文章基本信息

标题：Towards a Predictive Approach for Omni-channel Retailing Supply Chains
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作者：Marina Meireles Pereira ; Enzo Morosini Frazzon
期刊名称：IFAC PapersOnLine
印刷版ISSN：2405-8963
出版年度：2019
卷号：52
期号：13
页码：844-850
DOI：10.1016/j.ifacol.2019.11.235
语种：English
出版社：Elsevier
摘要：The adoption of omni-channel strategy has changed the relation between retailers and customers and brought more complexity to the retailing supply chains. To address the increasing complexity, it is necessary to adopt innovative approaches based on information technologies and intelligent decision methods. The challenges to retailers are improving the accuracy of offline and online channels demand forecasting, better managing offline and online customer’s needs, thus reducing the uncertainties of the omni-channel retailing supply chain. In this context, this research paper aims to propose a predictive approach for omni-channel retailing supply chain combining clustering with artificial neural network to handle demand uncertainty.
关键词：KeywordsSupply Chain ManagementRetail supply chainOmni-channelMachine LearningClusteringArtificial Neural Network