An Incentive Mechanism-Based Minimum Adjustment Consensus Model Under Dynamic Trust Relationship

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dc.contributor.authorXing, Yumei
dc.contributor.authorWu, Jian
dc.contributor.authorChiclana, Francisco
dc.contributor.authorLiang, Changyong
dc.contributor.authorYager, Ronald R.
dc.date.acceptance2023-12-30
dc.date.accessioned2024-02-08T14:00:02Z
dc.date.available2024-02-08T14:00:02Z
dc.date.issued2024-01-24
dc.descriptionThe file attached to this record is the author's final peer reviewed version. The Publisher's final version can be found by following the DOI link.
dc.description.abstractIn traditional group decision making, the inconsistent experts are usually forced to make compromises toward the group opinion to increase the group consensus level. However, the strategy of reaching group consensus via an incentive mechanism encouraging adjustment of preferences is more effective than forcing, which is the aim of this article. Specifically, this article establishes a novel incentive mechanism to support group consensus under dynamic trust relationship. First, the supremum and infimum incentives-based rule driven by trust relationship is defined. Based on the assumption that if incentive conditions are met, then experts will be willing to adjust their preferences, the incentive behavior-driven minimum adjustment consensus model is developed to generate optimal incentive-based recommendation preferences. Thus, the proposed incentive mechanism can effectively reduce the preference adjustment cost and promote group consensus reaching. Third, the updated trust relationships between experts are shown to be strengthen by the proposed incentive-driven preference revision. Consequently, the optimization model based on trust interaction relationship is constructed to obtain the final group preference matrix. Finally, a supplier selection case of high-end medical equipment is provided to illustrate the proposed method and show the rationality and advantages of the proposed methodology with both a sensitivity analysis and a comparison analysis.
dc.funderNo external funder
dc.identifier.citationXing, Y., Wu, J., Chiclana, F., Liang, C. and Yager, R.R. (2024) An incentive mechanism based minimum adjustment consensus model under dynamic trust relationship. IEEE Transactions on Cybernetics,
dc.identifier.doihttps://doi.org/10.1109/TCYB.2023.3349257
dc.identifier.issn2168-2267
dc.identifier.issn2168-2275
dc.identifier.urihttps://hdl.handle.net/2086/23522
dc.language.isoen
dc.peerreviewedYes
dc.publisherIEEE
dc.relation.ispartofIEEE Transactions on Cybernetics
dc.researchinstituteInstitute of Artificial Intelligence (IAI)
dc.rightsAttribution-NonCommercial-NoDerivs 2.0 UK: England & Walesen
dc.rights.urihttp://creativecommons.org/licenses/by-nc-nd/2.0/uk/
dc.titleAn Incentive Mechanism-Based Minimum Adjustment Consensus Model Under Dynamic Trust Relationship
dc.typeArticle

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