Trade credit or credit insurance? A green supply chain finance design scheme with multi-objective programming.

This article focuses on designing a green supply chain finance (GSCF) system that integrates environmental concerns into classical supply chain finance by considering financing from both banks (credit insurance financing, CIF) and consumers (trade credit financing, TCF). It proposes a bi-objective integer programming model to optimize the trade-off between total cost—including production, financing, and environmental investment—and carbon emissions, solved via an improved normalized normal constraint (INNC) method to generate Pareto optimal solutions. A numerical case study of a Taiwanese steel group demonstrates the model’s effectiveness in providing decision support for financing strategies and environmental investment levels under various parameters, including technological ratios, emission regulations, and interest rates. Sensitivity analyses reveal that higher trade credit costs discourage environmental investment and increase emissions, while financing cost reductions better support capital-constrained small and medium-sized enterprises in achieving emission reductions. The study highlights the potential of GSCF to balance economic and environmental objectives but notes limitations such as strong modeling assumptions and suggests future work to incorporate carbon trading mechanisms and develop enhanced solution methods.