文献类型：期刊文献

英文题名：Spatio-temporal Evolution Patterns and Differences in Driving Mechanisms of Urban Resilience in China's Three Major Urban Agglomerations

作者：Xu, Waner[1];Huang, Jianyi[1];Su, Fei[2];Yuan, Yitai[1];Wang, Mengyu[1]

第一作者：Xu, Waner

通讯作者：Huang, JY[1]

机构：[1]Beijing Union Univ, Coll Appl Arts & Sci, Beijing 100191, Peoples R China;[2]Zhejiang Gongshang Univ, Sch Tourism & Urban Rural Planning, Hangzhou 310018, Peoples R China

第一机构：北京联合大学应用文理学院

通讯机构：[1]corresponding author), Beijing Union Univ, Coll Appl Arts & Sci, Beijing 100191, Peoples R China.|[114172]北京联合大学应用文理学院;[11417]北京联合大学;

年份：2026

卷号：36

期号：6

起止页码：943-958

外文期刊名：CHINESE GEOGRAPHICAL SCIENCE

收录：;Scopus(收录号：2-s2.0-105042467775);WOS:【SCI-EXPANDED(收录号:WOS:001799840800010)】；

基金：Under the auspices of the National Natural Science Foundation of China (No. 42171206)

语种：英文

外文关键词：urban resilience; interpretative structural modeling method (ISM); urban agglomerations; entropy weight TOPSIS; China

摘要：Urban resilience is the ability of cities to maintain their core functions, recover quickly, and adapt to change in the face of external shocks such as natural disasters, economic crises and social change. With the acceleration of urbanization and the frequent occurrence of uncertain events, enhancing urban resilience has become an important issue in promoting sustainable urban development. Focusing on the three major urban agglomerations in China, this study utilizes the panel data of 49 cities from 2013-2022 to construct a multidimensional evaluation index system covering economic, social, ecological, and infrastructural resilience and comprehensively applies the entropy-weighted TOPSIS method, the coefficient of variation, and the interpretative structural model (ISM) to reveal their spatial and temporal evolutionary patterns as well as their intrinsic driving mechanisms. The results show that: 1) in terms of the mean value of resilience of the three major urban agglomerations, resilience shows a trend of 'the Pearl River Delta (PRD) > Yangtze River Delta (YRD) > Beijing-Tianjin-Hebei (BTH)'. All of them have experienced a decline from 2013 to 2017, a brief rebound from 2017 to 2019, and significant fluctuations during 2019-2022 due to the impact of major public health emergencies. Specifically, the overall resilience of the PRD is relatively high, the YRD demonstrates strong anti-disturbance capabilities, while the recovery process of the BTH lags behind relatively in terms of economic and social resilience. It is worth noting that the ecological resilience performs relatively stable among various urban agglomerations, which reflects the effectiveness of ecological governance since 2012; 2) the spatial heterogeneity within urban agglomerations is remarkable, with prominent differences in the 'core-periphery' gradient in BTH, a multi-center synergistic resilience network in YRD, and PRD characterized by the 'dual-core leadership', and unexpected events reflect that the difference in regional risk resistance within the PRD is greater than that in the YRD; 3) ISM analysis shows that the common point of the resilience driving mechanism of the three major urban agglomerations is that economic resilience occupies a central position in the resilience system of the urban agglomerations, but there are also stratified differences: BTH relies on people's wellbeing to drive the resilience system, the YRD focuses on the synergy between the economy and services, and the PRD shows a dual-layered structure pattern driven by the integration of 'foundation and industry'. This study provides a comparative empirical framework for understanding the dynamic evolution of urban resilience in China's major urban agglomerations and offers targeted policy insights for formulating regionally differentiated resilience planning and risk management strategies.