• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.154-163
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• 2017

Collaborative filtering, one of the most widely used techniques to build recommender systems, is based on the idea that users with similar preferences can help one another find useful items. Credit card user behavior analytics show that most customers hold three or less credit cards without duplicates. This behavior is one of the most influential factors to data sparsity. The 'cold-start' problem caused by data sparsity prevents recommender system from providing recommendation properly in the personalized credit card recommendation scenario. We propose a personalized credit card recommender system to address the cold-start problem, using multiple user profiles. The proposed system consists of a training process and an application process using five user profiles. In the training process, the five user profiles are transformed to five user networks based on the cosine similarity, and an integrated user network is derived by weighted sum of each user network. The application process selects k-nearest neighbors (users) from the integrated user network derived in the training process, and recommends three of the most frequently used credit card by the k-nearest neighbors. In order to demonstrate the performance of the proposed system, we conducted experiments with real credit card user data and calculated the F1 Values. The F1 value of the proposed system was compared with that of the existing recommendation techniques. The results show that the proposed system provides better recommendation than the existing techniques. This paper not only contributes to solving the cold start problem that may occur in the personalized credit card recommendation scenario, but also is expected for financial companies to improve customer satisfactions and increase corporate profits by providing recommendation properly.

• Culinary science and hospitality research
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• v.16 no.1
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• pp.191-208
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• 2010

The hotel business should enhance a service quality in order to improve management skills and profits. However, when compared the size of foodservice industry and hotel, it is show that the hotel management systems are insufficient. In this respect, this study examines how the culture of hotel business affects to service quality. The results of the analysis are as follows. First, the culture of hotel business affects restaurant tendency. Consequently, the hotel, which is open-minded culture, copes with the external changes in a flexible manner. Second, the culture of hotel business affects hotel management skills. Good culture of the business creates the positive result toward the employees, customers, prime cost and inventory control. Third, hotel restaurant tendency affects to efficient hotel service quality and management performance. Fourth, change of hotel management skills brings difference of service quality and management performance. Good hotel management skills will be able to raise the competitive power between hotels. In the future, various empirical researches are continuously expected. By doing so, the result of the study helps to scholars and hotel managers.

• Journal of Service Research and Studies
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• v.8 no.2
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• pp.41-65
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• 2018

With the dawn of society where individuals or enterprises based on data generate infinite profits, the significance of database operation management is growing centering on data quality. However, there are not many South Korean public or private entities managing them systematically. Against this backdrop, this study sought to investigate the current status and problems and explore how to improve from the perspective of auditors. To implement this study, audit checklist was improved and, based on it, auditors and IT experts were surveyed. The final data were analyzed to test the study hypotheses empirically. As a result of the analysis, it was found that the auditors had been highly satisfied with all of the items on the improved audit checklist for data quality-based database operation management. Moreover, non-auditors were also found to regard them within their acceptable range. This study is expected to help improve information system operation audit and enterprises data operation management.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.29 no.2
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• pp.83-91
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• 2006

Internet shopping mall has become a huge distribution channel with dramatic growth in recent years. The number of consumers has exponentially increased as the scale of shopping mall has been large so that shopping malls with thousands or millions of consumers become a general case. However, it is essential to evaluate whether current assortment of consumers is proper or not in the strategic aspect in order to operate Internet shopping mall effectively and gain profits. That is, it is important to evaluate whether consumer strategy of corporation is proper or not from the corporation. Despite this business importance, consumer assortment has not been evaluated well and related study is not sufficient. This study supposes a framework for consumer assortment evaluation, which evaluates whether consumer assortment of Internet shopping mall is proper or not. In the framework for consumer assortment evaluation, analysis data based on order data and consumer data in database is made. Then, four factors, consumer maintenance rate, consumer profitability, consumer securing rate and consumer conversion are setup, and 22 measurement indexes are drawn. Finally, a consumer assortment evaluation score card is made by integrating them. This study has applied a supposed framework to a domestic typical community based shopping mall, and it is expected that the evaluation result will be used as informant strategic information to operate the shopping mall effectively.

