Corporate sustainability and firm’s financial
performance: home country heterogeneity,
industry competition and firm’s public visibility
by
TITUS WITTEVEEN
University of Groningen Faculty of Economics and Business MSc. International Business & Management
Table of Content
ABSTRACT... 3
INTRODUCTION... 3
THEORETICAL FRAMEWORK AND HYPOTHESES... 6
The CSP-CFP relationship 6
Varieties of Capitalism 8
Industry Competition 10
Firm’s Public Visibility 11
METHODOLOGY... 12
Sample and Data 12
Variables 12
Method 15
RESULTS... 19 Descriptive Statistics and Variable Correlations 19
Regression and Non-Parametric results 22
DISCUSSION AND CONCLUSIONS... 27
The CSP-CFP Relationship 27
The Moderating Effects on the CSP-CFP Relationship 29
Implications 30
Limitations and Directions for Future Research 31
ABSTRACT
This paper presents empirical evidence on the relationship between corporate sustainable performance (CSP), measured using the Dow Jones Sustainability Index, and corporate financial performance (CFP). The main goal of this paper is to examine whether the relationship between CSP and CFP is moderated by a firm’s home country heterogeneity, industry competition level, and firm’s public visibility. A sample of the 3211 largest firms of the S&P Global Broad Market IndexSM is used to analyze whether there exist a significant link between CSP and CFP and more importantly whether this relationship is moderated by the three previously mentioned variables. Preliminary results show that the varieties of capitalism variable significantly moderates the CSP-CFP relationship. These findings implicate that there is a clear positive relationship between membership of the DJSI and firm’s financial performance, measured using the ROA indicator, in coordinated- as well as liberal market economies. Furthermore, as expected, the findings show that the CSP as well as the positive CSP-CFP link is the strongest in coordinated market economies.
Keywords: Corporate Sustainability, Corporate Performance, Dow Jones Sustainability Index, Varieties of Capitalism, Competition, Visibility
INTRODUCTION
a “significant business issue for senior managers and board directors”. CSP has emerged as an inescapable priority for business leaders, especially since the myriad CSP ranking organizations received a considerable amount of publicity (Porter & Kramer, 2006)
Lourenço, Branco, Curto, and Eugénio (2012) elaborated on the different definitions and conceptualizations of sustainability arguing that “although other concepts have been proposed over the years to conceptualize business and society relations, such as corporate social responsibility (CSR), CS has become the concept used most widely to address these relationships”. Corporate sustainability can be considered as the firms’ incorporation of economic growth, environmental protection, and social equity simultaneously (Lourenço et al, 2012). In his article, ‘corporate social responsibility and corporate sustainability: separate pasts, common futures’, Montiel (2008) elaborated on both the differences and similarities of the terms corporate social responsibility and corporate sustainability. The following was concluded: “both CSR and CS aim to balance economic prosperity, social integrity, and environmental responsibility” (Montiel, 2008). Therefore, throughout this article, both the terms CSR and CS will be used interchangeably. This method is already used in the article of Lourenço et al (2012), stating the following: “these concepts are considered to address the same basic issues, in the sense that they all are about companies’ impacts on, relationships with, and responsibilities to, society”.
The results of academic research on the corporate sustainable performance (CSP) relationship with corporate financial performance (CFP), in general, present mixed results. A significant amount of research has been undertaken on the relationship between CSP and CFP, “findings of the majority of them indicate no clear tendency or a positive but weak correlation between the two” (Lourenço et al, 2012). Furthermore, Lourenço et al (2012) also states the following: “more recent research still provides mixed results, they argue that there is evidence for both a negative relation, no relation, and a positive relation”. On the other hand, the meta-analysis performed by Orlitzky, Schmidt, & Rynes (2003), which integrated 30 years of research on the CSP-CFP topic, indicates that “there is a positive association between CSP and CFP across industries and study contexts”.
link. First, the well-known distinction between liberal market economies (LME) and coordinated market economies (CME) developed by Hall and Soskice (2001) is expected to explain varieties in CSP and moderate its relationship to firms’ financial performance. This home country heterogeneity influence is caused by significant institutional differences between LMEs and CMEs: including regulation, taxes, importance of shareholders vs stakeholders, concern for reputational damage, and relationship with the government. Second, the level of competition within an industry, in which a firm is operating, is expected to influence the level of corporate sustainability as well as its influence on firm’s financial performance. It is proposed in previous literature that the level of industry competition can influence the corporate sustainable performance of firms (Campbell, 2007; Fernández-Kranz & Santalo, 2010). Next to this expected determining influence, the competition level is expected to moderate the CSP-CFP relationship. Third, a firm-specific factor, which is expected to influence the theoretical relationship presented in this paper, is the visibility of a firm. It is expected that both the positive as well as the negative consequences are reinforced through visibility; “firms that are more visible are likely to gain more as a results of enhanced legitimacy and reputation effects, or may also suffer damages to their reputation, for inadequate participation in CSR initiatives” (Udayasankar, 2008). Furthermore, another dimension on which this paper distinguishes itself from the majority of papers on CS is the use of the Dow Jones Sustainability Index (DJSI) as a proxy for the corporate sustainable performance. Using the DJSI as an indicator of CSP is a relative new concept in the international business literature on sustainability, which especially gained increased recognition in scientific literature during the previous decade (Fowler and Hope, 2007; Lo and Sheu, 2007; López, Garcia, & Rodriguez, 2007; Lourenço et al, 2012; Peng, Dashdeleg, & Chih, 2014; Robinson, Kleffner, & Bertels, 2011; Searcy & Elkhawas, 2012).
Preliminary results present the existence of a significant moderating influence of firm’s home country heterogeneity on the CSP-CFP relationship. The different influence of CSP on CFP in the two varieties of capitalism is as expected. Furthermore, a significant difference in average corporate sustainability exist when grouping firms along the home country heterogeneity and firm’s public visibility variables.
results of the paper are reported. The fourth and final section of this paper will discuss and conclude the results, together with providing the limitations and directions for future research.
