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Early identification of intellectual structure based on co-word analysis from research grants

Author

Listed:
  • Xiuwen Chen

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Jianping Li

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Xiaolei Sun

    (Chinese Academy of Sciences
    University of Chinese Academy of Sciences)

  • Dengsheng Wu

    (Chinese Academy of Sciences)

Abstract

From the initial idea, writing, submitting, and reviewing to the online presentation of a research paper takes a long time. The identified intellectual structure of a research paper may have a certain time lag. In view of this problem, scholars have suggested that research grants may be an alternative way to identify intellectual structure as early as possible. However, these comments are mentioned qualitatively. Few researchers have verified the research grant by early identification of the intellectual structure of a field with a quantitative method. Therefore, this paper proposes a new method framework to confirm the lead-lag relationship quantitatively between intellectual structures identified by the research grant and the research paper. In empirical analysis, Operations Research and Management Science in China was selected as a specific research area. The results show that the intellectual structure identified by the research grant leads the intellectual structure of a research paper by approximately 1–2 years. These discoveries, to some extent, confirm the early identification of intellectual structure based on the research grant. In addition, the results also indicate that there is high similarity between intellectual structure identified by the research grant and that in the research paper in the previous year.

Suggested Citation

  • Xiuwen Chen & Jianping Li & Xiaolei Sun & Dengsheng Wu, 2019. "Early identification of intellectual structure based on co-word analysis from research grants," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 349-369, October.
  • Handle: RePEc:spr:scient:v:121:y:2019:i:1:d:10.1007_s11192-019-03187-9
    DOI: 10.1007/s11192-019-03187-9
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