Research on Logistics Financial Credit Evaluation of Third-Part Logistics Enterprises with Uncertain Information

Abstract

Logistics finance is an important component of modern logistics and one of the supporting factors for logistics service innovation, determining the developing orientation of value-added services of logistics. Logistics finance is a co-integrated new type of service innovated by modern logistics and finance, its production and development is inseparable from financial institutions. In this paper, we investigate the multiple attribute group decision making (MAGDM) problems for evaluating the logistics financial credit evaluation of third-part logistics enterprises with uncertain information. We utilize the uncertain weighted averaging (UWA) operator to aggregate the uncertain information corresponding to each alternative and get the overall value of alternatives, then rank the alternatives and select the most desirable one(s) by using the formula of the degree of possibility for the comparison between two uncertain variables. Finally an illustrative example for evaluating the logistics financial credit evaluation of third-part logistics enterprises with uncertain information has been given to show the developed approach.