June 18th, 2018
MASTER THESIS
A quantitative analysis of the effect of board diversity on
corporate social performance
Robin Ebbert Student number: 3475824 Nassaulaan 13 A, 9717 CE Groningen
r.ebbert@student.rug.nl
Supervisor: Dr. C.H. Rieneke Slager Co-assessor: Dr. Rudi W. de Vries
Wordcount: 12.946
ABSTRACT
This paper aims to shed light upon the relationship between board diversity and corporate social performance. To create an appropriate analytical concept to test this relation, the relevant literature - namely stakeholder management theory, the upper-echelons theory, board diversity literature and corporate social responsibility research - provides the theoretical insights. To examine the effects of the diversity characteristics director gender, age, nationality and board tenure on CSP, a stepwise multiple regression analysis is conducted. The used sample is based on 392 American Fortune 500 companies and consists of CSP data gathered from the Thomson Reuters ASSET 4 database from the year 2016 and 1-year lagged director characteristics and company data extracted from the databases BoardEx and Orbis. It is found that director gender, nationality and tenure diversity have a positive effect on CSP and age diversity a negative one. These significant findings can motivate future research to intensify the elaboration of this underdeveloped research stream and further highlight the possible enhancement of corporate governance systems. Politicians as well as corporate decision-makers receive the necessary knowledge to change corporate board structures towards increased heterogeneity to consequently improve CSP. Considering recent trends, this can become one of the major tasks of the near corporate future.
TABLE OF CONTENTS
1. INTRODUCTION ... 1
2. THEORETICAL FOUNDATION AND HYPOTHESES ... 3
2.1 Prior Board Diversity Research ... 3
2.2 Stakeholder Management and CSP ... 4
2.3 Upper-Echelons Theory ... 7
2.4 Board Diversity and Hypotheses Development ... 8
LIST OF FIGURES AND TABLES
Figures
Figure 1 − Conceptual Model ……….…………...13
Tables
Table 1 − Industry Classification………..……….21Table 2 − Descriptive Statistics………..………...23
Table 3 − Sample Distribution across 11 Industries……….……...…………..24
Table 4 − Pearson's Zero-Order Correlation………..………26
Table 5 − Stepwise Regression Analysis………..……….28
LIST OF ABBREVIATIONS
CSP – Corporate social performance CSR – Corporate social responsibility U.S. – Unites States
Et al. – et alii / aliae / alia (and others) e.g. – exempli gratia (for example) R&D − Research and Development CEO − Chief executive officer GDP − Gross domestic product SD − Standard deviation CO2 − Carbon dioxide ROA − Return on assets
ICB − Industry classification benchmark IBM − International Business Machines
1
1. INTRODUCTION
Enron. Lehman Brothers. Global financial crises. The biggest bankruptcy until 2001, the biggest bankruptcy in U.S. history and ultimately the global financial crises in 2008 which resulted in innumerable bankruptcies and worldwide unemployment. Among others, the reason for these three fatal events was highly unethical and in some instances criminal behaviour of the corporations’ decision-makers (Wolff, 2011). These far-reaching events revealed weaknesses in corporate governance practices and highlighted the irresponsible performance of top management teams (Ferrero-Ferrero et al., 2015). The recognition of these shortcomings triggered discussions on how to solve this problem. Beside the agreement on the Basel III rule which demands a higher financial stability, European countries intend to improve the corporate governance systems by increasing the diversity level in the board of directors. As a part of this process, the European Commission formulated an action plan which treats diversity in board composition as an important factor to improve the sustainability aspect in the decision-making process (European Commission, 2012). It is accompanied by governmental pressures and legislative changes to prevent unsustainable executive behavior. In particular countries from Western Europe passed laws to improve the situation through an increase of diversity in corporate boards (Harjoto et al., 2015). Germany for instance, passed a quota which requires a minimum of 30 percent of women in corporate supervisory boards (Bundesministerium für Familie Frauen und Jugend, 2017). Although the American system is considering board diversity as a possible vehicle to foster corporate sustainability, there is no intention to introduce such quotas as in Europe (Cassidy, 2016).
2 to focus mainly on the gender diversity aspect (Bear et al., 2010; Setó-Pamies, 2015; Zhang et al., 2013) but still contradict in their findings. Whereas Prado-Lorenzo and Garcia-Sanchez (2010) find no relation between gender diversity in corporate boards and CSP, Liao et al. (2015) uncover a positive relationship. This study strives to shed light not only on the influence of gender diversity on CSP, but also on other board diversity factors which may influence firms’ sustainability.
Therefore, I follow the stakeholder theory (Freeman, 1984 and 2010) which states that firms are able to develop a competitive advantage through other individuals or organizations making firm-specific investments. To ensure this competitive advantage, the firm must protect the interests of these investors through effective stakeholder management (Hillman and Keim, 2001) which consequently implies a sustainable CSP (Harjoto et al., 2015). To further develop this perspective, it is necessary to identify the ones responsible for these management decisions. Hambrick and Mason (1984) evolved the upper-echelons theory which reveals that decisions in a corporation are made by the representatives of the highest management level and are highly influenced by their personal values and characteristics. An important corporate organ on the top management level is the board of directors. Combining the views of the stakeholder theory and the upper-echelons theory, it is reasonable that this important department should represent the stakeholders in the most adequate way. For this reason, I examine the observable upper-echelons characteristics and associate them with recent board diversity research. This leads to four diversity factors and the same number of associated hypotheses which are tested for the influence on CSP with a stepwise multiple regression analysis to answer the following research question:
What is the effect of board diversity on corporate social performance?
