Abstract

This study explores the optimization of shared-bike station locations, emphasizing the cycling role in low-carbon mobility and local economic revitalization. A unique aspect of this research is the incorporation of the retail activity index in determining station locations, land-use mix, transit proximity, and population and employment densities. A novel weighting method, combining the multi-criteria decision method “Criteria Importance Through Inter-criteria Correlation (CRITIC)” with Ensemble-based predictive algorithms (Random Forest, XGBoost, Gradient Boosting), was developed to evaluate these factors. Using a geographic information system-based spatial model, this study conducted a suitability analysis by applying these weights to assess and propose bike station sites. The findings from the Seoul case indicate a balanced land-use mix, a low number of transactions linked to cyclists, and a significant gap in multimodal transport integration. The weighting results revealed a high priority for transit proximity and retail activity in station placement. Suitability scores across districts revealed significant variability, suggesting the need for greater integration of cycling policies into urban planning. High-scoring districts, such as Gangnam-gu and Seocho-gu, offer insights for improvements in less suitable areas. This study advocates expanded cycling planning, focusing on enhancing access to public transit and retail areas.

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.