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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

Abstract

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.

Suggested Citation

  • Yücel, Eda & Karaesmen, Fikri & Salman, F. Sibel & Türkay, Metin, 2009. "Optimizing product assortment under customer-driven demand substitution," European Journal of Operational Research, Elsevier, vol. 199(3), pages 759-768, December.
    • Handle: RePEc:eee:ejores:v:199:y:2009:i:3:p:759-768
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    References listed on IDEAS

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    Cited by:

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    6. 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.
    7. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    8. 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.
    9. Uzma Mushtaque & Jennifer A. Pazour, 2022. "Assortment optimization under cardinality effects and novelty for unequal profit margin items," Journal of Revenue and Pricing Management, Palgrave Macmillan, vol. 21(1), pages 106-126, February.
    10. Hübner, Alexander & Schaal, Kai, 2017. "A shelf-space optimization model when demand is stochastic and space-elastic," Omega, Elsevier, vol. 68(C), pages 139-154.
    11. Çömez-Dolgan, Nagihan & Fescioglu-Unver, Nilgun & Cephe, Ecem & Şen, Alper, 2021. "Capacitated strategic assortment planning under explicit demand substitution," European Journal of Operational Research, Elsevier, vol. 294(3), pages 1120-1138.
    12. Çömez-Dolgan, Nagihan & Moussawi-Haidar, Lama & Jaber, Mohamad Y. & Cephe, Ecem, 2022. "Capacitated assortment planning of a multi-location system under transshipments," International Journal of Production Economics, Elsevier, vol. 251(C).
    13. 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.
    14. 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.
    15. Morimura, Fumikazu & Sakagawa, Yuji, 2023. "The intermediating role of big data analytics capability between responsive and proactive market orientations and firm performance in the retail industry," Journal of Retailing and Consumer Services, Elsevier, vol. 71(C).
    16. Shin, Hojung & Park, Soohoon & Lee, Euncheol & Benton, W.C., 2015. "A classification of the literature on the planning of substitutable products," European Journal of Operational Research, Elsevier, vol. 246(3), pages 686-699.
    17. 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.
    18. Ghoniem, Ahmed & Maddah, Bacel, 2015. "Integrated retail decisions with multiple selling periods and customer segments: Optimization and insights," Omega, Elsevier, vol. 55(C), pages 38-52.
    19. Çömez-Dolgan, Nagihan & Dağ, Hilal & Fescioglu-Unver, Nilgun & Şen, Alper, 2023. "Multi-plant manufacturing assortment planning in the presence of transshipments," European Journal of Operational Research, Elsevier, vol. 310(3), pages 1033-1050.
    20. Menezes, Mozart B.C. & Pinto, Roberto, 2022. "Product proliferation, cannibalisation, and substitution: A first look into entailed risk and complexity," International Journal of Production Economics, Elsevier, vol. 243(C).
    21. Refael Hassin & Justo Puerto, 2024. "Pricing heterogeneous products to heterogeneous customers who buy sequentially," Annals of Operations Research, Springer, vol. 340(2), pages 863-890, September.
    22. Malinowski, Ethan & Karwan, Mark H. & Sun, Lei, 2021. "Customer selection and incentivization for SKU rationalization in a packaged gas supply chain," International Journal of Production Economics, Elsevier, vol. 234(C).
    23. Hübner, Alexander & Schaal, Kai, 2017. "An integrated assortment and shelf-space optimization model with demand substitution and space-elasticity effects," European Journal of Operational Research, Elsevier, vol. 261(1), pages 302-316.

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