Review times in peer review: quantitative analysis of editorial workflows

TL;DR

This study analyzes the peer review process in a scientific journal, modeling workflow stages with probabilistic graphs to identify potential improvements in efficiency.

Contribution

It introduces a graph-based probabilistic model of peer review workflows and evaluates policy modifications to enhance review process efficiency.

Findings

Identified bottlenecks in the review stages

Proposed modifications could reduce review times

Quantitative analysis of editorial workflows

Abstract

We examine selected aspects of peer review and suggest possible improvements. To this end, we analyse a dataset containing information about 300 papers submitted to the Biochemistry and Biotechnology section of the Journal of the Serbian Chemical Society. After separating the peer review process into stages that each review has to go through, we use a weighted directed graph to describe it in a probabilistic manner and test the impact of some modifications of the editorial policy on the efficiency of the whole process.