• Journal of Korean Society of Transportation
• /
• v.30 no.3
• /
• pp.107-118
• /
• 2012

The purpose of the study is to analyze the travel characteristics of freight trucks in metropolitan areas, focusing on activity generation, destination choice, and trip chaining behaviors. The results showed that the number of service companies at departure areas has a primary influence on the activity generation pattern and destination choice behavior of trucks in metropolitan areas. The number of trips within a trip chain is largest, in case where the prevailing industry in destination areas is wholesale or retail and the shipment item is food or beverage. These results imply that for the reasonable estimation of truck travel demand both the trip chaining behaviors and the industrial compositions in departure and destination areas should be separately considered for each type of commodity.

• Journal of Navigation and Port Research
• /
• v.40 no.5
• /
• pp.345-351
• /
• 2016

This study presents a system dynamics methodology to evaluate quantitatively the effect of the Korean government's development policy, such as tax reductions, on the industrial economy. System dynamics is often perceived as an optimized means to identify the dynamic inter-relationships among various factors of development policies, and in particular the industrial characteristics and uncertainties of the coastal shipping industry. The results of simulations used in this study shows that the impact of development policies such as tax reductions would increase shipping demand for about 4 years, and that tax incentives could raise the demand volume for cabotage cargo from 5.26 to 11.11%, through the available freight-down by 90~95% points. The system dynamics approach used in this paper represents an initial attempt to use this methodology in studies of the coastal shipping industry. On the basis of our simulations, the industrial effects of other development policies, such as ship financing support, investment of social overhead, or crew supply, could also be analyzed effectively. Additionally, it should be possible to extend these results by developing a comprehensive model encompassing these various analyses.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2009.10a
• /
• pp.185-186
• /
• 2009

According to increase of container transportation, demands of empty container handling has been increasing, so research of empty container has been studied steadily. However, the handling of containers and empty containers is not handled simultaneously. Moreover, as Korean ICD(Inland Container Depot) and ODCY(Off-Dock Container Yard), the inland depot in many environments, relocation research due to demand of empty container has not been studied sufficiently. This paper formulates and analyzes logical mathematical relocation model according to demands of empty container which are required in container terminal, ICD, and ODCY as cargo depots. This paper also aims to help reduce cost by improving q current empty container relocation as same as the past procedure.

• Korea Trade Review
• /
• v.47 no.1
• /
• pp.13-24
• /
• 2022

This study was conducted because the global economic downturn caused by COVID-19 caused a surge in logistics costs and it was no longer possible to predict logistics costs using existing methods. For this study, we made the assumption that economic indicators affect logistics cost. Chapter 2 examines the current status of the liner market and factors affecting logistics costs. Based on this, Chapter 3 collects independent and dependent variables to determine the analysis model. As the independent variable, economic indicators of major countries constituting the SCFI were selected, and the dependent variables were the SCFI Europe Index and the SCFI USA Index. In Chapter 4, a panel analysis was conducted based on this, and it was confirmed that major economic indicators had a negative (-) effect on SCFI. This is contrary to the existing research results, which can be attributed to the special situation caused by COVID-19 and the imbalance of demand and supply by region. The results of this study are meaningful in that they can predict long-term logistics cost volatility without analyzing supply and demand, and can be applied to other studies as well.

• Journal of Korea Trade
• /
• v.25 no.4
• /
• pp.17-36
• /
• 2021

Purpose - This study provides useful information to stakeholders by forecasting the tramp shipping market, which is a completely competitive market and has a huge fluctuation in freight rates due to low barriers to entry. Moreover, this study provides the most effective parameters for Baltic Dry Index (BDI) prediction and an optimal model by analyzing and comparing deep learning models such as the artificial neural network (ANN), recurrent neural network (RNN), and long short-term memory (LSTM). Design/methodology - This study uses various data models based on big data. The deep learning models considered are specialized for time series models. This study includes three perspectives to verify useful models in time series data by comparing prediction accuracy according to the selection of external variables and comparison between models. Findings - The BDI research reflecting the latest trends since 2015, using weekly data from 1995 to 2019 (25 years), is employed in this study. Additionally, we tried finding the best combination of BDI forecasts through the input of external factors such as supply, demand, raw materials, and economic aspects. Moreover, the combination of various unpredictable external variables and the fundamentals of supply and demand have sought to increase BDI prediction accuracy. Originality/value - Unlike previous studies, BDI forecasts reflect the latest stabilizing trends since 2015. Additionally, we look at the variation of the model's predictive accuracy according to the input of statistically validated variables. Moreover, we want to find the optimal model that minimizes the error value according to the parameter adjustment in the ANN model. Thus, this study helps future shipping stakeholders make decisions through BDI forecasts.

