A robust ordering strategy for retailers facing a free shipping option

Free shipping with conditions has become one of the most effective marketing tools available. An increasing number of companies, especially e-businesses, prefer to offer free shipping with some predetermined condition, such as a minimum purchase amount by the customer. However, in practice, the dema...

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Bibliographic Details
Published in:PloS one 2015-05, Vol.10 (5), p.e0125939-e0125939
Main Authors: Meng, Qing-chun, Wan, Xiao-le, Rong, Xiao-xia
Format: Article
Language:English
Subjects:
Commerce
Computer applications
Cost control
Costs and Cost Analysis
Electronic commerce
Experiments
Fees & charges
Game theory
Inventory
Linear programming
Operations management
Optimization
Researchers
Retail stores
Retail trade
Robustness (mathematics)
Shipping
Stochasticity
Studies
Suppliers
Transportation - economics
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Summary:Free shipping with conditions has become one of the most effective marketing tools available. An increasing number of companies, especially e-businesses, prefer to offer free shipping with some predetermined condition, such as a minimum purchase amount by the customer. However, in practice, the demands of buyers are uncertain; they are often affected by many factors, such as the weather and season. We begin by modeling the centralized ordering problem in which the supplier offers a free shipping service and retailers face stochastic demands. As these random data are considered, only partial information such as the known mean, support, and deviation is needed. The model is then analyzed via a robust optimization method, and the two types of equivalent sets of uncertainty constraints that are obtained provide good mathematical properties with consideration of the robustness of solutions. Subsequently, a numerical example is used to compare the results achieved from a robust optimization method and the linear decision rules. Additionally, the robustness of the optimal solution is discussed, as it is affected by the minimum quantity parameters. The increasing cost-threshold relationship is divided into three periods. In addition, the case study shows that the proposed method achieves better stability as well as computational complexity.
ISSN:1932-6203
1932-6203
DOI:10.1371/journal.pone.0125939