Shelf-space Allocation Model with Demand Learning

Kazuki Ishichi
Waseda University, Tokyo, Japan

Shunichi Ohmori
Waseda University, Tokyo, Japan

Masao Ueda
Waseda University, Tokyo, Japan

Kazuho Yoshimoto
Waseda University, Tokyo, Japan

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.

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This paper has been downloaded 16 times since published. The persistent DOI of this paper is DOI:10.31387/oscm0360219.