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In social network large-scale group decision-making (SN-LSGDM) problem, the decision results are usually affected by the complex social relationships among decision makers (DMs). The high trust degrees received by DMs may in turn motivate them to participate in SN-LSGDM, which is called the effect of trust excitation. Similarly, the high distrust degrees potentially reduce the enthusiasm of DMs to participate in the decision, a phenomenon is regarded as the influence of conflict hindrance. This paper aims to design a two-stage clustering method to classify DMs with complex social relationships, and presents a consensus feedback process which considers the effects of trust excitation and conflict hindrance. In this paper, a relationship propagation mechanism based on complex social relationship is proposed to obtain the indirect assessment. Afterwards, a two-stage social network-based agglomerative hierarchical clustering (TSN-AHC) method is proposed to classify DMs into trust set, conflict set or neutral set. Furthermore, the effects of trust excitation and conflict hindrance are taken into account the consensus of SN-LSGDM problem, and three feedback mechanisms are provided based on minimum cost consensus (MCC) model. Finally, case study and simulation experiments demonstrate the rationality and superiority of the proposed two-stage clustering and consensus based on trust excitation and conflict hindrance.
Lu et al. (Sat,) studied this question.