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As global climate change and environmental challenges intensify, low-carbon transformation has become a common goal worldwide. Intelligent manufacturing (IM) is a crucial driver of total factor productivity enhancement and carbon reduction, necessitating an in-depth exploration of its impact on enterprises' low-carbon transformation. This study utilizes data from Chinese A-share listed manufacturing enterprises from 2011 to 2022, taking the intelligent manufacturing demonstration projects (IMDP) policy. A staggered difference-in-differences (DID) model is adopted to analyze the impact and mechanism of IM on the total carbon emissions and carbon emission intensity. The study finds that IM reduces the total carbon emissions and carbon emission intensity of manufacturing enterprises. This effect is more pronounced in non-state-owned enterprises, high-pollution industries, and inland firms. Mechanism analysis indicates that enterprises achieve low-carbon transformation mainly through three pathways: promoting green technological innovation, improving total factor productivity, and alleviating financing constraints. Additionally, the transformation of the energy structure in the region where the enterprise is located contributes to enhancing the carbon reduction effect of IM. Research confirms that IM empowers enterprises in low-carbon transformation and provides insights for achieving green development and optimizing energy structures. • IMDP policy was evaluated using a staggered DID model. • IM can reduce enterprise carbon emissions. • Policy effect outcomes vary based on different enterprises. • Green innovation, total factor productivity and financing constraints are pathways. • Energy structure transformation has promoted the policy effect.
Zhu et al. (Fri,) studied this question.