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Managing inventory systems of slow-moving items

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  • Hahn, G.J.
  • Leucht, A.

Abstract

Slow-moving demand patterns frequently occur with spare parts as well as items in decentralized retail supply chains with large assortments. These patterns are commonly called lumpy since they exhibit comparably high demand variation and a high fraction of zero-demand events. In this paper, we examine two distribution-based approaches to model lumpy demand processes for inventory control: (i) a generalized hurdle negative binomial model, and (ii) a worst-case non-parametric model that is derived using a test-based approach. Considering a base stock inventory policy, we examine a set of lumpy time series from the industry to exemplify the suitability and benefit of the proposed approaches for managing inventory systems of slow-moving items.

Suggested Citation

  • Hahn, G.J. & Leucht, A., 2015. "Managing inventory systems of slow-moving items," International Journal of Production Economics, Elsevier, vol. 170(PB), pages 543-550.
    • Handle: RePEc:eee:proeco:v:170:y:2015:i:pb:p:543-550
    DOI: 10.1016/j.ijpe.2015.08.014
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    References listed on IDEAS

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    Cited by:

    1. Rezaei Somarin, Aghil & Chen, Songlin & Asian, Sobhan & Wang, David Z.W., 2017. "A heuristic stock allocation rule for repairable service parts," International Journal of Production Economics, Elsevier, vol. 184(C), pages 131-140.
    2. Mou, Shandong & Robb, David J. & DeHoratius, Nicole, 2018. "Retail store operations: Literature review and research directions," European Journal of Operational Research, Elsevier, vol. 265(2), pages 399-422.
    3. Costantino, Francesco & Di Gravio, Giulio & Patriarca, Riccardo & Petrella, Lea, 2018. "Spare parts management for irregular demand items," Omega, Elsevier, vol. 81(C), pages 57-66.

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