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The impact of intelligent computing centers construction on urban new-quality productivity: An empirical study based on 287 prefecture-level cities in China

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  • keyue, Chen
  • ximu, Wang

Abstract

New-quality productive forces (NQPFs) refer to an advanced form of modern productive forces. Their core elements include new technologies, new industries, new business models, and new factors of production. As computing power becomes a key driver of economic growth and aligns with the development logic of NQPFs, this study examines its role in urban development. We use panel data from 287 cities at or above prefecture level in China over the period 2010–2023 and construct a Difference-in-Differences (DID) model to examine how the construction of intelligent computing centers (ICCs) affects the level of NQPFs in host cities. Several robustness checks are employed, including baseline regressions, a parallel trend test, and a placebo test, to verify the validity of the estimated effects. Based on this framework, a two-step mediation model and a Spatial Durbin Model (SDM) are adopted to analyze the mediating mechanisms and spatial spillover effects of ICCs on NQPFs. The results indicate that ICCs have a significantly positive effect on the development of urban NQPFs. This effect operates through two channels. First, ICCs promote technological innovation. Second, they accelerate the upgrading of the industrial structure. Heterogeneity analysis shows that the current deployment of computing power clusters strengthens the positive impact of ICCs on NQPFs and supports more balanced development between eastern and western regions. Further analysis reveals that the construction of ICCs generates significant positive spatial spillover effects, producing beneficial impacts on neighboring regions.

Suggested Citation

  • keyue, Chen & ximu, Wang, 2026. "The impact of intelligent computing centers construction on urban new-quality productivity: An empirical study based on 287 prefecture-level cities in China," Socio-Economic Planning Sciences, Elsevier, vol. 105(C).
  • Handle: RePEc:eee:soceps:v:105:y:2026:i:c:s0038012126000637
    DOI: 10.1016/j.seps.2026.102476
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