Fortune world top MNCs from 2010 to 2016:
The impact of Board of Directors on Corporate Social
Performance
Siyu Li
1Faculty of Economics and Business MSc. International Business and Management
Supervisor: Dr. D.H.M. Akkermans Co-assessor: Dr. M.J. Klasing
June 18, 2018 Abstract
The purpose of this paper is to investigate the relationship between the board of directors and corporate social performance (CSP). Two board tiers (executive and non-executive board) are considered separately in this research. It is hypothesized that more gender diversity in the two boards, will increase the CSP of the MNC. Moreover, two additional hypotheses are formulated - the increase of cultural (individualism) diversity and educational diversity in the two boards lead to the decrease of CSP. The study’s empirical analysis was based on the Fortune world top MNCs from 2010 to 2016, 81 MNCs were selected by using balanced panel data. The fixed effect model was adopted to quantify the effects of the predictors in the research. The major finding indicates that none of the relationships regarding executive boards were significant. However, with respect to the non-executive board, gender diversity was found to have a positive effect on CSP, which is in line with the hypothesis. Additionally, the increase of educational diversity results in the increase of CSP, which was contradictory to the hypothesis. While, increase cultural diversity does not effect on CSP. Overall, this research contributes to academia by enhancing the understanding of board member diversity on CSP and has valuable implications for the optimal board composition for practitioners.
Key words: Board of director, Gender diversity, Cultural diversity, Education diversity, CSP
- 2 -
Acknowledgement
I am very grateful to my supervisor dr. D.H.M. (Dirk) Akkermans, who is a professor at the University of Groningen, and who has supported and helped me with my master thesis. Especially in the theoretical part of corporate governance and use of new method of diversity in the board research. He is a very responsible professor with critical thinking. He was willing to offer valuable advices and helps me facilitate the process of thesis. During this MSc thesis, not only did I complete an academic research paper, but cultivate my ability to manage project individually as well. I appreciate your guidance. Finally, I would like to thank University of Groningen for offering an outstanding master’s program that prepares for my future adventures.
Abbreviation List
AT = Agency Theory BoD = Board of directors
CSP = Corporate Social Performance CSR = Corporate Social Responsibility
ESG = Environmental, social and governmental ED = Executive director
HHI = Herfindahl-Hirschman Index HCT = Human Capital Theory
IND-COL = Individualism-Collectivism KPI = Key performance indicators
MNC = Multinational Corporation NED = Non-executive director RDT = Resource Dependency Theory ROE = Return on equity
- 3 -
1. Introduction
In recent years, corporate social responsibility (CSR) has become one of the main concerns of many companies, especially for multinational corporations (MNCs) (Muller, 2006). CSR is a business approach which promotes sustainability, including economic social and environmental benefits to all stakeholders (European Commission, 2011). The realization of these benefits closely relates to the top-level strategic decision-making in a company. The Board of Directors (BoDs) are the key group of people who conduct the governance of a company. They not only manage stakeholders by determining the company’s mission, objectives and strategies, but they link the organization’s interests to society as well (Hung, 2011). It is important to know that BoDs usually consists of two parts, non-executive directors (NED) and executive directors (ED). NED play a role in decision-making and monitoring business performance. ED are responsible for executing the decisions from NED and managing the operation (Jungmann, 2006). In the practice of CSR, the BoDs help the firm respond to the external environment with appropriate social responsibility actions. Therefore, the BoDs influence the CSR performance of a firm. Corporate social performance (CSP) is a widely-used measure to represent a company’s CSR performance (Muller & Kolk, 2010).
Considering the relationship between the BoDs and CSP, several scholars have confirmed that the behaviors of the enterprises will be affected by the characteristics of the BoDs, such as age, gender, nationality, education, experience and social status, etc. (Ilaboya & Ashafoke 2017; Nielsen & Nielsen, 2012; Dallas, 2002). Since these characteristics vary among different individuals, a key interesting point to be considered is the diversity of the board members’ backgrounds. From the practical point of view, studying the effect of diversity can help corporations to establish an optimal board composition, thereby improving the effectiveness of decision-making on CSP. On the other hand, for research purposes, it is also interesting to study the theoretical reasons of how and why the diversity influences CSP.
- 4 -
experiences that females contribute to the board. Although many have studied the topic of gender diversity, the discussion is still ongoing. Boulouta (2012), Byron & Post (2016) and Cook & Glass (2017) found in their research that there is a positive relationship between gender diversity and a firm’s CSP. While Wharton (2017) questioned the finding, pointing out the weak positive relationship. Additionality, despite the ongoing discussion of the topic, to the knowledge of current paper, most existing research has focused on the board as a whole, and there is little research studying the effects from ED and NED on CSP respectively. Concerning the different perspectives of ED and NED as mentioned above, this paper will build models to study gender diversity’s impact on CSP in the two parts of the board separately.
In terms of the effect of the cultural diversity of the BoDs on CSP, the explanation is related to the cultural background of the board members. Culture is deeply-rooted and slow moving, it is hard to change the existing values of a certain culture (Nielsen & Nielsen, 2012). Cultural heritage can shape one’s managerial behavior and influence corporate performance of the firm (Nguyen, Hagendorff & Eshraghi, 2017). Previous literature has focused almost exclusively on the impact of CSP at the nationality level. While the current paper aims to study culture itself instead of nationality. The reason is that nationality can easily become an attitude (Rosenauer et al., 2015) and everyone’s attitude is based largely on the cultural background of the home country. In a MNC’s board, there are many different cultures. Past research has little finding on how a diversity of culture in the board influences CSP. Hofstede’s model is a well-known model representing the composition of culture. It has six dimensions, one of which is individualism. Given that the board is working as a team, this individualism dimension is selected for its close relevance to the teamwork and intra-group processes. Again, the research of diversity regarding individualism will be carried out on ED and NED separately.
- 5 -
can be seen as an asset to enrich the knowledge pool of the board, but companies often face a dilemma due to the problem of group polarization. Thus, the current research will look at how the educational diversity of a board influences CSP. Like cultural diversity, educational diversity will also be considered at the ED and NED separately.
Overall, a model of CSP driven by gender diversity, cultural diversity and educational diversity in the board is presented. The research question is: “How does the diversity of board members on the executive and non-executive board influence CSP respectively?” To answer the main question, this paper describes CSP definitions, and relevant theories to explain how these key factors influence CSP. This paper contributes to the academia by filling the research gap to test the influence of gender, cultural and educational diversity on CSP regarding ED and NED separately on world top 100 MNCs. As a result, the strength of diversity on two parts of the board can be compared. Secondly, by using the Hofstede model individualism dimension, this paper reveals the effect of cultural diversity at a more detailed level, specifically about the teamwork process on the board. The research about educational diversity on a board sheds light on whether a heterogeneous or homogeneous educational background in the board is beneficial for a company’s CSP. In addition, this research applies Herfindahl-Hirschman Index (HHI) for the linear relationship between the diversity of directors and CSP. For international business practitioners, by answering why and how different characteristics of the board of directors’ influences CSP, the results can be used as input for better strategic design and management of MNCs.
