• Journal of Information Technology Applications and Management
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• v.18 no.2
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• pp.39-59
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• 2011

Information Technology (IT) has been working as an engine of growth in Korea since early 1990's. For the next leap of Korean economy and to overcome worldwide financial crisis, Korea's IT industry needs to find a new breakthrough. In this viewpoint, we tried to empirically analyze the impact of Korea's IT trade on domestic industry. Since Korean government is trying to set up a few free trade agreements (FTA) with major trade partners, more accurate understanding of the impact of FTA is required to find the correct way to promote Korea's IT industry. We first looked at the current status of Korea's IT trade with major partners such as the US, Japan, and China to understand the competitiveness of Korea's IT industry. Having done this, we measured the impact of IT trade on domestic industry using Granger causality test. The results showed that the positive impact of trade is bigger on IT industry than on whole industry. Also, the impact of import turned out to be bigger than that of export. Among the major trade partner countries, the US’s and China's impacts are bigger than Japan's impact. Another notable thing is that IT product import from the US has especially big impact on domestic IT industry. Our findings may have certain implications to the FTA related policy.

• International Commerce and Information Review
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• v.19 no.3
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• pp.107-127
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• 2017

This paper aims to analyze comparing the international competitiveness of Korea and China of ICT 10 goods in ASEAN Big 6 countries.(Malaysia, Indonesia, Vietnam, Singapore, Thailand, Philippines). In this study, we investigate major trends in Korea's ICT goods through various data analysis and evaluate. From 2009 to 2016, As analyzed by ESI, CTB, and EMS, This paper showed Korea has increased its export, EMS and Export Competitiveness to ASEAN. However, due to rapid imports, the trade balance deteriorated and ESI decreased. China showed signs of improvement in international competitiveness, although exports, ESI and EMS were declining. Compared to South Korea, China has seen less export bias to ASEAN. ASEAN is becoming an increasingly important trade partner in Korea's ICT exporting. This paper points out several policy implications drawn from its analyses and findings.

• 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.

• KIPS Transactions on Software and Data Engineering
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• v.11 no.10
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• pp.427-436
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• 2022

Korea Trade-Investment Promotion Agency (KOTRA) annually publishes the trade data in South Korea under the guidance of the Ministry of Trade, Industry and Energy in South Korea. The trade data usually contains Gross domestic product (GDP), a custom tariff, business score, and the price of export items in previous and this year, with regards to the trading items and the countries. However, it is challenging to figure out the meaningful insight so as to predict the future price on trading items every year due to the significantly large amount of data accumulated over the several years under the limited human/computing resources. Within this context, this paper proposes a multi layer perception that can predict the future price of potential trading items in the next year by training large amounts of past year's data with a low computational and human cost.

• International Commerce and Information Review
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• v.16 no.5
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• pp.361-385
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• 2014

This study focused on Spillover of Technology Trade against Post- BRICs of the Technology export of Korea. Therefore this study made an empirical analysis for investigating the competitiveness of technology export in Korea and using panel data 2003-2012 of technology trade data between 6 Countries(Indonesia, Mexico, Nigeria, South Africa, Turkey, Vietnam). In particular, the study deduced the correlation between technology export in Korea using the variables of Gross Domestic Expenditure on R&D and Per capita GDP, distance, population, free-trade index, FDI, Technology-Intensive Manufactures, Pattern Investment fixed effect model in panel linear regression model. It is found that the Technology export of Korea SMEs made a significant effect on the pop, free_trade, and distance. and also it is found that the Technology export of Korea Big Business made a significant effect on the per-GDP, Fdi from Korea, free_trade, and distance. The results suggest that the study should use technology gap variables and the strategy for activating the Technology export of Korea should be made for future works.

• THE INTERNATIONAL COMMERCE & LAW REVIEW
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• v.75
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• pp.137-158
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• 2017

Traditional banking systems of transactions are being replaced by FfinTech. Block Chain System can be a key point in Fourth Industrial Revolution such as AI, Big Data, IOT and also can be used as a tools of smart contract or smart payment systems in International Trade. If banking regulation is to be liberalized FinTech would be more activated in Korea and various attempts would be available especially smart payment in business. There are so many levels to be achieved from the time of contract to the time of clearance. We cannot expect speed and range of IT advancement and international trade, Block Chain system will challenge the traditional banking process. First, Block Chain Payment system can be used in P2P, B2B transaction and also T/T in small business. Second, Bit Coin transaction can be available within the parties without the Trusted Third Party. Third, By using of Block Chain system Traditional International Trade process can be altered.

