IDEAS home Printed from https://ideas.repec.org/a/sae/jospec/v15y2014i2p180-200.html
   My bibliography  Save this article

A DEA Approach to Performance-Based Budgeting of Formula One Constructors

Author

Listed:
  • Ester Gutiérrez
  • Sebastián Lozano

Abstract

This article assesses the relative efficiency of teams participating in Formula One (F1) World Constructors’ Championship. A nonparametric method based on data envelopment analysis (DEA) has been used. The aim is to measure each constructor’s performance, comparing its efficiency relative to all other competing constructors. The study uses financial and performance data to assess the proximity of the constructors to the best practices frontier. The analysis has been made considering the results of the 2003, 2006, 2008, 2010, and 2011 F1 seasons. In order to create a parsimonious DEA model, a variable screening method for dimensionality reduction is considered. The results indicate that, generally, a substantial reduction should be made to the constructors’ budget over the seasons in order to be efficient as compared to the identified benchmarks. In addition, scale efficiency reveals that most constructors operate below their most productive scale size.

Suggested Citation

  • Ester Gutiérrez & Sebastián Lozano, 2014. "A DEA Approach to Performance-Based Budgeting of Formula One Constructors," Journal of Sports Economics, , vol. 15(2), pages 180-200, April.
    • Handle: RePEc:sae:jospec:v:15:y:2014:i:2:p:180-200
    DOI: 10.1177/1527002512447629
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/1527002512447629
    Download Restriction: no
    File URL: https://libkey.io/10.1177/1527002512447629?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
    ---><---

    References listed on IDEAS

    as
    1. Castellucci, Fabrizio & Padula, Mario & Pica, Giovanni, 2011. "The age-productivity gradient: Evidence from a sample of F1 drivers," Labour Economics, Elsevier, vol. 18(4), pages 464-473, August.
    2. Carlos Pestana Barros & Albert Assaf & Fabio Sá-Earp, 2010. "Brazilian Football League Technical Efficiency: A Simar and Wilson Approach," Journal of Sports Economics, , vol. 11(6), pages 641-651, December.
    3. Simon Rottenberg, 1956. "The Baseball Players' Labor Market," Journal of Political Economy, University of Chicago Press, vol. 64(3), pages 242-242.
    4. 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.
    5. Banker, Rajiv D., 1984. "Estimating most productive scale size using data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 17(1), pages 35-44, July.
    6. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    7. A. Pedro Duarte Silva, 2000. "DISCARDING VARIABLES in PRINCIPAL COMPONENT ANALYSIS : ALGORITHMS for ALL-SUBSETS COMPARISONS," Working Papers de Economia (Economics Working Papers) 02, Católica Porto Business School, Universidade Católica Portuguesa.
    8. Yun Zhang & Robert Bartels, 1998. "The Effect of Sample Size on the Mean Efficiency in DEA with an Application to Electricity Distribution in Australia, Sweden and New Zealand," Journal of Productivity Analysis, Springer, vol. 9(3), pages 187-204, March.
    9. António Pedro Duarte Silva, 2002. "Discarding Variables in a Principal Component Analysis: Algorithms for All-Subsets Comparisons," Computational Statistics, Springer, vol. 17(2), pages 251-271, July.
    10. Fried, Harold O. & Lambrinos, James & Tyner, James, 2004. "Evaluating the performance of professional golfers on the PGA, LPGA and SPGA tours," European Journal of Operational Research, Elsevier, vol. 154(2), pages 548-561, April.
    11. Duarte Silva, António Pedro, 2001. "Efficient Variable Screening for Multivariate Analysis," Journal of Multivariate Analysis, Elsevier, vol. 76(1), pages 35-62, January.
    12. Sueyoshi, Toshiyuki & Ohnishi, Kenji & Kinase, Youichi, 1999. "A benchmark approach for baseball evaluation," European Journal of Operational Research, Elsevier, vol. 115(3), pages 429-448, June.
    13. Carlos Pestana Barros & Stephanie Leach, 2006. "Performance evaluation of the English Premier Football League with data envelopment analysis," Applied Economics, Taylor & Francis Journals, vol. 38(12), pages 1449-1458.
    14. Banker, Rajiv D. & Gadh, Vandana M. & Gorr, Wilpen L., 1993. "A Monte Carlo comparison of two production frontier estimation methods: Corrected ordinary least squares and data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 67(3), pages 332-343, June.
    15. Jie Wu & Zhixiang Zhou & Liang Liang, 2010. "Measuring the Performance of Nations at Beijing Summer Olympics Using Integer-Valued DEA Model," Journal of Sports Economics, , vol. 11(5), pages 549-566, October.
    16. Peter A. Groothuis & Jana D. Groothuis & Kurt W. Rotthoff, 2011. "Time on Camera," Journal of Sports Economics, , vol. 12(5), pages 561-570, October.
    17. KimMarie McGoldrick & Lisa Voeks, 2005. "“We Got Game!â€," Journal of Sports Economics, , vol. 6(1), pages 5-23, February.
    18. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    19. Karl W. Einolf, 2004. "Is Winning Everything?," Journal of Sports Economics, , vol. 5(2), pages 127-151, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Isidoro Guzmán-Raja & Manuela Guzmán-Raja, 2021. "Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence From Spanish Professional Football," SAGE Open, , vol. 11(1), pages 21582440219, February.
    2. Oliver Budzinski & Arne Feddersen, 2020. "Measuring competitive balance in Formula One racing," Chapters, in: Plácido Rodríguez & Stefan Kesenne & Brad R. Humphreys (ed.), Outcome Uncertainty in Sporting Events, chapter 1, pages 5-26, Edward Elgar Publishing.

