• Journal of Korean Port Research
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• v.13 no.2
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• pp.313-322
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• 1999

Pusan the principal port of South Korea, has opened its door since 1876. Currently, the four-stage port construction project is under way to handle ever-growing marine transportation volume. While the port unloading capabilities are increasing the infrastructure to deal with all the transportation volume failed to catch up with them. Accordingly the city had to suffer from worst traffic congestion on due to the increasing container traffic volume causing logistical costs to rise. This study was designed to inspect the enforcement of infrastructure construction plan and suggest systematical and effective ways to improve the plan. The study focused on :\circled1The decision-making procedure, \circled2Financial resource for the plan, \circled3Effectiveness of the project enforcement, and \circled4Who will be in charge of the project. As a result from the study, these followings were suggested to improve the plan. First, Pusan Port Infrastructure consisting of (Inter-city Free way, Belt Highway and Outer Highway) should be immediately legally-regulation project. Second, the method to finance the project should be deter-mined and investment consultation among the central government the city government and private sector should be also made. Measures to make the central government budget allocation for the project mandatory should be discussed. Third, Effectiveness of the project can be doubled by gradually or partialyl opening the routes based on long-term or short-term operating plans. Fourth, The organizer of the project should be appointed, or a special task-force team in charge of the plan can be formed.

• Journal of Navigation and Port Research
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• v.36 no.1
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• pp.59-67
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• 2012

This study shows how the logistics capability of container terminal impacts with service quality and customer response. Result of this study would be utilized in marketing strategy for container terminal. Sample design is based on shipping companies which are registered in Korea Shipowners' Association and Korea Shipmanagers' Association from Dec. 5 through 23 in 2011. And total of 243 questionnaires are collected through a personal visit. The result of empirical analysis, management capability of logistics capability factor which have an effect on service quality and customer response is the biggest influence to them. At the same time, Sympathy of service quality factor which have an effect on customer response is the biggest influence to it. Therefore, customers' requirements would be analyzed specifically when loading and unloading plans are devised in container terminal, and based on customers' requirements, best customer service would be provided.

• Journal of Korea Port Economic Association
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• v.37 no.4
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• pp.33-40
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• 2021

Currently, the shipping and port industries are implementing strategies to improve port processing capabilities through the expansion and efficient operation of port logistics resources to survive fierce competition with rapidly changing trends. The calculation of the port's processing capacity is determined by the loading and unloading equipment installed at the dock, and the port's processing capacity can be improved through various methods, such as additional deployment of logistics resources or efficient operation of resources in use. However, it is difficult to expect an improvement effect in a short period of time because the additional deployment of logistics resources is clearly limited in time is clear. Therefore, it is a feasible way to find an efficient operation method for resources being used to improve processing capacity. Domestic ports are also actively promoting informatization and digitalization with the development of the 4th industrial revolution technology. However, the calculation of the number of Y/T (Yard Tractor) assignments in the current unloading process depends on expert experience, and related previous studies also focus on the allocations of Y/T or Calculation of the total number of Y/T required. Therefore, this study analyzed the factors affecting the number of Y/T allocations using the loading and unloading information of incoming ships, and based on this, cluster analysis, regression analysis, and deep neural network(DNN) model were used.