The paper aims to investigate how innovations cluster in different technological systems (TSs) when their ‘‘techno-economic’’, rather than ‘‘territorial’’ space, is considered. Innovation clusters of economic sectors are identified by referring to the innovation ‘‘potential’’ represented by their R&D expenditure and by applying social network analysis to the intersectoral R&D flows matrices of 15 OECD countries in the mid-1990s. Different clusterization models are first tested in order to detect the way sectors group on the basis of the embodied R&D flows they exchange. Actual clusters are then mapped in the different TSs by looking for intersectoral relationships which can be qualified to constitute ‘‘reduced TSs’’ (ReTSs). In all the 15 TSs investigated the techno-economic space appears organized in hierarchies, along which its constitutive sectors grouped into clusters with different density and composition. Once ReTSs are looked for, the 15 TSs display highly heterogeneous structures, but with some interesting similarity on the basis of which different clusters of TSs can be identified in turn. , , ,

Innovation clusters in technological systems: a network analysis of 15 OECD countries for the middle ’90s

MONTRESOR, SANDRO;
2008

Abstract

The paper aims to investigate how innovations cluster in different technological systems (TSs) when their ‘‘techno-economic’’, rather than ‘‘territorial’’ space, is considered. Innovation clusters of economic sectors are identified by referring to the innovation ‘‘potential’’ represented by their R&D expenditure and by applying social network analysis to the intersectoral R&D flows matrices of 15 OECD countries in the mid-1990s. Different clusterization models are first tested in order to detect the way sectors group on the basis of the embodied R&D flows they exchange. Actual clusters are then mapped in the different TSs by looking for intersectoral relationships which can be qualified to constitute ‘‘reduced TSs’’ (ReTSs). In all the 15 TSs investigated the techno-economic space appears organized in hierarchies, along which its constitutive sectors grouped into clusters with different density and composition. Once ReTSs are looked for, the 15 TSs display highly heterogeneous structures, but with some interesting similarity on the basis of which different clusters of TSs can be identified in turn. , , ,
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11387/112607
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