A dynamic trust and prospect theory driven bilateral feedback mechanism for maximizing consensus income in social network group decision making

This article proposes a prospect theory-based bilateral feedback mechanism with dynamic trust to reach group consensus under social network. A trust evolution model is developed by the concept of trust gap to reflect the dynamic changes in the trust relationships between DMs. The concept of a loss prospect threshold is then proposed, combining dynamic trust and consensus index, to quantitatively describe the maximum acceptable psychological loss for DMs in each round of feedback. Additionally, two indexes are defined to study feedback behavior: the improvement of consensus level as an income prospect and the preference adjustment as a loss prospect. Therefore, a bilateral feedback optimization model is constructed by maximizing the consensus income prospect under the limitation of the loss prospect threshold. To explore the role of dynamic trust and psychological behavior on the consensus-reaching process, three different feedback mechanisms are designed and compared with the proposed model, demonstrating that the proposed model can reduce preference adjustment costs and improve satisfaction with the final decision. A numerical example with sensitivity analysis of parameters is provided to illustrate the feasibility of the proposed model.