The Evolution of Knowledge Base in Knowledge-Intensive Sectors: Social Network Analysis of Biotechnology
AbstractThis 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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Bibliographic InfoPaper 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.
Length: 36 pages
Date of creation: Jun 2009
Date of revision:
This paper has been announced in the following NEP Reports:
- NEP-ALL-2009-07-11 (All new papers)
- NEP-CSE-2009-07-11 (Economics of Strategic Management)
- NEP-KNM-2009-07-11 (Knowledge Management & Knowledge Economy)
- NEP-NET-2009-07-11 (Network Economics)
- NEP-SBM-2009-07-11 (Small Business Management)
- NEP-SOC-2009-07-11 (Social Norms & Social Capital)
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