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Mapping innovative clusters in national innovation systems

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  • Spielkamp, Alfred
  • Vopel, Katrin

Abstract

In the following paragraphs we will discuss the ?mapping of innovative clusters in national innovation systems?. For this we have used a data set of almost 3.000 firms that participated in the first and fifth survey of the Mannheimer Innovation Survey (which is comparable with CIS data). The Community Innovation Survey (CIS) is an initiative of the EU Commission and a joint survey of DG XIII/SPRINT/EIMS and Eurostat. To begin with we will, in the context of a definition of innovation systems, highlight the outline conditions for innovations in Germany, focusing above all on the basis of innovations, science and engineering. This is followed by a step-by-step empirical analysis of the mapping of innovative clusters at the company level which is based on the Community Innovation Survey set of data; and finally the structural influences (size-effect, effects of sectors/industries) on the innovative behaviour or innovative styles are presented. The explanatory power of structural influences on the innovative behaviour will also be analysed as well as the influence of other variables such as information flows and cooperation patterns within the innovation system of Germany. In the summary at the end of this paper we will suggest starting points for potential implications for innovation policy in order to be able to develop generic and specific policies for the different industry clusters. As far as we know from firms innovating at a certain level of organisation, they use a special portfolio of information and knowledge transfer strategies that can not simply be transferred to firms which are not (yet) innovative. While accepting that innovative inhouse activities are necessary to keep track with international developments and competition, a highly innovative atmosphere within the economy which supports innovative activities should be among the main goals of innovation policy. Furthermore, firms need to have an absorptive capacity to transform knowledge into innovations that bring economic success.

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  • Spielkamp, Alfred & Vopel, Katrin, 1998. "Mapping innovative clusters in national innovation systems," ZEW Discussion Papers 98-45, ZEW - Leibniz Centre for European Economic Research.
    • Handle: RePEc:zbw:zewdip:5215
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    as
    1. Philip McCann, 1995. "Rethinking the Economics of Location and Agglomeration," Urban Studies, Urban Studies Journal Limited, vol. 32(3), pages 563-577, April.
    2. Bernard, Andrew B & Jones, Charles I, 1996. "Productivity across Industries and Countries: Time Series Theory and Evidence," The Review of Economics and Statistics, MIT Press, vol. 78(1), pages 135-146, February.
    3. Mansfield, Edwin, 1998. "Academic research and industrial innovation: An update of empirical findings1," Research Policy, Elsevier, vol. 26(7-8), pages 773-776, April.
    4. Mansfield, Edwin, 1991. "Academic research and industrial innovation," Research Policy, Elsevier, vol. 20(1), pages 1-12, February.
    5. Durlauf, Steven N & Johnson, Paul A, 1995. "Multiple Regimes and Cross-Country Growth Behaviour," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 10(4), pages 365-384, Oct.-Dec..
    6. Debresson, Chris, 1989. "Breeding innovation clusters: A source of dynamic development," World Development, Elsevier, vol. 17(1), pages 1-16, January.
    7. Beise, Marian & Stahl, Harald, 1999. "Public research and industrial innovations in Germany," Research Policy, Elsevier, vol. 28(4), pages 397-422, April.
    8. Keith Smith, "undated". "Interactions in knowledge systems: Foundations, policy implications and empirical methods," STEP Report series 199410, The STEP Group, Studies in technology, innovation and economic policy.
    9. Hughes, Kirsty, 1988. "The interpretation and measurement of R&D intensity -- A note," Research Policy, Elsevier, vol. 17(5), pages 301-307, October.
    10. Cohen, Wesley M & Klepper, Steven, 1992. "The Anatomy of Industry R&D Intensity Distributions," American Economic Review, American Economic Association, vol. 82(4), pages 773-799, September.
    11. Kleinknecht, Alfred, 1987. "Measuring R&D in Small Firms: How Much Are We Missing?," Journal of Industrial Economics, Wiley Blackwell, vol. 36(2), pages 253-256, December.
    12. Felder, Johannes & Licht, Georg & Nerlinger, Eric A. & Stahl, Harald, 1995. "Appropriability, opportunity, firm size and innovation activities: empirical results using East and West German firm level data," ZEW Discussion Papers 95-21, ZEW - Leibniz Centre for European Economic Research.
    13. Eltis, Walter, 1996. "How Low Profitability and Weak Innovativeness Undermined UK Industrial Growth," Economic Journal, Royal Economic Society, vol. 106(434), pages 184-195, January.
    14. Kleinknecht, Alfred & Reijnen, Jeroen O. N., 1992. "Why do firms cooperate on R&D? an empirical study," Research Policy, Elsevier, vol. 21(4), pages 347-360, August.
    15. Giovanni Dosi & Christopher Freeman & Richard Nelson & Gerarld Silverberg & Luc Soete (ed.), 1988. "Technical Change and Economic Theory," LEM Book Series, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy, number dosietal-1988, November.
    16. Zoltan Acs & David Audretsch, 1990. "Innovation and Small Firms," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011131, April.
    17. Bernard, Andrew B & Jones, Charles I, 1996. "Comparing Apples to Oranges: Productivity Convergence and Measurement across Industries and Countries," American Economic Review, American Economic Association, vol. 86(5), pages 1216-1238, December.
    18. Gernot Hutschenreiter, 1994. "Technologische Cluster in der österreichischen Industrie," WIFO Monatsberichte (monthly reports), WIFO, vol. 67(11), pages 624-627, November.
    19. Teubal, Morris & Yinnon, Tamar & Zuscovitch, Ehud, 1991. "Networks and market creation," Research Policy, Elsevier, vol. 20(5), pages 381-392, October.
    20. John Scott, 1984. "Firm versus Industry Variability in R&D Intensity," NBER Chapters, in: R&D, Patents, and Productivity, pages 233-248, National Bureau of Economic Research, Inc.
    21. Bennett Harrison, 2007. "Industrial Districts: Old Wine in New Bottles? (Volume 26, Number 5, 1992)," Regional Studies, Taylor & Francis Journals, vol. 41(sup1), pages 107-121.
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    2. Tom Broekel & Thomas Brenner, 2011. "Regional factors and innovativeness: an empirical analysis of four German industries," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 47(1), pages 169-194, August.

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    More about this item

    Keywords

    Systems of Innovation; Cluster Analysis; Knowledge Distribution; Research and Technology Policy;
    All these keywords.

    JEL classification:

    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D
    • O38 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Government Policy

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    1. Socio-Economics of Innovation

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