The Effects of Nationality and Gender Diversity on Corporate Social Responsibility

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University of Groningen

Faculty of Economics and Business

Master’s Thesis in International Business and Management

The Effects of Nationality and Gender

Diversity on Corporate Social Responsibility

Name student: M.R. Komduur Student ID: 1907905

Student email: m.r.komduur@student.rug.nl Supervisor: Dr. G. de Jong

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Key words: CSR, nationality diversity, gender diversity, Top Management Team

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List of figures and tables

Figure 1: Conceptual research model ... 14

Table 1: Means, standard deviations, and zero-order Pearson correlations ……….19

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1 INTRODUCTION

International business strategy—the strategy of firms around the globe (Peng & Pluggenkuhle-Miles, 2009) and the process of strategic decision-making (SDMP) within internationalized firms—is a theme possessing considerable importance (Nielsen & Nielsen, 2011, Dimitratos et al., 2011). Therefore, developing global strategies for achieving

competitive advantages and realizing enhanced long-term performance has become a critical task for managers and executives (Hitt & Tyler, 1991, Dean & Sharfman, 1996, Hitt, Tihanyi, Miller & Connelly, 2006).

Integrating corporate social responsibility (CSR) practices within the organization’s strategic conversations and processes is a possible strategic direction to gain competitive advantages around the globe (Porter & Kramer, 2002, 2006, Wheeler, Colbert & Freeman, 2003). Furthermore, it offers an opportunity to address the different rules of the game around the world (Peng, 2003, Peng, Wang & Jiang, 2008). Corporate Social Responsibility has received significant attention as “the last three decades have witnessed a lively debate over the role of corporations in society” (Basu & Palazzo, 2008) and businesses have started to acknowledge the importance of CSR. Holme and Watts (2000) define CSR and the underlying goal as “the continuing commitment by businesses to behave ethically and contribute to economic development while improving the quality of life of the workforce and their families, as well as of the local community and society at large”. Corporate Social Responsibility as a strategic action can be defined as “actions that appear to further some social good, beyond the interests of the firm and that which is required by law” (McWilliams & Siegel, 2001) which should result in more shareholder value based on the belief that the needs of other

stakeholders could destroy this value. These could be, for example, consumer boycotts or penalties by governments (Eccles, Ioannou & Serafeim, 2012).

Corporate Social Responsibility is a top-management-driven strategic decision, where “from the very beginning the key player in undertaking such activities in the organizations has been top management and it has been the driving force in the area social responsibility” (Sharma, Sharma & Devi, 2009).

Recent studies demonstrate that, due to an emerging global economy, executive boards have become more nationality diverse in Europe (Heijltjes, Olie & Glumk, 2003, Van Veen & Marsman, 2008; Van Veen, Sahib & Aangeenbrug, 2014). Van Veen et al., (2008) argue that the environmental complexities around firms demand more heterogeneous teams (e.g.

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decision-making. These studies focus on how to explain nationality diversity and why multinationalism in executive boards develops faster in some countries than in others. They seek to explain these mechanisms through national differences (Van Veen et al., 2008).

As stated previously, research has established that the demand for heterogeneous teams becomes greater because of the increase of environmental complexities. Nationality diversity is not the only factor in heterogeneity, however. Multiple influencers affect

heterogeneity. The other factor this study focuses on in is gender diversity. Gender diversity in the Top Management Teams (TMTs) has received more attention in the last decade

(Campbell & Mínguez-Vera 2008, Francoeur Labelle & Sinclair-Desgagné 2008). Companies that work in a complex environment, with a higher proportion of women in the TMT, profit financially (Francoeur Labelle & Sinclair-Desgagné, 2008). Herring (2009) also stresses the importance of gender diversity in financial performance.

Earlier research focuses on explaining the differences regarding why, in some countries, companies are more nationality diverse than others concerning TMT. Diversity in TMT has been the subject of other studies focusing on firm performance (Nielsen & Nielsen, 2013, Carpenter, 2002). However, research is lacking when it comes to CSR. This study takes multinationalism as a given. Gender diversity in boards with connection to CSR has been a topic of interest in a recent study. Bear, Rahman and Post (2010) revealed that, when the number of female directors increases, the firms’ CSR scores increases as well. In this study, I do not focus on the directors, but on the executives who work on a daily basis, to determine whether this also holds true for the TMT.

How does diversity affect the decisions made within top management? One executive board is more diverse than another. This is where I place the focus of my research into CSR. Corporate Social Responsibility, as previously explained, is a strategic decision in which TMT plays a key role, and can be used to gain a competitive advantage around the globe.

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2 THEORETICAL BACKGROUND

In this section. I will provide an overview of earlier studies related to CSR, national culture, TMT, nationality diversity and the gender diversity of executive boards. After doing so, I will present my hypotheses and my conceptual model.

2.1 Corporate Social Responsibility

Managers should make decisions in line with a firm’s strategy that maximize

shareholders’ wealth (Friedman, 1962). However, as corporations use resources from society, managers have a duty to society which goes beyond shareholder value (Hinings &

Greenwood, 2002). These two viewpoints have been driving a debate concerning CSR activities where CSR, as stressed earlier, is “the continuing commitment by business to behave ethically and contribute to economic development while improving the quality of life of the workforce and their families as well as of the local community and society at large” (Holme & Watts 2000). Hence, managers of companies have the obligation to integrate social, environmental and economic concerns with their own values and culture to establish better practices within the company, create wealth and improve society (Canada, 2009, Inyang et al., 2011).

