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The influence of dispersion on journal impact measures

Author

Listed:
  • William M. Cockriel

    (Brigham Young University)

  • James B. McDonald

    (Brigham Young University)

Abstract

A family of measures of a journal’s impact is considered that takes account of the dispersion, as well as the mean, of the number of citations in a journal. These measures, called the Mean Dispersion Indices (MDI), generalize the stabilized-JIF recently introduced by Lando and Bertoli-Barsotti (J Informetr 11(3):689–703, 2017). The MDI use a geometric weighted average of the number of citations and the Gini coefficient to measure the dispersion of the number of citations. Journal rankings based on these measures are compared with those obtained from the Journal Impact Factor, the Scimago Journal Rank, the h-index measure, and the Eigenfactor rankings, four of the most well-known current impact measures. This comparison suggests that the different rankings may implicitly place different weights on dispersion and the average number of citations and some appear to show little correlation with dispersion.

Suggested Citation

  • William M. Cockriel & James B. McDonald, 2018. "The influence of dispersion on journal impact measures," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(1), pages 609-622, July.
    • Handle: RePEc:spr:scient:v:116:y:2018:i:1:d:10.1007_s11192-018-2755-1
    DOI: 10.1007/s11192-018-2755-1
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    References listed on IDEAS

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    1. Lando, Tommaso & Bertoli-Barsotti, Lucio, 2017. "Measuring the citation impact of journals with generalized Lorenz curves," Journal of Informetrics, Elsevier, vol. 11(3), pages 689-703.
    2. Florentin GLOETZL & Ernest AIGNER, 2017. "Six Dimensions of Concentration in Economics: Scientometric Evidence from a Large-Scale Data Set," Ecological Economics Papers ieep15, Institute of Ecological Economics.
    3. E. Garfield & I. H. Sher, 1963. "New factors in the evaluation of scientific literature through citation indexing," American Documentation, Wiley Blackwell, vol. 14(3), pages 195-201, July.
    4. Anne-Wil Harzing, 2013. "A preliminary test of Google Scholar as a source for citation data: a longitudinal study of Nobel prize winners," Scientometrics, Springer;Akadémiai Kiadó, vol. 94(3), pages 1057-1075, March.
    5. David I. Stern, 2013. "Uncertainty Measures for Economics Journal Impact Factors," Journal of Economic Literature, American Economic Association, vol. 51(1), pages 173-189, March.
    6. Judit Bar-Ilan, 2008. "Which h-index? — A comparison of WoS, Scopus and Google Scholar," Scientometrics, Springer;Akadémiai Kiadó, vol. 74(2), pages 257-271, February.
    7. Anne‐Wil Harzing & Ron van der Wal, 2009. "A Google Scholar h‐index for journals: An alternative metric to measure journal impact in economics and business," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(1), pages 41-46, January.
    8. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    9. Loet Leydesdorff, 2008. "Caveats for the use of citation indicators in research and journal evaluations," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 59(2), pages 278-287, January.
    10. Loet Leydesdorff, 2009. "How are new citation‐based journal indicators adding to the bibliometric toolbox?," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 60(7), pages 1327-1336, July.
    11. González-Pereira, Borja & Guerrero-Bote, Vicente P. & Moya-Anegón, Félix, 2010. "A new approach to the metric of journals’ scientific prestige: The SJR indicator," Journal of Informetrics, Elsevier, vol. 4(3), pages 379-391.
    12. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
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    3. 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.
    4. Bertoli-Barsotti, Lucio & Lando, Tommaso, 2019. "How mean rank and mean size may determine the generalised Lorenz curve: With application to citation analysis," Journal of Informetrics, Elsevier, vol. 13(1), pages 387-396.

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