• Korean Journal of Construction Engineering and Management
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• v.21 no.2
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• pp.79-87
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• 2020

The Korean domestic construction management at risk (CMAR) market is in the process of completing the pilot project execution under the leadership of the Ministry of Land, Infrastructure and Transport as of December 2019. The government starts practicing CMAR an alternative delivery method widely in order to diversify delivery methods and enhance construction technology. The CMAR market is thus expected to grow. This study was conducted to improve CMAR firms' capability by developing self-assessment tools for them to evaluate current capability more effectively. As a result of defining standard core capability and additional elements categorized by project execution phase and management area, and performing evaluation from the CMAR project participants, it was found that the general project management capability in the pre-design and procurement phase and quality management area was lower compared to the construction phase and other areas. In addition, the capability of cost management area was lower in spite of its high importance. Communication and coordination, process optimization, and target values achievement were at the initial level of capability and continuous improvement was required.

• Journal of Navigation and Port Research
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• v.43 no.1
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• pp.72-78
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• 2019

The second-hand ship market provides immediate access to the freight market for shipping investors. When introducing second-hand vessels, the precise estimate of the price is crucial to the decision-making process because it directly affects the burden of capital cost to investors in the future. Previous studies on the second-hand market have mainly focused on the market efficiency. The number of papers on the estimation of second-hand vessel values is very limited. This study proposes an artificial neural network model that has not been attempted in previous studies. Six factors, freight, new-building price, orderbook, scrap price, age and vessel size, that affect the second-hand ship price were identified through literature review. The employed data is 366 real trading records of Panamax second-hand vessels reported to Clarkson between January 2016 and December 2018. Statistical filtering was carried out through correlation analysis and stepwise regression analysis, and three parameters, which are freight, age and size, were selected. Ten-fold cross validation was used to estimate the hyper-parameters of the artificial neural network model. The result of this study confirmed that the performance of the artificial neural network model is better than that of simple stepwise regression analysis. The application of the statistical verification process and artificial neural network model differentiates this paper from others. In addition, it is expected that a scientific model that satisfies both statistical rationality and accuracy of the results will make a contribution to real-life practices.