IDEAS home Printed from https://ideas.repec.org/p/hal/journl/halshs-01952447.html

Technology networks: the autocatalytic origins of innovation

Author

Listed:
  • Lorenzo Napolitano
  • Evangelos Evangelou
  • Emanuele Pugliese
  • Paolo Zeppini

    (GREDEG - Groupe de Recherche en Droit, Economie et Gestion - UNS - Université Nice Sophia Antipolis (1965 - 2019) - CNRS - Centre National de la Recherche Scientifique - UniCA - Université Côte d'Azur)

  • Graham Room

Abstract

We analyse the autocatalytic structure of technological networks and evaluate its significance for the dynamics of innovation patenting. To this aim, we define a directed network of technological fields based on the International Patents Classification, in which a source node is connected to a receiver node via a link if patenting activity in the source field anticipates patents in the receiver field in the same region more frequently than we would expect at random. We show that the evolution of the technology network is compatible with the presence of a growing autocatalytic structure, i.e. a portion of the network in which technological fields mutually benefit from being connected to one another. We further show that technological fields in the core of the autocatalytic set display greater fitness, i.e. they tend to appear in a greater number of patents, thus suggesting the presence of positive spillovers as well as positive reinforcement. Finally, we observe that core shifts take place whereby different groups of technology fields alternate within the autocatalytic structure; this points to the importance of recombinant innovation taking place between close as well as distant fields of the hierarchical classification of technological fields.
(This abstract was borrowed from another version of this item.)

Suggested Citation

  • Lorenzo Napolitano & Evangelos Evangelou & Emanuele Pugliese & Paolo Zeppini & Graham Room, 2018. "Technology networks: the autocatalytic origins of innovation," Post-Print halshs-01952447, HAL.
    • Handle: RePEc:hal:journl:halshs-01952447
    as

    Download full text from publisher

    To our knowledge, this item is not available for download. To find whether it is available, there are three options:
    1. Check below whether another version of this item is available online.
    2. Check on the provider's web page whether it is in fact available.
    3. Perform a
    for a similarly titled item that would be available.

    Other versions of this item:

    Citations

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


    Cited by:

    1. Francesco de Cunzo & Alberto Petri & Andrea Zaccaria & Angelica Sbardella, 2022. "The trickle down from environmental innovation to productive complexity," Papers 2206.07537, arXiv.org.
    2. Napolitano, Lorenzo & Sbardella, Angelica & Consoli, Davide & Barbieri, Nicolò & Perruchas, François, 2022. "Green innovation and income inequality: A complex system analysis," Structural Change and Economic Dynamics, Elsevier, vol. 63(C), pages 224-240.
    3. Sabrina Aufiero & Giordano De Marzo & Angelica Sbardella & Andrea Zaccaria, 2023. "Mapping job complexity and skills into wages," Papers 2304.05251, arXiv.org.
    4. Angelica Sbardella & Andrea Zaccaria & Luciano Pietronero & Pasquale Scaramozzino, 2021. "Behind the Italian Regional Divide: An Economic Fitness and Complexity Perspective," LEM Papers Series 2021/30, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    5. Lafond, François, 2025. "Forecasting technological progress," INET Oxford Working Papers 2025-10, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford, revised Dec 2025.
    6. Hafele, Jakob & Le Lannou, Laure-Alizée & Rochowicz, Nils & Kuhls, Sonia & Gräbner-Radkowitsch, Claudius, 2023. "Securing future-fit jobs in the green transformation: A policy framework for industrial policy," ZOE Discussion Papers 10, ZOE. institute for future-fit economies, Bonn.
    7. Pichler, Anton & Lafond, François & Farmer, J. Doyne, 2020. "Technological interdependencies predict innovation dynamics," INET Oxford Working Papers 2020-04, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
    8. Savin, Ivan & Ott, Ingrid & Konop, Chris, 2022. "Tracing the evolution of service robotics: Insights from a topic modeling approach," Technological Forecasting and Social Change, Elsevier, vol. 174(C).
    9. Arnaud Persenda & Flora Bellone & Paolo Zeppini, 2021. "The Rise of China in the Global Production Network: What can Autocatalytic Sets teach us?," Post-Print halshs-03579942, HAL.
    10. Emanuele Pugliese & Lorenzo Napolitano & Andrea Zaccaria & Luciano Pietronero, 2019. "Coherent diversification in corporate technological portfolios," PLOS ONE, Public Library of Science, vol. 14(10), pages 1-22, October.
    11. DIODATO Dario, 2024. "Handbook of Economic Complexity for Policy," JRC Research Reports JRC138666, Joint Research Centre.
    12. Giambattista Albora & Matteo Straccamore & Andrea Zaccaria, 2024. "Machine learning-based similarity measure to forecast M&A from patent data," Papers 2404.07179, arXiv.org.
    13. Frank Neffke & Angelica Sbardella & Ulrich Schetter & Andrea Tacchella, 2024. "Economic Complexity Analysis," Papers in Evolutionary Economic Geography (PEEG) 2430, Utrecht University, Department of Human Geography and Spatial Planning, Group Economic Geography, revised Oct 2024.
    14. Emanuele Pugliese & Lorenzo Napolitano & Matteo Chinazzi & Guido Chiarotti, 2019. "The Emergence of Innovation Complexity at Different Geographical and Technological Scales," Papers 1909.05604, arXiv.org.
    15. Arnaud Persenda & Alexandre Ruiz, 2023. "Autocatalytic Networks and the Green Economy," GREDEG Working Papers 2023-16, Groupe de REcherche en Droit, Economie, Gestion (GREDEG CNRS), Université Côte d'Azur, France.

    More about this item

    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:hal:journl:halshs-01952447. 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.

    We have no bibliographic references for this item. You can help adding them by using 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: CCSD (email available below). General contact details of provider: https://hal.archives-ouvertes.fr/ .

    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.