The digital economy injects developmental momentum into urban–rural integration through technological penetration, while urban–rural integration expands application scenarios for the digital economy via spatial restructuring. By clarifying the coupling coordination mechanism between these two subsystems, this study employs the coupling coordination degree model, spatial autocorrelation analysis, Markov chain, and spatiotemporal geographically weighted regression model to systematically investigate the development levels of the digital economy and urban–rural integration, the dynamic evolution characteristics of their coupling coordination degree, and the spatiotemporal heterogeneity of influencing factors across 31 provinces of China from 2012 to 2022. The main findings are as follows: (1) The digital economy level exhibited a pronounced upward trajectory with substantial inter-provincial disparities, while urban–rural integration level displayed a modest upward trend accompanied by evident polarization. (2) The coupling coordination degree increased steadily, with the number of provinces experiencing moderate and mild imbalance declining markedly and the contiguous zone of near imbalance expanding. Spatially, the pattern was characterized as “high in the east, low in the west.” (3) The coupling coordination degree exhibited significant positive spatial correlation. High-High agglomeration was concentrated in the eastern coastal regions, while Low-Low agglomeration dominated the western inland areas. The dynamic transfer of the coupling coordination degree revealed a distinct “club convergence” phenomenon. (4) Government support and technological innovation exerted increasingly positive effects on the coupling coordination degree in northeast and north China. Economic development initially exerted a significant positive effect in northwest and southern China, but its impact subsequently shifted to regions north of the Yellow River basin. In several southwest provinces, the influence of industrial structure transitioned from positive to negative.
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Chen et al. (Sat,) studied this question.
www.synapsesocial.com/papers/68c1824b9b7b07f3a060eb3f — DOI: https://doi.org/10.3390/su17177828
Yu Chen
Y Wang
Danhua Mei
Sustainability
Linyi University
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