## 6 Case Study
### Evaluation of the Single Transportation Mode Networks  
To reflect the changes between the integrated transportation network and the single transportation mode networks, the candidate consolidation centers of the single transportation mode network were first evaluated and analyzed. It can be seen from the overall rankings of the railway transportation network from Table 8 that more connections among the candidate consolidation centers resulted in higher rankings, which is in line with the clustering effect of complex network theory. These cities are important nodes in the Chinese domestic railway transportation network, which plays an important role in railway cargo transportation. In addition, China Railway Express (CR Express) mainly passes through ports such as Manzhouli, Erenhot, and Alashankou to reach Europe. However, from the perspective of geographical area, only Shenyang in Northeast China is in the top 50% and Manzhouli has not played its corresponding role as a port of CR Express due to distance reasons. Correspondingly, Urumqi and Xi'an are ranked high in Northwest China, indicating that the northwest land ports are regarded as the important outbound ports by the cities that are serviced by CR Express in China. Chengdu was one of the earliest cities in China to be serviced by CR Express, and it is \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**ModeWeight** & **Degree** & **Betweenness** & **Closeness** & **Eigenvector** & **Constraint** & **Clustering** \\
**Centrality** & **Centrality** & **Centrality** & **Centrality** & **Coefficient** & **Coefficient** \\ \hline Railway & 0.1939 & 0.1363 & 0.2029 & 0.1994 & 0.1335 & 0.1339 \\ Highway & 0.1533 & 0.1979 & 0.1713 & 0.1681 & 0.1811 & 0.1283 \\ Air & 0.1746 & 0.1750 & 0.2092 & 0.1765 & 0.1489 & 0.1158 \\ Water & 0.1639 & 0.1504 & 0.1613 & 0.1771 & 0.1561 & 0.1911 \\ \hline \hline \end{tabular}
\end{table} 
Table 2: Weights of indicators of railway, highway, air, and water networks. also an important source of cargo consolidation centers. There are three cities in central China, Zhengzhou, Changsha, and Nanchang, which show the importance of the city's geographical location. Currently, these cities have been the important Chinese starting points of CR Express. However, Beijing is not in the top 50%, because its main task is passenger transportation as the capital of China, despite its well-developed rail network. The corresponding rankings of the candidate consolidation centers of the air transportation network are displayed in Table 14. The relevant indicator values for Suzhou, Dongguan, and Jiujiang were set to 0 due to them not having airports operating in air transportation. Similar to the railway transportation network, the more connections there are among node cities, the higher the rankings are. According to the geographical distribution of these cities, one can see that no cities were selected in the northwest region. The reasons are the vast territory, sparse population, backward economic development, or low industrial concentration. In addition, there are a few exceptions. Shanghai and Xi'an are not in the top 50%, although there are more routes among node cities. The reason is that these cities are affected by the direct routes, and the values of structural holes of these direct routes and other indicators are relatively low, resulting in their low ranking. Table 15 shows the corresponding rankings of the candidate consolidation centers of the highway transportation network. Based on the geographical distribution of these cities, the cities in Northeast China are all in the bottom 50%. The reason is that there are fewer national highway connections between cities in the northeast and cities in other regions. Additionally, the relevant indicator values for Dongguan were set to 0 because Dongguan is not connected by the national highway. However, Beijing is at the forefront of the ranking in the highway network because, as the capital of China, the highway network is centered around Beijing.