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On pricing of perishable assets with menu costs

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  • Berk, Emre
  • Gürler, Ülkü
  • YIldIrIm, Gonca

Abstract

We consider dynamic pricing of perishable assets in the presence of price-sensitive renewal demand processes. Unlike the existing works in the literature, we explicitly incorporate non-negligible price change costs which reflects the revenue management practice more realistically. These costs are also known as menu costs in the economic literature. The objective is to maximize the discounted expected profit for an initial inventory ofQ items by determining the selling prices dynamically. We employ a dynamic programming approach and formulate a model that captures the price-demand relationship. We establish some theoretical results on the properties of the problem at hand. Specifically, we establish the sufficient conditions under which the within-period profit is concave in the selling price and in the remaining shelf life and, furthermore, show the structure of the myopically and asymptotically optimal pricing policy. In a numerical study, we investigate the impact of various system parameters and, in particular, the existence of menu costs, on pricing decisions. We observe that ignoring menu costs may be significantly misleading for the implementation of revenue management. We also propose four implementable policy heuristics and examine their performances. Our findings support some results previously obtained in settings with continuous pricing and negligible price change costs; and, contradict some others.

Suggested Citation

  • Berk, Emre & Gürler, Ülkü & YIldIrIm, Gonca, 2009. "On pricing of perishable assets with menu costs," International Journal of Production Economics, Elsevier, vol. 121(2), pages 678-699, October.
  • Handle: RePEc:eee:proeco:v:121:y:2009:i:2:p:678-699
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    References listed on IDEAS

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    Cited by:

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    2. Bakker, Monique & Riezebos, Jan & Teunter, Ruud H., 2012. "Review of inventory systems with deterioration since 2001," European Journal of Operational Research, Elsevier, vol. 221(2), pages 275-284.
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    4. Dieudonné Tchuente & Serge Nyawa, 2022. "Real estate price estimation in French cities using geocoding and machine learning," Annals of Operations Research, Springer, vol. 308(1), pages 571-608, January.
    5. Buisman, M.E. & Haijema, R. & Bloemhof-Ruwaard, J.M., 2019. "Discounting and dynamic shelf life to reduce fresh food waste at retailers," International Journal of Production Economics, Elsevier, vol. 209(C), pages 274-284.

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