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Two-stage DEA models with undesirable input-intermediate-outputs

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Listed:
  • Liu, Wenbin
  • Zhou, Zhongbao
  • Ma, Chaoqun
  • Liu, Debin
  • Shen, Wanfang

Abstract

Data envelopment analysis (DEA) is a non-parametric approach for measuring the relative efficiencies of peer decision making units (DMUs). Many studies have examined DEA efficiencies of two-stage systems, where all the outputs from the first stage are the only inputs to the second stage. Although single-stage DEA models with undesirable input-outputs have been extensively studied, there still lacks of more systematical investigation on two-stage DEA with undesirable variables. For instance, depending on its operating model, even whether an intermediate variable is desirable or undesirable can be questionable for a particular two-stage system. Furthermore, most of the existing studies on two-stage systems focus on the case where only the final outputs are undesirable. In this work, we try to systematically examine two-stage DEA models with undesirable input-intermediate-outputs. Particularly, we utilize the free-disposal axioms to construct the production possibility sets (PPS) and the corresponding DEA models with undesirable variables. The proposed models are then used to illustrate some theoretical perspectives by using the data of China׳s listed banks.

Suggested Citation

  • Liu, Wenbin & Zhou, Zhongbao & Ma, Chaoqun & Liu, Debin & Shen, Wanfang, 2015. "Two-stage DEA models with undesirable input-intermediate-outputs," Omega, Elsevier, vol. 56(C), pages 74-87.
  • Handle: RePEc:eee:jomega:v:56:y:2015:i:c:p:74-87
    DOI: 10.1016/j.omega.2015.03.009
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    References listed on IDEAS

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    Cited by:

    1. Lee, Boon L. & Worthington, Andrew C., 2016. "A network DEA quantity and quality-orientated production model: An application to Australian university research services," Omega, Elsevier, vol. 60(C), pages 26-33.
    2. repec:spr:annopr:v:259:y:2017:i:1:d:10.1007_s10479-017-2523-2 is not listed on IDEAS
    3. repec:spr:annopr:v:266:y:2018:i:1:d:10.1007_s10479-018-2797-z is not listed on IDEAS
    4. Aghayi, Nazila & Maleki, Bentolhoda, 2016. "Efficiency measurement of DMUs with undesirable outputs under uncertainty based on the directional distance function: Application on bank industry," Energy, Elsevier, vol. 112(C), pages 376-387.
    5. repec:spr:orspec:v:40:y:2018:i:1:d:10.1007_s00291-017-0490-2 is not listed on IDEAS
    6. Haibo Zhou & Hanhui Hu, 2017. "Sustainability Evaluation of Railways in China Using a Two-Stage Network DEA Model with Undesirable Outputs and Shared Resources," Sustainability, MDPI, Open Access Journal, vol. 9(1), pages 1-23, January.
    7. repec:spr:ssefpa:v:10:y:2018:i:3:d:10.1007_s12571-018-0809-0 is not listed on IDEAS
    8. repec:eee:soceps:v:60:y:2017:i:c:p:77-86 is not listed on IDEAS
    9. Galagedera, Don U.A. & Watson, John & Premachandra, I.M. & Chen, Yao, 2016. "Modeling leakage in two-stage DEA models: An application to US mutual fund families," Omega, Elsevier, vol. 61(C), pages 62-77.
    10. repec:eee:jomega:v:77:y:2018:i:c:p:180-188 is not listed on IDEAS
    11. Ang, Sheng & Chen, Chien-Ming, 2016. "Pitfalls of decomposition weights in the additive multi-stage DEA model," Omega, Elsevier, vol. 58(C), pages 139-153.
    12. repec:eee:touman:v:65:y:2018:i:c:p:303-316 is not listed on IDEAS
    13. Chen, Lei & Wang, Ying-Ming & Lai, Fujun, 2017. "Semi-disposability of undesirable outputs in data envelopment analysis for environmental assessments," European Journal of Operational Research, Elsevier, vol. 260(2), pages 655-664.

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