Skip to main content
SpringerLink
Log in

A mathematical model to optimize decisions to impact multi-attribute rankings

  • Published:
Scientometrics Aims and scope Submit manuscript

Abstract

We formulate the problem of how to climb in multi-attribute rankings with known weights using mathematical optimization. A model is derived based on familiar practices used in rankings in higher education where several attributes are combined using known weights to obtain a score. The method applies in any situation where multiple attributes are used to rank entities. We invoke several assumptions such as independence among attributes and that administrators can affect the values of some of the attributes and know the cost of doing so. Our results suggest that a strategy to advance in the rankings is to focus on modifying the value of fewer rather than more attributes. The model is generalized to allow for synergies and antagonisms among the attributes.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3

Similar content being viewed by others

References

  • Billaut, J. C., Bouyssou, D. & Vincke, P. (2010). Should you believe in the Shanghai ranking? Scientometrics, 84, 237–263.

    Article  Google Scholar 

  • Bougnol, M. L. & Dulá, J. H. (2006). Validating DEA as a ranking tool: an application of DEA to assess performance in higher education, Annals of Operations Research, 145(1), 339–365.

    Article  MathSciNet  MATH  Google Scholar 

  • Brooks, J. P. & Dulá, J. H. (2012) The L-1-norm best-fit hyperplane problem. Applied Mathematics Letters. Eprint available at: http://www.optimization-online.org/DB_HTML/2009/05/2291.html. doi:10.1016/j.aml.2012.03.031.

  • Capaldi, E. D., Lombardi J. V., Abbey C. W., & Craig, D. D. (2010). The Top American Research Universities, 2010 Annual Report, The Center for measuring university performance at Arizona State University.

  • Eckles, J. E. (2010). Evaluating the efficiency of top liberal arts colleges. Research in Higher Education, 51, 266–293.

    Article  Google Scholar 

  • Eff, E. A., Klein, C. C., Kyle, R. (2012). Identifying the best buys in US higher education. Research in Higher Education, in press. doi:10.1007/s11162−012−9259–2.

  • Gerst, A. (2003). Law school eyes US News ranks. The Chronicle of Higher Education.

  • Johnes, J. (2006). Measuring efficiency: a comparison of multilevel modelling and data envelopment analysis in the context of higher education. Bulletin of Economic Research, 58, 0307–3378.

    Article  MathSciNet  Google Scholar 

  • Kuah, C. T. & Wong, K. Y. (2011). Efficiency assessment of universities through data envelopment analysis. Procedia Computer Science, 3, 499–506.

    Article  Google Scholar 

  • Liu, N. C. & Cheng, Y. (2005). The Academic Ranking of World Universities Higher Education in Europe, 30, 127–136. doi:10.1080/03797720500260116.

    Article  Google Scholar 

  • Marciszewski, A. (2006). TU rises, OU drops in the latest rankings. Tulsa World (Tulsa, OK).

  • Masterson, K. (2010). Fund raising. The Chronicle of Higher Education.

  • Murty, K. G. (1985). Linear and combinatorial programming, Malabar: R. E. Krieger.

    MATH  Google Scholar 

  • O’Leary, J., Quacquarelli, N., & Ince, M. (2011). Top Universities Guide 2011, 5th revised and updated edition exclusively featuring the QS-World University Rankings, retrieved August 08, 2012. http://www.topuniversities.com/.

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

    Article  Google Scholar 

  • Van Der Werf, M. (2009). Researcher offers unusually candid description of university’s effort to rise in rankings. The Chronicle of Higher Education.

  • Waltman, L., Calero-Medina, C., Kosten, J., Noyons, E. C. M., Tijssen, R. J. W., Van Eck, N. J., Van Leeuwen, T. N., Van Raan, A. F. J., Visser, M. S., & Wouters, P. (2012). The Leiden Ranking 2011/2012: Data collection, indicators, and interpretation, submitted to Computer Science.

  • Woodbury, R. L. (2003). How to make your college no.1 in U.S. News and World Report... and lose your integrity in the process. Connection: The Journal of the New England Board Education, pp. 18–20.

Download references

Author information

Authors and Affiliations

  1. Jacksonville University, Jacksonville, FL, 32211, USA

    M. L. Bougnol

  2. Virginia Commonwealth University, Richmond, VA, 23284, USA

    J. H. Dulá

Authors
  1. M. L. Bougnol
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. J. H. Dulá
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to M. L. Bougnol.

Rights and permissions

Reprints and permissions

About this article

Cite this article

Bougnol, M.L., Dulá, J.H. A mathematical model to optimize decisions to impact multi-attribute rankings. Scientometrics 95, 785–796 (2013). https://doi.org/10.1007/s11192-012-0844-0

Download citation

  • Received:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11192-012-0844-0

Keywords

Search

Navigation