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On the Consistency of Slacks-based Measure-Max Model and Super-Slacks-based Measure Model

机译:基于slacks的measure-max模型与基于超松弛的测量模型的一致性

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摘要

Slacks-based measure (SBM) (Tone (2001), Pastor et al. (1999)) has been widely utilized as a representative non-radial DEA model. However, this model, called SBM-Min here, evaluates the efficiency of an inefficient DMU referring to the furthest frontier point within a range. In contrast, the SBM-Max model looks for the nearest frontier point and hence its score is generally greater than the SBM-Min score. The Super-SBM model (Tone (2002)) evaluates the efficiency of an efficient DMU referring to the nearest point on the frontier except itself. We can foresee a close connection between SBM-Max and Super-SBM models, because the motivations behind the two models are same. In this paper we demonstrate this consistency using a real dataset.
机译:基于松弛的测度(SBM)(Tone(2001),Pastor等人(1999))已被广泛用作代表性的非径向DEA模型。但是,此模型在此处称为SBM-Min,它根据范围内最远的边界点来评估低效率DMU的效率。相反,SBM-Max模型寻找最近的边界点,因此其得分通常大于SBM-Min得分。 Super-SBM模型(Tone(2002))评估了有效DMU的效率,该效率是指除自身以外最接近边界的点。我们可以预见SBM-Max和Super-SBM模型之间的紧密联系,因为这两个模型背后的动机是相同的。在本文中,我们使用真实数据集演示了这种一致性。

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    TONE Kaoru;

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  • 年度 2016
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  • 正文语种 en
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