Table of Contents Author Guidelines Submit a Manuscript
Mathematical Problems in Engineering
Volume 2013, Article ID 785218, 8 pages
Research Article

Risks Analysis of Logistics Financial Business Based on Evidential Bayesian Network

1School of Economics and Business Administration, Southwest University of Science and Technology, Mianyang 621010, China
2Institute of Electronic Engineering, China Academy of Engineering Physics, Mianyang 621900, China

Received 19 February 2013; Revised 13 June 2013; Accepted 2 July 2013

Academic Editor: Yingwei Zhang

Copyright © 2013 Ying Yan and Bin Suo. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


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.