IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v322y2023i2d10.1007_s10479-022-05085-5.html
   My bibliography  Save this article

Multiobjective centralized DEA approach to Tokyo 2020 Olympic Games

Author

Listed:
  • Sebastián Lozano

    (Universidad de Sevilla)

  • Gabriel Villa

    (Universidad de Sevilla)

Abstract

There exist two types of Data Envelopment Analysis (DEA) approaches to the Olympic Games: conventional and fixed-sum outputs (FSO). The approach proposed in this paper belongs to the latter category as it takes into account the total number de medals of each type awarded. Imposing these constraints requires a centralized DEA perspective that projects all the countries simultaneously. In this paper, a multiobjective FSO approach is proposed, and the Weighted Tchebychef solution method is employed. This approach aims to set all output targets as close as possible to their ideal values. In order to choose between the alternative optima, a secondary goal has been considered that minimizes the sum of absolute changes in the number of medals, which also renders the computed targets to be as close to the observed values as possible. These targets represent the output levels that could be expected if all countries performed at their best level. For certain countries, the targets are higher than the actual number of medals won while, for other countries, these targets may be lower. The proposed approach has been applied to the results of the Tokyo 2020 Olympic Games and compared with both FSO and non-FSO DEA methods.

Suggested Citation

  • Sebastián Lozano & Gabriel Villa, 2023. "Multiobjective centralized DEA approach to Tokyo 2020 Olympic Games," Annals of Operations Research, Springer, vol. 322(2), pages 879-919, March.
    • Handle: RePEc:spr:annopr:v:322:y:2023:i:2:d:10.1007_s10479-022-05085-5
    DOI: 10.1007/s10479-022-05085-5
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-022-05085-5
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s10479-022-05085-5?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Pekka Korhonen & Sari Stenfors & Mikko Syrjänen, 2003. "Multiple Objective Approach as an Alternative to Radial Projection in DEA," Journal of Productivity Analysis, Springer, vol. 20(3), pages 305-321, November.
    2. Wu, Jie & Liang, Liang & Yang, Feng, 2009. "Achievement and benchmarking of countries at the Summer Olympics using cross efficiency evaluation method," European Journal of Operational Research, Elsevier, vol. 197(2), pages 722-730, September.
    3. Sekitani, Kazuyuki & Zhao, Yu, 2021. "Performance benchmarking of achievements in the Olympics: An application of Data Envelopment Analysis with restricted multipliers," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1202-1212.
    4. Li, Yongjun & Liu, Jin & Ang, Sheng & Yang, Feng, 2021. "Performance evaluation of two-stage network structures with fixed-sum outputs: An application to the 2018winter Olympic Games," Omega, Elsevier, vol. 102(C).
    5. Calzada-Infante, Laura & Lozano, Sebastián, 2016. "Analysing Olympic Games through dominance networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1215-1230.
    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. S Lozano & G Villa & F Guerrero & P Cortés, 2002. "Measuring the performance of nations at the Summer Olympics using data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 53(5), pages 501-511, May.
    8. Bouzidis, Thanasis & Karagiannis, Giannis, 2022. "An alternative ranking of DMUs performance for the ZSG-DEA model," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    9. Josef Jablonsky, 2018. "Ranking of countries in sporting events using two-stage data envelopment analysis models: a case of Summer Olympic Games 2016," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 951-966, December.
    10. Li, Yongjun & Liang, Liang & Chen, Yao & Morita, Hiroshi, 2008. "Models for measuring and benchmarking olympics achievements," Omega, Elsevier, vol. 36(6), pages 933-940, December.
    11. Juan Aparicio & José Ruiz & Inmaculada Sirvent, 2007. "Closest targets and minimum distance to the Pareto-efficient frontier in DEA," Journal of Productivity Analysis, Springer, vol. 28(3), pages 209-218, December.
    12. Gongbing Bi & Chenpeng Feng & Jingjing Ding & Liang Liang & Feng Chu, 2014. "The linear formulation of the ZSG-DEA models with different production technologies," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 65(8), pages 1202-1211, August.
    13. 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.
    14. Sebastian Lozano & Belarmino Adenso-Diaz, 2018. "Network DEA-based biobjective optimization of product flows in a supply chain," Annals of Operations Research, Springer, vol. 264(1), pages 307-323, May.
    15. Yang, Min & Li, Yong Jun & Liang, Liang, 2015. "A generalized equilibrium efficient frontier data envelopment analysis approach for evaluating DMUs with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 246(1), pages 209-217.
    16. Lozano, Sebastián & Khezri, Somayeh, 2021. "Network DEA smallest improvement approach," Omega, Elsevier, vol. 98(C).
    17. M P Estellita Lins & L Angulo-Meza & A C Moreira Da Silva, 2004. "A multi-objective approach to determine alternative targets in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1090-1101, October.
    18. D Zhang & X Li & W Meng & W Liu, 2009. "Measuring the performance of nations at the Olympic Games using DEA models with different preferences," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(7), pages 983-990, July.
    19. Alireza Amirteimoori & Simin Masrouri & Feng Yang & Sohrab Kordrostami, 2017. "Context-based competition strategy and performance analysis with fixed-sum outputs: an application to banking sector," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(11), pages 1461-1469, November.
    20. Despotis, Dimitris K. & Sotiros, Dimitris & Koronakos, Gregory, 2016. "A network DEA approach for series multi-stage processes," Omega, Elsevier, vol. 61(C), pages 35-48.