• Journal of Korea Trade
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• v.26 no.1
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• pp.113-125
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• 2022

Purpose - The primary purpose of this study is to verify whether the target set out by the International Maritime Organization (IMO) for reducing carbon emissions from ships can be achieved by quantitatively analyzing the trends in technological advances of fuel oil consumption in the container shipping market. To achieve this purpose, several scenarios are designed considering various options such as eco-friendly fuels, low-speed operation, and the growth in ship size. Design/methodology - The vessel size and speed used in prior studies are utilized to estimate the fuel oil consumption of container ships and the pace of technological progress and Energy Efficiency Design Index (EEDI) regulations are added. A database of 5,260 container ships, as of 2019, is used for multiple linear regression and quantile regression analyses. Findings - The fuel oil consumption of vessels is predominantly affected by their speed, followed by their size, and the annual technological progress is estimated to be 0.57%. As the quantile increases, the influence of ship size and pace of technological progress increases, while the influence of speed and coefficient of EEDI variables decreases. Originality/value - The conservative estimation of carbon emission drawn by a quantitative analysis of the technological progress concerning the fuel efficiency of container vessels shows that it is not possible to achieve IMO targets. Therefore, innovative efforts beyond the current scope of technological progress are required.

• The Journal of Society for e-Business Studies
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• v.22 no.4
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• pp.71-101
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• 2017

Since late 2016, protectionism has been a major trend in world trade with the Great Britain exiting the European Union and the United States electing Donald Trump as the 45th president. Consequently, there has been a huge public outcry regarding the negative prospects of heavy industry firms in Korea, which are highly dependent upon international trade with Western countries including the United States. In light of such trend and concerns, we have tried to predict business performance of heavy industry firms in Korea with data regarding trade policy of the United States. United States International Trade Commission (USITC) levies countervailing duties and anti-dumping duties to firms that violate its fair-trade regulations. In this study, we have performed data analysis with past records of countervailing duties and anti-dumping duties. With results from clustering analysis, it could be concluded that trade policy trends of the Unites States significantly affects the business performance of heavy industry firms in Korea. Furthermore, we have attempted to quantify such effects by employing long short-term memory (LSTM), a popular neural networks model that is well-suited to deal with sequential data. Our major contribution is that we have succeeded in empirically validating the intuitive argument and also predicting the future trend with rigorous data mining techniques. With some improvements, our results are expected to be highly relevant to designing regulations regarding heavy industry in Korea.

• Journal of Korea Trade
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• v.25 no.1
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• pp.89-111
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• 2021

Purpose - The U.S. Trade Preference Expansion Act (TPEA) of 2015 enables the US Department of Commerce (DOC) to inflate dumping margin when the particular market situation (PMS) exists in the exporter's home market. DOC applied PMS provisions to the steel products from Korea. This paper analyzes whether DOC's calculation by using the regression analysis is consistent with WTO rules. Design/methodology - This paper analyzes the PMS application in law and regression analysis that extends the data period from 10 years to 18 years using the same economic model with DOC, and changes the country group according to the quantities of steelmaking capacity. Findings - Results show that DOC's argument conflating the sales-based with cost-based PMS designed to inflate dumping margins might not be consistent with WTO Antidumping Agreement Article 2.2 and 2.2.1.1 in which costs shall normally be calculated on the basis of records kept by the exporter, providing generally accepted accounting principles and reasonably reflection of the costs and PMS that exists in the Korean steel product markets. Even if it will be consistent, DOC's calculated margin by the regression analysis using a 10-year data is a big gap (5 times) compared with an 18-year data projection and different countries' data through the same methodology, which is a huge gap of regression coefficient. It means that dumping margin would be very wide range from 7.8% to 38.54% and unstable to calculate. Inflating dumping margin by DOC using regression analysis would not only be inconsistent with WTO rules, but also projection result is unreliable. Originality/value - Literature papers have mainly analyzed WTO law itself. This paper however, would be the first attempt to analyze the DOC's new way of dumping margin calculation in both manners of law and an empirical methodology perspective at the same time.

• Journal of Korea Trade
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• v.25 no.2
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• pp.22-45
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• 2021

Purpose - This study aims to identify new attributes by analyzing reviews conducted by global automaker customers and to examine the influence of these attributes on satisfaction ratings in the U.S. automobile sales market. The present study used J.D. Power for customer responses, which is the largest online review site in the USA. Design/methodology - Automobile customer reviews are valid data available to analyze the brand personality of the automaker. This study collected 2,998 survey responses from automobile companies in the U.S. automobile sales market. Keyword analysis, topic modeling, and the multiple regression analysis were used to analyze the data. Findings - Using topic modeling, the author analyzed 2,998 responses of the U.S. automobile brands. As a result, Topic 1 (Competence), Topic 5 (Sincerity), and Topic 6 (Prestige) attributes had positive effects, and Topic 2 (Sophistication) had a negative effect on overall customer responses. Topic 4 (Conspicuousness) did not have any statistical effect on this research. Topic 1, Topic 5, and Topic 6 factors also show the importance of buying factors. This present study has contributed to identifying a new attribute, personality. These findings will help global automakers better understand the impacts of Topic 1, Topic 5, and Topic 6 on purchasing a car. Originality/value - Contrary to a traditional approach to brand analysis using questionnaire survey methods, this study analyzed customer reviews using text mining. This study is timely research since a big data analysis is employed in order to identify direct responses to customers in the future.