Impact of intercity low-carbon technology transfer on carbon emission reduction in China:Based on the “dichotomy” of knowledge learning and technology learning

Abstract

[Objective] Increasing the transfer of low-carbon technology (LCT) is the key to narrowing the gap in LCT between regions and improving the overall level of low-carbon technology of China. This study aims to explore the relationship between LCT transfer and carbon emission reduction, as well as the impact of knowledge learning and technical learning on China’s carbon emissions, in order to find an effective LCT transfer path. [Methods] Inspired by innovation dichotomy, LCT transfer can be divided into two innovation cooperation models—STI (Science, Technology, Innovation) and DUI (Doing, Using, Interacting), corresponding to knowledge learning and technology learning, respectively. Based on the data of intercity LCT patent transfer of 284 cities in China from 2005 to 2019, this study analyzes the pattern of China’s intercity low-carbon technology transfer, and explored the impact of STI and DUI on carbon emissions by using spatial econometric models. [Results] The research showed that: (1) China’s inter-city LCT transfer has the characteristics of high concentration and hierarchy, which presents a “core-periphery” structure with the main urban agglomerations in the country as the “core” and other cities as the “periphery”. However, the overall carbon emissions presented a geographical pattern of high in the north and low in the south. (2) China’s intercity low-carbon technology transfer has a positive impact on the carbon emission reduction of the place where the technology is transferred, but there are differences due to the way of technology transfer. Among them, technology transfer based on knowledge learning has a relatively stronger impact on carbon emission reduction. (3) Knowledge learning and technology learning both had positive effects in economically developed cities, but only knowledge learning has a positive impact in economically underdeveloped cities. All cities need to follow the law of heterogeneous LCT transfer and promote the efficient allocation of LCT resources. [Conclusion] There was a spatial mismatch between the level of LCT transfer and carbon emission intensity in cities China. Technology transfer based on knowledge learning can effectively compensate for the market failure of that based on technology learning. There was regional heterogeneity in the impact of China’s intercity LCT transfer on carbon emission reduction. Considering the positive impact of LCT transfer, it is necessary to actively build a multi-center, multi-level LCT transfer network, coordinate the role of academic research institutions and enterprises in low-carbon technology transfer, promote intercity low-carbon technology transfer in accordance with regional conditions, and actively improve the low-carbon technology transfer service system.

Keywords

• |low-carbon technology transfer|knowledge learning|technology learning|carbon emissions|spatial durbin model|china