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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

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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.

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References

  • Barabási, A., & Albert, R. (1999). Emergence of scaling in random networks. Science, 286(5439), 509–512.

    Article  Google Scholar 

  • Berger, R. L. (1981). A necessary and sufficient condition for reaching a consensus using DeGroot’s method. Journal of the American Statistical Association, 76(374), 415–418.

    Article  Google Scholar 

  • Cannon-Bowers, J. A., & Salas, E. (2001). Reflections on shared cognition. Journal of Organizational Behavior, 22, 195–202.

    Article  Google Scholar 

  • Chen, L., Xu, H. Y., & Pedrycz, W. (2023). Conflict analysis based on a novel three-way decisions graph model for conflict resolution method under hesitant fuzzy environment. Information Fusion, 100, 101936.

    Article  Google Scholar 

  • DeGroot, M. H. (1974). Reaching a consensus. Journal of the American Statistical Association, 69(345), 118–121.

    Article  Google Scholar 

  • Deja, R. (2002). Conflict analysis. International Journal of Intelligent Systems, 17(2), 235–253.

    Article  Google Scholar 

  • Dong, Y. C., Chen, X., & Herrera, F. (2015). Minimizing adjusted simple terms in the consensus reaching process with hesitant linguistic assessments in group decision making. Information Sciences, 297, 95–117.

    Article  Google Scholar 

  • Du, J. L., Liu, S. F., Liu, Y., & Yi, J. H. (2022). A novel approach to three-way conflict analysis and resolution with Pythagorean fuzzy information. Information Sciences, 584, 65–88.

    Article  Google Scholar 

  • Erdős, P., & Rényi, A. (1959). On random graphs. Publicationes Mathematicae, 6, 290–297.

    Article  Google Scholar 

  • Feng, X. F., Yang, H. L., & Guo, Z. L. (2023). Three-way conflict analysis in dual hesitant fuzzy situation tables. International Journal of Approximate Reasoning, 154, 109–132.

    Article  Google Scholar 

  • Friedkin, N. E., & Johnsen, E. C. (1990). Social influence and opinions. The Journal of Mathematical Sociology, 15, 193–206.

    Article  Google Scholar 

  • Friedkin, N. E., Proskurnikov, A. V., Tempo, R., & Parsegov, S. E. (2016). Network science on belief system dynamics under logic constraints. Science, 354(6310), 321–326.

    Article  Google Scholar 

  • Garcez, T. V., Cavalcanti, H. T., & Almeida, A. T. (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, 304, 199–231.

    Article  Google Scholar 

  • Goldani, N., & Ishizaka, A. (2024). A hybrid fuzzy multi-criteria group decision-making method and its application to healthcare waste treatment technology selection. Annals of Operations Research, 304, 199–231.

    Google Scholar 

  • Gou, X. J., Xu, Z. S., & Liao, H. C. (2019). Hesitant fuzzy linguistic possibility degree-based linear assignment method for multiple criteria decision-making. International Journal of Information Technology & Decision Making, 18, 35–63.

    Article  Google Scholar 

  • Gou, X. J., Xu, Z. S., Wang, X. X., & Liao, H. C. (2021). Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making. Fuzzy Optimization and Decision Making, 20(1), 51–79.

    Article  Google Scholar 

  • Hegselmann, R., König, S., Kurz, S., Niemann, C., & Rambau, J. (2015). Optimal opinion control: The campaign problem. Journal of Artificial Societies and Social Simulation, 18(3), 1–47.

    Article  Google Scholar 

  • Hegselmann, R., & Krause, U. (2002). Opinion dynamics and bounded confidence models, analysis, and simulation. Journal of Artificial Societies and Social Simulation, 5(3), 1–33.

    Google Scholar 

  • Holley, R. A., & Liggett, T. M. (1975). Ergodic theorems for weakly interacting infinite systems and the voter model. The Annals of Probability, 3(4), 643–663.

    Article  Google Scholar 

  • Hu, M. J. (2023). Modeling relationships in three-way conflict analysis with subsethood measures. Knowledge Based Systems, 260, 110131.

