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Risks Analysis of Logistics Financial Business Based on Evidential Bayesian Network

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  • Ying Yan
  • Bin Suo

Abstract

Risks in logistics financial business are identified and classified. Making the failure of the business as the root node, a Bayesian network is constructed to measure the risk levels in the business. Three importance indexes are calculated to find the most important risks in the business. And more, considering the epistemic uncertainties in the risks, evidence theory associate with Bayesian network is used as an evidential network in the risk analysis of logistics finance. To find how much uncertainty in root node is produced by each risk, a new index, epistemic importance, is defined. Numerical examples show that the proposed methods could provide a lot of useful information. With the information, effective approaches could be found to control and avoid these sensitive risks, thus keep logistics financial business working more reliable. The proposed method also gives a quantitative measure of risk levels in logistics financial business, which provides guidance for the selection of financing solutions.

Suggested Citation

  • Ying Yan & Bin Suo, 2013. "Risks Analysis of Logistics Financial Business Based on Evidential Bayesian Network," Mathematical Problems in Engineering, Hindawi, vol. 2013, pages 1-8, July.
    • Handle: RePEc:hin:jnlmpe:785218
    DOI: 10.1155/2013/785218
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    Cited by:

    1. Alptekin Ulutaş & Ieva Meidute-Kavaliauskiene & Ayse Topal & Ezgi Demir, 2021. "Assessment of Collaboration-Based and Non-Collaboration-Based Logistics Risks with Plithogenic SWARA Method," Logistics, MDPI, vol. 5(4), pages 1-14, November.

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