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Norwegian Input-Output Clusters and Innovation Patterns

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Abstract

Current understanding of innovation and technical change emphasises the importance of the systemic dimensions to innovation performance. Being a basis for the innovation system approach for analysing innovation activities, this emphasises the need for understanding economic and technological interaction beyond the level of firm to firm relations. Aggregate structural characteristics of user-producer links in the Norwegian economy are analysed in this paper through the use of input-output tables. The resulting clusters are described. The main question addressed in this paper is of the existence of cluster-wide innovation patterns; can we discern cluster specific modes of technical change and innovation at the cluster level, and if so, what are their main dimensions? We conclude that there is indeed cluster-specific signatures, or modes, of technical change, reflecting underlying innovation and technical specificities of industries and the complementary interaction between these that is highlighted by the cluster approach.

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  • Johan Hauknes, "undated". "Norwegian Input-Output Clusters and Innovation Patterns," STEP Report series 199815, The STEP Group, Studies in technology, innovation and economic policy.
    • Handle: RePEc:stp:stepre:1998r15
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    File URL: http://www.step.no/reports/Y1998/1598.pdf
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    Cited by:

    1. Ana Salome Garcia Muniz & Antonio Morillas Raya & Carmen Ramos Carvajal, 2008. "Key Sectors: A New Proposal from Network Theory," Regional Studies, Taylor & Francis Journals, vol. 42(7), pages 1013-1030.
    2. Narula, Rajneesh, 2002. "Innovation systems and 'inertia' in R&D location: Norwegian firms and the role of systemic lock-in," Research Policy, Elsevier, vol. 31(5), pages 795-816, July.
    3. Lee, Lena & Wong, Poh Kam, 2009. "Firms’ Innovative Performance: The Mediating Role of Innovative Collaborations," MPRA Paper 16193, University Library of Munich, Germany.
    4. Zdravko Zekic & Luka Samarzija & Nikolina Dukic, 2015. "Comparative Wood Cluster Mapping With A Special Focus On The Wood Clusters In Eastern Croatia," Economy of eastern Croatia yesterday, today, tommorow, Josip Juraj Strossmayer University of Osijek, Faculty of Economics, Croatia, vol. 4, pages 133-141.
    5. Henryk Gurgul & Pawel Majdosz, 2008. "The Modified Diagonalization Method for Analysing Clusters within Economies," Managing Global Transitions, University of Primorska, Faculty of Management Koper, vol. 6(1), pages 53-73.
    6. Gerardo A. Perez-Valdes & Vibeke S. Nørstebø & May-Britt Ellingsen & Jukka Teräs & Adrian T. Werner, 2019. "Bioeconomic Clusters—Background, Emergence, Localization and Modelling," Sustainability, MDPI, vol. 11(17), pages 1-17, August.
    7. Ana Salomé García Muñiz & Fidel Aroche Reyes & Carmen Ramos Carvajal, 2007. "Determinación de coeficientes importantes por niveles tecnológicos: una aproximación desde el modelo de Miyazawa," Investigaciones Economicas, Fundación SEPI, vol. 31(1), pages 161-190, January.
    8. Dumont, Michel & Tsakanikas, Aggelos, 2001. "Knowledge spillovers through R&D networking," MPRA Paper 70570, University Library of Munich, Germany.
    9. Hauknes, Johan & Knell, Mark, 2009. "Embodied knowledge and sectoral linkages: An input-output approach to the interaction of high- and low-tech industries," Research Policy, Elsevier, vol. 38(3), pages 459-469, April.
    10. Barbara Diaz & Laura Moniche & Antonio Morillas, 2006. "A Fuzzy clustering approach to the key sectors of the Spanish economy," Economic Systems Research, Taylor & Francis Journals, vol. 18(3), pages 299-318.
    11. Dumont, Michel & Tsakanikas, Aggelos, 2002. "The evolution of intra- and inter-sector knowledge spillovers in the EU Framework Programmes," MPRA Paper 70571, University Library of Munich, Germany.

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