考虑专家权威程度和社会网络下关系演变的大规模群体决策模型

IF 3.6 4区 管理学 Q2 MANAGEMENT
Hong Huo, Ruinan Sun, Hao He, Zongwei Ren
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引用次数: 0

摘要

在大规模群体决策(LSGDM)中,有效实施共识模型对于管理决策的复杂性至关重要。虽然基于信任的 LSGDM 已引起关注,但仍需深入了解专家间信任的动态以及权威效应对决策过程的影响。本研究为大规模群体决策引入了一个复杂的模型,将专家的 "可信度-权威性 "考虑在内。首先,研究根据社会网络关系和意见相似性来评估专家的可信度,同时利用背景信息和共识水平来确定专家的权威性。随后,根据专家的可信度和权威性评估结果,将专家分为四个不同的区域。此外,基于社会传染理论,为每个区域提出了量身定制的共识调整方法,以促进共识的达成。此外,考虑到专家的 "可信度-权威性",通过案例研究证明了所提出的 LSGDM 模型的合理性和有效性。最后,通过对比分析和敏感性分析,进一步验证了所提模型的必要性和优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

A Large-Scale Group Decision-Making Model Considering Expert Authority Degree and Relationship Evolution Under Social Network

A Large-Scale Group Decision-Making Model Considering Expert Authority Degree and Relationship Evolution Under Social Network

In Large-Scale Group Decision-Making (LSGDM), effectively implementing consensus models is pivotal for managing decision complexity. While trust-based LSGDM has garnered attention, there remains a need for deeper insights into the dynamics of interexpert trust and the impact of authority effects on the decision-making process. This study introduces a sophisticated model for large-scale group decision-making, incorporating considerations of expert “trustworthiness-authority.” Initially, the study assesses the trustworthiness of experts based on social network relationships and opinion similarity while using background information and consensus levels to establish their authority. Subsequently, experts are categorized into four distinct regions based on their trustworthiness and authority assessments. Furthermore, tailored consensus adjustment methods are proposed for each region based on social contagion theory to facilitate consensus achievement. Additionally, a case study is conducted to demonstrate the rationality and effectiveness of the proposed LSGDM model, considering expert “trustworthiness-authority.” Finally, the necessity and superiority of the proposed model are further verified through comparison analysis and sensitivity analysis.

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来源期刊
CiteScore
5.70
自引率
6.70%
发文量
32
期刊介绍: The idea underlying the journal, Group Decision and Negotiation, emerges from evolving, unifying approaches to group decision and negotiation processes. These processes are complex and self-organizing involving multiplayer, multicriteria, ill-structured, evolving, dynamic problems. Approaches include (1) computer group decision and negotiation support systems (GDNSS), (2) artificial intelligence and management science, (3) applied game theory, experiment and social choice, and (4) cognitive/behavioral sciences in group decision and negotiation. A number of research studies combine two or more of these fields. The journal provides a publication vehicle for theoretical and empirical research, and real-world applications and case studies. In defining the domain of group decision and negotiation, the term `group'' is interpreted to comprise all multiplayer contexts. Thus, organizational decision support systems providing organization-wide support are included. Group decision and negotiation refers to the whole process or flow of activities relevant to group decision and negotiation, not only to the final choice itself, e.g. scanning, communication and information sharing, problem definition (representation) and evolution, alternative generation and social-emotional interaction. Descriptive, normative and design viewpoints are of interest. Thus, Group Decision and Negotiation deals broadly with relation and coordination in group processes. Areas of application include intraorganizational coordination (as in operations management and integrated design, production, finance, marketing and distribution, e.g. as in new products and global coordination), computer supported collaborative work, labor-management negotiations, interorganizational negotiations, (business, government and nonprofits -- e.g. joint ventures), international (intercultural) negotiations, environmental negotiations, etc. The journal also covers developments of software f or group decision and negotiation.
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