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Multiple regression analysis of a patent’s citation frequency and quantitative characteristics: the case of Japanese patents

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  • Fuyuki Yoshikane

    (Graduate School of Library, Information and Media Studies, University of Tsukuba)

Abstract

Although many studies have been conducted to clarify the factors that affect the citation frequency of “academic papers,” there are few studies where the citation frequency of “patents” has been predicted on the basis of statistical analysis, such as regression analysis. Assuming that a patent based on a variety of technological bases tends to be an important patent that is cited more often, this study examines the influence of the number of cited patents’ classifications and compares it with other factors, such as the numbers of inventors, classifications, pages, and claims. Multiple linear, logistic, and zero-inflated negative binomial regression analyses using these factors are performed. Significant positive correlations between the number of classifications of cited patents and the citation frequency are observed for all the models. Moreover, the multiple regression analyses demonstrate that the number of classifications of cited patents contributes more to the regression than do other factors. This implies that, if confounding between factors is taken into account, it is the diversity of classifications assigned to backward citations that more largely influences the number of forward citations.

Suggested Citation

  • Fuyuki Yoshikane, 2013. "Multiple regression analysis of a patent’s citation frequency and quantitative characteristics: the case of Japanese patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 365-379, July.
    • Handle: RePEc:spr:scient:v:96:y:2013:i:1:d:10.1007_s11192-013-0953-4
    DOI: 10.1007/s11192-013-0953-4
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    References listed on IDEAS

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    1. H. P. F. Peters & A. F. J. van Raan, 1994. "On determinants of citation scores: A case study in chemical engineering," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 45(1), pages 39-49, January.
    2. Jeremy Foltz & Bradford Barham & Kwansoo Kim, 2000. "Universities and agricultural biotechnology patent production," Agribusiness, John Wiley & Sons, Ltd., vol. 16(1), pages 82-95.
    3. Fuyuki Yoshikane & Yutaka Suzuki & Keita Tsuji, 2012. "Analysis of the relationship between citation frequency of patents and diversity of their backward citations for Japanese patents," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 721-733, September.
    4. Ronald N. Kostoff, 2007. "The difference between highly and poorly cited medical articles in the journal Lancet," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(3), pages 513-520, September.
    5. Dietmar Harhoff & Francis Narin & F. M. Scherer & Katrin Vopel, 1999. "Citation Frequency And The Value Of Patented Inventions," The Review of Economics and Statistics, MIT Press, vol. 81(3), pages 511-515, August.
    6. 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.
    7. Lutz Bornmann & Hans‐Dieter Daniel, 2007. "Multiple publication on a single research study: Does it pay? The influence of number of research articles on total citation counts in biomedicine," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(8), pages 1100-1107, June.
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    Cited by:

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