Does organization life cycle moderate the relationship between
Corporate Social Performance (CSP) and Corporate Financial
Performance (CFP)?
Name: Mengmeng Wang Student number: 11623632
Thesis supervisor: Alexandros Sikalidis Date: August 19, 2018
Word count: 9731
MSc Accountancy & Control, specialization Control
Statement of Originality
This document is written by student Mengmeng Wang 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.
Abstract
This paper studies the correlation between Corporate Financial Performance and Corporate Social Performance and the moderating role of Organization Life cycle. According to dynamic resourced-based theory, I find a positive relationship between Corporate Financial Performance and Corporate Social Performance, more specifically an impact of Corporate Financial Performance on Corporate Social Performance. Then I examined the moderate role of Organization Life Cycle between the correlation between Corporate Financial Performance and Corporate Social Performance. Results showed that Size, Leverage, company’s financial performance play important roles of company’s engagement of Corporate Social Responsibility activities.
Contents
1 Introduction ... 5
2 Literature review and Hypothesis Development ... 8
2.1 Corporate Social Performance’s impact on Corporate Financial Performance ... 8
2.2 Corporate Financial Performance’s impact on Corporate Social Performance ... 11
2.3 The moderating role of Organization Life Cycle in CFP-CSP ... 14
3 Data and Method ... 17
3.1 Sample selection ... 17 3.2 Research Design ... 18 3.2.1 Dependent Variable ... 18 3.2.2 Independent Variables ... 19 3.2.3 Control Variables ... 20 3.2.4 Regression Models... 21 4 Results ... 22 4.1 Descriptive statistics ... 22
4.2 Association between CSP and CFP ... 24
4.3 Moderating Role of Organization Life Cycle ... 25
5 Conclusion and Discussion ... 28
1 Introduction
Corporate Social Responsibility (CSR) is a concept whereby companies integrate social and environmental concerns in their business operations and in their interaction with their stakeholders on a voluntary basis (Commission of the European Communities, 2001). Since Bowen (1953) firstly and formally defined Corporate Social Responsibility (CSR) in his book, CSR has been studied, applied and developed in both the practical area and academic area for a long period. Recently, firms (e.g. Dell, Microsoft, Apple, P&G, and Coca-Cola) published their CSR reports to disclose Corporate Social Responsibility activities to stakeholders (e.g. shareholders, customers and employees).
Prior research stated that, by doing so, firms can obtain competitive advantages, increase financial performance (e.g. sales, return on assets and stock price), increase non-financial performance (e.g. brand identification, customer loyalty and employee retention) and increase accountability and sustainability (Mcwilliams and Siegel 2010; Cochran, 1984; He & Li, 2010, Bhattacharya et al. 2008; Nevell, 2005; Kurucz et al. 2008). Therefore practically firms can use CSR activities to achieve their strategic goals. Although contradict findings about the correlation between Corporate Social Performance (CSP) and Corporate Financial Performance (CFP) can be found in the prior literatures (McWilliams & Siegel, 2000; Waddock & Graves, 1997; Wright & Ferris, 1997), Orlitzky et al. (2003) have conducted a meta-analysis integrating the 30 years of research about this correlation. In the research, Orlitzky proved that mixed findings are caused by statistical errors such as sampling error and measurement error. After correcting these errors, a positive correlation between Corporate Social Performance (CSP) and Corporate Financial Performance (CFP) is proved and confirmed. Based on this positive correlation, question has been raised into my mind- whether organizations’ CSR activities have different impact on CFP in their different organizational life cycle stages. More specifically, does the positive correlation between CSP and CFP still can be held when considering the moderating role of organizational life cycle? Does the impact of CFP on CSP have a different level based on organization’s different life cycle stages?
Researches on the moderating role of organization’s life cycle in the relationship of CSP and CFP cannot be found. However some researchers did mention in their literatures the importance to further study the role of organizational life cycle in the positive correlation between the CSP and CFP. McWilliams and Siegel (2001) stated that in different life cycle
4stages, amount of resources that organizations use to maximize its firm performance is different, in which organizations’ ability to conduct Corporate Social Responsibility (CSR) activities and its effectiveness might be different. Therefore, the impact of CSR activities might be different on the Corporate Financial Performance (CFP) on different life cycle stages. Also according to Jawahar and Gary (2001), in different organizational life cycle, there will be different stakeholder involvement, which makes firm’s demand for CSR various. In the context of the relationship between social market orientation and firm innovativeness (non-financial performance), the organizational life cycle negatively moderates the positive relationship (Dibrell et al, 2011). Following this finding, my research paper want to study the moderating role of the organizational life cycle in the relationship between the Corporate Social Performance (CSP) and Corporate Financial Performance (CFP).
Inspired by the conflict findings, this paper examines the impact of CFP on CSP. Combined slack resources theory and good management theory, it can be expected that when company has a good financial performance, it has more slack resources to conduct CSR activities and also have certain capability to manage these activities and gain a better Corporate Social Performance (CSP), while, when company has a poor financial performance, it has less slack resources to conduct CSR activities and also has less capability to manage this CSR activities and less possibility to gain a good Corporate Social Performance (CSP). And Called by Margolis et al. (2009), research of relationship between CSP-CFP should not only
concentrate on the impact of CSP on CFP but also emphasize the impact of CFP on CSP, and followed Waddock & Graves’s study (1997), I examine the impact of CFP on CSP (H1). Also combined organization life cycle theory and dynamic resourced-based theory, it can be expected that company in growth and mature stage would have a better CFP, more slack resources, more strong capability and a better CSP than company in other life cycle stages. And it also can be expected that the positive relation between CFP and CSP will be magnified in growth and mature stage. Called by Margolis et al. (2009), McWilliams and Siegel (2001) and Russo and Fouts (1997), Followed Hasan and Habib (2017), this paper studies whether organization lifecycle moderates the correlation between corporate financial performance (CFP) and corporate social performance (CSP)(H2).
