%0 Journal Article %A Qiuyu WANG %A Gang ZENG %A Guoqing LYU %T Structural evolution of innovation networks of China's equipment manufacturing industry %D 2016 %R 10.11821/dlxb201602006 %J Acta Geographica Sinica %P 251- %V 71 %N 2 %X

Industry-university-research institute collaborative innovation process and its spatial structures attract the interest of researchers in many fields. With the rise of emerging economies and their technological upgrading, their spatial structure of innovation network is developing into an important research topic. And China, in particular, provides the opportunity to study the evolution of such network structures. With the help of some sophisticated data analysis software like SPSS, UCINET and ArcGIS, this paper discusses the above-mentioned issues based on graphical analysis and an empirical analysis of co-inventor networks of China's equipment manufacturing industry using patent data issued by the State Intellectual Property Office of P.R.China from 1985 to 2012. We reached three conclusions about the structural evolution of the industry-university-research institute collaborative innovation network of Chinese equipment manufacture industry. Firstly, our systematic examination has identified a rapid growth of patents and significant changes of actor composition from 1985 to 2012, which shows the rise of privately owned enterprises and universities around 2000, with universities standing out as the most significant and strongest actors in the process of building innovation networks, while state-owned enterprises only dominate some specific fields. Secondly, city-level is the major geographical scale of industry-university-research institute collaboration in developed cities; while undeveloped cities tend to cooperate with competent ones at provincial or national level. It is mainly because concentration of universities and firms with strong innovative ability makes it easy to find the perfect local partner, while weaker actors have to look for the best innovation partners across city boundaries. Last but not least, political decisions concerning R&D investment supported by provincial governments have a positive influence on interprovincial innovation activities. Meanwhile, the spatial political bias in China can lead to the hierarchical structure of Chinese innovation networks, which shows the significance of municipalities and provincial capital like Peking, Shanghai and Guangzhou.

%U https://www.geog.com.cn/EN/10.11821/dlxb201602006