CEO impact on Corporate Social Performance

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CEO impact on Corporate Social

Performance

Author: Frank Veldkamp (10445072) Supervisor: Dr. P. Vishwanathan

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STATEMENT OF ORIGINALITY

This document is written by student Frank Veldkamp 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.

ACKNOWLEDGEMENTS

I wish to acknowledge Dr. P. Vishwanathan, my research supervisor, for her advice and support during this project. Furthermore, I would like to thank my family and friends for their support and encouragement throughout my study.

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ABSTRACT

Scholars have increasingly examined the impact of corporate social responsibility (CSR) on firm outcomes the past decades. The way firms are led and the influence of its top executives on strategic decision making is extensively investigated. These two matters have been rarely combined. To fill this gap, this research focusses on the relationship between CEO demographics and the level of CSP a company engages in. The little research that has been done focused primarily on American firms and question were made if the results also applied to other parts of the world. Therefore, this study focusses on a sample of 93 European and 92 American firms to see if there are any differences in the relationship between CEO demographics and CSP. KLD’s CSP strength and concern ratings are used as a proxy for a firm’s CSR effort. I find that CEO demographics do not predict CSP levels for European firms. Gender and educational specialization do affect the level of CSP of American firms, as well as firm size and financial performance. CEOs with a degree in social sciences and humanities often attain higher CSP levels. As prior research was mainly focused on American firms, this study should be the beginning of Upper Echelon research in other parts of the world, for example Asia.

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INTRODUCTION

Corporate social responsibility (CSR) is becoming more important in a constantly changing world where resources are getting scarce and the environmental impact of firms is increasing due to globalization. Companies become more aware of their environment and try to exceed government and society expectations to go further than what is already expected by law (McWilliams & Siegel, 2000). They start to proactively include CSR practices in their overall strategy and try to add value to the company (Aguilera et al., 2007; McWilliams & Siegel, 2001).

Waldman et al. (2006) claim that there is not enough research on the actual influence of the management on CSR and that the role of corporate leaders in CSR decisions has been ignored. Some prior studies have concentrated on the influence of Chief Executive Officers (CEOs) on the corporate social performance (CSP) of a company (Huang, 2012; Manner, 2010). It was found that certain CEO demographics have an impact on consistency in CSP for a sample of US firms. They argued that results in other parts of the world may differ from their results in the US. As the most powerful actor of a firm, CEOs have a considerable impact on the decision making process and thus the implementation of CSR initiatives. The Upper Echelon Theory implies that strategic choices and performance levels that lead to an organizational outcome are to a certain extent predicted by managerial background characteristics. Characteristics such as age, tenure and educational background tend to play a role in the decisions made by top management and the outcome on firm performance (Hambrick & Mason, 1984).

This study will focus on the impact of CEO demographics on the level of CSP of a company and tries to contribute to existing literature in two ways. First, this could provide companies new insights into where to focus on when they have to appoint a new CEO if they want to excel in CSP. Second, this study will focus on European companies, in contrast to prior research on CEO demographics, which mainly focused on US companies. Hambrick (2007)

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states that there is still need to further examine the Upper Echelon Theory and the effects top executives have on organizational strategy and performance of non-American companies. To test the hypotheses, the 100 biggest European and 100 biggest American companies, according to revenue, will be taken into account. This study tries to answer if and which CEO demographics have an impact on CSP.

THEORY AND HYPOTHESES

Based on the research question, literature on CSR and CSP is examined to give an overview of the topic and to see in what ways it affects firm outcomes. In addition, the impact of CEOs on strategic decision making and the role of CEO demographics is examined. This leads to several hypotheses.

CSR and CSP

The idea of how to run a company has changed significantly in the past few years. Managers were blamed for their focus on shareholder value and profit maximization and companies started to recognize the importance of all-round growth. After the turn of the century, scandals like the Enron corruption scandal, the Nike labor conditions scandal and the Shell oil spill scandal, caused companies to attach greater value to its CSR efforts. As they noticed that both a decline in trust by investors and a decline in firm reputation had an impact on their financial performance, CSR became an important factor in strategic decision making. Since stakeholders often have different and conflicting preferences, scholars have difficulties finding a generally accepted description of CSR. Aguinis & Glavas (2012) claim that this is partly explained by the diverse research areas investigating CSR, using different frameworks and often small and divergent samples.

