The influence of gender diversity on innovation : an analysis on the corporate governance level

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Amsterdam Business School

The influence of gender diversity on innovation

An analysis on the corporate governance level

Name: Eva Versloot Student number: 10184988

Thesis supervisor: Professor dr. Vincent O’Connell Date: 19 June 2016

Word count: 14.579

MSc Accountancy & Control, specialization Control

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Statement of Originality

This document is written by student Eva Versloot who declares to take full responsibility for the contents of this document.

I declare that the text and the work presented in this document is original and that no sources other than those mentioned in the text and its references have been used in creating it.

The Faculty of Economics and Business is responsible solely for the supervision of completion of the work, not for the contents.

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Abstract

This thesis explores how gender diversity on the board of directors influences innovation in firms. The focus of the paper is analyzing if a relationship exists between the percentage of women on a board of directors and the level of R&D expenditures of a firm. The data is gathered from 1.015 US firms over a sample period from 2007 up till 2014. The method to test the data is a panel regression. Due to the insignificant results, the hypothesis that gender diversity positively influences firm innovation cannot be accepted or rejected. Furthermore, the effect of two moderators is analyzed. The first is firm size and the second is board composition. The moderating effects on the relationship between gender diversity and innovation are not significant as well. The findings suggest that further research has to be done in order to draw conclusions on this research topic. These findings are consistent with prior research, were contradictory results or no results have been found when investigating board diversity. This study contributes to the literature by attempting to fill a gap in the literature. No research has been done before into gender diversity on the board and its influence on innovation, with the addition of two moderators.

Keywords: Board diversity, Women in boards, Corporate governance, Innovation, R&D expenditures

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1 Introduction

1.1 Background

Nowadays, boards should be diverse. Gender, racial and cultural composition of the board of directors is an important issue in the modern corporation (Carter et al., 2003). The word diversity often provokes intense reactions and scrutiny (Milliken and Martins, 1996; Bear et al., 2010). This term means ‘a range of different things or people’ (Cambridge advanced Learner’s dictionary, 2013). According to Carter et al. (2003), the definition of board diversity is the percentage of women, Asians, Hispanics and African Americans on the board of directors. The focus of this paper will be on gender diversity of the board of directors, defined in this study as the percentage of women on the board of directors. Historically, this percentage has always been low. In 2007 only 14,8% of all the directors in fortune 500 companies were women directors (Adams and Ferreira, 2009). In Canada, Australia, Japan and Europe these percentages were estimated to be 10,6%, 8,7%, 0,4% and 8,0% respectively. According to Bilimoria (1995), there are two reasons for the dearth of women on boards of directors. The first reason is that women lack the experience and do not have the background for leadership. If women would have the same qualifications, men and women would be equally represented on boards. The second reason is that, even if women have the same qualifications, they are held back because of their gender. They get less support, face higher expectations and are rewarded less for performance and effort (Bilimoria, 1995; Milliken and Martins, 1996). Nevertheless boards around the world are under more pressure to choose more female directors, so these low percentages of female board members are likely to increase in the future (Adams and Ferreira, 2009).

Due to four reasons, board diversity is an emerging aspect in the corporate governance regulation (Mcphail, 2010). The first reason concerns failures in corporate governance systems, which could have led to corporate scandals. There were a few recent scandals which increased the scrutiny of the composition of the board of directors. For example Enron, whose board of directors consisted of 17 board members. Of these 17 members, only one member was a woman. Thus this raises the question if Enron’s oversight by the board of directors might have been better if its board comprised of more women, in other words was more diverse in terms of gender (Erhardt et al., 2003)? Secondly, advocacy groups and institutional investors put pressure on entities to have a more diverse board (Carter et al., 2003; Mcphail, 2010). Thirdly, more and more regulation for equality is developed, for example in the form of quotas. The final reason for more diversity on the board of directors is the possible positive impact it has on firm

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performance (Carter et al., 2003; Erhardt et al., 2003; Campbell and Mínguez-Vera, 2008; Mcphail, 2010). However, there has also been research with results that showed a negative relationship between diversity and firm performance (Adams and Ferreira, 2009; Carter et al., 2010).

In the corporate governance literature, a central topic is how a board of directors can influence a firm’s outcomes. There are two types of supervision structures on the corporate management (Jungmann, 2006). The one-tier board system consists of executives and non-executives, which is adopted in the United States, Canada and the United Kingdom. Besides the one-tier system there is the two-tier system, which is adopted in most of Europe. The two-tier system consists of a separate management and supervisory board. Both types of boards serve the same two key functions: the monitoring of the management and the provision of resources (Hillman and Dalziel, 2003). The first function, the monitoring role, means the responsibility of the board to supervise the management on behalf of the shareholders. The theory behind this role comes from agency theory, which describes the conflicts of interest that arise through the separation of the decision and the risk-bearing functions in corporations (Fama and Jensen, 1985). The second important function comes from resource dependence theory. This function refers to the role of the board to bring resources into the organization (Hillman and Dalziel, 2003).

1.2 Research questions

Most of the research on board diversity investigates the direct relationship between diversity on the board and firm performance. Up to now, the results are contradictory. Some studies find a positive relationship (Carter et al., 2003; Erhardt et al., 2003; Campbell and Mínguez-Vera, 2008;

McPhail, 2010), some a negative (Adams and Ferreira, 2009; Carter et al., 2010). So research has shown diversity has effects on a firm’s performance. The ambiguous results might be due to different countries, different time-periods and different measures of firm performance (Campbell and Mínguez-Vera, 2008). In this thesis the focus is not on firm performance, but on the relationship between gender diversity of a board and innovation in a firm. The influence on innovation is chosen because the research of board diversity on innovation is still underdeveloped. Besides that, it is interesting to do research into the effect on innovation, because of the possible positive effect on future firm performance. Innovation is defined as strategies that provide new opportunities for the firm to create new or enhanced products or services (Miller and Del Carmen Triana, 2009). In this analysis innovation is measured by the firm’s expenditures on research and development (R&D). R&D expenditures lead to higher

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levels of innovation and that could lead to a higher firm performance (Klomp and Van Leeuwen, 2001; Janz et al., 2003; Van Leeuwen and Klomp, 2006). There are many different types of diversity. The most common distinction is made between visible and less visible types of diversity. This thesis is about visible diversity, that is diversity such as gender, race and age. We conceive of gender diversity as the number of female directors on the board. Less visible diversity is with regards to underlying characteristics such as education, tenure or personality (Milliken and Martins, 1996). Studies have suggested that there is a positive relationship between technological diversity in a firm and innovation (Almeida and Kogut, 1997; Suzuki and Kodama, 2004; Garcia-Vega, 2006; Sampson, 2007). Other research found a relation between gender diversity and innovation, but at the level of the employees or the top management. However, in this research an attempt is done to analyze if the same relation goes for gender diversity and innovation at the corporate governance level. The following research question is asked in order to conduct the research.

