Multi-criteria Decision Making based on Trust and Reputation in Supply Chain
Résumé
Decision making is a core problem in Supply Chains. A large number of studies in literature have reported various decision making techniques based on customers' requirements. Taking into account high risk transactions in virtual Supply Chain market, trust is a very critical element and should be treated as an important reference when customers try to select proper suppliers. Recently, a great effort has been carried out to develop decision making based on trust and reputation. However, these research works still stay on the stage of theoretical research. This paper presents and implements a multi-criteria decision making approach based on trust and reputation in Supply Chain. Firstly, this paper defines general trust indicators in real Supply Chain settings, and designs a multi-dimensional trust and reputation model. This paper also introduces K-mean clustering algorithm to remove unfair rating scores. Then, based on this trust and reputation model, we propose a multi-criteria decision making approach based on variable weights and satisfaction principle. In order to validate the performance of this approach, we simulate a practical Supply Chain setting with multi-agents platform. The simulation experiments demonstrate that the proposed trust and reputation model can effectively filter unfair ratings from those customers who did lie and the proposed multi-criteria decision making method can help customers make right decisions.