Knowledge complexity and intercity technology transfer in China, 2001–2020

While regional innovation capabilities play a crucial role in technology transfer, existing studies often lack nuanced measures of innovation capabilities and instead focus primarily on the “quantity” of technology transfer. This paper leverages the concept of knowledge complexity to explore its influences on both the “quantity” and “complexity” of intercity technology transfer. Drawing upon a dataset of more than 10 million patents from the China National Intellectual Property Administration (CNIPA), we calculate the knowledge complexity index (KCI) for 252 Chinese cities and the technological complexity index (TCI) for 622 four-digit technological fields from 2001 to 2020 to capture the “complexity” dimension of technology transfer. Our empirical results reveal an increasing polarization of the KCI distribution among Chinese cities and significant differences between the “quantity” and “complexity” networks of intercity technology transfer. Using fixed-effect panel regression models and an instrumental variable approach, we identify a robust, causal inverted-U relationship between intercity KCI disparities and both the “quantity” and “complexity” of technology transfer. While moderate intercity KCI disparities promote technology transfer, larger disparities hinder it due to limitations in absorptive capacity. Moreover, this inverted-U relationship is heterogeneous across technology sectors and cities, being more pronounced for the transfer of technologies with low and moderate TCI, and for technology transfers between cities with relatively stronger innovation capacities. These findings contribute to the understanding of technology transfer from a knowledge complexity perspective and provide policy insights for designing smart technological specialization strategies in China.