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Improving the Peer review process: Capturing more information and enabling high-risk/high-return research

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  • Linton, Jonathan D.

Abstract

The Black-Scholes model and the peer-review process are combined to offer more insight into the apparent value of research projects. In doing so high-risk/high-return research is found to be more attractive and financially rational than under the traditional peer review approach. In other words projects with the highest disagreement amongst panel members should sometimes be selected even though the average panel score may not be the highest under consideration. This finding is important as it improves the existing peer review process by utilizing not only the mean value of peer reviews, but also their standard deviation. This note also opens the consideration of the potential of Real Options approaches for decision support for project selection and management of research.

Suggested Citation

  • Linton, Jonathan D., 2016. "Improving the Peer review process: Capturing more information and enabling high-risk/high-return research," Research Policy, Elsevier, vol. 45(9), pages 1936-1938.
    • Handle: RePEc:eee:respol:v:45:y:2016:i:9:p:1936-1938
    DOI: 10.1016/j.respol.2016.07.004
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    References listed on IDEAS

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    1. Bornmann, Lutz & Mutz, Rüdiger & Daniel, Hans-Dieter, 2008. "Latent Markov modeling applied to grant peer review," Journal of Informetrics, Elsevier, vol. 2(3), pages 217-228.
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    5. Upali W. Jayasinghe & Herbert W. Marsh & Nigel Bond, 2003. "A multilevel cross‐classified modelling approach to peer review of grant proposals: the effects of assessor and researcher attributes on assessor ratings," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 166(3), pages 279-300, October.
    6. Bornmann, Lutz & Daniel, Hans-Dieter, 2007. "Gatekeepers of science—Effects of external reviewers’ attributes on the assessments of fellowship applications," Journal of Informetrics, Elsevier, vol. 1(1), pages 83-91.
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    Cited by:

    1. Chiara Franzoni & Paula Stephan & Reinhilde Veugelers, 2022. "Funding Risky Research," Entrepreneurship and Innovation Policy and the Economy, University of Chicago Press, vol. 1(1), pages 103-133.
    2. Elise S. Brezis & Aliaksandr Birukou, 2020. "Arbitrariness in the peer review process," Scientometrics, Springer;Akadémiai Kiadó, vol. 123(1), pages 393-411, April.
    3. Thomas Feliciani & Junwen Luo & Lai Ma & Pablo Lucas & Flaminio Squazzoni & Ana Marušić & Kalpana Shankar, 2019. "A scoping review of simulation models of peer review," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 555-594, October.

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