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Can patent family size and composition signal patent value?

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  • Francois P. Kabore
  • Walter G. Park

Abstract

Recent research has proposed a method of patent valuation based on weighting patent family size by the market size of the countries in the family. The premise is that inventors tend to seek greater international coverage for their more valuable patents. The paper presents a novel way to test the ability of market size-weighted patent families to predict patent value and compares the method against extant measures of patent valuation based on patent citations and renewal behaviour. We use forecasting techniques to show that the weighted patent family size measure outperforms other methods in terms of predicting patent life and the number of citations. An advantage of the weighted patent family size measure is that it is based on ex-ante information and is easy to construct for purposes of evaluating patent value. We demonstrate this advantage using a large, comprehensive database of international patent families.

Suggested Citation

  • Francois P. Kabore & Walter G. Park, 2019. "Can patent family size and composition signal patent value?," Applied Economics, Taylor & Francis Journals, vol. 51(60), pages 6476-6496, December.
    • Handle: RePEc:taf:applec:v:51:y:2019:i:60:p:6476-6496
    DOI: 10.1080/00036846.2019.1624914
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    Citations

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    Cited by:

    1. Nie, Pu-yan & Chen, Zi-rui & Wang, Chan, 2021. "Intellectual property pricing under asymmetric duopoly," Journal of Retailing and Consumer Services, Elsevier, vol. 58(C).
    2. Yuan, Xiaodong & Li, Xiaotao, 2021. "Mapping the technology diffusion of battery electric vehicle based on patent analysis: A perspective of global innovation systems," Energy, Elsevier, vol. 222(C).
    3. 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).
    4. Song, Haoyang & Hou, Jianhua & Zhang, Yang, 2023. "The measurements and determinants of patent technological value: Lifetime, strength, breadth, and dispersion from the technology diffusion perspective," Journal of Informetrics, Elsevier, vol. 17(1).
    5. Appio, Francesco Paolo & Baglieri, Daniela & Cesaroni, Fabrizio & Spicuzza, Lucia & Donato, Alessia, 2022. "Patent design strategies: Empirical evidence from European patents," Technological Forecasting and Social Change, Elsevier, vol. 181(C).
    6. Ronald B. Davies & Dieter Franz Kogler & Ryan M. Hynes, 2020. "Patent Boxes and the Success Rate of Applications," Working Papers 202018, School of Economics, University College Dublin.
    7. 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).
    8. Ekaterina Turkina & Boris Oreshkin, 2021. "The Impact of Co-Inventor Networks on Smart Cleantech Innovation: The Case of Montreal Agglomeration," Sustainability, MDPI, vol. 13(13), pages 1-17, June.
    9. Mohd Shadab Danish & Pritam Ranjan & Ruchi Sharma, 2022. "Assessing the Impact of Patent Attributes on the Value of Discrete and Complex Innovations," Papers 2208.07222, arXiv.org.
    10. Sergio Cuellar & Alberto Méndez-Morales & Milton M. Herrera, 2022. "Location Matters: a Novel Methodology for Patent’s National Phase Process," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 13(3), pages 2138-2163, September.
    11. Jianhua Hou & Xiucai Yang & Haoyang Song & Haiyue Yao, 2023. "Will patent family be dormant? Research on the identification and characteristics of sleeping beauty’s patent family," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(10), pages 5361-5387, October.
    12. Yang, Guancan & Lu, Guoxuan & Xu, Shuo & Chen, Liang & Wen, Yuxin, 2023. "Which type of dynamic indicators should be preferred to predict patent commercial potential?," Technological Forecasting and Social Change, Elsevier, vol. 193(C).
    13. Mohd Shadab Danish & Pritam Ranjan & Ruchi Sharma, 2021. "Identification of “Valuable” Technologies via Patent Statistics in India: An Analysis Based on Renewal Information," BASE University Working Papers 13/2021, BASE University, Bengaluru, India.
    14. Milani, Sahar & Neumann, Rebecca, 2022. "R&D, patents, and financing constraints of the top global innovative firms," Journal of Economic Behavior & Organization, Elsevier, vol. 196(C), pages 546-567.

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