While there are multiple definitions of CSR, there is one which is connected to strategic action: “…actions that appear to further some social good, beyond the interests of the firm and that which is required by law” (McWilliams & Siegel, 2001). Companies that obey the law by, for example, adhering to environmental rules, do not act with CSR. They simply follow the rules, whereas CSR involves taking activities a step beyond normal responsibilities. Recent studies demonstrated that even adopting CSR strategies may not be enough. Instead of CSR, they propose creating shared value. This follows the principle of creating value for the business while also creating value for the society by addressing its needs and challenges (Porter & Kramer, 2011). Creating Shared Value (CSV) takes CSR principles to the core of the company. Business practices still currently remain with CSR principles however.

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first party is composed of businesses that claim to be socially responsible. The second party consists of scholars, who Sheehy (2015) found not to be deriving at the core of the

phenomenon. Another party consists of the political participants who project their own political view on the matter. The last party consists of governments who are caught between the parties involved. Sheehy (2015) fails to arrive at a universal definition because of these complexities.

The question related to why firms engage in CSR activities is answered by Dare (2016). Three motives for CSR are found. The instrumental motive is related to business outcomes. The focus of this motivation is short-term and aimed at profit. Another aspect is the relational motive in which managers use CSR as a tool to create, maintain or restore

legitimacy. By satisfying the stakeholders through CSR, the company wants to legitimize its business activities. The last motive is the moral motive. The philanthropy of the firm is the main driver of this motive. The motivation level affects the level of commitment to CSR (Dare, 2016). Businesses who conduct CSR on an instrumental basis are found to be least committed to it because, before they adopt the CSR practices, they investigate whether doing so will have beneficial business outcomes.

Furthermore, the reputation of a company is becoming more important. Corporate Social Responsibility has been found to be an ideal instrument with which to increase a firm’s reputation (Fombrun & Shanely, 1990). Many companies listed on the Fortune Global 500, the companies of interest in this study, have separate CSR chapters in their reports. The visibility of the global players’ CSR practices offers reason to believe that these initiatives lead to a better reputation and perception of the companies (Lii & Lee, 2012). Corporate Social Responsibility can be used as a marketing tool because it is said to respond to

“consumer expectations, improve corporate performance and reputation, and at the same time, help worthy causes” (Lii & Lee, 2012). Corporate Social Responsibility initiatives can be used as a mere marketing tool or result from the philanthropy of the company. In my view, if CSR benefits society, the underlying principle does not matter.

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responsibility is the discretionary responsibility. There is no clear view from society regarding this responsibility. The decision is open for individual judgement.

Basu and Palazzo (2008) point out three streams within academic literature about CSR: stakeholder-driven CSR, performance-driven CSR and motivation-driven CSR.

Stakeholder-driven CSR is based on the demands of typically external parties such as NGOs, governments and lobby groups. These can create demands towards socially desirable goals or on a firm’s operations. Performance-driven CSR examines the link between what the external expectations are and what the firm actually does and its effectiveness. The last view,

motivation-driven CSR, considers the extrinsic and intrinsic factors for why firms engage in CSR activities.

Corporate Social Responsibility can be seen from multiple perspectives (Basu & Palazzo, 2008), and is affected by various stakeholders with different demands, as mentioned previously. Therefore, CSR goals can be ambiguous and sometimes even conflicting

(McWilliams & Siegel, 2001). Evidence was found decades ago by Roberts (1992) to support the stakeholder theory. Numerous studies have investigated whether the financial benefits could exceed the costs of contributing to society (Orlitzky, Schmidt, & Rynes, 2003, Margolis & Walsh, 2003). Barlett (2007) stresses the importance of this issue. If the benefits outweigh the costs, it can be seen as a sound investment. If, on the contrary, the costs exceed the

benefits, it should be seen as an agency problem (Barnett, 2007). In the upcoming paragraphs, I will return to the agency theory. However, McWilliams and Siegel (2001) found that the agency problem could be averted. They state that there is one level of CSR that maximizes profit as well as satisfying the demands of stakeholders.

In general, the importance of CSR can be argued from different theoretical

perspectives, as indicated by Chin et al. (2013). The institution-based view, which reflects stream 1, suggests that strategies are “enabled and constrained by the different rules of the game around the world” (Peng & Pluggenkuhle-Miles, 2009). Corporate Social Responsibility practices are driven externally by informal and formal rules (Peng & Pluggenkuhle-Miles, 2009), which implies that executives have minor influence over organizational outcomes (Chin et al., 2013). Based on this theory, CSR is forced by contextual influences such as governments (Basu & Palazzo, 2008), social legitimacy (Bansal & Roth, 2000) and consumer activism (Maignan, 2001).

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Meckling (1976). According to this theory, managers are able to serve their own interests instead of those of the shareholders. Therefore, managers could inject their own values, beliefs and experiences into CSR strategies to serve their own interests such as by enhancing their reputations (literature stream 3). Furthermore, managers could use CSR as a competitive instrument to increase financial performance and, as a result, shareholders’ wealth (literature stream 2).

The final theory I would like to discuss here, is the upper-echelons theory (Hambrick & Mason, 1984). Executives vary in the personal orientations they bring to strategic

decisions. Therefore, strategic decision-making is very much interpretive, since executives perceive situations through personalized lenses (e.g. values, beliefs, knowledge, education and experiences). In relation to CSR, these differences could lead to motivation-driven

(stream 3) or performance-driven (stream 2) CSR activities. Harrinson and Klein (2007) argue that a diversified composition of executives should lead to better decision quality. In contrast to the agency theory, the upper-echelon theory posits that organizational strategic outcomes vary since executives are different.

