A hybrid management method for heterogeneous non-cooperative behaviour in large-scale group decision-making

Driven by technological and societal demands, decision science has rapidly advanced, with large-scale group decision-making (LSGDM) widely applied to complex problems across diverse fields. In LSGDM, non-cooperative behaviours of decision-makers (DMs) often hinder consensus-reaching, making their effective identification and management critical for improving decision-making efficiency. Given differences among DMs in cognitive patterns, value orientations, and risk preferences, the motivations behind their non-cooperative behaviours exhibit significant heterogeneity. Therefore, a novel LSGDM framework considering heterogeneous non-cooperative behaviours is proposed. Specifically, an adaptive hierarchical clustering algorithm that integrates cohesion and opinion diversity is proposed to form subgroups that foster collaboration while preserving opinion diversity. Furthermore, a consensus measure method based on preference structures is proposed to accurately reflect the group consensus level. To flexibly provide adjustments for DMs, a feedback mechanism based on the minimum adjustment consensus model (MACM) is formulated, incorporating three types of feedback strategies. From the perspective of heterogeneous motivations underlying non-cooperative behaviours, a novel method is proposed to identify them. Following a “guidance-oriented with intervention as a supplement” principle, a hybrid management method is introduced to address these behaviours. Finally, a numerical example demonstrates the feasibility of the method, while comparative and simulation analyses highlight its advantages and effectiveness. As real-world problems grow in complexity, effective decision-making increasingly requires the participation of multiple DMs, leading to the widespread use of large-scale group decision-making (LSGDM) in areas such as public policy, supply chain coordination, technology planning, and organisational management. In LSGDM, decision-makers (DMs) come from diverse fields, educational backgrounds, and stakeholder groups, making opinion disagreements and conflicts almost inevitable. A common approach is to provide DMs with adjustment suggestions to gradually narrow opinion differences and reach consensus. However, not all DMs are willing to follow these suggestions, and some exhibit non-cooperative behaviours, such as refusing to compromise, which can reduce decision-making efficiency. In real-world decision-making, DMs differ in cognition, values, and risk attitudes, leading to a wide variety of motivations behind non-cooperative behaviours. To address this, this article proposes a new method to support LSGDM. By dividing DMs into subgroups with high internal cohesion while preserving opinion diversity, the method facilitates communication among DMs and supporting more comprehensive discussions of the decision problem. By identifying why subgroups fail to reach consensus and generating targeted adjustment suggestions based on the most widely accepted opinion, the method increases the likelihood that DMs will adjust their opinions. To address non-cooperative behaviours during the decision-making process, the method classifies non-cooperative behaviours into different types based on DMs’ heterogeneous motivations and applies management strategy that combines guidance with intervention to effectively promote consensus-reaching. Overall, this method provides a practical way to improve the efficiency and quality of LSGDM in real-world settings.