IDEAS home Printed from https://ideas.repec.org/p/zbw/zewdip/5215.html
   My bibliography  Save this paper

Mapping innovative clusters in national innovation systems

Author

Listed:
  • 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.

Suggested Citation

  • 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
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/24287/1/dp4598.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    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, April.
    16. Zoltan Acs & David Audretsch, 1990. "Innovation and Small Firms," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262011131, December.
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Chris Hendry & James Brown, 2006. "Dynamics of clustering and performance in the UK opto-electronics industry," Regional Studies, Taylor & Francis Journals, vol. 40(7), pages 707-725.
    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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Cohen, Wesley M., 2010. "Fifty Years of Empirical Studies of Innovative Activity and Performance," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 129-213, Elsevier.
    2. Acosta, Manuel & Coronado, Daniel, 2003. "Science-technology flows in Spanish regions: An analysis of scientific citations in patents," Research Policy, Elsevier, vol. 32(10), pages 1783-1803, December.
    3. Martin Falk & Mariya Hake, 2008. "Wachstumswirkungen der Forschungsausgaben," WIFO Studies, WIFO, number 34120, Juni.
    4. Aschhoff, Birgit & Sofka, Wolfgang, 2008. "Successful Patterns of Scientific Knowledge Sourcing: Mix and Match," ZEW Discussion Papers 08-033 [rev.], ZEW - Leibniz Centre for European Economic Research.
    5. Manuela Gussoni, 2009. "The determinants of inter-firms R&D cooperation and partner selection. A literature overview," Discussion Papers 2009/86, Dipartimento di Economia e Management (DEM), University of Pisa, Pisa, Italy.
    6. Kokko, Ari & Tingvall, Patrik Gustavsson & Videnord, Josefin, 2015. "The growth effects of R&D spending in the EU: A meta-analysis," Economics - The Open-Access, Open-Assessment E-Journal (2007-2020), Kiel Institute for the World Economy (IfW Kiel), vol. 9, pages 1-26.
    7. Nola Hewitt-Dundas, 2013. "The role of proximity in university-business cooperation for innovation," The Journal of Technology Transfer, Springer, vol. 38(2), pages 93-115, April.
    8. Bekkers, Rudi & Bodas Freitas, Isabel Maria, 2008. "Analysing knowledge transfer channels between universities and industry: To what degree do sectors also matter?," Research Policy, Elsevier, vol. 37(10), pages 1837-1853, December.
    9. David, Paul A. & Hall, Bronwyn H. & Toole, Andrew A., 2000. "Is public R&D a complement or substitute for private R&D? A review of the econometric evidence," Research Policy, Elsevier, vol. 29(4-5), pages 497-529, April.
    10. Becker Wolfgang & Peters Jürgen, 2005. "Innovation Effects of Science-Related Technological Opportunities / Innovationseffekte von technologischen Möglichkeiten aus dem Wissenschaftsbereich: Theoretical Considerations and Empirical Findings," Journal of Economics and Statistics (Jahrbuecher fuer Nationaloekonomie und Statistik), De Gruyter, vol. 225(2), pages 130-150, April.
    11. Bhushan Praveen Jangam & Badri Narayan Rath, 2020. "Cross-country convergence in global value chains: Evidence from club convergence analysis," International Economics, CEPII research center, issue 163, pages 134-146.
    12. Foray, Dominique & Lissoni, Francesco, 2010. "University Research and Public–Private Interaction," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 1, chapter 0, pages 275-314, Elsevier.
    13. Julie Le Gallo & Sandy Dall'erba, 2008. "Spatial and sectoral productivity convergence between European regions, 1975–2000," Papers in Regional Science, Wiley Blackwell, vol. 87(4), pages 505-525, November.
    14. Pamela Mueller, 2005. "Exploring the Knowledge Filter - How Entrepreneurship and University-Industry Relations Drive Economic Growth," ERSA conference papers ersa05p610, European Regional Science Association.
    15. Markus Eberhardt & Francis Teal, 2011. "Econometrics For Grumblers: A New Look At The Literature On Cross‐Country Growth Empirics," Journal of Economic Surveys, Wiley Blackwell, vol. 25(1), pages 109-155, February.
    16. Autant-Bernard, Corinne, 2001. "Science and knowledge flows: evidence from the French case," Research Policy, Elsevier, vol. 30(7), pages 1069-1078, August.
    17. Dirk Czarnitzki & Katrin Hussinger & Cédric Schneider, 2012. "The nexus between science and industry: evidence from faculty inventions," The Journal of Technology Transfer, Springer, vol. 37(5), pages 755-776, October.
    18. Manuel Acosta & Daniel Coronado & Esther Ferrándiz & M. Dolores León, 2014. "Regional Scientific Production and Specialization in Europe: The Role of HERD," European Planning Studies, Taylor & Francis Journals, vol. 22(5), pages 949-974, May.
    19. G. Urga & P. A. Geroski & S. Lazarova & C. F. Walters, 2003. "Are differences in firm size transitory or permanent?," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 18(1), pages 47-59.
    20. Rudi Bekkers & Bodas Freitas, 2008. "Analysing preferences for knowledge transfer channels between universities and industry: To what degree do sectors also matter?," Grenoble Ecole de Management (Post-Print) hal-01487467, HAL.

    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

    Lists

    This item is featured on the following reading lists, Wikipedia, or ReplicationWiki pages:
    1. Socio-Economics of Innovation

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:zbw:zewdip:5215. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/zemande.html .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.