Question 1: Does gender diversity of the board of directors influence the level of innovation in a firm? Besides the investigation of the direct relationship between these variables, the influence of two moderators is also investigated. A moderator can increase or decrease the strength of a relationship, or change the direction of a relationship. The first moderator is firm size and the second moderator is board composition. Board composition is defined as the percentage of outside members on the board of directors. The two moderators lead to the following second and third research questions.

Question 2: How does firm size influence the relationship between board gender diversity and innovation? Question 3: How does the percentage of outside members of the board influence the relationship between board

gender diversity and innovation?

1.3 Method and results

The sample for this study consists of 1.015 US firms. The data is gathered from Wharton Research Data Services from the period of 2007 till 2014. To test the data and the hypotheses a panel regression method is used. Four control variables are added to the analysis. These are firm age, the book-to-market ratio, firm liquidity and the average R&D industry intensity. The results do not allow to accept or reject the hypotheses we make in the next chapter. The results are insignificant and further research needs to be done in order to draw conclusions.

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1.4 Contribution

This research adds to existing literature, because research on the relation between gender diversity and innovation is still scarce. It will extend the literature in two ways. First, because existing research is done at the employee level or the top management, while this study will focus on the level of the board of directors. Talke et al. (2010), say that more research has to be done into diversity in the corporate governance structure and the effect on innovation. They proved that diversity in the top management team enhances firm performance by a bigger focus on innovative strategies. Second, this research does not only study the direct effect between diversity and innovation, but also the influence of moderators on this effect. The two moderators are unique and have not been studied before in this context. Milliken and Martins (1996) and Miller and Triana (2009) say that extra research has to be done with mediators or moderators to fill the gap in the literature. Hence, this paper is an attempt to fill the gap in the existing literature.

Besides the empirical contribution, this research is also interesting from a social point of view. The percentages of women on board of directors are increasing. In the data set of this research, the percentage in 2007 was 11% and in 2014 14.7%. This percentage remains far below 50%, which means that boards of directors are still dominated by men. But lots of countries are thinking about introducing a quota for women board directors or already have introduced one. As of January 2008 Norway mandated a 40% women director’s quota for public limited liability companies (Nygaard, 2011). They were the first and then Belgium, Canada, Finland, France, Iceland, Italy, the Netherlands, Spain and Sweden followed by implementing or considering to implement a similar quota (Nygaard, 2011; The Economist, 2014). This research will contribute in the debate if more regulation on the number of women directors is needed.

1.5 Structure

The remainder of this paper will continue as follows. The next section consists of the theoretical framework, which starts with describing the governance structure and the main functions of the board of directors. The chapter then gives insight into why gender diversity might be linked to innovation. It explains gender differences, the behavioral theory and gives a review of prior research towards the development of the three hypotheses. The third chapter contains the methodology. This chapter introduces the method, sample, data collection and the operationalization of the variables. Chapter four provides the results of the empirical analysis, which will be comprehensively reviewed in section five. Finally, in chapter five the limitations and suggestions for further research are mentioned. This chapter concludes the thesis.

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2 Literature review and hypothesis development

In the model below (figure one) the conceptual model of this research is presented. The direct relationship between gender diversity of the board of directors and innovation is researched. Besides that, also the influence of the two moderators, board composition and firm size, is researched. These moderators are chosen to see if they influence the strength or change the direction of the relationship between gender diversity on the board and innovation in the firm. In this chapter the literature and theories will provide the framework for this thesis. The chapter will continue as follows. First the functions of the board of directors are discussed, with the two main underlying theories; agency theory and resource dependence theory. Next, empirical research and theories are mentioned that will predict the relation between gender diversity of the board and innovation. This leads to the development of the first hypothesis. Finally, the theory on the moderators is discussed and this leads to the formulation of the second and third hypotheses.

Figure 1: Conceptual model

2.1 Governance and the board of directors

In order to analyze the relationship between board gender diversity and innovation in a firm, it is important to know what the board of directors is and what function it fulfils. Corporate governance refers to all the internal and external controls that should minimize the conflicts that arise due to the separation of ownership and control (Baysinger and Hoskisson, 1990). In the corporate governance there are two major structures for regulation of the board of directors. These are the one-tier and two-tier board systems. Both these structures are designed to support the independence of the board of directors (Maassen and Van Den Bosch, 1999). The one-tier board is a system with only one board, from which the members can be executives or non-executives. This one-tier model is adopted by the United States, Canada, the United Kingdom and some other European countries. All the board members are selected by the shareholders, and they also have the ability to remove them (Jungmann, 2006). In the two-tier board system,

Gender diversity of the board of directors Of Board composition Innovation in a firm Firm size

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the board consists of a management board and a supervisory board. This structure clearly separates the executive from the non-executive directors (Maassen and Van Den Bosch, 1999). The management board consists of executives and the supervisory board consists of non-executives who monitor and appoint the members of the management board (Maassen and Van Den Bosch, 1999). Employees or members of the management cannot act as a chairman in the supervisory board, so this enhances the independence. In this thesis we have a sample of US firms, where the one-tier board system applies.

In the next section, agency theory and resource dependence theory are discussed. These two theories represent the key functions of the board, the monitoring function and the function to provide resources (Hillman and Dalziel, 2003). Besides these two functions, the board can ratify and monitor major decisions and hire, fire and compensate the top level management of the firm (Fama and Jensen, 1983; Baysinger and Hoskisson, 1990).

