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

Listed author(s):
  • 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)

Registered author(s):

    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.

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    Article provided by INFORMS in its journal Management Science.

    Volume (Year): 49 (2003)
    Issue (Month): 7 (July)
    Pages: 890-906

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    Handle: RePEc:inm:ormnsc:v:49:y:2003:i:7:p:890-906
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    1. GĂ©rard P. Cachon & Martin A. Lariviere, 1999. "Capacity Allocation Using Past Sales: When to Turn-and-Earn," Management Science, INFORMS, vol. 45(5), pages 685-703, May.
    2. Ananth. V. Iyer & Jianming Ye, 2000. "Assessing the Value of Information Sharing in a Promotional Retail Environment," Manufacturing & Service Operations Management, INFORMS, vol. 2(2), pages 128-143, February.
    3. Jing-Sheng Song, 1994. "The Effect of Leadtime Uncertainty in a Simple Stochastic Inventory Model," Management Science, INFORMS, vol. 40(5), pages 603-613, May.
    4. Varian, Hal R, 1980. "A Model of Sales," American Economic Review, American Economic Association, vol. 70(4), pages 651-659, September.
    5. Hau L. Lee & V. Padmanabhan & Seungjin Whang, 1997. "Information Distortion in a Supply Chain: The Bullwhip Effect," Management Science, INFORMS, vol. 43(4), pages 546-558, April.
    6. Frank Chen & Zvi Drezner & Jennifer K. Ryan & David Simchi-Levi, 2000. "Quantifying the Bullwhip Effect in a Simple Supply Chain: The Impact of Forecasting, Lead Times, and Information," Management Science, INFORMS, vol. 46(3), pages 436-443, March.
    7. Susan L. Albin, 1986. "Delays for Customers from Different Arrival Streams to a Queue," Management Science, INFORMS, vol. 32(3), pages 329-340, March.
    8. Narasimhan, Chakravarthi, 1988. "Competitive Promotional Strategies," The Journal of Business, University of Chicago Press, vol. 61(4), pages 427-449, October.
    9. Charles R. Sox & L. Joseph Thomas & John O. McClain, 1997. "Coordinating Production and Inventory to Improve Service," Management Science, INFORMS, vol. 43(9), pages 1189-1197, September.
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