Previous studies have primarily targeted at positive causal linkages between the logistics industry and economic benefits, resulting in biased findings without the consideration of undesirable social and environmental problems. Therefore, this paper aims to develop a holistic approach to the assessment of logistics efficiency, through considering comprehensive inputs and desirable and undesirable outputs. In specific, contextualized in China, this paper comprehensively examined the spatiotemporal variations of China logistics efficiency and further investigated the impact of some exogenous factors. Results indicate that the overall logistics efficiency of China was low, but temporally showed a trend of increase. Spatially, the logistics efficiency followed the pattern of Eastern > Central > Western > Northeastern. Moreover, for the spatial interaction among adjacent provinces, there occurred high-high patterns in the Eastern, and low-low aggregation in the Western and Northeastern regions. However, along with time, the spatial interaction among adjacent provinces was weakening. For exogenous factors, level of economic development, urbanization level, utilization rate of logistics resources, and location advantage had a significant positive impact on SLE, while the effect of labor quality was not significant. Overall, this paper enriches the theoretical understandings of sustainable logistics efficiency evaluation and unbiasedly inform central and local governments with approaches to optimizing logistics efficiency.
Keywords: Moran’s I; Super-SBM-DEA model; Sustainable logistics efficiency; Tobit regression model; Undesirable outputs.