THEORETICAL FRAMEWORK AND HYPOTHESES
This theoretical framework will devote attention to the already well-researched relationship between corporate sustainability and organizational performance, furthermore new theoretical insights will be provided by adding the following moderating variables to the theoretical model: varieties of capitalism, industry competition and firm’s public visibility.
As already mentioned, the concept of sustainability overlaps with several additional classifications which are also focusing on the social, environmental and economic behavior of firms. And as Montiel (2008) shows, corporate sustainability (CS) as well as corporate social responsibility (CSR) both strive to balance economic prosperity, social integrity, and environment responsibility. This means that different terms are used for referring to the same economic, social and environmental issues. As was already mentioned, the CSP-CFP relationship is a topic which has received considerable attention in recent literature. Before going deeper into the relationship between these two concepts, brief attention is devoted to the arguments which explain the CSP-CFP link on both the short- and long-term.
The CSP-CFP relationship
resources or increased expenses on for example training, safety, pollution prevention or recycling (López et al, 2007). On the other hand, short-term positive influences can include reputational benefits or stakeholder satisfaction. Sustainability can be one of the key marketing strategies than can increase competitiveness and performance (Lu et al, 2013). The positive relationship between sustainability in the short-term can be caused by improved consumers’ attitudes toward the company and its products (Sen & Bhattacharya, 2001). Although the above mentioned arguments mainly focus on the positive influence between CSP and CFP, an analysis of previous literature shows positive, negative and no significant results between the two concepts.
30 years of research (52 studies), performed by Orlitzky et al (2003) shows that “in general there is a positive association between CSP and CFP across industries and study contexts”.
As the above presented analysis suggest, the evidence for the relationship between corporate sustainable and corporate financial performance presents mixed results. However, one of the most recent meta-analysis (Orlitzky et al, 2003) shows that often a significant positive relationship exist between corporate sustainability and corporate financial performance. Especially when accounting indicators are used to measure corporate financial performance. Therefore it is expected that the relationship between CSP and CFP, using the DJSI and ROA as indicators for both variables, is positive. This leads to the following hypothesis:
Hypothesis 1: A higher corporate sustainable performance of a firm has a
positive influence on corporate financial performance
Varieties of Capitalism
The first identified moderating variable in the CSP-CFP relationship is one which is derived from a comparative political economy perspective. The distinction between Liberal Market Economies and Coordinated market economies, developed by Hall and Soskice (2001), is expected to moderate the CSP-CFP relationship. Furthermore, these two comparative business systems are also expected to differ significantly in the average corporate sustainable performance of firms. The varieties of capitalism approach classifies developed countries into liberal or coordinated market economies. The classifications are based on certain characteristics present within each individual market economy, subsequently these characteristics can describe the behavior of firms within each end of the spectrum. Firms from CMEs are commonly theorized to be more society oriented and therefore focusing on meeting a broad range of stakeholders’ needs, whereas firm from LMEs are more market oriented and especially focus on satisfying shareholders (Amaeshi & Amao, 2009).
social behavior of firms can be explained using the varieties of capitalism approach. Especially the reputational concern and the importance firms from CMEs devote to the relationships with actors in their network explains the importance of CSP in these type of economies. This is especially stressed by the original authors of the varieties of capitalism approach: “in CMEs, managerial incentives tend to reinforce the operation of business networks; long-term employment contracts and the emphasis firm-structure places on one’s ability to secure consensus for one’s projects leads managers to focus heavily on the maintenance of their reputations, while the relative unimportance of stock option schemes in managerial compensations leads them to focus less on profitability than their counterpart” (Hall & Soskice, 2001). When relating these findings to the concept of corporate sustainability, it is expected that firms from CMEs score higher on corporate sustainable performance and more importantly, that there is a strong CSP-CFP relationship present within this variety of capitalism. Firms from CMEs who have a high corporate sustainability score are expected to satisfy stakeholders and have a success relationship with the actors in their network. When focusing on the positive impact of corporate sustainability on financial performance (Dixon-Fowler et al, 2013; López et al, 2007; Orlitzky et al, 2003), it is expected that the CSP-CFP relationship is strong within CMEs through the reputational benefits and stakeholders satisfaction which sustainable firms experience.
Summarizing the influence of the varieties of capitalism approach on the CSP-CFP relationship, it is expected that firms incorporated in one of the two above mentioned ‘ends of the spectrum’ differ substantially in their corporate sustainable performance, and especially the influence this CSP practices on the financial performance. It is expected that the average DJSI scores in CMEs are significantly higher compared to these average DJSI scores in LMEs. Moreover, the relationship between CSP and CFP is expected to be stronger within coordinated market economies. This leads to the following hypothesis:
Hypothesis 2: The positive relation between corporate sustainable
performance and firms’ financial performance is stronger in Coordinated Market Economies compared to Liberal Market Economies.
Industry Competition
A firm’s industry characteristics can influence the relationship between corporate sustainability and its influence on firms’ financial performance (Schreck, 2011). An industry characteristic which has not received a lot of attention in the scientific literature on the CSP-CFP relationship is the level of industry competition. Several papers (Beliveau, Cottrill, & O’Neill, 1994; Campbell, 2007; Chih, Chih, & Chen, 2010; Fernández-Kranz & Santalo, 2010) already investigated the link between industry competition and the level of corporate sustainability itself. The general findings implicate that a higher level of competition leads to an increase in corporate sustainable performance. A higher level of competition in the marketplace results in less negative social impact and to greater positive social impact initiatives (Fernández-Kranz & Santalo, 2010). Zhang, Zhu, Yeu, & Zhu (2010) find that firms in competitive industries use social initiatives “as a marketing strategy to differentiate themselves from their competitors with the intent to establish firm reputation and create economic value for shareholders”. Campbell (2007) proposes that “under normal competitive conditions, where at least a modest profit is assured and firm survival per se is not at stake, firms are most likely to engage in socially responsible practices”. This means that in competitive industries, in general, a significant higher average sustainable performance is expected.
