RESUMO
Digital transformation and green innovation are powerful initiatives to achieve carbon peaking, carbon neutrality targets and high-quality economic development. Using a sample of high energy-consuming listed enterprises from 2012 to 2021, a double fixed-effect model is constructed to verify the effect of green innovation on the carbon emission reduction performance of high energy-consuming enterprises, and digital transformation is used as a moderating variable to analyze the inner mechanism of green innovation affecting the carbon emission reduction performance of high energy-consuming enterprises under the effect of digital transformation. The empirical results show that green innovation can significantly improve the carbon emission reduction performance of energy-consuming enterprises, while digital transformation positively moderates the effect of green innovation on the carbon emission reduction performance of energy-consuming enterprises. When considering the industry heterogeneity, the moderation effect of digital transformation is significant in the chemical raw materials and chemical products manufacturing industry and the electricity and heat production and supply industry, but the petroleum processing and coking and nuclear fuel processing industry, the non-metallic mineral products industry, the ferrous metal smelting and rolling processing industry and the non-ferrous metal smelting and rolling processing industry are not yet significantly affected by green innovation and digital transformation. The findings of the study provide empirical evidence to promote the improvement of carbon emission reduction performance of energy-intensive enterprises in China and to achieve the "double carbon" target.
RESUMO
The intelligent city pilot policy is a major measure in China to promote urban development from factor driven and investment driven to innovation driven. Intelligent city construction can effectively coordinate specialized production factors and information sharing mechanism, promote digital information technology innovation, promote smart industry cluster, and expand ecological scenarios of clean industry application, so as to reduce carbon emissions. This paper reveals the internal mechanism of intelligent city construction to promote carbon emission reduction. Based on the quasi-natural experiments carried out in three batches of pilot construction of intelligent cities since 2012, the difference-in-difference model (DID) is used to identify its impact on urban carbon emissions. The research results show that the pilot construction of intelligent cities is conducive to reducing carbon emissions, which is still robust under multiple scenarios such as placebo test and endogenous test. Heterogeneity analysis shows that the pilot policies have a more significant carbon emission reduction effect on the Beijing-Tianjin-Hebei urban agglomeration, non-resource-based cities, and non-old industrial bases. After further quantitative analysis of 917 pilot policy texts based on Simhash algorithm, Jieba word segmentation, and word frequency statistics, it is found that intelligent industry policies reduce carbon emissions by driving data elements agglomeration and optimizing industrial structure, while intelligent government and intelligent people's livelihood policies improve energy efficiency and reduce carbon emissions through green technological innovation. Counterfactual tests using machine learning algorithms show that the later the pilot batch, the better the sustainable carbon emission reduction effect of intelligent city pilot policies.