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Identifying Clusters as Local Innovation Systems

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  • George Christopoulos

    (United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT))

  • René Wintjes

    (United Nations University - Maastricht Economic and Social Research Institute on Innovation and Technology (UNU-MERIT))

Abstract

This paper introduces an indicator for identifying innovation clusters that transcend traditional sectoral taxonomies and integrate the creation and use of knowledge in regional economic systems. Such clusters can be expected, based on the literature, to provide fertile ground for feedback mechanisms between knowledge supply and demand, hence contributing to circular cumulative growth dynamics through interactive learning. However, when it comes to operationalising the study of innovation, the creation and use of knowledge have been treated as distinct processes in related work. It is this gap that this paper seeks to address. Applying principal component analysis on location quotients of manufacturing employment data and patent microdata for 152 EU regions, we generate a mapping of co-located innovation-related activity that highlights the complex techno-economic structures of regional economies. Our analysis reveals clusters which include industries traditionally labelled as ‘high-tech’, as well as clusters that reflect centuries-old trajectories of geographically concentrated production specialisation. This research sheds new light on the co-location of innovation-related activity in regional economies and provides insights for policymakers and practitioners seeking to foster innovation and economic development in the context of evolving knowledge and production eco-systems.

Suggested Citation

  • George Christopoulos & René Wintjes, 2024. "Identifying Clusters as Local Innovation Systems," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(2), pages 9784-9823, June.
  • Handle: RePEc:spr:jknowl:v:15:y:2024:i:2:d:10.1007_s13132-023-01481-9
    DOI: 10.1007/s13132-023-01481-9
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