• Journal of Korea Multimedia Society
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• v.25 no.4
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• pp.559-567
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• 2022

The optimal shipping location is determined by measuring the volume and weights of cargo shipped to non-standard cargo carriers. Currently, workers manually measure cargo volume, but automate it to improve work inefficiency. In this paper, we proposed the method of a real-time volume calculation using LiDar sensor for automating cargo measurement of non-standard cargo. For this purpose, we utilized the statistical techniques for data preprocessing and volume calculation, also used Voxel Grid filter to light weighted of data which are appropriate in real-time calculation. We implemented the function of Normal vectors and Triangle Mesh to generate surfaces and Alpha Shapes algorithms to process 3D modeling.

• Journal of Korea Port Economic Association
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• v.37 no.1
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• pp.103-119
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• 2021

Ports in Korea have been increasing in terms of volume while they have performed functions and roles such as industrial ports in promoting industries of their hinterlands as well as commercial ports supporting imports and exports. Nevertheless, specialization degree is different from port to port by cargo type and the changes in cargo volume. This study aims to analyze the structural changes and the degree of concentration and specialization by cargo type and port between 2001 and 2020. Top 10 ports were analyzed in terms of traffic volume by categorizing liquid, dry, general cargo and containers. HHI(Herfindahl-Hirschman Index), LQ(Location Coefficient), and shift-share analysis were employed in order to identify the degree of concentration, specialization and changes in cargo volume by port and cargo type. As a result of the analysis, the degree of port concentration and specialization for each cargo of 4 categories have maintained a high level, and no significant difference were found in fluctuations over the past 20 years. As a result of calculating the flucation of cargo volume through the shift-share analysis, the growth rate of liquid cargo was high in Yeosu Gwangyang Port, Pyeongtaek Dangjin Port in dry cargo, and Busan Port in general cargo and container ports. The result implies that it is not expected that the structural changes including degree of cargo concentration, specialization and relative fluctuation of cargo volume is significant in Korean ports in the future since the effects of economies of scale and clustering were achieved to the great degree.

• Journal of the Korea Safety Management & Science
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• v.25 no.2
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• pp.91-97
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• 2023

Ensuring the safe arrival of delivery cargo at its intended destination is of utmost importance. Truck drivers play a crucial role in guaranteeing the secure delivery of cargo without any mishaps. However, there are various factors that may lead to delayed arrival of trucks at their destination, such as late departures or prolonged loading operations. The timely departure of cargo transportation is contingent upon several variables, including the driver's experience, cargo volume, and loading time. If the transportation commencement is delayed, it may increase the risk of accidents due to an elevated operating speed. Consequently, we conducted a study to investigate the correlation between cargo loading time, cargo volume, driving experience, and the likelihood of accidents. Our findings indicate that both cargo volume and driver experience can impact the likelihood of vehicle accidents. Furthermore, all factors can have an interactive effect on the occurrence of accidents. However, extending the loading time may mitigate the impact on the likelihood of accidents.

• Journal of Fisheries and Marine Sciences Education
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• v.26 no.1
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• pp.49-58
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• 2014

Variability factors of transship cargo in the container transportation market analysis short term factors. In the past, studies on the factor of variability in container cargo volume have focused on long term volume forecast and increase in investment and competitiveness from strategic perspectives. Unlike previous studies, this paper analyzes factors of variability in transshipment volume rapidly varying in short term and seeks measures. Since it was identified that transshipment volume depends on vessel operation cost and port volume in long term but effectively on special strategies launched by port authorities in short term, the port authority experienced rapid drop in volume should continue to observe strategies of competition ports and to make use of strategies seeking appropriate countermeasures.

• Journal of the Korean Society for Aviation and Aeronautics
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• v.32 no.2
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• pp.112-123
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• 2024

Responding to rapid changes of global supply chain and fast increasing air cargo volume and demand for e-commerce market, this paper researched the development plans for regional airport specially focused on air cargo logostics through policy research. According to this research, political implications and development plans for Cheong Ju airport (CJJ) to become a part of global supply chain, a regional air cargo hub. Firstly, it is necessary to increase the length of the existing runway from 2,744m to 3,200m or to develop 3^rd runway only for a civil aircraft use. Secondly, it is inevitable to develop new air cargo terminal to handle and export such high value-added products as semi-conductor or rechargeable battery through airport. In addition, facing re-shoring trends among global supply chain, CJJ can increase its air cargo volume and also provide feeder service to Incheon airport, inducing global distribution center near airport site.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.43 no.4
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• pp.15-22
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• 2020

