Do female board members influence firm
performance?
The influence of board gender diversity on firm
performance in the UK
Master’s Thesis
Multinational Corporations: Organization & Strategy By: Kimberly van Rooijen
Faculty of Economics and Business MSc International Business and Management
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TABLE OF CONTENTS
Abstract 2
Introduction 2
Literature review and hypotheses 5 Upper echelons theory 5 Resource dependency theory and human capital theory 6 Gender role theory 8 Board gender diversity and firm performance 9
CEO power 11
Corporate social performance 12
Methodology 14
Sample and data collection 14 Dependent variable 16 Independent variable 17 Moderator and mediator variables 17
Control variables 18
Analysis 19
Results 21
Descriptive statistics and correlations 21
OLS regressions 23
Robustness check 26
Discussion 27
Limitations and future research 30
Conclusion 33
References 34
Appendices 44
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ABSTRACT
A growing trend in the number of female board members has been uncovered. Whether female representation on boards displays positive performance results remains questionable as different studies display opposing results. This research identifies whether board gender diversity within UK companiesinfluences the firm’s performance levels. Moreover, it examines whether CEO power moderates and CSP mediates the relationship between board gender diversity and firm performance. It is expected that board gender diversity overall positively influences firm performance. Additionally, it is expected that the effect of board gender diversity is lower when CEO power is high, and that diversity positively affects CSP, which subsequently positively affects firm performance. From a final sample of 271 UK firms, the effect of board gender diversity on firm financial performance was researched by using OLS regression models. The results show that a positive relationship between board gender diversity and firm performance exists. In addition, the findings show that CEO power negatively moderates and CSP positively mediates the relationship between board gender diversity and firm performance.
Keywords: Board gender diversity, Board of directors, Corporate governance, Upper echelons, Gender roles, Corporate Social Performance, CEO power, Firm performance
INTRODUCTION
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attaching sanctions to non-compliance (European Commission, 2012). However, whether these initiatives of increasing the percentage of women occupying positions within company boards have positively contributed to the firm performance levels represents an area that still requires exploration, as the understanding of in what way board gender diversity influences the firm is highly conflicted.
Findings related to the relationship between board gender diversity and organizational outcomes are inconsistent, with some studies finding positive results (Carter et al. 2003, Erhardt et al. 2003), some finding negative effects (Shrader et al. 1997; Böhren & Ström, 2010; Adams & Ferreira, 2009), and some finding no significant relations (Rose, 2007; Dwyer et al., 2003; Marinova, Plantenga & Remery, 2010; Randøy, Thomsen & Oxelheim, 2006; Miller & Triana, 2009). Consequently, the exact influence of female board members on the organizational performance levels is still subject to discussion and is argued to be more complex than can be grasped by testing and formulating a direct relationship (Terjesen, Sealy & Singh, 2009). Therefore, scholars have stated that the context and underlying mechanisms surrounding the board diversity and performance relationship must be explored, to uncover how and when board diversity affects performance (Byron & Post, 2016). Specifically, this study takes into account different factors that have yet to be explored within the context of the board gender diversity-firm performance relationship, that is, the influence of CEO power and corporate social performance (CSP). If the board members cannot freely express their ideas and perspectives due to the large amount of power the CEO possesses, their unique and valuable contributions will potentially remain unimplemented, limiting the positive effects board gender diversity could have on firm performance (Miller & Triana, 2009; Triana, Miller & Trzebiatowksi, 2013). Additionally, CSP is argued to represent an underlying force of the relationship between board gender diversity and firm performance. As female board members are, stereotypically, stated to be more sensitive, risk-averse and sustainability-focused (Glass, Cook & Ingersoll, 2016), they may stimulate the engagement to corporate social practices (Boulouta, 2013), which could be linked to higher firm performance levels (Orlitzky, Schmidt & Rynes, 2003). In this paper financial firm performance measures are considered, which can be grouped as market-based or accounting measures (e.g. Tobin’s Q, return on assets (ROA), and return on equity (ROE)), because financial performance measures are most frequently used when measuring performance (Combs, Crook & Shook, 2005).
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the organizational outcomes (Hambrick, 2007; Hambrick & Mason, 1984). Following the argument of, for example, Hambrick (2007), this study pays more attention towards the whole board, rather than focusing on one individual, as it would provide a more detailed view of the organizational outcomes. Additionally, the upper echelons theory is combined with the resource dependency theory in order to examine how board composition affects firm performance levels (Hillman, Cannela, & Patzold, 2000), as it suggests that different board members will provide diverse beneficial resources to the organization. Simultaneously, human capital theory enhances the board gender diversity concepts related to the resource dependency theory, as it indicates that a person’s accumulation of experience, education, and skills can be valuable to the firm, with gender forming a meaningful division between directors, leading to the possession of unique human capital (Terjesen et al., 2009). Moreover, the influence of female board members is associated with gender role theory (Eagly, 1987; Eagly & Johnson, 1990), which states that people behave in accordance with stereotypes and beliefs related to their social roles. Due to the different gender roles that male and female executives are faced with, they will engage in dissimilar behavior, resulting in different organizational outcomes.
