Due to its high-risk nature, international construction projects are more vulnerable to adverse changes in project environment and company objectives. To achieve successful project outcomes, early provision of risks has a vital place in managing construction projects. Within the literature, several risk assessment methodologies have been offered to simulate probable consequences of risks. The majority of the proposed methodologies are limited in reflection of real project conditions as they require probabilistic measures or rely on solely intuition and experience of decision makers. In this study, it is argued that an additional assistance is needed for decision-makers when they are assessing magnitudes of risks under different project and country conditions. The purpose of this study is to develop a knowledge-based risk mapping tool for international construction projects using an ontology that relates risk and vulnerability to cost overrun and a novel risk-vulnerability assessment methodology. The tool incorporates a &lsquo / lessons learned database&rsquo / that utilizes learning from previous projects in order to assist decision-makers when quantifying the risk-related variables. The database is expected to aid decision-makers by retrieving and making use of the knowledge of previous projects that have been captured, codified, and stored within the database previously. In addition, to guide decision-makers by giving better understanding of the risk variables, attributes of the risk-related variables are identified that lists probable triggering events for the occurrence of the relevant variables. The tool has also been tested on a real construction project as well as its usability has been ensured by conducting some usability tests.
| Identifer | oai:union.ndltd.org:METU/oai:etd.lib.metu.edu.tr:http://etd.lib.metu.edu.tr/upload/12615342/index.pdf |
| Date | 01 January 2013 |
| Creators | Yildiz, Acelya Ecem |
| Contributors | Dikmen Toker, Irem |
| Publisher | METU |
| Source Sets | Middle East Technical Univ. |
| Language | English |
| Detected Language | English |
| Type | M.S. Thesis |
| Format | text/pdf |
| Rights | Access forbidden for 1 year |
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