Consensus‑trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large‑group Decision Making Gai, Tiantian Cao, Mingshuo Chiclana Parrilla, Francisco Zhang, Zhen Dong, Yucheng Herrera-Viedma, Enrique Wu, Jian Social network large-group decision making Consensus Feedback mechanism 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. 2025-12-09T09:08:26Z 2025-12-09T09:08:26Z 2022-09-17 journal article Gai, T., Cao, M., Chiclana, F. et al. Consensus-trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large-group Decision Making. Group Decis Negot 32, 45–74 (2023). https://doi.org/10.1007/s10726-022-09798-7 https://hdl.handle.net/10481/108648 10.1007/s10726-022-09798-7 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Springer Nature