The following research will contribute to streams of research on board gender diversity and firm performance, more specifically the former UK studies, as previous streams have been mostly US and Nordic region focused (e.g.Erhardt et al., 2003; Smith et al., 2006). Moreover, it introduces novel insights into the contextual factors surrounding and underlying forces explaining the board gender diversity-firm performance relationship by investigating the effects of the proposed moderator CEO power and the proposed mediator CSP. This research follows the upper echelons, resource dependency, human capital and gender role theory to explain the effect of the board’s gender diversity on displayed behavior, and subsequently, organizational outcomes and firm performance. Overall, the research question of this study is ‘What is the effect of board gender diversity on firm performance?’
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LITERATURE REVIEW AND HYPOTHESES
In the following section an explanation of the influence of board gender diversity on firm performance will be given by reviewing previous literature. It starts with the upper echelons theory, resource dependency theory, human capital theory and gender role theory and continues with a discussion of the relevant concepts related to board gender diversity and firm performance. Based on these research streams, hypotheses will be established. Moreover, the theoretical foundations surrounding the moderator CEO power and the mediator corporate social performance (CSP) will also be considered. The chapter concludes with the conceptual model.
Upper echelons theory
This research builds upon the foundations of the upper echelons theory, as established by Hambrick and Mason in 1984. The foundation of this perspective entails that executives are guided by their personal characteristics, including their personalities, norms, values and experiences, when perceiving situations and alternatives. This personalized perspective shapes and influences executives’ decisions (Hambrick & Mason, 1984; Hambrick, 2007). It follows Pfeffer (1983) in the approach that demographic characteristics can reflect managers’ dissimilarities along significant psychological constructs. Executives differ with respect to these personal characteristics, which in turn leads to varying decisions and outcomes, forming an explanation for existing heterogeneity among companies’ displayed behavior and results. Particularly with regards to complex and ambiguous contexts, forming the basis for bounded rationality (Cyert & March, 1963), which strategic decision-making processes often consist of, the executives’ values are reflected in the organizational outcomes due to their interpretations of the situations (Mischel, 1977). One can only understand why certain strategic choices have been made, or why certain organizational outcomes have occurred, by taking into account the biases and characteristics of the actors making up the ‘upper echelon’, that is, the body at the top of an organization with the power and responsibility to make decisions.
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Shamsie, 2001). Simultaneously, executives’ norms and values were also mentioned to influence organizational decision-making. The reason that this phenomenon is underrepresented in the upper echelons theory research streams is because it is harder to investigate due to different reasons. For example, according to agency theory, executives are expected to behave in line with the owners’ preferences rather than their own (Eisenhardt, 1989). Additionally, norms and values as attributes are more difficult to observe due to the tacit nature and are often reflected into leaders’ behavior in a conscious and subconscious manner, downgrading the awareness. Yet, these values are recognizable due to the process called ‘perceptual filtering’, which states that information is selectively searched, perceived and interpreted in accordance with the values of the executive (Starbuck & Milliken, 1988; Levitt & March, 1988). Consequently, executives’ values guide the evaluation and assessment of corporate activities, influencing the organizational outcomes. Moreover, executives influence the perspectives, values and targets of lower-level employees, inspiring and supporting entrepreneurial spirits among them (Damanpour & Schneider, 2008; Hornsby et al., 2009). On the other hand, the other stream of research relies on the heterogeneity within the team and the effect on strategic outcomes (e.g. Hambrick, Cho & Chen, 1996), which can be described as the variation in the team members’ characteristics. Various studies have identified considerable outcomes associated with female leadership styles and more diversity in teams and boards including higher innovation levels and profitability, larger focus on corporate social responsibility, bigger perceived success satisfaction by stakeholders and a broader consumer outreach (Dezső & Ross, 2012; Glass et al., 2016; Orser & Leck, 2010). For the purpose of this study, the second stream will be followed, by focusing on the boards’ heterogeneity as a result of the gender diversity present. Moreover, as other authors have argued that more attention must be paid towards the whole TMT or board when following the upper echelons theory, rather than focusing on one individual, this research will focus on the companies’ boards, because it would provide a more detailed view of the organizational outcomes (e.g. Hambrick, 2007).
Resource dependency theory and human capital theory
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to information and expertise, communication channels within the network, support from the external organizations, and legitimacy in the outside environment (Pfeffer & Salancik, 1978). Overall, this decreases uncertainty and increases firm performance (Taljaard et al., 2015). Different types of directors will equip the firm with access to these different benefits (Hillman et al., 2000). Consequently, directors with diverging backgrounds, e.g. male versus female directors, will supply the firm with resources of higher worth as a diverse board has more access to valuable networks, information and support, leading to higher firm performance (Bryant & Davis, 2012; Hillman & Dalziel, 2003).
In spite of the resource dependency theory being used by many scholars in the past due to its relevance in improving the understanding of the link between the firm and its outside environment, other research streams dissected the theory as it does not provide a comprehensive understanding of the specific resources directors bring to boards (Hillman, Withers & Collins, 2009; Drees & Heugens, 2013). To overcome this limitation of the resource dependency theory, the human capital theory can be used to complement this shortcoming, in order to understand the processes of why directors’ resource provisions can influence firm performance (Crook et al., 2011; Lester et al., 2008; Carter, D’Souza, Simkins & Simpson, 2010). The importance of the role of human capital has been emphasized by researchers studying a resource dependency theory of competitive advantage as it can illustrate why certain firms outperform other firms (Crook et al., 2011).
