Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data
Under the development pattern of the “double cycle”, optimizing urban economic resilience is tremendously meaningful to improving a city’s affordability and the adaptability of the economy and to promoting the Chinese economy to develop with high quality. Based on Baidu migration big data perspecti...
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| Format: | Article |
| Language: | English |
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Vilnius Gediminas Technical University
2023-02-01
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| Series: | Technological and Economic Development of Economy |
| Subjects: | |
| Online Access: | https://journals.vilniustech.lt/index.php/TEDE/article/view/17869 |
| _version_ | 1811170065253400576 |
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| author | Yu Chen Keyang Li Qian Zhou |
| author_facet | Yu Chen Keyang Li Qian Zhou |
| author_sort | Yu Chen |
| collection | DOAJ |
| description |
Under the development pattern of the “double cycle”, optimizing urban economic resilience is tremendously meaningful to improving a city’s affordability and the adaptability of the economy and to promoting the Chinese economy to develop with high quality. Based on Baidu migration big data perspective, exploratory spatial data analysis (ESDA) and multi-scale geographical weighted regression (MGWR) model were used to analyze the spatial characteristics and driving factors of economic resilience in 287 Chinese cities in 2019. The results show that (1) the number of low-level economically resilient cities is the largest and distributed continuously, while the number of high-level economically resilient cities is the lowest and distributed in clusters and blocks; (2) compared with the Pearl River Delta and Yangtze River Delta, the population accumulation characteristic of the Beijing- Tianjin-Hebei region is relatively slow; (3) Both net inflow of population after spring festival and daily flow scale are significantly correlated with urban economic resilience, and the former will affect urban economic resilience; and (4) the spatial heterogeneity of each factor driving is significant, and they have different impact scales. The impact intensity is as follows: net population inflow > innovation ability > public financial expenditure > financial efficiency > urban size.
First published online 07 February 2023
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| first_indexed | 2024-04-10T16:51:22Z |
| format | Article |
| id | doaj.art-d34be42288434c9789631cd277355a97 |
| institution | Directory Open Access Journal |
| issn | 2029-4913 2029-4921 |
| language | English |
| last_indexed | 2024-04-10T16:51:22Z |
| publishDate | 2023-02-01 |
| publisher | Vilnius Gediminas Technical University |
| record_format | Article |
| series | Technological and Economic Development of Economy |
| spelling | doaj.art-d34be42288434c9789631cd277355a972023-02-07T16:15:59ZengVilnius Gediminas Technical UniversityTechnological and Economic Development of Economy2029-49132029-49212023-02-0110.3846/tede.2023.17869Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big dataYu Chen0Keyang Li1Qian Zhou2School of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, ChinaSchool of Economics and Management, Zhengzhou University of Light Industry, Zhengzhou, ChinaEconomics School, Zhongnan University of Economics and Law, Wuhan, China Under the development pattern of the “double cycle”, optimizing urban economic resilience is tremendously meaningful to improving a city’s affordability and the adaptability of the economy and to promoting the Chinese economy to develop with high quality. Based on Baidu migration big data perspective, exploratory spatial data analysis (ESDA) and multi-scale geographical weighted regression (MGWR) model were used to analyze the spatial characteristics and driving factors of economic resilience in 287 Chinese cities in 2019. The results show that (1) the number of low-level economically resilient cities is the largest and distributed continuously, while the number of high-level economically resilient cities is the lowest and distributed in clusters and blocks; (2) compared with the Pearl River Delta and Yangtze River Delta, the population accumulation characteristic of the Beijing- Tianjin-Hebei region is relatively slow; (3) Both net inflow of population after spring festival and daily flow scale are significantly correlated with urban economic resilience, and the former will affect urban economic resilience; and (4) the spatial heterogeneity of each factor driving is significant, and they have different impact scales. The impact intensity is as follows: net population inflow > innovation ability > public financial expenditure > financial efficiency > urban size. First published online 07 February 2023 https://journals.vilniustech.lt/index.php/TEDE/article/view/17869economic resiliencepopulation mobilityspatial differenceMulti-scale Geographical Weighted Regression (MGWR) |
| spellingShingle | Yu Chen Keyang Li Qian Zhou Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data Technological and Economic Development of Economy economic resilience population mobility spatial difference Multi-scale Geographical Weighted Regression (MGWR) |
| title | Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data |
| title_full | Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data |
| title_fullStr | Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data |
| title_full_unstemmed | Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data |
| title_short | Spatial differentiation of urban economic resilience and its influencing factors: evidence from Baidu migration big data |
| title_sort | spatial differentiation of urban economic resilience and its influencing factors evidence from baidu migration big data |
| topic | economic resilience population mobility spatial difference Multi-scale Geographical Weighted Regression (MGWR) |
| url | https://journals.vilniustech.lt/index.php/TEDE/article/view/17869 |
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