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Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model

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  • Yu Chen

    (School of Economics and Management, Zhengzhou University of Light Industry, Science Avenue 136, Zheng Zhou 450000, China)

  • Mengke Zhu

    (School of Economics and Management, Zhengzhou University of Light Industry, Science Avenue 136, Zheng Zhou 450000, China)

  • Qian Zhou

    (Economics School, Zhongnan University of Economics and Law, Nanhu Avenue 182, Wuhan 430073, China)

  • Yurong Qiao

    (School of Economics and Management, Zhengzhou University of Light Industry, Science Avenue 136, Zheng Zhou 450000, China)

Abstract

Urban resilience in the context of COVID-19 epidemic refers to the ability of an urban system to resist, absorb, adapt and recover from danger in time to hedge its impact when confronted with external shocks such as epidemic, which is also a capability that must be strengthened for urban development in the context of normal epidemic. Based on the multi-dimensional perspective, entropy method and exploratory spatial data analysis (ESDA) are used to analyze the spatiotemporal evolution characteristics of urban resilience of 281 cities of China from 2011 to 2018, and MGWR model is used to discuss the driving factors affecting the development of urban resilience. It is found that: (1) The urban resilience and sub-resilience show a continuous decline in time, with no obvious sign of convergence, while the spatial agglomeration effect shows an increasing trend year by year. (2) The spatial heterogeneity of urban resilience is significant, with obvious distribution characteristics of “high in east and low in west”. Urban resilience in the east, the central and the west are quite different in terms of development structure and spatial correlation. The eastern region is dominated by the “three-core driving mode”, and the urban resilience shows a significant positive spatial correlation; the central area is a “rectangular structure”, which is also spatially positively correlated; The western region is a “pyramid structure” with significant negative spatial correlation. (3) The spatial heterogeneity of the driving factors is significant, and they have different impact scales on the urban resilience development. The market capacity is the largest impact intensity, while the infrastructure investment is the least impact intensity. On this basis, this paper explores the ways to improve urban resilience in China from different aspects, such as market, technology, finance and government.

Suggested Citation

  • Yu Chen & Mengke Zhu & Qian Zhou & Yurong Qiao, 2021. "Research on Spatiotemporal Differentiation and Influence Mechanism of Urban Resilience in China Based on MGWR Model," IJERPH, MDPI, vol. 18(3), pages 1-26, January.
    • Handle: RePEc:gam:jijerp:v:18:y:2021:i:3:p:1056-:d:486700
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    References listed on IDEAS

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    1. Abhas K. Jha & Todd W. Miner & Zuzana Stanton-Geddes, 2013. "Building Urban Resilience : Principles, Tools, and Practice," World Bank Publications - Books, The World Bank Group, number 13109.
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    2. Peng Cui & Yi Liu & Xuan Ju & Tiantian Gu, 2022. "Key Influencing Factors and Optimization Strategy of Epidemic Resilience in Urban Communities—A Case Study of Nanjing, China," IJERPH, MDPI, vol. 19(16), pages 1-20, August.
    3. Xiaoling Ke & Yuanyuan Min & Haixiang Guo & Deyun Wang & Amal Mougharbel, 2024. "What impact does the new urbanization in China’s Yangtze River economic belt have on the ecological environment?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(10), pages 26679-26698, October.
    4. Yanning Si & Lizhi Liang & Wenguang Zhou, 2024. "An Evaluation of Urban Resilience Using Structural Equation Modeling from Practitioners’ Perspective: An Empirical Investigation in Huangshi City, China," Sustainability, MDPI, vol. 16(16), pages 1-19, August.
    5. Weihao Shi & Jian Tian & Aihemaiti Namaiti & Xiaoxu Xing, 2022. "Spatial-Temporal Evolution and Driving Factors of the Coupling Coordination between Urbanization and Urban Resilience: A Case Study of the 167 Counties in Hebei Province," IJERPH, MDPI, vol. 19(20), pages 1-27, October.
    6. Jianhong Fan & You Mo & Yunnan Cai & Yabo Zhao & Dongchen Su, 2021. "Evaluation of Community Resilience in Rural China—Taking Licheng Subdistrict, Guangzhou as an Example," IJERPH, MDPI, vol. 18(11), pages 1-15, May.
    7. Ying Zhou & Qihao Su & Yulian Li & Xingwei Li, 2022. "Spatial-Temporal Characteristics of Multi-Hazard Resilience in Ecologically Fragile Areas of Southwest China: A Case Study in Aba," IJERPH, MDPI, vol. 19(19), pages 1-21, September.
    8. Rastko Jovanović & Miloš Davidović & Ivan Lazović & Maja Jovanović & Milena Jovašević-Stojanović, 2021. "Modelling Voluntary General Population Vaccination Strategies during COVID-19 Outbreak: Influence of Disease Prevalence," IJERPH, MDPI, vol. 18(12), pages 1-18, June.
    9. Zihan Tong & Zhenxing Kong & Xiao Jia & Hanyue Zhang & Yimin Zhang, 2022. "Multiscale Impact of Environmental and Socio-Economic Factors on Low Physical Fitness among Chinese Adolescents and Regionalized Coping Strategies," IJERPH, MDPI, vol. 19(20), pages 1-24, October.
    10. Yu Chen & Shuangshuang Liu & Wenbo Ma & Qian Zhou, 2023. "Assessment of the Carrying Capacity and Suitability of Spatial Resources and the Environment and Diagnosis of Obstacle Factors in the Yellow River Basin," IJERPH, MDPI, vol. 20(4), pages 1-26, February.
    11. Yu Chen & Keyang Li & Qian Zhou & Yuxin Zhang, 2022. "Can Population Mobility Make Cities More Resilient? Evidence from the Analysis of Baidu Migration Big Data in China," IJERPH, MDPI, vol. 20(1), pages 1-25, December.
    12. Jie Huang & Zimin Sun & Minzhe Du, 2022. "Differences and Drivers of Urban Resilience in Eight Major Urban Agglomerations: Evidence from China," Land, MDPI, vol. 11(9), pages 1-18, September.
    13. Hin Yu Micah Cheung, 2024. "Enriching Regional Economic Dynamics through a Knowledge-Driven Spatial Analysis Model: a Deep Learning Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 12293-12336, September.
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    15. Yu Chen & Xuyang Su & Xuekai Wang, 2022. "Spatial Transformation Characteristics and Conflict Measurement of Production-Living-Ecology: Evidence from Urban Agglomeration of China," IJERPH, MDPI, vol. 19(3), pages 1-20, January.

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