• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.

• Journal of Intelligence and Information Systems
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• v.19 no.2
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• pp.39-54
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• 2013

Recent explosive increase of electronic commerce provides many advantageous purchase opportunities to customers. In this situation, customers who do not have enough knowledge about their purchases, may accept product recommendations. Product recommender systems automatically reflect user's preference and provide recommendation list to the users. Thus, product recommender system in online shopping store has been known as one of the most popular tools for one-to-one marketing. However, recommender systems which do not properly reflect user's preference cause user's disappointment and waste of time. In this study, we propose a novel recommender system which uses data mining and multi-model ensemble techniques to enhance the recommendation performance through reflecting the precise user's preference. The research data is collected from the real-world online shopping store, which deals products from famous art galleries and museums in Korea. The data initially contain 5759 transaction data, but finally remain 3167 transaction data after deletion of null data. In this study, we transform the categorical variables into dummy variables and exclude outlier data. The proposed model consists of two steps. The first step predicts customers who have high likelihood to purchase products in the online shopping store. In this step, we first use logistic regression, decision trees, and artificial neural networks to predict customers who have high likelihood to purchase products in each product group. We perform above data mining techniques using SAS E-Miner software. In this study, we partition datasets into two sets as modeling and validation sets for the logistic regression and decision trees. We also partition datasets into three sets as training, test, and validation sets for the artificial neural network model. The validation dataset is equal for the all experiments. Then we composite the results of each predictor using the multi-model ensemble techniques such as bagging and bumping. Bagging is the abbreviation of "Bootstrap Aggregation" and it composite outputs from several machine learning techniques for raising the performance and stability of prediction or classification. This technique is special form of the averaging method. Bumping is the abbreviation of "Bootstrap Umbrella of Model Parameter," and it only considers the model which has the lowest error value. The results show that bumping outperforms bagging and the other predictors except for "Poster" product group. For the "Poster" product group, artificial neural network model performs better than the other models. In the second step, we use the market basket analysis to extract association rules for co-purchased products. We can extract thirty one association rules according to values of Lift, Support, and Confidence measure. We set the minimum transaction frequency to support associations as 5%, maximum number of items in an association as 4, and minimum confidence for rule generation as 10%. This study also excludes the extracted association rules below 1 of lift value. We finally get fifteen association rules by excluding duplicate rules. Among the fifteen association rules, eleven rules contain association between products in "Office Supplies" product group, one rules include the association between "Office Supplies" and "Fashion" product groups, and other three rules contain association between "Office Supplies" and "Home Decoration" product groups. Finally, the proposed product recommender systems provides list of recommendations to the proper customers. We test the usability of the proposed system by using prototype and real-world transaction and profile data. For this end, we construct the prototype system by using the ASP, Java Script and Microsoft Access. In addition, we survey about user satisfaction for the recommended product list from the proposed system and the randomly selected product lists. The participants for the survey are 173 persons who use MSN Messenger, Daum Caf$\acute{e}$, and P2P services. We evaluate the user satisfaction using five-scale Likert measure. This study also performs "Paired Sample T-test" for the results of the survey. The results show that the proposed model outperforms the random selection model with 1% statistical significance level. It means that the users satisfied the recommended product list significantly. The results also show that the proposed system may be useful in real-world online shopping store.

• Journal of Navigation and Port Research
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• v.39 no.6
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• pp.545-552
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• 2015

