An extended EDAS method under four-branch fuzzy environments and its application in credit evaluation for micro and small entrepreneurs

Abstract

With Chinese economic development in a new normal state, micro and small corporations have increasingly played an important role. The credit evaluation for micro and small corporations can contribute to efficient financial decisions. Traditional methods for the corporate credit evaluation rarely consider fuzzy features of micro and small entrepreneurs. Since the credit evaluation procedure for entrepreneurs consists of some alternatives and influential indicators, it can be recognized as a multi-criteria decision-making (MCDM) problem. To better express uncertainty information, a four-branch fuzzy set (FBFS) is presented to deal with the issue, which is characterized by a truth-membership function, an unknown-membership function and a falsity-membership function. In the paper, to handle the MCDM problems under four-branch fuzzy environments, the evaluation based on distance from average solution (EDAS) method is extended and utilized. These obvious improvement places include integrating an interval weight vector, determining an average solution, transforming a decision matrix and analyzing a change trend of the coefficients. To demonstrate the applicability and rationality of the proposed method in practice, an illustrative example is implemented, concerning a credit evaluation for some micro and small entrepreneurs. Its feasibility and validity are further verified by a sensitivity analysis and a comparative analysis. The results show the FBFSs and extended EDAS method can well match the reality and appropriately handle the credit evaluation problems for micro and small entrepreneurs.