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    Analysis of power asymmetry conflict based on fuzzy options graph models
    (Elsevier, 2024) Chen, Lu; Pedrycz, Witold; Xu, Haiyan
    Asymmetric power conflicts occur frequently. Because of the complexity of the conflict as well as the vagueness of the decision makers' cognition, it becomes urgent and highly motivated to propose an appropriate method to solve power asymmetry conflict. In this study, we consider that decision makers provide option choices quantified by some degrees of membership. The choice of an option is determined by the thresholds of selection degree. At the same time, due to the influence of the power, the follower adjusts its degree of option choice to reach consensus with the leader. The computational rules determining fuzzy truth value are given, and a fuzzy truth value option prioritization method is proposed to calculate the ranking of the states, where the states ordering is related to the fuzzy degree of option selection. Different from the previous studies, this paper is the first one to study the asymmetric power conflict from the perspective of options, considering the psychological threshold of decision maker for option selection, and pointing out that the option choice is described with the fuzzy values rather than being treated as two-valued (Boolean). Furthermore, the introduced stability analysis also reflects the interaction of the options of different decision makers, which makes the proposal being more in rapport with real-world scenarios. Finally, a case study of carbon emission reduction power asymmetry conflict in supply chain is studied to demonstrate the performance of the proposed method.
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    Öğe
    Conflict analysis based on a novel three-way decisions graph model for conflict resolution method under hesitant fuzzy environment
    (Elsevier, 2023) Chen, Lu; Xu, Haiyan; Pedrycz, Witold
    Multi-criteria decision aiding/making (MCDA/M) approach and three-way decisions (3WD) are embedded into the framework of graph model for conflict resolution (GMCR). The objective of this study is to develop more reasonable preference ranking for decision makers (DMs) produced from the perspective of options. This implies further simplification of the underlying computing behind conflict resolution. More specifically, DMs' original option statements are evaluated by hesitant fuzzy sets (HFSs), then a three-way decisions approach is used to screen out the infeasible and rank the feasible option statements, and the feasible option statements' loss values of three-way decisions approach are determined based on the hesitant fuzzy (HF) evaluation values. In addition, based on the value of conditional probability of the feasible option statements, an improved option prioritization technique with objective weights is developed to efficiently rank the conflict states, so that it can efficiently reflect the intensity of the ranking. Then, considering the preference thresholds of DMs, new definitions of threshold stabilities are proposed. As demonstrated by the case study in the problem of a carbon emission conflict in supply chain under 3060 carbon peak and neutrality goal in China, the proposed novel three-way decisions graph model for conflict resolution (3WD-GMCR) framework can be widely applied to the realistic scenarios of decision-making. Compared with previous studies, the proposed approach can not only obtain the intensity ranking of conflict states, but also resolve complex large-scale conflicts effectively.