    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. José L. Ruiz & Diego Pastor & Jesús T. Pastor, 2013. "Assessing Professional Tennis Players Using Data Envelopment Analysis (DEA)," Journal of Sports Economics, , vol. 14(3), pages 276-302, June.
    2. Anthony Glass & Karligash Kenjegalieva & Jason Taylor, 2015. "Game, set and match: evaluating the efficiency of male professional tennis players," Journal of Productivity Analysis, Springer, vol. 43(2), pages 119-131, April.
    3. I. García-Sánchez, 2007. "Efficiency and effectiveness of Spanish football teams: a three-stage-DEA approach," 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. 15(1), pages 21-45, March.
    4. Halkos, George & Tzeremes, Nickolaos, 2012. "Evaluating professional tennis players’ career performance: A Data Envelopment Analysis approach," MPRA Paper 41516, University Library of Munich, Germany.
    5. Halkos, George & Tzeremes, Nickolaos, 2011. "A non-parametric analysis of the efficiency of the top European football clubs," MPRA Paper 31173, University Library of Munich, Germany.
    6. Andrés Picazo-Tadeo & Francisco González-Gómez, 2010. "Does playing several competitions influence a team’s league performance? Evidence from Spanish professional football," 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. 18(3), pages 413-432, September.
    7. Emrouznejad, Ali & De Witte, Kristof, 2010. "COOPER-framework: A unified process for non-parametric projects," European Journal of Operational Research, Elsevier, vol. 207(3), pages 1573-1586, December.
    8. Francisco González-Gómez & Andrés J. Picazo-Tadeo, 2010. "Can We Be Satisfied With Our Football Team? Evidence From Spanish Professional Football," Journal of Sports Economics, , vol. 11(4), pages 418-442, August.
    9. An‐Pang Wang & Che‐Wei Chang & Juin‐Ming Tsai & Shiu‐Wan Hung, 2021. "A performance evaluation of Major League Baseball teams: An integrated social network and data envelopment analysis," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 42(6), pages 1421-1434, September.
    10. Plácido Moreno & Sebastián Lozano, 2014. "A network DEA assessment of team efficiency in the NBA," Annals of Operations Research, Springer, vol. 214(1), pages 99-124, March.
    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. Alexandre Marinho & Simone de Souza Cardoso & Vivian Vicente de Almeida, 2009. "Avaliação da Eficiência Técnica dos Países nos Jogos Olímpicos de Pequim – 2008," Discussion Papers 1394, Instituto de Pesquisa Econômica Aplicada - IPEA.
    13. Torben Tiedemann & Tammo Francksen & Uwe Latacz-Lohmann, 2011. "Assessing the performance of German Bundesliga football players: a non-parametric metafrontier approach," 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. 19(4), pages 571-587, December.
    14. Carlos Pestana Barros & Gaël Bertrand & Laurent Botti & Scott Tainsky, 2014. "Cost efficiency of French rugby clubs," Applied Economics, Taylor & Francis Journals, vol. 46(23), pages 2721-2732, August.
    15. 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.
    16. Resende, Marcelo, 2002. "Relative efficiency measurement and prospects for yardstick competition in Brazilian electricity distribution," Energy Policy, Elsevier, vol. 30(8), pages 637-647, June.
    17. Isidoro Guzmán-Raja & Manuela Guzmán-Raja, 2021. "Measuring the Efficiency of Football Clubs Using Data Envelopment Analysis: Empirical Evidence From Spanish Professional Football," SAGE Open, , vol. 11(1), pages 21582440219, February.
    18. Chien-Ming Chen & Magali A. Delmas, 2012. "Measuring Eco-Inefficiency: A New Frontier Approach," Operations Research, INFORMS, vol. 60(5), pages 1064-1079, October.
    19. Cooper, W.W. & Ruiz, José L. & Sirvent, Inmaculada, 2009. "Selecting non-zero weights to evaluate effectiveness of basketball players with DEA," European Journal of Operational Research, Elsevier, vol. 195(2), pages 563-574, June.
    20. Pelloneová Natalie, 2023. "Evaluating Hockey Players Using Andersen and Petersen's Super-Efficiency Model: Who is the Best Czech Hockey Player in the NHL?," Polish Journal of Sport and Tourism, Sciendo, vol. 30(3), pages 23-28, September.

    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:sae:jospec:v:15:y:2014:i:2:p:180-200. 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: SAGE Publications (email available below). General contact details of provider: .

    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.