Browse > Article
http://dx.doi.org/10.7232/IEIF.2011.24.2.119

Developing a Bayesian Network Model for Real-time Project Risk Management  

Kim, Jee-Young (Department of Information & Management Engineering, Hanyang University)
Ahn, Sun-Eung (Department of Industrial & Management Engineering, Hanyang University)
Publication Information
IE interfaces / v.24, no.2, 2011 , pp. 119-127 More about this Journal
Abstract
Most companies have been increasing temporary work projects to maximize the usage of their resources. They also have been developing the effective techniques for analyzing and managing the state of the projects. In order to monitor the state of a project in real-time and predict the project's future state more accurately, this paper suggests the Bayesian Network (BN) as a tool for discovering the causes of project risk and presenting the failure probability of the project. The proposed BN modeling method with consideration of the Earned Value Management (EVM) method shows how to induce the predictive and conditional probability of the risk occurrence in the future. The advantages of the suggested model are (1) that the cause of a project risk can be easily figured out via the BN, (2) that the future value of the project can be sufficiently increased by updating relevant components of the project, and (3) that more credible prediction can be made in the similar and future situation by using the data obtained in current analysis. A numerical example is also given.
Keywords
Project Risk Management; Earned Value Management; Bayesian Network;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Jung, Y. and Lee, Y. (1999), Understanding of the Concept and utilization method of EVMS, Construction Economy Research Institute of Korea Working Paper, 16, 1-41.
2 Kang, B., Cho, N., Kim, H., and Kang, S. (2008), Real-time Risk Measurement of Business Process Using Decision Tree, Journal of the Society of Korea Industrial and Systems Engineering, 31(4), 49-58.
3 Khodakarami, V., Fenton, N., and M. Neil (2007), Project Scheduling : Improved Approach to Incorporate Uncertainty Using Bayesian Networks, Project Management Journal, 38(1), 1-30.
4 Mary, S. (2000), Risk Factors in Enterprise Wide Information Management Systems Projects, the 2000 ACM SIGCPR Conference on Computer Personnel Research, 180-187.
5 Lee, S. (2002), A Study On the Predicting Method of the EAC according to the Performance Index of Construction Projects, Journal of The Korea Institute of Building Construction, 2(4), 105-112.   DOI
6 McFarlan, F. W. (1981), Portfolio Approach to Information Systems, Harvard Business Review, 142-150.
7 Mittal, A. and Kassim, A. (2007), Bayesian Network Technologies : Applications and Graphical Models, IGI Publishing, Pennsylvania, USA.
8 OMB (1997), Principles of Budgeting for Capital Asset Acquisitions, Office of Management and Budget (OMB), US Government Printing Office, Washington, USA.
9 Pearl, J. (2000), Causality : Models, Reasoning and Inference, Cambridge University Press, New York, USA.
10 PMI (2004), A Guide to the Project Management Body of Knowledge : PMBOK Guide, 3rd, Project Management Institute (PMI), USA.
11 Fleming, Q. W. and Koppelman, J. M. (1996), Earned Value Project Management, Project Management Institute, Newtown Square, USA.
12 Frank, L. and R. Dieter (2000), Production Workflow Concepts and Techniques, Prentice Hall, New Jersey, USA.
13 Jensen-Finn, V. (2001), Bayesian Networks and Decision Graphs, Springer, New York, USA.
14 Gamez-Jose, A., Moral, S., and Salmeron A. (2004), Advances in Bayesian Networks, Springer, New York, USA.
15 Grigori, D., Casati, F., Castellanos, M., Dayal, U., Sayal, M., and M. C. Shan (2004), Business Process Intelligence, Computers in Industry, 53, 321-343.   DOI   ScienceOn
16 Jensen-Finn, V., An Introduction to Bayesian Networks, UCL Press, London, UK, 1996.
17 John, W. and Edward Gibson, G. (2003), International Project Risk Assessment : Methods, Procedures and Critical Factors., Construction Industry Institute (CII), Australia.
18 Albaghdadi, M., Briley, B., and Evens, M. (2006), Event Storm Detection and Identification in Communication Systems, Reliability Engineering and System Safety, 91, 602-613.   DOI   ScienceOn
19 Barry, W. B. (1991), Software Risk Management : Principles and Practices, IEEE Software, 8, 32-41.   DOI
20 Ahn, H., Kim, K., and Han, I. (2005), Consolidated project management with time, cost, quality consideration : A case of web-site construction process, The e-Business Studies, 6(2),193-212.