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Sales Forecasting in Apparel and Fashion Industry: A Review

In: Intelligent Fashion Forecasting Systems: Models and Applications

Author

Listed:
  • Sébastien Thomassey

    (University Lille Nord of France)

Abstract

The fashion industry is a very fascinating sector for the sales forecasting. Indeed, the long time-to-market which contrasts with the short life cycle of products, makes the forecasting process very challenging. A suitable forecasting system should also deal with the specificities of the demand: fashion trends, seasonality, influence of many exogenous factors, …. We propose here a review of the different constraints related to the sales forecasting in the fashion industry, the methodologies and techniques existing in the literature to cope with these constraints and finally, the new topics which could be explored in the field of the sales forecasting for fashion products.

Suggested Citation

  • Sébastien Thomassey, 2014. "Sales Forecasting in Apparel and Fashion Industry: A Review," Springer Books, in: Tsan-Ming Choi & Chi-Leung Hui & Yong Yu (ed.), Intelligent Fashion Forecasting Systems: Models and Applications, edition 127, chapter 0, pages 9-27, Springer.
    • Handle: RePEc:spr:sprchp:978-3-642-39869-8_2
    DOI: 10.1007/978-3-642-39869-8_2
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    Citations

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    Cited by:

    1. Shuyun Ren & Hau-Ling Chan & Pratibha Ram, 2017. "A Comparative Study on Fashion Demand Forecasting Models with Multiple Sources of Uncertainty," Annals of Operations Research, Springer, vol. 257(1), pages 335-355, October.
    2. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2022. "Retail forecasting: Research and practice," International Journal of Forecasting, Elsevier, vol. 38(4), pages 1283-1318.
    3. Belvedere, Valeria & Goodwin, Paul, 2017. "The influence of product involvement and emotion on short-term product demand forecasting," International Journal of Forecasting, Elsevier, vol. 33(3), pages 652-661.
    4. Fildes, Robert & Ma, Shaohui & Kolassa, Stephan, 2019. "Retail forecasting: research and practice," MPRA Paper 89356, University Library of Munich, Germany.
    5. Giovanni Battista Gardino & Rosa Meo & Giuseppe Craparotta, 2021. "Multi-view Latent Learning Applied to Fashion Industry," Information Systems Frontiers, Springer, vol. 23(1), pages 53-69, February.
    6. Emmanuel Sirimal Silva & Hossein Hassani & Dag Øivind Madsen & Liz Gee, 2019. "Googling Fashion: Forecasting Fashion Consumer Behaviour Using Google Trends," Social Sciences, MDPI, vol. 8(4), pages 1-23, April.
    7. Swaminathan, Kritika & Venkitasubramony, Rakesh, 2024. "Demand forecasting for fashion products: A systematic review," International Journal of Forecasting, Elsevier, vol. 40(1), pages 247-267.
    8. Giovanni Battista Gardino & Rosa Meo & Giuseppe Craparotta, 0. "Multi-view Latent Learning Applied to Fashion Industry," Information Systems Frontiers, Springer, vol. 0, pages 1-17.

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