IDEAS home Printed from https://ideas.repec.org/a/eee/ejores/v197y2009i2p731-740.html
   My bibliography  Save this article

Organizational capability, efficiency, and effectiveness in Major League Baseball: 1901-2002

Author

Listed:
  • Lewis, Herbert F.
  • Lock, Kathleen A.
  • Sexton, Thomas R.

Abstract

Effective organizations need capabilities relevant to their missions and must manage those capabilities efficiently. We anticipate capability is more important in industries in which labor is highly paid, while efficiency is more important in industries in which labor is inexpensive. We explore the contributions of capability and efficiency to effectiveness for Major League Baseball teams from 1901 through 2002. Our analysis measures team capability using offensive and defensive statistics and uses Network Data Envelopment Analysis to derive efficiency scores to capture managerial performance. We define effectiveness as the team's winning percentage. Both capability and efficiency are significant contributors to regular season effectiveness. Capability is more important. Finally, we examine the post-season performance of post-season teams between 1903 and 2002. Our analysis measures post-season performance based on the team's winning percentage and that of its opponent. Post-season performance is unrelated to capability and managerial performance, accounting for about 1% of post-season success.

Suggested Citation

  • Lewis, Herbert F. & Lock, Kathleen A. & Sexton, Thomas R., 2009. "Organizational capability, efficiency, and effectiveness in Major League Baseball: 1901-2002," European Journal of Operational Research, Elsevier, vol. 197(2), pages 731-740, September.
  • Handle: RePEc:eee:ejores:v:197:y:2009:i:2:p:731-740
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0377-2217(08)00497-9
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Dieter J. Haas, 2003. "Technical Efficiency in the Major League Soccer," Journal of Sports Economics, , vol. 4(3), pages 203-215, August.
    2. 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.
    3. Thomas Sexton & Herbert Lewis, 2003. "Two-Stage DEA: An Application to Major League Baseball," Journal of Productivity Analysis, Springer, vol. 19(2), pages 227-249, April.
    4. 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.
    5. 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.
    6. 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.
    7. Herbert F. Lewis & Thomas R. Sexton & Kathleen A. Lock, 2007. "Player Salaries, Organizational Efficiency, and Competitiveness in Major League Baseball," Journal of Sports Economics, , vol. 8(3), pages 266-294, June.
    8. Zak, Thomas A & Huang, Cliff J & Siegfried, John J, 1979. "Production Efficiency: The Case of Professional Basketball," The Journal of Business, University of Chicago Press, vol. 52(3), pages 379-392, July.
    9. 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.
    10. Timothy Anderson & Gunter Sharp, 1997. "A new measure of baseball batters using DEA," Annals of Operations Research, Springer, vol. 73(0), pages 141-155, October.
    11. Herbert Lewis & Thomas Sexton, 2004. "Data Envelopment Analysis with Reverse Inputs and Outputs," Journal of Productivity Analysis, Springer, vol. 21(2), pages 113-132, March.
    12. 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. Jun Shen & Xiaoxue Ma & Weiliang Qiao, 2022. "A Model to Evaluate the Effectiveness of the Maritime Shipping Risk Mitigation System by Entropy-Based Capability Degradation Analysis," IJERPH, MDPI, vol. 19(15), pages 1-34, July.
    2. Abbas Sheikh Aboumasoudi & Saeed Mirzamohammadi Ahmad Makui & Ahmad Makui & Jolanta Tamošaitienė, 2016. "Development of Network-Ranking Model to Create the Best Production Line Value Chain: A Case Study in Textile Industry," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 50(1), pages 215-234.
    3. Pavitt Charles, 2011. "An Estimate of How Hitting, Pitching, Fielding, and Basestealing Impact Team Winning Percentages in Baseball," Journal of Quantitative Analysis in Sports, De Gruyter, vol. 7(4), pages 1-20, October.
    4. Thanasis Bouzidis, 2019. "On-field Performance Evaluation in Soccer based on Network Data Envelopment Analysis," Discussion Paper Series 2019_05, Department of Economics, University of Macedonia, revised Nov 2019.
    5. Ching-Chin Chern & Tzi-Yuan Chou & Bo Hsiao, 2016. "Assessing the efficiency of supply chain scheduling algorithms using data envelopment analysis," Information Systems and e-Business Management, Springer, vol. 14(4), pages 823-856, November.
    6. M. Mozaffari & J. Gerami & J. Jablonsky, 2014. "Relationship between DEA models without explicit inputs and DEA-R models," 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. 22(1), pages 1-12, March.
    7. 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.
    8. Banker, Rajiv D. & Zheng, Zhiqiang (Eric) & Natarajan, Ram, 2010. "DEA-based hypothesis tests for comparing two groups of decision making units," European Journal of Operational Research, Elsevier, vol. 206(1), pages 231-238, October.
    9. Nikolaos, Chatzistamoulou & Theodoros, Antonakis & Konstantinos, Kounetas, 2020. "Salary cap and National Basketball Association teams' productive performance. A two stage Data Envelopment Analysis approach under a metatechnology framework," MPRA Paper 98811, University Library of Munich, Germany.
    10. Bendickson, Joshua S. & Chandler, Timothy D., 2019. "Operational performance: The mediator between human capital developmental programs and financial performance," Journal of Business Research, Elsevier, vol. 94(C), pages 162-171.
    11. Lozano, Sebastián, 2016. "Slacks-based inefficiency approach for general networks with bad outputs: An application to the banking sector," Omega, Elsevier, vol. 60(C), pages 73-84.
    12. Pinto, Claudio, 2020. "Fuzzy DEA models for sports data analysis: The evaluation of the relative performances of professional (virtual) football teams," MPRA Paper 103129, University Library of Munich, Germany.
    13. Ester Gutiérrez & Sebastián Lozano, 2020. "Benchmarking Formula One auto racing circuits: a two stage DEA approach," Operational Research, Springer, vol. 20(4), pages 2059-2083, December.
    14. Abdulla S. Al-Shaiba & Sami G. Al-Ghamdi & Muammer Koc, 2019. "Comparative Review and Analysis of Organizational (In)Efficiency Indicators in Qatar," Sustainability, MDPI, vol. 11(23), pages 1-23, November.
    15. 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.
    16. 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.

