• The Journal of Information Technology
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• v.5 no.1
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• pp.157-171
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• 2002

The evolution of transaction-based business model is upon us. The business models of many e-Marketplace in their early stages have typically been based on transaction fees. Many e-Marketplaces have even called out transaction revenues as a core element of their business plans. The transaction business represents the most simple of business models, but it does not provide a long-term sustain able advantage. For buyer's convenience, wide selection and test price hold appeal. For suppliers, the extended global market reach and direct access to customers and consortiums of customers is powerful. To maxmize leverage of these new e-marketplace, you must from both a buyer perspective as well as a supplier perspective. Also required is a strategy that takes in account all of the various e-Marketplace transaction standards and one that allows the easy accomodation to new e-marketplace as the market change. These new e-marketplace will need to be factored into the sales channel strategies. To be successful, integration with these e-marketplaces should occur at a complete business process level. This study explored independent and industry-backed current and future business models that are emerging in the B2B electronic market industry, as well as value -added service models for the Net market maker industry. E-Marketplaces will evolve into digital work environments in which real industry collaboration can occur.

• Journal of Korea Society of Industrial Information Systems
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• v.24 no.6
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• pp.81-93
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• 2019

As customers' needs are more diversified, the issue of managing product variety has become more important to manufacturers. It is because an increase in product variety may cause various inefficiencies in operations, while satisfying more diverse needs. Consequently, firms have introduced the concept of modularity to improve operational performance. Yet there are only a few studies which analytically investigate the effect of modularity in new product development (NPD). Therefore, this research develops an analytical model of exploring the effect of modularity on firm profitability when a component built upon new technology is introduced into an existing product, and provides important managerial implications on the NPD and technology management, which can guide the decision making on modularity in practice. The results show that it is necessary to increase modularity level when i) the product is easy to upgrade, ii) the product's price should be high due to external factors, and iii) the effect of new technology investment is uncertain, while it is desirable to increase the investment cost for introducing new products with low demand elasticity for modularity.

• Journal of Digital Convergence
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• v.15 no.7
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• pp.359-365
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• 2017

This study was conducted structural model analysis focusing on the factors influencing UHDTV service usage. The perceived quality, innovativeness, price sensitivity are adopted as independent variables and perceived usefulness, perceived easy use are adopted as intervening variables. Especially symbolism used it as a control variable. As a result of the analysis by PLS, the influence coefficient of perceived quality was significantly higher than other variables. However, the combined effect of symbolism and perceived quality has a negative effect on perceived usefulness, and the more the users consider the symbolism of UHDTV usage, the more negative the evaluation of UHD quality and usefulness. With the launch of the terrestrial UHDTV service in May 2017, the most important issue is the production and distribution of high-quality content that users want.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.4
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• pp.55-64
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• 2021

The expansion of upland crop cultivation in rice paddy fields is recommended by the Korean government to solve the problem of falling rice price and reduction of rice farmer's income due to oversupply of rice. However, water use efficiency is significantly influenced by the land use change from paddy field to upland. Therefore, this study aimed to evaluate the water budget of soybean grown in using APEX (Agricultural Policy and Environmental eXtender) model. The amount of runoff was measured in a test bed located in Iksan, Jeollabu-do and used to calibrate and validate the simulated runoff by APEX model. From 2019 to 2020, the water budget of soybean grown in uplands were estimated and compared with the one grown in paddy fields. The calibration result of AP EX model for runoff showed that R² (Coefficient of determination) and NSE (Nash-Sutcliffe efficiency) were 0.90 and 0.89, respectively. In addition, the validated results of R² and NSE were 0.81 and 0.62, respectively. The comparative study of each component in water budget showed that the amounts of evapotranspiration and percolation estimated by APEX model were 549.1 mm and 375.8mm, respectively. The direct runoff amount from upland was 390.1 mm, which was less than that from paddy fields. The average amount of irrigation water was 28.7 mm, which was very small compared to the one from paddy fields.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.6
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• pp.3813-3820
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• 2014

Recently, with the increase in electrical consumption and the unbalanced power demand and supply, the power reserve rate is becoming smaller and the reliability of the power supply is deteriorating. Under this circumstance, a Battery Energy Storage System (BESS) is considered to be an essential countermeasure for demand side management. On the other hand, an economic evaluation is a critical issue for the introduction of a power system because the cost of BESS is quite high. Therefore, this paper presents economic evaluation method for utility use by considering the best mix method and successive approximation method, and an economic evaluation method for customer use by considering the peak shaving function based on the real time price. From a case study on a model power system and educational customer, it was confirmed that the proposed method is a practical tool for the economic analysis of BESS.

