Corporate Governance and Internationalization: Theory and evidence from the United States (2014)

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Corporate Governance and

Internationalization: Theory and evidence

from the United States (2014)

Stephan Jongsma (s2610086)

s.jongsma.3@student.rug.nl

Supervisor: dr. Gjalt de Jong

Master Thesis International Business & Management

University of Groningen

Faculty of Economics and Business

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Abstract

Internationalization remains one of the key features for multinational enterprises. The aim of this research is to understand the antecedents for internationalization. This study enhances the literature in this field and explores the impact of board age diversity on the degree of internationalization. Younger people are perceived to be more flexible, are higher risk-takers and have a better appreciation of new concepts and technologies in comparison to older people. However, the board may benefit from previous experience of current members. Because of this, the combination of younger and older people in one board is expected to positively influence the degree of internationalization. In relation to this, this research will investigate the role of the chairman of the boards, controlled by firm- and board size, debt ratio and industry. Findings suggest board age diversity and chairman age are not significantly related to internationalization, in this research, but are context dependent and significantly controlled by firm and board size.

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List of figures and tables

Figure 1 : Conceptual model

Figure 2 : Graphical analysis of normality assumption Figure 3 : Scatterplot

Table 1 : Industry categorization

Table 2 : Variables, descriptions and measures

Table 3 : Koenker’s Breusch-Pagan test for heteroscedasticity Table 4 : Test for multicollinearity

Table 5 : Descriptive statistics

Table 6 : Regression results of the impact of board age diversity on internationalization Table 7 : Literature overview

Table 8 : List of companies

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1. Introduction

In the modern world economy of today, internationalization remains one of the key features for multinational enterprises. Going abroad has led to a great success for many firms, whereas other firms fail. The aim of this research is to understand the antecedents for successful internationalization. More in particular, this research aims to understand whether, and if so, how, board composition matters for successful internationalization. It is known that large companies have boards, but among companies the composition of boards various tremendously. Diversity in board tenure, board previous internationalization experience, board size, board age etcetera can be identified and is particularly interesting from a managerial point of view. From a practical standpoint, top management team (TMT) composition, and board structure are factors that a board and management can directly control in international firms (Ghoshal and Nohria, 1989; Kim and Mauborgne, 1991, 1996). Given that, and also that a firm’s degree of internationalization is an important determinant of the complexity it faces, this research studies the relation between a firms’ degree of internationalization and its governance. Related to the management theory, evidence on board composition antecedents on the degree of internationalization might be of great importance for the board of directors in order to adjust or adapt the right strategy for the company. It can be expected that board age diversity will have a positive effect on internationalization for two reasons. On the one hand younger people are perceived to be more flexible, are higher risk-takers and have a better appreciation of new concepts and technologies in comparison to older people. On the other hand, the board may benefit from previous experience of current members. These senior members often have strong social networks and clout from which the company can leverage (Jhunjhunwala and Mishra, 2013). Because of this, the combination of younger and older people in one board is expected to positively influence the degree of internationalization. In relation to this, this research will investigate the role of the chairman of the boards. The chairman’s of boards differ in age, previous experience, tenure etcetera and therefore it can be expected, for instance, that a board with a high diversity in age headed by a young Chairman will export more than a board with a lower diversity in age headed by a relatively old chairman. In other words, the relationship between board composition diversity and internationalization will be moderated by the specific characteristics of the chairman. Therefore, the main research question of this study is:

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6 In order to answer the main research question the following sub questions are addressed;

1. What is board (age) diversity and how can this be measured? 2. What is internationalization and how can this be measured?

3. What is the relation between board age diversity and internationalization?

4. What is the moderator effect of chairman age on the relationship between board age diversity and internationalization?

5. Is there any evidence for this relationship in the United States?

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2. Literature Review

In order to find out the impact of board diversity on the internationalization of the firm, this section addresses the research questions mentioned in the introduction, by reviewing existing literature on these subjects. This study starts with focusing on board diversity and internationalization and how these are measured. Subsequently, the paper adds more complexity by including a moderator. Table 7 (Appendix I) provides an overview of the described literature in this section containing the authors’ main topic of research and their argumentation and findings.

2.1. Board (age) diversity

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8 measures of executive orientation. The latter goes through a filtering process resulting in managerial perceptions (Hambrick and Mason, 1984) or construed reality (Finklestein and Hambrick, 1996). In turn, these managerial perceptions affect executive’s actions and thus strategic choices. Based on this upper echelon framework, existing research has linked demographic diversity of the board of directors or top management teams to a multiplicity of organizational outcomes including strategic decisions on internationalization. Additional current research on boards has defined that the board is a group of directors which are elected or appointed by the shareholders in order to oversee the company’s activities, which are entrusted with the overall direction of the enterprise (Jhunjhunwala and Mishra, 2013). It has also been stressed that a well-performing board needs diversity of knowledge, skills, and perspectives. According to Jhunjhunwala and Mishra (2013) board diversity refers to: ‘’The

heterogeneous composition of the board in terms of gender, age, race, education, experience, nationality, lifestyle, culture, religion, and many other facets that make each of us unique as individuals’’. Yılmaz Argüden (2010) rightly commented that if everybody thinks in the same

way, what is the need of a board? Williamson (1984) stated that the monitoring control, and incentive arrangements surrounding the members of a top management team is described by governance structure. Accordingly, a top management team is also the group of executives that is most closely monitored by the board (Jensen and Murphy, 1990). Therefore we can assume from the theory that a board of directors is ultimately responsible for the overall strategic decisions of the firm and can be used as unit of analysis. In this study we particularly focus on board age diversity. A common technique that researchers have used in studies to measure diversity in terms of age is by computing the coefficient of variation in age of the members of the team (Knight et al., 1999; Pelled et al., 1999).

