IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v97y2013i3d10.1007_s11192-013-1013-9.html
   My bibliography  Save this article

Measuring institutional research productivity for the life sciences: the importance of accounting for the order of authors in the byline

Author

Listed:
  • Giovanni Abramo

    (National Research Council of Italy)

  • Ciriaco Andrea D’Angelo

    (University of Rome “Tor Vergata”)

  • Francesco Rosati

    (University of Rome “Tor Vergata”)

Abstract

Accurate measurement of institutional research productivity should account for the real contribution of the research staff to the output produced in collaboration with other organizations. In the framework of bibliometric measurement, this implies accounting for both the number of co-authors and each individual’s real contribution to scientific publications. Common practice in the life sciences is to indicate such contribution through the order of author names in the byline. In this work, we measure the distortion introduced to university-level bibliometric productivity rankings when the number of co-authors or their position in the byline is ignored. The field of observation consists of all Italian universities active in the life sciences (Biology and Medicine). The analysis is based on the research output of the university staff over the period 2004–2008. Based on the results, we recommend against the use of bibliometric indicators that ignore co-authorship and real contribution of each author to research outputs.

Suggested Citation

  • Giovanni Abramo & Ciriaco Andrea D’Angelo & Francesco Rosati, 2013. "Measuring institutional research productivity for the life sciences: the importance of accounting for the order of authors in the byline," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 779-795, December.
  • Handle: RePEc:spr:scient:v:97:y:2013:i:3:d:10.1007_s11192-013-1013-9
    DOI: 10.1007/s11192-013-1013-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-013-1013-9
    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/s11192-013-1013-9?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. Giovanni Abramo & Ciriaco Andrea D'Angelo & Flavia Di Costa, 2008. "Assessment of sectoral aggregation distortion in research productivity measurements," Research Evaluation, Oxford University Press, vol. 17(2), pages 111-121, June.
    2. Leo Egghe, 2006. "Theory and practise of the g-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(1), pages 131-152, October.
    3. Marianne Gauffriau & Peder Olesen Larsen & Isabelle Maye & Anne Roulin-Perriard & Markus Ins, 2008. "Comparisons of results of publication counting using different methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 77(1), pages 147-176, October.
    4. Lundberg, Jonas, 2007. "Lifting the crown—citation z-score," Journal of Informetrics, Elsevier, vol. 1(2), pages 145-154.
    5. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Rosati, Francesco, 2013. "The importance of accounting for the number of co-authors and their order when assessing research performance at the individual level in the life sciences," Journal of Informetrics, Elsevier, vol. 7(1), pages 198-208.
    6. Justus V. Verhagen & Karin J. Wallace & Stephan C. Collins & Thomas R. Scott, 2003. "QUAD system offers fair shares to all authors," Nature, Nature, vol. 426(6967), pages 602-602, December.
    7. Aksnes, Dag W. & Schneider, Jesper W. & Gunnarsson, Magnus, 2012. "Ranking national research systems by citation indicators. A comparative analysis using whole and fractionalised counting methods," Journal of Informetrics, Elsevier, vol. 6(1), pages 36-43.
    8. Pablo D. Batista & Mônica G. Campiteli & Osame Kinouchi, 2006. "Is it possible to compare researchers with different scientific interests?," Scientometrics, Springer;Akadémiai Kiadó, vol. 68(1), pages 179-189, July.
    9. William F. Laurance, 2006. "Second thoughts on who goes where in author lists," Nature, Nature, vol. 442(7098), pages 26-26, July.
    10. He, Bing & Ding, Ying & Yan, Erjia, 2012. "Mining patterns of author orders in scientific publications," Journal of Informetrics, Elsevier, vol. 6(3), pages 359-367.
    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. 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.
    2. Edson Melo Souza & Jose Eduardo Storopoli & Wonder Alexandre Luz Alves, 2022. "Scientific Contribution List Categories Investigation: a comparison between three mainstream medical journals," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(5), pages 2249-2276, May.
    3. William H. Walters & Esther Isabelle Wilder, 2015. "Worldwide contributors to the literature of library and information science: top authors, 2007–2012," Scientometrics, Springer;Akadémiai Kiadó, vol. 103(1), pages 301-327, April.
    4. Frode Eika Sandnes, 2021. "Everyone onboard? Participation ratios as a metric for research activity assessments within young universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(7), pages 6105-6113, July.
    5. Denis Kosyakov & Andrey Guskov, 2022. "Reasons and consequences of changes in Russian research assessment policies," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4609-4630, August.

