## 5 Results and Discussion
### Nonlinear Effect between Built Environment and Bus-Metro-Transfer Ridership  
This section may be divided by subheadings. It should provide a concise and precise description of the experimental results, their interpretation, as well as the experimental conclusions that can be drawn. Figure 4 describes the nonlinear influence of the four independent variables of the bus-metro connection characteristics on transfer ridership. Figure 4a shows the positive association between bus-network density and bus-metro-transfer ridership. When the bus-network density around metro stations is 4 km to 11 km per square kilometer, the transfer ridership shows a slow upward trend. When the bus-network density is 11 km to 13 km per square kilometer, the transfer ridership increases rapidly. However, the transfer ridership decreases slightly between 11 km and 12.5 km. When it rises to about 7000, the transfer ridership tends to be stable, after a period of time. The result implies that increasing the bus-network density helps increase the transfer ridership. It, however, has little effect on attracting transfer ridership, when the bus-network density increases to a threshold of 12.8 km per square kilometer. \begin{table}
\begin{tabular}{l c c} \hline \hline
**Variables** & **Relative Importance (\%)** & **Rank** \\ \hline _Bus–Metro Connection Characteristics (53.77\%)_ & & \\ Bus-network density & 27.56 & 1 \\ Bus-stop density & 17.27 & 3 \\ Network repetition ratio of bus–metro & 8.49 & 4 \\ Average transfer distance & 0.45 & 15 \\ _Network attributes of metro stations (22.1\%)_ & & \\ Closeness centrality & 21.6 & 2 \\ Distance to the central station & 0.5 & 14 \\ _Land-use attributes for trip attraction (5.39\%)_ & & \\ Commercial ratio & 3.28 & 7 \\ Employment density & 1.97 & 9 \\ Industrial ratio & 0.14 & 16 \\ _Land-use attributes for trip production (0.11\%)_ & & \\ Residential ratio & 0.11 & 17 \\ _Other land-use attributes (0.77\%)_ & & \\ Land-use diversity & 0.72 & 12 \\ Street density & 0.05 & 18 \\ _Demographic factors (17.86\%)_ & & \\ Average age & 6.18 & 5 \\ Population density (age between 20 and 44) & 5.73 & 6 \\ Average house size & 2.26 & 8 \\ Car ownership & 1.68 & 10 \\ Local population density & 1.37 & 11 \\ PGDP & 0.63 & 13 \\ Housing price & 0.01 & 19 \\ \hline \hline \end{tabular}
\end{table} 
Table 4: The relative importance of independent variables in predicting transfer ridership. Figure 4b shows the significant nonlinear relationship between the average transfer distance and bus-metro-transfer ridership. Transfer ridership presents a higher value, when the average transfer distance is between 0.15 km and 0.18 km. This implies that the transfer distance within the range has a high attraction for travelers, to travel with the bus-metro combination. When the average transfer distance exceeds 0.18 km, the transfer distance has a negative impact on the transfer ridership, indicating that too large a transfer distance will reduce the transfer intention of passengers. Similarly, a study [35] explored that the less transfer walking time and waiting time there is, the higher the probability of people choosing combined travel. Research [92] obtained the conclusion that it was better to build new metro stations within 0.55 km, around existing bus stations, and within 0.25 km, of new bus stations, around the existing metro stations. Figure 4c illustrates the positive influence of the network repetition ratio of bus-metro on the bus-metro-transfer ridership. When it is less than 0.07, the repetition ratio has almost no effect on transfer ridership. When the repetition ratio increases from 0.07 to 0.2, the transfer ridership increases continuously, but it decreases slightly between 0.11 and 0.115. When the repetition ratio exceeds 0.2, the transfer ridership tends to be stable. The result shows that the lower network-repetition ratio of bus-metro is not conducive to form a closely connected bus-metro-transfer hub.