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The Nonlinear Effect of the Built Environment on Bike–Metro Transfer in Different Times and Transfer Flows Considering Spatial Dependence
16 references·1 citing·45 second hop
The Nonlinear Effect of the Built Environment on Bike–Metro Transfer in Different Times and Transfer Flows Considering Spatial Dependence (2025)The Nonlinear Effect of the Built Environ…Non-Linear Associations Between the Urban Built Environment and Commuting Modal Split: A Random Forest Approach and SHAP Evaluation (2023)Non-Linear Associations Betwe…The spatially varying effects of built environment characteristics on the integrated usage of dockless bike-sharing and public transport (2022)The spatially varying effects…Housing price prediction incorporating spatio-temporal dependency into machine learning algorithms (2022)Housing price prediction inco…A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership (2022)A network-distance-based geog…The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people's actual cycling space (2021)The impacts of the built envi…Examining factors associated with bike-and-ride (BnR) activities around metro stations in large-scale dockless bikesharing systems (2021)Examining factors associated …Transit-oriented development: A review of research achievements and challenges (2019)Transit-oriented development:…Network design, built and natural environments, and bicycle commuting: Evidence from British cities and towns (2018)Network design, built and nat…Bikeability – Urban structures supporting cycling. Effects of local, urban and regional scale urban form factors on cycling from home and workplace locations in Denmark (2018)Bikeability – Urban structure…Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China (2016)Exploring the impact of built…Not all prospective bicyclists are created equal: The role of attitudes, socio-demographics, and the built environment in bicycle commuting (2015)Not all prospective bicyclist…Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto (2015)Effects of built environment …Transit ridership forecasting at station level: an approach based on distance-decay weighted regression (2011)Transit ridership forecasting…Introduction to Spatial Econometrics (2009)Introduction to Spatial Econo…Influences of Built Environments on Walking and Cycling: Lessons from Bogotá (2009)Influences of Built Environme…A Computer Movie Simulating Urban Growth in the Detroit Region (1970)A Computer Movie Simulating U…System-Wide Optimization of Free-Floating Bike-Sharing for Urban Rail Stations: A demand prediction and scheduling approach (2025)System-Wide Optimization of F…Innovation Diffusion As a Spatial Process (1967)Methods to account for spatial autocorrelation in the analysis of species distributional data: a review (2007)A measure of spatial stratified heterogeneity (2016)Multiscale Geographically Weighted Regression (MGWR) (2017)How Accessibility Shapes Land Use (1959)Travel demand and the 3Ds: Density, diversity, and design (1997)Built environments and mode choice: toward a normative framework (2002)Application of geographically weighted regression to the direct forecasting of transit ridership at station-level (2012)Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul (2015)A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership (2018)Travel and the Built Environment: A Synthesis (2001)Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures (2003)Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Environmental benefits of bike sharing: A big data-based analysis (2018)A review on bike-sharing: The factors affecting bike-sharing demand (2019)Built environment effects on the integration of dockless bike-sharing and the metro (2020)Travel and the Built Environment (2010)Bike-sharing systems and congestion: Evidence from US cities (2017)Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system (2019)Dockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence (2020)The Uncertain Geographic Context Problem (2012)Bikeability: Assessing the Objectively Measured Environment in Relation to Recreation and Transportation Bicycling (2019)A Scoping Review of Bikeability Assessment Methods (2020)Associations between built environment, perceived walkability/bikeability and metro transfer patterns (2021)Urban transportation networks: Equilibrium analysis with mathematical programming methods (1986)Discrete Choice Analysis: Theory and Application to Travel Demand. (1987)Discrete choice analysis: Theory and application to travel demand (1988)Weather and cycling in New York: The case of Citibike (2019)How does weather affect bikeshare use? 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An update and re-appraisal of cycling trends and policies (2011)Shaping cities for health: complexity and the planning of urban environments in the 21st century (2012)Transit-oriented development (TOD) typologies around metro station areas in urban China: A comparative analysis of five typical megacities for planning implications (2020)Nonlinear and synergistic effects of TOD on urban vibrancy: Applying local explanations for gradient boosting decision tree (2021)Transit-oriented development with urban sprawl? Four phases of urban growth and policy intervention in Tokyo (2021)Applied Spatial Econometrics: Raising the Bar (2010)Matlab Software for Spatial Panels (2012)THE SLX MODEL (2015)
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References

  • 1970A Computer Movie Simulating Urban Growth in the Detroit Region9,754 cited
  • 2009Introduction to Spatial Econometrics5,542 cited
  • 2009Influences of Built Environments on Walking and Cycling: Lessons from Bogotá832 cited
  • 2015Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto570 cited
  • 2019Transit-oriented development: A review of research achievements and challenges495 cited
  • 2011Transit ridership forecasting at station level: an approach based on distance-decay weighted regression371 cited
  • 2016Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China258 cited
  • 2022Housing price prediction incorporating spatio-temporal dependency into machine learning algorithms120 cited
  • 2018Network design, built and natural environments, and bicycle commuting: Evidence from British cities and towns109 cited
  • 2018Bikeability – Urban structures supporting cycling. Effects of local, urban and regional scale urban form factors on cycling from home and workplace locations in Denmark100 cited
  • 2015Not all prospective bicyclists are created equal: The role of attitudes, socio-demographics, and the built environment in bicycle commuting96 cited
  • 2021Examining factors associated with bike-and-ride (BnR) activities around metro stations in large-scale dockless bikesharing systems94 cited
  • 2022The spatially varying effects of built environment characteristics on the integrated usage of dockless bike-sharing and public transport

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87 cited
  • 2021The impacts of the built environment on bicycle-metro transfer trips: A new method to delineate metro catchment area based on people's actual cycling space81 cited
  • 2022A network-distance-based geographically weighted regression model to examine spatiotemporal effects of station-level built environments on metro ridership79 cited
  • 2023Non-Linear Associations Between the Urban Built Environment and Commuting Modal Split: A Random Forest Approach and SHAP Evaluation76 cited
  • Cited by

    • 2025System-Wide Optimization of Free-Floating Bike-Sharing for Urban Rail Stations: A demand prediction and scheduling approach5 cited