CSR could be defined as the continuing commitment of companies to act ethically, contribute to economic development and improve the quality of life of their employees, the

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local community and the society at large (Holme & Watts, 1999). The efforts of these companies go further than what is required by law and the companies pursue to do social good on a voluntary basis, instead of solely focusing on profits (McWilliams & Siegel, 2000). Carroll (1979) states that there are four groups of social responsibilities of a firm; economic, legal, ethical and discretionary. First a company has the responsibility to produce goods and services that are wanted by society. Laws and regulations give guidelines of how a company should operate within the market. Ethical responsibilities are additional actions that are not prescribed by law, but are expected by society in a certain way. Discretionary responsibilities are not expected by society, as companies are free to decide whether or not to implement them in their strategy. He argues that CSR has an economic aspect as well and companies need to perform well before they can take their responsibilities towards society. Aguilera et al. (2007) add that companies can use either reactive or proactive social change strategies. Previously, companies reacted on mistakes or scandals to save or recover trust and economic value. Proactive social change is seen more often lately, as companies apply the triple bottom line, where besides profitability, environmental sustainability and social performance are becoming more important. These companies are both influenced by internal and external actors, that keep on expecting improvements in their social performance.

Examples of CSR initiatives are pollution and waste reduction, supply chain improvements to reduce the ecological impact and supporting local businesses and (charity) initiatives. Whether or not a company sets CSR goals for themselves and which initiatives are implemented in their strategy differs a lot, as companies have to take into account the often conflicting demands of all the different stakeholders (McWilliams & Siegel, 2001).

CSR is considered to have several positive effects on firm performance and the way a company operates. One of the motivations to use CSR in the organizational strategy of a company is that it might boost corporate financial performance (CFP). Statistical research has

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been conducted on the CSR-CFP relationship to see if it adds value for companies and their managers. It was found that there is an overall positive relationship (Orlitzky, Schmidt & Rynes, 2003; Waddock & Graves, 1997). Another positive aspect of CSR is that it improves the overall corporate reputation of the company and therefore will attract more customers and please stakeholders. Companies become more attractive to invest in and to start partnerships with (Fombrun & Shanley, 1990). Furthermore, research suggest that employees and jobseekers are increasingly interested in CSR and have a stronger bond with or a preference for a company performing better on CSR. This will make it possible for companies to hire qualified workers and stay ahead of competitors (Turban & Greening, 1997). Luo & Bhattacharya (2006) state that consumers attach more value to products with CSR attributes or companies making use of CSR strategies. By using these strategies, they are able to create value and distinguish themselves from competitors. In this way, companies are able to differentiate and choose a certain amount of CSR activities, which best suits the company’s goals.

On the other hand, allocating resources to CSR activities increases costs for a company, without knowing if it will add value to the company. The money spent on CSR will influence the economic result and less money will be invested in the central role of the organization. Nevertheless, when a CSR strategy is implemented in a good way, it can be used as a differentiation strategy and this will create and add value to the company through competitive advantage (McWilliams & Siegel, 2001).

Since scholars have problems measuring CSR, CSP is often used as a variable to give an indication of the level of CSR engaged in by a company. Managers are struggling to find the social issues that matter the most for their company, as they can’t agree on what problems should be addressed (Carroll, 1979). CSP focusses on the measurable components of CSR in terms of environmental and social impact. Wood (1991, p. 693) describes CSP as: “the degree

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the degree to which the firm makes use of socially responsive processes, the existence and nature of policies and programs designed to manage the firm's societal relationships, and the social impacts (i.e., observable outcomes) of the firm's actions, programs, and policies.” CSP

focusses thus more on the observable actions and outcomes of using CSR in the organizational strategy.

The above review gives an explanation of CSR in general and shows what effect CSR might have on organizational strategy and firm outcomes. Most strategic decisions are made by top management executives. The decisions they make concerning overall strategy may differ between different CEOs (Hambrick & Mason, 1984).

CEO impact on strategy

Managers play an important role in the company’s differentiation strategy, as they are free to implement their own personal values along the process (McWilliams & Siegel, 2001). The decisions and strategic choices are often a reflection of beliefs and values of top management and the CEO is often the decision maker with the biggest influence. The CEO decides how and to what extent a company will make strategic decisions according to stakeholder preferences (Hambrick & Mason, 1984). This includes the decisions and the corporate strategy concerning CSR, as the CEO is the most important decision maker (Waldman et al., 2006).