3 for 2016 and the BoardEx and Orbis database allocate the 1-year lagged director characteristics and the company data. It is ascertained that director gender, nationality and board tenure diversity have a positive effect on CSP while director age diversity has a negative one. Determining that increasing certain levels of corporate board heterogeneity can increase CSP, this study offers theoretical as well as practical implications. Theorists receive significant evidence on a barely researched topic and can recognize the findings as incentives for further elaboration to create a more solid knowledge base. Practitioners can use these insights to improve corporate governance structures and consequently change corporations towards greater responsibility. Even though this topic is new and barely researched, the developments mentioned at the beginning of this chapter make it a very urgent one.
2. THEORETICAL FOUNDATION AND HYPOTHESES
2.1 Prior Board Diversity Research
Board diversity is a management topic of high interest which constitutes challenges as well as opportunities for managers and theorists (Adams et al., 2015). The topic offers a broad spectrum of possible research fields due to the various approaches to combine different diversity aspects (e.g. demographic diversity or functional diversity) with the effects diversity can have on corporate outcomes (e.g. firm performance). Even though a lot of research exists, the results are still equivocal (Harjoto et al., 2015). Most findings concern the effect board gender diversity has on financial performance (Ben-Amar et al., 2017). Within this accumulation of research there are studies which link gender diversity with positive performance (Carter et al., 2003) but also other studies which find no (Miller and del Carmen Triana, 2009) or even a negative effect of gender diversity on financial performance (Adams and Ferreria, 2009).
4 et al., 2013). Nevertheless, the findings about the influence of gender diversity on CSP are as controversial as the ones about the influence of board diversity on financial performance (Liao et al., 2015; Prado-Lorenzo and Garcia-Sanchez, 2010).
Although overall board diversity is expected to increase board efficiency by regulators, there are research findings which state the opposite (Veltrop et al., 2015). They find that demographic diversity in corporate boards can trigger demographic faultlines which in turn cause negative effects in terms of board efficiency and hence board performance.
2.2 Stakeholder Management and CSP
5 After Freeman published his stakeholder management concept, it was revised by many researchers and elaborated according to their specific research contexts. Clarkson (1995) focuses on primary stakeholders which he defines as ‘stakeholders who bear some risk as a result of having invested some form of capital, human or financial, something of value, in a firm’(Clarkson, 1994: p. 5). The effective management of these groups or individuals is essential to increase firm performance and finally ensure a firm’s persistence. Hillman and Keim (2001) build upon this approach and constitute that efficient stakeholder management can create value which exceeds the pure investment relationship of a firm and its stakeholders. If efficient management is in place, the relationship itself produces an intangible value which leads to the ability to outperform competitors and create a sustainable competitive advantage. Post et al. (2002) surmise that firms can create wealth by maintaining sustainable relationships with critical stakeholders and decrease wealth by being in conflict with them. Only a well-functioning relationship preserved by effective stakeholder management makes these resources available and is consequently substantial for firm survival.
6 automatically something good and emphasizes its meaning as a measurement which can either be positive or negative. Although this definition is well accepted within the CSP literature (Hillman and Keim, 2001; Ioannou and Serafeim, 2012) there are also voices which question the generalizability of the concept. Rowley and Berman (2000) accentuate that the different settings firms are operating in (e.g. the industry) are highly influential and hence decrease the comparability of different studies. This argumentation corresponds with Clarkson (1995) who claims that there is no clear definition of CSP to provide a guideline for the necessary data collection. It is not standardized which corporate data has to be used to evaluate a firm’s CSP which makes a comparison of results complicated.
7 the validity and value of this research. The elaborated diversity aspects are subsequently appraised on their effect on firms’ CSP.
2.3 Upper-Echelons Theory
With several hundred quotations in not only management literature but also other socioeconomic studies, the upper echelons theory by Hambrick and Mason (1984) is a fundamental corporate governance concept (Carpenter et al., 2004). Their main argument is that the main decision-makers in corporations, the upper-echelons, are mainly responsible for the corporate outcome. Furthermore, the upper-echelons’ individual characteristics, personalities, values and experiences determine how they interpret strategic situations and their subsequent decisions (Hambrick, 2007). This focus on the importance of the characteristics of individuals in top management teams, including the board of directors (Cannella et al., 2008), as well as the conceptual elaboration of the advantageousness of diversity of those characteristics within these teams make their research valuable for this study.
Moreover, the upper echelon characteristics are divided in psychological and observable factors. Because psychological characteristics are seen as a hard to generalize black-box, the observable characteristics age, functional tracks, other career experiences, education, socioeconomic roots, financial position and group characteristics serve as proxies and receive great attention. Cannella et al. (2008) state that this information is codable and reliable and hence constitute a sufficient measurement to examine the influence of individuals’ attributes on corporate outcome.
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2.4 Board Diversity and Hypotheses Development
The board of directors is an important corporate governance institution which has the function to ensure the separation of decision-making and control. It consists of inside and outside directors who are responsible for the ratification and monitoring of management decisions to, following stakeholder theory (Freeman, 2010), meet the stakeholders’ expectations. Equipped with the authority to decide about management’s rewards and to remove low-performing executives, they are not only the major assessors of companies but are also influencing the corporate strategic decision-making processes (Fama and Jensen, 1983). For this reason, the board of directors is a crucial determinant for corporate outcome including a firm’s CSP (Ferrero-Ferrero et al., 2015).
9 Considering the upper echelon characteristics developed by Hambrick and Mason (1984) as important indicators for corporate outcome, this study matches them with characteristics utilized in prior board diversity research (e.g. Adams et al., 2015; Ben-Amar et al., 2017; Hafsi and Turgut, 2013; Harjoto et al., 2015). This results in the examination of the influence of the diversity characteristics director gender, age, nationality and board tenure on CSP.
The presumably most researched field is the effect board gender diversity has on financial performance (Ben-Amar et al., 2017). On the one hand there is research which ascertains a positive impact of gender diversity on performance (Carter et al., 2003) whereas on the other hand for instance Adams and Ferreria (2009) find a negative impact and Miller and del Carmen Triana (2009) show no clear relationship between the two parameters.
