Supply Chain Intelligent Rating System: A Study on Its Adaptability and Application in Multiple Industries

Abstract

In the context of accelerating global economic integration, the complexity and significance of supply chain management have become increasingly prominent. Traditional supply chain rating methods, when confronted with dynamic market environments, exhibit numerous limitations and fail to meet enterprises’ demands for real-time risk warnings and precise management. The supply chain intelligent rating system developed in this study, leveraging big data analysis and artificial intelligence technologies, realizes real-time monitoring and intelligent assessment of supply chain risks. It has been widely applied across multiple industries, including real estate, petrochemicals, hotels, and grain and oil, significantly enhancing enterprises’ supply chain management efficiency and economic benefits. A scientific adaptability evaluation index system was constructed in this research to deeply analyze the application effects and cross-field adaptability of the system in different industries, providing strong support for its optimization and promotion. By optimizing data collection, improving the flexibility of functional modules and user experience, the system has demonstrated good adaptability and application value in various industries. In the future, this study will further expand data sources, deepen the customized development of functional modules, and explore more effective promotion models to facilitate the application and development of the supply chain intelligent rating system in more industries, thereby assisting enterprises in enhancing their competitiveness and economic benefits.