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Civil-Comp Conferences
ISSN 2753-3239
CCC: 1
PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON RAILWAY TECHNOLOGY: RESEARCH, DEVELOPMENT AND MAINTENANCE
Edited by: J. Pombo
Paper 23.23

What factors affect travellers to use ride-sharing with rail services in EU?

A. Kortsari and L. Mitropoulos

Centre for Research and Technology Hellas, Hellenic Institute of Transport, Greece

Full Bibliographic Reference for this paper
A. Kortsari, L. Mitropoulos, "What factors affect travellers to use ride-sharing with rail services in EU?", in J. Pombo, (Editor), "Proceedings of the Fifth International Conference on Railway Technology: Research, Development and Maintenance", Civil-Comp Press, Edinburgh, UK, Online volume: CCC 1, Paper 23.23, 2022, doi:10.4203/ccc.1.23.23
Keywords: ride-sharing, carpooling, factors, attitude, public transport, intermodal.

Abstract
Ride-sharing services promote sustainable transport as they reduce car use and minimize negative impacts related to environment and transport efficiency. Several studies have focused on understanding travellers’ attitudes and characteristics toward using ride-sharing services; however, just a few have focused on the travellers’ behaviour and ride-sharing services that are organized to feed public transport. This research investigates the factors that may affect travellers to accept a ride-sharing ride, as part of their trip, to/from public transport stations (i.e., rail, tram and metro). A survey is conducted in EU27 and the UK, by means of a conversational survey. In total 565 questionnaires are completed capturing travellers’ preferences when using ride-sharing with public transport. An analysis is performed on the basis of four user types: Household work user, Solo work user, Education user, and Recreation/entertainment user. A set of 33 factors is defined based on the set questions, that represent the reasons, motives and constraints the travellers may consider when using ride-sharing with public transport. Useful insights are provided by using descriptive and bivariate statistics to explore the relationships between individual variables and defined factors. Binary logit models are built to explore and estimate the likelihood of using ride-sharing with public transport as a traveller. The analysis shows that although socio-demographic variables are not correlated with ride-sharing, other factors in this report are found to be significant in planning of ride-sharing services with public transport. A sample of important recommendations include: the availability of the ride-sharing service through a smartphone application; availability of services in areas that lack or with low frequency of public transport; the reduction of journey cost; the accepted delay time - less than 5 minutes; the accepted ride-sharing time – 15 minutes; the ability to check the driver’s ID through the application and the availability of driver’s experience to all users upon request.

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