A less researched but very recent topic is the relationship between board gender diversity and CSP. Similar to research about the effects on firms’ financial performance, gender diversity is the most frequently investigated diversity aspect (Bear et al., 2010; Setó-Pamies, 2015; Zhang et al., 2013). However, the research findings show a lack of conformity. Liao et al. (2015) and Prado-Lorenzo and Garcia-Sanchez (2010) both investigate the influence of gender diversity in corporate boards on the disclosure of greenhouse gas emission as CSP measurement. Whereas the first-mentioned research group finds a positive relation in their conducted regression analysis, the latter did not find any significant gender related effect. The absence of such an effect is assumed to originate from low level institutional macro contexts in terms of board responsibilities towards stakeholder issues (Prado-Lorenzo and Garcia-Sanchez, 2010).
10 making which both can constitute enhanced CSP (Bear et al., 2010). Nevertheless, the existence of a single woman in corporate boards might not be sufficient to achieve a significant behavioral change, because it is more difficult for minorities within a group to assert their opinion (Nemeth, 1986). This explains Konrad’s et al. (2008) findings that a rising number of women in corporate boards increases their influence in the decision-making process. As a result of the prior argumentation, I assume the following:
H1: Board gender diversity positively influences corporate social performance.
The age of directors as members of top management teams was already recognized as an important characteristic by Hambrick and Mason (1984). They state that younger managers are associated with innovation and risk-taking tendencies which positively correlates which corporate growth. Older managers instead are less able to integrate new information in the decision-making process. Due to their experience, success and accumulated wealth, they show a greater commitment to the status quo of the organisation and are more risk-averse than their younger counterparts.
11 reached with an average age of 56. They try to explain this with a historical contemplation of social movements and show a connection to the Earth Day movements in 1970. Ferrero-Ferrero et al. (2015) view age diversity as positively influencing CSP. Like Post et al. (2011) and Hafsi and Turgut (2013) they assign older generations a higher ability for moral reasoning and a greater sensitivity towards the overall society. An increased appreciation of work-life balance and a higher sense of vulnerability of environmental consequences is the reason for a higher emphasis on social issues of younger generations. Therefore, they assume that a board which contains the values, thoughts and mindsets of several generations shows a greater CSP which corresponds with their findings. Following this argumentation and the overall belief that diversity increases the ability to understand the needs of various stakeholders, I formulate the following hypothesis:
H2: Board Age diversity positively influences corporate social performance.
12 perspective a board can perceive of a firm’s business environment including employees and local communities. He reasons this with an increased ability of minorities to build weak network relationships. Consequently, a corporation with ethnic minorities in the board of directors is more able to understand the needs of their various stakeholders and evince a superior CSP. Post et al. (2011) point out that the understanding of various stakeholders and the esteem of sustainability is also influenced by education. Therefore, they analyse the influence of board members who have an educational background in Western Europe, which is evaluated as forerunner in CSR education, on environmental CSR performance and find positive results. Having directors on the board who are educated in CSR issues might have similar effects than having an ethnical diverse board which is able to anticipate the needs of the corporation’s various stakeholder groups. Acknowledging the ethnicity diversity findings as meaningful for nationality diversity I constitute the following hypothesis:
13 concepts and procedures get questioned less and less which results in a decrease of the decision-making quality. Even though their candour towards change and new concepts decreases, their power increases over time. Carpenter et al. (2004) on the other hand state that long-tenure is connected with high performance and refer to Bergh (2001) who finds that a longer tenure is associated with more successful acquisitions. They conclude that the superior amount of interfirm knowledge and established relationships within firms as well as in the firm’s stakeholder environment are responsible for the increased success. The well-reasoned nature of these conflicting perspectives might be the reason for prior board diversity research (e.g. Hafsi and Turgut, 2013; Harjoto et al., 2015) to assume that tenure diversity positively influences CSP. Both, a short tenure and a long tenure reveal arguments which could lead to a higher CSP. Therefore, I agree with the aspects raised by both research groups and assume that a mix of eagerness and experience, accordingly a tenure diverse board, influences CSP positively and formulate the subsequent hypothesis:
H4: Board tenure diversity positively influences corporate social performance. The elaborated hypotheses result in the subsequent conceptual model:
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3. METHODOLOGY
In this section, the research methodology is presented. Firstly, the sample is explained. This contains the description of the collected data as well as an overview of the utilized databases and gives a first summary of the final dataset. Afterwards, the different variables are discussed, and the data analysis method is explained.
3.1 Sample
The sample consists of the different variables used in this study to test the four developed hypotheses. Firstly, the sample has to be chosen. Secondly, historical data of the different variables is collected from the most suitable databases and is lastly combined into a new dataset which is the foundation of this research.
15 Taking the Fortune 500 as a foundation, different databases have to be investigated to check the availability of the required company data. The most recent CSP data to be found is from the year 2016. Even though the time lag of the effect of board diversity on CSP is not clearly answered by research yet, I agree with the approaches by for instance Harjoto et al. (2015) that such a time lag exists. Due to the ambiguity of the exact lag, I run the generated models firstly with board diversity data of 2015 and afterwards use the 2014 data to run a robustness test. The CSP data is extracted from the Thomson Reuters ASSET 4 database. This database integrates over 750 equally weighted data points into 280 key performance indicators, 18 categories, four pillars (economic, environmental, social and corporate governance performance) and one comprehensive CSP score for over 4,300 companies (Thomson Reuters, 2012) and receives increased attention by CSP researchers (Cheng et al., 2014; Ioannou and Serafeim, 2012; Shaukat et al., 2016). The value of these integrating scores is appreciated because single measurable aspects of CSP, like corporate philanthropy, do not provide sufficient information about the overall environmental and social performance of a company (Ioannou and Serafeim, 2012). The ASSET 4 dataset is hence the multidimensional measure including a large amount of companies from various industries which was already requested by Waddock and Graves in 1997.
