| By: |
Jackie Krafft (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis);
Francesco Quatraro (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis, Department of Economics, University of Turin - University of Turin);
Pier-Paolo Saviotti (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - CNRS : UMR6227 - Université de Nice Sophia-Antipolis, GAEL - Grenoble Applied Economic laboratory - Aucune) |
| 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 |
| Date: |
2011 |
| URL: |
http://d.repec.org/n?u=RePEc:hal:journl:hal-00539002&r=knm |