Research on Regional Resilience After Flood-Waterlogging Disasters Under the Concept of Urban Resilience Based on DEMATEL-TOPSIS-AISM

Hong Zhang (), Jiahui Luo and Wenlong Li
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Hong Zhang: School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Jiahui Luo: School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, China
Wenlong Li: School of Urban Economics and Management, Beijing University of Civil Engineering and Architecture, Beijing 100044, China

Sustainability, 2025, vol. 17, issue 21, 1-21

Abstract: Under the dual pressures of global climate change and accelerated urbanization, the impacts of flood disasters on urban systems are becoming increasingly pronounced. Enhancing regional resilience has emerged as a critical factor in achieving sustainable urban development. Compared with existing methods such as CRITIC–Entropy, PCA–AHP, or SWMM-based resilience evaluations, grounded in urban resilience theory, this study takes Fangshan District in Beijing as empirical research to construct a post-flood disaster resilience evaluation index system spanning five dimensions (ecological, social, engineering, economic, and institutional) and leverages the integrated DEMATEL-TOPSIS-AISM model to synergistically identify key drivers, evaluate performance, and uncover internal hierarchies, thereby overcoming the limitations of existing research approaches. The findings indicate that the DEMATEL analysis identified the frequency of heavy rainfall (a12 = 0.889) and the proportion of flood disaster information databases (c51 = 1.153) as key driving factors. The TOPSIS assessment reveals that Fangshan District exhibits the strongest resilience in the economic dimension (Relative Closeness C = 0.21200), while the institutional dimension is the weakest (C = 0.00000), the AISM model constructs a hierarchical topology from a cause–effect priority perspective, elucidating the causal relationships and transmission mechanisms among factors across different dimensions. This study pioneers a novel perspective for urban resilience assessment, thereby establishing a theoretical foundation and practical references for enhancing flood resilience and advancing resilient city development.

Keywords: flood-waterlogging disasters; urban resilience; Decision-Making Trial and Evaluation Laboratory; Technique for Order Preference by Similarity to Ideal Solution; Adversarial Interpretive Structural Modeling Method; resilience; index system (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2025
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