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New Explanatory Models for Analysing Spatial Innovation: A Comparative Investigation

Author

Listed:
  • A. Reggiani

    (University of Bologna)

  • P. Nijkamp

    (Vrije Universiteit Amsterdam)

  • E. Sabella

    (University of Bologna and Vrije Universiteit Amsterdam)

Abstract

Innovation research has become an important topic in regional science analysis. Yet the modelling base of much innovation research is still feeble. This paper aims to map out the research potential of recent approaches in quantitative complexity analysis, in particular Neural Networks (NNs) analysis, from the perspective of their operational applicability in the space-economy. The urban context of European innovation processes is used as an empirical background. The paper addresses also the issue of space-time transferability of the tools employed.The first part of the paper is devoted to a concise conceptual overview and illustration of the innovation process, which is conceived of as a self-organising system. The second part presents empirical results on innovation processes in Europe. In this framework a comparative analysis is conducted between NN models and a conventional tool often used in spatial economics studies, viz. (non)linear regression analysis. The sensitivity of the various results, - by using 'transferability' experiments - is also examined. Theempirical experiments underline the advantages and limitations of these approaches from a methodological as well as an empirical viewpoint. They appear to offer a plausible range of values of empirical outcomes, which may highlight an acceptable degree of variation in spatial innovation processes.

Suggested Citation

  • A. Reggiani & P. Nijkamp & E. Sabella, 1999. "New Explanatory Models for Analysing Spatial Innovation: A Comparative Investigation," Tinbergen Institute Discussion Papers 98-131/3, Tinbergen Institute.
    • Handle: RePEc:tin:wpaper:19980131
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    References listed on IDEAS

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    1. Kangasharju, Aki & Nijkamp, Peter, 2001. "Innovation dynamics in space: local actors and local factors," Socio-Economic Planning Sciences, Elsevier, vol. 35(1), pages 31-56, March.
    2. Cristoforo S. Bertuglia & Silvana Lombardo & Peter Nijkamp (ed.), 1997. "Innovative Behaviour in Space and Time," Advances in Spatial Science, Springer, number 978-3-642-60720-2.
    3. Fischer, Manfred M. & Gopal, Sucharita, 1994. "Artificial Neural Networks. A New Approach to Modelling Interregional Telecommunication Flows," MPRA Paper 77822, University Library of Munich, Germany.
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