OOIR: Observatory of International Research

Papers

(The H4-Index of Travel Behaviour and Society is 36. 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 2022-06-01 to 2026-06-01.)

Article	Citations
Learning from user behavior: A survey-assist algorithm for longitudinal mobility data collection	142
Modeling evacuation activities amid compound hazards: Insights from hurricane Irma in Southeast Florida	135
Editorial Board	108
Impact of traffic campaigns on the average speed of vehicles on urban roads	100
Daily trip making during the COVID-19 pandemic: A national survey of older adults in the United States	97
Accessible taxi routing strategy based on travel behavior of people with disabilities incorporating vehicle routing problem and Gaussian mixture model	94
E-scooters in Qatar: Public perception, adoption intentions, and implications for urban mobility policy	86
Nowhere to go – Effects on elderly's travel during Covid-19	84
To grab or not? Revealing determinants of drivers’ willingness to grab orders in on-demand ride services	78
Identifying the heterogeneous effects of road characteristics on Motorcycle-Involved crash severities	76
Using Realtime GTFS to generate easy-to-use transit accessibility measures under travel time uncertainty	75
Investigating Opportunities in Crowd-Shipping by Parcel Receivers: A Behavioural Analysis	61
Impact of operating speed, roadway curvature, and precipitation on roadway departure risk in rural two-lane roads	61
Understanding cyclists’ conflicts in the streets of a Latin American metropolis	59
Demand responsive transport: New insights from peri-urban experiences	55
Decoding electric vehicle adoption using XGBoost and SHAP analysis	49
Gender difference in commuting travel: A comparative study of suburban residents in Beijing and Shanghai	49
Understanding factors associated with individuals’ non-mandatory activities using machine learning and SHAP interpretation: A case study of Guangzhou, China	47
Understanding short-distance travel to school in Singapore: A data-driven approach	46
Exploring the diversity of users of digital mobility services by developing personas – A case study of the Barcelona metropolitan area	46
Dynamic community detection considering daily rhythms of human mobility	46
Beyond time and cost: exploring the importance of factors in travel mode choices	44
A deeper look at switching intention to electric moped: Magnitude vs Uncertainty	44
Safety or efficiency? Estimating crossing motivations of intoxicated pedestrians by leveraging the inverse reinforcement learning	43
Evaluating the role of ride-hailing in multimodal travel to maximize travel utility in urban areas	40

Investigating emotion fluctuations in driving behaviors of online car-hailing drivers using naturalistic driving data	40
Misinformation and misperception in the market for parking	40
“I am dependent on others to get there”: Mobility barriers and solutions for societal participation by persons with disabilities	40
How daily activities and built environment affect health? A latent segmentation-based random parameter logit modeling approach	39
Complementary intermodal commuting and resident travel satisfaction: A nonlinear and interaction analysis	39
Linking accessibility, transportation satisfaction, and destination satisfaction: Evidence from a ten-year longitudinal study in Xishuangbanna, China	37
Exploring the differences between express and ride-pooling: A dual perspective on user perception and functional positioning in urban traffic system	36
How does low income affect older people’s travel practices? Findings of a qualitative case study on the links between financial poverty, mobility and social participation	36
Commuters’ intention to choose customized bus during COVID-19 pandemic: Insights from a two-phase comparative analysis	36
Modeling travelers’ joint car ownership and car type choice behavior: The role of autonomous vehicle safety-security perceptions	36
Evidence on e-scooter ownership and use in non-urban areas	36