Research on the Impact of Logistics Technology Progress on Employment Structure Based on DEA-Malmquist Method
Table 8
Regression analysis results of each logistics segment industry model.
Research study variables
Subdivided industry
Model (3)
Model (4)
Proportion of employees with college degree and above (Y1)
Percentage of nonproductive personnel (Y2)
Constant Ci
Air transport industry
0.592990
0.470530
Road transport industry
0.343011
0.337696
Water transport industry
0.391089
0.265077
Skill improved X1i
Air transport industry
0.394020
−0.132142
Road transport industry
0.096592
0.284305
Water transport industry
0.044584
0.011655
Enterprise size X2i
Air transport industry
0.323837
−0.318394
Road transport industry
1.499344
0.488669
Water transport industry
0.487271
−0.553805
Training structure X3i
Air transport industry
0.036073
−0.103128
Road transport industry
0.389798
0.408890
Water transport industry
0.242129
−0.787076
Salary structure X4i
Air transport industry
0.130568
0.020490
Road transport industry
3.757804
−2.709841
Water transport industry
0.865081
2.224235
Note. X1i, X2i, X3i, and X4i in the table represent three different subindustries corresponding to technological progress, enterprise scale, training structure, and work structure variables, respectively. For example, X11 represents the technological progress of the air transport industry, where i = 1, 2, 3. In addition, and indicate the significance level of 10%, 5%, and 1%, respectively.
