Research Article
With Whom Transport Operators Should Partner? An Urban Mobility and Services Geolocation Data Analysis
@INPROCEEDINGS{10.1007/978-3-030-14757-0_10, author={Marta Ferreira and Teresa Dias and Jo\"{a}o e Cunha}, title={With Whom Transport Operators Should Partner? An Urban Mobility and Services Geolocation Data Analysis}, proceedings={Intelligent Transport Systems, From Research and Development to the Market Uptake. Second EAI International Conference, INTSYS 2018, Guimar\"{a}es, Portugal, November 21--23, 2018, Proceedings}, proceedings_a={INTSYS}, year={2019}, month={2}, keywords={Public transport AFC systems Points-of-Interest}, doi={10.1007/978-3-030-14757-0_10} }- Marta Ferreira
Teresa Dias
João e Cunha
Year: 2019
With Whom Transport Operators Should Partner? An Urban Mobility and Services Geolocation Data Analysis
INTSYS
Springer
DOI: 10.1007/978-3-030-14757-0_10
Abstract
Automated Fare Collection (AFC) systems produce a large amount of very detailed data, which analysis may be very useful to authorities and transport planners to define future service delivery strategies. Such analysis can be further improved by relating to other data sources, such as points-of-interest (POI) data. As a result public transport operators are able to identify the city service providers with whom it would be more interesting to establish partnerships and propose joint value propositions benefiting both service providers. The objective of such partnerships is to attract new customers and retain those that already exist by providing combined offers, discounts or loyalty schemes. The potential of such analysis is demonstrated by using data related to the city of Porto, Portugal. This study relies on two different data sources: AFC system data and points-of interest data. Urban mobility data is used to identify mobility patterns of different segments of passengers and points-of-interest data is used to analyse the type of services that are likely to concentrate around public transport stations. The results allowed to identify the potential city services to establish partnerships according to the mobility profiles of passengers and the concentration levels of services around public transport stations.