According to stakeholder theory it depends on the manager if the stakeholder preferences are taken into account and that variation in demographics of the management often lead to different choices concerning the corporate strategy (Canella, Park & Lee, 2008). Freeman state that stakeholders are groups and individuals, that have a stake in the firm’s performance and are able to affect it. Top management has a contract with these stakeholders and makes the key decisions, hence serves as an important link between strategy and stakeholders (as cited in Jones, 1995). Jones (1995) adds that a company’s overall strategy often

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reflects the moral attitude of a firm’s top executives. Managers have an impact on the corporate culture of the firm, as their behavior will most likely be adopted by their subordinates. Decisions made regarding one stakeholder group might result in a cumulative effect on other stakeholder groups and firm reputation as well. Bad conditions for employees, for example, might cause discontent and a deteriorated reputation.

Hambrick & Mason (1984) mention that demographic data should be used to predict strategy and performance levels, as they are expected to be influential predictors. In their Upper Echelon Theory, they acknowledge that organizational strategies and outcomes are heavily influenced by its top executives and their characteristics and background. Past experience and own ideas determine the strategy that is chosen by the CEO, as well as answer different stakeholder demands (Hambrick, 2007). Therefore, it is likely that a CEO has a considerable contribution in defining overall strategy and thus a firm’s CSP level. Since ideologies and personal characteristics are difficult to measure and it would be difficult to compose a large sample, demographics are used in this study. Gender, age, tenure and educational specialization are expected to play a role in forming and adjusting the corporate strategy of a company (Godos-Díez, Fernández-Gago & Martínez-Campillo, 2011; Huang, 2013; Manner, 2010; Wiersema & Bantel, 1992). This study will build upon these findings and see whether these factors influence the level of CSP a company engages in.

CEO gender

An aspect that is not mentioned in Upper Echelon Theory is the influence of CEO gender on strategic decision making. Women are increasingly represented in top management teams and boards of directors, so it could give interesting insights in how their approach differ from men. Kahn & Vieito (2013) found that companies led by female CEOs are associated with better performance and a lower firm risk level, compared to companies led by male CEOs.

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Surprisingly they do get the same amount of risky stock options as part of their compensation. In social services companies, female CEOs were found to be more open to change than their male counterparts, but this needs to be examined in other contexts as well (Musteen, Barker III & Baeten, 2006). If female CEOs are more open to change, they might be more willing to use and try different CSR initiatives. Bear, Rahman & Post (2010) examined if the number of female board members influenced the CSP and found that a higher number of females in the board of directors both positively influences the CSP strength ratings and corporate reputation. All this considered, it is expected that the level of CSP is higher when a CEO is female.

H1: The level of CSP a company engages in is positively influenced by having a female CEO.

CEO age

The first proposition presented by Hambrick & Mason (1984) is age. They mention that age has not been used a lot to predict organizational outcomes, but that scholars who did use age as a proxy found that younger managers are associated with corporate growth. They also found that results of the related companies are less consistent and variations in sales and earnings are more common. Wiersema & Bantel (1992) expect that a higher average age of the top management teams has a negative effect on their willingness to change the corporate strategy. Managers also tend to be less convinced of their own abilities and easily adjust their behavior if they make a decision that was wrong. Their hypothesis that low age has an effect on strategic change is supported. Duarte (2010) found evidence in Brazil that suggests that commitment to sustainability issues vary among younger and older managers. Older managers are expected to be more conservative and are less likely including CSR initiatives. Later generations tend to see the opportunity to add value with CSR initiatives and the need to create a sustainable organization. Profit oriented managers have been succeeded by a younger generation with an

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emphasis more on ethical values. Godos-Díez, Fernández-Gago & Martínez-Campillo (2011) state that younger managers may have more interest in CSR and are more open to new ideas, but mentions that they might give priorities to personal growth. Therefore, companies are expected to have better CSP when their CEO is younger.

H2: The level of CSP a company engages in is positively influenced by having a younger CEO.

