Annals of Operations Research
https://doi.org/10.1007/s10479-019-03148-8
S.I.:REALCASEOR
Demand forecasting in retail operations for fashionable
products: methods, practices, and real case study
Shuyun Ren
1
· Hau-Ling Chan
2
· Tana Siqin
3
© Springer Science+Business Media, LLC, part of Springer Nature 2019
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
1 Introduction
Over the past years, there has been a significant revolution in the fashion industry. The rapid
development of big data and AI technologies have redefined the fashion retail operations as
it provides explosive information growth and affects both the behaviors of the customers and
operations of the companies significantly, including those in the fashion industry. In the past,
it was observed that the fashion retailers were the ones who had full information, however, this
phenomenon has been changed. Nowadays, due to the technological development, customers
B Hau-Ling Chan
itcling@yahoo.com.hk
Shuyun Ren
shuyun_shara@live.cn
Tana Siqin
tana525@126.com
1
Guangdong University of Technology, Yuexiu District, Guangzhou City, China
2
Division of Business, Hong Kong Community College, The Hong Kong Polytechnic University,
Hung Hom, Kowloon, Hong Kong
3
SHU-UTS SILC Business School, Shanghai University, Jiading District, Shanghai City, China
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