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The dynamics of performance space of Major League Baseball pitchers 1871–2006

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  • Wen-Chih Chen
  • Andrew Johnson
Abstract
A central decision-maker, the principal, employs performance evaluation criteria consistent with an organization’s overall goal(s) to measure the effectiveness of the agents who execute decisions and implement strategies within a specified period. The dataset of performance criteria spanning the performance space will change over time to reflect the principal’s strategic modifications. This paper applies a Data Envelopment Analysis (DEA) based approach to reveals the dynamics of the performance space of Major League Baseball (MLB) pitchers with minimum subjective judgment imposed on the data. The proposed approach is applied to data on MLB pitchers from 1871 to 2006. We conclude that many of the findings are consistent with the observations of baseball’s experts. The approach also suggests new directions for investigating a large dataset to identify revealed preferences or strategies by using historical and modern observations. Copyright Springer Science+Business Media, LLC 2010

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  • Wen-Chih Chen & Andrew Johnson, 2010. "The dynamics of performance space of Major League Baseball pitchers 1871–2006," Annals of Operations Research, Springer, vol. 181(1), pages 287-302, December.
    • Handle: RePEc:spr:annopr:v:181:y:2010:i:1:p:287-302:10.1007/s10479-010-0743-9
    DOI: 10.1007/s10479-010-0743-9
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    Cited by:

    1. Andrew Johnson & John Ruggiero, 2014. "Nonparametric measurement of productivity and efficiency in education," Annals of Operations Research, Springer, vol. 221(1), pages 197-210, October.
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    3. Amar Oukil & Srikrishna Madhumohan Govindaluri, 2017. "A systematic approach for ranking football players within an integrated DEA‐OWA framework," Managerial and Decision Economics, John Wiley & Sons, Ltd., vol. 38(8), pages 1125-1136, December.
    4. Eskelinen, Juha, 2017. "Comparison of variable selection techniques for data envelopment analysis in a retail bank," European Journal of Operational Research, Elsevier, vol. 259(2), pages 778-788.
    5. Yutaka Ueda & Yoko Ohzono, 2013. "A New Measure of Distributive Justice by Data Envelopment Analysis," Acta Universitatis Danubius. OEconomica, Danubius University of Galati, issue 9(3), pages 49-59, June.
    6. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.
    7. Qing Zhu & Renxian Zuo & Yuze Li & Shan Liu, 2021. "A system evaluation of NBA rookie contract execution efficiency with stacked Autoencoder and hybrid DEA," Operational Research, Springer, vol. 21(4), pages 2771-2807, December.
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    13. Konstantinos Petridis & Alexander Chatzigeorgiou & Emmanouil Stiakakis, 2016. "A spatiotemporal Data Envelopment Analysis (S-T DEA) approach: the need to assess evolving units," Annals of Operations Research, Springer, vol. 238(1), pages 475-496, March.

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