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Review time in peer review: quantitative analysis and modelling of editorial workflows.

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journal contribution
posted on 2016-11-23, 13:30 authored by M. J. Mrowinski, A. Fronczak, P. Fronczak, O. Nedic, Marcel Ausloos
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.

Funding

A.F. & P.F. were supported by the Foundation for Polish Science (grant no. POMOST/ 2012-5/5) and by the European Union within European Regional Development Fund (Innovative Economy). This paper is a part of scientific activities in COST Action TD1306 New Frontiers of Peer Review (PEERE).

History

Citation

Scientometrics (2016) 107: 271.

Author affiliation

/Organisation/COLLEGE OF SOCIAL SCIENCES, ARTS AND HUMANITIES/School of Management

Version

  • VoR (Version of Record)

Published in

Scientometrics (2016) 107: 271.

Publisher

Springer Verlag (Germany), Akadémiai Kiadó

issn

0138-9130

eissn

1588-2861

Copyright date

2016

Available date

2016-11-23

Publisher version

http://link.springer.com/article/10.1007/s11192-016-1871-z

Language

en

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