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Trends and Typology of Emerging Antenna Propagation Technologies: Citation Network Analysis

Author

Listed:
  • Yasutomo Takano

    (Department of Innovation, Graduate School of Innovation Management, Tokyo Institute of Technology, Campus Innovation Center 805N, 3-3-6 Shibaura, Minato-ku, Tokyo 108-0023, Japan)

  • Yuya Kajikawa

    (Department of Innovation, Graduate School of Innovation Management, Tokyo Institute of Technology, Campus Innovation Center 805N, 3-3-6 Shibaura, Minato-ku, Tokyo 108-0023, Japan)

  • Makoto Ando

    (Department of Electrical and Electronic Engineering, Graduate School of Science and Engineering, Tokyo Institute of Technology, 2-12-1-S3-19 O-Okayama, Meguro-ku, Tokyo 152-8552, Japan)

Abstract

The detection of emerging technologies is vital for R&D managers and policymakers; hence, the bibliometric approach to analyzing papers and patents was developed. In this study, we proposed a new method, the research classification schema (RCS). We used citation network analysis to classify technologies into four categories: change-maker, breakthrough, matured, and incremental. Each technology is then plotted on the RCS based on its publication profile. A case study in the field of antennas was undertaken to evaluate the relevance and effectiveness of the RCS. The RCS method demonstrates the usefulness of the identification process of promising technologies, and therefore, the convenience of target designing research projects in universities and companies. We also discussed the effect of the resolution limit of clustering algorithms on the RCS to improve reliability.

Suggested Citation

  • Yasutomo Takano & Yuya Kajikawa & Makoto Ando, 2017. "Trends and Typology of Emerging Antenna Propagation Technologies: Citation Network Analysis," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 14(01), pages 1-19, February.
    • Handle: RePEc:wsi:ijitmx:v:14:y:2017:i:01:n:s0219877017400053
    DOI: 10.1142/S0219877017400053
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    References listed on IDEAS

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    1. Chen, Ssu-Han & Huang, Mu-Hsuan & Chen, Dar-Zen & Lin, Siou-Zih, 2012. "Detecting the temporal gaps of technology fronts: A case study of smart grid field," Technological Forecasting and Social Change, Elsevier, vol. 79(9), pages 1705-1719.
    2. Small, Henry & Boyack, Kevin W. & Klavans, Richard, 2014. "Identifying emerging topics in science and technology," Research Policy, Elsevier, vol. 43(8), pages 1450-1467.
    3. Henry Small, 1999. "Visualizing science by citation mapping," Journal of the American Society for Information Science, Association for Information Science & Technology, vol. 50(9), pages 799-813.
    4. Ho, Jonathan C. & Saw, Ewe-Chai & Lu, Louis Y.Y. & Liu, John S., 2014. "Technological barriers and research trends in fuel cell technologies: A citation network analysis," Technological Forecasting and Social Change, Elsevier, vol. 82(C), pages 66-79.
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    Cited by:

    1. Takano, Yasutomo & Kajikawa, Yuya, 2019. "Extracting commercialization opportunities of the Internet of Things: Measuring text similarity between papers and patents," Technological Forecasting and Social Change, Elsevier, vol. 138(C), pages 45-68.
    2. Cristian Mejia & Yuya Kajikawa, 2018. "Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 883-904, March.
    3. Milad Dehghani & Ki Joon Kim, 2019. "Past and Present Research on Wearable Technologies: Bibliometric and Cluster Analyses of Published Research from 2000 to 2016," International Journal of Innovation and Technology Management (IJITM), World Scientific Publishing Co. Pte. Ltd., vol. 16(01), pages 1-21, February.

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