Models are often highly complex incorporating different processes, parameters, scenarios and subjects, and thereby producing different outcome endpoints. The first recommended model development step is the construction of a conceptual model, thereby specifying and defining the processes and relationships to be covered by the model. However, model results are also often highly complex, being fra...

Bayesian belief networks offer an alternative to conventional estimation methods in estimating user preference or utility functions. Because parameter estimates are updated sequentially, this approach seems very promising in user-centred design and data collection systems. The application of such networks however poses several questions, related to speed of learning, sample heterogeneity and di...