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Auctions and Peer Prediction for Academic Peer Review

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  • Siddarth Srinivasan
  • Jamie Morgenstern

Abstract

Peer reviewed publications are considered the gold standard in certifying and disseminating ideas that a research community considers valuable. However, we identify two major drawbacks of the current system: (1) the overwhelming demand for reviewers due to a large volume of submissions, and (2) the lack of incentives for reviewers to participate and expend the necessary effort to provide high-quality reviews. In this work, we adopt a mechanism-design approach to propose improvements to the peer review process, tying together the paper submission and review processes and simultaneously incentivizing high-quality submissions and reviews. In the submission stage, authors participate in a VCG auction for review slots by submitting their papers along with a bid that represents their expected value for having their paper reviewed. For the reviewing stage, we propose a novel peer prediction mechanism (H-DIPP) building on recent work in the information elicitation literature, which incentivizes participating reviewers to provide honest and effortful reviews. The revenue raised in the submission stage auction is used to pay reviewers based on the quality of their reviews in the reviewing stage.

Suggested Citation

  • Siddarth Srinivasan & Jamie Morgenstern, 2021. "Auctions and Peer Prediction for Academic Peer Review," Papers 2109.00923, arXiv.org, revised May 2023.
    • Handle: RePEc:arx:papers:2109.00923
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    References listed on IDEAS

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    1. Squazzoni, Flaminio & Bravo, Giangiacomo & Takács, Károly, 2013. "Does incentive provision increase the quality of peer review? An experimental study," Research Policy, Elsevier, vol. 42(1), pages 287-294.
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    4. Nolan Miller & Paul Resnick & Richard Zeckhauser, 2005. "Eliciting Informative Feedback: The Peer-Prediction Method," Management Science, INFORMS, vol. 51(9), pages 1359-1373, September.
    5. Paul Frijters & Benno Torgler, 2019. "Improving the peer review process: a proposed market system," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(2), pages 1285-1288, May.
    6. Oecd, 2008. "DAC Peer Review of the United Kingdom," OECD Journal on Development, OECD Publishing, vol. 7(3), pages 7-114.
    7. Martijn Arns, 2014. "Open access is tiring out peer reviewers," Nature, Nature, vol. 515(7528), pages 467-467, November.
    8. Oecd, 2008. "DAC Peer Review of Denmark," OECD Journal on Development, OECD Publishing, vol. 8(4), pages 7-125.
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    Cited by:

    1. Alexander Ugarov, 2023. "Peer Prediction for Peer Review: Designing a Marketplace for Ideas," Papers 2303.16855, arXiv.org.

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