Prediction of corporate financial distress based on corporate social responsibility: New evidence from DANP, VWP and MEOWA weights methodologies

Abstract

This study investigates the determinants of financial distress from the corporate social responsibility (CSR) perspective and examines how poor CSR performance leads to financial distress in enterprises. Based on theoretical analysis, we select predictive indicators and construct an early warning indicator system for predicting financial distress from a CSR standpoint. Additionally, we develop a novel dynamic financial distress prediction (FDP) model using decision‐making trial and evaluation laboratory (DEMATEL)‐based analytic network process (DANP), variable weights with penalty (VWP), and maximal entropy ordered weighted average (MEOWA) weight methods to assess corporate financial status. Furthermore, to evaluate the accuracy of our model, we apply it to Chinese listed companies for empirical analysis using a sample of 1142 listed Chinese companies spanning 2011–2023. The results demonstrate that our developed FDP model exhibits higher predictive accuracy compared to previous models, suggesting that poor CSR practices can contribute to corporate financial distress while significantly enhancing FDP performance.