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An opinion evolution-based consensus-reaching model for large-scale group decision-making: Incorporating implicit trust and individual influence

题目An opinion evolution-based consensus-reaching model for large-scale group decision-making: Incorporating implicit trust and individual influence
作者Wang, Pei; Zhang, Jing; Lin, Youwu; Huang, Shuai; Xu, Xuanhua
作者单位Guangdong Univ Foreign Studies, Sch Business, Guangzhou 510006, Peoples R China Guangdong Univ Foreign Studies, Expt Teaching Ctr, Guangzhou 510006, Peoples R China Guilin Univ Elect Technol, Sch Math & Comp Sci, Guangxi Coll & Univ Key Lab Data Anal & Computat, Guilin 541004, Peoples R China Ctr Appl Math Guangxi GUET, Guilin 541002, Peoples R China Peking Univ, Guanghua Sch Management, Beijing 100871, Peoples R China Guangdong Univ Technol, Sch Management, Guangzhou 510520, Peoples R China Cent South Univ, Sch Business, Changsha 410083, Peoples R China
关键词：LEADERSHIP DYNAMICS
时间：2025年5月1日
出版者：COMPUTERS & INDUSTRIAL ENGINEERING
摘要Large-scale group decision-making (LGDM) often involves complex challenges, such as effectively clustering decision-makers, modeling asymmetric trust relationships, and balancing the influence of leaders and members to achieve consensus. This study proposes a novel opinion evolution-based consensus-reaching model to address these issues. A convex clustering method is developed, combining the strengths of K-means and hierarchical clustering to enable adaptive subgroup formation and automatic determination of the optimal number of clusters. Anew asymmetric implicit trust measure is developed by combining partnership dynamics with the Pearson Correlation Coefficient, providing a realistic representation of trust relationships. Furthermore, the model identifies leaders and members within each subgroup, quantifies their mutual influence through dynamic weights, and incorporates these dynamics into an improved Friedkin-Johnsen framework to allow for iterative preference adjustments and alignment toward consensus. The feasibility and validity of the proposed method are demonstrated through a case study and sensitivity analysis, highlighting its adaptability and effectiveness. Simulation experiments further validate the model, showing superior performance compared to existing methods.
URLhttp://hdl.handle.net/20.500.11897/742494
ISSN0360-8352
DOI10.1016/j.cie.2025.110974
收录情况EI SCI€
分类企业家精神
作者单位 Guangdong Univ Foreign Studies, Sch Business, Guangzhou 510006, Peoples R China Guangdong Univ Foreign Studies, Expt Teaching Ctr, Guangzhou 510006, Peoples R China Guilin Univ Elect Technol, Sch Math & Comp Sci, Guangxi Coll & Univ Key Lab Data Anal & Computat, Guilin 541004, Peoples R China Ctr Appl Math Guangxi GUET, Guilin 541002, Peoples R China Peking Univ, Guanghua Sch Management, Beijing 100871, Peoples R China Guangdong Univ Technol, Sch Management, Guangzhou 510520, Peoples R China Cent South Univ, Sch Business, Changsha 410083, Peoples R China 时间 2025年5月1日
出版者 COMPUTERS & INDUSTRIAL ENGINEERING URL http://hdl.handle.net/20.500.11897/742494
ISSN 0360-8352 DOI 10.1016/j.cie.2025.110974
收录情况 EI SCI€ 分类 企业家精神
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