A consensus model considers managing manipulative and overconfident behaviours in large-scale group decision-making

When dealing with large-scale group decision-making problems, the central emphasis lies in the objective and rational acquisition of a collective opinion acceptable to the majority of decision makers. Manipulative and overconfident behaviours are two common behaviours that make the decision results deviate from the objective facts in the decision-making process. To manage manipulative and overconfident behaviours in decision-making, this paper investigated a novel consensus model based on social networks. A novel efficient clustering model is first proposed in the model, in which the subgroups' combined cohesion is considered. Furthermore, for the manipulative behaviour of decision makers, we proposed an improved method for the identification and management based on trust relationships. In the consensus reaching process, we proposed a new identification mechanism to promote consensus reaching effectively. In the feedback mechanism, the social network DeGroot model is employed to adjust the opinions of decision makers. Moreover, a management approach is proposed for the overconfident behaviour of decision makers in the social network DeGroot model. Lastly, the feasibility and applicability of the proposed model are verified by an illustrative example. Simulation experiments and comparative analysis demonstrate the effectiveness of the model in facilitating consensus reaching.

Automated summary

This paper investigates a novel consensus model based on social networks to manage manipulative and overconfident behaviors in large-scale group decision-making. By proposing a novel clustering model and improved methods, the consensus reaching is effectively facilitated. The feedback mechanism and management approach are employed to handle decision makers' behaviors. Simulation experiments and comparative analysis demonstrate the effectiveness of the model.