Purpose

The operational management of cold chain logistics has an important impact on the quality of cold chain products, but the service delivery process is subject to a series of potential problems such as product loss and cold storage temperature in the actual operation.

Design/methodology/approach

In this paper, the whole cold chain logistics system and risk events are analyzed. A Bayesian network is used for modeling and simulation to identify the main influencing factors and to conduct a sensitivity analysis of the main factors.

Findings

It is found that the operation of cold chain logistics systems can be divided into four links according to the degree of influence as follows: transportation and distribution, processing and packaging, information processing and warehousing. Transportation and distribution is the most influential factor of system failure, and extreme weather is the most risky event. At the same time, the four risk events that have the greatest impact on the operation of the cold chain system are in descending order: transportation equipment failure, extreme weather, unqualified pre-cooling and violation operation.

Originality/value

Therefore, enterprises should develop appropriate interventions for securing the transportation services, design strategies to deal with extreme weather conditions prior to and in the early stage of product delivery, and prepare additional effective measures for managing emergency events.

中文翻译：

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冷链物流系统的运营风险建模：贝叶斯网络方法

目的

冷链物流的运营管理对冷链产品的质量有重要影响，但是服务交付过程中会遇到一系列潜在问题，例如在实际操作中产品损失和冷藏温度。

设计/方法/方法

本文分析了整个冷链物流系统和风险事件。贝叶斯网络用于建模和仿真，以识别主要影响因素并对主要因素进行敏感性分析。

发现

研究发现，冷链物流系统的运行可以根据影响程度分为四个环节：运输与配送，加工与包装，信息加工与仓储。运输和分配是影响系统故障的最主要因素，极端天气是最危险的事件。同时，对冷链系统运行影响最大的四个风险事件是降序排列的：运输设备故障，极端天气，不合格的预冷和违规运行。

创意/价值

因此，企业应制定适当的干预措施以确保运输服务安全，设计策略以在产品交付之前和交付初期处理极端天气条件，并准备用于管理突发事件的其他有效措施。