• Environmental and Resource Economics Review
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• v.23 no.1
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• pp.1-19
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• 2014

Weather seems to influence industries in a variety of ways. On a day-to-day basis, it is the most volatile external factor influencing consumer and market behavior. And, because weather is constantly changing, industries must deal with a continuously shifting array of opportunities and risks. This study aims to examine how climate and weather changes and information, as external environmental factors, have affected the Korean industries, particularly marine shipping and logistics. To find out the economic value of marine weather information, we use measurable results of VVOS(Vessel and Voyage Optimization Services) in the ocean shipping, which the marine weather software tool can save fuel costs up to 4%. When the fuel saving is same as VVOS's performance, the saving of Korean flag ship is estimated about 62 billion won and the saving of total flag ship is estimated about 519 billion won. However, coastal shipping companies have been struggling with the heavy weather factors, such as wave height, wave period and wind. Major findings are that wind and wave height have a significant negative effect on cargo transport, while wave period has a significant positive effect on cargo transport. And to conclude, when we use efficiently the marine weather information, we can increase cargo transport and save fuel costs etc.

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

• Journal of the Korea Society of Computer and Information
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• v.26 no.7
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• pp.127-132
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• 2021

This paper applies a machine learning model to forecasting freight rates in dry bulk and tanker markets with wavelet decomposition and empirical mode decomposition because they can refect both information scattered in the time and frequency domain. The decomposition with wavelet is outperformed for the dry bulk market, and EMD is the more proper model in the tanker market. This result provides market players with a practical short-term forecasting method. This study contributes to expanding a variety of predictive methodologies for one of the highly volatile markets. Furthermore, the proposed model is expected to improve the quality of decision-making in spot freight trading, which is the most frequent transaction in the shipping industry.

• Journal of Korea Port Economic Association
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• v.40 no.2
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• pp.157-173
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• 2024

This study analyzed the connectivity of the dry bulk carrier market before and after COVID-19 to examine the impact of COVID-19 on the global shipping market. Using the Quantile Time Frequency Connectedness methodology, we analyzed the dynamic connectedness of major dry bulk indices: the Capesize Index (BCI), Supramax Index (BSI), Panamax Index (BPI), and Handysize Index (BHSI). The results are as follows. First, the total spillover connectedness of the dry bulk carrier market increased during the entire period and in the short term after the outbreak of COVID-19, while it slightly decreased in the long term. Second, the roles among the indices changed according to market conditions, with COVID-19 causing the BPI to change from a net receiver to a net transmitter in the short term and the BSI in the long term, affecting net spillover connectedness. Third, it was observed that long-term connectivity tended to increase more than short-term connectedness under extreme conditions. Fourth, the phenomenon of strengthened connectedness under extreme market conditions was confirmed. These results provide important insights into understanding short-term market shocks and long-term stability trends, demonstrating that the connectedness among dry bulk carrier markets strengthens in global crisis situations such as COVID-19. This provides a basis for assessing the resilience and vulnerability of the shipping market and offers useful information for investors and policymakers in crisis management and investment strategy formulation.

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

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.2
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• pp.373-378
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• 2017

While on-line shopping markets are growing, consumer's procurement processes are being confused regardless of on or off line market and, smart consumers who want intelligent tailored services have emerged. Depending on the changeable pattern of consumer, most of related companies provide various Omni channel and O2O service. However, reactions of the fashion companies are tend to be late. Recently, the IoT environment has changed to standards-based open platform and it requires a variety of intelligent services depending on the type of environment and objects. This thesis proposes fashion O2O system using smart fitting display that is adaptable to fashion companies. This proposed system provides fitting information which is performed on off-line by users after constructing the database, it also support the works as on-line status, thus, it makes users' procurements to maintain continuously. For the more, customer oriented intelligent fitting service would be expected by the information connection with the shop and delivery systems.

