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Title: Review time in peer review: quantitative analysis and modelling of editorial workflows.
Authors: Mrowinski, M. J.
Fronczak, A.
Fronczak, P.
Nedic, O.
Ausloos, Marcel
First Published: 9-Feb-2016
Publisher: Springer Verlag (Germany), Akadémiai Kiadó
Citation: Scientometrics (2016) 107: 271.
Abstract: In this paper, we undertake a data-driven theoretical investigation of editorial workflows. We analyse a dataset containing information about 58 papers submitted to the Biochemistry and Biotechnology section of the Journal of the Serbian Chemical Society. We separate the peer review process into stages that each paper has to go through and introduce the notion of completion rate - the probability that an invitation sent to a potential reviewer will result in a finished review. Using empirical transition probabilities and probability distributions of the duration of each stage we create a directed weighted network, the analysis of which allows us to obtain the theoretical probability distributions of review time for different classes of reviewers. These theoretical distributions underlie our numerical simulations of different editorial strategies. Through these simulations, we test the impact of some modifications of the editorial policy on the efficiency of the whole review process. We discover that the distribution of review time is similar for all classes of reviewers, and that the completion rate of reviewers known personally by the editor is very high, which means that they are much more likely to answer the invitation and finish the review than other reviewers. Thus, the completion rate is the key factor that determines the efficiency of each editorial policy. Our results may be of great importance for editors and act as a guide in determining the optimal number of reviewers.
DOI Link: 10.1007/s11192-016-1871-z
ISSN: 0138-9130
eISSN: 1588-2861
Version: Publisher Version
Status: Peer-reviewed
Type: Journal Article
Rights: © The Author(s) 2016 Open Access This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (, which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
Appears in Collections:Published Articles, School of Management

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