• Journal of the Korean Society of Marine Environment & Safety
• /
• v.16 no.1
• /
• pp.81-91
• /
• 2010

IMO(International Maritime Organization) and the Shipping World rave complied with various kinds of international regulations for maritime safety and marine environmental protection, but the main reason of maritime accidents is that developing countries cannot implement maritime safety related regulations. Although Korea has been a member of the "A group" council of IMO, maritime technology transfer records of Korea are not good. To promote the project of official development assistance in Korea, it is required to select the technology which has a high degree of importance in the fields of maritime safety and has a high degree of demand on the transfer to developing countries, and to concentrate on the selected technology. So, it is necessary to draw valuation factors for maritime safety technology and to decide the priority in order among maritime safety technologies on the basis of valuation factors. Because the weights which show the degree of importance among valuation factors are different from factor to factor, interdependent relationship between factors should be considered on evaluation. In this study, the valuation factors were divided into three groups as the maturity of maritime safety technology, the promotion probability of projects and the degree of importance of technology, and the detailed factors of each group were drawn. A model which used Fuzzy AHP and limiting probability to consider the weights of importance and correlation among valuation factors was developed. To adopt this model, nine types of maritime safety technology in the field of maritime safety information were selected and points were scored for each technology through evaluation. In conclusion, first, ENC related technology was scored to be the highest as 0.0139. Second, the point of ship monitoring technology was scored as 0.0133. Last, oil spill response technology was scored as 0.0132.

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

• Information Systems Review
• /
• v.5 no.1
• /
• pp.1-18
• /
• 2003

Many organizations experience that the value they gained from IT (information technology) investment is lower than they expected prior to the actual implementation of a system - the value gap between expected value and realized value from IT. Research on the barriers to the expectation and realization is of high importance both in practice and in IS research. This study analyzed such barriers observed in three companies that have adopted such IT systems as Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Customer Relationship Management (CRM) systems each. From analyses of the three companies we specifically identified eight types of barriers: barriers related to industry, organization, knowledge, resource, usage, competence, product, and safety. Common barriers among the three cases were classified into six types, e.g. lack of strategic mind-set, improper organizational structure, lack of human resource, etc. We expect that the results help managers in IS investment to minimize the valuation gap and maximize realized values.