• ISSN 0258-2724
  • CN 51-1277/U
  • EI Compendex
  • Scopus
  • Indexed by Core Journals of China, Chinese S&T Journal Citation Reports
  • Chinese S&T Journal Citation Reports
  • Chinese Science Citation Database
Volume 31 Issue 3
Jun.  2018
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Article Contents
FU Zhuo, YAN Yusong, GUO Qian, QIU Zhongquan. Risk Transfer Mechanism and Control in Logistics of Fresh Agriculture Product Supply Chain[J]. Journal of Southwest Jiaotong University, 2018, 53(3): 654-660. doi: 10.3969/j.issn.0258-2724.2018.03.029
Citation: FU Zhuo, YAN Yusong, GUO Qian, QIU Zhongquan. Risk Transfer Mechanism and Control in Logistics of Fresh Agriculture Product Supply Chain[J]. Journal of Southwest Jiaotong University, 2018, 53(3): 654-660. doi: 10.3969/j.issn.0258-2724.2018.03.029

Risk Transfer Mechanism and Control in Logistics of Fresh Agriculture Product Supply Chain

doi: 10.3969/j.issn.0258-2724.2018.03.029
  • Received Date: 22 May 2017
  • Publish Date: 01 Jun 2018
  • In order to better reflect the transmission of financial risk caused by the time deviation of a logistics operation, the transmission problem of overdue risk caused by logistics delays in the supply chain of fresh agricultural products was analysed, based on the condition of time constraints of a logistics service. First, by applying the principles of disease transmission of lemology, the three infectious elements, which are infection source, transmission carrier, and infected person, were introduced into the identification of logistics risk transmission, and five risk factors were established. These included logistics operation standards, management ability, environmental protection, logistics extension, and spatial risk transmission. Then, the numerical analysis of an iterative method was used to calculate the value of the supply chain overdue risk based on the risk transfer model of logistics of a fresh agricultural products supply chain. In addition, the factors that influence the overdue risk value of a supply chain, which is affected by controlling risks, were studied including internal nodes, spatial transfer, and logistics delay. These were analysed using an example. The analysis showed that calculating the risk node is beneficial to finding the key node for controlling risk transmission, and after optimizing the risk elements of key nodes it can be used to reduce the risk value effectively for the circumstance when the supply chain follows a single logistics direction. In the example analysis, nodes 2 and 4 were recognized as the key nodes for generating the supply chain overdue risk and their risk values were calculated as 0.45 and 0.39, respectively. After the factors were optimized the overdue risk value of the supply chain was reduced from 0.39 to 0.29.

     

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