What drives the change in China's provincial industrial carbon unlocking efficiency? Evidence from a geographically and temporally weighted regression model

In this paper, we propose the concept of carbon unlocking efficiency based on carbon lock-in. Supported by the "Techno-Institutional Complex" theory, we measure the industrial carbon unlocking efficiency (ICUE) of 30 Chinese provinces and analyze its spatial and temporal jump probabilities through spatial Markov chains, and finally identify and discuss the influencing factors through the GTWR model. We found that the ICUE of each province in China follows a decreasing distribution from east to central to west, with Shanghai, Beijing, and Guangdong having the highest ICUEs among all provinces and cities; although the overall ICUE converges to a higher level in the long run, there is still a certain predatory effect of developed regions on less developed regions in the short term, and the intensification of market com-petition may adversely affect the growth of ICUE in the lagging regions. The results of GTWR show that factors such as energy use efficiency, FDI, and industrial enterprise size mainly promote ICUE growth, and energy structure mainly shows negative effects on ICUE of each province, while factors such as economic efficiency, R&D intensity, ownership structure, marketization level, share of high-tech industries, and industrial upgrading show obvious spatial heterogeneity, and different regions need to adopt different policy instruments for their strengths and weaknesses. These research results have important policy guidance implications for accelerating the process of industrial carbon unlocking in each region.