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Exploring the Built Environment Factors in the Metro That Influence the Ridership and the Market Share of the Elderly and Students
16 references·5 citing·39 second hop
Exploring the Built Environment Factors in the Metro That Influence the Ridership and the Market Share of the Elderly and Students (2021)Exploring the Built Environment Factors i…Statistical and Econometric Methods for Transportation Data Analysis (2020)Statistical and Econometric M…Understanding the impact of built environment on metro ridership using open source in Shanghai (2019)Understanding the impact of b…Active travel for active ageing in China: The role of built environment (2019)Active travel for active agei…Spatio-temporal travel characteristics of the elderly in an ageing society (2017)Spatio-temporal travel charac…The influence of built environment on travel behavior of the elderly in urban China (2016)The influence of built enviro…Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul (2015)Land use characteristics of s…What influences Metro station ridership in China? Insights from Nanjing (2013)What influences Metro station…Activity-based models of travel demand: promises, progress and prospects (2013)Activity-based models of trav…Application of geographically weighted regression to the direct forecasting of transit ridership at station-level (2012)Application of geographically…Transit ridership forecasting at station level: an approach based on distance-decay weighted regression (2011)Transit ridership forecasting…Factors generating boardings at Metro stations in the Seoul metropolitan area (2010)Factors generating boardings …Panel data methods for fractional response variables with an application to test pass rates (2008)Panel data methods for fracti…The Four-Step Model (2007)The Four-Step ModelSchool Location and Student Travel Analysis of Factors Affecting Mode Choice (2004)School Location and Student T…Factors influencing light-rail station boardings in the United States (2004)Factors influencing light-rai…Activity-based disaggregate travel demand model system with activity schedules (2001)Activity-based disaggregate t…Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network (2025)Machine Learning-Based Analys…Barriers and facilitators to urban mobility for older adults in LMICs: A scoping review (2025)Barriers and facilitators to …Evaluation and determinants of metro users' regularity: Insights from transit one-card data (2024)Evaluation and determinants o…A machine learning comparison of transportation mode changes from high-speed railway promotion in Thailand (2024)A machine learning comparison…Factors influencing the market share of e-bike sharing: evidence from New York City (2023)Factors influencing the marke…Impacts of Mixed Use and Density on Utilization of Three Modes of Travel: Single-Occupant Vehicle, Transit, and Walking (1994)A micro-analysis of land use and travel in five neighborhoods in the San Francisco Bay Area (1997)Travel demand and the 3Ds: Density, diversity, and design (1997)A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership (2018)How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds (2019)Examining the relationship between built environment and metro ridership at station-to-station level (2020)On the Pooling of Time Series and Cross Section Data (1978)Specification Tests in Econometrics (1978)Econometric Analysis of Cross Section and Panel Data (2001)Estimating dynamic panel models in corporate finance (2012)Participation of Developing Countries in Global Value Chains (2015)Correlated random effects models with unbalanced panels (2018)The Geography of Urban Transportation (1988)New evidence on walking distances to transit stops: identifying redundancies and gaps using variable service areas (2013)How Accessibility Shapes Land Use (1959)Built environments and mode choice: toward a normative framework (2002)WHAT ABOUT PEOPLE IN REGIONAL SCIENCE? (1970)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Discrete choice analysis: Theory and application to travel demand (1988)Does active commuting improve psychological wellbeing? Longitudinal evidence from eighteen waves of the British Household Panel Survey (2014)Spatial Econometrics: Methods and Models (1988)Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity (1996)Geographically Weighted Regression: The Analysis of Spatially Varying Relationships (2002)The role of distance in peri-urban national park use: Who visits them and how far do they travel? (2015)Spatially non-stationary relationships between urban residential land price and impact factors in Wuhan city, China (2016)Fast Geographically Weighted Regression (FastGWR): a scalable algorithm to investigate spatial process heterogeneity in millions of observations (2018)Annals of the Association of American Geographers (1921)Space‐Time and Integral Measures of Individual Accessibility: A Comparative Analysis Using a Point‐based Framework (1998)Discovering urban activity patterns in cell phone data (2015)Land use–transport interaction modeling: A review of the literature and future research directions (2015)Econometric Models of Probabilistic Choice (1981)Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures (2003)School Trips: Effects of Urban Form and Distance on Travel Mode (2006)Parks and People: An Environmental Justice Inquiry in Baltimore, Maryland (2009)A comparative study of machine learning classifiers for modeling travel mode choice (2017)Applying mobile phone data to travel behaviour research: A literature review (2017)Service Quality Attributes Affecting Customer Satisfaction for Bus Transit (2007)The role of social capital, personal networks, and emergency responders in post-disaster recovery and resilience: a study of rural communities in Indiana (2017)Gender gap generators for bike share ridership: Evidence from Citi Bike system in New York City (2019)
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References

  • 2008Panel data methods for fractional response variables with an application to test pass rates1,319 cited
  • 2020Statistical and Econometric Methods for Transportation Data Analysis963 cited
  • 2001Activity-based disaggregate travel demand model system with activity schedules763 cited
  • 2004Factors influencing light-rail station boardings in the United States443 cited
  • 2007The Four-Step Model436 cited
  • 2004School Location and Student Travel Analysis of Factors Affecting Mode Choice435 cited
  • 2012Application of geographically weighted regression to the direct forecasting of transit ridership at station-level377 cited
  • 2011Transit ridership forecasting at station level: an approach based on distance-decay weighted regression371 cited
  • 2015Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul320 cited
  • 2013Activity-based models of travel demand: promises, progress and prospects320 cited
  • 2013What influences Metro station ridership in China? Insights from Nanjing260 cited
  • 2010Factors generating boardings at Metro stations in the Seoul metropolitan area248 cited
  • 2019Active travel for active ageing in China: The role of built environment248 cited
  • 2019Understanding the impact of built environment on metro ridership using open source in Shanghai

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214 cited
  • 2017Spatio-temporal travel characteristics of the elderly in an ageing society203 cited
  • 2016The influence of built environment on travel behavior of the elderly in urban China201 cited
  • Cited by

    • 2024A machine learning comparison of transportation mode changes from high-speed railway promotion in Thailand18 cited
    • 2023Factors influencing the market share of e-bike sharing: evidence from New York City12 cited
    • 2025Barriers and facilitators to urban mobility for older adults in LMICs: A scoping review12 cited
    • 2024Evaluation and determinants of metro users' regularity: Insights from transit one-card data10 cited
    • 2025Machine Learning-Based Analysis of Travel Mode Preferences: Neural and Boosting Model Comparison Using Stated Preference Data from Thailand’s Emerging High-Speed Rail Network7 cited