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Scientometrics
Article . 2020 . Peer-reviewed
License: CC BY
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Scientometrics
Article
License: CC BY
Data sources: UnpayWall
SSRN Electronic Journal
Article . 2019 . Peer-reviewed
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DBLP
Article . 2020
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EconStor
Research . 2019
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Drivers of Article Processing Charges in Open Access

Authors: Oliver Budzinski; Thomas Grebel; Jens Wolling; Xijie Zhang;

Drivers of Article Processing Charges in Open Access

Abstract

AbstractLarge publishing companies have been dominating scientific publishing for long, which leads to high subscription fees and inhibited access to scientific knowledge. At digital era, the opportunity of an unrestricted access appears feasible, because the cost of publishing should be low. It is no longer the readers and libraries to pay subscription fees, but scientific organizations and authors themselves who pay for the cost of having their article published. As the data shows, there is a tremendous variance of article processing charges (APC) across journals, which obviously cannot be explained by the costs. One of the explanatory variables could be reputation, but it only contributes less than 5% to the variance in average APC. This study is meant to shed light on the various determinants of APC. Based on the data from the OpenAPC Initiative, the Directory of Open Access Journals and three different datasets of Web of Science, we employ ANOVAs and multivariate regressions. The results show that market power plays an important role to explain APC, inter alia, through market concentration, market position of individual publishers (publisher size), and the choice of hybrid publishing model.

Related Organizations
Keywords

open access, L13, ddc:330, article processing charges, market power, L11, market concentration, D40, D43, D22

  • BIP!
    Impact byBIP!
    selected citations
    These citations are derived from selected sources.
    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    67
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Top 1%
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    Top 10%
    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
    Top 10%
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Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
67
Top 1%
Top 10%
Top 10%
hybrid