IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v107y2016i2d10.1007_s11192-016-1882-9.html
   My bibliography  Save this article

Large-scale assessment of research outputs through a weighted combination of bibliometric indicators

Author

Listed:
  • Alberto Anfossi

    (National Agency for the Evaluation of Universities and Research Institutes (ANVUR)
    Compagnia di San Paolo Sistema Torino)

  • Alberto Ciolfi

    (National Agency for the Evaluation of Universities and Research Institutes (ANVUR))

  • Filippo Costa

    (National Agency for the Evaluation of Universities and Research Institutes (ANVUR)
    Università di Pisa)

  • Giorgio Parisi

    (Università “La Sapienza” di Roma)

  • Sergio Benedetto

    (National Agency for the Evaluation of Universities and Research Institutes (ANVUR))

Abstract

The paper describes a method to combine the information on the number of citations and the relevance of the publishing journal (as measured by the Impact Factor or similar impact indicators) of a publication to rank it with respect to the world scientific production in the specific subfield. The linear or non-linear combination of the two indicators is represented on the scatter plot of the papers in the specific subfield in order to immediately visualize the effect of a change in weights. The final rank of the papers is therefore obtained by partitioning the two-dimensional space through linear or higher order curves. The procedure is intuitive and versatile since it allows, after adjusting few parameters, an automatic and calibrated assessment at the level of the subfield. The derived evaluation is homogeneous among different scientific domains and can be used to address the quality of research at the departmental (or higher) levels of aggregation. We apply this method, that is designed to be feasible on a scale typical of a national evaluation exercise and to be effective in terms of cost and time, to some instances of the Thomson Reuters Web of Science database and discuss the results in view of what was done recently in Italy for the Evaluation of Research Quality exercise 2004–2010. We show how the main limitations of the bibliometric methodology used in that context can be easily overcome.

