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Indirect patent citations

Author

Listed:
  • Gamal Atallah

    (Department of Economics
    CIRANO)

  • Gabriel Rodríguez

    (Department of Economics)

Abstract

Patent citations are extensively used as a measure of patent quality. However, counting citations does not account for the fact that citations come from patents of different qualities, and that citations are of variable qualities. We develop a citation index which takes into account the cumulative quality of the citing patents. We apply this index to the 2,139,314 utility patents granted in the U.S. between 1975 and 1999. We study the properties of this index by year and by technological category, and analyse the links between patents.

Suggested Citation

  • Gamal Atallah & Gabriel Rodríguez, 2006. "Indirect patent citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 67(3), pages 437-465, June.
    • Handle: RePEc:spr:scient:v:67:y:2006:i:3:d:10.1556_scient.67.2006.3.7
    DOI: 10.1556/Scient.67.2006.3.7
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    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Guan-Can Yang & Gang Li & Chun-Ya Li & Yun-Hua Zhao & Jing Zhang & Tong Liu & Dar-Zen Chen & Mu-Hsuan Huang, 2015. "Using the comprehensive patent citation network (CPC) to evaluate patent value," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1319-1346, December.
    2. Chao Min & Qingyu Chen & Erjia Yan & Yi Bu & Jianjun Sun, 2021. "Citation cascade and the evolution of topic relevance," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 72(1), pages 110-127, January.
    3. Andrew Rodriguez & Byunghoon Kim & Mehmet Turkoz & Jae-Min Lee & Byoung-Youl Coh & Myong K. Jeong, 2015. "New multi-stage similarity measure for calculation of pairwise patent similarity in a patent citation network," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(2), pages 565-581, May.
    4. Chandra, Praveena & Dong, Andy, 2018. "The relation between knowledge accumulation and technical value in interdisciplinary technologies," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 235-244.
    5. George Messinis, 2011. "Triadic citations, country biases and patent value: the case of pharmaceuticals," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(3), pages 813-833, December.
    6. Wang, Xiaoli & Daim, Tugrul & Huang, Lucheng & Li, Zhiqiang & Shaikh, Ruqia & Kassi, Diby Francois, 2022. "Monitoring the development trend and competition status of high technologies using patent analysis and bibliographic coupling: The case of electronic design automation technology," Technology in Society, Elsevier, vol. 71(C).
    7. Lyu, Haihua & Bu, Yi & Zhao, Zhenyue & Zhang, Jiarong & Li, Jiang, 2022. "Citation bias in measuring knowledge flow: Evidence from the web of science at the discipline level," Journal of Informetrics, Elsevier, vol. 16(4).
    8. Hu, Xiaojun & Rousseau, Ronald, 2016. "Scientific influence is not always visible: The phenomenon of under-cited influential publications," Journal of Informetrics, Elsevier, vol. 10(4), pages 1079-1091.
    9. Eleni Fragkiadaki & Georgios Evangelidis, 2014. "Review of the indirect citations paradigm: theory and practice of the assessment of papers, authors and journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 99(2), pages 261-288, May.
    10. Burak Dindaroğlu, 2018. "Determinants of patent quality in U.S. manufacturing: technological diversity, appropriability, and firm size," The Journal of Technology Transfer, Springer, vol. 43(4), pages 1083-1106, August.
    11. Andreas Reinstaller & Peter Reschenhofer, 2017. "Using PageRank in the analysis of technological progress through patents: an illustration for biotechnological inventions," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(3), pages 1407-1438, December.
    12. Hu, Xiaojun & Rousseau, Ronald & Chen, Jin, 2011. "On the definition of forward and backward citation generations," Journal of Informetrics, Elsevier, vol. 5(1), pages 27-36.
    13. Eleni Fragkiadaki & Georgios Evangelidis, 2016. "Three novel indirect indicators for the assessment of papers and authors based on generations of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(2), pages 657-694, February.
    14. Jiang, Hongxun & Fan, Shaokun & Zhang, Nan & Zhu, Bin, 2023. "Deep learning for predicting patent application outcome: The fusion of text and network embeddings," Journal of Informetrics, Elsevier, vol. 17(2).
    15. Jiang, Xiaorui & Zhuge, Hai, 2019. "Forward search path count as an alternative indirect citation impact indicator," Journal of Informetrics, Elsevier, vol. 13(4).
    16. repec:izm:wpaper:1207 is not listed on IDEAS
    17. Hsi-Yin Yeh & Yi-Shan Sung & Hsiao-Wen Yang & Wan-Chu Tsai & Dar-Zen Chen, 2013. "The bibliographic coupling approach to filter the cited and uncited patent citations: a case of electric vehicle technology," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(1), pages 75-93, January.
    18. Manuel Krauskopf & Erwin Krauskopf & Bernardita Méndez, 2007. "Low awareness of the link between science and innovation affects public policies in developing countries: The Chilean case," Scientometrics, Springer;Akadémiai Kiadó, vol. 72(1), pages 93-103, July.
    19. 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.
    20. Chen, Dar-Zen & Huang, Mu-Hsuan & Hsieh, Hui-Chen & Lin, Chang-Pin, 2011. "Identifying missing relevant patent citation links by using bibliographic coupling in LED illuminating technology," Journal of Informetrics, Elsevier, vol. 5(3), pages 400-412.

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    More about this item

    JEL classification:

    • C25 - Mathematical and Quantitative Methods - - Single Equation Models; Single Variables - - - Discrete Regression and Qualitative Choice Models; Discrete Regressors; Proportions; Probabilities
    • O31 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Innovation and Invention: Processes and Incentives
    • O34 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Intellectual Property and Intellectual Capital

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