• Journal of Bio-Environment Control
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• v.14 no.2
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• pp.114-118
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• 2005

The experiment was conducted to establish the blanching culture of chicon expected to become exporting crop, for preventing Korea fiom importing the ffreign chicon and increasing the growers' profits, the days of blanching culture are based on the 5 treatments such as 10 days, 15 days ,20 days, 25 days, and 30 days. In the blanching culture days of chicory, the growth was good as blanching culture days were longer, there were too many outer leaves, and the ratio of bolting was $16\%$ on the 25 days, $30\%$ on the 30days. On the 10th day, the weight of chicon was light, the hardness was low, the density was low. The quality of chicon had no differences among the treatments. Therefore, the optimal condition for blanching culture of chicory is that the days of blanching culture is 20 days.

• Journal of Digital Convergence
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• v.17 no.11
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• pp.569-576
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• 2019

The purpose of this study was to analyze the sports ethics awareness of college student athletes. To this end, data was collected from 312 college student athletes. The collected data were analyzed by descriptive statistic and chi-square analysis by the experience of college student athlete's intentional defeat, recognition of intentional defeat, cause of match-fixing, and necessity of sports ethics education. The conclusions are as follows. First, 7.1% of the college students had experienced losing intentionally. Second, 16.3% of the college student athletes did not perceive intentional losses irrelevant to gambling as match-fixing. Third, the college student athletes perceived that the causes of match-fixing included illegal pursuit of profits, environmental factors, human relationships, lack of education, etc. Fourth, 8.1% of the college student athletes viewed that sports ethics education is necessary. This study can be used as a basic data of sports ethics education for student athletes and it is expected to grow as a student player who can maintain moral character.

• The Journal of the Korea Contents Association
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• v.21 no.6
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• pp.561-571
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• 2021

As the game industry grows, the companies are promoting price discounts to increase game sales and profits. Consumers generally feel guilt when they are purchasing games. Previous studies argue that consumers feel less guilty and justify their consumption more easily when they are purchasing hedonic products at discounted price. In this study, we argue that there are different types of games; multi-game where consumers socialize each other and single games not supporting socializing. In the multi-game, consumers make social relationship which can provide substantial benefits. Since multi-games are promoting consumers' socializing expected to have those benefits. Although most of game consumptions bring a sense of guilty feeling, purchasing multi-game may not cause guilt much because the benefits of socializing justify the consumption. To support my hypothesis, we collect the data from global game platform Steam to analyze the relationship between price promotion and number of consumers. As a result, price promotion has significantly different relationship between multi-and single game. The results of this study suggest several managerial implications.

• The Korean Journal of Franchise Management
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• v.1 no.1
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• pp.87-103
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• 2010

Today, banks offer banking services to a large number of customers by a branch network spread all over the nation. The quantity and quality of services are advanced by fierce competition in their field. So they are attracting customers based on high confidence in the financial industry. In spite of these developments, the retail bank market currently does not satisfy customers demands and various desires. In this research, the problems with banking services were observed. It was proposed that the banking services apply a franchise business model. First, this proposal will reduce the business expenses by collaborating profits with head office of banks and affiliates. Second, it will offer greater satisfaction to the customers. Through the mutual collaboration with head office of banks and affiliates in this proposal, it is anticipated that banks will reduce their business expenses and improve services for customers by offering convenient and fast banking services. It is also expected that the banks will expand and make up their weakness through increased profit and customers will be provided additional services.