analysis. Despite the positive effect of the industry competition level on the CSP, it is expected that the industry level will negatively moderate the CSP-CFP relationship. It is likely that the positive effects of CSP on CFP, through i.e. reputational gains or stakeholder satisfaction, will be diminished in highly competitive industries. Because a higher level of competition will lead to a higher level of average CSP (Chih et al, 2010; Fernández-Kranz & Santalo, 2010; Zhang et al, 2010) the positive effects of CSP on CFP will not outweigh the negative consequences of acting sustainable (López et al, 2007; Lu et al, 2013; Sen & Bhattacharya). This leads to the following hypothesis:
Hypothesis 3: A higher level of competition negatively moderates the
positive relationship between corporate sustainable and firms financial performance
Firm’s Public Visibility
Another characteristic, in this case firm-specific, which influences the corporate sustainable performance and arguably moderate its relation with firm financial performance, is the level of firm’s public visibility. Puck, Rogers, & Mohr (2013) define a firm’s visibility as “the degree to which stakeholders, including consumer groups, unions, or the general public, are able to observe the particular firms activities in the location”. More visible firms face increased external control, this means that an increase in visibility leads to a higher level of social pressure for firms (Meznar & Nigh, 1995). “Stakeholders who are more informed concerning corporate actions are more likely to take action towards companies and, in consequence, more visible organizations are subject to greater levels of scrutiny by, and regulation from, their stakeholder constituencies” (Brammer & Millington, 2006). Therefore, as Arlow and Gannon (1982) find: “public visibility can influence the importance firms give to their sustainable performance”. This means that more visible firms will experience a higher amount of public resistance from stakeholders it the case of social, environment or economic misbehavior. Therefore, the sustainable score is expected to significantly differ along the visibility dimension. In other words, it can be expected that more visible firms score higher on corporate sustainable performance.
stronger for highly visible firms. This means that a positive moderating influence is expected from the firm’s visibility. This afore mentioned argument is based on the fact that when firms are rated as sustainable, highly public visible firms can more easily reach and convince a wider audience of their positive behavior and in this way more easily enhance financial performance through i.e. stakeholder satisfaction and reputational benefits (Dixon-Fowler et al, 2013). This leads to the following hypothesis:
Hypothesis 4: A higher level of firms’ public visibility leads to a stronger
positive relationship between corporate sustainable and firms’ financial performance.
METHODOLOGY Sample and Data
The empirical base of this study relies on the 3211 invited firms for the annual corporate sustainability assessment performed by RobecoSAM over the year 2012. This list of firms is labelled as the DJSI World Eligible Universe 2012. The DJSI World Eligible universe is derived from the assessment of the 2500 largest listed companies in terms of float adjusted capitalization in the S&P Global Broad Market IndexSM (DJSI World Guidebook, 2013). In addition, it consist of all current DJSI World components (as of end of December of the preceding year) with a float adjusted market capitalization above USD 500 million (DJSI World Guidebook, 2013). The DJSI World eligible 2012 existed out of a total of 3211 firms, these firms are therefore the focus of this empirical analysis. Out of these 3211 firms, for the year 2012, 465 firms are qualified for the DJSI sustainability yearbook 2013. These firms can be labelled as the sustainable firms over the year 2012. The DJSI World eligible 2012 list furthermore provided information on industry and country data for each firm individual firm. The Thomson Worldscope Database was used to collect the accounting as well as data for the additional variables used in the analysis.
Variables
Dependent variable. Previous literature, focusing on organizational performance in the
reflect organizational performance: ‘it would be difficult to justify the conclusion that CSR practices influence corporate performance if there were no differences in the most significant performance indicators (López et al, 2007). Furthermore, especially the paper by Orlitzky et al (2003) displays the common use of accounting data in the CSP-CFP relationship: out of the 52 analyzed studies on the CSP-CFP link, 34 studies used accounting data to measure the dependent variable. Out of these 32 studies using accounting data, 16 included the ‘return on assets’ (ROA) indicator in their measurement. Organization performance, in this paper the dependent variable, therefore will be measured using ROA as the performance indicator. The ROA of the year 2012 will be used to analyze whether there is a link between CSP and CFP. Although the ROA is taken from the same year which the main independent variable is reflecting, this does not per se means that only the short-term performance is analyzed. This because the biggest share of firms considered as sustainable over the year 2012 are already rated as sustainable in previous years.
an no more than 30% from this specific industry leader. Furthermore, RobecoSAM grants individual classifications to firms having a sustainability score within a certain percentage from the industry leader. Companies receive the RobecoSAM gold class award when their score is within 1% of the industry leader’s score. The RobecoSAM silver class is awarded to firms scoring within a range of 1% to 5% from the industry leader, additionally firms receive the bronze class award when their score deviates in the range of 5% to 10% from the industry leader. This means that next to being included in the DJSI yearbook 2013, firms can receive an additional award for having a sustainability score which falls within a specific range from the industry leader. This however, does not signifies that firms included in the DJSI yearbook 2013 automatically receive one of these additional classifications.
Moderating Variables. For the first moderating variable in the analysis, the distinction between liberal- and coordinated market economies, the specific countries are ranked by the original authors of this variety of capitalism approach. Six of the large OECD nations are classified as liberal market economies (the U.S., Britain, Canada, Ireland, Australia, New Zealand), whereas another 10 of the large OECD nations are classified as coordinated market economies (Germany, Japan, The Netherlands, Belgium, Norway, Sweden, Switzerland, Denmark, Finland, and Austria) (Hall & Soskice, 2001). Therefore, firms from these 16 countries are included in the analysis to measure the influence of the ‘varieties of capitalism’ variable.
small local private companies may not be competing with large national or international companies even if they operate in the same NAICS code” (Fernández-Kranz & Santalo, 2010). Still however, only competitive statistics are used for industries with a minimum of 20 firms present in the dataset. Although for the regression analyses the competition variable is included on the continuous HHI scale, a distinction in level of competition is made for analyzing the difference in sustainable performance. Consequently, for this test the whole sample is divided into two subsamples as comparable to Zhang et al (2010): firms operating in industries with HHI < 0.1 (competitive industries) and with HHI ≥ 0.1 (medium to low competition).
