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考虑非合作行为的社会网络大群体共识决策模型

楚俊峰1, 鲁亚南1, 王燕燕2   

  1. 1. 福州大学经济与管理学院, 福州 350000;
    2. 福建农林大学经济管理学院, 福州 350000
  • 收稿日期:2022-07-04 修回日期:2022-11-01 发布日期:2023-05-18
  • 通讯作者: 楚俊峰, Email:chujunfeng1987@163.com
  • 基金资助:
    国家自然科学基(72201066),福建省自然科学基金(2020J01463)资助课题.

楚俊峰, 鲁亚南, 王燕燕. 考虑非合作行为的社会网络大群体共识决策模型[J]. 系统科学与数学, 2023, 43(4): 961-981.

CHU Junfeng, LU Yanan, WANG Yanyan. A Large-Group Consensus Decision-Making Model in Social Networks Considering Non-Cooperative Behaviors[J]. Journal of Systems Science and Mathematical Sciences, 2023, 43(4): 961-981.

A Large-Group Consensus Decision-Making Model in Social Networks Considering Non-Cooperative Behaviors

CHU Junfeng1, LU Yanan1, WANG Yanyan2   

  1. 1. School of Economics and Management, Fuzhou University, Fuzhou 350000;
    2. School of Economics and Management, Fujian Agriculture and Forestry University, Fuzhou 350000
  • Received:2022-07-04 Revised:2022-11-01 Published:2023-05-18
在社会网络环境下的大群体决策问题当中,决策专家之间的社会网络关系对决策过程和结果的影响至关重要.文章创新地提出一种考虑决策专家社会网络关系和非合作行为的大群体共识决策模型,有效促进大群体共识的达成.首先,根据决策专家的偏好信息和社会网络关系,改进经典Louvain社区发现算法,对大决策群体进行社区划分.其次,运用社会网络分析方法确定决策专家个体和社区的权重.随后,根据决策专家的偏离程度对决策专家非合作行为进行识别,并考虑社会网络关系的影响对非合作行为进行管理,以此构建共识决策模型.最后,通过案例分析来验证所建立共识决策模型的可行性和有效性.文章构建的共识决策模型,不仅在大群体社区划分过程中,创新性地同时考虑决策专家的偏好信息和社会网络关系的影响,并且在非合作行为管理过程中,也考虑到了社会网络关系对非合作行为决策专家偏好调整的影响,使其更适应社会网络决策环境.
In the large group decision-making problem under the social network environment, the social network relationship between decision experts is crucial to the decision-making process and results. This paper innovatively proposes a large group consensus decision-making model that considers decision-making experts’ social network relationships and non-cooperative behaviors. And it effectively promotes the reaching of large group consensus. First, according to decision experts’ preference information and social network relationships, we improve the classical Louvain community discovery algorithm to divide the large decision group into communities. Second, through social network analysis, we determine the weights of individual decision-making experts and communities. Then, according to the deviation degree of decision-making experts, we identify the non-cooperative behaviors of decision-making experts. And we consider the influence of social network relationships to manage non-cooperative behaviors. Based on this, we build a consensus decision-making model. Finally, we verify the feasibility and effectiveness of the established consensus decision-making model through case analysis. The consensus decision-making model constructed in this paper innovatively considers the influence of preference information and decision-making experts’ social network relationship in the large group community division process. Moreover, it also considers the influence of social network relationships on the preference adjustment of non-cooperative decision-making experts in the process of non-cooperative behavior management. It is more suitable for the social network decision-making environment.

MR(2010)主题分类: 

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