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Patent Deployment Strategies and Patent Value in LED Industry

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  • Ming-Fu Wu
  • Keng-Wei Chang
  • Wei Zhou
  • Juan Hao
  • Chien-Chung Yuan
  • Ke-Chiun Chang

Abstract

This study applies two variables in the measurement of company patent deployment strategies: patent family depth and earn plan ratio. Patent family depth represents the degree to which certain fields and markets are valued by the patent owner. Earn plan ratio defined as the ratio of the number of patent forward citations to patent family size. Earn plan ratio indicates the degree to which a patent family could be cited by later innovators and competitors. This study applies a logistic regression model in the analysis LED industry data. The results demonstrate that patent value has a positive relationship with the patent family depth, and earn plan ratio.

Suggested Citation

  • Ming-Fu Wu & Keng-Wei Chang & Wei Zhou & Juan Hao & Chien-Chung Yuan & Ke-Chiun Chang, 2015. "Patent Deployment Strategies and Patent Value in LED Industry," PLOS ONE, Public Library of Science, vol. 10(6), pages 1-10, June.
    • Handle: RePEc:plo:pone00:0129911
    DOI: 10.1371/journal.pone.0129911
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    References listed on IDEAS

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    Cited by:

    1. Jeong, Yujin & Park, Inchae & Yoon, Byungun, 2019. "Identifying emerging Research and Business Development (R&BD) areas based on topic modeling and visualization with intellectual property right data," Technological Forecasting and Social Change, Elsevier, vol. 146(C), pages 655-672.
    2. Way-Ren Huang & Chia-Jen Hsieh & Ke-Chiun Chang & Yen-Jo Kiang & Chien-Chung Yuan & Woei-Chyn Chu, 2017. "Network characteristics and patent value—Evidence from the Light-Emitting Diode industry," PLOS ONE, Public Library of Science, vol. 12(8), pages 1-14, August.
    3. Hu, Zewen & Zhou, Xiji & Lin, Angela, 2023. "Evaluation and identification of potential high-value patents in the field of integrated circuits using a multidimensional patent indicators pre-screening strategy and machine learning approaches," Journal of Informetrics, Elsevier, vol. 17(2).
    4. Chung, Park & Sohn, So Young, 2020. "Early detection of valuable patents using a deep learning model: Case of semiconductor industry," Technological Forecasting and Social Change, Elsevier, vol. 158(C).

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