An integrated MCDM framework for evaluating the environmental, social, and governance (ESG) sustainable business performance

As a responsible business philosophy, sustainable management is becoming a widely accepted management mode among managers, practitioners, stakeholders, and customers. The sustainable development of business management calls for the practice of the environmental, social, and governance (ESG) principle. Companies that neglect ESG criteria in their business operations may face unexpected consequences. Therefore, the ESG sustainable performance of the company is becoming a benchmark to evaluate environmental and social responsibility of companies worldwide. This paper proposes an integrated MCDM framework combining the interval type-2 fuzzy analytic hierarchy process (IT2FAHP) and the interval type-2 fuzzy combined compromise solution (IT2F-CoCoSo) method for evaluating the ESG sustainable performance of listed companies. In the integrated MCDM framework, the interval type-2 fuzzy sets serve as an effective tool to transform qualitative linguistic evaluation into quantitative expression, the criteria weights are obtained using the IT2FAHP, and the rankings of alternatives are determined by the IT2F-CoCoSo method. The proposed method is applied in a case study on the ESG sustainable performance evaluation of five medical listed companies, which are evaluated based on three aspects: E, S, and G and further divided into 14 criteria. Results reveal that the most important criterion in the E, S, and G aspects are pollution treatment, health and safety, and risk management. It suggests that the Pfizer biopharmaceutical company has the best ESG sustainable performance among the five alternative medical listed companies. We perform a sensitivity analysis with random criteria weights and different parameter values to show the stability of the proposed approach. A comparison is also performed between our approach and some existing methods for validating the proposed approach. This analysis shows that the proposed approach is efficient and well-consistent with the other methods.