    21. Cooper, W.W. & Pastor, Jesus T. & Aparicio, Juan & Borras, Fernando, 2011. "Decomposing profit inefficiency in DEA through the weighted additive model," European Journal of Operational Research, Elsevier, vol. 212(2), pages 411-416, July.
    22. Xiyang Lei & Yongjun Li & Qiwei Xie & Liang Liang, 2015. "Measuring Olympics achievements based on a parallel DEA approach," Annals of Operations Research, Springer, vol. 226(1), pages 379-396, March.
    23. Yang, Feng & Wu, Desheng Dash & Liang, Liang & O'Neill, Liam, 2011. "Competition strategy and efficiency evaluation for decision making units with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 212(3), pages 560-569, August.
    24. Lozano, Sebastián, 2023. "Bargaining approach for efficiency assessment and target setting with fixed-sum variables," Omega, Elsevier, vol. 114(C).
    25. Sebastián Lozano & Narges Soltani & Akram Dehnokhalaji, 2020. "A compromise programming approach for target setting in DEA," Annals of Operations Research, Springer, vol. 288(1), pages 363-390, May.
    26. M. Flegl & L. A. Andrade, 2018. "Measuring countries’ performance at the Summer Olympic Games in Rio 2016," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 823-846, November.
    27. Trevor Collier & Andrew L. Johnson & John Ruggiero, 2011. "Measuring Technical Efficiency in Sports," Journal of Sports Economics, , vol. 12(6), pages 579-598, December.
    28. Rajiv D. Banker & Richard C. Morey, 1986. "Efficiency Analysis for Exogenously Fixed Inputs and Outputs," Operations Research, INFORMS, vol. 34(4), pages 513-521, August.
    29. Gutiérrez, Ester & Lozano, Sebastián, 2016. "Efficiency assessment and output maximization possibilities of European small and medium sized airports," Research in Transportation Economics, Elsevier, vol. 56(C), pages 3-14.
    30. Wu, Jie & Liang, Liang & Chen, Yao, 2009. "DEA game cross-efficiency approach to Olympic rankings," Omega, Elsevier, vol. 37(4), pages 909-918, August.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Alexandre de Cássio Rodrigues & Carlos Alberto Gonçalves & Tiago Silveira Gontijo, 2019. "A two-stage DEA model to evaluate the efficiency of countries at the Rio 2016 Olympic Games," Economics Bulletin, AccessEcon, vol. 39(2), pages 1538-1545.
    2. Li, Yongjun & Liu, Jin & Ang, Sheng & Yang, Feng, 2021. "Performance evaluation of two-stage network structures with fixed-sum outputs: An application to the 2018winter Olympic Games," Omega, Elsevier, vol. 102(C).
    3. Sekitani, Kazuyuki & Zhao, Yu, 2021. "Performance benchmarking of achievements in the Olympics: An application of Data Envelopment Analysis with restricted multipliers," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1202-1212.
    4. Lozano, Sebastián, 2023. "Bargaining approach for efficiency assessment and target setting with fixed-sum variables," Omega, Elsevier, vol. 114(C).
    5. Calzada-Infante, Laura & Lozano, Sebastián, 2016. "Analysing Olympic Games through dominance networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 462(C), pages 1215-1230.
    6. Bouzidis, Thanasis & Karagiannis, Giannis, 2022. "An alternative ranking of DMUs performance for the ZSG-DEA model," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    7. Thanasis Bouzidis & Giannis Karagiannis, 2021. "An Alternative Ranking of DMUs Performance for the ZGS-DEA Model," Discussion Paper Series 2021_12, Department of Economics, University of Macedonia, revised Oct 2021.
    8. 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.
    9. Josef Jablonsky, 2018. "Ranking of countries in sporting events using two-stage data envelopment analysis models: a case of Summer Olympic Games 2016," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(4), pages 951-966, December.
    10. 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.
    11. Villa, G. & Lozano, S., 2016. "Assessing the scoring efficiency of a football match," European Journal of Operational Research, Elsevier, vol. 255(2), pages 559-569.
    12. Xiyang Lei & Yongjun Li & Qiwei Xie & Liang Liang, 2015. "Measuring Olympics achievements based on a parallel DEA approach," Annals of Operations Research, Springer, vol. 226(1), pages 379-396, March.
    13. Yang, Min & Li, Yongjun & Chen, Ya & Liang, Liang, 2014. "An equilibrium efficiency frontier data envelopment analysis approach for evaluating decision-making units with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 239(2), pages 479-489.
    14. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    15. Thanasis Bouzidis & Giannis Karagiannis, 2022. "Extending the Zero-Sum Gains Data Envelopment Analysis Model," Discussion Paper Series 2022_06, Department of Economics, University of Macedonia, revised Aug 2022.
    16. M. Flegl & L. A. Andrade, 2018. "Measuring countries’ performance at the Summer Olympic Games in Rio 2016," OPSEARCH, Springer;Operational Research Society of India, vol. 55(3), pages 823-846, November.
    17. Xi Xiong & Guo-liang Yang & Kai-di Liu & De-qun Zhou, 2022. "A proposed fixed-sum carryovers reallocation DEA approach for social scientific resources of Chinese public universities," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(7), pages 4097-4121, July.
    18. Ding, Tao & Zhang, Yun & Zhang, Danlu & Li, Feng, 2023. "Performance evaluation of Chinese research universities: A parallel interactive network DEA approach with shared and fixed sum inputs," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    19. Thanasis Bouzidis & Giannis Karagiannis, 2022. "Extending the zero-sum gains data envelopment analysis model," Journal of Productivity Analysis, Springer, vol. 58(2), pages 171-184, December.
    20. Yu, Shasha & Lei, Ming & Deng, Honghui, 2023. "Evaluation to fixed-sum-outputs DMUs by non-oriented equilibrium efficient frontier DEA approach with Nash bargaining-based selection," Omega, Elsevier, vol. 115(C).

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:spr:annopr:v:322:y:2023:i:2:d:10.1007_s10479-022-05085-5. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.