This research has two contributions. First, it can further testify the positive correlation between CSP and CFP by test the reversal direction between CSP and CFP. Second, it fills the gap of research topic that organizational life cycle’s moderating role in this correlation.
Also the findings can contribute on a practical level, it helps to integrate the information that manager needs when considering management decisions related to CSR. Moreover it can help manager to consider CSR activities in a cost- benefit analysis when the firm in different life cycle stages.
2 Literature review and Hypothesis Development
2.1 Corporate Social Performance’s impact on Corporate Financial Performance
Corporate Social Performance (CSP) shows whether and how well a company conducts discretionary socially beneficial activity for different stakeholder groups, including customers, shareholders, employee, investors, and local community (Caroll, 1991). Those activities are called Corporate Social Responsibility (CSR) activities that defined as “context-specific organizational actions and policies that take into account stakeholders’ expectations and the triple bottom line of economic, social, and environmental performance.” (Rupp et al., 2010) For example, Corporate Social Responsibility (CSR) activity can be environment beneficial (less use of fertilizer to reduce the damage for soil), product quality optimized (project of biological vegetables and fruits), employee satisfaction increased (internal projects that improve working environment and employee welfare), and etc. Since companies can voluntarily conduct and disclose (though some countries are required) those socially beneficial activities, companies’ Corporate Social Performance (CSP) are various (Caroll, 2008).
Literatures have studied CSR from three levels-institutional levels, organizational level and individual level (Aguinis & Glavas, 2012). From institutional level, researchers try to study Scoot’s (1995) three pillars of institutions: normative, cultural-cognitive, and regulative elements. From organizational level, researchers try to study on a macro level about organization’s motivation, outcome and factors that can moderate the relationship between the CSR and its outcome. From individual level, researchers try to study on a micro level about the correlation between the firm and individual’s interest and value. And this paper will study from an organizational level to consider firms as a whole to have it’s own interest and motivation to make decisions on engagement of Corporate Social Responsibilities (CSR) activities.
According to traditional shareholder theory, company engage in socially beneficial activities only to maximize shareholder value (Moser and Martin, 2012; Friedman, 1970; Jansen, 2000). Therefore, it can be expected that the reason that company conduct Corporate Social Responsibility activity is they believe a good CSP can have a good impact on Company’s financial performance. And lots of literature has studied and tested whether this correlation is positive or negative (Barnett & Salomon, 2006; Dhaliwal et al. , 2012; Hillman & Keim,
2001; Hull & Rothenberg, 2008; Klassen & McLaughlin, 1996; Lev et al., 2010; McWilliams & Siegel, 2000; Orlitzky, Schmidt, & Rynes, 2003; Waddock & Graves, 1997; Wright & Ferris, 1997). Most of these literatures are studying the impact of Corporate Social Performance (CSP) on Corporate Financial Performance, and, based on the their results, most of these literatures find a positive correlation between Corporate Social performance (CSP) and Corporate Financial Performance (CFP) (Huang & Watson, 2015). For example, earlier study found a linkage between environment management and stock market’ performance, in which company that don’t have a strong environment management, for example a long-term goal on sustainability, can have a negative return on stock market (Klassen & McLaughlin, 1996). And later Dhaliwal et al. (2012) found that Corporate Social Responsibilities related activity could increase company’s reputation, which leads to an increase in sales and eventually improves company’s financial performance. And according to Waddock & Graves (1997), CFP depends on a good CSP, because a good CSP is usually related with a good managerial practice and a good managerial practice can help company improving financial performance. Also, Barnett & Salomon (2006) suggests company that has a good and close relationship with local community has a better financial performance than those doesn’t. Similarly, company’s philanthropy activity helps company to generate future revenue, especially for company that are highly sensitive to customer’ perception, because public donation and philanthropy activity are found to be helpful to increase customer’s satisfaction, and then help to improve Corporate Financial Performance (CFP) (Lev et al., 2010; Navarro, 1988; Greening and Turban, 2000). Moreover, when company has a good CSR engagement, customer tends to believe the good quality of its product and services, for example, little possibility of damaging products. Therefore, customers have an unintentional effect on their judgment of choosing brand and buying products (Freedman & Stagliano, 1991; Peloza, 2006).
However, for the second group of literatures, there is a contrary perspective holds by these scholars (Balotti and Hanks, 1999; Hillman & Keim, 2001; Elliott et al., 2013; Griffin and Mahon 1997; Margolis and Walsh 2001; Friedman1970; Levitt 1958; Jensen and Meckling, 1976). They find a negative relationship or non-significant relationship between CSP and CFP. Following the agency theory, they believe involvement of socially related activities might due to manager’s self-interest and as a cost of company and shareholder. For example, a manager might invest enormously on research and development of environmental-friendly technology, but the possible benefit from this action (less fuel costs for customer, higher
customer satisfaction and higher sales) might be lower than the initial investment and then decrease shareholder’s return. Hillman & Keim (2001) found that management’s investment on Corporate Social Performance is not positively correlated with shareholder’s wealth creation and that can be caused by managerial self-interests on participation in Corporate Social Responsibility activities, while as an agency costs for company, and also can be caused by a failure on stakeholder management, failed interaction with primary stakeholders. And earlier, Balotti and Hanks (1999) state that company philanthropy activities are possible to be abused due to lack of oversight, accountability and disclosure, which hinders company’s realization of their anticipated increased reputation and profit maximization. And results from Elliott et al. ’s experimental study (2013) show that there is a negative relation between Corporate Social Performance and firm’s fundamental value estimated by investors. In the experiment, investors’ estimates of fundamental value will be lower if investors have explicit assessment of CSP and found out a low score on CSP.
