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Individual research performance: A proposal for comparing apples to oranges

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  • Abramo, Giovanni
  • Cicero, Tindaro
  • D’Angelo, Ciriaco Andrea

Abstract

The evaluation of performance at the individual level is of fundamental importance in informing management decisions. The literature provides various indicators and types of measures, however a problem that is still unresolved and little addressed is how to compare the performance of researchers working in different fields (apples to oranges). In this work we propose a solution, testing various scaling factors for the distributions of research productivity in 174 scientific fields. The analysis is based on the observation of scientific production by all Italian university researchers active in the hard sciences over the period 2004–2008, as indexed by the Web of Science. The most effective scaling factor is the average of the productivity distribution of researchers with productivity above zero.

Suggested Citation

  • Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2013. "Individual research performance: A proposal for comparing apples to oranges," Journal of Informetrics, Elsevier, vol. 7(2), pages 528-539.
  • Handle: RePEc:eee:infome:v:7:y:2013:i:2:p:528-539
    DOI: 10.1016/j.joi.2013.01.013
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    1. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "Revisiting the scaling of citations for research assessment," Journal of Informetrics, Elsevier, vol. 6(4), pages 470-479.
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    Cited by:

    1. Zharova, Alona & Härdle, Wolfgang Karl & Lessmann, Stefan, 2023. "Data-driven support for policy and decision-making in university research management: A case study from Germany," European Journal of Operational Research, Elsevier, vol. 308(1), pages 353-368.
    2. Giovanni Abramo & Ciriaco Andrea D’Angelo & Flavia Di Costa, 2019. "The collaboration behavior of top scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 118(1), pages 215-232, January.
    3. Giovanni Abramo & Ciriaco Andrea D’Angelo & Francesco Rosati, 2016. "The north–south divide in the Italian higher education system," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2093-2117, December.
    4. Diniz-Filho, José Alexandre F. & Fioravanti, Maria Clorinda S. & Bini, Luis Mauricio & Rangel, Thiago Fernando, 2016. "Drivers of academic performance in a Brazilian university under a government-restructuring program," Journal of Informetrics, Elsevier, vol. 10(1), pages 151-161.
    5. Gauffriau, Marianne, 2017. "A categorization of arguments for counting methods for publication and citation indicators," Journal of Informetrics, Elsevier, vol. 11(3), pages 672-684.
    6. Mutz, Rüdiger & Daniel, Hans-Dieter, 2018. "The bibliometric quotient (BQ), or how to measure a researcher’s performance capacity: A Bayesian Poisson Rasch model," Journal of Informetrics, Elsevier, vol. 12(4), pages 1282-1295.
    7. Mehdi Rhaiem & Nabil Amara, 2020. "Determinants of research efficiency in Canadian business schools: evidence from scholar-level data," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(1), pages 53-99, October.
    8. 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.
    9. Petr Praus, 2019. "High-ranked citations percentage as an indicator of publications quality," Scientometrics, Springer;Akadémiai Kiadó, vol. 120(1), pages 319-329, July.
    10. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2015. "Should the research performance of scientists be distinguished by gender?," Journal of Informetrics, Elsevier, vol. 9(1), pages 25-38.
    11. Giovanni Abramo & Ciriaco Andrea D’Angelo & Francesco Rosati, 2016. "Gender bias in academic recruitment," Scientometrics, Springer;Akadémiai Kiadó, vol. 106(1), pages 119-141, January.
    12. Díaz-Faes, Adrián A. & Costas, Rodrigo & Galindo, M. Purificación & Bordons, María, 2015. "Unravelling the performance of individual scholars: Use of Canonical Biplot analysis to explore the performance of scientists by academic rank and scientific field," Journal of Informetrics, Elsevier, vol. 9(4), pages 722-733.
    13. Ana C. M. Brito & Filipi N. Silva & Diego R. Amancio, 2023. "Analyzing the influence of prolific collaborations on authors productivity and visibility," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(4), pages 2471-2487, April.
    14. 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.
    15. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2020. "A novel methodology to assess the scientific standing of nations at field level," Journal of Informetrics, Elsevier, vol. 14(1).
    16. Giovanni Abramo & Ciriaco Andrea D’Angelo & Francesco Rosati, 2014. "Career advancement and scientific performance in universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 98(2), pages 891-907, February.
    17. Alona Zharova & Wolfgang K. Härdle & Stefan Lessmann, 2017. "Is Scientific Performance a Function of Funds?," SFB 649 Discussion Papers SFB649DP2017-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
    18. Wildgaard, Lorna, 2016. "A critical cluster analysis of 44 indicators of author-level performance," Journal of Informetrics, Elsevier, vol. 10(4), pages 1055-1078.
    19. Abramo, Giovanni & D’Angelo, Ciriaco Andrea, 2015. "A methodology to compute the territorial productivity of scientists: The case of Italy," Journal of Informetrics, Elsevier, vol. 9(4), pages 675-685.
    20. Lee, O-Joun & Jeon, Hyeon-Ju & Jung, Jason J., 2021. "Learning multi-resolution representations of research patterns in bibliographic networks," Journal of Informetrics, Elsevier, vol. 15(1).
    21. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2014. "Are the authors of highly cited articles also the most productive ones?," Journal of Informetrics, Elsevier, vol. 8(1), pages 89-97.

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