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The Synergy and Cycle Values in Regional Innovation Systems: The Case of Norway

Author

Listed:
  • Inga Ivanova

    (National Research University Higher School of Economics (Russia))

  • Oivind Strand

    (Norwegian University of Science and Technology (NTNU, Norway))

  • Loet Leydesdorff

    (University of Amsterdam (The Netherlands))

Abstract

The innovation capacity of a system can be measured as the synergy in interactions among its parts. Synergy can be considered as a consequence of negative entropies among three parts of the system. We analyze the development of synergy value in the Norwegian innovation system in terms of mutual information among geographical, sectorial, and size distributions of firms. We use three different techniques for the evaluation of the evolution of synergy over time: rescaled range analysis, DFT, and geographical synergy decomposition. The data was provided by Statistics Norway for all Norwegian firms registered in the database between 2002 and 2014. The results suggest that the synergy at the level of both the country and its seven regions show non-chaotic oscillatory behavior which resonates in a set of natural frequencies. The finding of a set of frequencies implies a complex Triple-Helix structure, composed of many elementary triple helices, which can be theorized in terms of a fractal TH manifold.

Suggested Citation

  • Inga Ivanova & Oivind Strand & Loet Leydesdorff, 2019. "The Synergy and Cycle Values in Regional Innovation Systems: The Case of Norway," Foresight and STI Governance (Foresight-Russia till No. 3/2015), National Research University Higher School of Economics, vol. 13(1), pages 48-61.
  • Handle: RePEc:hig:fsight:v:13:y:2019:i:1:p:48-61
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    References listed on IDEAS

    as
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    6. Dixon, Robert & Shepherd, David, 2001. "Trends and Cycles in Australian State and Territory Unemployment Rates," The Economic Record, The Economic Society of Australia, vol. 77(238), pages 252-269, September.
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    11. Inga A. Ivanova & Loet Leydesdorff, 2014. "A simulation model of the Triple Helix of university–industry–government relations and the decomposition of the redundancy," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(3), pages 927-948, June.
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    18. de Groot, Bert & Franses, Philip Hans, 2012. "Common socio-economic cycle periods," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 59-68.
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    21. Loet Leydesdorff & Ping Zhou, 2014. "Measuring the knowledge-based economy of China in terms of synergy among technological, organizational, and geographic attributes of firms," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1703-1719, March.
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    Cited by:

    1. Vladimir Byvshev & Kristina Parfenteva & Irina Panteleeva & Danil Uskov & Vadim Demin, 2022. "Methodology for assessing the effectiveness of regional infrastructure facilities to support scientific, technical and innovation activities in the context of the synergy effect: analysis, formation a," Journal of Innovation and Entrepreneurship, Springer, vol. 11(1), pages 1-17, December.

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    More about this item

    Keywords

    triple helix; knowledge base; innovations; synergy; cycles; regional innovation system; regions of Norway;
    All these keywords.

    JEL classification:

    • O21 - Economic Development, Innovation, Technological Change, and Growth - - Development Planning and Policy - - - Planning Models; Planning Policy
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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