Location via proxy:   [ UP ]  
[Report a bug]   [Manage cookies]                
Skip to main content
Springer Nature Link
Log in

An Adaptive Core-Nash Bargaining Game Consensus Mechanism for Group Decision Making

  • Published:
Group Decision and Negotiation Aims and scope Submit manuscript

Abstract

As a process for ensuring the agreeable degree of individual opinions, consensus analysis is crucial for GDM. This paper focuses on the adaptive consensus mechanism. That's, different adjustment strategies are employed for various consensus levels. Unlike the feedback iteration method, this paper introduces an optimization model-based consensus-reaching procedure. To do this, optimal models are built to determine the minimum consensus adjustment at different levels. Then, the individual minimum consensus adjustment is analyzed, and the inconsistency between individual and group minimum consensus adjustments is concluded. After that, consensus adjustment cooperative games at three levels are proposed to allocate the total minimum consensus adjustment in view of the comprehensive evaluation. We can obtain the coalitional stability allocation scheme using the core of constructed cooperative games. Additionally, core-Nash bargaining games at three levels are proposed to ensure the fairness and coalitional stability of allocation results. Finally, a numerical example is offered to indicate the application of the new theoretical developments.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Subscribe and save

Springer+ Basic
$34.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or eBook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Algorithm 1

Similar content being viewed by others

References

  • Ben-Arieh D, Easton T (2007) Multi-criteria group consensus under linear cost opinion elasticity. Decis Support Syst 43(3):713–721

    Article  Google Scholar 

  • Cao M, Wu J, Chiclana F, Ureña R, Herrera-Viedma E (2021) A personalized consensus feedback mechanism based on maximum harmony degree. IEEE Trans Syst Man Cybern Syst 51(10):6134–6146

    Article  Google Scholar 

  • Chen S, Lee L, Yang S, Sheu T (2012) Adaptive consensus support model for group decision making systems. Expert Syst Appl 39(16):12580–12588

    Article  Google Scholar 

  • Chiclana F, Mata F, Martínez L, Herrera-Viedma E, Alonso S (2008) Integration of a consistency control module within a consensus decision making model. Int J Uncertain Fuzz 16(1):35–53

    Article  Google Scholar 

  • Dong Y, Xu Y, Li H, Feng B (2010) The OWA-based consensus operator under linguistic representation models using position indexes. Eur J Oper Res 203(2):455–463

    Article  Google Scholar 

  • Dong Y, Zhang H, Herrera-Viedma E (2016) Integrating experts’ weights generated dynamically into the consensus reaching process and its applications in managing non-cooperative behaviors. Decis Support Syst 84:1–15

    Article  Google Scholar 

  • Gou X, Xu Z, Wang X, Liao H (2021) Managing consensus reaching process with self-confident double hierarchy linguistic preference relations in group decision making. Fuzzy Optim Decis Ma 20(1):51–79

    Article  Google Scholar 

  • Herrera-Viedma E, Herrera F, Chiclana F (2002) A consensus model for multiperson decision making with different preference structures. IEEE Trans Syst Man Cy 32(3):394–402

    Article  Google Scholar 

  • Herrera-Viedma E, Martínez L, Mata F, Chiclana F (2005a) A consensus support system model for group decision-making problems with multigranular linguistic preference relations. IEEE Trans Fuzzy Syst 13(5):644–658

    Article  Google Scholar 

  • Herrera-Viedma E, Mata F, Martínez L, Pérez LG (2005b) An adaptive module for the consensus reaching process in group decision making problems. Springer, Berlin, pp 89–98

    Google Scholar 

  • Herrera-Viedma E, Alonso S, Chiclana F, Herrera F (2007) A consensus model for group decision making with incomplete fuzzy preference relations. IEEE Trans Fuzzy Syst 15(5):863–877

    Article  Google Scholar 

  • Ji F, Cao Q, Li H, Fujita H, Liang C, Wu J (2023) An online reviews-driven large-scale group decision making approach for evaluating user satisfaction of sharing accommodation. Expert Syst Appl 213:118875

    Article  Google Scholar 

  • Li S, Rodriguez RM, Wei C, Shu T (2022) A consensus model for large scale group decision making with hesitant fuzzy linguistic information and hierarchical feedback mechanism. Comput Ind Eng 173:108669

    Article  Google Scholar 

  • Liu P, Dong X, Wang P (2023) Limited budget-based consensus model for large group decision making with hesitant fuzzy linguistic information. Appl Soft Comput 142:110368

    Article  Google Scholar 

  • Mata F, Martínez L, Herrera-Viedma E (2009) An adaptive consensus support model for group decision-making problems in a multigranular fuzzy linguistic context. IEEE Trans Fuzzy Syst 17(2):279–290

    Article  Google Scholar 

  • Meng F, Zhao D, Tan C, Li Z (2023a) Ordinal-cardinal consensus analysis for large-scale group decision making with uncertain self-confidence. Inform Fusion 93:344–362

