Proceedings of the 2015 Industrial and Systems Engineering Research Conference S. Cetinkaya and J. K. Ryan, eds. An Integrated Gray-Fuzzy Cause and Effect Approach to Determine the Most Significant Categories of Project Risks Amin Vafadarnikjoo Allameh Tabataba’i University, Tehran, Iran. Mohammadsadegh Mobin, Christian Salmon Western New England University, MA, USA. Nikbakhsh Javadian Mazandaran University of Science and Technology, Mazandaran, Iran. Abstract Identifying critical risks in projects has become a core step in project risk management process; however, the nature of this step can be complex and unstructured, suggesting a benefit in research towards prioritizing project risks on the basis of a cogent method. This paper presents a Gray Decision Making Trial and Evaluation Laboratory (GDEMATEL) method for prioritizing sources of project risk within a multi-criteria decision making (MCDM) framework. The framework categorizes sources of risk via the Project Management Institutes’ (PMI) Risk Breakdown Structure (RBS). For this study, project expert judgments and preferences are the source of knowledge about project risk. Uncertainty and variation between expert preferences are controlled by gray theory which converts linguistic preference collection terms into numerical intervals. Since the knowledge and experience of the experts are different, we consider the importance level of expert judgments in terms of triangular fuzzy numbers. Ultimately, a Gray Decision Making Trial and Evaluation Laboratory technique was applied to prioritize the project risks. Keywords Gray System Theory, DEMATEL, Project Risk Management, Fuzzy Set Theory Notations ⊗ Gray number  Lower bound of a gray number  Upper bound of a gray number Z Crisp value of a gray number T Total relation matrix D Sum of rows of the total relation matrix R Sum of columns of the total relation matrix W  p Fuzzy importance weight of expert p a  ୧୨ Aggregated fuzzy influence value of risk i on risk j a ୧୨ Aggregated crisp influence value of risk i on risk j a ୧୨ p Influence value of risk i on risk j by expert  1. Introduction Risk in projects can be defined as the chance of an event occurring that is likely to have a negative influence on project objectives, measured as a function of likelihood that some event will occur, and the consequence of that event if it does occur [1-4]. Aggregate project risk is simply the collective impact of all individual risks. In order to arrive at a strong and on time delivery of projects, risk management is a crucial practice. Risk categories provide a structure that enables a thorough process of systematically identifying individual sources of risk at a consistent detail. A Risk Breakdown Structure (RBS) lists categories and sub-categories where risk may arise for a typical project [5]. It also helps a risk manager to manage the risks efficiently and be familiar with sources which are recurring in a typical project. The RBS frequently illustrated in the PMI’s PMBOK Guide is depicted in Figure 1.