Tavasoli, Mohammadamin, Baldacci, Roberto, Kayvanfar, Vahid, Zhang, Yu, Triki, Chefi, Elomri, Adel (2026) Methodological Advances in Online Food Delivery: A Systematic Review, Taxonomy, and Research Outlook. Transportation Research Part E: Logistics and Transportation Review, 213 . Article Number 104972. ISSN 1366-5545. (doi:10.1016/j.tre.2026.104972) (KAR id:115371)
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| Official URL: https://doi.org/10.1016/j.tre.2026.104972 |
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Abstract
Since the platformization of restaurant delivery, Online Food Delivery (OFD) has expanded rapidly, intensifying competition, compressing margins, and amplifying operational complexity. As in other transportation domains, Operation Research (OR) provides the methodological backbone for structuring and optimizing the Food Delivery Service (FDS). The literature on OFD optimization is now flourishing, while emerging technologies create new challenges and modeling requirements. This article presents a Systematic Literature Review (SLR) of quantitative OFD research and offers a coherent reference for scholars and practitioners. We introduce a multidimensional classification that organizes the field by decision level, problem setting, and analytical approach, and we formalize a methodology that maps real-world OFD complexities into precise OR problem components, enabling consistent categorization and comparison. We also curate standardized tabular and visual summaries to support transparent description, benchmarking, and reproducibility. Finally, we articulate open research areas and corresponding directions to guide subsequent work.
| Item Type: | Article |
|---|---|
| DOI/Identification number: | 10.1016/j.tre.2026.104972 |
| Projects: | RATIONAL - Robust And daTa-drIven Optimization for iNstAnt Logistics |
| Additional information: | For the purpose of open access, the author(s) has applied a Creative Commons Attribution (CC BY) licence to any Author Accepted Manuscript version arising. |
| Uncontrolled keywords: | Online food delivery; Operations research; Food delivery systems; Review; Optimization; Emerging technologies |
| Subjects: | H Social Sciences |
| Institutional Unit: | Schools > Kent Business School |
| Former Institutional Unit: |
There are no former institutional units.
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| Depositing User: | Chefi Triki |
| Date Deposited: | 19 May 2026 14:57 UTC |
| Last Modified: | 11 Jun 2026 16:03 UTC |
| Resource URI: | https://kar.kent.ac.uk/id/eprint/115371 (The current URI for this page, for reference purposes) |
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https://orcid.org/0000-0002-8750-2470
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