• Journal of Distribution Science
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• v.14 no.8
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• pp.123-128
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• 2016

Purpose - Korean Wave that overspreads around Asia and America, especially the Korean beauty wave, has reached Mongolia and Mongolian consumers. Mongolia consumers usually prefer foreign cosmetic brands to local brands, because the local brands cannot satisfy fast changing needs and wants of local consumers. Research design, data, and methodology - Based on previous studies about life style of Mongolian consumers, advertisement properties and consumer behaviors, we propose a research model and related hypothesis. In order to test hypotheses, we analyzed 366 survey data out of 376 by eliminating improper 10 responses. Factor analysis and reliability analysis was conducted by SPSS 22.0. We used multiple regression analysis and parameter analysis to test the relation between variables. Results - As exploring the Mongolian consumers' current usage of cosmetic products, we found that the customers' focus is how the products fit with their skin. Mongolian consumers often get the information about cosmetic products through TV and internet. Mongolian consumers show positive attitudes on the appearance of Korean celebrities in responsibility, while there is no significant effect on attractiveness. Mongolian consumer's behaviors toward brand have positive effect on both responsibility and attractiveness of Korean commercial celebrities. Responsibility and attractiveness of Korean commercial celebrities have positive effect on the behaviors toward advertisements of cosmetic products. Conclusions - Behaviors toward advertisements of cosmetic products have positive effect on both purchase intention and loyalty of customer. Responsibility and attractiveness of Korean commercial celebrities have positive effect on mediating variable of behavior toward advertisement and independent variable of purchase intention. Responsibility and attractiveness of Korean commercial celebrities have positive effect on mediating variable of behavior toward advertisement and independent variable of loyalty of customer. In order to improve the effect of advertisements, firms need to consider not only the technique of the model but also the image of model in regard to trust and professionalism appealing to consumers. In addition, firms need to choose the model who fits in with the image of the firms and the products and service of the firms. Finally, Mongolian consumers tend to acquire the shopping information through TV advertisements, especially featuring Korean popular stars, thus, TV advertisements can be a wise option in Mongolian cosmetic market.

• Proceedings of the IEEK Conference
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• 2000.09a
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• pp.429-432
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• 2000

We propose a new frame rate up-conversion algorithm for high quality video. In the proposed scheme bidirectional motion estimation (ME) is performed to construct the motion vector. (MV) field for the frame to be interpolated. Unlike conventional motion-compensated interpolation (MCI) algorithms, the proposed technique does not produce any overlapped pixel and hole region in the interpolated frame, and thus can utilize the overlapped block motion compensation technique to reduce the blocking artifacts. The proposed algoritm is very simple to implement on consumer products when compared to conventional MCI methods. Computer simulation shows a high visual performance of the proposed frame rate up-conversion algorithm.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.7
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• pp.23-29
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• 2012

A single line diagram is a graphic user interface to represent electrical connectivity between power equipments in distribution automation systems. This paper proposes a new single line auto-drawing technique based on the service oriented architecture. Web service, CIM(Common Information Model) and SVG(Scalable Vector Graphics) are adopted to implement SOA concept. A web service demo system was established which is configured with the service provider, consumer and broker to verify the feasibility of this study.

• IE interfaces
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• v.20 no.4
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• pp.448-457
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• 2007

The small & micro business has the characteristics of both consumer credit risk and business credit risk. In predicting the bankruptcy for small-micro businesses, the problem is that in most cases, the financial data for evaluating business credit risks of small & micro businesses are not available. To alleviate such problem, we propose a bankruptcy prediction mechanism using the credit card sales information available, because most small businesses are member store of some credit card issuers, which is the main purpose of this study. In order to perform this study, we derive some variables and analyze the relationship between good and bad signs. We employ the new statistical learning technique, support vector machines (SVM) as a classifier. We use grid search technique to find out better parameter for SVM. The experimental result shows that credit card sales information could be a good substitute for the financial data for evaluating business credit risk in predicting the bankruptcy for small-micro businesses. In addition, we also find out that SVM performs best, when compared with other classifiers such as neural networks, CART, C5.0 multivariate discriminant analysis (MDA), and logistic regression.

• Journal of Korea Society of Industrial Information Systems
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• v.14 no.5
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• pp.209-225
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• 2009

This research has been studied to analyze affecting factors for the consumer's acceptance to mobile advertisement by worldwide survey into mobile users of Korea, U.S. and Japan. Based on TAM & Flow theory, our research adopts some factors for a theoretical model such as entertainment, information, irritation, credibility, flow experience, attitudes and acceptance intention. And our research collects data from common consumers & students of each countries to try comparative study with mobile users who has different scope & environment of markets. This data was analyzed based on using AMOS, the structural equation modeling and a second-generation multi variant technique, and has gained distinct advantages over other technique.

