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<p>While the digital economy significantly impacts the ecological environment (EE), their multidimensional spatial interactions remain underexplored. This study investigates the nonlinear and spatial effects of digital economy on carbon emissions (CE) to uncover these complex regional interactions. Utilizing panel data from Chinese prefecture-level cities (2014–2023), this research constructs a digital economy index via the entropy-weighted TOPSIS method and measures CE using the IPCC approach. The analysis strictly employs GIS-supported spatial visualization, mediation models, and the Spatial Durbin Model. Empirical results reveal a significant inverted U-shaped relationship between digital economy and CE, with a turning point around 0.40. By 2023, the average digital economy level exceeded this threshold, indicating an overall transition to a carbon reduction effect. Technological innovation plays a partial mediating role, accounting for 14.5% of the total effect. Furthermore, GIS mapping confirms strong positive spatial autocorrelation, and the digital economy exhibits significant spatial spillover effects, systematically affecting the EE of neighboring cities. Regional heterogeneity is also pronounced. Eastern cities have higher turning points, while resource-based cities face lower thresholds. Policymakers should promote digital infrastructure in less-developed regions and encourage green digital technologies to accelerate emission reductions. Additionally, strengthening interregional cooperation and improving digital governance for environmental management are crucial for achieving coordinated ecological sustainability.</p>

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Spatial analysis of the digital economy’s impact on the ecological environment: evidence from Chinese cities

  • 期刊论文

  • 发表日期：

    2026年8月3日

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  • Siwei Yue

摘要

While the digital economy significantly impacts the ecological environment (EE), their multidimensional spatial interactions remain underexplored. This study investigates the nonlinear and spatial effects of digital economy on carbon emissions (CE) to uncover these complex regional interactions. Utilizing panel data from Chinese prefecture-level cities (2014–2023), this research constructs a digital economy index via the entropy-weighted TOPSIS method and measures CE using the IPCC approach. The analysis strictly employs GIS-supported spatial visualization, mediation models, and the Spatial Durbin Model. Empirical results reveal a significant inverted U-shaped relationship between digital economy and CE, with a turning point around 0.40. By 2023, the average digital economy level exceeded this threshold, indicating an overall transition to a carbon reduction effect. Technological innovation plays a partial mediating role, accounting for 14.5% of the total effect. Furthermore, GIS mapping confirms strong positive spatial autocorrelation, and the digital economy exhibits significant spatial spillover effects, systematically affecting the EE of neighboring cities. Regional heterogeneity is also pronounced. Eastern cities have higher turning points, while resource-based cities face lower thresholds. Policymakers should promote digital infrastructure in less-developed regions and encourage green digital technologies to accelerate emission reductions. Additionally, strengthening interregional cooperation and improving digital governance for environmental management are crucial for achieving coordinated ecological sustainability.