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Optimal two-period inventory allocation under multiple service level contracts

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  • Protopappa-Sieke, Margarita
  • Sieke, Marcel A.
  • Thonemann, Ulrich W.

Abstract

Optimal inventory allocation policies have a significant impact on profits in the retail industry. A manufacturer ships products to the retailers’ stores where the end customers buy the product during the selling season. It has been put forward that it is beneficial for the manufacturer to reserve a certain fraction of the inventory for a second replenishment. Then the manufacturer can replenish the retailers’ inventories optimally and can take advantage of the risk pooling effect. In practice, retailers require a certain availability of the product throughout the selling season. Supply contracts are used to coordinate the delivery of products. Under such a contract, the manufacturer agrees to achieve a certain service level and to pay a financial penalty if she misses it. We analyze how a manufacturer responds to a service level contract if she wants to minimize her expected costs. We develop an allocation strategy for the multiple retailer case and find that our results allow for a better understanding of the effect of service level contracts on manufacturers and retailers.

Suggested Citation

  • Protopappa-Sieke, Margarita & Sieke, Marcel A. & Thonemann, Ulrich W., 2016. "Optimal two-period inventory allocation under multiple service level contracts," European Journal of Operational Research, Elsevier, vol. 252(1), pages 145-155.
    • Handle: RePEc:eee:ejores:v:252:y:2016:i:1:p:145-155
    DOI: 10.1016/j.ejor.2016.01.013
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    References listed on IDEAS

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    Cited by:

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    2. Qiuxiang Li & Xingli Chen & Yimin Huang & Huangbao Gui & Shengyang Liu, 2019. "The Impacts of Green Innovation Input and Channel Service in a Dual-Channel Value Chain," IJERPH, MDPI, vol. 16(22), pages 1-26, November.
    3. Güllü, Refik & Erkip, Nesim, 2024. "Risk pooling under demand and price uncertainty," European Journal of Operational Research, Elsevier, vol. 315(1), pages 120-129.
    4. Abbasi, B. & Hosseinifard, Z. & Alamri, O. & Thomas, D. & Minas, J.P., 2018. "Finite time horizon fill rate analysis for multiple customer cases," Omega, Elsevier, vol. 76(C), pages 1-17.
    5. Raul Oltra-Badenes & Hermenegildo Gil-Gomez & Jose M Merigo & Daniel Palacios-Marques, 2019. "Methodology and model-based DSS to managing the reallocation of inventory to orders in LHP situations. Application to the ceramics sector," PLOS ONE, Public Library of Science, vol. 14(7), pages 1-19, July.
    6. Junhai Ma & Weiya Di & Hao Ren, 2017. "Complexity Dynamic Character Analysis of Retailers Based on the Share of Stochastic Demand and Service," Complexity, Hindawi, vol. 2017, pages 1-12, September.

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