• Journal of Digital Policy
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• v.2 no.4
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• pp.17-23
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• 2023

In this paper, in order to improve production processing for small and medium-sized precision processing companies, we apply a manufacturing execution system to existing process methods and integrate precision processing data to strengthen process management within the company, increase facility operation efficiency, and realize a reduction in defect rates. The differences in productivity improvement and cost reduction rates were compared and analyzed. As a result, production productivity improved by 7.0% and product defect rate improved by 0.1% point due to the introduction of the manufacturing execution system. It was confirmed that manufacturing cost reduction improved by 10.0% and delivery compliance rate improved by 1.1%. If additional smart factory technology is applied based on the manufacturing execution system proposed in this study in the future, sales and profits in the processing industry are expected to increase due to an increase in the PQCD index.

• Journal of Intelligence and Information Systems
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• v.16 no.2
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• pp.19-32
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• 2010

Volatility plays a central role in both academic and practical applications, especially in pricing financial derivative products and trading volatility strategies. This study presents a novel mechanism based on generalized autoregressive conditional heteroskedasticity (GARCH) models that is able to enhance the performance of intelligent volatility trading systems by predicting Korean stock market volatility more accurately. In particular, we embedded the concept of the volatility asymmetry documented widely in the literature into our model. The newly developed Korean stock market volatility index of KOSPI 200, VKOSPI, is used as a volatility proxy. It is the price of a linear portfolio of the KOSPI 200 index options and measures the effect of the expectations of dealers and option traders on stock market volatility for 30 calendar days. The KOSPI 200 index options market started in 1997 and has become the most actively traded market in the world. Its trading volume is more than 10 million contracts a day and records the highest of all the stock index option markets. Therefore, analyzing the VKOSPI has great importance in understanding volatility inherent in option prices and can afford some trading ideas for futures and option dealers. Use of the VKOSPI as volatility proxy avoids statistical estimation problems associated with other measures of volatility since the VKOSPI is model-free expected volatility of market participants calculated directly from the transacted option prices. This study estimates the symmetric and asymmetric GARCH models for the KOSPI 200 index from January 2003 to December 2006 by the maximum likelihood procedure. Asymmetric GARCH models include GJR-GARCH model of Glosten, Jagannathan and Runke, exponential GARCH model of Nelson and power autoregressive conditional heteroskedasticity (ARCH) of Ding, Granger and Engle. Symmetric GARCH model indicates basic GARCH (1, 1). Tomorrow's forecasted value and change direction of stock market volatility are obtained by recursive GARCH specifications from January 2007 to December 2009 and are compared with the VKOSPI. Empirical results indicate that negative unanticipated returns increase volatility more than positive return shocks of equal magnitude decrease volatility, indicating the existence of volatility asymmetry in the Korean stock market. The point value and change direction of tomorrow VKOSPI are estimated and forecasted by GARCH models. Volatility trading system is developed using the forecasted change direction of the VKOSPI, that is, if tomorrow VKOSPI is expected to rise, a long straddle or strangle position is established. A short straddle or strangle position is taken if VKOSPI is expected to fall tomorrow. Total profit is calculated as the cumulative sum of the VKOSPI percentage change. If forecasted direction is correct, the absolute value of the VKOSPI percentage changes is added to trading profit. It is subtracted from the trading profit if forecasted direction is not correct. For the in-sample period, the power ARCH model best fits in a statistical metric, Mean Squared Prediction Error (MSPE), and the exponential GARCH model shows the highest Mean Correct Prediction (MCP). The power ARCH model best fits also for the out-of-sample period and provides the highest probability for the VKOSPI change direction tomorrow. Generally, the power ARCH model shows the best fit for the VKOSPI. All the GARCH models provide trading profits for volatility trading system and the exponential GARCH model shows the best performance, annual profit of 197.56%, during the in-sample period. The GARCH models present trading profits during the out-of-sample period except for the exponential GARCH model. During the out-of-sample period, the power ARCH model shows the largest annual trading profit of 38%. The volatility clustering and asymmetry found in this research are the reflection of volatility non-linearity. This further suggests that combining the asymmetric GARCH models and artificial neural networks can significantly enhance the performance of the suggested volatility trading system, since artificial neural networks have been shown to effectively model nonlinear relationships.