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An exploration of the relationships between socioeconomics, land use and daily trip chain pattern among low-income residents

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References

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1997Work travel mode choice and number of non-work commute stops210 cited
2004Travel behavior of low-income residents: studying two contrasting locations in the city of Chennai, India153 cited
2000Evaluating the Effects of Traveler and Trip Characteristics on Trip Chaining, with Implications for Transportation Demand Management Strategies87 cited
2014Daily travel behaviour in Beijing, China: An analysis of workers' trip chains, and the role of socio-demographics and urban form79 cited
2010An exploratory analysis of relationships between socioeconomic, land use, activity participation variables and travel patterns63 cited
2009An analysis of trip chaining among older London residents58 cited
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2013Exploring the causal relationship between bicycle choice and trip chain pattern43 cited
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2021Understanding non-commuting travel demand of car commuters – Insights from ANPR trip chain data in Cambridge23 cited
2017Improving Travel Quality of Low-Income Commuters in China22 cited
2019

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Applying an ensemble-based model to travel choice behavior in travel demand forecasting under uncertainties

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2017Public Transit Market Research of Low-Income Commuters Using Attitude-Based Market Segmentation Approach: Case Study of Fushun, China16 cited

2020Exploring the relationship between the built environment, trip chain complexity, and auto mode choice, applying a large national data set16 cited

2020Examining Interrelationships between Tourist Travel Mode and Trip Chain Choices Using the Nested Logit Model15 cited

2018Inferring the Economic Attributes of Urban Rail Transit Passengers Based on Individual Mobility Using Multisource Data13 cited

2020Observing the Characteristics of Multi-Activity Trip Chain and Its Influencing Mechanism13 cited

2022Estimation Markov Decision Process of Multimodal Trip Chain between Integrated Transportation Hubs in Urban Agglomeration Based on Generalized Cost11 cited

2019The Effects of Latent Attitudinal Variables and Sociodemographic Differences on Travel Behavior in Two Small, Underdeveloped Cities in China11 cited

2024Understanding tourists’ behavior toward transport mode choice by using machine learning methods5 cited

2025Evaluating the effect of post-pandemic hybrid work on travel behaviour and sustainable transportation: A tour-based analysis4 cited

2024Exploring the Commuting Decision-Making Behavior of Low-Income Groups Based on Cumulative Prospect Theory4 cited

2023Accounting for Heterogeneity in Stop Frequency Models of Work Tours Using Latent Class Poisson Models3 cited