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Exploring knowledge diffusion among nations: a study of core technologies in fuel cells

Author

Listed:
  • Mei Hsiu-Ching Ho

    (National Taiwan University of Science and Technology)

  • Vincent H. Lin

    (National Taiwan University of Science and Technology)

  • John S. Liu

    (National Taiwan University of Science and Technology)

Abstract

Technological trajectory is a representation of the development of technology. Based on the analysis of the trajectories of prominent technologies, we can explore the phenomena of technology evolution and knowledge diffusion. In this study, we focus on explaining knowledge diffusion in the core technology used in fuel cells, i.e. the development of 5-layer membrane electrode assembly (MEA) technologies. Through an investigation of path analysis, this study explores how the knowledge of this technology has evolved and diffused across different locations. The empirical analysis also explains how certain technological knowledge plays a critical role in main path. In this study, patent data of 5-layer MEA technologies for fuel cells is collected from the US Patent Office, for a total of 1,356 patents, followed by constructing a patent citation network based on citation relationships, recognising prominent patents with many citations through path analysis. Using the local main path analysis and global key-route method, we identify three stages of technological development, including an improvement of the proton exchange membrane (PEM) and catalyst synthesis. Additionally, we use regression analysis to demonstrate that patents with specific characteristics play a vital role in the process of knowledge diffusion. Patents from Japan and South Korea are relatively more important than patents from other countries. The brokerage characteristics of a patent (e.g., coordinating domestically or liaising among three or more countries) also facilitate the diffusion of technological knowledge. However, the importance of these brokerages changes when we look at inventing time. Furthermore, the technological diversification of a patent exerted no substantial influence on its network position.

Suggested Citation

  • Mei Hsiu-Ching Ho & Vincent H. Lin & John S. Liu, 2014. "Exploring knowledge diffusion among nations: a study of core technologies in fuel cells," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(1), pages 149-171, July.
    • Handle: RePEc:spr:scient:v:100:y:2014:i:1:d:10.1007_s11192-014-1265-z
    DOI: 10.1007/s11192-014-1265-z
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    Cited by:

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    2. Lai, Kuei-Kuei & Bhatt, Priyanka C. & Kumar, Vimal & Chen, Hsueh-Chen & Chang, Yu-Hsin & Su, Fang-Pei, 2021. "Identifying the impact of patent family on the patent trajectory: A case of thin film solar cells technological trajectories," Journal of Informetrics, Elsevier, vol. 15(2).
    3. Roman Jurowetzki, 2015. "Unpacking Big Systems - Natural Language Processing meets Network Analysis. A Study of Smart Grid Development in Denmark," SPRU Working Paper Series 2015-15, SPRU - Science Policy Research Unit, University of Sussex Business School.
    4. Ying Huang & Donghua Zhu & Yue Qian & Yi Zhang & Alan L. Porter & Yuqin Liu & Ying Guo, 2017. "A hybrid method to trace technology evolution pathways: a case study of 3D printing," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(1), pages 185-204, April.
    5. Lai, Kuei-Kuei & Chen, Yu-Long & Kumar, Vimal & Daim, Tugrul & Verma, Pratima & Kao, Fang-Chen & Liu, Ruirong, 2023. "Mapping technological trajectories and exploring knowledge sources: A case study of E-payment technologies," Technological Forecasting and Social Change, Elsevier, vol. 186(PB).
    6. Chi, Yuxue & Tang, Xianyi & Liu, Yijun, 2022. "Exploring the “awakening effect” in knowledge diffusion: a case study of publications in the library and information science domain," Journal of Informetrics, Elsevier, vol. 16(4).
    7. Blandy Pamplona Solis & Julio César Cruz Argüello & Leopoldo Gómez Barba & Mayra Polett Gurrola & Zakaryaa Zarhri & Danna Lizeth TrejoArroyo, 2019. "Bibliometric Analysis of the Mass Transport in a Gas Diffusion Layer in PEM Fuel Cells," Sustainability, MDPI, vol. 11(23), pages 1-18, November.
    8. Xia Cao & Chuanyun Li & Jinqiu Li & Yunchang Li, 2022. "Modeling and simulation of knowledge creation and diffusion in an industry-university-research cooperative innovation network: a case study of China’s new energy vehicles," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 3935-3957, July.

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