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Grey Target Negotiation Consensus Model Based on Super Conflict Equilibrium

Author

Listed:
  • Jun-liang Du

    (Nanjing University of Aeronautics and Astronautics)

  • Si-feng Liu

    (Nanjing University of Aeronautics and Astronautics)

  • Yong Liu

    (Jiangnan University)

Abstract

Group consensus decision-making refers to achieving a consensus result accepted by more decision makers with a certain stability. The consensus stability is mainly affected by game conflicts among decision makers. Therefore, considering super conflict analysis as the ideological basis and the minimum cost consensus model as the method basis, this paper establishes a grey target negotiation consensus model. The model can achieve game negotiation in the grey target region and determine a super continuous stable consensus bull’s-eye. Firstly, this paper proposes a generalized super conflict analysis framework in group decision-making and defines several concepts of conflict stability. Then, we integrate minimum cost consensus and grey target decision to set up a condition that meets the super conflict equilibrium and propose a grey target negotiation consensus model. Finally, an emission reduction consensus from Chinese manufacturing enterprises is applied to verify the rationality of the model.

Suggested Citation

  • Jun-liang Du & Si-feng Liu & Yong Liu, 2021. "Grey Target Negotiation Consensus Model Based on Super Conflict Equilibrium," Group Decision and Negotiation, Springer, vol. 30(4), pages 915-944, August.
  • Handle: RePEc:spr:grdene:v:30:y:2021:i:4:d:10.1007_s10726-021-09742-1
    DOI: 10.1007/s10726-021-09742-1
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    References listed on IDEAS

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    1. Majchrzak Joanna & Goliński Marek & Mantura Władysław, 2020. "The concept of the qualitology and grey system theory application in marketing information quality cognition and assessment," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(2), pages 817-840, June.
    2. Ren, Xianqiang & Zhang, Huiming & Hu, Ruohan & Qiu, Yueming, 2019. "Location of electric vehicle charging stations: A perspective using the grey decision-making model," Energy, Elsevier, vol. 173(C), pages 548-553.
    3. Liu, Yong & Du, Jun-liang & Yang, Jin-bi & Qian, Wu-yong & Forrest, Jeffrey Yi-Lin, 2019. "An incentive mechanism for general purpose technologies R&D based on the concept of super-conflict equilibrium: Empirical evidence from nano industrial technology in China," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 185-197.
    4. 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.
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