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Geo-fence planning for dockless bike-sharing systems: a GIS-based multi-criteria decision analysis framework

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posted on 2023-01-16, 09:36 authored by Max Mangold, Pengxiang Zhao, Haitao HeHaitao He, Ali Mansourian

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.

History

School

  • Architecture, Building and Civil Engineering

Published in

Urban Informatics

Volume

1

Issue

1

Publisher

Springer Science and Business Media LLC

Version

  • VoR (Version of Record)

Rights holder

© The Author(s)

Publisher statement

This is an Open Access article published by Springer Nature and is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The version of record of this article, first published in Urban Informatics, is available online at Publisher’s website: https://doi.org/10.1007/s44212-022-00013-1

Acceptance date

2022-11-07

Publication date

2022-12-05

Copyright date

2022

eISSN

2731-6963

Language

  • en

Depositor

Dr Haitao He. Deposit date: 13 January 2023

Article number

17