IDEAS home Printed from https://ideas.repec.org/a/spr/grdene/v30y2021i3d10.1007_s10726-021-09723-4.html
   My bibliography  Save this article

A Consensus Model for Large-Scale Group Decision-Making Based on the Trust Relationship Considering Leadership Behaviors and Non-cooperative Behaviors

Author

Listed:
  • Chenxi Zhang

    (Northeastern University
    Sichuan University)

  • Meng Zhao

    (Northeastern University
    Sichuan University
    Northeastern University at Qinhuangdao)

  • Lichao Zhao

    (Northeastern University)

  • Qinfei Yuan

    (Northeastern University)

Abstract

Large-scale group decision-making (LSGDM) based on social networks has become an important part of practical decision-making. The trust relationship in social networks has an influence on not only the clustering process but also the consensus reaching process (CRP). Decision-makers (DMs) can take different behaviors by using the trust relationship to influence consensus reaching, so identifying the adjustment behaviors of DMs in CRP is essential. This study considers the influence of the trust relationship on the CRP and proposes a behavior analysis-based consensus model that comprehensively considers the leadership behaviors and non-cooperative behaviors. First, based on the clustering result, the preference similarity of two DMs with the direct trust relationship is calculated to judge whether leadership behavior exists. By judging the leadership behaviors, the number of effective DMs involved in LSGDM will be reduced. Second, based on the identification of leadership behaviors, the non-cooperative or cooperative behaviors are defined by judging whether the adjustment behaviors of effective DMs are conducive to achieving group consensus. Third, the weights of effective DMs and subgroups are punished or rewarded by quantifying the degree of non-cooperative or cooperative behaviors. Finally, the simulation experiments and comparative analysis are presented to illustrate the efficiency of the proposed method.

Suggested Citation

  • Chenxi Zhang & Meng Zhao & Lichao Zhao & Qinfei Yuan, 2021. "A Consensus Model for Large-Scale Group Decision-Making Based on the Trust Relationship Considering Leadership Behaviors and Non-cooperative Behaviors," Group Decision and Negotiation, Springer, vol. 30(3), pages 553-586, June.
  • Handle: RePEc:spr:grdene:v:30:y:2021:i:3:d:10.1007_s10726-021-09723-4
    DOI: 10.1007/s10726-021-09723-4
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10726-021-09723-4
    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/s10726-021-09723-4?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. Tversky, Amos & Kahneman, Daniel, 1992. "Advances in Prospect Theory: Cumulative Representation of Uncertainty," Journal of Risk and Uncertainty, Springer, vol. 5(4), pages 297-323, October.
    2. Liu, Bingsheng & Shen, Yinghua & Zhang, Wei & Chen, Xiaohong & Wang, Xueqing, 2015. "An interval-valued intuitionistic fuzzy principal component analysis model-based method for complex multi-attribute large-group decision-making," European Journal of Operational Research, Elsevier, vol. 245(1), pages 209-225.
    3. Jianjun Zhu & Shitao Zhang & Ye Chen & Lili Zhang, 2016. "A Hierarchical Clustering Approach Based on Three-Dimensional Gray Relational Analysis for Clustering a Large Group of Decision Makers with Double Information," Group Decision and Negotiation, Springer, vol. 25(2), pages 325-354, March.
    4. Yager, Ronald R., 2002. "Defending against strategic manipulation in uninorm-based multi-agent decision making," European Journal of Operational Research, Elsevier, vol. 141(1), pages 217-232, August.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Xiaohong Chen & Weiwei Zhang & Xuanhua Xu & Wenzhi Cao, 2022. "Managing Group Confidence and Consensus in Intuitionistic Fuzzy Large Group Decision-Making Based on Social Media Data Mining," Group Decision and Negotiation, Springer, vol. 31(5), pages 995-1023, October.
    2. ming, Luo & GuoHua, Zhou & Wei, Wei, 2021. "Study of the Game Model of E-Commerce Information Sharing in an Agricultural Product Supply Chain based on fuzzy big data and LSGDM," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    3. Lu Chen & Ayad Hendalianpour & Mohammad Reza Feylizadeh & Haiyan Xu, 2023. "Factors Affecting the Use of Blockchain Technology in Humanitarian Supply Chain: A Novel Fuzzy Large-Scale Group-DEMATEL," Group Decision and Negotiation, Springer, vol. 32(2), pages 359-394, April.