    Article  Google Scholar 

  • Huang, H., & Siraj, S. (2024). Quantifying and reducing the complexity of multi-line charts as a visual aid in multi-criteria decision-making. Annals of Operations Research. https://doi.org/10.1007/s10479-024-06090-6

    Article  Google Scholar 

  • Jia, F., & Liu, P. D. (2019). A novel three-way decision model under multiple-criteria environment. Information Sciences, 471, 29–51.

    Article  Google Scholar 

  • Jiang, Q., Liu, Y., Yi, J. H., & Forrest, J. Y. L. (2024). A three-way conflict analysis model with decision makers’ varying preferences. Applied Soft Computing Journal, 151, 111171.

    Article  Google Scholar 

  • Lang, G. M., Miao, D. Q., & Cai, M. J. (2017). Three-way decision approaches to conflict analysis using decision-theoretic rough set theory. Information Sciences., 406–407, 185–207.

    Article  Google Scholar 

  • Lang, G. M., Miao, D. Q., & Fujita, H. (2020). Three-Way Group Conflict Analysis Based on Pythagorean Fuzzy Set Theory. IEEE Transactions on Fuzzy Systems., 28(3), 447–461.

    Article  Google Scholar 

  • Liang, D. C., Fu, Y. Y., & Xu, Z. S. (2022). Three-way group consensus decision based on hierarchical social network consisting of decision makers and participants. Information Sciences, 585, 289–312.

    Article  Google Scholar 

  • Liang, D. C., Yi, B. C., & Xu, Z. S. (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, 72(12), 2783–2803.

    Article  Google Scholar 

  • Liao, H. C., Gou, X. J., Xu, Z. S., Zeng, X. J., & Herrera, F. (2020). Hesitancy degree-based correlation measures for hesitant fuzzy linguistic term sets and their applications in multiple criteria decision making. Information Sciences, 508, 275–292.

    Article  Google Scholar 

  • Liu, P. D., Chen, S. M., & Liu, J. L. (2017). Multiple attribute group decision making based on intuitionistic fuzzy interaction partitioned Bonferroni mean operators. Information Sciences, 411, 98–121.

    Article  Google Scholar 

  • Liu, Q., Wu, H. Y., & Xu, Z. S. (2021). Consensus model based on probability K-means clustering algorithm for large scale group decision making. International Journal of Machine Learning and Cybernetics, 12, 1609–1626.

    Article  Google Scholar 

  • Pawlak, Z. (1998). An inquiry into anatomy of conflicts. Information Sciences, 109, 65–78.

    Article  Google Scholar 

  • Ren, Z. L., Xu, Z. S., & Wang, H. (2018). Multi-criteria group decision-making based on quasi-order for dual hesitant fuzzy sets and professional degrees of decision makers. Applied Soft Computing, 71, 20–35.

    Article  Google Scholar 

  • Suo, L. W. Q., & Yang, H. L. (2022). Three-way conflict analysis based on incomplete situation tables: A tentative study. International Journal of Approximate Reasoning, 145, 51–74.

    Article  Google Scholar 

  • Tang, J., Meng, F. Y., Xu, Z. S., & Yuan, R. P. (2020). Qualitative hesitant fuzzy group decision making: An additively consistent probability and consensus-based perspective. Expert Systems, 37, e12510.

    Article  Google Scholar 

  • Tian, X. L., Xu, Z. S., Gu, J., & Herrera, F. (2021). A consensus process based on regret theory with probabilistic linguistic term sets and its application in venture capital. Information Sciences, 562, 347–369.

    Article  Google Scholar 

  • Tong, S. R., Sun, B. Z., Chu, X. L., Zhang, X. R., Wang, T., & Jiang, C. (2021). Trust recommendation mechanism-based consensus model for Pawlak conflict analysis decision making. International Journal of Approximate Reasoning, 135, 91–109.

    Article  Google Scholar 

  • Wang, H., Yu, D. J., & Xu, Z. S. (2021). A novel process to determine consensus thresholds and its application in probabilistic linguistic group decision-making. Expert Systems with Applications, 168, 114315.

