基于大数据分析的供应链风险识别与监控研究

Research on Supply Chain Risk Identification and Monitoring Model Based on Big Data Analysis

文章旨在利用大数据分析为改进供应链风险识别与监控提供强有力的技术支持。将用于供应链风险识别的大数据分为供应链内部大数据和供应链外部大数据,其中,供应链内部大数据是指从供应链合作伙伴处收集的数据,供应链外部大数据则是指从公共新闻、社交媒体等收集的数据,基于两类数据识别潜在的供应链风险。在分析风险识别的基础上,依托多阶段随机优化技术、场景分析方法和云计算基础设施,构建了一个基于大数据分析的供应链风险监控框架模型,该框架包括供应链内部风险监测模块、供应链外部风险监测模块、供应链规划模块三个主要模块,利用大数据分析方法对供应链内外风险进行监测,在随机环境下制定应对供应链风险的柔性供应链计划。通过提出基于大数据分析的供应链风险识别与监控流程与方法,为大数据在供应链风险管理中的应用提供了理论与实践指导。

The purpose of this study is to use big data to improve supply chain risk identification and monitoring.Firstly,the big data used for identifying the supply chain risk is divided into internal big data and external big data.The big data inside supply chain refers to the data collected from supply chain partners,while the big data outside supply chain refers to the data collected from public news,social media,etc.Based on the identification of supply chain risk,with multi-stage stochastic optimization technology,scenario analysis method and cloud computing infrastructure,this study constructs a framework model of supply chain risk monitoring based on big data analysis,which includes three main modules:internal risk monitoring module,external risk monitoring module and supply chain planning module.This study uses big data analysis method to monitor the internal and external risks of the supply chain,and makes flexible supply chain plans to deal with the supply chain risks in a random environment.This study provides guidance for the implementation of supply chain risk identification and monitoring by using big data analysis,and provides a novel direction of utilizing big data in supply chain risk management.