Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/99013
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dc.contributorDepartment of Logistics and Maritime Studiesen_US
dc.creatorWang, Sen_US
dc.creatorYan, Ren_US
dc.date.accessioned2023-06-08T01:09:12Z-
dc.date.available2023-06-08T01:09:12Z-
dc.identifier.issn2772-3909en_US
dc.identifier.urihttp://hdl.handle.net/10397/99013-
dc.language.isoenen_US
dc.publisherElsevieren_US
dc.rights© 2022 The Authors. Published by Elsevier Ltd. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).en_US
dc.rightsThe following publication Wang, S., & Yan, R. (2022). A global method from predictive to prescriptive analytics considering prediction error for “Predict, then optimize” with an example of low-carbon logistics. Cleaner Logistics and Supply Chain, 4, 100062 is available at https://doi.org/10.1016/j.clscn.2022.100062.en_US
dc.titleA global method from predictive to prescriptive analytics considering prediction error for “predict, then optimize” with an example of low-carbon logisticsen_US
dc.typeJournal/Magazine Articleen_US
dc.identifier.volume4en_US
dc.identifier.doi10.1016/j.clscn.2022.100062en_US
dcterms.accessRightsopen accessen_US
dcterms.bibliographicCitationCleaner logistics and supply chain, July 2022, v. 4, 100062en_US
dcterms.isPartOfCleaner logistics and supply chainen_US
dcterms.issued2022-07-
dc.identifier.scopus2-s2.0-85135393429-
dc.identifier.artn100062en_US
dc.description.validate202306 bcwwen_US
dc.description.oaVersion of Recorden_US
dc.identifier.FolderNumbera2087-
dc.identifier.SubFormID46517-
dc.description.fundingSourceSelf-fundeden_US
dc.description.pubStatusPublisheden_US
dc.description.oaCategoryCCen_US
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