• Title/Summary/Keyword: freight

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A Study on the Change of Hire Payment Method to Reduce the FFA Basis Risk (FFA 베이시스위험 축소를 위한 용선료 지급기준 변경의 타당성 검토)

  • Lee, Seung-Cheol;Yun, Heesung
    • Journal of Navigation and Port Research
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    • v.46 no.4
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    • pp.359-366
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    • 2022
  • While the Forward Freight Agreement (FFA) has emerged as an effective hedging tool since early 1990, the basis risk and cash flow distortions have been addressed as obstacles to the active use of FFAs. This research analyses the basis risk of FFAs and provides a feasible suggestion to reduce it. Basis risk is divided into timing basis, route basis, size basis, and low liquidity basis. The timing basis is defined as the difference between the physical hire, fixed on the specific contract date and the FFA settlement price, calculated by averaging spot rates for a certain period. Timing basis is considered the worst in eroding the effectiveness of FFAs. This paper suggests a change of hire payment criterion from contract date to 15-day moving average, as a means of mitigating the basis risk, and analyzed the effectiveness through historical simulation. The result revealed that the change is effective in mitigating the timing basis. This study delivers a meaningful implication to shipping practice in that the change of hire payment criterion mitigates the basis risk and eventually activates the use of FFAs in the future.

A Study on the Market Concentration Analysis of Korean Ocean-going Shipping Companies (국적외항선사의 시장집중도 분석)

  • Ha, Min-Ho
    • Journal of Navigation and Port Research
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    • v.46 no.4
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    • pp.351-358
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    • 2022
  • This study analyzed changes in the market concentration of Korean ocean-going shipping companies using shipping revenue based CR (Concentration Ratio), and HHI (Herfindahl - Hirschman Index) to examine the effects of the government's selection and concentration based the shipping reconstruction scheme. The results of this study showed that the market structure of the Korean shipping industry has changed from a competitive market to a rather concentrated market, as CR as well as HHI values have increased from 2019 to 2021. In particular, the market share of the deep-sea shipping lines has risen significantly compared to the intra-Asian short-sea shipping lines and the tramp carriers, implying that the Korean liner shipping market has become a monopoly, or highly concentrated oligopoly market. Compared to other shipping markets, the high rise in ocean freight rates (i.e. Asia-Europe America) was the leading cause of the increase in the revenues of the ocean-going shipping lines, and the increased fleet through preemptive government support has enabled them to achieve more revenues. As a result, it can be interpreted that the government's fleet expansion strategy has been more effective than expected, but it is too early to conclude if the market structure of the Korean ocean-going shipping companies has been strengthened.

Risk Spillover between Shipping Company's Stock Price and Marine Freight Index (해운선사 주가와 해상운임지수 사이의 위험 전이효과)

  • Choi Ki-Hong
    • Journal of Korea Port Economic Association
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    • v.39 no.1
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    • pp.115-129
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    • 2023
  • This study analyzed the risk spillover of BDI on shipping company stock prices through the Copula-CoVaR method based on daily data from January 4, 2010, to October 31, 2022. The main empirical analysis results and policy implications are as follows. First, copula results showed that there was a weak dependence between BDI and shipping company stock prices, and PAN, KOR, and YEN were selected as the most fitting model for dynamic Student-t copula, HMM was selected as the rotated Gumbel copula, and KSS was selected as the best model. Second, in the results of CoVaR, it was confirmed that the upside (downside) CoVaR was significantly different from the upside (downside) VaR in all shipping companies. This means that BDI has a significant risk spillover on shipping companies. In addition, as for the risk spillover, the downside risk is generally lower than the upside risk, so the downside and upside risk spillover were found to be asymmetrical. Therefore, policymakers should strengthen external risk supervision and establish differentiated policies suitable for domestic conditions to prevent systematic risks from BDI shocks. And investors should reflect external risks from BDI fluctuations in their investment decisions and construct optimal investment portfolios to avoid risks. On the other hand, investors propose that the investment portfolio should be adjusted in consideration of the asymmetric characteristics of up and down risks when making investment decisions.

Structural Analysis of the Governing Variables Affecting the Structural Strength Evaluation of the Lashing Bridges in Container Vessels (컨테이너선 라싱 브릿지 구조 강도 평가에 영향을 미치는 주요 변수의 구조해석)

  • Myung-Su Yi;Joo-Shin Park
    • Journal of the Korean Society of Marine Environment & Safety
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    • v.29 no.2
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    • pp.230-237
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    • 2023
  • Due to the COVID-19 pandemic and climate change, shortages of essential commodities and resources continue to occur globally. To address this problem, trade volume demand suddenly increased, driving up the freight rate of container ships sharply. The size of container vessels progressively increased from 1,500 TEU (twenty-foot equivalent unit) in the 1960s to 24,400 TEU in 2021. As the improvement of container loading capacity is closely related to the enlargement of the lashing bridge structure, it is necessary to design a structure effective for good container securing and safe under the various external loads that occur during voyage. Major classification societies have recently issued structural-analysis-based guidelines to evaluate the structural safety of lashing bridges, but their acceptance criteria and evaluation methods are different, causing confusion among engineers during design. In this study, the strength change characteristics are summarized by variations in the main variables (modeling range, opening consideration, mesh size) likely to affect the results. Based on this result, the authors propose a reasonable structural-analysis-based evaluation that is expected to serve as a reference in the next revision of classification standards.

