Research on Cold Chain Logistics Risk in E-commerce Using Text Mining Technology

Abstract

In recent years, with the rapid development of e-commerce and Internet, more and more products transfer to the information-based transformation. Numerous of goods such as fresh products are turning to online sales model. Selling fresh agricultural products on e-commerce platform can not only broaden the sales channels and increase the profits of peasants but also enable people to buy high-quality fresh products. However, at the same time we cannot ignore that due to the relatively slow development of cold supply chain, there are still a lot of problems. For example, untimely and unreasonable transportation will cause fresh products are corrupted and deteriorated in the transportation process every year, which damages the interests of supply chain members. Accurate identification and quantitative analysis of supply chain hazards have great significance in the improvement of transport efficiency of supply chain and reducing the transport cost of supply chain. This paper indicates the methods of literature analysis to collect and summarize the relevant keywords in the theory of supply chain risk and uses text mining technology to collect and analyze supply chain risk in CNKI literatures. It catches those literatures containing keywords about supply chain risk in database, stores the related information in the Excel. Then it calculates the frequency of each keyword appears in the final statistics. Then it removes the supply chain risk factors that have less attention. At last, using the analytic hierarchy process (AHP) to quantitatively analyze and evaluate the risks in the cold supply chain of fresh agricultural products. Finally, the weight of risks in the cold supply chain of fresh agricultural products is calculated.