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  • PostScipt_Retail Forecasting: Research and Practice

    Rights statement: This is the author’s version of a work that was accepted for publication in International Journal of Forecasting. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Forecasting, 38, 4, 2022 DOI: 10.1016/j.ijforecast.2021.09.012

    Accepted author manuscript, 596 KB, PDF document

    Embargo ends: 17/11/23

    Available under license: CC BY-NC-ND: Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License

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Post-script - Retail forecasting: Research and Practice

Research output: Contribution to Journal/MagazineJournal articlepeer-review

Published
<mark>Journal publication date</mark>31/10/2022
<mark>Journal</mark>International Journal of Forecasting
Issue number4
Volume38
Number of pages6
Pages (from-to)1319-1324
Publication StatusPublished
Early online date17/11/21
<mark>Original language</mark>English

Abstract

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.

Bibliographic note

This is the author’s version of a work that was accepted for publication in International Journal of Forecasting. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in International Journal of Forecasting, 38, 4, 2022 DOI: 10.1016/j.ijforecast.2021.09.012