Abstract
Green challenges such as global warming call for deeper low-carbon technology changes in manufacturing firms, and digital transformation (DT) may play a major role. Most existing studies have investigated the impact of DT as a whole on green technology innovation but lack a dynamic mechanism analysis from a process perspective. Therefore, this article proposes a theoretical framework for multistage DT to drive low-carbon technology innovation (LCTI) in manufacturing firms, which is closely linked to three dynamic capabilities (DCs). Based on the panel data of A-share manufacturing firms in China from 2011 to 2019, this article finds the following. First, DT effectively promotes LCTI, and this effect is a “leverage effect” superimposed on existing innovation. Second, the theoretical mechanism shows that the data analysis, data operation, and data empowerment stages of DT enhance the absorptive capacity, innovation capacity, and adaptive capacity of enterprises, respectively, which in turn promote LCTI. Empirical tests support the mediating effects of the first two capabilities; however, adaptive capacity is validated to be effective only for low-tech firms due to the limited increase in strategic flexibility of high-tech firms by marginal DT enhancement. Third, the heterogeneity analysis shows that the promotion effect of DT on LCTI is stronger for carbon reduction and decarbonization technologies, more significant for low-emission firms, and stronger for firms in the cohort network. These conclusions add new microevidence of the environmental benefits of the digital economy and provide new explanations for opening the “black box” of DT and LCTI based on a process perspective. At the same time, this work can help manufacturing firms in developing countries follow the low-carbon transformation path by independent innovation and, moreover, reduce the originally enormous amounts of energy consumption and carbon emissions of these countries and contribute to the response to global warming and the energy crisis.
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