Baker, Power, and Weaver (1999) researched whether or not listing on the NYSE helps to increase a firm’s visibility and whether market capitalization, earnings growth, or both, affect visibility gains. They actually argue that it is not the listing itself that can explain visibility, it is however the market capitalization of a firm which reflects the visibility; ‘the regression analysis suggest that increases in firm visibility are primarily associated with increases in market capitalization, rather than listing (Baker et al, 1999). This shows that market capitalization can be a good proxy for measuring the firm-specific visibility. As with the competition variable, visibility is included in the regression on a continuous scale. For analyzing the difference in sustainable performance between highly visible and low to medium visible firms, the sample is divided into two groups. The largest ten percent of the sample, in terms of market capitalization, is considered as highly visible.
Furthermore, several relevant control factors in accordance with previous literature on the CSP-CFP topic (Garcia-Castro, Ariño, & Canela, 2010; López et al, 2007; Lourenço et al, 2012) are included in the analysis. To control for the influence of size (SIZE), firm’s total assets is used as the indicator. The total debt in percentage of total capital is used as a proxy for the risk (RISK) a firm is taking. Additional control factors include the total amount of employees (TEMP) and the size of the board (TBOA).
Method
To test the hypotheses, presented in the theoretical section of this paper, several multiple regression analysis will be performed. Table I presents the main variables used in the analyses of this paper, furthermore it also includes a brief description of each individual variable. Although the abbreviations of the variables are not always used in the tables, the do sometimes occur for lay-out purposes or when presenting the regression equations.
¹ This dummy variable only includes firms from the sample located in LMEs or CMEs
TABLE I Variable definitions
Variable name Variable description Source
Dependent variable
ROA Return on Assets, measured as the total net
income (in 1000 US $) in percentage of total assets (in 1000 US $)
Datastream (Worldscope)
Independent variable
DJSI Dummy variable, 0 if the firm is only included
in the DJSI world eligible universe and 1 if the firm belongs to the DJSI yearbook 2013
The Dow Jones Sustainability Yearbook 2013 Moderating variables
CME Dummy variable, 1 if the firm’s home country
is considered as a CME and 0 otherwise
Hall & Soskice (2001)
LME Dummy variable, 1 if the firm’s home country
is considered as a LME and 0 otherwise
Hall & Soskice (2001)
VOC¹ Dummy variable, 1 if the firm’s home country
is considered as a CME and 2 when considered as a LME
Hall & Soskice (2001)
COMP Competition, measured using the
Herfindahl-Hirschman Index. The lower the HHI, the higher the competition is within an industry.
Datastream (Worldscope)
COMP_DUMMY Competition dummy, 0 if the firm is operating
in a low/medium competitive industry (HHI ≥ 0.01) and 1 if the firm is operating in a
competitive industry (HHI < 0.01)
Datastream (Worldscope)
PVIS Visibility, measured using total market
capitalization as a proxy. The higher the market capitalization, the more visible the firm
Datastream (Worldscope)
PVIS_DUMMY Public visibility dummy, 0 if the firm scores
medium to low on public visibility and 1 if the firm scores high on public visibility (top 10%)
Datastream (Worldscope)
Control variables
SIZE Total assets in 1000 US $ Datastream
(Worldscope)
RISK Debt ratio, measured as the total debt in
percentage of the total capital of the firm
Datastream (Worldscope)
TEMP Total employees Datastream
(Worldscope)
TBOA Total board size Datastream
of this paper, it is also expected that firms differ significantly in their CSP when grouping them along the categorical values of the moderating variables. To test whether the different variables (VOC, COMP, and PVIS) explain the DJSI factor significantly, the difference in distribution along these dimensions will be analyzed using the non-parametric Mann Whitney U test. This means that after grouping each individual variable into two groups, the differences between the two are compared and checked for significance.
To investigate whether there is a direct link between the sustainable performance and the financial performance of firms, a multiple regression analysis is performed. For this multiple regression analysis an equation is used to analyze the CSP-CFP relationship. To recap, a firm is considered as having a sufficient sustainable performance when it is included in the DJSI yearbook 2013. The proposed model, as explained before, includes ROA as the dependent variable. The independent dummy variable distinguished firms on their inclusion in the DJSI yearbook 2013, firms receive a score of 1 if they are included in the DJSI list and 0 otherwise. Furthermore, the control variables used in the model are the total assets to control for size (SIZE), total employees (TEMP), debt to total capital/assets as risk (RISK), and the total board members of the firm (TBOA). This results in the first regression equation (1), presented below:
ROA = b1 + b2DJSI + b3SIZE + b4TEMP + b5RISK + b6TBOA + e (1)
To analyze whether the influence of corporate sustainable performance on corporate financial performance is moderated by the VOC variable, industry competition or firms’ public visibility, new multiple regressions equations are produced.
