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Closest target for the orientation-free context-dependent DEA under variable returns to scale

Author

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  • Jie Wu
  • Yafei Yu
  • Qingyuan Zhu
  • Qingxian An
  • Liang Liang

Abstract

An important branch of data envelopment analysis (DEA) is context-dependent DEA, which evaluates efficiency by combining the attractiveness and progress for a particular decision-making unit (DMU). Traditionally, context-dependent DEA models are based on the assumption of constant returns to scale. Two limitations are found when directly extending original radial context-dependent DEA (ORCD-DEA) models into variable returns to scale versions. One is that it may not be possible to determine the attractiveness of a DMU that logically must be attractive in that context. The other problem is that the progress measure cannot ensure an inefficient DMU projects to a Pareto-efficient frontier. A small numerical example is used to illustrate these two issues. In order to overcome these deficiencies, the concept of closest target is introduced to determine the attractiveness and progress for each DMU. The closest target method can further improve DMUs’ performance with less wastes in inputs or underproduction in outputs. Finally, a practical application involving computer printers is presented.

Suggested Citation

  • Jie Wu & Yafei Yu & Qingyuan Zhu & Qingxian An & Liang Liang, 2018. "Closest target for the orientation-free context-dependent DEA under variable returns to scale," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 69(11), pages 1819-1833, November.
    • Handle: RePEc:taf:tjorxx:v:69:y:2018:i:11:p:1819-1833
    DOI: 10.1080/01605682.2017.1409865
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    Cited by:

    1. Zhou, Xiaoyang & Xu, Zhongwen & Chai, Jian & Yao, Liming & Wang, Shouyang & Lev, Benjamin, 2019. "Efficiency evaluation for banking systems under uncertainty: A multi-period three-stage DEA model," Omega, Elsevier, vol. 85(C), pages 68-82.
    2. Yongjun Li & Feng Li & Ali Emrouznejad & Liang Liang & Qiwei Xie, 2019. "Allocating the fixed cost: an approach based on data envelopment analysis and cooperative game," Annals of Operations Research, Springer, vol. 274(1), pages 373-394, March.
    3. Chen, Lei & Wang, Ying-Ming, 2020. "DEA target setting approach within the cross efficiency framework," Omega, Elsevier, vol. 96(C).
    4. 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.
    5. An, Qingxian & Tao, Xiangyang & Chen, Xiaohong, 2023. "Nested frontier-based best practice regulation under asymmetric information in a principal–agent framework," European Journal of Operational Research, Elsevier, vol. 306(1), pages 269-285.
    6. Anna Labijak-Kowalska & Miłosz Kadziński, 2023. "Exact and stochastic methods for robustness analysis in the context of Imprecise Data Envelopment Analysis," Operational Research, Springer, vol. 23(1), pages 1-34, March.
    7. Lozano, S. & Hinojosa, M.A. & Mármol, A.M., 2019. "Extending the bargaining approach to DEA target setting," Omega, Elsevier, vol. 85(C), pages 94-102.
    8. Qingxian An & Fanyong Meng & Beibei Xiong & Zongrun Wang & Xiaohong Chen, 2020. "Assessing the relative efficiency of Chinese high-tech industries: a dynamic network data envelopment analysis approach," Annals of Operations Research, Springer, vol. 290(1), pages 707-729, July.
    9. Khoveyni, Mohammad & Fukuyama, Hirofumi & Eslami, Robabeh & Yang, Guo-liang, 2019. "Variations effect of intermediate products on the second stage in two-stage processes," Omega, Elsevier, vol. 85(C), pages 35-48.
    10. An, Qingxian & Wen, Yao & Ding, Tao & Li, Yongli, 2019. "Resource sharing and payoff allocation in a three-stage system: Integrating network DEA with the Shapley value method," Omega, Elsevier, vol. 85(C), pages 16-25.
    11. Jin-Li Hu & Tzu-Pu Chang, 2021. "Evaluating the Context-Dependent Total-Factor Energy Efficiency of Counties and Cities in Taiwan," Energies, MDPI, vol. 14(15), pages 1-10, July.

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