The aforementioned theoretical underpinnings of CSR practices are based on a down approach (Inyang et al., 2011). Corporate Social Responsibility has remained a top-management-driven activity for a considerable period. Bhattacharya, Sen and Korschum (2008) argue that this top-down approach creates a gap between executives and employees concerning CSR practices and initiatives.

2.2 National culture and strategic decision-making

National culture refers to the collective programming of the mind that distinguishes one human group from another (Hofstede, 1994). This definition highlights shared values, norms, beliefs and expected behaviors that are deeply embedded in a person’s mind (Hofstede, 1994). Hofstede (1980) developed four dimensions to distinguish cultural differences among countries. These dimensions are power distance, individualism vs. collectivism, uncertainty avoidance and masculinity vs. femininity. A fifth dimension, long-term vs. short-long-term orientation was developed by Hofstede and Bond (1988). Recently a sixth dimension, describing indulgence vs. restraint, was added to the existing five dimensions (Hofstede, Hofstede, & Minkov, 2010). Previous research provided evidence that the role of national culture has an impact on the mindset of executives and how they make strategic decisions (Geletkanycz, 1997; Schneider & De Meyer, 1991).

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interactions are managed by the top management (Ginsberg, 1988). Strategic decisions have their roots in internal (psychological, structural, cultural and political) factors as well as external ones (Pettigrew, 1992). Furthermore, Elbanna (2006) found that these decisions are of major importance to organizations as they are related to their survival. These decisions steer the organization in a particular direction and often require significant resources. He further stresses that these decisions are difficult to assess. This is because of the fluctuating risk and trade-offs per situation. Moreover, they are connected to other decisions throughout the company and involve uncertainty.

Nielsen and Nielsen (2013) mention that national culture explains a part of the deviation in the strategic decision-making processes of executives. Another aspect is formal institutions, which differ per country and also affect information processing (Crossland & Hambrick, 2011). A study by Abramson, Keating and Lane (1996) explored the linkage between the information gathering and decision-making schemata of different nationalities. They found that one of the underlying predictors of decision-making can be the culture of the managers. Organizational decision-making can be a mixture of multiple aspects. Cunha (2007) stresses three possible modes which affect decision-making: rational, intuitive and improvisational. This line of reasoning is supported by Aharoni (1966). He highlights the fact that there is a subjectivity concerning the decision-making process due to internationalization of firms. Their judgement differs towards contextual stimuli. Another study, that investigated the SDMP for internationalization, found that firms from different countries systematically took the same decisions (Dimitratos et al., 2011). The study largely credited these findings to the national culture differences of Hofstede (1980). Most research is focused on the rational mode of Nielsen and Nielsen (2013), as defined by Aharoni (1966).

The behavioral theory of the firm (Cyert & March, 1963), in connection with SDMP, investigates how decisions are confined by the bounded rationality of the individual. The upper-echelons theory is also an example of this. The characteristics of the manager are connected to different strategic outcomes. The backgrounds and experiences of managers influence how they act in the SDMP, which affects how they react and make decisions

(Hambrick & Mason, 1984). Nationality diversity and international experience can both be influencers of SDMP. International experience can influence SDMP for obvious reasons such as knowledge of the international market, gaining benefits from a network of contacts, or learned skills. Caligiuri and Di Santo (2001) stress however that the benefits gained from experience are limited in time and scope. The underlying value and cognition of the

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of the individual and are the basis for strategic choice (Shaw, 1990). Therefore, nationality diversity is a sizable influencer of the SDMP. These values are embedded in the national cultures and are lasting. Top Management Teams’ nationality diversity, and thereby diversity in values and cognition, is a strong influencer of the SDMP.

2.3 Top Management Teams

Top Management Teams have operational control over an organization and oversee the performance of its operations, for which they are accountable, and present that

performance to outside constituents (Ridge & Ingram, 2017). There is evidence to support the idea that the personality of the CEO influences the dynamics of TMTs (Peterson et al., 2003). The study further indicates that TMT dynamics are related to business performance. A similar study on TMT dynamics demonstrates that successful groups exhibit levels of group-think, while unsuccessful groups are affected by vigilance (Peterson et al., 1998). The characteristics of TMTs include composition, structure, incentives and process (Hambrick, 1994). The

upper-echelon theory of Hambrick and Mason (1984) is key to many studies that followed. The TMTs are investigated by examining their deviating characteristics. The composition of the team, and the diversity of the different members’ characteristics, are said to influence the team processes (Carpenter, 2002). Finkelstein et al. (2009) offer an overview of the consistent literature on TMTs, but overall there have been mixed findings. An explanatory factor may be differences in the composition of the team, a structural issue possibly indicating why findings have varied (Hambrick, Humphrey, & Gupta, 2015). The structures of TMT are found to be very diverse. Hambrick et al. (2015) derive from this that, for TMT heterogeneity (diversity) to have an effect, there must be interaction between individual managers. If the structure of the management team restrains managers from exchanging ideas, this will have minor or zero effect.

2.4 Hypotheses

Boards in Europe have become more nationality diverse (Van Veen et al., 2014). “This increase in the variety of nationalities on boards tends to enrich the supply of ideas, unique approaches, and knowledge available within a group, which subsequently enhances creativity, quality of decision-making and performance” (Van Veen et al., 2014). Previous research suggests that nationality diversity on executive boards and TMT is related to better

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the early stages. They found that cultural differences affected entry modes and the degree of investment.

