Poor cost performance of construction projects has been a major concern for bothcontractors and clients. The effective management of risk is thus critical to the success of any construction project and the importance of risk management has grown as projects have become more complex and competition has increased. Contractors havetraditionally used financial mark-ups to cover the risk associated with constructionprojects but as competition increases and margins have become tighter they can no longer rely on this strategy and must improve their ability to manage risk. Furthermore, the construction industry has witnessed significant changes particularly in procurementmethods with clients allocating greater risks to contractors.Evidence shows that there is a gap between existing risk management techniques andtools, mainly built on normative statistical decision theory, and their practical applicationby construction contractors. The main reason behind the lack of use is that risk decisionmaking within construction organisations is heavily based upon experience, intuition andjudgement and not on mathematical models.This thesis presents a model for managing global risk factors affecting construction costperformance of construction projects. The model has been developed using behaviouraldecision approach, fuzzy logic technology, and Artificial Intelligence technology. Themethodology adopted to conduct the research involved a thorough literature survey onrisk management, informal and formal discussions with construction practitioners toassess the extent of the problem, a questionnaire survey to evaluate the importance ofglobal risk factors and, finally, repertory grid interviews aimed at eliciting relevantknowledge. There are several approaches to categorising risks permeating construction projects. Thisresearch groups risks into three main categories, namely organisation-specific, global andActs of God. It focuses on global risk factors because they are ill-defined, lessunderstood by contractors and difficult to model, assess and manage although they havehuge impact on cost performance. Generally, contractors, especially in developingcountries, have insufficient experience and knowledge to manage them effectively. Theresearch identified the following groups of global risk factors as having significant impacton cost performance: estimator related, project related, fraudulent practices related,competition related, construction related, economy related and political related factors.The model was tested for validity through a panel of validators (experts) and crosssectionalcases studies, and the general conclusion was that it could provide valuableassistance in the management of global risk factors since it is effective, efficient, flexibleand user-friendly. The findings stress the need to depart from traditional approaches andto explore new directions in order to equip contractors with effective risk managementtools.