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Evaluating research and researchers by the journal impact factor: Is it better than coin flipping?

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  • Brito, Ricardo
  • Rodríguez-Navarro, Alonso

Abstract

The journal impact factor (JIF) is the average of the number of citations of the papers published in a journal, calculated according to a specific formula; it is extensively used for the evaluation of research and researchers. The method assumes that all papers in a journal have the same scientific merit, which is measured by the JIF of the publishing journal. This implies that the number of citations measures scientific merits but the JIF does not evaluate each individual paper by its own number of citations. Therefore, in the comparative evaluation of two papers, the use of the JIF implies a risk of failure, which occurs when a paper in the journal with the lower JIF is compared to another with fewer citations in the journal with the higher JIF. To quantify this risk of failure, this study calculates the failure probabilities, taking advantage of the lognormal distribution of citations. In two journals whose JIFs are ten-fold different, the failure probability is low. However, in most cases when two papers are compared, the JIFs of the journals are not so different. Then, the failure probability can be close to 0.5, which is equivalent to evaluating by coin flipping.

Suggested Citation

  • Brito, Ricardo & Rodríguez-Navarro, Alonso, 2019. "Evaluating research and researchers by the journal impact factor: Is it better than coin flipping?," Journal of Informetrics, Elsevier, vol. 13(1), pages 314-324.
    • Handle: RePEc:eee:infome:v:13:y:2019:i:1:p:314-324
    DOI: 10.1016/j.joi.2019.01.009
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    References listed on IDEAS

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    Cited by:

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    3. James W. Vaupel & Marie-Pier Bergeron-Boucher & Ilya Kashnitsky, 2021. "Outsurvival as a measure of the inequality of lifespans between two populations," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(35), pages 853-864.
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    5. Raminta Pranckutė, 2021. "Web of Science (WoS) and Scopus: The Titans of Bibliographic Information in Today’s Academic World," Publications, MDPI, vol. 9(1), pages 1-59, March.
    6. Alonso Rodríguez-Navarro & Ricardo Brito, 2019. "Probability and expected frequency of breakthroughs: basis and use of a robust method of research assessment," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 213-235, April.
    7. Avick Kumar Dey & Pijush Kanti Dutta Pramanik & Prasenjit Choudhury & Goutam Bandopadhyay, 2021. "Distinctive author ranking using DEA indexing," Quality & Quantity: International Journal of Methodology, Springer, vol. 55(2), pages 601-620, April.
    8. Claudiu Vasile Kifor & Ana Maria Benedek & Ioan Sîrbu & Roxana Florența Săvescu, 2023. "Institutional drivers of research productivity: a canonical multivariate analysis of Romanian public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2233-2258, April.
    9. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Costa, 2023. "Correlating article citedness and journal impact: an empirical investigation by field on a large-scale dataset," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(3), pages 1877-1894, March.
    10. Batista-Jr, Antônio de Abreu & Gouveia, Fábio Castro & Mena-Chalco, Jesús P., 2021. "Predicting the Q of junior researchers using data from the first years of publication," Journal of Informetrics, Elsevier, vol. 15(2).
    11. Nash Jett D. G. Reyes & Franz Kevin F. Geronimo & Heidi B. Guerra & Lee-Hyung Kim, 2023. "Bibliometric Analysis and Comprehensive Review of Stormwater Treatment Wetlands: Global Research Trends and Existing Knowledge Gaps," Sustainability, MDPI, vol. 15(3), pages 1-23, January.
    12. Gabriel-Alexandru Vȋiu & Mihai Păunescu, 2021. "The lack of meaningful boundary differences between journal impact factor quartiles undermines their independent use in research evaluation," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(2), pages 1495-1525, February.
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