School of Mathematical Sciences
E-commerce credit risk assessment can better maintain market rules and prevent the legitimate rights and interests of trading entities. According to linguistic evaluation information, this paper utilizes multi-attribute group decision making methods to investigate the approach to E-commerce credit risk assessment. First, individual consensus measure and group consensus measure are proposed. Then, an integer programming model is developed to improve the consensus level of decision group with lower consensus level by revising the original linguistic evaluation information. Finally, an approach to E-commerce credit risk assessment based on linguistic consensus model is presented. The feasibility and effectiveness of this approach are verified by E-commerce credit risk assessment problem.