An ESG Assessment Approach with Multi-Agent Preference Differences: Based on Fuzzy Reasoning and Group Decision-Making

Abstract

The adoption of Environmental, Social, and Governance (ESG) to measure the green development, social responsibility, and public interest of companies is a commonly accepted theme and approach in the industry and academia at present. As ESG assessment is characterized by heterogeneity of subjects, complexity of contents, diversity of scales, and uncertainty of weights, it has led to the variability of ESG assessment results given by different assessment organizations in the same company, which has attracted a lot of criticism. This paper proposes a group decision-making method based on the preferences of multiple subjects to solve the problem of heterogeneity of subjects in ESG assessment. Specifically, for the given ESG evaluation data, the first step is to identify the preferences of subjects and structure the initial group matrix; secondly, the fuzzy inference system is employed to mine the hidden preference information; further, the initial group matrix is revised using the preference information; and finally, the TOPSIS method is applied to aggregate the information and obtain the final ESG score and ranking of each company. This study was tested using statistics from 30 companies released by Harvest Fund in May 2021, which verified the validity and advantages of the method proposed in this paper. The proposed method integrates the preferences of heterogeneous subjects and mines the possible hidden preference information, which increases the interpretation of the information contained in the original ESG data and facilitates the achievement of group consensus.