• Korean Management Science Review
• /
• v.19 no.2
• /
• pp.75-89
• /
• 2002

According to the fast-paced environment of information technology and improving customer services, the design activities of logistics systems improve customer centric services and delivery performance implementing e-logistics system. The fundamental design issues that arise in the delivery system planning are optimizing the system with minimum cost and maximum throughput and service level. This study is concerned with the integrated model development of delivery system with customer responsive service level for DCM, Demand Chain Management. We used a two-step approach for this study. First, we formulated the supply. center facility planning using stochastic set-covering problem and assigned the customers to the supply center using clustering algorithm. Second, we developed vehicle delivery planning for a supply center based on GIS, GIS-VRP. Also we developed a GUI-type computer program for proposed method for supply center problem using GIS and Geo-DataBase of Busan area. The computational results showed that the proposed method was very effective on a set of test problems.

• Journal of Navigation and Port Research
• /
• v.48 no.1
• /
• pp.62-77
• /
• 2024

In the maritime shipping industry, imbalance between supply and demand has persistently increased, leading to the utilization of blank sailings by major shipping companies worldwide as a key means of flexibly adjusting vessel capacity in response to shipping market conditions. Traditionally, blank sailings have been frequently implemented around the Chinese New Year period. However, due to unique circumstances such as the global pandemic starting in 2020 and trade tensions between the United States and China, shipping companies have recently conducted larger-scale blank sailings compared to the past. As blank sailings directly impact freight transport delays, they can have negative repercussions from perspectives of both businesses and consumers. Therefore, this study employed Poisson regression models and negative binomial regression models to analyze the influence of maritime freight rate determinants on shipping companies' decisions regarding blank sailings, aiming to proactively address potential consequences. Results of the analysis indicated that, in Poisson regression analysis for 2M, significant variables included global container shipping volume, container vessel capacity, container ship scrapping volume, container ship newbuilding index, and OECD inflation. In negative binomial regression analysis, ocean alliance showed significance with global container shipping volume and container ship order volume, the alliance with container ship capacity and interest rates, non-alliance with international oil prices, global supply chain pressure index, container ship capacity, OECD inflation, and total alliance with container ship capacity and interest rates.

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

• Journal of East Asia Management
• /
• v.3 no.2
• /
• pp.21-41
• /
• 2022

This study aims to analyze the characteristics of the management situation of the Korea Railroad Corporation(KORAIL) through the management innovation process of the KORAIL and to suggest its implications for military application. Despite stable demand, the railway passenger industry had the limitation of not being able to abolish deficit routes due to public service obligations. In addition, the launch of the Suseo High-Speed Line has introduced a competitive system, posing a threat to corporate management. KORAIL wanted to overcome this crisis by innovating its management through the utilization of big data, improvement of the freight business, decentralization of demand, the introduction of tourism railroads, and development of station influence areas. By utilizing big data, KORAIL was able to optimize the railway fare system while reducing fixed costs spent on railway maintenance. It also drastically reduced the station of cargo and created a base station to pursue economies of scale. On the other hand, the existing exclusive station system was abolished to solve the chronic saturation of the downtown area, and the railway demand was moved to Gwangmyeong Station and Suwon Station to optimize the passenger supply. In particular, it developed a new business model called the tourism railway by developing the mountain Byeokjin Line, which was a chronic deficit line, and sought to improve liquidity through the development of the station influence area. Such a process of innovation at KORAIL suggests an appropriate direction in seeking ways to innovate the military medical institutions. First of all, the necessity of improving organizational immersion through the development of a personnel structure suitable for the compulsory organization, while expanding the facilities of the division and corps, and reducing the time required for medical treatment and waiting through the establishment of a data-based medical system was suggested. Next, it was also discussed to integrate the National Health Medical College, which received accreditation as a medical facility through the designation of advanced general hospitals and is ultimately under discussion with the Medical Institution. Through this, we hope that the military medical institutions, which are facing various challenges, will overcome existing limitations and be re-lighted as innovative institution that provides comprehensive public health services.

• Journal of the Korean Society for Railway
• /
• v.10 no.1 s.34
• /
• pp.23-37
• /
• 2007

Since 1964, HSR, which was opened in Japan, has had a hoge impact on the world. Historically, HSR has similar characteristics to the Roman Road, which promoted rapid movement and hada great influence on international society as transport infrastructure. Recently the development of HSR has become more rapid because of economic, environmental and external cost concern, emphasizing Environmentally Sustainable Transport(EST). In particular, the external cost has become more important factor for justifying HSR. The successful factors of HSR are high demand and cost minimal construction costs. There are two successful HSR models, the Japanese and the French. The former operates based on high demand oriented and the latter focuses on its minimizing costs. The demand orientated model means HSR carries over 100,000 passengers per day as in Japan and Far East Asian countries. The cost minimized model focuses on lower operation and construction costs as in France. In particular, Germany carries both passengers and freight on HSR. The construction costs in Germany are in between those of Japan and France. In future, Korea, Taiwan and China HSR will follow Japan's successful model because of high population density and concentration of economic activity along railway lines. This paper supports Vickerman's argument that HSR is justified where there is a demand of between 12 million and 15 million railway passenger a year(about 40thousand persons/day) between two urban center. This will be shown in the future in Korea, in Taiwan and China. Finally, this paper reviews that HSR activates at 250km/h for dedicated new lines and 200km/h for upgraded lines. In particular, it is successful in area of high population density and cost minimizing technology.