期刊
JOURNAL OF TRANSPORT GEOGRAPHY
卷 92, 期 -, 页码 -出版社
ELSEVIER SCI LTD
DOI: 10.1016/j.jtrangeo.2021.103004
关键词
Bicycle Sharing System; Urban Transport Equality; Global South; Data Visualisation; Public Tendering
资金
- CONICYT/Becas Chile scholarship [72160366]
- WISE-ACT COST Action [CA16222-43582]
Bicycle Sharing Schemes (BSS) are promising components of urban mobility solutions worldwide, but the lack of consistent collaboration strategies between different actors and institutions is a challenge. Utilizing a Multi-Level Perspective (MLP) framework and introducing new tools through mixed methods can help manage BSS effectively in the Global South.
Bicycle Sharing Schemes (BSS) are re-emerging as promising components of urban mobility solutions worldwide. However, the lack of consistent collaboration strategies between different actors and institutions, which have been tested in a wide range of cities and contexts regarding their design, tender, operation and expansion, raises significant social and governance implications. Urban transport features as a melting pot for diverse policy objectives, ranging from business model innovation, public tendering, and accessibility increase to the equity and social justice agenda. By employing a Multi-Level Perspective (MLP) framework and by introducing alluvial diagrams and circular dendrograms to BSS planning through a mixed-methods approach, this article illustrates an innovative tool in managing BSS in the context of the Global South. The strength of such diagrams has been underestimated to date since they can be particularly useful for public and private urban transport planners and policy-makers. Visualising user flows in such a manner, particularly in near-live time, may offer valuable insight on the operational challenges of BSS. Findings of the cross-sectional survey in Santiago de Chile confirm that maintenance is significant for user satisfaction levels. Furthermore, decisions regarding BSS expansion and modification could be based on such analysis and diagrams due to the precise identification of both the busiest and those underrepresented BSS stations based on revealed preferences.
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