Spatio-temporal evolution of interurban technological flow network in the Yangtze River Delta Urban Agglomeration:From the perspective of patent transaction network
Taking the Yangtze River Delta Urban Agglomeration as an example, based on the perspective of patent transaction network and applying the big-data mining technology, social network analysis and GIS, this paper describes the regular laws of the spatiotemporal evolution of the interurban technological flow network systemically. The results are obtained as follows:First, enterprise is the main body of interurban technological transfer, while universities and institutes play a minor role in the patent transferring relationship. Besides, technological transfer tends to generate in an internal system, instead of spillovers outside. What's more, the patent related to appearance designs is less than innovative patent and utility-oriented patent. Second, as the diffusion centers of the interurban technological flow network under a hub-and-spoke organization, Shanghai, Hangzhou, Nanjing and Suzhou make a transfer from technical convergences to technical centers. Furthermore, Hefei, Nantong and Jiaxing become the main technological absorbers. Third, two diffusion models in the interurban technological flow network are observed. One is hierarchical diffusion model from hubs towards lower-tier cities or sub-centers. The other is contacting diffusion models and technological flows have emerged between those neighboring city pairs because of spatial proximity. Fourth, interurban technological transfers are not well distributed. Under the Matthew Effect, the dynamics of the technological flow network is self-organized with the coupling mechanism including place dependence and path creation. Finally, the spatial evolution of the network presents an evolutionary law from discrete homogeneity with single core (e.g., Shanghai) to dual-hub driven pattern (i.e., Shanghai and Suzhou) to multi-core network with a hub-and-spoke system (e.g., Shanghai, Suzhou, Hangzhou and Nanjing).
NETL
NSTL
万方数据
维普
