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In International journal of forecasting

This note updates the 2019 review article "Retail forecasting: Research and practice" in the context of the COVID-19 pandemic and the substantial new research on machine-learning algorithms, when applied to retail. It offers new conclusions and challenges for both research and practice in retail demand forecasting.

Fildes Robert, Kolassa Stephan, Ma Shaohui

COVID-19, Disruption, Instability, Machine learning, Omni-retailing, Online retail, Structural change