• Journal of Korean Society of Transportation
• /
• v.28 no.6
• /
• pp.43-54
• /
• 2010

In recent years there have been studies on tour based approaches for freight travel demand modelling. The purpose of this paper is to analyze tour type choice behavior of commercial vehicles which are divided into round trips and chained tours. The methods of the study are based on the decision tree and the logit model. The results indicates that the explanation variables for classifying tour types of commercial vehicles are loading factor, average goods quantity, and total goods quantity. The results of the decision tree method are similar to those of logit model. In addition, the explanation variables for tour type classification of small trucks are not different from those for medium trucks', implying that the most important factor on the vehicle tour planning is how to load goods such as shipment size and total quantity.

• Journal of Korea Port Economic Association
• /
• v.36 no.2
• /
• pp.109-124
• /
• 2020

Using panel data on freight rates and ship prices in the dry freighter market from January 2015 to December 2019, this study investigates the characteristics of shipping industry fluctuations. The analysis aims at two aspects of academic contribution. First, this study analyzes the relationship between shipping indicators and ship price based on separate dry-bulk ships, while the previous research considered the overall shipping index and weighted average ship prices. Second, the VAR model for the causality test is extended to a heterogeneous mixed panel model capable of limiting coefficients. There is a peak estimated by removing the cross-correlation problem, which is mainly raised in panel data analysis, using bootstrap estimation and solving the problem of information loss due to differences in non-stationary data. An empirical investigation of the causal relationship between economic fluctuations and ship price shows that the effect on the ship price from the freight is significant at the 1% level. This implies that there is a one-way relationship with demand in the shipping industry rather than a bilateral relationship.

• The Journal of the Convergence on Culture Technology
• /
• v.6 no.2
• /
• pp.191-197
• /
• 2020

As an effective means of price discrimination, some suppliers offer trade credit to the distributors for the purpose of increasing the demand of the product they produce. 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. In this regard, we consider the problem of determining the distributor's optimal price and lot size simultaneously when the supplier permits delay in payments for an order of a product whose demand rate is represented by a constant price elasticity function. It is 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. For the analysis, it is also assumed that inventory is depleted not only by customer's demand but also by decay. We are able to develop a solution algorithm from the properties of the mathematical model. A numerical example is presented to illustrate the algorithm developed.

• The Journal of Korean Institute of Communications and Information Sciences
• /
• v.39C no.3
• /
• pp.291-297
• /
• 2014

Due to the rapid increase in demand for transportation of human and freight in modern railway systems, the CBTC system has been proposed, which is the solution for improvement of the line capacity that has been limited by the conventional track circuit based train control system. In the CBTC system, higher reliability of the communication system should be guaranteed for the safety of passengers and trains. However, due to the inherent characteristics of the wireless channel environment, performance degradations are inevitable. The diversity techniques can increase the reliability of data transmission using multiple antennas. In this paper, we investigate the performance of the STBC in the railway channel environment. Rician fading model is used for the viaduct scenarios which take important roles in the railway system. Also, considered is the Doppler effect which is an important factor in the mobile communication system. Simulations are performed to analyze the performance of the STBC in various channel environments. Results show that the performance degradation due to the phase error in viaduct scenarios is independent of the diversity order but is affected by the constellation of the modulation.

• Journal of Navigation and Port Research
• /
• v.39 no.4
• /
• pp.361-370
• /
• 2015

Wind energy began to receive attention as a new alternative fuel since 20 years ago and is growing as a booming global business model. Global wind power generation in the world has been continuously increasing for the past 10 years, accounting for over 30% of cumulative rate compared to total power generation. Global demand for wind power generation is gradually expanding due to restriction on carbon emission and environmental problems caused by increased greenhouse effect. Accordingly in this study, current transportation routes are classified into three types including access-priority route, economics-priority route, and convenience- priority route depending on distribution characteristics of wind power equipment in order to suggest transportation methods other than ships. The three types of transportation route that this study declared can make the Wind power equipment manufacturing companies can judge not only the duration of transportation but also effectiveness and economic feasibility. It means that the manufacturers can analyze and compare the effectiveness and economic feasibility, which are proceed by the shipping company and freight forwarder until now days.

• Journal of Korean Society of Transportation
• /
• v.27 no.1
• /
• pp.73-81
• /
• 2009

While various factors in passenger and freight demand analysis affect on destination choice, a key factor, in general. is an attractiveness measure by size variable (e.g., population. employment etc) in destination zone. In order to measure the attractiveness, some empirical studies suggested that disaggregate gravity model are more suitable than aggregate gravity model. This study proposes that truck travelers trip diary data among Korean commodity flow data could be used to estimate the behaviors of incorporating trip departure time, activity duration and attractiveness in destination. As a result, the main findings of size and distance variables coincide with the conventional gravity model having a positive effect of population variable and a negative effect of distance variable. Due to disaggregate gravity modeling, the unique findings of this study reports that small trucks are more likely to choose short distance and early morning, morning peak and afternoon peak departure time choice. On the other hand, large trucks are more likely to choose long distance and night time departure time choice.

• Proceedings of the Korean Institute of Navigation and Port Research Conference
• /
• 2022.06a
• /
• pp.391-393
• /
• 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.

• Journal of Korea Port Economic Association
• /
• v.35 no.2
• /
• pp.61-76
• /
• 2019

The purpose of this study is to use the EGARCH model and Granger causality test to analyze how the change in the BDI affects the Korean stock price volatility. The main analysis results are summarized as follows. First, according to the results of the mean equation, the change in the BDI is significant in large-cap stocks, as well as in the manufacturing, service, and chemistry indexes, but not in others. This implies that the Korean stock market does not respond appropriately to the maritime market situation; further, the increase in demand for raw materials has not led to a real economic recovery. Second, in the result of the variance equation, the coefficient on the change in the BDI is negative(-), and the change in the BDI is significant for all size indexes. Particularly, the change in the BDI has a greater impact on the volatility of small-cap stocks than that of large-cap stocks. The results of the analysis of the sector indexes were statistically significant for the service, financial, construction, and electric and electronics industries, but not for the manufacturing and chemical industries. In particular, the changes in the BDI have the greatest impact on the construction industry. Third, according to the Granger causality test results, the change in the BDI leads the financial industry and construction industry. There is, however, no relationship between the BDI and the other indexes. This shows that change in the shipping freight index can be used to predict the volatility in the Korean stock market. This can help investors and policymakers make better decisions.