The expected and reported benefits in earlier studies of nationality diversity on

executive boards are consistent with the information-processing/decision-making perspective, since nationality-diverse teams bring various knowledge and experiences to different

institutional environments (Nielsen & Nielsen, 2013). It is to be expected that a diverse team composition results in better decision quality, group performance and more creative thinking (Harrison & Klein, 2007; Solonas, Nelvam, Navarro & Leiva, 2012). Hambrick, Davidson, Snell and Snow (1998) suggest that multinational teams strive to integrate their different institutionally embedded experiences and engage in in-depth discussions, which should result in more creative ideas, better problem solving of complex tasks and innovative solutions. As stated by Basu and Palazzo (2008): “decisions regarding CSR activities are made by

managers and stem from their mental models regarding their sense of who they are in the world”.

Considering these theories. Strategic decision making, which CSR is a part of, is a top-down activity. These actors are influenced by their culture, as well as their nationality. A higher diversity of nationalities can result in better decision quality, group performance and more creative thinking. Linking this together leads to the following hypothesis:

H1: Higher nationality diversity between executives affects CSR positively

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philanthropy, which can be related to CSR, is also affected by the number of women, and other minorities, on boards. A higher presence of women is positively related to corporate giving (Wang & Coffey, 1992). The difference in characteristics of men and women can be an explanation for their attitude towards CSR. Women are believed to be ‘associated with traits

such as empathy, caring, greater concern for others and being interested in actualizing values in relationships of greater importance to community’ (Boulouta, 2013).Another study found evidence to support the statement that women need to be incorporated in the strategic

decision-making process. The study states that “having women on corporate boards, in top and middle management and in charge of CSR departments affects the deployment of CSR initiatives with gender equality objectives” (Celis et al., 2015). Their study focused on multiple Spanish companies and conducted research with questionnaires to support their statement. I want to investigate whether this statement still holds true for businesses in the Fortune Global 500 and their corresponding CSR scores. This results in the following hypothesis:

H2: Higher gender diversity between executives affects CSR positively

The conceptual research model of this study is presented in Figure 1.

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3 METHODOLOGY

3.1 Sample and data collection

For this study, I choose to use a quantitative methodology. All data used are

secondary. The samples consist of Fortune Global 500 companies. These companies are the largest global companies measured by total annual revenue (Global 500). Data of these companies are easily accessible because all companies on the Fortune Global 500 list must publish financial data and report part of all their figures to a government agency (Global 500). These companies are global players and must all address CSR. This is the ideal sample for this research. To build my dataset, I selected 100 of the 500 companies of the Fortune Global 500 with a randomizer. These 100 companies will be entered into an excel sheet in

alphabetical order. The companies selected vary in board composition. Some companies have two-tier boards, with an executive and a supervisory board. Control is either separated, in a two-tier board, or incorporated in a one-tier board (Jungmann, 2006). For this study, I chose to examine the executive managers, who are in charge of everyday control. Thus, when a company has a two-tier board system, only the executive board will be incorporated into the study. Regarding the companies with a one-tier system, this means that only the executive members will be selected. This choice was made because I want to measure the effect for managers who are executives rather than supervisors. The variables (dependent, independent and control variables) will be inserted in the same file with their corresponding values. When there is missing data for one or more variables, the data will be deleted. To determine the nationalities, genders and other data of the different board members, I have accessed the annual reports of the chosen companies or seek other means such as databases or articles to obtain the information. When nationality is not given, I examined the courses of lives: where the executives grew up and where they studied. I take their educational background as crucial lead. An example of the data of the selected companies and their executives can be found in appendix 7.1 table 1-2.

3.2 Independent variable: Nationality diversity and Gender Diversity

Nationality diversity, or demographic diversity, is categorized as variety (Harrinson & Klein, 2007; Solonas et al., 2012). Therefore, the Blau Index is an optimal measure

concerning the calculation of diversity among group members as it fulfills four criteria for a useful measurement: “…it has a zero point to represent complete homogeneity, larger

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not unbounded’ (Miller & Triana, 2009). It was also used in earlier studies concerning nationality diversity (e.g. Nielsen & Nielsen, 2013).

The same criteria are applicable to gender diversity. In my research, making a dummy variable of gender is not ideal because in the study all high executives are taken from each company. All executives of the single company must ultimately be represented by one number. The Blau Index is therefore an excellent solution. The Blau Index was also used in earlier studies concerning gender diversity (Campbell & Mínguez-Vera, 2008)

Moreover, I use the normalized Blau Index since researchers are able “to compare the values obtained to their suitable maximum values and thus make proper conclusions for specific conditions” (Solonas et al., 2012). The normalized Blau Index ranges from 0 (all executives have the same nationality, which is a completely homogenous composition) to 1 (the composition of executives is completely heterogeneous). I therefore measure the

nationality diversity variable among executives (nationality executives) by using formulae 1-4. 𝐵_𝑁= 𝐵 𝐵𝑀𝑎𝑥 Formula 1. Where, 𝐵 = 1 − ∑𝑘_𝑖=1𝑝_𝑖2 Formula 2. And, 𝐵_𝑚𝑎𝑥 = 𝑛2(𝑘−1)+𝑎(𝑎−𝑘) 𝑘𝑛2 Formula 3. And, 𝑎 = 𝑛 − 𝑘 ∗ 𝐼𝑛𝑡[𝑛 𝑘 ] Formula 4.

n = the total amount of executives on the board k = the number of categories (nationalities) pi = the proportion for the ith category.

