Estimation of cost overrun risk in interrnational project by using fuzzy set theory

Han, Sedat
In the global construction market, most construction companies are willing to undertake international projects in order to maximise their profitability by taking advantage of attractive emerging markets and minimise dependence on unfavorable domestic market conditions. In order to be awarded a contract in highly competitive global construction market, companies should excel in choosing the most attractive markets and prepare winning bids for the selected construction projects in those markets. While preparing bids, the major concern of companies is to offer an optimum price that will enable them to earn enough profits and win the contract at the same time, where profit making ability is strongly correlated with proper estimation of a risk premium that is added onto the estimated cost of the project. Due to the nature of construction works, there are lots of uncertainties associated with the project, market and country conditions. Therefore, how the profitability of the project changes with occurrence of various risk events, in other words, the sensitivity of project costs to risk events, should be estimated by bidders realistically. In this study, fuzzy set theory is used to estimate cost overrun risk in international projects at the bidding stage. The objective is to propose a methodology which can be used by bidders to quantify cost overrun risk so that a realistic risk premium may be determined. A fuzzy risk rating approach is proposed to quantify cost overrun risk rating, which takes into account of risks characterised in international construction projects. For this purpose, risk sources have been identified and a risk model is put forward by using influence diagramming method. Based on this risk model, a fuzzy risk rating algorithm has been defined and software has been developed to conduct fuzzy risk rating calculations easily. After a decision-maker inserts


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Citation Formats
S. Han, “Estimation of cost overrun risk in interrnational project by using fuzzy set theory,” M.S. - Master of Science, Middle East Technical University, 2005.