2.1.1 Agency theory

Boards have a monitoring function. This refers to their responsibility to monitor the management on behalf of the stakeholders (Hillman and Dalziel, 2003; Bear et al., 2010). The theory behind this monitoring role is derived from the agency theory. Boards play a role in mitigating agency problems that exist due to the separation of ownership and control. According to agency theory, there are conflicts of interest between the ones who bare the risk and the ones who do the decision-making in a firm (Fama and Jensen, 1985). The agents are the managers who make the decisions and the principals are the shareholders who bare the risk (Jensen and Meckling, 1976). In agency relationships two problems can occur (Eisenhardt, 1989). The first is the agency problem that arises when the goals of the principal and the agent conflict and when it is difficult for the principal to monitor what the agent is doing. The second agency problem is the problem of risk sharing when the principal and agent do not have the same attitudes towards risk. They can prefer different actions because of the different risk preferences they have (Eisenhardt, 1989). The board of directors can mitigate the risks that arise due to the conflict of interests. They monitor agents to see if their actions are in the best interest of the principals (Jensen and Meckling, 1976). The board’s role is also referred to as the role of guardian of shareholders’ welfare (Hill and Snell, 1988). This monitoring role is important, because it reduces the agency costs that arise due to agency problems. Agency costs are the negative effects of the agency problems. An example would be the costs that arise when managers pursue their own interests, instead of the interests of the shareholders which is profit maximization (Hillman and Dalziel, 2003). Other agency costs are costs of monitoring and sometimes even setting up

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contracts in order to minimize the agency problems (Fama and Jensen, 1983). Besides the direct monitoring role the board plays, they also act as an information system for the shareholders and the management. The shareholders can get more information on the behavior of the agents and this will decrease the agency problems (Fama and Jensen, 1983). And on the other hand the management knows that shareholders are getting more information when there is a good board in place. Therefore the management is more likely to engage in behavior that is consistent with the shareholder’s interests (Eisenhardt, 1989). If the shareholders are interested in being innovative, then agency theory links the board of directors to innovation in the firm.

2.1.2 Resource dependence theory

The second important function of the board of directors is the provision of resources to the firm. The theoretical underpinning is the resource dependence theory, one of the most influential organizational theories (Hillman et al., 2009). The theory comes from a book on resource dependency from Pfeffer and Salancik (1978). When directors connect the firm to external factors, they serve the resource dependence role (Hillman et al., 2000). In the book they say the following about the board’s function to provide resources: “When an organization appoints an individual to a board, it expects the individual to support the organization, will concern himself with its problems, will favorably present it to others, and will try to aid it” (Pfeffer and Salancik, 1978, p.163). The provision of resources can be a variety of things, for example providing advice, expertise, counseling, experience, giving access to capital or provide a network to the firm. Hillman and Dalziel (2003) summarize the resources the board members have as board capital. Firms need to deal with the uncertainty they face in their environment in order to increase their likelihood of survival (Hillman et al., 2000). When directors fulfil the role of resource dependence, they link the organization with the external environment and reduce the uncertainty and help the firm manage challenges (Hillman et al., 2000; Bear et al., 2010). According to Hillman et al (2002), an important part of resource dependence theory is the legitimacy that is gained from the environmental linkages. Legitimacy is one reason for a firm to bring in more women on the board of directors, but besides legitimacy board members can bring in many more resources. The extension of the theory by Hillman et al. (2000) states that directors with different characters and background will provide different types of resources. This suggests that a more diverse board will provide more various and valuable resources, due to the unique information held by diverse directors (Hillman et al., 2000). Therefore resource dependence theory provides arguments in favor of more diversity on boards.

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2.2 Board gender diversity and innovation

Many papers hold arguments in favor of more gender diversity on a board of directors. A board with more diverse members makes sure that the directors acquire more diverse competencies, ideas and resources (Carter et al., 2003). Empirically, there are mixed findings in the literature about the positive influence of gender diversity in the board of directors on firm outcomes. Some papers come with positive results (Bantel and Jackson, 1989; Milliken and Martins, 1996; Carter et al., 2003; Mcphail, 2010) and others with negative (Adams and Ferreira 2009; Carter et al., 2010). The results of Baysinger et al. (1991) give evidence that the members in the company’s governance structure can influence strategic variables, like R&D expenditures. This is an importing finding for this research into the composition of the board and the level of innovation in a firm. This paragraph will continue as follows. The first section discusses some general differences between men and women in leadership positions. The second section will explain what women can add to the board of directors that might be of value for company innovation. Next, the behavioral theory is explained. Finally, some prior research is mentioned which will lead to the development of the first hypothesis.

2.2.1 Gender differences in general

Not all studies are positive about women’s characteristics, when it comes to fulfilling leading roles in a firm. They state that women are risk averse, less competitive and less confident than men are. Croson and Gneezy (2009) made a review of all the literature on the differences between men and women with respect to economic situations. They found differences in risk preferences, social preferences and competitive preferences. With regards to risk preferences, studies find that women are more risk averse than men. This holds for experiments in laboratory settings but also for field research on investment decisions (Croson and Gneezy, 2009). The reason for women being more risk averse is that women experience more emotions than men. And when facing risky choices, people tend to make emotional choices rather than cognitive choices. Women hold more fear when they expect negative outcomes and are therefore more likely to make less risky choices. Another reason for the difference in risk preference is that men are more overconfident about the probability of their success. This holds especially when it comes to finance decisions (Barber and Odean, 2001). Men think that they are competent to make the best decision so they are willing to accept the risk associated with their choice. Another interesting analysis on this topic is conducted by Atkinson et al. (2003). They researched if the difference in risk preference between men and women also hold for the managers of funds. The findings of their study suggest that the funds managed by either women or men do not differ

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significantly with regards to risk and performance. These results suggest that the gender difference might not hold for women who possess sufficient knowledge and experience (Atkinson et al., 2003). The findings of the research of Adams and Funk (2011) revealed even that female members of the board of directors are less risk averse than the male members of the board of directors.

Another difference between men and women is that women do not like to participate in a competitive environment. Men, on the other hand, like competition and their performance increases under competitive pressure (Croson and Gneezy, 2009; Hogarth et al., 2011). For this difference there is both a nature and a nurture reason. The nature reason lies in the different genetics men and women have. The dislike of competition has to do with women’s hormones (Croson and Gneezy, 2009). The nurture reason is about women being treated differently than men and can be penalized for being assertive in competitive situations. Hence, women dislike working in a competitive environment and their performance suffers under competitive pressure (Hogarth et al., 2011).

