| Regional innovation network is a new regional economic development pattern, which will not only help integrate regional innovation resource and exchange knowledge between innovation subjects (universities, firms, public research institutions, etc.), but also have significant effects on making regional policies and improving regional competitiveness. The level of development of science and technology is an important indicator to measure regional innovation ability, and scientific papers and patents are prime output results of science and technology, therefore, in this paper, we discuss regional innovation network by building scientific cooperation network (SCN) and technology cooperation network (TCN) from co-published papers and co-applied patents perspective. Using papers published in VIP (the Chinese Science&Technology Journal Database/Chongqing VIP (http://www.cqvip.com)) and SCI-Extended (the Thompson Reuters’Web of KnowledgeSM database (http://apps.isiknowledge.com)) as scientific paper data sources, and patents applied in China intellectual property rights net (CNIPR) as patent data sources, according to social network analysis software:UCINET and geographic information system software: Arcgis9.2, we analyze the evolution of network structure of SCN and TCN during2000to2009year by taking centrality, density, average path length, core-periphery and other social network analysis indexes. Besides that, gini coefficient, theil index, rank size rule, ESDA and other methods are used to measure geographical spatial structure. This article studies Chinese provincial innovation network structure characteristic and its spatial-temporal evolution at the macro level, explores the status of each province at the medium scale, and discusses the role and position of different innovation subjects (universities, firms, public research institutions) at the micro view. In addition, this paper discusses the relationships between academic papers and the output of patents combining correlation analysis.By social network analysis, we find that Ties between the provinces are more and more, and the network structure has become increasingly complex. The differences in the number of cooperation between the various provinces of the SCN reduce, and the situation reverses in TCN. The network structure is beginning to show a dispersed trend, while there is still significant concentration in TCN. The core periphery model shows that the number of core area provinces experienced the process of distributed-centralized-distributed-centralize. The cooperation between universities and public research institutes, universities and universities accounts for the main part. enterprises has no significant effect in SCN; the cooperation between firms and universities, firms and public research institutes takes the major proportion, and the innovative role of firms is quite extraordinary.Through the temporal and spatial evolution characteristics of the two networks, the results can be summarized as follows:(1) There are big regional disparity in China, which is mainly affected by the impact of differences within the economic zone; the rank size scale analysis finds out that the innovation potential of the province meet the rank size scale distribution, and the distribution of provinces’innovation potential is basically normal, primacy is not obvious.(2) Exploratory spatial data analysis manifest that inter-provinces cooperation exist spatial correlation, and provinces in type of high-high and low-low have "club convergence" phenomenon. Spatial interaction analysis confirmed by kernel density estimation reveals that spatial network structure experiences the Chinese word "ge" to "tao" transition, sphere of influence of the inter-provincial cooperation is also gradually increasing. Spatial network structure is relatively simple in TCN, inter-provincial cooperation in the Matthew effect is obvious, and the level of co-paper and co-patent is not balance in most provinces.(3) The correlation analysis confirmed that the higher position and greater innovation potential of province in the SCN will have higher status and innovation potential. Research and experimental development expenditures of the whole society, technology market turnover and innovation potential have highly positive correlation in SCN, and there is also a high positive correlation between GDP per capita and innovation potential in TCN. The correlation between health technicians and innovative potential of the two networks is gradually increased.This paper explores the structure features and temporal and spatial evolution characteristics of SCN and TCN, and analysis the spatial interactions and differences between the provinces, which provide a reference for quantitative analysis of the status and role of the provinces in the regional innovation networks, and offer support for making regional innovation policy. |
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