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<p>With the rapid advancement of digital technologies, the digital economy has become a key driver of regional integration and high-quality economic growth. Understanding the spatial interaction and convergence dynamics of the digital economy is essential for narrowing regional disparities and promoting coordinated development. This study constructs an interprovincial digital economy network for China from 2011 to 2022 using a modified gravity model that integrates digital economy development levels, per capita GDP, regional GDP, and policy intensity. By combining complex network analysis with spatial econometric modeling, we examine the evolution of interprovincial linkages and their impact on regional convergence. The results reveal that China’s digital economy network has evolved from a coastal-centered, unidirectional structure to a nationwide, multidirectional system, reflecting increasingly frequent and complex flows of information, capital, and technology. Spatial convergence analysis shows significant absolute and conditional <InlineEquation ID="IEq1"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10614_2025_11138_Article_IEq1.gif" Format="GIF" Height="17" Rendition="HTML" Resolution="72" Type="Linedraw" Width="15" /> </InlineMediaObject> <EquationSource Format="TEX">\(\beta\)</EquationSource> </InlineEquation> convergence, indicating that lower-level provinces are catching up with higher-level ones. Furthermore, the integrated network weight matrix (<InlineEquation ID="IEq2"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10614_2025_11138_Article_IEq2.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="33" /> </InlineMediaObject> <EquationSource Format="TEX">\(\varvec{W}^w\)</EquationSource> </InlineEquation>) outperforms the traditional economic distance matrix (<InlineEquation ID="IEq3"> <InlineMediaObject> <ImageObject Color="BlackWhite" FileRef="10614_2025_11138_Article_IEq3.gif" Format="GIF" Height="14" Rendition="HTML" Resolution="72" Type="Linedraw" Width="30" /> </InlineMediaObject> <EquationSource Format="TEX">\(\varvec{W}^c\)</EquationSource> </InlineEquation>) in capturing non-proximal, cross-regional diffusion, particularly in economic restructuring and industrial digitalization dimensions. These findings provide new empirical evidence on the mechanisms through which network structures shape regional digital economy development and highlight the need for policies that strengthen infrastructure, foster innovation, and promote cross-regional collaboration to achieve balanced and sustainable growth.</p>

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Analysis of the Dynamic Evolution and Convergence Characteristics of China’s Provincial Digital Economy Spatial Association Network

  • 期刊论文

  • 发表日期：

    2025年10月21日

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  • Yaqian Zheng,
  • Dongya Han,
  • Jiabao Liu

摘要

With the rapid advancement of digital technologies, the digital economy has become a key driver of regional integration and high-quality economic growth. Understanding the spatial interaction and convergence dynamics of the digital economy is essential for narrowing regional disparities and promoting coordinated development. This study constructs an interprovincial digital economy network for China from 2011 to 2022 using a modified gravity model that integrates digital economy development levels, per capita GDP, regional GDP, and policy intensity. By combining complex network analysis with spatial econometric modeling, we examine the evolution of interprovincial linkages and their impact on regional convergence. The results reveal that China’s digital economy network has evolved from a coastal-centered, unidirectional structure to a nationwide, multidirectional system, reflecting increasingly frequent and complex flows of information, capital, and technology. Spatial convergence analysis shows significant absolute and conditional \(\beta\) convergence, indicating that lower-level provinces are catching up with higher-level ones. Furthermore, the integrated network weight matrix ( \(\varvec{W}^w\) ) outperforms the traditional economic distance matrix ( \(\varvec{W}^c\) ) in capturing non-proximal, cross-regional diffusion, particularly in economic restructuring and industrial digitalization dimensions. These findings provide new empirical evidence on the mechanisms through which network structures shape regional digital economy development and highlight the need for policies that strengthen infrastructure, foster innovation, and promote cross-regional collaboration to achieve balanced and sustainable growth.