2.2.2 What can women contribute to the board of directors

Women have different characters and societal backgrounds than men. Their background often lies outside the business area (Miller and Triana, 2009). These differences can contribute to the board of directors. To begin with many researchers say that women bring in new ideas and different and fresh perspectives (Bilimoria, 1995; Milliken and Martins, 1996; Miller and Triana, 2009). According to Bilimoria (1995), women also have unique leadership qualities, such as collaboration and flexibility. This can be caused by their nature but also by their level of education. Women, who pursue a career in a board of directors, are more educated than men (Hillman et al., 2002; Miller and Triana, 2009). It is important though that women feel comfortable in their position. As research suggests that people who feel different from others in their work environment, tend to have lower job satisfaction, higher absence levels and have less intention to stay (Milliken and Martins, 1996). Eagly and Johannesen‐Schmidt (2001) also did research on differences in leadership styles between men and women. They state that it is clear that women face more difficulties in obtaining a leadership position. Especially when the work environment of the leadership position is male-dominated, because people are more willing to accept leaders who are similar to them (Bilimoria, 1995; Eagly and Johannesen‐Schmidt, 2001). Once women attain a leadership role, there can also be differences in the style of leadership. Men tend to have more autocratic leadership styles and women more democratic styles (Eagly and Johannesen‐Schmidt, 2001). Autocratic leadership is a dominant way of leading where you do

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not let subordinates participate in the decision-making process. Women behave more democratically in their leading role and do allow subordinates to participate in the decision-making process. Besides the difference in autocratic and democratic leadership styles, women also have more active transformational and transactional leadership characteristics (Eagly and Johannesen‐Schmidt, 2001). A transformational style is when you set high standards for behavior and give yourself a role-model position. A transactional style is monitoring and rewarding behavior strictly. Men on the other hand are more passive and take less responsibility. These qualities of being an active leader are also related to being an innovative leader (Eagly and Johannesen‐Schmidt, 2001).

2.2.3 Diversity and innovation; the behavioral theory

Besides the characteristics and background women bring into the board, their presence brings also diversity to the board of directors. This gender diversity might have an effect on the board of directors and also on the level of innovation. The relationship between gender diversity of the board and the level of innovation can be explained by the behavioral theory of the firm (Cyert and March, 1963). The decision-making in firms is done by individuals or groups. According to the behavioral theory, the decisions these individuals or groups make, are biased by the information and priorities they have (Miller and Triana, 2009). As mentioned above, the board of directors influence the decision-making of a firm as well (Baysinger et al., 1991). So according to the behavioral theory the decisions that are made in a firm are biased by the characteristics of the members of the board of directors. When the members of the board of directors are more diverse, there is a more heterogeneous group. Heterogeneous groups are more likely to have a broader range of task-relevant knowledge, skills and perspectives that are specific compared to those of individuals in homogeneous groups (Cyert and March, 1963). This approach suggests that group heterogeneity may lead to more creativity and innovation in the work environment and the decision-making (Bilimoria, 1995; Carter et al., 2010; Roberge and Van Dick, 2010). So the characteristics of the group influence the making in the firm and the decision-making can influence the level of innovation. Miller and Triana (2009) confirm this behavioral theory in their paper. Their analysis provides evidence that heterogeneous groups have different ideas and more information that help in identifying new research opportunities. Not only do heterogeneous groups identify new research opportunities, they also have a positive influence on existing innovations (Miller and Triana, 2009). Chen et al. (2005) support this theory by proving that heterogeneous groups will have more conflict of opinions and that will lead to more innovation. This positive effect of heterogeneous groups can take up to a few months to manifest itself. In the research of Watson et al. (1993) the diverse group needed up to 17 weeks

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to get used to each other and only then they scored higher on all the performance measures than homogenous groups.

2.2.4 Empirical research

Not much research has been conducted into the effects of gender diversity on innovation in a firm, especially not at the corporate governance level. Though there is some prior research that could provide evidence for this case. The research of Østergaard et al. (2011) found a positive relationship between diversity in gender of employees and the innovative performance in firms. Their results indicate that gender diversity is one of the diversity variables that has the strongest impact on the likelihood of innovation in a firm. So even though their analysis was done at the employee level, this might be evidence that gender diversity at the board level can also influence innovation. Very low levels of diversity and very high levels of diversity do not have a significantly different effect on innovation, but moderate levels of diversity do (Østergaard et al., 2011). This finding is in line with the research of Milliken and Martins (1996). Their findings implicate that gender diversity leads to cognitive consequences such as innovation. However their findings apply only when a certain level of diversity is reached. They name the following reason for this diversity threshold. Members that belong to a minority gender group experience discomfort, have less commitment and have a high likelihood of being absent (Milliken and Martins, 1996). However, these negative effects decrease with the size of the minority group and the time they stay together (Milliken and Martins, 1996; Watson et al., 1993). Hence, from a certain percentage of women, the influence on innovation should be positive. Talke et al. (2010) also conducted research into gender diversity and its effect on innovation, but the analysis was done at the top management team level. They concluded in the paper that diversity in the top management team leads to an innovative strategy of the firm (Talke et al., 2010). These results imply that diversity in the governance structure could also positively influence innovation. This is due to the influence the board of directors have on the top management and the decisions they make (Baysinger et al., 1991; Talke et al., 2010). Talke et al. (2010) suggest that this implication needs further investigation in order to be confirmed.

Besides studies on the relation between gender diversity and innovation, there have been more studies conducted into the relation between technological diversity and innovation in a firm. These researches suggest that there is a positive relationship between technological diversity in a firm and innovation (Almeida and Kogut, 1997; Suzuki and Kodama, 2004; Garcia-Vega, 2006; Sampson, 2007). In table 1 there is an overview presented of the studies that are conducted on the diversity-innovation relationship.

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Table 1: Summary of the findings on the relationship between diversity and innovation

Authors Sample Findings

Østergaard et al. (2011) 1.648 Danish firms with at least 20 employees during the period 2003-2005

A positive relation between diversity in gender of the employees on the likelihood of introducing an innovation

Talke et al. (2010) 107 Publicly listed manufacturing

firms from 17 different countries Diversity of the top management team has a strong impact on the strategic choice of firms to focus on innovation fields. Such focus drives new product portfolio innovativeness and firm performance. Garcia-Vega, 2006 544 firms over 15 different industries

in 15 European countries in the period 1995-2000.

Research shows that both R&D intensity and the number of patents increase with the level of technological diversification of the firm. Technological diversification can create incentives to enhance innovation, and to raise the investments in R&D Almeida and Kogut, 1997 20 start-up firms and 20 ‘large’ firms

with highly cited patents in the period 1975-1990

Small firms explore new technological areas by innovating in less ‘crowded’ areas. The analysis reveals that small firms are tied into regional knowledge networks (like Silicon Valley) to a greater extent than large firms, and are therefore more innovative. Suzuki and Kodama, 2004 Two large Japanese firms in the period

1965-1999 Diversity of technology contributes to product diversification, innovation and sales growth. Taking advantage of

economies of scope in technology through diversification is necessary for a

technology-based firm to survive and grow.