CEO tenure

Companies appointing CEOs with more prior functional experience and the ability to maintain a good relationship with stakeholders often have stronger CSP (Manner, 2010). However, CEOs tend to be less willing to make adaptive changes as tenure increases, as organizational inertia takes over (Hambrick, 2007). Miller (1991) found that long-tenured CEOs get stuck in a routine, as they take things for granted and like to keep the company stable. Due to this, CEOs fail to successfully match the strategy with environmental aspects, which eventually leads to worse financial performance as well. Long-tenured CEOs create a cooperating and cohesive entity with strict goals to maintain a certain momentum. The overall fit with stakeholders and the environment deteriorates, as the CEO is less able to gather and analyze information, due to overconfidence and the tendency of having the knowledge already. Wiersema & Bantel (1992) expected that lower tenure leads to CEOs that are more open to new initiatives and opinions from employees and other stakeholders. They found that a low average tenure in top management teams lead to strategic change. Overall it is reasonable to expect that managers become less suitable to react to a changing environment. Thus, for this study, it is expected that longer CEO tenure leads to weaker CSP.

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CEO educational specialization

Upper Echelon Theory implies that CEOs and their behavior are partly shaped by their educational background. It can provide interesting information about individuals and their norms and values concerning strategic decisions. Someone who studied engineering, often has different values than someone who studied law (Hambrick & Mason, 1984).

Wiersema & Bantel (1992, p.100) suggest that executives with a specialization in science and engineering are more inclined to act on changing circumstances, since they are concerned with “progress, invention, and improvement”. They found that a science specialization is positively related to being able to adjust the overall strategy. However, this might not hold for the CSR strategy, as this is often not included in a curriculum focused on science. Other scholars have found a positive relationship between having MBA degree and good corporate environmental performance (Slater & Dixon-Fowler, 2010). They found that business related degrees include ethics and sustainability, which leads to better involvement of CSR initiatives. As education forms someone’s personality and CSR is not really a part of science and engineering degrees, it is expected that CEOs with a background in management or other social sciences pursue better CSP.

H4: CEO educational specialization influences the level of CSP a company engages in, such that a CEO with a degree in Social Sciences and Humanities relates to better CSP, compared to a CEO with a degree in Science and Engineering.

Country of origin

Hambrick (2007) noted that research concentrating on the Upper Echelon Theory is mainly focused on American CEOs. There is a tendency to say that American CEOs are very

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homogeneous, but he claims the opposite and says that other countries might have more structured ways to form their CEOs, which leads to more similar CEOs. He further states that American CEOs are more discrete and that there is more space for them to shape the company, according to their own values and ideas. In addition, Manner (2010) thinks that CEOs in Europe might have an inferior role in comparison to the board of directors. Therefore, it is expected that European CEOs have less impact on overall strategy and thus CSP.

H5: CEO demographics are better indicators of the level of CSP a company engages in for American companies than for European companies.

DATA AND METHODS

In this section, a description of the data and sample selection process is given, the variables are explained and the research method is introduced.

Sample and data sources

Since Hambrick & Mason (1984) suggested that characteristics of top executives could be used as predictors of strategic decisions and performance levels, several scholars used demographics in their studies (Godos-Díez, Fernández-Gago & Martínez-Campillo, 2011; Wiersema & Bantel, 1992). The majority used a sample for their research consisting of solely US based companies. Several scholars suggested to investigate if their conclusions are valid in other parts of the world as well, to compare possible different outcomes (Hambrick, 2007; Manner, 2010). Therefore, this study will focus on the impact of CEO demographics on CSP for the 100 biggest European and 100 biggest American companies listed on a stock exchange. These companies are ordered by revenue to create a workable sample and to ensure the availability of data. To collect the financial data for the European companies, I used the OSIRIS database. This database gives comprehensive financial information about listed companies and provides

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financial data and ratios that are not available through other databases. Financial data from American companies is retrieved from the COMPUSTAT database. COMPUSTAT provides financial information of companies worldwide, but has a separated section for American companies. This data was matched with CSP data provided by MSCI Environmental, Social and Governance indices, which acquired the Kinder, Lyndenberg, Domini (KLD) database in 2010. After the two databases were combined, 93 out of 100 European companies and 92 out of 100 American companies were used for this study. The companies that were excluded had incomplete CSP data or were listed on more than one stock exchange. KLD rated the CSP of companies all over the world since 1991 and until 2013. From 2013 on they added a considerable amount of European companies to the database. Therefore, the financial and CSP data of European and American companies in 2013 are considered for this research. CEO data was collected from EXECUCOMP database, company websites and Bloomberg. EXECUCOMP, as a part of COMPUSTAT is a database that provides detailed information about top executives.

