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What affects a patent’s value? An analysis of variables that affect technological, direct economic, and indirect economic value: An exploratory conceptual approach

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  • Yong-Gil Lee

    (Korea Institute of Science and Technology
    Korea University of Science and Technology)

Abstract

The paper investigates three aspects of patent value - technological value, direct economic value, and indirect economic value. The paper suggests that we measure the technological value of a patent by looking at its number of citations, direct economic value by looking at its licensing and income from royalties, and indirect economic value by looking at its life (i.e., duration). For the research, the author’s two previous studies are deeply explored. It is found that these three aspects of patent value are positively correlated with one another. In addition, their domains overlap and interrelate. Research collaboration is the one variable found to have a significant effect on all three aspects. The field effect of electronics positively affects technological and indirect economic value, whereas research team size negatively affects technological and indirect economic value.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:scient:v:79:y:2009:i:3:d:10.1007_s11192-007-2020-5
    DOI: 10.1007/s11192-007-2020-5
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    References listed on IDEAS

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    1. Jean O. Lanjouw & Ariel Pakes & Jonathan Putnam, 1998. "How to Count Patents and Value Intellectual Property: The Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Wiley Blackwell, vol. 46(4), pages 405-432, December.
    2. Yong-Gil Lee, 2008. "Patent licensability and life: A study of U.S. patents registered by South Korean public research institutes," Scientometrics, Springer;Akadémiai Kiadó, vol. 75(3), pages 463-471, June.
    3. 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.
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    6. Lanjouw, Jean O & Pakes, Ariel & Putnam, Jonathan, 1998. "How to Count Patents and Value Intellectual Property: The Uses of Patent Renewal and Application Data," Journal of Industrial Economics, Wiley Blackwell, vol. 46(4), pages 405-432, December.
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    Cited by:

    1. Yong-Gil Lee & Ji-Hoon Lee, 2010. "Different characteristics between auctioned and non-auctioned patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 135-148, January.
    2. Yong-Gil Lee, 2010. "Sectoral strategic differences of technological development between electronics and chemistry: a historical view from analyses of Korean-invented US patents during the period of 1989–1992," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(1), pages 83-92, January.
    3. Daim, Tugrul & Lai, Kuei Kuei & Yalcin, Haydar & Alsoubie, Fayez & Kumar, Vimal, 2020. "Forecasting technological positioning through technology knowledge redundancy: Patent citation analysis of IoT, cybersecurity, and Blockchain," Technological Forecasting and Social Change, Elsevier, vol. 161(C).
    4. Fuyuki Yoshikane & Takafumi Suzuki, 2014. "Diversity of fields in patent citations: synchronic and diachronic changes," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1879-1897, March.
    5. Weresa Marzenna Anna, 2019. "Technological competitiveness of the EU member states in the era of the fourth industrial revolution," Economics and Business Review, Sciendo, vol. 5(3), pages 50-71, September.
    6. Lee, Pei-Chun & Su, Hsin-Ning, 2014. "How to forecast cross-border patent infringement? — The case of U.S. international trade," Technological Forecasting and Social Change, Elsevier, vol. 86(C), pages 125-131.
    7. Yi Zhang & Yue Qian & Ying Huang & Ying Guo & Guangquan Zhang & Jie Lu, 2017. "An entropy-based indicator system for measuring the potential of patents in technological innovation: rejecting moderation," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1925-1946, June.
    8. Yutao Sun & Chen Zhang & Robert A. W. Kok, 2020. "The role of research outcome quality in the relationship between university research collaboration and technology transfer: empirical results from China," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1003-1026, February.
    9. 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).
    10. Leila Tahmooresnejad & Catherine Beaudry, 2019. "Capturing the economic value of triadic patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 127-157, January.
    11. Bo Kyeong Lee & So Young Sohn, 2017. "Exploring the effect of dual use on the value of military technology patents based on the renewal decision," Scientometrics, Springer;Akadémiai Kiadó, vol. 112(3), pages 1203-1227, September.
    12. Torben Schubert, 2011. "Assessing the value of patent portfolios: an international country comparison," Scientometrics, Springer;Akadémiai Kiadó, vol. 88(3), pages 787-804, September.
    13. José Luis Ortega, 2011. "Collaboration patterns in patent networks and their relationship with the transfer of technology: the case study of the CSIC patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(3), pages 657-666, June.
    14. Jong-Hyun Kim & Yong-Gil Lee, 2024. "Investigating Technological Advancement Strategies for the Innovation Impact of Alternative Energy Patents," Sustainability, MDPI, vol. 16(2), pages 1-25, January.
    15. Zafer Sonmez, 2018. "Interregional inventor collaboration and the commercial value of patented inventions: evidence from the US biotechnology industry," The Annals of Regional Science, Springer;Western Regional Science Association, vol. 61(2), pages 399-438, September.
    16. 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).
    17. Hsin-Ning Su & Carey Ming-Li Chen & Pei-Chun Lee, 2012. "Patent litigation precaution method: analyzing characteristics of US litigated and non-litigated patents from 1976 to 2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(1), pages 181-195, July.
    18. 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.
    19. Guifeng Liu, 2013. "Visualization of patents and papers in terahertz technology: a comparative study," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1037-1056, March.

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