- 6 -
2. Literature review
First, it is important to find out theoretical definitions of CSP and the BoDs’ characteristics. Upper Echelons Theory, Agency Theory, Resource Dependency Theory, Human Capital Theory and Hofstede Theory are applied to link the theoretical relevance of BoDs and CSP. After that, the relationship between gender diversity and CSP, culture diversity and CSP as well as the relationship between educational diversity and CSP will be argued (Figure 1). Overall, six hypotheses will be formulated.
Figure 1: Conceptual model
2.1 Corporate social performance
CSR is becoming more and more important in modern management (Piasecki & Gudowski, 2017). CSR activities create environmental, social and economic values for a company’s stakeholders (Skilton & Purdy, 2016). This means that the managers and owners of the company should not simply pursue profit maximization, but also be responsible for the management and legal aspects of their activities. In other words, they are responsible for the whole society (Carroll & Shabana, 2010; Piasecki & Gudowski, 2017). McCarthy (2017) defined CSR as a set of practices and policies formulated by private businesses, limiting the negative impact of enterprises (do-no harm) and contributing to society by activities that take advantage to people and planet. In addition, the European Commission (2011) indicated that, in order to fully meet the requirements of CSR, companies “should have in place a process to integrate social, environmental, ethical human rights and consumer concerns into their business operations and core strategy in close collaboration with their stakeholders”.
Board of Directors Corporate Social Performance of MNCs Control Variables Company size, board
size, industry and ROE Cultural Diversity
(ED & NED) Educational Diversity
(ED & NED) Gender Diversity
(ED & NED)
- 7 -
Corporate Social Performance (CSP), as a measurement of CSR, is a widely-used tool to represent CSR performance. Muller and Kolk (2010) defined CSP as “a snapshot of a firm’s overall social performance at a particular point in time”. CSP covers the behaviors and results of economic, social and environmental responsibility within the concept of corporate social responsibility (Hudson, Bryson & Michelotti, 2017). Jacobs, Kraude & Narayanan (2016) found that CSP practices have multiple dimensions, including community relations, environmental projects, and human rights, etc. In this study, the definition of Oikonomou, Brooks & Pavelin (2014) is adopted, where CSP is formulated as a composite score composed of certain indicators representing the social, economic and environmental impact of the enterprise on business operation.
2.2 Board of directors
Generally speaking, the board of directors (BoDs) have the responsibility of directing and managing the company. It is an integral part of the corporate governance system including supervising, guiding senior management, and providing resources to the company as well (Wang, Xie & Zhu, 2015; Cannella, Jones & Withers, 2014). In order to see how the BoDs influences the performance of an organization, instead of investigating the effects of the BoDs as a whole, it is necessary to further look at the effects from different functions of the BoDs, since the BoDs are organized in two parts.
- 8 -
2.3 Gender diversity in the board and corporate social performance
In recent years, the position of female directors has been significantly promoted around the world, the number of female directors on boards have been increasing. Since traditionally a board mostly consists of male members, involving more female members increases board diversity. According to Hutchinson, Jack & Plastow (2014), it is found that gender diversity at board level correlates with enhanced corporate performance. To investigate the effect of female board members on CSP, it is necessary to build up rationales from upper echelons theory, agency theory, and resource dependency theory.
First, “Upper Echelons Theory” (UET) indicated that managerial decisions are a function of their experiences, personalities and values, which will form strategic decision-making and ultimately corporate strategy, even performance of the company (Byron and Post, 2016). According to UET, each director has his or her own cognitive base and value and views the business situation from a personalized perspective. These individualized views lead to several strategic choices in management concepts (Hambrick and Mason, 1984; Hambrick, 2007; Lee, Kim & Moon, 2016; Juravich, et al., 2017). The strategic decisions from the board are influenced by the cognitive biases and values of the members. From a gender point of view, females have a different cognitive framework compared to males. Chin, Hambrick & Treviño (2013) mentioned in their research that there is evidence that women and men tend to bring different knowledge, experience, and values to the decision-making of boards. Thanks to more female members in the board, a board’s decision on CSR would become more comprehensive (Post & Byron, 2015). Regarding the non-executive board, involving more female directors increases the thoroughness of strategic decision-making. Particularly, it is indicated that when a company encounters a controversial voice, female directors are usually better at listening and they can take border stakeholders’ perspectives into account when making strategic decisions (Post & Byron, 2015). On the other hand, on executive board level, females are more willing to take responsibilities in communicating with employees, and they use careful reasoning to support their actions (Krishnan & Park, 2005). Therefore, it helps to deliver clearer and reasonable messages to the management, guiding employees to reach higher CSP for the organization.
- 9 -
of the principal (McGee, Thomas & Wilson, 2010). Most of the literature on agency theory is about financial performance. CSP can also be discussed by agency theory. CSP is concerned with the impact of an organization’s activities on society and the environment. Particularly talking about MNCs, they are involved in diverse economic, cultural and political systems around the globe. These organizations have different operating and governance standards (Lozano, 2012). It is important for the board of directors to monitor and guide the performance of diversified employees in the company to satisfy stakeholder interests. Especially from the non-executive board point of view, literature finds that bringing in more female members on the board could mitigate internal control weakness. That is because women are more likely to discuss difficult issues, they are less tolerant of opportunistic behaviors, and they are better monitors (Chen, Eshleman & Soileau, 2016). Women are more likely to bring new input for complex social issues and correct strategic biases. Thus, they can generally hold the organization to higher ethical standards. As a result, it contributes to the increased CSP of the company (Terjesen, Couto & Francisco, 2015).
Thirdly, a major theory that often used in explaining the diversity in the board of directors and corporate governance is “Resource Dependency Theory” (RDT). Although resource dependency theory does not specifically predict a relationship between board diversity and corporate performance, it is highly suggestive of a positive linkage (Carter et al., 2010). RDT considers that valuable, rare, indivisible, and irreplaceable resources can bring a sustainable competitive advantage to the company (Coff & Raffiee, 2015). From RDT’s point of view, increased resource diversity in the boardroom helps a corporation in understanding and responding to its environment (Singh, 2007). The board can be seen as a linking mechanism for the MNCs to connect to external resources. Involving more female directors especially contributes to the executive board. Because the key advantage of having more females based on resource dependency theory is that they can bring in valuable legitimacy to customers, especially by taking broader social influences into account. It could strengthen the relations with more customer stakeholders (Lückerath-Rovers, 2009).
- 10 -
the CSP of the company will increase. The following hypotheses were formulated.
Hypothesis 1a: With a higher gender diversity in the executive board, the CSP of the MNC will increase.
Hypothesis 1b: With a higher gender diversity in the non-executive board, the CSP of the MNC will increase.