Measures

Dependent variable: CSP

CSP data will be collected by using the Kinder, Lydenberg, Domini (KLD) database. This is a research institute that concentrates on the corporate social performance of companies and consistently releases a rating every year. They rate the companies by making a distinction in seven main categories: community, corporate governance, diversity, employee relations, environment, human rights and product. The KLD database is frequently used in prior research concerning CSP and it is seen as very extensive, as it includes a lot of important measures and is rated by professional analysts, solely focusing on a company’s environmental performance (Manner, 2010; Waldman et al., 2006). Waddock & Graves (1997) stated that KLD focuses on

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a wide range of measures, such as annual reports, CSR reports and newspapers. They further acknowledge that KLD measures cover most important indicators of CSP and that they include more companies than any other database. KLD provides both strength and concern ratings on the seven main topics. Strength ratings resemble good CSP and concern ratings resemble bad CSP, where companies could improve on. For this study, the sum of both strength and concern ratings is used to measure a firm’s CSP.

Independent variables: gender, age, tenure and educational specialization

The independent variables used for this study are gender, age, tenure and educational specialization, as they were considered influential according to prior research (Godos-Díez, Fernández-Gago & Martínez-Campillo, 2011; Wiersema & Bantel, 1992). They often found a relationship between CEO demographics and strategic decision making, but did not made a link with CSP. Gender will be recorded as one for male and zero for female. Exact age is used, instead of forming groups, as this gives a precise approximation and groups might differ in size. Tenure is equal to the years an executive is active as the CEO of the company. For educational specialization, distinction is made between degrees in social sciences and humanities and degrees in science and engineering, using a dummy variable.

Control variables: size, risk and financial performance

To control for other variables that might influence CSP, this study includes firm size, firm risk and financial performance as control variables. According to prior research, these variables have an impact on CSP and are frequently used to control for (McWilliams & Siegel, 2000). Waddock & Graves (1997) found that bigger companies have often more money to spend and possible mistakes have a bigger impact. To control for firm size, I used the log of total assets. Firm risk is calculated as debt divided by total assets. As a proxy for financial performance,

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return on assets (ROA) is used, calculated as net income divided by total assets. Orlitzky et al. (2003) found that CSR practices and financial performance are positively related in two directions. Companies that perform better financially have more resources to increase CSP as well, and is thus added as control variable. The financial data to calculate the firm size, firm risk and financial performance are derived from OSIRIS and COMPUSTAT databases.

Methods

This study makes use of a multiple regression analysis to see whether there is a connection between the CEO of a company and its CSP and test the hypotheses by using CEO demographics. First a Pearson correlation matrix will be provided to give an indication of how the dependent and independent variables relate to each other.

ANALYSIS AND RESULTS

In this section, the output is analyzed and the results are provided. The descriptive statistics, a correlation matrix and the results of the regression analysis are given for further explanation.

Descriptive statistics

A presentation of the descriptive statistics is given in Table 1. Descriptives of dependent and independent variables are shown for the 93 European companies and for the 92 American companies separately.

Table 1. Descriptive statistics

Mean SD Max Min N Mean SD Max Min N

EU US CSP 5.87 3.36 12 -4 93 4.96 3.69 17 -6 92 Gender 0.98 0.15 1 0 93 0.91 0.28 1 0 92 Age 56.16 5.98 70 43 93 57.85 5.29 82 40 92 Tenure 6.14 5.69 37 1 93 5.79 5.17 34 1 92 Education 0.72 0.45 1 0 93 0.75 0.44 1 0 92 Size 7.87 0.53 9.35 6.88 93 7.89 0.55 9.38 6.68 92 Risk 25.04 12.92 53.04 0.15 93 21.90 16.27 98.42 0.04 92 ROA 4.27 5.07 24.14 -5.16 93 6.30 5.08 22.47 -4.34 92

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The descriptives show that European companies on average have better CSP, but that the variation between high and low levels of CSP is bigger for American companies, as their CSP scores range between 17 and -6 instead of 12 and -4. The amount of female CEOs is low in comparison to the large amount of male CEOs, especially for European companies (2% compared to 9%). CEO age is quite similar, but average age is higher in the US and the standard deviation is higher for EU. In the EU there are slightly more CEOs with a degree in science and engineering compared to the US, but differences are very small (28% compared to 25%). The descriptives regarding size are almost identical. Average firm risk in the EU (25.04%) is relatively higher than in the US (21.90%). The standard deviation of risk is high, indicating that there is considerable difference in the use of debt financing. Looking at the sample, US firms tend to perform better if ROA is considered as financial performance measure (6.30% compared to 4.27%). Overall, these descriptives show that there is enough spread to see whether these demographics influence CSP and the variables seem reliable to work with. One problem could be the small percentage of women in CEO positions.