3.3 Dependent variable: CSR

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and governance as separate indicators of CSR. To obtain an authentic view, I will incorporate all scores. I will add all four indicators and take the mean. The data collected from CSRHUB are updated quarterly. All data per company are data from the quarter of January 2017. There are companies that are not listed on CSRHUB. These companies are deleted from the sample group before obtaining other data to facilitate appropriate research.

3.4 Control variables

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4 RESULTS

To answer the main question, “What influence does the nationality and gender diversity of Fortune Global 500 executive boards have on CSR?” I will perform statistical analysis to test both hypotheses which are higher nationality diversity between executives

affects CSR positively and higher gender diversity between executives affects CSR positively.

Answers to both hypotheses will provide an answer to the main question.

In total, 100 companies were taken as a sample of the Fortune Global 500 companies as listed on their website. Companies without a CSR score were omitted. One company had to be deleted because of missing data. This brought the final count to 99 companies. For each company, the executives were selected. One company had more than 30 executives. In this case, I limited the selection to executive officers. The highest number of executives was 22. The company with the lowest number had only one executive. In the sample, the highest number of nationalities in a company was 11. This was an exception, because a large proportion had no more than only one nationality. There were 47 different nationalities observed, divided over four continents. No companies from Africa or Australia were found in the sample. The companies are active in 18 different sectors. Sixty-seven companies had at least one female in their TMT. All data collected was first coded per company and

subsequently recoded so all executives were combined. Each company, in this way, had per variable one number.All executives per company are represented in this number. An example of the recoded data can be found in appendix 7.1 table 1. An example of the data before recoding can be found in appendix 7.1 table 2.

For the analysis, we must first understand what kind of variables we are considering. Our dependent variable, CSR mean, is an interval variable. We have multiple independent (nationality diversity) and control variables which are interval or categorical variables. Because of this, I choose to perform a multiple regression analysis. With this analysis, I tried to explain in what way the dependent variable depends on the other variables. The multiple regression analysis is an analysis of many independent variables, or at least two, to one dependent variable.

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control variable that seems to have some linearity is the ROA variable. The dummy variables, as expected, do not show normality because they can either have a value of 0 or 1. The

variable of total assets is prone to transformation. The variable is non-linear. Appendix 7.2, table 1, illustrates that total assets are skewed and have kurtosis issues. Therefore, I transform the variable by taking the log. Appendix 7.2, table 2, demonstrates that, by taking the log, these issues are appropriately resolved. Return on assets and (semi)state owned exhibit signs of having heavy tails. To test for normality, I used the Shapiro-Wilk test. Because the dataset is small, this method is preferred over the Kolmogorov-Smirnov test. In appendix 7.2, table 3, we can see that only one variable, CSR, has a p-value exceeding 0.05. This means that, besides CSR, all variables are significantly different from being normally distributed. Although the skewness and kurtosis of total assets is reduced by taking the log, it is still not normally distributed. The estimators are not biased by non-normality. However, t-tests and f-tests can lose their power. This must be taken into account when interpreting the results. Nevertheless, the outcomes can still be correct, even if there is non-normality and all other assumptions are met, when Ordinary Least Squares (OLS) is used (Hill, Griffiths, & Lim, 2009) A Levene’s test is performed to check if homogeneity can be assumed. As can be seen in appendix 7.2, table 4, no significant results were found. This means that there are no signs of heteroscedasticity.

To check for multicollinearity, I performed the zero-order Pearson correlations test.

Table 1: Means, standard deviations, and zero-order Pearson correlations

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correlated with ROA (r = -.24, p < 0.05). Both of these correlations must be kept in mind. The variable of CEO of different nationality .18 means that the largest proportion of companies incorporated in the study do not have CEOs from a different nationality than the nationality of the company itself. Gender diversity correlated with ROA as well (r = .22, p < 0.05). The mean of .40 illustrates that the diversity levels are closer to being not diverse. The standard deviation of .33 explains large differences in the sample of the diversity levels. Both

explanations hold for nationality diversity as well. However, the variable correlated with three other variables, ROA (r = .26, p < 0.01), (semi)state owned (r = .34, p < 0.01), and CEO of different nationality (r = .53, p < 0.01). The .52 score may be a cause for multicollinearity. Corporate Social Responsibility correlated with gender diversity (r = .21, p < 0.05) as can be seen in table 1. Correlation with the dependent variable of our independent variables, gender diversity and nationality diversity, would be ideal. This is partly true for gender diversity.

The next step in the analysis was to actually perform the multiple regression analysis. I used the ordinary least squares method and a variant of the standard multiple regression: the hierarchical multiple regression. This regression analysis is a stepwise procedure in which one can enter sets of variables step by step. This is a suitable method to test the control variables in the first step to ensure that they do not explain what I actually wanted to test, namely, the influence of the diversities on CSR. In the first step of the analysis, I incorporated all control variables. In the second step, both variables of interest—nationality diversity and gender diversity—were added to test their significance.

The R-squared can be misleading in a multiple regression analysis. Two problems arise. Every time a predictor is added, R-squared increases. This can be because of the true effect of the variable or just by chance. Another problem is the problem of overfitting. Too many variables can lead to noise in the data and may lead to a misleading high variance (Hawkins, 2004). The adjusted R-squared controls for the number of added variables.