2.4 Cultural diversity in the board and corporate social performance
Culture was defined by Schwartz (2006) as a rich complex of meaning, belief, practice, symbols, norms and values of society, to guide people how to select the action or evaluation, policy, events, or others. Nielsen & Nielsen (2012) illustrated that the key focus of multinational team research is mainly in terms of national culture, which represents a system of collectively held beliefs and values. Schwartz (2006) and Hofstede (2011) indicated that culture is an emergent property, which evolves out of the interaction between personal values and the environment. Culture affects all individuals, even members of elite strategic decision-making groups, such as corporate boards, and how they perceive and interpret information and communicate with others. Therefore, the directors are not immune from cultural bias, and a lack of cultural diversity may weaken the decision-making efficiency of the board, but it may also bring different cognitive forces to the board and make more accurate decisions. Moreover, culture is intrinsic to human beings, which is difficult to change (Frijns, et al., 2016). The key reason, as explained by Hofstede (2005), is that a person’s early childhood would generate a cultural pattern of thinking, feeling, and behavior, because at that time a person is most susceptible to learning and assimilation. These patterns are deeply rooted and once established in a person’s mind, they are unlikely to change substantially in the future. Despite that, the outcome of a board is based on its members’ cognition. The efficient workflow of the board is closely related to their social and psychological processes (Frijns, et al., 2016). Culture is one of the cornerstones of strategic decision-making; the cultural backgrounds of the board members will have an impact on the strategic decision-making of the organization.
- 11 -
itself. There are six dimensions illustrated by Hofstede, which includes individualism-collectivism, power distance, masculinity-femininity, uncertainty avoidance, long & short-term orientation and indulgence-restraint. The current research is only interested in individualism, because this dimension is related to the perception of how the team process should work (Frijns, et al., 2016), it will directly influence the decision-making of the board. According to Hofstede (2011), individualism indicates the degree that the citizens in a country tend to be individualistic and value their own interests. Their personal time, freedom and independence is very important to them. On the opposite, in collectivism, rather than a personal characteristic, is the degree to which people in a country are integrated to a community. The individualism dimension of the Hofstede model focuses on whether the society focuses on self-improvement, or the goals of the group. This dimension is related to the different processing of persons belonging to the group and those belonging to the outside group.
- 12 -
the degree of task-related and relationships conflict. The task-related or cognitive conflict is associated with different perspectives, ideas, views and different interpretations by the others. In this case, diversity reduces groupthink if the board members have diverse levels of individualism (Frijns, et al., 2016).
There are three levels of individualism defined in the current research, which are “Low individualism”, “Medium individualism” and “High individualism”. In the Hofstede model, the total score on the dimension is 100 points, the higher the score, the more individualistic the country is. Therefore, these 100 points are divided into three intervals (0-33: Low; 34-67: Medium; 68-100: High). For instance, in Singapore (20, Low individualism), people have a strong sense of belonging to groups; in Japan (46, Medium individualism), people’s standpoint regarding individualism is neutral; in Netherlands (80, High individualism), people tend to have a focus on the views of themselves (Hofstede, 2011).
Taken as a whole, as Sekiguchi, Bebenroth & Li (2011) mentioned that because top management plays a key role in shaping the main organizational outcome. Therefore, with the increase of individualism diversity in the board, although the board could look at problems from several aspects, the cost of reaching into the same action in the board will be significant, and it could bring negative effect to firm performance.
Hypothesis 2a: With a higher degree of individualism diversity in the executive board, the CSP of the MNC will decrease.
Hypothesis 2a: With a higher degree of individualism diversity in the non-executive board, the CSP of the MNC will decrease.
2.5 Educational diversity in the board and corporate social performance
- 13 -
Carter et al., (2010) indicated that, based on the competitive advantage of “Resource Dependency Theory”, human capital is described as the key resource of the company, which brings diversified blood (perspectives) and pluralistic perspectives to the organization. As a result, when companies face complex problems, the available resources across education backgrounds will facilitate a problem-solving process in the organization. Secondly, based on “Upper Echelon Theory” (UET), education can be seen as a reflection of one’s cognitive understanding. The idea asserts that directors interpret business situations and make decisions based on their own experience (Juravich, et al., 2017). Organizational performance measure is usually associated with individuals who hold key positions in the organization (Juravich, et al., 2017). The decisions on innovation, sustainability or social responsibility are reflected from the backgrounds of the individuals.
There is currently limited literature regarding education’s impact on CSP. Current paper uses the insights from the general firm performance. In the process of strategic decision-making, because of the difference in viewpoints, board members may only associate with other board members who have similar opinions. It creates ingroup and outgroup categories, which give rise to stereotyping. Board members infer threat from different educational levels as a possible source of conflict. Therefore, communication and group-functioning are hampered. As a result, firm performance is negatively affected (Kagzi & Guha, 2018). Specifically speaking of social responsibility, for example regarding the social issue of consumer data privacy, directors who have a higher level of education (such as Master, PhD, MBA) may use more theoretical knowledge and problem solving ability that they have acquired to support why and how to design and execute consumer privacy policies strategies in a rational way to increase the CSP of the firm.On the contrary, directors with standard educational level (Bachelor Degree) may use more insights from the real-world exercises and experience that they have observed to build up their arguments, they may spot other factors like the real-world obstacles to tackle in the process of execution, which questions the feasibility of the strategies. Thus, due to the difference in viewpoints, conflicts are very likely to happen.
Although more perspectives are obtained from the diversity of educational level, and it could enrich the thoroughness of solving problems to an extent. However, as indicated above, the communication and functioning of the board towards CSP issues could be hindered due to that people tend to favor the opinions from other members with similar educational level background. In the end, the outcome of the strategies may not improve current CSP of the firm, even deteriorate the status quo.
- 14 -
practice of the company, the impact of educational level diversity on CSP should be both negative in terms of both NED and ED.
Hypothesis 3a: With a higher educational level diversity in the executive board, the CSP of the MNC will decrease.
Hypothesis 3b: With a higher educational level diversity in the non-executive board, the CSP of the MNC will decrease.
3. Methodology
The methodology part shows the research design. The settings of empirical research includes methods (data collection, variables measurement, modelling and analysis). The purpose of this study is to examine the impact of the board of directors (gender, culture, and education) on corporate social performance. The dataset used in this study includes cross-sectional and time series data points. Therefore, it is panel data.
3.1 Data collection
Three main secondary data sources will be used in this research. The first one is ASSET4 including environmental, social and governance data (ESG) scores collected from Thomson Reuters DataStream database for CSP. (Thomson Reuters ESG scores replace the existing ASSET4, because it will directly reflect strategic ESG framework). ESG score provides in-depth environmental, social and corporate governance information since 2002. Three main items accounted for different proportions, with the largest share in society 35.5%, 34% in the environment, and 30.5% in corporate governance (Reuters, 2017). Observations are collected from 2010 to 2016 for relatively complete coverage of records of CSP.
Secondly, the BoardEX database of Wharton Research Data Services (WRDS) covers information including an organization summary, individual profile, and board summaries with longitudinal data from different countries. The current paper used the BoardEX database to gather the gender, nationality, educational level of directors and board size in the board.
