Our paper focuses on a robustness analysis of efficiency scores in the context of Data Envelopment Analysis (DEA) assuming interval scale data, as defined in A. Dehnokhalaji, P. J. Korhonen, M. Köksalan, N. Nasrabadi and J. Wallenius, “Efficiency Analysis to incorporate interval scale data”, European Journal of Operational Research 207 (2), 2010, pp. 1116–1121. We first show that the definition of the efficiency score used in our paper is a well-defined measure according to Aparicio and Pastor (J. Aparicio and J. T. Pastor, “A well-defined efficiency measure for dealing with closest targets in DEA”, Applied Mathematics and Computation 219 (17), 2013, pp. 9142–9154.). Next, we characterize how robust the efficiency scores are with respect to improvements and deteriorations of inputs and outputs. We illustrate our analysis with two examples: a simple numerical example and a more complex example using real-world data.

我们的论文侧重于在假设区间尺度数据的数据包络分析 (DEA) 背景下对效率得分的稳健性分析，如 A. Dehnokhalaji、PJ Korhonen、M. Köksalan、N. Nasrabadi 和 J. Wallenius，“效率分​​析纳入区间尺度数据”，欧洲运筹学杂志 207 (2)，2010 年，第 1116-1121 页。我们首先表明，我们论文中使用的效率得分的定义是根据 Aparicio 和 Pastor（J. Aparicio 和 JT Pastor，“处理 DEA 中最接近目标的明确定义的效率度量”，Applied数学与计算 219 (17), 2013, pp. 9142–9154.)。接下来，我们描述了效率得分在输入和输出的改进和恶化方面的稳健性。我们用两个例子来说明我们的分析：