“High risk high return” is a general rule in the overall industry; however, high-risk projects in the construction industry frequently fail to yield a high return. In order to achieve a sustainable business in the international construction market, contractors require an average to high return yield under high-risk conditions. This study aims to reveal what risk factors and risk management performance enables high-risk projects to yield high returns. The study investigated 124 international construction projects by Korean contractors and classified them into four groups: high-risk high-return (HH), high-risk low-return (HL), low-risk high-return (LH), and low-risk low-return (LL). The study found that risk assessment accuracy was the most important trigger in discriminating between high return projects (HH, LH) and low return projects (HL, LL), whereas risk mitigation performance showed little difference between high return and low return projects. In addition, the contingency amount did not significantly affect project return in HL, LH, and LL projects, but HH projects showed a positive relation between contingency and predicted risk amount. This article contributes to recognizing the differences between high return and low return projects and provides insights for practitioners into the relation between risk management performance and high returns in different risk conditions.
Recently, The importance of modular construction method has increased by market environmental change.However, it's application in the actual project is restricted due to the lack of understanding of modularization and the absence of utilization system. To overcome this problem, this study propose the decision-making model for selecting modular or conventional (stick-built) construction method at early stage. First the needs of modular method in plant project is derived and the benefits and barriers of modular construction are analyzed through literature review.Based on this analysis, 6 decision-making factors covered project and modular characteristics are derived and the decision-making model is developed. Finally, 12 actual overseas project cases is evaluated by this model for verifying its applicability. This proposed model can provide the guideline to select the construction method in early stage for successful execution of plant project.
Recently, Official Development Assistance (ODA) projects are increasing. Since ODA projects are financially stable, engineering companies planning to enter the international construction market need to make ODA projects as a first step. Engineering ODA project evaluates bidders by Quality Cost Based Selection (QCBS) method. Under the QCBS, companies make up for their lack of capacity through collaboration. Therefore, collaboration network information is required for winning. In this study, Social Network Analysis (SNA) is performed using the bidding information of socialbase, road, and water sector provided by World Bank (WB) for Vietnam ODA projects. The objectives of this study is to identify the network characteristics of the three sectors with the network shape and the density calculated through SNA, and to identify the main player by degree centrality and betweenness centrality, and to suggest an appropriate strategy. This is helpful information for decision makers when deciding whether to go overseas or not.
In recent decades, market uncertainties such as unpredicted economic recessions and expansions have significantly affected to the international construction market. These uncertainties arise simultaneously either at the country level or more broadly and traditional project-based risk management has limited to manage a contractor' profit. From the perspective of managing the market uncertainties, therefore, this study proposes country portfolio model that provides an optimized country portfolio solution through considering on the market outlook, country risk and expected profitability. These are evaluated by country-specific data related construction market and actual project performance data using monte-carlo simulation and genetic algorism. It is expected that the proposed country portfolio model will support to decide better decision about entering new international construction market by giving the ideal country portfolio considering market uncertainties.
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