The results are presented in table 2. The variance explained in the control model is ΔR²

= .04, F = 1.92, p = .13. The control model has a small explained variance of .04. However, the p-value of .13>.05 makes the control model not significant. Total assets does have a significant influence on the model: B = 1.32, t(99) =2.27, p = .02. All other variables were not significant, return on assets: B = .08, t(99) =.69, p = .49, (semi)state owned: B = -3.72, t(99) = -1.54, p = .02, CEO of different nationality: B = 1.23, t(99) = .64, p = .53. The explained variance would have been higher if the R-squared of .08 was taken but, because this is a multiple regression, the adjusted R-squared is used.

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added. The variance explained in the main model is ΔR² = .07, F = 2.29, p = .04. Overall, this means that the model is significant at a p-value of .05. To interpret the result again, the adjusted R-squared is taken instead of the R-squared of .13. The adjusted coefficient of determination (Adj R-squared) is extremely small. This indicates that only a small proportion of the dependent variable (CSR) is predicted by the independent variables. The conclusion can be made that the overall model is weak.

The main model is analyzed to answer hypothesis 1, Higher nationality diversity between

executives affects CSR positively. It proved to be not significant: B = 1.60, t(99) = .65, p = .52.

I expected to find that higher nationality diversity between executives affected CSR positively but I found no evidence to support this theory. Therefore, H1 is not supported.

Finally, to answer hypothesis 2, Higher gender diversity between executives affects

CSR positively, I checked whether gender diversity significantly influenced CSR. In this

model, gender diversity is significant with B = 5.03, t(99) = .65, p = .04. I expected to find that higher gender diversity between executives affected CSR positively and I found evidence to support this theory. Therefore, H2 is supported.

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5 DISCUSSION

In this section, I will discuss the hypotheses and findings. Furthermore, I will elaborate on the theoretical and practical implications. Finally, I will talk about the limitations and future research.

5.1 Hypotheses and findings

This study had two main goals. The first goal of this study was to investigate whether higher nationality diversity in the executive boards had a significant positive impact on CSR.

As stated by Sharma, Sharma and Devi (2009) “…from the very beginning the key player in undertaking such activities in the organizations has been top management and it has been the driving force in the area social responsibility”. In this study by Sharma, Sharma and Devi

(2009), they discussed the TMT with respect to CSR. Furthermore, Hambrick and Mason (1984) stated, in their upper-echelons theory, that the personal orientation of executives differs per person. The variation in mindsets can have an influence on strategic decisions. Variety in nationalities, or nationality diversity, made the decision-making process more diverse and creative (Van Veen et al., 2014). From this followed the first hypothesis, which was: ‘Higher nationality diversity between executives affects CSR positively’. The other aspect that was investigated, was also an aspect of diversity. The goal was to determine whether higher gender diversity in executive boards has a significant influence on CSR. Literature suggested that gender diversity led to increased financial performance (Brammer et al., 2009, Francoeur Labelle & Sinclair-Desgagné, 2008). One other study found that a larger presence of females in boards did affect CSR scores positively (Bear, Rahman & Post, 2010). The focus of these studies lies on the executives of the company. This resulted in the

following hypothesis: ‘Higher gender diversity between executives affects CSR positively’. With these two hypotheses in mind, I conducted research on a sample of Fortune Global 500 companies.

When the regression analysis with respect to the first hypothesis is investigated, the analysis presents the following results: B = 1.60, t(99) = .65, p = .52. The positive B-value of 1.60 means that nationality diversity has a minor, though positive, effect on CSR. Would it not be that the p-value is .52 > .05 from which the conclusion has to be drawn that the results are not significant. Hypothesis one is therefore not supported. The effect, although small, was what I expected, though nothing can be concluded from this without a more significant result.

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analysis, which investigated whether gender diversity significantly influenced CSR, provides the next results: B = 5.03, t(99) = .65, p = .04. The larger B-value opposed to nationality diversity means that the effect from a change in gender diversity would have a larger, and positive, impact on CSR. The p-value .04 > .05 is significant. The suggested positive influence is found and is significant as well. Therefore, H2 is supported, although, as mentioned before, it must be taken into account that the variables were not normally distributed.

5.2 Theoretical and practical implications

As mentioned in the previous section, CSR is a top management activity. As proposed in my hypotheses, diversity in the TMT, would have a positive influence on the CSR scores. However, only partially significant effects were found. One hypothesis was supported, one was not. However, while hard conclusions cannot be made, this does not mean that the effects are not present.

Nevertheless, there are scholars who not only highlight the positive impacts diversity could have, but also examine the downside of diversity. There is a paradox of strategic decision-making. The quality of decision-making increases when diversity is higher.

However, coming to a consensus in a harmonious manner to ensure high performance is not effortless. According to Amason and Schweiger (1994) “…in many ways, decision quality, consensus, and affective acceptance are contradictory”. When a field is created in which high diversity is secured, lower levels of affective acceptance and lower consensus rates are found to improve the quality of decision (Schwenk, 1990). The value created, due to higher

diversity, can therefore be undermined by the inability of the management team to implement decisions. They can lose the commitment, or even the will to work together in a coherent manner in the future (Amason, 1996). These effects may hinder the selected TMTs in the sample as well and could represent a reason why I found only partially significant results.

Another reason why the results were only partially as I suspected, is that other researchers focused on the financial aspect of diversity. Here they found evidence that diversity was beneficial to a company’s financial performance (Brammer et al., 2009,

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that the decisions concerning CSR would be affected more significantly than other firm performance measures.

