The role of data analysis and financial engineering in managing industrial projects with a circular economy approach

This study investigates the integration of data analytics and financial engineering within the framework of circular economy principles to enhance sustainability and decision-making in industrial project management. The primary objective is to develop a systematic understanding of how emerging technologies and financial models can be combined to evaluate and prioritize projects more effectively. Utilizing a structured literature review methodology, this research identifies key theoretical foundations, examines recent empirical studies, and highlights technological advancements such as artificial intelligence, IoT, and blockchain. Findings reveal that while each domain data analytics, financial modeling, and circular economy― has evolved significantly, their combined application remains limited and fragmented in current literature. The study identifies major research gaps including the lack of hybrid models, insufficient real-world implementation of interpretability tools like SHAP, and underrepresentation of small and medium enterprises in case studies. It proposes the development of integrated decision-making frameworks that incorporate real-time data, lifecycle assessment, and multi-criteria evaluation. The results emphasize that aligning financial tools with sustainability indicators and leveraging data-driven insights can significantly enhance project transparency, resource optimization, and long-term environmental impact. This research contributes to the growing field of sustainable industrial management by offering a roadmap for future studies and practical applications.

کلیدواژه ها:

Circular economy ، Data analytics ، Financial engineering ، Industrial project management ، Sustainability