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

Erjia Yan, Chaojiang Wu, Min Song

Research output: Contribution to journalArticle

12 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)369-384
Number of pages16
JournalScientometrics
Volume115
Issue number1
DOIs
Publication statusPublished - 2018 Apr 1

All Science Journal Classification (ASJC) codes

  • Social Sciences(all)
  • Computer Science Applications
  • Library and Information Sciences

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