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What do global university rankings really measure? The search for the X factor and the X entity

Abstract

Most academic rankings attempt to measure the quality of university education and research. However, previous studies that examine the most influential rankings conclude that the variables they use could be an epiphenomenon of an X factor that has little to do with quality. The aim of this study is to investigate the existence of this hidden factor or profile in the two most influential global university rankings in the world: the Academic Ranking of World Universities (ARWU) of the University of Shanghai Jiao Tong, and the Times Higher Education (THE) ranking. Results support the existence of an underlying entity profile, characterized by institutions normally from the US that enjoy a high reputation. Results also support the idea that rankings lack the capacity to assess university quality in all its complexity, and two strategies are suggested in relation to the vicious circle created between institutional reputation and rankings.

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Notes

  1. One exception is the study by Li et al. (2011a), which focuses on the effects of country and language.

  2. This principle is based on the functioning of the memory of individuals and the social processes that occur in science.

  3. As the sample is reduced, the variance of the variables increases and the t statistics associated with its parameters decrease. This problem occurs in Model 3 (n = 181) and particularly in Model 2 (n = 100).

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Appendices

Appendix 1. Variables studied as possible X factors and their measures

University in U.S. 1 if the university is in the U.S., 0 if it is not.

English-speaking country (excluded U.S.). 1 if the official national language is English, 0 if it is not or the university is in the U.S.

Size (students). Variable measured on a 4-point scale, where 1 = small, 2 = medium-sized, 3 = large y 4 = very large. Taken from the Quacquarelli Symonds database. See description at www.topuniversities.com.

Age. Variable measured on a 5-point scale: 1-New (<10 years), 2-Young (<25 years), 3-Established (<50 years), 4-Mature (<100 years), 5-Historic (>100 years). Variable taken from the Quacquarelli Symonds database.

Annual income. Variable taken from the ARWU database. Coded in the form of a ranking, so that a smaller number indicates larger income.

Scope (number of disciplines). Variable measured on a 4-point scale, ranging from 1 = very few subjects offered to 4 = a wide variety of subjects. Variable taken from the Quacquarelli Symonds database.

Activity in hard sciences. This variable measures whether the university carries out activities in hard sciences. It is measured using a dichotomous variable with a value of 1 if the university published papers on Nature and Science between 2007 and 2011, and 0 if not (data taken from the ARWU database).

Orientation towards research. Variable taken from the Quacquarelli Symonds database. Coded in the form of a score from faculty to student ratio. See an explanation at: http://www.iu.qs.com/university-rankings/rankings-indicators/methodology-faculty-student. Student staff ratio is commonly used as a measure of teaching quality (Longden 2011). According to literature, a lower academic staff to student ratio indicates that the university is more teaching oriented than research oriented (Li et al. 2011b).

Reputation. Variable ranging from 0 = no reputation to 100 = the highest reputation among academics. Taken from the “Quacquarelli Symonds Global Academic Survey”, using a sample of 34,000 academics from a broad, balanced variety of subjects and countries. See an explanation at: http://www.iu.qs.com/university-rankings/world-university-rankings/2011-academic-survey-responses/.

Appendix 2. Correlations between the X factors and the affected THE indicators

See Table 5.

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Safón, V. What do global university rankings really measure? The search for the X factor and the X entity. Scientometrics 97, 223–244 (2013). https://doi.org/10.1007/s11192-013-0986-8

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Keywords

  • Rankings
  • Reputation
  • Universities
  • Factor analysis
  • Multivariate regression

Mathematics Subject Classification

  • 62J05
  • 91C15
  • 97B99

JEL Classification

  • L14
  • L25