Studies on firms’ relationships and network structures have attracted more and more attention from several scholars, but surprisingly little is known about the role played by heterogeneous knowledge ties among the same set of actors and to what extent they follow overlapping or different routes of exchanging knowledge. In this vein, an investigation of multiple knowledge networks in clusters is a fundamental approach to interpret the reasons for innovation and economic performance. With an original dataset comprised of data collected by surveys directly administered in local wineries in the Montefalco wine region of Italy, this paper aims to analyse the roles played by different local knowledge ties, within a sector that is critically driven by the exchange of knowledge among economic actors. Social Network Analysis and Exponential Random Graph Modelling were applied in order to investigate the driving forces of the knowledge flows. The empirical results show that different kinds of relationships positively impact the spread of knowledge, but they are different in magnitude, and they follow complementary routes of exchange rather than overlapping ones.
Do firms exchange knowledge through complementary or substitutive routes of diffusion?
Maghssudipour A.;Lazzeretti L.;Capone F.
2019
Abstract
Studies on firms’ relationships and network structures have attracted more and more attention from several scholars, but surprisingly little is known about the role played by heterogeneous knowledge ties among the same set of actors and to what extent they follow overlapping or different routes of exchanging knowledge. In this vein, an investigation of multiple knowledge networks in clusters is a fundamental approach to interpret the reasons for innovation and economic performance. With an original dataset comprised of data collected by surveys directly administered in local wineries in the Montefalco wine region of Italy, this paper aims to analyse the roles played by different local knowledge ties, within a sector that is critically driven by the exchange of knowledge among economic actors. Social Network Analysis and Exponential Random Graph Modelling were applied in order to investigate the driving forces of the knowledge flows. The empirical results show that different kinds of relationships positively impact the spread of knowledge, but they are different in magnitude, and they follow complementary routes of exchange rather than overlapping ones.Pubblicazioni consigliate
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