Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/115396
DC FieldValueLanguage
dc.contributorDepartment of Industrial and Systems Engineering-
dc.creatorWang, Y.-J-
dc.creatorWang, Y-
dc.creatorHuang, GQ-
dc.creatorLin, C-
dc.date.accessioned2025-09-23T03:16:45Z-
dc.date.available2025-09-23T03:16:45Z-
dc.identifier.issn0377-2217-
dc.identifier.urihttp://hdl.handle.net/10397/115396-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.subjectLogisticsen_US
dc.subjectCrowdsourced deliveryen_US
dc.subjectAcceptance modelingen_US
dc.subjectTrusten_US
dc.subjectSocial influenceen_US
dc.titlePublic acceptance of crowdsourced delivery from a customer perspectiveen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.spage793-
dc.identifier.epage805-
dc.identifier.volume317-
dc.identifier.issue3-
dc.identifier.doi10.1016/j.ejor.2023.03.028-
dcterms.abstractThe goals of crowdsourced delivery are to enable customers to be served efficiently and flexibly by occasional deliverymen. It could also be considered pro-social behavior by utilizing available human resources as deliverymen. The successful implementation of crowdsourced delivery highly depends on customers' willingness to adopt the crowdsourced delivery service considering its characteristics. This study develops a novel theoretical acceptance model of crowdsourced delivery service, integrating the technology acceptance model and norm activation model with the considerations of trust, social influence, and loss of privacy. The proposed model is tested based on the empirical data captured by a cross-sectional survey administered to 2333 participants in China through partial least squares structural equation modeling. Multiple group analyses are conducted to test whether the results were different or identical among various factors. The results indicate the proposed acceptance model interprets 84.5% of the variance in the behavioral intention of using the crowdsourced delivery service. The influences of predictors from the technology acceptance model are greater than those of predictors from the norm activation model, while social influence and trust are revealed to contribute most to explaining whether customers would accept crowdsourced delivery services. In contrast, loss of privacy negatively affects behavioral intention. Age, usage experience, and experience of being occasional deliverymen also moderate the path coefficients between antecedent factors and behavioral intention to use crowdsourced delivery services. We also provide theoretical findings and practical suggestions for developing crowdsourced delivery services based on the results and our analysis.-
dcterms.accessRightsembargoed accessen_US
dcterms.bibliographicCitationEuropean journal of operational research, Sept 2024, v. 317, no. 3, p. 793-805-
dcterms.isPartOfEuropean journal of operational research-
dcterms.issued2024-09-
dc.identifier.scopus2-s2.0-85152640863-
dc.identifier.eissn1872-6860-
dc.description.validate202509 bcrc-
dc.description.oaNot applicableen_US
dc.identifier.FolderNumbera4084ben_US
dc.identifier.SubFormID52061en_US
dc.description.fundingSourceRGCen_US
dc.description.fundingTextthe 2019 Guangdong Special Support Talent Program – Innovation and Entrepreneurship Leading Team (China) (2019BT02S593) ;en_US
dc.description.pubStatusPublisheden_US
dc.date.embargo2026-09-16en_US
dc.description.oaCategoryGreen (AAM)en_US
Appears in Collections:Journal/Magazine Article
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Embargo End Date 2026-09-16
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