• Journal of Intelligence and Information Systems
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• v.23 no.4
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• pp.147-168
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• 2017

There have been many studies on accurate stock market forecasting in academia for a long time, and now there are also various forecasting models using various techniques. Recently, many attempts have been made to predict the stock index using various machine learning methods including Deep Learning. Although the fundamental analysis and the technical analysis method are used for the analysis of the traditional stock investment transaction, the technical analysis method is more useful for the application of the short-term transaction prediction or statistical and mathematical techniques. Most of the studies that have been conducted using these technical indicators have studied the model of predicting stock prices by binary classification - rising or falling - of stock market fluctuations in the future market (usually next trading day). However, it is also true that this binary classification has many unfavorable aspects in predicting trends, identifying trading signals, or signaling portfolio rebalancing. In this study, we try to predict the stock index by expanding the stock index trend (upward trend, boxed, downward trend) to the multiple classification system in the existing binary index method. In order to solve this multi-classification problem, a technique such as Multinomial Logistic Regression Analysis (MLOGIT), Multiple Discriminant Analysis (MDA) or Artificial Neural Networks (ANN) we propose an optimization model using Genetic Algorithm as a wrapper for improving the performance of this model using Multi-classification Support Vector Machines (MSVM), which has proved to be superior in prediction performance. In particular, the proposed model named GA-MSVM is designed to maximize model performance by optimizing not only the kernel function parameters of MSVM, but also the optimal selection of input variables (feature selection) as well as instance selection. In order to verify the performance of the proposed model, we applied the proposed method to the real data. The results show that the proposed method is more effective than the conventional multivariate SVM, which has been known to show the best prediction performance up to now, as well as existing artificial intelligence / data mining techniques such as MDA, MLOGIT, CBR, and it is confirmed that the prediction performance is better than this. Especially, it has been confirmed that the 'instance selection' plays a very important role in predicting the stock index trend, and it is confirmed that the improvement effect of the model is more important than other factors. To verify the usefulness of GA-MSVM, we applied it to Korea's real KOSPI200 stock index trend forecast. Our research is primarily aimed at predicting trend segments to capture signal acquisition or short-term trend transition points. The experimental data set includes technical indicators such as the price and volatility index (2004 ~ 2017) and macroeconomic data (interest rate, exchange rate, S&P 500, etc.) of KOSPI200 stock index in Korea. Using a variety of statistical methods including one-way ANOVA and stepwise MDA, 15 indicators were selected as candidate independent variables. The dependent variable, trend classification, was classified into three states: 1 (upward trend), 0 (boxed), and -1 (downward trend). 70% of the total data for each class was used for training and the remaining 30% was used for verifying. To verify the performance of the proposed model, several comparative model experiments such as MDA, MLOGIT, CBR, ANN and MSVM were conducted. MSVM has adopted the One-Against-One (OAO) approach, which is known as the most accurate approach among the various MSVM approaches. Although there are some limitations, the final experimental results demonstrate that the proposed model, GA-MSVM, performs at a significantly higher level than all comparative models.

• Journal of Intelligence and Information Systems
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• v.22 no.4
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• pp.19-43
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• 2016

This study examines the causes of the Asian exchange rate crisis and compares it to the European Monetary System crisis. In 1997, emerging countries in Asia experienced financial crises. Previously in 1992, currencies in the European Monetary System had undergone the same experience. This was followed by Mexico in 1994. The objective of this paper lies in the generation of useful insights from these crises. This research presents a comparison of South Korea, United Kingdom and Mexico, and then compares three different models for prediction. Previous studies of economic crisis focused largely on the manual construction of causal models using linear techniques. However, the weakness of such models stems from the prevalence of nonlinear factors in reality. This paper uses a structural equation model to analyze the causes, followed by a neural network model to circumvent the linear model's weaknesses. The models are examined in the context of predicting exchange rates In this paper, data were quarterly ones, and Consumer Price Index, Gross Domestic Product, Interest Rate, Stock Index, Current Account, Foreign Reserves were independent variables for the prediction. However, time periods of each country's data are different. Lisrel is an emerging method and as such requires a fresh approach to financial crisis prediction model design, along with the flexibility to accommodate unexpected change. This paper indicates the neural network model has the greater prediction performance in Korea, Mexico, and United Kingdom. However, in Korea, the multiple regression shows the better performance. In Mexico, the multiple regression is almost indifferent to the Lisrel. Although Lisrel doesn't show the significant performance, the refined model is expected to show the better result. The structural model in this paper should contain the psychological factor and other invisible areas in the future work. The reason of the low hit ratio is that the alternative model in this paper uses only the financial market data. Thus, we cannot consider the other important part. Korea's hit ratio is lower than that of United Kingdom. So, there must be the other construct that affects the financial market. So does Mexico. However, the United Kingdom's financial market is more influenced and explained by the financial factors than Korea and Mexico.

