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Citation lag analysis in supply chain research

Author

Listed:
  • Hiroko Nakamura

    (The University of Tokyo)

  • Shinji Suzuki

    (The University of Tokyo)

  • Tomobe Hironori

    (The University of Tokyo)

  • Yuya Kajikawa

    (The University of Tokyo)

  • Ichiro Sakata

    (The University of Tokyo)

Abstract

Interdisciplinary research is expected to contribute to industrial and economic development. However, due to expansion of knowledge and the fragmentation of research fields, knowledge dissemination among different research fields is rare and we need a methodology for measuring such dissemination and promoting it. In this paper, we introduce a citation lag analysis of inter- and intra-clusters extracted by citation network analysis as a new indicator to represent the speed of knowledge diffusion in subfields of a research field. A case study was performed within supply chain research to investigate knowledge integration among its subfields. Based on the analysis, we discuss knowledge structure and reciprocal influence of subfields in supply chain research. This study contributes to offering a new approach for analyzing and understanding the development of boundary spanning research.

Suggested Citation

  • Hiroko Nakamura & Shinji Suzuki & Tomobe Hironori & Yuya Kajikawa & Ichiro Sakata, 2011. "Citation lag analysis in supply chain research," Scientometrics, Springer;Akadémiai Kiadó, vol. 87(2), pages 221-232, May.
  • Handle: RePEc:spr:scient:v:87:y:2011:i:2:d:10.1007_s11192-011-0341-x
    DOI: 10.1007/s11192-011-0341-x
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    References listed on IDEAS

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    Cited by:

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    2. Joao Victor Rojas Luiz & Daniel Jugend & Charbel José Chiappeta Jabbour & Octaviano Rojas Luiz & Fernando Bernardi Souza, 2016. "Ecodesign field of research throughout the world: mapping the territory by using an evolutionary lens," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(1), pages 241-259, October.
    3. Shino Iwami & Junichiro Mori & Ichiro Sakata & Yuya Kajikawa, 2014. "Detection method of emerging leading papers using time transition," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1515-1533, November.
    4. Hiroko Nakamura & Shinji Suzuki & Yuya Kajikawa & Masataka Osawa, 2015. "The effect of patent family information in patent citation network analysis: a comparative case study in the drivetrain domain," Scientometrics, Springer;Akadémiai Kiadó, vol. 104(2), pages 437-452, August.
    5. Wen-Yau Cathy Lin, 2021. "Effects of open access and articles-in-press mechanisms on publishing lag and first-citation speed: a case on energy and fuels journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(6), pages 4841-4869, June.
    6. Nakamura, Hiroko & Suzuki, Shinji & Sakata, Ichiro & Kajikawa, Yuya, 2015. "Knowledge combination modeling: The measurement of knowledge similarity between different technological domains," Technological Forecasting and Social Change, Elsevier, vol. 94(C), pages 187-201.
    7. Song, Haoyang & Hou, Jianhua & Zhang, Yang, 2023. "The measurements and determinants of patent technological value: Lifetime, strength, breadth, and dispersion from the technology diffusion perspective," Journal of Informetrics, Elsevier, vol. 17(1).
    8. Hou, Jianhua & Tang, Shiqi & Zhang, Yang & Song, Haoyang, 2023. "Does prior knowledge affect patent technology diffusion? A semantic-based patent citation contribution analysis," Journal of Informetrics, Elsevier, vol. 17(2).

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