- 15 -
Multinational companies’ practice of social responsibilities can have a great impact on society. By integrating the data from the above-mentioned sources, the current paper will conduct empirical analysis on the top 100 companies from Fortune Global top list. The Fortune Global list is very diverse and operates in multiple industries (Krishnan & Park, 2005). Studying the composition of these MNCs’ board is meaningful to understand the different CSP within different years. Overall, the sample only consists of a balanced panel data of 81 MNCs from 2010 to 2016, 567 observations, because of data availability and year restriction for the completeness of balanced panel sample. The statistical analysis was performed in STATA.
3.2 Variables and measurement 3.2.1 Dependent variable
There are four main identified dimensions of social performance, which includes workforce, human rights, community relations, and product responsibility. In this study, the ESG score is selected to measure the social performance of MNCs. ESG issues become not only a passion for speculators, shareholders and the government as a risk management concern, but for enterprises, it has become an emerging part of their competitive strategy as well. More and more companies realize that ESG disclosure is crucial to their reputation and image in the face of green issues to their stakeholders (Tarmuji, et al., 2016). ESG provides a comprehensive platform to establish customizable benchmarks for evaluating the performance of corporations and focuses on creating long-term shareholder value. It offers the overall aggregate corporates value for each firm, and every company score is calculated by three pillars, including environmental, social and governmental categories. Such as resource use, innovation, human rights, product responsibility, community, shareholders and CSR strategy, etc. Each category includes a set of key performance indicators (KPI). The overall ESG score is calculated on the basis of an equal weighting of all relevant data points, the range is from 0 to 100 (Velte, 2016). In this paper, it is determined to only use social score, 35.5% of the total ESG score, since the interest of this paper is about the social performance of the corporation, which improves the accuracy of the study.
3.2.2 Independent variables
- 16 -
However, current study will use a new measurement. Gender is classified into two categories: “Female” and “Male” in general. BoardEX provides detailed information about each board member’s profile.
Secondly, cultural diversity is another independent variable. Although culture itself cannot be observed, several measures have been taken to quantify the different aspects of culture (Frijns, et al., 2016). There are different nationalities in the board and each nationality has its own score on each Hofstede dimension. In the current research it was decided to divide all nationalities in the board into three categories: “Low individualism”, “Medium individualism”, “High individualism”. In the Hofstede model, the total score of the dimension is 100 points, the higher the score, the more individualistic the country is (Hofstede, 2011). Thirdly, for educational level diversity, similar logic can be applied here. Educational level is classified into five level of the educational qualifications (“Bachelor”, “Master”, “MBA”, “PhD”, “Others”, such as fellow, studied, attended).
Afterward, gender diversity, individualism diversity and educational level diversity are calculated with the “Herfindahl-Hirschman Index (HHI)2”, which is defined as a common statistical measure of concentration in a variety of contexts. The HHI is calculated by squaring the market share of each company competing in the market, then a unique score is calculated by adding all squares. The HHI range is from 0 to 10,000 (Law, 2009). In this research, HHI could be a suitable method to quantify the effect of gender, individualism and education diversity on the board of a firm. An example is, if there is only one gender/individualism/education level in a company, then the single gender/individualism /education level will have 100% of the company share, the HHI will be 10,000, which indicates a monopoly of single type in the board. If there are different gender/individualism/education level “competing” in a company, the company shares of each gender/individualism/education level will be close to 0%, the HHI will be close to zero, indicating very high level of diversity (Investopedia.com). By using the HHI formula, the gender/individualism/educational diversity of Fortune 100 listed MNCs can be calculated in the executive board and non-executive board respectively. It is computed as:
!!" = % &'( )
'*+
- 17 -
The formula, in which Si is the share of gender/individualism/educational level i in the executive board and non-executive board, and N is the total number of gender/individualism/educational level in the executive board and non-executive board. An example of HHI calculation is that if there are 7 directors in the non-executive board, 4 directors come from high individualism countries, 2 from the medium individualism countries and 1 director come from low individualism country.
Step 1: Actual HHI (CAG: 3) → (4/7*100)2 + (2/7*100)2+ (1/7*100)2= 4286;
Step 2: Standardization should be applied, because different companies have different board sizes, variables should represent in the same metric unit, avoiding outliers. Standardization needs to take into account of the HHI with maximum diversity in theory, with the maximum diversity calculated, standardization helps to generate smaller coefficient estimates will improve the interpretation. The theoretical maximum HHI diversity should consider that the board size and category are differently distributed across three individualism categories. Thus, the value of maximum HHI diversity is (2/7*100)2 + (2/7*100)2 + (3/7*100)2 = 3469;
Step 3: The standardized HHI (H*) is computed as H*=HHI/max.HHI. In this case,
H*=4286/3469= 1.24. The range of cultural diversity is from 1 to 3, it means that the closer
the value to 1, the higher the diversity, the closer the value to 3, the lower the diversity. Gender diversity and educational diversity follows the same logic.
3.2.3 Control variables
Control variables are used to account for the effects from other variables that may affect the dependent variable in the research. Company size (number of employees), board size (number of board members), industry (9 types) and ROE are the four control variables.
First, company size is considered, which directly influences CSP. The reason is that MNCs are usually very eye-catching in the business world. They tend to attract more consumers and the public’s attention, so they are forced to show a positive social image. In addition, MNCs have a higher number of employees than small firms. Therefore, MNCs will be more concerned about their social performance than small companies (Hyun, et al., 2016). It is measured by the number of employees that firm reported (Van veen & Elbertsen, 2008).
- 18 -
lead to better corporate performance. However, from the perspective of resource dependence theory, a large board size could help corporations become less dependent on external resources. Because if the board size is large, the board is linked to greater opportunities in the external environment via the different board members’ personal network. As a result, the board’s decision making and strategy could be more effective. Board size is measured by the number of directors in the board (Ilaboya & Ashafoke, 2017).
Thirdly, industry is also a control variable, because the nature of different industries could directly influence the performance of the company, which depend on the specific industry it operates in (Mahadeo, et al. 2011). Comparing social performance in the same industry is more accurate. Such as, there is no comparison between the financial service industry and the engineering industry. In order to control for the effect of industry, the Thomson Reuters business classification will be used in this research. Nine dummy variables are created to represent major industries. (1: Energy; 2: Basic Materials; 3: Industrials; 4: Consumer Cyclical; 5: Non-Cyclical Consumer Goods & Services; 6: Financials; 7: Healthcare; 8: Technology; 9: Telecommunications Services).
Lastly, there are three commonly used measurement for firm financial performance, which are return on equity (ROE), return on asset (ROA) and return on sales (ROS). In this study, ROE can be considered a control variable as well. The reason is that ROE takes into account how investors assess how their investments generate revenue and corporations will get a chance to gain more profits. It is the most commonly used measure by researchers, which measures the ratio that indicates effective and efficient management of the use of a company’s equity to increase inventory turnover and sales for profit. In addition, Wan Ahamed, et. al. (2014) and Pan, et. al. (2014) indicated that there is a positive relationship between social responsibility and corporate firm performance. ROE is measured as net income divided by total stockholders’ equity. The overview of variables can be found in Table 1 (Appendix 1).
