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Resolving the infeasibility of the super-efficiency DEA based on DDF

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  • Guo-Ya Gan

    (Nanjing Audit University)

  • Hsuan-Shih Lee

    (National Taiwan Ocean University
    Ming Chuan University)

Abstract

Chen et al. Omega 41:621–625, 2013 propose a DEA model which measures the super-efficiency with directional distance function. Their model avoids the infeasibility when the inputs have zero and it also prevents the negative projection. However, their model might be infeasible when there is zero in the outputs. Besides, their model relies on complex predetermined parameters. Recently, Lin and Chen (Lin and Chen Journal of the Operational Research Society 66:1506–1510, 2015) propose a new model which prevents infeasibility and negative projection. However, Lin and Chen’s method introduces a constant which might dominate the input of the target DMU. To overcome the drawbacks of the models proposed in Chen et al. Omega 41:621–625, 2013 and Lin and Chen Journal of the Operational Research Society 66:1506–1510, 2015, we will develop a new DEA model to compute the super-efficiency, which prevents negative projection and the infeasibility when zero data occurs and works in the same way as the N-L model (Ray, Ray Journal of the Operational Research Society 59:788–797, 2008) when no abnormal input occurs.

Suggested Citation

  • Guo-Ya Gan & Hsuan-Shih Lee, 2021. "Resolving the infeasibility of the super-efficiency DEA based on DDF," Annals of Operations Research, Springer, vol. 307(1), pages 139-152, December.
    • Handle: RePEc:spr:annopr:v:307:y:2021:i:1:d:10.1007_s10479-021-04293-9
    DOI: 10.1007/s10479-021-04293-9
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    References listed on IDEAS

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    1. Per Andersen & Niels Christian Petersen, 1993. "A Procedure for Ranking Efficient Units in Data Envelopment Analysis," Management Science, INFORMS, vol. 39(10), pages 1261-1264, October.
    2. Chen, Yao & Du, Juan & Huo, Jiazhen, 2013. "Super-efficiency based on a modified directional distance function," Omega, Elsevier, vol. 41(3), pages 621-625.
    3. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    4. Chen, Yao, 2005. "Measuring super-efficiency in DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 161(2), pages 545-551, March.
    5. S C Ray, 2008. "The directional distance function and measurement of super-efficiency: an application to airlines data," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(6), pages 788-797, June.
    6. W D Cook & L Liang & Y Zha & J Zhu, 2009. "A modified super-efficiency DEA model for infeasibility," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 60(2), pages 276-281, February.
    7. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    8. Chambers, Robert G. & Chung, Yangho & Fare, Rolf, 1996. "Benefit and Distance Functions," Journal of Economic Theory, Elsevier, vol. 70(2), pages 407-419, August.
    9. Lee, Hsuan-Shih & Zhu, Joe, 2012. "Super-efficiency infeasibility and zero data in DEA," European Journal of Operational Research, Elsevier, vol. 216(2), pages 429-433.
    10. Lee, Hsuan-Shih & Chu, Ching-Wu & Zhu, Joe, 2011. "Super-efficiency DEA in the presence of infeasibility," European Journal of Operational Research, Elsevier, vol. 212(1), pages 141-147, July.
    11. Banker, Rajiv D. & Chang, Hsihui, 2006. "The super-efficiency procedure for outlier identification, not for ranking efficient units," European Journal of Operational Research, Elsevier, vol. 175(2), pages 1311-1320, December.
    12. Hsuan-Shih Lee, 2021. "An integrated model for SBM and Super-SBM DEA models," Journal of the Operational Research Society, Taylor & Francis Journals, vol. 72(5), pages 1174-1182, May.
    13. Chen, Yao & Liang, Liang, 2011. "Super-efficiency DEA in the presence of infeasibility: One model approach," European Journal of Operational Research, Elsevier, vol. 213(1), pages 359-360, August.
    14. Guo, I-Lung & Lee, Hsuan-Shih & Lee, Dan, 2017. "An integrated model for slack-based measure of super-efficiency in additive DEA," Omega, Elsevier, vol. 67(C), pages 160-167.
    15. Ruiyue Lin & Zhiping Chen, 2015. "Super-efficiency measurement under variable return to scale: an approach based on a new directional distance function," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 66(9), pages 1506-1510, September.
    16. Lee, Hsuan-Shih, 2021. "Slacks-based measures of efficiency and super-efficiency in presence of nonpositive data," Omega, Elsevier, vol. 103(C).
    17. Lee, Hsuan-Shih, 2021. "Efficiency decomposition of the network DEA in variable returns to scale: An additive dissection in losses," Omega, Elsevier, vol. 100(C).
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    Cited by:

    1. Lee, Hsuan-Shih, 2022. "Integrating SBM model and Super-SBM model: a one-model approach," Omega, Elsevier, vol. 113(C).
    2. Mostafa Davtalab-Olyaie & Hadis Mahmudi-Baram & Masoud Asgharian, 2023. "Measuring individual efficiency and unit influence in centrally managed systems," Annals of Operations Research, Springer, vol. 321(1), pages 139-164, February.
    3. Li, Hui & Wu, Dongdong, 2024. "Online investor attention and firm restructuring performance: Insights from an event-based DEA-Tobit model," Omega, Elsevier, vol. 122(C).

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