Authors: MEIQI JIAO*, Institute of Global Innovation & Development, East China Normal University, DEBIN DU, Institute of Global Innovation & Development, East China Normal University, QINCHANG GUI, Institute of Global Innovation & Development, East China Normal University, WENLONG YANG, Institute of Global Innovation & Development, East China Normal University
Topics: Economic Geography, Urban and Regional Planning
Keywords: global city, technical cooperation network, Complex network analysis
Session Type: Paper
Start / End Time: 5:00 PM / 6:40 PM
Room: 8223, Park Tower Suites, Marriott, Lobby Level
Presentation File: No File Uploaded
The global city technical cooperation network is constructed based on 2015 public PCT patent data. By complex network analyzing methods and spatial analyzing methods, this article demonstrates the topology structure and spatial pattern of global city technical cooperating activities. The results show that: In terms of the topological structure, the density of the network is relatively low, which means the strength of linkages in the network are unbalanced. The network is scale-free network and has prominent city nodes. The network has significant group structure and there are 11 groups which contain over 50 nodes. In terms of spatial pattern, cities with higher patent output distribute in zonal pattern. Cities with more links with others distribute in the area of Calgary (Canada), Silicon Valley (USA) and Boston-Cambridge-New York-Philadelphia (United States) of North America, Paris metropolitan (France), Greater London (United Kingdom), Randstad (Netherland), Essen (Germany) and Basel (Switzerland) of Europe, Tokyo (Japan), Seoul (South Korea), Beijing (China), Yangtze River Delta Urban Agglomerations (China) and Pearl River Delta (China) of East Asia. Tokyo and Paris are in the leading position in both total patent output and number of linkages. The spatial distribution of degree centrality is similar with the distribution of the patent output. Moreover, the distribution of nodes’ betweenness centrality is more concentrated than nodes’ degree centrality.