Managing noncooperative behaviors in large-scale group decision-making: Integration of independent and supervised consensus-reaching models

Abstract

Large-scale group decision-making (LSGDM) has been widely studied to address increasingly complex decision-making problems. The consensus-reaching process is usually designed to reduce differences between decision-makers and achieve high-consensus decision results. Opinion adjustment is a good solution for promoting consensus, but there are always some decision-makers who refuse to adjust or make small compromises. Many noncooperative behaviors may exist in the consensus-reaching process. Traditional consensus-reaching models dealing with noncooperative behaviors focus on situations where only one decision-maker modifies his or her opinion in each consensus iteration. However, some, or even all, decision-makers may adjust their opinions in one iteration, especially at the beginning. In this study, a mixed consensus-reaching model for managing noncooperative behaviors is proposed. We first develop a novel method to calculate the weights of decision-makers in LSGDM environments. An independent consensus-reaching model is then put forward to address situations where multiple decision-makers modify their opinions in each iteration. By combining this independent consensus model with traditional consensus models, a mixed consensus model is constructed. Finally, a case study is used to show the feasibility and applicability of the proposed model, and a comparative analysis illustrates its advantages for managing noncooperative behaviors in LSGDM situations.