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Constructing a patent citation map using bibliographic coupling: A study of Taiwan's high-tech companies

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  • Mu-Hsuan Huang

    (National Taiwan University)

  • Li-Yun Chiang

    (National Taiwan University)

  • Dar-Zen Chen

    (National Taiwan University)

Abstract

This paper uses bibliographic coupling analysis to plot out a patent citation map. It explores the current research and development in the high-tech electronic companies in Taiwan, and the relationship between companies and industries. Fifty-eight high-tech electronic companies under this study, between 1998 and 2000, obtained 4162 patents from U.S., and cited 24,852 patents during these years. Through the data from bibliographic coupling analysis, the paper categorizes these companies into 6 major groups: semiconductor, peripheral, scanners, notebook / monitor, system, IC design / packaging. This research also uses multidimensional scaling to plot out a patent citation map, graphically displaying the association among the groups. The result shows a higher similarity among companies in semiconductor sector, whereas the distinction between industries grows more and more ambivalent, even overlapping in some cases.

Suggested Citation

  • Mu-Hsuan Huang & Li-Yun Chiang & Dar-Zen Chen, 2003. "Constructing a patent citation map using bibliographic coupling: A study of Taiwan's high-tech companies," Scientometrics, Springer;Akadémiai Kiadó, vol. 58(3), pages 489-506, November.
    • Handle: RePEc:spr:scient:v:58:y:2003:i:3:d:10.1023_b:scie.0000006876.29052.bf
    DOI: 10.1023/B:SCIE.0000006876.29052.bf
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    References listed on IDEAS

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    1. M. M. Kessler, 1963. "Bibliographic coupling between scientific papers," American Documentation, Wiley Blackwell, vol. 14(1), pages 10-25, January.
    2. Karki, M. M. S., 1997. "Patent citation analysis: A policy analysis tool," World Patent Information, Elsevier, vol. 19(4), pages 269-272, December.
    3. R. J. W. Tussen & R. K. Buter & Th. N. van Leeuwen, 2000. "Technological Relevance of Science: An Assessment of Citation Linkages between Patents and Research Papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 389-412, February.
    4. Martin Meyer, 2000. "Patent Citations in a Novel Field of Technology — What Can They Tell about Interactions between Emerging Communities of Science and Technology?," Scientometrics, Springer;Akadémiai Kiadó, vol. 48(2), pages 151-178, September.
    5. Bart Verspagen, 2000. "The Role of Large Multinationals in the Dutch Technology Infrastructure. A Patent Citation Analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 47(2), pages 427-448, February.
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    Cited by:

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    2. Hain, Daniel S. & Jurowetzki, Roman & Buchmann, Tobias & Wolf, Patrick, 2022. "A text-embedding-based approach to measuring patent-to-patent technological similarity," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    3. WANG, La-yin & ZHAO, Dong, 2021. "Cross-domain function analysis and trend study in Chinese construction industry based on patent semantic analysis," Technological Forecasting and Social Change, Elsevier, vol. 162(C).
    4. 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.
    5. Wenyuan Liu & Andrea Nanetti & Siew Ann Cheong, 2017. "Knowledge evolution in physics research: An analysis of bibliographic coupling networks," PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
    6. Shen, Yung-Chi & Wang, Ming-Yeu & Yang, Ya-Chu, 2020. "Discovering the potential opportunities of scientific advancement and technological innovation: A case study of smart health monitoring technology," Technological Forecasting and Social Change, Elsevier, vol. 160(C).

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