Given inconclusive results of CSP’s impact on CFP, Orlitzky et al. (2003) conduct a meta-analysis of 52 research papers of this topic, and they find a positive relation between CSP and CFP across a wide variety of industry. Company that have a higher CSP not only have a higher market-based return (e.g. price per share or share price appreciation) and but also accounting-based return (e.g. return on assets-ROA, return on equity-ROE, or earnings per share-EPS), which contradicts the findings of prior studies. For example, (Belkaoui & Karpik, 1989) found CSP most likely have an impact on market-based return, not on accounting-based return, because the impact of the disclosure of good or bad poor CSP can only be detected through the short-term market’ reaction while hard to be detected through a long-term accounting-based measures. Moreover, Orlitzky et al. (2003) found that CSP and CFP mutually affect each other through a virtuous cycle: financially successful companies invest more on CSP because they can afford it and manage it well, and in turn, CSP also helps them become a bit more successful.
And previous research papers that found a negative relation between CSP and CFP might contain sampling error, less validity on measures of variables, or fail to include necessary control variables. For example, research papers (Jones and Wicks, 1999; Pava and Krausz 1995) that find a negative relation between CSP and CFP also use survey measures of CFP and CSP, and those measure are less valid because of the high possibility of bias and artefactual errors. Similarly Margolis et al. (2009)’s meta-analysis also finds the significant positive correlation between CSP and CFP. Besides, size, organizational effectiveness,
consumer sensitivity, risks can moderate the correlation between CSP and CFP (Andrews 1987; Judge 1994). And they also suggest future researchers to identify unexplained and untested moderators (Orlitzky et al., 2003). Even though this positive correlation between CSP and CFP is steady and significant, most of prior literature emphasize on the mechanism of the direction CSP → CFP and less literature studied the reverse direction CFP → CSP (the impact of CFP on CSP). Called by Margolis et al. (2009), the future research should emphasis on reverse direction of causality and to study how CFP ultimately gives rise to CSP. And in what position, company can use its strong financial performance to engage in Corporate Social Responsibility activities and to gain a good CSP.
Therefore inspired by prior literature, this paper tries to study the impact of CFP on CSP and to further expand the knowledge of bidirectional relationship between CFP and CSP (details are explained in next section).
2.2 Corporate Financial Performance’s impact on Corporate Social Performance
Resources-based theory argues that company are different through their resources, including financial, physical, human capital, technological, reputation and organizational resources, and are different through how they use these resources to achieve certain performance, including Corporate Financial Performance (CFP) and Corporate Social Performance (CSP) (Barney, 1991; Grant, 1991; Hasan & Habib, 2017). Unlike those literatures discussed in the previous section, studying the CSP-CFP relationship, these literatures (Barney, 1991; Campbell, 2007; Preston & O’Bannon, 1997; Waddock & Graves, 1997) studied the impact of Corporate Financial Performance (CFP) on Corporate Social Performance (CSP). “One key issue for studies of CSR and financial performance to consider is reverse causality; that is, CSR is a product of financial performance” (Hong, Kubik, & Scheinkman, 2011).
According to Barney (1991), slack resources include assets, capabilities, organizational process, knowledge, etc. And these resources provide company opportunities to utilize them to set strategies, to achieve competitive advantages and to improve company’s performance. Also, based on slack resource theory, better financial performance can provide organizations slack resources, in which organizations can use those slack resources to conduct CSR
have more potential slack resources available, and with those slack resources, companies have more freedom to decide whether to invest CSR activities. Thus, it’s possible to expect that company with more slack resources will spend more on CSR activities and also
according to good management theory; those companies are more effective and efficient thus can also have a higher CSP in the end. This argument can be supported by Margolis et al. (2009), company’s financial performance can be an indicator of how good they manage their resources, and then further indicate how good they engage in their Corporate Social
Responsible (CSR) activities and how good their CSP is. Prior literatures have been studying this direction very early and emphasize the importance of lead-lag influence, which means the impact of prior Corporate Financial Performance (CFP) and Corporate Social
Performance. McGuire et al., (1988) find that company’s prior performance, measured by stock-market returns and ROA (return on assets) ROE (return on equity), is much more closely correlated with CSP than is subsequent performance. Preston & O’Bannon (1997) states that a company’s profitability allows the company to engage in CSR activities, and slack resources paly an important role in this relationship. For example, a less profitable company will spend less money on philanthropy, since this money can be used on other financial project that accelerate company’s growth and improve its financial performance (Campbell, 2007). Also Waddock & Graves (1997) find that company that have a good prior (CFP) are positively related to a good Corporate Social Performance (CSP), which suggests that company’s financial condition and slack resources can have an impact on its CSP. The dynamic resource-based view suggest that company’s ability to use its limited resources to generate revenue, to develop, and to improve its performance are varies and changing over time (Hasan & Habib, 2017). And slack resources theory argues that effectiveness of using these interchangeable resources is based on company’s development. And company’s Age, size and life cycle stages can also play a crucial role in the application of these resources (Wernerfelt, 1984). According to Hasan & Habib (2017), more mature company can utilize these resources more effectively and then achieve their competitive advantage. Also Hasan & Habib (2017) argue the dynamic resource-based theory together with the development of company can moderate company’s capability to apply its slack resources. Thus a company’s profitability, financial position, and maturity influence the initiative and outcome of one company’s engagement in CSR activities.
Also according to good management theory, company’s good management is closely related company’s Corporate Social Performance (CSP) bi-directionally (Waddock & Graves, 1997).
