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A study of DEA models without explicit inputs

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  • Liu, W.B.
  • Zhang, D.Q.
  • Meng, W.
  • Li, X.X.
  • Xu, F.
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    Abstract

    In performance evaluations, data without explicit inputs (such as index data, pure output data) are widely used. To directly use such data, this paper presents a study on building DEA models without explicit inputs, so-called DEA-WEI models, which are applicable to the evaluation applications where inputs are not directly considered. We provide an axiom foundation of these kinds of models, and further discuss how to incorporate value judgments of decision makers into these DEA-WEI models. Several such models are derived. Finally, applications of the DEA-WEI models are presented.

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    Bibliographic Info

    Article provided by Elsevier in its journal Omega.

    Volume (Year): 39 (2011)
    Issue (Month): 5 (October)
    Pages: 472-480

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    Handle: RePEc:eee:jomega:v:39:y:2011:i:5:p:472-480

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    Keywords: Performance evaluation Data without explicit input DEA;

    References

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    16. Thanassoulis, E. & Boussofiane, A. & Dyson, R. G., 1996. "A comparison of data envelopment analysis and ratio analysis as tools for performance assessment," Omega, Elsevier, vol. 24(3), pages 229-244, June.
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    Cited by:
    1. Färe, Rolf & Karagiannis, Giannis, 2014. "Benefit-of-the-doubt aggregation and the diet problem," Omega, Elsevier, vol. 47(C), pages 33-35.
    2. Yang, Guo-liang & Yang, Jian-bo & Liu, Wen-bin & Li, Xiao-xuan, 2013. "Cross-efficiency aggregation in DEA models using the evidential-reasoning approach," European Journal of Operational Research, Elsevier, vol. 231(2), pages 393-404.

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