This paper proposes a critical analysis of the “Academic Ranking of World Universities”, published every year by the Institute of Higher Education of the Jiao Tong University in Shanghai and more commonly known as the Shanghai ranking. After having recalled how the ranking is built, we first discuss the relevance of the criteria and then analyze the proposed aggregation method. Our analysis uses tools and concepts from Multiple Criteria Decision Making (MCDM). Our main conclusions are that the criteria that are used are not relevant, that the aggregation methodology is plagued by a number of major problems and that the whole exercise suffers from an insufficient attention paid to fundamental structuring issues. Hence, our view is that the Shanghai ranking, in spite of the media coverage it receives, does not qualify as a useful and pertinent tool to discuss the “quality” of academic institutions, let alone to guide the choice of students and family or to promote reforms of higher education systems. We outline the type of work that should be undertaken to offer sound alternatives to the Shanghai ranking.
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Since then, the authors of the Shanghai ranking have also produced, starting in 2007, a ranking of institutions distinguishing 5 different fields within Science, see http://www.arwu.org/ARWU-FIELD2008.htm. Since the methodology for these “field rankings” is quite similar to the one used for the “global ranking” analyzed in this paper, we will not further analyze them here.
Furthermore, several special issues of the journal Higher Education in Europe have been devoted to the debate around university rankings
Letter dated 5 July 2007, our translation from French, source http://www.elysee.fr/, last accessed 18 September 2009. Unless otherwise stated, all URL mentioned below have been accessed at this date.
See http://www.arwu.org/rank2008/ARWU2008Methodology(EN).htm. The 2009 edition of the ranking is scheduled to be released in November 2009.
We will often simply refer to them in this paper as “the authors of the ranking”.
In ARWU (2003–2009), the authors of the ranking say that this number was obtained for “institutions in USA, UK, France, Japan, Italy, China, Australia, Netherlands, Sweden, Switzerland, Belgium, South Korea, Czech, Slovenia, New Zealand, etc.”. We do not know if this means that this number was obtained for all institutions in these countries and only for them.
More precisely, they mention in ARWU (2003–2009) that this number was obtained “from national agencies such as National Ministry of Education, National Bureau of Statistics, National Association of Universities and Colleges, National Rector’s Conference”.
Awarded every year since 1966 by the Association for Computing Machinery, see http://www.awards.acm.org/homepage.cfm?awd=140.
Awarded every year since 1898 by the Astronomical Society of the Pacific, see http://www.phys-astro.sonoma.edu/bruceMedalists.
Let us mention here several other problems with the criteria used by the authors of the ranking. First they have chosen to publish their ranking on an annual basis. This is probably a good choice if what is thought is media coverage. However, given the pace of most research programs, we cannot find any serious justification for such a periodicity. As observed in Gingras (2008), the ability of a university to produce excellent research, is not likely to change much from one year to another. Therefore, changes from one edition of the ranking to the next one are more likely to reflect random fluctuations than real changes. This is all the more true that several important points in the methodology and the criteria have changed over the years (Saisana and D’Hombres (2008), offer an overview of these changes). Second, the choice of an adequate period of reference to assess the “academic performance” of an institution is a difficult question. It has been implicitly answered by the authors of the ranking in a rather strange way. Lacking any clear analysis of the problem, they mix up in the model several very different time periods: one century for criteria ALU and AWA, 20 years for criterion HiCi, 5 years for criterion N&S, and 1 year for criterion PUB. There may be a rationale behind these choices but it is not made explicit by the authors of the ranking. As observed in van Raan (2006a, b), “academic performance” can mean two very different things: the prestige of an institution based on its past performances and its present capacity to attract excellent researchers. These two elements should not be confused. Third, five of the six criteria used by the authors of the ranking are counting criteria (prizes and medals, highly cited researchers, papers in N&S, papers indexed by Thomson Scientific). Hence, it should be no surprise that all these criteria are strongly linked to the size of the institution. As Zitt and Filliatreau (2006) have forcefully shown, using so many criteria linked to the size of the institution is the sign that big is made beautiful. Hence, the fact that criteria are highly correlated should not be a surprise. Although the authors of the ranking view this fact as a strong point of their approach, it is more likely to simply reflect the impact of size effects. Fourth, Since the criteria used by the authors of the ranking are linked with “academic excellence”, we should expect that they are poorly discriminatory between institutions that are not ranked among the top ones. A simple statistical analysis reveals that this is indeed the case, see Billaut et al. (2009).
Keeney (1992, p. 147) calls this the “most common critical mistake”.
Let us remark that we disagree here with Principle 8 in International Ranking Expert Group (2006): a production process, whether it is or not scientific, cannot be analyzed without explicitly considering outputs and inputs.
During the preparation of this text, a European research consortium (CHERPA) won a call for tenders launched by the European Union on the question of university rankings. We wish much success to this international consortium and we, of course, hope that they will find parts of this text useful to them.
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We wish to thank Florence Audier, Ghislaine Filliatreau, Thierry Marchant, Michel Zitt, and an anonymous referee for their useful comments on an earlier draft of this text.
This paper is an abridged version of Billaut et al. (2009)
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Billaut, J., Bouyssou, D. & Vincke, P. Should you believe in the Shanghai ranking?. Scientometrics 84, 237–263 (2010). https://doi.org/10.1007/s11192-009-0115-x
- Shanghai ranking
- Multiple criteria decision analysis
- Evaluation models
- Higher education