3.3 Model
3.3.1 Modelling specification
- 19 -
assumed to be realized value of a random variable, it is called a random effect. Pooled OLS model
This study focuses on the relationship between the board of directors (gender diversity, cultural diversity and educational diversity) and CSP. The dependent variable is CSP score, which measures the performance of corporate social responsibility. Three independent variables were all distinguished in executive board as “1” and non-executive board as “2”. The first independent variable is gender diversity as “GD”. The second independent variable is individualism diversity as “IDVD” and the last independent variable is educational diversity as “ED”. The control variables are company size as “CS”, board size as “BS”, industry types as “IND” and return on equity as “ROE”. In the pooled OLS model, all the independent variables and control variables are regressed on CSP. The specification is shown below.
CSP= α + β1 GD1 + β2 GD2 + β3 IDVD1 +β4 IDVD2 +β5 ED1+ β6 ED2+ β7 CS + β8 BS + β9 IND + β10 ROE+ ε
- α is the common intercept; - β1 is the coefficient for IV;
- ε is the corresponding error terms. Fixed-effects model
In the fixed effects model, the relationship between all independent variables and CSP is explored within each company. Each company has its own individual characteristics that may influence the predictors. In addition, since company size and industry type are time-invariant variables, they are removed from the fixed effect model below.
CSPit = αit + β1 GD1it + β2 GD2it + β3 IDVD1it +β4IDVD2it +β5 ED1it + β6 ED2it + β8 BSit + β10 ROEit + ,i + λt + εit
- i represents firms
- αi is the unknown intercept for each firm; - βi is the coefficient for IV;
- ,i is firm fixed effects; - λt is time fixed effects.
- 20 - Random-effects model
In a random effects model, it is assumed that each company’s error term is not correlated with the predictors. It allows time-invariant variables (company size “2016” and industry type) to play a role as explanatory variables. The specification is listed below.
CSPit = αi + β1 GD1it + β2 GD2it + β3 IDVD1it +β4IDVD2it +β5 ED1it+ β6 ED2it + β7 CSi + β8 BSit + β7 INDi + β8 ROEi t+ ,it + λt + εit
- t represents year;
- ,i is firm fixed effects; - λt is time fixed effects.
- εit is the corresponding error terms.
3.3.2 Specification tests
After establishing three models (OLS, Fixed effect and random effect model), by applying appropriate specification tests, it is aimed to find out the best model to use. A Lagrange Multiplier (LM) Test is used to determine whether to use the pooled OLS model or the random effects model. An F-test is used to choose fixed effect model or pooled OLS model. Lastly, the Hausman Test is used to decide between the fixed and random effects models.
The current research conducted a Variance Inflation Factor (VIF) test in pooled OLS regression model as a measure. As a rule of thumb, with all VIF scores reported below 5, it assures that the multicollinearity problem does not exist among independent variables in Table 2 (Appendix 2).
As indicated above, the process of analyzing panel data will go through three specification tests to determine the best model to use. Three models (OLS, fixed effect model and random effect model) are established. Firstly, LM test generates a p value significantly lower than 0.05, indicating that random effects model is better than the pooled OLS model. Secondly, F test result (df1 =71; df2 = 478; F=35.8; p <0.05) illustrates that the fixed effects model is also better than the pooled OLS model in Table 3 (Appendix 2). Thus, the pooling model is the least preferred option. The individual effects need to be taken into account in the model specification.
- 21 -
considered as the most appropriate model. Moreover, previous research by Carter et al. (2010) indicated that applying the fixed effects model could help to reduce omitted variables bias and deal with unobserved variable change over time.
3.4. Analysis of fixed-effects model Individual fixed effects or time-fixed effects
- 22 -
4. Results
This part will display the research result of this research. The setting of empirical result includes descriptive statistics and correlation results. In addition, results of the OLS regression between board directors and corporate social performance will be shown. After that, the result of the fixed effect models and robustness check are illustrated.
4.1 Descriptive Statistics
Table 6 illustrates the descriptive statistics of the MNCs in this research. The total sample includes 81 MNCs (567 observations) between 2010 to 2016. The number of observations, mean, standard deviations, minimum and maximum for independent, dependent and control variables are shown below.
Table 6 Descriptive Statistics
Variables N Mean St. Dev. Min Max
CSP 567 28.37 7.41 2.15 34.37
ED Gender diversity 567 1.65 0.37 1 2
NED Gender diversity 567 1.41 0.31 1 2
ED Cultural diversity 567 2.25 0.69 1 3
NED Cultural diversity 567 2.46 0.52 1 3
ED Educational diversity 567 1.81 0.75 1 5
NED Educational diversity 567 1.66 0.54 1 5
Board size 567 15.36 4.34 7 30
ED size 567 5.26 4.33 1 9
NED size 567 11.88 7.41 1 23
Company size 567 240,161.00 268,933.80 8,939 2,300,000
ROE (%) 567 22.85 38.44 -86.72 681.52
- 23 -
Table 7: The distribution of MNCs’ industry
Industry Number of MNCs Percentage
Energy 8 9.88%
Basic Materials 2 2.47%
Industrials 8 9.88%
Consumer Cyclical 7 8.64%
Non-Cyclical Consumer Goods & Services 11 13.58%
Financials 26 32.10%
Healthcare 5 6.17%
Technology 7 8.64%
Telecommunications Services 7 8.64%
As shown in Table 6, the mean of CSP is 28.87, which indicates that for most of the MNCs social performance was relatively high. But, there was a substantial difference between the minimum (2.15) and maximum value (34.37).
Looking at gender diversity, as mentioned before, boards have traditionally been dominated by men, the diversity of boards that involve more women has increased. The average HHI value of gender diversity both in ED (1.65) and NED (1.41) with a minimum of 1 and a maximum of 2, which is indicated that gender diversity in NED is higher than ED. Regarding cultural diversity, the mean of HHI in ED (2.25) and NED (2.46) with a minimum of 1 (the highest level of diversity) and a maximum of 3 (the lowest level of diversity), which indicated that both ED and NED in cultural perspective are not diverse. In terms of educational diversity, the average of HHI in ED (1.81) and NED (1.66), which means that education diversity in NED is higher than ED.