Human capital theory originates from Becker’s work (1964) which states that a person’s know-how, experience, education and skills can be of valuable use to the firm. Due to the tacit nature of human capital, because it is embedded within people, it cannot be easily duplicated or substituted by other firms (Crook et al., 2011). Therefore, it represents a source of competitive advantage for firms (Barney, 1991). As differences in the gender of the directors bring about unique types of human capital among the members (Terjesen et al., 2009), it will influence strategic decision-making because of novel perspectives and sources of knowledge (Fagan, González Menéndez, & Gómez Ansón, 2012). Consequently, human capital is affected by the amount of diversity present on the board and can be used to explain firm performance (Carter et al., 2010).
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effectiveness (e.g. Kim, Pantzalis & Park, 2013; Carter et al., 2003). However, another stream found a negative relationship, as it is argued that higher diversity leads to more conflicts. For example, Smith et al. (2006) argued that diverging opinions and perspectives slow decision-making processes extensively and raise areas of disagreement. Especially for firms doing business in competitive markets, facing shorter time to markets, board diversity could lead to lower performance levels, as the requirement for fast responses might outweigh the value of better decision in the end (Hambrick et al., 1996).
Gender role theory
Gender role theory, as explained by Eagly (1987), states that both men and women act according to stereotypes and beliefs related to the social role they play within an environment. Eagly, Wood and Diekman (2000) argue that behavioral sex differences and similarities represent ‘gender role beliefs’ and these beliefs are what reflect the society’s perception of men’s and women’s ‘social roles’. These beliefs result from the perceived attributes that men and women possess necessary for sex-typical roles, also referred to as gender stereotypes. Gender roles influence behavior through different mechanisms, biologically through hormones, internally through the feelings one must adhere to the self-established gender identity, and socially through displaying behavior consistent with others’ expectations (Wood & Eagly, 2010). Most of these gender role assumptions can be grouped together in two dimensions, regularly labelled as ‘agentic’ and ‘communal’ (Bakan, 1966). Men are perceived to be agentic, which consists of being dominant, assertive and competitive. On the other hand, women are thought to be more communal, including the concepts of being friendly, concerned with others, unselfish and emotionally expressive. These gender-specific characteristics also follow into the division of labor and the fulfilment of the tasks that need to be performed (Wood & Eagly, 2010).
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Similarly, Vandergrift and Brown (2005) proposed the theory of women being more risk-averse than men, which affects their approaches to doing business. Women and men also differ with regards to their preference for activities, where women prefer activities related to supporting and helping people and focused on sustainability, while men are more focused on money-making activities (Glass et al., 2016; Betz, O’Connell & Shepard, 1989). Female executives are also expected to possess a leadership style more focused on harmony, inclusion and openness than male executives, creating a sense of collaboration and facilitating information and power sharing (Hurst et al., 1989). Overall, female executives differ in values from their male counterparts (Selby, 2000), and these personality traits and behaviors have been discovered to influence firm performance levels (Jennings & Brush, 2013).
Board gender diversity and firm performance
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gender diversity, where a study can focus on the ratio of female representation (e.g.Randøy et al., 2006), a dummy variable for the presence of women on a board or team (e.g. Haslam et al., 2010), and/or the Blau index (a diversity index) (e.g. He & Huang, 2011).
Theoretically, regarding the association between gender diversity and firm performance, different arguments persist in the literature, consistent with the upper echelons and gender role theory foundations, which state that directors act according to the gender roles they are expected to fulfill and influence organizational outcomes accordingly (Hambrick & Mason, 1984; Eagly, 1987). These gender-specific attributes influence a director’s values and these shape and influence the director’s strategic decisions subsequently. Due to the different manners in which male and female board members conduct themselves within a board (e.g. Vandergrift & Brown, 2005; Glass et al., 2016), varied decisions will be made, leading to diverging organizational outcomes, including firm performance levels. In short, different levels of gender diversity in a board will have different effects on the strategic choices and ultimately on firm performance. As an illustration, one stream of research associates diversity with positive organizational outcomes, due to the different benefits female board members bring, such as more business and segmental growth (Khan & Vieito, 2013), more economic value (Dezső & Ross, 2012), and different perspectives and experiences leading to broader and richer knowledge (Cox, 1994; Carter et al., 2003). Female board members are also less involved in the ‘old boys’ networks, which enables them to be better and more objective in monitoring and alleviating stakeholder conflicts (Adams & Ferreira, 2009). Additionally, more diverse boards are linked to more creative initiatives, higher levels of information and resources sharing (Earley & Mosakowski, 2000) and, subsequently, to higher levels of innovation (Jackson, 1992).
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diversity brings about great benefits (e.g. Carter et al., 2003). The above mentioned positive aspects, for example, better monitoring, richer knowledge, and more innovation (e.g. Adams & Ferreira, 2009; Cox, 1994; Jackson, 1992), are argued to outweigh the negative effects associated with gender diverse teams (Erhardt et al., 2003). For these reasons, it can be stated that the net relationship between gender diversity in a board, represented by the percentage of women on the board, and firm performance is expected to be positive. Consequently, the following hypothesis arose, predicting that a gender diverse board has a positive influence on firm performance:
H1: There is a positive relationship between board gender diversity and firm performance. CEO power
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statements containing fraudulent information. Consequently, CEO duality greatly influences the ability of a board to effectively exert control and monitor.
