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

Author

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  • M. L. Bougnol

    (Jacksonville University)

  • J. H. Dulá

    (Virginia Commonwealth University)

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.

Suggested Citation

  • M. L. Bougnol & J. H. Dulá, 2013. "A mathematical model to optimize decisions to impact multi-attribute rankings," Scientometrics, Springer;Akadémiai Kiadó, vol. 95(2), pages 785-796, May.
    • Handle: RePEc:spr:scient:v:95:y:2013:i:2:d:10.1007_s11192-012-0844-0
    DOI: 10.1007/s11192-012-0844-0
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    References listed on IDEAS

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    1. Jean-Charles Billaut & Denis Bouyssou & Philippe Vincke, 2010. "Should you believe in the Shanghai ranking?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 237-263, July.
    2. Jean-Charles Billaut & Denis Bouyssou & Philippe Vincke, 2010. "Should you believe in the Shanghai ranking?," Scientometrics, Springer;Akadémiai Kiadó, vol. 84(1), pages 237-263, July.
    3. repec:dau:papers:123456789/2947 is not listed on IDEAS
    4. Ludo Waltman & Clara Calero-Medina & Joost Kosten & Ed C.M. Noyons & Robert J.W. Tijssen & Nees Jan Eck & Thed N. Leeuwen & Anthony F.J. Raan & Martijn S. Visser & Paul Wouters, 2012. "The Leiden ranking 2011/2012: Data collection, indicators, and interpretation," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 63(12), pages 2419-2432, December.
    5. Jill Johnes, 2006. "Measuring Efficiency: A Comparison of Multilevel Modelling and Data Envelopment Analysis in the Context of Higher Education," Bulletin of Economic Research, Wiley Blackwell, vol. 58(2), pages 75-104, April.
    6. Marie-Laure Bougnol & José Dulá, 2006. "Validating DEA as a ranking tool: An application of DEA to assess performance in higher education," Annals of Operations Research, Springer, vol. 145(1), pages 339-365, July.
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    Cited by:

    1. A. Ferrer-Sapena & E. Erdogan & E Jiménez-Fernández & E. A. Sánchez-Pérez & F. Peset, 2020. "Self-defined information indices: application to the case of university rankings," Scientometrics, Springer;Akadémiai Kiadó, vol. 124(3), pages 2443-2456, September.
    2. Enis Siniksaran & M. Hakan Satman, 2020. "WURS: a simulation software for university rankings—software review," Scientometrics, Springer;Akadémiai Kiadó, vol. 122(1), pages 701-717, January.

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