Forecasting and planning during a pandemic: COVID-19 growth rates, supply chain disruptions, and governmental decisions

DOI10.1016/j.ejor.2020.08.001zbMath1487.90037OpenAlexW3047031799WikidataQ98659765 ScholiaQ98659765MaRDI QIDQ2029312

Andreas Schäfers, Christos Tsinopoulos, Konstantinos Nikolopoulos, Chrysovalantis Vasilakis, Sushil Punia

Publication date: 3 June 2021

Published in: European Journal of Operational Research (Search for Journal in Brave)

Full work available at URL: https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7413852

zbMATH Keywords

forecastingexcess demandpandemicCOVID-19lockdown

Mathematics Subject Classification ID

Inference from stochastic processes and prediction (62M20) Learning and adaptive systems in artificial intelligence (68T05) Inventory, storage, reservoirs (90B05)

Related Items (21)

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Uses Software

• caret
• Keras
• GitHub

Cites Work

• Unnamed Item
• The bullwhip effect: progress, trends and directions
• Supply chain management of blood products: a literature review
• Deep learning with long short-term memory networks for financial market predictions
• On the calculation of safety stocks when demand is forecasted
• `Horses for courses' in demand forecasting
• Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information
• Information Distortion in a Supply Chain: The Bullwhip Effect
• Forecasting Trends in Time Series
• Random forests

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