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Spatial-Temporal Heterogeneity and Built Environment Nonlinearity in Inconsiderate Parking of Dockless Bike-Sharing
16 references·6 citing·39 second hopsampled
Spatial-Temporal Heterogeneity and Built Environment Nonlinearity in Inconsiderate Parking of Dockless Bike-Sharing (2022)Spatial-Temporal Heterogeneity and Built …Nonlinear effects of built environment on intermodal transit trips considering spatial heterogeneity (2021)Nonlinear effects of built en…Prediction of probable backorder scenarios in the supply chain using Distributed Random Forest and Gradient Boosting Machine learning techniques (2020)Prediction of probable backor…Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China (2020)Exploring travel patterns and…Built environment effects on the integration of dockless bike-sharing and the metro (2020)Built environment effects on …A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data (2020)A comparison in travel patter…Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system (2019)Unravel the landscape and pul…To be or not to be dockless: Empirical analysis of dockless bikeshare development in China (2018)To be or not to be dockless: …Environmental benefits of bike sharing: A big data-based analysis (2018)Environmental benefits of bik…Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo (2018)Applying gradient boosting de…Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system (2016)Incorporating the impact of s…How does our natural and built environment affect the use of bicycle sharing? (2016)How does our natural and buil…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…Bikeshare trip generation in New York City (2016)Bikeshare trip generation in …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 …Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system (2015)Analysing bicycle-sharing sys…How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal (2014)How land-use and urban form i…Investigating user preferences for dockless bike- and electric bike-sharing through tracking usage patterns (2025)Investigating user preference…What limits improper bike-sharing parking most: Penalties or incentives? Findings from an online behavioral experiment (2024)What limits improper bike-sha…Spatially Varying Effect Mechanism of Intermodal Connection on Metro Ridership: Evidence from a Polycentric Megacity with Multilevel Ring Roads (2024)Spatially Varying Effect Mech…How does the built environment affect the usage efficiency of dockless-shared bicycle? An exploration of time-varying nonlinear relationships (2024)How does the built environmen…Examining the impact of station location on dockless bikesharing-metro integration: Evidence from Beijing (2024)Examining the impact of stati…Changes in visitor behaviour across COVID-19 pandemic: Unveiling urban visitation dynamics and non-linear relationships with the built environment using mobile big data (2024)Changes in visitor behaviour …Bike-sharing: History, Impacts, Models of Provision, and Future (2009)Bikesharing in Europe, the Americas, and Asia (2010)Bike Share: A Synthesis of the Literature (2013)Bike sharing: A review of evidence on impacts and processes of implementation and operation (2015)A review on bike-sharing: The factors affecting bike-sharing demand (2019)Travel and the Built Environment: A Synthesis (2001)Environmental correlates of walking and cycling: Findings from the transportation, urban design, and planning literatures (2003)Transit ridership forecasting at station level: an approach based on distance-decay weighted regression (2011)The impact of weather conditions on bikeshare trips in Washington, DC (2014)Modeling Bike Share Station Activity: Effects of Nearby Businesses and Jobs on Trips to and from Stations (2015)Examining usage patterns of a bike-sharing scheme in a medium sized city (2017)Bike sharing differences among Millennials, Gen Xers, and Baby Boomers: Lessons learnt from New York City’s bike share (2018)Examining spatiotemporal changing patterns of bike-sharing usage during COVID-19 pandemic (2021)Specification and Estimation of Spatial Panel Data Models (2003)Dockless bike-sharing as a feeder mode of metro commute? The role of the feeder-related built environment: Analytical framework and empirical evidence (2020)Travel demand and the 3Ds: Density, diversity, and design (1997)Travel and the Built Environment (2010)Bike-sharing systems and congestion: Evidence from US cities (2017)Central Places in Southern Germany (1967)Ensemble approach based on bagging, boosting and stacking for short-term prediction in agribusiness time series (2019)Examining non-linear built environment effects on elderly’s walking: A random forest approach (2020)To walk or not to walk? Examining non-linear effects of streetscape greenery on walking propensity of older adults (2021)China statistical yearbook (1988)Clarifying the concept of product–service system (2002)Understanding mobility based on GPS data (2008)The sharing economy promotes sustainable societies (2019)Digital economy: An innovation driving factor for low-carbon development (2022)Making Cycling Irresistible: Lessons from The Netherlands, Denmark and Germany (2008)Bike-sharing systems’ impact on modal shift: A case study in Delft, the Netherlands (2020)Identifying the nonlinear relationship between free-floating bike sharing usage and built environment (2020)Exploring non-linear built environment effects on the integration of free-floating bike-share and urban rail transport: A quantile regression approach (2022)How the built environment affects physical activity (2002)Spatial analysis of shared e-scooter trips (2021)Public transport for smart cities: Recent innovations and future challenges (2022)Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity (1996)Geographically and temporally weighted regression for modeling spatio-temporal variation in house prices (2010)The effects of built environment spatial variation on bike-sharing usage: A case study of Suzhou, China (2021)Bike Share Usage and the Built Environment: A Review (2022)Spatiotemporal exploration of the non-linear impacts of accessibility on metro ridership (2022)
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References

  • 2015Effects of built environment and weather on bike sharing demand: a station level analysis of commercial bike sharing in Toronto570 cited
  • 2018Environmental benefits of bike sharing: A big data-based analysis508 cited
  • 2014How land-use and urban form impact bicycle flows: evidence from the bicycle-sharing system (BIXI) in Montreal486 cited
  • 2018Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo446 cited
  • 2020Built environment effects on the integration of dockless bike-sharing and the metro324 cited
  • 2016Bikeshare trip generation in New York City258 cited
  • 2016Exploring the impact of built environment factors on the use of public bikes at bike stations: Case study in Zhongshan, China258 cited
  • 2020A comparison in travel patterns and determinants of user demand between docked and dockless bike-sharing systems using multi-sourced data243 cited
  • 2016Incorporating the impact of spatio-temporal interactions on bicycle sharing system demand: A case study of New York CitiBike system235 cited
  • 2018To be or not to be dockless: Empirical analysis of dockless bikeshare development in China234 cited
  • 2016How does our natural and built environment affect the use of bicycle sharing?215 cited
  • 2015Analysing bicycle-sharing system user destination choice preferences: Chicago’s Divvy system199 cited
  • 2019Unravel the landscape and pulses of cycling activities from a dockless bike-sharing system

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188 cited
  • 2020Prediction of probable backorder scenarios in the supply chain using Distributed Random Forest and Gradient Boosting Machine learning techniques167 cited
  • 2020Exploring travel patterns and trip purposes of dockless bike-sharing by analyzing massive bike-sharing data in Shanghai, China154 cited
  • 2021Nonlinear effects of built environment on intermodal transit trips considering spatial heterogeneity145 cited
  • Cited by

    • 2024Changes in visitor behaviour across COVID-19 pandemic: Unveiling urban visitation dynamics and non-linear relationships with the built environment using mobile big data18 cited
    • 2024How does the built environment affect the usage efficiency of dockless-shared bicycle? An exploration of time-varying nonlinear relationships17 cited
    • 2024Examining the impact of station location on dockless bikesharing-metro integration: Evidence from Beijing10 cited
    • 2025Investigating user preferences for dockless bike- and electric bike-sharing through tracking usage patterns10 cited
    • 2024Spatially Varying Effect Mechanism of Intermodal Connection on Metro Ridership: Evidence from a Polycentric Megacity with Multilevel Ring Roads8 cited
    • 2024What limits improper bike-sharing parking most: Penalties or incentives? Findings from an online behavioral experiment7 cited