Based on this, positive effects related to gender diversity on boards might not directly have an effect if the power that the board members possess is limited. Therefore, it can be expected that the relationship between board gender diversity and firm performance might be negatively influenced when a board operates under conditions of having a dual CEO-chairman, so that the female members’ knowledge sources, ideas and perspectives are not being heard nor implemented (Miller & Triana, 2009; Combs et al., 2007). This explains why the moderator of CEO power must be investigated within this board gender diversity research, leading to the following proposed hypothesis:
H2: CEO power negatively moderates the relationship between board gender diversity and firm performance, such that higher CEO power levels will weaken the positive relationship between board gender diversity and firm performance.
Corporate social performance
Corporate social performance (CSP) can generally be defined as engaging in socially responsible practices and generating a beneficial reputation among the stakeholders of the organization (Orlitzky et al., 2003), or the principles, processes and results related to a firm’s societal linkages (Wood, 1991). Various studies have found a positive association between CSP and organizational practices and outcomes, such as higher stakeholder and employee satisfaction (Carroll, 1999; Bauman & Skitka, 2012), organizational commitment (Brammer, Millington, & Rayton, 2007), and as representing a competitive advantage for organizations (McWilliams, Siegel, & Wright, 2006). Higher levels of CSP enhances the efficiency of stakeholder management. Combining the positive effects, meta-analytic research has found that CSP can positively influence firm performance (Waddock & Graves, 1997; Orlitzky et al., 2003; Wood, 2010).
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practices of the organization and its reputation among stakeholders (Terjesen et al., 2009). For example, women on boards are expected to act in line with female stereotypical behavior (more sensitive, caring and empathetic), which enhances the organization’s social performance (Boulouta, 2013) and leads towards the pursuit of a more sustainable strategy (Apesteguia et al., 2012). Additionally, Bear, Rahman & Post (2010) have stated that female directors result in more socially responsible behavior, as they bring a broader focus due to different backgrounds, can be more democratic when making decisions, provide a better oversight of activities, and attribute more attention and resources towards minorities than their male counterparts. Therefore, it can be expected that board gender diversity positively influences CSP and that CSP, subsequently, positively influences firm performance, as previously discussed. Grouped together, this leads to the following hypothesis:
H3: Corporate social performance positively mediates the relationship between board gender diversity and firm performance.
The previously hypothesized relationships are displayed in the conceptual model in figure 1, which is based on the abovementioned literature review.
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METHODOLOGY
The following section will describe the research methods used to test the relationships between board gender diversity, firm performance, CEO power, and CSP. The research can be labelled as being deductive, as it is formed on the foundations of theory, after which hypotheses are tested based on theory (Jonker & Pennink, 2010). With regards to the nature of the research question and deductive rationale pursued in this research, a quantitative research approach has been undertaken (Blumberg, Cooper & Schindler, 2011). The section will continue as follows: First, the sample and data collection method will be discussed. After that, the different types of variables used in this study are discussed. Then, the corresponding regression analyses will be introduced that are used to test the expected relationships between the variables. Moreover, the robustness check will be presented.
Sample and data collection
The sample to investigate the effect of board gender diversity on firm performance was constructed as a result of the combination of several databases. It is comprised of listed firms in the United Kingdom (UK) during 2014 and 2016. In order to collect data on firms’ financial performance the Bureau van Dijk’s Orbis database was considered, which possesses data on firm characteristics all over the world. The relevant data regarding CSP was obtained from the Thomson Reuters ASSET4 database, which consists of the relevant environmental, social and governance (ESG) metrics, often used by professional investors to build portfolios on firms. It has collected data and scored firms on ESG measures since 2002 by focusing, for example, on annual reports, CSR reports, stock exchange filings and news sources. The ASSET4 database was also accessed for the data on the board gender diversity and the CEO power levels measured as duality, as these variables were included under the pillar ‘governance’. Combining the datasets resulted in a sample of 345 firms.
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board governance mechanisms, with the Cadbury Report (1992) emphasizing the need for including non-executive directors (at least three members) and recommending that the positions of CEO and chairman of the board should be fulfilled by two different individuals, discouraging CEO duality (Ozkan, 2007). Due to the UK’s focus to increase the power of the board of directors, the effect these directors have on firm performance could be more distinguishable when researching the effect of diversity on performance. Nevertheless, a relevant subset among the largest UK companies (10-15%) still decided not to follow this dual strategic leadership approach (Aguilera et al., 2006), and have the same individual as CEO and chairman, indicating that the expected CEO power influence can be studied in the UK as well. Additionally, it is important to highlight that the UK did not implement a gender board quota that has to be adhered to, but did introduce a code of governance that stimulates board gender diversity (Terjesen, Aguilera & Lorenz, 2015). This UK Corporate Governance Code requires listed firms in the London Stock Exchange to include a description of their boardroom policy in their annual reports, including a section on the balance of diversity on the board, and how to facilitate this, as influenced by Davies (2013). As the sample includes publicly listed companies, the data will be more easily obtainable. This is also of essence as Tobin’s Q can only be calculated for listed firms as it is based on the market capitalization.
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accordingly, deleted if necessary. Missing values were attempted to be retrieved by using other sources. For example, BoardEx and annual reports were accessed for data on the board of directors and firm performance. Despite these efforts, not for all firms from the original sample could data be found on the variables included in the regression models. Consequently, the final sample of firms incorporated in the full OLS regression models consists of 271 firms.
