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On the interaction between retailers inventory policies and manufacturer trade deals in response to supply-uncertainty occurrences

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  • F. Arcelus
  • T. Pakkala
  • G. Srinivasan

Abstract

This paper models a retailer’s response to temporary manufacturer’s trade deals characterized by a time interval of random length and of uncertain duration. Uncertainty is handled primarily through the establishment of a reordering point, which serves as a trigger mechanism for new special orders. The timing at which this point is activated becomes another decision variable to be determined optimally. The model generates relatively easy-to-implement ordering policies, applicable to any probability distribution. Copyright Springer Science + Business Media, Inc. 2006

Suggested Citation

  • F. Arcelus & T. Pakkala & G. Srinivasan, 2006. "On the interaction between retailers inventory policies and manufacturer trade deals in response to supply-uncertainty occurrences," Annals of Operations Research, Springer, vol. 143(1), pages 45-58, March.
    • Handle: RePEc:spr:annopr:v:143:y:2006:i:1:p:45-58:10.1007/s10479-006-7371-4
    DOI: 10.1007/s10479-006-7371-4
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    References listed on IDEAS

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    1. Ülkü Gürler & Mahmut Parlar, 1997. "An Inventory Problem with Two Randomly Available Suppliers," Operations Research, INFORMS, vol. 45(6), pages 904-918, December.
    2. Gullu, Refik & Onol, Ebru & Erkip, Nesim, 1999. "Analysis of an inventory system under supply uncertainty," International Journal of Production Economics, Elsevier, vol. 59(1-3), pages 377-385, March.
    3. Mahmut Parlar, 2000. "Probabilistic Analysis of Renewal Cycles: An Application to a Non-Markovian Inventory Problem with Multiple Objectives," Operations Research, INFORMS, vol. 48(2), pages 243-255, April.
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    Citations

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    Cited by:

    1. Shib Sana, 2015. "An EOQ model for stochastic demand for limited capacity of own warehouse," Annals of Operations Research, Springer, vol. 233(1), pages 383-399, October.
    2. E. Borgonovo & L. Peccati, 2010. "Moment calculations for piecewise-defined functions: an application to stochastic optimization with coherent risk measures," Annals of Operations Research, Springer, vol. 176(1), pages 235-258, April.
    3. Suresha Kharvi & T. P. M. Pakkala & G. Srinivasan, 2019. "Ordering policies under currency risk sharing agreements: a Markov chain approach," OPSEARCH, Springer;Operational Research Society of India, vol. 56(3), pages 945-964, September.
    4. Arpita Roy & Shib Sankar Sana & Kripasindhu Chaudhuri, 2018. "Optimal Pricing of competing retailers under uncertain demand-a two layer supply chain model," Annals of Operations Research, Springer, vol. 260(1), pages 481-500, January.
    5. Marcos Singer & Patricio Donoso & Garo Konstantinidis, 2009. "Who wants to break the hockey-stick sales pattern in the supply chain?," Annals of Operations Research, Springer, vol. 169(1), pages 131-147, July.
    6. Sujit De & Shib Sana, 2015. "Backlogging EOQ model for promotional effort and selling price sensitive demand- an intuitionistic fuzzy approach," Annals of Operations Research, Springer, vol. 233(1), pages 57-76, October.
    7. Jiarong Luo & Xu Chen, 2017. "Risk hedging via option contracts in a random yield supply chain," Annals of Operations Research, Springer, vol. 257(1), pages 697-719, October.

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