• Journal of Korea Trade
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• v.24 no.8
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• pp.39-62
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• 2020

Purpose - Korean exports account for a vast proportion of Korean GDP, and large volumes of Korean products are sold in the United States. Identifying and characterizing actual and potential product hazards related to Korean products is critical to safeguard Korean export trade, as severe quality issues can impair Korea's reputation and reduce global consumer confidence in Korean products. In this study, we develop country-of-origin-based product risk analysis methods for social media with a specific focus on Korean-labeled products, for the purpose of safeguarding Korean export trade. Design/methodology - We employed two social media datasets containing consumer-generated product reviews. Sentiment analysis is a popular text mining technique used to quantify the type and amount of emotion that is expressed in the text. It is a useful tool for gathering customer opinions regarding products. Findings - We document and discuss the specific potential risks found in Korean-labeled products and explain their implications for safeguarding Korean export trade. Finally, we analyze the false positive matches that arise from the established dictionaries that were used for risk discovery and utilize these classification errors to suggest opportunities for the future refinement of the associated automated text analytic methods. Originality/value - Various studies have used online feedback from social media to analyze product defects. However, none of them links their findings to trade promotion and the protection of a specific country's exports. Therefore, it is important to fill this research gap, which could help to safeguard export trade in Korea.

• Journal of the Korean Society of Food Culture
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• v.33 no.2
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• pp.199-205
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• 2018

This study has utilized the Quality Function Deployment (QFD) technique in order to plan the tangible (menu) and intangible (service) product of dumpling restaurant. The engineering characteristics of tangible products were classified into product planning, purchase management, production management, and information management based on the production system of foodservice. The engineering characteristics of intangible products were also classified into physical evidence, human interaction, and pre-communication based on the service operation and delivery system. As a result of analyzing the QFD, it was found that the customer hope the hygiene factor and response factor to be improved. It is analyzed that product planning, information management, and production management should be improved first in terms of engineering characteristics considering consumer needs. In the future, by utilizing the systematic product development process that the requirements of tangible and intangible product consumers are converted to the engineering characteristics, the development of competitive product within the market will be possible, and furthermore it is expected to be useful for reducing the unnecessary time and design costs due to failure of product development.

• Journal of Korean Institute of Industrial Engineers
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• v.28 no.3
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• pp.331-343
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• 2002

This paper proposes a fuzzy rule-based model as a means to build usability models between emotional satisfaction and design variables of consumer products. Based on a subtractive clustering algorithm, this model obtains partially overlapping rules from existing data and builds multiple local models each of which has a form of a linear regression equation. The best subset procedure and cross validation technique are used to select appropriate input variables. The proposed technique was applied to the modeling of luxuriousness, balance, and attractiveness of office chairs. For comparison, regression models were built on the same data in two different ways; one using only potentially important variables selected by the design experts, and the other using all the design variables available. The results showed that the fuzzy rule-based model had a great benefit in terms of the number of variables included in the model. They also turned out to be adequate for predicting the usability of a new product. Better yet, the information on the product classes and their satisfaction levels can be obtained by interpreting the rules. The models, when combined with the information from the regression models, are expected to help the designers gain valuable insights in designing a new product.

• The Journal of Asian Finance, Economics and Business
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• v.8 no.5
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• pp.971-977
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• 2021

The purpose of this research paper is: (1) to describe the service quality index; (2) describe the data quality index; and (3) describe the anti-corruption index of BPS Trenggalek, Indonesia. The approach chosen is quantitative with the type of survey research. The primary data collection technique was mainly based on a questionnaire distributed to 40 respondents, namely BPS service users in 5 (five) categories: the private sector, the banking industry, academics, offices, or agencies in Trenggalek Regency and universities. The results showed that the quality of BPS services was good and the data quality index where the respondents were satisfied with the data presented by BPS. Meanwhile, testing the anti-corruption index shows that BPS Trenggalek is very anti-corruption in providing services to consumers. The findings of this study suggested that to improve service quality, it is necessary to pay attention to several aspects, including published service requirements, easy requirements to be fulfilled, published procedure information, clear service process flow, published service times, and costs/tariffs are communicated. This study suggests updating data, data relevance, data accessibility, and data completeness to improve data quality. Furthermore, to maintain the very anti-corruption predicate, this study suggests maintaining service by upholding the prevailing ethics and norms.

• Journal of Korean Institute of Industrial Engineers
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• v.27 no.3
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• pp.305-314
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• 2001

In this paper, we construct an automatic evaluation system of psychological feeling for corporate identity (CI) symbol mark based on a fuzzy neural network technique. The system is modelled by trainable fuzzy inference rules with several input variables (qualitative and quantitative design components of CI symbol mark) and a single output variable (consumer's feeling). The back propagation learning algorithm, which is a conventional learning method of multilayer feedforward neural networks, is used for parameter identification of the fuzzy inference system. The learning ability to train data and the generalization ability to test data are evaluated for the proposed evaluation system by computer simulations.