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Inventory Allocation in the Presence of Service†Level Agreements

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  • Chun†Miin (Jimmy) Chen
  • Douglas J. Thomas

Abstract

Retailers often use service†level agreements (SLAs) to evaluate their supplier's performance. Based on an examination of 70 SLAs from practice, we conclude that in terms of evaluating fill rate, these SLAs vary in at least three key dimensions: (i) Supplier performance can be evaluated for each demand request or over some longer horizon, (ii) the acceptable fill rate can be 100% or something less than 100%, and (iii) the non†compliance charge can be a flat fee, a per†unit†short fee, or both. For a supplier operating a periodic†review inventory system and serving multiple retailers, each with an SLA, we investigate the impact of inventory allocation rules on SLA compliance and expected non†compliance costs across the three dimensions of review horizon, fill rate target and non†compliance cost structure. We derive several analytic results when retailers are symmetric. For the single†period setting and a fill rate target of 100%, we characterize the optimal allocation rule and rank other rules common in practice and the literature. We also characterize the optimal rule for the single†period setting when the fill rate target is less than 100% and the SLA specifies a flat†fee non†compliance charge. In the multiple†period case, we characterize the optimal rule when the fill rate target is 100%. When the fill rate target is less than 100% and the performance review horizon is more than one period, we develop a simple heuristic that outperforms common allocation rules.

Suggested Citation

  • Chun†Miin (Jimmy) Chen & Douglas J. Thomas, 2018. "Inventory Allocation in the Presence of Service†Level Agreements," Production and Operations Management, Production and Operations Management Society, vol. 27(3), pages 553-577, March.
  • Handle: RePEc:bla:popmgt:v:27:y:2018:i:3:p:553-577
    DOI: 10.1111/poms.12814
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    Cited by:

    1. Eirini Spiliotopoulou & Karen Donohue & Mustafa Çagri Gürbüz, 2022. "Ordering Behavior and the Impact of Allocation Mechanisms in an Integrated Distribution System," Production and Operations Management, Production and Operations Management Society, vol. 31(2), pages 422-441, February.
    2. Ghamat, Salar & Pun, Hubert, 2023. "The impact of capacity information on lexicographical capacity allocation," European Journal of Operational Research, Elsevier, vol. 308(2), pages 636-649.
    3. Mónica López-Campos & Pablo Escalona & Alejandro Angulo & Francisca Recabarren & Raúl Stegmaier, 2024. "On the Number of Customer Classes in a Single-Period Inventory System," Mathematics, MDPI, vol. 12(10), pages 1-22, May.
    4. Xufeng Yang & Juliang Zhang & Wen Jiao & Hong Yan, 2023. "Optimal Capacity Rationing Policy for a Container Leasing System with Multiple Kinds of Customers and Substitutable Containers," Management Science, INFORMS, vol. 69(3), pages 1468-1485, March.
    5. Masih Fadaki & Babak Abbasi & Prem Chhetri, 2022. "Quantum game approach for capacity allocation decisions under strategic reasoning," Computational Management Science, Springer, vol. 19(3), pages 491-512, July.
    6. Gary E. Bolton & Sabrina Bonzelet & Tobias Stangl & Ulrich W. Thonemann, 2023. "Decision making under service‐level contracts: The role of cost saliency," Production and Operations Management, Production and Operations Management Society, vol. 32(4), pages 1243-1261, April.
    7. Kim, Nayeon & Montreuil, Benoit & Klibi, Walid, 2022. "Inventory availability commitment under uncertainty in a dropshipping supply chain," European Journal of Operational Research, Elsevier, vol. 302(3), pages 1155-1174.
    8. Saldanha, John P., 2022. "Estimating the reorder point for a fill-rate target under a continuous review policy in the presence of non-standard lead-time demand distributions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    9. Fadaki, Masih & Asadikia, Atie, 2024. "Augmenting Monte Carlo Tree Search for managing service level agreements," International Journal of Production Economics, Elsevier, vol. 271(C).

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