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  • × author_ss:"Dobrota, M."
  1. Dobrota, M.; Dobrota, M.: ARWU ranking uncertainty and sensitivity : what if the award factor was Excluded? (2016) 0.02
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    Abstract
    The Academic Ranking of World Universities (ARWU) uses six university performance indicators, including "Alumni" and "Awards"-the number of alumni and staff winning Nobel Prizes and Fields Medals. These two indicators raised doubts about the reliability of this ranking method because they are difficult to cope with. Recently, a newsletter was published featuring a reduced ARWU ranking list, leaving out Nobel Prize and Fields Medal indicators: the Alternative Ranking (Excluding Award Factor). We used uncertainty and sensitivity analyses to examine and compare the stability and confidence of the official ARWU ranking and the Alternative Ranking. The results indicate that if the ARWU ranking is reduced to the 4-indicator Alternative Ranking, it shows greater certainty and stability in ranking universities.
    Date
    22. 1.2016 14:40:53
    Type
    a
  2. Dobrota, M.; Bulajic, M.; Bornmann, L.; Jeremic, V.: ¬A new approach to the QS university ranking using the composite I-distance indicator : uncertainty and sensitivity analyses (2016) 0.00
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    Abstract
    Some major concerns of universities are to provide quality in higher education and enhance global competitiveness, thus ensuring a high global rank and an excellent performance evaluation. This article examines the Quacquarelli Symonds (QS) World University Ranking methodology, pointing to a drawback of using subjective, possibly biased, weightings to build a composite indicator (QS scores). We propose an alternative approach to creating QS scores, which is referred to as the composite I-distance indicator (CIDI) methodology. The main contribution is the proposal of a composite indicator weights correction based on the CIDI methodology. It leads to the improved stability and reduced uncertainty of the QS ranking system. The CIDI methodology is also applicable to other university rankings by proposing a specific statistical approach to creating a composite indicator.
    Type
    a