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A fuzzy-based scoring rule for author ranking

Author

Listed:
  • Marta Cardin

    () (Department of Economics, Ca� Foscari University of Venice.)

  • Marco Corazza

    () (Department of Economics, Ca� Foscari University of Venice; Advanced School of Economics in Venice.)

  • Stefania Funari

    () (Department of Management, Ca� Foscari University of Venice.)

  • Silvio Giove

    () (Department of Economics, Ca� Foscari University of Venice.)

Abstract

The measurement of the quality of research has reached nowadays an increasing interest not only for scientific reasons but also for the critical problem of researchers' ranking, due to the lack of grant assignments. The most commonly used approach is based on the so-called $h$-index, even if the current literature debated a lot about its pros and cons. This paper, after a brief review of the $h$-index and of alternative models, focuses on the characterization and the implementation of a modified scoring rule approach by means of a fuzzy inference system a l� Sugeno.

Suggested Citation

  • Marta Cardin & Marco Corazza & Stefania Funari & Silvio Giove, 2011. "A fuzzy-based scoring rule for author ranking," Working Papers 2011_11, Department of Economics, University of Venice "Ca' Foscari".
  • Handle: RePEc:ven:wpaper:2011_11
    as

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    References listed on IDEAS

    as
    1. Denis Bouyssou & Thierry Marchant, 2011. "Ranking scientists and departments in a consistent manner," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 62(9), pages 1761-1769, September.
    2. Costas, Rodrigo & Bordons, María, 2007. "The h-index: Advantages, limitations and its relation with other bibliometric indicators at the micro level," Journal of Informetrics, Elsevier, vol. 1(3), pages 193-203.
    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. Alonso, S. & Cabrerizo, F.J. & Herrera-Viedma, E. & Herrera, F., 2009. "h-Index: A review focused in its variants, computation and standardization for different scientific fields," Journal of Informetrics, Elsevier, vol. 3(4), pages 273-289.
    5. Bouyssou, D. & Marchant, T., 2010. "Consistent bibliometric rankings of authors and of journals," Journal of Informetrics, Elsevier, vol. 4(3), pages 365-378.
    6. Cabrerizo, F.J. & Alonso, S. & Herrera-Viedma, E. & Herrera, F., 2010. "q2-Index: Quantitative and qualitative evaluation based on the number and impact of papers in the Hirsch core," Journal of Informetrics, Elsevier, vol. 4(1), pages 23-28.
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    Cited by:

    1. Muhammad Imtiaz Subhani & Amber Osman & Syed Akif Hasan & Muhammad Saad & Sabeen Mir, 2013. "Formulation of Advanced H-Index: The S-Index," South Asian Journal of Management Sciences (SAJMS), Iqra University, Iqra University, vol. 7(2), pages 63-70, Fall.

    More about this item

    Keywords

    Research evaluation; bibliometrics; author ranking; $h$-index; scoring rules; fuzzy inference system.;

    JEL classification:

    • C02 - Mathematical and Quantitative Methods - - General - - - Mathematical Economics
    • I23 - Health, Education, and Welfare - - Education - - - Higher Education; Research Institutions
    • Z19 - Other Special Topics - - Cultural Economics - - - Other

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