01661406

Component

The aim of this study is twofold: 1. to describe the procedure of matching longitudinal smartphone based travel survey data with open operational data, and 2. to quantify the effect of both types of data on customers satisfaction with using rail-based public transport modes. The travel data utilized in this paper originate from the smartphone-based London Mobility Survey (LMS) and was collected between November 2016 to February 2017. The open data matched to the LMS data has been derived from the open TfL API. An ordered logit model is developed to quantify the effect of public transport service status, and individuals’ socio-demographic and trip characteristics on satisfaction with using public transport mode for each one of their trip-stages. The authors' results indicate that customer satisfaction is indeed associated with the open public transport status data and that satisfaction depends on each trip and the conditions of the trip. Activities while travelling and trip purpose also affect customers satisfactions, while these results provide insights for offering products that can advance customers experience in the Mobility-as-a-Service and automated vehicles era that lies ahead.

This paper was sponsored by TRB committee AP000 Public Transportation Group.

18-05772

English

21p

2018

Transportation Research Board 97th Annual Meeting

Digital/other

Figures; References; Tables

Customer satisfaction; Logits; Machine learning; Mobility; Public transit; Smartphones; Travel surveys

Open data; Travel data

Greater London

Data and Information Technology; Planning and Forecasting; Public Transportation

Transportation Research Board Annual Meeting 2018 Paper #18-05772

TRIS, TRB, ATRI

Jan 8 2018 11:29AM