The impact of Corporate Social Responsibility on Firm Performance continues to attract the interest of researchers, policy makers and the community in general. This interest has motivated a considerable body of research examining the impact of Corporate Social Performance (CSP) on Corporate Financial Performance (CFP). Although many reviews of these studies have been published (Aldag & Bartol, 1978 ; Arlow & Gannon, 1982 ; Ullman, 1985 ; Griffin & Mahon, 1997 ; Roman, Haybor & Agle, 1999 ; Margolis & Walsh, 2003), there have been little attempts to use formal statistical tools to synthesize the results. Orlitsky, Schmidt & Rynes (2003) obviously made valuable contributions, presenting the first meta-analysis of the empirical evidence on the impact of CSP on firm financial performance. However, since this last meta-analytic review, dozens of studies examining the link between CSP and CFP have been published in academic journals and recent studies have also focused on the effect of CSP on CFP in a broader international context. In this paper, we provide a new meta-analytic synthesis of published research on the relationship between CSP and CFP and identify promising directions for future research. Unlike previous meta-analytic reviews, we employ a multivariate framework and regression analysis (known as meta-regression) using 373 observations from 82 studies.
Finally, our study makes multiple contributions beyond Orlitsky, Schmidt & Rynes (2003). First, our meta-analysis is based on a larger sample of published studies (82 vs 53), allowing better estimation of the population value for the relationship between CSP and CFP. Second, our study is the first to cumulate research findings for US and other countries, especially UK studies. The Orlitsky et al. (2003) study includes only US studies. Third, our meta-analysis cumulates also research findings for both social performance as a dependent variable and as an independent variable. The Orlitsky et al. (2003) study does not include all studies with CFP as a determinant of CSP even if their meta-analytic data set examined for temporal association and causality. We therefore sought to use all the knowledge created in the field to assess the slack resources theory. Fourth, while Orlitsky et al. (2003) used subgroup meta-analysis to evaluate potential moderation, we use meta-regression analysis to facilitate the identification of moderating effects, a significant contribution of our study. Finally, our use of up-to-date meta-analytic methods, especially Meta-Significance Testing (MST), facilitates the identification of selection and publication bias in this literature. An interesting issue that has never been addressed before in this field of research.
Specifically, the aims of our meta-analysis are to: (1) provide a statistical integration of the existing research on the relationship between CSP and firm financial performance; (2) assess the competing claims made about the impact of CSP on CFP; (3) examine the effect of moderators such as risk, size and industry; (4) assess the impact of measurement issues, such as the measurement of social and financial performances; (5) explore the sensitivity of empirical results across varying contexts (industries and countries) and time periods; and (6) investigate the presence of publication bias. It is well known that methodological, specification and data differences impact on empirical estimates. The issue is how to quantify that impact. Meta-analysis is a set of statistical techniques that has been developed to identify and quantify associations drawn from an existing body of literature (see Wolf, 1986; Hunter and Schmidt, 1990; and Stanley, 2001). Meta-analysis is based on a pronounced examination of differences in specification and data sets, and is used in this paper to quantify the impact these have on reported CSP-CFP effects.
The next section discusses the theory of CSP-CFP effects. This is followed by a discussion on the methodology used in section 2. The meta-analysis results are presented and discussed in section 3. We conclude the meta-analysis by discussing implications of the findings and directions for future research.