Correlation matrix

Table 2. lists all the correlations and its significance for the measurement variables of both European and American companies. Correlations that are significant are labeled with a + at the 0.1 level, * at the 0.05 level and ** at the 0.01 level.

The correlation matrix shows that for European companies, CSP is not significantly correlated to CEO gender, age, tenure and education and neither to the control variables size, risk and ROA. Gender is negatively correlated to CSP, indicating that female CEOs do attain a higher CSP level (hypothesis 1), but this correlation is not significant. Age and tenure show a small positive correlation with CSP, in contrast to what is expected in hypotheses 2 and 3, but is not significant.

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Table 2. Correlation matrix

CSP GEN AGE TEN EDU SIZE RISK ROA

EU CSP Gender -0.094 (0.369) Age 0.132 (0.207) 0.028 (0.787) Tenure 0.086 (0.412) 0.043 (0.682) 0.405** (0.000) Education -0.081 (0.439) -0.092 (0.379) -0.207* (0.047) -0.163 (0.119) Size 0.155 (0.138) -0.144 (0.169) 0.206* (0.047) -0.043 (0.681) 0.196+ (0.060) Risk 0.152 (0.145 0.012 (0.910) 0.096 (0.361) 0.108 (0.302) -0.158 (0.131) 0.002 (0.981) ROA -0.031 (0.769) 0.081 (0.441) 0.014 (0.897) -0.071 (0.497) 0.054 (0.604) -0.256* (0.013) -0.098 (0.350) US CSP Gender -0.204+ (0.052) Age 0.092 (0.382) 0.020 (0.847) Tenure -0.018 (0.866) 0.123 (0.244) 0.437** (0.000) Education 0.336** (0.001) 0.000 (1.000) 0.141 (0.181) 0.050 (0.636) Size 0.227* (0.029) 0.055 (0.603) 0.026 (0.802) -0.014 (0.898) 0.157 (0.134) Risk -0.157 (0.135) 0.007 (0.949) 0.171 (0.103) 0.078 (0.462) -0.041 (0.697) -0.153 (0.145) ROA 0.102 (0.331) -0.069 (0.515) 0.051 (0.629) 0.165 (0.117) -0.142 (0.177) -0.263* (0.011) 0.102 (0.335) +_{P < 0.1, *P < 0.05, **P < 0.01}

CSP = Coporate social performance, ROA = Return on assets

The correlations for American companies show substantial differences. In the case of American companies, CSP is negatively correlated to gender (-0.204) with a p-value of 0.052. The table further indicates that there is a significant correlation between CSP and educational specialization and the control variable size. Educational specialization has a relatively high correlation and is very significant (p < 0.01).

The table further shows that age and tenure are correlated in both Europe and America, indicating that long-tenured CEOs are often older. Surprisingly, firm size and financial performance are negatively correlated, such that smaller companies perform better financially. To better understand these findings and before taking too strong assumptions a regression analysis is needed to answer the hypotheses.

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Regression analysis

Table 3. shows the regression results for the dependent variable CSP and the CEO demographics. The control variables firm size, firm risk and financial performance (ROA) are included in the model. Model 1 only includes the control variables. Model 6 is the complete model with all the independent variables included. Model 2-5 show the impact of all the independent variables separately, without the impact of the other variables. Finally, R2 and R2 change are taken into account to see how much of the variance in CSP they explain.

