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The Evolution of Knowledge Base in Knowledge-Intensive Sectors: Social Network Analysis of Biotechnology

This paper applies the methodological tools typical of social network analysis within an evolutionary framework, to investigate the dynamics of the knowledge base of the biotechnology sector. Knowledge is here considered a collective good represented as a co-relational and a retrieval-interpretative structure. The internal structure of knowledge is described as a network the nodes of which are small units within traces of knowledge, such as patent documents, connected by links determined by their joint utilisation. We used measures referring to the network, like density, and to its nodes, like degree, closeness and betweenness centrality, to provide a synthetic description of the structure of the knowledge base and of its evolution over time.Eventually, we compared such measures with more established properties of the knowledge base calculated on the basis of co-occurrences of technological classes within patent documents. Empirical results show the existence of interesting and meaningful relationships across the different measures, providing support for the use of social network analysis to study the evolution of the knowledge bases of industrial sectors and their lifecycles.

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File URL: http://www.unito.it/unitoWAR/ShowBinary/FSRepo/D031/Allegati/WP2009Dip_L&B/9_WP_Momigliano.pdf
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Paper provided by University of Turin in its series Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio Carlo Alberto. WP series with number 200909.

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Length: 36 pages
Date of creation: Jun 2009
Date of revision:
Handle: RePEc:uto:labeco:200909
Contact details of provider: Web page: http://www.unito.it/
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  1. Lionel Nesta, 2004. "Knowledge and Productivity in the World's Largest Manufacturing Corporations," SPRU Working Paper Series 119, SPRU - Science and Technology Policy Research, University of Sussex.
  2. Andrea Morrison, 2004. "Gatekeepers of knowledge within industrial districts:who they are, how they interact," KITeS Working Papers 163, KITeS, Centre for Knowledge, Internationalization and Technology Studies, Universita' Bocconi, Milano, Italy, revised Nov 2004.
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  12. Krafft, Jackie & Quatraro, Francesco & Saviotti, Paolo, 2009. "Evolution of the Knowledge Base in Knowledge Intensive Sectors," Department of Economics and Statistics Cognetti de Martiis LEI & BRICK - Laboratory of Economics of Innovation "Franco Momigliano", Bureau of Research in Innovation, Complexity and Knowledge, Collegio 200906, University of Turin.
  13. Gert Sabidussi, 1966. "The centrality index of a graph," Psychometrika, Springer, vol. 31(4), pages 581-603, December.
  14. Lionel Nesta & Pier Paolo Saviotti, 2005. "COHERENCE OF THE KNOWLEDGE BASE AND THE FIRM'S INNOVATIVE PERFORMANCE: EVIDENCE FROM THE U.S. PHARMACEUTICAL INDUSTRY -super-* ," Journal of Industrial Economics, Wiley Blackwell, vol. 53(1), pages 123-142, 03.
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  18. Thomas Grebel & Jackie Krafft & Pier-Paolo Saviotti, 2006. "On the Life Cycle of Knowledge Intensive Sectors," Revue de l'OFCE, Presses de Sciences-Po, vol. 97(5), pages 63-85.
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