Development and Assessment for Resilient Modulus Prediction Model of Railroad Trackbeds Based on Modulus Reduction Curve (탄성계수 감소곡선에 근거한 철도노반의 회복탄성계수 모델 개발 및 평가)

  • Park, Chul Soo;Hwang, Seon Keun;Choi, Chan Yong;Mok, Young Jin
    • KSCE Journal of Civil and Environmental Engineering Research
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    • v.29 no.2C
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    • pp.71-79
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    • 2009
  • This study is to develope the resilient modulus prediction model, which is the function of mean effective principal stress and axial strain, for three types of railroad trackbed materials such as crushed stone, weathered granite soil, and crushed-rock soil mixture. The model consists of the maximum Young's modulus and nonlinear values for higher strain, analogous to dynamic shear modulus. The maximum value is modeled by model parameters, $A_E$ and the power of mean effective principal stress, $n_E$. The nonlinear portion is represented by modified hyperbolic model, with the model parameters of reference strain, ${\varepsilon}_r$ and curvature coefficient, a. To assess the performance of the prediction models proposed herein, the elastic response of a test trackbed near PyeongTaek, Korea, was evaluated using a 3-D elastic multilayer computer program (GEOTRACK). The results were compared with measured elastic vertical displacement during the passages of freight and passenger trains at two locations, whose sub-ballasts were crushed stone and weathered granite soil, respectively. The calculated vertical displacements of the sub-ballasts are within the order of 0.6mm, and agree well with measured values. The prediction models are thus concluded to work properly in the preliminary investigation.

A Study on the Early Warning Model of Crude Oil Shipping Market Using Signal Approach (신호접근법에 의한 유조선 해운시장 위기 예측 연구)

  • Bong Keun Choi;Dong-Keun Ryoo
    • Journal of Navigation and Port Research
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    • v.47 no.3
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    • pp.167-173
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    • 2023
  • The manufacturing industry is the backbone of the Korean economy. Among them, the petrochemical industry is a strategic growth industry, which makes a profit through reexports based on eminent technology in South Korea which imports all of its crude oil. South Korea imports whole amount of crude oil, which is the raw material for many manufacturing industries, by sea transportation. Therefore, it must respond swiftly to a highly volatile tanker freight market. This study aimed to make an early warning model of crude oil shipping market using a signal approach. The crisis of crude oil shipping market is defined by BDTI. The overall leading index is made of 38 factors from macro economy, financial data, and shipping market data. Only leading correlation factors were chosen to be used for the overall leading index. The overall leading index had the highest correlation coefficient factor of 0.499 two months ago. It showed a significant correlation coefficient five months ago. The QPS value was 0.13, which was found to have high accuracy for crisis prediction. Furthermore, unlike other previous time series forecasting model studies, this study quantitatively approached the time lag between economic crisis and the crisis of the tanker ship market, providing workers and policy makers in the shipping industry with an framework for strategies that could effectively deal with the crisis.

Time series and deep learning prediction study Using container Throughput at Busan Port (부산항 컨테이너 물동량을 이용한 시계열 및 딥러닝 예측연구)

  • Seung-Pil Lee;Hwan-Seong Kim
    • Proceedings of the Korean Institute of Navigation and Port Research Conference
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    • 2022.06a
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    • pp.391-393
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    • 2022
  • In recent years, technologies forecasting demand based on deep learning and big data have accelerated the smartification of the field of e-commerce, logistics and distribution areas. In particular, ports, which are the center of global transportation networks and modern intelligent logistics, are rapidly responding to changes in the global economy and port environment caused by the 4th industrial revolution. Port traffic forecasting will have an important impact in various fields such as new port construction, port expansion, and terminal operation. Therefore, the purpose of this study is to compare the time series analysis and deep learning analysis, which are often used for port traffic prediction, and to derive a prediction model suitable for the future container prediction of Busan Port. In addition, external variables related to trade volume changes were selected as correlations and applied to the multivariate deep learning prediction model. As a result, it was found that the LSTM error was low in the single-variable prediction model using only Busan Port container freight volume, and the LSTM error was also low in the multivariate prediction model using external variables.

