A quantum cognition based group decision making model considering interference effects in consensus reaching process

Group decision making (GDM) is widely used in a complex and uncertain real-world to help multiple experts collectively evaluate and select appropriate alternatives. Consensus reaching process (CRP) is a critical step to help experts reach agreement in GDM. There exist interference effects in CRP since subjective beliefs of experts can drive interference effects. However, interference effects between experts are rarely considered. Superposition states in quantum can effectively explain the interference effects due to the superposition of expert beliefs. Therefore, this paper proposes a new quantum cognition-based group decision-making model considering the interference effects between experts during the CRP by integrating quantum probability theory. Firstly, a quantum Bayesian network is constructed to explore the interference effects of experts' psychology in GDM. Secondly, experts' weights are updated based on their contributions influenced by the inter-expert's interference, and it can reflect experts' subjective attitudes. Then, only the individual preferences furthest from the group preferences are modified. The above two models are applied together in the feedback mechanism. Thirdly, the quantum Bayesian networks continuously prioritize alternatives based on modified experts' weights and preferences. The proposed model can better model the conflict, ambiguity, and uncertainty in GDM and perceive changes in psychological interference among experts during CRP. Finally, the proposed model is verified by applying a personnel selection example. Detailed sensitivity analysis and comparative analysis are presented to show the novelty and validity of the proposed model.

Automated summary

This paper proposes a quantum cognition-based group decision-making model that considers the interference effects between experts. The model integrates quantum probability theory and uses a quantum Bayesian network to explore the interference effects of experts' psychology. Experts' weights and preferences are updated based on inter-expert's interference, and the model can better model conflict and uncertainty in group decision making.