Furthermore, Carpenter (2002) found that the level the study is conducted on matters. Different situations cause different outcomes. For example, a positive effect was found on the performance of firms who conduct business in a low complexity environment. When firms conducted business in a high complexity business environment, the effect was found to be negative (Carpenter, 2002). This is not in line with the theories that are the basis for my model. The sample used in my research consists of businesses that are almost all active internationally. This is another explanatory factor of the difference in expected and actual results

Additionally, TMTs which have the same composition over time profit less from diversity. Top Management Teams are affected by their differences but their differences diminish over time. Carpenter (2002) found evidence to support this theory. The measured difference in CSR value with respect to diversity can consequently differ per company. In relatively newly composed TMTs the effect would be the largest. On the other hand, in TMTs that have had the same composition for a longer time, we would measure a smaller effect. The total measured effect, as result, is lower than expected.

5.3 Limitations and future research

There are multiple limitations in this study. First, the effect of NGOs on CSR is overlooked. Non-Governmental Organizations are key players in CSR (Arenas, Lozano & Albareda 2009). Non-Governmental Organizations are not present, or even accepted, in every business environment and have a greater influence on some companies than others. This must be taken into account when investigating CSR. The cultural background of the country from which the company originates is also not incorporated in the study and is also an effect that should be considered.

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Moreover, the sample size is also a limitation. With a small sample size of merely 99 companies, it is hard to obtain significant results. To secure a reasonable image of the entire population, a larger sample size should be selected in future research to acquire more significant results.

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7 APPENDICES

Appendix 7.1 Dataset tables

Appendix - Table 1: Per company variables table

* Appendix 7.1 table 1 is a sample of the full dataset. The full dataset is available upon request. The email address for requests is presented on the title

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Company name Employee Nationality Number of Nat Total number executives

1 State Grid

Chairman State Grid Mr. Y Shu China 1 11

President State Grid Mr. W Kou China 1 11

EVP State Grid Mr. B Xin China 1 11

EVP State Grid Ms. Y Chen China 1 11

EVP State Grid Mr. J Luan China 1 11

CFO State Grid Mr. R Li China 1 11

CCO State Grid Mr. X Pan China 1 11

EVP State Grid Mr. M Wang China 1 11

EVP State Grid Mr. G Liu China 1 11

EVP State Grid Mr. J Han China 1 11

EVP State Grid Mr. H Liu Ze China 1 11

2 Royal Dutch Shell

CEO Royal Dutch Shell Mr. B van Beurden The Netherlands 4 8

CFO Royal Dutch Shell Ms. J Uhl USA 4 8

D Director Royal Dutch Shell Mr. J Abbot UK 4 8

P&T Director Royal Dutch Shell Mr. H Brekelmans The Netherlands 4 8

U Director Royal Dutch Shell Mr. A Brown UK 4 8

CHR & CO Royal Dutch Shell Mr. R Cassidy UK 4 8

L Director Royal Dutch Shell Mr. D Ching Malaysia 4 8

IG & NE Director Royal Dutch Shell Mr. M Wetselaar The Netherlands 4 8

3 McKesson

CEO McKesson Mr. J H Hammergren USA 3 8

CFO McKesson Mr. J Beer USA 3 8

EVP McKesson Mr. P J Blake USA 3 8

HR EVP McKesson Mr. J L Figueredo Cuba 3 8

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CIO & CTO EVP McKesson Ms. McElligott USA 3 8

EVP McKesson Mr. B Nagji UK 3 8

EVP McKesson Ms. L A Schechter USA 3 8

4 Glencore

CEO Glencore Mr. I Glasenberg Switzerland 1 1

5 CVS Health

CEO CVS Health Mr. L J Merlo USA 1 12

CFO CVS Health Mr. D M Denton USA 1 12

EVP CVS Health Ms. H B Foulkes USA 1 12

COO CVS Health Mr. J C Roberts USA 1 12

CMO CVS Health Mr. T Brennan USA 1 12

EVP CVS Health Mr. T M Moriarty USA 1 12

EVP CVS Health Mr. R O Kraft USA 1 12

EVP CVS Health Ms. L Bisaccia USA 1 12

EVP CVS Health Mr. A J Sussman USA 1 12

EVP CVS Health Mr. S J Gold USA 1 12

EVP CVS Health Mr. J D Joyner USA 1 12

SVP CVS Health Ms. E Boratto USA 1 12

6 AT&T

CEO AT&T Mr. R L Stephenson USA 1 10

CEO AT&T Mr. T Arroyo USA 1 10

EVP AT&T Mr. W A Blase Jr. USA 1 10

CSO AT&T Mr. J Donovan USA 1 10

CCO AT&T Mr. D S Huntley USA 1 10

GMO AT&T Ms. L Lee USA 1 10

EVP AT&T Mr. D R McAtee II USA 1 10

EVP AT&T Mr. R W Quinn Jr. USA 1 10

CEO AT&T Ent Gr AT&T Mr. J Stankey USA 1 10

CFO AT&T Mr. J J Stephens USA 1 10

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CEO AmerisourceBergen Mr. S H Collis South Africa 2 15