2.2. Internationalization

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9 1965) and the liabilities of foreignness (Hymer, 1976; Zaheer, 1995). For firms whose home country market is limited it is very important to have a clear growth strategy in order to be able to internationalize. This enables the firm to increase their market power (Kogut, 1985), realize economies of scale and scope (Caves, 1996) and to reduce input costs (Dunning, 1988). An internationalization growth strategy also allows firms to exploit their firm-specific assets in international markets (Caves, 1996; Delios & Beamish, 1999). Firms that are already present in foreign countries have opportunities to access host-country-specific advantages and, in turn increase their knowledge base, capabilities, and competitiveness through experiential learning (Barkema & Vermeulen, 1998; Ghoshal & Bartlett, 1990). In addition, managing subsidiaries in host countries is a complex process and requires significant internal coordination (Hsu et al., 2013). The authors suggest that one source of complexity arises from the great diversity among cultures, competitors, customers and regulations. Managers are forced to invest in time and effort to establish the firm’s presence, when entering a new market. They emphasize that senior manager having a domestic managerial mindset, are mostly unprepared and unfamiliar for new cultures, and therefore pressuring the management to fragment their geographic attention (Ghoshal & Nohria, 1989). Starting operations into a highly distant and institutional country may therefore negatively influence a firm’s performance. The second source of complexity suggested by Hsu et al. (2013) is competitive pressure. According to Bartlett & Ghoshal (1989), firms must extract synergies across products and markets and develop a sense of community within the organization’s global web of subsidiaries in order to compete worldwide. Internal coordination and both complexities increase the information processing demands and workload placed on senior managers, to be successful. Internationalization is interpreted as the extent of a firm’s present involvement in international operations (Luostarinen and Welch, 1990; Buckly and Ghauri, 1999). Another definition of internationalization in the literature and also used in this research is: ‘’the degree

to which an MNE is active in multiple countries via subsidiaries or exports, and thereby implicitly also addresses the geographical diversification’’ (Lu and Beamish, 2004). The

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10 2.3. Board age diversity and internationalization

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11 members often have strong social networks and clout from which the company can leverage. Therefore, the following hypothesis can be derived from the theory:

Hypothesis 1: Board age diversity is positively related to the internationalization of the firm. 2.4. Chairman age and internationalization

This study also attempts to fill the research gap by incorporating the effect of the age of the chairman of the board related to the degree of internationalization. The chairman’s of boards also differ in age, previous experience, tenure etcetera. In this study the relationship between board age diversity and internationalization is moderated by the specific characteristic, age, of the chairman. Moving into new international locations increases the information-processing demands resulting in more complexity (Roth, 1995; Sanders & Carpenter, 1998; Tihanyi & Thomas, 2005). A chairman of the board or a CEO plays a key role as his or her attributes exert a critical impact on the firm’s ability to process the information associated with internationalization (Roth, 1995). Hambrick and Mason (1984) also suggest that CEO characteristics greatly influence their interpretation of strategic decision-making situations and, in turn, affect the firm’s outcome. The upper echelons theory proposes also that, managers should possess characteristics that enable them to process information effectively in order to manage international ambiguity and complexity (Herrmann & Datta, 2002, 2006; Nielsen & Nielsen, 2011). Therefore, based on the discussed theories, it is of great importance why and how the attributes of a chairman matter. When going global, it is highly necessary for firms to learn how to operate in new cultural and institutional settings. Setting up a new subsidiary leads to a firm and its managers being confronted with new experiences in terms of customers, competitors, and stakeholders (Barkema, Bell, & Pennings, 1996). Managers are simultaneously required to adapt their home-grown mental maps and, consequently, the structures, systems, and processes rooted in these maps to fit a new international setting (Nohria & Ghoshal, 1994). Younger managers have more physical and mental stamina, and are better able to change their mental maps easily, which may result in a poorer degree of information processing capability for older managers (Herrmann & Datta, 2002; Taylor, 1975). This may limit their understanding of foreign cultures, consumer behavior and local regulations and may reduce the benefits of internationalization. The following hypothesis can be derived from the above set of arguments.

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12 Figure 1 depicts the conceptual model based on the existing academic literature as described in the previous subsections.

H1: Positive

H2: Negative

Figure 1 Conceptual Model

3. Research Methods

In this section I will introduce the sample I will use for the empirical test of the hypothesis specified above. Additionally, I will describe the how the variables are operationalized and provide an assessment of whether the methodological assumptions are satisfied.

3.1. Sample

Orbis is used to gather data on executive information and internationalization. This dataset is compiled by Bureau van Dijk and contains information on 18 million companies in the United States. The prevailing objective of this paper is to discover the relationship between board age diversity and internationalization of the firm, with the age of the chairman as a moderator effect. We sample the board members of the 84 largest leading United States firms by firm size, in terms of operating revenue, listed by Orbis combined with Fortune 500. For each corporation we collect data on individual board members (incl. chairman) with regards to the age of the members. Data on the ages of board members is gathered from corporate websites, Bloomberg1 and NNDB2. Data on the dependent variable, degree of internationalization, and on the control variables are collected from the Orbis database. The outliers in this sample have been equalized with the calculated upper and lower bound limits (Fields, A., 2009) for all relevant variables, due to a relatively small sample size.

1_{Bloomberg Business delivers business and markets news, data, analysis, and video to the world, featuring}

stories from Businessweek and Bloomberg News.

