On sensitivity analysis for a class of decision systems
Decision Support Systems
An agent-based framework for building decision support systems
Decision Support Systems - Special issue on decision support technologies for complex and open organizations
Advances in Engineering Software
A jini-based software framework for developing distributed cooperative decision support systems
Software—Practice & Experience
BBN-based software project risk management
Journal of Systems and Software - Special issue: Applications of statistics in software engineering
Project Management: A Systems Approach to Planning, Scheduling, and Controlling
Project Management: A Systems Approach to Planning, Scheduling, and Controlling
Model-driven decision support systems: Concepts and research directions
Decision Support Systems
Eight key issues for the decision support systems discipline
Decision Support Systems
Large engineering project risk management using a Bayesian belief network
Expert Systems with Applications: An International Journal
A risk oriented model to assess strategic decisions in new product development projects
Decision Support Systems
Software project risk analysis using Bayesian networks with causality constraints
Decision Support Systems
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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.