Can industrial intelligence promote carbon emission efficiency? --empirical research based on the Yangtze River Economic Belt - Xiao, Xiangtao; Chen, Ming; Zhang, Aoxiang; Wu, Yunfeng (Frontiers in Environmental Science, 2024)
The development of artificial intelligence technology provides a new path for China's carbon emission reduction. This research uses the robot penetration rate as a characteristic index of industrial intelligence development, and uses panel quantile regression, spatial measurement, and threshold effect models to provide a more thorough theoretical and empirical discussion of the impact, mechanism, and spatial effect of industrial intelligence development on urban carbon emission efficiency (CEE), based on panel data from 108 cities in the Yangtze River Economic Belt (YEB) in China from 2006 to 2020. The results show that, the regression coefficient of industrial intelligence on carbon emission efficiency is 0.057, shows that urban CEE may be greatly increased with the use of industrial intelligence, and this finding remains true even after endogeneity and robustness tests are controlled; Industrial intelligence advances technology, optimizes industrial structure, and ultimately enhances regional CEE; There is a Matthew effect on the degree of development of carbon emission efficiency, and the impact of industrial intelligence on CEE is more pronounced in non-resource-based cities and the lower portions of YEB; Urban CEE increases positively with the spatial spillover impact of industrial intelligence development. The ability for regional sustainable development will be significantly increased if cross-regional cooperative prevention and control of environmental governance can be successfully achieved. This study verifies the enabling effect of industrial intelligence development on the improvement of urban CEE, and provides enlightenment for China to *Corresponding author.