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DEA-based benchmarking for performance evaluation in pay-for-performance incentive plans

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  • Cook, Wade D.
  • Ramón, Nuria
  • Ruiz, José L.
  • Sirvent, Inmaculada
  • Zhu, Joe

Abstract

Incentive plans involve payments for performance relative to some set of goals. In this paper, we extend Data Envelopment Analysis (DEA) to the evaluation of performance in the specific context of pay-for-performance incentive plans. The approach proposed ensures that the evaluation of performance of decision making units (DMUs) that follow the implementation of incentive plans, is made in terms of targets that are attainable, as well as representing best practices. A model is developed that adjusts the benchmarking to the goals through the corresponding payment of incentives, thus DEA targets are established taking into consideration the improvement strategies that were set out in the incentive plans. To illustrate, we examine an application concerned with the financing of public Spanish universities.

Suggested Citation

  • Cook, Wade D. & Ramón, Nuria & Ruiz, José L. & Sirvent, Inmaculada & Zhu, Joe, 2019. "DEA-based benchmarking for performance evaluation in pay-for-performance incentive plans," Omega, Elsevier, vol. 84(C), pages 45-54.
    • Handle: RePEc:eee:jomega:v:84:y:2019:i:c:p:45-54
    DOI: 10.1016/j.omega.2018.04.004
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    2. Panagiotis Ravanos & Giannis Karagiannis, 2022. "In search for the most preferred solution in value efficiency analysis," Journal of Productivity Analysis, Springer, vol. 58(2), pages 203-220, December.
    3. Monge, Juan F. & Ruiz, José L., 2023. "Setting closer targets based on non-dominated convex combinations of Pareto-efficient units: A bi-level linear programming approach in Data Envelopment Analysis," European Journal of Operational Research, Elsevier, vol. 311(3), pages 1084-1096.
    4. Matthias Klumpp & Dominic Loske, 2021. "Long-Term Economic Sustainability of Humanitarian Logistics—A Multi-Level and Time-Series Data Envelopment Analysis," IJERPH, MDPI, vol. 18(5), pages 1-19, February.
    5. Contreras, I. & Lozano, S., 2022. "Size efficiency, splits and merger gains, and centralized resource reallocation of Spanish public universities," Socio-Economic Planning Sciences, Elsevier, vol. 81(C).
    6. Kadziński, Miłosz & Stamenković, Mladen & Uniejewski, Maciej, 2022. "Stepwise benchmarking for multiple criteria sorting," Omega, Elsevier, vol. 108(C).
    7. Benítez-Peña, Sandra & Bogetoft, Peter & Romero Morales, Dolores, 2020. "Feature Selection in Data Envelopment Analysis: A Mathematical Optimization approach," Omega, Elsevier, vol. 96(C).
    8. Battisti, Enrico & Alfiero, Simona & Quaglia, Roberto & Yahiaoui, Dorra, 2022. "Financial performance and global start-ups: the impact of knowledge management practices," Journal of International Management, Elsevier, vol. 28(4).
    9. Yin, Pengzhen & Chu, Junfei & Wu, Jie & Ding, Jingjing & Yang, Min & Wang, Yuhong, 2020. "A DEA-based two-stage network approach for hotel performance analysis: An internal cooperation perspective," Omega, Elsevier, vol. 93(C).
    10. An, Qingxian & Zhang, Qiaoyu & Tao, Xiangyang, 2023. "Pay-for-performance incentives in benchmarking with quasi S-shaped technology," Omega, Elsevier, vol. 118(C).
    11. Ming-Fu Hsu & Ying-Shao Hsin & Fu-Jiing Shiue, 2022. "Business analytics for corporate risk management and performance improvement," Annals of Operations Research, Springer, vol. 315(2), pages 629-669, August.
    12. Contreras, I. & Lozano, S., 2020. "Allocating additional resources to public universities. A DEA bargaining approach," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    13. Kalinichenko, Olena & Amado, Carla A.F. & Santos, Sérgio P., 2022. "Exploring the potential of Data Envelopment Analysis for enhancing pay-for-performance programme design in primary health care," European Journal of Operational Research, Elsevier, vol. 298(3), pages 1084-1100.
    14. Xiangrui Chao & Yucheng Dong & Gang Kou & Yi Peng, 2022. "How to determine the consensus threshold in group decision making: a method based on efficiency benchmark using benefit and cost insight," Annals of Operations Research, Springer, vol. 316(1), pages 143-177, September.
    15. An, Qingxian & Tao, Xiangyang & Xiong, Beibei, 2021. "Benchmarking with data envelopment analysis: An agency perspective," Omega, Elsevier, vol. 101(C).
    16. Onesmo Kaiya Mackenzie, 2021. "Efficiency of tax revenue administration in Africa," Working Papers 02/2021, Stellenbosch University, Department of Economics.
    17. Joe Zhu, 2022. "DEA under big data: data enabled analytics and network data envelopment analysis," Annals of Operations Research, Springer, vol. 309(2), pages 761-783, February.
    18. An, Qingxian & Tao, Xiangyang & Xiong, Beibei & Chen, Xiaohong, 2022. "Frontier-based incentive mechanisms for allocating common revenues or fixed costs," European Journal of Operational Research, Elsevier, vol. 302(1), pages 294-308.

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