers feel confident that they can overcome the differences between the countries. That the effect found is in line with the stated hypothesis, and provides input for further research on the effect of TMT national diversity on the perception of distance.
The results of this research paper will help managers in making entry mode decisions and help scholars by adding to the existing literature on entry mode decisions, institutional distance, and upper echelons theory. This study shows that managers need to take into account institutional distance as a factor, as it influences the preference for a full or partial owned entry mode. The second point of interest for managers is the influence of managerial characteristics on the decision-making process, especially in the case of rational choice models like institutional distance. Despite the insignificant results of the moderator, other scholars like Nielsen and Nielsen (2011) show the effect of nationality on the entry mode decision process. Being aware of the influence could improve the decision-making process by knowing which factors could lead to a preference for a certain entry mode.
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Appendix 1
Appendix 1 Target country distribution
Target country Number of acquisitions Percentage of total
SI 2 0,9% TN 1 0,5% TR 1 0,5% US 51 23,0% VE 1 0,5% Total 222 100%
Appendix 2
Appendix 2 distribution across industries
Industry Total per industry Percentage of total
Chemicals, rubber, plastics, non-metallic
products 32 14%
Construction 3 1%
Food, beverages, tobacco 1 0%
Gas, Water, Electricity 8 4%
Insurance companies 3 1%
Machinery, equipment, furniture, recycling 63 28%
Metals & metal products 10 5%
Other services 50 23%
Post and telecommunications 3 1%
Primary Sector (agriculture, mining, etc.) 1 0%
Publishing, printing 25 11%
Textiles, wearing apparel, leather 4 2%
Transport 4 2%
Wholesale & retail trade 15 7%
Appendix 3
Logistic Binary Regression Output with coefficients
Dependent variable Entry Mode Choice Partial (0) Full (1) Model 3 Model 4
Control variables Company age 0.004 -0.008 (0.004) (0.009) Industry -0.524 -0.205 (0.058) (0.171) Board size 0.150 0.068 (0.122) (0.421)
Total assets -1.84e-0.8* -1.31e-09
(1.09e-08) (3.31e-08) International experience of TMT 0.258 (0.184) Independent variable Institutional distance -0.776*** -0.569* (0.176) (0.518) Moderator
Board nationality diversity 0.323 -1.284
(0.222) (0.939)
Interaction effect