2

NNDB is an intelligence aggregator that tracks the activities of people we have determined to be noteworthy, both living and dead.

Board Age Diversity

Chairman Age

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13 3.2. Dependent Variable

The dependent variable is degree of internationalization. In this paper internationalization is measured in terms of the number of foreign countries that each firm operates, via subsidiaries. The data on internationalization is gathered from the corporate websites.

3.3. Independent and Control Variables

The independent variables are board age diversity and chairman age. Again, Orbis, Bloomberg and NNDB are the sources used to gather data on the age of board members and the chairman. Age is measured from the date of birth. This paper uses the coefficient of variation (standard deviation divided by the mean) to measure the board age diversity (Allison, P. D., 1978). The control variables are included in order to test the validity of this research. These are variables that are held in constant in order to assess or clarify the relationship between the dependent and independent variables. In order to exclude the influence of other risk factors on the internationalization of the firm several control variables are incorporated. First, industry is incorporated as control variable. Industries might have different levels of internationalization and are therefore categorized. To control the effect of industry, the paper uses dummy variables. Based on the Bureau van Dijk major sector classification (BvD), the paper identifies five major industry categories, namely: Mining, utilities and construction, manufacturing, professional & information services, wholesale and retail and other services. A frequency table (table 1), indicates the number of companies for each industry.

Table 1 Industry Categorization

a

Obtained from Orbis: BvD major sector classification

Category N Initial Industry Categorization a _N

I1 (Mining, utilities & construction) 5 Gas, Water, Electricity 3

Primary sector 2

I2 (Manufacturing) 38 Chemicals, rubber, plastics, non-metallic products 16 Machinery, equipment, furniture, recycling 16

Food, beverages, tobacco 6

I3 (Professional & information services) 17 Post & telecommunications 3

Publishing, printing 3

Insurance companies 4

Banks 1

Transport 5

Education, Health 1

I4 (Wholesale & retail) 16 Wholesale & retail trade 16

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14 The second and a commonly adopted resource-based control variable is firm size, measured by the logarithm of employees. Larger firms are typically more capable of exploiting economies of scale which in turn allow a larger return on assets and sales (Chao and Kumar, 2010; Gomez Mejia and Palich, 1997) and therefore firm size may influence a company’s degree of internationalization, since they might have more power to internationalize compared to smaller firms. Thirdly, we control on board size, since firms with more human resource achieve substantial internationalization. Successful firms often have sufficient members playing distinct roles, working together and providing a variety of resources to deal with the turbulent environment of foreign markets. Existing research indicates that larger boards provide firms with depth and breadth of tangible financial assets and intangible cognitive resources. Therefore, larger boards with more physical, and interrelation resources fit better in situations of uncertainty and more uncontrollable factors from international markets (Levy, 2005). The fourth control variable is debt ratio. Debt ratio may affect a firm’s ability to expand and impact its performance. Because of this, firms facing debts might be less likely to internationalize. Data on total liabilities and assets to calculate the debt ratio is collected from Orbis, balance sheets from corporate websites, and ycharts3. An overview of all variables and relevant details can be found in table 2 below.

Table 2 Variables, Description and Measures

* Based on the BvD major sector classification from Orbis

3

YCharts is a financial software company providing investment research tools including stock charts, stock ratings and economic indicators.

Type Variable Description Measure

Dependent Internationalization The number of foreign countries that a firm operates Continuous Independent Board age diversity Coefficient of variance (i.e. st.dev. / mean) of board members Ratio Independent Chairman age Age as established by year of birth Continuous

Control Firm size Number of employees Continuous

Control Board size Number of board members (incl. chairman) Continuous Control Debt ratio Total liabilities / total assets Ratio

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Chi2 = 0.854

Prob > Chi2 = 0.653 H0: Homoskedasticity

Variables: Board age diversity, Chairman age 3.4. Evaluation of method assumptions

The OLS regression model will be used to test all hypotheses in the full sample period during the year 2014 In order to provide the best linear unbiased estimates (BLUE), OLS makes four crucial assumptions which have to be satisfied, namely; homoscedasticity, multicollinearity, endogeneity and normality.

Homoscedasticity

OLS assumes that the variance of the error term is constant (homoscedastic) and the same for all observations (i) (var(ei) = σ²). Heteroscedasticity is present, if this assumption is violated and the error variance for all observations is not identical. Heteroscedasticity results in biased estimates of the standard errors which leads in turn to bias in the test statistics and thus to incorrect hypotheses tests, p-values and confidence intervals. Heteroscedasticity itself does not lead to biased coefficients estimates thus OLS is still a linear and unbiased estimator, but no longer the best with the smallest variance (Hill, Griffiths & Lim, 2009). The problem with heteroscedasticity is that more weight is given to observations with potentially larger error terms. In that case observations furthest away from the true regression line provide us with the least information about the true regression line. In case heteroscedasticity is detected, there are methodological ways to correct for the weight of larger error variances to get estimates with the smallest sum of squared errors. Figure 2 in appendix 4 plots the residuals, which estimate the errors, against internationalization, measured by the number of foreign countries that the firm operates. According to this graph there appears to be no problem with heteroscedasticity. In order to determine whether

or not this will be a problem, Koenker’s version of the Breusch-Pagan test for heteroscedasticity has been computed. This test has been chosen since it provides more reliable results with

smaller sample sizes (Koenker, 1981). Table 3 shows that heteroscedasticity is not an issue, since the test provides an insignificant result, and since in this sample is measured for one period in time (2014) it is unfeasible to test for autocorrelation.