The board diversity data is collected from the BoardEx database which provides biographical data of company board members and senior executives for more than 800,000 companies worldwide. Orbis by Bureau van Dijk is the data source for the company data used as control variables.
16 age is 62,78 (SD 7,95) years, the oldest director is 94 and the youngest one 30 years old. The tenure mean is 8,38 (SD 7,07) years with the longest duration of a director on a corporate board being 52,9 years. The proportion of female board members is with 19,12 % low but still higher than the proportion of foreign board members with 7,74 %. The distribution in 2015 is similar with a mean age of 62,96 (SD 7,98), the oldest director being 92 and the youngest one 31 years old. The tenure mean shows a minor increase to 8,43 (SD 7,15) years while the longest duration on board increases exactly by one to 53,9 years. The proportion of female board members slightly rises to 20,22 % whereas the proportion of foreign board members decreases to 7,43 %.
3.2 Measures
Within this section, the different measurements are explained. Firstly, the independent variable CSP is elucidated. This is followed by the description of the independent variables gender diversity, age diversity, nationality diversity and tenure diversity and ends with the clarification of the control variables firm size, board size, firm performance, R&D, risk, CEO duality and industry.
3.2.1 Dependent Variable
17 investigated effect. As mentioned in the theory part, a comprehensive multidimensional approach is superior to methods which evaluate a firm’s CSP just on the basis of selected financial data. The ASSET 4 indicators are calculated by professional analysts who evaluate publicly available company data (e.g. annual reports and proxy statements) and transform the quantitative and qualitative information into the comparable dimensions (Thomson Reuters, 2012). This professionalized process finally provides an indicator which is as comprehensive as comparable. Therefore, the equally weighted environmental and social score is seen as an adequate measure for this study.
3.2.2 Independent Variables
Age diversity, tenure diversity, gender diversity and nationality diversity are the independent variables. These characteristics are not unknown in board diversity research because they are either observable or publicly available and are therefore relatively easy to access (Rao and Tilt, 2016).
There are two commonly used concepts to measure board diversity. Research defines board diversity either as the percentage of board members of a specific group (e.g. Setó-Pamies, 2015) or uses Blau's (1977) index of heterogeneity (e.g. Harjoto et al., 2015; Zhang, 2012). The first alternative is limited to samples with only two categories. This study uses Blau’s index of heterogeneity to calculate the independent variables due to its usability for the entirety of the study.
Blau’s index of heterogeneity = 1 −
18 Klein (2007) furthermore outline that the maximum is limited by i ((i-1) / i) and hence varies when the number of categories differs. If there are for instance two categories present, the maximum of 0.5 ((2-1) / 2) would be reached when the individuals are evenly spread over the two categories. If there would be four categories the formula would be (4-1) / 4 and result in an evenness score of 0,75.
Gender diversity has the two categories 0 = female and 1 = male and would reach the evenness score of 0,5 when there is an equal number of female and male directors on the board.
The nationality diversity calculation works according to the same principle. Due to the vast majority of directors being American, nationality diversity is only categorized in the two categories foreign = 0 and non-foreign = 1 (American). The maximum heterogeneity calculated with the Blau index is 0.5.
The independent variable age diversity depicts the age of the directors and differs from the previous two. It is partitioned in five categories: less than 40-years old (1), 40 – 49 (2), 50 – 59 (3), 60 – 69 (4) and 70-years old and older (5). The maximum homogeneity is 0 and evenness 0.8 ((5-1) / 5).
Tenure diversity describes the variety of the duration the directors are on the firm’s board and its categorization is based on the statement of Harjoto et al. (2015) who say that an average term is three years. Therefore, I establish six categories: less than 3 years (1), 3 – 6 years (2), 6 – 9 years (3), 9 – 12 years (4), 12 – 15 years (5) and 15 years and longer (6). Perfect heterogeneity is 0.83 ((6-1) / 6) and would be reached when the members of the board are equally spread over the six categories.
3.2.3 Control Variables
19 included in this study are firm size, board size, firm performance, R&D, risk, CEO duality and industry.
Firm size is a commonly used control variable in board diversity research (Harjoto et al., 2015; Ioannou and Serafeim, 2012; Prado-Lorenzo and Garcia-Sanchez, 2010; Shaukat et al., 2016; L. Zhang, 2012). Mallin et al. (2013) state that larger firms have a greater stakeholder network and hence encounter greater responsibility. The high stakeholder responsibility results in an increased pressure to evince a high CSP. Consequently, firm size is expected to affect CSP positively and is measured as the natural logarithm of total assets taken from the Orbis database. Board size is also integrated as a control variable because it is agreed with the argumentation of Hafsi and Turgut (2013) that a larger board might have more connecting points with its stakeholder environment. A larger board is therefore associated with an improved CSP (Clarkson, 1995; Hillman et al. 2001). Board size is a numerical variable measured as the number of directors on a board.
Firm performance is used as control variable when measuring the effect of board diversity on firms’ CSP (Bear et al., 2010; Harjoto et al., 2015; Ioannou and Serafeim, 2012; C. Post et al., 2011; Shaukat et al., 2016). Hillman and Keim (2001) and Waddock and Graves (1997) both find a positive relation between CSP and financial performance and Hafsi and Turgut (2013) state that the relation is not clear yet. For this study, the return on assets (ROA) is used as financial performance indicator. It is defined as the ratio of net income to the book value of assets and provides insights about the firm’s profitability (Adams et al. 2005).
20 Risk is likewise believed to have an influence on CSP. Campbell (2007) outlines that firms operating in very competitive industries try to be as cost efficient as possible and often accept to engage in irresponsible practices. I agree that risk-affine environments like very competitive industries can influence a firm’s CSP and follow Campbell’s (2007) approach to take the profit margin as proxy for risk.
