• Journal of Korea Port Economic Association
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• v.36 no.1
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• pp.129-140
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• 2020

In the future, the global container handling market will be reorganized into larger ships and shipping alliances, and the bargaining power of shipping companies will be further strengthened. Therefore, the global terminal operator (GTO), which has a global network, vast experience, and operational know-how, is expected to strengthen its competitiveness. In Korea, the central government promoted the development of GTOs in the mid-2000s, but it failed, mainly due to disagreements between port stakeholders. In this study, the macroeconomic indicators that have the same effect in all regions were used to analyze GTO management performance. In the short term, it could be used to establish the business strategy of domestic terminal operators based on changes in macroeconomic indicators. In the long term, it would be used to establish a promotion strategy for GTOs in Korea. The results of analyzing the impact of macroeconomic indicators on the GTO's profit show that the GTO's profit is significantly affected by cargo handling capacity, the consumer price index of the United States, the Shanghai Composite Index, the Crude Oil Price, and the London Inter-bank Offered Rate (LIBOR). However, the scale of impact was not significantly different between public and private GTOs.

• Journal of Information Management
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• v.40 no.4
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• pp.135-150
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• 2009

Existing bibliometric laws have been established on the basis of well defined science journals with a long history. However, the history of technology innovation research in Korea is young and the scope of the research is diverse compared with other fields. The main purpose of this research can be summarized as follows : Can the traditional bibliometric laws be used to explain the young and diverse data derived from technology innovation studies in Korea. Second, we want to compare the explain ability of the power law, compared with the traditional laws in the field. Third, we propose a quasi index related to the well-known impact factor to measure the contribution of a journal or a group of journals to the development of innovation research in Korea. We confirmed Lotka's and Bradford's laws which are used to measure the productivity of researchers, but we could not support the validity of Price's Square Root law as Nicholls (1998) could not. On the citations to journals, Garfield's laws is not observed. However, the power law fits well the citations to author, journal, article, and book. The estimated parameters between 1.6 and 3.5 are similar to the values in the range of 1.5 and 3 in previous studies. Finally the quasi index shows that the influence of international leading journals on innovation research in Korea is weaker than on innovation studies in the world.

• Journal of the Korea Society of Computer and Information
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• v.13 no.4
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• pp.231-240
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• 2008

In respect complication, group and period, the foreign direct investment of korea is composed of various factors. This paper studies focus on estimating the determinants of foreign direct investment of korea. The region of analysis consist of 7 groups, that is, Asia, Europe, Central and South America, Oceania, Africa, Middle East. Analyzing period be formed over a 67 point(2002. 6${\sim}$2007. 12). In this paper dependent variable setting up an amount of foreign direct investment, explanatory(independent) variables composed of gross domestic product, a balance of current accounts, the foreign exchange rate, employment to population ratio, an average of the rate of operation(the manufacturing industry), consumer price index, the amount of export, wages(a service industry). For an actual proof analysis, LIMDEP 8.0 software, analysis model is random effect in TWECR The result of estimating the determinants of foreign direct investment of korea provides empirical evidences of significance positive relationships between employment to population ratio and wages(a service industry). However this study provides empirical evidences of significance negative relationships between the foreign exchange rate, censurer price index and the amount of export. The explanatory variables, that is, an average of the rate of operation(the manufacturing industry), gross domestic product and a balance of current accounts, are non-significance variables.

• Current Research on Agriculture and Life Sciences
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• v.4
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• pp.163-168
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• 1986

This study was carried out to compare the conditions of Korean and Japanese forestry. Two countries were appeared same trend in forestry condition, so our forestry in future can be estimated with compared Japanese forestry, but the results obtained are as follows ; 1) The average forest area per capita of the world, Japan and Korea are 0.9, 0.23 and 0.16 ha, respectively, this means that Korean forest area is not sufficient. The growing stock of forest per capita is $22.5m^3$ in Japan and $3.9m^3$ in Korea, but timber consumptions per capita are $1m^3$ in Japan and $0.2m^3$ in Korea. Those mean that both countries have not a plentiful resource of forestry. 2) The forestry production activity becomes gradually stagnation. Both in Korea and Japan, the reforestation and stumpage felling area show gradually decreasing tendency, the artificial forest ratio of total forest area is, at present, 28% in Korea and 40% in Japan. 3) In forestry demand aspect, the ratio of imported timber is 79% in Korea and 62.4% in Japan. Because the price index of timber is lower than the general price index, the dullness of forestry-related industries is expected in future. 4) The forestry labour supply has gradually difficulty because of the reduction in farming labour. 5) The managements of national forests show deficit operation, at present, both in Korea and Japan. The results above mentioned are derived form the poor forest resources, therefore, it is considered that rather more and continuous investment is necessary, but also forestry should be invested in the territorial conservation aspect.