Endogeneity

OLS further assumes that the error term is uncorrelated with the independent variables. If this assumption is violated such that xi is correlated with unmeasured variables (ei), then it will consistently overestimate the effect of xi on y. Consequently least square estimates are

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Variable VIF 1/VIF

Mining, utilities & construction 1,638 0,611

Manufacturing 2,116 0,473

Professional & information services 1,714 0,583 Wholesale & retail 1,792 0,558

Firm size 1,695 0,590

Board size 1,316 0,760

Debt ratio 1,132 0,883

Board age diversity 1,409 0,710

Chairman age 1,107 0,903

Board age diversity * Chairman age 1,474 0,678

Mean VIF 1,539

inconsistent and do not converge even in large samples. In addition, none of the hypothesis test procedures are valid (Hill et al., 2009: 272). There is no simple statistical or numerical test for this assumption and needs therefore to be satisfied theoretically. This is because the sample residuals will always be uncorrelated to the independent variables, so using those to test for endogeneity will not be appropriate (Hill et al., 2009). From a theoretical point of view there is no reason to assume board age diversity or chairman age tenure to be correlated with unobserved variables in the error term as they can easily be estimated and observed. Therefore, the exogenous nature of the independent variables in this study has to be assumed.

Multicollinearity

Another assumption of OLS is that the independent variables are not perfectly correlated such that “the values of xik are not exact linear functions of other explanatory variables” (Hill et al., 2009: 154). If this assumption is violated, variables are said to be collinear, which makes it difficult to isolate the relationship between variables. To test whether multicollinearity is present, the variance inflation factor (VIF)

has been calculated (table 4), estimating how much the variance of an estimated regression coefficient is inflated due to collinearity. From this table we can conclude that the multicollinearity is not problematic as all variables have values well below the cut-off value of 10 recommended by Neter et al. (1985). For all correlation values, see appendix IV (table 9).

Normality

The final test examines whether the normality assumption is satisfied, since OLS assumes that the values of the error term are normally distributed about their mean. A violation of the normality assumption might lead to biased p-values and thus affects the test for statistical significance (Hill et al. 2009). Following a graphical analysis from figure 2 (appendix III), which plots the residuals against the normal distribution (straight line), it can be concluded that the residuals are not normal distributed, approximately.

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4. Empirical Results

4.1. Descriptive statistics

Table 5 below provides an overview of the most relevant descriptive statistics for leading U.S. firms. The sample consists of 84 companies, ranked by operating revenue (Orbis Database). The table shows the means, standard deviation and the minimum and maximum of the variables used in this research. The degree of internationalization has an average of 53 among the top firms selected and varies from 0 to 200. The highest diversity in board age among board members is 0.19 and 0.03 for the lowest diversity with on average 0.11. The age among chairman’s’ is on average 61 with an age of 84 for the oldest and 49 for the youngest chairman. The control variable firm size shows that the smallest firm had 75 and the largest 2 million employees with on average 135493 employees per firm. The board size of companies is on average 12 with the smallest board of 4 and largest board of 17 members. The firm with the smallest debt ratio in this sample is 0.15 and 1.08 with the highest debt ratio with on average 0.54, which indicates that firms in this sample have on average more assets than debts (i.e. debt ratio < 1).

Table 5 Descriptive Statistics a (N=84).

a

See appendix 4 (table 9) for a more elaborate version of this table including correlations.

b_{For industry categorization see table 1.}

In appendix 4 (table 9), a more elaborate version of this table can be found including the industry variables and the correlations between the indicators. This table shows that all values of the correlation coefficients are below 0.8, which is the common threshold value for multicollinearity, also confirmed by the VIF values which are substantially lower than 10. The correlation among the independent variables is rather small with its highest absolute values between the control variables and industry dummies still well below any critical value.

Variable Mean St. Dev. Min Max

Dependent variable

Internationalization 52.92 56.17 0 200

Independent variables

Board age diversity 0.11 0.03 0.03 0.19

Chairman age 60.96 6.87 49 84

Control variables

Firm size 135493.36 245962.86 75 2,00E+06

Board size 11.67 2.36 4 17

Debt ratio 0.54 0.19 0.15 1.08

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18 4.2. Regression results

Table 6 below provides a summary of OLS regression results. All independent variables have been standardized before calculating the interaction term and entering them into the regressions in order to avoid multicollinearity problems (Baron & Kenny, 1986). Additionally, this also makes the interpretation of the regression coefficients more meaningful since the value of 0 does not exist nor occur for this study’s independent variables (Siero, et al., 2009). The various fit parameters show that the overall model fits the data well as indicated by the significant F-statistics along all four models. Also the R2 improves from 26.7% in model 1 to 29% in model 4. There is thus statistical support to reject the null hypothesis of all coefficients being 0.

Table 6 Regression Results of the Impact of Board Age Diversity on the Degree of Internationalization (N=84).

