Research

Under China's ‘dual carbon’ goals, the manufacturing sector faces significant carbon reduction challenges. As an essential driver of new quality productive forces, intelligent manufacturing (IM) presents a potential solution to these challenges. This study incorporated IM and carbon emission factors into a heterogeneous firms model, analyzing the carbon reduction impact of IM on manufacturing firms using merged data from Chinese listed manufacturing companies. Both theoretical and empirical perspectives were employed to examine the effects of IM and their underlying mechanisms. Key findings included: (i) The development of IM significantly reduced firms' carbon emissions. For every 1% increase in IM level, carbon emissions decreased by 0.618%, equivalent to an average reduction of 2 862.395 tons of CO2. (ii) Robustness tests, accounting for carbon intensity, alternative core variables, extended sample years, and the use of intensity DID and system GMM, confirmed the stability of the baseline results. (iii) Mechanism analysis revealed that IM reduced carbon emissions through green innovation effects (GIE), control optimization effects (COE), and digital-intelligence synergy effects (DSE). Specifically, GIE involved enhancing green innovation, advancing energy-saving and emission-reducing technologies, and promoting lifecycle greening; COE included optimizing both supply chain and internal controls; and DSE comprised the synergy of digital-intelligence technologies with digital-intelligence platforms. (iv) Heterogeneity analysis indicated that IM's carbon reduction effects varied across cities, firms, and industries. Consequently, policies should adopt a differentiated approach rather than a ‘one-size-fits-all’ solution. This study is among the first to reveal IM's impact on carbon reduction at the micro level of firms, providing policy insights for promoting green, high-quality development in manufacturing through intelligent technology and contributing to the timely achievement of China's ‘dual carbon’ goals.