Affiliations:
College of Economics and Management, Taiyuan University of Technology, Taiyuan, China
Correspondence:
[*]
Corresponding author. Weijing Liang, College of Economics and
Management, Taiyuan University of Technology, Taiyuan 030024, China.
Tel.:+86 15135154399; E-mail: liangweijing@ncst.edu.cn.
Abstract: With the increasing global disaster risks, constructing more inclusive, flexible, and resilient communities has become crucial for effectively carrying out disaster prevention, mitigation, and relief work. However, existing research on community resilience mostly focuses on the selection of key factors and the assessment of community resilience, lacking in-depth exploration of the interactions between factors and simulation studies of key paths. Therefore, this paper applies the Fuzzy Decision-Making Trial and Evaluation Laboratory (Fuzzy DEMATEL) method to select important factors of community resilience. Based on this, the maximum average difference entropy method is used to analyze the relationships and influence mechanisms among different factors, thus identifying the key factors and key paths affecting community resilience. The Fuzzy Cognitive Map (FCM) is then used to simulate the paths. The study finds that factors of community resilience can be categorized as input, intermediary, and output types, and further analysis of their influence mechanisms reveals four key paths and four key factors. Through pathway simulation, different improvement states of community resilience are observed when triggering the input-type factors of the key paths. Therefore, under limited resources, a phased and systematic approach to enhancing community resilience should be adopted. The contribution of this study lies in providing a comprehensive analysis of factors and pathway selection methods, and through pathway simulation, it offers a scientific basis and decision support for improving and constructing community resilience in practice.
Keywords: Fuzzy cognitive map, fuzzy
DEMATEL, maximum average difference entropy method, community
resilience, simulation analysis