The first model estimates the effect of industry effects and other control variables on the degree of internationalization, excluding the two independent variables. The other services industry is chosen as control group and the findings of the remaining industry groups are interpreted accordingly. The industry groups all show positive significant results, except for

Model 1 Model 2 Model 3 Model 4

Constant -0.713 (0.233) -0.711 (0.236) -0.716 (0.234) -0.717 (0.238)

Control variables: Industry

Mining, utilities & construction 0.085 (0.510) 0.086 (0.515) 0.094 (0.511) 0.095 (0.530) Manufacturing 0.468*** (0.275) 0.465*** (0.286) 0.468*** (0.283) 0.468*** (0.286) Proffesional & information services 0.287** (0.318) 0.287** (0.320) 0.292** (0.317) 0.292** (0.319) Wholesale & retail 0.389*** (0.443) 0.389*** (0.446) 0.383*** (0.442) 0.383*** (0.447)

Firm size 0.283** (0.125) 0.285** (0.127) 0.284** (0.126) 0.285** (0.128) Board size 0.218** (0.107) 0.219** (0.108) 0.228** (0.107) 0.226** (0.113) Debt ratio 0.041 (0.102) 0.039 (0.104) 0.062 (0.104) 0.061 (0.105)

Board age diversity -0.010 (0.107) -0.019 (0.106) -0.021 (0.117)

Chairman age 0.155 (0.100) 0.154 (0.104)

Board age diversity * Chairman age 0.005 (0.081)

Model fit

Observations (N) 84 84 84 84

R2 0.267 0.267 0.290 0.290

Adjusted R2 0.200 0.189 0.204 0.193

F-value 3.958*** 3.419** 3.366** 2.989**

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20 4.3. Robustness test

Robustness checks are frequently used to examine how certain empirical coefficients estimates are. When the model specification is modified by adding or removing repressor, it is for example investigated how these regression coefficients behave. In case these coefficients do not change sign and magnitude significantly following such modifications, it is commonly taken to be evidence that estimates are robust. Generally, we speak of structural validity when coefficients are plausible and robust (White and Lu, 2010). First I will test a different measurement standard of the dependent variable internationalization. So far, the degree of internationalization is measured in terms of the number of countries that a firm operates and this makes the variable measurement continuous. However, there are only 201 countries4 that a firm theoretically can enter, making this measurement limited. So, instead of looking only at absolute values, it can be useful to check whether the regression coefficients remain the same when transforming data on internationalization in a ratio. In this way, values become relative to the maximum number of countries that firms can possibly enter. In appendix 5 (table 10) the regression results are shown. When looking at the coefficients and the model fit, we see no changes in the results and therefore we can conclude that the different standard (i.e. absolute vs. relative) of measuring the degree of internationalization make no difference. As a second robustness check, I will delete the outliers from the total sample. The Cook’s distance is calculated to specify influential cases in the independent variables (Siero, Huisman & Kiers, 2009), if the distance exceeds the upper or lower bound limit, the observation is seen as influential. Having calculated these limits, 6 firms are identified that exceeds either one or multiple variables. Outliers are extreme values that can misrepresent the regressions coefficients. Variables that are indicated as outliers are excluded from the dataset. In appendix 5 (table 11), the regression results are shown for the adjusted sample (i.e. outliers excluded). From this table we can see that the overall model fit increased in significance level, minor changes in the coefficients and a decrease in significance level of board size. However, for this research it is decided to follow the regression results with the outliers included, due to a relatively small sample size, as explained in the research method (paragraph 3.1).

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5. Conclusions

Firm internationalization studies report ambiguous and sometimes contradictory findings on internationalization (Hitt et al., 1997; Lin, Lui and Cheng, 2011; Tihanyi et al., 2005). While a vast amount of literature on firm internationalization in relation to performance is available, more understanding is needed for internationalization as a dependent variable. Previous research on internationalization did not clearly focus on one specific demographic attribute of board members from the U.S. Using the upper echelons theory, internationalization framework and the information/decision making perspective (Williams and O’Reilly, 1998) I have tested the variable age diversity on the boards of 84 leading U.S. firms. This sampling frame results in a total of 980 board directors. The results of this research reject hypothesis 1 which implies that there is no relationship between board age diversity and the degree of internationalization. A possible explanation for this outcome could be the fact that board age diversity might have an inverted U-shape instead of a linear relationship. When diversity in board age becomes too great, this may cause synergy problems. According to Taylor (1975), younger managers have a higher ability to organize information effectively, which may result in better performance, with regards to the decision making process, than older managers. When these individual characteristics between members in a board differ tremendously, it may have a negative effect on the collaboration between board members when diversity in the board becomes too great and therefore the degree of internationalization might decrease at some point. Also hypothesis 2 is not confirmed in this research. In the literature section it is described that chairman age negatively moderates the relationship between board age diversity and firm internationalization. This is supported by existing literature where managerial age is related to risk propensity and to the formulation of innovative strategies (Barker and Mueller, 2002). However, due the relatively small sample size future research is necessary to confirm this hypothesis.

5.1. Added value of this study

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22 influences a company’s degree of internationalization, since they might have more power to internationalize compared to smaller firms. Finally, this paper makes an important managerial implication regarding the board size, since this paper shows that also larger boards play an important role since it provide firms with depth and breadth of tangible financial assets and intangible cognitive resources. Consequently, larger boards with more physical, and interrelation resources fit better in situations of uncertainty and more uncontrollable factors from international markets (Levy, 2005).

5.2. Limitations and future research

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6. Bibliography

Allison, P. D. (1978). Measures of inequality. American Sociological Review. 43: 865-880 Argüden, Y. (2010). Diversity at The Head Table, Bringing Complementary Skills and Experiences to the Board, Private Sector. Opinion 19. A Global Corporate Governance

Forum Publication.

Bantel, K. A., and Jackson, S. E., (1989). Top Management and Innovations Banking: Does the Composition of a Top Team Make a Difference? Strategic Management Journal,

Summer Special Issue. 10:107-124.

Barkema, H. G., and Vermeulen, F. (1998). International expansion through start-up or acquisition: A learning perspective. Academy of Management Journal, 41(1): 7–26. Barker, V. L. and Mueller, G. C., (2002). CEO Characteristics and Firm R&D Spending.

Management Science. 48(6): 782-801.

