No abstract

Faced with economic recession, firms struggle to find ways to stay competitive and maintain market share. Effective coordination of the supply chain can solve this problem, but this may fail if existing capital constraints and financial flows are ignored. This study addresses the challenge by exploiting coordination through joint decision-making on the physical and financial flows of a capital-constrained supply chain. We also consider the capital-constrained member’s financing limitations that lead to lost sales. Two scenarios based on non-coordinated and coordinated structures are modeled in the form of bi-objective optimization problems that simultaneously optimize system costs and service levels. The models are solved using the $$\varepsilon$$ ε -constraint method. The results indicate that the non-coordinated model cannot satisfy more than about 50% of the demand due to capital shortage and financing limitations, while the coordinated model can satisfy all of the demand via internal financing. Furthermore, the proposed coordination scheme leads to cost reduction for the members and the total system. To motivate all members to accept the proposed coordination scheme, a cost-sharing mechanism is applied to the coordination procedure. Finally, a sensitivity analysis concerning financial parameters is provided for validating the coordination model.

This study is designed to solve supply chain inefficiencies caused by some members' financial problems, such as capital shortages and financing restrictions in a stochastic environment. To this end, we have established a supply chain finance framework by designing two novel coordinating contracts based on trade credit financing for different problem settings. These contracts are modeled in the form of multi-leader Stackelberg games that address horizontal and vertical competition in a supply chain consisting of multiple suppliers and a financially constrained manufacturer. However, previous studies in the trade credit literature have addressed only simple vertical competition, that is, seller-buyer competition. To solve the proposed models, two algorithms were developed by combining population-based metaheuristics, the Nash-domination concept, and the Nikaido-Isoda function. The results demonstrate that the proposed supply chain finance framework can eliminate supply chain inefficiencies and make a large profit for suppliers, as well as the financially constrained manufacturer. Furthermore, the results of the contracts’ analysis showed that if the manufacturer is required to settle its payments to suppliers before the end of the period, the trade credit contract cannot coordinate the supply chain because of a lack of incentive for suppliers. However, if the manufacturer is allowed to extend its payments to the end of the period, the proposed trade credit financing contract can coordinate the supply chain. Finally, the sensitivity analysis results indicate that the worse the financial status of the manufacturer, the more bargaining power suppliers have in determining the contract parameters for more profit.