IDEAS home Printed from https://ideas.repec.org/a/eee/transe/v180y2023ics1366554523003484.html
   My bibliography  Save this article

A beautiful shock? Exploring the impact of pandemic shocks on the accuracy of AI forecasting in the beauty care industry

Author

Listed:
  • Jackson, Ilya
  • Ivanov, Dmitry

Abstract

This research focuses on the profound impact of the shocks caused by the COVID-19 pandemic on the accuracy of AI-based demand forecasting in the beauty care industry. It aims to understand the key factors that led to decreased forecasting accuracy during the pandemic and employs causal mediation analysis to systematically investigate this complex issue. The empirical analysis is conducted using extensive order data from a major beauty care product manufacturer and distributor, covering the pre-pandemic, pandemic, and post-pandemic periods. The findings reveal that it is primarily the increase in demand volatility, and not the surge in sales volume, that has led to an increase in forecasting errors. This research provides crucial insights into the nuanced effects of macroeconomic shocks and consumer behavior changes on AI-based forecasting within the beauty care industry. Furthermore, it highlights the importance of understanding the underlying mechanisms that drive forecasting errors, paving the way for more resilient and robust demand forecasting systems in the future.

Suggested Citation

  • Jackson, Ilya & Ivanov, Dmitry, 2023. "A beautiful shock? Exploring the impact of pandemic shocks on the accuracy of AI forecasting in the beauty care industry," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 180(C).
  • Handle: RePEc:eee:transe:v:180:y:2023:i:c:s1366554523003484
    DOI: 10.1016/j.tre.2023.103360
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S1366554523003484
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.tre.2023.103360?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:transe:v:180:y:2023:i:c:s1366554523003484. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600244/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.