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Article: Understanding order cancellation behavior in on-demand delivery services

TitleUnderstanding order cancellation behavior in on-demand delivery services
Authors
KeywordsMatching and pick-up
On-demand services
Order cancellation
Reference effect
Survival analysis
Issue Date1-Aug-2025
PublisherElsevier
Citation
Transportation Research Part A: Policy and Practice, 2025, v. 198 How to Cite?
AbstractThe rise of digital platforms has transformed urban mobility by offering a wide range of on-demand transportation and delivery services, such as ride-hailing, grocery delivery, and food delivery. Consumers using these services typically experience two key waiting stages: waiting online for matching and waiting physically for driver pick-up. A common consequence of waiting is order cancellation, which not only disrupts platform operations but also generates inefficient vehicle movements and puts strain on urban road networks. This paper examines the dynamics of order cancellations in the two stages and their interactions by using a two-stage survival analysis combined with a Heckman correction model. Based on a dataset of delivered and cancelled orders from an on-demand food delivery platform in Asia, we reveal several key findings. First, we identify an asymmetric effect of accumulated waiting time on cancellations before and after the expected waiting time, which provides evidence to the existence of reference-dependence preferences in on-demand services. Second, while higher delivery fees reduce cancellations in the matching stage, they increase the risk of orders being cancelled shortly after they are matched to drivers. Third, the risk of cancellation is significantly reduced when the order is delivered by a familiar driver. Lastly, we reveal how the risk of order cancellation varies with waiting time in both the matching and pick-up stages. These findings provide valuable insights for optimizing pricing and matching strategies to mitigate order cancellations, enhance the efficiency of on-demand services, and reduce inefficient trips caused by cancellations.
Persistent Identifierhttp://hdl.handle.net/10722/357896
ISSN
2023 Impact Factor: 6.3
2023 SCImago Journal Rankings: 2.182
ISI Accession Number ID

 

DC FieldValueLanguage
dc.contributor.authorLiang, Jian-
dc.contributor.authorZhao, Ya-
dc.contributor.authorWang, Hai-
dc.contributor.authorYang, Linchuan-
dc.contributor.authorKe, Jintao-
dc.date.accessioned2025-07-22T03:15:39Z-
dc.date.available2025-07-22T03:15:39Z-
dc.date.issued2025-08-01-
dc.identifier.citationTransportation Research Part A: Policy and Practice, 2025, v. 198-
dc.identifier.issn0965-8564-
dc.identifier.urihttp://hdl.handle.net/10722/357896-
dc.description.abstractThe rise of digital platforms has transformed urban mobility by offering a wide range of on-demand transportation and delivery services, such as ride-hailing, grocery delivery, and food delivery. Consumers using these services typically experience two key waiting stages: waiting online for matching and waiting physically for driver pick-up. A common consequence of waiting is order cancellation, which not only disrupts platform operations but also generates inefficient vehicle movements and puts strain on urban road networks. This paper examines the dynamics of order cancellations in the two stages and their interactions by using a two-stage survival analysis combined with a Heckman correction model. Based on a dataset of delivered and cancelled orders from an on-demand food delivery platform in Asia, we reveal several key findings. First, we identify an asymmetric effect of accumulated waiting time on cancellations before and after the expected waiting time, which provides evidence to the existence of reference-dependence preferences in on-demand services. Second, while higher delivery fees reduce cancellations in the matching stage, they increase the risk of orders being cancelled shortly after they are matched to drivers. Third, the risk of cancellation is significantly reduced when the order is delivered by a familiar driver. Lastly, we reveal how the risk of order cancellation varies with waiting time in both the matching and pick-up stages. These findings provide valuable insights for optimizing pricing and matching strategies to mitigate order cancellations, enhance the efficiency of on-demand services, and reduce inefficient trips caused by cancellations.-
dc.languageeng-
dc.publisherElsevier-
dc.relation.ispartofTransportation Research Part A: Policy and Practice-
dc.rightsThis work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.-
dc.subjectMatching and pick-up-
dc.subjectOn-demand services-
dc.subjectOrder cancellation-
dc.subjectReference effect-
dc.subjectSurvival analysis-
dc.titleUnderstanding order cancellation behavior in on-demand delivery services-
dc.typeArticle-
dc.identifier.doi10.1016/j.tra.2025.104515-
dc.identifier.scopuseid_2-s2.0-105005958375-
dc.identifier.volume198-
dc.identifier.eissn1879-2375-
dc.identifier.isiWOS:001504577100003-
dc.identifier.issnl0965-8564-

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