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Shelf-space Allocation Model with Demand Learning

Author(s):

  • Kazuki Ishichi (Waseda University, Tokyo, Japan)
  • Shunichi Ohmori (Waseda University, Tokyo, Japan)
  • Masao Ueda (Waseda University, Tokyo, Japan)
  • Kazuho Yoshimoto (Waseda University, Tokyo, Japan)

DOI: http://doi.org/10.31387/oscm0360219

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Abstract:
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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