This study One of the key elements of corporate competitiveness in the modern world of unlimited competition is human resource management. The reason that the world's leading companies are devoting a lot of investment and effort for good human resource development and management is that human resource can impact firm survival. In particular, there is little research on the internal and external environmental stimuli and job stress in the employee of small business which are often led to turnover, while they have suffered from chronic shortage of manpower. The purpose of this study is to determine the turnover factors in the small logistics companies and contribute to stable maintenance of workforce, facilitating human resource management and minimizing turnover. This study empirically analyzed the factors of the turnover in the organization of logistics companies from Busan Port, South Korea, which became one of the national infrastructure and the fifth world largest harbor. The conclusion proposed the development and direction of the human resource management which could promote the job environment improving the turnover factors and creating sustainable work condition through conducting preventive measures. The results indicated that the highest turnover rates was found in the category of field work, and the highest turnover group was from the 'less than one year', which implies that high turnover rates after and during job training might be greater cost to the companies than early turnover. The most common reasons for the high employee turnover were 'excessive workload' and 'dissatisfaction with wages'. Followed reasons including 'troubles with managers' and 'failure in organizational adaptation' can be understood in line with worse working conditions of the small logistic companies. It turned out that the preventive programs of the logistic enterprises had little effect through 'incentives system' and 'improving wage system' which are mainly conducted. The human resource managers appreciated the importance of 'wage raise' and 'benefits improvement'. This study is aimed at contributing to efficient human resource management through understanding of the turnover causes and human resource managers applying preventive measures. In particular, this can benefit small port logistics companies securing competitiveness and promoting persistent growth and development.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.4
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• pp.881-893
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• 2007

IT(Information Technology)-based industries have caused a recent digital revolution and the appearance of various types' information service, being largely expanded toward info-communication device company, info-communication service company, software company etc.. Therefore, the needs to evaluate the company value of IT business for M&A or liquidation are growing tremendously. Unlike other industries, however, IT industry has a short lift cycle and so it doesn't have not only a company value-evaluating model for general businesses but the objective one for IT companies yet. So, this thesis analyzes various value-evaluating technique and newly rising ROV. DCF, the change method of company's cash flow including tangible assets into future value, had been applied during the past industrialization economy era and has been persuasively applied to the present. However, the DCF valuation has no option but to make many mistakes because IT companies have more intangible assets than tangible assets. Accordingly, it is ROV, recognized as the new method of evaluating companies' various options normally and quantitatively, that is brought up recently. But the evaluation on the companies' various options is too subjective and theoretical up to now and due to the lack of objective ground and options, it's not possible to be applied to reality. In this thesis, it is found that ROV is more accurate than DCF, comparing DCF and ROV through four examples. As the options applied to ROV are excessively limited, we tried to develop ROV into a new method by deriving five invisible value factors within IT companies. Therefore, on this occasion, we should set up the basic valuation methods on IT companies and should research and develop an effective and various valuation methods suitable to each company like an internet-based company, a S/W developing enterprise, a network-related company among IT companies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.11 no.7
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• pp.2358-2370
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• 2010

This research aims to empirically analyze the factors that affect the success of technology marketing by Korean universities. The total of 207 universities which successfully made technology transfers from 2006 to 2008 was examined to test the nine hypotheses. For the purpose of testing the hypotheses, technology infrastructure (research costs and the number of SCIE papers), the compensation system for the patents (application and registration), the number of patents (application and registration), TLO staff (the number of people in charge of technology transfer and the job experience in industries), the compensation system for technology transfers (researchers and contributors), and attitudes of university management and industries were analyzed with structural equation methods to figure out their effects on the revenues of technology transfer. The results of this research are summarized as follows. First, technology infrastructures of universities were found to have positive effects on securing patents. As the university research costs in the field of science and technology are increases, the research capabilities are enhanced and this a larger number of researchers are conducted. Second, this research shows that compensation systems for patent application and registration in universities have motivated researchers to take out patents for the outputs of their research. Third, the number of patents universities possess was found to have a positive effect on technology transfer. An increase in the number of patents universities possess implies an increase in the diversity and excellence of the target technologies for transfer. Fourth, the number of patents universities possess turned out to have a positive effect on TLO staff. The number of experts in charge of technology transfer including technology dealers, valuation analysis and patent attorneys should be increased as target technologies for transfer increase according to the increase of patents possessed. Because the technologies are transferee from universities to businesses, businesses (job) experience of TLO staff in industries are also important. This research is meaningful because it has identified the factors affecting the results of technology transfer by employing structural equation methods. In particular, an official governmental survey data for the academic-industrial cooperation were analyzed systematically in terms of technology infrastructure, compensation systems related to patents, the number of patents, TLO staff, compensation systems for technology transfer, and attitudes of university management and industries. All these facts might could differentiate this study from the previous studies.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6234-6241
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• 2014