Dependent variable
To measure the performance of a firm, the most commonly used indicator is a financial performance measure (Combs et al., 2005), which can be organized in two categories: accounting measures (e.g. return on assets (ROA), return on equity (ROE), and return on investment (ROI)) and market-based measures (e.g. Tobin’s Q). Within this research setting, most studies have either used Tobin’s Q to measure firm performance (e.g. Ahern & Dittmar, 2012; Rose, 2007) and/or ROA (e.g. He & Huang, 2011; Erhardt et al., 2003; Shrader et al., 1997).
The indicator used to measure the dependent variable firm performance in this study is based on the market-based profitability indicator, Tobin’s Q. Tobin’s Q is an often applied measure of performance focused on the future and a risk-adjusted capital-market ratio, which reflects present and future expectations regarding a firm’s profitability. It is calculated by dividing the market’s valuation of the assets of a firm by their current replacement costs (Chung & Pruitt, 1994), representing the firm’s market value to its book value. A value greater than 1 indicates that a firm’s stock is overvalued, as the costs to replace its assets are lower than the firm’s stock value. As the Tobin’s Q measure provides an overall view of the firm’s current and upcoming profitability, it is a popular and extensive approach to reflect firm performance.
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Independent variable
The independent variable of this study is board gender diversity. The amount of diversity is measured as the percentage of female board members present in the board of directors. The values are calculated by the number of female board members divided by the total number of members on the board. This ratio has been considered to be the most inclusive measure to capture the essence of gender diversity, as opposed to other measures such as the number of female executives or the overall presence of female top managers reflected in a dummy variable (e.g. Torchia et al., 2011; Haslam et al., 2010). To further illustrate this, Campbell and Mínguez-Vera’s (2008) study displayed insignificant results when using a dummy variable as the proxy for the presence of women on the board, and a positive link when using the women on board’s ratio. Consequently, this study will focus on the amount of diversity by taking into account the ratio of women on boards, following previous studies (e.g. Ahern and Dittmar, 2012; Smith et al., 2006; Shrader et al., 1997).
Moderator and mediator variables
The moderator CEO power in this study follows Combs et al. (2007) by using the proxy of measuring the presence of duality power. Even though power is a multifaceted construct (Finkelstein, 1992), this measure fits the current study as it relates to and affects the power of the board. CEO duality occurs when a CEO has multiple titles, more specifically, the title of CEO and board chair. It is measured by using a dummy variable representing whether the CEO is also the chair of the board (CEO duality = 1).
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to the multi-dimensional focus and the comprehensiveness of the research data on the companies’ environmental, social and governance scores, the ESG data can be used to effectively assess the overall CSP levels of companies.
In order to prevent the measure for CSP and the measure for the independent variable, board gender diversity, to overlap, the pillar containing the ‘governance’ scores will be eliminated, as board gender diversity is an indicator included in this pillar. Consequently, the ‘social’ and ‘environmental’ pillars will be used to construct a composite CSP score by assigning equal weight to both pillars’ scores, ranging from 0-100%, for every firm in this sample (Ioannou & Serafeim, 2012). The higher the percentage, the higher the CSP level that the firm displayed for that year. The social pillar focuses on a company’s ability to create loyalty and trust among its workers, customers, and society by using best management practices, which displays the firm’s reputation. The environmental pillar measures the company’s influence on living and non-living natural systems, such as air, water, land and complete ecosystems, to reflect the avoidance of environmental risks and capitalization of environmental opportunities. Appendix A includes a table with an overview of the ‘social’ and ‘environmental’ pillars and the categories included within these pillars.
Control variables
In order to accurately test for the hypotheses related to the board gender diversity and firm performance, it is necessary to control for several other factors that could influence this process. Firstly, larger firms display larger vulnerability towards agency problems and require higher monitoring (Lehn, Patro, & Zhao, 2009), and have more complex and international activities that demand more diversity (Oxelheim et al., 2013). Moreover, as the size of a firm is also related to market returns and to Tobin’s Q (Faleye, 2007), firm size was included as a control variable (e.g. Carter et al., 2003). In this study it is measured as the natural logarithm of total assets at the end of 2014, obtained from the Orbis database. The natural logarithm was taken in order to control for a non-normal distribution.
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example, Campbell and Minguez-Vera (2008), board size was added as a control variable, measured as the number of directors present on the boards, collected from the ASSET4 database categorized under the pillar ‘governance’ and complemented by the BoardEx database, from the end of the year 2014.
Furthermore, the industry and the leverage effects were controlled for by including an industry dummy and the leverage ratio. Industry effects were found to have an effect on board diversity (Randøy et al., 2006), which is why the different industries that are categorized by using the main industry groups as recognized by the Standard Industrial Classification (SIC) standards are taken into account. The different industry sectors were grouped into different categories (e.g. Erhardt et al., 2003), with a SIC code between 0 and 3900 it was labelled ‘agriculture, mining, construction or manufacturing’, with a SIC code between 4000 and 5900 it was labelled ‘transportation, communication, electric, gas, or trade’ and with a SIC code between 6000 and 9900 it was labelled ‘finance, insurance, services or public administration’, representing three industry categories. Leverage was added as it represents the financial risk a firm is faced with and can affect firm performance (e.g. Campbell & Minguez-Vera, 2008). It is measured in this study as the ratio of total debt to total equity. The higher the leverage, the closer the firm is to breaching its debt covenants, that is, violating its agreements with creditors, risking potential bankruptcy (Abdullah, 2014). Both the industry codes and the leverage ratio were present in the Orbis database, collected from 2014.
