## 5 Conclusions and Implications  
This study used a super-efficiency data envelopment analysis model with a slack-based measure (Super-SBM DEA), considering undesirable outputs, to measure the integrated transport efficiency of 31 provinces in China in the period 2009-2016. Following this, a spatial autocorrelation analysis was applied to analyze \(ITE\) and verify the spatial correlation of \(ITE\) in these 31 provinces. Spatial absolute \(\beta\)-convergence and conditional \(\beta\)-convergence model were then constructed by further considering spatial effects. Based on this, the convergence characteristics of China's \(ITE\) were examined. The study draws the following conclusions. Overall, the \(ITE\) of 31 provinces in China showed varying degrees of growth with the average \(ITE\) showing a linear increase. However, the number of effective decision making units (whose value of \(ITE\) was found to be greater than 1) was relatively few. By 2016, provinces with efficiency values greater than 1 accounted for about 35%. This indicates that there is much room for adjustment in the amount of investment in transport resources in each province, and that output needs to be improved. The average \(ITE\) was expressed as Eastern region > Central region > Western region, which is in line with the level of economic development and the presence of development policies in these three regions. However, from the perspective of future development advantages, the Central Zone and Western Zone have a better efficiency improvement trend compared to the Eastern Zone. The Moran's \(I\) index during 2009-2016 emerged as greater than zero, indicating that there exists a positive spatial autocorrelation in the integrated transport efficiency of the 31 studied regions. The Moran's \(I\) index during 2009-2014 was found to be decreasing, indicating that the spatial autocorrelation of positive transport efficiency was weakening, and that the mutual influence between neighboring provinces decreased. However, the Moran's \(I\) index gradually increased from 2014 to 2015 with an increasing effect of mutual influence in terms of \(ITE\) between adjacent provinces. The existence of spatial correlation proves the correctness of the spatial effect introduced in the convergence analysis and provides a theoretical basis for the choice of the \(\beta\)-convergence model. The results of the Moran scatter plots constructed to depict the \(ITE\) of China's provinces indicate that the spatial aggregation effects are mainly characterized by high-high aggregation, low-high aggregation, and low-low aggregation, while few provinces have high-low aggregation characteristics. Through our empirical analysis, the introduction of spatial effects was seen to have a significant impact on the \(\beta\)-convergence of regional integrated transport efficiency, indicating that inter-regional connections and cooperation play a crucial role in narrowing regional gaps in transport efficiency. While China's regional _ITE_ contains the clear characteristics of both absolute \(\beta\)-convergence and conditional \(\beta\)-convergence, it requires a long-term development process. Under the influence of external condition variables, the convergence rate of the conditions was found to be faster than the absolute convergence rate. The level of economic development, per capita household transport consumption, transport industry scale, technological advancement and transport intensity all contributed to the convergence of regional integrated transport efficiency. Based on this study, some policy recommendations can be put forward for management department. Because the improvement of _ITE_ of each province is a systematic engineering, we should propose some countermeasures from the supply chain view of all the factors which influence the _ITE_. Therefore, it is necessary to analyze the influence factors from the input and output perspective to increase effective output.