Table of Contents
Journal of Construction Engineering
Volume 2015, Article ID 203468, 10 pages
Research Article

Risk Determination, Prioritization, and Classifying in Construction Project Case Study: Gharb Tehran Commercial-Administrative Complex

1University of Science and Technology of Iran, Unit 3, No. 59, 38th Street, Gisha Avenue, Tehran 14489 43593, Iran
2Bordeaux University, France

Received 26 May 2015; Revised 18 August 2015; Accepted 8 September 2015

Academic Editor: Eric Lui

Copyright © 2015 Azadeh Sohrabinejad and Mehdi Rahimi. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Construction projects play an important role in infrastructure projects in developing countries. According to type, size, and complexity of the project, the number and importance of each risk could be different and many projects cannot reach the project goals due to exposure to multiple risks. Many papers have been published on the subject of risk management in construction projects; unfortunately most of them have not been implemented in practical conditions. The aim of this study is to identify and prioritize risks in construction projects. The classical approach used probability and impact for risk assessment, but these criteria do not sufficiently address all aspects of projects risks and there might be a relationship between different criteria. This study proposes the hierarchical dependencies between criteria. A case study of construction project is presented to illustrate performance and usage of the proposed model. Utilizing library studies and interview with experts, managers, and specialists, decision criteria were identified through brain storming. Risks were categorized by the experts into eleven risks. Important risks were evaluated based on the fuzzy ANP, fuzzy DEMATEL, and fuzzy TOPSIS methods. The proposed model is more suitable than the traditional decision-making methods in prioritizing risk concerning cost, time, and quality.