Sampson, 2007 463 R&D alliances in the

telecommunications industry in the period 1991-1993

R&D alliances contribute more to firm innovation when technological diversity is moderate, rather than low or high

Considering all of the above the first hypothesis will be formulated. Women have different characteristics than men. Women are different with respect to risk preferences, social preferences and competitive preferences. However, these differences in gender might not hold for women in leadership positions. Besides that, more women members means more board gender diversity and gender diversity of the board can lead to more innovation. This is supported by the behavioral theory and evidence from prior research.

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2.3 Moderator firm size

The first moderator in this research is the size of the firm. Firm size is often studied as a control variable, but it is also interesting to test its direct impact on the relationship between diversity of the board of directors and the level of innovation. There are three reasons to research this moderating variable (O’Connell and Cramer, 2010). First, smaller firms have less diverse coalitions of opinions in their boards. This is because they are smaller and that could relate to their boards being smaller. But this is also because they are less able to attract diversity out of their environment (O’Connell and Cramer, 2010). When they have less coalitions of opinions, the goal consistency between members of the board is stronger. In this way the effect of diversity becomes smaller. This argument is consistent with behavioral theory. With more goal consistency, the heterogeneity of the group is smaller and the creativity and innovativeness decreases. The second reason for choosing firm size as a moderator is that prior research has shown that boards are less capable of influencing the R&D strategies in smaller sized firms (Baysinger et al., 1991; Finkelstein and Hambrick, 1996). Thus not only will the diversity have less effect in a smaller sized firm, but the boards will also have less influence on the decision-making of the firm. The final reason why firm size leads to more innovation lies in the resource dependence theory, discussed in the beginning of this chapter. A firm’s information environment is related to its size (O’Connell and Cramer, 2010). Larger firms have richer information environments. Due to these rich information environments, these large firms have bigger advantages of the information and resources the board members bring into the firm.

Research has been conducted before into the effect of firm size on innovation. The majority of the results show that firm size positively effects a company’s R&D spending (Hill and Snell, 1988; Baysinger and Hoskisson, 1989; Baysinger et al., 1991). The managers of large firms in concentrated industries are more willing to invest in R&D than the managers of small firms (Baysinger and Hoskisson, 1989). Multiple reasons are mentioned to explain the positive relationship between firm size and R&D expenditures. To begin with, this positive relation is due to the fact that larger companies will benefit from the economies of scale in R&D. So firm size increases R&D spending and higher R&D expenditures increases productivity. Another reason for the positive relationship between firm size and R&D expenditures is that large firms have more extensive R&D programs (Hitt et al., 1990; Hitt et al., 1991). A third reason is that there are many innovations that only large firms are willing to enter into (Hansen and Hill, 1991). On the contrary, there is also research that states that when firms become much larger, they stop investing in R&D (Hitt et al., 1990). This can be caused by firms becoming more risk-averse when maturing. For example the study of Hansen and Hill (1991) found that in some industries

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firm size had a positive relation to R&D expenditures and in other industries a negative relation. Hitt et al. (1990) state that it is not exactly sure how firm size influences R&D expenditures, but that there is a strong relation.

When we consider all the prior research mentioned above, the following hypothesis is formulated. The majority of the research into firm size and innovation finds that bigger sized firms are more innovative. The hypothesis therefore states that a positive moderating effect exists on the relationship between gender diversity of the board of directors and innovation.

Hypothesis 2: The relationship between gender diversity and innovation is more positive for bigger firms.

2.4 Moderator board composition

The second moderator is the composition of the board. Board composition is in this study defined as the percentage of outsiders on the board of directors. Outsiders are the non-executive board members who are independent of the firm (O’Connell and Cramer, 2010). The board members who are not outsiders are insiders. Insiders are executives that come from inside the firm, for example employees. Also members of the top management like CEO’s can become members of the board. Usually, a positive relation between percentage of outsiders and firm performance is found in research on this topic (Hill and Snell, 1988; O’Connell and Cramer, 2010). Baysinger and Hoskisson (1990) conducted research on the relation between the percentage of outsiders and R&D expenditures in firms. According to their research, the percentage of outsiders on the board is negatively related to R&D expenditures. Hill and Snell (1988) found the same connection in their research, while hypothising the other way around. Their hypothesis was that more outsiders on the board leads to higher levels of investments in R&D. They argued that this is caused by outsiders protecting the interests of the stakeholders better than insiders on the board. Insiders’ interests are more aligned with those of the management and outsiders’ interests are more in line with shareholder’s interests. This is in line with agency theory, we discussed in the previous paragraph. As agency theory suggest that greater board independence will minimize the agency problems and leads to a more effective monitoring role. So outsiders are better monitors and make the agency problems in a firm smaller (Hill and Snell, 1988). The monitoring role is to guard the shareholders’ interests and Hill and Snell (1988) suggest that those interests are to invest in R&D. The results of their study are not consistent with this hypothesis, because they find a negative significant relation between the percentage of outsiders and the level of R&D expenditures (Hill and Snell, 1988).

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Baysinger and Hoskisson (1990) give the following reason for the negative relation between the percentage of outsiders and the level of R&D expenditures of a firm. They state that insiders and outsiders differ in their way of monitoring and evaluating the behavior of the management. It is more likely that insiders implement strategic controls instead of financial controls. Strategic controls require very detailed information when being implemented and for insiders, who are relatively close to the firm and its CEO, this information is easier to obtain (Baysinger and Hoskisson, 1990). Outsiders are not involved in the day-to-day decision-making of the firm, so they do not obtain the accurate information that is needed for implementing strategic controls. When managers are evaluated on the basis of strategic controls and not only on financial controls, it is likely that they will spend more on R&D. The reason for this is that R&D expenses have uncertain and more risky cash flows. When managers are evaluated on strategic controls, they are more likely to make risky investments because strategic controls are a more subjective form of performance evaluation (Baysinger and Hoskisson, 1990). With only financial controls, managers are afraid to make risky investments because if the investment has a bad outcome, their performance evaluation will suffer. This can be a reason for the negative relationship between the percentage of outsiders and R&D expenditures. Top management is less likely to invest in risky projects if there are many outside directors that will penalize them for choosing risky R&D projects (Baysinger et al., 1991). The agency theory, that Hill and Snell (1988) mention in their article, also provides an argument for the negative relationship between the percentage of outsiders and innovation. Outsiders have a better guardian role and look out for shareholder’s interests. Shareholders carry the consequences of bad investments, so are slightly more risk-averse than the top-management. Thus more outsiders on the board, means less risky decisions and therefore less innovative investments (Hill and Snell, 1988). This leads to the following hypothesis on the moderating role of board composition on the relation between board gender diversity and innovation.

