A Dynamic Trust Consensus Model in Large‐Scale Group Decision: Managing Overconfidence and Non‐Cooperative Behaviors

In this paper, we propose a dynamic trust consensus model, considering the closeness of the relationship and trust relationship between decision makers (DMs) in a social network. First, the propagation efficiency of indirect trust is proposed for obtaining a complete social trust network based on the closeness of relationships among DMs and the similarity of evaluations. The large‐scale DMs are clustered into subgroups using the social‐similarity index between DMs. In the consensus reaching process (CRP), this paper proposes a new way to identify overconfident and non‐cooperative behaviors. For overconfident and inconsistent DMs, it is essential to not only adjust their evaluated values but also reduce their confidence levels in the feedback adjustment stage. This paper proposes a new dynamic trust approach to penalize DMs with overconfident or non‐cooperative behaviors. Finally, an investment problem of a new energy project is used to test the feasibility of the proposed approach in this paper. The results of the comparative analysis illustrate the feasibility and innovation of the consensus decision‐making method proposed in this paper.