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

  • Shuyun Ren
  • Hau-Ling ChanEmail author
  • Tana Siqin


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.


Demand forecasting Fashion retail Case study Big data 



Funding was provided by National Natural Science Foundation of China (Grant No. 71801054).


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© Springer Science+Business Media, LLC, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Guangdong University of TechnologyYuexiu District, Guangzhou CityChina
  2. 2.Division of Business, Hong Kong Community CollegeThe Hong Kong Polytechnic UniversityHung Hom, KowloonHong Kong
  3. 3.SHU-UTS SILC Business SchoolShanghai UniversityJiading District, Shanghai CityChina

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