Economic indicators are a factor that affects air cargo volume. This study analyzes the different factors affecting air cargo volume by each Chinese cities according to the main characteristics. The purpose of this study is to help companies related to China, airlines, and other stakeholders predict and prepare for the fluctuations in air cargo volume and make optimal decisions. To this end, 20 economic data were used, and the entire data was reduced to 5 dimensions through factor analysis to build a dataset necessary and evaluated the influencing factors by multi regression. The result shows that Macro-Economic Indicators, Production/Service indicators are significant for every cities and Chinese manufacture/Customer indicators, Korean manufacture/Oil Price indicators, Trade/Current indicators are significant for each other city. All adjusted R2 values are high enough to explain our model and the result showed excellent performance in terms of analyzing the different factors which affects air cargo volume. If companies that are currently doing business with China can identify factors affecting China's cargo volume, they can be flexible in response to changes in plans such as plans to enter China, production plans and inventory management, and marketing strategies, which can be of great help in terms of corporate operations.

• Korea Trade Review
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• v.47 no.6
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• pp.291-305
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• 2022

In this study, the volume of Pohang Port was predicted. All cargo of Pohang port, iron ore, steel, and bituminous coals were selected as prediction targets. SARIMA, Prophet, and Neural Prophet were used as analysis methods. The predictive power of each model was verified, and a predictive model with high performance was used to predict the volume of goods in Pohang port. As a result of the analysis, it was found that Neural Prophet showed the highest performance in all predictive power. As a result of predicting the future volume of goods until August 2027 using Neural Prophet, it was found that the volume of all items in Pohang port was decreasing. In particular, it was analyzed that the decline in steel cargo was steep. In order to increase the volume of cargo at Pohang port, it is necessary to diversify the cargo handled at Pohang port and check the policy of increasing the volume of cargo.

• Journal of Navigation and Port Research
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• v.40 no.2
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• pp.57-65
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• 2016

The port throughput situation has changed since the 2008 financial crisis in the US. Therefore, we studied the situation, accurately estimating port traffic of Korean port after the 2008 financial crisis. We ensured the proper port facilities in response to changes in port traffic. In the results of regression analysis, Korean GDP and the real effective exchange rate of Korean Won were found to increase the container throughput in Korean and Busan port, as well as trade volume with China. Also, the real effective exchange rate of Korean Won was found to increase the port transshipment cargo volume. Based on the ARIMA models, we forecasted port throughput and port transshipment cargo volume for the next six years (72 months), from 2015 to 2020. As a result, port throughput of Korean and Busan ports was forecasted by increasing annual the average from about 3.5% to 3.9%, and transshipment cargo volume was forecasted by increasing the annual average about 4.5%.

• Korea Trade Review
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• v.47 no.4
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• pp.197-213
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• 2022

This study aims to investigate the relationship between cargo volume and logistics performance index published by World Bank which indicate countries' logistics performance. In this study, the results were derived through panel regression analysis consisting of variables such as gross domestic product, geographical distance, population, and LPI using container export/import volume and bulk export/import volume as dependent variables. As a result of the empirical analysis, it was found that Korea's container volume was affected by the overall level of logistics, in particular, was deeply related to the logistics infrastructure, while bulk volume was not related to the logistics level or was less influential.

• Journal of Fisheries and Marine Sciences Education
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• v.27 no.1
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• pp.262-272
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• 2015

The aim of this study is to analysis factors that determine the competitiveness of container ports using the KJ and AHP methods. For this, 54 detailed attributing factors were identified both by previous studies and port users. 24 attributing factors were identified by a group of port experts. also, These were grouped 18 detailed attributing factors into 6 attributing factors by a group of port experts using the KJ method. These were made into a model of hierarchical structure with 3 levels, taking 1 goal factor, 6 evaluation factors and 18 detailed evaluation factors. The collected date of questionnaires were analyzed by a group of port experts using the AHP method. The analysis result of the evaluation factors in container port shows that port cargo volume is the most important factor, followed by port location, port cost, port service, port facility and port management. The analysis results of detailed evaluation factors in container port shows that import and export cargo volume is the most important factor, followed by transshipment cargo volume, distance from main trunk, cargo handling cost, distance from the point of importing and exporting, speediness of cargo handling, stability of cargo handling, vessel/cargo cost in port entry and leaving, punctuality in port entry and leaving, number and length of berth, collateral service cost, terminal area, hinterland accessibility, ability of terminal operation company, front depth of berth, etc.