## 2 Literature Review  
The study of transport efficiency first emerged in the mid-to-late 1970s and mainly focused on Western countries [4; 5]. To date, scholars have achieved rich results in studies on transport efficiency [6; 7; 8; 9; 10], and the current studies tend to be conducted from two research perspectives. The first is the study of the technical efficiency of different transport modes. For example, [PERSON] et al. calculated the technical efficiency of different public transport types and put forward the way of improving transport efficiency in metropolitan areas [11]. [PERSON] et al. analyzed the general technical, pure technical and scale efficiency of 34 Italian airports by means of the Data Envelopment Analysis (DEA) method [12]. The DEA-BCC model was applied to evaluate the effectiveness of highway transport efficiency in the Yangtze River Delta Region, and further to analyze the problems of non-DEA effective units from the perspective of input redundancy and output insufficiency, respectively [13]. Traditional DEA and the Malmquist index model were used to measure water transport efficiency in the Yangtze River Economic Zone [14]. [PERSON] et al. constructed a DEA model to measure the efficiency of selected European countries in terms of the transport accessibility of freight transport by road and rail [15]. [PERSON] et al. studied the technical efficiency of the urban rail transit system using DEA [16]. A two-stage combination of Stochastic Data Envelopment Analysis was used to analyze urban transportation efficiency in 285 cities of the world [17]. [PERSON] et al. proposed a novel slack-based measure network DEA to measure the technical efficiency of airlines [18]. [PERSON] and [PERSON] evaluated the transport efficiency of off-peak urban goods deliveries, studying transport efficiency in a number of dimensions including driving efficiency, delivery reliability, energy efficiency and service efficiency [19]. The two-stage DEA was used to assess the efficiency of Brazilian rail freight transport between 2010 and 2014 [20]. The second evaluation facet has mainly focused on the environmental and energy efficiency of transport [21; 22; 23]. For example, a non-radial DEA model was used to measure the regional energy and environmental efficiency of China's transport sector, considering undesirable outputs [24]. A parallel slack-based measure model (SBM) was proposed and used to evaluate the overall environmental efficiency of the land transport sector, individual environmental efficiencies of railway transport, and highway transport subsectors [25]. Another study examined the energy efficiency of China's transport sector from 2003 to 2009 using a DEA approach [26]. [PERSON] et al. combined the super-efficiency slack-based measure model (Super-SBM DEA) to calculate the environmental efficiencies of highway transport systems in different regions of China [27], with a key focus on the problems of energy consumption and pollutant emissions of highway transport. As highlighted by the studies reviewed, thus far, the most common method used in transport efficiency research is DEA--an effective, non-parametric method favored by numerous scholars [28; 29; 30; 31]. The reason DEA is so frequently used to analyze efficiency is that it does not require any prior assumptions to be made about the underlying functional relationships between inputs and outputs [32; 33; 34]. The traditional DEA model has also been gradually improved and innovated upon. For example, a slack-based measure DEA model was used to analyze the efficiency of China's transport sector in 2009 [35]. Based on the DEA method, another study assessed road transport efficiency by using the value added of the road transport industry and passenger and cargo turnover as outputs, finding clear regional differences in the efficiency of road transport [36]. Other research has also taken the added value of the road transport industry, passenger volume, freight and turnover as outputs to measure road transport efficiency [37].