## 4 Empirical Analysis
### Results Analysis and Discussion  
#### 4.2.1 Evaluation of Integrated Transport Efficiency  
Using Formula (1), we calculated the \(ITE\) values from 2009 to 2016 for the 31 provinces, as summarized in Table 3. \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline  & **Index** & **Minimal** & **Maximal** & **Mean** &
\begin{tabular}{c} **Standard** \\ **Deviation** \\ \end{tabular} \\ \hline \multirow{3}{*}{inputs} & Fixed asset investment & 78.89 & 3516.28 & 918.68 & 643.47 \\  & Number of employees & 3290 & 635,533 & 178,217.08 & 117,576.54 \\  & Energy consumption & 114.83 & 20,275.60 & 1656.10 & 3174.61 \\ \hline \multirow{3}{*}{desirable outputs} & added value in transport industry & 21.19 & 3209.72 & 892.34 & 676.16 \\  & Passenger turnover & 29.98 & 2998.23 & 771.99 & 554.23 \\  & Freight turnover & 35.34 & 21,801.65 & 4772.51 & 4455.83 \\ \hline \multirow{3}{*}{undesirable outputs} & Carbon dioxide emissions & 78.08 & 13,787.41 & 1126.15 & 2158.73 \\  & Traffic accident property loss & 290.54 & 10,726.59 & 3392.20 & 2255.92 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: The statistical description of input and output indexes. \begin{table}
\begin{tabular}{c c c c c c c c c c} \hline \hline
**Province** & **2009** & **2010** & **2011** & **2012** & **2013** & **2014** & **2015** & **2016** & **Average ITE** \\ \hline Beijing & 0.58 & 0.60 & 0.78 & 0.89 & 0.98 & 1.03 & 1.00 & 1.02 & 0.86 \\ Tianjin & 1.15 & 1.14 & 1.14 & 1.32 & 1.20 & 1.05 & 1.03 & 1.04 & 1.13 \\ Hebei & 1.07 & 1.07 & 1.07 & 1.13 & 1.22 & 1.16 & 1.23 & 1.21 & 1.15 \\ Shanxi & 0.39 & 0.39 & 0.48 & 0.52 & 0.56 & 0.68 & 0.63 & 0.75 & 0.55 \\ Inner Mongolia & 0.84 & 0.73 & 0.93 & 0.95 & 0.87 & 0.83 & 0.90 & 0.84 & 0.86 \\ Liaoning & 0.61 & 0.59 & 0.79 & 0.69 & 0.83 & 0.75 & 0.92 & 0.90 & 0.76 \\ Jilin & 0.58 & 0.49 & 0.56 & 0.54 & 0.65 & 0.61 & 0.66 & 0.73 & 0.60 \\ Heilongjiang & 0.47 & 0.42 & 0.34 & 0.35 & 0.39 & 0.47 & 0.54 & 0.67 & 0.46 \\ Shanghai & 1.19 & 1.28 & 1.26 & 1.20 & 1.28 & 1.30 & 1.24 & 1.25 & 1.25 \\ Jiangsu & 1.05 & 1.06 & 1.04 & 1.02 & 0.98 & 0.87 & 0.93 & 0.87 & 0.98 \\ Zhejiang & 0.59 & 0.64 & 0.51 & 0.57 & 0.61 & 0.65 & 0.58 & 0.79 & 0.62 \\ Anhui & 1.14 & 1.11 & 1.10 & 1.19 & 1.05 & 1.12 & 1.08 & 1.05 & 1.11 \\ Fujian & 0.66 & 0.58 & 0.47 & 0.54 & 0.56 & 0.67 & 0.58 & 0.84 & 0.61 \\ Jiangxi & 1.03 & 1.01 & 0.89 & 0.66 & 0.87 & 0.93 & 1.01 & 1.03 & 0.93 \\ Shandong & 1.09 & 1.01 & 1.02 & 1.05 & 0.78 & 0.64 & 0.79 & 0.83 & 0.90 \\ Henan & 1.03 & 1.07 & 1.13 & 1.09 & 1.08 & 1.09 & 1.07 & 1.06 & 1.08 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: \(ITE\) results from 2009 to 2016. Figure 2: Total carbon emissions of integrated transport. Calculating the results in Table 2, we found that the average _ITE_ of the 31 provinces increased over time in a straight line. However, the number of effective provinces (i.e., _ITEs_ greater than 1) was clearly lacking and only about 22.58% from the perspective of average _ITE_. By 2016, there were only 11 provinces with a transport efficiency value greater than 1, accounting for about 35%. This indicates the need to adjust the amount of investment into the transport resources of each province as well as to improve the effective outputs. From the perspective of changes in integrated transport efficiency, the _ITE_ values in Beijing, Shanxi, Hubei, Hunan, Yunnan, Shaanxi and Ningxia showed a linear upward trend, reflecting the gradual increase in the effective use of input elements in these regions. Among them, Beijing and Hunan achieved the value of effective decision making units in 2014 and 2013, respectively, reflecting the largest output of input factors. Conversely, the _ITE_ value in Jiangsu began to decline slightly in 2013. One of the main reasons for this was the redundant input of fixed assets investment. The _ITE_ has changed volatlily from 2014 to 2016 in Jiangsu. In addition, the _ITE_ value in Jiangxi manifests the phenomenon of first decreasing and then increasing, with a difference of 0.37 between the minimum and maximum efficiency values.