• Journal of Korea Society of Digital Industry and Information Management
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• v.12 no.3
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• pp.299-309
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• 2016

This study proposed a logistics plan for sending supply to be distributed to areas other than producing areas to wholesalers and allocating supply to be distributed to areas near producing areas to local distribution center in the vicinity instead of shipping the entire quantity to wholesalers for fruits auction to increase the competitive edge of the domestic fruits and vegetables logistics market in the ear of infinite competition. A video auction-based short distance division logistics operation model was developed to enhance competitiveness related to the circulation of fruits and vegetables, reduce logistics costs, and rationalize logistics by distributing the items sent to wholesalers through field auction and the shipments at local distribution center to neighboring areas through video auction connected to wholesalers real-time. The study especially came up with a logistics rationalization plan by examining and analyzing the stages and costs of transportation between producing areas and wholesalers on the circulation routes of fruits.

• IE interfaces
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• v.23 no.1
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• pp.12-23
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• 2010

A semiconductor market is one of the most competitive markets in the world. To survive this competition, important targets for production planning are on-time delivery and profit maximization. In our research, we modify the linear programming model for the current production planning by adding new objective functions that maximize the profit. In addition, we propose a production planning process that gives a priority to new products, reflecting daily fluctuations in demand to weekly production planning. We validate our model with real data sets obtained from a major company semiconductor manufacturer and performed the paired t-test to verify the results. The results showed that our model forecasted profit and loss with 93.2% accuracy and improved the due date satisfaction by 10%.

• The Journal of Information Systems
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• v.21 no.4
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• pp.155-183
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• 2012

Means-Ends Network model was used to identify factors of means objective(means supplied by vendor) and fundamental objectives(purchasing motivations) for purchasing decision-making structure and dimensions of customer values on purchasers of internet shopping mall in Korea and China. In Means-Ends Network 6 factors(shopping travel, shipping assurance, vendor trust, online payment, product choice, and recommender systems) were found as a means objectives and 3 factors(shopping convenience, internet environment, customer support) as a fundamental objectives of shopping. However the results of hypotheses test for Means-Ends Network show some important differences between two countries. Something important to notice here is that Chinese customers shopping in China recognize shipping assurance factor and vendor trust factor as important factors satisfying all fundamental objectives unlike as in the case of our country. As these two factors are attribution factors responsible to the sellers, it is identified that customers do not trust the sellers and sellers have not met the expectations of customers. Therefore, these results show that the seller efforts assuring the reliability of the seller themselves, such as conducting its own compensation scheme are more important rather than the establishment of the guarantee institution to guarantee reliability and delivery assurance of sellers and implementation of legal and institutional apparatus such as the settlement of e-commerce licence system. Though this study presents such an important marketing implications, it can be pointed out that the limits are this research was done on the general Internet shopping malls without considering the Internet shopping mall types of diversity, the survey was designed around the student samples for convenience of the investigation because it was an international survey and the collected data has been limited to the western coast cities, such as China's Beijing, Shanghai, and Dalian.

• International conference on construction engineering and project management
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• 2005.10a
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• pp.1028-1035
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• 2005

Traditional Industries were planning the major role for Taiwan's economy. However, we need to face the competition from developing countries. Moving manufacturing department to other low salary countries, such as China, can only temporarily release some limited pressure. The final and complete solutions are to equip on R&D, refine techniques, improve management capabilities, upgrade business, and reform physique. Currently there are some ERP systems on the market; however, they are designed for common purpose and difficult to introduce into industry. The expensive price is another factor to make them be popular. In this research we will Object Oriented, Visual Modeling, ER Model and Windows Environment to develop an Integrated Management System for Sports Requisites Industries (IMSSRI). We will integrate all information from all departments such as development, business, material administration, manufacture, shipping, and financial. When development people construct the all modules, components, cutting molds, materials and accessories, IMSSRI will calculate all needed materials and cost for each product. This cost will be used for quotation to report to our customers. When customers confirm the order, system will transfer all necessary materials into Material Administration System. IMSSRI can generate manufacturing forms and material raw lists for manufacture department. All related information such as stocking, returning goods, material requesting, and material returning can be integrated so we can control all details of the whole enterprise. Through the help of this system, we hope we can save man-power, reduce human mistakes, raise management capabilities for tradition manufacturing industries and create another possibility of eternal operating for Taiwan's Industries.