A simulation-based risk network model for decision support in project risk management

• Published in: Decision Support Systems 2012-02, Vol.52 (3), p.635-644
• Main Authors: Fang, Chao, Marle, Franck
• Format: Article
• Language: English
• Subjects: Applied sciences; Assessments; Complexity; Computer science; control theory; systems; Computer simulation; Decision making models; Decision support system; Decision support systems; Decision theory. Utility theory; Exact sciences and technology; Information systems. Data bases; Memory organisation. Data processing; Networks; Operational research and scientific management; Operational research. Management science; Project management; Project risk management; Risk; Risk management; Risk network; Risk theory. Actuarial science; Simulation; Software; Software engineering; Studies; Utilities
• ISSN: 0167-9236; 1873-5797
• DOI: 10.1016/j.dss.2011.10.021

This paper presents a decision support system (DSS) for the modeling and management of project risks and risk interactions. This is a crucial activity in project management, as projects are facing a growing complexity with higher uncertainties and tighter constraints. Existing classical methods have limitations for modeling the complexity of project risks. For example, some phenomena like chain reactions and loops are not properly taken into account. This will influence the effectiveness of decisions for risk response planning and will lead to unexpected and undesired behavior in the project. Based on the concepts of DSS and the classical steps of project risk management, we develop an integrated DSS framework including the identification, assessment and analysis of the risk network. In the network, the nodes are the risks and the edges represent the cause and effect potential interactions between risks. The proposed simulation-based model makes it possible to re-evaluate risks and their priorities, to suggest and test mitigation actions, and then to support project manager in making decisions regarding risk response actions. An example of application is provided to illustrate the utility of the model. ► Present an integrated decision support system for project risk management. ► An interactions-based risk network model using advanced simulation. ► Address the limitations of current methods for modeling complexity in PRM. ► Provide a series of methods to model, analyze and control the risk network.