The Interplay between Sustainability Initiatives and Capital Structure Dynamics using Machine Learning and Shap Analysis: Are we there yet?

Abstract

This research explores the relationship between sustainability performance and capital structure in industrial and resources firms listed on the Johannesburg and London Stock Exchanges. The study leverages environmental, social, and governance factors to assess their influence on capital structure decisions using machine learning techniques, including Shapley additive explanations analysis. The findings reveal that traditional financial metrics, such as operating profit margin and total assets, are more significant predictors of capital structure than sustainability factors. While environmental, social, and governance factors play a role, their impact on capital structure is limited. The study highlights the importance of integrating sustainable practices with financial performance.