Understanding the Role of Built Environment and Accessibility Measures on Smartphone-based Transport-support Application Usage in Daily Trip Planning Purposes

This paper examines smartphone-based transport-support application usage for daily trip planning purposes, specifically, in the case of deciding departure time and trip destinations. Using a smartphone survey data, this study develops two latent segmentation-based random parameter logit (LSRPL) models that accommodate two layers of unobserved heterogeneity by introducing latent segments and random parameters within the modeling framework. It develops latent segment allocation models within LSRPL model formulations based on individuals’ socio-demographic characteristics, and probabilistically identifies two latent segments – tech savvy and non-tech savvy segments. The study exclusively estimates the influence of built environment and accessibility measures on transport-support application usage in trip planning purposes. For instance, people tend to use transport-support application more to decide their departure time while living in higher mixed land-use neighborhoods, whereas they have higher likelihood to use less transport-support applications to decide their trip destinations. Also, considerable heterogeneity is found during model analysis. For example, commuting by transit and a higher number of bikes in the household increases tech savvy individuals’ probability of higher TSA usage while deciding departure time. Non-tech savvy individuals on the other hand exhibit opposite relationships. Furthermore, heterogeneity is observed within both tech savvy and non-tech savvy segments that represent the preference variations among individuals with similar characteristics. Results of this study could be useful to evaluate ICT-based smart city policies that focus on improving quality and performance of overall transportation infrastructure.


  • English

Media Info

  • Media Type: Digital/other
  • Features: References; Tables;
  • Pagination: 16p

Subject/Index Terms

Filing Info

  • Accession Number: 01764126
  • Record Type: Publication
  • Report/Paper Numbers: TRBAM-21-00980
  • Files: TRIS, TRB, ATRI
  • Created Date: Dec 23 2020 11:20AM