Predicting Out-of-Stock Using Machine Learning: An Application in a Retail Packaged Foods Manufacturing Company
For decades, Out-of-Stock (OOS) events have been a problem for retailers and manufacturers. In grocery retailing, an OOS event is used to characterize the condition in which customers do not find a certain commodity while attempting to buy it. This paper focuses on addressing this problem from a man...
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| Auteurs principaux: | , , |
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| Format: | article |
| Langue: | EN |
| Publié: |
MDPI AG
2021
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| Accès en ligne: | https://doaj.org/article/6cb49aaca9b343dfab19bb79b7415530 |
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