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A novel approach to explore patent development paths for subfield technologies

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  • Jae Ha Gwak
  • So Young Sohn

Abstract

Many algorithms for searching the main paths according to a subfield technology have been suggested using patent citation networks. However, the process by which the specific field is divided into subfields is problematic, in the sense that citation information among individual patents in different subfields is lost. If convergence technologies are common among different subfields, this problem can result in an inappropriate main path being found. To resolve this problem, we propose a new algorithm capable of extracting the main paths for each subfield of a technology by using the International Patent Classification (IPC) codes of patents. The proposed algorithm is applied to the waste management field to allow core technologies in the subfields of waste disposal, waste treatment, and the reuse of waste materials to be found. Finally, a sensitivity analysis is performed by considering the standard of the component ratio along a specific path to demonstrate the robustness of the proposed algorithm in the waste management field.

Suggested Citation

  • Jae Ha Gwak & So Young Sohn, 2018. "A novel approach to explore patent development paths for subfield technologies," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 69(3), pages 410-419, March.
    • Handle: RePEc:bla:jinfst:v:69:y:2018:i:3:p:410-419
    DOI: 10.1002/asi.23962
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    Cited by:

    1. Lai, Kuei-Kuei & Bhatt, Priyanka C. & Kumar, Vimal & Chen, Hsueh-Chen & Chang, Yu-Hsin & Su, Fang-Pei, 2021. "Identifying the impact of patent family on the patent trajectory: A case of thin film solar cells technological trajectories," Journal of Informetrics, Elsevier, vol. 15(2).
    2. Wang, Xiaoli & Liang, Wenting & Ye, Xuanting & Chen, Lingdi & Liu, Yun, 2024. "Disruptive development path measurement for emerging technologies based on the patent citation network," Journal of Informetrics, Elsevier, vol. 18(1).
    3. Jeon, Eunji & Yoon, Naeun & Sohn, So Young, 2023. "Exploring new digital therapeutics technologies for psychiatric disorders using BERTopic and PatentSBERTa," Technological Forecasting and Social Change, Elsevier, vol. 186(PA).
    4. Feng, Sida & Magee, Christopher L., 2020. "Technological development of key domains in electric vehicles: Improvement rates, technology trajectories and key assignees," Applied Energy, Elsevier, vol. 260(C).
    5. Shu-Hao Chang, 2022. "Examining Key Technologies Among Academic Patents Through an Analysis of Standard-Essential Patents," SAGE Open, , vol. 12(3), pages 21582440221, July.

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