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

Erjia Yan (), Chaojiang Wu and Min Song
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Erjia Yan: Drexel University
Chaojiang Wu: Drexel University
Min Song: Yonsei University

Scientometrics, 2018, vol. 115, issue 1, 369-384

Abstract: 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.

Keywords: Funding; Citation impact; Disciplinarity; STEM (search for similar items in EconPapers)
Date: 2018
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