Hypothesis 3: The relationship between gender diversity and innovation is less positive for a high percentage of

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3 Methodology

In this chapter the research method is described. First, the chosen sample, time period and databases used are discussed. The next paragraph is about the data and the operationalization of the variables. Finally, the regression models are formulated and explained.

3.1 Sample and data

As mentioned before, the objective of this analysis is to explore the relationship between gender diversity of the board of directors and innovation in a firm. After the analysis of the direct relationship between these two variables, the influence of the moderators firm size and percentage of outsiders will be investigated. In order to make the sample as big as possible, the sample started with all of the firms in the database. Unfortunately, not all data was available for all the firms and therefore some firms had to be removed. In the end the sample consists of 1.015 firms with 5.683 observations. In the table below you can see how the sample is created.

Table 2: Sample selection

# Observations (N) # Firms

Data retrieved from COMPUSTAT 100,496 2,051

Data retrieved from ISS 11,828 16,659

112,324 18,710 Merge data from two databases (102,240) (16,901)

10,084 1,809 Remove observations with missing data (4,401) 794

Final sample 5,683 1,015

All data is gathered out of the Wharton Research Data Services (WRDS) database system. Financial data is found in COMPUSTAT Annual Fundamentals North America, which contains annual and quarterly report data of American and Canadian listed firms. The information about corporate governance characteristics is found in the ISS (former RiskMetrics) database. The Directors part of the database starts with data from 2007, data from before 2007 is gathered in the Directors Legacy database. But these two databases can differ a little, therefore the sample period is chosen to start at 2007. The sample period ends at 2014.

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3.2 Variables

3.2.1 Independent variable

The independent variable is the diversity of gender in the board of directors of the sample firms. This variable is measured as the number of women members present on the board divided by the total amount of members on the board. In other words, the percentage of women in the board of directors.

3.2.2 Dependent variable

The dependent variable is innovation of a firm. Innovation is measured with R&D expenditures divided by total sales of the firm. This is the most common way to operationalize innovation, since this is a good indicator of the intensity of innovation (Hansen and Hill, 1990; Baysinger et al., 1991; Kemp et al., 2003). Furthermore, this measure is frequently used in other research, so this enhances the comparability of the findings. R&D expenditures divided by total sales is also a relatively easy way to measure innovation and data can be easily collected since firms state the R&D expenditures in their income statement. The data can be found in COMPUSTAT.

3.2.3 Moderating variables

Firm size: Firm size is measured as the natural logarithm of the total assets of the firm. These

assets are reported on the balance sheet. This measure is chosen as it is an effective proxy for firm size (Dalbor et al., 2004). This data is retrieved from COMPUSTAT.

Board composition: The second moderating variable is board composition. Board composition

is defined as the percentage of outsiders on the board of directors. Outsiders are the non-executive board members who are independent of the firm (O’Connell and Cramer, 2010). In the ISS database these are given the ‘Independent’ label. The board members who are not outsiders are insiders. Insiders are executives that come from inside the firm or are closely linked to the firm. In the ISS database these board members are formulated as ‘Linked’ or ‘Employees’.

3.2.4 Control variables

The following control variables are added to this research. Based on prior research these variables are chosen, because they can possibly influence the relation between the percentage of women and the level of innovation in a firm.

- Board size: Is defined as the total number of directors in the board. There are two reasons why board size is a control variable in this research. First, because boards with more members, automatically have a greater chance of having more women present on

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the board (Carter et al., 2010). By measuring gender diversity as a percentage you control for this effect. The second reason is that, according to Bantel and Jackson (1989), board size is also related to heterogeneity. This means that a bigger board will increase the chance of having a heterogeneous board. A more heterogeneous group means a higher representation of women, which will increase the chance of innovation (Bantel and Jackson, 1989).

- Book-to-market ratio: The next control variable is the book-to-market ratio of the sample firms. We control for the book-to-market ratio, because it is negatively related to R&D expenditures (Lev and Sougiannis, 1999). This ratio is defined as the book value of equity divided by the market value of equity. Again, this data can be found in COMPUSTAT. The book value of equity is the value of equity on the balance sheet. The market value of equity is calculated by multiplying the number of outstanding shares by the share price.

- Firm liquidity: The next control variable is firm liquidity. According to the literature, firm liquidity is positively related to R&D expenses (Baysinger and Hoskisson, 1989; Miller and Triana, 2009). There are three reasons for the positive relationship. First, a liquid firm has more internal resources available which it needs to engage in R&D activities. Second, with more financial liquidity, a firm has less borrowing costs and that reduces the cost to finance R&D projects (Baysinger and Hoskisson, 1989). So investing in R&D is less costly and therefore firms are more willing to invest in R&D. And third, more liquidity is associated with profitability and that leads to optimism in a firm. And optimism can increase the willingness to invest in R&D (Hitt et al., 1991). In this research a standard measure of liquidity is used (Baysinger and Hoskisson, 1989). This is the current ratio, which is the current assets divided by the current liabilities. The data is reported on the balance sheet, which can be retrieved from COMPUSTAT.

- Average industry R&D intensity: The last control variable is the weighted average R&D intensity in the industry the firm operates. This measure controls for different industries and that is in line with previous literature (Baysinger and Hoskisson, 1989; Hansen and Hill, 1990; Baysinger et al., 1991; Carter et al., 2003; Miller and Triana, 2009; Carter et al., 2010; Østergaard et al., 2011). If a firm operates in an innovative industry, this is expected to spillover onto the firm itself. So average industry R&D intensity is positively related to R&D expenditures of a firm. Industry R&D intensity is measured as an average of industry R&D spending for all firms that operate in an industry (Baysinger and Hoskisson, 1989; Baysinger et al., 1991; Miller and Triana, 2009). This is R&D

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expenditures divided by sales averaged for all firms in an industry. For practical reasons only the firms of the sample are taken to calculate the average of the industry. Industry is defined with Standard Industrial Classification (SIC) codes at the two-digit level. All firms in COMPUSTAT only get one SIC code, so there is no weighted average of the different industries a firm operates in.

3.3 Research method

In this thesis a quantitative research method is used in combination with the program STATA. Due to the fact that we have panel data, a panel regression is used to test the data. Panel data is data that contains multiple observations for multiple time frames (years in this case) for the same firms. This regression model is a linear model which analyses the relationship between the dependent and independent variable. There are five models regressed. The first model is a regression with only the control variables and the dependent variable. In the second model the independent variable, percentage of women on the board, is added. The third, fourth and fifth model are the models that contain the moderators as well. The third is with the moderators added to the linear function. The fourth model contains the interaction term between the moderator firm size and the independent variable. Finally, the fifth model contains the interaction term between the moderator board composition and the independent variable. Table three below shows the equations of the regression models.