24 4.2 Correlation
Table 8: Correlation matrix
Variables (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11)
(1) CSP 1
(2) ED Gender diversity -0.1587 1
(3) NED Gender diversity -0.2947 0.2928 1
(4) ED Cultural diversity -0.2685 0.3207 0.1297 1
(5) NED Cultural diversity -0.1542 -0.0101 -0.0722 0.323 1
(6) ED Education diversity -0.0079 0.1103 -0.0464 0.3246 0.0339 1
(7) NED Education diversity -0.1007 -0.0441 0.0776 0.0868 0.2388 0.0414 1
(8) Company size -0.0247 -0.0253 0.0252 0.1251 -0.0162 0.047 0.0113 1
(9) Board size 0.225 -0.1203 -0.2942 0.0335 -0.1024 0.0989 -0.0725 0.2003 1
(10) Industry dummy -0.0801 0.0648 -0.1522 0.1113 0.1497 0.0335 -0.1038 0.0395 0.0035 1
(11) ROE (%) 0.0928 -0.0556 -0.0751 0.1552 0.1066 0.0442 0.0274 0.0173 0.0779 0.0222 1
25
In order to test potential multicollinearity among individual and control variables, a Pearson correlation test was conducted. Firstly, In Table 8 above, it shows that all the correlation values are under 0.7, which is in line with the requirement in econometric research. Therefore, no signs of multicollinearity was found. Secondly, looking at the correlation values of IVs and CSP, the correlations are not very strong. NED gender diversity, ED cultural diversity, board size scored higher than absolute value of 0.2, the rest scored even lower. The following regression analysis will further look at the effect of these variables on CSP.
4.3 Fixed-effects model
Table 9: Individual fixed-effects model
Dependent variable: CSP
ED Gender diversity -0.215
(0.517)
NED Gender diversity -1.602**
(0.669)
ED Cultural diversity 0.230
(0.349)
NED Cultural diversity -0.001
(0.577)
ED Education diversity -0.011
(0.262)
NED education diversity -0.640**
(0.384) Board Size -0.026 (0.098) ROE (%) 0.008* (0.004) Observations 567 R2 within 0.0307 R2 between 0.0610 R2 overall 0.0482 Adjusted R2 -0.148 F Statistic 1.90* (df = 8; 478)
Firm fixed effects Yes
26 4.3.1 Results of final fixed effects model
Table 9 above shows the fixed effect (individual) model with all the time-variant independent variables and control variables effects. Before interpreting the results of gender diversity, culture diversity and education diversity, it is important to keep in mind that the measure is standardized HHI. To give an example of gender diversity, the range is from 1 to 2, which means that the closer the value to 1, the higher the diversity, the closer the value to 2, the lower the diversity.
Regarding gender diversity, it is denoted by the standardized HHI of gender diversity in non-executive board and executive board. Controlling the effects of board size and ROE, the parameter estimate of ED gender diversity is not statistically significant (p>0.05), while that of NED gender diversity shows significant results (β = -1.602, p<0.05). It indicates that gender diversity in the executive board does not lead to higher CSP performance. While in terms of non-executive board, bringing gender diversity (more female members basically) will indeed improve CSP. Specifically, one percent increase of HHI ratio in NED will lead to -1.602 unit decrease in CSP. In the other words, the more diverse the gender in the non-executive board, the better the CSP. Therefore, hypothesis 1a is rejected and hypothesis 1b is supported.
Looking at the coefficients of cultural diversity, it is represented by the individualism diversity among board members. Surprisingly, neither ED cultural diversity nor NED cultural diversity have a significant influence on CSP of the firm (p>0.05). The outcomes are contradictory to the assumptions in hypothesis 2a and hypothesis 2b. Therefore, the composition of directors’ individualism backgrounds does not lead to the change of CSP. Thus, hypothesis 2a and hypothesis 2b are both rejected.
Next, with respect to educational diversity, no significant result was found for ED educational diversity, while a significant result was found for NED educational diversity (β = -0.64, p <0.05). The standardized HHI denotes that the ratio of actual HHI to the HHI with maximum diversity in theory. Thus, the outcome of NED educational diversity indicates that one percent increase of the HHI ratio will lead to -0.64 unit decrease of CSP of the company. Regarding the insights for the boards, if the distribution of educational levels in the board tend to be even, put it differently, the more diverse the educational levels in the non-executive board, the better the CSP. Overall, hypothesis 3a and hypothesis 3b are both rejected.
27
positively influence CSP (β = 0.008, p<0.05), with 1 percent increase of ROE contributing to 0.008 unit increase of CSP value.
Company size (year 2016) and industry are not included in the fixed effects model since they are time-invariant, which means there is no variation within companies. In order to see the effects from these two control variables, the parameter estimates of these two variables are regressed on CSP in a pooled model to interpret the effects. Firstly, since company size is a on a very large scale, all the values are transformed by the natural log. And company size has a negative significant influence (β = -1.59, p<0.05) on CSP, which means that 1 percent increase of company size will decrease 1.59 unit of CSP. Next, with respect to industry type, there are 9 industry types in the panel data of current research. Industry type is regarded as a factor variable in the OLS regression, industry 6 “Financials” is considered as a benchmark level, because the financial sector is the largest sector in the sample of the current research. Thus, it is interesting to compare all the other industries to see how does the industry effect on CSP differ compared to financial industry. To give an example, compared to benchmark financials industry, companies from healthcare industry in general has a significantly lower CSP value by -7.080 unit than companies from financial industry. In order to compare the difference of industry’s effect on CSP, the benchmark level changed nine times. The detailed results of the OLS models can be found in Table 10 (Appendix 4).
4.4 Robustness check
Literature suggested that robustness checks how certain a regression coefficient estimates behave when the specification of the model is changed by adding or removing predictors (Lu & White, 2014). In order to test the robustness of the fixed effects model above, there are two robustness checks conducted in this study. It was decided to remove two control variables (Board size and ROE) in the fixed effect model each time respectively. Control variables are also predictors in the regression. Because the interest of the current paper is to look at the effects of individual effects. By removing each control variable in every check, it was determined to check if the significance of the model had changed dramatically. If the change was dramatic, the fixed effect model is not robust. On the other hand, if the change is slight, the fixed effect model is robust.
28
deleted from the model, its significance did not have a substantial change. When Board size was deleted from the model, the results were not significantly different compared to the original model. With regard to those insignificant individual variables in the original fixed effects model, they are still insignificant in both robustness checks. Overall, it can be concluded that the original fixed effect model are robust and the results of hypotheses testing remains consistent.
5. Discussion
This part will discuss the results of the empirical analysis. The outcomes of the six hypotheses are summarized in Table 13 below. At the same time, the explanation gathered from the literature review is also used in this discussion.
Table 13: Summary of results
Hypotheses Results
Hypothesis 1a: With a higher gender diversity in the executive board, the CSP of
the MNC will increase. Rejected
Hypothesis 1b: With a higher gender diversity in the non-executive board, the CSP of the MNC will increase
Supported
Hypothesis 2a: With a higher degree of individualism diversity in the executive
board, the CSP of the MNC will decrease. Rejected
Hypothesis 2a: With a higher degree of individualism diversity in the non-executive board, the CSP of the MNC will decrease.
Rejected
Hypothesis 3a: With a higher educational level diversity in the executive board, the
CSP of the MNC will decrease. Rejected
Hypothesis 3b: With a higher educational level diversity in the non-executive board, the CSP of the MNC will decrease.
Rejected
29
on board issues and facilitates ED’s strategic decisions. In addition, normally, the number of NED exceeds that of ED. Thus, the effect of the diversity of NED is more obvious than ED.
