APC Costs
I. Grypari 
N. Manola
H. Papageorgiou
P. Stavropoulos
Description
Αrticle Processing Charges (APCs) represent the price that publishers demand from authors to pay in order to publish their articles and books under an open access license. They capture the affordability and accessibility of Open Access publishing for different types of stakeholders, such as researchers, institutions, and funding agencies. It is also relevant for policy-makers seeking to optimize Open Science policies.
Tracking and comparing APCs could also be used to encourage publishers to adopt more transparent and equitable pricing policies and support the development of sustainable Open Access publishing models accessible to all researchers regardless of their financial resources.
APCs have both benefits and drawbacks. In a strict sense, they do not remove the economic barriers between the writing and the reading of scientific results but shift these costs from the readers to the authors. In countries where funder reimbursement of APC costs or transformative agreements do not cover these costs, APCs can create a financial barrier that limits access to Open Access journals, often generating asymmetries between richer and poorer countries and academic institutions. On the other hand, APCs also incentivize publishers to offer Open Access publishing, which promotes Open Science.
Metrics
Average APC
Description:
The “average APC” metric measures the average cost of Article Processing Charges (APCs) across a defined level of interest (per year, country, organization, etc.).
Usefulness:
The “average APC” metric can help assess the affordability and accessibility of Open Access publishing. It provides a broad understanding of the cost of Open Access publishing and identifies trends and changes in APC pricing over time. This metric can help researchers, institutions, and funding agencies to compare the cost-effectiveness of different Open Access publishing models and identify affordable publishing options.
Limitations:
- The cost of APCs can vary widely depending on the field of research, the region, and the specific publisher or journal, therefore taking an average may be misleading.
- Not knowing who incurred that APC (funder, institution, author, etc.) limits the usefulness of this metric.
Measurement
Datasources
OpenAIRE Graph
The OpenAPC APC dataset, which is integrated in the OpenAIRE Graph.
Limitations:
- Incomplete data: Publishers do not generally provide data on their APC fees, OpenAPC (openapc.net) has a growing collection but it is not complete.
- In an (organization, publication, APC cost) triplet of OpenAPC, to the best of our knowledge, it is not possible to distinguish if the APC cost is the entire cost of the publication or just the what the organization paid.
Methodology
Via OpenAIRE MONITOR (monitor.openaire.eu)
- Identify the unit of analysis (e.g. average APCs for an institution)
- Examine the coverage of APCs for the relevant publications (see metric Number of OA publications with APC).
- Examine if the coverage is adequate and the distribution of costs meaningful for taking an average.
- Take the average APC for that level of analysis.
Limitations:
- Averages have the benefit of summarizing and normalizing information, however depending on the underlying distribution of costs, they may be misleading (e.g. via outliers)
Total APC
Description:
The “Total APC” metric measures the sum of APCs paid for all the articles published for a defined level of interest (a year, country, organization, etc.)
Usefulness:
- The “total APC” metric can help assess the affordability and accessibility of Open Access publishing. It provides a broad understanding of the cost of Open Access publishing and identifies trends and changes in APC pricing over time. By summing the APCs this metric measures the total financial burden of OA publishing for the unit of analysis and can be compared to other aggregate measures.
Limitations:
- Not knowing who incurred that APC (funder, institution, author, etc.) limits the usefulness of this metric, more than the previous ones.
- It does not contain information of the distribution of APCs across a subdomain, e.g. Total cost does not give info on how it is distributed across scientific domains.
Measurement
Datasources
OpenAIRE Graph
The OpenAPC APC dataset, which is integrated in the OpenAIRE Graph.
Limitations:
- Incomplete data: Publishers do not generally provide data on their APC fees, OpenAPC (openapc.net) has a growing collection but it is not complete.
- In an (organization, publication, APC cost) triplet of OpenAPC, to the best of our knowledge, it is not possible to distinguish if the APC cost is the entire cost of the publication or just the what the organization paid.
Methodology
Via OpenAIRE MONITOR
- Identify the unit of analysis (e.g. total APCs for an institution)
- Examine the coverage of APCs for the relevant publications (see metric Number of OA publications with APC).
- Examine if the coverage is adequate.
- Sum the APCs for that level of analysis.
Limitations:
- Totals have the benefit of giving a bird’s eye view, however depending on the underlying distribution of costs, they can have different implications.
Known correlates
Via: https://direct.mit.edu/qss/article/1/1/6/15582/Article-processing-charges-Mirroring-the-citation
- Year
- Publisher
- Hybrid vs. Gold OA
- SNIP
Estimating unknown APCs
An APC extrapolation exercise was conducted for the purpose of an EC study (Monitoring the open access policy of Horizon 2020: final report 2021). The authors defined groupings, and imputed the average APC of the group to each publication in the group for which the APC is unknown. The groupings were based on the following variables, similar to the correlates above: - quantile of the Source Normalised Impact per Paper (SNIP) score in the CWTS journal indicators, - whether the publication is pure ‘gold’ open access or ‘hybrid’, - the year of publication.
The French Open Science Monitor also uses several extrapolations when the APC for a DOI is not available in OpenAPC (Bracco et al. 2022). They are listed here in order of preference (only when one computation is not possible is the following used): - average APC for the same journal and the same year in OpenAPC (provided \(n \geq 10\)) - average APC for the same publisher in OpenAPC, for the same year as the article (provided \(n \geq 10\)) - average APC for the same journal in OpenAPC, for all years available - average APC for the same publisher in OpenAPC, for all years available - APC for the journal in DOAJ.
References
Reuse
Citation
@online{apartis2024,
author = {Apartis, S. and Catalano, G. and Consiglio, G. and Costas,
R. and Delugas, E. and Dulong de Rosnay, M. and Grypari, I. and
Karasz, I. and Klebel, Thomas and Kormann, E. and Manola, N. and
Papageorgiou, H. and Seminaroti, E. and Stavropoulos, P. and Stoy,
L. and Traag, V.A. and van Leeuwen, T. and Venturini, T. and
Vignetti, S. and Waltman, L. and Willemse, T.},
title = {Open {Science} {Impact} {Indicator} {Handbook}},
date = {2024},
url = {https://handbook.pathos-project.eu/sections/1_open_science/APC_costs.html},
doi = {10.5281/zenodo.14538442},
langid = {en}
}