CEO duality is as well taken into account as a control variable. Prado-Lorenzo and Garcia-Sanchez (2010) reason that CEO duality supports the enforcement of the CEOs personal interests and not those of the stakeholders. Post et al. (2011) agree with this statement and declare that irresponsible firm behaviour is more often found when CEO duality is present. Therefore, I use a dummy variable to control for CEO duality (0 = CEO is not the chairman of the board, 1 = CEO is the chairman of the board).
21 Table 1 Industry Classification
Dummy Variable ICB Industry Classification
1 Technology 2 Telecommunications 3 Health Care 4 Financials 5 Real Estate 6 Consumer Discretionary 7 Consumer Staples 8 Industrials 9 Basic Materials 10 Energy 11 Utilities
3.3 Data Analysis
To measure the effect of board diversity on CSP, a regression analysis is identified as the appropriate statistical instrument. Furthermore, the presence of one continuous dependent variable and multiple independent variables (here: independent and control variables) which are either continuous or nominal specify the statistical method to be a multiple regression analysis. Before doing the analysis, it has to be checked whether the data is suitable for this specific method. Therefore, several tests are run, and it is found that heteroscedasticity is present. To solve this issue, the regression is done with robust standard errors. In addition, three outliers are found. Considering that the outliers present valid data and do not affect the coefficients, they nonetheless remain in the dataset (Full test procedure can be found in the appendix).
22 one independent variable each resulting in the following model 6 with the dependent variable explained by the control variables and all independent variables:
( ) = ( ) + ( ! "# ! " $) + (%& "# ! " $) + ' '(( " )" $ "# ! " $) + * *(+ ,! "# ! " $) + - -(."!/ "0 ) + 1 1(2 ! "0 ) + 3 3(."!/ !4 !/ ) + 5 5(6 ! ℎ 8 # ) / ) + 9 9(6" :) + ( ;< , )" $) + (= , !$) + >( !! ! !/).
3.4 Descriptive Statistics
23 categories. The minimum value of 0,00 implies that a board has been established at a certain point and all directors joined at the same time which could be due to an acquisition or similar activities. The average tenure diversity is 0,66 (SD 0,19).
Table 2 Descriptive Statistics
Variables N Minimum Maximum Mean SD
CSP 392 10,30 96,15 68,51 25,66
Gender Diversity 392 0,00 0,50 0,30 0,11
Age Diversity 392 0,15 0,76 0,59 0,10
Nationality Diversity 392 0,00 0,50 0,12 0,13
Tenure Diversity 392 0,00 0,82 0,66 0,19
Firm Size (log) 392 20,80 28,49 23,77 1,35
Board Size 392 4,00 20,00 11,03 2,01 Firm Performance 392 -85,80 48,78 4,81 8,58 R&D 392 0,00 122.569 2.050 8.118 Risk 392 -96,72 80,15 10,00 16,19 CEO Duality 392 0,00 1,00 0,65 0,48 Industries 392 1,00 11,00 6,44 2,56 Valid N (listwise) 392
24 shows an average value of 0,65 (SD 0,48). This means that there are still more companies where the chief executive officer is also the chairman of the board.
Table 3 shows the distribution of the companies over the 11 ICB industry categories. The smallest proportion of companies is active in the real estate industry and the largest proportion in the consumer discretionary industry.
Table 3 Sample distribution across 11 Industries
Industries Frequency Percent Cumulative
Technology 18 4,6 4,6 Telecommunications 10 2,6 7,1 Health Care 27 6,9 14,0 Financials 49 12,5 26,5 Real Estate 5 1,3 27,8 Consumer Discretionary 97 24,7 52,6 Consumer Staples 33 8,4 61,0 Industrials 83 21,2 82,1 Basic Materials 20 5,1 87,2 Energy 24 6,1 93,4 Utilities 26 6,6 100,0 Total 392 100,0
Table 4 shows Pearson’s zero-order correlation matrix which reveals information about the strength and direction of the linear relationships of the variables. The values vary between -1, a perfect negative linear relationship and +1 – a perfect positive linear relationship. The assigned p-value shows the significance of the relationship.
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Table 4 Pearson's Zero-Order Correlation
Variable 1 2 3 4 5 6 7 8 9 10 11 1 CSP 1,000 2 Gender Diversity ,349**** 1,000 3 Age Diversity -,127*** -,136*** 1,000 4 Nationality Diversity ,216**** ,059 ,052 1,000 5 Tenure Diversity ,298**** ,088** -,051 ,061 1,000
6 Firm Size (log) ,332**** ,260**** -,048 0,076* ,049 1,000
7 Firm Performance ,046 ,061 ,009 ,101** ,056 -,125*** 1,000
8 R&D ,217**** ,113** -,049 ,096** ,071* ,212**** ,034 1,000
9 Risk ,066* ,131*** ,005 ,074* ,029 ,294**** ,545**** ,054 1,000
10 CEO Duality ,154**** ,163**** -0,066* -,027 ,051 ,198**** ,070* ,071* ,131*** 1,000
11 Board Size ,338**** ,198**** ,080* ,078* ,177**** ,446**** ,034 ,129*** ,229**** ,126*** 1,000
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4. RESULTS
To answer the hypotheses formulated in the theory part of this study, I conduct a stepwise multiple regression analysis with lagged variables. The independent and the control variables are from t-1 (2015) and the dependent variable from t (2016). Furthermore, six models are created for being able to separate the effects of the control variables from the effects of each independent variable on the dependent variable CSP. After meeting all assumptions tested in the preliminary analysis, table 5 presents the results for all six models of the main regression analysis. Each model contains the unstandardized coefficients, the standard errors and the associated significance level for each variable. In addition, the lower part of the table provides information about the explanatory power per model.