Baron, R. M., and Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations.

Journal of Personality and Social Psychology, 51: 1173–1182.

Bartlett, C. A., & Ghoshal, S. (1989). Managing across borders: The transnational solution. Boston, MA: Harvard Business School Press.

Buckly, P. J., and Ghauri, P., (1999). The internationalization of the firm. London:

International Thomson Business Press.

Cannella, A. A., & Holcomb, T. R. (2005). A multilevel analysis of the upper echelon model. In F. Dansereau & F. Yammarino (Eds.), Multilevel issues in strategy and methods. Oxford: Elsevier.

Caves, R. E. (1996). Multinational enterprise and economic analysis. MA: Harvard University Press.

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24 Child, J. (1974). Managerial and organizational factors associated with company performance. Journal of Management Studies, 11(1): 13–27.

Contractor, F. J., Kumar, V., and Kundu, S. K. (2007). Nature of the relationship between international expansion and performance: The case of emerging market firms.

Journal of World Business, 42(4): 401–417.

Cyert, R. M. and March, J. G., (1963). A Behavioral Theory of the Firm. Prentice-Hall,

Englewood Cliffs, NJ.

Delios, A., and Beamish, P. W. (1999). Geographic scope, product diversification and the corporate performance of Japanese firms. Strategic Management Journal, 20(8): 711–727.

Dunning, J. H. (1988). The eclectic paradigm of international production: A restatement and some possible extension. Journal of International Business Studies, 19(1): 1–32.

Fields, A. (2009). Discovering Statistics Using SPSS Third Edition, London: Sage.

Finkelstein, S., and Hambrick, D. C., (1996). Strategic Leadership: Top Executives and their Effects on Organizations. West St. Paul, MN.

Ghoshal, S. and Nohria, N., (1989). International Differentiation within Multinational Corporations. Strategic Management Journal. 10: 323-337.

Glick, W. H., C. C. Miller and G. P. Huber (1993). The Impact of Upper-echelon Diversity on Organizational Performance. In G. P. Huber and W. H. Glick (eds.), Organizational Change and Redesign: Ideas and Insights for Improving Performance. Oxford University

Press, New York. 176–214.

Gomez-Meija, L. R., and Palich, L. E., (1997). Cultural Diversity and the Performance of Multinational Firms. Journal of International Business Studies. 28: 309-335

Hambrick, D. C., and Mason, P. A., (1984). Upper echelons: The organization as a Reflection of its Top Managers. Academy of Management Review. 9(2): 193-206.

Herrmann, P., & Datta, D. K. (2002). CEO successor characteristics and the choice of foreign market entry mode: An empirical study. Journal of International Business

(25)

25 Herrmann, P., & Datta, D. K. (2006). CEO experiences: Effects on the choice of FDI entry mode. Journal of Management Studies, 43(4): 755–778.

Hill, R. C., Griffiths, W. E., and Lim, G. C. (2009). Principles of Econometrics 4th Edition. John Wiley & Sons Ltd.

Hymer, S. (1976). The international operations of national firms: A study of direct investment. Boston, MA: MIT Press.

Jhunjhunwala, S., and Mishra, R. K., (2013). Diversity and the Effective Corporate Board: Diversity Toward an Effective Board. Academic Press Forbes. 1-11.

Johanson, J., and Vahlne, J. E., (1990). The Mechanism of Internationalization.

International Marketing Review. 7(4): 11-24.

Jong, de G., and Houten, van J., (2014). The Impact of MNE Cultural Diversity on the Internationalization Performance Relationship: Theory and Evidence from European Multinational Enterprises. International Business Review. 23: 313-326.

Jong, de G., and Witteloostuijn, van A., (2009). Ecology of National Rule Birth: A Longitudinal Study of Dutch Higher Education Law, 1960-2004. Oxford University Press. 20: 187-213.

Kim, W., and Mauborgne, R., (1991). Implementing Global Strategies: The Role of Procedural Justice. Strategic Management Journal. 12: 125-143.

Kim, W., and Mauborgne, R., (1996). Procedural Justice and Managers' in-role and extra-role Behavior: The Case of the Multinational. Management Science. 42: 499-515.

Knight, D. et al. (1999). Top Management Team Diversity, Group Process, and Strategic Consensus. Strategic Management Journal. 20: 445-465.

Kogut, B. (1985). Designing global strategies: Profiting from operational flexibility.

Sloan Management Review, 21(1): 27–38.

Levy, O. (2005). The Influence of Top Management Team Attention Patterns on Global Strategic Posture of Firm’s. Journal of Organizational Behavior, 26: 797–819.

(26)

26 Luostarinen, R., and Welch, L., (1990). International Businnes Operations. Helsinki: KY

Book Store.

Michel, J. C. and D. C. Hambrick (1992). Diversification Posture and Top Management Team Characteristics. Academy of Management Journal. 35: 9–37.

Murray, A. I. (1989). Top Management Group Heterogeneity and Firm Performance.

Strategic Management Journal, Summer Special Issue. 10: 125– 141.

Neter, J., Wasserman, W., Nachtsheim, C., and Kutner, M. (1985). Applied Linear Statistical Models. McGraw-Hill/Irwin

Nielsen, B.B., Nielsen, S. (2013). Top management team nationality diversity and firm performance: A multilevel study. Strategic Management Journal, 34(3): 373-194.

O’Reilly, C. A., Snyder, R. C., and Boothe, J. N., (1993). Executive Team Demography and Organizational Change. In Huber, G. P., and Glick, W. H. (eds.). Organizational Change and Redesign: Ideas and Insights for Improving Performance. Oxford University Press,

New York. 147-175.

