• International Journal of Advanced Culture Technology
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• v.8 no.3
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• pp.300-306
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• 2020

This study analyzes the distributor's inventory model in a two-stage supply chain consisting of the supplier, the distributor and the end customer. The supplier will allow a credit period before the distributor settles the account with him in order to stimulate the demand for the product he produces. It is also assumed that the distributor pays the shipping cost for the order and hence, the distributor's ordering cost consists of a fixed ordering cost and the shipping cost that depend on the order quantity. The availability of the delay in payments from the supplier enables discount of the distributor's selling price from a wider range of the price option in anticipation of increased customer's demand. As a result, the availability of a credit transaction leads to an increase in inventory levels. On the other hand, in the case of deteriorating products in which the utility of the product perish over time, the deterioration rate with time plays a role in reducing inventory levels. In this regard, we analyze the effect of the length of the credit period and the degree of product deterioration on the distributor's inventory level. For the analysis, we formulate the distributor's annual net profit and analyze the effect of the length of credit period and deterioration rate of the product on inventory policy numerically.

• Journal of Korea Port Economic Association
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• v.24 no.2
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• pp.289-315
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• 2008

In Korea-China shipping route, the level of freight rate has been maintained very low for last two decades not only because supply of shipping capacity is higher than its demand but also because the route was regulated by the two governments. An examination is made of the effects of openness of Korea-China Liner Shipping Route on competitiveness of Korean-flag Liner Shipping companies. This task is undertaken by detailing the development of the cargo sharing respectively by shipping companies of each country. Then it is suggested the ways to cope with the new environmental changes in Korea-China liner shipping route for the future by examining the future strategies for Korean-flag companies by in-depth interviews with major shipping companies.

• Journal of Korea Port Economic Association
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• v.33 no.1
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• pp.75-87
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• 2017

The purpose of this study is to utilize the system dynamics to carry out a medium and long-term forecasting analysis of the bunker price. In order to secure accurate bunker price forecast, a quantitative analysis was established based on the casual loop diagram between various variables that affects bunker price. Based on various configuration variables such as crude oil price which affects crude oil consumption & production, GDP and exchange rate which influences economic changes and freight rate which is decided by supply and demand in shipping and logistic market were used in accordance with System Dynamics to forecast bunker price and then objectivity was verified through MAPEs. Based on the result of this study, bunker price is expected to rise until 2029 compared to 2016 but it will not be near the surge sighted in 2012. This study holds value in two ways. First, it supports shipping companies to efficiently manage its fleet, offering comprehensive bunker price risk management by presenting structural relationship between various variables affecting bunker price. Second, rational result derived from bunker price forecast by utilizing dynamic casual loop between various variables.

• Journal of Navigation and Port Research
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• v.33 no.7
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• pp.469-476
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• 2009

Recent collapse of shipping market right after unprecedent surge clearly demonstrates that shipping industry is extremely risky. Due to the volatile movements of the freight rates, investors tend to ask higher rate of return; higher required return reduces the total net present value of the investment project. For several decades, the Discounted Cash Flow(DCF hereafter) analysis has been the most frequently used valuation technique. However, the main problem of the DCF analysis is its assumption that the discount rate would stay the same during the project life. In other words, it usually does not address the decisions that managers have after a project has been accepted. The purpose of this study is investigate a new valuation method of investment: the Real Option Analysis(ROA hereafter) on ship investment. By replacing the existing valuation methods with the new one, the research will present a new perspective on investment with uncertainty. While uncertainty increases risk of investment and consequently discounts the value of it in the traditional feasibility analysis, in the ROA, a new valuation method which will be addressed in the research, uncertainty means some additional value of flexibility so that the tool can help investors produce more accurate decisions. Contrary to the DCF analysis, the ROA takes managerial flexibilities into account. In reality, capital budgeting and project management is typically dynamic, rather than static in nature. The ROA finds and assesses the values of managerial flexibilities or real options in the investments. The main structures of the research will be as follows: (1) overview of the ship investment project, (2) evaluation of the project by the Net Present Value analysis, (3) evaluation of the same project by the Real Option Analysis, (4) comparision of the two techniques.

• Journal of Navigation and Port Research
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• v.42 no.6
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• pp.539-545
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• 2018

In recent years, research on shipping market forecasting with the employment of non-linear AI models has attracted significant interest. In previous studies, input variables were selected with reference to past papers or by relying on the intuitions of the researchers. This paper attempts to address this issue by applying the stepwise regression model and the random forest model to the Cape-size bulk carrier market. The Cape market was selected due to the simplicity of its supply and demand structure. The preliminary selection of the determinants resulted in 16 variables. In the next stage, 8 features from the stepwise regression model and 10 features from the random forest model were screened as important determinants. The chosen variables were used to test both models. Based on the analysis of the models, it was observed that the random forest model outperforms the stepwise regression model. This research is significant because it provides a scientific basis which can be used to find the determinants in shipping market forecasting, and utilize a machine-learning model in the process. The results of this research can be used to enhance the decisions of chartering desks by offering a guideline for market analysis.

