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The Knowledge Base Evolution in Biotechnology: A Social Network Analysis

Jackie Krafft, Francesco Quatraro and Pier Paolo Saviotti

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Abstract: This paper applies the methodological tools typical of social network analysis (SNA) within an evolutionary framework, to investigate the knowledge base dynamics 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 SNA to study the evolution of the knowledge bases of industrial sectors and their lifecycles.

Keywords: Knowledge Base; Social Network Analysis; Variety; Coherence; Industry lifecycles; exploration/exploitation (search for similar items in EconPapers)
Date: 2011
New Economics Papers: this item is included in nep-cse, nep-evo, nep-knm, nep-net and nep-sbm
Note: View the original document on HAL open archive server: https://hal.science/hal-00539002v1
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Citations: View citations in EconPapers (56)

Published in Economics of Innovation and New Technology, 2011, 20 (5), pp.445-475

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Journal Article: The knowledge-base evolution in biotechnology: a social network analysis (2011) Downloads
Working Paper: The Knowledge Base Evolution in Biotechnology: A Social Network Analysis (2011)
Working Paper: The knowledge-base evolution in biotechnology: a social network analysis (2011) Downloads
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