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Analysis of technological innovation based on citation information

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  • Gabjin Oh

    (Chosun University)

  • Ho-Yong Kim

    (Chosun University)

  • Ayoung Park

    (Chosun University)

Abstract

The paper discusses the dynamic properties of the patent network. Technological innovation occurs frequently, and predicting where it will happen is difficult because an economic system can adapt to changing technology. We construct a patent network based on the cited relations between patents and analyze the properties of the patent network from January 1976 to December 2005 by using USPTO patent data. We find that technology trends, which are calculated by our measures, are similar with historical trends of technology, showing that our measures would be useful to predict future technology relations. Also, we find that the change of similarity between patents shows meaningful results in terms of technological innovation.

Suggested Citation

  • Gabjin Oh & Ho-Yong Kim & Ayoung Park, 2017. "Analysis of technological innovation based on citation information," Quality & Quantity: International Journal of Methodology, Springer, vol. 51(3), pages 1065-1091, May.
    • Handle: RePEc:spr:qualqt:v:51:y:2017:i:3:d:10.1007_s11135-016-0460-9
    DOI: 10.1007/s11135-016-0460-9
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    References listed on IDEAS

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    Citations

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    Cited by:

    1. Bernard Sinclair-Desgagné, 2022. "Measuring innovation and innovativeness: a data-mining approach," Quality & Quantity: International Journal of Methodology, Springer, vol. 56(4), pages 2415-2434, August.
    2. Chengkai Zhang & Yu Li & Lili Yang & Zheng Wang, 2023. "Does the Development of Digital Inclusive Finance Promote the Construction of Digital Villages?—An Empirical Study Based on the Chinese Experience," Agriculture, MDPI, vol. 13(8), pages 1-23, August.
    3. Concepta McManus & Abilio Afonso Baeta Neves & Alvaro Toubes Prata, 2021. "Scientific publications from non-academic sectors and their impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(11), pages 8887-8911, November.
    4. Lin Zhu & Donghua Zhu & Xuefeng Wang & Scott W. Cunningham & Zhinan Wang, 2019. "An integrated solution for detecting rising technology stars in co-inventor networks," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 137-172, October.

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