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Article type: Research Article
Authors: Cao, Jinga | Xu, Xuan-huaa; * | Dai, Feib | Pan, Binc; *
Affiliations: [a] School of Business, Central South University, Changsha, Hunan, China | [b] Department of Civil and Environmental Engineering, West Virginia University, US | [c] School of Accountancy, Hunan University of Finance and Economics, Changsha, Hunan, China
Correspondence: [*] Corresponding author. Xuan-hua Xu, School of Business, Central South University, Changsha, Hunan 410083, China. E-mail: [email protected]; Bin Pan, School of Accountancy, Hunan University of Finance and Economics, Changsha, Hunan 410205, China. E-mail: [email protected].
Abstract: This study uses opinion dynamics to explore the influence of extremists in the consensus process of large group decision-making. When moderates are exposed to extremists, their risk preference will be affected. By using the opinion leader theory for reference, the influence model of extremists is constructed. To better study the influence of extremists, the similarity of risk preference between extremists and moderates is modeled to measure their similarity degree. From this model, for every moderate, the extremists are divided into two groups: homogeneous group and heterogeneous group. Finally, the risk preference evolution model is structured by considering that moderates change their risk preference dynamically according to their initial preference, their attitude towards the homogeneous groups, and the heterogeneous groups. Finding from data analysis shows that moderates with high acceptance toward the influence of extremists are more likely to reach group consensus. It is also found that the preference trend of moderates with a certain degree of acceptance toward heterogeneous groups fluctuates with a ‘W’ shape. This study bridges the gap between opinion dynamics and group decision making. Meanwhile, the model inspires new explanations and new perspectives for the group consensus process.
Keywords: Extremists, opinion dynamics, group emergency decision-making, group consensus, risk preference evolution
DOI: 10.3233/JIFS-201106
Journal: Journal of Intelligent & Fuzzy Systems, vol. 39, no. 5, pp. 7733-7746, 2020
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