Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains
type: Item
instance of: scholarly article
title: Using shared sell-through data to forecast wholesaler demand in multi-echelon supply chains
zbMATH Open document ID: 1487.90050
author: Jente Van Belle
author: Tias Guns
author: Wouter Verbeke
published in: European Journal of Operational Research
publication date: 2021-06-03T00:00:00Z
Mathematics Subject Classification ID: 90B05
Mathematics Subject Classification ID: 62M20
Mathematics Subject Classification ID: 62P20
Mathematics Subject Classification ID: 68T05
zbMATH DE Number: 7354095
zbMATH Keywords: forecasting
zbMATH Keywords: bullwhip effect
zbMATH Keywords: information sharing
zbMATH Keywords: sell-through data
zbMATH Keywords: machine learning
describes a project that uses: R
describes a project that uses: DYNAMO
describes a project that uses: forecast
describes a project that uses: caret
describes a project that uses: ElemStatLearn
describes a project that uses: smooth
describes a project that uses: MASS (R)
describes a project that uses: Forecast
describes a project that uses: Kernlab
describes a project that uses: expsmooth
describes a project that uses: glmnet
describes a project that uses: ranger
MaRDI profile type: Publication
full work available at URL: j.ejor.2020.05.059
OpenAlex ID: W3033619708
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DOI: 10.1016/J.EJOR.2020.05.059
description: scientific article; zbMATH DE number 7354095