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

Mario Coccia () and Saeed Roshani ()
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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

Journal of the Knowledge Economy, 2025, vol. 16, issue 1, No 173, 5024 pages

Abstract: 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.

Keywords: Quantum computing; Patent analysis; Topic modeling; Entity linking; S-Curve analysis; Logistic model; Technometrics; Technological change; Innovation management; Knowledge economy (search for similar items in EconPapers)
JEL-codes: O31 O32 (search for similar items in EconPapers)
Date: 2025
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DOI: 10.1007/s13132-024-01977-y

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