Affiliation:
1. School of Business, Fuyang Normal University, Fuyang 236037, China
2. School of Marxism, Fuyang Normal University, Fuyang 236037, China
3. Ginling College, Nanjing Normal University, Nanjing 210000, China
Abstract
Promoting the development of China’s digital economy and the level of urban disaster reduction and governance is of great significance for accelerating the improvement of China’s urban resilience and promoting the coordinated development of regional cities. This paper analyzed the spatial and temporal distribution characteristics and driving paths of urban resilience in 31 Chinese provinces, autonomous regions, and municipalities directly under the central government and proposed relevant measures to promote urban resilience. First, the urban resilience evaluation system was constructed and the entropy value method was applied to calculate the urban resilience index of each region. Second, the spatial distribution of urban resilience was explored based on the urban resilience index of each region. Finally, a qualitative comparative analysis method was used to explore the driving paths of urban resilience enhancement. The study showed that there were large regional differences in the urban resilience index, with an overall spatial pattern of “good in the east, middle in the center, and low in the west” and an overall trend of gradual increase. There are five configuration paths to generate a high urban resilience index, which can be specifically digital industry-driven path, technology factor-driven path, government input- and talent pool-driven path under market factors, technology factor- and government factor-driven path, and government investment- and infrastructure-driven path under market factors, and it is found that the digital industry-driven path is a more common path of digital economy-driven urban resilience improvement in China. The finding of this study reveals the nature of complex interactions among drivers in the process of urban resilience enhancement in China, which breaks through the limitations of traditional statistical analysis methods and provides a new perspective for the study of urban resilience issues.
Funder
National Natural Science Foundation of China
Cited by
1 articles.
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