• Journal of Korean Society for Quality Management
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• v.42 no.2
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• pp.253-264
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• 2014

Purpose: The aim of this study is to gain a competitive advantage in the global marketplace by examining the current situation of three domestic Food Dehydrator companies' products. Food Dehydrators are sort of small domestic appliances(SDA), first introduced by Korean companies. Furthermore, this study suggests the improvement plans in the rapidly changing world situation. Methods: Evaluate through comparing three domestic Food Dehydrator companies' products based on the PQI(Premium Quality Index) model, developed by product quality evaluation experts group. Results: At first, we classified evaluation factors into three parts - usability quality, emotional quality - and each of the factors includes sub factors. Under this condition, the results of this study are as follows; the brand quality is remaining at a high satisfaction level compare to other two factors but emotional quality is assessed to be low. This study has shown at customers consider brand and usability quality factors as the most important factor due to the nature of the product. Conclusion: As the possibility of increasing customer needs such as product design and sensitive quality besides usability quality has risen in a competitive global market, the manufacturing companies in Korea are recommended to put forth the necessary effort to improve their product quality, especially in terms of emotional quality.

• Korean Journal of Construction Engineering and Management
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• v.14 no.1
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• pp.43-51
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• 2013

The changes in business structure of domestic construction companies suggest that there is a close relationship between the volume of overseas project and a company's financial condition. Based on this assumption, this study conducts an empirical analysis on a relationship between overseas project and financial stability of a construction company. The ratio of liquidity and liability was used as liquidity index and stability index respectively. The analysis was based on quarterly time-series data between 2000 and 2010. Two models were constructed for the analysis: Model 1 was based on the liquidity ratio and the amount of domestic and overseas construction project; Model 2 was based on the debt ratio and the amount of domestic and overseas construction project. The analysis results showed that the increasing amount of overseas project facilitated short-term financing with greater liquidity, and yet it was not very effective in lowering the debt ratio. This suggests that the dramatic increase in overseas construction project, which is observed recently, is not entirely an optimistic sign.

• Journal of the Korean Operations Research and Management Science Society
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• v.40 no.2
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• pp.1-17
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• 2015

In this paper, we propose a portfolio selection model utilizing a Markov chain for investing in the foreign exchange market based on market forecasts and exchange rate movement predictions. The proposed model is utilized to compute optimum investment portfolio weights for investing in margin-based markets such as the FX margin market. We further present an objective investment algorithm for applying the proposed model in real-life investments. Empirical performance of the proposed model and investment algorithm is evaluated by conducting an experiment in the FX market consisting of the 7 most traded currency pairs, for a period of 9 years, from the beginning of 2005 to the end of 2013. We compare performance with 1) the Dollar Index, 2) a 1/N Portfolio that invests the equal amount in the N target assets, and 3) the Barclay BTOP FX Index. Performance is compared in terms of cumulated returns and Sharpe ratios. The results suggest that the proposed model outperforms all benchmarks during the period of our experiment, for both performance measures. Even when compared in terms of pre- and post-financial crisis, the proposed model outperformed all other benchmarks, showing that the model based on objective data and mathematical optimization achieves superior performance empirically.

• Journal of Digital Convergence
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• v.16 no.7
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• pp.71-78
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• 2018

The purpose of this study is to investigate the impact of win-win growth activity of domestic large firms on their management performance. we classified the management performance into four factors such as ROE(Return On Equity), ROA(Return On Assets), net income to net sales and operating income to sales. The finding of this study is outlined as follows. This paper show that the win-win growth activity has a negative impact on the firms' management performance. This study shows that win-win growth activity could generate additional costs of business activity. So, we think that industrial policy is needed for expansion of win-win growth activity.

