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Unpacking the Drivers of Corporate Social Performance: A Multilevel, Multistakeholder, and Multimethod Analysis

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Abstract

The question of what drives corporate social performance (CSP) has become a vital concern for many managers and researchers of large corporations. This study addresses this question by adopting a multilevel, multistakeholder, and multimethod approach to theorize and estimate the relative influence of macro (national business system and country), meso (industry), and micro (firm-level) factors on CSP. Applying three different methods of variance decomposition analysis to an international sample of 2060 large public companies over a time span of 5 years, our results show that firm-level factors explain the largest proportion of variance in aggregate CSP as well as CSP oriented toward communities, the natural environment, and employees. These results support our hypotheses according to which CSP is not primarily driven by macrolevel or mesolevel factors, except for shareholder-oriented CSP, which is relatively more influenced by country-level factors. As a whole, our findings also point to the value of subdividing CSP into its stakeholder-specific components as this disaggregation allows for a more careful examination of distinct drivers of distinct aspects of CSP.

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Notes

  1. Strictly speaking, corporate social responsibility differs from corporate social performance (CSP). However, following previous arguments by Barnett (2007) and Baird et al. (2012), we prefer CSP for expositional purposes in this empirical study.

  2. The outcome variable of choice is profitability in strategic management where largely descriptive studies such as ours have, for 20 years, been aimed at explaining variance in firm profitability.

  3. The key point here is that managers anticipate appropriate economic rents from increasing CSP—not that these economic rents are necessarily forthcoming. Hence, we refer to appropriable rents in this context.

  4. On its website, Sustainalytics defines itself as “an award-winning global responsible investment research firm specialized in environmental, social and governance (ESG) research and analysis. The firm offers global perspectives and solutions that are underpinned by local expertise, serving both values-based and mainstream investors that integrate ESG information and assessments into their investment decisions” (source: Sustainalytics website, consulted on the 28/01/2015).

  5. The dataset was unbalanced because the number of firms in each NBS varied (see Table 5 in Appendix).

  6. For follow-up studies, HLM would also have the advantage of allowing for the inclusion of continuous—rather than only dummy/categorical—variables (Misangyi et al. 2006).

  7. The MLE HLM results were very similar to the findings obtained from the REMLE HLM.

  8. We are grateful to one of the reviewers for this interpretation. In line with this reviewer's feedback, the results may simply indicate that the domain of shareholder CSP is more institutionalized in the countries studied, and therefore firm agency is more limited here than in other CSP domains for this sample of firm-year observations.

  9. We are grateful to one of the reviewers for these points.

  10. These supplementary analyses are omitted from this paper, but available in another working paper available from the authors.

Abbreviations

ANOVA:

Analysis of variance

CSP:

Corporate social performance

HLM:

Hierarchical linear modeling

MLE:

Maximum likelihood estimation

NBS:

National business system

REMLE:

Restricted maximum likelihood estimation

VCA:

Variance components analysis

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Acknowledgments

We would like to thank Dutch Sustainability Research (DSR), the Benelux partner of SiRi Company for making their data available for this research as well as the support and assistance provided by Hans-Ulrich Beck, Research Director, DSR, in the course of this study.

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Authors and Affiliations

  1. Business School, The University of South Australia, GPO Box 2471, Adelaide, SA, 5001, Australia

    Marc Orlitzky

  2. Audencia Nantes School of Management, 8 Route de la Joneliere, B.P. 31222, 44312, Nantes Cedex 3, France

    Céline Louche

  3. Cass Business School, City University London, 106 Bunhill Row, London, EC1Y 8TZ, UK

    Jean-Pascal Gond

  4. International Centre for Corporate Social Responsibility (ICCSR), Nottingham University Business School, Wollaton Road, Nottingham, NG8 1BB, UK

    Wendy Chapple

Authors
  1. Marc Orlitzky
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  2. Céline Louche
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  3. Jean-Pascal Gond
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  4. Wendy Chapple
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Corresponding author

Correspondence to Marc Orlitzky.

Appendix

Appendix

See Tables 5 and 6.

Table 5 Sample size (n) and firm size across and within NBS clusters
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Table 6 Description and main components of SiRi’s CSR ratings
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Orlitzky, M., Louche, C., Gond, JP. et al. Unpacking the Drivers of Corporate Social Performance: A Multilevel, Multistakeholder, and Multimethod Analysis. J Bus Ethics 144, 21–40 (2017). https://doi.org/10.1007/s10551-015-2822-y

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