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

Shuyun Ren (), Hau-Ling Chan () and Tana Siqin ()
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Shuyun Ren: Guangdong University of Technology
Hau-Ling Chan: The Hong Kong Polytechnic University
Tana Siqin: Shanghai University

Annals of Operations Research, 2020, vol. 291, issue 1, No 29, 777 pages

Abstract: 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.

Keywords: Demand forecasting; Fashion retail; Case study; Big data (search for similar items in EconPapers)
Date: 2020
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Citations: View citations in EconPapers (10)

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DOI: 10.1007/s10479-019-03148-8

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