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A partial-postponement decision cost model

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  • Graman, Gregory A.

Abstract

A number of factors, including product proliferation and increased customer service-level requirements, have led many companies to consider adopting postponement as a supply chain strategy. Packaging postponement is the process of delaying packaging of a common item into a final product configuration until the customer order is received. For a given product, a portion of demand is known with a high level of certainty and would not benefit from postponement. The remaining portion of demand is known with little certainty and would benefit from delaying the differentiating stage of the operation until demand is known. We develop a single-period, two-product, order-up-to cost model to aid in setting the levels of finished-goods inventory and postponement capacity. Minimum-cost optimal solutions to inventory levels and capacity are obtained by solving the derived analytical expressions using a non-linear programming formulation. We examine the sensitivity of the model to different levels of the model parameters to generate managerial insights beyond those of previous work. We show that changing product value, packaging cost, cost of postponement, holding cost, fill rate, and demand correlation can decrease expected total cost and increase postponement capacity.

Suggested Citation

  • Graman, Gregory A., 2010. "A partial-postponement decision cost model," European Journal of Operational Research, Elsevier, vol. 201(1), pages 34-44, February.
  • Handle: RePEc:eee:ejores:v:201:y:2010:i:1:p:34-44
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    References listed on IDEAS

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    Cited by:

    1. Fu, Qi & Lee, Chung-Yee & Teo, Chung-Piaw, 2012. "Modified critical fractile approach for a class of partial postponement problems," International Journal of Production Economics, Elsevier, vol. 136(1), pages 185-193.
    2. Fernandes, Rui & Gouveia, Borges & Pinho, Carlos, 2010. "Modeling Overstock," MPRA Paper 25126, University Library of Munich, Germany.
    3. Weskamp, Christoph & Koberstein, Achim & Schwartz, Frank & Suhl, Leena & Voß, Stefan, 2019. "A two-stage stochastic programming approach for identifying optimal postponement strategies in supply chains with uncertain demand," Omega, Elsevier, vol. 83(C), pages 123-138.
    4. 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.
    5. Afshin Mansouri, S. & Gallear, David & Askariazad, Mohammad H., 2012. "Decision support for build-to-order supply chain management through multiobjective optimization," International Journal of Production Economics, Elsevier, vol. 135(1), pages 24-36.
    6. Slim Zidi & Nadia Hamani & Lyes Kermad, 2022. "New metrics for measuring supply chain reconfigurability," Journal of Intelligent Manufacturing, Springer, vol. 33(8), pages 2371-2392, December.

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