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A queueing model of delayed product differentiation

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  • Jewkes, Elizabeth M.
  • Alfa, Attahiru S.

Abstract

We consider a production system in which a supplier produces semi-finished items on a make-to-stock basis for a manufacturer that will customize the items on a make-to-order basis. The proportion of total processing time undertaken by the supplier determines how suitable the semi-finished items will be to meet customer demand. The manufacturer wishes to determine the optimal point of differentiation (the proportion of processing completed by the supplier) and its optimal semi-finished goods buffer size. We use matrix geometric methods to evaluate various performance measures for this system, and then, with enumeration techniques, obtain optimal solutions. We find that delayed product differentiation is attractive when the manufacturer can balance the costs of customer order fulfillment delay with the costs associated with unsuitable items.

Suggested Citation

  • Jewkes, Elizabeth M. & Alfa, Attahiru S., 2009. "A queueing model of delayed product differentiation," European Journal of Operational Research, Elsevier, vol. 199(3), pages 734-743, December.
    • Handle: RePEc:eee:ejores:v:199:y:2009:i:3:p:734-743
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    References listed on IDEAS

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    1. Yossi Aviv & Awi Federgruen, 2001. "Design for Postponement: A Comprehensive Characterization of Its Benefits Under Unknown Demand Distributions," Operations Research, INFORMS, vol. 49(4), pages 578-598, August.
    2. Hau L. Lee, 1996. "Effective Inventory and Service Management Through Product and Process Redesign," Operations Research, INFORMS, vol. 44(1), pages 151-159, February.
    3. Yossi Aviv & Awi Federgruen, 2001. "Capacitated Multi-Item Inventory Systems with Random and Seasonally Fluctuating Demands: Implications for Postponement Strategies," Management Science, INFORMS, vol. 47(4), pages 512-531, April.
    4. Hau L. Lee & Christopher S. Tang, 1997. "Modelling the Costs and Benefits of Delayed Product Differentiation," Management Science, INFORMS, vol. 43(1), pages 40-53, January.
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    Cited by:

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    2. Kim, Hyunjung & Kim, Eungab, 2022. "A hybrid manufacturing system with demand for intermediate goods and controllable make-to-stock production rate," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1244-1257.
    3. Latifa Benhamou & Pierre Féniès & Vincent Giard, 2020. "Avantages Potentiels Du Reverse Blending Sur La Chaine Logistique De L'Industrie Des Engrais," Post-Print hal-03005688, HAL.
    4. Ngniatedema, Thomas & Fono, Louis Aimé & Mbondo, Georges Dieudonné, 2015. "A delayed product customization cost model with supplier delivery performance," European Journal of Operational Research, Elsevier, vol. 243(1), pages 109-119.
    5. Zhiming Shi & Yisong Li & Gábor Bohács & Qiang Zhou, 2022. "A Study on Optimal Location Selection and Semi-Finished Product Inventory Allocation in the Steel Industry," Sustainability, MDPI, vol. 14(22), pages 1-21, November.
    6. Wu, Jun & Du, Gang & Jiao, Roger J., 2021. "Optimal postponement contracting decisions in crowdsourced manufacturing: A three-level game-theoretic model for product family architecting considering subcontracting," European Journal of Operational Research, Elsevier, vol. 291(2), pages 722-737.

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