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Impact of Subjective and Objective Factors on Subway Travel Behavior: Spatial Differentiation
16 references·1 citing·51 second hop
Impact of Subjective and Objective Factors on Subway Travel Behavior: Spatial Differentiation (2022)Impact of Subjective and Objective Factor…Computational improvements to multi-scale geographically weighted regression (2020)Computational improvements to…Inference in Multiscale Geographically Weighted Regression (2019)Inference in Multiscale Geogr…Synergistic effects of the built environment and commuting programs on commute mode choice (2018)Synergistic effects of the bu…Is transport poverty socially or environmentally driven? Comparing the travel behaviours of two low-income populations living in central and peripheral locations in the same city (2018)Is transport poverty socially…Applying gradient boosting decision trees to examine non-linear effects of the built environment on driving distance in Oslo (2018)Applying gradient boosting de…The impact of online brand community characteristics on customer engagement: An application of Stimulus-Organism-Response paradigm (2017)The impact of online brand co…Multiscale Geographically Weighted Regression (MGWR) (2017)Multiscale Geographically Wei…Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice (2016)Joint analysis of the spatial…The objective versus the perceived environment: what matters for bicycling? 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Examining non-linear effects of streetscape greenery on walking propensity of older adults (2021)Travel and the Built Environment: A Synthesis (2001)Examining the Impacts of Residential Self‐Selection on Travel Behaviour: A Focus on Empirical Findings (2009)Examining threshold effects of built environment elements on travel-related carbon-dioxide emissions (2019)Elaborating non-linear associations and synergies of subway access and land uses with urban vitality in Shenzhen (2020)Nonlinear effect of accessibility on car ownership in Beijing: Pedestrian-scale neighborhood planning (2020)Geographically Weighted Regression: A Natural Evolution of the Expansion Method for Spatial Data Analysis (1998)Exploring differentiated impacts of socioeconomic factors and urban forms on city-level CO2 emissions in China: Spatial heterogeneity and varying importance levels (2022)Multiscale GIS based-model to assess urban social vulnerability and associated risk: Evidence from 146 urban centers of Eastern India (2023)
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References

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  • 2019Inference in Multiscale Geographically Weighted Regression414 cited
  • 2014The analysis of transit-oriented development (TOD) in Washington, D.C. and Baltimore metropolitan areas268 cited
  • 2018Synergistic effects of the built environment and commuting programs on commute mode choice199 cited
  • 2012Exploring the relationships between housing, neighbourhoods and mental wellbeing for residents of deprived areas190 cited
  • 2020Computational improvements to multi-scale geographically weighted regression170 cited
  • 2016Joint analysis of the spatial impacts of built environment on car ownership and travel mode choice157 cited
  • 2014The objective versus the perceived environment: what matters for bicycling?

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153 cited
  • 2014Mismatch between Perceived and Objectively Measured Land Use Mix and Street Connectivity: Associations with Neighborhood Walking115 cited
  • 2018Is transport poverty socially or environmentally driven? Comparing the travel behaviours of two low-income populations living in central and peripheral locations in the same city103 cited
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    • 2024Exploring the Impact of Built Environment on Elderly Metro Ridership at Station-to-Station Level4 cited