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Mean value and volume-based sensitivity analysis for Olympic rankings

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  • Sitarz, Sebastian

Abstract

This article describes two methods of creating Olympic rankings based on number of medals won. One method is based on the weighted mean value, which we will show is equivalent to the compromise programming known in Multi-Criteria Decision Analysis (MCDM). The other method uses volume-based sensitivity analysis. Both methods presented in this paper can also be used to construct rankings that include more than just the three top positions.

Suggested Citation

  • Sitarz, Sebastian, 2012. "Mean value and volume-based sensitivity analysis for Olympic rankings," European Journal of Operational Research, Elsevier, vol. 216(1), pages 232-238.
    • Handle: RePEc:eee:ejores:v:216:y:2012:i:1:p:232-238
    DOI: 10.1016/j.ejor.2011.07.010
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    References listed on IDEAS

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    1. Lahdelma, Risto & Hokkanen, Joonas & Salminen, Pekka, 1998. "SMAA - Stochastic multiobjective acceptability analysis," European Journal of Operational Research, Elsevier, vol. 106(1), pages 137-143, April.
    2. Lins, Marcos P. Estellita & Gomes, Eliane G. & Soares de Mello, Joao Carlos C. B. & Soares de Mello, Adelino Jose R., 2003. "Olympic ranking based on a zero sum gains DEA model," European Journal of Operational Research, Elsevier, vol. 148(2), pages 312-322, July.
    3. Wu, Jie & Liang, Liang & Chen, Yao, 2009. "DEA game cross-efficiency approach to Olympic rankings," Omega, Elsevier, vol. 37(4), pages 909-918, August.
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    Cited by:

    1. Sebastian Sitarz, 2013. "Compromise programming with Tchebycheff norm for discrete stochastic orders," Annals of Operations Research, Springer, vol. 211(1), pages 433-446, December.
    2. Hladík, Milan & Sitarz, Sebastian, 2013. "Maximal and supremal tolerances in multiobjective linear programming," European Journal of Operational Research, Elsevier, vol. 228(1), pages 93-101.
    3. Baker, Rose D. & McHale, Ian G., 2014. "A dynamic paired comparisons model: Who is the greatest tennis player?," European Journal of Operational Research, Elsevier, vol. 236(2), pages 677-684.
    4. Pedro Garcia‐del‐Barrio & Carlos Gomez‐Gonzalez & José Manuel Sánchez‐Santos, 2020. "Popularity and Visibility Appraisals for Computing Olympic Medal Rankings," Social Science Quarterly, Southwestern Social Science Association, vol. 101(5), pages 2137-2157, September.
    5. Mohammad Izadikhah & Reza Farzipoor Saen, 2019. "Solving voting system by data envelopment analysis for assessing sustainability of suppliers," Group Decision and Negotiation, Springer, vol. 28(3), pages 641-669, June.
    6. Li, Yongjun & Lei, Xiyang & Dai, Qianzhi & Liang, Liang, 2015. "Performance evaluation of participating nations at the 2012 London Summer Olympics by a two-stage data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 243(3), pages 964-973.
    7. Podinovski, Vladislav V., 2012. "Sensitivity analysis for choice problems with partial preference relations," European Journal of Operational Research, Elsevier, vol. 221(1), pages 198-204.

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