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Demand forecasting in retail operations for fashionable products: methods, practices, and real case study

Author

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  • Shuyun Ren

    (Guangdong University of Technology)

  • Hau-Ling Chan

    (The Hong Kong Polytechnic University)

  • Tana Siqin

    (Shanghai University)

Abstract

Demand forecasting for the fashionable products is still a difficult task for both academia and industry regardless of how many effective approaches have been investigated and studied in the literature. The arriving of big data era leads to a round of revolution on the demand forecasting for the fashionable products, and at the same time, it makes a great challenge to traditional forecasting methods and inventory planning. In this study, we firstly conduct a comprehensive literature review on demand forecasting methods for the fashionable products and find out the challenges of the traditional forecasting methods. Then, we examine how fashion retailer tackles the future demand forecasting and inventory planning problem in practice via a real-world case study. Finally, an in-depth analysis and future research directions are discussed.

Suggested Citation

  • Shuyun Ren & Hau-Ling Chan & Tana Siqin, 2020. "Demand forecasting in retail operations for fashionable products: methods, practices, and real case study," Annals of Operations Research, Springer, vol. 291(1), pages 761-777, August.
    • Handle: RePEc:spr:annopr:v:291:y:2020:i:1:d:10.1007_s10479-019-03148-8
    DOI: 10.1007/s10479-019-03148-8
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    References listed on IDEAS

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    5. Xinxue (Shawn) Qu & Aslan Lotfi & Dipak C. Jain & Zhengrui Jiang, 2022. "Predicting upgrade timing for successive product generations: An exponential‐decay proportional hazard model," Production and Operations Management, Production and Operations Management Society, vol. 31(5), pages 2067-2083, May.

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