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Table 5 Stepwise Regression Analysis
Model 1 Model 2 Model 3 Model 4 Model 5 Model 6
B S.E. B S.E. B S.E. B S.E. B S.E. B S.E.
Independent Variables Gender Diversity 56,683**** 25,170 51,394**** 11,008 Age Diversity -34,282*** 12,061 -25,599** 11,090 Nationality Diversity 27,086*** 8,723 26,481**** 7,838 Tenure Diversity 26,957**** 7,038 24,321**** 7,126 Control Variables
Firm Size (log) 8,935**** 1,268 7,982**** 1,216 8,798**** 1,255 8,559**** 1,246 8,742**** 1,220 7,426**** 1,146
Firm Performance ,295 ,296 ,229 ,263 ,278 ,303 ,246 ,294 ,257 ,320 ,140 ,293 R&D ,000 ,001 ,000 ,000 ,000 ,000 ,000 ,001 ,000 ,001 ,000 ,000 Risk -,121 ,136 -,088 ,130 -,121 ,130 -,125 ,131 -,085 ,136 -,062 ,124 CEO Duality 2,168 2,501 ,709 2,466 1,693 2,457 2,780 2,473 1,751 2,424 ,712 2,323 Board Size 2,690**** ,703 2,437**** ,653 2,914**** ,712 2,631**** ,687 2,257*** ,688 2,178**** ,631 Constant -175,996**** 26,938 -166,800**** 25,170 -154,233**** 28,293 -169,804**** 26,458 -183,328**** 26,320 -151,969**** 25,500 R² ,347 ,397 ,364 ,366 ,381 ,454 Adjusted R² ,319 ,369 ,335 ,337 ,353 ,424 F-Test 15,234**** 21,523**** 15,785**** 15,850**** 16,783**** 23,129**** Number of Firms 392 392 392 392 392 392
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4.1 Hypotheses Testing
Hypothesis 1
Hypothesis 1 predicts a positive effect of board gender diversity on CSP. Consequently, the B is expected to be positive and significant. Considering model 2, this expectation is confirmed. The B-value of 56,683 is positive and significant p ≤ 0,001 and hence presents that an increase in board diversity leads to an increase of a firm’s CSP. Analysing the values of the gender diversity variable in model 6, it is observable that the coefficient decreased to 51,394 but is still positive and highly significant p ≤ 0,001. Taken together, hypothesis 1 is found to be supported. Hypothesis 2
Hypothesis 2 is treating the aspect of director age diversity and anticipates that age diversity has a positive effect on CSP. This hypothesis is covered by model 3. Differing from the expectations, age diversity is significantly negative related to CSP B = -34,282, p ≤ 0,01. This means that a board which consists of directors of various age groups yields a negative effect on CSP. Comparing these results to the comprehensive model 6, the coefficient decreased B = -25,599 but stays negative and significant p ≤ 0,05. Due to the opposing results found by the regression, hypothesis 2 is rejected.
Hypothesis 3
30 Hypothesis 4
The fourth and last hypothesis discusses the topic board tenure diversity and assumes a positive effect of board tenure diversity on CSP. Heterogeneity in terms of board membership duration promises a vital distribution of experienced directors who know the company and new members who bring in new perspectives. Considering the tenure diversity B-values of model 5 in table 5, this is verified. Tenure diversity exhibits a B of 26,957 and is highly significant p ≤ 0,001. Moreover, this statement does not change when perceiving model 6. Tenure diversity shows a positive B-value 24,321 and is highly significant p ≤ 0,001. This results in the support of hypothesis 4.
Overall, the B- and significant-values of the independent variables and the control variables have the same tendencies throughout all six models and just slightly vary. The R² and the adjusted R² are very closely connected and show nearly the same effects with the addition of each new variable. The R² of model 6 is ,454 and the adjusted R² ,424 and it hence has a high explanatory power. The significance throughout all five models is also very high and stays at p = ,000 for 392 companies.
Table 6 Hypotheses overview
Hypothesis Expectation Result
H1 influences corporate social performance. Board gender diversity positively Confirmed
H2 influences corporate social performance. Board age diversity positively Rejected
H3 influences corporate social performance. Board nationality diversity positively Confirmed
31
4.2 Additional Analysis
Research can not deliver sufficient information about the time lag which exists for the effect of board diversity on CSP. For this reason, I conduct the analyses again for 2014 to check whether the effects stay the same or change (see appendix).
First of all, it is to mention that the main results of the stepwise regression analysis stay the same. All independent variables significantly influence CSP, whereas gender, nationality and tenure diversity show a positive effect and age diversity a negative one. The values of the control variables reveal an overall slightly different pattern compared to the 2015 sample. Likewise, the only two significant variables are firm size and board size whereas the latter is only significant in model 1. Noticeable is also the change of the risk variable from a negative influence in 2015 to a positive one in 2014 and the opposite pattern for firm performance. Firm performance affects CSP in 2015 positively and in 2014 negatively. Furthermore, other than in the 2015 sample, all control variables except firm size and board size change their signs to negative in model 6.
Taking a closer look at the independent variables, it is observable that the effects of the variables with a positive sign are stronger in 2015 than in 2014 but the negativity of age diversity increases with a 2-year lag. The B-value of board gender diversity increases from 47,534 in 2014 to 51,394 in 2015. Nationality diversity’s B rises from 21,675 in 2014 to 26,481 in 2015. Similarly, tenure diversity’s B-coefficient increases from 20,338 in 2014 to 24,321 in 2015. Age diversity is decreasing its negativity from -29,065 in 2014 to -25,599 in 2015.
