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The inappropriate parking of free-floating shared bikes is a critical issue that needs to be addressed to realize the potential environmental, socioeconomic, and health benefits of this emerging green mode of transport. To address this challenge, this paper developes a Geographic Information Systems (GIS) based Multi-Criteria Decision Analysis (MCDA) framework for geo-fence planning of dockless bike-sharing systems based on openly accessible data. The Analytic Hierarchy Process (AHP) and the VIKOR (VIseKriterijumska Optimizacija I Kompromisno Resenje) method are applied in the proposed framework to derive optimal geo-fence locations. The proposed framework is validated in a case study using a dataset of dockless bike-sharing trips from February 2020 in the City of Zurich and comparing the selected geo-fence locations with the existing bike-sharing stations. The assessment results show that the calculated geo-fence locations have a smaller average distance of 1395 m than that of 1692 m, and a larger demand coverage of 81% than that of 77% for bike-sharing stations. Overall, the proposed framework and the insights from the case study can help transport planners better implement shared micro-mobility hence facilitating the uptake of this sustainable mode of urban transport. |
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