• Management & Information Systems Review
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• v.34 no.4
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• pp.1-13
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• 2015

This paper presents a mathematical formulation for container slot chartering model through strategic alliance between liner shipping companies. This paper develops a solution procedure to apply the model to real world problems and its applicability is demonstrated by a numerical example. The model presented in this paper has some important features which have never been considered in the previous researches. The model is linear model and pursuits profit maximization. And also it considers slot chartering capacity selection. This paper attempts to perform sensitivity analysis and compares slot chartering model with basic non-collaborating model in which there is no alliance and collaboration. As a result of sensitivity analysis, some interesting findings are obtained; Even though freight rate is more and more decreasing, the profit by slot chartering model is always higher than the basic model but the profit gaps become smaller. But The ratio of the profit gap to the profit of basic model is more increasing.

• Journal of Korea Port Economic Association
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• v.22 no.3
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• pp.141-160
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• 2006

In order to obtain and maintain competitive advantage, under rapidly changing maritime environment, liners should make efforts to reinforce their logistics service capabilities. Most of all, for this, shipping lines should accurately recognize and evaluate their logistics service attributes. In the present research, various logistics service attributes for ocean carriers were selected from previous studies and the observed data for 6 main service attributes were collected through a questionnaire survey to 31 maritime experts. Moreover, shipping lines' relative logistics service capabilities were measured by an additional survey process. The comparative gravity between core evaluation factors were measured by AHP technique and the relative capability levels of 2 Korean liners and 5 foreign shipping companies were assessed by utilizing a fuzzy model. The empirical result presents that Korean liners are superior at customer service capability but inferior at freight rate competitiveness. This research shows that Korean liners are ranked at high position for overall logistics service capabilities and focusing on the differentiation strategy but not on the cost related strategy.

• Journal of Korea Port Economic Association
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• v.34 no.1
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• pp.99-110
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• 2018

This study empirically examines simple methodology to quantify the risk resulted from the uncertainty of bunker price and foreign exchange rate, which cause main resources of the cost in shipping industry during the periods between $1^{st}$ of January 2010 and $31^{st}$ of January 2018. To shed light on the risk measurement in cash flows we tested GBM(Geometric Brownian Motion) frameworks such as the model with conditional heteroskedasticity and jump diffusion process. The main contribution based on empirical results are summarized as following three: first, the risk analysis, which is dependent on a single variable such as freight yield, is extended to analyze the effects of multiple factors such as bunker price and exchange rate return volatility. Second, at the individual firm level, the need for risk management in bunker price and exchange rate is presented as cash flow. Finally, based on the scale of the risk presented by the analysis results, the shipping companies are required that there is a need to consider what is appropriate as a means of risk management.

• Journal of Navigation and Port Research
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• v.46 no.4
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• pp.375-384
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• 2022

The shipping industry is cyclically impacted by complex variables such as various economic indicators, social events, and supply and demand. The purpose of this study was to analyze the operating profit of 13 Korean liner companies over 30 years, including the financial crisis of the late 1990s, the global financial crisis of the late 2000s, and the COVID-19 global pandemic. This study was conducted to also identify factors that impacted the profit ratio of Korea's liner shipping companies according to economic conditions. It was divided into ocean-going and short-sea shipping, reflecting the characteristics of liner shipping companies, and was analyzed by hierarchical multiple regression analysis. The time series data are based on the Korean International Financial Reporting Standards (K-IFRS) and comprise seaborne trade volume, fleet evolution, and macroeconomic indicators. The outliers representing the economic downturn due to social events were separately analyzed. As a result of the analysis, the China Container Freight Index (CCFI) positively impacted ocean-going as well as short-sea liner shipping companies. However, the Korean container shipping volume only impacted ocean-going liners positively. Additionally, world and Korea's GDP, world seaborne trade volume, and fuel price are factored in the operating profit of short sea liner shipping. Also, the GDP growth rate of China, exchange rate, and interest rate did not significantly impact both groups. Notably, the operating profitability of Korea's liner shipping shows an exceptionally high rate during the recessions of 1998 and 2020. It is paradoxical, and not correlated with the classical economic indicators. Unlike other studies, this paper focused on the operating profit before financial expenses, considering the complexity as well as difficulty in forecasting the shipping cycle, and rendered conclusions using relatively long-term empirical analysis, including three economic shocks.

• Journal of Korea Port Economic Association
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• v.35 no.4
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• pp.107-120
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• 2019

Crude oil is a resource that is being used as a raw material in major industries, representing the price of the raw material market. It is also an important element that affects the shipping market in terms of fuel costs for freight vessels. As a result, crude oil and freight rates are closely related. Therefore, from January 2009 to June 2019, this study analyzed the dependency structure between oil price (WTI) and freight rates (BDI, BCI, BPI, BSI, and BHI) using daily data. The main results are summarized as follows. First, according to the copula results, survival Gumbel copula in WTI-BDI, Clayton copula in WTI-BCI, Survival Joe copula in WTI-BPI, Joe copula in WTI-BSI, and survival Gumbel copula in WTI-BHI were selected as the best-fitted model. Second, looking at Kendall's tau correlation, there is a positive correlation between BDI and oil price. Furthermore, freight rate index (BCI, BPI, BSI) and oil price show positive dependencies. In particular, the strongest dependence was found in BCI and oil price returns. However, BHI and oil price show a negative dependency. Third, looking at the tail-dependency structure, a pair between oil price and BDI, BCI showed a lower tail-dependency. The pair between oil price and BSI showed the upper tail-dependency.