32
4.3 Robustness Tests
To check the robustness of the results, I run the stepwise regression analysis again but with different measures. Instead of using Blau’s index of heterogeneity to calculate board diversity, I refer to other methods used in previous diversity research. Prado-Lorenzo and Garcia-Sanchez (2010) as well as Setó-Pamies (2015) use the percentage of women in a corporate board as gender diversity measure. This method does similarly apply to the nationality diversity dimension because it also has just two characteristics: American and Foreign. For board age and tenure diversity another method has to be used. To measure how diverse the board is in terms of those two aspects, I use the same method as Hafsi and Turgut (2013). They state that the coefficient of variation is a suitable measure of dispersion to calculate the diversity within a board. It is calculated by dividing the standard deviation by the mean. A board which has a tenure standard deviation of 9 and a tenure mean of 12 would thus have a coefficient of variation of 0,75 or formulated differently, 75 percent.
33 Considering the described findings, hypotheses 1, 3 and 4 are confirmed and hypothesis 2 rejected. The results of this final test and the previously executed analysis of the 2014 data confirm the findings from the main analysis which can hence be seen as robust.
5. DISCUSSION
This paper aims to contribute to the question how companies can increase their stakeholder management, or, more specifically, their CSP. There is a broad range of research which connects economic factors with CSP (e.g. Hillman and Keim, 2001), but also various attempts which evaluate how corporate governance mechanisms affect CSP (e.g. Hafsi and Turgut, 2013; Harjoto et al., 2015; Setó-Pamies, 2015). This study belongs to the latter research stream and investigates the effect of the composition of corporate boards in terms of demographic diversity on CSP. Therefore, four hypotheses are developed to answer the research question ‘What is the effect of board diversity on corporate social performance?’. This section aims to discuss the results of the quantitative analysis conducted and described in the previous sections and associates these with findings elaborated by other researchers. This leads to the ability to derive practical implications for companies and politics who both aim to improve CSP. Subsequently, limitations and opportunities for future research are carved out and a conclusion presents a final overview of the study and provides a comprehensive answer to the research question.
34 create a higher amount of accountability, show enhanced ethical behaviour and care more about firm related environmental issues. Ferreira (2015) highlights the higher independence of female directors compared to male directors of the company’s management. For this reason, more women on corporate boards can lead to a more critical appraisal of management’s actions and bear a higher possibility to uncover unethical stakeholder related behaviour. He concludes that ‘female directors are more likely to be tough monitors of CEOs.” (Ferreira, 2015: p. 108). Konrad et al. (2008) agree with this argumentation and add that criticism on tough issues raised by women is generally perceived in a more productive way. In addition, the robustness test which is analysing board gender diversity as the percentage of women in the board finds the same significant positive effect. Overall, it can be stated that the literature offers reasonable arguments which build a solid foundation for the significant positive influence of gender diversity on CSP found in my study. There is still no agreement reached in the debate about the influence of gender diversity on CSP, however, the findings of this study contribute to the debate by providing clear evidence that gender diversity influences CSP positively.
35 investigated sample and mention possible occurring communication problems within age diverse boards as cause for their results. The average in this sample is 62,78 and the standard deviation is 7,95. That means that most of the directors included in the study are part of two age groups and hence do also not show a high level of diversity. Veltrop et al. (2015) do not specifically study the effect of age diversity on CSP but do analyse the effect of demographic diversity, including age diversity, on team performance. Their results suggest, that perceived demographic faultlines lead to the building of different factions within teams and might be the cause for inefficient board functioning. This could be seen as an explanation for the rejection of hypothesis 2. Moreover, age diversity increasingly causes age discrimination which in turn negatively affects team performance (Kunze et al., 2011). Discrimination within the board caused by the variation of age might indeed explain the negative effect of age diversity. The maximum age in the sample is 92 and the minimum age 31. It is reasonable to believe that at least directors who are either rather old or rather young experience age discrimination in any form which then causes a decrease of board efficiency. Considering the argumentation above, it seems that age diversity is either negative because it is not very much pronounced in this sample or because it is indeed the case that the differences between young and old individuals are too big to reach consistent agreements and therefore impede efficient stakeholder management.
36 this research does not always find significant results. Hafsi and Turgut (2013) hypothesize that ethnic diversity affects CSP positively but do not find significance in their results. They still believe in the concept that nationality diversity, or in their case ethnic diversity, increases CSP and expect results comparable to gender diversity. Furthermore, they outline that the number of ethnic diverse board members is maybe just too small to efficiently reach an impact. Azmat and Rentschler (2017) analyse the influence of ethnic diversity in corporate boards on corporate responsibility and find that ethnic diversity can lead to a stronger connection between the companies and their stakeholders. This goes along with the expectations raised in the theory part of this study and helps to explain the findings. As nationality diversity in boards increases, they are more able to understand and anticipate the needs of their diverse stakeholder groups. Miller and del Carmen Triana (2009) think in the same direction and trace their positive results to the increased understanding of the firm’s stakeholder environment. Walt and Ingley (2003) already discuss that talent and ability is spread equally over all ethnic groups and recruiting people from diverse groups would hence not decrease the capabilities of boards but open its mindset towards new perspectives. The small proportion of foreign directors (7,43%) in the sample of this study might serve as an explanation for the lack of research in this field. For this reason, the significant positive results of this study are of even larger importance and provide sufficient evidence that board nationality diversity increases the ability to understand a corporation’s stakeholder environment.
37 significant findings clearly reveal that a board which consists of new and old members leads to a higher CSP. Hambrick (2007) does not deliver a direct answer why board tenure diversity affects CSP positively, but his assessment presents the insight that top managers with short tenures react more radical to changing environments than managers who are already longer positioned within the company. Carpenter et al. (2004) highlight the possible long-term relationships long tenured managers can establish with their environment. Both aspects taken together can constitute a possible reason for my findings. Directors who are not so long a part of the board might recognize stakeholder demands which kept unheard before and are eager to create change. Long tenured directors on the other hand, can have established long-term relationships with the firm’s stakeholder environment and hence being able to manage their demands efficiently. A board which combines these two characteristics seems most likely to have a high stakeholder management performance and thus a high CSP. Keeping this argumentation in mind, the results of this study are reasonable. The more heterogenous a board is in terms of director tenure, the higher is the firm’s CSP.
