DocumentCode :
3302506
Title :
Risk element transmission prediction model of grid infrastructure project capital flow
Author :
Zhang Chen-Song ; Li Cun-Bin ; Xiong Xue-Qin ; Xu Liang
Author_Institution :
Sch. of Econ. & Manage., North China Electr. Power Univ., Beijing, China
fYear :
2013
fDate :
13-15 Dec. 2013
Firstpage :
423
Lastpage :
427
Abstract :
Since participants involved in a grid infrastructure project are a community of interests, we should not focus only on a party´s internal risk. Based on risk element transmission theory, this paper studies risk transmission process of capital flow among the participants involved in a grid infrastructrue project. This paper indentifies the inventory time and accounts receivable as risk elements based on the capital flow diagram, predicts the value of inventory time risk element by using gray system model, analyzes accounts receivable risk element which follows Poissionian distribution and under the influence of inventory time, and thereby establishes a model which describes the risk transmission along project capital flow. Combined with practical an example of the grid infrastructure project, this paper quantitatively analyzed the transmission of funding risks among enterprises involved in a grid infrastructrue project, and confirmed the validity of the model.
Keywords :
Poisson distribution; flowcharting; grey systems; inventory management; risk analysis; supply chain management; supply chains; Poissionian distribution; funding risk transmission; gray system model; grid infrastructure project capital flow diagram; inventory time risk element value prediction; party internal risk; quantitative analysis; receivable risk element; risk element transmission prediction model; Economics; Educational institutions; Materials; Mathematical model; Power grids; Predictive models; Supply chains; capital flow; grey prediction; risk element; risk transmission;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Granular Computing (GrC), 2013 IEEE International Conference on
Conference_Location :
Beijing
Type :
conf
DOI :
10.1109/GrC.2013.6740448
Filename :
6740448
Link To Document :
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