Geo-fence planning for dockless bike-sharing systems : a GIS-based multi-criteria decision analysis framework
Mangold, Max ; Zhao, Pengxiang LU ; Haitao, He and Mansourian, Ali LU
(2022)
In Urban Informatics
1.
- Abstract
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... (More)
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.
(Less)
- author
- Mangold, Max
; Zhao, Pengxiang
LU
; Haitao, He
and Mansourian, Ali
LU
- organization
- publishing date
- 2022-12
- type
- Contribution to journal
- publication status
- published
- subject
- keywords
- AHP, Dockless bike-sharing, Geo-fence planning, GIS, Multi-criteria decision analysis, VIKOR
- in
- Urban Informatics
- volume
- 1
- article number
- 17
- publisher
- Springer
- external identifiers
-
- scopus:105041949637
- ISSN
- 2731-6963
- DOI
- 10.1007/s44212-022-00013-1
- language
- English
- LU publication?
- yes
- additional info
- Publisher Copyright: © The Author(s) 2022.
- id
- 5a0a534b-6a48-44b2-9629-32a28f46f32d
- date added to LUP
- 2026-08-14 13:31:49
- date last changed
- 2026-08-17 06:33:09
@article{5a0a534b-6a48-44b2-9629-32a28f46f32d,
abstract = {{<p>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.</p>}},
author = {{Mangold, Max and Zhao, Pengxiang and Haitao, He and Mansourian, Ali}},
issn = {{2731-6963}},
keywords = {{AHP; Dockless bike-sharing; Geo-fence planning; GIS; Multi-criteria decision analysis; VIKOR}},
language = {{eng}},
publisher = {{Springer}},
series = {{Urban Informatics}},
title = {{Geo-fence planning for dockless bike-sharing systems : a GIS-based multi-criteria decision analysis framework}},
url = {{http://dx.doi.org/10.1007/s44212-022-00013-1}},
doi = {{10.1007/s44212-022-00013-1}},
volume = {{1}},
year = {{2022}},
}