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Benchmarking research performance at the university level with information theoretic measures

Author

Listed:
  • J. A. García

    (Universidad de Granada)

  • Rosa Rodriguez-Sánchez

    (Universidad de Granada)

  • J. Fdez-Valdivia

    (Universidad de Granada)

  • Nicolas Robinson-García

    (Universidad de Granada)

  • Daniel Torres-Salinas

    (Universidad de Navarra)

Abstract

This paper presents a new method for comparing universities based on information theoretic measures. The research output of each academic institution is represented statistically by an impact-factor histogram. To this aim, for each academic institution we compute the probability of occurrence of a publication with impact factor in different intervals. Assuming the probabilities associated with a pair of academic institutions our objective is to measure the Information Gain between them. To do so, we develop an axiomatic characterization of relative information for predicting institution-institution dissimilarity. We use the Spanish university system as our scenario to test the proposed methodology for benchmarking three universities with the rest as a case study. For each case we use different scientific fields such as Information and Communication Technologies, Medicine and Pharmacy, and Economics and Business as we believe comparisons must take into account their disciplinary context. Finally we validate the Information Gain values obtained for each case with previous studies.

Suggested Citation

  • J. A. García & Rosa Rodriguez-Sánchez & J. Fdez-Valdivia & Nicolas Robinson-García & Daniel Torres-Salinas, 2013. "Benchmarking research performance at the university level with information theoretic measures," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(1), pages 435-452, April.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:1:d:10.1007_s11192-012-0854-y
    DOI: 10.1007/s11192-012-0854-y
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    References listed on IDEAS

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    Cited by:

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    2. Johannes Sorz & Wolfgang Glänzel & Ursula Ulrych & Christian Gumpenberger & Juan Gorraiz, 2020. "Research strengths identified by esteem and bibliometric indicators: a case study at the University of Vienna," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(2), pages 1095-1116, November.

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