Knowledge network is a kind of inter-connected network that is born in the process of diffusion and communication of knowledge by the actors who create, transfer, absorb and apply knowledge, such as enterprises, universities, organizations and institutions. Network structures may exert influence on the actors and regions involved, and the potential for successful knowledge absorption and learning may be partly determined by network positions. Up to present, there are no researches about the evolution of spatial structure of knowledge network in China. In recent years, the evolutionary economic geography in Europe and USA begins to explore the spatial structure and evolution of knowledge networks from the geographical angle. But because of language and cultural barriers, the western research focused more on international knowledge flows and connections about knowledge networks in China, while the evolution of Chinese domestic knowledge networks were rarely involved. Purposes of this paper are: 1) to establish the estimation model to analyze the formation mechanism of spatial patterns of knowledge network, and to reveal the dynamic mechanism of its evolution; 2) to provide some advice to the government for policy making of national innovation system.This paper takes statistical data of the papers published in cooperation about the biotechnology in the database of Chinese Scientific and Technical Journals (Journal of Chongqing VIP) from 2000 to 2009 as data source. Based on the theory and methods of social network analysis in New Economic Sociology, it uses UCINET and ArcGIS to analyze the spatial structure and the evolution of knowledge network of biotechnology at provincial level in China. In recent 10 years, the knowledge network developed in three phases: infant stage, expansion stage and maturity stage. Accordingly, the major pattern of knowledge diffusion in the network changed from contagious diffusion to hierarchical diffusion. The spatial high-density of knowledge connections also changed from decentralization to concentration, then again to decentralization. The interactions of geographical proximity and organizational proximity between nodes impact the evolution of network. Based on the result, this paper suggests that the national innovation system should improve the biotechnology through two ways: 1) shortening the social distance of actors who create knowledge; 2) optimizing spatial disposition of innovation resources.
WANG Tao, Stefan HENNEMANN, Ingo LIEFNER, LI Dan-dan
. Spatial structure evolution of knowledge network and its impact on the NIS:Case study of biotechnology in China[J]. GEOGRAPHICAL RESEARCH, 2011
, 30(10)
: 1861
-1872
.
DOI: 10.11821/yj2011100012
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