    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. Abramo, Giovanni & D’Angelo, Ciriaco Andrea & Rosati, Francesco, 2013. "The importance of accounting for the number of co-authors and their order when assessing research performance at the individual level in the life sciences," Journal of Informetrics, Elsevier, vol. 7(1), pages 198-208.
    2. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    3. Rahman, Mohammad Tariqur & Regenstein, Joe Mac & Kassim, Noor Lide Abu & Haque, Nazmul, 2017. "The need to quantify authors’ relative intellectual contributions in a multi-author paper," Journal of Informetrics, Elsevier, vol. 11(1), pages 275-281.
    4. Kaur, Jasleen & Radicchi, Filippo & Menczer, Filippo, 2013. "Universality of scholarly impact metrics," Journal of Informetrics, Elsevier, vol. 7(4), pages 924-932.
    5. Kuan, Chung-Huei & Huang, Mu-Hsuan & Chen, Dar-Zen, 2013. "Cross-field evaluation of publications of research institutes using their contributions to the fields’ MVPs determined by h-index," Journal of Informetrics, Elsevier, vol. 7(2), pages 455-468.
    6. 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.
    7. 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.
    8. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2013. "The impact of unproductive and top researchers on overall university research performance," Journal of Informetrics, Elsevier, vol. 7(1), pages 166-175.
    9. Waltman, Ludo & van Eck, Nees Jan, 2015. "Field-normalized citation impact indicators and the choice of an appropriate counting method," Journal of Informetrics, Elsevier, vol. 9(4), pages 872-894.
    10. Giovanni Abramo & Ciriaco Andrea D’Angelo & Fulvio Viel, 2013. "The suitability of h and g indexes for measuring the research performance of institutions," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(3), pages 555-570, December.
    11. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    12. Patrick Herron & Aashish Mehta & Cong Cao & Timothy Lenoir, 2016. "Research diversification and impact: the case of national nanoscience development," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(2), pages 629-659, November.
    13. Lin Zhang & Wolfgang Glänzel, 2012. "Where demographics meets scientometrics: towards a dynamic career analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 91(2), pages 617-630, May.
    14. Shahryar Rahnamayan & Sedigheh Mahdavi & Kalyanmoy Deb & Azam Asilian Bidgoli, 2020. "Ranking Multi-Metric Scientific Achievements Using a Concept of Pareto Optimality," Mathematics, MDPI, vol. 8(6), pages 1-46, June.
    15. Serge Galam, 2011. "Tailor based allocations for multiple authorship: a fractional gh-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 89(1), pages 365-379, October.
    16. Kim, Jinseok & Kim, Jinmo, 2015. "Rethinking the comparison of coauthorship credit allocation schemes," Journal of Informetrics, Elsevier, vol. 9(3), pages 667-673.
    17. Parul Khurana & Kiran Sharma, 2022. "Impact of h-index on author’s rankings: an improvement to the h-index for lower-ranked authors," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(8), pages 4483-4498, August.
    18. Abramo, Giovanni & Cicero, Tindaro & D’Angelo, Ciriaco Andrea, 2012. "The dispersion of research performance within and between universities as a potential indicator of the competitive intensity in higher education systems," Journal of Informetrics, Elsevier, vol. 6(2), pages 155-168.
    19. Giovanni Abramo & Ciriaco Andrea D’Angelo & Francesco Rosati, 2014. "Relatives in the same university faculty: nepotism or merit?," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(1), pages 737-749, October.
    20. Thomas R. Anderson & Robin K. S. Hankin & Peter D. Killworth, 2008. "Beyond the Durfee square: Enhancing the h-index to score total publication output," Scientometrics, Springer;Akadémiai Kiadó, vol. 76(3), pages 577-588, September.

    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:97:y:2013:i:3:d:10.1007_s11192-013-1013-9. 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.