This paper proposes a novel model of inverse data envelopment analysis (IDEA) based on the slack‐based measure (SBM) approach. The developed inverse SBM model can maintain relative efficiency of decision making units (DMUs) with new input and output. This model can also measure the input and output volumes when a decision maker (DM) increases efficiency score. The inverse SBM model is a kind of multi‐objective non‐linear programming (MONLP) problem, which is not easy to solve. Therefore, we suggest a linear programming model for solving inverse SBM model. In this model efficiency score of DMU under evaluation remains unchanged. Furthermore, we suggest an optimal combination of inputs and outputs in the production possibility set (PPS). A case study is presented to demonstrate the efficacy of our proposed model.

中文翻译：

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开发一种新颖的逆数据包络分析（DEA）模型来评估售后单位

本文提出了一种基于基于松弛的度量（SBM）方法的逆数据包络分析（IDEA）模型。所开发的逆SBM模型可以通过新的输入和输出来维持决策单元（DMU）的相对效率。当决策者（DM）提高效率得分时，该模型还可以测量输入和输出量。SBM逆模型是一种不易解决的多目标非线性规划（MONLP）问题。因此，我们建议使用线性规划模型来求解反SBM模型。在该模型中，评估中的DMU效率得分保持不变。此外，我们建议在生产可能性集（PPS）中输入和输出的最佳组合。案例研究表明了我们提出的模型的有效性。