Social Trust-Driven Consensus Reaching Model for Multiattribute Group Decision Making: Exploring Social Trust Network Completeness
Пэйдэ Лю, Yueyuan Li, Peng Wang
Abstract
With the development of social media, social networks (SNs) have gradually become the link of information exchange between people. The social trust network (STN), a typical SN, is considered the basis of interaction for experts. Therefore, in the STN environment, an STN-driven consensus decision framework of multiattribute group decision making is developed. First, a two-stage analysis method of STN completeness considering the social psychology of experts is proposed to obtain a complete STN, which includes the processes of trust propagation and aggregation. Second, based on the complete modified STN, an STN-driven consensus-reaching process is presented with a consensus optimization model aiming at minimum adjustments. In addition, a numerical example is used to further elaborate on the applicability of these methods. Finally, a series of simulation experiments are designed to objectively determine the parameters in the proposed methods and highlight the rationality and superiority of the proposed methods by comparisons and discussions with related studies.