Study on the Spatial Association Network Structure of Urban Digital Economy and Its Driving Factors in Chinese Cities DOI Creative Commons
Wei Yang,

Meihui Yan,

Xiaohe Wang

et al.

Systems, Journal Year: 2025, Volume and Issue: 13(5), P. 322 - 322

Published: April 27, 2025

The digital economy has become an important engine for global economic development by promoting optimal resource allocation and advancing industrial restructuring. Based on the panel data from 279 prefecture-level cities in China 2012 to 2021, this paper constructs spatial association networks of urban using a modified gravity model analyzes complex network characteristics driving factors growth social analysis methods Quadratic Assignment Procedure (QAP). This study finds that (1) level shows rising trend year displays uneven distribution. (2) Spatial are relatively well-connected, with increasing density stability associations, yet some hierarchical structure remains, overall connectivity still needs be improved. (3) Most east region occupy core positions within network, significantly influencing through “siphon effect”, while central play more “bridge” role network. In contrast, northwest, northeast, southwest regions situated periphery (4) level, informatization technological innovation, urbanization structure, human capital contribute formation economy. these conclusions, specific policy implications future proposed.

Language: Английский

Study on the Spatial Association Network Structure of Urban Digital Economy and Its Driving Factors in Chinese Cities DOI Creative Commons
Wei Yang,

Meihui Yan,

Xiaohe Wang

et al.

Systems, Journal Year: 2025, Volume and Issue: 13(5), P. 322 - 322

Published: April 27, 2025

The digital economy has become an important engine for global economic development by promoting optimal resource allocation and advancing industrial restructuring. Based on the panel data from 279 prefecture-level cities in China 2012 to 2021, this paper constructs spatial association networks of urban using a modified gravity model analyzes complex network characteristics driving factors growth social analysis methods Quadratic Assignment Procedure (QAP). This study finds that (1) level shows rising trend year displays uneven distribution. (2) Spatial are relatively well-connected, with increasing density stability associations, yet some hierarchical structure remains, overall connectivity still needs be improved. (3) Most east region occupy core positions within network, significantly influencing through “siphon effect”, while central play more “bridge” role network. In contrast, northwest, northeast, southwest regions situated periphery (4) level, informatization technological innovation, urbanization structure, human capital contribute formation economy. these conclusions, specific policy implications future proposed.

Language: Английский

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