## 6 Case Study
### Comprehensive Evaluation of the Integrated Transportation Network
\begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Number** & **City** & \(x_{r}\) & \(x_{a}\) & \(x_{h}\) & \(x_{w}\) & \(C_{s}\) & **Ranking** \\ \hline
1 & Chongqing & 0.468878 & 0.504407 & 0.551215 & 0.515338 & 0.537127 & 2 \\
2 & Wuhan & 0.483948 & 0.507661 & 0.563992 & 0.500424 & 0.545447 & 1 \\
3 & Zhengzhou & 0.495845 & 0.50155 & 0.480866 & 0 & 0.401084 & 34 \\
4 & Suzhou & 0.481240 & 0 & 0.427225 & 0.532996 & 0.450306 & 24 \\
5 & Guangzhou & 0.500474 & 0.498788 & 0.510489 & 0.547004 & 0.515681 & 5 \\
6 & Xi’an & 0.506751 & 0.494832 & 0.571843 & 0 & 0.468879 & 19 \\
7 & Hefei & 0.47762 & 0.48491 & 0.496015 & 0.505258 & 0.495783 & 9 \\
8 & Shenyang & 0.480288 & 0.500712 & 0.475598 & 0 & 0.395705 & 37 \\
9 & Ningbo & 0.483715 & 0.482786 & 0.455729 & 0.527235 & 0.470540 & 18 \\
10 & Changsha & 0.504486 & 0.513417 & 0.434066 & 0.511659 & 0.454045 & 23 \\
11 & Lianyungang & 0.454819 & 0.457044 & 0.50935 & 0.505318 & 0.497178 & 8 \\
12 & Urumqi & 0.507032 & 0.489342 & 0.437345 & 0 & 0.370250 & 44 \\
13 & Harbin & 0.454941 & 0.504578 & 0.477364 & 0 & 0.394531 & 38 \\
14 & Lanzhou & 0.475377 & 0.497409 & 0.515617 & 0 & 0.424580 & 32 \\
15 & Qingdao & 0.499621 & 0.525641 & 0.454680 & 0.538485 & 0.473226 & 16 \\
16 & Kunming & 0.478006 & 0.508767 & 0.530426 & 0 & 0.435700 & 28 \\
17 & Xiamen & 0.466563 & 0.490206 & 0.430196 & 0.524528 & 0.449684 & 25 \\
18 & Changchun & 0.457503 & 0.489678 & 0.464427 & 0 & 0.385290 & 41 \\
19 & Nanchang & 0.503 & 0.511331 & 0.464533 & 0.522685 & 0.478111 & 15 \\
20 & Dalian & 0.458258 & 0.520965 & 0.493271 & 0.518903 & 0.494194 & 10 \\
21 & Dongguan & 0.450085 & 0 & 0.416530 & 0.509409 & 0.435441 & 29 \\
22 & Nanjing & 0.492756 & 0.505921 & 0.483643 & 0.529569 & 0.492293 & 11 \\
23 & Xining & 0.45753 & 0.482772 & 0.477001 & 0 & 0.394515 & 39 \\
24 & Tianjin & 0.496518 & 0.496931 & 0.542425 & 0.537336 & 0.537000 & 3 \\
25 & Taiyuan & 0.476714 & 0.497693 & 0.472072 & 0 & 0.392770 & 40 \\
26 & Shenzhen & 0.484054 & 0.512061 & 0.449829 & 0.524569 & 0.465798 & 20 \\
27 & Jinan & 0.48326 & 0.48285 & 0.478785 & 0 & 0.398330 & 36 \\
28 & Shanghai & 0.493701 & 0.49673 & 0.518560 & 0.542556 & 0.520190 & 4 \\
29 & Tangshan & 0.455568 & 0.45325 & 0.487910 & 0.504278 & 0.487521 & 12 \\
30 & Shijiazhuang & 0.458857 & 0.485398 & 0.449369 & 0 & 0.374376 & 43 \\
31 & Chengdu & 0.509849 & 0.499575 & 0.524607 & 0 & 0.434533 & 30 \\
32 & Yinchuan & 0.432786 & 0.485644 & 0.485985 & 0 & 0.398694 & 35 \\
33 & Nanning & 0.481669 & 0.494052 & 0.493179 & 0.446181 & 0.484117 & 14 \\
34 & Hohhot & 0.470704 & 0.485132 & 0.453534 & 0 & 0.378585 & 42 \\
35 & Hangzhou & 0.466891 & 0.505555 & 0.507410 & 0.514296 & 0.504626 & 7 \\
36 & Fuzhou & 0.42889 & 0.499014 & 0.453631 & 0.524839 & 0.463257 & 21 \\
37 & Guiyang & 0.472797 & 0.504032 & 0.522408 & 0 & 0.429311 & 31 \\
38 & Beijing & 0.471305 & 0.520587 & 0.504772 & 0 & 0.416231 & 33 \\
39 & Xuzhou & 0.452254 & 0.456481 & 0.452537 & 0.487505 & 0.458418 & 22 \\
40 & Quanzhou & 0.427987 & 0.476879 & 0.430582 & 0.510794 & 0.443887 & 27 \\
41 & Jiujiang & 0.458679 & 0 & 0.484654 & 0.507533 & 0.485931 & 13 \\
42 & Yantai & 0.46756 & 0.492713 & 0.511687 & 0.510318 & 0.507155 & 6 \\
43 & Liuzhou & 0.46174 & 0.473039 & 0.480385 & 0.447931 & 0.473085 & 17 \\
44 & Wuxi & 0.440172 & 0.455676 & 0.437343 & 0.482609 & 0.445269 & 26 \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Comprehensive score and ranking of each node city. Based on the spatial layout and government policies under the BRI, with reference to [11], five attributes were employed to analyze the selection of candidate consolidation centers, including service by CR Express, along inland river, along the coast, along the key railway, and the final comprehensive score. Finally, the ten major cities, including Wuhan, Chongqing, Tianjin, Shanghai, Guangzhou, Yantai, Hangzhou, Lianyungang, Hefei, and Dalian, were selected as consolidation centers of the integrated transportation network in this study.