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

• Food Science and Preservation
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• v.23 no.7
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• pp.1065-1073
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• 2016

This study investigated the sensory attributes and quality characteristics of Fuji apples based on market commodity price to provide data for quality index of Fuji apples. Samples were purchased from the Garak market (Seoul Agro-Fisheries & Food Corporation) and divided into four groups depending on the price such as group A, B, C, D. There were no significant differences in their volume and weight among groups. In the soluble solid content and total free sugar, A and B group (high price) showed higher content than those of C and D (low price) group. And also, the A group and B, C, D group showed 386.29 mg% and 320.09~359.28 mg% in the total organic acid content, respectively. As an sensory evaluation results, A group and B group were evaluated higher score than those of C and D group in the uniformity of red color and glossiness of skin and unique apple sensory attributes using quantitative descriptive analysis. Consumer test showed similar to quantitative descriptive analysis results in the various sensory attributes. In the analysis results between quality characteristics and sensory attributes of Fuji apples, total acceptability was correlated positively with titratable acidity (r=0.58), soluble solid (r=0.89), soluble solid content/titratable acidity ratio (r=0.42), total free sugar (r=0.36) and total organic acid (r=0.38). Based on principal component analysis of apple's quality characteristics, apples were primary separated along the first principal component (pH, acidity, soluble solid content, total free sugar, organic acid), which accounted for 66.01% of total variance. In addition, principal component analysis of sensory evaluation revealed a total variance for the quantitative descriptive of 55. 65% and a total variance for the consumer test of 55.84%.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.127-146
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• 2017

Services using artificial intelligence have begun to emerge in daily life. Artificial intelligence is applied to products in consumer electronics and communications such as artificial intelligence refrigerators and speakers. In the financial sector, using Kensho's artificial intelligence technology, the process of the stock trading system in Goldman Sachs was improved. For example, two stock traders could handle the work of 600 stock traders and the analytical work for 15 people for 4weeks could be processed in 5 minutes. Especially, big data analysis through machine learning among artificial intelligence fields is actively applied throughout the financial industry. The stock market analysis and investment modeling through machine learning theory are also actively studied. The limits of linearity problem existing in financial time series studies are overcome by using machine learning theory such as artificial intelligence prediction model. The study of quantitative financial data based on the past stock market-related numerical data is widely performed using artificial intelligence to forecast future movements of stock price or indices. Various other studies have been conducted to predict the future direction of the market or the stock price of companies by learning based on a large amount of text data such as various news and comments related to the stock market. Investing on commodity asset, one of alternative assets, is usually used for enhancing the stability and safety of traditional stock and bond asset portfolio. There are relatively few researches on the investment model about commodity asset than mainstream assets like equity and bond. Recently machine learning techniques are widely applied on financial world, especially on stock and bond investment model and it makes better trading model on this field and makes the change on the whole financial area. In this study we made investment model using Support Vector Machine among the machine learning models. There are some researches on commodity asset focusing on the price prediction of the specific commodity but it is hard to find the researches about investment model of commodity as asset allocation using machine learning model. We propose a method of forecasting four major commodity indices, portfolio made of commodity futures, and individual commodity futures, using SVM model. The four major commodity indices are Goldman Sachs Commodity Index(GSCI), Dow Jones UBS Commodity Index(DJUI), Thomson Reuters/Core Commodity CRB Index(TRCI), and Rogers International Commodity Index(RI). We selected each two individual futures among three sectors as energy, agriculture, and metals that are actively traded on CME market and have enough liquidity. They are Crude Oil, Natural Gas, Corn, Wheat, Gold and Silver Futures. We made the equally weighted portfolio with six commodity futures for comparing with other commodity indices. We set the 19 macroeconomic indicators including stock market indices, exports & imports trade data, labor market data, and composite leading indicators as the input data of the model because commodity asset is very closely related with the macroeconomic activities. They are 14 US economic indicators, two Chinese economic indicators and two Korean economic indicators. Data period is from January 1990 to May 2017. We set the former 195 monthly data as training data and the latter 125 monthly data as test data. In this study, we verified that the performance of the equally weighted commodity futures portfolio rebalanced by the SVM model is better than that of other commodity indices. The prediction accuracy of the model for the commodity indices does not exceed 50% regardless of the SVM kernel function. On the other hand, the prediction accuracy of equally weighted commodity futures portfolio is 53%. The prediction accuracy of the individual commodity futures model is better than that of commodity indices model especially in agriculture and metal sectors. The individual commodity futures portfolio excluding the energy sector has outperformed the three sectors covered by individual commodity futures portfolio. In order to verify the validity of the model, it is judged that the analysis results should be similar despite variations in data period. So we also examined the odd numbered year data as training data and the even numbered year data as test data and we confirmed that the analysis results are similar. As a result, when we allocate commodity assets to traditional portfolio composed of stock, bond, and cash, we can get more effective investment performance not by investing commodity indices but by investing commodity futures. Especially we can get better performance by rebalanced commodity futures portfolio designed by SVM model.

