• Proceedings of the Korean Institute of Navigation and Port Research Conference
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• 2003.05a
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• pp.115-120
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• 2003

This study aims at calculating berth length required of the given volume of containers. For this, unlike previous studies assuming 300,000 TEU per berth as the capacity of a berth, this study attempts to apply more realistic situation such as the distribution of vessel size, lifts per vessel, berth time by vessel size, and average berth occupancy ratio. the result are compared with that of Pusan New port planning.

• Journal of Korea Port Economic Association
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• v.32 no.2
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• pp.137-156
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• 2016

This study analyzes the optimal service levels of exclusive container terminals in terms of the optimal berth occupancy rate and the ships' waiting ratios, based on the number of berths. We develop a simulation model using berth throughput data from pier P, Busan New Port, a representative port in Korea, and apply the simulation results to different numbers of berths. In addition to the above results, we analyze the financial data and costs of delayed ships and delayed cargoes for the past three years from the viewpoints of the terminal operation company (TOC), shipping companies, and shippers to identify the optimal service level for berth occupancy rates that generate the highest net profit. The results show that the optimal levels in the container terminal are a 63.4% berth occupancy rate and 10.6% ship waiting ratio in berth 4,66.0% and 9.6% in berth 5, and 69.0% and 8.5% in berth 6. However, the results of the 2013 study by the Ministry of Maritime Affairs and Fisheries showed significantly different optimal service levels: a 57.1% berth occupancy rate and 7.4% ship waiting ratio in berth 4; 63.4% and 6.6% in berth 5; and 66.6% and 5.6% in berth 6. This suggests that optimal service level could change depending on when the analysis is performed. In other words, factors affecting the optimal service levels include exchange rates, revenue, cost per TEU, inventory cost per TEU, and the oil price. Thus, optimal service levels can never be fixed. Therefore, the optimal service levels for container terminals need to be able to change relatively quickly, depending on factors such as fluctuations in the economy, the oil price, and exchange rates.

• Journal of Navigation and Port Research
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• v.41 no.3
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• pp.137-148
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• 2017

Port service level is a metric of competitiveness among ports for the operating/managing bodies such as the terminal operation company (TOC), Port Authority, or the government, and is used as an important indicator for shipping companies and freight haulers when selecting a port. Considering the importance of metrics, we developed software to objectively define and manage six important service indicators exclusive to container and bulk terminals including: berth occupancy rate, ship's waiting ratio, berth throughput, number of berths, average number of vessels waiting, and average waiting time. We computed the six service indicators utilizing berth 1 through berth 5 in the container terminals and berth 1 through berth 4 in the bulk terminals. The software model allows easy computation of expected ship's waiting ratio over berth occupancy rate, berth throughput, counts of berth, average number of vessels waiting and average waiting time. Further, the software allows prediction of yearly throughput by utilizing a ship's waiting ratio and other productivity indicators and making calculations based on arrival patterns of ship traffic. As a result, a TOC is able to make strategic decisions on the trade-offs in the optimal operating level of the facility with better predictors of the service factors (ship's waiting ratio) and productivity factors (yearly throughput). Successful implementation of the software would attract more shipping companies and shippers and maximize TOC profits.

• Journal of Navigation and Port Research
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• v.27 no.2
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• pp.179-184
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• 2003

In order to mitigate the overcapacity of Busan port, Busan new port has been developed as transshipment port which is capable of handling 8,000 TEU containership. Generally, design of transshipment port has to reflect the capacity of feeder because both mother vessels and feeders enter the planned port at the same time. However, the existing plan of Busan new port capacity needs to be reexamined since the adopted capacity of each berth at new port, 300,000 TEU, does not seem to be enough to handle both mother vessels and feeders. Therefore, in this study we calculated the required number of berth and berth length by considering cargo handling capacity in terms of the ship size and this study makes some implications in relation with the terminal development plan.

• Journal of Navigation and Port Research
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• v.40 no.1
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• pp.35-41
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• 2016

Port congestion has been recognized as one of the critical factors for port service competitiveness and port selection criteria. However, congestion ratio, the congestion index currently used by Korea, plays a very limited role in shipping companies' and shippers' selection of port and port authorities' decision making regarding port management and development. This is mainly due to the fact that this ratio is only calculated as the ratio of the number of vessels by each port. Therefore, this study aims to measure service level related to vessel entry and departure in Korea ports by evaluating waiting ratio(WR) according to terminals and vessel types. The results demonstrate that the waiting ratio of containerships and non-containerships is less than 4% and 15% respectively, which satisfies the reasonable level suggested by the UNCTAD and OECD. Port of Pohang is revealed to have the highest WR of 57% and among the terminals, No. 1 Terminal of the Shinhang area has the highest WR. In terms of ship types, WR of Steel Product Carrier is highest, followed by General Cargo Ship and Bulk Carrier at the Pohang Shinhang area. In addition to WR, berth occupancy ratio as well as the number and time of waiting vessels can be utilized to evaluate service level by ports and terminals from port users' perspective, and furthermore, to improve the port management and development policy for port managers or authorities.

• Journal of Korea Port Economic Association
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• v.34 no.2
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• pp.69-82
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• 2018

The number of ships serviced at the container terminals in Busan is increasing by 2.9% per year. In spite of the increase in calling ships, there are no official records of waiting rate by the port authority. This study attempts to compare the theoretical ship waiting ratio and actual ship waiting ratio. The actual ship waiting ratio of container terminals is acquired from the 2014 to 2016 data of PORT-MIS and Terminal Operating System (TOS). Furthermore, methods and procedures to measure the actual ship's waiting rate of container terminal are proposed for ongoing measurement. In drawing the theoretical ship waiting ratio, the queuing theory is applied after deploying the ship arrival probability distribution and ship service probability distribution by the Chi Square method. As a result, the total number of ships waiting in a terminal for three years was 587, the average monthly service time and the average waiting time was 13.8 hours and 17.1 hours, respectively, and the monthly number of waiting ships was 16.3. Meanwhile, according to the queuing theory with multi servers, the ship waiting ratio is 31.1% on a 70% berth occupancy ratio. The reason behind the huge gap is the congested sailing in the peak days of the week, such as Sunday, Tuesday, and Wednesday. In addition, the number of waiting ships recorded on Sundays was twice as much as the average number of waiting ships.

• Journal of Korea Port Economic Association
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• v.26 no.3
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• pp.198-220
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• 2010

This paper investigate the problems of standard container port handling capacity in establishing national port development plan in Korea. Considering container port developing, it's not easy to adopt container port service quality parameters such as lay time constraint of very large container ships by using the standard guideline of container port handling capacity. A simple methodology that connects vessel waiting to service time(w/s) and berth occupancy to costs has been used to evaluate the performance of a container terminal. But the total handling capacity have to be calculated by the performance of the handling system and number of equipments and layout of terminal by using computer simulation that represents of reality events needs to be performed by probabilistic techniques. A simulation model of estimation of container terminal capacity is introduced in order to establish a hub terminal for very large container ships that focus the port's quality of service and also suggest as tool for policy maker to justify a required port investment.