Secondly, hypothesis 1a expected a positive relationship between ED gender diversity and CSP. From the results of the fixed effect model in Table 9, there is no significant relationship between gender diversity in ED and CSP. The possible reason is that executive board size is smaller than non-executive board size. Moreover, according to descriptive statistics, it can be found that there are very few female companies in ED, the position occupied by females in ED is not common. Therefore, I cannot support hypothesis 1a. Hypothesis 1b can meet the expectation that there is a positive correlation between NED gender diversity and CSP. As mentioned before, OLS provides biased estimates, thus its results should not be interpreted. In order to consider the omitted variables and the heterogeneity across companies, an individual fixed effect model is adopted. The results of the fixed effects regression equation shows that there is a positive relationship between NED gender diversity and CSP. This suggests that the increase of gender diversity on non-executive board will lead to the increase of CSP, which is in line with former research by Byron & Post (2016) and Kyaw et al. (2017). Upper echelons theory, agency theory and resource dependency theory provide an explanation for this positive coefficient. Compared with males, female directors of non-executive directors bring a different cognitive framework, experiences and values. In addition, companies can bring more women to boards, easing internal controls because women are more likely to discuss difficult issues and correct strategic biases. Moreover, hiring more females to non-executive boards, in order to increase the gender diversity, which could help maintain relationships with clients (Chin, Hambrick & Treviño, 2013; Chen, Eshleman & Soileau, 2016). The maximization of gender diversity is conducive to the company having different ideas and strategies for social responsibility. Thus, hypothesis 1b is supported.
30
has been shown to cause tension among these groups, which may raise concerns about the fairness and performance of employees from different backgrounds (Rosenauer, et al. 2015). When tasks are less interdependent, the diversity of culture is less important. While, high task interdependence is typical in the international context, every team member plays a very important role to achieve their goals together. Therefore, performance is more sensitive to diversity. Based on these mixed findings I cannot support both hypotheses 2a and 2b.
31
6. Conclusions
This part is the conclusion, which is mainly focused on answering the research question. In addition, limitations, recommendations, and contributions will be contained.
6.1 Relevance and grounded conclusions
Board diversity has become a hot topic for multinational corporations, which is closely related to the issue of board composition (both in the executive and non-executive boards). The objective of this research is to investigate the relationship between directors (ED and NED) in the board and corporate social performance, specifically in MNCs. The combination of the upper echelons theory, agency theory, resource dependency theory, human capital and Hofstede theory are used to help understand and demonstrate the relationship between the board and CSP.
An individual fixed-effects model was determined to be the most appropriate model in this research. With regards to the results of the final fixed effect regression equation, it shows that there is no significant relationship between gender/cultural/educational diversity in the executive board and CSP. Regarding the non-executive board, the result shows that there is no significant relationship between cultural diversity and CSP. However, there is a significant relationship between gender/educational diversity and CSP, because increased gender/educational diversity will improve the different cognitions, values and knowledge of the non-executive board. Hence, it could help top management to do the strategic decision-making in a better way. Thus, NED has more research value than ED for board diversity since NED not only provides feedback to the board, but also facilitates ED’s strategic decisions.
6.2 Limitations and Recommendations
32
diverse directors and firm performance (Carter et al., 2010). Another problem of endogeneity is reverse causality. Theoretically, a change in diversity is the causal driven of change. However, it could also be possible that companies change the structure of the board due to the incentives to boost the performance. Therefore, future researchers can find more effective variables to control possible reverse causality problems.
Secondly, empirical research also has limitations. R squared should be discussed. According to the final model, R square is very small (3.1%), which indicates the percentage of variance in the dependent variable (CSP) explained by a model. Nevertheless, a small R squared does not mean the model is useless or unworthy of being interpreted. R squared is small, but it still has scientific significance. The discussion of the estimated coefficients proved the reliability of the relationships formulated in the hypotheses. Furthermore, an important limitation of this research is the negative adjusted R squared, which is -0.148. Negative Adjusted R squared means insufficient significance of the explanatory variables. Two reasons can lead to this outcome, the first reason is due to the collinearity of individual variables. It should not be relevant in current research case after testing for VIF score. The second reason can be the low correlation of predictors to the dependent variable. This reason reflects the situation in the current research, the correlation of the characteristics of board of directors and CSP are very low, which lead to the negative adjusted R square in the model. Thirdly, this study only used 81 companies from 2010 to 2016 as a sample, based on a fixed effects model, it was found not necessary to add time-invariant variables into model. It should be noticed that CSP across years in current research was not fluctuating. In order to more deeply understand the annual fluctuations, future research could extend the time range to 10 years of data, which could improve the heterogeneity of the data and help with the understanding of the effect from time on CSP. In addition, increasing the number of corporations could also be helpful to empirically examine the individual effects across companies. Lastly, future studies could seek to explore the mediator or moderator mechanism (such as various strategic decision) via director in the board influence on the CSP (Nielsen & Nielsen, 2012).
6.3 Contributions
33
the Herfindahl-Hirschman Index was used to explore the board composition in this study. It is important to note that to calculate standardized HHI, the actual value of HHI and the maximum value of HHI was also used. This was done because the value depends on the different categories and board size in the ED and the NED respectively and to make the standardized HHI more accurate. Moreover, the results showed that the diversity of gender/education will bring significant positive impact to corporate social performance, but the impact of threshold for gender diversity and social performance, which is worthy of further research, especially on the non-executive board. Future researches could ignore the executive directors and focus directly on the influence of non-executive directors or the entire board on corporate performance.
34
References
Adams, R., & Ferreira, D. 2009. Women in the boardroom and their impact on governance and performance. Journal of Financial Economics, 94(2): 291-309.
Byron, K., & Post, C. 2016. Women on Boards of Directors and Corporate Social Performance: A Meta-Analysis. Corporate Governance: An International Review, 24(4): 428-442. Boulouta, I. 2012. Hidden Connections: The Link Between Board Gender Diversity and
Corporate Social Performance. Journal of Business Ethics, 113(2): 185-197.
Carroll, A., & Shabana, K. 2010. The Business Case for Corporate Social Responsibility: A Review of Concepts, Research and Practice. International Journal of Management Reviews, 12(1): 85-105.
Cannella, A., Jones, C., & Withers, M. 2014. Family- versus Lone-Founder-Controlled Public Corporations: Social Identity Theory and Boards of Directors. Academy of Management Journal, 58(2): 436-459.
Cook, A., & Glass, C. 2017. Women on corporate boards: Do they advance corporate social responsibility? Human Relations, 001872671772920.
Coff, R., & Raffiee, J. 2015. Toward a Theory of Perceived Firm-Specific Human Capital. Academy of Management Perspectives, 29(3): 326-341.
Carter, D., D'Souza, F., Simkins, B., & Simpson, W. 2010. The Gender and Ethnic Diversity of US Boards and Board Committees and Firm Financial Performance. Corporate Governance: An International Review, 18(5): 396-414.
Corporate Social Responsibility (CSR) - Growth - European Commission. 2011. Growth.
http://ec.europa.eu/growth/industry/corporate-social-responsibility_en , March 12, 2018.
