An Analysis of the Spatial–Temporal Evolution and Influencing Factors of the Coupling Coordination Degree Between the Digital and Real Economies in China DOI Open Access
Xiaoya Li, Zhao Min,

Guang Yang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3384 - 3384

Published: April 10, 2025

The digital economy (DE) and real (RE) are dual pillars of the modern economic system. deep integration (IDR) has emerged as a pivotal strategic trend. IDR not only can enhance international competitiveness but also contributes to sustainable development goals. This work collects DE RE data from 30 provinces in China between 2012 2022. entropy weight method coupling coordination degree (CCD) model employed measure level IDR. Furthermore, Dagum Gini coefficient, Kernel density estimation, spatial autocorrelation model, geographically temporally weighted regression (GTWR) utilized analyze spatial–temporal evolution influencing factors CCD. following conclusions drawn: (1) During study period, CCD shows an upward trend, value is relatively low. (2) There significant differences CCD, inter-regional difference primary cause. (3) regional continuously widening. (4) obvious global agglomeration feature, been enhanced (5) policy intensity, infrastructure, industrial structure, human capital, technological innovation, market environment have impacts on obtained findings provide important theoretical support for coordinated RE.

Language: Английский

An Analysis of the Spatial–Temporal Evolution and Influencing Factors of the Coupling Coordination Degree Between the Digital and Real Economies in China DOI Open Access
Xiaoya Li, Zhao Min,

Guang Yang

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(8), P. 3384 - 3384

Published: April 10, 2025

The digital economy (DE) and real (RE) are dual pillars of the modern economic system. deep integration (IDR) has emerged as a pivotal strategic trend. IDR not only can enhance international competitiveness but also contributes to sustainable development goals. This work collects DE RE data from 30 provinces in China between 2012 2022. entropy weight method coupling coordination degree (CCD) model employed measure level IDR. Furthermore, Dagum Gini coefficient, Kernel density estimation, spatial autocorrelation model, geographically temporally weighted regression (GTWR) utilized analyze spatial–temporal evolution influencing factors CCD. following conclusions drawn: (1) During study period, CCD shows an upward trend, value is relatively low. (2) There significant differences CCD, inter-regional difference primary cause. (3) regional continuously widening. (4) obvious global agglomeration feature, been enhanced (5) policy intensity, infrastructure, industrial structure, human capital, technological innovation, market environment have impacts on obtained findings provide important theoretical support for coordinated RE.

Language: Английский

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