Risk Assessment and Decision-Making of a Listed Enterprise’s L/C Settlement Based on Fuzzy Probability and Bayesian Game Theory


Zhang Cheng, Nanni Huang, Journal of Information Processing Systems Vol. 16, No. 2, pp. 318-328, Apr. 2020

10.3745/JIPS.04.0156
Keywords: Bayesian Game Theory, Fuzzy Probability, Listed Enterprise, L/C Settlement
Fulltext:

Abstract

"Letter of Credit (L/C) is currently a very popular international settlement method frequently used in international trade processes amongst countries around the globe. Compared with other international settlement methods, however, L/C has some obvious shortcomings. Firstly, it is not easy to use due to the sophisticated processes its usage involves. Secondly, it is sometimes accompanied by a few risks and some uncertainty. Thus, highly efficient methods need to be used to assess and control these risks. To begin with, FAHP and KMV methods are used to resolve the problem of incomplete information associated with L/C and then, on this basis, Bayesian game theory is used in order to make more scientific and reasonable decisions with respect to international trade."


Statistics
Show / Hide Statistics

Statistics (Cumulative Counts from November 1st, 2017)
Multiple requests among the same browser session are counted as one view.
If you mouse over a chart, the values of data points will be shown.




Cite this article
[APA Style]
Zhang Cheng and Nanni Huang (2020). Risk Assessment and Decision-Making of a Listed Enterprise’s L/C Settlement Based on Fuzzy Probability and Bayesian Game Theory. Journal of Information Processing Systems, 16(2), 318-328. DOI: 10.3745/JIPS.04.0156.

[IEEE Style]
Z. Cheng and N. Huang, "Risk Assessment and Decision-Making of a Listed Enterprise’s L/C Settlement Based on Fuzzy Probability and Bayesian Game Theory," Journal of Information Processing Systems, vol. 16, no. 2, pp. 318-328, 2020. DOI: 10.3745/JIPS.04.0156.

[ACM Style]
Zhang Cheng and Nanni Huang. 2020. Risk Assessment and Decision-Making of a Listed Enterprise’s L/C Settlement Based on Fuzzy Probability and Bayesian Game Theory. Journal of Information Processing Systems, 16, 2, (2020), 318-328. DOI: 10.3745/JIPS.04.0156.