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How Does the Urban Built Environment Affect Online Car-Hailing Ridership Intensity among Different Scales?
Guanwei Zhao1,2, Zhitao Li1, Yuzhen Shang1
1School of Geography and Remote Sensing, Guangzhou University, Guangzhou 510006, China.
Summary
The impact of urban built environments on online car-hailing (OCH) ridership varies significantly with analysis scale. Key factors like population and road density consistently influence OCH trips, while others shift effects across different spatial resolutions.
Area of Science:
- Urban Planning and Transportation Geography
- Geographic Information Systems (GIS) and Spatial Analysis
- Environmental Science and Urban Studies
Background:
- Understanding the urban built environment's influence on transportation demand is vital for effective urban planning.
- The scale of analysis significantly impacts the observed relationships between built environment factors and transportation patterns.
- Online car-hailing (OCH) services represent a growing mode of urban mobility, necessitating research into their ridership determinants.
Purpose of the Study:
- To investigate the multiscale effects of the urban built environment on online car-hailing (OCH) trip intensity in Chengdu, China.
- To identify how the significance and nature of built environment factors change across different spatial analysis scales.
- To analyze the spatial variability of these effects at various scales.
Main Methods:
- Utilized stepwise regression selection and three spatial regression models for multiscale analysis.
- Examined built environment factors across grid sizes ranging from 500 m to 3000 m.
- Employed spatial statistical techniques to assess the geographic distribution of factor effects.
Main Results:
- The number of significant built environment factors influencing OCH trip intensity decreased as grid size increased.
- Population density and road density consistently showed positive effects across all scales.
- Proximity to public transportation shifted from inhibitory to facilitative with increasing scale, while land-use mix effect strengthened.
Conclusions:
- The scale of analysis is a critical determinant in understanding the relationship between the urban built environment and OCH ridership.
- Different built environment factors exhibit scale-dependent significance and spatial variability, impacting urban planning strategies.
- Findings highlight the need for multiscale approaches in transportation planning and OCH service optimization.
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