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Retailer’s optimal replenishment and early-payment decisions in a deteriorating items supply chain with longer downstream credit period

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Abstract

While receiving trade credit from their suppliers, many retailers are willing to provide trade credit to their customers for certain fashion goods and electronic products. Usually, customers’ delay payment term is longer than the retailer’s, which is ignored in the existing literature. In this paper, we study such deteriorating-items supply chain where the supplier offers flexible two-part trade credit allowing the retailer to pay part of purchase cost at early-payment term with discount and the rest with no discount at later-payment period; meanwhile, the retailer provides one-part trade credit allowing the customers to delay payment. We discuss the retailer’s optimal replenishment and payment decisions where downstream credit periods are not limited to less than upstream early-payment terms. Numerical examples and sensitivity analysis serve to verify theoretical results and support three critical managerial insights. First, the retailer can extend downstream delay payment terms to profit, especially for the young generation’s products. Second, when the downstream credit period is longer than the upstream early-payment term, it makes economic sense for the retailer to order items more frequently. Finally, the retailer would take more benefits from flexible two-part trade credit contracts on longer shelf-time products.

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Acknowledgements

The authors would like to thank editors and anonymous reviewers for their constructive comments, which help improve the paper significantly. This work was supported the Funds for First-class Discipline Construction (XK1802-5), China Postdoctoral Science Foundation (2021M690317), and the Fundamental Research Funds for the Central Universities (ZY2114).

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Correspondence to Yi Zhang.

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He, G., Ji, X. & Zhang, Y. Retailer’s optimal replenishment and early-payment decisions in a deteriorating items supply chain with longer downstream credit period. J Ambient Intell Human Comput 14, 16325–16335 (2023). https://doi.org/10.1007/s12652-022-03854-5

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