Regional logistics efficiency and performance in China along the Belt and Road Initiative: The analysis of integrated DEA and hierarchical regression with carbon constraint

Although some studies have focused on the evaluation of regional logistics efficiency in China along the Belt and Road Initiative (B&R Initiative), there exist research gaps pertaining to systematically exploring the effects of internal and external influencing factors on the efficiency, economic performance and environmental performance of regional logistics industry for different regions and time periods. Therefore, in this paper, the integration of the slack-based measure (SBM) model and hierarchical regression is developed to perform an 11-year dynamic analysis (2007-2017) with carbon emission constraint. The improvement directions for inefficient regions are provided by benchmark analysis. The decrement rate and increment rate are proposed to further reveal the redundancy or shortage degree of indicators. Our results reveal the large imbalance in logistics efficiency among China's regions along the B&R Initiative. However, the gaps in efficiency between the eastern and western regions have narrowed since the launch of the B&R Initiative. With regression analysis, we find whether in regions along the Silk Road Economic Belt or the Maritime Silk Road, whether from 2007 to 2012 or from 2013 to 2017, the specialization degree of logistics industry plays a prominently positive role in logistics efficiency and a negative role in environmental performance. It is interesting to find the opposite effect of opening up level on efficiency between regions along the Maritime Silk Road (positive effect) and the Silk Road Economic Belt (negative effect). We find the seesaw effect of economic development level and government regulation on economic performance and environmental performance for the southwest region. In addition, from 2013 to 2017, the external factors that have a positive effect on efficiency have changed from the opening up level before 2013 to the regional economic development level. (C) 2020 Elsevier Ltd. All rights reserved.