When a company manages its resources effectively, it would have more slack resources to use to engage in CSR activities. And engagement in CSR activities allows company to build a strong relationship with key stakeholders, which can lead to an improvement on overall performance. For example, company that conducting employee related CSR activities can have a close relationship with its employee, which can decrease information asymmetry and top level of company can understand the trouble, challenge, and potential improvement that can be made on the low level of daily business, and can increase employee productivity, morale and satisfaction (Waddock & Graves, 1997). Company that involved in local
community ‘s public-construction and development can apply and acquire certain tax-refund from government (Prahalad and Hamel, 1994). And according to McGuire et al. (1988), because CSR activities are highly related to managerial interests, the engagement of CSR activities depends on availability of slack resources and excess funds. Also, the line between good managementand better CSP are becoming blurry (Margolis & Walsh, 2003), since a well-managed company should also have a good stakeholder management, which needs CSR activities involved. However, some existing literatures suggest contrary findings (Hillman & Keim, 2001; Balotti and Hanks, 1999). They find when management decides company’s strategy; they handle not only the pressure from shareholder but also the pressure from government and regulator. Therefore, some CSR projects might benefit stakeholders while not shareholders. Also because of information asymmetry, less transparent disclosure, board of directors might only access to those CSR projects that are less expensive. Therefore, management’s self-interests are involved and also can affect company’s engagement of CSR activities.
Inspired by the conflict findings, this paper examines the impact of CFP on CSP. Combined slack resources theory and good management theory, it can be expected that when company has a good financial performance, it has more slack resources to conduct CSR activities and also have certain capability to manage these activities and gain a better Corporate Social Performance (CSP), while, when company has a poor financial performance, it has less slack resources to conduct CSR activities and also has less capability to manage this CSR activities and less possibility to gain a good Corporate Social Performance (CSP). And Called by Margolis et al. (2009), research of relationship between CSP-CFP should not only
concentrate on the impact of CSP on CFP but also emphasize the impact of CFP on CSP, and followed Waddock & Graves’s study (1997), this paper’s first hypothesis is:
H1: Better Corporate Financial Performance (CFP) results in better Corporate Social Performance (CSP).
2.3 The moderating role of Organization Life Cycle in CFP-CSP
According to Margolis et al. (2009), conflicting findings existed among research paper that study the relation between CFP and CSP can be caused by missing crucial moderating variables. Also McWilliams and Siegel (2001) and Russo and Fouts (1997) state that organization life cycle can place an important role of CSR engagement. While previous research suggests the role of organization life cycle in capital structure, risk appetite, and cost of capital (Fama & French, 200; Hasan et al., 2015; Hasan & Habib, 2017), little studies examine the possible impact of organization life cycle on the relationship between CFP and CSP.
According to Organizational life cycle theory, company in different life cycle stages would have capital and financial structure, different strategies, slack resources, capabilities and characteristics (Helfat & Peteraf, 2003; Bender & Ward, 1993), so it can be expected that their initiatives and capability to invest activities like CSR activities are various. And existing research find that company in growth and mature stage are less-constraint and more profitable (Dickinson, 2011; Habib & Hasan, 2015), while company in their introduction and decline stage has less slack resources, and they are more likely to invest more on activities that directly improve their capabilities and effectiveness to compete with other companies (Spence, 1981). Also according to dynamic resourced-based view, company in their early stage of organization life cycle is more likely lack of enough financial capital and non-financial capital (human capital and social capital) (Helfat & Peteraf, 2003). And company in introduction and decline stages face a lot of uncertainties, difficulty to generate cash flows and high possibilities of financial distress (Al-Hadi et al., 2017; Kim & Suh, 2009; Hasan et al., 2015). Also recent studies show that company’s financial position determines the initiatives of company to engage in CSR activities, and more profitability company has more slack resources and are more effectively using these resources on CSR activities (Clarkson et al., 2011; Cormier and Magnan, 1999; Reverte, 2009).
Therefore, it can be expected that these difference can influence company’s initiatives and capability to engage in CSR activities over the organization life cycle. Companies in introduction and decline life cycle stages are smaller and less profitable (Dickinson, 2011); generate financial capital mainly rely on debt market (Berger & Udell, 1998); they are less
likely to have sufficient slack resources to conduct CSR activities, without investing projects that have an directly impact on financial return (Artiach, 2010); and they are less likely to easily absorb the costs of CSR activities (Hasan & Habib, 2017); Therefore it can be expected that companies in their introduction and decline life cycle stages have less initiative to conduct CSR activities and are less capable to achieve a good CSP and CFP. Also company in their early life cycle stage is most likely to pursue a growth, to largely loan debts, and maintain enough resources to support its market expanding and reduce the possibility of financial disress, therefore less likely to engage in CSR activities (Ramaswamy et al., 2008; Al-Hadi et al., 2017).
Companies in growth and mature life cycle stages are larger, more profitable (Dickinson, 2011); generate their financial capital mainly rely on public market (Berger & Udell, 1998); their strategies, investment and retained earnings decisions are more closely related to key stakeholders (Hasan & Habib, 2017); they are more likely to have sufficient slack resources to invest in CSR activities and also have sufficient resources to invest in activities that directly affect financial returns (Artiach, 2010); more mature firms are more capable to absorb the costs of CSR activities and to acquire a long-term CSR return (Hasan & Habib, 2017); and they also have good capability management and face less possibility of financial distress(Ramaswamy et al., 2008; Al-Hadi et al., 2017). Therefore it can be expected that more mature companies are more profitable, better managed, sufficiently resourced and are capable to use their slack resources to achieve a better CSP.
Also Penrose (1959) argue that company’s slack resources and excess funds are crucial through company’s growth. And according to dynamic resourced-based theory, company would utilize its slack resources to achieve and maintain certain competitive advantages (Wernerfelt, 1984). And later Hong et al. (2011) find that less-constrained companies tend to invest more on Corporate Social Responsibility (CSR) activities, because those companies have better CFP, more slack resources to invest in CSR activities. More importantly, more mature companies concerned largely on its reputation and the close relationship with its primary stakeholders, therefore will more demand a CSP than less mature companies (Hasan & Habib, 2017). And the reason for companies in the early and decline life cycle stages less likely engaging in CSR activities is they are more concerned of survival and growth and return of CSR activities are risky and uncertain (Al-Hadi et al., 2017).
