Improving the logistics ecological efficiency (LEE) has become a significant part of ensuring a sustainable development and tackling environmental pollution. Previous studies in the logistics industry seldom considered air pollutants and the association of spatial information. Therefore, innovatively considering SO2, NOx, and PM, this study adopted the super-SBM-undesirable model to calculate the LEE of 30 provinces in China from 2005 to 2019 and, thereafter, developed information-based matrix to explore its influencing factors by using the spatial Dubin model. The results indicated that (1) the overall LEE was low with the average of 0.657, presenting a three-stage trend of "decreasing first, then rising, and later stable," and significant regional differences with the decreasing gradient pattern of the "Eastern-Central-Western." (2) A spatial directionality distributed from the northeast to southwest and a significant spatial autocorrelation were observed. (3) The LEE had a significant positive spillover effect. Industrial structure, urbanization level, environmental regulation, and technological innovation level had a positive impact on the local LEE, and industrial structure displayed the most promoting effects. Energy intensity, economic level, energy structure, and opening level had a significant effect on the local LEE with varying degree of inhibition. Local energy intensity and environmental regulation had a positive influence on the LEE in neighboring areas, while local opening level had inhibiting effects. In addition, policy recommendations for enhancing the LEE were made.
Keywords: Air pollutants; Logistics ecological efficiency; Spatial Dubin model; Spatial autocorrelation; Spatial directionality; Spatial information association; Super-SBM-undesirable.
© 2021. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.