## 5 Results and Discussion
### Global Impact on Metro Ridership  
The average value of the absolute value of each explanatory variable SHAP is calculated and the influence degree of the explanatory variable on metro ridership is expressed. The greater the mean value of SHAP, the greater the influence of the explanatory variables on metro ridership and vice versa. The results of the average SHAP values of the explanatory variables for ridership at metro stations in different zones are shown in Figures 5 and 6, with positive correlations in red and negative correlations in blue.  
For metro stations inside the 4 th Ring Road, the top three explanatory variables in the order of the influence degree are the number of entrances and exits > mixed utilization of land > the density of bus lines. There is a positive relationship between all three explanatory variables and SHAP values (Figure 5), i.e., the larger the eigenvalues of these three explanatory variables, the larger the SHAP values. This means that the larger these three explanatory variables are, the greater the impact on metro ridership. The mixed utilization of land has a large impact on metro ridership. That proves that the mixed utilization of land development has a strong promoting effect on metro ridership. That is consistent with the existing research [21]. However, as a very important index of land development, the floor area ratio is negatively correlated with metro ridership. It is proved  
Figure 5: Global impact of explanatory variables on metro ridership inside the 4 th Ring Road.  
Figure 6: Global impact of explanatory variables on metro ridership outside the 4 th Ring Road.  
that for the metro station in the 4 th Ring Road, the ridership of metro stations with a higher floor area ratio is not necessarily higher. The likely reason is that the higher floor area ratios are generally concentrated in the core commercial office areas, where the morning peak is dominated by alighting ridership and does not generate much boarding ridership. Conversely, residential cores can generate high boarding ridership, but have a relatively low floor area ratio due to design constraints. The effect of population on ridership at metro stations inside the 4 th Ring Road is positive, which is consistent with existing studies [4; 36].  
For metro stations outside the 4 th Ring Road, the top three explanatory variables in the order of the influence degree are the number of public services facilities > building density > road density (Figure 6). Building density is negatively correlated with metro ridership and road density is negatively correlated with metro ridership. And, the average SHAP value for the number of office facilities is much greater than the average SHAP values for building density and road density. This proves that for metro stations outside the 4 th Ring Road, the number of public service facilities is the explanatory variable with the greatest degree of influence. That said, for metro stations outside the 4 th Ring Road, it may be more effective to adjust the ridership of metro stations by adjusting the number of public service facilities.  
Figures 5 and 6 show that there is a significant difference in the ranking of the effects of the explanatory variables on metro ridership inside and outside the 4 th Ring Road. This demonstrates the need for this study partition to examine the built environment's impact on metro ridership. Understanding the global impact of built environment explanatory variables on metro ridership in both zones can help planning decision makers and operations and design departments to adjust metro ridership from a zone-wide perspective.