DOI number:10.1016/j.rtbm.2026.101627
Affiliation of Author(s):中南大学交通运输工程学院
Journal:Research in Transportation Business & Management
Funded by:湖南省自科基金
Key Words:Shared bike-metro interactions; Multi-scale analysis; Spatiotemporal heterogeneity;Emission mitigation; Sustainable transport management
Abstract:Shared bikes and metro systems intertwine to enhance low-carbon urban mobility, yet their diverse interactions, including connectivity, substitution, and gap-filling, pose untapped potential for sustainable transport. This study pioneers a multi-scale spatiotemporal weighted regression (MSTWR) model, using Shanghai's trip data, to outperform geographically and temporally weighted regression (GTWR) by 18% with tailored bandwidths, revealing how residential zones and bicycle lanes enhance connectivity in morning peaks. High metro density unexpectedly curbs substitution, while mixed land use subtly dampens bike usage with varied transit options. Environmentally, shared bikes in Shanghai's central district reduce approximately 143.81 tons of daily CO2 emissions, with connective trips dominating at 48.32%. While usage-phase emissions offset 31.42% of the total benefits, presenting a striking operational challenge. This study advances sustainable mobility theory by uncovering scale-sensitive interaction mechanisms and proposes actionable strategies integrating infrastructure investment, land use planning, and behavioral incentives to achieve carbon neutrality goals.
Co-author:Ying Zhou, Yaxin Wang, Yanzi Xiao, Ruiting Cai
First Author:Jianming Cai
Indexed by:Journal paper
Discipline:Engineering
Document Type:J
Volume:66
Issue:2026
Page Number:101627
Translation or Not:no
Included Journals:SSCI
Links to published journals:https://doi.org/10.1016/j.rtbm.2026.101627