Optimal trade credit and replenishment policies for supply chain network design. (December 2018)

• Record Type: Journal Article
• Authors: Zhong, Yuanguang; Shu, Jia; Xie, Wei; Zhou, Yong-Wu
• Is Part Of: Omega. Volume 81(2018)
• Page Start: 26
• Page End: 37
• Publication Date: 2018-12
• Subjects: Supply chain management -- Trade credit -- Column generation -- OWMR model; Management -- Periodicals; 658.4005
• DOI: 10.1016/j.omega.2017.09.006
• Languages: English
• ISSNs: 0305-0483

Abstract

Highlights: We propose an integrated supply chain network design model that incorporates payment time. We make first attempt to minimize the system-wise location, transportation, multi-echelon inventory, and financing costs. The impacts of deferred payment time on the associated decisions are examined analytically and numerically. Abstract: Classical supply chain models usually overlook the impact of financial factors on the overall supply chain performance. In practice, however, it has been demonstrated that financial flow, as one of the three major flows, significantly affects the operational decisions. When it is difficult to obtain funds from the financial institutes, trade credit is frequently adopted as an important financial tool that affects the firm's ordering behavior. In this paper, with the consideration of trade credit, we propose an integrated supply chain network design model that simultaneously determines the location of warehouses, the assignments of retailers to warehouses, the policy of warehouse-retailer inventory management, and the deferred payment time allowed by the warehouses for each retailer to minimize the system-wise location, transportation, multi-echelon inventory, and financing costs. The impacts of trade credit on warehouse locations and warehouse-retailer assignments are examined analytically and numerically. Through numerical studies, we show that the optimal network will be more consolidated with higher financing costs and significant cost reduction can be achieved by considering financial decisions at the strategic supply chain design stage.