Therefore combined organization life cycle theory and dynamic resourced-based theory, it can be expected that company in growth and mature stage would have a better CFP, more
slack resources, more strong capability and a better CSP than company in other life cycle stages. And it also can be expected that the positive relation between CFP and CSP will be magnified in growth and mature stage. Called by Margolis et al. (2009), McWilliams and Siegel (2001) and Russo and Fouts (1997), Followed Hasan and Habib (2017), this paper studies whether organization lifecycle moderates the correlation between corporate financial performance (CFP) and corporate social performance (CSP). Hypothesis 2 is:
H2: More mature companies have a better CFP and also a better CSP than less mature companies.
3 Data and Method
3.1 Sample selection
I firstly have 43,131 firm-year observations from KLD database from 1991 to 2013, and lost 17,566 firm-year observations when I match these data with COMPUSTAT North America database. And then I dropped 12,308 observations that refer to financial company (two-digit sic code 48 and 49) and insurance company (two-digit SIC code 60–69), which followed prior study (Hasan & Habib, 2017; ). In the end, after dropping 7,563 observations that miss variables needed data, the final sample consists of 5694 firm-year observations. Sample selection is presented in Table 1. Panel A. And Panel B describes the industry distribution, in which manufacturing companies (65.24%) dominate in my sample.
Table 1 Sample selection and distribution
Panel A Sample Selection Observations
CSR data from 1991 to 2013 from KLD
43,131
Less：
Merging with Compustat North America
(17,566)
Financial and insurance data
(12,308)
Firms with missing data
(7,563)
Final sample 5,694
Panel B: Industry distribution Observations Percent
Agriculture, Forestry, & Fishing 23 0.40%
Mining 75 1.32%
Construction 24 0.42%
Manufacturing 3,715 65.24%
Transportation & Public Utilities 184 3.23%
Wholesale Trade 164 2.88%
Retail Trade 514 9.03%
Services 973 17.09%
3.2 Research Design
In order to examines the relation between CFP and CSP, more specifically, the impact of CFP on CSP, I conduct a quantitatively research. To test H1, I regress CSP on the CFP, OLC and other control variables to examine the effect of Corporate Financial Performance,
Organizational Life cycle and other variables on Corporate Social Performance. To test H2, I regress CSP on the CFP, OLC, interaction terms-OLC*CFP and other control variables to examine the effect of Corporate Financial Performance, Organization Life Cycle and other control variables in different life cycle stages.
3.2.1 Dependent Variable
Corporate Social Performance (CSR) are depend variables in this paper. Followed by prior literature (Hasan & Habib, 2017; Al-Hadi et al., 2017), I choose KLD rates as the measure of CSP. KLD is Kinder, Lydenberg and Domini Research & Analytics, Inc., an independent company that evaluate companies’ social performance and scores companies based on performance of their CSP and the relation with different stakeholder groups. KLD’s score standard depends on 94 measurement items in 7 social dimensions, including community, diversity, employee relations, environment, corporate governance, human rights and product safety. In each measurement, KLD will score a ‘‘strength” and ‘‘concern” on companies’ performance. For example, KLD investigates a lot of sources to determine, whether the company has paid fines or penalties in this area, if there is, then KLD will score a “concern”, or whether the company has major strengths (e.g., strong eco policies for environment category) in this area, is there is, then KLD will score a “strength” (Waddock & Graves, 1997). And following the prior researches, I excluded corporate governance dimension, which is distinct from other dimension (Hasan & Habib, 2017; Kim et al., 2014).
CSR_NET is first dependent variable, which is the sum of net score of total six dimensions and calculated by total strengths minus total concerns in all six dimensions. Also, called by McGuire et al. (1988) and Waddock and Graves (1997), I use one-year lag score in the analysis be more precise on the specific direction of causality, since prior research calls for including the temporal analysis, which indicate the the impact of companies’ previous year’s financial performance on the subsequent social performance.
Also, following prior research (Hasan & Habib, 2017; Kim et al., 2014), I also create the second dependent variables CSR_IND that ranges from zero to one to facilitate comparison of CSR scores across year and calculated by:
CSR_INDi,t = (CSR_NETi,t – MIN.CSR_NETj,t) / (MAX.CSR_NETj,t – MIN.CSR_NETj,t )
Where i, j, t denote firm i, industry j (two-digit SIC codes) and year t, respectively. Moreover, MIN and MAX refer to the minimum and maximum CSR_NET for firm i’s industry in year t, respectively. Following prior studies (Hasan & Habib, 2017), I also use positive CSR scores (CSR_STR) and negative CSR scores (CSR_CON) as dependent variables in the regression analyses.
3.2.2 Independent Variables
Corporate Financial Performance
I have two market-based measures for Corporate Financial Performance. Firstly I use Tobin’Q (TBQ) as independent Variable, following (Lee & Grewal 2004; Rao et al., 2004), calculated by:
Tobin’Q (TBQ) = (Total Assets + Common shares outstanding * share price closed annually – Total Common Equity) / Total Assets
Secondly I use Liquid Assets / Total Assets (LID) to measure firms financial position, following (Yilmaz, 2013). According to Subramaniam et al. (2016), high liquidity means
Organization Life Cycle
Following prior research (Hasan & Habib, 2017; Al-Hadi et al., 2017), I also used two proxy to measure Organization Life Cycle (OLC). Firstly I usedDeAngelo et al.’s (2006) life cycle proxy, which is calculated by retained earnings-to-total assets (RE/TA); it indicates the level of the company is self-financing or reliant on external capital. A high RE/TA indicates a more mature or declining life cycle stage, while a low RE/TA indicates an introduction and growing life cycle stage (DeAngelo et al., 2006).