Table 3: Regression models

Model 1 R&D = B0 + B1*BOARDSIZE + B2*BOOKTOMARKET + B3*FIRMLQUIDTY + B4*INDUSTRYRD + ε

Model 2 R&D = B0 + B1*BOARDSIZE + B2*BOOKTOMARKET + B3*FIRMLQUIDTY + B4*INDUSTRYRD + B5*%WOMEN + ε

Model 3 R&D = B0 + B1*BOARDSIZE + B2*BOOKTOMARKET + B3*FIRMLQUIDTY + B4*INDUSTRYRD + B5*%WOMEN + B6*FIRMSIZE + B7*%OUTSIDERS + ε

Model 4

R&D = B0 + B1*BOARDSIZE + B2*BOOKTOMARKET + B3*FIRMLQUIDTY + B4*INDUSTRYRD + B5*%WOMEN + B6*FIRMSIZE +

B7*FIRMSIZE*%WOMEN + ε

Model 5

R&D = B0 + B1*BOARDSIZE + B2*BOOKTOMARKET + B3*FIRMLQUIDTY + B4*INDUSTRYRD + B5*%WOMEN + B6*%OUTSIDERS +

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Continuation of table 3 R&D BOARDSIZE BOOKTOMARKET FIRMLIQUIDTY INDUSTRYRD %WOMEN FIRMSIZE %OUTSIDERS

R&D expenditures / Total Sales Number of board members

Book value of equity / Market value of equity Current ratio

R&D expenditures / Total Sales. Averaged for all firms in the industry Percentage of women board members

Natural logarithm of the firm’s total assets Percentage of outside board members

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4 Results

4.1 Descriptive statistics

Before the regression is conducted, the variables have been ‘winsorized’. This means that the outliers are removed, without deleting the observations. Outliers are extreme values which can influence the results of the descriptive statistics and also of the regression. A 99% winsorization is done which means that all the data in the smallest and largest percentile are set equal to the value of the second percentile.

Table four clearly displays the gender inequality of the members on the board of directors. On average only 12% of the board members in the sample are women. In the table we can also see the changes over the sample years. The average percentage of women on the board increased from 11% in 2007 up to 14.7% in 2014. This is in line with the literature that is discussed in this paper. Furthermore, table four shows that in 2007 33% of the boards did not have any woman present among the board members. In 2014 this percentage decreased to 20%. As shown in table four the average amount of board members remained the almost the same over the sample years. On average the boards of this US sample have around nine directors.

Table 4: Average number of board members and percentages of women over the sample years

Year 2007 2008 2009 2010 2011 2012 2013 2014

Average number of

members on the board 8.8 9.0 8.9 8.9 8.9 9.0 9.0 9.0 Percentage women 11.0% 11.2% 11.4% 11.6% 12.4% 12.9% 13.9% 14.7% % of firms with 0 women on

the board 32.6% 31.2% 32.0% 31.7% 29.1% 26.3% 24.5% 20.1% % of firms with 1 woman on

the board 39.4% 38.4% 37.0% 36.4% 36.7% 38.4% 36.2% 37.5% % of firms with 2 women on

the board 21.3% 23.3% 23.1% 23.1% 25.0% 24.6% 26.5% 28.8% % of firms with 3 women on

the board 4.4% 5.1% 5.9% 6.7% 6.3% 7.8% 9.2% 9.5% % of firms with 4 women or

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In table five a chart is shown of the average R&D expenditures per sector over the sample years. A sector is defined as a group of industries with two-digit SIC codes which are similar. Appendix two shows which industries belong to the sectors. The chart reveals the major differences in levels of R&D intensity between different sectors. The manufacturing and services sectors are the two sectors with the highest R&D expenditures relative to the level of total sales. In most sectors there is a pattern shown. The construction, manufacturing and wholesale trade sectors are exceptions to this trend over the sample years. The trend shows a slight decrease in R&D intensity at first, but afterwards an increase. This pattern can be explained by two factors. The first is the financial crisis which started in 2008. Firms are less likely to invest in R&D in a period of a recession (Archibugi et al., 2013). Over the sample years the economic conditions recovered and therefore the willingness to invest in R&D increased. The second reason for the increasing trend over the sample years is the increased emphasis on the importance of innovations in the past years. Firm innovation is important for the firm’s outcomes and the chances of survival in a competitive environment (Janz et al., 2003; Van Leeuwen and Klomp, 2006).

Table 5: Average R&D intensity per sector per year

0 10000 20000 30000 40000 50000 60000 70000 80000 2007 2008 2009 2010 2011 2012 2013 2014

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In table six the descriptive statistics are shown for all the variables. The table shows the mean, the standard deviation, the minimum and the maximum of the observations. In the table it is also possible to see that the maximum percentage of women is 0.67, which is two thirds of the board members. When you look at the percentage of outsiders there is a maximum of one, which means that there are boards with all outside members in the sample. Noteworthy is that that the minimum of the book-to-market ratio is a negative value, which means that the firm either has a negative book value or a negative market value. Another remarkable point is that the mean of the R&D expenses of the sample firms is higher than the average of the industries they operate in.

Table 6: Descriptive statistics

Variable Mean Stand dev. Min Max

R&D 0.06082 0.08339 0 0.60191 BOARDSIZE 8.96340 2.10296 4 21 BOOKTOMARKET 0.47608 0.33810 -0.11090 3.41704 FIRMLIQUIDITY 2.68178 1.81101 0.50792 11.82082 INDUSTRYRD 0.04625 0.03715 0 0.10811 %WOMEN 0.12385 0.10171 0 0.66667 FIRMSIZE 7.70961 1.58163 4.65351 12.08770 %OUTSIDERS 0.79061 0.10905 0.14287 1

R&D and INDUSTRYRD are stated in millions of dollars.

