A Prospect Theory-Based Consensus Method for Heterogeneous Large-Scale Group Decision-Making

In recent years, the issue of large-scale group decision-making (LSGDM) has garnered widespread attention. Considering that decision-makers (DMs) may come from various professional fields and possess different knowledge backgrounds, they often use heterogeneous preference structures to provide their evaluation opinions and exhibit different psychological behaviors in the decision-making process. To address this, this paper proposes a novel heterogeneous LSGDM model that integrates decision-making theory with prospect theory, taking into account the psychological behaviors of DMs. Firstly, the large group of experts is divided into different communities based on the departmental information, and opinion representatives from each community are identified based on the trust relationships among experts to reduce the complexity within the DMs. Secondly, during the individual selection phase, the heterogeneous preference information of the experts is transformed into preference orderings through a direct method, and a preference approval structure is introduced to determine the reference point in prospect theory. Subsequently, the prospect value function calculates the experts' and the group's prospect values regarding alternatives. Furthermore, this paper designs a two-stage feedback mechanism to adjust the experts' evaluation information and preference approval structure, thereby enhancing the level of group consensus. Finally, the methodology presented in this paper was applied to a specific case and successfully resulted in an optimal solution, providing a new approach to address enterprise financial investment decision-making problems.