CFO AmerisourceBergen Mr. T G Guttman USA 2 15

EVP AmerisourceBergen Mr. J G Chou USA 2 15

CMO AmerisourceBergen Ms. G. K Clark USA 2 15

EVP AmerisourceBergen Mr. J F Cleary Jr. USA 2 15

CIO AmerisourceBergen Mr. D Danilewitz South Africa 2 15

EVP AmerisourceBergen Mr. J Frary USA 2 15

CHRO AmerisourceBergen Ms. K H Gaddes USA 2 15

EVP AmerisourceBergen Ms. P. Howell USA 2 15

EVP AmerisourceBergen Mr. R P Mauch USA 2 15

EVP AmerisourceBergen Mr. S Park USA 2 15

SVP CC AmerisourceBergen Mr. L Krikorian USA 2 15

VP AmerisourceBergen Mr. H Bak USA 2 15

VP AmerisourceBergen Mr. J F Quinn USA 2 15

Director AmerisourceBergen Ms. V L Bausinger USA 2 15

8 Chevron

CEO Chevron Mr. J S Watson USA 1 7

EVP Chevron Mr. P R Breber USA 1 7

EVP Chevron Mr. J C Geagea USA 1 7

EVP Chevron Mr J W Johnson USA 1 7

General Counsel Chevron Mr. R Hewtt Page USA 1 7

EVP Chevron Mr. M K Wirth USA 1 7

CFO Chevron Ms. P E Yarrington USA 1 7

9 E.ON

CEO E.ON Mr. J Teyssen Germany 1 5

COO E.ON Mr. L Birnbaum Germany 1 5

CFO E.ON Mr. M Sen Germany 1 5

CFO E.ON Mr. M Spieker Germany 1 5

COO E.ON Mr. K Wildberger Germany 1 5

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CEO Japan Post Holdings Mr. M Nagato Japan 1 5

EVP Japan Post Holdings Mr. Y Suzuki Japan 1 5

EVP Japan Post Holdings Mr. S Atsuki Japan 1 5

EVP Japan Post Holdings Mr. T Komatsu Japan 1 5

EVP Japan Post Holdings Mr. Y Iwasaki Japan 1 5

11 BMW

CEO BMW Mr. H Krüger Germany 2 8

HR BMW Ms. M C Carreiro-Andree Germany 2 8

P & SN BMW Mr. M Duesmann Germany 2 8

Development BMW Mr. K Fröhlich Germany 2 8

Finance BMW Mr. N Peter Germany 2 8

Sales & Brand BMW Mr. I Robertson UK 2 8

CE & DBI BMW Mr. P Schwarzenbauer Germany 2 8

Production BMW Mr. O Zipse Germany 2 8

12 Nissan Motor

CEO Nissan Motor Mr. C Ghosn Brazil 6 11

Co-CEO Nissan Motor Mr. H saikawa Japan 6 11

CPO Nissan Motor Mr. P Klein France 6 11

CFO Nissan Motor Mr. J Peter USA 6 11

Rep Dir Nissan Motor Mr. T Shiga Japan 6 11

SVP Nissan Motor Mr. S Nakamura Japan 6 11

CCO Nissan Motor Mr. J Adashek USA 6 11

CVP Nissan Motor Mr. P Guerin-Boutad France 6 11

CVP Nissan Motor Mr. K Kato Japan 6 11

EVP Nissan Motor Mr. D Schillaci Italy 6 11

CVP Nissan Motor Mr. R de Vries The Netherlands 6 11

13 J. P. Morgan Chase

CEO J. P. Morgan Chase Mr. J Dimon USA 3 10

CRO J. P. Morgan Chase Mr. A Bacon UK 3 10

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A & WM CEO J. P. Morgan Chase Ms. M Callahan Erdoes USA 3 10

GC J. P. Morgan Chase Ms. S Friedman USA 3 10

CFO J. P. Morgan Chase Ms. M Lake UK 3 10

CB CEO J. P. Morgan Chase Mr. D B Petno USA 3 10

C & IB CEO J. P. Morgan Chase Mr. D E Pinto Argentina 3 10

C & CB CEO J. P. Morgan Chase Mr. G A Smith USA 3 10

COO J. P. Morgan Chase Mr. M E Zames USA 3 10

14 China Railway Engineering

Executive Dir China Railway Engineering Mr. C Li China 1 3

Executive Dir China Railway Engineering Mr. G Yao China 1 3

Executive Dir China Railway Engineering Mr. Z Zhang China 1 3

15 Petrobras

CEO Petrobras Mr. P Parente Brazil 1 8

P&T Dev Director Petrobras Mr. R Moro Brazil 1 8

E&P Director Petrobras Ms. S da Silva Guedes Brazil 1 8

R&NG Director Petrobras Mr. J Celestino Ramos Brazil 1 8

F&IR Director Petrobras Mr. I de Souza Monteiro Brazil 1 8

HR HSE & S Director Petrobras Mr. H Repsold Junior Brazil 1 8

GR&S Director Petrobras Mr. J Adalberto Elek Junior Brazil 1 8

ED of SO&MS Petrobras Mr. N Silva Brazil 1 8

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Appendix 7.2 Analysis tables

Appendix – Table 1 descriptive statistics original data

Appendix – Table 2 descriptive statistics transformed data

Appendix- Table 3 Shapiro-Wilk test for normality

Variable Mean SD Min Max Skewness Kurtosis

1 Total Assets ($M) 260252.82 525435.70 9239 2654413 3.38 11.34 2 ROA (%) 4.23 7.04 -21.07 34.93 .62 4.48 3 (Semi)State Owned .11 .32 0 1 2.51 4.4 4 CEO of Different Nationality .18 .39 0 1 1.67 .82 5 Gender Diversity .40 .33 0 1 .01 -1.30 6 Nationality Diversity .41 .37 0 1 .11 -1.6 7 CSR 59.94 7.39 40 76 -.45 -.02