• Journal of Korea Trade
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• 제27권3호
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• pp.119-146
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• 2023

Purpose - As the severity of air pollution caused by the shipping industry is becoming evident, port authorities have started making efforts to reduce air pollutants. Considering the limitations of the currently implemented emission-control area (ECA) and vessel-speed reduction program (VSRP), which are narrow in the designation range and navigation behavior of ships, this study proposes an emission-control route (ECR) that can complement the aforementioned two environmental policies. Design/methodology - This study was conducted on Korea-China trade service routes (ports of call) of regular liners. This study employed vessel-specific data, which is from an automatic identification system (AIS), for 1,728 maritime transportations performed by 387 container vessels during one year (July 1, 2021, to June 30, 2022). Performing a scenario analysis, this study analyzed the effectiveness of reduced air-pollutant emissions. Findings - This study found that the implementation of ECRs could increase average voyage time by 12.38%-25.28% but reduced air-pollutant emissions by 29.02%-43.54%. Additionally, the increase in average voyage times reduces the anchorage time of ships outside ports, providing an incentive for ship operators to voluntarily participate in compliance with regulations, thereby contributing to the establishment of a virtuous cycle of air-environmental policies related to ships. Originality/value - This study aims to verify the policy effectiveness by designing an ECR scope for liner trade routes between Korea and China. Therefore, originality and the value of this study includes conceptualizing the ECR system, analyzing its environmental performance, and exploring new policies that can be implemented while complementing existing policies.

• 한국항해항만학회지
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• 제47권3호
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• pp.167-173
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• 2023

한국 경제에 근간이 되는 산업은 제조업이고, 그중 석유화학산업은 전량 원유를 수입하여 우리나라의 기술력으로 가공하여 재수출하는 전략적 성장 산업이다. 수많은 제조업의 원료가 되는 원유를 전량 해상운송을 통해 수입하는 우리나라는 변동성이 심한 유조선 운임 시장에 대해 기민하게 대응해야 한다. 유조선 운임 시장의 위기는 관련 해운회사의 위기에서 끝나지 않고 원유를 사용하는 산업에서부터 국민의 생활까지 영향을 미칠 수 있으므로, 본 연구에서 신호접근법을 활용한 조기경보모형을 제시했다. BDTI 운임지수를 활용하여 유조선 해운시장 위기를 정의하고, 38개의 거시경제, 금융, 원자재 지표 그리고 해운시장 데이터를 활용해 시차상관관계를 분석하여 유조선 해운시장 위기에 선행적으로 반응하는 종합선행지수를 도출했다. 연구 결과, 종합선행지수는 두 달 전 가장 높은 0.499의 시차상관계수 값을 가졌으며, 5개월 전부터 유의미한 상관계수 값을 나타냈다. QPS 값은 0.13으로 위기 예측에 대해 높은 정확성을 지니는 것으로 검증됐다. 더불어 기존의 다른 시계열 예측모형 연구들과 달리 본 연구는 경제 위기와 유조선 해운시장의 위기 간의 시차를 계량적으로 접근하여, 관련 해운산업 종사자들과 정책 입안자들에게 위기에 효과적으로 대처할 수 있는 전략의 기틀을 제공함에 의의가 있다.

• 해양환경안전학회:학술대회논문집
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• 해양환경안전학회 2017년도 공동학술발표회
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• pp.247-247
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• 2017

• 한국항해항만학회지
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• 제48권2호
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• pp.109-115
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• 2024

To develop a shipping company insolvency prediction model, we sampled shipping companies that closed between 2005 and 2023. In addition, a closed company and a normal company with similar asset size were selected as a paired sample. For this study, data of a total of 82 companies, including 42 closed companies and 42 general companies, were obtained. These data were randomly divided into a training set (2/3 of data) and a testing set (1/3 of data). Training data were used to develop the model while test data were used to measure the accuracy of the model. In this study, a prediction model for Korean shipping insolvency was developed using financial ratio variables frequently used in previous studies. First, using the LASSO technique, main variables out of 24 independent variables were reduced to 9. Next, we set insolvent companies to 1 and normal companies to 0 and fitted logistic regression, LDA and QDA model. As a result, the accuracy of the prediction model was 82.14% for the QDA model, 78.57% for the logistic regression model, and 75.00% for the LDA model. In addition, variables 'Current ratio', 'Interest expenses to sales', 'Total assets turnover', and 'Operating income to sales' were analyzed as major variables affecting corporate insolvency.