dummy variable CME receives the value 1 if the firm was located in a coordinated market economy in 2012, and 0 otherwise. In contrast, the dummy variable LME takes the value 1 if the firm was located in a liberal market economy in 2012. This results in equation 2, which is presented below:
ROA = b1 + b2DJSI + b3CME + b4LME + b5DJSI_CME + b6DJSI_LME
+ b7SIZE + b8TEMP + b9RISK + b10TBOA + e (2)
The moderating effect of industry competition is included in the same way as the ‘varieties of capitalism’ variable. As mentioned above, it is expected that the CSP-CFP relationship differs between firms operating in competitive industries and firms operating in industries where there is medium to low competition. In order to analyze whether the CSP-CSP relationship is moderated by the level of competition within an industry, again a new equation is produced (equation 3). Next to the individual influences of the DJSI and ‘Competition’ variables a new variable is created and included in regression equation: DJSI_COMP. This new variable is created by multiplying the variables DJSI and COMP. This results into regression equation 3, presented below:
ROA = b1 + b2DJSI + b3COMP + b4DJSI_COMP + b5SIZE + b6TEMP + b7RISK + b8TBOA + e (3)
The final moderating variable included in the analysis of this paper is the firm’s public visibility. The public visibility of firms is expected to significantly influence the corporate sustainable performance of firms and especially the influence of this CSP on firm’s financial performance. To analyze this moderating effect of visibility, again a new variable is created: DJSI_PVIS. This variable is a result of multiplying the PVIS with the DJSI variable, in this way the moderating effect of visibility on the CSP-CFP relationship can be tested. The new regression equation (4), which includes both the individual as well as the moderating influence of visibility, is displayed below:
ROA = b1 + b2DJSI + b3PVIS + b4DJSI_PVIS + b5SIZE + b6TEMP
To test whether a significant influence is present when differentiating the DJSI firms according to their RobecoSAM award scores, a fifth regression equation is created. For this analysis, the CSP-CFP relationship is analyzed using only firms included in the DJSI yearbook 2013. To recap, next to being included on the DJSI list, firms can receive an extra award only when their sustainability score falls within a specific range from the industry leader. Accordingly, firms are classified along four RobecoSAM distinctions: DJSI_Gold, DJSI_Silver, DJSI_Bronze and only DJSI. Dummy variables are created to test the individual influences of the three additional classifications. The DJSI_Gold variable receives the score 1 when it received a gold award from the RobecoSAM assessment and 0 otherwise. Similarly, the variable DJSI_Silver assumes the value 1 if the firm received a silver score and 0 otherwise. Finally, the DJSI_Bronze variable received the value 1 when the firm was awarded a bronze score and 0 otherwise. Including these individual variables in the multiple regression model, together with the control variables, results in the below presented regression equation (5):
ROA = b1 + b2DJSI_Gold + b3DJSI_Silver + b4DJSI_Bronze + b5SIZE + b6TEMP + b7RISK + b8TBOA + e (5)
RESULTS
Descriptive Statistics and Variable Correlations
firms mean and median are higher for the variables Visibility, Size, Risk, Total Employees, and Total Board Size. After having performed the Shapiro-Wilk test, of which the results are presented in table III included in appendix A, it can be assumed that all the variables used in the analysis are non-normally distributed. Therefore a non-parametric test is applied to test whether the observed differences between the two groups are significant. The Mann-Whitney
TABLE II Descriptive Statistics
Mean Median SD Min Max
All firms with data available for 2012 (n = 1931)
Return on Assets 5.071 4.072 5.272 -11.813 28.516 DJSI 0.172 0 0.378 0 1 CME 0.245 0 0.430 0 1 LME 0.475 0 0.500 0 1 Competition 0.054 0.040 0.043 0.015 0.257 Visibility 14967210.818 6795120 26723198.783 565335 389648100 Size 45420376.602 10477000 116594299.757 666507 1365813861 Risk 37.867 36.830 22.443 0.000 101.380 Total Employees 33243.965 14500 49969.664 97 364969
Total Board Size 10.835 11 3.055 5 21
DJSI 2012 firms (n = 333) Return on Assets 4.594 3.627 5.367 -11.802 25.313 CME 0.297 0 0.458 0 1 LME 0.411 0 0.493 0 1 Competition 0.054 0.040 0.041 0.015 .257 Visibility 27849366.111 14324971 37771127.693 937486 234062589 Size 95359875.583 24921977 197818228.915 933541 1365813861 Risk 42.413 39.340 21.897 0.000 94.530 Total Employees 58800.555 34916 67581.365 196 364969
Total Board size 11.832 12 3.167 5 21
Non_DJSI 2012 firms (n = 1598) Return on Assets 5.171 4.179 5.249 -11.813 28.516 CME 0.235 0 0.424 0 1 LME 0.488 0 0.500 0 1 Competition 0.055 0.040 0.044 0.015 0.257 Visibility 12282756.668 5902218.5 22904913.350 565335 389648100 Size 35013710.043 8863828 87551671.073 666507 932935000 Risk 36.920 36.185 22.446 0.000 101.380 Total Employees 27918.342 12217.500 43629.945 97 343000
U test shows that a significant (p ≤ 0.01) positive difference exist between the continuous variables, Visibility, Size, Risk, Total Employees, and Total Board Size. The results of the Mann-Whitney U test are presented in table IV which is included in appendix B. Several of these findings are consistent with previous literature focusing on corporate sustainability. Lourenço et al (2012), for example, find that the sustainable firms in their sample are significantly larger and more risk taking compared to the non-sustainable firms. Furthermore, a study focusing on the financial industry shows that larger firms more often engage in sustainable behavior (Chih et al, 2010). The descriptive statistics in the paper of Lo and Shue (2007) support these findings: the sustainable firms in there sample score higher on total assets as well as their debt to equity ratio. Additional descriptive information for this final sample, on e.g. industry and country data, is available in Table V included in appendix C.
Since the data is non-normally distributed and discrete as well as continuous data is used, the Spearman’s rank correlation coefficient is applied to show the individual correlation between the different variables. The results of this test are presented in Table VI. As can be observed, most of variables in the analysis significantly correlate with the main dependent
TABLE VI Correlation coefficients
ROA DJSI CME LME COMP PVIS SIZE RISK TEMP TBOA
ROA 1 - - - - DJSI -.042 1 - - - - CME -.138** .055* 1 - - - - - - - LME -.160** -.058* -.542** 1 - - - - - - Competition .264** .009 -.060** -.095** 1 - - - - - Visibility .147** .254** -.081** .035 -.039 1 - - - - Size -.473** .259** .070** -.146** -.338** .627** 1 - - - Risk -.417** .087** -.010 -.051* -.207** .044 .360** 1 - - Employees -.035 .248** .042 -.136** .162** .500** .458** .109** 1 - Board Size -.149** .155** .049* -.103** -.125** .318** .411** .173** .312** 1 ** p < 0.01 * p < 0.05
high, it is appropriate to test for multicollinearity. In all five regression models the variance inflation factor (VIF) scores were well below 10, this indicates that multicollinearity will not be a problem in the individual analyzes.