    Article  Google Scholar 

  • Wang, M. W., Liang, D. C., & Xu, Z. S. (2020). Sequential three-way multiple attribute group decisions with individual attributes and its consensus achievement based on social influence. Information Sciences, 518, 286–308.

    Article  Google Scholar 

  • Wang, T. X., Huang, B., Li, H. X., Liu, D., & Yu, H. (2023). Three-way decision for probabilistic linguistic conflict analysis via compounded risk preference. Information Sciences, 631, 65–90.

    Article  Google Scholar 

  • Wang, T. X., Li, H. X., Hu, W. T., & Zhang, L. B. (2021). A prospect theory-based three-way conflict analysis approach for agent evaluation. In 2021 IEEE 24th international conference on computer supported cooperative work in design (pp. 575–580).

  • Wang, Q. M., Dai, J. H., & Xu, Z. S. (2022). A new three-way multi-criteria decision-making method with fuzzy complementary preference relations based on additive consistency. Information Sciences, 592, 277–305.

    Article  Google Scholar 

  • Watts, D., & Strogatz, S. (1998). Collective dynamics of ‘small-world’ networks. Nature, 393, 440–442.

    Article  Google Scholar 

  • Weisbuch, G., Deffuant, G., Amblard, F., & Nadal, J. P. (2002). Meet, discuss, and segregate! Complexity, 7, 55–63.

    Article  Google Scholar 

  • Xie, H. T., Ma, Z. M., Xu, Z. S., Fu, Z. W., & Yang, W. (2022). Novel consistency and consensus of generalized intuitionistic fuzzy preference relations with application in group decision making. Applied Intelligence, 52, 16832–16851.

    Article  Google Scholar 

  • Yang, H., Yao, Y. Y., & Qin, K. Y. (2024). A lattice-theoretic model of three-way conflict analysis. Knowledge-Based Systems, 288, 111470.

    Article  Google Scholar 

  • Yao, Y. Y. (2010). Three-way decisions with probabilistic rough sets. Information Sciences, 180, 341–353.

    Article  Google Scholar 

  • Yao, Y. Y. (2018). Three-way decision and granular computing. International Journal of Approximate Reasoning, 103, 107–123.

    Article  Google Scholar 

  • Yao, Y. Y. (2019). Three-way conflict analysis: Reformulations and extensions of the Pawlak model. Knowledge-Based Systems, 180, 26–37.

    Article  Google Scholar 

  • Zhang, K., & Dai, J. H. (2022). Three-way multi-criteria group decision-making method in a fuzzy \(\beta \)-covering group approximation space. Information Sciences, 599, 1–24.

    Article  Google Scholar 

  • Zhang, H. J., Dong, Y. C., Carrascosa, I. P., & Zhou, H. W. (2019). Failure mode and effect analysis in a linguistic context: A consensus-based multiattribute group decision-making approach. IEEE Transactions on Reliability, 68, 566–582.

    Article  Google Scholar 

  • Zhi, H. L., & Li, J. H. (2024). Component similarity based conflict analysis: An information fusion viewpoint. Information Fusion, 104, 102157.

    Article  Google Scholar 

Download references

Funding

This work is partially supported by the National Natural Science Foundation of China (Nos. 72071030, 72471046), the National Key R&D Program of China (No. 2020YFB1711900) and the Planning Fund for the Humanities and Social Sciences of Ministry of Education of China (No. 19YJA630042).

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Correspondence to Zeshui Xu.

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Appendix: The abbreviations and notations list

Appendix: The abbreviations and notations list

In this section, we firstly conclude the abbreviations used in this paper as shown in Table 9.

Table 9 The abbreviations in this paper

Besides, to improve the readability, the main notations of this paper are also summarized in Table 10:

Table 10 The main notations in this paper

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Liang, D., Zheng, Q. & Xu, Z. Exploiting experts’ asymmetric knowledge structures for consensus reaching: a multi-criteria group decision making model with three-way conflict analysis and opinion dynamics. Ann Oper Res (2024). https://doi.org/10.1007/s10479-024-06330-9

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