The purpose of this study was to examine the status of medical staff stress and accommodating manners on the death of patients in a hospital setting for serving the basic information to develop a death education program of medical personnel from April 1 to April 30, 2014. A survey was performed on 353 medical personnel at K university hospital, located in Daejeon metropolitan city. Frequency analysis, chi-square test, and independent t-test were used to analyze the data. The results showed that 'to understand the value of the time and preparedness of a meaningful future' were the most important perspectives on the contents of death education (p<0.05), 'in order to change perceptions and attitudes toward death positively' was the most important reason why they required death education'(p<0.05), 'case-based teaching and problem-based learning' was the most effective way of death education (p<0.05), 'negative or hostile response of a patient's guardian to medical personnel' was the largest stress that medical personnel confront upon witnessing a death'(p<0.05). An understanding of the death of patients by medical personnel and an awareness of the need for death education will help improve the understanding of the patient, their guardian, and medical personnel themselves. The main findings will contribute to the development of a specific death education program on the medical personnel in a hospital setting.

• International Journal of Highway Engineering
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• v.12 no.4
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• pp.93-100
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• 2010

Trip generation is the first step in the conventional four-step model and has great effects on overall demand forecasting, so accuracy really matters at this stage. A linear regression model is widely used as a current trip generation model for such plans as urban transportation and SOC facilities, assuming that the relationship between each socio-economic index and trip generation stays linear. But when rapid urban development or an urban planning structure has changed, socio-economic index data for trip estimation may be lacking to bring many errors in estimated trip. Hence, instead of assuming that a socio-economic index widely used for a general purpose, this study aims to develop a new trip generation model by type based on the market separation for the variables to reflect the characteristics of various zones. The study considered the various characteristics (land use, socio-economic) of zones to enhance the forecasting accuracy of a trip generation model, the first-step in forecasting transportation demands. For a market separation methodology to improve forecasting accuracy, data mining (CART) on the basis of trip generation was used along with a regression analysis. Findings of the study indicated as follows : First, the analysis of zone characteristics using the CART analysis showed that trip production was under the influence of socio-economic factors (men-women relative proportion, age group (22 to 29)), while trip attraction was affected by land use factors (the relative proportion of business facilities) and the socio-economic factor (the relative proportion of third industry workers). Second, model development by type showed as a result that trip generation coefficients revealed 0.977 to 0.987 (trip/person) for "production" 0.692 to 3.256 (trip/person) for "attraction", which brought the necessity for type classifications. Third, a measured verification was conducted, where "production" and "attraction" showed a higher suitability than the existing model. The trip generation model by type developed in this study, therefore, turned out to be superior to the existing one.

• Journal of Korean Society of Rural Planning
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• v.20 no.4
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• pp.253-262
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• 2014

This, an association research for design-improvement and model-development of exhibition shops at rural tourism communities, is to secure objective data by analyzing customers' awareness-tendency of and demand for agricultural-specialty exhibition shops. Survey-questions for finding out consumers' awareness-tendency and demand were determined through brainstorming of a professional council, 30 rural communities of which visit-rate by consumers is considerably high were selected for the recruit of 200 consumers. For investigation and analysis, survey and in-depth interview were carried out at the scene with the application of frequency analysis and summarization of their opinions, which revealed that they have a strong will to visit the rural tourism communities for the purchase of agricultural specialties along with the experience of learning-program and on-the-scene direct dealing and that their viewpoint on the direct dealing at the scene was very positive. Also it was confirmed hat their satisfaction with the purchase of agricultural specialties by on-the-scene direct dealing, their pleasure at the purchase, their satisfaction with services and their intention for re-purchase of them were very high while their satisfaction with the exhibition shops was very low. With on-the-scene survey, the consumers' opinions could be listened to in depth. Almost all of them said their satisfaction with the trip to those rural tourism communities was considerably high since they could go to those communities themselves to relieve the stress from their modern life, to experience healing and to see the goods on the scene. Their satisfaction also was attributed to the fact that they have enough trust in purchase along with feeling the warm-heartedness of rural residents. As to their awareness of exhibition shops, they showed a positive response to the on-the-scene direct dealing at rural communities while they, thinking that the space in those exhibition shops was not sufficiently wide, demanded for more systematic counters in more accessible and affordable exhibition shops so that they might be more satisfied with the exhibition shops. Their demand for the necessity of exhibition shops selling agricultural specialties was found to be over 80%, which indicates that the necessity is very high. As to the suitability of function, they have the opinion that the business at those shops had better be focused on sales since they have the understanding of information when they take a trip to the rural communities, while there was another opinion: since agricultural products are seasonal items they should be exhibited and sold at the same time. More than 90% of the respondents had a positive viewpoint on direct dealing of agricultural specialties on the scene, which showed that their response to it was very high. They preferred the permanent shops equipped with roll-around table-booths. In addition, it was revealed that they want systematic exhibition shops in rural communities because they frequent those communities for on-the-scene direct purchase. The preferred type and opinion resulting from estimation of consumers' demands have been reflected for development of practical designs. The structure of variable principles has been designed so that the types of display-case and table-booth might be created. The result of this study is a positive data as a design model which can be utilized at rural communities and will be commercialized for the verification of its validity.