An overview containing which variables are used, which year the variables are collected from, and a description how the variables are measured is displayed in table 1.
Analysis
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Furthermore, due to the large sample size, potential non-normality issues will not affect the validity of the research. Additionally, heteroscedasticity was checked for by considering a residual plot analysis, which showed a specific cone pattern to be formed, indicating heteroscedasticity. Statistically, heteroscedasticity was checked by using the Breusch-Pagan/Cook-Wesiberg test, to determine whether the error term has a constant variance or not, with non-constant variance representing heteroscedasticity (Breusch & Pagan, 1978). Due to the p-value being 0.000, the null hypothesis has to be rejected, which indicates that heteroscedasticity is present in the dataset (Wooldridge, 2002). To mitigate the threat of heteroscedasticity, heteroscedasticity-consistent standard errors (Huber-White’s robust standard errors) will be used when estimating the OLS regressions (White, 1980; Wooldrigde, 2002). As a robustness check, ROA is used as an alternative measure for firm performance. The use of another proxy for firm performance minimizes the likelihood that outcomes are based on coincidence due to a specifically chosen measure (Joecks et al., 2012).
Table 1. Overview variables
Variable Year Measurement
Tobin’s Q 2016 Total market value of the firm divided by total value of assets
ROA (%) 2016 Total value of assets divided by net income before taxes Board Gender
Diversity (BGD) (%)
2014 Amount of female board members divided by total amount of board members (0-100%)
CSP (%) 2015 Average of the ‘social’ and ‘environmental’ pillars total scores (0-100%)
CEO power 2014 Dummy variable indicating whether the CEO is also the chair of the board; CEO duality (0 or 1)
Log Firm size 2014 Natural logarithm of total assets Board size 2014 Total number of directors on the board Leverage ratio 2014 Ratio of total debt divided by total equity
Industry dummy 1 2014 Dummy variable indicating whether the firm is categorized with a SIC code between 0 and 3900; Agriculture, mining, construction or manufacturing (0 or 1)
Industry dummy 2 2014 Dummy variable indicating whether the firm is categorized with a SIC code between 4000 and 5900; Transportation, communication, electric, gas, or trade (0 or 1)
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RESULTS
This section will display the empirical results of the performed analyses to test the hypotheses. First, the descriptive statistics and correlation matrix will be displayed. After that, the results of the OLS regression between the relationship of board gender diversity and firm performance are shown. Moreover, the results of the analyses testing the moderator and mediator effects are presented. Lastly, the results of the robustness check will be discussed.
Descriptive statistics and correlations
Table 2 displays the descriptive statistics of the sample used in this study. The mean of 1,159 of the firm performance measure used as a dependent variable in this study, Tobin’s Q, would suggest that the market value of the firms used in this sample during 2016 is higher than the book value. Nevertheless, the difference between the maximum (8,37) and the minimum (0,03) is of importance. A positive mean is in line with the mean of the accounting-based ROA measure (5,872), which also shows that on average the firms in the sample have been financially successful. The independent variable board gender diversity displays a relatively high mean of 18,267%, which corresponds with more recent board diversity research streams (e.g. Dezső, & Ross, 2012 (23,6%)) and is, as expected, remarkably higher than the average of earlier studies’ means (e.g. Carter et al., 2003 (9,6%)). This increase could be explained by the growing importance of gender equality and the rising number of imposed quotas (Ahern & Dittmar, 2012). Moreover, it is important to highlight that the mean of the presence of CEO duality is 0,105, indicating that 10,5% of the CEOs in the sample also function as chairman of the board. Additionally, the different industry dummies are relatively evenly distributed, displaying no issues related to the groupings of the industry SIC codes.
Table 2. Descriptive statistics
Variable N Mean Standard Deviation Min. Max.
Tobin’s Q 284 1,159 1,152 0,03 8,37
ROA (%) 294 5,872 10,427 -55,93 42,91
BGD (%) 313 18,267 10,126 0 44,44
CSP 316 56,157 27,463 10,03 96,97
CEO power 314 0,105 0,307 0 1
Log Firm size 322 14,689 1,81903 10,99 21,25
Board size 314 9,060 2,468 3 19
Leverage 324 86,693 132,691 0 1041,84
Industry dummy 1 325 0,3754 0,485 0 1
Industry dummy 2 325 0,2123 0,410 0 1
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The correlation between the variables has been investigated as well, as displayed in table 3. The values of correlation can range from -1 to 1, which would indicate full correlation, while values closer to zero would indicate less correlation between the variables. The results of the correlation matrix display, as previously argued by former studies, a positive association between firm size and board gender diversity (0,286 at the 0.01 significance level) (e.g. Adams & Ferreira, 2004). A positive association can also be found between board gender diversity and Tobin’s Q (0.006), the independent and dependent variable of this study, as previously expected. However, this direct correlation between the variables is insignificant. Nevertheless, the OLS regression analyses will include the complete models including the control variables, the moderator and the mediator, investigating the full effect upon which the conclusions can be drawn for the relationship between board gender diversity and firm performance.
