Skip to main content

WURS: a simulation software for university rankings—software review


The reproducibility of the results of university ranking systems and the problem of how to climb in rankings have been discussed in the literature for a long time. We created the simulation software WURS which can be a useful tool to shed light on these discussions. In this paper, we present the features and usage of WURS.

This is a preview of subscription content, access via your institution.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9


  • Adler, N. J., & Harzing, A. W. (2009). When knowledge wins: Transcending the sense and nonsense of academic rankings. Academy of Management Learning & Education,8(1), 72–95.

    Article  Google Scholar 

  • ARWU. (2018). Academic ranking of world universities. Accessed July 19, 2019, from

  • Bollen, K., Cacioppo, J. T., Kaplan, R., Krosnick, J., & Olds, J. L. (2015). Social, behavioral, and economic sciences perspectives on robust and reliable science. Report of the Subcommittee on Replicability in Science Advisory Committee to the National Science Foundation Directorate for Social, Behavioral, and Economic Sciences. Accessed July 19, 2019, from

  • Bougnol, M. L., & Dula, J. H. (2013). A mathematical model to optimize decisions to impact multi-attribute rankings. Scientometrics,95, 785–796.

    Article  Google Scholar 

  • Bowman, N. A., & Bastedo, M. N. (2011). An anchoring effect on assessments of institutional reputation. Higher Education,61(4), 431–444.

    Article  Google Scholar 

  • Cano, A. F., Marin, E. C., Rodrigues, M. T., & Ruiz, M. V. (2018). Questioning the Shanghai Ranking methodology as a tool for the evaluation of universities: An integrative review. Scientometrics,116(3), 2069–2083.

    Article  Google Scholar 

  • Daraio, C., Bonaccorsi, A., & Simar, L. (2015). Rankings and university performance: A conditional multidimensional approach. European Journal of Operational Research,244(3), 918–930.

    Article  Google Scholar 

  • Dill, D., & Soo, M. (2005). Academic quality, league tables, and public policy: A cross-national analysis of university ranking systems. Higher Education,49(4), 495–533.

    Article  Google Scholar 

  • Docampo, D. (2013). Reproducibility of the Shanghai academic ranking of world universities results. Scientometrics,94(2), 567–587.

    Article  Google Scholar 

  • Florian, R. V. (2007). Irreproducibility of the results of the Shangai academic ranking of world universities. Scientometrics,72(1), 25–32.

    Article  Google Scholar 

  • Goodman, S. N., Fanelli, D., & Ioannidis, J. P. A. (2016). What does research reproducibility mean? Science Translational Medicine,8(341), 12.

    Article  Google Scholar 

  • Hazelkorn, E. (2008). Learning to live with league tables and ranking: The experience of institutional leaders. Higher Education Policy,21, 193–215.

    Article  Google Scholar 

  • InCites. (2013). Thomson Reuters. New address: Clarivate Analytics.

  • Ioannidis, J. P. A., Patsopoulos, N. A., Kavvoura, F. K., Tatsioni, A., Evangelou, E., & Kouri, I. (2007). International ranking systems for universities and institutions: A critical appraisal. BioMed Central Medicine,5, 30.

    Google Scholar 

  • Johnes, J. (2018). University rankings: What do they really show? Scientometrics,72(1), 25–32.

    Google Scholar 

  • Longden, B. (2011). Ranking indicators and weights. In J. C. Shin, R. K. Toutkoushian, & U. Teichler (Eds.), University rankings: Theoretical basis, methodology and impacts on global higher education (pp. 73–104). Dordrecht: Springer.

    Chapter  Google Scholar 

  • Marginson, S., & Wende, V. D. M. (2007). To rank or to be ranked: The impact of global rankings in higher education. Journal of Studies in International Education,11(3–4), 306–329.

    Article  Google Scholar 

  • Matthews, A. P. (2012). South African universities in world rankings. Scientometrics,92(3), 675–695.

    Article  Google Scholar 

  • Peng, R. D. (2011). Reproducible research in computational science. Science,334, 1226–1227.

    Article  Google Scholar 

  • QS. (2019). QS world university rankings. Accessed July 19, 2019, from

  • Shehatta, I., & Mahmood, K. (2016). Correlation among top 100 universities in the major six global rankings: Policy implications. Scientometrics,109(2), 1231–1254.

    Article  Google Scholar 

  • THE. (2019). THE world university rankings. Accessed July 19, 2019, from

  • Tofallis, C. (2012). A different approach to university rankings. Higher Education,63(1), 1–18.

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations


Corresponding author

Correspondence to Enis Siniksaran.

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Siniksaran, E., Satman, M.H. WURS: a simulation software for university rankings—software review. Scientometrics 122, 701–717 (2020).

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI:


  • University rankings
  • Simulation
  • THE
  • QS
  • ARWU
  • WURS