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A Measure of Total Research Impact Independent of Time and Discipline

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  • Alberto Pepe
  • Michael J Kurtz

Abstract

Authorship and citation practices evolve with time and differ by academic discipline. As such, indicators of research productivity based on citation records are naturally subject to historical and disciplinary effects. We observe these effects on a corpus of astronomer career data constructed from a database of refereed publications. We employ a simple mechanism to measure research output using author and reference counts available in bibliographic databases to develop a citation-based indicator of research productivity. The total research impact (tori) quantifies, for an individual, the total amount of scholarly work that others have devoted to his/her work, measured in the volume of research papers. A derived measure, the research impact quotient (riq), is an age-independent measure of an individual's research ability. We demonstrate that these measures are substantially less vulnerable to temporal debasement and cross-disciplinary bias than the most popular current measures. The proposed measures of research impact, tori and riq, have been implemented in the Smithsonian/NASA Astrophysics Data System.

Suggested Citation

  • Alberto Pepe & Michael J Kurtz, 2012. "A Measure of Total Research Impact Independent of Time and Discipline," PLOS ONE, Public Library of Science, vol. 7(11), pages 1-7, November.
    • Handle: RePEc:plo:pone00:0046428
    DOI: 10.1371/journal.pone.0046428
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    References listed on IDEAS

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    1. Michael J. Kurtz & Guenther Eichhorn & Alberto Accomazzi & Carolyn Grant & Markus Demleitner & Stephen S. Murray & Nathalie Martimbeau & Barbara Elwell, 2005. "The bibliometric properties of article readership information," Journal of the American Society for Information Science and Technology, Association for Information Science & Technology, vol. 56(2), pages 111-128, January.
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    8. Moed, Henk F., 2010. "Measuring contextual citation impact of scientific journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 265-277.
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    Cited by:

    1. Giovanni Abramo & Corrado Costa & Ciriaco Andrea D’Angelo, 2015. "A multivariate stochastic model to assess research performance," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1755-1772, February.
    2. Shaon Sahoo, 2016. "Analyzing research performance: proposition of a new complementary index," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 489-504, August.
    3. Aliakbar Akbaritabar & Niccolò Casnici & Flaminio Squazzoni, 2018. "The conundrum of research productivity: a study on sociologists in Italy," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 859-882, March.
    4. Frank Havemann & Birger Larsen, 2015. "Bibliometric indicators of young authors in astrophysics: Can later stars be predicted?," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(2), pages 1413-1434, February.
    5. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2014. "How do you define and measure research productivity?," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1129-1144, November.
    6. Gobinda Chowdhury & Kushwanth Koya & Pete Philipson, 2016. "Measuring the Impact of Research: Lessons from the UK’s Research Excellence Framework 2014," PLOS ONE, Public Library of Science, vol. 11(6), pages 1-15, June.

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