Abstract
How to accurately assess logistics industry efficiency to identify production issues and provide support for optimizing logistics efficiency has become a current research challenge. Range adjust measure (RAM) is a method for efficiency assessment in data envelopment analysis. Currently, the RAM model only applies under the variable returns to scale condition and not to other conditions. This paper aims to establish a modified RAM (MRAM) model by revising the ranges for inputs and outputs of the RAM model. Under the constant returns to scale (CRS) condition, we first develop the RAM-CRS model. Then, by introducing radial models to define the lower bounds of inputs and the upper bounds of outputs, the MRAM is proposed. The logistics data from 18 provinces are collected to validate the practicality of the MRAM model. We compare the results of the MRAM with those of the RAM-CRS and conclude that the range bounds under RAM-CRS are too tight, which results in efficiency values at a relatively low level. The MRAM with modified bounds appropriately alleviates this restriction. We also compare the MRAM and the additive model. The results show that the efficiency of the MRAM is more accurate.