Regression and Non-Parametric Results
Table VII presents the multiple regression statistics for the first equation measuring the main CSP-CFP relationship, furthermore also the control variables are included in the analysis. Table VII displays the unstandardized regression coefficients as well as the individual p-value of the variables in relation to the dependent variable. Additionally, the number of observations, r-square, and the models significance level are included in the analysis. As can be concluded
TABLE VII
CSP-CFP relationship: regression coefficients and statistics
Variables B Sign Overall
Constant 9.504
DJSI .291 .336
Size -.00000005*** .000
Risk -.082*** .000
Total Employees .000001 .753
Total Board Size -.110*** .004
N 1931
R² .168
Model Significance .000
*** p < 0.01
Dependent variable: ROA
variables are found to have a negative and significant influence on the financial performance of firms. This means that firms which are larger, take more risk, and have more board members are associated with a lower financial performance measured in ROA. As mentioned earlier, the negative influence of size, risk and total board size is in accordance with previous literature using accounting performance indicators (Barnett & Salomon, 2012; Bromiley, 1991; López et al, 2007; Yermack, 1996).
The results of the non-parametric Mann-Whitney U test, applied to test whether significant differences exist in CSP between the three grouping variables (varieties of capitalism, industry competition, and firm’s public visibility), are presented in table VIII. As can be observed from this table, 474 firms from this sample are classified as CMEs while 917 firms can be considered as an LME according to Hall and Soskice (2001). Adding these CMEs and LMEs countries does not constitute for the complete dataset, this means that the total sample of 1931 firms also included countries which did not receive a CME or LME classification. Table VIII shows that a significant difference exist in corporate sustainable performance with the grouping variables VOC and PVIS. This means that, as expected, there is a significant difference in CSP when grouping firms according to the VOC and PVIS_DUMMY variable. In other words, when comparing the average sustainable
TABLE VIII
CSP differences; mean rank and significance level
Variable N Mean Rank Asymp. Sig.
Varieties of Capitalism 1 = 474 2 = 917 723.26 681.91 .005*** Competition dummy 0 = 185 1 = 1746 950.85 967.61 .552
Public Visibility dummy 0 = 1750
1 = 181
940.19 1215.57
.000***
*** p < 0.01
Although firms operating in competitive industries are also more often included in the DJSI, no significant difference is found between the two observed groups.
The summary statistics from the additional multiple regression equations (2, 3 & 4), designed to test the remaining hypotheses, are presented in table IX. The individual as well as the moderating variables, which are expected to interact with the CSP-CFP relationship, are
TABLE IX
CSP-CFP relationship: varieties of capitalism, industry competition level & firm public visibility. Regression coefficients and statistics
Independent and control variables Equation 2 Equation 3 Equation 4
Main variables Constant 9.661 9.140 9.323 DJSI -.709 (.189) .059 (904) -.180 (.610) CME -1.576 (.000) *** LME .317 (.270) DJSI_CME 1.705 (.024) ** DJSI_LME 1.460 (.035) ** Competition 4.353 (.124) DJSI_Competition 3.984 (.574) Visibility .000 (.000) *** DJSI_Visibility .000 (.291) Control Variables Size -.000 (.000) *** -.000 (.000) *** -.000(.000) *** Risk -.081 (.000) *** -.080 (.000) *** -.074 (.000) *** Total Employees .000 (.722)) .000 (.976) -.000 (.001) ***
Total Board Size -.105 (.003) *** -.103 (.008) *** -.136 (.000) ***
N 1931 1931 1931
Overall R² .190 .170 .207
Model Significance .000*** .000*** .000***
*** p < 0.01 ** p < 0.05
included in the table. Each individual regression model is highly significant with an R² score ranging from 0.170 to 0.207, as mentioned earlier these scores are comparable with existing literature on the CSP-CFP relationship. Furthermore, as can be observed, the control variables show similar results compared with the first regression model. As is in accordance with previous literature (Barnett & Salomon, 2012; Bromiley, 1991; López et al, 2007; Yermack, 1996), the control variables Size, Risk and Total Board Size have a significant negative influence on the performance of firms measured in ROA. This again shows that larger, risk taking, firms who have more board members are experiencing a lower financial performance in terms of ROA. Surprisingly, the Total Employees control variable shows a small significant negative effect in the fourth regression model. The regression results of equation two, with the varieties of capitalism as the moderating variable, show that for both the CMEs (1.705, p ≤ 0.05) as well as LMEs (1.460, p ≤ 0.05) a significant positive influence is present. In other words, evidence is found for a significant positive moderating influence when including the two varieties of capitalism as control variables in the second regression model.
To analyze whether the hypothesized moderating effect is present, the individual influence of both varieties of capitalism moderators needs to be calculated. The analyses of the regression results for the second equation, testing hypothesis 2, are presented below.
CSP-CFP in CMEs
ROA = -.709*DJSI - 1.576*CME + 1.705*DJSI*CME CME = 1
ROA = -.709*DJSI – 1.576 + 1.705*DJSI
ROA = .996*DJSI – 1.576
CSP-CFP in LMEs
ROA = -.709*DJSI + .317*LME + 1.460*DJSI*LME
LME = 1
ROA = -.709*DJSI + .317 + 1.460*DJSI
ROA = .751*DJSI + .317
variable (DJSI_CME) on firms’ performance. The unstandardized regression coefficients of these individual variables are derived from Table VI. When firms are considered to be located in a CME, they receive a score of 1 (CME=1). After giving the CMEs a score of 1, the effect of the DJSI variable on firm’s performance can be calculated. This same method is applied to the CSP-CFP equation of firms from Liberal Market Economies. When comparing the two individual equations, it can be concluded that the moderating influence of the varieties of capitalism variable is as expected. The relationship between corporate sustainability and firm’s performance is stronger in Coordinated Market Economies (.996) compared to Liberal Market Economies (.751). This means that support is found for hypothesis 2, which argues that the influence of CSP on CFP is higher in CMEs compared to LMEs. When focusing on the control variables, the results again show a similar pattern compared with the first equation. Furthermore, although only the CME variable has a significant direct influence on firms accounting performance, the direct influence of the VOC variables are as expected. Firms from CMEs usually are associated with a negative performance (-1.576, p = 0.000) using accounting indicators, whereas firms from LMEs are associated with a positive performance (.317, p = .270). This is in accordance with previous literature (Hall & Soskice, 2001; Jones & Temouri, 2013) in which it is often argued that firms from CMEs are more stakeholder oriented, while firms from LMEs focus more on satisfying stakeholders which highly value positive accounting indicators.