• Korean Security Journal
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• no.28
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• pp.181-205
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• 2011

There are various discussions about introducing private investigation in South Korea these days, and training private investigators is one of the main topics. Training private investigators, unlike other training, is required to instill expertise and ethical quality into the trainees since the major task of the investigators includes protecting the lives of the citizens as well as their properties. Therefore, many agree to the idea that systematic educational programs need to be organized to produce private investigators with expertness and morality. In this study, we explored the opinions of those who are concerned with this issue of establishing private investigation in the university education and analyzed the data by using the NVivo 2 program. The result revealed that the reasons that people supported the idea of launching private investigator services were as follows. First, there is lack of manpower to maintain peace and public order in the country. Second, the police does not intervene actively and help harmed victims unless it is a consequential incident. Third, in position to wield public power, police officers cannot get involved in civil affairs. Also, absence of an academic institution to educate private investigators and lack of the police and clients' trust in private investigation were the two biggest reasons that people approved the proposal to introduce department of private investigation in universities. The interviewees of the study believed the outlook and future direction for private investigation would change depending on the status of the licensed private investigation business bill. Before the bill passes, they thought that the work of private investigators will be performed by insurance companies, foreign private investigation businesses, domestic consulting firms, and security providers which supply similar services. On the other hand, after the bill passes, they believed that numerous private investigator corporations resembling existing security corporations will be founded in addition to the current market, and that private investigation in the academic field will also be vitalized.

• Korean Security Journal
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• no.28
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• pp.33-56
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• 2011

This study is to practice a analysis of Q-methodological preference degree about the subjects on school curriculum centering around the views of the policemen in active service who are with Gwang Ju and Jeon Nam region. Concretely, this study mixed the subjects on school curriculum related to the police administration of universities located in Gwang Ju and Jeon Nam region and abstracted the twenty seven items as the final question point. Above this, this study integrated the similar or repeated subjects and drew up the question items through seperation process among the different subjects. After this, this study selected the twenty policemen as a first P-sample in active service presently on fourth month in the year 2011. In this process, this study eliminated the materials of six policemen who replyed unhonestly and selected the materials of ten-four policemen as a final effective sample. Furthermore, this study applicated a principal component analysis. This study practiced the I.II.III types of a preference degree analysis of the subjects related to the police administration. the concrete results are as follows: In a I type, the positive consent was showed in the subjects of criminal law, criminal procedure law, criminal speciality law and so on. In a II type, the positive consent was showed in criminal investigation science, emergency measure, the art of self-defence, criminal law, criminal procedure law and so on. In a III type, the positive consent was showed in criminal science, criminal investigation science, criminal procedure law, introduction to police science, police ethics and so on. On this basis, this study concluded the following common opinions. Firstly the actual and evidencial subjects which the policemen in active service feel as the commons were criminal investigation, criminal science, police ethics, criminal speciality law, criminal law business, police administration science, police law practice, emergency measure, the art of self-defence, general rules of civil law, administrative law and so on.