Distrust Behavior in Social Network Large-Scale Group Decision Making and Its Application in Water Pollution Management

Author:

Lu Yanling1,Liu Gaofeng1,Xu Yejun2ORCID

Affiliation:

1. Business School, Hohai University, Nanjing 210000, China

2. College of Management and Economics, Tianjin University, Tianjin 300072, China

Abstract

Distrust behavior is a human behavior that has a significant impact on water pollution management, but it is neglected in existing approaches. To solve this problem, we design a large-scale group decision making in social network (LSGDM-SN) approach based on distrust behavior and apply it to water pollution management. The purpose of this paper is to develop an LSGDM-SN method to assist managers choose the optimal water pollution management plan. In the presented method, fuzzy preference relations (FPRs) are used to express experts’ assessment of alternatives. To utilize the proposed LSGDM-SN approach to solve the water pollution problem, a novel agglomerative hierarchical clustering (AHC) method is proposed by combing preference similarity and social relationships. Afterward, consensus feedback based on distrust behavior and social network analysis (SNA) is developed to encourage the subset to modify its FPR. A mechanism for the identification and management of distrust behavior is introduced. Based on the situations of distrust behaviors, two pieces of feedback advice are provided to the subset to adjust its FPR. Subsequently, a score function of the FPR is proposed to obtain the best solution for water pollution management. Finally, some comparative analyses and discussions demonstrate the effectiveness and feasibility of the proposed method.

Publisher

MDPI AG

Subject

Water Science and Technology,Aquatic Science,Geography, Planning and Development,Biochemistry

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Trust Improvement Consensus Model Considering Unreliability Degree of Opinions with Hesitant Fuzzy Sets;International Journal of Computational Intelligence Systems;2024-05-13

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