2019 CSCE Annual Conference - Laval (Greater Montreal) Conference
Dr. Ossama Hosny, AUC
Dr. Elkhayam Dorra, American University in Cairo
Dr. Ahmed Waly, The American University in Cairo
Whether forced by economic conditions or internal motivations, contractors may choose to minimize their mark-up margins in order to maximize their chances of winning a bid. In such cases, they are often more focused to submit bids with the lowest price possible with less regard to the proper profit or contingency margins needed to execute the project. Such drastic bidding conditions render contractors sensitive towards all types of risks associated with executing a project. This is why it is important for contractors to fully understand intricate risk dynamics for effective and efficient risk management. This paper explores risk identification and classification through the risk path approach as a substitute for the traditional risk source-risk factor approach mostly used in Egypt till this day. An ontology model is developed to illustrate the identified risk path, the interdependent relations amongst its elements, and its effect on projects’ costs overruns. The risk path identified in this paper consists mainly of risk elements and vulnerability factors, where risk elements are project uncertainties categorized according to their places within the risk path while vulnerability factors are project vulnerabilities that determines the extent or capacity to resist or cope with risk elements. Risk elements consist of risk sources, risk events, and risk consequences, while vulnerability factors consist of robustness factors, resistance factors and sensitivity factors. An artificial neural network (ANN) is then constructed based on the information logged in the ontology model, where training and testing cases are retrieved from surveying both the literature and experts in the Egyptian construction field. Simulations are conducted using the ANN algorithm to establish the sensitivity of cost overruns to each of the identified risk elements and vulnerability factors. Following this enhanced understanding of risk elements, their relation, and their effect on cost overruns, the paper identifies and develops contract conditions that effectively address the identified risk elements with the greatest impact on projects’ costs. Such information allows contractors to minimize such costs, thus enabling them to minimize their contingency estimates and, consequently, reduce their bid prices.