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The Logistics Impact of a Mixture of Order-Streams in a Manufacturer-Retailer System

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  • Ananth V. Iyer

    (Krannert Graduate School of Management, 1310 Krannert Building, Purdue University, West Lafayette, Indiana 47907-1310)

  • Apurva Jain

    (University of Washington Business School, Box 353200, Seattle, Washington 98195-3200)

Abstract

We model a supply chain with two retail warehouses that place replenishment orders with a common manufacturing capacity. The two retailers differ in the variability of their order-streams. The order-stream from one retail warehouse is modeled as a Poisson process and from the other as a hyperexponential renewal process. Each retail warehouse uses a base-stock policy to place replenishment orders with the manufacturer. The manufacturer is modeled as a first-come-first-serve, single exponential server queue. We analyze the supply-side impact of this mixture of order-streams received by the manufacturer on both retailers. An exact analysis of this base-model generates closed-form expressions for distributions of the lead-time, outstanding orders, and expected inventory costs for each retailer, and leads to comparative results about the two retailers- performance measures. The base-model is extended to accommodate finished goods at the manufacturer, more than two retailers, and bulk-arrivals. We use the model to suggest managerial insights about the impact of the presence of a high-variability retailer on other retailers who share capacity, the distorting impact of manufacturer finished goods inventory on retailer incentives, and the incentives for retailers to participate in variability-reduction programs in the grocery industry.

Suggested Citation

  • Ananth V. Iyer & Apurva Jain, 2003. "The Logistics Impact of a Mixture of Order-Streams in a Manufacturer-Retailer System," Management Science, INFORMS, vol. 49(7), pages 890-906, July.
    • Handle: RePEc:inm:ormnsc:v:49:y:2003:i:7:p:890-906
    DOI: 10.1287/mnsc.49.7.890.16378
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    References listed on IDEAS

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    Cited by:

    1. Cheung, Ki Ling & Song, Jing-Sheng & Zhang, Yue, 2017. "Cost reduction through operations reversal," European Journal of Operational Research, Elsevier, vol. 259(1), pages 100-112.
    2. Zhu, Wanshan & Wu, Zhengping, 2014. "The stochastic ordering of mean-preserving transformations and its applications," European Journal of Operational Research, Elsevier, vol. 239(3), pages 802-809.
    3. Jing-Sheng Song & Hanqin Zhang & Yumei Hou & Mingzheng Wang, 2010. "The Effect of Lead Time and Demand Uncertainties in ( r, q ) Inventory Systems," Operations Research, INFORMS, vol. 58(1), pages 68-80, February.
    4. Ananth V. Iyer & Apurva Jain, 2004. "Modeling the Impact of Merging Capacity in Production-Inventory Systems," Management Science, INFORMS, vol. 50(8), pages 1082-1094, August.
    5. Sanajian, Nima & BalcIog[small tilde]lu, BarIs, 2009. "The impact of production time variability on make-to-stock queue performance," European Journal of Operational Research, Elsevier, vol. 194(3), pages 847-855, May.
    6. V. Daniel R. Guide , Jr. & Gilvan C. Souza & Luk N. Van Wassenhove & Joseph D. Blackburn, 2006. "Time Value of Commercial Product Returns," Management Science, INFORMS, vol. 52(8), pages 1200-1214, August.
    7. Jain, Apurva, 2007. "Value of capacity pooling in supply chains with heterogeneous customers," European Journal of Operational Research, Elsevier, vol. 177(1), pages 239-260, February.
    8. N Sanajian & H Abouee-Mehrizi & B Balcıog̃lu, 2010. "Scheduling policies in the M/G/1 make-to-stock queue," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(1), pages 115-123, January.

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