The concept of returns to scale (RTS) or local scale elasticities in data envelopment analysis (DEA)—stemming from variable returns to scale (VRS) technology—has been recently criticized because of its misbehavior in the case of decreasing returns to scale (DRS). Here, the instrument should imply a downsizing force for improving productivity. In classical VRS technologies, however, it can hide respective improvement potentials: the more, the larger a company is. The non-monotonic behavior of local scale elasticities can address this effect. This study shows this phenomenon does not apply when using multiplicative DEA models. Therefore, we propose a new global scaling index that works in the classical VRS technology. We prove the new index is weakly monotonic and illustrate our theoretical findings in a banking context.

中文翻译：

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数据包络分析：从非单调到单调尺度弹性


数据包络分析 (DEA) 中的规模收益 (RTS) 或局部规模弹性概念（源于可变规模收益 (VRS) 技术）最近受到批评，因为它在规模收益递减 (DRS) 的情况下表现不佳）。在这里，该工具应该意味着为提高生产率而缩小规模的力量。然而，在经典的 VRS 技术中，它可以隐藏各自的改进潜力：越多，公司就越大。局部尺度弹性的非单调行为可以解决这种影响。这项研究表明，当使用乘法 DEA 模型时，这种现象并不适用。因此，我们提出了一种适用于经典 VRS 技术的新的全局缩放指数。我们证明新指数是弱单调的，并说明了我们在银行业背景下的理论发现。