TY - JOUR
T1 - Optimizing shared bike systems for economic gain
T2 - Integrating land use and retail
AU - Bencekri, Madiha
AU - Van Fan, Yee
AU - Lee, Doyun
AU - Choi, Minje
AU - Lee, Seungjae
N1 - Publisher Copyright:
© 2024 Elsevier Ltd
PY - 2024/6
Y1 - 2024/6
N2 - 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.
AB - 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.
KW - Ensemble algorithms
KW - Land use mix
KW - Multi-criteria decision making
KW - Multi-modal transport
KW - Retail activity
KW - Shared bike
KW - Suitability analysis
UR - http://www.scopus.com/inward/record.url?scp=85196254986&partnerID=8YFLogxK
U2 - 10.1016/j.jtrangeo.2024.103920
DO - 10.1016/j.jtrangeo.2024.103920
M3 - Article
AN - SCOPUS:85196254986
SN - 0966-6923
VL - 118
JO - Journal of Transport Geography
JF - Journal of Transport Geography
M1 - 103920
ER -