23
Table 3. Correlation matrix
Variable 1 2 3 4 5 6 7 8 9 1 Tobin’s Q 1,000 N=284 2 ROA (%) ,486*** (0.000) N=283 1,000 N=294 3 BGD (%) ,006 (0.924) N=273 ,075 (0.208) N=283 1,000 N=313 4 CSP -,098 (0.106) N=276 ,009 (0.875) N=286 ,203*** (0.000) N=313 1,000 N=316 5 CEO power ,094 (0.122) N=274 -,010 (0.871) N=284 -,141** (0.012) N=313 -,088 (0.118) N=314 1,000 N=314 6 Log Firm size -,423*** (0.000) N=282 -,198*** (0.001) N=292 ,286*** (0.000) N=311 ,389*** (0.000) N=314 -,114** (0.043) N=312 1,000 N=322 7 Board size -,240*** (0.000) N=274 -,101* (0.088) N=284 ,234*** (0.000) N=313 ,362*** (0.000) N=314 -,152*** (0.007) N=314 ,637*** (0.000) N=312 1,000 N=314 8 Leverage -,211*** (0.000) N=283 -,067 (0.254) N=293 ,091 (0.110) N=312 ,032 (0.571) N=315 ,016 (0.778) N=313 ,262*** (0.000) N=321 ,133** (0.018) N=313 1,000 N=324 9 Industry dummy ,062 (0.299) N=284 ,076 (0.196) N=294 ,045 (0.451) N=288 -,229*** (0.000) N=291 -,091 (0.122) N=289 ,050 (0.387) N=297 ,085 (0.152) N=289 ,051 (0.382) N=298 1,000 N=299 Note: p-values for each of the correlation coefficients in parentheses
*** p < 0.01, ** p <0.05, * p < 0.10
OLS Regressions
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effects related to board gender diversity and firm performance. Therefore, it can be argued that hypothesis 2 is supported, finding a negative moderating effect for CEO power, in line with previous studies’ expectations (e.g. Miller & Triana, 2009). Notably the separate effect of CEO power itself displays a small positive effect, but is highly insignificant (p=0.584).
Table 4. Results of regression analyses including the moderating effects
Dependent variable: Tobin’s Q Model 1 Model 2 Model 3 Board Gender Diversity (BGD) (%) 0,123*
(0,007)
0,131** (0,007) Log Firm size -0,428***
(0,049) -0,450*** (0,049) -0,453*** (0,049) Board size 0,059 (0,034) 0,044 (0,034) 0,058 (0,035) Leverage -0,122*** (0,000) -0,125*** (0,000) -0,129*** (0,000) Industry dummy category 2 0,083
(0,155)
0,074 (0,156)
0,077 (0,157) Industry dummy category 3
Reference category: category 1
0,102 (0,150) 0,096 (0,147) 0,103 (0,148) CEO power 0,033 (0,213) BGD x CEO power -0,107* (0,021) N 272 271 271 Model F statistics 11,95*** 10,16*** 7,89*** Model R^2 0,197 0,211 0,226 Adjusted R^2 0,182 0,193 0,203
Note: Presents the standardized regression coefficients. Robust standard errors in parentheses. *** p < 0.01, ** p <0.05, * p < 0.10
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Table 5. Results of regression analyses including the mediation effects Dependent variable: Model 1
Tobin’s Q Model 2 CSP Model 3 Tobin’s Q Model 4 Tobin’s Q Board Gender Diversity (BGD) (%) 0,123*
(0,007) 0,100* (0,156) 0,113* (0,007) Log Firm size -0,450***
(0,049) 0,272*** (1,087) -0,461*** (0,051) -0,477*** (0,051) Board size 0,044 (0,034) 0,205*** (0,715) 0,033 (0,033) 0,023 (0,034) Leverage -0,125*** (0,000) -0,046 (0,013) -0,117*** (0,000) -0,120*** (0,000) Industry dummy category 2 0,074
(0,156) -0,209*** (4,082) 0,106* (0,163) 0,095 (0,165) Industry dummy category 3
Reference category: category 1
0,096 (0,147) -0,273*** (3,222) 0,133** (0,151) 0,123* (0,147) CSP 0,116** (0,002) 0,101* (0,002) N 271 271 272 271 Model F statistics 10,16*** 26,85*** 10,13*** 8,83*** Model R^2 0,211 0,277 0,207 0,219 Adjusted R^2 0,193 0,260 0,189 0,198
Note: Presents the standardized regression coefficients. Robust standard errors in parentheses. *** p < 0.01, ** p <0.05, * p < 0.10
26
Regarding the control variables, in all the models, the coefficient of firm size (natural logarithm of total assets) on firm performance is significant and negative. This result is contrary to the expectations, as it is often argued that larger firms display higher performance (e.g. Lee, 2009). However, Campbell and Minguez-Vera (2008) have found similar results regarding the effect of firm size on Tobin’s Q. Additionally, a finding to highlight is the significant and positive effect of board size on CSP (in Model 2 of table 5). Apparently, these findings are in line with the resource dependency theory and human capital theory, which state that larger boards have access to more valuable networks and resources and possess a broader focal point, enabling and stimulating the firms with larger boards to increase their CSP levels. In the other models, board size only presents a small, positive, and insignificant coefficient, which is related to the larger effect firm size displays, as both are correlated (not representing an issue as the VIFs were far below the threshold of 10). Moreover, firm size had a positive and significant effect on CSP (Model 2 of Table 5), which can indicate that larger firms have more resources available and face lower average costs when engaging in socially responsible behavior (McWilliams & Siegel, 2001). Another noteworthy result is the negative and significant effect of leverage on Tobin’s Q, which can be explained by the fact that having excessive amounts of debt could cause higher agency costs. Consequently, higher costs due to debt can impede the process of increasing the firm’s profitability levels (Campello, 2006).
