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The determinants of patent citations: an empirical analysis of French and British patents in the US

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  • C. Gay
  • C. Le Bas
  • P. Patel
  • K. Touach

Abstract

The aim of the article is to investigate the determinants of patent citations which are reasonably good proxy for the technological value of an invention. The analysis is based on patents granted by the US Patent and Trademark Office (USPTO) to French and British inventors from 1969 to 1998. Our aim is to explain the frequency of citations rather than why a patent may or may not be cited. This is achieved by examining some of the characteristics associated with highly cited patents. The models we estimate predict that a patent that is frequently cited, and therefore a technologically important patent, is a patent that it is quickly cited and more frequently cited by patent from other technological fields. When the patent is cited by patents from other technological fields this tends to indicate that the cited patent is broader.

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  • C. Gay & C. Le Bas & P. Patel & K. Touach, 2005. "The determinants of patent citations: an empirical analysis of French and British patents in the US," Economics of Innovation and New Technology, Taylor & Francis Journals, vol. 14(5), pages 339-350.
    • Handle: RePEc:taf:ecinnt:v:14:y:2005:i:5:p:339-350
    DOI: 10.1080/1040859042000307329
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    References listed on IDEAS

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    1. Yong-Gil Lee & Jeong-Dong Lee & Yong-Il Song & Se-Jun Lee, 2007. "An in-depth empirical analysis of patent citation counts using zero-inflated count data model: The case of KIST," Scientometrics, Springer;Akadémiai Kiadó, vol. 70(1), pages 27-39, January.
    2. Beneito, Pilar, 2006. "The innovative performance of in-house and contracted R&D in terms of patents and utility models," Research Policy, Elsevier, vol. 35(4), pages 502-517, May.
    3. Manuel Acosta & Daniel Coronado & Esther Ferrándiz & Manuel Jiménez, 2022. "Effects of knowledge spillovers between competitors on patent quality: what patent citations reveal about a global duopoly," The Journal of Technology Transfer, Springer, vol. 47(5), pages 1451-1487, October.
    4. Acosta, Manuel & Coronado, Daniel & Martínez, M. Ángeles, 2012. "Spatial differences in the quality of university patenting: Do regions matter?," Research Policy, Elsevier, vol. 41(4), pages 692-703.
    5. Grimaldi, Michele & Cricelli, Livio & Di Giovanni, Martina & Rogo, Francesco, 2015. "The patent portfolio value analysis: A new framework to leverage patent information for strategic technology planning," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 286-302.
    6. Kim, Dong-hyu & Lee, Heejin & Kwak, Jooyoung, 2017. "Standards as a driving force that influences emerging technological trajectories in the converging world of the Internet and things: An investigation of the M2M/IoT patent network," Research Policy, Elsevier, vol. 46(7), pages 1234-1254.
    7. Manuel Acosta & Daniel Coronado & Ana Fernández, 2009. "Exploring the quality of environmental technology in Europe: evidence from patent citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 80(1), pages 131-152, July.
    8. 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).
    9. Altuntas, Serkan & Dereli, Turkay & Kusiak, Andrew, 2015. "Analysis of patent documents with weighted association rules," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 249-262.
    10. 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).
    11. Yong-Gil Lee, 2009. "What affects a patent’s value? An analysis of variables that affect technological, direct economic, and indirect economic value: An exploratory conceptual approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 79(3), pages 623-633, June.
    12. Fernández, Ana María & Ferrándiz, Esther & Medina, Jennifer, 2022. "The diffusion of energy technologies. Evidence from renewable, fossil, and nuclear energy patents," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
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    14. Jungpyo Lee & So Young Sohn, 2017. "What makes the first forward citation of a patent occur earlier?," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 279-298, October.
    15. Chihmao Hsieh, 2011. "Explicitly searching for useful inventions: dynamic relatedness and the costs of connecting versus synthesizing," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 381-404, February.

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