Abstract

It is now widely accepted that innovation is a territorially embedded process, which cannot be fully understood independent of the social and institutional conditions of individual places. On the basis of these considerations, some authors identified criteria to define the geographic confines for the innovative process, introducing the concept of the local systems of innovation (LIS), defined as networks of technologically specialized and locally situated firms, institutions and research agencies. Nevertheless empirical evidences show that especially in high tech industry like life sciences, relatively few clusters are completely self-sufficient in terms of the knowledge base from which they draw suggesting that the knowledge flows that feed innovation in a cluster are often both local and global.According to these considerations and starting from the knowledge based theory of innovations systems the paper proposes a theoretical framework that classifies the innovation systems considering the place of knowledge sourcing and the place of knowledge development. The framework has then been used to classify the European life sciences clusters. The empirical analysis shows that Local Innovation System is only a possible configuration of technology clusters that can be assumes also the configurations of Imported Innovation Systems, Exported Innovation Systems and Global Innovation Systems.

Highlights

  • Some authors underline as the phenomenon of the globalization of the world market have increased and not reduced the importance of the characteristics of local context as driver of the firms ‘competitive advantage

  • On the basis of these considerations, some authors identified criteria to define the geographic confines for the innovative process, introducing the concept of the “national innovation system” (NIS) (Freeman, 1987),“regional innovation system” (RIS), (Doloreux, 2002) and of local systems of innovation (LIS)(Cooke 2001, 2004; Asheim & Coenen, 2005)

  • The paper will be organised as follows: the section 2 presents a short review of the studies of the knowledge based theory of innovation systems summarising both the traditional approaches and the more recent studies on global knowledge flows; the section 3 presents the original framework; the section 4 shows the application of the framework to the European Life Sciences Clusters; the section 4 summarizes the papers’ conclusions

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Summary

Introduction

Some authors underline as the phenomenon of the globalization of the world market have increased and not reduced the importance of the characteristics of local context as driver of the firms ‘competitive advantage. At the same time some authors have defined the generation of innovation as a local embedded process in which the firm collaborates with other actors, such as research agencies and government institutions, in both developmental and implementation phases (Fagerberg, 2004) This observation concerning institutions, and the consideration that geographic proximity permits role-players to interact more quickly led to a realisation of the importance of the territorial variable in stimulating development of innovation (Lundvall & Johnson 1994; Etzkowitz & Leyedsdorff, 2000). While some elements of these complex technologies may be co-located in an individual cluster, increasingly the components of these networks are situated across a wide array of locations This suggests that the knowledge flows that feed innovation in a cluster are often both local and global (Bathelt et al, 2004). The paper will be organised as follows: the section 2 presents a short review of the studies of the knowledge based theory of innovation systems summarising both the traditional approaches and the more recent studies on global knowledge flows; the section 3 presents the original framework; the section 4 shows the application of the framework to the European Life Sciences Clusters; the section 4 summarizes the papers’ conclusions

The Importance of Local Dimension
A New Framework of Innovation Systems
Empirical Analysis
Findings
Conclusions
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