Travel Behaviour and Society

(The H4-Index of Travel Behaviour and Society is 34. The table below lists those papers that are above that threshold based on CrossRef citation counts [max. 250 papers]. The publications cover those that have been published in the past four years, i.e., from 2020-04-01 to 2024-04-01.)
Prediction and behavioral analysis of travel mode choice: A comparison of machine learning and logit models182
Dockless E-scooter usage patterns and urban built Environments: A comparison study of Austin, TX, and Minneapolis, MN152
COVID-19, activity and mobility patterns in Bogotá. Are we ready for a ‘15-minute city’?88
Commute satisfaction, neighborhood satisfaction, and housing satisfaction as predictors of subjective well-being and indicators of urban livability86
Ready for Mobility as a Service? Insights from stakeholders and end-users74
Future implementation of mobility as a service (MaaS): Results of an international Delphi study66
Why travelers trust and accept self-driving cars: An empirical study56
The role of habit and the built environment in the willingness to commute by bicycle53
Spatial accessibility assessment of COVID-19 patients to healthcare facilities: A case study of Florida51
Relationships of the multi-scale built environment with active commuting, body mass index, and life satisfaction in China: A GSEM-based analysis51
A big data approach to understanding pedestrian route choice preferences: Evidence from San Francisco50
Who are the potential users of shared e-scooters? An examination of socio-demographic, attitudinal and environmental factors49
Creation of mobility packages based on the MaaS concept48
Modelling work- and non-work-based trip patterns during transition to lockdown period of COVID-19 pandemic in India47
Who is interested in a crowdsourced last mile? A segmentation of attitudinal profiles45
An exploratory investigation of public perceptions towards key benefits and concerns from the future use of flying cars43
Personal and societal impacts of motorcycle ban policy on motorcyclists’ home-to-work morning commute in China41
Measuring spatial mismatch and job access inequity based on transit-based job accessibility for poor job seekers41
Long commutes and transport inequity in China’s growing megacity: New evidence from Beijing using mobile phone data40
Investigating heterogeneity in preferences for Mobility-as-a-Service plans through a latent class choice model40
Predicting the travel mode choice with interpretable machine learning techniques: A comparative study39
Young people's perceived service quality and environmental performance of hybrid electric bus service39
Perception of the built environment and walking in pericentral neighbourhoods in Santiago, Chile38
Understanding user practices in mobility service systems: Results from studying large scale corporate MaaS in practice38
Factors influencing consumer acceptance of vehicle-to-grid by electric vehicle drivers in the Netherlands38
Impacts of personalized accessibility information on residential location choice and travel behavior38
Understanding electric bike riders’ intention to violate traffic rules and accident proneness in China37
Public transit travel choice in the post COVID-19 pandemic era: An application of the extended Theory of Planned behavior36
A comparative analysis of the users of private cars and public transportation for intermodal options under Mobility-as-a-Service in Seoul35
Examining public acceptance of autonomous mobility35
Investigating day-to-day variability of transit usage on a multimonth scale with smart card data. A case study in Lyon34
The impact of shared mobility on trip generation behavior in the US: Findings from the 2017 National Household Travel Survey34
Exploring rider satisfaction with arterial BRT: An application of impact asymmetry analysis34
Public transport users versus private vehicle users: Differences about quality of service, satisfaction and attitudes toward public transport in Madrid (Spain)34