    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. Liu, Hu-Chen & Li, Zhaojun & Zhang, Jian-Qing & You, Xiao-Yue, 2018. "A large group decision making approach for dependence assessment in human reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 135-144.
    2. Qifeng Wan & Xuanhua Xu & Xiaohong Chen & Jun Zhuang, 2020. "A Two-Stage Optimization Model for Large-Scale Group Decision-Making in Disaster Management: Minimizing Group Conflict and Maximizing Individual Satisfaction," Group Decision and Negotiation, Springer, vol. 29(5), pages 901-921, October.
    3. Tang, Ming & Liao, Huchang, 2021. "From conventional group decision making to large-scale group decision making: What are the challenges and how to meet them in big data era? A state-of-the-art survey," Omega, Elsevier, vol. 100(C).
    4. Oliver Linton & Esfandiar Maasoumi & Yoon-Jae Wang, 2002. "Consistent testing for stochastic dominance: a subsampling approach," CeMMAP working papers 03/02, Institute for Fiscal Studies.
    5. Heiko Karle & Georg Kirchsteiger & Martin Peitz, 2015. "Loss Aversion and Consumption Choice: Theory and Experimental Evidence," American Economic Journal: Microeconomics, American Economic Association, vol. 7(2), pages 101-120, May.
    6. Shoji, Isao & Kanehiro, Sumei, 2016. "Disposition effect as a behavioral trading activity elicited by investors' different risk preferences," International Review of Financial Analysis, Elsevier, vol. 46(C), pages 104-112.
    7. Muhammad Kashif & Thomas Leirvik, 2022. "The MAX Effect in an Oil Exporting Country: The Case of Norway," JRFM, MDPI, vol. 15(4), pages 1-16, March.
    8. Boone, Jan & Sadrieh, Abdolkarim & van Ours, Jan C., 2009. "Experiments on unemployment benefit sanctions and job search behavior," European Economic Review, Elsevier, vol. 53(8), pages 937-951, November.
    9. Jos'e Cl'audio do Nascimento, 2019. "Behavioral Biases and Nonadditive Dynamics in Risk Taking: An Experimental Investigation," Papers 1908.01709, arXiv.org, revised Apr 2023.
    10. Martín Egozcue & Sébastien Massoni & Wing-Keung Wong & RiÄ ardas Zitikis, 2012. "Integration-segregation decisions under general value functions: "Create your own bundle — choose 1, 2, or all 3!"," Documents de travail du Centre d'Economie de la Sorbonne 12057, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne.
    11. Howard Kunreuther & Erwann Michel-Kerjan, 2015. "Demand for fixed-price multi-year contracts: Experimental evidence from insurance decisions," Journal of Risk and Uncertainty, Springer, vol. 51(2), pages 171-194, October.
    12. Francesco GUALA, 2017. "Preferences: Neither Behavioural nor Mental," Departmental Working Papers 2017-05, Department of Economics, Management and Quantitative Methods at Università degli Studi di Milano.
    13. Shi, Yun & Cui, Xiangyu & Zhou, Xunyu, 2020. "Beta and Coskewness Pricing: Perspective from Probability Weighting," SocArXiv 5rqhv, Center for Open Science.
    14. Bin Zou, 2017. "Optimal Investment In Hedge Funds Under Loss Aversion," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 20(03), pages 1-32, May.
    15. Alex Stomper & Marie-Louise Vierø, 2015. "Iterated Expectations Under Rank-dependent Expected Utility And Model Consistency," Working Paper 1228, Economics Department, Queen's University.
    16. Liu, Zhiqiang & Yan, Miao & Fan, Youqing & Chen, Liling, 2021. "Ascribed or achieved? The role of birth order on innovative behaviour in the workplace," Journal of Business Research, Elsevier, vol. 134(C), pages 480-492.
    17. Kazi Iqbal & Asad Islam & John List & Vy Nguyen, 2021. "Myopic Loss Aversion and Investment Decisions: From the Laboratory to the Field," Framed Field Experiments 000730, The Field Experiments Website.
    18. Filiz-Ozbay, Emel & Guryan, Jonathan & Hyndman, Kyle & Kearney, Melissa & Ozbay, Erkut Y., 2015. "Do lottery payments induce savings behavior? Evidence from the lab," Journal of Public Economics, Elsevier, vol. 126(C), pages 1-24.
    19. Shuli Liu & Xinwang Liu, 2016. "A Sample Survey Based Linguistic MADM Method with Prospect Theory for Online Shopping Problems," Group Decision and Negotiation, Springer, vol. 25(4), pages 749-774, July.
    20. Nicholas Barberis, 2012. "A Model of Casino Gambling," Management Science, INFORMS, vol. 58(1), pages 35-51, January.

    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:3:d:10.1007_s10726-021-09723-4. 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.