Suggested Citation

  • Alberto Anfossi & Alberto Ciolfi & Filippo Costa & Giorgio Parisi & Sergio Benedetto, 2016. "Large-scale assessment of research outputs through a weighted combination of bibliometric indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 107(2), pages 671-683, May.
    • Handle: RePEc:spr:scient:v:107:y:2016:i:2:d:10.1007_s11192-016-1882-9
    DOI: 10.1007/s11192-016-1882-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-016-1882-9
    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/s11192-016-1882-9?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. Katharine Barker, 2007. "The UK Research Assessment Exercise: the evolution of a national research evaluation system," Research Evaluation, Oxford University Press, vol. 16(1), pages 3-12, March.
    2. Alessio Ancaiani & Alberto F. Anfossi & Anna Barbara & Sergio Benedetto & Brigida Blasi & Valentina Carletti & Tindaro Cicero & Alberto Ciolfi & Filippo Costa & Giovanna Colizza & Marco Costantini & F, 2015. "Evaluating scientific research in Italy: The 2004–10 research evaluation exercise," Research Evaluation, Oxford University Press, vol. 24(3), pages 242-255.
    3. Johan Bollen & Herbert Van de Sompel & Aric Hagberg & Ryan Chute, 2009. "A Principal Component Analysis of 39 Scientific Impact Measures," PLOS ONE, Public Library of Science, vol. 4(6), pages 1-11, June.
    4. Linda Butler, 2003. "Modifying publication practices in response to funding formulas," Research Evaluation, Oxford University Press, vol. 12(1), pages 39-46, April.
    5. Franceschet, Massimo & Costantini, Antonio, 2010. "The effect of scholar collaboration on impact and quality of academic papers," Journal of Informetrics, Elsevier, vol. 4(4), pages 540-553.
    6. Wolfgang Glänzel & Bart Thijs, 2004. "The influence of author self-citations on bibliometric macro indicators," Scientometrics, Springer;Akadémiai Kiadó, vol. 59(3), pages 281-310, March.
    7. Emanuela Reale & Anna Barbara & Antonio Costantini, 2007. "Peer review for the evaluation of academic research: lessons from the Italian experience," Research Evaluation, Oxford University Press, vol. 16(3), pages 216-228, September.
    8. Adam Eyre-Walker & Nina Stoletzki, 2013. "The Assessment of Science: The Relative Merits of Post-Publication Review, the Impact Factor, and the Number of Citations," PLOS Biology, Public Library of Science, vol. 11(10), pages 1-8, October.
    9. Dag W Aksnes & Randi Elisabeth Taxt, 2004. "Peer reviews and bibliometric indicators: a comparative study at a Norwegian university," Research Evaluation, Oxford University Press, vol. 13(1), pages 33-41, April.
    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. Daniele Checchi & Alberto Ciolfi & Gianni De Fraja & Irene Mazzotta & Stefano Verzillo, 2021. "Have you Read This? An Empirical Comparison of the British REF Peer Review and the Italian VQR Bibliometric Algorithm," Economica, London School of Economics and Political Science, vol. 88(352), pages 1107-1129, October.
    2. Cappelletti-Montano, Beniamino & Columbu, Silvia & Montaldo, Stefano & Musio, Monica, 2022. "Interpreting the outcomes of research assessments: A geometrical approach," Journal of Informetrics, Elsevier, vol. 16(1).
    3. Franceschini, Fiorenzo & Maisano, Domenico, 2017. "Critical remarks on the Italian research assessment exercise VQR 2011–2014," Journal of Informetrics, Elsevier, vol. 11(2), pages 337-357.
    4. Giovanni Abramo & Ciriaco Andrea D’Angelo, 2016. "Refrain from adopting the combination of citation and journal metrics to grade publications, as used in the Italian national research assessment exercise (VQR 2011–2014)," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 2053-2065, December.
    5. Tindaro Cicero & Marco Malgarini, 2020. "On the use of journal classification in social sciences and humanities: evidence from an Italian database," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1689-1708, November.
    6. Abramo, Giovanni & Aksnes, Dag W. & D’Angelo, Ciriaco Andrea, 2020. "Comparison of research performance of Italian and Norwegian professors and universities," Journal of Informetrics, Elsevier, vol. 14(2).
    7. Andrea Bonaccorsi & Brigida Blasi & Carmela Anna Nappi & Sandra Romagnosi, 2022. "Quality of research as source and signal: revisiting the valorization process beyond substitution vs complementarity," The Journal of Technology Transfer, Springer, vol. 47(2), pages 407-434, April.
    8. Sandra Rousseau & Ronald Rousseau, 2021. "Bibliometric Techniques And Their Use In Business And Economics Research," Journal of Economic Surveys, Wiley Blackwell, vol. 35(5), pages 1428-1451, December.
    9. Abramo, Giovanni, 2018. "Revisiting the scientometric conceptualization of impact and its measurement," Journal of Informetrics, Elsevier, vol. 12(3), pages 590-597.

