Abstract:
The shortcomings of current project risk management processes, tools and techniques, the construction industry still suffers from poor project performance. The increasingly complex and dynamic nature of projects, coupled with new procurement methods, the tendency to use risk quantification and risk response planning amongst the project team members. However, communication of construction project risks is poor, incomplete, and inconsistent throughout the construction supply chain. Project team members adopt different terminologies for describing risks, use different methods and techniques for dealing with risk analysis and management, which producing different and conflicting results, leads to poor project performance. Consequently, project members do not adequately deal with problems resulting from decisions taken elsewhere in the chain. The focus of quantitative risk analysis based on estimating probabilities and probability distributions for time and cost risk analysis, do not encourage project participants to in-depth understanding of the underlying elements and structures which constitute project risk. It does not allow the risks, problems, remedial measures, and lessons learned from previous projects to be captured and re-used when developing new projects. A common methodology for describing risks based on a hierarchical-risk breakdown structure has been identified and it provides the basis for developing a sharable knowledge-driven approach to risk management. A need for better knowledge through research is present in many of the above areas, but what seems to be especially important is the present lack of frameworks for decision support within supply chain risk. The work presented in this research is aimed to Explore the Risks Associated with Construction Supply Chain and identify a continuous risk management framework capable of enhancing the probability of project success. And also to lead the industry to establish construction supply chain risk management practices that are self-sustaining and continuously improving, effective continuous knowledge capture, re-use and learning process.
