When Competition Is Pushed Too Hard. An Agent-Based Model Of Strategic Behaviour Of Referees In Peer Review

This paper examines the impact of strategic behaviour of referees on the quality and efficiency of peer review. We modelled peer review as a process based on knowledge asymmetry and subject to evaluation bias. We built two simulation scenarios to investigate largescale implications of referee behaviour and judgment bias. The first one was inspired by “the luck of the reviewer draw” idea. In this case, we assumed that referees randomly fell into Type I and Type II errors, i.e., recommending submissions of low quality to be published or recommending against the publishing of submissions which should have been published. In the second scenario, we assumed that certain referees tried intentionally to outperform potential competitors by underrating the value of their submissions. We found that when publication selection increased, the presence of a minority of cheaters may dramatically undermine the quality and efficiency of peer review even compared with a scenario purely dominated by “the luck of the reviewer draw”. We also found that peer review outcomes are significantly influenced by differences in the way scientists identify potential competitors in the system.