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Product, operation, and demand relationships between manufacturers and retailers

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  • Wanke, Peter F.

Abstract

This paper presents a framework for identifying the most adequate distribution structure between manufacturing and retailers, considering different characteristics of product, operation, and demand. Based on the random generation of different scenarios, it is indicated the adequacy of direct, echeloned, and mixed distribution structures to a given set of demand uncertainty, lead time variability, holding costs, and transportation costs. Sensitivity analyses are also performed to address managerial issues, such as the mission of a Local DC and the convenience of lead time demand pooling. Findings suggest an increase of mixed distribution structures to the detriment of purely direct/echeloned ones.

Suggested Citation

  • Wanke, Peter F., 2012. "Product, operation, and demand relationships between manufacturers and retailers," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 340-354.
    • Handle: RePEc:eee:transe:v:48:y:2012:i:1:p:340-354
    DOI: 10.1016/j.tre.2011.07.010
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    References listed on IDEAS

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    1. Bharadwaj, Neeraj & Matsuno, Ken, 2006. "Investigating the antecedents and outcomes of customer firm transaction cost savings in a supply chain relationship," Journal of Business Research, Elsevier, vol. 59(1), pages 62-72, January.
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    Cited by:

    1. Wang, Wenbin & Yue, Shuai, 2015. "An inventory pooling model for spare units of critical systems that serve multi-companies," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 76(C), pages 34-44.
    2. Sternbeck, Michael G. & Kuhn, Heinrich, 2014. "An integrative approach to determine store delivery patterns in grocery retailing," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 205-224.
    3. Sadeghi, Javad & Mousavi, Seyed Mohsen & Niaki, Seyed Taghi Akhavan & Sadeghi, Saeid, 2014. "Optimizing a bi-objective inventory model of a three-echelon supply chain using a tuned hybrid bat algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 70(C), pages 274-292.

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