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Relationship between built environment characteristics of TOD and subway ridership: A causal inference and regression analysis of the Beijing subway

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References

2010Travel and the Built Environment5,396 cited
1997Travel demand and the 3Ds: Density, diversity, and design4,588 cited
1996Geographically Weighted Regression: A Method for Exploring Spatial Nonstationarity3,562 cited
2002How the built environment affects physical activity1,916 cited
2005Correlation or causality between the built environment and travel behavior? Evidence from Northern California1,145 cited
2009Examining the Impacts of Residential Self‐Selection on Travel Behaviour: A Focus on Empirical Findings1,080 cited
2009Influences of Built Environments on Walking and Cycling: Lessons from Bogotá832 cited
2007Examining the impacts of residential self-selection on travel behavior: A focus on methodologies828 cited
2007Do changes in neighborhood characteristics lead to changes in travel behavior? A structural equations modeling approach438 cited
2012Application of geographically weighted regression to the direct forecasting of transit ridership at station-level377 cited
2018A geographically and temporally weighted regression model to explore the spatiotemporal influence of built environment on transit ridership333 cited
2015Land use characteristics of subway catchment areas and their influence on subway ridership in Seoul320 cited
2019How does the station-area built environment influence Metrorail ridership? Using gradient boosting decision trees to identify non-linear thresholds

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311 cited

2020Examining the relationship between built environment and metro ridership at station-to-station level280 cited

2013What influences Metro station ridership in China? Insights from Nanjing260 cited

1993Regional Versus Local Accessibility: Implications for Nonwork Travel253 cited

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