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The funding factor: a cross-disciplinary examination of the association between research funding and citation impact

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Listed:
  • Erjia Yan

    (Drexel University)

  • Chaojiang Wu

    (Drexel University)

  • Min Song

    (Yonsei University)

Abstract

This paper intends to illuminate the relationship between science funding and citation impact in seven STEMM disciplines (science, technology, engineering, mathematics, and medicine). Using a regression model with Heckman bias correction, we find that funding has a positive, significant association with a paper’s citations in STEMM fields. Further analyses show that this association is magnified by the factors of multiple authorship and multiple institutions. For funded papers in STEM, multi-author and multi-institution papers tend to receive even more citations than single-authored and single-institution papers; however, funded papers in Medicine received less gain in citation impact when either factor is considered. Based on the finding that funding support has a stronger association with citation impact when it is treated as a binary variable than as a count variable, this paper recommends the allocation of funding to researchers without active funding support, instead of giving awards to those with multiple funding supports at hand.

Suggested Citation

  • Erjia Yan & Chaojiang Wu & Min Song, 2018. "The funding factor: a cross-disciplinary examination of the association between research funding and citation impact," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(1), pages 369-384, April.
    • Handle: RePEc:spr:scient:v:115:y:2018:i:1:d:10.1007_s11192-017-2583-8
    DOI: 10.1007/s11192-017-2583-8
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