Environmental, Social and Governance Investing Assessment under Incomplete Information by the Power Aggregation Model on Probabilistic Linguistic Terms

Abstract

Environmental, social and governance(ESG) investing is being a popular strategy in global financial markets, which includes more comprehensive concerns over the environmental, social and governance aspects of the investment targets. However, how to evaluate ESG performance faces multiple challenges because of incomplete information, subjective judgments and multiple attribute decision-making problems. To address those issues, we develop a new multi-attribute group decision making (MAGDM) model based on power average of probabilistic linguistic terms (PLTs), not only can take advantage of PLTs in expressing the information by human natural language, but also effectively aggregates information from the individual evaluations under ambiguous market. The validity and advantages of our model for ranking ESG alternatives can be illustrated by the numerical study in the end.