Robustness check
27
firm performance is lower and less significant in the final model (0,114 (p=0.08)) (Model 1 and Model 4 in table 7), proving mediation.
Additionally, a noteworthy difference lies in the values for the squared and the adjusted R-squared, which are significantly lower in the models using ROA. This coefficient of determination explains how much of the variance in the dependent variable (Tobin’s Q or ROA) is explained by the model. For the test of the first hypothesis, for example, the adjusted R-squared values are 0,193 for Tobin’s Q and 0,045 for ROA, respectively. This means that 19,3% of the variance in Tobin’s Q is explained by the model (Model 2 in table 4) and only 4,5% of the variance in ROA (Model 2 in table 6). However, Adams and Ferreira (2009), who researched the effect of the presence of female board members on Tobin’s Q and ROA, came across similar outcomes and have not reported this to be an issue.
DISCUSSION
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Furthermore, this study has furthered the current understanding of the board gender diversity and firm performance research streams by including important innovative contextual factors and underlying forces conditioning the relationship, in the form of a moderator and mediator. For example, Adams and Ferreira (2009) have found a negative link in their diversity and firm performance research based on US firms, but have concluded that the relationship is extremely complex and more variables would be necessary to sufficiently display the association between the two variables. To extend the present knowledge and also consider indirect relationships related to board diversity and firm performance, Miller and Triana (2009) have considered the mediation effects of firm reputation and innovation. They also argued that previous inconsistency in the findings can be attributed to missing explanatory variables related to the board gender diversity-firm performance link. Consequently, this study makes a theoretical contribution to the existing literature in this field as it not only finds a significant, positive link among UK listed firms, but also incorporates new dimensions for this phenomenon in the form of the moderator CEO power and mediator CSP. To fill the gap in the literature, this study accounts for intermediary mechanisms potentially explaining why board diversity might be related to firm financial performance.
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Additionally, as it was argued that more factors might be of importance within the gender diversity and firm performance framework, the influence of CSP was tested, because it was expected to be related to both the independent and the dependent variable. Extending other articles which found that more female board members generated a strategy with a larger focus on sustainability (Apesteguia et al., 2012) and which found a positive link between diversity and CSP (e.g. Bear, Rahman & Post, 2010; Orlitzky et al., 2003), this study includes the influence of CSP on firm performance as well, representing a mediation effect. For this, support was found after performing the different regression steps, which indicated the importance of CSP for pursuing higher firm performance, generated by higher board gender diversity. Therefore, it can be argued that firms must adjust their attention span towards increasing their CSP levels, mainly accomplished by assigning more female board members. Subsequently, as shown by this study, firm performance levels will increase. Moreover, the firm’s reputation will enhance among stakeholders, creating more access to resources, and the firm will become more attractive for employees (Neville, Bell & Mengüç, 2005; Albinger & Freeman, 2000). Thus, women on boards play a remarkable role in increasing a firm’s moral legitimacy among stakeholders.
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Besides the suggestion for governments to introduce more severe regulations, companies themselves can foster the advantageous effects of diversity in a more effective way as well. The results have suggested that appointing women to boards is most beneficial when the conditions surrounding the board are favorable, meaning that the female directors can freely speak up and contribute to the decision-making, realizing their full potential, and that conflicts are brought to a minimum, as also found by Nielsen and Huse (2010) and Byron and Post (2016). Moreover, the findings show that different levels of diversity lead to different outcomes, which can indicate that different directors can have different impacts on the tasks performed and decisions made by the board. Therefore, it is important to consider beforehand which qualities and characteristics are needed to improve the board’s effectiveness when appointing members. As explained by gender role theory and human capital theory, male and female directors’ values and behavior are according to stereotypes and the role they are expected to fulfill within society, and have diverse and valuable information and skills (Withers, Hillman & Cannella, 2012). For example, women are perceived to be more risk-averse, inclusive and sustainability-focused (e.g. Glass et al., 2016). Consequently, if firms are looking for specific types of knowledge, experience or values that women directors may bring, they should diversify the board in such a way that it can capture these features and stimulate the effects they desire to achieve.
Limitations and future research
31
on boards have an effect on some firm performance indicators, but not or differently on others, remains valid, as illustrated by the robustness check performed (e.g. hypothesis 2 was not significant with ROA as the dependent variable). Since different indicators grasp different elements of performance (Combs et al., 2005), perhaps varied theoretical mechanisms can explain the inconsistent results. Therefore, other dimensions of performance that are rarely used within this field can be considered as well, for example, measures of growth (e.g. in sales or shares) and operational performance (e.g. customer satisfaction or new product development time), as theory has predicted a potential link with board diversity. By doing this, the understanding of the different effects that board gender diversity has on firm performance measures will be furthered, displaying the boundaries of these relationships.
32
shift in opposite direction, more observations from the upper bounds of board diversity would be necessary, providing a full theoretical range of diversity (0-100%). However, currently, not enough boards with a majority of female members exist in the world to be able to create an evenly distributed sample. To illustrate this, this study’s maximum observation for diversity was 44,4%, indicating that there was no firm in which female board members formed the majority. Potentially, in the future, board gender equality may be realized, which could form an innovative area for diversity-performance non-linear relationship studies.
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CONCLUSION
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