A location choice model explains how travellers choose their trip destinations especially for those activities which are flexible in space and time. The model is usually estimated using travel survey data; however, little is known about how to use smart card data (SCD) for this purpose in a public transport network.
We took three steps in this study:
- First, we extracted trip information from SCD to model location choice of after-work activities;
- We newly defined the metrics of travel impedance in this case;
- Moreover, since socio-demographic information is missing in such anonymous data, we used observable proxy indicators, including commuting distance and the characteristics of one’s home and work locations, to capture some interpersonal heterogeneity. Such heterogeneity is expected to distinguish the population and better explain the difference of their location choice behaviour.
The approach was applied to metro commuters in the city of Shanghai, China. As a result, the model performed well in explaining location choice of after-work activities. Our new metrics of travel impedance to access an after-work activity resulted in a better model fit than the existing metrics and added interpretability to the results. Moreover, the proxy variables distinguishing the population seem to influence the choice behaviour and thus improve the model performance.
Wang, Yihong, Gonçalo Homem de Almeida Correia, Erik de Romph, and H. J. P. Timmermans. “Using metro smart card data to model location choice of after-work activities: An application to Shanghai.” Journal of Transport Geography 63 (2017): 40-47.