In spite of the nature of construction contract risks, the variability involved in their
outcomes and the potential benefits that applying rigorous and probabilistic approaches
offers the analysis of such risks, existing predominant practices continue to involve the
use of risk assessment and analysis approaches that are often arbitrary, illogical,
inadequate, misleading and subject to considerable personal perceptions and biases of
the "solo" analyst. The lack of rigour and systematic approach is often blamed on the
possible high cost of pursuing a rigorous process and the unavailability of relative
frequency data on the separate risks. The practice of using lump sum or percentage
contingency, individual approaches to risk analysis and at best three-point or triangular
distributions for risk analysis have thus persisted even though evidence from other
industries suggests that rigorous and probabilistic approaches could be applied to
construction contract risks.This thesis aims to conduct a review and survey to establish the appropriateness of the
types of risk management techniques currently used in the construction industry, to
investigate risk perception in construction and its impact on project performance, and to
develop a procedural model for the elicitation of expert opinions about risks that
minimises the adverse effects of risk perception on individual estimates of risk, and
provides these opinions as input variables to the rigorous and probabilistic analysis of
contractual risks. The work is a cross-cultural study, applying mail questionnaire
surveys, interviews, Delphi and Vignette techniques, and analyzing risk management
approaches and applications of the elicitation model developed by the study in both
United Kingdom and Ghana. The data generated by the elicitation model are analysed
using relative likelihood methods to develop subjective prior probability distributions for
use as input variables in the Bayesian analysis of contractual risks in construction.The study concludes that although relative frequency data are often unavailable for
contractual risks, existing predominant practices for contractual risk analysis are
inappropriate for the nature of contractual risks. Furthermore, individual perceptions
about risks significantly affect expert judgements about risks (and consequently project
performance) in spite of their expertise. Using the expert elicitation model developed by
the study and the analytical approaches applied, it is possible to capture, encode and
aggregate the knowledge and experiences of a group of relevant experts to derive
probability distribution functions of contractual risks to be applied as input variables to a
Bayesian analysis of contractual risks, and thereby achieve a more appropriate,
systematic and rigorous approach to contractual risk analysis. Evidence from the study
also indicates that this approach need not involve any significantly high costs as the
analysis can be done using standard spreadsheet software and add-in programmes that
companies already have on their computer systems.Recommendations are thus made for the use of expert team approaches and the
elicitation model developed in the study in the management of contractual risks. In
addition, implications on existing types of contract, risk management education and
further research are highlighted
