Abstract
In this paper, the authors describe an innovative means of identifying patterns present in systems engineering activity when government organization acquire and build complex information systems. The research uses a Bayesian belief network to model causal relationships present in government acquisitions to create a systems engineering relative effectiveness index model that can be used to identify and analyze systems engineering patterns; and subsequently forecast possible areas of performance risks within projects and organizations.
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