• Asian-Australasian Journal of Animal Sciences
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• v.25 no.12
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• pp.1667-1673
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• 2012

The objective of this study was to estimate economic weights of Hanwoo carcass traits that can be used to build economic selection indexes for selection of seedstocks. Data from carcass measures for determining beef yield and quality grades were collected and provided by the Korean Institute for Animal Products Quality Evaluation (KAPE). Out of 1,556,971 records, 476,430 records collected from 13 abattoirs from 2008 to 2010 after deletion of outlying observations were used to estimate relative economic weights of bid price per kg carcass weight on cold carcass weight (CW), eye muscle area (EMA), backfat thickness (BF) and marbling score (MS) and the phenotypic relationships among component traits. Price of carcass tended to increase linearly as yield grades or quality grades, in marginal or in combination, increased. Partial regression coefficients for MS, EMA, BF, and for CW in original scales were +948.5 won/score, +27.3 $won/cm^2$, -95.2 won/mm and +7.3 won/kg when all three sex categories were taken into account. Among four grade determining traits, relative economic weight of MS was the greatest. Variations in partial regression coefficients by sex categories were great but the trends in relative weights for each carcass measures were similar. Relative economic weights of four traits in integer values when standardized measures were fit into covariance model were +4:+1:-1:+1 for MS:EMA:BF:CW. Further research is required to account for the cost of production per unit carcass weight or per unit production under different economic situations.

• Journal of the Korean Regional Science Association
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• v.34 no.1
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• pp.61-75
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• 2018

The study on urban regeneration began in 2006 and has actively proceeded for 10 years. Also, there are a lot of studies related to urban regeneration have analyzed urban regeneration effects but have just focused on qualitative analysis. Therefore, this study has intended to analyze the urban regeneration effects of Junang-Dong, a central business district in Cheong City, where urban regeneration projects have been undertaking, in the manner of quantitative analysis. To reach this objective, we selected such indicators as floating population, public land price, a and vacancy rate, and set analysis time span from 2011 to 2016, when urban regeneration projects have been actively operated. As a result, this study has found the following results. 1) As for floating population, population index grew gradually and showed an drastic increase of about 65 percent in 2014 when the project was active. 2) Public land price of Jungang-Dong has been showed the greatest increase from 2011 to 2012 when the city started to regenerate, and slight decrease from 2015 to 2016 with the gradual decrease until 2015. 3) In terms of vacancy rate, there has been declined about 15 percent from 27 percent to 12 percent, with a steady downward curve. This study has dedicated itself to analyzing the urban regeneration effects quantitatively especially in commercial business district.

• Journal of the Korean Geographical Society
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• v.48 no.6
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• pp.879-896
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• 2013

The assessed land values and housing prices have been widely utilized as a basic information for the land and house trades and for evaluating governmental and local taxes. However, there exists a price difference in actual markets between the assessment level and assessed land values or housing prices. This paper emphasizes the spatial mismatch between the assessed land values and housing market prices and particularly addresses the following two aspects by focusing on spatial effects of the modifiable areal units, which would substantially affect the estimation of the assessed land values and housing prices. First, we examine the spatial distributions of the assessed land values and housing market prices, and the gap between those prices, on the basis of the aggregated spatial units(i.e., aggregation districts). Second, we explore the scale effect of the MAUP(modifiable areal unit problem) generally embedded in estimating the prices of the sampled standard lands and houses, and calibrating the correction index for the land values and housing prices for the individuals. For the application, we analysed the land values and housing prices in Seoul utilizing GIS and statistical software. As a result, some spatial clusters that the housing market prices are significantly higher than the assessed land values were identified at a finer geographic level. Also, it was empirically revealed that the statistical results from the regression of regional variables on the assessed land values for the individuals are significantly affected by the aggregation levels of the spatial units.