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Exploring Promising Research Frontiers Based on Knowledge Maps in the Solar Cell Technology Field

Author

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  • Inchae Park

    (Department of Industrial & Systems Engineering, Dongguk University-Seoul, 30, Pildong-ro 1 gil, Jung-gu, Seoul 100-715, Korea)

  • Keeeun Lee

    (Department of Industrial & Systems Engineering, Dongguk University-Seoul, 30, Pildong-ro 1 gil, Jung-gu, Seoul 100-715, Korea)

  • Byungun Yoon

    (Department of Industrial & Systems Engineering, Dongguk University-Seoul, 30, Pildong-ro 1 gil, Jung-gu, Seoul 100-715, Korea)

Abstract

Given the challenging environmental issues in the energy sector, the importance of strategic research and development (R&D) planning has been emphasized to manage a turbulent business situation. This study aims to propose a methodology for exploring promising research frontiers in the energy sector. To this end, first, core documents are collected from scientific documents such as patents and academic papers. Second, the research frontiers are extracted by clustering the core documents based on the bibliographic relations. Third, a knowledge map is generated by mapping the relations between research frontiers. Finally, the promising research frontiers (RFs) are identified by conducting dynamic analyses and the contents of promising RFs are suggested. As an illustration of the method, the field of solar cell technology is chosen and analyzed As a result, the promising research frontiers from the patent knowledge map are related to development (D) themes and promising research frontiers from scientific paper knowledge map are related to the research (R) themes. The proposed method and results can be utilized by researchers, R&D policy makers, and administrations in practice.

Suggested Citation

  • Inchae Park & Keeeun Lee & Byungun Yoon, 2015. "Exploring Promising Research Frontiers Based on Knowledge Maps in the Solar Cell Technology Field," Sustainability, MDPI, vol. 7(10), pages 1-30, October.
  • Handle: RePEc:gam:jsusta:v:7:y:2015:i:10:p:13660-13689:d:56890
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    References listed on IDEAS

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    1. Bo Jarneving, 2005. "A comparison of two bibliometric methods for mapping of the research front," Scientometrics, Springer;Akadémiai Kiadó, vol. 65(2), pages 245-263, November.
    2. Peters, H. P. F. & van Raan, A. F. J., 1993. "Co-word-based science maps of chemical engineering. Part II: Representations by combined clustering and multidimensional scaling," Research Policy, Elsevier, vol. 22(1), pages 47-71, February.
    3. Kevin W. Boyack & Richard Klavans, 2010. "Co‐citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    4. Altwies, Joy E. & Nemet, Gregory F., 2013. "Innovation in the U.S. building sector: An assessment of patent citations in building energy control technology," Energy Policy, Elsevier, vol. 52(C), pages 819-831.
    5. Diana Lucio‐Arias & Loet Leydesdorff, 2009. "An indicator of research front activity: Measuring intellectual organization as uncertainty reduction in document sets," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(12), pages 2488-2498, December.
    6. Kevin W. Boyack & Richard Klavans & Katy Börner, 2005. "Mapping the backbone of science," Scientometrics, Springer;Akadémiai Kiadó, vol. 64(3), pages 351-374, August.
    7. C.M. Calero Medina & T.N. van Leeuwen, 2012. "Seed journal citation network maps: A method based on network theory," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 63(6), pages 1226-1234, June.
    8. Kevin W. Boyack & Richard Klavans, 2010. "Co-citation analysis, bibliographic coupling, and direct citation: Which citation approach represents the research front most accurately?," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 61(12), pages 2389-2404, December.
    9. Jarneving, Bo, 2007. "Bibliographic coupling and its application to research-front and other core documents," Journal of Informetrics, Elsevier, vol. 1(4), pages 287-307.
    10. William W. Hood & Concepción S. Wilson, 2001. "The Literature of Bibliometrics, Scientometrics, and Informetrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 52(2), pages 291-314, October.
    11. Byungun Yoon & Sungjoo Lee & Gwanghee Lee, 2010. "Development and application of a keyword-based knowledge map for effective R&D planning," Scientometrics, Springer;Akadémiai Kiadó, vol. 85(3), pages 803-820, December.
    12. Lee, Woo Jin & Sohn, So Young, 2014. "Patent analysis to identify shale gas development in China and the United States," Energy Policy, Elsevier, vol. 74(C), pages 111-115.
    13. Wong, Chan-Yuan & Fatimah Mohamad, Zeeda & Keng, Zi-Xiang & Ariff Azizan, Suzana, 2014. "Examining the patterns of innovation in low carbon energy science and technology: Publications and patents of Asian emerging economies," Energy Policy, Elsevier, vol. 73(C), pages 789-802.
    14. Peters, H. P. F. & van Raan, A. F. J., 1993. "Co-word-based science maps of chemical engineering. Part I: Representations by direct multidimensional scaling," Research Policy, Elsevier, vol. 22(1), pages 23-45, February.
    15. Lee, Kyungpyo & Lee, Sungjoo, 2013. "Patterns of technological innovation and evolution in the energy sector: A patent-based approach," Energy Policy, Elsevier, vol. 59(C), pages 415-432.
    16. C.M. Calero Medina & T.N. Leeuwen, 2012. "Seed journal citation network maps: A method based on network theory," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(6), pages 1226-1234, June.
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    2. Xiaodong Yuan & Weiling Song, 2022. "Evaluating technology innovation capabilities of companies based on entropy- TOPSIS: the case of solar cell companies," Information Technology and Management, Springer, vol. 23(2), pages 65-76, June.
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    5. BangRae Lee & DongKyu Won & Jun-Hwan Park & LeeNam Kwon & Young-Ho Moon & Han-Joon Kim, 2016. "Patent-Enhancing Strategies by Industry in Korea Using a Data Envelopment Analysis," Sustainability, MDPI, vol. 8(9), pages 1-17, September.

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