• Journal of the Korean Data and Information Science Society
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• v.25 no.6
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• pp.1253-1262
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• 2014

Regression tree is a tree-structured solution in which a simple regression model is fitted to the data in each node made by recursive partitioning of predictor space. There have been many efforts to apply tree algorithms to various regression problems like logistic regression and quantile regression. Recently, algorithms have been expanded to the panel data analysis such as RE-EM algorithm by Sela and Simonoff (2012), and extension of GUIDE by Loh and Zheng (2013). The algorithms are briefly introduced and prediction accuracy of three methods are compared in this paper. In general, RE-EM shows good prediction accuracy with least MSE's in the simulation study. A RE-EM tree fitted to business survey index (BSI) panel data shows that sales BSI is the main factor which affects business entrepreneurs' economic sentiment. The economic sentiment BSI of non-manufacturing industries is higher than that of manufacturing ones among the relatively high sales group.

• Informatization Policy
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• v.29 no.4
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• pp.43-66
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• 2022

With the development of artificial intelligence technology, competition for artificial intelligence technology patents around the world is intensifying. During the period 2000 ~ 2021, artificial intelligence technology patent applications at the US Patent and Trademark Office have been steadily increasing, and the growth rate has been steeper since the 2010s. As a result of analyzing Korea's artificial intelligence technology competitiveness through patent indices, it is evaluated that patent activity, impact, and marketability are superior in areas such as auditory intelligence and visual intelligence. However, compared to other countries, overall Korea's artificial intelligence technology patents are good in terms of activity and marketability, but somewhat inferior in technological impact. While noise canceling and voice recognition have recently decreased as topics for artificial intelligence, growth is expected in areas such as model learning optimization, smart sensors, and autonomous driving. In the case of Korea, efforts are required as there is a slight lack of patent applications in areas such as fraud detection/security and medical vision learning.

• The Journal of Asian Finance, Economics and Business
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• v.7 no.12
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• pp.109-114
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• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.

• Journal of Technology Innovation
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• v.19 no.3
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• pp.115-140
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• 2011

The fact that innovation activities of venture firms and start-ups play crucial role in driving industrial development and economic growth has significantly increased the importance of business incubator and techno-park which promote new businesses creations. This review paper aims at not only generating performance measurement index of business incubators but also categorizing performance determinants in accordance with three different theoretical perspectives of resource-based view, strategy patterns, and social networks. Futhermore, as future direction of research, this paper emphasizes structured research efforts on the critical effects of incubator's governance patterns, external and regional contexts, and analysis of government incubator policy.

• Journal of Information Technology Services
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• v.4 no.1
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• pp.129-139
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• 2005

This paper proposes a framework of Operational Risk-based Business Continuity System(ORBCS), and develops protection system for operational risk through operational risk assessment and loss distribution approach based on risk management guideline announced in the basel II. In order to find out financial operational risk, business processes of domestic bank are assorted by seven event factors and eight business activities so that we can construct the system. After we find out KRI(Key Risk Indicator) index, tasks and risks, we calculated risk possibility and expected cost by analyzing quantitative data, questionnaire and qualitative approach for AHP model from the past events. Furthermore, we can assume unexpected cost loss by using loss distribution approach presented in the basel II. Each bank can also assume expected loss distributions of operational risk by seven event factors and eight business activities. In this research, we choose loss distribution approach so that we can calculate operational risk. In order to explain number of case happened, we choose poisson distribution, log-normal distribution for loss cost, and estimate model for Monte-Carlo simulation. Through this process which is measured by operational risk. of ABC bank, we find out that loss distribution approach explains closer unexpected cost directly compared than internal measurement approach, and makes less unexpected cost loss.

• Proceedings of the Safety Management and Science Conference
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• 2009.04a
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• pp.455-475
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• 2009

According to the returns of Housing and business cycle over the period 1992 to 2007, it is a measure of the total volatility faced by investors in Housing properties. First, it isn't a distinct difference from business cycle contrary to U.S. Second, the rise of purchase price in total apartments moves up the consumer price index. According to the cross-sectional dispersion of returns and growth in net operating income (NOI) of apartments, industrial, retail and office properties using panel data for U.S. metropolitan areas over the period 1986 to 2002, it is a measure of the total volatility faced by investors in commercial real estate. To the extent that most of that volatility is difficult to diversify, cross-sectional dispersion may be an appropriate measure of risk.