A Hybrid Multi-Criteria Decision-Making Model for Evaluating Companies’ Green Credit Rating

Abstract

Along with economic development and social progress, environmental issues are increasingly becoming the subject of public concern. Through green credit, banks intentionally direct money into resource-conserving technology development and environmental protection industries, thus, encouraging enterprises to focus on green products. Therefore, establishing a reasonable green credit evaluation mechanism for banks is an important issue. Based on this, this study combines grey relational analysis (GRA), the Decision-Making Trial and Evaluation Laboratory technique (DEMATEL), analytic network process (ANP) and the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to develop a hybrid multi-criteria decision-making (MCDM) model for quantifying data and, thereby, to establish a green credit rating mechanism. In order to verify the model, this study combines credit risk and economic, environmental and social performance evaluation criteria as green credit evaluation criteria. There are 55 high-tech listed companies in Taiwan in 2014 taken as the evaluation objects and conducted for a performance ranking. The empirical results can serve as a reference for financial authorities promoting green finance policies and for investors making investment decisions.