@misc{10481/108648,
year = {2022},
month = {9},
url = {https://hdl.handle.net/10481/108648},
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.},
organization = {National Natural Science Foundation of China
(NSFC) (No. 71971135, 71971039 and 71910107002)},
organization = {Shanghai Maritime University (No. 2021YBR006)},
organization = {China Scholarship Council (No.202108310183)},
organization = {Shanghai Foreign Experts Program(22WZ2506100)},
organization = {MCIN/AEI/10.13039/501100011033 - Andalusian Government (PID2019-103880RB-I00)},
publisher = {Springer Nature},
keywords = {Social network large-group decision making},
keywords = {Consensus},
keywords = {Feedback mechanism},
title = {Consensus‑trust Driven Bidirectional Feedback Mechanism for Improving Consensus in Social Network Large‑group Decision Making},
doi = {10.1007/s10726-022-09798-7},
author = {Gai, Tiantian and Cao, Mingshuo and Chiclana Parrilla, Francisco and Zhang, Zhen and Dong, Yucheng and Herrera-Viedma, Enrique and Wu, Jian},
}