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Towards Sustainable Development: Can Industrial Intelligence Promote Carbon Emission Reduction

Author

Listed:
  • Hanqing Xu

    (School of Management, Ocean University of China, Qingdao 266100, China)

  • Zhengxu Cao

    (School of Management, Ocean University of China, Qingdao 266100, China)

  • Dongqing Han

    (Department of Chinese and Media, Bozhou University, Bozhou 236800, China)

Abstract

The realization of intelligent transformation is an important path for the industry to move towards low-carbon development. Based on panel data from 30 provinces in China, this study utilizes the intermediate effect model and spatial econometric model to analyze the influence of industrial intelligence on carbon emissions. The research reveals that industrial intelligence helps with carbon reduction, and the result is still valid after undergoing various tests. Industrial intelligence relies on green technological innovation, industrial structure upgrading, and energy intensity to realize carbon reduction. There is a spatial spillover role of industrial intelligence on carbon emissions, which has a positive influence on carbon reduction in local and adjoining regions. The influence of industrial intelligence on carbon emissions exhibits heterogeneity in the regional dimension, time dimension, and industrial intelligence level dimension. The research provides empirical evidence and implications for using artificial intelligence to achieve carbon reduction.

Suggested Citation

  • Hanqing Xu & Zhengxu Cao & Dongqing Han, 2025. "Towards Sustainable Development: Can Industrial Intelligence Promote Carbon Emission Reduction," Sustainability, MDPI, vol. 17(1), pages 1-19, January.
    • Handle: RePEc:gam:jsusta:v:17:y:2025:i:1:p:370-:d:1561264
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    References listed on IDEAS

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    Cited by:

    1. Yushi Ou & Yanhua Li & Tingyu Zhang, 2025. "Implementation Pathways for Carbon Emission Reduction Through Environmental Regulations: Synergistic Mechanisms of Industrial Intelligence and Green Technological Innovation," Sustainability, MDPI, vol. 17(17), pages 1-30, September.

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