As for the influence of competition as a moderating variable, a positive but non-significant influence (4.353, p =.124) is found. Therefore, competition does not have a significant moderating effect on the CSP-CFP relationship. This means that there is no significant support for hypothesis 3, arguing that the influence of CSP on CFP is significantly higher in more competitive industries.
When including the moderating effect of firm visibility in the CSP-CFP model, again no significant influence is found. Although there is a small positive effect (.000, p =.291), no significant evidence is found for the visibility moderator. This means that hypothesis 4 is not supported. Interestingly, there is a small positive direct influence between a higher visibility and an increase in financial performance.
1.423, p = .191; .383, p = 629). This shows that no significant different influence is found on the CSP-CFP relationship when distinguishing between different levels of sustainable performance.
TABLE X
DJSI distinctions and CFP: regression coefficients and statistics
Variables B Sign Overall
Constant 8.727 DJSI_Gold .404 .683 DJSI_Silver 1.423 .191 DJSI_Bronze .383 .629 Size -.000* .096 Risk -.083*** .000 Total Employees .000001 .829
Total Board Size -.082 .425
N 333 R² .136 Model Significance .000 *** p < 0.01 ** p < 0.05 * p < 0.10
Dependent variable: ROA
DISCUSSION AND CONCLUSIONS
performance indicators (Lo & Shue, 2007; Lourenço et al, 2012; Patten, 1990; Robinson et al, 2011). Especially the new insight from the influence of the three moderating variables contributed to the novelty of this paper. Furthermore, using the DJSI as an indicator of sustainable performance can be seen as a relative new and highly valued benchmark. The DJSI can be considered as one of the best sustainability indices employing a best in practice assessment approach, this high quality of the DJSI was especially reflected when it received the highest score out of 16 well-established rating organizations (Searcy & Elkhawas, 2012). Its importance is furthermore stressed with the fact that firms heavily signal their inclusion in the DJSI on their websites and in their annual reports.
The CSP-CFP Relationship
The Moderating Effects on the CSP-CFP Relationship
When, however, including the moderating effect of the varieties of capitalism approach, a significant effect is found between corporate sustainable and corporate financial performance in both the CMEs and LMEs. This means that for 1391 firms out of the final sample of 1931 firms, a significant CSP-CFP relationship is found. Before elaborating on the relationship between CSP and CFP in the two varieties of capitalism, the difference in average CSP scores are interesting. Evidence is found for a significant higher average corporate sustainable performance in CMEs. In other words, firms from CMEs are more often included in the DJSI compared to firms from LMEs. Arguably, this is in accordance with the expectations that firms from CMEs are more concerned with their reputation and network relationships (Hall & Soskice, 2001; Jones & Temouri, 2013) and therefore have a higher CSP.
More importantly, as was expected, the relationship between corporate sustainability and corporate financial performance is the strongest within CMEs in comparison to LMEs. This means that the argued positive effects of CSP (Dixon-Fowler et al, 2013; Orlitzky et al, 2003; Lu et al, 2013; Sen & Bhattacharya, 2001), such as reputational gains or stakeholder satisfaction, are especially present in CMEs and eventually lead to increased financial performance. Although firms from CMEs are associated with a lower accounting performance, a higher CSP has a positive influence on the CFP for these firms. Despite the effects of CSP on CFP are higher in CMEs, surprisingly there is also a positive CSP-CFP relationship present for firms located in LMEs. Next to the expected positive relationship between firms from LMEs and performance, sustainability also leads to improved financial performance in these liberal market economies. Although it was argued that in LMEs less value is attached to the sustainable behavior of firms, there is still a significant positive link between CSP and CFP. The significant lower average CSP performance of firms from LMEs can be an explanation for this surprisingly high positive effect. Because the average CSP is lower in LMEs, an increase in sustainability can more easily create reputational benefits or lead to higher stakeholder satisfaction. Stakeholders do not require firms located in LMEs to have a high CSP, however when they do show sustainable behavior it leads to increased accounting performance. Since the average sustainability score in LMEs is low, it is relatively easy for a firm to differentiate itself from competitors when implementing methods to increase sustainability. Adhering to the sustainability standards, even for firms located in LMEs, can therefore give firms an edge over competitors and lead to increased financial accounting performance.
visibility has no moderating influence on the CSP-CFP relationship for the biggest firms of the S&P Global Broad Market IndexSM. Additionally, no significant difference in CSP is found between highly competitive and medium or low competitive industries. Therefore, in this paper no significant evidence is found for the higher CSP performance in more competitive industries as argued in previous literature (Fernández-Kranz & Santalo, 2010; Zhang et al, 2010). The argument of Campbell (2007) can explain why no significant difference in CSP is found for the competition variable. Campbell (2007) proposes that ‘corporations will be less likely to act in socially responsible ways if there is either too much or too little competition. This means that firms which experience extreme competition will less likely show sustainable behavior. Also, the negative moderating effect of competition can be distorted since the CSP-CFP relationship of a firm depends, among others, on the sustainable behavior of competitors.
