ABSTRACT

Technology transfer is pivotal in narrowing regional disparities, optimizing resource allocation, and fostering collaborative innovation. By constructing a systematic network analytical framework and analyzing data on invention patent transfers obtained from the China National Intellectual Property Administration, this research examines the evolutionary characteristics of intercity technology transfer networks in the Guangdong-Hong Kong-Macao Greater Bay Area from 2007-2018 and the underlying mechanisms. The main findings are as follows: (1) The technology transfer network in the Greater Bay Area has evolved from loose and homogeneous linkages to a dual-core pattern and subsequently to a polycentric structure. Shenzhen and Guangzhou are regional technology trade centers, while Dongguan, Foshan, Zhongshan, and Huizhou are second-tier cities. Hong Kong and Macao are relatively marginalized within the urban agglomeration, primarily engaged in one-way technology transfer due to institutional differences and regional division. (2) The scale and structure of the technology transfer network have significantly improved. The technology transfer path has undergone steady changes and gradual optimization, demonstrating increasing reciprocity. The hierarchical structure of the network tends to converge, exhibiting enhanced connectivity and cohesion as it develops into a balanced, clustering, and polycentric network. (3) Both endogenous and exogenous forces drive the evolution of the technology transfer network in the Greater Bay Area. Endogenous factors can reduce cities’ reliance on exogenous factors. The level of economic development, R&D investment, and the ability to transform technological and scientific outputs within a city can promote technology transfer. Moreover, there are sender effects and receiver effects. Institutional proximity facilitates technology transfer, followed by spatial contiguity and technological proximity. Structural dependence and time dependence are crucial endogenous driving forces for the evolution of the technology transfer network in the Greater Bay Area, as evidenced by delayed reciprocity, transfer closure, stability, and innovation.

THE SPEAKER

Liang Dai holds a BSc and MSc from Nanjing University in China and a PhD from Ghent University in Belgium. She is an Associate Professor in the School of Public Administration at Nanjing University of Finance and Economics. Her research interests include urban networks and regional development, and urban and transport geography. She specializes in network visualization, analysis, simulation, and its application in urban studies. Her research sheds light on an emergent networked urban system whose development and innovation increasingly depend on multiple intercity flows such as capital, people, transport, information, knowledge, and technology. She has published more than 40 journal articles and 3 books in both Chinese and English. She has earned 11 software copyrights and two patents granted by China National Intellectual Property Administration. She is the principal investigator for multiple prestigious research grants, including two from the National Natural Science Foundation of China and others from the Natural Science Foundation of Jiangsu Province and the Scientific and Technological Innovation Foundation for Returnees of Nanjing. She has also received accolades from Jiangsu Province, such as the title of “Double-Innovation Doctor” and recognition as a “333 high-level talent”.