IDEAS home Printed from https://ideas.repec.org/a/spr/jknowl/v16y2025i1d10.1007_s13132-024-01977-y.html
   My bibliography  Save this article

Path-Breaking Directions in Quantum Computing Technology: A Patent Analysis with Multiple Techniques

Author

Listed:
  • Mario Coccia

    (CNR - National Research Council of Italy, IRCRES - Turin Research Area of the National Research Council, Strada Delle Cacce)

  • Saeed Roshani

    (Amirkabir University of Technology)

Abstract

The rapid advancement of quantum computing technology has profound implications in knowledge economy for various sectors including cybersecurity, healthcare, finance, and logistics, among others. The understanding of evolutionary patterns in quantum computing is a basic goal for strategic planning and technological development of nations. This study applies, using patent data, different approaches, such as the logistic model and the entity-linking technique, to analyze the evolutionary trajectories of topics in quantum computing. Technology analysis of patents here detects three distinctive stages—the emerging stage (1992–2008), the growth stage (2009–2017), and the maturity stage (2018–2022)— and shows main characteristics of the technology life cycle in quantum computing for technological forecasting and management. Logistic model suggests that quantum computing technology seems to be in a maturity stage, as evidenced by a surge in patent filings since 2016. Dominant topics are given by qubits, quantum gates, quantum information, and quantum dots exhibit exponential growth, and suggest their pivotal role in technological evolution of quantum computing. In addition, the entity-linking method uncovers complex and evolving interconnections in quantum computing topics over time: a suggested categorization in emerging, declining, dominant, and saturated topics clarifies critical groups that guide new directions of technological progress in quantum computing. The insights of this study can shed light on complex scientific and technological dynamics that drive the co-evolution of quantum computing technologies that can support strategies of innovation management and policies to foster technological change for competitive advantage of firms and nations in turbulent markets.

Suggested Citation

  • Mario Coccia & Saeed Roshani, 2025. "Path-Breaking Directions in Quantum Computing Technology: A Patent Analysis with Multiple Techniques," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 16(1), pages 4991-5024, March.
  • Handle: RePEc:spr:jknowl:v:16:y:2025:i:1:d:10.1007_s13132-024-01977-y
    DOI: 10.1007/s13132-024-01977-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13132-024-01977-y
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s13132-024-01977-y?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    More about this item

    Keywords

    Quantum computing; Patent analysis; Topic modeling; Entity linking; S-Curve analysis; Logistic model; Technometrics; Technological change; Innovation management; Knowledge economy;
    All these keywords.

    JEL classification:

    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

    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:spr:jknowl:v:16:y:2025:i:1:d:10.1007_s13132-024-01977-y. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.