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Entropy statistics as a framework to analyse technological evolution

In: Applied Evolutionary Economics and Complex Systems

Author

Listed:
  • Koen Frenken
  • Alessandro Nuvolari

Abstract

This book takes up the challenge of developing an empirically based foundation for evolutionary economics built upon complex system theory. The authors argue that modern evolutionary economics is at a crossroads. At a theoretical level, modern evolutionary economics is moving away from the traditional focus of the operation of selection mechanisms and towards concepts of ‘complex adaptive systems' and self-organisation. On an applied level, new and innovative methods of empirical research are being developed and considered. The contributors take up this challenge and examine aspects of complexity and evolution in applied contexts.

Suggested Citation

  • Koen Frenken & Alessandro Nuvolari, 2004. "Entropy statistics as a framework to analyse technological evolution," Chapters, in: John Foster & Werner Hölzl (ed.), Applied Evolutionary Economics and Complex Systems, chapter 5, Edward Elgar Publishing.
    • Handle: RePEc:elg:eechap:3061_5
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    Cited by:

    1. Silverberg, G. & Verspagen, B., 2003. "Brewing the future: stylized facts about innovation and their confrontation with a percolation model," Working Papers 03.06, Eindhoven Center for Innovation Studies.
    2. Triulzi, Giorgio & Alstott, Jeff & Magee, Christopher L., 2020. "Estimating technology performance improvement rates by mining patent data," Technological Forecasting and Social Change, Elsevier, vol. 158(C).
    3. Jackie Krafft & Francesco Quatraro & Pier Saviotti, 2014. "Knowledge characteristics and the dynamics of technological alliances in pharmaceuticals: empirical evidence from Europe, US and Japan," Journal of Evolutionary Economics, Springer, vol. 24(3), pages 587-622, July.
    4. Jackie Krafft & Francesco Quatraro & Pier-Paolo Saviotti, 2008. "Evolution of the knowledge base in knowledge intensive sectors," Working Papers hal-00264261, HAL.
    5. Jackie Krafft & Francesco Quatraro, 2011. "The Dynamics of Technological Knowledge: From Linearity to Recombination," Chapters, in: Cristiano Antonelli (ed.), Handbook on the Economic Complexity of Technological Change, chapter 7, Edward Elgar Publishing.
    6. Emilia Tomczyk, 2012. "Information content of survey data: applications of entropy and dissimilarity measures," Working Papers 62, Department of Applied Econometrics, Warsaw School of Economics.
    7. Koen Frenken & Alessandro Nuvolari, 2004. "The early development of the steam engine: an evolutionary interpretation using complexity theory," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 13(2), pages 419-450, April.
    8. Francesco Quatraro, 2016. "Co-evolutionary Patterns in Regional Knowledge Bases and Economic Structure: Evidence from European Regions," Regional Studies, Taylor & Francis Journals, vol. 50(3), pages 513-539, March.
    9. Francesco Quatraro, 2012. "The Co-Evolution of Knowledge and Economic Structure: Evidence from European Regions," GREDEG Working Papers 2012-16, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.
    10. Jackie Krafft & Francesco Quatraro & Pier Paolo Saviotti, 2011. "The knowledge-base evolution in biotechnology: a social network analysis," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 20(5), pages 445-475.
    11. Mirko Titze & Matthias Brachert & Alexander Kubis, 2011. "The Identification of Regional Industrial Clusters Using Qualitative Input-Output Analysis (QIOA)," Regional Studies, Taylor & Francis Journals, vol. 45(1), pages 89-102.
    12. Francesco Lamperti & Roberto Mavilia & Simona Castellini, 2017. "The role of Science Parks: a puzzle of growth, innovation and R&D investments," The Journal of Technology Transfer, Springer, vol. 42(1), pages 158-183, February.

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