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

Tiantian Gai (), Mingshuo Cao (), Francisco Chiclana (), Zhen Zhang (), Yucheng Dong (), Enrique Herrera-Viedma () and Jian Wu ()
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Tiantian Gai: Shanghai Maritime University
Mingshuo Cao: Shanghai Maritime University
Francisco Chiclana: De Montfort University
Zhen Zhang: Dalian University of Technology
Yucheng Dong: Sichuan University
Enrique Herrera-Viedma: University of Granada
Jian Wu: Shanghai Maritime University

Group Decision and Negotiation, 2023, vol. 32, issue 1, No 3, 45-74

Abstract: 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.

Keywords: Social network large-group decision making; Consensus; Feedback mechanism; Bidirectional interaction; Trust (search for similar items in EconPapers)
Date: 2023
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Citations: View citations in EconPapers (2)

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DOI: 10.1007/s10726-022-09798-7

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