Roth, K. (1995). Managing international interdependence: CEO characteristics in a resource-based framework. Academy of Management Journal, 38(1): 200–231.

Sanders, V. G., and Carpenter, M. A. (1998). Internationalization and firm governance: The roles of CEO compensation, top team composition, and board structure. Academy of

Management Journal, 41(2): 158–178.

Siero W., Huisman, M. & Kiers, H. (2009). Voortgezette regressie- en variantieanalyse. Nederland: Bohn Stafleu van Loghum

Smith, K. G., K. A. Smith, J. D. Olian, H. P. Sims, D. P. O’Bannon and Scully, J. A. (1994). Top Management Team Demography and Process: The Role of Social Integration and Communication. Administrative Science Quarterly. 39: 412–438.

(27)

27 Tihanyi, L., and Thomas, W. B. (2005). Information processing demands and the multinational enterprise: A comparison of foreign and domestic earnings estimates.

Journal of Business Research, 58(3): 285–292.

White, H., and Lu, X. (2010). Robustness Checks and Robustness Tests in Applied Economics. UCSD Department of Economics discussion paper, 2010.

Wiersema, M. F. and Bantel, K. A., (1992). Top Management Team Demography and Corporate Strategic Change. Academy of Management Journal. 35: 91–121.

Wiersema, M. F. and Bantel, K. A., (1993). Top Management Team Turnover as an Adaptation Mechanism: The Role of the Environment. Strategic Management Journal. 14 (7): 485–504.

Pelled, L. H. (1996). Demographic Diversity, Conflict, and Work Group Outcomes: An Intervening Process Theory. Organization Science, 7: 615–631.

Zaheer, S. (1995). Overcoming the liability of foreignness. Academy of Management

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7. Appendices

Appendix I – Literature Overview

Table 7 Literature Overview

Name authors Main topic Findings

Bantel and Jackson (1989)

Board diversity Higher levels of diversity lead to executive creativity, more effective executive decision-making, and more positive organizational outcomes.

O’Reilly, Snyder and Boothe (1993)

Board diversity Higher levels of diversity have a negative impact, resulting in less effective executive decision-making, less

communication among executives and less positive organizational outcomes.

Jhunjhunwala and Mishra (2013)

Board diversity The board may benefit from previous experience of current members who often have strong social networks and clout from which the company can leverage.

Knight et al. (1999)

Board diversity A fundamental principle of upper echelons theory is that the physiological and cognitive elements of executive orientation are consistently related to observable experiences.

Pelled et al. (1999)

Board diversity A common technique that researchers have used in studies to measure diversity in terms of age is by computing the coefficient of variation in age of the members of the team. De Jong and

Houten (2014)

Internationalization The impact of the degree of internationalization on MNE performance is contingent on MNE cultural diversity. Gomez-Mejia

and Palich (1997)

Internationalization The impact on the degree of internationalization on MNE performance is positive for MNE’s that operate in

culturally similar countries and negative for MNEs that operate in culturally diverse countries.

Buckly and Ghauri (1999)

Internationalization Internationalization is interpreted as the extent of a firm’s present involvement in international operations.

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29 (2004) active in multiple countries via subsidiaries or exports, and

thereby implicitly also addresses the geographical diversification.

Barker and Mueller (2002)

Board age diversity and

internationalization

Managerial age is related to risk propensity and to the formulation of innovative strategies.

Jhunjhunwala and Mashra (2013)

Board age diversity and

It can be expected that board age diversity will have a positive effect on internationalization, since younger people are perceived to be more flexible, take higher risks and have a better appreciation of new concepts and technologies in comparison to older people.

Child (1974) Board age diversity and

Younger manager possess more physical and mental stamina and are higher risk takers compared to older managers. Roth, 1995; Sanders & Carpenter, 1998; Tihanyi & Thomas (2005)

Chairman age and internationalization

Moving into new international locations increases the information-processing demands resulting in more complexity.

Roth (1995) Chairman age and internationalization

A chairman of the board or a CEO plays a key role as his or her attributes exert a critical impact on the firm’s ability to process the information associated with

internationalization. Nohria &

Ghoshal, (1994)

Managers are simultaneously required to adapt their home-grown mental maps and, consequently, the structures, systems, and processes rooted in these maps to fit a new international setting.

Herrmann & Datta, 2002; Taylor (1975)

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Appendix II – Sample (list of companies)

Table 8 List of Companies

N Company name N Company name

1 WAL-MART STORES, INC 43 INTEL CORP

2 EXXON MOBIL CORP 44 ENERGY TRANSFER EQUITY, L.P.

3 CHEVRON CORPORATION 45 CATERPILLAR INC

4 APPLE INC. 46 LOWE'S COMPANIES, INC.

5 PHILLIPS 66 47 CONOCOPHILLIPS

6 GENERAL MOTORS COMPANY 48 PFIZER INC 7 GENERAL ELECTRIC COMPANY 49 WALT DISNEY CO

8 FORD MOTOR CO 50 ENTERPRISE PRODUCTS PARTNERS L P

9 CVS HEALTH CORPORATION 51 CISCO SYSTEMS INC

10 MCKESSON CORPORATION 52 SUNOCO INC

11 AT&T INC. 53 SYSCO CORP

12 VALERO ENERGY CORP 54 COCA-COLA COMPANY (THE)

13 VERIZON COMMUNICATIONS INC 55 LOCKHEED MARTIN CORP 14 AMERISOURCEBERGEN CORP 56 FEDEX CORP

15 COSTCO WHOLESALE CORP 57 PLAINS GP HOLDINGS LP 16 HEWLETT-PACKARD COMPANY 58 WORLD FUEL SERVICES CORP

17 KROGER CO 59 JOHNSON CONTROLS INC

18 EXPRESS SCRIPTS HOLDING COMPANY 60 CHS INC.

19 CARGILL INC 61 AMERICAN AIRLINES GROUP INC.

20 MARATHON PETROLEUM CORPORATION 62 MERCK & CO., INC. 21 INTERNATIONAL BUSINESS MACHINES COR 63 TESORO CORPORATION 22 CARDINAL HEALTH INC 64 DELTA AIR LINES, INC. 23 BOEING COMPANY (THE) 65 BEST BUY CO, INC

