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How Does the Industrial Digitization Affect Carbon Emission Efficiency? Empirical Measurement Evidence from China’s Industry

Author

Listed:
  • Ren-Long Zhang

    (School of Management, Guizhou University, Guiyang 550025, China)

  • Xiao-Hong Liu

    (School of Management, Guizhou University, Guiyang 550025, China)

  • Wei-Bo Jiang

    (School of Management, Guizhou University, Guiyang 550025, China)

Abstract

Based on the panel data of China’s industrial carbon emissions from 2015 to 2022, the S-SBM model is scientifically used to measure the industrial carbon emission efficiency, and a spatial model is constructed to empirically analyze the spatial effect of industrial digitalization on carbon emission efficiency. From the regional perspective, it is interesting to find that industrial digitization has shown an overall downward trend of the central, western and northeastern regions showing a roughly N-shaped trend of change. From an industry perspective, we also find that industrial digitization has a relatively high overall impact on the carbon emissions performance of the mining industry with significant changes in the performance of electricity and heat and gas and water production and supply industries. Therefore, the experimental results effectively provide the substantive empirical evidence for policy makers on how to best promote the development of industrial digitization and strengthen the effective application of digital technology affecting carbon emission control in China.

Suggested Citation

  • Ren-Long Zhang & Xiao-Hong Liu & Wei-Bo Jiang, 2023. "How Does the Industrial Digitization Affect Carbon Emission Efficiency? Empirical Measurement Evidence from China’s Industry," Sustainability, MDPI, vol. 15(11), pages 1-16, June.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:11:p:9043-:d:1163126
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    References listed on IDEAS

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    1. Tao, Jing & Xie, Xiaoqing & Peng, Rongsheng & Bei, Na, 2024. "Digital economy and environmental pollution in the manufacturing sector: Emission reduction effects and mechanisms," International Review of Economics & Finance, Elsevier, vol. 96(PC).
    2. Wang, Shan & Chen, Haiqian & Yu, Donghua, 2025. "How robot application empowers industrial low-carbon development: A study based on the perspective of carbon reduction and efficiency enhancement," Technological Forecasting and Social Change, Elsevier, vol. 220(C).

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