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Does the average JIF percentile make a difference?

Author

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  • Liping Yu

    (Yunan University of finance and economics)

  • Houqiang Yu

    (Wuhan University)

Abstract

Average journal impact factor (JIF) percentile is a novel bibliometric indicator introduced by Thomson Reuters. It’s of great significance to study the characteristics of its data distribution and relationship with other bibliometric indicators, in order to assess its usefulness as a new bibliometric indicator. The research began by analyzing the meaning of average JIF percentile, and compared its statistical difference with impact factor. Based upon factor analysis, the paper used multivariate regression and quantile regression to study the relationship between average JIF percentile and other bibliometric indicators. Results showed that average JIF percentile had changed the statistical characteristic of impact factor, e.g. improved the relative value of impact factor, having smaller variation coefficient and distribution closer to normal distribution. Because it’s non-parametric transformation, it cannot be used to measure the relative gap between journals; Average JIF percentile had the highest regression coefficient with journal impact, followed by timeliness and lastly the citable items; The lower the average JIF percentile, the higher the elastic coefficient of journal impact; When average JIF percentile was extremely high or extremely low, citable items were not correlated with the average JIF percentile at all; When average JIF percentile was low, elastic coefficient of timeliness was even higher; Average JIF percentile was not a proper indicator for multivariate journal evaluation; Average JIF percentile had both the advantages and disadvantages of impact factor, and thus had the same limitation in applying as the impact factor.

Suggested Citation

  • Liping Yu & Houqiang Yu, 2016. "Does the average JIF percentile make a difference?," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1979-1987, December.
    • Handle: RePEc:spr:scient:v:109:y:2016:i:3:d:10.1007_s11192-016-2156-2
    DOI: 10.1007/s11192-016-2156-2
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    References listed on IDEAS

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    1. Bornmann, Lutz & Leydesdorff, Loet & Mutz, Rüdiger, 2013. "The use of percentiles and percentile rank classes in the analysis of bibliometric data: Opportunities and limits," Journal of Informetrics, Elsevier, vol. 7(1), pages 158-165.
    2. Loet Leydesdorff, 2012. "Alternatives to the journal impact factor: I3 and the top-10% (or top-25%?) of the most-highly cited papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 355-365, August.
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