TY - JOUR
T1 - Shelf-space allocation model with demand learning
AU - Ishichi, Kazuki
AU - Ohmori, Shunichi
AU - Ueda, Masao
AU - Yoshimoto, Kazuho
N1 - Publisher Copyright:
© 2018 China Anti-Cancer Association. All rights reserved.
PY - 2019
Y1 - 2019
N2 - In this paper, we studied the shelf-space allocation problem (SSAP). It is quite common recently to implement product design during a selling season and drastically change assortment decisions based on shelf-space allocation in response to up-to-date demand observations. While there are many literatures related to SSAP, However, existing literature assume that the demand is stationary. In this paper, we propose a dynamical framework to make shelf-space display decisions, in which space elasticity and potential demand are sequentially estimated using the latest data containing display space and sales for each product.
AB - In this paper, we studied the shelf-space allocation problem (SSAP). It is quite common recently to implement product design during a selling season and drastically change assortment decisions based on shelf-space allocation in response to up-to-date demand observations. While there are many literatures related to SSAP, However, existing literature assume that the demand is stationary. In this paper, we propose a dynamical framework to make shelf-space display decisions, in which space elasticity and potential demand are sequentially estimated using the latest data containing display space and sales for each product.
KW - Demand management
KW - Retail operations
KW - Shelf-space allocation problem
UR - http://www.scopus.com/inward/record.url?scp=85061239867&partnerID=8YFLogxK
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U2 - 10.31387/oscm0360219
DO - 10.31387/oscm0360219
M3 - Article
AN - SCOPUS:85061239867
VL - 12
SP - 24
EP - 30
JO - Operations and Supply Chain Management
JF - Operations and Supply Chain Management
SN - 1979-3561
IS - 1
ER -