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Understanding journal usage: A statistical analysis of citation and use

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  • John D. McDonald

Abstract

This study examined the relationship between print journal use, online journal use, and online journal discovery tools with local journal citations. Local use measures were collected from 1997 to 2004, and negative binomial regression models were designed to test the effect that local use, online availability, and access enhancements have on citation behaviors of academic research authors. Models are proposed and tested to determine whether multiple locally recorded usage measures can predict citations and if locally controlled access enhancements influence citation. The regression results indicated that print journal use was a significant predictor of local journal citations prior to the adoption of online journals. Publisher‐provided and locally recorded online journal use measures were also significant predictors of local citations. Online availability of a journal was found to significantly increase local citations, and, for some disciplines, a new access tool like an OpenURL resolver significantly impacts citations and publisher‐provided journal usage measures.

Suggested Citation

  • John D. McDonald, 2007. "Understanding journal usage: A statistical analysis of citation and use," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 58(1), pages 39-50, January.
    • Handle: RePEc:bla:jamist:v:58:y:2007:i:1:p:39-50
    DOI: 10.1002/asi.20420
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    Citations

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    Cited by:

    1. Juan Gorraiz & Christian Gumpenberger & Christian Schlögl, 2014. "Usage versus citation behaviours in four subject areas," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1077-1095, November.
    2. Ajiferuke, Isola & Famoye, Felix, 2015. "Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models," Journal of Informetrics, Elsevier, vol. 9(3), pages 499-513.
    3. Christian Schloegl & Juan Gorraiz, 2010. "Comparison of citation and usage indicators: the case of oncology journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 567-580, March.
    4. Lee, So-Eun & Kim, Seongcheol & Lim, Chulmin, 2019. "Do special issues offer something special? An overview of research trends in Telecommunications Policy special issues," Telecommunications Policy, Elsevier, vol. 43(10).
    5. Barbara McGillivray & Mathias Astell, 2019. "The relationship between usage and citations in an open access mega-journal," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(2), pages 817-838, November.
    6. Isidro F. Aguillo & José L. Ortega & Mario Fernández & Ana M. Utrilla, 2010. "Indicators for a webometric ranking of open access repositories," Scientometrics, Springer;Akadémiai Kiadó, vol. 82(3), pages 477-486, March.
    7. Wolfgang Glänzel & Juan Gorraiz, 2015. "Usage metrics versus altmetrics: confusing terminology?," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(3), pages 2161-2164, March.
    8. Wood-Doughty, Alex & Bergstrom, Ted & Steigerwald, Douglas, 2017. "Do download reports reliably measure journal usage? Trusting the fox to count your Hens?," University of California at Santa Barbara, Economics Working Paper Series qt1f221007, Department of Economics, UC Santa Barbara.
    9. Andrés Fernández-Ramos & Blanca Rodríguez-Bravo & Ángela Diez-Diez, 2023. "Use of scientific journals in Spanish universities: analysis of the relationship between citations and downloads in two university library consortia," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2489-2505, April.
    10. Thelwall, Mike & Wilson, Paul, 2014. "Regression for citation data: An evaluation of different methods," Journal of Informetrics, Elsevier, vol. 8(4), pages 963-971.

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