The main purpose of this chapter is to emphasize the problem of e-government project risks and to introduce a methodology for risk assessment and calculation of costs associated with risk occurrence in e-government projects based on Bayesian networks. The proposed methodology presents a new approach to the assessment of risks and costs related to e-government project risks. As such, it facilitates the holistic decision making procedure for project managers. The application of Bayesian networks in the context of risks and risk related costs reduces the level of uncertainty in e-government projects and provides a graphical structure of risks and corresponding costs. Finally, the sensitivity analysis has also been integrated into the methodology and its results can have a significant impact on the overall project management quality.
The main purpose of this chapter is to emphasize the problem of e-government project risks and to introduce a methodology for risk assessment and calculation of costs associated with risk occurrence in e-government projects based on Bayesian networks. The proposed methodology presents a new approach to the assessment of risks and costs related to e-government project risks. As such, it facilitates the holistic decision making procedure for project managers. The application of Bayesian networks in the context of risks and risk related costs reduces the level of uncertainty in e-government projects and provides a graphical structure of risks and corresponding costs. Finally, the sensitivity analysis has also been integrated into the methodology and its results can have a significant impact on the overall project management quality.
The main purpose of this chapter is to emphasize the problem of e-government project risks and to introduce a methodology for risk assessment and calculation of costs associated with risk occurrence in e-government projects based on Bayesian networks. The proposed methodology presents a new approach to the assessment of risks and costs related to e-government project risks. As such, it facilitates the holistic decision making procedure for project managers. The application of Bayesian networks in the context of risks and risk related costs reduces the level of uncertainty in e-government projects and provides a graphical structure of risks and corresponding costs. Finally, the sensitivity analysis has also been integrated into the methodology and its results can have a significant impact on the overall project management quality.
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