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dc.rights.licenseopenen_US
dc.contributor.authorROSTAMI-TABAR, B.
hal.structure.identifierKedge Business School [Kedge BS]
dc.contributor.authorBABAI, Mohamed Zied
hal.structure.identifierLaboratoire de l'intégration, du matériau au système [IMS]
dc.contributor.authorDUCQ, Yves
ORCID: 0000-0001-5144-5876
IDREF: 119003791
dc.contributor.authorSYNTETOS, A.
dc.date.accessioned2021-02-25T12:30:40Z
dc.date.available2021-02-25T12:30:40Z
dc.date.issued2015
dc.identifier.issn0925-5273en_US
dc.identifier.urihttps://oskar-bordeaux.fr/handle/20.500.12278/26351
dc.description.abstractEnIn this paper the relative effectiveness of top-down (TD) versus bottom-up (BU) approaches is compared for cross-sectionally forecasting aggregate and sub-aggregate demand. We assume that the sub-aggregate demand follows a non-stationary Integrated Moving Average (IMA) process of order one and a Single Exponential Smoothing (SES) procedure is used to extrapolate future requirements. Such demand processes are often encountered in practice and SES is one of the standard estimators used in industry (in addition to being the optimal estimator for an IMA process). Theoretical variances of forecast error are derived for the BU and TD approach in order to contrast the relevant forecasting performances. The theoretical analysis is supported by an extensive numerical investigation at both the aggregate and sub-aggregate level, in addition to empirically validating our findings on a real dataset from a European superstore. The results demonstrate the increased benefit resulting from cross-sectional forecasting in a non-stationary environment than in a stationary one. Valuable insights are offered to demand planners and the paper closes with an agenda for further research in this area. © 2015 Elsevier B.V. All rights reserved.
dc.language.isoENen_US
dc.subject.enCross-Sectional Aggregation
dc.subject.enDemand Forecasting
dc.subject.enNon-Stationary Processes
dc.subject.enSingle Exponential Smoothing
dc.title.enNon-stationary demand forecasting by cross-sectional aggregation
dc.title.alternativeInt J Prod Econen_US
dc.typeArticle de revueen_US
dc.identifier.doi10.1016/j.ijpe.2015.10.001
dc.subject.halSciences de l'ingénieur [physics]/Autreen_US
bordeaux.journalInternational Journal of Production Economicsen_US
bordeaux.page297-309en_US
bordeaux.volume170en_US
bordeaux.hal.laboratoriesLaboratoire d’Intégration du Matériau au Système (IMS) - UMR 5218en_US
bordeaux.institutionUniversité de Bordeauxen_US
bordeaux.institutionBordeaux INPen_US
bordeaux.peerReviewedouien_US
bordeaux.inpressnonen_US
hal.identifierhal-03173378
hal.version1
hal.date.transferred2021-03-18T13:19:46Z
hal.exporttrue
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