Second proxy I used is Dickinson’s (2011) life cycle proxy, which captures company’s different life cycle stages. And this proxy uses cash flows patterns to capture differences in a firms’ profitability, growth, and risk. Following Hasan and Habib’s (2017) study, I classify all observations into five groups, in which, each group indicates a life cycle stages. And classification is following cash flow pattern:
(1) Introduction: if OANCF < 0, IVNCF < 0 and FINCF > 0; (2) Growth: if OANCF > 0, IVNCF < 0 and FINCF > 0; (3) Mature: if OANCF > 0, IVNCF < 0 and FINCF < 0;
(4) Decline: if OANCF < 0, IVNCF > 0 and FINCF or ! 0; and
(5) Shake-out: the remaining firm years are classified into the shake-out stage.
Where OANCF is operating net cash flow; IVNCF is investment net cash flow; FINCF is financing net cash flow.
3.2.3 Control Variables
Following prior literature, I conclude five control variables that has been studied, examined and tested for likely influencing Companies’ CSR engagement.
SIZE is natural logarithm of total assets, which can be expected to be positively associated with CSR. According to Wu (2006), Larger firms more likely have more resources for CSR engagement and also a pressure to make CSR investments.
SLACK is measured by (cash and marketable securities) scaled by total assets, which can be expected to be positively associated with CSR. According to Jensen and Meckling (1976), a high SLACK indicates fewer resource constraints and more managerial discretional activities; and also indicates company’s capability to conduct CSR activities.
Leverage (LEV) is measured by total debt scaled by total assets, which can be expected to be negatively associated with CSR. According to Jensen and Meckling (1976), a high leverage means constraint in resources and with less managerial discretionary activities.
Firm Growth (MTB) is measured by market value of equity divided by the book value of equity, which can be expected to be positively associated with CSR (McWilliams & Siegel, 2001).
R&D intensity is measured as Research & Development Expense scaled by total assets, which can be expected to be positively associated with CSR (McWilliams & Siegel, 2000). A high R&D intensity indicates company is engaged a lot of product innovations, which is valued by customers, and indicates company well interact with stakeholders and indicates more engagement in CSR activities.
3.2.4 Regression Models
To test hypothesis 1, I develop the first regression model to test the correlation between Corporate Financial Performance (CFP) and Corporate Social Performance CSP.
Model 1
CSR = γ0 + γ1 OLC + γ2 TBQ + γ3 LID + γ4 SIZE + γ5 RDINT + γ6 MTB + γ7 LEV + γ8
SLACK + IND FE + YEAR FE + ε
In the above model 1, CSR denotes four measures including CSR_NET, CSR_IND, CSR_STR and CSR_CON, which first three measures can be expected to be positively and significantly associated with TBQ and LID and OLC (TBQ denotes Tobin’s Q; LID denotes liquidity ratio; OLC denotes RE/TA). In this model I only used DeAngelo et al.’s (2006) proxy. Also I controlled five variables, SIZE, R&D intensity, Firm growth (MTB), Leverage (LEV) and SLACK.
To test Hypothesis 2, I develop the second regression model to test interactive terms OLC * TBQ and OLC*LID (interaction between organization life cycle and corporate financial performance (CFP)) and standards controls used in Models 1. This can examine the effect of CFP, Organization Life Cycle and other controls on CSR and also in different organization life cycle stages.
Model 2
CSR = γ0 + γ1 OLC +γ2 OLC * TBQ +γ3 OLC * LID + γ4 TBQ + γ5 LID + γ6 SIZE + γ7
4 Results
4.1 Descriptive statistics
Table 2 provides the total and life cycle-wise descriptive statistics for all the variables used in the regression models. The average CSR_NET is 1.045, with a large standard deviation of 3.032 and median is 0, indicates a relatively balanced distribution of companies with negative and positive CSR engagement. The mean (median) CSR_IND is 0.372 (0.333). The mean for CSR strengths (CSR_STR) is higher than the mean for CSR concerns (CSR_CON). About half of observations in the sample are in Growth stage, while only 1.5% observations are in Mature stage and 30% observations are in introduction stages, which indicates there might be statistical errors. The life cycle-wise descriptive statistics show TBQ and LID are highest in the introduction stage while lowest in decline stages. And important things to be mentioned should be the high standard deviation of TBQ in introduction stages 6.613; the high standard deviation of RE/TA in introduction stages 10.306; the high standard deviation of LID in introduction stages 5.250; the high standard deviation of R&D in introduction stage and shake-out stage; the high standard deviation of MTB in all five life cycle stages. Overall, the descriptive statistics among CSR variables, SIZE, LID,SLACK, LEV consistent with prior literature (Hasan & Habib, 2017).