24 AMAZON.COM, INC. 66 HONEYWELL INTERNATIONAL INC

25 MICROSOFT CORP. 67 UNITED CONTINENTAL HOLDINGS, INC.

26 PROCTER & GAMBLE CO 68 ORACLE CORP 27 ARCHER-DANIELS-MIDLAND COMPANY 69 TYSON FOODS INC 28 WALGREEN BOOTS ALLIANCE CO 70 HCA HOLDINGS INC 29 AMERICAN INTERNATIONAL GROUP INC 71 DEERE & CO

30 KOCH INDUSTRIES INC 72 E. I. DU PONT DE NEMOURS AND COMPAN

31 DELL INC 73 MONDELEZ INTERNATIONAL, INC.

32 CARLYLE HOLDING CORP 74 INTL FCSTONE INC. 33 STATE FARM MUTUAL AUTOMOBILE INSURA 75 HALLIBURTON CO

34 METLIFE INC 76 TWENTY-FIRST CENTURY FOX, INC.

35 JOHNSON & JOHNSON 77 3M COMPANY

36 TARGET CORP 78 SEARS HOLDINGS CORPORATION

37 JPMORGAN CHASE BANK, NATIONAL ASSOC 79 GENERAL DYNAMICS CORP 38 COMCAST CORPORATION 80 SEMPRA ENERGY SALES LLC

39 PEPSICO INC 81 FLUOR PLANT SERVICES INTERNATIONAL

40 GOOGLE INC. 82 PENSCO TRUST CO

41 UNITED TECHNOLOGIES CORPORATION 83 LEIDOS HOLDINGS INC

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Appendix III – Evaluation of Assumptions

Figure 2 Graphical analysis of normality assumption

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Appendix IV – Descriptive and Correlation Statistics

Table 9 Descriptive and Correlation statistics (N=84)

Variable Mean St. Dev. 1 2 3 4 5

1. Internationalization 52.92 56.17 1

2. Board age diversity 0.03 0.19 -0.033 1

3. Chairman age 60.96 6.87 0.145 0.059 1

4. Firm size 135493.36 245962.86 0.259 0.053 -0.006 1

5. Board size 11.67 2.36 0.288 0.126 -0.062 0.285 1

6. Debt ratio 0.54 0.19 -0.065 -0.082 -0.154 -0.072 0.009 7. Mining, utilities & construction (I1) 0.06 0.24 -0.141 0.117 -0.065 -0.293 0.122 8. Manufacturing (I2) 0.45 0.50 0.238 -0.319 0.008 0.175 -0.024 9. Professional & information services (I3) 0.20 0.40 0.060 0.170 -0.023 0.107 0.135 10. Wholesale & retail (I4) 0.10 0.30 0.043 0.069 0.067 -0.440 -0.127

Mean St. Dev. 6 7 8 9 10

1. Internationalization 52.92 56.17 2. Board age diversity 0.03 0.19

3. Chairman age 60.96 6.87

4. Firm size 135493.36 245962.86

5. Board size 11.67 2.36

6. Debt ratio 0.54 0.19 1

7. Mining, utilities & construction (I1) 0.06 0.24 -0.065 1

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Appendix V – Robustness tests

Table 10 Robustness test: internationalization (ratio)

Constant -0.713 (0.233) -0.711 (0.236) -0.716 (0.234) -0.717 (0.238)

Firm size 0.283** (0.125) 0.285** (0.127) 0.284** (0.126) 0.285** (0.128) Board size 0.218** (0.107) 0.219** (0.108) 0.228** (0.107) 0.226** (0.113) Debt ratio 0.041 (0.102) 0.039 (0.104) 0.062 (0.104) 0.061 (0.105)

Board age diversity -0.010 (0.107) -0.019 (0.106) -0.021 (0.117)

Chairman age 0.155 (0.100) 0.154 (0.104)

Model fit

R2 0.267 0.267 0.290 0.290

Adjusted R2 0.200 0.189 0.204 0.193

F-value 3.958*** 3.419** 3.366** 2.989**

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Table 11 Robustness test: Outliers excluded

Constant -0.702 -0.709 -0.713 -0.724

Firm size 0.311** (0.133) 0.304** (0.134) 0.313** (0.132) 0.316** (0.132) Board size 0.231** (0.121) 0.235** (0.121) 0.225** (0.120) 0.220* (0.120) Debt ratio 0.124 (0.127) 0.136 (0.130) 0.174 (0.131) 0.166 (0.132)

Board age diversity 0.061 (0.123) 0.067 (0.121) 0.054 (0.123)

Chairman age 0.183* (0.118) 0.165 (0.122)

Model fit

R2 0.292 0.296 0.327 0.332

Adjusted R2 0.222 0.214 0.238 0.233

F-value 4.134*** 3.622*** 3.677*** 3.337***

Corporate Governance and Internationalization: Theory and evidence from the United States (2014)