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Using Linear Programming to Determine Post-Facto Consistency in Performance Evaluations of Major League Baseball Players

Author

Listed:
  • Christopher Zappe

    (Management Department, Bucknell University, Lewisburg, Pennsylvania 17837)

  • William Webster

    (Decision and Information Sciences Department, 351 Business Building, University of Florida, Gainesville, Florida 32611-2017)

  • Ira Horowitz

    (Decision and Information Sciences Department, 351 Business Building, University of Florida, Gainesville, Florida 32611-2017)

Abstract

We use linear programming to judge the consistency of the performance appraisals that Bill James has made of major league baseball players. In particular, we use a linear programming model to determine whether weights for the set of performance measures can be found such that the players' ordinal ratings can be reconstructed. This approach can be used to judge the consistency of performance appraisals for groups of employees.

Suggested Citation

  • Christopher Zappe & William Webster & Ira Horowitz, 1993. "Using Linear Programming to Determine Post-Facto Consistency in Performance Evaluations of Major League Baseball Players," Interfaces, INFORMS, vol. 23(6), pages 107-113, December.
    • Handle: RePEc:inm:orinte:v:23:y:1993:i:6:p:107-113
    DOI: 10.1287/inte.23.6.107
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    Citations

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    Cited by:

    1. Srinivas K. Reddy & Antonie Stam & Per J. Agrell, 2015. "Brand Equity, Efficiency and Valuation of Professional Sports Franchises: The Case of Major League Baseball," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 5(1), pages 63-89, January.
    2. Leo H. Kahane & Todd L. Idson, 2002. "Editorial Board Changes," Journal of Sports Economics, , vol. 3(1), pages 3-5, February.
    3. Horowitz, I. & Zappe, C., 1995. "The linear programming alternative to policy capturing for eliciting criteria weights in the performance appraisal process," Omega, Elsevier, vol. 23(6), pages 667-676, December.
    4. Bruce A. Reinig & Ira Horowitz, 2018. "Using Mathematical Programming to Select and Seed Teams for the NCAA Tournament," Interfaces, INFORMS, vol. 48(3), pages 181-188, June.
    5. Chen, Xiqun (Michael) & Chen, Chuqiao & Ni, Linglin & Li, Li, 2018. "Spatial visitation prediction of on-demand ride services using the scaling law," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 508(C), pages 84-94.
    6. Kornbluth, J. S. H., 1997. "Identifying feasible orderings for performance appraisal," Omega, Elsevier, vol. 25(3), pages 329-334, June.
    7. Jung, Ho-Won, 2001. "A linear programming model dealing with ordinal ratings in policy capturing of performance appraisal," European Journal of Operational Research, Elsevier, vol. 134(3), pages 493-497, November.

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