Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic reasoning in intelligent systems: networks of plausible inference
Probabilistic inference and influence diagrams
Operations Research
Managing the software process
The EM algorithm for graphical association models with missing data
Computational Statistics & Data Analysis - Special issue dedicated to Toma´sˇ Havra´nek
Bayesian Networks and Decision Graphs
Bayesian Networks and Decision Graphs
COBIT and Its Utilization: A Framework from the Literature
HICSS '04 Proceedings of the Proceedings of the 37th Annual Hawaii International Conference on System Sciences (HICSS'04) - Track 8 - Volume 8
IT Governance: How Top Performers Manage IT Decision Rights for Superior Results
IT Governance: How Top Performers Manage IT Decision Rights for Superior Results
Awareness of IT Control Frameworks in an Australian State Government: A Qualitative Case Study
HICSS '05 Proceedings of the Proceedings of the 38th Annual Hawaii International Conference on System Sciences - Volume 08
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 08
IT Governance: Reviewing 17 IT Governance Tools and Analysing the Case of Novozymes A/S
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 08
HICSS '06 Proceedings of the 39th Annual Hawaii International Conference on System Sciences - Volume 08
Learning Bayesian Networks
Enterprise architecture analysis with extended influence diagrams
Information Systems Frontiers
HICSS '08 Proceedings of the Proceedings of the 41st Annual Hawaii International Conference on System Sciences
Identifying Incentive Factors in IT Governance: An Exploratory Study
ICCIT '07 Proceedings of the 2007 International Conference on Convergence Information Technology
Implementing Information Technology Governance: Models, Practices and Cases
Implementing Information Technology Governance: Models, Practices and Cases
The Bayesian structural EM algorithm
UAI'98 Proceedings of the Fourteenth conference on Uncertainty in artificial intelligence
A literature review: IT governance guidelines and areas
Proceedings of the 6th International Conference on Theory and Practice of Electronic Governance
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The goal of IT governance is not only to achieve internal efficiency in an IT organization, but also to support IT's role as a business enabler. The latter is here denoted IT governance performance. IT management cannot control the IT governance performance directly. Instead, their realm of control includes several IT governance maturity indicators such as the existence of different IT activities, documents, metrics and roles. Current IT governance frameworks are suitable for describing IT governance, IT-systems, and business processes, but lack the ability to predict how changes to the IT governance maturity indicators affect IT governance performance. Bayesian networks are widely used for goal modeling and prediction in several research fields. This paper presents an application of Bayesian networks for IT governance performance prediction. Data from 35 case studies conducted in a variety of organizations has been used to determine the behavior of the network. An assumption on linearity is introduced in order to compensate for the limited amount of data, and the network learns using the proposed Linear Conditional Probability Matrix Generator. The resulting Bayesian network for IT governance performance prediction can be used to support IT governance decision-making.