Author_Institution :
Sch. of Inf. & Manage. Sci., Henan Agric. Univ., Zhengzhou, China
Abstract :
Notice of Retraction
After careful and considered review of the content of this paper by a duly constituted expert committee, this paper has been found to be in violation of IEEE´s Publication Principles.
We hereby retract the content of this paper. Reasonable effort should be made to remove all past references to this paper.
The presenting author of this paper has the option to appeal this decision by contacting TPII@ieee.org.
Logistics finance is an innovative financial solution which combines goods flow with funds flow, with diverse benefits that appeal to buyers, sellers, logistics enterprises and commercial banks. For example, Commercial banks can widen service ranges and enlarge the loans with lower risks and small and medium-sized enterprises can obtain working capital and speed up their development. Logistics finance has attracted great attention in both academia and in business recently, but the logistics finance has developed in china for only several years and its related mechanisms are still immature, and its participation subjects are diversified, the risk exists in the operation of logistics finance. Therefore, it is very necessary to present quantitative risk analysis to perform on logistics finance. According to the characteristics of complexity, subjectivity and uncertainty of logistics finance, this paper introduces the unascertained theory and fuzzy method to establish early warning model, the model combines the unascertained theory with fuzzy method. Firstly the risk probability and risk loss are given by utilizing the unascertained theory and fuzzy method respectively, and then the whole risk of logistics finance is given according to the mean of risk by the utility function of the risk probability and the risk loss. Finally, an example application is given, where the method was tested, and the relate preventive measures are presented.
Keywords :
finance; fuzzy set theory; logistics; number theory; probability; risk analysis; China; early warning system; fuzzy method; logistics finance; quantitative risk analysis; risk assessment; risk loss; risk probability; unascertained theory; utility function; working capital; Alarm systems; Finance; Logistics; Programmable logic arrays; early warning system; fuzzy method; logistics finance; unascertained theory;