Using metro smart card data to model location choice of after-work activities: An application to Shanghai

Yihong Wang, Gonçalo Homem de Almeida Correia, Erik de Romph, H. J.P.(Harry) Timmermans

Research output: Contribution to journalArticleScientificpeer-review

34 Citations (Scopus)
27 Downloads (Pure)

Abstract

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. Our study 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 workplace stations, 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 travellers in the city of Shanghai, China. As a result, the model performs well in explaining the choices. Our new metrics of travel impedance to access an after-work activity result in a better model fit than the existing metrics and add additional interpretability to the results. Moreover, the proxy variables distinguishing the population seem to influence the choice behaviour and thus improve the model performance.

Original languageEnglish
Pages (from-to)40-47
Number of pages8
JournalJournal of Transport Geography
Volume63
DOIs
Publication statusPublished - 1 Jul 2017

Keywords

  • demand forecast
  • discrete choice model
  • location choice modelling
  • Public transport
  • smart card data
  • transport planning

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