Abstract
Slacks-based measurement (SBM), as an important branch of data envelopment analysis (DEA) for evaluating the efficiency of decision making units (DMUs) was firstly proposed by Tone and has been well developed in different directions. Many models based on SBM have been built, such as SBM of super efficiency, SBM of network DEA, SBM of the worst-practise DEA and dynamic SBM. In this paper, we extend the SBM models in different returns to scale (RTS) and build a comprehensive SBM model. Based on the SBM models above, a new approach for estimating returns to scale of DMUs is proposed. This approach has a specific advantage that it can gain projection of inefficient observations from input-output orientation. At last, a numerical example demonstrates the process of estimating returns to scale.
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