Street matters: Linking perceived street environment to older adults’ bike-sharing
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Date
2025-10
Publication Type
Journal Article
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Abstract
Shared micromobility has established its role as a viable solution for sustainable transportation worldwide. Despite the widespread discourse on bike-sharing, there remains a paucity of research addressing its utilization among older adults (aged 65 and over). To this end, this research delves into the analysis of docked bike-sharing trip records in Chicago, aiming to understand the impact of land use and perceived street environment (derived from Google Street View Images) on the utilization of bike-sharing services among older adults at both the station and route levels. This study adopts the Extreme Gradient Boosting (XGBoost) method and interprets the results using Shapley Additive explanations (SHAP). Results show that older adults have specific preferences for different land use and perceived street environments when using shared bikes, differing notably from the general user population. Regarding land use effects, older adults are more likely to use shared bikes in areas with high mixed land use and more green spaces. Areas with more cycling lane density also increase older adults’ likelihood to cycle more. For perceived street environments, older adults are prone to streets with high enclosure and low sky openness levels. This research also finds that the route-level perceived street environment has more pronounced marginal effects in comparison to the station-level counterparts. Our findings can provide evidence-based guidance to transportation planners to develop age-friendly transportation systems, thus alleviating the potential inequalities in access to bike-sharing services.
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published
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Journal / series
Volume
41
Pages / Article No.
101071
Publisher
Elsevier
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Subject
Bike-sharing; Older adults; Built environment; Google Street View (GSV); Route-level modeling; Nonlinearity; Street environment