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The success-index: an alternative approach to the h-index for evaluating an individual’s research output

Author

Listed:
  • Fiorenzo Franceschini

    (Politecnico di Torino)

  • Maurizio Galetto

    (Politecnico di Torino)

  • Domenico Maisano

    (Politecnico di Torino)

  • Luca Mastrogiacomo

    (Politecnico di Torino)

Abstract

Among the most recent bibliometric indicators for normalizing the differences among fields of science in terms of citation behaviour, Kosmulski (J Informetr 5(3):481–485, 2011) proposed the NSP (number of successful paper) index. According to the authors, NSP deserves much attention for its great simplicity and immediate meaning—equivalent to those of the h-index—while it has the disadvantage of being prone to manipulation and not very efficient in terms of statistical significance. In the first part of the paper, we introduce the success-index, aimed at reducing the NSP-index’s limitations, although requiring more computing effort. Next, we present a detailed analysis of the success-index from the point of view of its operational properties and a comparison with the h-index’s ones. Particularly interesting is the examination of the success-index scale of measurement, which is much richer than the h-index’s. This makes success-index much more versatile for different types of analysis—e.g., (cross-field) comparisons of the scientific output of (1) individual researchers, (2) researchers with different seniority, (3) research institutions of different size, (4) scientific journals, etc.

Suggested Citation

  • Fiorenzo Franceschini & Maurizio Galetto & Domenico Maisano & Luca Mastrogiacomo, 2012. "The success-index: an alternative approach to the h-index for evaluating an individual’s research output," Scientometrics, Springer;Akadémiai Kiadó, vol. 92(3), pages 621-641, September.
    • Handle: RePEc:spr:scient:v:92:y:2012:i:3:d:10.1007_s11192-011-0570-z
    DOI: 10.1007/s11192-011-0570-z
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    References listed on IDEAS

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    4. Lutz Bornmann & Werner Marx, 2014. "How to evaluate individual researchers working in the natural and life sciences meaningfully? A proposal of methods based on percentiles of citations," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(1), pages 487-509, January.
    5. Franceschini, Fiorenzo & Galetto, Maurizio & Maisano, Domenico & Mastrogiacomo, Luca, 2013. "An informetric model for the success-index," Journal of Informetrics, Elsevier, vol. 7(1), pages 109-116.
    6. Bornmann, Lutz & Haunschild, Robin, 2016. "Citation score normalized by cited references (CSNCR): The introduction of a new citation impact indicator," Journal of Informetrics, Elsevier, vol. 10(3), pages 875-887.
    7. Fiorenzo Franceschini & Domenico Maisano & Luca Mastrogiacomo, 2014. "The citer-success-index: a citer-based indicator to select a subset of elite papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 963-983, November.
    8. Istvan-Szilard Szilagyi & Gregor A. Schittek & Christoph Klivinyi & Holger Simonis & Torsten Ulrich & Helmar Bornemann-Cimenti, 2022. "Citation of retracted research: a case-controlled, ten-year follow-up scientometric analysis of Scott S. Reuben’s malpractice," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2611-2620, May.
    9. John Rigby & Barbara Jones, 2020. "Bringing the doctoral thesis by published papers to the Social Sciences and the Humanities: A quantitative easing? A small study of doctoral thesis submission rules and practice in two disciplines in ," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(2), pages 1387-1409, August.
    10. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    11. Franceschini, Fiorenzo & Maisano, Domenico, 2014. "Sub-field normalization of the IEEE scientific journals based on their connection with Technical Societies," Journal of Informetrics, Elsevier, vol. 8(3), pages 508-533.
    12. Fiorenzo Franceschini & Domenico Maisano & Luca Mastrogiacomo, 2015. "Research quality evaluation: comparing citation counts considering bibliometric database errors," Quality & Quantity: International Journal of Methodology, Springer, vol. 49(1), pages 155-165, January.
    13. Zhi Li & Qinke Peng & Che Liu, 2016. "Two citation-based indicators to measure latent referential value of papers," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1299-1313, September.
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    15. Fiorenzo Franceschini & Domenico Maisano & Luca Mastrogiacomo, 2013. "The effect of database dirty data on h-index calculation," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(3), pages 1179-1188, June.

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