Optimal bike allocations in a competitive bike sharing market
Zhang, Jie, Meng, Meng, Wang, David, Zhou, Li ORCID: https://orcid.org/0000-0001-7132-5935 and Han, Linghui (2022) Optimal bike allocations in a competitive bike sharing market. Journal of Cleaner Production, 384:135602. ISSN 0959-6526 (doi:10.1016/j.jclepro.2022.135602)
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Abstract
This paper studies the bike allocation problem in a competitive bike sharing market. To overcome computational challenges, a continuum approximation (CA) approach is applied, where the allocation points and user demand are assumed to be continuously distributed in a two-dimensional region. Companies offering bike sharing service bear both allocation cost and bike depreciation cost while earning revenue from fare collection. The user’s selection of bike service is affected by both walking distance and preference towards bike quality. The elasticity of the demand is considered in relation to the density of allocation points in the market. A leader-follower Stackelberg competition model is developed to derive the optimal allocation strategy for market leader. Two sets of numerical studies - one hypothetical case and one from a real case - are conducted to specify the impact of the parameters on model performance and illustrate how the proposed model can be applied to support the decision making.
Item Type: | Article |
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Additional Information: | An earlier conference version of the paper is found here: Title of host publication: 24th International Symposium on Transportation and Traffic Theory (ISTTT24) Publication status Published -2021 http://isttt24.buaa.edu.cn/pdf/Optimal_bike_allocations_in_a_competitive_bike_sharing_market_A_continuum_approximation_approach.pdf -MP |
Uncontrolled Keywords: | bike sharing; allocation strategy; demand elasticity; continuous approximation; stackelberg competition |
Subjects: | H Social Sciences > HB Economic Theory H Social Sciences > HE Transportation and Communications H Social Sciences > HF Commerce |
Faculty / School / Research Centre / Research Group: | Faculty of Business Faculty of Business > Department of Systems Management & Strategy Faculty of Business > Networks and Urban Systems Centre (NUSC) Faculty of Business > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group Greenwich Business School > Networks and Urban Systems Centre (NUSC) Greenwich Business School > Networks and Urban Systems Centre (NUSC) > Connected Cities Research Group (CCRG) |
Last Modified: | 14 Dec 2024 03:00 |
URI: | http://gala.gre.ac.uk/id/eprint/38250 |
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