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Factors Influencing Travel Behaviors in Bikesharing

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References

2010Bikesharing in Europe, the Americas, and Asia1,149 cited
2009Sensing and predicting the pulse of the city through shared bicycling307 cited
1999The effect of weather and climate on bicycle commuting285 cited
2011Temporal and Weather Impacts on Bicycle Volumes36 cited

Cited by

2021Factors affecting bike-sharing system demand by inferred trip purpose: Integration of clustering of travel patterns and geospatial data analysis34 cited
2013Encouraging Equitable Access to Public Bikesharing Systems28 cited
2022Effect of dockless bike-sharing scheme on the demand for London Cycle Hire at the disaggregate level using a deep learning approach22 cited
2021Evaluating the Efficiency of Bike-Sharing Stations with Data Envelopment Analysis21 cited
2023Combatting the mismatch: Modeling bike-sharing rental and return machine learning classification forecast in Seoul, South Korea21 cited
2017Potential user profiles of innovative bike-sharing systems: the case of BiciMAD (Madrid, Spain)18 cited
2022Competition, Integration, or Complementation? Exploring Dock-Based Bike-Sharing in New York City15 cited
2014Spatial analytical approaches in public bicycle sharing programs15 cited
2024Forecasting the Usage of Bike-Sharing Systems through Machine Learning Techniques to Foster Sustainable Urban Mobility14 cited

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2024

The nonlinear impact of cycling environment on bicycle distance: A perspective combining objective and perceptual dimensions

13 cited

2023Short‐Term Forecasting of Dockless Bike‐Sharing Demand with the Built Environment and Weather12 cited

2024Understanding the Competition and Cooperation between Dockless Bike-Sharing and Metro Systems in View of Mobility12 cited

2020The suitability level of bike-sharing station in Yogyakarta using SMCA technique11 cited

2016User characteristics of an electric bike sharing system at UMONS as part of a smart district concept10 cited

2024Interpretable Bike-Sharing Activity Prediction with a Temporal Fusion Transformer to Unveil Influential Factors: A Case Study in Hamburg, Germany7 cited

2015User requirements on intermodal traveler information systems6 cited