Reducing sustainable supply chain risks: a digital technology-enabled risk management framework for ESG-oriented engineering procurement

Facing increased societal demands for corporate sustainability, the challenges faced by companies in engineering procurement risk management (EPRM) expand from economic to environmental, social and governance aspects. Based on a systematic review, this study finds that current research focuses on a single Environmental, Social, and Governance (ESG) dimension or procurement risk management (PRM) business orientation. Companies urgently need to address multiple pressures of ESG compliance, transparent supplier ecology, and real-time risk management. However, fragmented ESG assessment, siloed data systems and reactive strategies have led to operational inefficiencies and missed technology dividends, and there is an urgent need to build a procurement risk solution that integrates ESG and digital technologies (DTs). Therefore, this paper proposes a framework, namely DEEP-RM, for ESG-oriented circulated PRM that leverages DTs such as the Large Language Model, Multi-Agent System, and Blockchain. The DEEP-RM aims to facilitate enterprises in PRM through ESG transformations and DTs to enhance supply chain resilience and achieve sustainability in supply chain management. This paper enriches the theory of EPRM by revealing, for the first time, the evolutionary path of research in PRM through literature analysis. Breaking the traditional linear management model, the research proposes a closed-loop framework that integrates DTs and ESG to achieve global visualisation of risk management and a trusted collaboration ecology. The framework innovatively uses various emerging technologies to overcome the problems in traditional EPRM, and promotes the transformation of risk management from experience-driven to machine intelligence-driven. The new energy company S has successfully implemented the framework and achieved remarkable results.