After discussing all occurred results, I am able to formulate an answer to the main research question. Because the influence of the investigated board diversity patterns is not uniform, the answer cannot be given in a general manner but has to be specified to the investigated director characteristics.
Board diversity affects corporate social performance. Gender diversity, nationality diversity and tenure diversity have a positive effect on CSP whereas age diversity has a negative
effect on CSP.
5.1 Implications
38 common diversity aspect gender influences CSP but also the factors director age, director nationality and director tenure. With giving an answer to the research question, I shed light into this interesting and important field and strive to engage other researchers and practitioners to evaluate the now given implications and implement these into their future strategies. In this section, I firstly outline the theoretical implications and afterwards evaluate which practical implications this study provides.
39 that each diversity aspect alone influences corporations’ CSP differently - differently in the strength of impact but also different in terms of positivity or negativity. Furthermore, it also highlights that these influences are impacted when merging in a comprehensive model. This implies that even though each characteristic has its own impact on CSP, their individual effects decrease when various characteristics are present in the same board.
Furthermore, despite the focus on diversity research, this study also contributes to the field of CSP research. Wood's (1991) highly used definition comprises company processes and concepts to enhance CSP. This study adds value to CSP research by stressing the importance of general corporate governance mechanisms apart from programs which are focused on an enhancement of CSP. Increasing board diversity can, apart from other impacts, be an instrument to enhance corporations’ CSP without integrating specific CSP promoting programs. Acknowledging this, CSP research can broaden its perspective and investigate structures and programs which might have an indirect influence on CSP and hence reveal new possibilities to promote sustainable companies.
40 al. (2010) mention the long duration of increasing board diversity in practice, examples like France show that it is possible to manage this process within a few years. They introduced a gender quota and the proportion of female directors rose from 8 percent in 2006 to 35 percent in 2015 (Zillman, 2017). Realizing the controversies about the introduction of quotas, these numbers should at least make politicians in the USA think about the elaboration of a strategy to increase the ratio of female directors from 20,22 percent in 2015 (this sample) towards greater gender heterogeneity in corporate boards in the future. Considering the findings of this paper in terms of nationality diversity in combination with the insights discovered by van Veen and Elbertsen (2008), it might also be necessary to restructure the institutionalized recruitment processes for directors to increase nationality diversity in boards. They find that the recruitment processes of institutional environments vary in their ability to employ foreign nationals. Changing recruitment structures which might prevent board diversity must hence be seen as a first step towards future heterogeneity in corporate boardrooms. Moreover, the findings of this study exhibit ways for corporations to increase investor attractiveness. ESG (Environmental, social and governance) – investing is becoming larger recently because more investors focus on sustainable companies to generate long-term profits while making a positive social impact instead of short-term profits through investments in firms showing irresponsible behaviour (Forbes, 2017). Acknowledging the results of this study, managers could be motivated to increase board diversity to attract new capital inflows.
5.2 Limitations and Opportunities for Future Research
41 recognize in their study, findings are hardly transferable to other environments. It cannot be stated that diversity would affect CSP the same in developing countries or even in Europe. Therefore, it can be determined that the study provides insights about a specific group of American corporations, but the findings are hard to generalise. This in turn offers room for future research. Scientists can either extent the scope of the study within the same environment by analysing smaller, or private firms, conduct research in another environment or go even a step further and make a comparative analysis. In addition, researcher could use panel-data to check for time dependent effects.
Another aspect of this study which can be identified as improvable is the dependent variable CSP and its measurement. Although CSP is a commonly used measurement of stakeholder management efficiency, there is still no consensus about the definition of CSP (Ioannou and Serafeim, 2012). This makes the term vague and creates a leeway for interpretation. Future research could invest effort in analysing the existing CSP definitions and create a term which is commonly accepted and hence increases the comparability of CSP studies. Besides the definition difficulties, the used measurement also leaves scope for optimization. The ESG ASSET 4 database is a comprehensive and accepted source in the research field but solely relies on publicly available company data. Ioannou and Serafeim (2012) remark that the CSP information published by the companies might not accurately reflect their organizational outcomes. This opens room for the eventuality that my research results could lose their validity and hence accentuates the need for more work improving the measurement of CSP.
42 in diverse boards compared to non-diverse boards could shed light upon the procedures and reasons which lead to an increased CSP of diverse boards.
Considering the results of this study and the research paper revised during the compilation process, board diversity and its effect on CSP requires a lot of future research to be understood in its whole complexity.
5.3 Conclusion
This study has the objective to shed light onto the relationship of corporate board diversity and CSP. This research field is barely discovered and comprehensive research approaches like the ones from Hafsi and Turgut (2013) and Harjoto et al. (2015) are rarely found. Even the effect of board gender diversity on CSP, the most common research stream, does not provide definite results yet. For this reason, I created the research question ‘What is the effect of board diversity on corporate social performance?’. To answer the initial question, I refer to stakeholder management theory, upper-echelons theory, board diversity literature and CSP research to subsequently create four hypotheses. The hypotheses focus on the effect the four director diversity characteristics – namely gender, age, nationality and board tenure – have on CSP. All hypotheses assume that higher diversity leads to higher CSP. It transpires that hypotheses 1, 3, and 4 are confirmed while hypothesis 2 is rejected.
Due to the highly significant results and the reasonable sample size, I am able to enhance the targeted research field by constituting that
board diversity does affect CSP. Board gender, nationality and tenure diversity influence CSP positively and age diversity negatively.
44
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