Assessing longitudinal stability of public transport users with smartcard data
Sep-2020
Study addresses the applicability of the temporal segmented data identified in 18 clusters for measuring the stability of users' temporal habits as well as conducting descriptive analysis of the clusters, fare types and dates of the week to support their findings.
Big data for big issues: Revealing travel patterns of low-income population based on smartcard data mining in a global south unequal city
Sep-2021
Study makes use of smart card data mining to compare the urban transit movements of low income residents with middle/high income residents. Research finds that most lower income residents start their journey between 05:00 - 07:00, whilst higher income residents start between 07:00 - 09:00. Paper suggests that the empirical evidence from this paper shows the potential of smart card data to infold low employment spatial and temporal patterns.
Discovering the evolution of urban structure using smartcard data: The case of London
Dec-2020
Study intended to examine how urban spatial structures evolve, specifically focusing on incentives behind movement dynamics. The study makes use of network community detection and smart card data from the years 2013, 2015, and 2017 from Greater London. Study found that London's urban structure has become more polycentric and compact, that Greater London can be clustered into five distinct communities based on characteristics of passengers' travel patterns, and that the dynamics of structural change in different urban clusters differ in both changing intensity and potential motivation.
Individual mobility pattern prediction using smartcard data
Jan-2018
Study intends to develop a system of prediction for determining if a transport user will make another trip, and if so, the attributes of said trip. The researchers tested their methodology using smart card records from over 10,000 users in London, over two years. The model was able to achieve median accuracy levels of over 80%, with the study finding the first trip of the day hardest to predict. The study also found significant variations found across individuals, implying diverse travel behaviour patterns.
Variability in regularity: Mining temporal mobility patterns in London, Singapore and Beijing using smartcard data
Feb-2016
Study investigates regularities in human mobility, questioning if the detected regularities are stable, explicable and sustainable. The study makes use of 1 week of smart card data from three world cities (London, Singapore and Beijing), intending to contribute to a deeper understanding of regularities in patterns of transport use, establishing a general analytical framework for comparative studies using urban mobility data.
Measuring the influence of bus service quality on the perception of passengers
Nov-2015
Study analyses data from 512 questionnaires conducted in Belfast to determine the influence that perceived bus quality has upon the perceptions of both current and potential users. Research identifies 11 significant indicators that are reported to have a significant influence on the perception of bus users. The study uses these indicators to suggest optimisations that could be made to improve quality of bus services with the perceptions of current and potential users.
Using smartcard data to model public transport user profiles in light of the COVID-19 pandemic
Jun-2023
Study aiming to identify passenger profiles using smartcard in Santiago, Chile by studying their recovery post pandemic. The study identified two groups: those who returned to their pre-pandemic patterns, and those who adapted their mobility patterns.
AI-based neural network models for bus passenger demand forecasting using smartcard data
May-2022
Study intends to improve short -term forecasting of public transport demand, using AI-based deep learning models for prediction of bus passenger demands based on real patronage data obtained from the smartcard ticketing system in Melbourne. Study found that the models were able to predict passenger demand with over 90% accuracy.
Integrated transport planning: The ‘Rehabilitation’ of a contested concept in UK bus reforms
May-2019
Study makes the case against policies of austerity and competition which have been applied to the UK's local public transport systems. The study urges for greater coordination within the sector to tackle social, environmental, financial and sustainability issues.
An ideal journey: making bus travel more desirable
Apr-2016
Study exploring the ways people make use of their time whilst on buses, and how the knowledge can be used to make bus travel more appealing and drive modal shift away from private cars. Study combines a 840 person survey of bus users in Bristol, with an analysis of online discussions and focus groups.
Identifying human mobility patterns using smart card data
Aug-2023
Study conducts systematic review into the use of smart card data for analysing mobility patterns, noting that clustering and segmentation techniques have been adapted to conduct market segmentation and analyse urban activity locations.
Seamless public transport ticket inspection: Exploring users’ reaction to next generation ticket inspection
Apr-2022
Study investigates ticket inspection preferences and identified factors that may influence a user's likelihood of accepting "seamless" ticket inspection. Study found that, given the five inspection options, women and young people selected "seamless ticket inspection". The study recommends further research on aspects surrounding "seamless ticket inspection".
User’s willingness to ride an integrated public-transport service: A literature review
Mar-2016
Study evaluating existing literature on focused on factors influencing mode changes towards an integrated public transport system. Study highlights the importance of effective transfers for integrated transport, as a smoother transfer between modes should improve the service. The study notes the lack of existing literature on the psychological aspect of transfers and cites this as a major shortcoming when attempting to improve the transfer experience.
Bridging the digital divide: Consumer engagement with transportation payment apps in emerging economies
Aug-2024
Study makes use of ethnographic observation, semi-structured interviews, and the ALARA model of information search to examine consumer engagement with mobile payment apps in Lagos, Nigeria. Study finds that cultural preferences and trust in traditional payment systems significantly impact willingness to adopt mobile apps. The study recommends an inclusive technological strategy, developing accessible information channels and user-friendly design features, engaging with users to make continuous improvements to the app and adopting a nuanced understanding of socio-cultural influences on technology adoption to inform policy and business strategies.
Improving public transport through machine learning influence flow analysis (MIFA): Southern England bus case study
Apr-2025
Paper introduces a Machine Learning Influence Flow Analysis framework intended to identify key influencers of public transport usage. Study finds that easy payments, e-ticketing and mobile applications can substantially improve public transport service. Study recommends making use of smart ticketing systems and contactless payments to enable more efficient allocation of resources, resulting in a more streamlined service that encourages increased ridership and improves user satisfaction.
Financial inclusion as an important factor influencing digital payments in passenger transport: A case study of EU countries
Jun-2021
Study into the influences on digital payments in the EU. Research finds that level of digital payments is dependent on the degree of mobile device usage as well as the level of financial inclusion provided through electronic banking services.
Retaining bus riders: A lifecycle longitudinal analysis of behavioural status transitions from entry to exit
Jun-2024
Using smart card data, study aims to analyse user behaviour to determine how users may begin to transition away from bus user. Study notes that users first decrease travel frequency before transitioning to irregular travel patterns. Study recommends retention policies such as tiered usage incentives and personalised communication strategies, aimed at different stages of the user life cycle.
Evaluation of an integrated mobile payment, route planner and social network solution for public transport
Jun-2017
Paper presents a concept for an integrated mobile payment, route planning and social network platform for public transport. The concept aims to incorporate various features together to improve transport user experiences. The concept was tested in Porto, Portugal using a mobile app called OneRide. Results showed that users found the app to be highly valuable, with some users taking time to adapt to the concept.
Demographic disparities, service efficiency, safety and user satisfaction in public bus transit system: A survey-based case study in the City of Charlotte, NC
Dec-2024
Study concerning attitudes towards service limitations, safety concerns and technological improvements through a demographic lens. The research finds that East Charlotte residents and women face limited routes and longer wait times, black and East Charlotte residents have higher concerns about safety, there are privacy concerns among wealthier and infrequent users and there is strong preference for technological improvements, especially among infrequent users.
Can transit apps boost ridership? An empirical study in San Antonio, Texas
May-2025
Study investigates the impact of a mobile app on bus ridership in San Antonio, Texas. Study used random effect regression models to analyse the transit app influence on ridership between 2015 and 2019, accounting for various alternative ridership influences such as fare changes, route characteristics, weather, socioeconomic conditions and the price of petrol. Research found that the app had a positive impact on ridership for infrequent routes, but had less of an impact on frequent services.