Abstract:
This paper proposes an adaptive subgroup rescue mechanism to better balance efficiency and information loss in large-scale group decision-making. We calculate the consens...Show MoreMetadata
Abstract:
This paper proposes an adaptive subgroup rescue mechanism to better balance efficiency and information loss in large-scale group decision-making. We calculate the consensus for different clusters through linguistic preferences and trust relations, find the group with the lowest consensus level, and advise the group to exit from the process. A rescue process is triggered once the group has low cohesion or can propose a new idea. A trust-based feedback mechanism is designed to ensure enough decision makers in consensus reaching. Finally, we conduct an empirical study to verify the feasibility of our mechanism.
Date of Conference: 01-04 October 2023
Date Added to IEEE Xplore: 29 January 2024
ISBN Information: