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Number of performance measures versus number of decision making units in DEA

Author

Listed:
  • Dariush Khezrimotlagh

    (Pennsylvania State University Harrisburg)

  • Wade D. Cook

    (York University)

  • Joe Zhu

    (Nanjing Audit University
    Worcester Polytechnic Institute)

Abstract

Sufficient numbers of decision-making units (DMUs) in comparison to the number performance measures that are classified as inputs and outputs has been a concern when applying data envelopment analysis (DEA) in real world settings. As the number of DMUs decreases (or the numbers of inputs and outputs increases) the discrimination power and accuracy of DEA with respect to the performance of DMUs decreases. The current study proposes a technique which increases the discrimination power of DEA and allows for increasing the numbers of inputs and outputs even if the number of DMUs is relatively small. An adjusted DEA methodology is proposed which is stronger and more accurate than the routine DEA methodology, and permits one to identify the reference units for each best-practice unit (more than the DMU itself) and to distinguish the performance and rank of DMUs relative to one another, thereby enhancing the discrimination power of DEA. The scores from the adjusted methodology are logically meaningful. The pros of the new approach are demonstrated by several examples and simulation experiments in controlled environments. The results show that the proposed technique significantly improves the discrimination power over that of the conventional DEA model when the number of DMUs decreases or the number of inputs and outputs increases. In addition, the proposed technique is used to evaluate the quality-of-life related to twelve input–output combinations for two sets of DMUs, namely fifteen USA cities and five international cities, where none of the rules of thumb are satisfied.

Suggested Citation

  • Dariush Khezrimotlagh & Wade D. Cook & Joe Zhu, 2021. "Number of performance measures versus number of decision making units in DEA," Annals of Operations Research, Springer, vol. 303(1), pages 529-562, August.
  • Handle: RePEc:spr:annopr:v:303:y:2021:i:1:d:10.1007_s10479-019-03411-y
    DOI: 10.1007/s10479-019-03411-y
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    References listed on IDEAS

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    4. Khezrimotlagh, Dariush, 2022. "Simulation designs for production frontiers," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1321-1334.
    5. Toloo, Mehdi & Tone, Kaoru & Izadikhah, Mohammad, 2023. "Selecting slacks-based data envelopment analysis models," European Journal of Operational Research, Elsevier, vol. 308(3), pages 1302-1318.

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