Addressing ESG rating divergence: A group decision-making approach with individual preferences

Reliable and transparent ESG (Environmental, Social, and Governance) ratings are a crucial instrument for governments, institutions, and individual investors to make value judgments and investment decisions. However, this criterion is subject to some criticism due to the observed inconsistencies in ESG ratings across different third-party rating agencies. Thus, this paper focuses on proposing a novel method to address the divergence in ESG ratings resulting from differences in weight vectors and individual preferences. In this paper, UW-TOPSIS is employed to obtain ESG ratings, eliminating the necessity for a priori weight vectors. Further, since UW-TOPSIS does not inherently account for individual preference heterogeneity, we introduce a group decision matrix incorporating individual preferences to compensate for its limitations. The proposed method is applied to the cases of Harvest Fund and Refinitiv, and Spearman's rank correlation coefficient analysis is employed to test the new ESG ratings. Results show that the new ESG ratings demonstrate a stronger correlation with ESG dimensions despite discrepancies in raw data from third-party rating agencies, indicating the proposed model is capable of accurately assessing the current ESG status of enterprises.