{"ID":2875163,"CreatedAt":"2026-06-01T04:54:23.091178241Z","UpdatedAt":"2026-06-01T04:54:23.091178241Z","DeletedAt":null,"paper_url":"https://arxiv.org/abs/2509.03673","arxiv_id":"2509.03673","title":"A Machine Learning-Based Study on the Synergistic Optimization of Supply Chain Management and Financial Supply Chains from an Economic Perspective","abstract":"Based on economic theories and integrated with machine learning technology, this study explores a collaborative Supply Chain Management and Financial Supply Chain Management (SCM - FSCM) model to solve issues like efficiency loss, financing constraints, and risk transmission. We combine Transaction Cost and Information Asymmetry theories and use algorithms such as random forests to process multi-dimensional data and build a data-driven, three-dimensional (cost-efficiency-risk) analysis framework. We then apply an FSCM model of \"core enterprise credit empowerment plus dynamic pledge financing.\" We use Long Short-Term Memory (LSTM) networks for demand forecasting and clustering/regression algorithms for benefit allocation. The study also combines Game Theory and reinforcement learning to optimize the inventory-procurement mechanism and uses eXtreme Gradient Boosting (XGBoost) for credit assessment to enable rapid monetization of inventory. Verified with 20 core and 100 supporting enterprises, the results show a 30\\% increase in inventory turnover, an 18\\%-22\\% decrease in SME financing costs, a stable order fulfillment rate above 95\\%, and excellent model performance (demand forecasting error \u003c= 8\\%, credit assessment accuracy \u003e= 90\\%). This SCM-FSCM model effectively reduces operating costs, alleviates financing constraints, and supports high-quality supply chain development.","short_abstract":"Based on economic theories and integrated with machine learning technology, this study explores a collaborative Supply Chain Management and Financial Supply Chain Management (SCM - FSCM) model to solve issues like efficiency loss, financing constraints, and risk transmission. We combine Transaction Cost and Information...","url_abs":"https://arxiv.org/abs/2509.03673","url_pdf":"https://arxiv.org/pdf/2509.03673v1","authors":"[\"Hang Wang\",\"Huijie Tang\",\"Ningai Leng\",\"Zhoufan Yu\"]","published":"2025-09-03T19:43:35Z","proceeding":"cs.LG","tasks":"[\"cs.LG\"]","methods":"[\"Reinforcement Learning\",\"Large Language Model\"]","has_code":false}