Table 2
Total and Life cycle-wise Descriptive Statistics
Variable Introduction Growth Mature Shake-out Decline Total
CSR_NET Mean -0.263 0.779 1.785 0.572 -0.102 1.045 Median -1.000 0.000 0.000 0.000 -1.000 0.000 SD 1.438 2.783 3.462 2.621 1.640 3.032 CSR_STR Mean 0.728 1.849 2.937 1.600 0.761 2.132 Median 0.000 1.000 1.000 1.000 0.000 1.000 SD 1.220 2.805 3.573 2.546 1.422 3.086 CSR_CON Mean 0.991 1.070 1.153 1.028 0.864 1.087 Median 1.000 1.000 1.000 1.000 1.000 1.000 SD 0.704 0.972 1.200 1.006 0.698 1.054 CSR_IND Mean 0.324 0.362 0.399 0.355 0.330 0.372 Median 0.296 0.333 0.333 0.333 0.296 0.333 SD 0.053 0.103 0.128 0.097 0.061 0.112 TBQ Mean 4.492 2.726 2.174 2.678 1.772 2.670 Median 3.005 1.923 1.716 1.857 1.511 1.855 SD 6.613 2.898 1.727 2.655 1.068 3.206 RE/TA Mean -2.462 -0.125 0.157 -1.529 -2.351 -0.502 Median -1.061 0.107 0.276 -0.292 -1.202 0.105 SD 10.306 0.990 0.715 4.192 3.464 4.004 SIZE Mean 4.953 6.711 7.419 5.986 5.403 6.690 Median 4.909 6.476 7.215 5.775 5.088 6.492 SD 1.447 1.715 1.861 1.948 1.622 1.960 LID Mean 3.185 1.785 1.297 2.626 2.818 1.871 Median 1.739 1.321 1.042 1.654 1.665 1.250 SD 5.250 1.795 1.046 3.496 5.641 2.684 R&D Mean 12.276 0.114 0.063 9.095 1.923 2.676 Median 0.421 0.053 0.020 0.173 0.277 0.050 SD 79.339 0.403 0.468 152.204 5.826 62.362 SLACK Mean 0.505 0.270 0.162 0.417 0.484 0.275 Median 0.540 0.217 0.115 0.405 0.491 0.192 SD 0.313 0.228 0.154 0.266 0.273 0.251 LEV Mean 0.142 0.154 0.164 0.140 0.181 0.155 Median 0.032 0.105 0.124 0.012 0.040 0.093 SD 0.225 0.169 0.180 0.243 0.343 0.196 MTB Mean 9.776 3.906 3.304 4.902 0.122 4.397 Median 3.786 2.714 2.439 2.246 1.622 2.582 SD 86.836 6.953 41.024 45.630 16.764 43.382 N 1764 2441 88 617 784 5694
4.2 Association between CSP and CFP
Table 3 presents the regression results for Model 1.
Coefficient for RE/TA (using the life cycle proxy of Dickinson (2011)) is negatively and partial significantly, implying the more mature firms are less engaged in CSR activities, which is not consistent with my previous expectation and one plausible explanations is that more mature firms are more financially stable and less like needs to conduct CSR activities to gain competitive advantage (Russo and Fouts, 1997).
Coefficient for TBQ is significant and positive with CSR_NET, CSR_IND, which support the hypothesis 1 and consistent with prior literature (Hasan & Habib, 2017) However, TBQ is negatively correlated with CSR_STR, which implies that more profitable company may conduct more on CSR activities while also can have a bad performance on them.
Coefficient for LID is negatively for CSR_STR, which implies that high liquidity company does have slack resources and does have capability to conduct CSR activities, while less possibility to have good Corporate Social Performance.
Coefficient for Size, Leverage, and R&D intensity are all-significant with CSR, which implies that company that are larger size, less leverage and high R&D intensity are much more likely to conduct CSR activities and more likely to gain a better Corporate Docial Performance, which is consistent with prior studies (Hasan & Habib, 2017).
Table 3
Regression results.
Corporate Social Performance (CSP) and Corporate Financial Performance (CFP)
CSR = γ0 + γ1 OLC + γ2 TBQ + γ3 LID + γ4 SIZE + γ5 RDINT + γ6 MTB + γ7 LEV + γ8
SLACK + IND FE + YEAR FE + ε (Model 1)
Variables CSR_NET CSR_IND CSR_STR CSR_CON
RE/TA -0.003 -0.013* -0.009*** 0 (-0.39) (-1.65) (-2.73) (-0.39) TBQ 0.100*** 0.091*** -0.008 0.004*** -7.9 -7.83 (-1.61) -7.9 LID 0.007 -0.005 -0.012** 0 -0.51 (-0.42) (-2.16) -0.51 SIZE 1.123*** 1.178*** 0.055*** 0.042*** -51.93 -58.97 -6.11 -51.93 R&D 0.894*** 0.743*** -0.151* 0.033*** -4.79 -4.31 (-1.96) -4.79 MTB 0 -0.001 0 0 (-0.85) (-1.05) (-0.30) (-0.85) LEV -1.005*** -1.166*** -0.161** -0.037*** (-6.57) (-8.26) (-2.54) (-6.57) SLACK -0.28 -0.322** -0.041 -0.01 (-1.62) (-2.01) (-0.58) (-1.62)
Year FE Yes Yes Yes Yes
Industry FE Yes Yes Yes Yes
N 5694 5694 5694 5694
Adj. R-squared 0.65 0.67 0.59 0.64
Notes: Variable definitions are in the Appendix A.
*** p < 0.01. ** p < 0.5. * p < 0.10.
4.3 Moderating Role of Organization Life Cycle
In table 4, we explore whether the positive correlation between CSP and CFP is various through different organization life cycle stages. Results in table 4 Panel A shows that coefficient for TBQ are positive and significant for CSR engagement through different organization life cycle stages except for mature stages. And one possible explanation is the low distribution of observations that are in mature stage. Therefore, the organization life cycle stages do explaining the variation in CSR activities.
And interactive coefficients OLC* TBP are only positive and significant for the total sample while not in each organization life cycle stage. But it still can suggest that these results generally suggest that a larger size allows firms to participate more in CSR-related activities. In Table 4
Panel B, after including the possible effect of organization life cycle, results still shows that only size positively and significantly related with CSR in all firm life cycle stages.
Results in tables 4 shows that Organization did not have an interaction effect between CFP and CSP.
