Risk Event Management for International Construction Project Using Case-Based Learning

Abstract

International construction projects normally involve high level of risks because of the differences in construction practices, working conditions, cultures, and political, legal, and economic conditions between domestic and overseas markets. The risks (e.g., Knowns, Known-unknowns, and Unknown-unknowns) from uncertainties of international construction projects cause risk events during construction execution, which arise losses in project cost and schedule. To manage the risks from their projects uncertainties, the construction contractors have introduced the risk management with its principles and framework to their projects for its success. Based on the risk management process including risk identification, analysis, and evaluation, the construction contractors propose a financial and other risk treatments such as removing or avoiding the identified risks in planning phase, planning response strategies for predictable risk events in advance, and estimating a contingency covering potentially required changes (i.e., contingency reserve).

However, the risk management process based approach still has limitations for managing risk events of construction execution. In other words, the current practices of risk management cannot cover the entire risk events, and unexpected risk events still remain in construction execution because of a complexity of the interrelationship between risks, a limitation of risk identification, and difficulties in predicting risk value. As a result, the estimated contingency reserve and planned response strategy cover only predictable risk events. For instance, despite its role and importance, the contingency for unplanned changes (i.e., management reserve) is often estimated as a percentage of the estimated project cost baseline (i.e., deterministic point estimation). In addition, the response strategies for recovering risk events are still determined based on the experiences of contractors when the unpredictable risk events occur, which has no theoretical and scientific foundation. These weaknesses have raised the need for a more robust and systematic approach to manage the risk events in international construction projects.

As an effort to address these challenging issues, this research proposes a risk event management framework for international construction projects. In particular, a management reserve estimation method and a response strategy decision-making support model are developed using pertinent or similar instances with an application of case-based learning. It starts by analyzing backgrounds on risk management of international construction projects and methodologies applied in this research for developing the case-based learning. Then, variables are selected by considering uncertainties of international construction projects. Based on the extracted variables, the management reserve estimation method and response strategy decision support model are developed by applying the Case-Based Reasoning (CBR) for retrieving pertinent cases. In addition, this research also adopts Genetic Algorithm (GA) and Analytic Hierarchy Process (AHP) for variable weighting and as a result, improves the performance of CBR classifications. Finally, to clarify the developed management reserve estimation method and response strategy decision support model, case studies are conducted to validate retrieval performance of the proposed methods and test its applicability in international construction projects.

This research contributes to a risk event management with a consideration of its unpredictable characteristic until realized as outcomes. Specially, the management reserve is estimated as a budget set aside in addition to the specific risk provision (i.e., the contingency reserve) to achieve the project objectives in the face of as yet unidentified risks. With this, the response strategies and solutions can support decision-making of contractors for determining an appropriate and immediate recovery plan when the risk events are caused. As a result, this research enables construction contractors to cope with emergent risk events during construction execution, and then minimizes a likelihood of project cost increase and losses in time of international construction projects. Academically, this research proposes a more robust, systematic, and suitable approach for estimating the management reserve and developing case-based decision-support model for managing international construction risk events.