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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\u2009m than that of 1692\u2009m, 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.<\/jats:p>","DOI":"10.1007\/s44212-022-00013-1","type":"journal-article","created":{"date-parts":[[2022,12,5]],"date-time":"2022-12-05T11:02:33Z","timestamp":1670238153000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":22,"title":["Geo-fence planning for dockless bike-sharing systems: a GIS-based multi-criteria decision analysis framework"],"prefix":"10.1007","volume":"1","author":[{"given":"Max","family":"Mangold","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Pengxiang","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"He","family":"Haitao","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Ali","family":"Mansourian","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"297","published-online":{"date-parts":[[2022,12,5]]},"reference":[{"key":"13_CR1","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1016\/j.compenvurbsys.2017.05.004","volume":"65","author":"G Boeing","year":"2017","unstructured":"Boeing, G. 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