Table 3. Regression analysis

Dependent variable: CSP

EU Control

variables

Model 1 Model 2 Model 3 Model 4 Model 5 Model 6 Size 0.161 (0.136) 0.151 (0.166) 0.141 (0.203) 0.166 (0.126) 0.182 (0.100) 0.160 (0.177) Risk 0.155 (0.141) 0.156 (0.139) 0.145 (0.169) 0.147 (0.165) 0.140 (0.187) 0.133 (0.215) ROA 0.025 (0.814) 0.029 (0.787) 0.018 (0.867) 0.032 (0.770) 0.035 (0.749) 0.038 (0.736) Independent variables Gender -0.077 (0.466) -0.087 (0.414) Age 0.089 (0.407) 0.051 (0.680) Tenure 0.080 (0.448) 0.051 (0.662) Education -0.097 (0.371) -0.083 (0.464) R2 _0.048 _0.054 _0.055 _0.054 _0.056 _0.070 R2_change _0.006 _0.007 _0.006 _0.008 _0.022 US Control variables Size 0.254* (0.018) 0.263* (0.013) 0.248* (0.022) 0.256* (0.018) 0.213* (0.038) 0.219* (0.031) Risk -0.136 (0.187) -0.132 (0.192) -0.155 (0.142) -0.134 (0.198) -0.133 (0.175) -0.140 (0.153) ROA 0.183+ (0.085) 0.171 (0.102) 0.178+ (0.095) 0.189+ (0.081) 0.218* (0.032) 0.213* (0.037) Independent variables Gender -0.205* (0.042) -0.193* (0.047) Age 0.103 (0.321) 0.090 (0.408) Tenure -0.035 (0.736) -0.070 (0.516) Education 0.328** (0.001) 0.317** (0.002) R2 _0.098 _0.140 _0.108 _0.099 _0.202 _0.249 R2 _change _0.042 _0.010 _0.001 _0.104 _0.151 +_{P < 0.1, *P < 0.05, **P < 0.01}

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The regression analysis provides some interesting information. The regression analysis for European firms reveals that none of the control and independent variables have a significant impact on CSP. This is in line with the findings in the correlation matrix. When examining the R2_{and R}2_{change, the control variables in Model 1 only explain 4.8% of the variance in CSP.}

By adding the CEO demographics, there are only minor changes in R2 noticeable. Model 6 has a low R2 of 7%. Therefore, no support is found for hypotheses 1-4 if European companies are examined.

The regression analysis for American firms reveals other results. Both firm size (p < 0.05) and financial performance (p < 0.1) are considered to have a positive effect on CSP in Model 1, where only control variables are included. The control variables in Model 1 explain 9.8% of the variance in CSP. By adding the independent variables to the model, R2 increases by 0.151 to 0.249, indicating that 24.9% of the variance in CSP is explained by the included variables. Gender (p < 0.05) and educational specialization (p < 0.01) have a significant influence on CSP. According to hypothesis 1, female CEOs are expected to attain a higher CSP level. This hypothesis is supported if only American firms are considered (-0.193*). Hypothesis 4 is also supported, since the results show a positive relationship between having a degree in social sciences and humanities and CSP (0.317**). Both age and tenure are not significantly related to CSP. Model 2-5 give a clear view on their relative importance. By adding the independent variables separately, R2_{increases by 0.042 for gender, 0.010 for age, 0.001 for}

tenure and 0.104 for educational specialization. This confirms hypothesis 1 and 4, as they can serve as predictors for CSP.

DISCUSSION AND CONCLUSION

The goal of this study was to see whether CEO demographics have an impact on CSP. I examined data of 93 European companies and 92 American companies and used data from several databases, including KLD, OSIRIS and COMPUSTAT. Managers are expected to be

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influenced by their background and experiences and likely to become less open minded as they grow older and remain at the same company for a longer period of time. The results suggest that CEO demographics can be used to explain strategy and performance levels for American companies. Prior research found that CEOs are more inclined to implement strategic change when they are female, younger and have a shorter tenure. Some of these findings show similarities with the implementation of CSR initiatives. CEO gender and educational specialization are found to be related to a firm’s CSP level. This does not hold in Europe, as there was no significant relation between CEO demographics and the level of CSP for European companies. CEO age and tenure did not seem to have any impact on a firm’s level of CSP. Although gender was found to be influential, questions should be asked, since the sample contained few female CEOs. The results possibly imply that CEOs in the US have more impact on strategic decisions in comparison to Europe, since CEO demographics seem to have no influence on CSP. This might indicate that a CEO in Europe has to consult the other members of the board of directors before making a decision. This would be interesting for future research, as well as examining the impact of CEO demographics in other parts of the world like Asia for example. An interesting variable to add might be the work experience of the executive before he became CEO, as this might influence their values as well.

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CEO impact on Corporate Social Performance