Despite the insignificant influence of visibility as a moderating variable, a significant difference is found in CSP when distinguishing between highly visible and medium/low visible firms. The higher the firm’s public visibility in terms of market capitalization, the more often firms are considered as performing sustainable. These results are consistent with the expectation of previous literature on the public visibility and corporate sustainability relationship (Arlow & Gannon, 1982; Brammer & Millington, 2006; Meznar & Nigh, 1995). These CSP differences can be a possible explanation for the insignificant moderating influence of visibility in the CSP-CFP relationship. Although more visible firms can more easily inform a wider audience of their increased sustainable performance (Udayasankar, 2008), the positive results through i.e. reputational gains or stakeholder satisfaction (Dixon-Fowler et al, 2013; López et al, 2007; Lu et al, 2013; Sen & Bhattacharaya, 2001) are diminished because their highly visible main competitors also are likely to have a high sustainable performance. Furthermore, the characteristics of the sample can be another possible explanation for the insignificant influence of the visibility moderator. The original sample, labelled as the DJSI World Eligible Universe 2012, exist exclusively out of the biggest listed firms in terms of float adjusted market capitalization. This means that the sample already exists out of relatively high visible firms, and therefore it can be an explanation why no evidence is found for the moderating effects of visibility.
Implications
to the existing literature by adding the varieties of capitalism approach to the CSP-CFP relationship. This implies that the results of this paper are especially relevant for business leaders operating in one of the sixteen countries with a liberal- or coordinated market economy. To recap, the liberal market economies included in the final sample consist of the United States, Britain, Canada, Ireland, Australia, and New Zealand. Whereas the coordinated market economies in the final sample exist out of Germany, Japan, the Netherlands, Belgium, Norway, Sweden, Switzerland, Denmark, Finland and Australia. An increase in corporate sustainable performance in one of the above mentioned countries leads to improved corporate financial performance measured using accounting indicators.
The findings of this study indicate that that the proposed negative financial consequences of sustainable behavior (López et al, 2007) are not present for the largest multinationals listed on the S&P Global Broad Market IndexSM. In fact, sustainable behavior leads to superior financial performance among these firms located in liberal- or coordinated market economies. Therefore, managers are able to satisfy stakeholders, by implementing sustainable behavior on both the social, environmental and economic dimensions, while at the same time being able to satisfy shareholders through increased financial performance.
Furthermore, the results show that a significant difference in CSP performance exist along the varieties of capitalism concept. Firms from LMEs are on average scoring significantly lower on their sustainable behavior; they are less often included in the DJSI. Since the results show that even in Liberal Market Economies a significant positive relationship exist between CSP and CFP, policy makers should stimulate and convince firms from LMEs to increase their CSP. This increase in CSP will, next to the positive developments on societal, environmental and economic aspects, lead to an increase in financial performance of the largest corporations and can therefore boost the economy as a whole.
Limitations and Directions for Future Research
multiple-year average ROA as a performance indicator for firms which are rated sustainable over these same years. This multiply-year performance measurement will most likely result in a stronger CSP-CFP relationship since previous literature especially stresses the long-term advantages of CSP on CFP (López et al, 2007; Lu et al, 2013).
Furthermore, the measurement of the visibility variable is considered as a limitation of this study. The first intention was to measure visibility using the Business to Business (B2B) or Business to consumer (B2C) distinction used by Puck et al (2013), or in some cases even the Business to Government (B2G) distinction. Measuring visibility with these previously mentioned description, however, was not feasible due to the extensive sample size. Furthermore, many firms from the DJSI World Eligible listcan be classified as doing business with both business as well as end-customers. Although the market capitalization of firms can be seen as a good alternative, the business defining distinctions would arguable results in a more appropriate reflection of firm’s visibility.
Another limitation of this study relates to a possible endogenous influence on the CSP-CFP relationship. Next to the argued endogeneity of social strategic decisions (Garcia-Castro et al, 2010), a loop of causality between the independent and dependent variables in this CSP-CFP relationship can lead to endogeneity. Firms with a higher return on assets can arguably have a higher sustainable performance due to a higher availability of financial resources. Therefore, future research on the CSP-CFP topic should account for endogeneity.
An interesting future research topic, building on the methodology of this study, concerns the moderating influence of competition. Although the use of Herfindahl-Hirschman Index for measuring the competition is supported in previous literature, future research should make additional distinction concerning the level of competition. Especially the proposed influence of competition on CSP according to Campbell (2007) can be a topic for future research. As was already mentioned, Campbell (2007) argues that firms which experience extreme competition are expected to have a lower average CSP. It can be expected that the CSP-CFP relationship is stronger in highly competitive industries, since the positive CSP effects (reputational gains or stakeholder satisfaction) will lead to a competitive advantage over competitors who are not able to show sustainable behavior. A possible future research topic includes the influence of competition on the CSP-CFP relationship while including this additional competition level.
Conclusions
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APPENDICES
Appendix A
TABLE III Testing for normality
Variable N Skewness Kurtosis Sig. (Shapiro Wilk)
Return on Assets 1931 0.892 2.042 .000*** DJSI 1931 1.735 1.013 .000*** CME 1931 1.184 -0.599 .000*** LME 1931 0.101 -1.992 .000*** Varieties of Capitalism 1391¹ -0.383 -1.500 .000*** Competition 1931 2.455 6.865 .000*** Competition dummy 1931 -2.749 5.561 .000*** Public Visibility 1931 5.515 42.960 .000***
Public Visibility dummy 1931 2.790 5.790 .000***
Size 1931 5.444 36.015 .000***
Risk 1931 0.280 -0.439 .000***
Total Employees 1931 3.092 11.698 .000***
Total Board Size 1931 0.707 0.545 .000***
*** p ≤ 0.01
Appendix B
TABLE IV
Difference between DJSI and Non_DJSI firms; mean rank and significance level
Variable N Mean rank Asymp. Sig.
Return on Assets 0 = 1598 1 = 333 976.721 914.554 0.064 * CME 0 = 1598 1 = 333 955.572 1016.041 0.016 ** LME 0 = 1598 1 = 333 978.770 904.718 0.011 ** Competition 0 = 1598 1 = 333 963.742 976.838 0.696 Public Visibility 0 = 1598 1 = 333 901.441 1275.805 0.000 *** Size 0 = 1598 1 = 333 900.097 1282.258 0.000 *** Risk 0 = 1598 1 = 333 943.864 1072.228 0.000 *** Total Employees 0 = 1598 1 = 333 902.988 1268.383 0.000 ***
Total Board size 0 = 1598
