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Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making

Author

Listed:
  • Tiantian Gai

    (Shanghai Maritime University)

  • Mingshuo Cao

    (Shanghai Maritime University)

  • Francisco Chiclana

    (De Montfort University
    University of Granada)

  • Zhen Zhang

    (Dalian University of Technology)

  • Yucheng Dong

    (Sichuan University)

  • Enrique Herrera-Viedma

    (University of Granada
    King Abdulaziz University)

  • Jian Wu

    (Shanghai Maritime University)

Abstract

This paper proposes a consensus-trust driven framework of bidirectional interaction for social network large-group decision making. Firstly, the concepts of interaction consensus threshold and interaction trust threshold are defined, which are used to discriminate the interaction modes between subgroups into four categories. Corresponding hybrid feedback strategies are designed in which the consensus level and trust level of subgroups are regarded as reliable resources to facilitate the achievement of group consensus. Secondly, a minimum adjustment bidirectional feedback model considering cohesion is developed to help the interacting subgroups reach mutual consensus with minimum opinion modification. Finally, the proposed consensus framework is applied to a blockchain platform selection problem in supply chain to demonstrate the effectiveness and applicability of the model.

Suggested Citation

  • Tiantian Gai & Mingshuo Cao & Francisco Chiclana & Zhen Zhang & Yucheng Dong & Enrique Herrera-Viedma & Jian Wu, 2023. "Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making," Group Decision and Negotiation, Springer, vol. 32(1), pages 45-74, February.
    • Handle: RePEc:spr:grdene:v:32:y:2023:i:1:d:10.1007_s10726-022-09798-7
    DOI: 10.1007/s10726-022-09798-7
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    References listed on IDEAS

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    Cited by:

    1. Wenfeng Zhu & Hengjie Zhang & Jing Xiao, 2023. "Coming to Consensus on Classification in Flexible Linguistic Preference Relations: The Role of Personalized Individual Semantics," Group Decision and Negotiation, Springer, vol. 32(5), pages 1237-1271, October.

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