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Consensus Measure with Multi-stage Fluctuation Utility Based on China’s Urban Demolition Negotiation

Author

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  • Zaiwu Gong

    (Nanjing University of Information Science and Technology)

  • Chao Xu

    (Nanjing University of Information Science and Technology)

  • Francisco Chiclana

    (De Montfort University)

  • Xiaoxia Xu

    (Nanjing University of Information Science and Technology)

Abstract

Utility functions are often used to reflect decision makers’ (DMs’) preferences. They have the following two merits: one refers to the representation of the DM’s utility (satisfaction) level, the other one to the measuring of the consensus level in a negotiation process. Taking the background of China’s urban house demolition, a new kind of consensus model is established by using different types of multi-stage fluctuation utility functions, such as concave, convex, S-shaped, reversed S-shaped, reversed U-shaped as well as their combinations, to reveal negotiators’ dynamic physiological preferences and consensus level. Moreover, the effects of the decision-making budget and the individual compensation tolerance on the consensus level are also discussed in this paper. Compared with previous research, the proposed model takes both the negotiation cost and DM’s preference structure into consideration, and most importantly, it is computational less complex.

Suggested Citation

  • Zaiwu Gong & Chao Xu & Francisco Chiclana & Xiaoxia Xu, 2017. "Consensus Measure with Multi-stage Fluctuation Utility Based on China’s Urban Demolition Negotiation," Group Decision and Negotiation, Springer, vol. 26(2), pages 379-407, March.
    • Handle: RePEc:spr:grdene:v:26:y:2017:i:2:d:10.1007_s10726-016-9486-6
    DOI: 10.1007/s10726-016-9486-6
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    References listed on IDEAS

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    Cited by:

    1. Zhang, Bowen & Dong, Yucheng & Zhang, Hengjie & Pedrycz, Witold, 2020. "Consensus mechanism with maximum-return modifications and minimum-cost feedback: A perspective of game theory," European Journal of Operational Research, Elsevier, vol. 287(2), pages 546-559.
    2. Wenqi Liu & Hengjie Zhang & Haiming Liang & Cong-cong Li & Yucheng Dong, 2022. "Managing Consistency and Consensus Issues in Group Decision-Making with Self-Confident Additive Preference Relations and Without Feedback: A Nonlinear Optimization Method," Group Decision and Negotiation, Springer, vol. 31(1), pages 213-240, February.
    3. Cheng, Dong & Yuan, Yuxiang & Wu, Yong & Hao, Tiantian & Cheng, Faxin, 2022. "Maximum satisfaction consensus with budget constraints considering individual tolerance and compromise limit behaviors," European Journal of Operational Research, Elsevier, vol. 297(1), pages 221-238.
    4. Shaojian Qu & Yefan Han & Zhong Wu & Hassan Raza, 2021. "Consensus Modeling with Asymmetric Cost Based on Data-Driven Robust Optimization," Group Decision and Negotiation, Springer, vol. 30(6), pages 1395-1432, December.
    5. Dong Cheng & Yong Wu & Yuxiang Yuan & Faxin Cheng & Dianwei Chen, 2024. "Modeling the Maximum Perceived Utility Consensus Based on Prospect Theory," Group Decision and Negotiation, Springer, vol. 33(5), pages 951-975, October.
    6. Du, Junliang & Liu, Sifeng & Liu, Yong, 2022. "A limited cost consensus approach with fairness concern and its application," European Journal of Operational Research, Elsevier, vol. 298(1), pages 261-275.
    7. Zhang, Hengjie & Dong, Yucheng & Chiclana, Francisco & Yu, Shui, 2019. "Consensus efficiency in group decision making: A comprehensive comparative study and its optimal design," European Journal of Operational Research, Elsevier, vol. 275(2), pages 580-598.
    8. Weijun Xu & Xin Chen & Yucheng Dong & Francisco Chiclana, 2021. "Impact of Decision Rules and Non-cooperative Behaviors on Minimum Consensus Cost in Group Decision Making," Group Decision and Negotiation, Springer, vol. 30(6), pages 1239-1260, December.
    9. Yangjingjing Zhang & Xia Chen & Mengting Gao & Yucheng Dong, 2024. "Maximum Utility Consensus with Inequity Aversion in Social Network Group Decision Making," Group Decision and Negotiation, Springer, vol. 33(5), pages 1115-1142, October.
    10. Guo, Weiwei & Gong, Zaiwu & Zhang, Wei-Guo & Xu, Yanxin, 2023. "Minimum cost consensus modeling under dynamic feedback regulation mechanism considering consensus principle and tolerance level," European Journal of Operational Research, Elsevier, vol. 306(3), pages 1279-1295.
    11. Zhang, Huanhuan & Kou, Gang & Peng, Yi, 2019. "Soft consensus cost models for group decision making and economic interpretations," European Journal of Operational Research, Elsevier, vol. 277(3), pages 964-980.

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