How Important Is Corporate Social Responsibility for Corporate Financial Performance? A Machine Learning Prediction and Model Interpretability Approach

Research output: Contribution to journalArticlepeer-review

1 Scopus citations

Abstract

Corporate social responsibility (CSR) has become central to corporate strategy, yet its impact on corporate financial performance (CFP) remains debated. Existing literature, which often relies on conventional statistical methods, overlooks the complex, nonlinear interactions between CSR and CFP. This study revisits the CSR-CFP relationship by analyzing CSR's contribution to predicting CFP and identifying the most influential CSR dimensions on financial outcomes using interpretable machine learning models, specifically Shapley Additive Explanations (SHAP). Based on data from the South African market (2015–2019), the results show that while CSR influences CFP, its impact is less strong than other factors, such as firm characteristics, shareholding structures, and board attributes. Among CSR dimensions, governance exerts the strongest effect on CFP, positively impacting market value but negatively affecting profitability. These findings challenge the assumption that robust CSR practices always correlate with financial success, emphasizing the need for a deeper understanding of CSR's role in CFP and considering competing organizational and financial factors.

Original languageEnglish
JournalBusiness Ethics, the Environment and Responsibility
DOIs
StateAccepted/In press - 2025

Keywords

  • corporate financial performance
  • corporate social responsibility
  • explainable artificial intelligence
  • interpretable machine learning
  • machine learning

Fingerprint

Dive into the research topics of 'How Important Is Corporate Social Responsibility for Corporate Financial Performance? A Machine Learning Prediction and Model Interpretability Approach'. Together they form a unique fingerprint.

Cite this