Modelling complex human-based industrial systems

This thesis is a case study in modelling a complex human-based industrial system which addresses the problem of network peak demand for electricity by residential customers. The study demonstrates the importance of designing interventions aimed at reducing peak demand that take into account the interactions of the various elements of the system. Available data from industry-specific and public sources was combined with data from relevant expert opinion through a Bayesian network (BN) approach. Applying the BN to investigate various market-based and government interventions provided insights into the major influencing factors in the system