    Article  Google Scholar 

  • Meng F, Pedrycz W, Tang J (2023b) Consensus reaching process for traditional group decision making in view of the optimal adjustment mechanism. IEEE Trans Cybern 53(6):3748–3759

    Article  Google Scholar 

  • Meng F, Gong Z, Pedrycz W, Chu J (2023c) Selfish-dilemma consensus analysis for group decision making in the perspective of cooperative game theory. Eur J Oper Res 308:290–305

    Article  Google Scholar 

  • Meng F, Tang J, An Q (2023d) Cooperative game based two-stage consensus adjustment mechanism for large-scale group decision making. Omega 117:102842

    Article  Google Scholar 

  • Nash J (1950) The bargaining problem. Econometrica 18(2):155–162

    Article  Google Scholar 

  • Nash J (1953) Two-person cooperative games. Econometrica 21(1):128–140

    Article  Google Scholar 

  • Okada A (2010) The Nash bargaining solution in general n-person cooperative games. J Econ Theory 145(6):2356–2379

    Article  Google Scholar 

  • Shapley LS (1967) On balanced sets and cores. Nav Res Log 14(4):453–460

    Article  Google Scholar 

  • Sun Q, Chiclana F, Wu J, Liu Y, Liang C, Herrera-Viedma E (2023) Weight penalty mechanism for non-cooperative behavior in large-scale group decision making with unbalanced linguistic term sets. IEEE Trans Fuzzy Syst 31:3507–3521

    Article  Google Scholar 

  • Tang J, Chen S, Meng F (2019) Heterogeneous group decision making in the setting of incomplete preference relations. Inf Sci 483:396–418

    Article  Google Scholar 

  • Tang M, Liao H, Xu J, Streimikiene D, Zheng X (2020) Adaptive consensus reaching process with hybrid strategies for large-scale group decision making. Eur J Oper Res 282:957–971

    Article  Google Scholar 

  • Tang M, Liao H, Mi X, Lev B, Pedrycz W (2021) A hierarchical consensus reaching process for group decision making with noncooperative behaviors. Eur J Oper Res 293:632–642

    Article  Google Scholar 

  • Wan S, Rao T, Dong J (2023) Time-series based multi-criteria large-scale group decision making with intuitionistic fuzzy information and application to multi-period battery supplier selection. Expert Syst Appl 232:120749

    Article  Google Scholar 

  • Wu Y, Dong Y, Qin J, Pedrycz W (2020) Flexible linguistic expressions and consensus reaching with accurate constraints in group decision-making. IEEE Trans Cybern 50(6):2488–2501

    Article  Google Scholar 

  • Yager RR (1988) On ordered weighted averaging aggregation operators in multicriteria decision making. IEEE Trans Syst Man Cybern 18(1):183–190

    Article  Google Scholar 

  • Yin L, Zhang Q, Wu C, Mou Q (2024) Novel three-way decision model in medical diagnosis based on inexact reasoning. Eng Appl Artif Intel 130:107731

    Article  Google Scholar 

  • Zhang G, Dong Y, Xu Y (2012) Linear optimization modeling of consistency issues in group decision making based on fuzzy preference relations. Expert Syst Appl 39(3):2415–2420

    Article  Google Scholar 

  • Zhang H, Xiao J, Dong Y (2019) Integrating a consensus-reaching mechanism with bounded confidences into failure mode and effect analysis under incomplete context. Knowl Based Syst 183:104873

    Article  Google Scholar 

  • Zhang H, Dong Y, Chiclana F, Yu S (2019b) Consensus efficiency in group decision making: a comprehensive comparative study and its optimal design. Eur J Oper Res 275:580–598

    Article  Google Scholar 

  • Zhang B, Dong Y, Zhang H, Pedrycz W (2020) Consensus mechanism with maximum-return modifications and minimum-cost feedback: a perspective of game theory. Eur J Oper Res 287:546–559

    Article  Google Scholar 

Download references

Acknowledgements

This work was supported by the National Natural Science Foundation of China (No. 72371134), the Ministry of Education Humanities and Social Science Foundation of China (No. 22YJ630061), the National Social Science Fund of China (No. 22BJY019), the Natural Science Foundation of Hunan Province of China (No. 2024JJ5451), and the Startup Foundation for Introducing Talent of NUIST (Nos. 2020r001, 2020r059).

Author information

Authors and Affiliations

  1. School of Management Science and Engineering, Nanjing University of Information Science and Technology, Nanjing, 210044, China

    Jie Tang

  2. School of Business, Central South University, Changsha, 410083, China

    Fanyong Meng

Authors
  1. Jie Tang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Fanyong Meng
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Fanyong Meng.

Ethics declarations

Conflict of interest

The authors declare that they have no conflict of interest.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Tang, J., Meng, F. An Adaptive Core-Nash Bargaining Game Consensus Mechanism for Group Decision Making. Group Decis Negot 33, 805–837 (2024). https://doi.org/10.1007/s10726-024-09888-8

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s10726-024-09888-8

Keywords