Research Article
Efficiency Evaluation and Influencing Factors Analysis of Logistics Industry based on Multiobjective Intelligent Computing
Table 4
First-stage logistics industry efficiency.
| Province | Technical efficiency | Ranking | Pure technical efficiency | Ranking | Scale efficiency | Ranking |
| Inner Mongolia | 0.913 | 2 | 1 | 1 | 0.913 | 3 | Guangxi | 0.656 | 7 | 0.752 | 9 | 0.879 | 8 | Hainan | 0.581 | 10 | 0.699 | 10 | 0.825 | 10 | Chongqing | 0.685 | 6 | 0.831 | 6 | 0.847 | 9 | Sichuan | 0.532 | 12 | 0.817 | 8 | 0.671 | 11 | Guizhou | 0.740 | 5 | 0.817 | 7 | 0.907 | 5 | Yunnan | 0.615 | 9 | 0.669 | 12 | 0.901 | 6 | Shaanxi | 0.855 | 3 | 0.956 | 4 | 0.899 | 7 | Gansu | 0.796 | 4 | 0.882 | 5 | 0.908 | 4 | Qinghai | 0.544 | 11 | 0.972 | 3 | 0.560 | 12 | Ningxia | 0.961 | 1 | 1 | 1 | 0.961 | 1 | Xinjiang | 0.645 | 8 | 0.688 | 11 | 0.931 | 2 | Maximum | 0.961 | 1 | 0.961 | Minimum | 0.532 | 0.669 | 0.560 | Average | 0.71 | 0.84 | 0.85 |
|
|
Note. Provincial averages for technical efficiency, pure technical efficiency, and scale efficiency range from 2010 to 2019.
|