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Exploiting experts’ asymmetric knowledge structures for consensus reaching: a multi-criteria group decision making model with three-way conflict analysis and opinion dynamics

Author

Listed:
  • Decui Liang

    (University of Electronic Science and Technology of China)

  • Qiang Zheng

    (University of Electronic Science and Technology of China)

  • Zeshui Xu

    (Sichuan University)

Abstract

In multi-criteria group decision making (MCGDM), experts from various backgrounds hold asymmetric knowledge structures, which may impact the opinion aggregation of MCGDM. Hence, considering the experts’ different knowledge structures, this paper applies three-way conflict analysis into opinion interaction for consensus reaching process (CRP). More specifically, we first construct a social network of experts based on the asymmetric influence, which can guide the opinion interaction process. Then, with the aid of three-way conflict analysis, three levels are taken into consideration: (1) With respect to the conflicts from the social relationship level, we identify the conflict relation between the experts and the group via three-way conflict analysis. (2) From the perspective of the alternative level, we develop an opinion interaction rule by dividing the alternatives into strong conflict, weak conflict, and no conflict. (3) From the criteria level, we also design a criteria interaction rule based on the similarity and asymmetry of the experts’ knowledge structures. Thirdly, direction rules with the three levels above are proposed for the CRP. Our proposed method with three-way conflict analysis not only resolves conflicts among experts and minimizes information loss during the process of opinion interaction, but also promotes the CRP. Finally, numerical experiments and comparative simulations are conducted to demonstrate the viability and efficacy of our proposed method.

Suggested Citation

  • Decui Liang & Qiang Zheng & Zeshui Xu, 2025. "Exploiting experts’ asymmetric knowledge structures for consensus reaching: a multi-criteria group decision making model with three-way conflict analysis and opinion dynamics," Annals of Operations Research, Springer, vol. 346(2), pages 1217-1255, March.
    • Handle: RePEc:spr:annopr:v:346:y:2025:i:2:d:10.1007_s10479-024-06330-9
    DOI: 10.1007/s10479-024-06330-9
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    References listed on IDEAS

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    1. Xunjie Gou & Zeshui Xu & Xinxin Wang & Huchang Liao, 2021. "Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making," Fuzzy Optimization and Decision Making, Springer, vol. 20(1), pages 51-79, March.
    2. Xunjie Gou & Zeshui Xu & Huchang Liao, 2019. "Hesitant Fuzzy Linguistic Possibility Degree-Based Linear Assignment Method for Multiple Criteria Decision-Making," International Journal of Information Technology & Decision Making (IJITDM), World Scientific Publishing Co. Pte. Ltd., vol. 18(01), pages 35-63, January.
    3. Rainer Hegselmann & Ulrich Krause, 2002. "Opinion Dynamics and Bounded Confidence Models, Analysis and Simulation," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 5(3), pages 1-2.
    4. Rainer Hegselmann & Stefan König & Sascha Kurz & Christoph Niemann & Jörg Rambau, 2015. "Optimal Opinion Control: The Campaign Problem," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 18(3), pages 1-18.
    5. Decui Liang & Bochun Yi & Zeshui Xu, 2021. "Opinion dynamics based on infectious disease transmission model in the non-connected context of Pythagorean fuzzy trust relationship," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(12), pages 2783-2803, December.
    6. Thalles Vitelli Garcez & Helder Tenório Cavalcanti & Adiel Teixeira de Almeida, 2021. "A hybrid decision support model using Grey Relational Analysis and the Additive-Veto Model for solving multicriteria decision-making problems: an approach to supplier selection," Annals of Operations Research, Springer, vol. 304(1), pages 199-231, September.
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