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Using acknowledgement data to characterize funding organizations by the types of research sponsored: the case of robotics research

Author

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  • Cristian Mejia

    () (Tokyo Institute of Technology)

  • Yuya Kajikawa

    () (Tokyo Institute of Technology)

Abstract

Abstract Funded research has been linked to academic production and performance. While the presence of funding acknowledgements may serve as an indicator of quality to some extent, we still lack tools to evaluate whether funding agencies allocate resources to novel and innovative research rather than mature fields. We address this issue in the present study by using bibliometrics. In particular, we exploit the citation network properties of academic articles to classify specific research fields into four categories: change maker, breakthrough, incremental, and matured. We then use funding acknowledgement information to identify the sponsors involved in each research type to characterize funding agencies. We focus our analysis on the robotics field in order to reveal international trends of financial acknowledgements. We find that the incremental and matured research areas show the highest counts of funding acknowledgements. Moreover, although research funded by some agencies is mostly recognized as incremental-type research, those in other categories may perform better in terms of the number of citations. Additionally, we analyze the interest of selected funding agencies in granular subject categories. The characterization of funding agencies in this study may help policymakers and funding organizations assess or adjust their strategies, benchmark with other key players, and obtain an overview of local and global acknowledgement trends.

Suggested Citation

  • 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.
  • Handle: RePEc:spr:scient:v:114:y:2018:i:3:d:10.1007_s11192-017-2617-2
    DOI: 10.1007/s11192-017-2617-2
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    References listed on IDEAS

    as
    1. Yan, Erjia, 2014. "Research dynamics: Measuring the continuity and popularity of research topics," Journal of Informetrics, Elsevier, vol. 8(1), pages 98-110.
    2. Braun, Dietmar, 1998. "The role of funding agencies in the cognitive development of science," Research Policy, Elsevier, vol. 27(8), pages 807-821, December.
    3. Adèle Paul-Hus & Nadine Desrochers & Rodrigo Costas, 2016. "Characterization, description, and considerations for the use of funding acknowledgement data in Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(1), pages 167-182, July.
    4. Abdullah Gök & John Rigby & Philip Shapira, 2016. "The impact of research funding on scientific outputs: Evidence from six smaller European countries," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 67(3), pages 715-730, March.
    5. Grant Lewison & Valentina Markusova, 2010. "The evaluation of Russian cancer research," Research Evaluation, Oxford University Press, vol. 19(2), pages 129-144, June.
    6. Holly N. Wolcott & Matthew J. Fouch & Elizabeth R. Hsu & Leo G. DiJoseph & Catherine A. Bernaciak & James G. Corrigan & Duane E. Williams, 2016. "Modeling time-dependent and -independent indicators to facilitate identification of breakthrough research papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 807-817, May.
    7. repec:spr:scient:v:87:y:2011:i:3:d:10.1007_s11192-011-0362-5 is not listed on IDEAS
    8. repec:bla:jinfst:v:68:y:2017:i:4:p:999-1017 is not listed on IDEAS
    9. repec:bla:jinfst:v:68:y:2017:i:4:p:984-998 is not listed on IDEAS
    10. repec:spr:scient:v:91:y:2012:i:2:d:10.1007_s11192-011-0591-7 is not listed on IDEAS
    11. repec:spr:scient:v:84:y:2010:i:2:d:10.1007_s11192-010-0191-y is not listed on IDEAS
    12. Moritaka Hosotsubo & Ryuei Nishii, 2016. "Relation between awarding of Grants-in-aid for scientific research and characteristics of applicants in Japanese universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 1097-1116, November.
    13. repec:spr:scient:v:97:y:2013:i:2:d:10.1007_s11192-013-1008-6 is not listed on IDEAS
    14. repec:wsi:ijitmx:v:14:y:2017:i:01:n:s0219877017400053 is not listed on IDEAS
    15. John Rigby, 2011. "Systematic grant and funding body acknowledgement data for publications: new dimensions and new controversies for research policy and evaluation," Research Evaluation, Oxford University Press, vol. 20(5), pages 365-375, December.
    16. Lepori, Benedetto, 2011. "Coordination modes in public funding systems," Research Policy, Elsevier, vol. 40(3), pages 355-367, April.
    17. Nicola Grassano & Daniele Rotolo & Joshua Hutton & Frédérique Lang & Michael M. Hopkins, 2017. "Funding Data from Publication Acknowledgments: Coverage, Uses, and Limitations," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 68(4), pages 999-1017, April.
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    More about this item

    Keywords

    Acknowledgement analysis; Funding analysis; Citation network; Emerging technology; Robotics;

    JEL classification:

    • C38 - Mathematical and Quantitative Methods - - Multiple or Simultaneous Equation Models; Multiple Variables - - - Classification Methdos; Cluster Analysis; Principal Components; Factor Analysis
    • C81 - Mathematical and Quantitative Methods - - Data Collection and Data Estimation Methodology; Computer Programs - - - Methodology for Collecting, Estimating, and Organizing Microeconomic Data; Data Access
    • D02 - Microeconomics - - General - - - Institutions: Design, Formation, Operations, and Impact
    • O32 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Management of Technological Innovation and R&D

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