Table 4 Panel A
Interaction Effect of Organization Life Cycle (OLC) between Corporate Social Performance (CSP) and Corporate Financial Performance (CFP)
CSR = γ0 + γ1 TBQ + γ2 LID + γ3 OLC * TBP + γ4OLC*LID + γ5 LID + γ6 SIZE + γ7 R&D + γ8 MTB + γ9 LEV + γ10 SLACK + IND FE + YEAR FE + ε
CSR_NET
Variables Introduction Growth Mature Shake-out Decline Total
TBQ 0.087*** 0.098*** 0.302 0.032** 0.116*** 0.117*** -3.20 -2.66 -0.76 -1.98 -3.62 -9.05 LID -0.093*** -0.081 -0.034 0.042** 0.028 -0.031* (-3.15) (-1.42) (-0.90) -2.26 -0.76 (-1.91) OLC*TBP 0.016 -0.032 -0.006 0.000 0.003 0.001*** -1.28 (-0.82) (-0.07) (-0.49) -1.05 -3.99 OLC*LID -0.113*** -0.018 -0.012 -0.010 -0.007 -0.023*** (-3.57) (-0.42) (-0.51) (-1.19) (-0.68) (-3.38) OLC 0.008 -0.002 0.120 0.020 -0.073* -0.083*** -0.11 (-0.01) -0.87 -0.61 (-1.93) (-4.02) SIZE 1.127*** 1.325*** 0.243 0.337*** 0.779*** 1.159*** -27.46 -34.03 -0.98 -5.05 -13.59 -52.14 R&D -0.035 -0.007 0.024 0.001 0.000 0.000 (-0.32) (-0.08) -0.77 -1.56 (-0.02) -0.34 MTB 0.002 0.000 0.001 0.000 0.001 0.000 -0.29 -0.09 -0.05 (-0.66) -0.49 (-0.81) LEV -1.913*** -1.373*** -0.010 -0.024 -0.122 -1.210*** (-5.30) (-4.27) (-0.02) (-0.09) (-0.40) (-7.79) SLACK 0.297 -0.100 0.218 -0.733*** -1.019** -0.383** -0.93 (-0.23) -0.16 (-2.64) (-2.30) (-2.18) Constant -7.185*** -8.700*** -0.219 -3.304** -0.476 -7.871*** (-7.15) (-3.24) (-0.07) (-2.55) (-0.25) (-3.12)
Year FE Yes Yes Yes Yes Yes Yes
Industry FE Yes Yes Yes Yes Yes Yes
N 1764 2441 88 617 784 5694
Adj. R-Squared 0.65 0.70 0.67 0.34 0.57 0.65
Notes: Variable definitions are in the Appendix A. *** p < 0.01.
** p < 0.5. * p < 0.10.
Table 4 (continued) Panel B
CSR_IND
Variables Introduction Growth Mature Shake-out Decline Total TBQ 0.003*** 0.004*** 0.011 0.001** 0.004*** 0.004*** -3.20 -2.66 -0.76 -1.98 -3.62 -9.05 LID -0.003*** -0.003 -0.001 0.002** 0.001 -0.001* (-3.15) (-1.42) (-0.90) -2.26 -0.76 (-1.91) OLC*TBP 0.001 -0.001 0.000 0.000 0.000 0.000*** -1.28 (-0.82) (-0.07) (-0.49) -1.05 -3.99 OLC*LID -0.004*** -0.001 0.000 0.000 0.000 -0.001*** (-3.57) (-0.42) (-0.51) (-1.19) (-0.68) (-3.38) OLC 0.000 0.000 0.004 0.001 -0.003* -0.003*** -0.11 (-0.01) -0.87 -0.61 (-1.93) (-4.02) SIZE 0.042*** 0.049*** 0.009 0.012*** 0.029*** 0.043*** -27.46 -34.03 -0.98 -5.05 -13.59 -52.14 R&D -0.001 0.000 0.001 0.000 0.000 0.000 (-0.32) (-0.08) -0.77 -1.56 (-0.02) -0.34 MTB 0.000 0.000 0.000 0.000 0.000 0.000 -0.29 -0.09 -0.05 (-0.66) -0.49 (-0.81) LEV -0.071*** -0.051*** 0.000 -0.001 -0.005 -0.045*** (-5.30) (-4.27) (-0.02) (-0.09) (-0.40) (-7.79) SLACK 0.011 -0.004 0.008 -0.027*** -0.038** -0.014** -0.93 (-0.23) -0.16 (-2.64) (-2.30) (-2.18) Constant 0.067* 0.011 0.325*** 0.211*** 0.316*** 0.042 -1.81 -0.11 -2.89 -4.39 -4.43 -0.45
Year FE Yes Yes Yes Yes Yes Yes
Industry FE Yes Yes Yes Yes Yes Yes
N 1764 2441 88 617 784 5694
Adj. R-Squared 0.65 0.70 0.67 0.34 0.57 0.65
Notes: Variable definitions are in the Appendix A. *** p < 0.01.
** p < 0.5. * p < 0.10.
5 Conclusion and Discussion
This paper studies the correlation between Corporate Financial Performance and Corporate Social Performance and the moderating role of Organization Life cycle. According to dynamic resourced-based theory, I find a positive relationship between Corporate Financial Performance and Corporate Social Performance, more specifically an impact of Corporate Financial Performance on Corporate Social Performance. One contribution can be it further examines the positive relation between CSP and CFP, and prove this relationship is bi-directional, in which a company have a better financial performance also are more likely to conduct CSR activities and gain a better CSP. An form another direction, a company that conduct CSR activities and gain a better CSP also help to improve financial performance. However, I tried to examine the moderate role of Organization Life Cycle between the correlation between Corporate Financial Performance and Corporate Social Performance. Results show that organization life cycle stages did not moderate the relationship.
Further, Results also showed that Size, Leverage, R&D intensity play important roles of company’s engagement of Corporate Social Responsibility activities.
Limitation of this study could be the not well-distributed sample for different life cycle stages, especially for mature stages.
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