Chin, M., Hambrick, D., & Treviño, L. 2013. Political Ideologies of CEOs. Administrative Science Quarterly, 58(2): 197-232.
Chen, Y., Eshleman, J., & Soileau, J. 2016. Board Gender Diversity and Internal Control Weaknesses. Advances in Accounting, 33: 11-19.
Dallas, L. 2002. The New Managerialism and Diversity on Corporate Boards of Directors. SSRN Electronic Journal.
Deloitte., 2015. Diversity in the boardroom, retrieved February 26, 2018
35
Does Gender Diversity on Boards Really Boost Company Performance? - Knowledge@Wharton. 2017. Wharton.
http://knowledge.wharton.upenn.edu/article/will-gender-diversity-boards-really-boost-company-performance/ , March 12, 2018.
De Jong, G., & van Houten, J. 2014. The impact of MNE cultural diversity on the internationalization-performance relationship. International Business Review, 23(1): 313-326.
Eulerich, M., Velte, P., & van Uum, C. 2014. The impact of management board diversity on corporate performance – an empirical analysis for the German two-tier system. Problems and Perspectives in Management, 12(1): 25-39.
Ford, E. 2016. Non-executive director vs executive director, what is the difference? – NEDonBoard | NED on Board. NEDonBoard | Professional Organisation for Non-Executive Directors. https://www.nedonboard.com/what-are-the-key-differences-between-executive-and-non-executive-directors/,March 25, 2018.
Gallén, M., & Peraita, C. 2017. The effects of national culture on corporate social responsibility disclosure: a cross-country comparison. Applied Economics, 50(27): 2967-2979. Frijns, B., Dodd, O., & Cimerova, H. 2016. The impact of cultural diversity in corporate boards
on firm performance. Journal of Corporate Finance, 41: 521-541.
Hyun, E., Yang, D., Jung, H., & Hong, K. 2016. Women on Boards and Corporate Social Responsibility. Sustainability, 8(4): 300.
Hambrick, D.C., 2007. Upper Echelons Theory: An update. Academy of Management Review, 32(2): 334-343.
Hambrick, D., & Mason, P. 1984. Upper Echelons: The Organization as a Reflection of Its Top Managers. The Academy of Management Review, 9(2): 193.
Hung, H. 2011. Directors’ Roles in Corporate Social Responsibility: A Stakeholder Perspective. Journal of Business Ethics, 103(3): 385-402.
Hofstede, G., & Hofstede, G. 2005. Cultures and organizations (2nd ed.). New York: McGraw-Hill.
Hofstede, G. 2011. Dimensionalizing Cultures: The Hofstede Model in Context. Online Readings in Psychology and Culture, 2(1).
36
Hutchinson, M., Mack, J., & Plastow, K. 2014. Who selects the ‘right’ directors? An examination of the association between board selection, gender diversity and outcomes. Accounting & Finance, 55(4): 1071-1103.
Hirschman, A. (1945). National Power and the Structure of Foreign Trade. Berkeley: University of California Press.
Ilaboya, J., & Ashafoke, T. 2017. Board Diversity and Firm Performance in Nigeria. International Journal of Management, Accounting and Economics, Vol. 4, No. 2383-2126.
Isik, O., & Riza, A. 2016. Board Size, Board Composition and Performance: An Investigation on Turkish Banks. International Business Research, 9(2): 74.
Jacobs, B., Kraude, R., & Narayanan, S. 2016. Operational Productivity, Corporate Social Performance, Financial Performance, and Risk in Manufacturing Firms. Production and Operations Management, 25(12): 2065-2085.
Jungmann, C. 2006. The Effectiveness of Corporate Governance in One-Tier and Two-Tier Board Systems – Evidence from the UK and Germany. European Company and Financial Law Review, 3(4).
Juravich, M., Salaga, S., & Babiak, K. 2017. Upper Echelons in Professional Sport: The Impact of NBA General Managers on Team Performance. Journal of Sport Management, 31(5): 466-479.
Kirkman, B., Lowe, K., & Gibson, C. 2006. A quarter century of Culture's Consequences: a review of empirical research incorporating Hofstede's cultural values framework. Journal of International Business Studies, 37(3): 285-320.
Krishnan, H., & Park, D. 2005. A few good women—on top management teams. Journal of Business Research, 58(12): 1712-1720.
Kagzi, M., & Guha, M. 2018. Does board demographic diversity influence firm performance? Evidence from Indian-knowledge intensive firms. Benchmarking: An International Journal, 25(3): 1028-1058.
Kyaw, K., Olugbode, M., & Petracci, B. 2017. Can board gender diversity promote corporate social performance?. Corporate Governance: The international journal of business in society, 17(5): 789-802.
Lückerath-Rovers, M. 2009. Female Directors on Corporate Boards Provide Legitimacy to a Company: A Resource Dependency Perspective, retrieved March 3, 2018
37
Lozano, R. 2012. How can theories of the Firm help make societies more sustainable? Sustainability Research Institute, (1753-1330).
Lee, W., Kim, I., & Moon, J. 2016. Determinants of restaurant internationalization: an upper echelons theory perspective. International Journal of Contemporary Hospitality Management, 28(12): 2864-2887
Lu, X., & White, H. 2014. Robustness checks and robustness tests in applied economics. Journal of Econometrics, 178: 194-206.
Mahadeo, J., Soobaroyen, T., & Hanuman, V. 2011. Board Composition and Financial Performance: Uncovering the Effects of Diversity in an Emerging Economy. Journal of Business Ethics, 105(3): 375-388.
Muller, A. 2006. Global Versus Local CSR Strategies. European Management Journal, 24(2-3): 189-198.
Muller, A., & Kolk, A. 2010. Extrinsic and Intrinsic Drivers of Corporate Social Performance: Evidence from Foreign and Domestic Firms in Mexico. Journal of Management Studies, 47(1): 1-26.
McCarthy, L. 2017. Empowering Women Through Corporate Social Responsibility: A Feminist Foucauldian Critique. Business Ethics Quarterly, 27(04): 603-631.
McGee, J., Thomas, H., & Wilson, D. 2010. Strategy: analysis and practice. Maidenhead: McGraw-Hill Higher Education.
Nielsen, B., & Nielsen, S. 2012. Top management team nationality diversity and firm performance: A multilevel study. Strategic Management Journal, 34(3): 373-382. Nguyen, D., Hagendorff, J., & Eshraghi, A. 2017. Does a CEO’s Cultural Heritage Affect
Performance under Competitive Pressure? The Review of Financial Studies, 31(1): 97-141.
Oikonomou, I., Brooks, C., & Pavelin, S. 2014. The Effects of Corporate Social Performance on the Cost of Corporate Debt and Credit Ratings. Financial Review, 49(1): 49-75. Piasecki, R., & Gudowski, J. 2017. Corporate Social Responsibility: The Challenges and
Constraints. Comparative Economic Research, 20(4).
Post, C., & Byron, K. 2015. Women on Boards and Firm Financial Performance: A Meta-Analysis. Academy of Management Journal, 58(5): 1546-1571.