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Effect of Supply Chain Risk on Port Container Throughput: Focusing on the Case of Busan Port (공급망 리스크가 항만 컨테이너 물동량에 미치는 영향에 관한 연구: 부산항 사례를 중심으로)

  • Kim, Sung-Ki;Kim, Chan-Ho
    • Journal of Korea Port Economic Association
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    • v.39 no.2
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    • pp.25-39
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    • 2023
  • As the scope of supply chains expands globally, unpredictable risks continue to arise. The occurrence of these supply chain risks affects port cargo throughput and hinders port operation. In order to examine the impact of global supply chain risks on port container throughput, this study conducted an empirical analysis on the impact of variables such as the Global Supply Chain Pressure Index (GSCPI), Shanghai Container Freight Index (SCFI), Industrial Production Index, and Retail Sales Index on port traffic using the vector autoregressive(VAR) model. As a result of the analysis, the rise in GSCPI causes a short-term decrease in the throughput of Busan Port, but after a certain point, it acts as a factor increasing the throughput and affects it in the form of a wave. In addition, the industrial production index and the retail sales index were found to have no statistically significant effect on the throughput of Busan Port. In the case of SCFI, the effect was almost similar to that of GSCPI. The results of this study reveal how risks affect port cargo throughput in a situation where supply chain risks are gradually increasing, providing many implications for establishing port operation policies for future supply chain risks.

An Empirical Study on the Driving Force for Diffusion of Surrender B/L as an International Trade Payment Document (무역결제서류로서 Surrender B/L의 확산 동인에 관한 실증연구)

  • Hye-Young Joo;Byoung-Boo You
    • Korea Trade Review
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    • v.48 no.2
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    • pp.153-174
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    • 2023
  • Electronic bill of lading, Letter of Guarantee, Surrender B/L, Seaway Bill, etc. have been proposed as alternative tools to overcome the crisis of bill of lading, but the most useful of these is by far the Surrender B/L. However, since the Surrender B/L has various problems due to the absence of a legal basis, studies so far have been conducted focusing on these legal limitations or problems in use of the Surrender B/L. This study tried to empirically identify the factors that affect the spread of Surrender B/L by expanding this point of research view. A hierarchical regression analysis was conducted by acquiring 190 valid samples centered on member companies of the Korea International Freight Forwarders Association. In addition, the R program was used to diagnose the research data and analyze the degree of spread by region. As a result of the empirical analysis, it was found that the utilization of Surrender B/L increased due to the convenience and cost reduction effect of Surrender B/L and the apprenticeship training of forwarding companies. In addition, as a result of regional analysis, the spread of Surrender B/L was notable not only in neighboring regions but also even in areas far from Korea.

Analysis of the Association between Air Pollutant Distribution and Mobile Sources in Busan Using Spatial Analysis (공간 분석을 통한 부산광역시 대기오염물질의 분포와 이동오염원 간의 관련성 연구)

  • Jae-Hee Min;Byoung-Gwon Kim;Hyunji Ju;Na-Young Kim;Yong-Sik Hwang;Seungho Lee;Young-Seoub Hong
    • Journal of Environmental Health Sciences
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    • v.50 no.3
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    • pp.191-200
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    • 2024
  • Background: Busan is a rapidly industrializing city with many mixed residential and industrial areas. Fine dust emissions from mobile pollution sources such as ships and vehicles are particularly high in Busan. Objectives: This study analyzed the spatial distribution of air pollutants over the past three years and identified the impact of air pollutants through mobile source data in Busan. Methods: We obtained air pollutant data on fine particulate matter (PM10), ultrafine particulate matter (PM2.5), nitrogen dioxide (NO2), sulfurous acid gas (SO2), and ozone (O3) for the last three years (source: airkorea.or.kr) and analyzed the spatial distribution using SAS 9.4 and Surfer 23. For the mobile pollutant data, we used CCTV data from major intersections in Busan to identify truck and car traffic, and visualized traffic density with QGIS. Results: The analysis of the concentration of air pollutants over three years (2020~2022) showed that all were lower than the annual environmental standards with the exception of PM2.5. PM10 and PM2.5 were found to be highly concentrated in the western part of the area, while NO2 was high in the port area of Busan and SO2 was high in the western part of the area and near the new port of Busan. In the case of O3, it was high in the eastern part of the city. The traffic volume of freight vehicles by intersection was concentrated in the West Busan area, and the traffic volume for all cars was also confirmed to be concentrated at "Mandeok Intersection" located in the West Busan area. Conclusions: This study was conducted to determine the relationship between air pollutants emitted from motor vehicles and the distribution of air pollutants in Busan. The spatial distribution of PM10 and PM2.5 correlates with traffic volume, while high concentrations of SO2 and NO2 near the port are associated with ship emissions.