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Optimizing product assortment under customer-driven demand substitution


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  • Yücel, Eda
  • Karaesmen, Fikri
  • Salman, F. Sibel
  • Türkay, Metin
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    The problem of product assortment and inventory planning under customer-driven demand substitution is analyzed and a mathematical model for this problem is provided in this paper. Realistic issues in a retail context such as supplier selection, shelf space constraints, and poor quality procurement are also taken into account. The performance of three modified models, one that neglects customers' substitution behavior, another that excludes supplier selection decision, and one that ignores shelf space limitations, are analyzed separately with computational experiments. The results of the analysis demonstrate that neglecting customer-driven substitution or excluding supplier selection or ignoring shelf space limitations may lead to significantly inefficient assortments. The effects of demand variability and substitution cost on optimal assortment and supplier selection decisions as well as on the optimal revenue are also investigated. The main contribution of this paper is the development of a practical and flexible model to aid retailers in finding optimal assortments to maximize the expected profit.

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    Bibliographic Info

    Article provided by Elsevier in its journal European Journal of Operational Research.

    Volume (Year): 199 (2009)
    Issue (Month): 3 (December)
    Pages: 759-768

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    Handle: RePEc:eee:ejores:v:199:y:2009:i:3:p:759-768

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    Keywords: Retailing Inventory Demand substitution Product assortment Supplier selection;


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    Cited by:
    1. Tan, Baris & Karabati, Selcuk, 2013. "Retail inventory management with stock-out based dynamic demand substitution," International Journal of Production Economics, Elsevier, vol. 145(1), pages 78-87.
    2. Kim, Sang-Won & Bell, Peter C., 2011. "Optimal pricing and production decisions in the presence of symmetrical and asymmetrical substitution," Omega, Elsevier, vol. 39(5), pages 528-538, October.
    3. Kevin Glazebrook & Joern Meissner & Jochen Schurr, 2012. "How big should my store be? On the interplay between shelf-space, demand learning and assortment decisions," Working Papers MRG/0021, Department of Management Science, Lancaster University, revised Dec 2012.
    4. Ozer, Muammer, 2011. "Understanding the impacts of product knowledge and product type on the accuracy of intentions-based new product predictions," European Journal of Operational Research, Elsevier, vol. 211(2), pages 359-369, June.
    5. Hübner, Alexander H. & Kuhn, Heinrich, 2012. "Retail category management: State-of-the-art review of quantitative research and software applications in assortment and shelf space management," Omega, Elsevier, vol. 40(2), pages 199-209, April.
    6. Rodríguez, Betzabé & AydIn, Göker, 2011. "Assortment selection and pricing for configurable products under demand uncertainty," European Journal of Operational Research, Elsevier, vol. 210(3), pages 635-646, May.


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