Exploring socio-spatial differentiation in bike-sharing: A daily activity space analysis of cyclists across different socioeconomic statuses

Existing studies underscore the significance of traditional public transportation systems (e.g., buses and metros) in shaping residents' daily mobility patterns and social interactions. However, limited research has examined the spatiotemporal interaction patterns among users of dockless bike-sharing (DBS), an emerging low-carbon mode of public transportation. To address this gap, we investigate the daily spatiotemporal interaction patterns and disparities among bike-sharing users across different socioeconomic statuses (SES) in Shenzhen, China. Leveraging massive DBS trip datasets with user IDs, we delineate the individual daily activity spaces of frequent users across different SES groups. Taking into account spatiotemporal proximity and distance decay effects, we compute multiple activity-space-based differentiation indices, followed by comprehensive analyses. The results reveal that middle-SES users experience the greatest diversity in interactions with users from different socioeconomic backgrounds during daily cycling activities, followed by high-SES users, while low-SES users exhibit the least interaction. Furthermore, the activity-space-based differentiation for each SES group follows a consistent periodic temporal pattern, characterized by two alternating peaks and troughs throughout the day. Peaks emerge in midday and late-night hours, whereas troughs align with the morning and evening commuting periods. The degree of activity-space-based differentiation is strongly associated with proximity to central city and land-use functions. These findings provide valuable implications for promoting social integration and promoting equity in non-motorized and sustainable transportation services.