IDEAS home Printed from https://ideas.repec.org/a/spr/grdene/v30y2021i4d10.1007_s10726-021-09742-1.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10726-021-09742-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10726-021-09742-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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. 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.
    3. 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.
    4. 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.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Gong, Zaiwu & Guo, Weiwei & Słowiński, Roman, 2021. "Transaction and interaction behavior-based consensus model and its application to optimal carbon emission reduction," Omega, Elsevier, vol. 104(C).
    2. Liang, Decui & Fu, Yuanyuan & Ishizaka, Alessio, 2023. "A consensual group ELECTRE-SORT approach considering the incomparable classes with the application of machine maintenance strategy assignment," Omega, Elsevier, vol. 118(C).
    3. Milan Straka & Pasquale De Falco & Gabriella Ferruzzi & Daniela Proto & Gijs van der Poel & Shahab Khormali & v{L}ubov{s} Buzna, 2019. "Predicting popularity of EV charging infrastructure from GIS data," Papers 1910.02498, arXiv.org.
    4. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
    5. Ferro, G. & Minciardi, R. & Robba, M., 2020. "A user equilibrium model for electric vehicles: Joint traffic and energy demand assignment," Energy, Elsevier, vol. 198(C).
    6. Zhang, Hao & Wang, Mingyue & Cheng, Zhixuan & Wan, Ling, 2020. "Technology-sharing strategy and incentive mechanism for R&D teams of manufacturing enterprises," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 555(C).
    7. Lin, Haiyang & Bian, Caiyun & Wang, Yu & Li, Hailong & Sun, Qie & Wallin, Fredrik, 2022. "Optimal planning of intra-city public charging stations," Energy, Elsevier, vol. 238(PC).
    8. Li, Chengzhe & Zhang, Libo & Ou, Zihan & Wang, Qunwei & Zhou, Dequn & Ma, Jiayu, 2022. "Robust model of electric vehicle charging station location considering renewable energy and storage equipment," Energy, Elsevier, vol. 238(PA).
    9. Li, Yanhong & Kou, Gang & Li, Guangxu & Peng, Yi, 2022. "Consensus reaching process in large-scale group decision making based on bounded confidence and social network," European Journal of Operational Research, Elsevier, vol. 303(2), pages 790-802.
    10. Mehmet Onur Olgun, 2022. "Collaborative airline revenue sharing game with grey demand data," 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. 30(3), pages 861-882, September.
    11. Zhang, Lihui & Zhao, Zhenli & Yang, Meng & Li, Songrui, 2020. "A multi-criteria decision method for performance evaluation of public charging service quality," Energy, Elsevier, vol. 195(C).
    12. Andrea Stabile & Michela Longo & Wahiba Yaïci & Federica Foiadelli, 2020. "An Algorithm for Optimization of Recharging Stops: A Case Study of Electric Vehicle Charging Stations on Canadian’s Ontario Highway 401," Energies, MDPI, vol. 13(8), pages 1-19, April.
    13. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
    14. Mansur Arief & Yan Akhra & Iwan Vanany, 2023. "A Robust and Efficient Optimization Model for Electric Vehicle Charging Stations in Developing Countries under Electricity Uncertainty," Papers 2307.05470, arXiv.org.
    15. Men, Jinkun & Zhao, Chunmeng, 2024. "A Type-2 fuzzy hybrid preference optimization methodology for electric vehicle charging station location," Energy, Elsevier, vol. 293(C).
    16. Karim, Mohammed Shamsul & Nahar, Sharmin & Demirbag, Mehmet, 2022. "Resource-Based Perspective on ICT Use and Firm Performance: A Meta-analysis Investigating the Moderating Role of Cross-Country ICT Development Status," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    17. Alcázar-García, Désirée & Romeral Martínez, José Luis, 2022. "Model-based design validation and optimization of drive systems in electric, hybrid, plug-in hybrid and fuel cell vehicles," Energy, Elsevier, vol. 254(PA).
    18. 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.
    19. Qingyou Yan & Hua Dong & Meijuan Zhang, 2021. "Service Evaluation of Electric Vehicle Charging Station: An Application of Improved Matter-Element Extension Method," Sustainability, MDPI, vol. 13(14), pages 1-25, July.
    20. Rodríguez, Rosa M. & Labella, Álvaro & Nuñez-Cacho, Pedro & Molina-Moreno, Valentin & Martínez, Luis, 2022. "A comprehensive minimum cost consensus model for large scale group decision making for circular economy measurement," Technological Forecasting and Social Change, Elsevier, vol. 175(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:grdene:v:30:y:2021:i:4:d:10.1007_s10726-021-09742-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.