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A network analytic method for measuring patent thickets: A case of FCEV technology

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  • Yuan, Xiaodong
  • Li, Xiaotao

Abstract

Patent thickets may hinder technology innovation by preventing manufacturers from access to given technology fields. How to prove the existence of patent thickets or how to hack through patent thickets in complex technology areas has attracted a great concern in academia since Shapiro (2000) put forward the theory of patent thickets. This needs a valid and simple method to measure patent thickets. The existing methods are hard to further explore who own complementary patents in patent thickets. The paper proposes a novel method of combining triad census and data-driven social role analysis to measure patent thickets. Taking fuel cell electric vehicle (FCEV) patents at the USPTO and EPO as examples, the paper demonstrates the proposed method is valid and feasible in practice. Both the density of patent thickets and key patent holders in patent thickets can be accurately detected. It can help downstream manufacturers to make a decision whether they should enter given technologies or who could be potential licensors in patent thickets. Researchers or company managers can use this method to measure patent thickets over time from a microscopic perspective.

Suggested Citation

  • Yuan, Xiaodong & Li, Xiaotao, 2020. "A network analytic method for measuring patent thickets: A case of FCEV technology," Technological Forecasting and Social Change, Elsevier, vol. 156(C).
    • Handle: RePEc:eee:tefoso:v:156:y:2020:i:c:s0040162519302793
    DOI: 10.1016/j.techfore.2020.120038
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    Cited by:

    1. Li, Xiaotao & Yuan, Xiaodong, 2022. "Tracing the technology transfer of battery electric vehicles in China: A patent citation organization network analysis," Energy, Elsevier, vol. 239(PD).
    2. Yuan, Xiaodong & Li, Xiaotao, 2021. "The evolution of the industrial value chain in China's high-speed rail driven by innovation policies: A patent analysis," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    3. Xiaodong Yuan & Weiling Song, 2022. "Evaluating technology innovation capabilities of companies based on entropy- TOPSIS: the case of solar cell companies," Information Technology and Management, Springer, vol. 23(2), pages 65-76, June.
    4. Yuan, Xiaodong & Cai, Yuchen, 2021. "Forecasting the development trend of low emission vehicle technologies: Based on patent data," Technological Forecasting and Social Change, Elsevier, vol. 166(C).
    5. Higham, Kyle & Contisciani, Martina & De Bacco, Caterina, 2022. "Multilayer patent citation networks: A comprehensive analytical framework for studying explicit technological relationships," Technological Forecasting and Social Change, Elsevier, vol. 179(C).
    6. Xiaodong Yuan & Xiaotao Li, 2022. "Pledging Patent Rights for Fighting Against the COVID-19: From the Ethical and Efficiency Perspective," Journal of Business Ethics, Springer, vol. 179(3), pages 683-696, September.

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