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A quantitative study on the effectiveness of peer review for academic journals

Author

Listed:
  • Zheng Ma

    (Institute of Scientific and Technical Information of China
    ISTIC-Thomson Reuters Joint Lab for Scientometrics Research)

  • Yuntao Pan

    (Institute of Scientific and Technical Information of China
    ISTIC-Thomson Reuters Joint Lab for Scientometrics Research)

  • Zhenglu Yu

    (Institute of Scientific and Technical Information of China)

  • Jingting Wang

    (Institute of Scientific and Technical Information of China)

  • Jia Jia

    (Peking University)

  • Yishan Wu

    (Institute of Scientific and Technical Information of China)

Abstract

Peer review is a classic method in the field of quality analysis, but the effectiveness of peer reviewing has never been researched using quantity analysis indicators. A new indicator for academic journals, Effectiveness of Peer Review (EPR), is defined for evaluating the effectiveness of peer reviewing. If the assumption is valid, EPR could be a simple indicator of such effectiveness. In a sample experiment, 28 academic journals were tested, and the EPR indicator was able to reflect accurately the academic impact of those journals.

Suggested Citation

  • Zheng Ma & Yuntao Pan & Zhenglu Yu & Jingting Wang & Jia Jia & Yishan Wu, 2013. "A quantitative study on the effectiveness of peer review for academic journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 1-13, April.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:1:d:10.1007_s11192-012-0879-2
    DOI: 10.1007/s11192-012-0879-2
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    References listed on IDEAS

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    1. Anthony F. J. van Raan, 2004. "Sleeping Beauties in science," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 467-472, March.
    2. Spiro Stefanou & Kristiaan Kerstens, 2008. "Applied production analysis unveiled in open peer review: introductory remarks," Journal of Productivity Analysis, Springer, vol. 30(1), pages 1-6, August.
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    Cited by:

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    2. Niccolò Casnici & Francisco Grimaldo & Nigel Gilbert & Pierpaolo Dondio & Flaminio Squazzoni, 2017. "Assessing peer review by gauging the fate of rejected manuscripts: the case of the Journal of Artificial Societies and Social Simulation," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 533-546, October.
    3. Justus Haucap & Johannes Muck, 2015. "What drives the relevance and reputation of economics journals? An update from a survey among economists," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(3), pages 849-877, June.
    4. J. Rigby & D. Cox & K. Julian, 2018. "Journal peer review: a bar or bridge? An analysis of a paper’s revision history and turnaround time, and the effect on citation," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 1087-1105, March.
    5. J. A. Garcia & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia, 2019. "The optimal amount of information to provide in an academic manuscript," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(3), pages 1685-1705, December.

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