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The Research Based On The Project Investment Risk Evaluation And Decision Method Of Bayesian Networks

Posted on:2005-01-18Degree:DoctorType:Dissertation
Country:ChinaCandidate:B G GuoFull Text:PDF
GTID:1116360152465777Subject:Management Science and Engineering
Abstract/Summary:PDF Full Text Request
Project management is often and widely used in organizations, because of Economy Globalization, dynamic characteristics of competition and increasing speed of technology innovation, project management in such highly turbulence environment is of uncertainty and complexity, that' why the research on investment risk evaluation and decision system has important realistic value.Investment risk evaluation and decision under uncertain condition includes pre-inyestment evaluation (static risk evaluation, to decide if a project should be approved and initiated.) and stop-evaluation (to decide if the project should be stopped.) This paper, which focuses on difficulties and importance on risk evaluation, discussed the following points: The first Qualitative analysis on project risk management by investment process analysis. And for imperfect data and subjective data, the criteria take D-S evidence amalgamation way and mass decision technology. Considering complexity of criteria and correlation of indices, the paper takes multi-meta statistic way to decrease dimension, which avoids false and complexity and then can provide objective, scientific and rational decision. At the same time build the Risk evaluation model based on Bayesian Networks (BN) and investment risk presentiment model based on Dynamic Bayesian Networks (DBN), which can realize risk control of ongoing investment. With real option theory, the paper realized dynamic benefit and risk evaluation, built static selection and dynamic management of project investment; At last, chose the project investment of a enterprise which occupied in vehicle manufacture as the example, to validate the validity of the method in this paper.
Keywords/Search Tags:project management, risk evaluation, Bayesian Networks, Real option
PDF Full Text Request
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