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Echelon Reorder Points, Installation Reorder Points, and the Value of Centralized Demand Information

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  • Fangruo Chen

    (Graduate School of Business, Columbia University, New York, New York 10027)

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    Abstract

    We consider a serial inventory system with N stages. The material flows from an outside supplier to stage N, then to stage N - 1, etc., and finally to stage 1 where random customer demand arises. Each stage replenishes a stage-specific inventory position according to a stage-specific reorder point/order quantity policy. Two variations of this policy are considered. One is based on echelon stock, and the other installation stock. The former requires centralized demand information, while the latter does not. The relative cost difference between the two policies is called the value of centralized demand information. For fixed order quantities, we develop efficient algorithms for computing both the optimal echelon reorder points and the optimal installation reorder points. These algorithms enable us to conduct an extensive computational study to assess the value of centralized demand information and to understand how this value depends on several key system parameters, i.e., the number of stages, leadtimes, batch sizes, demand variability, and the desired level of customer service.

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    File URL: http://dx.doi.org/10.1287/mnsc.44.12.S221
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    Bibliographic Info

    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 44 (1998)
    Issue (Month): 12-Part-2 (December)
    Pages: S221-S234

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    Handle: RePEc:inm:ormnsc:v:44:y:1998:i:12-part-2:p:s221-s234

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    Related research

    Keywords: Supply Chain Management; Stochastic Demand; Batch Ordering; Centralized Information; Electronic Data Interchange;

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    Cited by:
    1. E. Vanpoucke & K. Boyer & A. Vereecke, 2009. "Supply Chain Information Flow Strategies: an empirical taxonomy," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 09/567, Ghent University, Faculty of Economics and Business Administration.
    2. Zhu, Xiaowei & Mukhopadhyay, Samar K. & Yue, Xiaohang, 2011. "Role of forecast effort on supply chain profitability under various information sharing scenarios," International Journal of Production Economics, Elsevier, vol. 129(2), pages 284-291, February.
    3. Fu, Yonghui & Piplani, Rajesh, 2004. "Supply-side collaboration and its value in supply chains," European Journal of Operational Research, Elsevier, vol. 152(1), pages 281-288, January.
    4. Li, Xiaoming, 2010. "Optimal inventory policies in decentralized supply chains," International Journal of Production Economics, Elsevier, vol. 128(1), pages 303-309, November.
    5. Glenn, David & Bisi, Arnab & Puterman, Martin L., 2004. "The Bayesian Newsvendors in Supply Chains with Unobserved Lost Sales," Working Papers 04-0110, University of Illinois at Urbana-Champaign, College of Business.
    6. Chao, Gary H., 2013. "Production and availability policies through the Markov Decision Process and myopic methods for contractual and selective orders," European Journal of Operational Research, Elsevier, vol. 225(3), pages 383-392.
    7. Axsäter, Sven & Viswanathan, S., 2012. "On the value of customer information for an independent supplier in a continuous review inventory system," European Journal of Operational Research, Elsevier, vol. 221(2), pages 340-347.
    8. Qi, Xiangtong & Bard, Jonathan F. & Yu, Gang, 2004. "Supply chain coordination with demand disruptions," Omega, Elsevier, vol. 32(4), pages 301-312, August.
    9. Ryu, Seung-Jin & Tsukishima, Takahiro & Onari, Hisashi, 2009. "A study on evaluation of demand information-sharing methods in supply chain," International Journal of Production Economics, Elsevier, vol. 120(1), pages 162-175, July.
    10. Forgionne, Guisseppi & Guo, Zhiling, 2009. "Internal supply chain coordination in the electric utility industry," European Journal of Operational Research, Elsevier, vol. 196(2), pages 619-627, July.
    11. Son, Joong Y. & Sheu, Chwen, 2008. "The impact of replenishment policy deviations in a decentralized supply chain," International Journal of Production Economics, Elsevier, vol. 113(2), pages 785-804, June.
    12. Mohtadi, Hamid, 2005. "The Empirics of Information Sharing in Supply Chains: The Case of the Food Industry," Working Papers 14323, University of Minnesota, The Food Industry Center.
    13. Shamir, Noam, 2012. "Strategic information sharing between competing retailers in a supply chain with endogenous wholesale price," International Journal of Production Economics, Elsevier, vol. 136(2), pages 352-365.

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