    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. 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.
    2. 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.
    3. 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.
    4. Nikos Chatzistamoulou & Kounetas Kostas & Antonakis Theodor, 2022. "Salary Cap, Organizational Gap, and Catch-up in the Performance of NBA Teams: A Two-Stage DEA Model Under Heterogeneity," Journal of Sports Economics, , vol. 23(2), pages 123-155, February.
    5. 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.
    6. Thomas Sexton & Herbert Lewis, 2012. "Measuring efficiency in the presence of head-to-head competition," Journal of Productivity Analysis, Springer, vol. 38(2), pages 183-197, October.
    7. Debnath Roma Mitra & Malhotra Ashish, 2015. "Measuring Efficiency of Nations in Multi Sport Events: A case of Commonwealth Games XIX," Naše gospodarstvo/Our economy, Sciendo, vol. 61(1), pages 25-36, March.
    8. Chih-Hai Yang & Hsuan-Yu Lin & Chiang-Ping Chen, 2014. "Measuring the efficiency of NBA teams: additive efficiency decomposition in two-stage DEA," Annals of Operations Research, Springer, vol. 217(1), pages 565-589, June.
    9. 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.
    10. 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.
    11. Nikolaos, Chatzistamoulou & Theodoros, Antonakis & Konstantinos, Kounetas, 2020. "Salary cap and National Basketball Association teams' productive performance. A two stage Data Envelopment Analysis approach under a metatechnology framework," MPRA Paper 98811, University Library of Munich, Germany.
    12. 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.
    13. 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.
    14. Manuel Espitia-Escuer & Lucia Isabel Garcia-Cebrián, 2010. "Measurement of the efficiency of football teams in the Champions League," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 31(6), pages 373-386.
    15. Herbert F. Lewis & Thomas R. Sexton & Kathleen A. Lock, 2007. "Player Salaries, Organizational Efficiency, and Competitiveness in Major League Baseball," Journal of Sports Economics, , vol. 8(3), pages 266-294, June.
    16. 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.
    17. 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.
    18. Trevor Collier & Andrew L. Johnson & John Ruggiero, 2011. "Measuring Technical Efficiency in Sports," Journal of Sports Economics, , vol. 12(6), pages 579-598, December.
    19. Yanzhi Bi, 2021. "Analyzing the performance of the Major League Baseball Teams by using the Data Envelopment Analysis," Business & Entrepreneurship Journal, SCIENPRESS Ltd, vol. 10(1), pages 1-1.
    20. 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.

    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:eee:ejores:v:197:y:2009:i:2:p:731-740. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/eor .

    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.