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Can technology life-cycles be indicated by diversity in patent classifications? The crucial role of variety

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  • Loet Leydesdorff

    (University of Amsterdam)

Abstract

In a previous study of patent classifications in nine material technologies for photovoltaic cells, Leydesdorff et al. (Scientometrics 102(1):629–651, 2015) reported cyclical patterns in the longitudinal development of Rao–Stirling diversity. We suggested that these cyclical patterns can be used to indicate technological life-cycles. Upon decomposition, however, the cycles are exclusively due to increases and decreases in the variety of the classifications, and not to disparity or technological distance, measured as (1 − cosine). A single frequency component can accordingly be shown in the periodogram. Furthermore, the cyclical patterns are associated with the numbers of inventors in the respective technologies. Sometimes increased variety leads to a boost in the number of inventors, but in early phases—when the technology is still under construction—it can also be the other way round. Since the development of the cycles thus seems independent of technological distances among the patents, the visualization in terms of patent maps, can be considered as addressing an analytically different set of research questions.

Suggested Citation

  • Loet Leydesdorff, 2015. "Can technology life-cycles be indicated by diversity in patent classifications? The crucial role of variety," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1441-1451, December.
  • Handle: RePEc:spr:scient:v:105:y:2015:i:3:d:10.1007_s11192-015-1639-x
    DOI: 10.1007/s11192-015-1639-x
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    References listed on IDEAS

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    1. Loet Leydesdorff & Duncan Kushnir & Ismael Rafols, 2014. "Interactive overlay maps for US patent (USPTO) data based on International Patent Classification (IPC)," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(3), pages 1583-1599, March.
    2. Andy Stirling, 2007. "A General Framework for Analysing Diversity in Science, Technology and Society," SPRU Working Paper Series 156, SPRU - Science Policy Research Unit, University of Sussex Business School.
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    4. Loet Leydesdorff & Ismael Rafols & Chaomei Chen, 2013. "Interactive overlays of journals and the measurement of interdisciplinarity on the basis of aggregated journal–journal citations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(12), pages 2573-2586, December.
    5. Ismael Rafols & Martin Meyer, 2010. "Diversity and network coherence as indicators of interdisciplinarity: case studies in bionanoscience," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(2), pages 263-287, February.
    6. Nees Jan Eck & Ludo Waltman, 2010. "Software survey: VOSviewer, a computer program for bibliometric mapping," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(2), pages 523-538, August.
    7. Loet Leydesdorff & Floortje Alkemade & Gaston Heimeriks & Rinke Hoekstra, 2015. "Patents as instruments for exploring innovation dynamics: geographic and technological perspectives on “photovoltaic cells”," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 629-651, January.
    8. Jaffe, Adam B, 1986. "Technological Opportunity and Spillovers of R&D: Evidence from Firms' Patents, Profits, and Market Value," American Economic Review, American Economic Association, vol. 76(5), pages 984-1001, December.
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    11. Rafols, Ismael & Leydesdorff, Loet & O’Hare, Alice & Nightingale, Paul & Stirling, Andy, 2012. "How journal rankings can suppress interdisciplinary research: A comparison between Innovation Studies and Business & Management," Research Policy, Elsevier, vol. 41(7), pages 1262-1282.
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    Cited by:

    1. Loet Leydesdorff & Caroline S. Wagner & Lutz Bornmann, 2018. "Betweenness and diversity in journal citation networks as measures of interdisciplinarity—A tribute to Eugene Garfield," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(2), pages 567-592, February.
    2. Ronald Rousseau, 2018. "The repeat rate: from Hirschman to Stirling," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 645-653, July.
    3. We Shim & Oh-jin Kwon & Yeong-ho Moon & Keun-hwan Kim, 2016. "Understanding the Dynamic Convergence Phenomenon from the Perspective of Diversity and Persistence: A Cross-Sector Comparative Analysis between the United States and South Korea," PLOS ONE, Public Library of Science, vol. 11(7), pages 1-29, July.
    4. Zhang, Lin & Sun, Mengting & Peng, Yujie & Zhao, Wenjing & Chen, Lixin & Huang, Ying, 2022. "How public investment fuels innovation: Clues from government-subsidized USPTO patents," Journal of Informetrics, Elsevier, vol. 16(3).
    5. Chang, Shu-Hao & Fan, Chin-Yuan, 2016. "Identification of the technology life cycle of telematics: A patent-based analytical perspective," Technological Forecasting and Social Change, Elsevier, vol. 105(C), pages 1-10.
    6. Zhao Qu & Shanshan Zhang & Chunbo Zhang, 2017. "Patent research in the field of library and information science: Less useful or difficult to explore?," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 205-217, April.
    7. Moro, Alberto & Boelman, Elisa & Joanny, Geraldine & Garcia, Juan Lopez, 2018. "A bibliometric-based technique to identify emerging photovoltaic technologies in a comparative assessment with expert review," Renewable Energy, Elsevier, vol. 123(C), pages 407-416.
    8. Deyu Li & Floor Alkemade & Koen Frenken & Gaston Heimeriks, 2023. "Catching up in clean energy technologies: a patent analysis," The Journal of Technology Transfer, Springer, vol. 48(2), pages 693-715, April.

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