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Assortment selection and pricing for configurable products under demand uncertainty

Listed author(s):
  • Rodríguez, Betzabé
  • AydIn, Göker
Registered author(s):

    Consider a firm selling a configurable product (e.g., a computer), which is a combination of a required component (e.g., processor) and an optional component (e.g., a speaker). Each component's assortment allows the consumer to choose from several variants (e.g., processors with different speeds, speakers in different styles). The demands for the two components are complementary: broadening the assortment of one component, or decreasing the price of one of its variants, would increase the demand for the other component. We find that, at optimality, all variants of a component (e.g., all processors offered by the firm) share the same "effective profit margin," which is a function of not only the selling price and the unit cost, but also the unit underage and overage costs, service level, and demand variability. As for assortment selection, we show the importance of a variant's "surplus," which is the difference between the customers utility from a variant and the costs incurred by the firm for the variant (including inventory-related costs). When choosing from two variants that belong to the same component (e.g., two processors with different speeds), the firm should pick the one with the higher surplus. However, when choosing from two variants that belong to different components (e.g., a new processor versus a new speaker), the firm must rely on a measure that we call the "attraction" of a product configuration, which increases in the surpluses of variants that make up the configuration. When choosing from two variants that belong to different components, the firm must compare the total attraction of new product configurations enabled by the addition of each variant. In addition, we show that if the optional component's assortment and margin influence the customer's decision to purchase from the firm, then the optional component must bear zero effective margin.

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

    Volume (Year): 210 (2011)
    Issue (Month): 3 (May)
    Pages: 635-646

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    Handle: RePEc:eee:ejores:v:210:y:2011:i:3:p:635-646
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    1. David Besanko & Sachin Gupta & Dipak Jain, 1998. "Logit Demand Estimation Under Competitive Pricing Behavior: An Equilibrium Framework," Management Science, INFORMS, vol. 44(11-Part-1), pages 1533-1547, November.
    2. Vishal Gaur & Dorothée Honhon, 2006. "Assortment Planning and Inventory Decisions Under a Locational Choice Model," Management Science, INFORMS, vol. 52(10), pages 1528-1543, October.
    3. Gérard P. Cachon & A. Gürhan Kök, 2007. "Category Management and Coordination in Retail Assortment Planning in the Presence of Basket Shopping Consumers," Management Science, INFORMS, vol. 53(6), pages 934-951, June.
    4. Pentico, David W., 2008. "The assortment problem: A survey," European Journal of Operational Research, Elsevier, vol. 190(2), pages 295-309, October.
    5. Garrett van Ryzin & Siddharth Mahajan, 1999. "On the Relationship Between Inventory Costs and Variety Benefits in Retail Assortments," Management Science, INFORMS, vol. 45(11), pages 1496-1509, November.
    6. 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.
    7. Rajaram, Kumar, 2001. "Assortment planning in fashion retailing: methodology, application and analysis," European Journal of Operational Research, Elsevier, vol. 129(1), pages 186-208, February.
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