Factors affecting the risk ratings assigned by decision-makers under uncertain situations: The case of international construction

Thesis Type: Postgraduate

Institution Of The Thesis: Orta Doğu Teknik Üniversitesi, Faculty of Engineering, Department of Civil Engineering, Turkey

Approval Date: 2014




Assessing risk in international construction projects is an essential part of the risk management process. Due to the lack of available data and knowledge about the project risks, objective/quantitative risk assessment is facing with some challenges and subjective/qualitative risk assessment is still a prevailing technique in the construction industry. The Probability-Impact (P-I) risk matrix/table is one of the frequently used techniques among the subjective/qualitative risk assessment methods, which usually utilizes a 1 to 5 Likert scale. However, although it is very widely used, lack of knowledge still exists about the factors that may affect the risk ratings that decision-makers assign to risks during qualitative risk assessment process. Therefore, this research examines the effects of two important factors such as ‘‘decision-makers’ attitudes toward risk’’ and their assumption about ‘‘risk controllability’’ on the risk ratings using 1-5 scaling. The research was conducted via a questionnaire survey where the 74 professionals and 7 academics from the construction industry participated in this survey. Two hypotheses are proposed and then tested for their validity, confirming that risk attitude and assumptions about risk controllability are the two critical factors that can affect the risk ratings while decision-makers assign ratings during the risk assessment process. The aim of this study is to help professionals who carry risk assessment exercises to measure risk in international construction projects. Also, to help decision-makers who are looking for the causes of variance in the risk ratings being assigned by different individuals. This research is a reminder for the industry professionals to think about the efficient usage of the Probability-Impact risk ratings and become aware of the factors that affect these ratings before their application.