Abstract
Large-scale group decision-making (LSGDM) based on social networks has become an important part of practical decision-making. The trust relationship in social networks has an influence on not only the clustering process but also the consensus reaching process (CRP). Decision-makers (DMs) can take different behaviors by using the trust relationship to influence consensus reaching, so identifying the adjustment behaviors of DMs in CRP is essential. This study considers the influence of the trust relationship on the CRP and proposes a behavior analysis-based consensus model that comprehensively considers the leadership behaviors and non-cooperative behaviors. First, based on the clustering result, the preference similarity of two DMs with the direct trust relationship is calculated to judge whether leadership behavior exists. By judging the leadership behaviors, the number of effective DMs involved in LSGDM will be reduced. Second, based on the identification of leadership behaviors, the non-cooperative or cooperative behaviors are defined by judging whether the adjustment behaviors of effective DMs are conducive to achieving group consensus. Third, the weights of effective DMs and subgroups are punished or rewarded by quantifying the degree of non-cooperative or cooperative behaviors. Finally, the simulation experiments and comparative analysis are presented to illustrate the efficiency of the proposed method.
Published Version
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