IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v116y2018i1d10.1007_s11192-018-2755-1.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-018-2755-1
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-018-2755-1?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Glötzl, Florentin & Aigner, Ernest, 2017. "Six Dimensions of Concentration in Economics: Scientometric Evidence from a Large-Scale Data Set," Ecological Economic Papers 15, WU Vienna University of Economics and Business.
    2. 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.
    3. 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.
    4. 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.
    5. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    6. 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.
    7. 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.
    8. 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.
    9. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
    10. 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.
    11. 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.
    12. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Horenberg, Frank & Lungu, Daniel Adrian & Nuti, Sabina, 2020. "Measuring research in the big data era: The evolution of performance measurement systems in the Italian teaching hospitals," Health Policy, Elsevier, vol. 124(12), pages 1387-1394.
    3. Zhang, Baolong & Wang, Hao & Deng, Sanhong & Su, Xinning, 2020. "Measurement and analysis of Chinese journal discriminative capacity," Journal of Informetrics, Elsevier, vol. 14(1).
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Mingers, John & Leydesdorff, Loet, 2015. "A review of theory and practice in scientometrics," European Journal of Operational Research, Elsevier, vol. 246(1), pages 1-19.
    2. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    3. Mingkun Wei, 2020. "Research on impact evaluation of open access journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(2), pages 1027-1049, February.
    4. Mingers, John & Yang, Liying, 2017. "Evaluating journal quality: A review of journal citation indicators and ranking in business and management," European Journal of Operational Research, Elsevier, vol. 257(1), pages 323-337.
    5. Weibin Wang & Zheng Wang & Tian Yu & CholMyong Pak & Guang Yu, 2020. "Research on citation mention times and contributions using a neural network," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2383-2400, December.
    6. Ziqiang Zeng & Lantian Shi, 2021. "A two-dimensional journal classification method based on output and input factors: perspectives from citation and authorship related indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(5), pages 3929-3964, May.
    7. Vanclay, Jerome K., 2011. "An evaluation of the Australian Research Council's journal ranking," Journal of Informetrics, Elsevier, vol. 5(2), pages 265-274.
    8. Walters, William H., 2017. "Do subjective journal ratings represent whole journals or typical articles? Unweighted or weighted citation impact?," Journal of Informetrics, Elsevier, vol. 11(3), pages 730-744.
    9. Wolfgang Glänzel & Henk F. Moed, 2013. "Opinion paper: thoughts and facts on bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(1), pages 381-394, July.
    10. Zhang, Fang & Wu, Shengli, 2020. "Predicting future influence of papers, researchers, and venues in a dynamic academic network," Journal of Informetrics, Elsevier, vol. 14(2).
    11. Currie, Russell R. & Pandher, Gurupdesh S., 2020. "Finance journal rankings: Active scholar assessment revisited," Journal of Banking & Finance, Elsevier, vol. 111(C).
    12. Xu, Shuqi & Mariani, Manuel Sebastian & Lü, Linyuan & Medo, Matúš, 2020. "Unbiased evaluation of ranking metrics reveals consistent performance in science and technology citation data," Journal of Informetrics, Elsevier, vol. 14(1).
    13. Juan Gorraiz & Ursula Ulrych & Wolfgang Glänzel & Wenceslao Arroyo-Machado & Daniel Torres-Salinas, 2022. "Measuring the excellence contribution at the journal level: an alternative to Garfield’s impact factor," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(12), pages 7229-7251, December.
    14. Loet Leydesdorff & Ping Zhou & Lutz Bornmann, 2013. "How can journal impact factors be normalized across fields of science? An assessment in terms of percentile ranks and fractional counts," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 64(1), pages 96-107, January.
    15. Gianfranco Ennas & Battista Biggio & Maria Chiara Di Guardo, 2015. "Data-driven journal meta-ranking in business and management," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1911-1929, December.
    16. 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.
    17. Yves Fassin, 2021. "Does the Financial Times FT50 journal list select the best management and economics journals?," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 5911-5943, July.
    18. Michel Zitt, 2012. "The journal impact factor: angel, devil, or scapegoat? A comment on J.K. Vanclay’s article 2011," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(2), pages 485-503, August.
    19. Lucio Bertoli-Barsotti & Tommaso Lando, 2017. "A theoretical model of the relationship between the h-index and other simple citation indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 111(3), pages 1415-1448, June.
    20. Zhang, Lin & Thijs, Bart & Glänzel, Wolfgang, 2011. "The diffusion of H-related literature," Journal of Informetrics, Elsevier, vol. 5(4), pages 583-593.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:scient:v:116:y:2018:i:1:d:10.1007_s11192-018-2755-1. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.