Please use this identifier to cite or link to this item:
http://hdl.handle.net/10397/112757
| DC Field | Value | Language |
|---|---|---|
| dc.contributor | Department of Logistics and Maritime Studies | en_US |
| dc.creator | Jin, Z | en_US |
| dc.creator | Pan, K | en_US |
| dc.creator | Shen, ZJM | en_US |
| dc.creator | Xu, W | en_US |
| dc.date.accessioned | 2025-04-29T01:33:04Z | - |
| dc.date.available | 2025-04-29T01:33:04Z | - |
| dc.identifier.issn | 2472-5854 | en_US |
| dc.identifier.uri | http://hdl.handle.net/10397/112757 | - |
| dc.language.iso | en | en_US |
| dc.publisher | Taylor & Francis Inc. | en_US |
| dc.rights | © 2024 IISE | en_US |
| dc.rights | This is an Accepted Manuscript of an article published by Taylor & Francis in IISE transactions on 22 Oct 2024 (published online), available at: https://doi.org/10.1080/24725854.2024.2404555. | en_US |
| dc.subject | Allocation and relocation | en_US |
| dc.subject | Capacity sharing | en_US |
| dc.subject | Competition | en_US |
| dc.subject | Shared micromobility | en_US |
| dc.subject | Two-stage stochasticprogramming | en_US |
| dc.title | Integrated vehicle allocation and relocation for shared micromobility under competition and demand uncertainty | en_US |
| dc.type | Journal/Magazine Article | en_US |
| dc.identifier.spage | 994 | en_US |
| dc.identifier.epage | 1013 | en_US |
| dc.identifier.volume | 57 | en_US |
| dc.identifier.issue | 8 | en_US |
| dc.identifier.doi | 10.1080/24725854.2024.2404555 | en_US |
| dcterms.abstract | This article aims to understand the shared micromobility firms’ operations under competition and provide managerial guidance to the firms and the regulator. We consider two shared micromobility firms competing in the same service area, each providing micromobility vehicles to satisfy uncertain demands. Concerning allocation restrictions by the regulator, we propose an innovative capacity-sharing agreement between the two firms. Each firm solves an integrated vehicle allocation and relocation problem, modeled as a two-stage stochastic program on a spatial-temporal network. We explore the optimality condition of each firm’s decision-making and seek a Nash equilibrium by optimizing certain objectives over the joint optimality conditions of both firms. We prove that capacity sharing helps reduce the total demand loss in the system. We perform extensive numerical experiments based on real data to obtain managerial insights. We find that regulator restrictions impact firms’ profitability and service level. After introducing capacity sharing, one firm may act like a free rider that relies on the vehicles transferred from her opponent. Meanwhile, many vehicles are shared in periods and regions with high trip demands. Capacity sharing can reduce the number of relocated vehicles by serving as a substitution for relocation and also improves the firms’ profitability. | en_US |
| dcterms.accessRights | open access | en_US |
| dcterms.bibliographicCitation | IISE transactions, 2025, v. 57, no. 8, p. 994-1013 | en_US |
| dcterms.isPartOf | IISE transactions | en_US |
| dcterms.issued | 2025 | - |
| dc.identifier.eissn | 2472-5862 | en_US |
| dc.description.validate | 202504 bcch | en_US |
| dc.description.oa | Accepted Manuscript | en_US |
| dc.identifier.FolderNumber | a3558 | - |
| dc.identifier.SubFormID | 50362 | - |
| dc.description.fundingSource | RGC | en_US |
| dc.description.pubStatus | Published | en_US |
| dc.description.oaCategory | Green (AAM) | en_US |
| Appears in Collections: | Journal/Magazine Article | |
Files in This Item:
| File | Description | Size | Format | |
|---|---|---|---|---|
| Jin_Integrated_Vehicle_Allocation.pdf | Pre-Published version | 4.26 MB | Adobe PDF | View/Open |
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