• KOREAN JOURNAL OF CROP SCIENCE
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• v.51 no.5
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• pp.466-476
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• 2006

The objective of this study was to compare and analyze the acceptability and consumption attitude for soy foods between Korean and Canadian university students as young consumers. This survey was carried out by questionnaire and the subjects were n=516 in Korea and n=502 in Canada. Opinions for soy foods in terms of general knowledge were that soy foods are healthy (86.5% in Korean and 53.4% in Canadian) or neutral (11.6% in Korean and 42.8% in Canadian), dairy foods can be substituted by soy foods (51.9% in Korean and 41.8% in Canadian), and soy foods are not only for vegetarians and milk allergy Patients but also for ordinary People (94.2% in Korean and 87.6% in Canadian). In main sources of information about soy foods, the rate by commercials on TV, radio or magazine was the highest (58.0%) for Korean students and the rate by family or friend was the highest(35.7%) for Canadian students. In consumption attitude, all of Korean students have purchased soy foods but only 55.4% of Canadian students have purchased soy foods, and soymilk was remarkably recognized and consumed then soy beverage and margarine in order. 76.4% of Korean students and 65.1% of Canadian students think soy foods are general and popular and can purchase easily, otherwise, in terms of price, soy foods were expensively recognized as 'more expensive than dairy foods' was 59.1% (Korean) and 54.7% (Canadian), and 'similar to dairy foods' was 36.8% (Korean) and 39.9% (Canadian). Major reasons for the rare consumption were 'I am not interested in soy foods' in Korean students (27.3%) and 'I prefer dairy foods to soy foods' in Canadian students (51.7%). However, consumption of soy foods in both countries are very positive and it will be increased.

• Journal of the Korean association of regional geographers
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• v.22 no.2
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• pp.307-330
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• 2016

This article aims to explain how Gangnam, as a model and standard of compressed urbanization in South Korea, was created. Gangnam and Gangnam-style urbanization need attention not only because they contrast with Korea's urbanization in the past as well as urbanization in the West but also they provide an important model in contemporary Korea's politics, economy and culture. However, there are little studies of how Gangnam's peculiar urbanism was created. To fill this gap, this article will first capture Gangnam's peculiar urbanism as a material landscape and sociocultural lifestyle. Gangnam-style urbanism is (a) materially characterized by high-rise apartment complexes owned by the middle and upper class for dwelling and asset growth and (b) socio-culturally characterized by political conservatism, public indifference, competition over academic performance, appearance, and fashion, and nightlife. Then it will show Gangnam's archetype was created in a spatially and temporally compressed way in and through the spatial selectivity of Korean anti-communist authoritarian developmental state strategies: (1) anti-communism led to the diffusion and accommodation of the population through apartments in Gangnam in the context of its confrontation with North Korea and the fast-growing population of Seoul; (2) military authoritarianism excluded the low-income class and the urban poor from urban development; and (3) the developmental state adopted selective housing policy which treated construction companies and the middle class preferentially through exceptional zoning and price distortions, promoting the construction of apartment in Gangnam and its resultant uneven development.

• Journal of Distribution Research
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• v.16 no.4
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• pp.29-64
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• 2011

Overview of Research: Product availability is one of important competences of store to fulfill consumer needs. If stock-outs which means a product what consumer wants to buy is not available occurs, consumer will face decision-making uncertainty that leads to consumer's negative responses such as consumer dissatisfaction on store. Stockouts was much studied in the field of academia as well as practice in other countries. However, stock-outs has not been researched at all in Marketing and/or Distribution area in Korea. The main objectives of this study are to find out determinants of consumer responses such as Substitute, Delay, and Leave(SDL) when consumer encounters out-of-stock situation and then to examine the effects of these factors on consumer responses. Specifically, this study focuses on situational characteristics(e.g., purchase urgency and surprise), store characteristics (e.g., product assortment and store convenience), and consumer characteristics (e.g., brand loyalty and store loyalty). Then, this study empirically investigates relationships these factors with consumers behaviors such as product substitution, purchase delay, and store switching.