4.2 Correlations

Table seven shows the correlation matrix and the level of significance. Only the relation between R&D intensity in a firm and the book-to-market ratio is not significant. The rest of the values in the matrix show significant correlations. In the previous chapters, arguments are presented for a positive relationship between the percentage of women on boards and the R&D intensity in firms. The correlation matrix shows a negative correlation between the percentage of women and the R&D intensity. This is against the expectation. Looking at the two moderators, firm size and percentage of outsiders, you find one remarkable correlation. That is the correlation between firm size and R&D intensity. In the table it is a significant, small and negative value, while the

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expectation was to find a positive correlation. The other moderator, percentage of outsiders, has a negative correlation as predicted. When looking at the four control variables, two variables have an outcome as expected. The relation between firm liquidity and industry average R&D and the dependent variable are as expected. However, board size and R&D has a small, significant negative value, while the prediction was to find a positive value. Book-to-market ratio and R&D has a negative value, but this correlation is not significant. When analyzing the correlation matrix not very strong correlations are found. The only strong correlation is a positive significant correlation of 0.63 between firm size and board size. This finding is in line with the expectation that larger firms have more members on the board (O’Connell and Cramer, 2010).

Table 7: Correlation matrix

Variable 1 2 3 4 5 6 7 1. R&D 2. BOARDSIZE -.20*** 3. BOOKTOMARKET -.04 -.09*** 4. FIRMLIQUIDTY .36*** -.33*** .11*** 5. INDUSTRYRD .54*** -.12*** -.11*** .21*** 6. %WOMEN -.17*** .36*** -.11*** -.27*** -.12*** 7. FIRMSIZE -.16*** .63*** -.14*** -.39*** -.08*** 0.37*** 8. %OUTSIDERS -.02*** .23*** -.07*** -.16*** .07*** .23*** .25*** Note: *_p<0.05;**_p<0.01;***_p<0.001

Next, a check for the multicollinearity of the data is conducted. This is not standard for a panel regression, so in order to check for multicollinearity we assume a OLS regression will be conducted. Multicollinearity refers to independent variables being highly correlated to other independent variables. It is important to check for this, because it can make results insignificant while they should be significant. Multicollinearity does not affect the reliability of the regression to predict the dependent variable, but it can affect the result of individual independent variables. In STATA you can check for multicollinearity with the variance inflation factor (VIF). When checking for multicollinearity, the VIF’s hold values between 1 and 2. This implicates that there is no need for further investigation. The results of the test for multicollinearity are displayed in appendix 1.

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4.3 Results of regression

In this section the results from the panel regression will be discussed. The five models together will examine whether gender diversity is positively related to innovation and if and how the moderators influence this relationship. Besides that, the regression will also show if the four control variables have an influence on innovation. Table eight presents the results of the regression.

Model 1 of the regression is the linear model with only the control variables and their influence on the dependent variable of innovation. The results show how the control variables affect the dependent variable. This model does not test the hypothesis, but this approach helps to see the difference in effect when the independent variable in model 2 is added. The F-test points out the relation between the control variables and R&D. The F-test with F(4,4402) = 21.51 is significant, with p<.001. Table eight shows the results of the regression. Among other things, it displays the estimates of the regression coefficients and the level of significance. The coefficient of the control variable BOARDSIZE is the only one that is not significant, so this shows that there are differences between the variables and their effect on R&D. The control variable INDUSTRYRD is highly significant with p<0.001 and has a positive coefficient of 0.6. This finding is in line with the expectation of the positive relation between the average industry R&D intensity and the firm’s R&D intensity. This variable has the strongest influence on the R&D variable. The coefficients of BOOKTOMARKET and FIRMLIQUIDITY are also significant. BOOKTOMARKET has a value of 0.006. This is a small positive value, so not in line with the negative relation that was expected. FIRMLIQUIDITY has a negative small value (-.001), while the expectation was to find a positive relationship with the dependent variable. The R-squared is 0.25 which means that this model explains 25% of the variability of the data around its mean. There is also a large part of the variation influenced by other variables that are not in the model.

In the second model the independent variable %WOMEN is added to the regression. The F-test, F(5,4401)=17.25 with p<0.001, gives a significant result. The coefficient of the independent variable is slightly negative (-0.003) but not significant (p=0.6). Therefore it is not possible to reject or accept the first hypothesis. The adding of the independent variable does not change the outcome of the control variables on the R&D. The R-squared is still 25% in model 2. The R-squared did not increase due to the addition of the independent variable.

The third, fourth and fifth model are the models with addition of the two moderators. The third model adds the two moderators as normal variables in the regression. While the fourth and

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fifth are the models of the regression with the interaction terms that determine how the moderators influence the relation between gender diversity and innovation. All three F tests are significant (F(7,4398)=13.01; F(7,4399)=12.97; F(7,4398)=12.58). The values of the R-squared are 26%, 27% and 25% respectively. These models have little meaning due to the lack of significance of the estimates. The estimate of the independent variable percentage of women on the board and of the estimates of the moderators are not significant in the (moderating) effect on the R&D intensity of the sample firms. The p-values of the interaction terms are 0.9 and 0.2 in model four and five. Therefore, it is not possible to accept or reject hypothesis two and three. Only the direct effect of FIRMSIZE on R&D intensity is significant and negative. This is not in line with the assumptions that have been made before. Chapter two predicted that firm size positively influences R&D intensity in firms. In the last three models the estimates of the control variables do not change. The negative estimate of the %WOMEN differs a bit over the three models, but the value remains insignificant. Table eight with the results of the regression is displayed on the next page.

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Table 8: Regression estimates

R&D

Model 1 Model 2 Model 3 Model 4 Model 5

Estimate (Stand. error) Estimate (Stand. error) Estimate (Stand. error) Estimate (Stand. error) Estimate (Stand. error) BOARDSIZE .0005 .0005 .0006 .0006 .0005 (.0004) (.0004) (.0004) (.0004) (.0004) BOOKTOMARKET .006*** .006*** .006*** .006*** .006*** (.001) (.001) (.001) (.001) (.001) FIRMLIQUIDITY -.001** -.001** -.001** -.001** -.001** (.0004) (.0004) (.0004) (.0004) (.0004) INDUSTRYRD .6*** .6*** .6*** .6*** .6*** (.07) (.07) (.08) (.08) (.07) %WOMEN -.003 -.001 -.0006 -.003 (.007) (.007) (.007) (.007) FIRMSIZE -.002* -.002* (.001) (.001) %OUTSIDERS .003 .001 (.007) (.007) FIRMSIZE*%WOMEN -.00004 (.0007) %OUTSIDERS*%WOMEN -.0008 (.0006) N 5330 5330 5329 5330 5329 R2 _.25 _.25 _.26 _.27 _.25 F 21.51 17.25 13.01 12.97 12.58 Note: *_p<0.05;**_p<0.01;***_p<0.001

The influence of gender diversity on innovation : an analysis on the corporate governance level

Amsterdam Business School