Understanding CSR Champions: A Machine Learning Approach
In this paper, we study champions of corporate social responsibility (CSR) performance among the U.S. publicly traded firms and their common characteristics by utilizing machine learning algorithms to identify predictors of firms’ CSR activity. We contribute to the CSR and leadership determinants literature by introducing the first comprehensive framework for analyzing the factors associated with corporate engagement with socially responsible behaviors by grouping all relevant predictors into four broad categories: corporate governance, managerial incentives, leadership, and firm characteristics. We find that strong corporate governance characteristics, as manifested in board member heterogeneity and managerial incentives, are the top predictors of CSR performance. Our results suggest policy implications for providing incentives and fostering characteristics conducive to firms “doing good.”
