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An inventory reservation problem with nesting and fill rate-based performance measures

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  • Samii, Amir-Behzad
  • Pibernik, Richard
  • Yadav, Prashant
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    Abstract

    In many inventory settings companies wish to provide customer-differentiated service levels. These may, for example, be motivated by differences in the perceived customer lifetime value or by specific contractual agreements. One approach to provide differentiated service levels is to reserve some portion of the available inventory exclusively for specific customer classes. Existing approaches to inventory reservation are typically based on the assumption that a company can assign a customer specific revenue or penalty cost to any order or unit of demand filled or unfulfilled. In practice, however, it is usually extremely difficult to accurately estimate (especially long term) monetary implications of meeting or not meeting customer demand and corresponding service level requirements. The research presented in this paper addresses the problem of setting appropriate inventory reservations for different customer classes based on fill rate-based performance measures. We model a single period inventory reservation problem with two customer classes and nesting. We develop exact expressions for two conflicting performance measures: (1) the expected fill rate of high priority customers and (2) the expected loss in the system fill rate induced by inventory reservation. With these expressions a decision maker can analyze the tradeoff between the loss in overall system performance and the higher expected fill rates for prioritized customers. We provide analytical insights into the effects of nesting and the impact of relevant problem parameters on these two performance measures. The analytical insights are illustrated and highlighted through a set of numerical examples. Although we limit our analysis to a single period inventory reservation problem, we expect that our results can be utilized in a wide range of problem settings in which a decision maker has to ration a perishable resource among different classes of customers.

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    Bibliographic Info

    Article provided by Elsevier in its journal International Journal of Production Economics.

    Volume (Year): 133 (2011)
    Issue (Month): 1 (September)
    Pages: 393-402

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    Handle: RePEc:eee:proeco:v:133:y:2011:i:1:p:393-402

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    Web page: http://www.elsevier.com/locate/ijpe

    Related research

    Keywords: Inventory reservation Service differentiation Fill rate-based performance measures;

    References

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    1. Hasan Arslan & Stephen C. Graves & Thomas A. Roemer, 2007. "A Single-Product Inventory Model for Multiple Demand Classes," Management Science, INFORMS, vol. 53(9), pages 1486-1500, September.
    2. Steven Nahmias & W. Steven Demmy, 1981. "Operating Characteristics of an Inventory System with Rationing," Management Science, INFORMS, vol. 27(11), pages 1236-1245, November.
    3. Francis de VĂ©ricourt & Fikri Karaesmen & Yves Dallery, 2002. "Optimal Stock Allocation for a Capacitated Supply System," Management Science, INFORMS, vol. 48(11), pages 1486-1501, November.
    4. Alan Kaplan, 1969. "Stock Rationing," Management Science, INFORMS, vol. 15(5), pages 260-267, January.
    5. Richard V. Evans, 1968. "Sales and Restocking Policies in a Single Item Inventory System," Management Science, INFORMS, vol. 14(7), pages 463-472, March.
    6. Albert Y. Ha, 1997. "Inventory Rationing in a Make-to-Stock Production System with Several Demand Classes and Lost Sales," Management Science, INFORMS, vol. 43(8), pages 1093-1103, August.
    7. Vinayak Deshpande & Morris A. Cohen & Karen Donohue, 2003. "A Threshold Inventory Rationing Policy for Service-Differentiated Demand Classes," Management Science, INFORMS, vol. 49(6), pages 683-703, June.
    8. Eric T. Anderson & Gavan J. Fitzsimons & Duncan Simester, 2006. "Measuring and Mitigating the Costs of Stockouts," Management Science, INFORMS, vol. 52(11), pages 1751-1763, November.
    9. Donald M. Topkis, 1968. "Optimal Ordering and Rationing Policies in a Nonstationary Dynamic Inventory Model with n Demand Classes," Management Science, INFORMS, vol. 15(3), pages 160-176, November.
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