    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. Robert A. Buckle & John Creedy, 2022. "Methods to evaluate institutional responses to performance‐based research funding systems," Australian Economic Papers, Wiley Blackwell, vol. 61(3), pages 615-634, September.
    2. Dag W. Aksnes & Liv Langfeldt & Paul Wouters, 2019. "Citations, Citation Indicators, and Research Quality: An Overview of Basic Concepts and Theories," SAGE Open, , vol. 9(1), pages 21582440198, February.
    3. Franceschet, Massimo & Costantini, Antonio, 2011. "The first Italian research assessment exercise: A bibliometric perspective," Journal of Informetrics, Elsevier, vol. 5(2), pages 275-291.
    4. Buckle, Robert A. & Creedy, John & Ball, Ashley, 2020. "A Schumpeterian Gale: Using Longitudinal Data to Evaluate Responses to Performance-Based Research Funding Systems," Working Paper Series 21104, Victoria University of Wellington, Chair in Public Finance.
    5. Buckle, Robert A. & Creedy, John & Ball, Ashley, 2020. "A Schumpeterian Gale: Using Longitudinal Data to Evaluate Responses to Performance-Based Research Funding Systems," Working Paper Series 9447, Victoria University of Wellington, Chair in Public Finance.
    6. Rebora, Gianfranco & Turri, Matteo, 2013. "The UK and Italian research assessment exercises face to face," Research Policy, Elsevier, vol. 42(9), pages 1657-1666.
    7. Carmen Osuna & Laura Cruz Castro & Luis Sanz Menéndez, 2010. "Knocking down some Assumptions about the Effects of Evaluation Systems on Publications," Working Papers 1010, Instituto de Políticas y Bienes Públicos (IPP), CSIC.
    8. Alberto Baccini & Giuseppe De Nicolao, 2016. "Do they agree? Bibliometric evaluation versus informed peer review in the Italian research assessment exercise," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(3), pages 1651-1671, September.
    9. Bar-Ilan, Judit, 2008. "Informetrics at the beginning of the 21st century—A review," Journal of Informetrics, Elsevier, vol. 2(1), pages 1-52.
    10. Aleksander Galas & Aleksandra Pilat & Matilde Leonardi & Beata Tobiasz-Adamczyk, 2018. "Research Project Evaluation—Learnings from the PATHWAYS Project Experience," IJERPH, MDPI, vol. 15(6), pages 1-18, May.
    11. Jacques Wainer & Paula Vieira, 2013. "Correlations between bibliometrics and peer evaluation for all disciplines: the evaluation of Brazilian scientists," Scientometrics, Springer;Akadémiai Kiadó, vol. 96(2), pages 395-410, August.
    12. Giovanni Abramo & Ciriaco Andrea D’Angelo & Emanuela Reale, 2019. "Peer review versus bibliometrics: Which method better predicts the scholarly impact of publications?," Scientometrics, Springer;Akadémiai Kiadó, vol. 121(1), pages 537-554, October.
    13. Waltman, Ludo, 2016. "A review of the literature on citation impact indicators," Journal of Informetrics, Elsevier, vol. 10(2), pages 365-391.
    14. Ehsan Mohammadi & Mike Thelwall, 2013. "Assessing non-standard article impact using F1000 labels," Scientometrics, Springer;Akadémiai Kiadó, vol. 97(2), pages 383-395, November.
    15. Andersen, Jens Peter, 2017. "An empirical and theoretical critique of the Euclidean index," Journal of Informetrics, Elsevier, vol. 11(2), pages 455-465.
    16. Vieira, Elizabeth S. & Cabral, José A.S. & Gomes, José A.N.F., 2014. "How good is a model based on bibliometric indicators in predicting the final decisions made by peers?," Journal of Informetrics, Elsevier, vol. 8(2), pages 390-405.
    17. Li, Jiang & Sanderson, Mark & Willett, Peter & Norris, Michael & Oppenheim, Charles, 2010. "Ranking of library and information science researchers: Comparison of data sources for correlating citation data, and expert judgments," Journal of Informetrics, Elsevier, vol. 4(4), pages 554-563.
    18. Giovanni Abramo & Ciriaco Andrea D'Angelo, 2015. "The VQR, Italy's second national research assessment: Methodological failures and ranking distortions," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 66(11), pages 2202-2214, November.
    19. Tombazos, Christis G. & Dobra, Matthew, 2014. "Formulating research policy on expert advice," European Economic Review, Elsevier, vol. 72(C), pages 166-181.
    20. Thiago H. P. Silva & Alberto H. F. Laender & Clodoveu A. Davis & Ana Paula Couto Silva & Mirella M. Moro, 2017. "A profile analysis of the top Brazilian Computer Science graduate programs," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(1), pages 237-255, October.

    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:107:y:2016:i:2:d:10.1007_s11192-016-1882-9. 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.