| Summary: | The management of economic risks is critical for the success of major infrastructure
projects. As with other management challenges, the tasks associated with risk
management rely heavily on knowledge and experience, and also involve the use of a
diverse and sizeable set of information. Thus, computer-based methodologies that can
allow the application and re-use of information and knowledge have the potential to be
particularly useful to an organization in managing risks. Described in this thesis are the
results of an effort to develop such a methodology.
The methodology represents the risks and the context to which they apply by
considering five dimensions or views. The five dimensions are the Risks, the Physical
components of the project, the Processes required to procure and operate it, the
Organizational entities involved, and the Environment in which it is being procured and
operated. The methodology facilitates the creation of enterprise-level ontologies or
libraries for each of these views. The libraries which can be augmented over time are
made up of components relevant to a particular view which are modeled in a project-neutral
format. Information and knowledge that is relevant to supporting project risk
management is modeled within the components.
In analysing the risks of an individual project, the methodology facilitates the
development of project-specific models for each of the five dimensions for that particular
project making use of the content of the libraries. The relationship between the context
and risks is modeled through a driver-issue relationship and refined using the notion of
spatial and temporal gateways. The methodology also allows the user to leverage the
representations to derive insights such as the distribution of risks among spatial location
and among project participants, and the evolution of risks as project conditions change. It
is anticipated that the functionality provided for re-using information and knowledge and
for leveraging available information will assist an organization in identifying a more
complete set of risks, in providing more refined input to economic models used in
decision making, and in deciding on appropriate risk assignments, thus bringing an
organization closer to achieving success on the projects they undertake. === Applied Science, Faculty of === Civil Engineering, Department of === Graduate
|
|---|
