Author(s)

Jiaming Chen

Corresponding Author

Jiaming Chen

Abstract

With the rapid development of big data technology, supply chain management has entered a new era driven by data, and supply chain risk management has also entered a stage of high-quality development. It is necessary to propose solutions for supply chain risk management that better meet market demand, based on the concept of data centered supply chain risk management. Based on the dynamic evolution of big data technology development, a theoretical analysis framework for supply chain risk management is constructed according to the internal logic of supply chain risk management. This framework can explain the development mechanism of supply chain risk management jointly generated by the supply chain risk identification mechanism and risk assessment cycle mechanism participated in by data collection and analysis, and explore the possibility of achieving the high-quality development goal of supply chain risk management from the perspective of practical changes and deduction of supply chain risk management. The purpose of supply chain risk management is to provide security guarantees that meet the expected standards for supply chain participants and to strive to improve the quality of supply chain risk management and enhance supply chain efficiency. To this end, measures such as strengthening risk control based on data analysis quality internal circulation, constructing mechanisms for interaction and communication between risk perception and risk management, and establishing an evaluation system for risk assessment and response should be taken to achieve high-quality development of supply chain risk management, promote supply chain optimization, and truly meet the needs of the market and customers.

Keywords

Big Data Analysis; Supply Chain Risk Management; Data-Driven; Risk Assessment; Risk Control