• 한국항해항만학회지
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• 제48권3호
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• pp.206-213
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• 2024

본 연구는 지정학적 위기와 해운기업 주식가격 변동성의 인과관계를 분석하였다. 해운산업은 국가간의 교역에 의해서 수요가 파생되는 국제성을 가지기 때문에, 여러 가지 종류의 불확실성과 리스크에 직면하고 있다. 이에 본 연구에서는 최근 러시아-우크라이나 전쟁 및 이스라엘-하마스 전쟁 등으로 부상하고 있는 지정학적 위기가 해운산업에 미치는 영향을 분석하고자 한다. 특히, 지정학적 불확실성이 해운기업의 주식가격 변동성에 미치는 영향에 대해서 분석함으로서 이에 대한 시사점을 제공하고자 한다. 2000~2023년 기간 동안 한국거래소에 상장된 해운기업 5개사의 주식가격 변동성과 지정학적 위기 지수의 관계를 벡터자기회귀모형 기반의 인과성을 검정한 결과, 다음과 같은 결론이 도출되었다. 첫째, 지정학적 위기가 고조될수록 해운기업 주식가격의 변동성은 확대되었다. 둘째, 외교적 마찰로 인한 지정학적 위기보다는 실제 발생하는 이벤트에 의한 지정학적 위기의 영향이 통계적으로 유의하였다. 마지막으로, 지정학적 위기로 인한 주식가격 변동성의 확대는 주로 벌크부문에 나타났다.

• 한국항해항만학회지
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• 제39권5호
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• pp.393-399
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• 2015

Recently, the fierce competitions in the shipping industry and the global economic downturn have heavily influenced ports' operational strategies. In order for port authorities to remain competitive at an international level and to provide more accurate information to develop National policies, ports are required to analyse and improve operations' efficiency. In this paper, the efficiency of 19 Italian ports in 2013, handling different types of cargoes, is assessed through the application of Data Envelopment Analysis (DEA), with constant return to scale (CRS) and variable return to scale (VRS). The purpose of this study is to analyze the efficiency of Italian ports and evaluate whether differences in size and specialization of each port (or cargo handled) are directly correlated with ports' efficiency.

• 한국항해항만학회:학술대회논문집
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• 한국항해항만학회 2016년도 춘계학술대회
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• pp.237-238
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• 2016

해운선사들은 IMO를 비롯한 많은 연구단체에서 제시하고 있는 에너지 효율성 개선방안을 기반으로 선사의 실정과 유가의 등락 상황에 따라 투자환수(payback) 기간을 고려하여 에너지 효율성 개선방안을 결정하고 있다. 그러나 저유가 시대에서는 갈수록 투자환수 기간이 늘어나고 있어 현존 운항선에 대한 레트로피트(Retrofit)는 극히 1~2년 내 투자비용 회수가 가능한 항목에 국한되는 경향이다. 특히 용선 선박의 경우 설비의 투자를 통한 에너지 효율성 개선은 용선계약 특성상 이해관계 및 인센티브 차이로 인하여 매우 어려운.

• Journal of Ship and Ocean Technology
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• 제1권1호
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• pp.57-72
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• 1997

The larger trends related to cracking in ocean going vessels (primarily tankers and bulk carriers) are reviewed on the basis of available data. The typical interrelated causes of such cracking are: high local stresses, extensive use of higher strength steels, inadequate treatment of dynamic loads, adverse operational factors (harsh weather, improper vessel handling), and controllable structural degradation (corrosion, wear, stevedore damage). Three consequences of cracking are then discussed: structural failure, pollution, and increased maintenance. The first two, while rare, are potentially of high consequence including loss of life. The types of solutions that can be employed to improve the durability of ships in the face of fatigue cracking are then presented. For existing vessels, these solutions range from repairs based on structural analysis or service experience, control of corrosion, and enhanced surveys. For new vessels, the use of advanced design procedures that specifically address dynamic loads and fatigue cracking is necessary. As the preferred solution to the problem of cracking in ships, this paper advocates prevention by explicit design by first principles.

• 한국해양공학회지
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• 제34권2호
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• pp.120-127
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• 2020

Evaluation of fatigue strength considering the springing effect of very large container ships is crucial in the design stage. In this study, we established a fatigue strength evaluation method considering a linear springing component in the frequency domain. Based on a three-dimensional global model, a fluid-structure interaction analysis was performed and the modal superposition method was applied to determine the hot spot stress at the hatch corner of very large container ships. Fatigue damage was directly estimated using the stress transfer function with a linear springing response. Furthermore, we proposed a new methodology to apply the springing effect to fatigue damage using hull girder loads. Subsequently, we estimated the fatigue damage contribution due to linear springing components along the ship length. Finally, we discussed the practical application of the proposed methods.

• 한국항해항만학회지
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• 제42권5호
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• pp.341-346
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• 2018

Supramax bulk carriers cover a wide range of ocean transportation requirements, from major to minor bulk cargoes. Market forecasting for this segment has posed a challenge to researchers, due to complexity involved, on the demand side of the forecasting model. This paper addresses this issue by using technical indicators as input features, instead of complicated supply-demand variables. Artificial neural networks (ANN), one of the most popular machine-learning tools, were used to replace classical time-series models. Results revealed that ANN outperformed the benchmark binomial logistic regression model, and predicted direction of the spot market with more than 70% accuracy. Results obtained in this paper, can enable chartering desks to make better short-term chartering decisions.