Methodology for Project Risk Assessment of Building Construction Projects Using Bayesian Belief Networks

The study aims to establish a risk assessment methodology to improve the performance of building construction projects especially in developing countries. A survey of randomly selected samples to evaluate risk factors experienced by construction practitioners was conducted based on the likelihood of occurrence and impacts on projects. A response rate of 53% comprising 305 contractors and subcontractors and 38 clients was received. Risk Acceptability Matrix (RAM) was used to rank/prioritise risk factors in order to determine critical risks that could affect building construction projects especially in developing countries. Bayesian Belief Network was then constructed by structural learning and used to appreciate the relationship amongst the risk factors. Results showed that critical risks affecting building construction projects were mainly improper construction methods, poor communication between involved parties, supplies of defective materials, delayed payment in contracts, fluctuation of materials prizes and unsuitable leadership style.