关键词: 全球城市, 技术合作网络, 复杂网络分析

Abstract:

In the background of economic globalization, the technology globalization has become significant. International technical collaboration and R&D activities are major forms of technology globalization. Cities are the engine of innovation and economic development. Due to the development of transportation technology and telecommunication technology, cities are getting closer and the impact of geography distance is weakened. By providing good entrepreneurial environment, cities attract talents, information and capital from all over the world. As a result, innovation is the major function of cities. Global cities make great efforts to become the global science and technology innovation centers with world influence. These kind of centers are cities with leading innovation abilities and most of them are hubs of innovation activities. Patents are an important indicator of measuring technology development and innovation activities. Exploring cities’ role in the global technical cooperation networks is key to understand global technical cooperation pattern. Meanwhile, it is also meaningful for Chinese researchers to explore what position Chinese cities are in and how to construct Chinese cities as global science and technology innovation centers with world influence. Although plenty of articles have focused on the global technical cooperation network at multiple scales such national, regional, urban and community scales, few research has focused on the global city technical cooperation network. 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), the Yangtze River Delta Urban Agglomerations (China) and the 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. The ranks of Beijing and Shanghai’s betweenness are higher than Shenzhen’s. The reason is that Beijing is the capital city of china. And Beijing holds a variety of universities, institutes and high-tech companies, which provides Beijing with science and technology innovation. Shanghai has a large number of FDI, and it has close connection with foreign companies to do transnational R&D activities. However, Shenzhen has relatively less links with cities in foreign countries, which means the technology output of Shenzhen still depends on its own market. This phenomenon is due to the special immigration culture, open market mechanism and competitive environment.

Key words: global city, technical cooperation network, complex network analysis