This study presents a comprehensive framework for Project Risk Management (PRM), tailored specifically for Engineering, Procurement, and Construction (EPC) projects. Addressing gaps in traditional risk assessment methodologies, the proposed approach integrates advanced techniques for risk identification, analysis, and evaluation based on risk characteristics. A three-stage framework is proposed utilizing the Delphi method for risk identification and contextualization of risks, the risk analysis stage employs the Fuzzy Level-Based Weight Assessment (F-LBWA) method to achieve fuzzy weights for risk characteristics which the risks will be evaluated by. The final evaluation stage uses the Fuzzy Combined Compromise Solution (F-CoCoSo) method to rank risks, categorizing them as threats, opportunities, or hybrids. A case study of an EPC project demonstrates the framework’s practical application, highlighting construction-phase risks as the most critical threats (negative risks) while also emphasizing opportunities (positive risks) which can be exploited. By incorporating fuzzy logic and innovative Multi-Criteria Decision-Making (MCDM) methods, the framework provides a flexible and robust tool for modern PRM.

This study investigates the critical role of information technology integration in enhancing project risk management, specifically examining the mediating effect of risk identification effectiveness. Based on a quantitative approach, the study collected data from 173 respondents working in the construction, engineering, and telecommunication sectors using a comprehensive questionnaire. We employed Smart PLS-SEM for data analysis to test the study hypotheses. Our findings reveal that IT integration significantly and positively influences both risk identification effectiveness and overall project risk management. Importantly, the study confirms the mediating role of risk identification effectiveness, indicating that IT's contribution to successful project risk management is significantly enhanced when it empowers teams to identify potential risks early and accurately. These findings indicate the strategic importance for organizations in these sectors to prioritize investments in IT solutions that not only streamline project management processes but also specifically enhance risk identification capabilities. Discussion and conclusion were depicted at the end of work.

Risk response planning is a widely concerned issue. Project managers usually struggle to control different kinds of risks. In project risk management, after evaluating risks, the final process relates to choosing desirable responses to the risks. In this paper, a comprehensive framework confronts the issue in three main phases. In the first phase, all the risks, responses and their relations in a geothermal drilling project are detected. These relations imply there are inner dependent and outer dependent relations. In the second phase, ANP, DEMATEL and fuzzy theory play important roles in weighting risks and responses. In the third phase, to enable a more realistic solution, a zero-one integer programming reflects a budget constraint and other required constraints. After obtaining the optimal responses, the effect of budget is analyzed. In addition, the influences of risks on each other are discussed more deeply. Collectively, this study offers a new perspective on how to handle project risks and choose their responses

Risk management plays an important role on the success of the any project. There are several techniques, which are available to help different phases of risk management process. This paper presents a survey to identify the necessary tools, which are mostly implemented and related to the success of any project management, and more specifically with effective project risk management. The survey is based on a questionnaire designed to a sample of project managers from the construction industries. The response data was studied to determine which tools are more used in the organizations, which could yield a better project management performance.