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• W2885454300 abstract "We study a credit term determination problem in the context of a supplier-buyer supply chain. The supplier's credit term decision is simultaneously made with its production and inventory decisions, and most importantly, it is impacted by the buyer's order quantity. We present a new game-theoretic framework to model this problem, which captures the interaction between the supplier's credit term decision and the buyer's order decision in a multi-period setting. An exact method based on nonlinear programming is implemented to obtain the optimal solutions. We apply our methodologies on a real world case. The computational results show that our approach significantly outperforms the heuristics with fixed credit terms, and either a short or a long credit term can be sub-optimal for the supplier in profitability. Our work offers the first data-driven model and solution approach that assists purchasing and supply managers to make optimal dynamic credit term decision in conjunction with production, ordering and inventory decisions in a game-theoretic setting." @default.
• W2885454300 created "2018-08-22" @default.
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• W2885454300 date "2019-03-01" @default.
• W2885454300 modified "2023-10-17" @default.
• W2885454300 title "Optimizing the credit term decisions in supply chain finance" @default.
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• W2885454300 doi "https://doi.org/10.1016/j.pursup.2018.07.006" @default.
• W2885454300 hasPublicationYear "2019" @default.
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